diff --git a/common/common.cpp b/common/common.cpp index e58dad7ec8a2b..f286e51d934a8 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1036,6 +1036,9 @@ static ggml_type kv_cache_type_from_str(const std::string & s) { if (s == "q5_1") { return GGML_TYPE_Q5_1; } + if (s == "q6_0") { + return GGML_TYPE_Q6_0; + } throw std::runtime_error("Unsupported cache type: " + s); } diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index f8d7b0a378c44..5078d33de026b 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -21,6 +21,7 @@ static const std::vector QUANT_OPTIONS = { { "Q4_1", LLAMA_FTYPE_MOSTLY_Q4_1, " 4.78G, +0.4511 ppl @ Llama-3-8B", }, { "Q5_0", LLAMA_FTYPE_MOSTLY_Q5_0, " 5.21G, +0.1316 ppl @ Llama-3-8B", }, { "Q5_1", LLAMA_FTYPE_MOSTLY_Q5_1, " 5.65G, +0.1062 ppl @ Llama-3-8B", }, + { "Q6_0", LLAMA_FTYPE_MOSTLY_Q6_0, " 6.5 bpw quantization", }, { "IQ2_XXS", LLAMA_FTYPE_MOSTLY_IQ2_XXS, " 2.06 bpw quantization", }, { "IQ2_XS", LLAMA_FTYPE_MOSTLY_IQ2_XS, " 2.31 bpw quantization", }, { "IQ2_S", LLAMA_FTYPE_MOSTLY_IQ2_S, " 2.5 bpw quantization", }, diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 6c9066c43f70b..4998cae314b0f 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -396,6 +396,8 @@ extern "C" { GGML_TYPE_Q4_0_8_8 = 33, GGML_TYPE_TQ1_0 = 34, GGML_TYPE_TQ2_0 = 35, + // + GGML_TYPE_Q6_0 = 133, GGML_TYPE_COUNT, }; @@ -440,6 +442,8 @@ extern "C" { GGML_FTYPE_MOSTLY_Q4_0_4_4 = 25, // except 1d tensors GGML_FTYPE_MOSTLY_Q4_0_4_8 = 26, // except 1d tensors GGML_FTYPE_MOSTLY_Q4_0_8_8 = 27, // except 1d tensors + // + GGML_FTYPE_MOSTLY_Q6_0 = 127, // except 1d tensors }; // available tensor operations: diff --git a/ggml/src/ggml-common.h b/ggml/src/ggml-common.h index 050161393456e..901e1c7fa088d 100644 --- a/ggml/src/ggml-common.h +++ b/ggml/src/ggml-common.h @@ -88,6 +88,9 @@ typedef sycl::half2 ggml_half2; #define QI5_1 (QK5_1 / (4 * QR5_1)) #define QR5_1 2 +#define QI6_0 (QK6_0 / (4 * QR6_0)) +#define QR6_0 2 + #define QI8_0 (QK8_0 / (4 * QR8_0)) #define QR8_0 1 @@ -183,6 +186,14 @@ typedef struct { } block_q5_1; static_assert(sizeof(block_q5_1) == 2 * sizeof(ggml_half) + sizeof(uint32_t) + QK5_1 / 2, "wrong q5_1 block size/padding"); +#define QK6_0 32 +typedef struct { + ggml_half d; // delta + uint8_t qh[QK6_0/4]; // 5+6-th bit of quants + uint8_t qs[QK6_0/2]; // nibbles / quants +} block_q6_0; +static_assert(sizeof(block_q6_0) == sizeof(ggml_half) + QK6_0/2 + QK6_0/4, "wrong q6_0 block size/padding"); + #define QK8_0 32 typedef struct { ggml_half d; // delta diff --git a/ggml/src/ggml-cuda.cu b/ggml/src/ggml-cuda.cu index 46d48c0af391d..fa3a8b61722c7 100644 --- a/ggml/src/ggml-cuda.cu +++ b/ggml/src/ggml-cuda.cu @@ -3007,6 +3007,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: @@ -3078,6 +3079,9 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_Q5_1) { return true; } + if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_Q6_0) { + return true; + } if (src0_type == GGML_TYPE_F32 && src1_type == GGML_TYPE_IQ4_NL) { return true; } diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh index dd203fcded3aa..e15746803b079 100644 --- a/ggml/src/ggml-cuda/common.cuh +++ b/ggml/src/ggml-cuda/common.cuh @@ -387,6 +387,13 @@ struct ggml_cuda_type_traits { static constexpr int qi = QI5_1; }; +template<> +struct ggml_cuda_type_traits { + static constexpr int qk = QK6_0; + static constexpr int qr = QR6_0; + static constexpr int qi = QI6_0; +}; + template<> struct ggml_cuda_type_traits { static constexpr int qk = QK8_0; diff --git a/ggml/src/ggml-cuda/convert.cu b/ggml/src/ggml-cuda/convert.cu index c0a4447075c6e..e45e8f4e6fb9c 100644 --- a/ggml/src/ggml-cuda/convert.cu +++ b/ggml/src/ggml-cuda/convert.cu @@ -122,6 +122,36 @@ static __global__ void dequantize_block_q4_1(const void * __restrict__ vx, dst_t } } +template +static __global__ void dequantize_block_q6_0(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) { + + const int64_t i = blockIdx.x; + + // assume 32 threads + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; + const int64_t ir = tid%8; + const int64_t ib = 8*i + ir; + if (ib >= nb32) { + return; + } + + dst_t * y = yy + 256*i + 32*ir + 4*il; + + const block_q6_0 * x = (const block_q6_0 *)vx + ib; + const float d = __half2float(x->d); + const float dm = -32*d; + + const uint8_t * qs = x->qs + 4*il; + const uint8_t * qh = x->qh + 4*(il%2); + + for (int l = 0; l < 4; ++l) { + const uint8_t h = qh[l] >> 4*(il/2); + y[l+ 0] = d * ((qs[l] & 0xF) | ((h << 4) & 0x30)) + dm; + y[l+16] = d * ((qs[l] >> 4) | ((h << 2) & 0x30)) + dm; + } +} + //================================== k-quants template @@ -497,6 +527,13 @@ static void dequantize_row_q4_1_cuda(const void * vx, dst_t * y, const int64_t k dequantize_block_q4_1<<>>(vx, y, nb32); } +template +static void dequantize_row_q6_0_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb32 = k / 32; + const int nb = (k + 255) / 256; + dequantize_block_q6_0<<>>(vx, y, nb32); +} + template static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { const int nb = k / QK_K; @@ -598,6 +635,8 @@ to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) { return dequantize_block_cuda; case GGML_TYPE_Q5_1: return dequantize_block_cuda; + case GGML_TYPE_Q6_0: + return dequantize_row_q6_0_cuda; case GGML_TYPE_Q8_0: if (ggml_cuda_info().devices[ggml_cuda_get_device()].cc >= CC_PASCAL) { return dequantize_block_q8_0_f16_cuda; @@ -648,6 +687,8 @@ to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type) { return dequantize_block_cuda; case GGML_TYPE_Q5_1: return dequantize_block_cuda; + case GGML_TYPE_Q6_0: + return dequantize_row_q6_0_cuda; case GGML_TYPE_Q8_0: return dequantize_block_cuda; case GGML_TYPE_Q2_K: diff --git a/ggml/src/ggml-cuda/cpy.cu b/ggml/src/ggml-cuda/cpy.cu index 8531886f555af..ace85b726b013 100644 --- a/ggml/src/ggml-cuda/cpy.cu +++ b/ggml/src/ggml-cuda/cpy.cu @@ -225,6 +225,41 @@ static __device__ void cpy_blck_f32_q5_1(const char * cxi, char * cdsti) { memcpy(dsti->qh, &qh, sizeof(qh)); } +static __device__ void cpy_blck_f32_q6_0(const char * cxi, char * cdsti) { + const float * xi = (const float *) cxi; + block_q6_0 * dsti = (block_q6_0 *) cdsti; + + float amax = 0.0f; + float vmax = 0.0f; + + for (int j = 0; j < QK6_0; ++j) { + const float v = xi[j]; + const float av = fabsf(xi[j]); + if (amax < av) { + amax = av; + vmax = v; + } + } + + const float d = vmax / -32; + const float id = d ? 1.0f/d : 0.0f; + + dsti->d = d; + memset(dsti->qh, 0, QK6_0/4); + + for (int j = 0; j < QK6_0/2; ++j) { + const float x0 = xi[0 + j]*id; + const float x1 = xi[QK4_0/2 + j]*id; + + const uint8_t xi0 = min(63, (int8_t)(x0 + 32.5f)); + const uint8_t xi1 = min(63, (int8_t)(x1 + 32.5f)); + + dsti->qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4); + const uint8_t h = (xi0 >> 4) | ((xi1 >> 4) << 2); + dsti->qh[j%(QK6_0/4)] |= (h << 4*(j/(QK6_0/4))); + } +} + static __device__ const int8_t iq4nl_index[241] = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 17, 17, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 18, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, @@ -427,6 +462,17 @@ static void ggml_cpy_f32_q5_1_cuda( (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } +static void ggml_cpy_f32_q6_0_cuda( + const char * cx, char * cdst, const int ne, + const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02, + const int nb03, const int ne10, const int ne11, const int ne12, const int nb10, const int nb11, const int nb12, const int nb13, cudaStream_t stream) { + + GGML_ASSERT(ne % QK6_0 == 0); + const int num_blocks = ne / QK6_0; + cpy_f32_q<<>> + (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); +} + static void ggml_cpy_f32_iq4_nl_cuda( const char * cx, char * cdst, const int ne, const int ne00, const int ne01, const int ne02, const int nb00, const int nb01, const int nb02, @@ -499,6 +545,8 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, gg ggml_cpy_f32_q4_1_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream); } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_0) { ggml_cpy_f32_q5_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream); + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q6_0) { + ggml_cpy_f32_q6_0_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream); } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_IQ4_NL) { ggml_cpy_f32_iq4_nl_cuda(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream); } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) { @@ -539,6 +587,8 @@ void* ggml_cuda_cpy_fn(const ggml_tensor * src0, ggml_tensor * src1) { return (void*) cpy_f32_q; } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q5_1) { return (void*) cpy_f32_q; + } else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_Q6_0) { + return (void*) cpy_f32_q; } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16) { return (void*) cpy_f32_f16; } else if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32) { diff --git a/ggml/src/ggml-cuda/mmvq.cu b/ggml/src/ggml-cuda/mmvq.cu index 7dbbc993903c3..80785542fdad1 100644 --- a/ggml/src/ggml-cuda/mmvq.cu +++ b/ggml/src/ggml-cuda/mmvq.cu @@ -8,6 +8,7 @@ static constexpr __device__ vec_dot_q_cuda_t get_vec_dot_q_cuda(ggml_type type) type == GGML_TYPE_Q4_1 ? vec_dot_q4_1_q8_1 : type == GGML_TYPE_Q5_0 ? vec_dot_q5_0_q8_1 : type == GGML_TYPE_Q5_1 ? vec_dot_q5_1_q8_1 : + type == GGML_TYPE_Q6_0 ? vec_dot_q6_0_q8_1 : type == GGML_TYPE_Q8_0 ? vec_dot_q8_0_q8_1 : type == GGML_TYPE_Q2_K ? vec_dot_q2_K_q8_1 : type == GGML_TYPE_Q3_K ? vec_dot_q3_K_q8_1 : @@ -31,6 +32,7 @@ static constexpr __device__ int get_vdr_mmvq(ggml_type type) { type == GGML_TYPE_Q4_1 ? VDR_Q4_1_Q8_1_MMVQ : type == GGML_TYPE_Q5_0 ? VDR_Q5_0_Q8_1_MMVQ : type == GGML_TYPE_Q5_1 ? VDR_Q5_1_Q8_1_MMVQ : + type == GGML_TYPE_Q6_0 ? VDR_Q6_0_Q8_1_MMVQ : type == GGML_TYPE_Q8_0 ? VDR_Q8_0_Q8_1_MMVQ : type == GGML_TYPE_Q2_K ? VDR_Q2_K_Q8_1_MMVQ : type == GGML_TYPE_Q3_K ? VDR_Q3_K_Q8_1_MMVQ : @@ -229,6 +231,13 @@ static void mul_mat_vec_q5_1_q8_1_cuda( mul_mat_vec_q_cuda(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, stream); } +static void mul_mat_vec_q6_0_q8_1_cuda( + const void * vx, const void * vy, float * dst, + const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, const int nrows_dst, cudaStream_t stream) { + + mul_mat_vec_q_cuda(vx, vy, dst, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, stream); +} + static void mul_mat_vec_q8_0_q8_1_cuda( const void * vx, const void * vy, float * dst, const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, const int nrows_dst, cudaStream_t stream) { @@ -367,6 +376,9 @@ void ggml_cuda_op_mul_mat_vec_q( case GGML_TYPE_Q5_1: mul_mat_vec_q5_1_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream); break; + case GGML_TYPE_Q6_0: + mul_mat_vec_q6_0_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream); + break; case GGML_TYPE_Q8_0: mul_mat_vec_q8_0_q8_1_cuda(src0_dd_i, src1_ddq_i, dst_dd_i, ne00, row_diff, src1_padded_row_size, src1_ncols, nrows_dst, stream); break; diff --git a/ggml/src/ggml-cuda/vecdotq.cuh b/ggml/src/ggml-cuda/vecdotq.cuh index 40091a0ef07b4..001f29e950df2 100644 --- a/ggml/src/ggml-cuda/vecdotq.cuh +++ b/ggml/src/ggml-cuda/vecdotq.cuh @@ -41,6 +41,30 @@ template static __device__ __forceinline__ float vec_dot_q4_0_q8_1_imp return d4 * (sumi * ds8f.x - (8*vdr/QI4_0) * ds8f.y); } +#define VDR_Q6_0_Q8_1_MMVQ 2 +#define VDR_Q6_0_Q8_1_MMQ 4 + +template static __device__ __forceinline__ float vec_dot_q6_0_q8_1_impl( + const int * vl, const int * vh, const int * u, const float & d6, const half2 & ds8) { + + int sumi = 0; + +#pragma unroll + for (int i = 0; i < vdr; ++i) { + const int vi0 = ((vl[i] >> 0) & 0x0F0F0F0F) | ((vh[i] << 4) & 0x30303030); + const int vi1 = ((vl[i] >> 4) & 0x0F0F0F0F) | ((vh[i] << 2) & 0x30303030); + + // SIMD dot product of quantized values + sumi = ggml_cuda_dp4a(vi0, u[2*i+0], sumi); + sumi = ggml_cuda_dp4a(vi1, u[2*i+1], sumi); + } + + const float2 ds8f = __half22float2(ds8); + + // second part effectively subtracts 8 from each quant value + return d6 * (sumi * ds8f.x - (32.f*vdr/QI6_0) * ds8f.y); +} + #define VDR_Q4_1_Q8_1_MMVQ 2 #define VDR_Q4_1_Q8_1_MMQ 4 @@ -542,6 +566,26 @@ static __device__ __forceinline__ float vec_dot_q4_0_q8_1( return vec_dot_q4_0_q8_1_impl(v, u, bq4_0->d, bq8_1->ds); } +static __device__ __forceinline__ float vec_dot_q6_0_q8_1( + const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) { + + const block_q6_0 * bq6_0 = (const block_q6_0 *) vbq + kbx; + + int vl[VDR_Q6_0_Q8_1_MMVQ]; + int vh[VDR_Q6_0_Q8_1_MMVQ]; + int u[2*VDR_Q6_0_Q8_1_MMVQ]; + +#pragma unroll + for (int i = 0; i < VDR_Q6_0_Q8_1_MMVQ; ++i) { + vl[i] = get_int_b2(bq6_0->qs, iqs + i); + vh[i] = get_int_b2(bq6_0->qh, i) >> 4*(iqs/2); + u[2*i+0] = get_int_b4(bq8_1->qs, iqs + i); + u[2*i+1] = get_int_b4(bq8_1->qs, iqs + i + QI6_0); + } + + return vec_dot_q6_0_q8_1_impl(vl, vh, u, bq6_0->d, bq8_1->ds); +} + static __device__ __forceinline__ float vec_dot_q4_1_q8_1( const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) { diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m index b1f179b1297be..7321fdebd2189 100644 --- a/ggml/src/ggml-metal.m +++ b/ggml/src/ggml-metal.m @@ -124,6 +124,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1, GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0, GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1, + GGML_METAL_KERNEL_TYPE_GET_ROWS_Q6_0, GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0, GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K, GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K, @@ -154,6 +155,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32, + GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32, @@ -178,6 +180,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_1_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32, + GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q8_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q2_K_F32, GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q3_K_F32, @@ -199,6 +202,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32, + GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32, @@ -220,6 +224,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_1_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F32, + GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q6_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F32, GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F32, @@ -267,6 +272,7 @@ static void ggml_backend_metal_device_rel(struct ggml_backend_metal_device_conte GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1, GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0, GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1, + GGML_METAL_KERNEL_TYPE_CPY_F32_Q6_0, GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL, GGML_METAL_KERNEL_TYPE_CONCAT, GGML_METAL_KERNEL_TYPE_SQR, @@ -572,6 +578,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1, get_rows_q4_1, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0, get_rows_q5_0, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1, get_rows_q5_1, true); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q6_0, get_rows_q6_0, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0, get_rows_q8_0, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K, get_rows_q2_K, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K, get_rows_q3_K, true); @@ -602,6 +609,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q4_1_F32, mul_mv_q4_1_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_0_F32, mul_mv_q5_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32, mul_mv_q5_1_f32, support_simdgroup_reduction); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_0_F32, mul_mv_q6_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q8_0_F32, mul_mv_q8_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q2_K_F32, mul_mv_q2_K_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_Q3_K_F32, mul_mv_q3_K_f32, support_simdgroup_reduction); @@ -626,6 +634,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q4_1_F32, mul_mv_id_q4_1_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_0_F32, mul_mv_id_q5_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32, mul_mv_id_q5_1_f32, support_simdgroup_reduction); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_0_F32, mul_mv_id_q6_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q8_0_F32, mul_mv_id_q8_0_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q2_K_F32, mul_mv_id_q2_K_f32, support_simdgroup_reduction); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q3_K_F32, mul_mv_id_q3_K_f32, support_simdgroup_reduction); @@ -647,6 +656,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32, mul_mm_q4_1_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32, mul_mm_q5_0_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32, mul_mm_q5_1_f32, support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_0_F32, mul_mm_q6_0_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32, mul_mm_q8_0_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32, mul_mm_q2_K_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_Q3_K_F32, mul_mm_q3_K_f32, support_simdgroup_mm); @@ -669,6 +679,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F32, mul_mm_id_q5_0_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F32, mul_mm_id_q5_1_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F32, mul_mm_id_q8_0_f32, support_simdgroup_mm); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F32, mul_mm_id_q8_0_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F32, mul_mm_id_q2_K_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F32, mul_mm_id_q3_K_f32, support_simdgroup_mm); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_K_F32, mul_mm_id_q4_K_f32, support_simdgroup_mm); @@ -715,6 +726,7 @@ @implementation GGMLMetalClass GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1, cpy_f32_q4_1, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0, cpy_f32_q5_0, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1, cpy_f32_q5_1, true); + GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_Q6_0, cpy_f32_q6_0, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL, cpy_f32_iq4_nl, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_CONCAT, concat, true); GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SQR, sqr, true); @@ -893,6 +905,7 @@ static bool ggml_metal_supports_op(const struct ggml_backend_metal_device_contex case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_IQ4_NL: return true; default: @@ -1783,6 +1796,7 @@ static void ggml_metal_encode_node( case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_0_F32 ].pipeline; break; case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q4_1_F32 ].pipeline; break; case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_0_F32 ].pipeline; break; + case GGML_TYPE_Q6_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q6_0_F32 ].pipeline; break; case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q5_1_F32 ].pipeline; break; case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q8_0_F32 ].pipeline; break; case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_Q2_K_F32 ].pipeline; break; @@ -1879,6 +1893,12 @@ static void ggml_metal_encode_node( nth1 = 8; pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q5_1_F32].pipeline; } break; + case GGML_TYPE_Q6_0: + { + nth0 = 8; + nth1 = 8; + pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_Q6_0_F32].pipeline; + } break; case GGML_TYPE_Q8_0: { nth0 = 8; @@ -1997,7 +2017,7 @@ static void ggml_metal_encode_node( [encoder setBytes:&r2 length:sizeof(r2) atIndex:17]; [encoder setBytes:&r3 length:sizeof(r3) atIndex:18]; - if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 || + if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 || src0t == GGML_TYPE_Q6_0 || src0t == GGML_TYPE_Q5_1 || src0t == GGML_TYPE_Q8_0 || src0t == GGML_TYPE_Q2_K || src0t == GGML_TYPE_IQ1_S || src0t == GGML_TYPE_IQ1_M || src0t == GGML_TYPE_IQ2_S) { [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, ne11, ne12*ne13) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; @@ -2086,6 +2106,7 @@ static void ggml_metal_encode_node( case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q4_1_F32 ].pipeline; break; case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_0_F32 ].pipeline; break; case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q5_1_F32 ].pipeline; break; + case GGML_TYPE_Q6_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q6_0_F32 ].pipeline; break; case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q8_0_F32 ].pipeline; break; case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q2_K_F32 ].pipeline; break; case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MM_ID_Q3_K_F32 ].pipeline; break; @@ -2175,6 +2196,12 @@ static void ggml_metal_encode_node( nth1 = 8; pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q5_1_F32].pipeline; } break; + case GGML_TYPE_Q6_0: + { + nth0 = 8; + nth1 = 8; + pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_MUL_MV_ID_Q6_0_F32].pipeline; + } break; case GGML_TYPE_Q8_0: { nth0 = 8; @@ -2303,8 +2330,8 @@ static void ggml_metal_encode_node( const int64_t _ne1 = 1; const int tgz = dst_rows; - - if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 || + + if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 || src0t == GGML_TYPE_Q5_0 || src0t == GGML_TYPE_Q6_0 || src0t == GGML_TYPE_Q5_1 || src0t == GGML_TYPE_Q8_0 || src0t == GGML_TYPE_Q2_K || src0t == GGML_TYPE_IQ1_S || src0t == GGML_TYPE_IQ1_M || src0t == GGML_TYPE_IQ2_S) { [encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7)/8, _ne1, tgz) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)]; @@ -2352,6 +2379,7 @@ static void ggml_metal_encode_node( case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q4_1 ].pipeline; break; case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_0 ].pipeline; break; case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1 ].pipeline; break; + case GGML_TYPE_Q6_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q5_1 ].pipeline; break; case GGML_TYPE_Q8_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q8_0 ].pipeline; break; case GGML_TYPE_Q2_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q2_K ].pipeline; break; case GGML_TYPE_Q3_K: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_GET_ROWS_Q3_K ].pipeline; break; @@ -2997,6 +3025,7 @@ static void ggml_metal_encode_node( case GGML_TYPE_Q4_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_0].pipeline; break; case GGML_TYPE_Q4_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q4_1].pipeline; break; case GGML_TYPE_Q5_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_0].pipeline; break; + case GGML_TYPE_Q6_0: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q6_0].pipeline; break; case GGML_TYPE_Q5_1: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_Q5_1].pipeline; break; case GGML_TYPE_IQ4_NL: pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_CPY_F32_IQ4_NL].pipeline; break; default: GGML_ABORT("not implemented"); diff --git a/ggml/src/ggml-metal.metal b/ggml/src/ggml-metal.metal index 71b58be1fd8a4..98e604976d6e1 100644 --- a/ggml/src/ggml-metal.metal +++ b/ggml/src/ggml-metal.metal @@ -1137,8 +1137,30 @@ inline float block_q_n_dot_y(device const block_q5_1 * qb_curr, float sumy, thre + yl[i + 1] * ((qs[i / 2] & 0x0F00) | ((qh >> (i+1+il ) << 12) & 0x01000)); acc[1] += yl[i + 8] * ((qs[i / 2] & 0x00F0) | ((qh >> (i+0+il+QK5_0/2) << 8 ) & 0x00100)) + yl[i + 9] * ((qs[i / 2] & 0xF000) | ((qh >> (i+1+il+QK5_0/2) << 16) & 0x10000)); + } + return d * (acc[0] + acc[1]) + sumy * m; +} + +// function for calculate inner product between half a q6_0 block and 16 floats (yl), sumy is SUM(yl[i]) +// il indicates where the q6 quants begin (0 or QK6_0/4) +// we assume that the yl's have been multiplied with the appropriate scale factor +// that corresponds to the missing bit shifts (1, 1/16, 1/256, 1/4096) +inline float block_q_n_dot_y(device const block_q6_0 * qb_curr, float sumy, thread float * yl, int il) { + float d = qb_curr->d; + + float2 acc = 0.f; + + device const uint16_t * qh = (device const uint16_t *)qb_curr->qh; + device const uint16_t * qs = (device const uint16_t *)qb_curr->qs + il/2; + + const int shift = 4*(il/8); + for (int i = 0; i < 8; i += 2) { + acc[0] += yl[i + 0] * ((qs[i/2] & 0x000F) | ((qh[i/2] << (4-shift)) & 0x0030)) + + yl[i + 1] * ((qs[i/2] & 0x0F00) | ((qh[i/2] << (4-shift)) & 0x3000)); + acc[1] += yl[i + 8] * ((qs[i/2] & 0x00F0) | ((qh[i/2] << (6-shift)) & 0x0300)) + + yl[i + 9] * ((qs[i/2] & 0xF000) | (((uint32_t)qh[i/2] << (6-shift)) & 0x30000)); } - return d * (acc[0] + acc[1]) + sumy * m; + return d * (sumy * -32.f + acc[0] + acc[1]); } // putting them in the kernel cause a significant performance penalty @@ -1320,6 +1342,31 @@ kernel void kernel_mul_mv_q5_1_f32( mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); } +kernel void kernel_mul_mv_q6_0_f32( + device const void * src0, + device const float * src1, + device float * dst, + constant int64_t & ne00, + constant int64_t & ne01, + constant int64_t & ne02, + constant uint64_t & nb00, + constant uint64_t & nb01, + constant uint64_t & nb02, + constant int64_t & ne10, + constant int64_t & ne11, + constant int64_t & ne12, + constant uint64_t & nb10, + constant uint64_t & nb11, + constant uint64_t & nb12, + constant int64_t & ne0, + constant int64_t & ne1, + constant uint & r2, + constant uint & r3, + uint3 tgpig[[threadgroup_position_in_grid]], + uint tiisg[[thread_index_in_simdgroup]], + uint sgitg[[simdgroup_index_in_threadgroup]]) { + mul_vec_q_n_f32_impl(src0,src1,dst,ne00,ne01,ne02,ne10,ne12,ne0,ne1,r2,r3,nullptr,tgpig,tiisg,sgitg); +} #define NB_Q8_0 8 @@ -3263,6 +3310,77 @@ kernel void kernel_cpy_f32_q5_1( } } +kernel void kernel_cpy_f32_q6_0( + device const float * src0, + device void * dst, + constant int64_t & ne00, + constant int64_t & ne01, + constant int64_t & ne02, + constant int64_t & ne03, + constant uint64_t & nb00, + constant uint64_t & nb01, + constant uint64_t & nb02, + constant uint64_t & nb03, + constant int64_t & ne0, + constant int64_t & ne1, + constant int64_t & ne2, + constant int64_t & ne3, + constant uint64_t & nb0, + constant uint64_t & nb1, + constant uint64_t & nb2, + constant uint64_t & nb3, + uint3 tgpig[[threadgroup_position_in_grid]], + uint3 tpitg[[thread_position_in_threadgroup]], + uint3 ntg[[threads_per_threadgroup]]) { + const int64_t i03 = tgpig[2]; + const int64_t i02 = tgpig[1]; + const int64_t i01 = tgpig[0]; + + const int64_t n = i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00; + + const int64_t i3 = n / (ne2*ne1*ne0); + const int64_t i2 = (n - i3*ne2*ne1*ne0) / (ne1*ne0); + const int64_t i1 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0) / ne0; + const int64_t i0 = (n - i3*ne2*ne1*ne0 - i2*ne1*ne0 - i1*ne0)/QK6_0; + + device block_q6_0 * dst_data = (device block_q6_0 *) ((device char *) dst + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0); + + for (int64_t i00 = tpitg.x*QK6_0; i00 < ne00; i00 += ntg.x*QK6_0) { + device const float * src = (device float *)((device char *) src0 + i03*nb03 + i02*nb02 + i01*nb01 + i00*nb00); + + float amax = 0.0f; // absolute max + float max = 0.0f; + + for (int j = 0; j < QK6_0; j++) { + const float v = src[j]; + if (amax < fabs(v)) { + amax = fabs(v); + max = v; + } + } + + const float d = max / -32; + const float id = d ? 1.0f/d : 0.0f; + + device block_q6_0 & b6 = dst_data[i00/QK6_0]; + b6.d = d; + device uint16_t * aux16 = (device uint16_t *)b6.qh; + aux16[0] = aux16[1] = aux16[2] = aux16[3] = 0; + + for (int j = 0; j < QK6_0/2; ++j) { + const float x0 = src[0 + j]*id; + const float x1 = src[QK6_0/2 + j]*id; + + const uint8_t xi0 = MIN(63, (int8_t)(x0 + 32.5f)); + const uint8_t xi1 = MIN(63, (int8_t)(x1 + 32.5f)); + + b6.qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4); + const uint8_t h = (xi0 >> 4) | ((xi1 >> 4) << 2); + b6.qh[j%(QK6_0/4)] |= (h << 4*(j/(QK6_0/4))); + } + } +} + static inline int best_index_int8(int n, constant float * val, float x) { if (x <= val[0]) return 0; if (x >= val[n-1]) return n-1; @@ -5396,6 +5514,21 @@ void dequantize_q5_1(device const block_q5_1 *xb, short il, thread type4x4 & reg } } +template +void dequantize_q6_0(device const block_q6_0 *xb, short il, thread type4x4 & reg) { + const float d = xb->d; + const float m = -32.h * xb->d; + device const uint8_t * qh = xb->qh; + device const uint8_t * qs = qh + 8; + + for (int i = 0; i < 8; i++) { + reg[i/4][i%4] = d * (((qs[i] >> 4*il) & 0xf) | (((qh[i] >> 2*il) << 4) & 0x30)) + m; + } + for (int i = 0; i < 8; i++) { + reg[2+i/4][i%4] = d * (((qs[i+8] >> 4*il) & 0xf) | ((qh[i] >> 2*il) & 0x30)) + m; + } +} + template void dequantize_q8_0(device const block_q8_0 *xb, short il, thread type4x4 & reg) { device const int8_t * qs = ((device const int8_t *)xb->qs); @@ -6171,6 +6304,7 @@ template [[host_name("kernel_get_rows_q4_0")]] kernel get_rows_q_t kernel_get template [[host_name("kernel_get_rows_q4_1")]] kernel get_rows_q_t kernel_get_rows_q; template [[host_name("kernel_get_rows_q5_0")]] kernel get_rows_q_t kernel_get_rows_q; template [[host_name("kernel_get_rows_q5_1")]] kernel get_rows_q_t kernel_get_rows_q; +template [[host_name("kernel_get_rows_q6_0")]] kernel get_rows_q_t kernel_get_rows_q; template [[host_name("kernel_get_rows_q8_0")]] kernel get_rows_q_t kernel_get_rows_q; template [[host_name("kernel_get_rows_q2_K")]] kernel get_rows_q_t kernel_get_rows_q; template [[host_name("kernel_get_rows_q3_K")]] kernel get_rows_q_t kernel_get_rows_q; @@ -6199,6 +6333,7 @@ template [[host_name("kernel_mul_mm_q4_0_f32")]] kernel mat_mm_t kernel_mul_m template [[host_name("kernel_mul_mm_q4_1_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q5_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q5_1_f32")]] kernel mat_mm_t kernel_mul_mm; +template [[host_name("kernel_mul_mm_q6_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q8_0_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q2_K_f32")]] kernel mat_mm_t kernel_mul_mm; template [[host_name("kernel_mul_mm_q3_K_f32")]] kernel mat_mm_t kernel_mul_mm; @@ -6226,6 +6361,7 @@ template [[host_name("kernel_mul_mm_id_f16_f32")]] kernel mat_mm_id_t kernel template [[host_name("kernel_mul_mm_id_q4_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q4_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q5_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; +template [[host_name("kernel_mul_mm_id_q6_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q5_1_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q8_0_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; template [[host_name("kernel_mul_mm_id_q2_K_f32")]] kernel mat_mm_id_t kernel_mul_mm_id; @@ -6437,6 +6573,7 @@ template [[host_name("kernel_mul_mv_id_q4_0_f32")]] kernel kernel_mul_mv_id_t template [[host_name("kernel_mul_mv_id_q4_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q5_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q5_1_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; +template [[host_name("kernel_mul_mv_id_q6_0_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>>; template [[host_name("kernel_mul_mv_id_q2_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q3_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; template [[host_name("kernel_mul_mv_id_q4_K_f32")]] kernel kernel_mul_mv_id_t kernel_mul_mv_id>; diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c index 148073f73865e..f036cd4dc774d 100644 --- a/ggml/src/ggml-quants.c +++ b/ggml/src/ggml-quants.c @@ -845,6 +845,59 @@ void quantize_row_q5_1(const float * restrict x, void * restrict y, int64_t k) { quantize_row_q5_1_ref(x, y, k); } +void quantize_row_q6_0_ref(const float * restrict x, block_q6_0 * restrict y, int64_t k) { + static const int qk = QK6_0; + + assert(k % qk == 0); + + const int nb = k / qk; + + for (int i = 0; i < nb; i++) { + float amax = 0.0f; // absolute max + float max = 0.0f; + + for (int j = 0; j < qk; j++) { + const float v = x[i*qk + j]; + if (amax < fabsf(v)) { + amax = fabsf(v); + max = v; + } + } + + const float d = max / -32; + const float id = d ? 1.0f/d : 0.0f; + + //y[i].d = GGML_FP32_TO_FP16(d); + memset(y[i].qh, 0, qk/4); + + float sumqx = 0, sumq2 = 0; + for (int j = 0; j < qk/2; ++j) { + const float x0 = x[i*qk + 0 + j]*id; + const float x1 = x[i*qk + qk/2 + j]*id; + const float w0 = x0*x0; + const float w1 = x1*x1; + + const uint8_t xi0 = MIN(63, (int8_t)(x0 + 32.5f)); + const uint8_t xi1 = MIN(63, (int8_t)(x1 + 32.5f)); + + y[i].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4); + + const uint8_t h = (xi0 >> 4) | ((xi1 >> 4) << 2); + y[i].qh[j%(qk/4)] |= (h << 4*(j/(qk/4))); + + const float q0 = (float)xi0 - 32.f; + const float q1 = (float)xi1 - 32.f; + sumqx += w0*x[i*qk + j]*q0 + w1*x[i*qk + qk/2 + j]*q1; + sumq2 += w0*q0*q0 + w1*q1*q1; + } + y[i].d = sumq2 > 0 ? GGML_FP32_TO_FP16(sumqx/sumq2) : GGML_FP32_TO_FP16(d); + } +} + +void quantize_row_q6_0(const float * restrict x, void * restrict y, int64_t k) { + quantize_row_q6_0_ref(x, y, k); +} + // reference implementation for deterministic creation of model files void quantize_row_q8_0_ref(const float * restrict x, block_q8_0 * restrict y, int64_t k) { assert(k % QK8_0 == 0); @@ -1614,6 +1667,28 @@ void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int6 } } +void dequantize_row_q6_0(const block_q6_0 * restrict x, float * restrict y, int64_t k) { + static const int qk = QK6_0; + + assert(k % qk == 0); + + const int nb = k / qk; + + for (int i = 0; i < nb; i++) { + const float d = GGML_FP16_TO_FP32(x[i].d); + + for (int j = 0; j < qk/2; ++j) { + const uint8_t h = x[i].qh[j%(qk/4)] >> 4*(j/(qk/4)); + + const int32_t x0 = ((x[i].qs[j] & 0x0F) | ((h << 4) & 0x30)) - 32; + const int32_t x1 = ((x[i].qs[j] >> 4) | ((h << 2) & 0x30)) - 32; + + y[i*qk + j + 0 ] = x0*d; + y[i*qk + j + qk/2] = x1*d; + } + } +} + void dequantize_row_q8_0(const block_q8_0 * restrict x, float * restrict y, int64_t k) { static const int qk = QK8_0; @@ -3307,6 +3382,54 @@ size_t quantize_q5_1(const float * restrict src, void * restrict dst, int64_t nr return nrow * row_size; } +static void quantize_row_q6_0_impl(const float * restrict x, block_q6_0 * restrict y, int64_t n_per_row, const float * quant_weights) { + static_assert(QK6_0 == 32, "QK6_0 must be 32"); + + float weight[QK6_0]; + int8_t L[QK6_0]; + + float sigma2 = 0; + if (quant_weights) { + float sum_x2 = 0; + for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j]; + sigma2 = sum_x2/n_per_row; + } + + const int64_t nb = n_per_row/QK6_0; + for (int ib = 0; ib < nb; ++ib) { + const float * xb = x + QK6_0 * ib; + if (quant_weights) { + const float * qw = quant_weights + QK6_0 * ib; + for (int j = 0; j < QK6_0; ++j) weight[j] = qw[j] * sqrtf(sigma2 + xb[j]*xb[j]); + } else { + for (int j = 0; j < QK6_0; ++j) weight[j] = xb[j]*xb[j]; + } + float d = make_qx_quants(QK6_0, 32, xb, L, 1, weight); + y[ib].d = GGML_FP32_TO_FP16(d); + + memset(y[ib].qh, 0, QK6_0/4); + + for (int j = 0; j < 16; ++j) { + const uint8_t xi0 = L[j]; + const uint8_t xi1 = L[j+16]; + y[ib].qs[j] = (xi0 & 0x0F) | ((xi1 & 0x0F) << 4); + const uint8_t h = (xi0 >> 4) | ((xi1 >> 4) << 2); + y[ib].qh[j%8] |= (h << 4*(j/8)); + } + } +} + +size_t quantize_q6_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) { + size_t row_size = ggml_row_size(GGML_TYPE_Q6_0, n_per_row); + char * qrow = (char *)dst; + for (int64_t row = 0; row < nrow; ++row) { + quantize_row_q6_0_impl(src, (block_q6_0*)qrow, n_per_row, quant_weights); + src += n_per_row; + qrow += row_size; + } + return nrow * row_size; +} + size_t quantize_q8_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) { (void)quant_weights; // not used const size_t row_size = ggml_row_size(GGML_TYPE_Q8_0, n_per_row); @@ -5516,6 +5639,21 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * restrict s, size_t bs, const void * r *s = sumf; } +void ggml_vec_dot_q6_0_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) { +#if GGML_USE_IQK_MULMAT +#ifdef __AVX2__ + const enum ggml_type vec_dot_type = GGML_TYPE_Q8_1; +#else + const enum ggml_type vec_dot_type = GGML_TYPE_Q8_0; +#endif + if (iqk_mul_mat(nrc, nrc, n, GGML_TYPE_Q6_0, vx, bx, vec_dot_type, vy, by, s, bs, 0, 1)) { + return; + } +#endif + // TODO + *s = 0; +} + void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * restrict vx, size_t bx, const void * restrict vy, size_t by, int nrc) { const int qk = QK8_0; const int nb = n / qk; @@ -15646,6 +15784,10 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte { VALIDATE_ROW_DATA_DM_F16_IMPL(block_q5_1, data, nb, d, m); } break; + case GGML_TYPE_Q6_0: + { + VALIDATE_ROW_DATA_D_F16_IMPL(block_q5_0, data, nb); + } break; case GGML_TYPE_Q8_0: { VALIDATE_ROW_DATA_D_F16_IMPL(block_q8_0, data, nb); @@ -15732,6 +15874,14 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte { VALIDATE_ROW_DATA_D_F16_IMPL(block_iq4_nl, data, nb); } break; + // case GGML_TYPE_Q6_0: break; + // case GGML_TYPE_IQ2_K: break; + // case GGML_TYPE_IQ3_K: break; + // case GGML_TYPE_IQ4_K: break; + // case GGML_TYPE_IQ5_K: break; + // case GGML_TYPE_IQ6_K: break; + // case GGML_TYPE_IQ2_TN: break; + // case GGML_TYPE_IQ1_TN: break; case GGML_TYPE_Q4_0_4_4: case GGML_TYPE_Q4_0_4_8: { diff --git a/ggml/src/ggml-quants.h b/ggml/src/ggml-quants.h index df9c4b24ae74f..8c5771f4668fb 100644 --- a/ggml/src/ggml-quants.h +++ b/ggml/src/ggml-quants.h @@ -18,6 +18,7 @@ void quantize_row_q5_0_ref(const float * GGML_RESTRICT x, block_q5_0 * GGML_REST void quantize_row_q5_1_ref(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int64_t k); void quantize_row_q8_0_ref(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int64_t k); void quantize_row_q8_1_ref(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int64_t k); +void quantize_row_q6_0_ref(const float * GGML_RESTRICT x, block_q6_0 * GGML_RESTRICT y, int64_t k); void quantize_row_q2_K_ref(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int64_t k); void quantize_row_q3_K_ref(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int64_t k); @@ -41,6 +42,7 @@ void quantize_row_q5_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, in void quantize_row_q5_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); +void quantize_row_q6_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); void quantize_row_q2_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); void quantize_row_q3_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); @@ -65,6 +67,7 @@ void dequantize_row_q5_0(const block_q5_0 * GGML_RESTRICT x, float * GGML_RESTRI void dequantize_row_q5_1(const block_q5_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); void dequantize_row_q8_0(const block_q8_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); //void dequantize_row_q8_1(const block_q8_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); +void dequantize_row_q6_0(const block_q6_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); void dequantize_row_q2_K(const block_q2_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); void dequantize_row_q3_K(const block_q3_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); @@ -92,6 +95,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); +void ggml_vec_dot_q6_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc); @@ -136,6 +140,7 @@ size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); +size_t quantize_q6_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); void iq2xs_init_impl(enum ggml_type type); void iq2xs_free_impl(enum ggml_type type); diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 83fb4d4482b1c..f3d24aabefd83 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -899,6 +899,23 @@ static const struct ggml_type_traits type_traits[GGML_TYPE_COUNT] = { .vec_dot_type = GGML_TYPE_Q8_1, .nrows = 1, }, + [GGML_TYPE_Q6_0] = { + .type_name = "q6_0", + .blck_size = QK6_0, + .type_size = sizeof(block_q6_0), + .is_quantized = true, + .to_float = (ggml_to_float_t) dequantize_row_q6_0, + .from_float = quantize_row_q6_0, + .from_float_ref = (ggml_from_float_t) quantize_row_q6_0_ref, + .vec_dot = ggml_vec_dot_q6_0_q8_0, +#if GGML_USE_IQK_MULMAT && defined __AVX2__ + .vec_dot_type = GGML_TYPE_Q8_1, +#else + .vec_dot_type = GGML_TYPE_Q8_0, +#endif + .nrows = 1, + .row_meta_size = 0, + }, [GGML_TYPE_Q8_0] = { .type_name = "q8_0", .blck_size = QK8_0, @@ -3612,6 +3629,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { case GGML_FTYPE_MOSTLY_Q4_1: wtype = GGML_TYPE_Q4_1; break; case GGML_FTYPE_MOSTLY_Q5_0: wtype = GGML_TYPE_Q5_0; break; case GGML_FTYPE_MOSTLY_Q5_1: wtype = GGML_TYPE_Q5_1; break; + case GGML_FTYPE_MOSTLY_Q6_0: wtype = GGML_TYPE_Q6_0; break; case GGML_FTYPE_MOSTLY_Q8_0: wtype = GGML_TYPE_Q8_0; break; case GGML_FTYPE_MOSTLY_Q2_K: wtype = GGML_TYPE_Q2_K; break; case GGML_FTYPE_MOSTLY_Q3_K: wtype = GGML_TYPE_Q3_K; break; @@ -9563,6 +9581,7 @@ static void ggml_compute_forward_add( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: @@ -9942,6 +9961,7 @@ static void ggml_compute_forward_add1( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: case GGML_TYPE_Q2_K: @@ -10072,6 +10092,7 @@ static void ggml_compute_forward_acc( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: case GGML_TYPE_Q2_K: @@ -13158,6 +13179,7 @@ static void ggml_compute_forward_out_prod( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q2_K: case GGML_TYPE_Q3_K: @@ -13347,6 +13369,7 @@ static void ggml_compute_forward_set( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: case GGML_TYPE_Q2_K: @@ -13611,6 +13634,7 @@ static void ggml_compute_forward_get_rows( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: case GGML_TYPE_Q2_K: @@ -14202,6 +14226,7 @@ static void ggml_compute_forward_clamp( case GGML_TYPE_Q4_1: case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: + case GGML_TYPE_Q6_0: case GGML_TYPE_Q8_0: case GGML_TYPE_Q8_1: case GGML_TYPE_Q2_K: @@ -22000,6 +22025,7 @@ size_t ggml_quantize_chunk( case GGML_TYPE_Q4_1: result = quantize_q4_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q5_0: result = quantize_q5_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q5_1: result = quantize_q5_1(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; + case GGML_TYPE_Q6_0: result = quantize_q6_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q8_0: result = quantize_q8_0(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q2_K: result = quantize_q2_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q3_K: result = quantize_q3_K(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; diff --git a/ggml/src/iqk/iqk_mul_mat.cpp b/ggml/src/iqk/iqk_mul_mat.cpp new file mode 100644 index 0000000000000..0c1c16251d143 --- /dev/null +++ b/ggml/src/iqk/iqk_mul_mat.cpp @@ -0,0 +1,8660 @@ +// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;coding:utf-8 -*- +// vi: set et ft=cpp fenc=utf-8 :vi +// +// +// Copyright (C) 2024 Iwan Kawrakow +// MIT license +// SPDX-License-Identifier: MIT +// + +#if defined IQK_IMPLEMENT +#undef IQK_IMPLEMENT +#endif + +#if defined __AVX2__ || defined __ARM_FEATURE_DOTPROD +#define IQK_IMPLEMENT +#endif + +#include +#include + +#if defined IQK_IMPLEMENT + +#include "ggml-impl.h" +#include "ggml-quants.h" +#include "iqk_mul_mat.h" + +#define GGML_COMMON_IMPL_C +#include "ggml-common.h" + +// clang-format off + +// This matrix - vector and matrix - matrix multiplication implementation +// for k-quants, i-quants, and legacy quants, makes prompt processing +// 150-350% faster (depending on quantization type) compared to mainline llama.cpp. +// It is AVX2 and ARM_NEON only for now. +// There are also implementations for fp16/32 x fp16/32 matrix multiplications +// on AVX2 and fp16 x fp16 on ARM_NEON. +// +// Main idea is that unpacking the quants and the block scales to +// be ready for dot products with the corresponding Q8_X quants +// takes time. Hence, if we are performing a QX x Q8_X matrix matrix +// multiplication (as needed for prompt processing), we can get +// a significant speedup by reusing the unpacked QX quants and scales +// for multiplication with several Q8_X columns. +// +// For fp16/fp32 matri multiplications tiling is used to improve +// performance. + +#include +#include + +#ifdef _MSC_VER +#define IQK_NOINLINE __declspec(noinline) +#define IQK_ALWAYS_INLINE inline +#else +#define IQK_NOINLINE __attribute__((__noinline__)) +#define IQK_ALWAYS_INLINE __attribute__((__always_inline__)) +#endif + +namespace { + +typedef struct { + int32_t i1; + int32_t i2; +} mmid_row_mapping; + +struct DataInfo { + float * s; + const char * cy; + size_t bs; + size_t by; + int cur_y = 0; + int ne11; + const mmid_row_mapping * row_mapping = nullptr; + size_t bs2 = 0; + + inline const char * src1_row(int iy) const { + if (!row_mapping) return cy + (cur_y + iy)*by; + int i11 = row_mapping[cur_y + iy].i1 % ne11; + int i12 = row_mapping[cur_y + iy].i2; + return cy + (i11 + i12*ne11)*by; + } + + inline void store(int ix, int iy, float result) const { + *(dst_row(iy) + ix) = result; + } + inline float * dst_row(int iy) const { + if (!row_mapping) return s + (cur_y + iy)*bs; + int i12 = row_mapping[cur_y + iy].i2; + int i1 = row_mapping[cur_y + iy].i1; + int i2 = i12; + return s + i1*bs + i2*bs2; + } +}; + +typedef void (*mul_mat_t)(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x); + +struct MulMat { + std::array funcs = {}; + inline void mul_mat_NxM(int n, const void * vx, size_t bx, DataInfo& info, int nrc_x, int nrc_y) { +#ifdef __aarch64__ + constexpr int k_x_step = 64; //8192; // Tiling does not seem to help on my M2 Max (but difference to tiling is small) +#else + constexpr int k_x_step = 64; // This works best on my Ryzen-7950X (but differences to other tile size are small) +#endif + int ny = funcs.size(); + while (!funcs[ny-1] && ny > 0) --ny; + int n_step = (nrc_y - info.cur_y)/ny; + if (n_step > 0) { + if (n_step*ny != nrc_y) { + ++n_step; + int ny1 = nrc_y/n_step; + int ny2 = ny1 + 1; + int my1 = n_step*ny2 - nrc_y; + int my2 = n_step - my1; + for (int ix = 0; ix < nrc_x; ix += k_x_step) { + auto this_info = info; + this_info.s += ix; + int this_nrc_x = ix + k_x_step <= nrc_x ? k_x_step : nrc_x - ix; + for (int iy = 0; iy < my1; ++iy) { + funcs[ny1-1](n, (const void *)((const char *)vx + ix*bx), bx, this_info, this_nrc_x); + this_info.cur_y += ny1; + } + for (int iy = 0; iy < my2; ++iy) { + funcs[ny2-1](n, (const void *)((const char *)vx + ix*bx), bx, this_info, this_nrc_x); + this_info.cur_y += ny2; + } + } + info.cur_y += nrc_y; + } + else { + for (int ix = 0; ix < nrc_x; ix += k_x_step) { + auto this_info = info; + this_info.s += ix; + int this_nrc_x = ix + k_x_step <= nrc_x ? k_x_step : nrc_x - ix; + for (int iy = 0; iy < n_step; ++iy) { + funcs[ny-1](n, (const void *)((const char *)vx + ix*bx), bx, this_info, this_nrc_x); + this_info.cur_y += ny; + } + } + info.cur_y += ny * n_step; + } + } + int n_left = nrc_y - info.cur_y; + if (n_left > 0) { + funcs[n_left-1](n, vx, bx, info, nrc_x); + } + } + static bool prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny); +private: + template static void set_functions(MulMat& m); +}; + +} + +bool iqk_mul_mat(long Nx, long Ny, long ne00, + int typeA, const void * A, long strideA, + int typeB, const void * B, long strideB, + float * C, long stride_C, int ith, int nth) { + + MulMat mm; + if (!MulMat::prepare(typeA, typeB, ne00, mm, Ny)) { + return false; + } + + size_t row_size_qx = strideA; //*ggml_type_size(ggml_type(typeA)); + size_t row_size_qy = strideB; //*ggml_type_size(ggml_type(typeB)); + //if (ith == 0) printf("%s: ne00 = %d, row_size_qx = %d, strideA = %d\n", __func__, int(ne00), int(row_size_qx), int(strideA)); + + auto nrc_x = (Nx + nth - 1)/nth; + auto first_x = ith*nrc_x; + if (first_x + nrc_x > Nx) nrc_x = Nx - first_x; + + DataInfo info{C + first_x, (const char *)B, (size_t)stride_C, row_size_qy, 0, 1, nullptr, 0}; + + mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny); + + return true; +} + +bool iqk_mul_mat_moe(long Nx, long Ny, long ne00, int ne11, + int typeA, const void * A, long strideA, + int typeB, const void * B, long strideB, + float * C, long nb1, long nb2, const void * vrow_mapping, int ith, int nth) { + const mmid_row_mapping * row_mapping = (const mmid_row_mapping *)vrow_mapping; + assert(row_mapping != nullptr); + + MulMat mm; + if (!MulMat::prepare(typeA, typeB, ne00, mm, Ny)) { + return false; + } + size_t row_size_qx = strideA; //*ggml_type_size(ggml_type(typeA)); + size_t row_size_qy = strideB; //*ggml_type_size(ggml_type(typeB)); + int nrc_x = (Nx + nth - 1)/nth; + int first_x = ith*nrc_x; + if (first_x + nrc_x > Nx) nrc_x = Nx - first_x; + DataInfo info{C + first_x, (const char *)B, nb1/sizeof(float), + row_size_qy, 0, ne11, row_mapping, nb2/sizeof(float)}; + mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny); + return true; +} + +namespace { + +inline void make_q4_scales(const uint8_t * scales8, uint32_t * aux32) { + const uint16_t * scales = (const uint16_t *)scales8; + const uint32_t a0 = scales[0] | (scales[1] << 16); + const uint32_t a1 = scales[2] | (scales[3] << 16); + const uint32_t a2 = scales[4] | (scales[5] << 16); + aux32[3] = ((a2 >> 4) & 0x0f0f0f0f) | ((a1 >> 2) & 0x30303030); + aux32[1] = ((a2 >> 0) & 0x0f0f0f0f) | ((a0 >> 2) & 0x30303030); + aux32[2] = a1 & 0x3f3f3f3f; + aux32[0] = a0 & 0x3f3f3f3f; +} + +#ifndef HAVE_FANCY_SIMD +const uint64_t keven_signs[128] = { + 0x0101010101010101, 0xff010101010101ff, 0xff0101010101ff01, 0x010101010101ffff, + 0xff01010101ff0101, 0x0101010101ff01ff, 0x0101010101ffff01, 0xff01010101ffffff, + 0xff010101ff010101, 0x01010101ff0101ff, 0x01010101ff01ff01, 0xff010101ff01ffff, + 0x01010101ffff0101, 0xff010101ffff01ff, 0xff010101ffffff01, 0x01010101ffffffff, + 0xff0101ff01010101, 0x010101ff010101ff, 0x010101ff0101ff01, 0xff0101ff0101ffff, + 0x010101ff01ff0101, 0xff0101ff01ff01ff, 0xff0101ff01ffff01, 0x010101ff01ffffff, + 0x010101ffff010101, 0xff0101ffff0101ff, 0xff0101ffff01ff01, 0x010101ffff01ffff, + 0xff0101ffffff0101, 0x010101ffffff01ff, 0x010101ffffffff01, 0xff0101ffffffffff, + 0xff01ff0101010101, 0x0101ff01010101ff, 0x0101ff010101ff01, 0xff01ff010101ffff, + 0x0101ff0101ff0101, 0xff01ff0101ff01ff, 0xff01ff0101ffff01, 0x0101ff0101ffffff, + 0x0101ff01ff010101, 0xff01ff01ff0101ff, 0xff01ff01ff01ff01, 0x0101ff01ff01ffff, + 0xff01ff01ffff0101, 0x0101ff01ffff01ff, 0x0101ff01ffffff01, 0xff01ff01ffffffff, + 0x0101ffff01010101, 0xff01ffff010101ff, 0xff01ffff0101ff01, 0x0101ffff0101ffff, + 0xff01ffff01ff0101, 0x0101ffff01ff01ff, 0x0101ffff01ffff01, 0xff01ffff01ffffff, + 0xff01ffffff010101, 0x0101ffffff0101ff, 0x0101ffffff01ff01, 0xff01ffffff01ffff, + 0x0101ffffffff0101, 0xff01ffffffff01ff, 0xff01ffffffffff01, 0x0101ffffffffffff, + 0xffff010101010101, 0x01ff0101010101ff, 0x01ff01010101ff01, 0xffff01010101ffff, + 0x01ff010101ff0101, 0xffff010101ff01ff, 0xffff010101ffff01, 0x01ff010101ffffff, + 0x01ff0101ff010101, 0xffff0101ff0101ff, 0xffff0101ff01ff01, 0x01ff0101ff01ffff, + 0xffff0101ffff0101, 0x01ff0101ffff01ff, 0x01ff0101ffffff01, 0xffff0101ffffffff, + 0x01ff01ff01010101, 0xffff01ff010101ff, 0xffff01ff0101ff01, 0x01ff01ff0101ffff, + 0xffff01ff01ff0101, 0x01ff01ff01ff01ff, 0x01ff01ff01ffff01, 0xffff01ff01ffffff, + 0xffff01ffff010101, 0x01ff01ffff0101ff, 0x01ff01ffff01ff01, 0xffff01ffff01ffff, + 0x01ff01ffffff0101, 0xffff01ffffff01ff, 0xffff01ffffffff01, 0x01ff01ffffffffff, + 0x01ffff0101010101, 0xffffff01010101ff, 0xffffff010101ff01, 0x01ffff010101ffff, + 0xffffff0101ff0101, 0x01ffff0101ff01ff, 0x01ffff0101ffff01, 0xffffff0101ffffff, + 0xffffff01ff010101, 0x01ffff01ff0101ff, 0x01ffff01ff01ff01, 0xffffff01ff01ffff, + 0x01ffff01ffff0101, 0xffffff01ffff01ff, 0xffffff01ffffff01, 0x01ffff01ffffffff, + 0xffffffff01010101, 0x01ffffff010101ff, 0x01ffffff0101ff01, 0xffffffff0101ffff, + 0x01ffffff01ff0101, 0xffffffff01ff01ff, 0xffffffff01ffff01, 0x01ffffff01ffffff, + 0x01ffffffff010101, 0xffffffffff0101ff, 0xffffffffff01ff01, 0x01ffffffff01ffff, + 0xffffffffffff0101, 0x01ffffffffff01ff, 0x01ffffffffffff01, 0xffffffffffffffff, +}; +#endif + +} + +#if defined __x86_64__ + +#if defined HAVE_FANCY_SIMD + #undef HAVE_FANCY_SIMD +#endif +#if defined(__AVX512F__) && defined(__AVX512VNNI__) && defined(__AVX512VL__) && defined(__AVX512BW__) && defined(__AVX512DQ__) + #define HAVE_FANCY_SIMD +#endif + +namespace { + +inline float hsum_float_4(__m128 x) { + x = _mm_add_ps(x, _mm_movehl_ps(x, x)); + x = _mm_add_ss(x, _mm_movehdup_ps(x)); + return _mm_cvtss_f32(x); +} +inline float hsum_float_8(__m256 x) { + return hsum_float_4(_mm_add_ps(_mm256_castps256_ps128(x), _mm256_extractf128_ps(x, 1))); +} +inline int hsum_i32_8(const __m256i a) { + const __m128i sum128 = _mm_add_epi32(_mm256_castsi256_si128(a), _mm256_extractf128_si256(a, 1)); + const __m128i hi64 = _mm_unpackhi_epi64(sum128, sum128); + const __m128i sum64 = _mm_add_epi32(hi64, sum128); + const __m128i hi32 = _mm_shuffle_epi32(sum64, _MM_SHUFFLE(2, 3, 0, 1)); + return _mm_cvtsi128_si32(_mm_add_epi32(sum64, hi32)); +} +inline float hmax_float_8(__m256 x) { + __m128 max4 = _mm_max_ps(_mm256_extractf128_ps(x, 1), _mm256_castps256_ps128(x)); + max4 = _mm_max_ps( max4, _mm_movehl_ps(max4, max4)); + max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4)); + return _mm_cvtss_f32(max4); +} + +#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1) + +template struct Q8 { + + constexpr static int nrc_y = nrc; + + Q8(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy); + } + +#ifdef HAVE_FANCY_SIMD + inline __m512i load_quants64(int iy, int i, int j) const { return _mm512_loadu_si512((const __m512i*)y[iy][i].qs + j); } +#endif + inline __m256i load_quants(int iy, int i, int j) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].qs + j); } + inline __m256i load_bsums(int iy, int i) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].bsums); } + inline float scale(int iy, int i) const { return y[iy][i].d; } + + const block_q8 * y[nrc_y]; +}; + +struct Scales8KBase { + template + inline void accum_mins(const __m128i& mins128, const Q8& q8, int i, float c, __m256 * accd) const { + const __m256i mins = MM256_SET_M128I(_mm_shuffle_epi8(mins128, shuffles[1]), _mm_shuffle_epi8(mins128, shuffles[0])); + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i q8s = q8.load_bsums(iy, i); + const __m256i prod = _mm256_madd_epi16(mins, q8s); + accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(c*q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accd[iy]); + } + } + inline __m256i shuffle(__m128i mins) const { + return MM256_SET_M128I(_mm_shuffle_epi8(mins, shuffles[1]), _mm_shuffle_epi8(mins, shuffles[0])); + } + const __m128i shuffles[2] = {_mm_set_epi32(0x07060706, 0x05040504, 0x03020302, 0x01000100), + _mm_set_epi32(0x0f0e0f0e, 0x0d0c0d0c, 0x0b0a0b0a, 0x09080908)}; +}; + +// Handles q4_K and q5_K scales/mins +struct Scales8K { + template + inline __m256i process_mins_and_scales(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) { + make_q4_scales(data, utmp); + const __m256i mins_and_scales = _mm256_cvtepu8_epi16(_mm_set_epi32(utmp[3], utmp[2], utmp[1], utmp[0])); + const __m128i mins128 = _mm256_extracti128_si256(mins_and_scales, 1); + accum_mins(mins128, q8, i, c, accd); + const __m128i sc128 = _mm256_extracti128_si256(mins_and_scales, 0); + return MM256_SET_M128I(sc128, sc128); + } +#ifdef HAVE_FANCY_SIMD + template + inline __m512i process_mins_and_scales_64(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) { + auto scales = process_mins_and_scales(data, c, i, q8, accd); + return _mm512_inserti32x8(_mm512_castsi256_si512(scales), scales, 1); + } +#endif + template + inline void accum_mins(const __m128i& mins128, const Q8& q8, int i, float c, __m256 * accd) const { + base.accum_mins(mins128, q8, i, c, accd); + } +#ifdef HAVE_FANCY_SIMD + const __m512i shuffles512[2] = { + _mm512_set_epi64(0x0706070607060706, 0x0302030203020302, 0x0706070607060706, 0x0302030203020302, + 0x0504050405040504, 0x0100010001000100, 0x0504050405040504, 0x0100010001000100), + _mm512_set_epi64(0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a, 0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a, + 0x0d0c0d0c0d0c0d0c, 0x0908090809080908, 0x0d0c0d0c0d0c0d0c, 0x0908090809080908) + }; +#endif + Scales8KBase base; + + uint32_t utmp[4]; +}; + +template +inline void process_mins_16(const __m256i& all_scales, const Q8& q8, int i, float d, __m256 * accm) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i prod = _mm256_madd_epi16(all_scales, q8.load_bsums(iy, i)); + accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]); + } +} +inline void prepare_scales_16(const __m256i& all_scales, __m256i * scales) { + const __m128i l_scales = _mm256_extracti128_si256(all_scales, 0); + const __m128i h_scales = _mm256_extracti128_si256(all_scales, 1); + scales[0] = MM256_SET_M128I(l_scales, l_scales); + scales[1] = MM256_SET_M128I(h_scales, h_scales); +} + +struct ScaleQ3 { + inline __m128i make_scales(const uint16_t * s8) const { + const uint16_t * scales16 = (const uint16_t *)s8; + uint32_t aux0 = scales16[0] | (scales16[1] << 16); + uint32_t aux1 = scales16[2] | (scales16[3] << 16); + uint32_t aux2 = scales16[4] | (scales16[5] << 16); + __m128i scales128 = _mm_set_epi32( + ((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030), + ((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030), + (aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030), + (aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030)); + return _mm_add_epi8(scales128, m32); + } + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct ScaleIQ4XS { + inline __m128i make_scales(const uint32_t scales_l, const uint16_t scales_h) { + uint32_t tmp32 = scales_h | (scales_h << 14); + const __m128i sh = _mm_slli_epi16(_mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(tmp32), hshift), hmask), 4); + const __m128i sl = _mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(scales_l), lshift), lmask); + return _mm_add_epi16(_mm_or_si128(sh, _mm_cvtepi8_epi16(_mm_shuffle_epi8(sl, lshuffle))), m32); + } + const __m128i hshift = _mm_set_epi32(12, 8, 4, 0); + const __m128i lshift = _mm_set_epi32(4, 0, 4, 0); + const __m128i hmask = _mm_set1_epi16(0x03); + const __m128i lmask = _mm_set1_epi8(0xf); + const __m128i lshuffle = _mm_set_epi32(0x07030602, 0x05010400, 0x07030602, 0x05010400); + const __m128i m32 = _mm_set1_epi16(-32); +}; + +template +struct BaseDequantizer { + BaseDequantizer(const void * vx, size_t bx) : vx(vx), bx(bx) {} + inline void new_row(int ix) { + if constexpr (per_row_scale) { + const float * dptr = (const float *)((const char *)vx + bx*ix); + d = *dptr; + x = (const Block *)(dptr + 1); + } else { + x = (const Block *)((const char *)vx + bx*ix); + } + } + + const void * vx; + const size_t bx; + const Block * x; + + float d; +}; + +inline __m256i get_scale_shuffle_8(int i) { + return _mm256_set1_epi16((2*i) | ((2*i+1) << 8)); +} + +inline void set_scales_8(const __m256i& all_scales, int j, __m256i * scales) { + scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+0)); + scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+1)); + scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+2)); + scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+3)); +} + +inline __m256i get_scale_shuffle_16(int i) { + static const uint8_t k_shuffle[128] = { + 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, + 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, + 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11, + 12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13, 14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15, + }; + return _mm256_loadu_si256((const __m256i*)k_shuffle + i); +} + +inline void set_scales_16(const __m256i& all_scales, __m256i * scales) { + scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(0)); + scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(1)); + scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(2)); + scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(3)); +} + +template +inline void multiply_add(const Bits& bits, const __m256i * scales, int j, int i, const Q8& q8, __m256i * sumi) { + if (j == 0) { +#if defined(__AVX512VNNI__) && defined(__AVX512VL__) + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + sumi[iy] = _mm256_dpwssd_epi32(_mm256_setzero_si256(), scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 0))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 1))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 2))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 3))); + } +#else + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 0))); + const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 1))); + const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 2))); + const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 3))); + sumi[iy] = _mm256_add_epi32(_mm256_add_epi32(p1, p3), _mm256_add_epi32(p2, p4)); + } +#endif + } else { +#if defined(__AVX512VNNI__) && defined(__AVX512VL__) + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 5))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 6))); + sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 7))); + } +#else + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4))); + const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 5))); + const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 6))); + const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 7))); + sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p1, p3)); + sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p2, p4)); + } +#endif + } +} + +struct SignHelper { + inline __m256i make_signs(uint32_t sign_bits) const { + auto aux256 = _mm256_set1_epi32(sign_bits); + aux256 = _mm256_and_si256(_mm256_shuffle_epi8(aux256, mask1), mask2); + return _mm256_or_si256(_mm256_cmpeq_epi8(aux256, mask2), mone); + } +// inline __m256i make_signs(const uint16_t * sign_bits) const { +//#ifdef HAVE_FANCY_SIMD +//#else +// return make_signs(sign_bits[0] | (sign_bits[1] << 16)); +//#endif +// } + inline __m256i sign_value(const uint16_t * sign_bits, const __m256i& value) const { +#ifdef HAVE_FANCY_SIMD + const __mmask32 * mask = (const __mmask32 *)sign_bits; + return _mm256_mask_sub_epi8(value, mask[0], _mm256_setzero_si256(), value); +#else + return _mm256_sign_epi8(value, make_signs(sign_bits[0] | (sign_bits[1] << 16))); +#endif + } + inline void sign_4_values(const uint16_t * sign_bits, __m256i * values) const { +#ifdef HAVE_FANCY_SIMD + const __mmask32 * mask = (const __mmask32 *)sign_bits; + values[0] = _mm256_mask_sub_epi8(values[0], mask[0], _mm256_setzero_si256(), values[0]); + values[1] = _mm256_mask_sub_epi8(values[1], mask[1], _mm256_setzero_si256(), values[1]); + values[2] = _mm256_mask_sub_epi8(values[2], mask[2], _mm256_setzero_si256(), values[2]); + values[3] = _mm256_mask_sub_epi8(values[3], mask[3], _mm256_setzero_si256(), values[3]); +#else + auto s128 = _mm_loadu_si128((const __m128i *)sign_bits); + auto s256 = MM256_SET_M128I(s128, s128); + __m256i aux256; + auto shuffle = mask1; + auto step = _mm256_set1_epi8(4); + aux256 = _mm256_and_si256(_mm256_shuffle_epi8(s256, shuffle), mask2); shuffle = _mm256_add_epi8(shuffle, step); + values[0] = _mm256_sign_epi8(values[0], _mm256_or_si256(_mm256_cmpeq_epi8(aux256, mask2), mone)); + aux256 = _mm256_and_si256(_mm256_shuffle_epi8(s256, shuffle), mask2); shuffle = _mm256_add_epi8(shuffle, step); + values[1] = _mm256_sign_epi8(values[1], _mm256_or_si256(_mm256_cmpeq_epi8(aux256, mask2), mone)); + aux256 = _mm256_and_si256(_mm256_shuffle_epi8(s256, shuffle), mask2); shuffle = _mm256_add_epi8(shuffle, step); + values[2] = _mm256_sign_epi8(values[2], _mm256_or_si256(_mm256_cmpeq_epi8(aux256, mask2), mone)); + aux256 = _mm256_and_si256(_mm256_shuffle_epi8(s256, shuffle), mask2); shuffle = _mm256_add_epi8(shuffle, step); + values[3] = _mm256_sign_epi8(values[3], _mm256_or_si256(_mm256_cmpeq_epi8(aux256, mask2), mone)); +#endif + } + const __m256i mask1 = _mm256_set_epi64x(0x0303030303030303, 0x0202020202020202, 0x0101010101010101, 0x0000000000000000); + const __m256i mask2 = _mm256_set1_epi64x(0x8040201008040201ull); + const __m256i mone = _mm256_set1_epi8(1); +}; + +struct SimpleBits { + __m256i values[4]; +}; + +__m128i inline load_iq4nl_values_128() { + static const uint8_t kvalues_iq4nl[16] = {1, 24, 45, 63, 79, 93, 106, 118, 129, 141, 153, 166, 181, 197, 217, 241}; + return _mm_loadu_si128((const __m128i *)kvalues_iq4nl); +} + +__m256i inline load_iq4nl_values_256() { + auto val128 = load_iq4nl_values_128(); + return MM256_SET_M128I(val128, val128); +} + +#ifdef HAVE_FANCY_SIMD +//====================================== Zen4 ================================================== + +struct BlockPermuter { + const __m512i permute1 = _mm512_set_epi64(11, 10, 9, 8, 3, 2, 1, 0); + const __m512i permute2 = _mm512_set_epi64(15, 14, 13, 12, 7, 6, 5, 4); +}; + +struct Q4Bits { + inline void prepare(const uint8_t * q4) { + auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0); + auto tmp1 = _mm512_and_si512(q4bits, ml); + auto tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml); + values[0] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2); + values[1] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2); + q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1); + tmp1 = _mm512_and_si512(q4bits, ml); + tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml); + values[2] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2); + values[3] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2); + } + inline void prepare64(const uint8_t * q4) { + auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0); + values[0] = _mm512_and_si512(q4bits, ml); + values[1] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml); + q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1); + values[2] = _mm512_and_si512(q4bits, ml); + values[3] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml); + } + __m512i values[4]; + const __m512i ml = _mm512_set1_epi8(0xf); + BlockPermuter perm; +}; + +struct Q2Bits { + inline void prepare(const uint8_t * q2) { + + auto q2bits = _mm512_loadu_si512((const __m512i*)q2); + auto tmp = _mm512_srli_epi16(q2bits, 2); + + values[0] = _mm512_permutex2var_epi64(q2bits, perm.permute1, tmp); + values[2] = _mm512_permutex2var_epi64(q2bits, perm.permute2, tmp); + values[1] = _mm512_and_si512(_mm512_srli_epi16(values[0], 4), ml); + values[3] = _mm512_and_si512(_mm512_srli_epi16(values[2], 4), ml); + values[0] = _mm512_and_si512(values[0], ml); + values[2] = _mm512_and_si512(values[2], ml); + } + __m512i values[4]; + const __m512i ml = _mm512_set1_epi8(0x03); + BlockPermuter perm; +}; + +struct DequantizerQ4K final : public BaseDequantizer { + DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + bits.prepare(x[i].qs); + auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd); + scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]); + scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]); + } + + Q4Bits bits; + Scales8K s8k; +}; + +__m512i inline load_iq4nl_values_512() { + auto val256 = load_iq4nl_values_256(); + return _mm512_inserti32x8(_mm512_castsi256_si512(val256), val256, 1); +} + + +struct DequantizerIQ4XS final : public BaseDequantizer { + DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_iq4nl_values_512()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs); + auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h); + s8k.accum_mins(scales128, q8, i, -128.f*d, accd); + auto scales256 = MM256_SET_M128I(scales128, scales128); + auto all_scales = _mm512_inserti32x8(_mm512_castsi256_si512(scales256), scales256, 1); + scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]); + scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]); + } + inline void prepare(const uint8_t * q4) { + bits.prepare64(q4); + // We now have in bits.valuse[0]: 0...15, 32...47, 64...79, 96...111 + // bits.valuse[1]: 16..31, 48...63, 80...95, 112..127 + // etc. + auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]); + bits.values[1] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1])); + bits.values[0] = _mm512_shuffle_epi8(values, tmp); + tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]); + bits.values[3] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3])); + bits.values[2] = _mm512_shuffle_epi8(values, tmp); + } + + Q4Bits bits; + Scales8K s8k; + ScaleIQ4XS siq4; + const __m512i values; + const __m512i permute1 = _mm512_set_epi64(11, 10, 3, 2, 9, 8, 1, 0); + const __m512i permute2 = _mm512_set_epi64(15, 14, 7, 6, 13, 12, 5, 4); +}; + +struct HighBit5 { + inline void apply(const uint8_t * h, Q4Bits& bits) { + auto hbits256 = _mm256_loadu_si256((const __m256i *)h); + auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1); + bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh)); + bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh)); + bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(hbits, mh)); + bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh)); + } + const __m512i mh = _mm512_set1_epi8(0x10); +}; + +struct HighBit3 { + inline void apply(const uint8_t * h, Q2Bits& bits) { + auto hbits256 = _mm256_loadu_si256((const __m256i *)h); + auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1); + bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh)); + bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(hbits, mh)); + bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh)); + bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 4), mh)); + } + const __m512i mh = _mm512_set1_epi8(0x04); +}; + +struct DequantizerQ5K final : public BaseDequantizer { + DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + bits.prepare(x[i].qs); + hbits.apply(x[i].qh, bits); + auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd); + scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]); + scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]); + } + + Q4Bits bits; + HighBit5 hbits; + Scales8K s8k; +}; + +struct Scale16 { + inline void make_scales(const __m128i& scales8, __m512i * scales) const { + auto all_scales8 = MM256_SET_M128I(scales8, scales8); + auto scales1 = _mm256_shuffle_epi8(all_scales8, shuffle1); + auto scales2 = _mm256_shuffle_epi8(all_scales8, shuffle2); + scales[0] = _mm512_cvtepi8_epi16(scales1); + scales[1] = _mm512_cvtepi8_epi16(scales2); + } + template + inline void process_mins_and_scales(int i, float c, const __m128i& mins8, const __m128i& scales8, + const Q8& q8, __m256 * accm, __m512i * scales) const { + process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, c, accm); + make_scales(scales8, scales); + } + const __m256i shuffle1 = _mm256_set_epi32(0x07070707, 0x03030303, 0x06060606, 0x02020202, + 0x05050505, 0x01010101, 0x04040404, 0x00000000); + const __m256i shuffle2 = _mm256_set_epi32(0x0f0f0f0f, 0x0b0b0b0b, 0x0e0e0e0e, 0x0a0a0a0a, + 0x0d0d0d0d, 0x09090909, 0x0c0c0c0c, 0x08080808); +}; + +struct DequantizerQ2K final : public BaseDequantizer { + DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + bits.prepare(x[i].qs); + const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales); + const __m128i scales8 = _mm_and_si128(mins_and_scales, m4); + const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4); + sc16.process_mins_and_scales(i, -GGML_FP16_TO_FP32(x[i].dmin), mins8, scales8, q8, accm, scales); + } + + Q2Bits bits; + Scale16 sc16; + const __m128i m4 = _mm_set1_epi8(0xf); + +}; + +struct DequantizerIQ2TN final : public BaseDequantizer { + DequantizerIQ2TN(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, [[maybe_unused]] const Q8& q8, [[maybe_unused]] __m256 * accm, [[maybe_unused]] __m512i * scales) { + new_block(i); + } + inline void new_block(int i) { + bits.prepare(x[i].qs); + } + Q2Bits bits; +}; + +struct DequantizerQ3K final : public BaseDequantizer { + DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + bits.prepare(x[i].qs); + hbits.apply(x[i].hmask, bits); + auto scales128 = sc3.make_scales((const uint16_t *)x[i].scales); + sc16.process_mins_and_scales(i, -4.f*d, scales128, scales128, q8, accm, scales); + } + + Q2Bits bits; + HighBit3 hbits; + ScaleQ3 sc3; + Scale16 sc16; + const __m128i m4 = _mm_set1_epi8(0xf); + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct DequantizerQ6K final : public BaseDequantizer { + DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + bits.prepare64(x[i].ql); + add_high_bits(x[i].qh, bits); + auto scales128 = _mm_loadu_si128((const __m128i *)x[i].scales); + sc16.process_mins_and_scales(i, -32.f*d, scales128, scales128, q8, accm, scales); + } + + inline void add_high_bits(const uint8_t * qh, Q4Bits& bits) const { + auto hbits = _mm512_loadu_si512((const __m512i *)qh); + auto tmp1 = _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh); + auto tmp2 = _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh); + bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2)); + bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2)); + tmp1 = _mm512_and_si512(hbits, mh); + tmp2 = _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh); + bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2)); + bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2)); + } + + Q4Bits bits; + HighBit3 hbits; + Scale16 sc16; + + const __m512i mh = _mm512_set1_epi8(0x30); + +}; + +struct IQXKScales { + IQXKScales(uint8_t shift, int8_t min_val) : eshift(_mm256_set1_epi16(shift)), min(_mm256_set1_epi16(min_val)) {} + template + inline void process(int i, float d, uint16_t extra, __m128i scales8, const Q8& q8, __m256 * accm, __m512i * scales) const { + auto scales16 = _mm256_cvtepi8_epi16(_mm_shuffle_epi8(scales8, scale_shuffle)); + scales16 = _mm256_mullo_epi16(scales16, _mm256_mask_add_epi16(min, extra, min, eshift)); + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i prod = _mm256_madd_epi16(scales16, q8.load_bsums(iy, i)); + accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]); + } + scales16 = MM256_SET_M128I(scales8, scales8); + scales[0] = _mm512_cvtepi8_epi16(_mm256_shuffle_epi8(scales16, shuffle1)); + scales[1] = _mm512_cvtepi8_epi16(_mm256_shuffle_epi8(scales16, shuffle2)); + } + const __m256i eshift; + const __m256i min; + const __m128i scale_shuffle = _mm_set_epi32(0x0f070e06, 0x0d050c04, 0x0b030a02, 0x09010800); + const __m128i emask = _mm_set_epi32(0x80804040, 0x20201010, 0x08080404, 0x02020101); + const __m128i eshuffle = _mm_set_epi32(0x0f0d0b09, 0x07050301, 0x0e0c0a08, 0x06040200); + const __m256i shuffle1 = _mm256_set_epi64x(0x0b0b0b0b09090909, 0x0303030301010101, 0x0a0a0a0a08080808, 0x0202020200000000); + const __m256i shuffle2 = _mm256_set_epi64x(0x0f0f0f0f0d0d0d0d, 0x0707070705050505, 0x0e0e0e0e0c0c0c0c, 0x0606060604040404); +}; +struct IQXKScales2 { + IQXKScales2(uint8_t shift, int8_t min_val) : eshift(_mm256_set1_epi16(shift)), min(_mm256_set1_epi16(min_val)) {} + template + inline void process(int i, float d, uint16_t extra, __m128i scales8, const Q8& q8, __m256 * accm, __m512i * scales) const { + process(i, d, extra, _mm256_cvtepi8_epi16(_mm_shuffle_epi8(scales8, scale_shuffle)), q8, accm, scales); + } + template + inline void process(int i, float d, uint16_t extra, __m256i scales16, const Q8& q8, __m256 * accm, __m512i * scales) const { + auto scales_s = _mm256_mullo_epi16(scales16, _mm256_mask_add_epi16(min, extra, min, eshift)); + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i prod = _mm256_madd_epi16(scales_s, q8.load_bsums(iy, i)); + accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]); + } + auto aux_1 = MM256_SET_M128I(_mm256_castsi256_si128(scales16), _mm256_castsi256_si128(scales16)); + auto aux_2 = MM256_SET_M128I(_mm256_extracti128_si256(scales16, 1), _mm256_extracti128_si256(scales16, 1)); + auto scales16_1 = _mm512_inserti32x8(_mm512_castsi256_si512(aux_1), aux_1, 1); + auto scales16_2 = _mm512_inserti32x8(_mm512_castsi256_si512(aux_2), aux_2, 1); + scales[0] = _mm512_shuffle_epi8(scales16_1, shuffles[0]); + scales[1] = _mm512_shuffle_epi8(scales16_1, shuffles[1]); + scales[2] = _mm512_shuffle_epi8(scales16_2, shuffles[0]); + scales[3] = _mm512_shuffle_epi8(scales16_2, shuffles[1]); + } + const __m256i eshift; + const __m256i min; + const __m128i scale_shuffle = _mm_set_epi32(0x0f070e06, 0x0d050c04, 0x0b030a02, 0x09010800); + const __m128i emask = _mm_set_epi32(0x80804040, 0x20201010, 0x08080404, 0x02020101); + const __m128i eshuffle = _mm_set_epi32(0x0f0d0b09, 0x07050301, 0x0e0c0a08, 0x06040200); + const __m512i shuffles[2] = { + _mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_setzero_si512(), + _mm_set1_epi16(0x0100), 0), _mm_set1_epi16(0x0302), 1), _mm_set1_epi16(0x0504), 2), _mm_set1_epi16(0x0706), 3), + _mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_inserti32x4(_mm512_setzero_si512(), + _mm_set1_epi16(0x0908), 0), _mm_set1_epi16(0x0b0a), 1), _mm_set1_epi16(0x0d0c), 2), _mm_set1_epi16(0x0f0e), 3) + }; +}; + +struct DequantizerIQ2K final : public BaseDequantizer { + DequantizerIQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(IQXKScales(5, -32)), values(load_values()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales), q8, accm, scales); + } + inline void prepare(const uint8_t * q2) { + bits.prepare(q2); + bits.values[0] = _mm512_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm512_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm512_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm512_shuffle_epi8(values, bits.values[3]); + } + static inline __m512i load_values() { + static const uint8_t kvalues_iq2nl[16] = {1, 19, 33, 49, 0, 0, 0, 0, 6, 24, 38, 54, 0, 0, 0, 0}; + auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq2nl); + auto val256 = MM256_SET_M128I(val128, val128); + return _mm512_inserti32x8(_mm512_castsi256_si512(val256), val256, 1); + } + inline __m128i make_scales(const uint8_t * scales_l) const { + uint64_t aux64; std::memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), _mm_set1_epi8(0xf)); + return _mm_add_epi8(_mm_slli_epi16(scl, 1), m15); + } + Q2Bits bits; + const IQXKScales iqxk; + + const __m512i values; + const __m128i m15 = _mm_set1_epi8(-15); +}; + +struct DequantizerIQ3K final : public BaseDequantizer { + DequantizerIQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(4, -64), values(load_values()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs, x[i].qh); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_h, x[i].scales_l), q8, accm, scales); + } + inline void prepare(const uint8_t * q2, const uint8_t * qh) { + bits.prepare(q2); + auto h256 = _mm256_loadu_si256((const __m256i *)qh); + auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(h256), _mm256_srli_epi16(h256, 1), 1); + bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), hmask)); + bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(hbits, hmask)); + bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), hmask)); + bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 4), hmask)); + bits.values[0] = _mm512_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm512_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm512_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm512_shuffle_epi8(values, bits.values[3]); + } + static inline __m512i load_values() { + static const uint8_t kvalues_iq3nl[16] = {1, 24, 41, 54, 65, 77, 92, 111, 5, 28, 45, 58, 69, 81, 96, 115}; + auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq3nl); + auto val256 = MM256_SET_M128I(val128, val128); + return _mm512_inserti32x8(_mm512_castsi256_si512(val256), val256, 1); + } + inline __m128i make_scales(uint16_t signs, const uint8_t * scales_l) const { + uint64_t aux64; std::memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), _mm_set1_epi8(0xf)); + scl = _mm_add_epi8(_mm_slli_epi16(scl, 1), m1); + const __m128i sc_signs = _mm_cmpeq_epi8(_mm_and_si128(_mm_set1_epi16(signs), sign_mask), sign_mask); + const __m128i sch = _mm_shuffle_epi8(_mm_or_si128(sc_signs, _mm_set1_epi8(1)), hshuff); + return _mm_sign_epi8(scl, sch); + } + Q2Bits bits; + const IQXKScales2 iqxk; + + const __m512i values; + const __m512i hmask = _mm512_set1_epi8(4); + const __m128i m1 = _mm_set1_epi8(1); + const __m128i sign_mask = _mm_set_epi64x(0x8080404020201010, 0x0808040402020101); + const __m128i hshuff = _mm_loadu_si128((const __m128i*)k_shuff); + constexpr static uint8_t k_shuff[16] = {0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15}; +}; + +struct DequantizerIQ4K final : public BaseDequantizer { + DequantizerIQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(4, -128), values(load_iq4nl_values_512()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_l, (const uint16_t *)x[i].scales_h), q8, accm, scales); + } + inline void prepare(const uint8_t * q4) { + bits.prepare64(q4); + // We now have in bits.valuse[0]: 0...15, 32...47, 64...79, 96...111 + // bits.valuse[1]: 16..31, 48...63, 80...95, 112..127 + // etc. + auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]); + bits.values[1] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1])); + bits.values[0] = _mm512_shuffle_epi8(values, tmp); + tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]); + bits.values[3] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3])); + bits.values[2] = _mm512_shuffle_epi8(values, tmp); + } + __m128i make_scales(const uint8_t * scales_l, const uint16_t * scales_h) const { + uint64_t aux64; + memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), maskl); + const uint32_t aux32 = scales_h[0] | (scales_h[1] << 16); + auto aux = _mm_and_si128(_mm_set_epi32(aux32 >> 2, aux32, aux32 << 2, aux32 << 4), maskh); + auto sch = _mm_shuffle_epi8(aux, iqxk.scale_shuffle); + return _mm_add_epi8(_mm_or_si128(scl, sch), m32); + } + + Q4Bits bits; + const IQXKScales2 iqxk; + const __m512i values; + const __m512i permute1 = _mm512_set_epi64(11, 10, 3, 2, 9, 8, 1, 0); + const __m512i permute2 = _mm512_set_epi64(15, 14, 7, 6, 13, 12, 5, 4); + const __m128i maskl = _mm_set1_epi8(0xf); + const __m128i maskh = _mm_set1_epi8(0x30); + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct DequantizerIQ5K final : public BaseDequantizer { + DequantizerIQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(2, -128) { load_values(values); } + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs, x[i].qh); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_l, (const uint16_t *)x[i].scales_h), q8, accm, scales); + } + inline void prepare(const uint8_t * q4, const uint8_t * qh) { + bits.prepare64(q4); + auto h256 = _mm256_loadu_si256((const __m256i *)qh); + auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(h256), _mm256_srli_epi16(h256, 2), 1); + auto m1 = _mm512_cmpeq_epi8_mask(_mm512_and_si512(hbits, hmask1), hmask1); + auto m2 = _mm512_cmpeq_epi8_mask(_mm512_and_si512(hbits, hmask2), hmask2); + bits.values[0] = _mm512_mask_shuffle_epi8(_mm512_maskz_shuffle_epi8(_knot_mask64(m1), values[0], bits.values[0]), m1, values[1], bits.values[0]); + bits.values[1] = _mm512_mask_shuffle_epi8(_mm512_maskz_shuffle_epi8(_knot_mask64(m2), values[0], bits.values[1]), m2, values[1], bits.values[1]); + hbits = _mm512_srli_epi16(hbits, 4); + m1 = _mm512_cmpeq_epi8_mask(_mm512_and_si512(hbits, hmask1), hmask1); + m2 = _mm512_cmpeq_epi8_mask(_mm512_and_si512(hbits, hmask2), hmask2); + bits.values[2] = _mm512_mask_shuffle_epi8(_mm512_maskz_shuffle_epi8(_knot_mask64(m1), values[0], bits.values[2]), m1, values[1], bits.values[2]); + bits.values[3] = _mm512_mask_shuffle_epi8(_mm512_maskz_shuffle_epi8(_knot_mask64(m2), values[0], bits.values[3]), m2, values[1], bits.values[3]); + // We now have in bits.valuse[0]: 0...31, 64...95 + // bits.valuse[1]: 32..63, 96..127 + // etc. + auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]); + bits.values[1] = _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1]); + bits.values[0] = tmp; + tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]); + bits.values[3] = _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3]); + bits.values[2] = tmp; + } + __m128i make_scales(const uint8_t * scales_l, const uint16_t * scales_h) const { + uint64_t aux64; + memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), maskl); + const uint32_t aux32 = scales_h[0] | (scales_h[1] << 16); + auto aux = _mm_and_si128(_mm_set_epi32(aux32 >> 2, aux32, aux32 << 2, aux32 << 4), maskh); + auto sch = _mm_shuffle_epi8(aux, iqxk.scale_shuffle); + return _mm_add_epi8(_mm_or_si128(scl, sch), m32); + } + static void load_values(__m512i * values) { + static const uint8_t kvalues_iq5nl[32] = { + 2, 14, 25, 36, 45, 54, 63, 71, 78, 85, 92, 98, 104, 110, 116, 122, 127, + 133, 139, 145, 151, 157, 164, 171, 179, 187, 196, 205, 215, 225, 237, 249, + }; + auto values128_1 = _mm_loadu_si128((const __m128i *)kvalues_iq5nl + 0); + auto values128_2 = _mm_loadu_si128((const __m128i *)kvalues_iq5nl + 1); + auto values256_1 = MM256_SET_M128I(values128_1, values128_1); + auto values256_2 = MM256_SET_M128I(values128_2, values128_2); + values[0] = _mm512_inserti32x8(_mm512_castsi256_si512(values256_1), values256_1, 1); + values[1] = _mm512_inserti32x8(_mm512_castsi256_si512(values256_2), values256_2, 1); + } + + Q4Bits bits; + const IQXKScales2 iqxk; + __m512i values[2]; + const __m512i hmask1 = _mm512_set1_epi8(1); + const __m512i hmask2 = _mm512_set1_epi8(2); + const __m512i permute1 = _mm512_set_epi64(11, 10, 9, 8, 3, 2, 1, 0); + const __m512i permute2 = _mm512_set_epi64(15, 14, 13, 12, 7, 6, 5, 4); + const __m128i maskl = _mm_set1_epi8(0xf); + const __m128i maskh = _mm_set1_epi8(0x30); + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct DequantizerIQ6K final : public BaseDequantizer { + DequantizerIQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(1, -128) { load_values(values); } + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + prepare(x[i].qs, x[i].qh); + auto scales8 = _mm_loadu_si128((const __m128i*)x[i].scales); + iqxk.process(i, d, x[i].extra, _mm256_cvtepi8_epi16(scales8), q8, accm, scales); + } + inline __m512i make_one(__m512i l, __m512i h) const { + auto p = _mm512_shuffle_epi8(values[0], l); + p = _mm512_mask_shuffle_epi8(p, _mm512_cmpeq_epi8_mask(_mm512_and_si512(h, masks[0]), masks[0]), values[1], l); + p = _mm512_mask_shuffle_epi8(p, _mm512_cmpeq_epi8_mask(_mm512_and_si512(h, masks[1]), masks[1]), values[2], l); + p = _mm512_mask_shuffle_epi8(p, _mm512_cmpeq_epi8_mask(_mm512_and_si512(h, masks[2]), masks[2]), values[3], l); + return p; + } + inline void prepare(const uint8_t * q4, const uint8_t * qh) { + bits.prepare64(q4); + auto h256_1 = _mm256_loadu_si256((const __m256i *)qh + 0); + auto h256_2 = _mm256_loadu_si256((const __m256i *)qh + 1); + auto h1 = _mm512_inserti32x8(_mm512_castsi256_si512(h256_1), _mm256_srli_epi16(h256_1, 4), 1); + auto h2 = _mm512_inserti32x8(_mm512_castsi256_si512(h256_2), _mm256_srli_epi16(h256_2, 4), 1); + bits.values[0] = make_one(bits.values[0], h1); + bits.values[1] = make_one(bits.values[1], _mm512_srli_epi16(h1, 2)); + bits.values[2] = make_one(bits.values[2], h2); + bits.values[3] = make_one(bits.values[3], _mm512_srli_epi16(h2, 2)); + // We now have in bits.valuse[0]: 0...31, 64...95 + // bits.valuse[1]: 32..63, 96..127 + // etc. + auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]); + bits.values[1] = _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1]); + bits.values[0] = tmp; + tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]); + bits.values[3] = _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3]); + bits.values[2] = tmp; + } + static void load_values(__m512i * values) { + static const uint8_t kvalues_iq6nl[64] = { + 1, 7, 13, 19, 24, 30, 35, 40, 44, 49, 54, 58, 62, 66, 70, 74, + 77, 81, 84, 88, 91, 94, 97, 100, 103, 106, 109, 112, 115, 117, 120, 123, + 126, 128, 131, 134, 137, 140, 142, 145, 148, 151, 155, 158, 161, 164, 168, 172, + 175, 179, 183, 187, 191, 196, 200, 205, 210, 215, 220, 226, 231, 237, 243, 249, + }; + for (int k = 0; k < 4; ++k) { + auto values128 = _mm_loadu_si128((const __m128i *)kvalues_iq6nl + k); + auto values256 = MM256_SET_M128I(values128, values128); + values[k] = _mm512_inserti32x8(_mm512_castsi256_si512(values256), values256, 1); + } + } + + Q4Bits bits; + IQXKScales2 iqxk; + __m512i values[4]; + __m512i masks[3] = { _mm512_set1_epi8(0x01), _mm512_set1_epi8(0x02), _mm512_set1_epi8(0x03) }; + const __m512i permute1 = _mm512_set_epi64(11, 10, 9, 8, 3, 2, 1, 0); + const __m512i permute2 = _mm512_set_epi64(15, 14, 13, 12, 7, 6, 5, 4); +}; + +template +inline void compute_block(int iy, int i, float d, const Q8& q8, const __m512i * values, const __m512i * scales, __m512 * accd) { + const __m512i p1 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), values[0], q8.load_quants64(iy, i, 0)); + const __m512i p2 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), values[1], q8.load_quants64(iy, i, 1)); + const __m512i p3 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), values[2], q8.load_quants64(iy, i, 2)); + const __m512i p4 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), values[3], q8.load_quants64(iy, i, 3)); + auto sumi = _mm512_dpwssd_epi32(_mm512_setzero_si512(), scales[0], _mm512_packs_epi32(p1, p2)); + sumi = _mm512_dpwssd_epi32(sumi, scales[1], _mm512_packs_epi32(p3, p4)); + accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]); +} + +template +inline void compute_block_iq2tn(int iy, int i, float d, const Q8& q8, const __m512i * values, __m512 * accd) { + auto sumi_scales = _mm256_madd_epi16(_mm256_set1_epi16(-1), q8.load_bsums(iy, i)); + auto sumi = _mm512_dpbusd_epi32(_mm512_dpbusd_epi32(_mm512_dpbusd_epi32(_mm512_dpbusd_epi32( + _mm512_inserti32x8(_mm512_setzero_si512(), sumi_scales, 0), + values[0], q8.load_quants64(iy, i, 0)), values[1], q8.load_quants64(iy, i, 1)), + values[2], q8.load_quants64(iy, i, 2)), values[3], q8.load_quants64(iy, i, 3)); + accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]); +} + +template +static void mul_mat_qX_K_q8_K_AVX512(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + Dequantizer deq(vx, bx); + + __m256 accm[nrc_y]; + __m512 accd[nrc_y]; + __m512i scales[2]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm512_setzero_ps(); + for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm256_setzero_ps(); + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + deq.new_block(i, q8, accm, scales); + + for (int iy = 0; iy < nrc_y; ++iy) { + if constexpr (std::is_same_v) { + auto sumi_scales = _mm256_madd_epi16(_mm256_set1_epi16(-1), q8.load_bsums(iy, i)); + auto sumi = _mm512_dpbusd_epi32(_mm512_dpbusd_epi32(_mm512_dpbusd_epi32(_mm512_dpbusd_epi32( + _mm512_inserti32x8(_mm512_setzero_si512(), sumi_scales, 0), + deq.bits.values[0], q8.load_quants64(iy, i, 0)), deq.bits.values[1], q8.load_quants64(iy, i, 1)), + deq.bits.values[2], q8.load_quants64(iy, i, 2)), deq.bits.values[3], q8.load_quants64(iy, i, 3)); + accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(deq.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]); + } else { + const __m512i p1 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[0], q8.load_quants64(iy, i, 0)); + const __m512i p2 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[1], q8.load_quants64(iy, i, 1)); + const __m512i p3 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[2], q8.load_quants64(iy, i, 2)); + const __m512i p4 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[3], q8.load_quants64(iy, i, 3)); + auto sumi = _mm512_dpwssd_epi32(_mm512_setzero_si512(), scales[0], _mm512_packs_epi32(p1, p2)); + sumi = _mm512_dpwssd_epi32(sumi, scales[1], _mm512_packs_epi32(p3, p4)); + accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(deq.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]); + } + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum256 = _mm256_add_ps(_mm512_castps512_ps256(accd[iy]), _mm512_extractf32x8_ps(accd[iy], 1)); + info.store(ix, iy, hsum_float_8(_mm256_add_ps(accm[iy], sum256))); + } + + } +} + +template +static void mul_mat_iq2tn_q8_K_AVX512(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + DequantizerIQ2TN deq1(vx, bx), deq2(vx, bx); + + __m512 accd[2*nrc_y]; + + for (int ix = 0; ix < nrc_x; ix += 2) { + + for (int iy = 0; iy < 2*nrc_y; ++iy) accd[iy] = _mm512_setzero_ps(); + + deq1.new_row(ix+0); + deq2.new_row(ix+1); + + for (int i = 0; i < nb; ++i) { + + deq1.new_block(i); + deq2.new_block(i); + //float d = 0.5f*(deq1.d + deq2.d); // The scale is supposed to be per per tensor, so we can use the same scale for both rows + + for (int iy = 0; iy < nrc_y; ++iy) { + auto sumi_scales_256 = _mm256_madd_epi16(_mm256_set1_epi16(-1), q8.load_bsums(iy, i)); + auto sumi_scales_512 = _mm512_inserti32x8(_mm512_setzero_si512(), sumi_scales_256, 0); + auto q8q = q8.load_quants64(iy, i, 0); + auto sumi_1 = _mm512_dpbusd_epi32(sumi_scales_512, deq1.bits.values[0], q8q); + auto sumi_2 = _mm512_dpbusd_epi32(sumi_scales_512, deq2.bits.values[0], q8q); + q8q = q8.load_quants64(iy, i, 1); + sumi_1 = _mm512_dpbusd_epi32(sumi_1, deq1.bits.values[1], q8q); + sumi_2 = _mm512_dpbusd_epi32(sumi_2, deq2.bits.values[1], q8q); + q8q = q8.load_quants64(iy, i, 2); + sumi_1 = _mm512_dpbusd_epi32(sumi_1, deq1.bits.values[2], q8q); + sumi_2 = _mm512_dpbusd_epi32(sumi_2, deq2.bits.values[2], q8q); + q8q = q8.load_quants64(iy, i, 3); + sumi_1 = _mm512_dpbusd_epi32(sumi_1, deq1.bits.values[3], q8q); + sumi_2 = _mm512_dpbusd_epi32(sumi_2, deq2.bits.values[3], q8q); + // The scale is supposed to be per per tensor, so we can use the same scale + auto vd = _mm512_set1_ps(/*d* */q8.scale(iy, i)); + accd[2*iy+0] = _mm512_fmadd_ps(vd, _mm512_cvtepi32_ps(sumi_1), accd[2*iy+0]); + accd[2*iy+1] = _mm512_fmadd_ps(vd, _mm512_cvtepi32_ps(sumi_2), accd[2*iy+1]); + // Leaving this here just in case ternary models start using per row scales + //accd[2*iy+0] = _mm512_fmadd_ps(_mm512_set1_ps(deq1.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi_1), accd[2*iy+0]); + //accd[2*iy+1] = _mm512_fmadd_ps(_mm512_set1_ps(deq2.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi_2), accd[2*iy+1]); + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix+0, iy, deq1.d*_mm512_reduce_add_ps(accd[2*iy+0])); + info.store(ix+1, iy, deq2.d*_mm512_reduce_add_ps(accd[2*iy+1])); + } + + } +} + +template +static void mul_mat_iqX_k_q8_K_AVX512(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + Dequantizer deq(vx, bx); + + __m256 accm[nrc_y]; + __m512 accd[nrc_y]; + __m512i scales[4]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm512_setzero_ps(); + for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm256_setzero_ps(); + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + deq.new_block(i, q8, accm, scales); + + for (int iy = 0; iy < nrc_y; ++iy) { + const __m512i p1 = _mm512_maddubs_epi16(deq.bits.values[0], q8.load_quants64(iy, i, 0)); + const __m512i p2 = _mm512_maddubs_epi16(deq.bits.values[1], q8.load_quants64(iy, i, 1)); + const __m512i p3 = _mm512_maddubs_epi16(deq.bits.values[2], q8.load_quants64(iy, i, 2)); + const __m512i p4 = _mm512_maddubs_epi16(deq.bits.values[3], q8.load_quants64(iy, i, 3)); + auto sumi = _mm512_dpwssd_epi32(_mm512_dpwssd_epi32(_mm512_dpwssd_epi32(_mm512_dpwssd_epi32(_mm512_setzero_si512(), + p1, scales[0]), p2, scales[1]), p3, scales[2]), p4, scales[3]); + accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(deq.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]); + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum256 = _mm256_add_ps(_mm512_castps512_ps256(accd[iy]), _mm512_extractf32x8_ps(accd[iy], 1)); + info.store(ix, iy, hsum_float_8(_mm256_add_ps(accm[iy], sum256))); + } + + } +} + +template +static void mul_mat_qX_K_q8_K_AVX512_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + constexpr int k_nx = 2; + + Q8<1> q8(info); + + Dequantizer deq1(vx, bx); + Dequantizer deq2(vx, bx); + + Dequantizer * deq[k_nx]; + deq[0] = &deq1; + deq[1] = &deq2; + + __m512i scales[2*k_nx]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + auto accd = _mm512_setzero_ps(); + auto accm = _mm256_setzero_ps(); + + for (int kx = 0; kx < k_nx; ++kx) deq[kx]->new_row(ix); + + for (int i = 0; i < nb/k_nx; ++i) { + + for (int kx = 0; kx < k_nx; ++kx) deq[kx]->new_block(k_nx*i+kx, q8, &accm, scales+2*kx); + + if constexpr (std::is_same_v) { + for (int kx = 0; kx < k_nx; ++kx) { + compute_block_iq2tn(0, k_nx*i+kx, deq[kx]->d, q8, deq[kx]->bits.values, &accd); + } + } else { + for (int kx = 0; kx < k_nx; ++kx) { + compute_block(0, k_nx*i+kx, deq[kx]->d, q8, deq[kx]->bits.values, scales+2*kx, &accd); + } + } + + } + if (2*(nb/2) < nb) { + int i0 = 2*(nb/2); + deq[0]->new_block(i0, q8, &accm, scales); + if constexpr (std::is_same_v) { + compute_block_iq2tn(0, i0, deq[0]->d, q8, deq[0]->bits.values, &accd); + } else { + compute_block(0, i0, deq[0]->d, q8, deq[0]->bits.values, scales, &accd); + } + } + + if constexpr (std::is_same_v) { + info.store(ix, 0, _mm512_reduce_add_ps(accd)); + } else { + auto sum256 = _mm256_add_ps(_mm512_castps512_ps256(accd), _mm512_extractf32x8_ps(accd, 1)); + info.store(ix, 0, hsum_float_8(_mm256_add_ps(accm, sum256))); + } + } +} + +#else +// ===================================== Vanilla AVX2 ===================================== + +struct Q4Bits { + inline void prepare(const uint8_t * q4, int j) { + auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0); + values[0] = _mm256_and_si256(q4bits, ml); + values[1] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml); + q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1); + values[2] = _mm256_and_si256(q4bits, ml); + values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml); + } + inline void prepare64(const uint8_t * q4, int j) { + auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0); + values[0] = _mm256_and_si256(q4bits, ml); + values[2] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml); + q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1); + values[1] = _mm256_and_si256(q4bits, ml); + values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml); + } + inline void prepare16(const uint8_t * q4, int j) { + values[0] = dequant16(q4 + 64*j + 0); + values[1] = dequant16(q4 + 64*j + 16); + values[2] = dequant16(q4 + 64*j + 32); + values[3] = dequant16(q4 + 64*j + 48); + } + inline __m256i dequant16(const uint8_t * qs) const { + const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs); + const __m256i aux256 = MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128); + return _mm256_and_si256(ml, aux256); + } + __m256i values[4]; + const __m256i ml = _mm256_set1_epi8(0xf); +}; + +struct Q2Bits { + inline void prepare(const uint8_t * q2, int j) { + auto q2bits = _mm256_loadu_si256((const __m256i *)q2 + j); + values[0] = _mm256_and_si256(q2bits, ml); + values[1] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 2), ml); + values[2] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 4), ml); + values[3] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 6), ml); + } + __m256i values[4]; + const __m256i ml = _mm256_set1_epi8(0x03); +}; + +struct HighBit5 { + inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); } + inline void apply(Q4Bits& bits, bool do_shift) { + bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh)); + bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 3), mh)); + bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh)); + bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh)); + if (do_shift) { + hbits = _mm256_srli_epi16(hbits, 4); + } + } + const __m256i mh = _mm256_set1_epi8(0x10); + __m256i hbits; +}; + +struct HighBit3 { + inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); } + inline void apply(Q2Bits& bits, bool do_shift) { + bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh)); + bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh)); + bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh)); + bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 1), mh)); + if (do_shift) { + hbits = _mm256_srli_epi16(hbits, 4); + } + } + const __m256i mh = _mm256_set1_epi8(0x04); + __m256i hbits; +}; + +struct DequantizerQ4K final : public BaseDequantizer { + DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline __m256i new_block(int i, const Q8& q8, __m256 * accd) { + d = GGML_FP16_TO_FP32(x[i].d); + return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + } + + Q4Bits bits; + Scales8K s8k; +}; + +struct DequantizerIQ4XS final : public BaseDequantizer { + DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_iq4nl_values_256()) {} + template + inline __m256i new_block(int i, const Q8& q8, __m256 * accd) { + d = GGML_FP16_TO_FP32(x[i].d); + auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h); + s8k.accum_mins(scales128, q8, i, -128.f*d, accd); + return MM256_SET_M128I(scales128, scales128); + } + inline void prepare(int i, int j) { + bits.prepare16(x[i].qs, j); + bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]); + } + + Q4Bits bits; + Scales8K s8k; + ScaleIQ4XS siq4; + const __m256i values; +}; + +struct IQXKScales { + IQXKScales(int8_t shift, int8_t min_val) : min(_mm256_set1_epi16(min_val)), eshift(_mm_set1_epi8(shift)) {} + template + inline void process(int i, float d, uint16_t extra, __m128i scales8, const Q8& q8, __m256 * accm, __m256i * scales) const { + auto scales16 = _mm256_cvtepi8_epi16(_mm_shuffle_epi8(scales8, hshuff)); + process(i, d, extra, scales16, q8, accm, scales); + //auto extra128 = _mm_set1_epi16(extra); + //extra128 = _mm_cmpeq_epi8(_mm_and_si128(extra128, emask), emask); + //extra128 = _mm_and_si128(extra128, eshift); + //extra128 = _mm_shuffle_epi8(extra128, eshuffle); + //auto scales_s = _mm256_mullo_epi16(scales16, _mm256_add_epi16(min, _mm256_cvtepi8_epi16(extra128))); + //for (int iy = 0; iy < Q8::nrc_y; ++iy) { + // const __m256i prod = _mm256_madd_epi16(scales_s, q8.load_bsums(iy, i)); + // accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]); + //} + //prepare_scales_16(scales16, scales); + } + template + inline void process(int i, float d, uint16_t extra, __m256i scales16, const Q8& q8, __m256 * accm, __m256i * scales) const { + auto extra128 = _mm_set1_epi16(extra); + extra128 = _mm_cmpeq_epi8(_mm_and_si128(extra128, emask), emask); + extra128 = _mm_and_si128(extra128, eshift); + extra128 = _mm_shuffle_epi8(extra128, eshuffle); + auto scales_s = _mm256_mullo_epi16(scales16, _mm256_add_epi16(min, _mm256_cvtepi8_epi16(extra128))); + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + const __m256i prod = _mm256_madd_epi16(scales_s, q8.load_bsums(iy, i)); + accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]); + } + prepare_scales_16(scales16, scales); + } + + const __m256i min; + const __m128i eshift; + const __m128i hshuff = _mm_set_epi32(0x0f070e06, 0x0d050c04, 0x0b030a02, 0x09010800); + const __m128i emask = _mm_set_epi32(0x80804040, 0x20201010, 0x08080404, 0x02020101); + const __m128i eshuffle = _mm_set_epi32(0x0f0d0b09, 0x07050301, 0x0e0c0a08, 0x06040200); +}; + +struct DequantizerIQ2K final : public BaseDequantizer { + DequantizerIQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(5, -32), values(load_values()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales), q8, accm, scales); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]); + } + static inline __m256i load_values() { + static const uint8_t kvalues_iq2nl[16] = {1, 19, 33, 49, 0, 0, 0, 0, 6, 24, 38, 54, 0, 0, 0, 0}; + auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq2nl); + return MM256_SET_M128I(val128, val128); + } + inline __m128i make_scales(const uint8_t * scales_l) const { + uint64_t aux64; std::memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), maskl); + return _mm_add_epi8(_mm_slli_epi16(scl, 1), m15); + } + + Q2Bits bits; + const IQXKScales iqxk; + const __m256i values; + const __m128i m15 = _mm_set1_epi8(-15); + const __m128i maskl = _mm_set1_epi8(0xf); +}; + +struct DequantizerIQ3K final : public BaseDequantizer { + DequantizerIQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(4, -64), values(load_values()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_h, x[i].scales_l), q8, accm, scales); + hbits = _mm256_loadu_si256((const __m256i *)x[i].qh); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + auto h256 = j == 0 ? hbits : _mm256_srli_epi16(hbits, 4); + bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(h256, 2), hmask)); + bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(h256, 1), hmask)); + bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(h256, hmask)); + bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(h256, 1), hmask)); + bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]); + } + static inline __m256i load_values() { + static const uint8_t kvalues_iq3nl[16] = {1, 24, 41, 54, 65, 77, 92, 111, 5, 28, 45, 58, 69, 81, 96, 115}; + auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq3nl); + return MM256_SET_M128I(val128, val128); + } + inline __m128i make_scales(uint16_t signs, const uint8_t * scales_l) const { + uint64_t aux64; std::memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), _mm_set1_epi8(0xf)); + scl = _mm_add_epi8(_mm_slli_epi16(scl, 1), m1); + const __m128i sc_signs = _mm_cmpeq_epi8(_mm_and_si128(_mm_set1_epi16(signs), sign_mask), sign_mask); + const __m128i sch = _mm_shuffle_epi8(_mm_or_si128(sc_signs, _mm_set1_epi8(1)), hshuff); + return _mm_sign_epi8(scl, sch); + } + + Q2Bits bits; + const IQXKScales iqxk; + const __m256i values; + __m256i hbits; + const __m256i hmask = _mm256_set1_epi8(4); + const __m128i m1 = _mm_set1_epi8(1); + const __m128i sign_mask = _mm_set_epi64x(0x8080404020201010, 0x0808040402020101); + const __m128i hshuff = _mm_loadu_si128((const __m128i*)k_shuff); + constexpr static uint8_t k_shuff[16] = {0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15}; +}; + +struct DequantizerIQ4K final : public BaseDequantizer { + DequantizerIQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(4, -128), values(load_iq4nl_values_256()) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_l, (const uint16_t *)x[i].scales_h), q8, accm, scales); + } + inline void prepare(int i, int j) { + bits.prepare16(x[i].qs, j); + bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]); + bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]); + bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]); + bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]); + } + __m128i make_scales(const uint8_t * scales_l, const uint16_t * scales_h) const { + uint64_t aux64; + memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), maskl); + const uint32_t aux32 = scales_h[0] | (scales_h[1] << 16); + auto aux = _mm_and_si128(_mm_set_epi32(aux32 >> 2, aux32, aux32 << 2, aux32 << 4), maskh); + auto sch = _mm_shuffle_epi8(aux, iqxk.hshuff); + return _mm_add_epi8(_mm_or_si128(scl, sch), m32); + } + + Q4Bits bits; + const IQXKScales iqxk; + const __m256i values; + const __m128i maskl = _mm_set1_epi8(0xf); + const __m128i maskh = _mm_set1_epi8(0x30); + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct DequantizerIQ5K final : public BaseDequantizer { + DequantizerIQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(2, -128) { load_values(values); } + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + iqxk.process(i, d, x[i].extra, make_scales(x[i].scales_l, (const uint16_t *)x[i].scales_h), q8, accm, scales); + hbits = _mm256_loadu_si256((const __m256i *)x[i].qh); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + auto h = j == 0 ? hbits : _mm256_srli_epi16(hbits, 4); + for (int k = 0; k < 4; ++k) { + auto qh = _mm256_and_si256(_mm256_slli_epi16(h, 7-k), mh); + auto q5vl = _mm256_or_si256(bits.values[k], qh); + auto q5vh = _mm256_or_si256(bits.values[k], _mm256_xor_si256(qh, mh)); + bits.values[k] = _mm256_or_si256(_mm256_shuffle_epi8(values[0], q5vl), _mm256_shuffle_epi8(values[1], q5vh)); + } + } + __m128i make_scales(const uint8_t * scales_l, const uint16_t * scales_h) const { + uint64_t aux64; + memcpy(&aux64, scales_l, 8); + auto scl = _mm_and_si128(_mm_set_epi64x(aux64 >> 4, aux64), maskl); + const uint32_t aux32 = scales_h[0] | (scales_h[1] << 16); + auto aux = _mm_and_si128(_mm_set_epi32(aux32 >> 2, aux32, aux32 << 2, aux32 << 4), maskh); + auto sch = _mm_shuffle_epi8(aux, iqxk.hshuff); + return _mm_add_epi8(_mm_or_si128(scl, sch), m32); + } + static void load_values(__m256i * values) { + static const uint8_t kvalues_iq5nl[32] = { + 2, 14, 25, 36, 45, 54, 63, 71, 78, 85, 92, 98, 104, 110, 116, 122, 127, + 133, 139, 145, 151, 157, 164, 171, 179, 187, 196, 205, 215, 225, 237, 249, + }; + auto values128_1 = _mm_loadu_si128((const __m128i *)kvalues_iq5nl + 0); + auto values128_2 = _mm_loadu_si128((const __m128i *)kvalues_iq5nl + 1); + values[0] = MM256_SET_M128I(values128_1, values128_1); + values[1] = MM256_SET_M128I(values128_2, values128_2); + } + + Q4Bits bits; + const IQXKScales iqxk; + __m256i hbits; + __m256i values[2]; + const __m128i maskl = _mm_set1_epi8(0xf); + const __m128i maskh = _mm_set1_epi8(0x30); + const __m128i m32 = _mm_set1_epi8(-32); + const __m256i mh = _mm256_set1_epi8(-128); // to avoid stupid warning about 0x80 overflowing +}; + +struct DequantizerIQ6K final : public BaseDequantizer { + DequantizerIQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx), iqxk(1, -128) { load_values(values); } + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + auto scales8 = _mm_loadu_si128((const __m128i*)x[i].scales); + auto scales16 = _mm256_cvtepi8_epi16(scales8); + iqxk.process(i, d, x[i].extra, scales16, q8, accm, scales); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + auto hbits = _mm256_loadu_si256((const __m256i *)x[i].qh + j); + for (int k = 0; k < 4; ++k) { + bits.values[k] = make_one(bits.values[k], hbits); + hbits = _mm256_srli_epi16(hbits, 2); + } + } + inline __m256i make_one(__m256i l, __m256i hbits) const { + auto mask4 = _mm256_cmpeq_epi8(_mm256_and_si256(hbits, mh3), mh3); + auto h1 = _mm256_andnot_si256(mask4, hbits); + auto mask2 = _mm256_cmpeq_epi8(_mm256_and_si256(h1, mh1), mh1); + auto mask3 = _mm256_cmpeq_epi8(_mm256_and_si256(h1, mh2), mh2); + auto mask1 = _mm256_andnot_si256(_mm256_or_si256(mask4, _mm256_or_si256(mask2, mask3)), _mm256_set1_epi8(0xff)); + return _mm256_or_si256(_mm256_or_si256(_mm256_and_si256(mask1, _mm256_shuffle_epi8(values[0], l)), + _mm256_and_si256(mask2, _mm256_shuffle_epi8(values[1], l))), + _mm256_or_si256(_mm256_and_si256(mask3, _mm256_shuffle_epi8(values[2], l)), + _mm256_and_si256(mask4, _mm256_shuffle_epi8(values[3], l)))); + } + static void load_values(__m256i * values) { + static const uint8_t kvalues_iq6nl[64] = { + 1, 7, 13, 19, 24, 30, 35, 40, 44, 49, 54, 58, 62, 66, 70, 74, + 77, 81, 84, 88, 91, 94, 97, 100, 103, 106, 109, 112, 115, 117, 120, 123, + 126, 128, 131, 134, 137, 140, 142, 145, 148, 151, 155, 158, 161, 164, 168, 172, + 175, 179, 183, 187, 191, 196, 200, 205, 210, 215, 220, 226, 231, 237, 243, 249, + }; + for (int k = 0; k < 4; ++k) { + auto values128 = _mm_loadu_si128((const __m128i *)kvalues_iq6nl + k); + values[k] = MM256_SET_M128I(values128, values128); + } + } + + Q4Bits bits; + const IQXKScales iqxk; + __m256i values[4]; + const __m256i mh1 = _mm256_set1_epi8(1); + const __m256i mh2 = _mm256_set1_epi8(2); + const __m256i mh3 = _mm256_set1_epi8(3); + const __m256i mh = _mm256_set1_epi8(-128); // to avoid stupid warning about 0x80 overflowing +}; + +struct DequantizerQ5K final : public BaseDequantizer { + DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline __m256i new_block(int i, const Q8& q8, __m256 * accd) { + d = GGML_FP16_TO_FP32(x[i].d); + hbits.load(x[i].qh); + return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + hbits.apply(bits, j == 0); + } + + Q4Bits bits; + HighBit5 hbits; + Scales8K s8k; +}; + +template +inline void process_mins_and_scales_16(const __m128i& scales128, const Q8& q8, int i, float d, + __m256 * accm, __m256i * scales) { + const __m256i all_scales = _mm256_cvtepi8_epi16(scales128); + process_mins_16(all_scales, q8, i, d, accm); + prepare_scales_16(all_scales, scales); +} + +struct DequantizerQ3K final : public BaseDequantizer { + DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + hbits.load(x[i].hmask); + process_mins_and_scales_16(sc3.make_scales((const uint16_t *)x[i].scales), q8, i, -4.f*d, accm, scales); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + hbits.apply(bits, j == 0); + } + + Q2Bits bits; + HighBit3 hbits; + ScaleQ3 sc3; + + const __m128i m32 = _mm_set1_epi8(-32); +}; + +struct DequantizerQ2K final : public BaseDequantizer { + DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales); + const __m128i scales8 = _mm_and_si128(mins_and_scales, m4); + const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4); + process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, -GGML_FP16_TO_FP32(x[i].dmin), accm); + prepare_scales_16(_mm256_cvtepi8_epi16(scales8), scales); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + } + + Q2Bits bits; + + const __m128i m4 = _mm_set1_epi8(0xf); +}; + +struct DequantizerQ6K final : public BaseDequantizer { + DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + template + inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) { + d = GGML_FP16_TO_FP32(x[i].d); + process_mins_and_scales_16(_mm_loadu_si128((const __m128i *)x[i].scales), q8, i, -32.f*d, accm, scales); + } + inline void prepare(int i, int j) { + bits.prepare64(x[i].ql, j); + auto hbits = _mm256_loadu_si256((const __m256i *)x[i].qh + j); + bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh)); + bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh)); + bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh)); + bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 2), mh)); + } + + Q4Bits bits; + const __m256i mh = _mm256_set1_epi8(0x30); +}; + +struct DequantizerIQ2TN final : public BaseDequantizer { + DequantizerIQ2TN(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + inline void prepare(int i, int j) { + bits.prepare(x[i].qs, j); + } + + Q2Bits bits; +}; + + +template +IQK_NOINLINE void mul_mat_iq2tn_q8_K(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n%QK_K == 0); + const int nb = n/QK_K; + + Q8 q8(info); + DequantizerIQ2TN deq1(vx, bx), deq2(vx, bx); + + __m256 accd[nrc_y]; + const auto m1 = _mm256_set1_epi16(1); + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq1.new_row(ix); + deq2.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + if constexpr (nrc_y == 1) { + deq1.prepare(i, 0); + auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[0], q8.load_quants(0, i, 0)), + _mm256_maddubs_epi16(deq1.bits.values[1], q8.load_quants(0, i, 1))); + sumi1 = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[2], q8.load_quants(0, i, 2)), + _mm256_maddubs_epi16(deq1.bits.values[3], q8.load_quants(0, i, 3))), sumi1); + + deq2.prepare(i, 1); + auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[0], q8.load_quants(0, i, 4)), + _mm256_maddubs_epi16(deq2.bits.values[1], q8.load_quants(0, i, 5))); + sumi2 = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[2], q8.load_quants(0, i, 6)), + _mm256_maddubs_epi16(deq2.bits.values[3], q8.load_quants(0, i, 7))), sumi2); + auto sumi = _mm256_add_epi16(sumi2, _mm256_sub_epi16(sumi1, q8.load_bsums(0, i))); + auto vd = _mm256_set1_ps(deq1.d*q8.scale(0, i)); + auto sf = _mm256_cvtepi32_ps(_mm256_madd_epi16(m1, sumi)); + accd[0] = i > 0 ? _mm256_fmadd_ps(vd, sf, accd[0]) : _mm256_mul_ps(vd, sf); + } + else { + + deq1.prepare(i, 0); deq2.prepare(i, 1); + for (int iy = 0; iy < nrc_y; ++iy) { + auto vd = _mm256_set1_ps(deq1.d*q8.scale(iy, i)); + auto sumi = _mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[0], q8.load_quants(iy, i, 0)), + _mm256_maddubs_epi16(deq1.bits.values[1], q8.load_quants(iy, i, 1))); + sumi = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[2], q8.load_quants(iy, i, 2)), + _mm256_maddubs_epi16(deq1.bits.values[3], q8.load_quants(iy, i, 3))), sumi); + sumi = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[0], q8.load_quants(iy, i, 4)), + _mm256_maddubs_epi16(deq2.bits.values[1], q8.load_quants(iy, i, 5))), sumi); + sumi = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[2], q8.load_quants(iy, i, 6)), + _mm256_maddubs_epi16(deq2.bits.values[3], q8.load_quants(iy, i, 7))), sumi); + sumi = _mm256_sub_epi16(sumi, q8.load_bsums(iy, i)); + + //auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[0], q8.load_quants(iy, i, 0)), + // _mm256_maddubs_epi16(deq1.bits.values[1], q8.load_quants(iy, i, 1))); + //auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(deq1.bits.values[2], q8.load_quants(iy, i, 2)), + // _mm256_maddubs_epi16(deq1.bits.values[3], q8.load_quants(iy, i, 3))); + //sumi1 = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[0], q8.load_quants(iy, i, 4)), + // _mm256_maddubs_epi16(deq2.bits.values[1], q8.load_quants(iy, i, 5))), sumi1); + //sumi2 = _mm256_add_epi16(_mm256_add_epi16(_mm256_maddubs_epi16(deq2.bits.values[2], q8.load_quants(iy, i, 6)), + // _mm256_maddubs_epi16(deq2.bits.values[3], q8.load_quants(iy, i, 7))), sumi2); + //auto sumi = _mm256_add_epi16(sumi2, _mm256_sub_epi16(sumi1, q8.load_bsums(iy, i))); + auto sf = _mm256_cvtepi32_ps(_mm256_madd_epi16(m1, sumi)); + accd[iy] = i > 0 ? _mm256_fmadd_ps(vd, sf, accd[iy]) : _mm256_mul_ps(vd, sf); + } + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, hsum_float_8(accd[iy])); + } + + } +} + +template +static void mul_mat_qY_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n%QK_K == 0); + const int nb = n/QK_K; + + Q8 q8(info); + + __m256i all_scales[2]; + __m256i scales[4]; + __m256 accd[nrc_y]; + + Dequantizer deq(vx, bx); + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps(); + + for (int i = 0; i < nb; ++i) { + + deq.new_block(i, q8, accd, all_scales); + + __m256i sumi[nrc_y]; + + for (int j = 0; j < QK_K/128; ++j) { + deq.prepare(i, j); + set_scales_16(all_scales[j], scales); + multiply_add(deq.bits, scales, j, i, q8, sumi); + } + + for (int iy = 0; iy < nrc_y; ++iy) { + accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(deq.d*q8.scale(iy, i)), _mm256_cvtepi32_ps(sumi[iy]), accd[iy]); + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, hsum_float_8(accd[iy])); + } + + } + +} + +template +static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + Dequantizer deq(vx, bx); + + __m256 accd[nrc_y]; + __m256i scales[4]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps(); + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + auto all_scales = deq.new_block(i, q8, accd); + + __m256i sumi[nrc_y]; + + for (int j = 0; j < QK_K/128; ++j) { + + deq.prepare(i, j); + + set_scales_8(all_scales, j, scales); + + multiply_add(deq.bits, scales, j, i, q8, sumi); + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + const __m256 vd = _mm256_set1_ps(deq.d*q8.scale(iy, i)); + accd[iy] = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(sumi[iy]), accd[iy]); + } + + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, hsum_float_8(accd[iy])); + } + + } +} + +#endif // Zen4 or vanilla AVX2 + +template +inline void multiply_add_1(int j, const Bits& bits, const __m256i * scales, const __m256i * q8, __m256i * sumi) { + if (j == 0) { +#if defined(__AVX512VNNI__) && defined(__AVX512VL__) + auto p1 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[0], q8[0]); + auto p2 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[1], q8[1]); + auto p3 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[2], q8[2]); + auto p4 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[3], q8[3]); + sumi[0] = _mm256_dpwssd_epi32(_mm256_setzero_si256(), scales[0], _mm256_packs_epi32(p1, p2)); + sumi[1] = _mm256_dpwssd_epi32(_mm256_setzero_si256(), scales[1], _mm256_packs_epi32(p3, p4)); +#else + const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8[0])); + const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8[1])); + const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8[2])); + const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8[3])); + sumi[0] = _mm256_add_epi32(p1, p3); + sumi[1] = _mm256_add_epi32(p2, p4); +#endif + } else { +#if defined(__AVX512VNNI__) && defined(__AVX512VL__) + auto p1 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[0], q8[0]); + auto p2 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[1], q8[1]); + auto p3 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[2], q8[2]); + auto p4 = _mm256_dpbusd_epi32(_mm256_setzero_si256(), bits.values[3], q8[3]); + sumi[0] = _mm256_dpwssd_epi32(sumi[0], scales[0], _mm256_packs_epi32(p1, p2)); + sumi[1] = _mm256_dpwssd_epi32(sumi[1], scales[1], _mm256_packs_epi32(p3, p4)); +#else + const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8[0])); + const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8[1])); + const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8[2])); + const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8[3])); + sumi[0] = _mm256_add_epi32(sumi[0], _mm256_add_epi32(p1, p3)); + sumi[1] = _mm256_add_epi32(sumi[1], _mm256_add_epi32(p2, p4)); +#endif + } +} + +inline void set_scales_8_iq(int j, const __m256i& all_scales, __m256i * scales) { +#ifdef HAVE_FANCY_SIMD + auto shuffle = j == 0 ? _mm256_set_epi64x(0x0302030203020302, 0x0100010001000100, 0x0302030203020302, 0x0100010001000100) + : _mm256_set_epi64x(0x0b0a0b0a0b0a0b0a, 0x0908090809080908, 0x0b0a0b0a0b0a0b0a, 0x0908090809080908); + scales[0] = _mm256_shuffle_epi8(all_scales, shuffle); + scales[1] = _mm256_shuffle_epi8(all_scales, _mm256_add_epi8(shuffle, _mm256_set1_epi8(4))); +#else + set_scales_8(all_scales, j, scales); +#endif +} + +inline void set_scales_16_iq(const __m256i& all_scales, __m256i * scales) { +#ifdef HAVE_FANCY_SIMD + auto shuffle = _mm256_set_epi64x(0x0706070607060706, 0x0302030203020302, 0x0504050405040504, 0x0100010001000100); + scales[0] = _mm256_shuffle_epi8(all_scales, shuffle); + scales[1] = _mm256_shuffle_epi8(all_scales, _mm256_add_epi8(shuffle, _mm256_set1_epi8(8))); +#else + set_scales_16(all_scales, scales); +#endif +} + +template +static void mul_mat_qX_K_q8_K_IQ_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_K; + Q8<1> q8(info); + Dequantizer deq(vx, bx); + __m256i scales[2]; + __m256i q8_quants[4]; + for (int ix = 0; ix < nrc_x; ++ix) { + + __m256 accd = _mm256_setzero_ps(); + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + __m256i sumi[2], all_scales[Dequantizer::num_blocks/8]; + deq.new_block(i, all_scales); + + for (int j = 0; j < QK_K/128; ++j) { + deq.prepare(i, j, q8, q8_quants); + if constexpr (Dequantizer::num_blocks == 8) { + set_scales_8_iq(j, all_scales[0], scales); + } else { + set_scales_16_iq(all_scales[j], scales); + } + multiply_add_1(j, deq.bits, scales, q8_quants, sumi); + } + accd = _mm256_fmadd_ps(_mm256_set1_ps(deq.d*q8.scale(0, i)), _mm256_cvtepi32_ps(_mm256_add_epi32(sumi[0], sumi[1])), accd); + } + + info.store(ix, 0, hsum_float_8(accd)); + } +} + +// So, if I uncomment this function and the call to it in mul_mat_qX_K_q8_K_IQ_N() below, +// PP performance improves by ~2-3% (when we have __AVX512VNNI__ and __AVX512VL__). +// But TG performance for iq3_xs drops by 35%. Seriously? I mean, c'mon, +// what does the compilation of mul_mat_qX_K_q8_K_IQ_1 (which gets invoked during TG) +// have to do with the compilation of mul_mat_qX_K_q8_K_IQ_N (invoked during PP)? +//template +//inline void multiply_add_iq(const Bits& bits, const __m256i * scales, int j, int i, const Q8& q8, __m256i * sumi) { +//#if defined(__AVX512VNNI__) && defined(__AVX512VL__) +// for (int iy = 0; iy < Q8::nrc_y; ++iy) { +// sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4*j+0))); +// sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 4*j+1))); +// sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 4*j+2))); +// sumi[iy] = _mm256_dpwssd_epi32(sumi[iy], scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 4*j+3))); +// } +//#else +// for (int iy = 0; iy < Q8::nrc_y; ++iy) { +// const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4*j+0))); +// const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 4*j+1))); +// const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 4*j+2))); +// const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 4*j+3))); +// sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p1, p3)); +// sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p2, p4)); +// } +//#endif +//} + +template +static void mul_mat_qX_K_q8_K_IQ_N(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_K; + Q8 q8(info); + Dequantizer deq(vx, bx); + __m256i scales[4]; + __m256 accd[nrc_y]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps(); + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + __m256i sumi[nrc_y], all_scales[Dequantizer::num_blocks/8]; + //for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = _mm256_setzero_si256(); + __m256i mins; + float dmin = deq.new_block(i, all_scales, mins); + for (int iy = 0; iy < nrc_y; ++iy) { + auto bsums = q8.load_bsums(iy, i); + auto prod = _mm256_madd_epi16(mins, bsums); + accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(dmin*q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accd[iy]); + } + + for (int j = 0; j < QK_K/128; ++j) { + deq.prepare(i, j); + if constexpr (Dequantizer::num_blocks == 8) { + set_scales_8(all_scales[0], j, scales); + } else { + set_scales_16(all_scales[j], scales); + } + //multiply_add_iq(deq.bits, scales, j, i, q8, sumi); + multiply_add(deq.bits, scales, j, i, q8, sumi); + } + for (int iy = 0; iy < nrc_y; ++iy) { + const __m256 vd = _mm256_set1_ps(deq.d*q8.scale(iy, i)); + accd[iy] = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(sumi[iy]), accd[iy]); + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, hsum_float_8(accd[iy])); + } + } +} + +template struct Q8_K64 { + + constexpr static int nrc_y = nrc; + + Q8_K64(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) { + const float * dptr = (const float *)info.src1_row(iy); + std::memcpy(d + 8*iy, dptr, 8*sizeof(float)); + y[iy] = (const int8_t *)(dptr + 8); + } + } + + inline __m256i load_quants(int iy, int i, int j) const { return _mm256_loadu_si256((const __m256i*)y[iy] + 4*i + j); } + inline __m128 scale(int iy) const { return _mm_loadu_ps(d + 8*iy); } + inline __m128 minus(int iy) const { return _mm_loadu_ps(d + 8*iy + 4); } + + float d[8*nrc_y]; + const int8_t * y[nrc_y]; +}; + +struct DequantizerIQ1BN { + const __m256i m1_8 = _mm256_set1_epi8(1); + static __m256i load_shuffle(int i) { + static const uint8_t data[128] = { + 0, 255, 0, 255, 0, 255, 0, 255, 0, 255, 1, 255, 1, 255, 1, 255, 1, 255, 1, 255, 2, 255, 2, 255, 2, 255, 2, 255, 2, 255, 12, 255, + 3, 255, 3, 255, 3, 255, 3, 255, 3, 255, 4, 255, 4, 255, 4, 255, 4, 255, 4, 255, 5, 255, 5, 255, 5, 255, 5, 255, 5, 255, 12, 255, + 6, 255, 6, 255, 6, 255, 6, 255, 6, 255, 7, 255, 7, 255, 7, 255, 7, 255, 7, 255, 8, 255, 8, 255, 8, 255, 8, 255, 8, 255, 12, 255, + 9, 255, 9, 255, 9, 255, 9, 255, 9, 255, 10, 255, 10, 255, 10, 255, 10, 255, 10, 255, 11, 255, 11, 255, 11, 255, 11, 255, 11, 255, 12, 255, + }; + return _mm256_loadu_si256((const __m256i*)data + i); + } + const __m256i shuff[4] = { load_shuffle(0), load_shuffle(1), load_shuffle(2), load_shuffle(3) }; + const __m256i mult[4] = { + _mm256_set_epi64x(0x5100010003000900, 0x1b00510001000300, 0x09001b0051000100, 0x030009001b005100), + _mm256_set_epi64x(0x1b00010003000900, 0x1b00510001000300, 0x09001b0051000100, 0x030009001b005100), + _mm256_set_epi64x(0x0900010003000900, 0x1b00510001000300, 0x09001b0051000100, 0x030009001b005100), + _mm256_set_epi64x(0x0300010003000900, 0x1b00510001000300, 0x09001b0051000100, 0x030009001b005100), + }; + const __m256i m3 = _mm256_set1_epi16(3); +#ifdef HAVE_FANCY_SIMD + const __m256i bmask = _mm256_set_epi8(62, 60, 58, 56, 54, 52, 50, 48, 46, 44, 42, 40, 38, 36, 34, 32, 30, 28, 26, 24, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0); +#endif + + IQK_ALWAYS_INLINE void prepare_iq1bn_quants(const block_iq1_bn * x, __m256i& v1, __m256i& v2) const { + auto data128 = _mm_loadu_si128((const __m128i *)x); // Note: we load 16 instead of 13 bytes! + auto data = MM256_SET_M128I(data128, data128); + auto val1 = _mm256_mulhi_epu16(_mm256_mullo_epi16(_mm256_shuffle_epi8(data, shuff[0]), mult[0]), m3); + auto val2 = _mm256_mulhi_epu16(_mm256_mullo_epi16(_mm256_shuffle_epi8(data, shuff[1]), mult[1]), m3); + auto val3 = _mm256_mulhi_epu16(_mm256_mullo_epi16(_mm256_shuffle_epi8(data, shuff[2]), mult[2]), m3); + auto val4 = _mm256_mulhi_epu16(_mm256_mullo_epi16(_mm256_shuffle_epi8(data, shuff[3]), mult[3]), m3); +#ifdef HAVE_FANCY_SIMD + v1 = _mm256_permutex2var_epi8(val1, bmask, val2); + v2 = _mm256_permutex2var_epi8(val3, bmask, val4); +#else + v1 = _mm256_permute4x64_epi64(_mm256_packs_epi16(val1, val2), 216); + v2 = _mm256_permute4x64_epi64(_mm256_packs_epi16(val3, val4), 216); +#endif + } + +}; + +template +IQK_NOINLINE void mul_mat_iq1bn_q8_K64(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_IQ1BN; + Q8_K64 q8(info); + DequantizerIQ1BN deq; + __m256i accd[nrc_y]; + __m256i val[4]; + +#if !(defined __AVX512VNNI__ && defined __AVX512VL__) + const auto m1_16 = _mm256_set1_epi16(1); +#endif + + const block_iq1_bn * x; + const char * cx0 = (const char *)vx; + float scale; + + for (int ix = 0; ix < nrc_x; ++ix) { + + const char * cx = cx0 + ix*bx; + if constexpr (is_iq1_tn) { + scale = GGML_FP16_TO_FP32(*(const ggml_half *)cx); + cx += sizeof(ggml_half); + } + x = (const block_iq1_bn *)cx; + + if constexpr (nrc_y == 1) { + __m256i acc1 = _mm256_setzero_si256(), acc2 = _mm256_setzero_si256(); + for (int i = 0; i < nb/2; ++i) { + deq.prepare_iq1bn_quants(x + 2*i + 0, val[0], val[1]); + deq.prepare_iq1bn_quants(x + 2*i + 1, val[2], val[3]); +#if defined __AVX512VNNI__ && defined __AVX512VL__ + acc1 = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(acc1, val[0], q8.load_quants(0, i, 0)), val[1], q8.load_quants(0, i, 1)); + acc2 = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(acc2, val[2], q8.load_quants(0, i, 2)), val[3], q8.load_quants(0, i, 3)); +#else + auto dot1 = _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(0, i, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(0, i, 1))); + auto dot2 = _mm256_add_epi16(_mm256_maddubs_epi16(val[2], q8.load_quants(0, i, 2)), + _mm256_maddubs_epi16(val[3], q8.load_quants(0, i, 3))); + acc1 = _mm256_add_epi32(acc1, _mm256_madd_epi16(m1_16, dot1)); + acc2 = _mm256_add_epi32(acc2, _mm256_madd_epi16(m1_16, dot2)); +#endif + } + accd[0] = _mm256_add_epi32(acc1, acc2); + } + else { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_si256(); + + for (int i = 0; i < nb/2; ++i) { + + deq.prepare_iq1bn_quants(x + 2*i + 0, val[0], val[1]); + deq.prepare_iq1bn_quants(x + 2*i + 1, val[2], val[3]); + + for (int iy = 0; iy < nrc_y; ++iy) { +#if defined __AVX512VNNI__ && defined __AVX512VL__ + accd[iy] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(_mm256_dpbusd_epi32(_mm256_dpbusd_epi32(accd[iy], + val[0], q8.load_quants(iy, i, 0)), + val[1], q8.load_quants(iy, i, 1)), + val[2], q8.load_quants(iy, i, 2)), + val[3], q8.load_quants(iy, i, 3)); +#else + auto dot1 = _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(iy, i, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(iy, i, 1))); + auto dot2 = _mm256_add_epi16(_mm256_maddubs_epi16(val[2], q8.load_quants(iy, i, 2)), + _mm256_maddubs_epi16(val[3], q8.load_quants(iy, i, 3))); + dot1 = _mm256_madd_epi16(m1_16, _mm256_add_epi16(dot1, dot2)); + accd[iy] = _mm256_add_epi32(dot1, accd[iy]); +#endif + } + } + } + int i = 2*(nb/2); + if (i < nb) { + deq.prepare_iq1bn_quants(x + i, val[0], val[1]); + for (int iy = 0; iy < nrc_y; ++iy) { +#if defined __AVX512VNNI__ && defined __AVX512VL__ + accd[iy] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(accd[iy], + val[0], q8.load_quants(iy, i/2, 0)), val[1], q8.load_quants(iy, i/2, 1)); +#else + auto dot = _mm256_madd_epi16(m1_16, _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(iy, i/2, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(iy, i/2, 1)))); + accd[iy] = _mm256_add_epi32(dot, accd[iy]); +#endif + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + auto vd = q8.scale(iy); + auto sumi = _mm_add_epi32(_mm256_castsi256_si128(accd[iy]), _mm256_extractf128_si256(accd[iy], 1)); + auto sumf = _mm_fmsub_ps(vd, _mm_cvtepi32_ps(sumi), q8.minus(iy)); + if constexpr (is_iq1_tn) { + info.store(ix, iy, scale*hsum_float_4(sumf)); + } else { + info.store(ix, iy, hsum_float_4(sumf)); + } + } + + } +} + +struct DequantizeIQ2BN final : public BaseDequantizer { + DequantizeIQ2BN(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + IQK_ALWAYS_INLINE void prepare4(int i, __m256i * val) const { + auto q2bits_1 = _mm256_loadu_si256((const __m256i *)x[2*i].qs); + auto q2bits_2 = _mm256_srli_epi16(q2bits_1, 2); + make2(_mm256_permute2x128_si256(q2bits_1, q2bits_2, 0x20), val+0); + make2(_mm256_permute2x128_si256(q2bits_1, q2bits_2, 0x31), val+2); + } + IQK_ALWAYS_INLINE void make2(__m256i q2_1, __m256i * val) const { + val[0] = _mm256_and_si256(q2_1, mask2); + val[1] = _mm256_and_si256(_mm256_srli_epi16(q2_1, 4), mask2); + } + IQK_ALWAYS_INLINE void prepare2(int i, __m256i * val) const { + auto q2bits_1 = _mm_loadu_si128((const __m128i *)x[i].qs); + make2(MM256_SET_M128I(_mm_srli_epi16(q2bits_1, 2), q2bits_1), val); + } + const __m256i m1_8 = _mm256_set1_epi8(1); + const __m256i mf_8 = _mm256_set1_epi8(16); + const __m256i mask2 = _mm256_set1_epi8(0x03); + const __m256i mask3 = _mm256_set1_epi8(0x30); +}; + +template +IQK_NOINLINE void mul_mat_iq2bn_q8_K64(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_IQ1BN; + Q8_K64 q8(info); + DequantizeIQ2BN deq(vx, bx); + __m256i accd[nrc_y]; + __m256i val[4]; + +#if !(defined __AVX512VNNI__ && defined __AVX512VL__) + const auto m1_16 = _mm256_set1_epi16(1); +#endif + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + if constexpr (nrc_y == 1) { + __m256i acc[2] = {}; + for (int i = 0; i < nb/2; ++i) { + deq.prepare4(i, val); +#if defined __AVX512VNNI__ && defined __AVX512VL__ + acc[0] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(acc[0], val[0], q8.load_quants(0, i, 0)), + val[1], q8.load_quants(0, i, 1)); + acc[1] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(acc[1], val[2], q8.load_quants(0, i, 2)), + val[3], q8.load_quants(0, i, 3)); +#else + auto dot1 = _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(0, i, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(0, i, 1))); + auto dot2 = _mm256_add_epi16(_mm256_maddubs_epi16(val[2], q8.load_quants(0, i, 2)), + _mm256_maddubs_epi16(val[3], q8.load_quants(0, i, 3))); + acc[0] = _mm256_add_epi32(acc[0], _mm256_madd_epi16(m1_16, dot1)); + acc[1] = _mm256_add_epi32(acc[1], _mm256_madd_epi16(m1_16, dot2)); +#endif + } + accd[0] = _mm256_add_epi32(acc[0], acc[1]); + } + else { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_si256(); + + for (int i = 0; i < nb/2; ++i) { + deq.prepare4(i, val); + for (int iy = 0; iy < nrc_y; ++iy) { +#if defined __AVX512VNNI__ && defined __AVX512VL__ + accd[iy] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(_mm256_dpbusd_epi32(_mm256_dpbusd_epi32(accd[iy], + val[0], q8.load_quants(iy, i, 0)), val[1], q8.load_quants(iy, i, 1)), + val[2], q8.load_quants(iy, i, 2)), val[3], q8.load_quants(iy, i, 3)); +#else + auto dot = _mm256_madd_epi16(m1_16, _mm256_add_epi16( + _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(iy, i, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(iy, i, 1))), + _mm256_add_epi16(_mm256_maddubs_epi16(val[2], q8.load_quants(iy, i, 2)), + _mm256_maddubs_epi16(val[3], q8.load_quants(iy, i, 3))))); + accd[iy] = _mm256_add_epi32(dot, accd[iy]); +#endif + } + } + } + int i = 2*(nb/2); + if (i < nb) { + deq.prepare2(i, val); + for (int iy = 0; iy < nrc_y; ++iy) { +#if defined __AVX512VNNI__ && defined __AVX512VL__ + accd[iy] = _mm256_dpbusd_epi32(_mm256_dpbusd_epi32(accd[iy], val[0], q8.load_quants(iy, i/2, 0)), + val[1], q8.load_quants(iy, i/2, 1)); +#else + auto dot = _mm256_madd_epi16(m1_16, _mm256_add_epi16(_mm256_maddubs_epi16(val[0], q8.load_quants(iy, i/2, 0)), + _mm256_maddubs_epi16(val[1], q8.load_quants(iy, i/2, 0)))); + accd[iy] = _mm256_add_epi32(dot, accd[iy]); +#endif + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + auto vd = q8.scale(iy); + auto sumi = _mm_add_epi32(_mm256_castsi256_si128(accd[iy]), _mm256_extractf128_si256(accd[iy], 1)); + auto sumf = _mm_fmsub_ps(vd, _mm_cvtepi32_ps(sumi), q8.minus(iy)); + info.store(ix, iy, hsum_float_4(sumf)); + } + } +} + +template +static void mul_mat_qX_K_q8_K_IQ(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + if constexpr (nrc_y == 1) { + mul_mat_qX_K_q8_K_IQ_1(n, vx, bx, info, nrc_x); + } else { + mul_mat_qX_K_q8_K_IQ_N(n, vx, bx, info, nrc_x); + } +} + +//#ifdef HAVE_FANCY_SIMD +// Strangely enough, the following implementation makes PP ~6% slower and TG ~6% faster +// compared to the vanilla AVX2 version below. +//struct IndexHelperIQ3S { +// union index_t { +// __m256i vec; +// uint16_t val[16]; +// }; +// inline void make2(const uint8_t * qs, const uint8_t * qh, __m256i * values) const { +// auto idx_l = _mm256_cvtepu8_epi16(_mm_loadu_si128((const __m128i *)qs)); +// const __mmask16 * m16 = (const __mmask16 *)qh; +// index_t idx; +// idx.vec = _mm256_mask_add_epi16(idx_l, m16[0], idx_l, offset); +// values[0] = _mm256_set_epi32(iq3s_grid[idx.val[ 7]], iq3s_grid[idx.val[ 6]], iq3s_grid[idx.val[ 5]], iq3s_grid[idx.val[ 4]], +// iq3s_grid[idx.val[ 3]], iq3s_grid[idx.val[ 2]], iq3s_grid[idx.val[ 1]], iq3s_grid[idx.val[ 0]]); +// values[1] = _mm256_set_epi32(iq3s_grid[idx.val[15]], iq3s_grid[idx.val[14]], iq3s_grid[idx.val[13]], iq3s_grid[idx.val[12]], +// iq3s_grid[idx.val[11]], iq3s_grid[idx.val[10]], iq3s_grid[idx.val[ 9]], iq3s_grid[idx.val[ 8]]); +// } +// const __m256i offset = _mm256_set1_epi16(256); +//}; +//#else +struct IndexHelperIQ3S { + union index_t { + __m256i vec; + uint32_t val[8]; + }; + inline void make2(const uint8_t * qs, const uint8_t * qh, __m256i * values) const { + index_t idx; + auto idx_l = _mm256_cvtepu8_epi32(_mm_loadl_epi64((const __m128i *)qs)); + auto idx_h = _mm256_and_si256(_mm256_sllv_epi32(_mm256_set1_epi32(qh[0]), idx_shift), idx_mask); + idx.vec = _mm256_or_si256(idx_h, idx_l); + values[0] = _mm256_set_epi32(iq3s_grid[idx.val[7]], iq3s_grid[idx.val[6]], iq3s_grid[idx.val[5]], iq3s_grid[idx.val[4]], + iq3s_grid[idx.val[3]], iq3s_grid[idx.val[2]], iq3s_grid[idx.val[1]], iq3s_grid[idx.val[0]]); + idx_l = _mm256_cvtepu8_epi32(_mm_loadl_epi64((const __m128i *)(qs+8))); + idx_h = _mm256_and_si256(_mm256_sllv_epi32(_mm256_set1_epi32(qh[1]), idx_shift), idx_mask); + idx.vec = _mm256_or_si256(idx_h, idx_l); + values[1] = _mm256_set_epi32(iq3s_grid[idx.val[7]], iq3s_grid[idx.val[6]], iq3s_grid[idx.val[5]], iq3s_grid[idx.val[4]], + iq3s_grid[idx.val[3]], iq3s_grid[idx.val[2]], iq3s_grid[idx.val[1]], iq3s_grid[idx.val[0]]); + } + const __m256i idx_mask = _mm256_set1_epi32(256); + const __m256i idx_shift = _mm256_set_epi32(1, 2, 3, 4, 5, 6, 7, 8); +}; +//#endif + +struct DequantizerIQ3S final : public BaseDequantizer { + DequantizerIQ3S(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + constexpr static int num_blocks = 8; + + inline __m128i make_scales(int i, float& dd) const { + dd = GGML_FP16_TO_FP32(x[i].d); + uint32_t aux32[2]; + std::memcpy(aux32, x[i].scales, 4); + aux32[1] = (aux32[0] >> 4) & 0x0f0f0f0f; + aux32[0] &= 0x0f0f0f0f; + auto scales8 = _mm_shuffle_epi8(_mm_loadl_epi64((const __m128i *)aux32), _mm_set1_epi64x(0x0703060205010400)); + auto scales16 = _mm256_castsi256_si128(_mm256_cvtepi8_epi16(scales8)); + return _mm_or_si128(_mm_slli_epi16(scales16, 1), _mm_set1_epi16(1)); + } + inline void new_block(int i, __m256i * scales) { + auto scales16 = make_scales(i, d); + scales[0] = MM256_SET_M128I(scales16, scales16); + } + inline float new_block(int i, __m256i * scales, __m256i& mins) { + auto scales16 = make_scales(i, d); + mins = scb.shuffle(scales16); + scales[0] = MM256_SET_M128I(scales16, scales16); + return -minv*d; + } + + inline void prepare(int i, int j) { + prepare_unsigned(i, j); + sh.sign_4_values((const uint16_t *)x[i].signs + 8*j, bits.values); + for (int k = 0; k < 4; ++k) bits.values[k] = _mm256_add_epi8(bits.values[k], min_value); + } + inline void prepare(int i, int j, const Q8<1>& q8, __m256i * q8_quants) { + prepare_unsigned(i, j); + for (int k = 0; k < 4; ++k) q8_quants[k] = q8.load_quants(0, i, 4*j+k); + sh.sign_4_values((const uint16_t *)x[i].signs + 8*j, q8_quants); + } + + inline void prepare_unsigned(int i, int j) { + auto qs = x[i].qs + 32*j; + auto qh = x[i].qh + 4*j; + helper.make2(qs+ 0, qh+0, bits.values+0); + helper.make2(qs+16, qh+2, bits.values+2); + } + + constexpr static int minv = 16; + + SimpleBits bits; + SignHelper sh; + Scales8KBase scb; + IndexHelperIQ3S helper; + const __m256i min_value = _mm256_set1_epi8(minv); + +}; + +struct EvenSignHelper { +#ifdef HAVE_FANCY_SIMD + union sbits_t { + __m128i vec; + __mmask32 mask[4]; + }; + IQK_ALWAYS_INLINE void sign_2_values(__m256i aux, __m256i * values) const { + aux = _mm256_and_si256(_mm256_srlv_epi32(aux, shifts), mask); + auto pcnt = _mm256_popcnt_epi32(aux); + sbits_t sbits; + sbits.vec = _mm256_cvtepi32_epi8(_mm256_or_si256(aux, _mm256_slli_epi32(_mm256_and_si256(pcnt, mone), 7))); + values[0] = _mm256_mask_sub_epi8(values[0], sbits.mask[0], _mm256_setzero_si256(), values[0]); + values[1] = _mm256_mask_sub_epi8(values[1], sbits.mask[1], _mm256_setzero_si256(), values[1]); + //auto sign_bits = _mm256_cvtepi32_epi8(_mm256_or_si256(aux, _mm256_slli_epi32(_mm256_and_si256(pcnt, mone), 7))); + //const __mmask32 * m32 = (const __mmask32 *)&sign_bits; + //values[0] = _mm256_mask_sub_epi8(values[0], m32[0], _mm256_setzero_si256(), values[0]); + //values[1] = _mm256_mask_sub_epi8(values[1], m32[1], _mm256_setzero_si256(), values[1]); + } + const __m256i shifts = _mm256_set_epi32(21, 14, 7, 0, 21, 14, 7, 0); + const __m256i mask = _mm256_set1_epi32(127); + const __m256i mone = _mm256_set1_epi32(1); +#else + inline void sign_value(uint32_t aux32, __m256i& value) const { + auto signs = _mm256_set_epi64x(keven_signs[(aux32 >> 21) & 127], keven_signs[(aux32 >> 14) & 127], + keven_signs[(aux32 >> 7) & 127], keven_signs[(aux32 >> 0) & 127]); + value = _mm256_sign_epi8(value, signs); + } +#endif +}; + +struct DequantizerIQ3XXS final : public BaseDequantizer { + DequantizerIQ3XXS(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + constexpr static int num_blocks = 8; + + inline __m128i prepare_scales(int i) { + d = 0.25f * GGML_FP16_TO_FP32(x[i].d); + auto tmp = _mm256_loadu_si256((const __m256i *)(x[i].qs + QK_K/4)); + auto scales32 = _mm256_srli_epi32(tmp, 28); + scales32 = _mm256_or_si256(_mm256_slli_epi32(scales32, 1), _mm256_set1_epi32(1)); + return _mm_packs_epi32(_mm256_castsi256_si128(scales32), _mm256_extractf128_si256(scales32, 1)); + } + + inline void new_block(int i, __m256i * scales) { + auto scales16 = prepare_scales(i); + scales[0] = MM256_SET_M128I(scales16, scales16); + } + inline float new_block(int i, __m256i * scales, __m256i& mins) { + auto scales16 = prepare_scales(i); + mins = scb.shuffle(scales16); + scales[0] = MM256_SET_M128I(scales16, scales16); + return -d*minv; + } + + inline static __m256i make_quants(const uint8_t * qs) { + return _mm256_set_epi32(iq3xxs_grid[qs[7]], iq3xxs_grid[qs[6]], iq3xxs_grid[qs[5]], iq3xxs_grid[qs[4]], + iq3xxs_grid[qs[3]], iq3xxs_grid[qs[2]], iq3xxs_grid[qs[1]], iq3xxs_grid[qs[0]]); + } + inline static void make4_unsigned(const uint8_t * qs, __m256i * values) { + values[0] = make_quants(qs+ 0); + values[1] = make_quants(qs+ 8); + values[2] = make_quants(qs+16); + values[3] = make_quants(qs+24); + } + + IQK_ALWAYS_INLINE void sign_2_values(const uint16_t * signs, __m256i * values) const { +#ifdef HAVE_FANCY_SIMD + esh.sign_2_values(MM256_SET_M128I(_mm_set1_epi32(signs[2] | (signs[3] << 16)), _mm_set1_epi32(signs[0] | (signs[1] << 16))), values); +#else + esh.sign_value(signs[0] | (signs[1] << 16), values[0]); + esh.sign_value(signs[2] | (signs[3] << 16), values[1]); +#endif + } + + inline void prepare(int i, int j) { + auto qs = x[i].qs + 32*j; + const uint16_t * signs = (const uint16_t *)(x[i].qs + QK_K/4) + 8*j; + make4_unsigned(qs, bits.values); + sign_2_values(signs+0, bits.values+0); + sign_2_values(signs+4, bits.values+2); + for (int k = 0; k < 4; ++k) bits.values[k] = _mm256_add_epi32(bits.values[k], min_value); + } + inline void prepare(int i, int j, const Q8<1>& q8, __m256i * q8_quants) { + for (int k = 0; k < 4; ++k) q8_quants[k] = q8.load_quants(0, i, 4*j+k); + auto qs = x[i].qs + 32*j; + const uint16_t * signs = (const uint16_t *)(x[i].qs + QK_K/4) + 8*j; + make4_unsigned(qs, bits.values); + sign_2_values(signs+0, q8_quants+0); + sign_2_values(signs+4, q8_quants+2); + } + + constexpr static int minv = 64; + + SimpleBits bits; + Scales8KBase scb; + EvenSignHelper esh; + const __m256i min_value = _mm256_set1_epi8(minv); + +}; + +struct DequantizerIQ2S final : public BaseDequantizer { + DequantizerIQ2S(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + constexpr static int num_blocks = 16; + + inline __m256i load_scales(int i) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + auto tmp = _mm_loadl_epi64((const __m128i *)x[i].scales); + auto all = _mm_and_si128(_mm_unpacklo_epi8(tmp, _mm_srli_epi16(tmp, 4)), _mm_set1_epi8(0xf)); + auto scales8 = _mm_or_si128(_mm_slli_epi16(all, 1), _mm_set1_epi8(1)); + return _mm256_cvtepi8_epi16(scales8); + } + inline static void prepare_scales(const __m256i& all, __m256i * scales) { + auto scales_l = _mm256_castsi256_si128(all); + auto scales_h = _mm256_extractf128_si256(all, 1); + scales[0] = MM256_SET_M128I(scales_l, scales_l); + scales[1] = MM256_SET_M128I(scales_h, scales_h); + } + + inline void new_block(int i, __m256i * scales) { + prepare_scales(load_scales(i), scales); + } + inline float new_block(int i, __m256i * scales, __m256i& mins) { + mins = load_scales(i); + prepare_scales(mins, scales); + return -d*minv; + } + + union index_t { + __m256i vec; + uint32_t val[8]; + }; + + inline static void make2(const uint8_t * qs, const uint8_t * qh, const __m256i& idx_shift, const __m256i& idx_mask, __m256i * values) { + auto idx_l = _mm256_cvtepu8_epi32(_mm_loadl_epi64((const __m128i *)qs)); + auto idx_h = MM256_SET_M128I(_mm_set1_epi32(qh[1]), _mm_set1_epi32(qh[0])); + index_t idx; + idx.vec = _mm256_or_si256(idx_l, _mm256_and_si256(_mm256_sllv_epi32(idx_h, idx_shift), idx_mask)); + values[0] = _mm256_set_epi64x(iq2s_grid[idx.val[3]], iq2s_grid[idx.val[2]], iq2s_grid[idx.val[1]], iq2s_grid[idx.val[0]]); + values[1] = _mm256_set_epi64x(iq2s_grid[idx.val[7]], iq2s_grid[idx.val[6]], iq2s_grid[idx.val[5]], iq2s_grid[idx.val[4]]); + } + inline static void make2_signed(const SignHelper& sh, const uint8_t * qs, const uint8_t * qh, const uint16_t * sidx, + const __m256i& idx_shift, const __m256i& idx_mask, const __m256i& min_value, __m256i * values) { + make2(qs, qh, idx_shift, idx_mask, values); + values[0] = _mm256_add_epi8(sh.sign_value(sidx+0, values[0]), min_value); + values[1] = _mm256_add_epi8(sh.sign_value(sidx+2, values[1]), min_value); + } + + inline void prepare(int i, int j) { + auto qs = x[i].qs + 16*j; + auto qh = x[i].qh + 4*j; + const uint16_t * signs = (const uint16_t *)(x[i].qs + QK_K/8) + 8*j; + make2_signed(sh, qs+0, qh+0, signs+0, idx_shift, idx_mask, min_value, bits.values+0); + make2_signed(sh, qs+8, qh+2, signs+4, idx_shift, idx_mask, min_value, bits.values+2); + } + inline void prepare(int i, int j, const Q8<1>& q8, __m256i * q8_quants) { + auto qs = x[i].qs + 16*j; + auto qh = x[i].qh + 4*j; + const uint16_t * signs = (const uint16_t *)(x[i].qs + QK_K/8) + 8*j; + make2(qs+0, qh+0, idx_shift, idx_mask, bits.values+0); + make2(qs+8, qh+2, idx_shift, idx_mask, bits.values+2); + q8_quants[0] = _mm256_sign_epi8(q8.load_quants(0, i, 4*j+0), sh.make_signs(signs[0] | (signs[1] << 16))); + q8_quants[1] = _mm256_sign_epi8(q8.load_quants(0, i, 4*j+1), sh.make_signs(signs[2] | (signs[3] << 16))); + q8_quants[2] = _mm256_sign_epi8(q8.load_quants(0, i, 4*j+2), sh.make_signs(signs[4] | (signs[5] << 16))); + q8_quants[3] = _mm256_sign_epi8(q8.load_quants(0, i, 4*j+3), sh.make_signs(signs[6] | (signs[7] << 16))); + } + + constexpr static int minv = 43; + + SimpleBits bits; + SignHelper sh; + const __m256i idx_shift = _mm256_set_epi32(2, 4, 6, 8, 2, 4, 6, 8); + const __m256i idx_mask = _mm256_set1_epi32(0x300); + const __m256i min_value = _mm256_set1_epi8(minv); + +}; + +struct DequantizerIQ2XS final : public BaseDequantizer { + DequantizerIQ2XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + constexpr static int num_blocks = 16; + + inline __m256i load_scales(int i) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + auto tmp = _mm_loadl_epi64((const __m128i *)x[i].scales); + auto all = _mm_and_si128(_mm_unpacklo_epi8(tmp, _mm_srli_epi16(tmp, 4)), _mm_set1_epi8(0xf)); + auto scales8 = _mm_or_si128(_mm_slli_epi16(all, 1), _mm_set1_epi8(1)); + return _mm256_cvtepi8_epi16(scales8); + } + inline static void prepare_scales(const __m256i& all, __m256i * scales) { + auto scales_l = _mm256_castsi256_si128(all); + auto scales_h = _mm256_extractf128_si256(all, 1); + scales[0] = MM256_SET_M128I(scales_l, scales_l); + scales[1] = MM256_SET_M128I(scales_h, scales_h); + } + + inline void new_block(int i, __m256i * scales) { + prepare_scales(load_scales(i), scales); + } + inline float new_block(int i, __m256i * scales, __m256i& mins) { + mins = load_scales(i); + prepare_scales(mins, scales); + return -d*minv; + } + + struct Helper { + const __m256i mone = _mm256_set1_epi8(1); + const __m256i mask = _mm256_set1_epi64x(0x8040201008040201); + //const __m256i bhelper = _mm256_set_epi64x(0x8000008000808000, 0x0080800080000080, 0x8000008000808000, 0x0080800080000080); + const __m256i bhelper = load_bhelper(); + const __m256i shuff1 = _mm256_set_epi64x(0x0606060606060606, 0x0404040404040404, 0x0202020202020202, 0x0000000000000000); + const __m256i shuff2 = _mm256_set_epi64x(0x0e0e0e0e0e0e0e0e, 0x0c0c0c0c0c0c0c0c, 0x0a0a0a0a0a0a0a0a, 0x0808080808080808); + static __m256i load_bhelper() { + static const uint8_t k_bit_helper[32] = { + 0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00, + 0x00, 0x80, 0x80, 0x00, 0x80, 0x00, 0x00, 0x80, 0x80, 0x00, 0x00, 0x80, 0x00, 0x80, 0x80, 0x00, + }; + return _mm256_loadu_si256((const __m256i*)k_bit_helper); + } + }; + + union index_t { + __m256i vec; + uint16_t val[8]; + }; + + inline static void make4(const __m256i& data, const __m256i& mask, __m256i * values) { + index_t idx; + idx.vec = _mm256_and_si256(data, mask); + values[0] = _mm256_set_epi64x(iq2xs_grid[idx.val[ 3]], iq2xs_grid[idx.val[ 2]], iq2xs_grid[idx.val[ 1]], iq2xs_grid[idx.val[ 0]]); + values[1] = _mm256_set_epi64x(iq2xs_grid[idx.val[ 7]], iq2xs_grid[idx.val[ 6]], iq2xs_grid[idx.val[ 5]], iq2xs_grid[idx.val[ 4]]); + values[2] = _mm256_set_epi64x(iq2xs_grid[idx.val[11]], iq2xs_grid[idx.val[10]], iq2xs_grid[idx.val[ 9]], iq2xs_grid[idx.val[ 8]]); + values[3] = _mm256_set_epi64x(iq2xs_grid[idx.val[15]], iq2xs_grid[idx.val[14]], iq2xs_grid[idx.val[13]], iq2xs_grid[idx.val[12]]); + } + inline static void sign_value(const __m256i& sign_bits, const __m256i& shuffle, const __m256i& mask, + const __m256i& mone, __m256i& value) { + auto signs = _mm256_shuffle_epi8(sign_bits, shuffle); + signs = _mm256_cmpeq_epi8(_mm256_and_si256(signs, mask), mask); + value = _mm256_sign_epi8(value, _mm256_or_si256(signs, mone)); + } + inline void sign_values(const __m256i& data, __m256i * values) const { +#ifdef HAVE_FANCY_SIMD + auto partial_bits = _mm256_cvtepi16_epi8(_mm256_srli_epi16(data, 9)); + auto pcnt = _mm_popcnt_epi8(partial_bits); + auto full_bits = _mm_or_si128(partial_bits, _mm_slli_epi16(_mm_and_si128(pcnt, _mm_set1_epi8(1)), 7)); + const __mmask32 * m32 = (const __mmask32 *)&full_bits; + auto zero = _mm256_setzero_si256(); + values[0] = _mm256_mask_sub_epi8(values[0], m32[0], zero, values[0]); + values[1] = _mm256_mask_sub_epi8(values[1], m32[1], zero, values[1]); + values[2] = _mm256_mask_sub_epi8(values[2], m32[2], zero, values[2]); + values[3] = _mm256_mask_sub_epi8(values[3], m32[3], zero, values[3]); +#else + auto psb1 = _mm256_srli_epi16(data, 9); + auto psb2 = _mm256_srli_epi16(data, 13); + auto psbc = _mm256_xor_si256(psb1, psb2); + auto oddb = _mm256_shuffle_epi8(helper.bhelper, psbc); + auto full = _mm256_or_si256(psb1, oddb); + auto full_l = _mm256_castsi256_si128(full); + auto full_h = _mm256_extractf128_si256(full, 1); + auto full_1 = MM256_SET_M128I(full_l, full_l); + auto full_2 = MM256_SET_M128I(full_h, full_h); + sign_value(full_1, helper.shuff1, helper.mask, helper.mone, values[0]); + sign_value(full_1, helper.shuff2, helper.mask, helper.mone, values[1]); + sign_value(full_2, helper.shuff1, helper.mask, helper.mone, values[2]); + sign_value(full_2, helper.shuff2, helper.mask, helper.mone, values[3]); +#endif + } + inline void make4_signed(const uint16_t * qs, const __m256i& m511, + const __m256i& min_value, __m256i * values) const { + auto q2 = _mm256_loadu_si256((const __m256i *)qs); + make4(q2, m511, values); + sign_values(q2, values); + for (int k = 0; k < 4; ++k) values[k] = _mm256_add_epi8(values[k], min_value); + } + inline void make4(const uint16_t * qs, const __m256i& m511, __m256i * values, __m256i * q8) const { + auto q2 = _mm256_loadu_si256((const __m256i *)qs); + make4(q2, m511, values); + sign_values(q2, q8); + } + + inline void prepare(int i, int j) { + make4_signed(x[i].qs + 16*j, idx_mask, min_value, bits.values); + } + inline void prepare(int i, int j, const Q8<1>& q8, __m256i * q8_quants) { + for (int k = 0; k < 4; ++k) q8_quants[k] = q8.load_quants(0, i, 4*j+k); + make4(x[i].qs + 16*j, idx_mask, bits.values, q8_quants); + } + + constexpr static int minv = 43; + + SimpleBits bits; +#ifndef HAVE_FANCY_SIMD + Helper helper; +#endif + const __m256i idx_mask = _mm256_set1_epi16(511); + const __m256i min_value = _mm256_set1_epi8(minv); + +}; + +struct DequantizerIQ2XXS final : public BaseDequantizer { + DequantizerIQ2XXS(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {} + + constexpr static int num_blocks = 8; + + union Data { + __m256i vec; + uint32_t val[8]; + }; + + inline __m128i load_scales(int i) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + const uint16_t * a16 = (const uint16_t *)x[i].qs; + auto scales = _mm_srli_epi16(_mm_set_epi16(a16[31], a16[27], a16[23], a16[19], a16[15], a16[11], a16[7], a16[3]), 12); + return _mm_or_si128(_mm_slli_epi16(scales, 1), _mm_set1_epi16(1)); + } + + inline void new_block(int i, __m256i * scales) { + auto sc16 = load_scales(i); + scales[0] = MM256_SET_M128I(sc16, sc16); + } + inline float new_block(int i, __m256i * scales, __m256i& mins) { + auto sc16 = load_scales(i); + mins = scb.shuffle(sc16); + scales[0] = MM256_SET_M128I(sc16, sc16); + return -d*minv; + } + + inline static void make4(const uint32_t * aux32, __m256i * values) { + const uint8_t * aux8 = (const uint8_t *)aux32; + values[0] = _mm256_set_epi64x(iq2xxs_grid[aux8[ 3]], iq2xxs_grid[aux8[ 2]], iq2xxs_grid[aux8[ 1]], iq2xxs_grid[aux8[ 0]]); + values[1] = _mm256_set_epi64x(iq2xxs_grid[aux8[11]], iq2xxs_grid[aux8[10]], iq2xxs_grid[aux8[ 9]], iq2xxs_grid[aux8[ 8]]); + values[2] = _mm256_set_epi64x(iq2xxs_grid[aux8[19]], iq2xxs_grid[aux8[18]], iq2xxs_grid[aux8[17]], iq2xxs_grid[aux8[16]]); + values[3] = _mm256_set_epi64x(iq2xxs_grid[aux8[27]], iq2xxs_grid[aux8[26]], iq2xxs_grid[aux8[25]], iq2xxs_grid[aux8[24]]); + } + + IQK_ALWAYS_INLINE void sign_values(const uint32_t * aux32, __m256i * values) const { +#ifdef HAVE_FANCY_SIMD + esh.sign_2_values(MM256_SET_M128I(_mm_set1_epi32(aux32[3]), _mm_set1_epi32(aux32[1])), values+0); + esh.sign_2_values(MM256_SET_M128I(_mm_set1_epi32(aux32[7]), _mm_set1_epi32(aux32[5])), values+2); +#else + esh.sign_value(aux32[1], values[0]); + esh.sign_value(aux32[3], values[1]); + esh.sign_value(aux32[5], values[2]); + esh.sign_value(aux32[7], values[3]); +#endif + } + inline void make4_signed(const uint32_t * aux32, const __m256i& min_value, __m256i * values) const { + make4(aux32, values); + sign_values(aux32, values); + for (int k = 0; k < 4; ++k) values[k] = _mm256_add_epi8(values[k], min_value); + } + inline void make4(const uint32_t * aux32, __m256i * values, __m256i * q8) const { + make4(aux32, values); + sign_values(aux32, q8); + } + inline void prepare(int i, int j) { + Data data; data.vec = _mm256_loadu_si256((const __m256i *)x[i].qs + j); + make4_signed(data.val, min_value, bits.values); + } + inline void prepare(int i, int j, const Q8<1>& q8, __m256i * q8_quants) { + for (int k = 0; k < 4; ++k) q8_quants[k] = q8.load_quants(0, i, 4*j+k); + Data data; data.vec = _mm256_loadu_si256((const __m256i *)x[i].qs + j); + make4(data.val, bits.values, q8_quants); + } + + constexpr static int minv = 43; + SimpleBits bits; + Scales8KBase scb; + EvenSignHelper esh; + const __m256i min_value = _mm256_set1_epi8(minv); + const __m256i shuffle = _mm256_set_epi32(7, 5, 3, 1, 7, 5, 3, 1); +}; + +// +// ============================== Legacy quants +// + +struct DotHelper { + const __m256i m1 = _mm256_set1_epi16(1); +#if defined(__AVX512VNNI__) && defined(__AVX512VL__) + inline __m256i dot(__m256i x, __m256i y) const { + return _mm256_dpbusd_epi32(_mm256_setzero_si256(), x, y); + } +#else + inline __m256i dot(__m256i x, __m256i y) const { + return _mm256_madd_epi16(m1, _mm256_maddubs_epi16(x, y)); + } +#endif +}; + +struct SignedDot { + DotHelper helper; + inline __m256i compute(__m256i x, __m256i y) const { + return helper.dot(_mm256_sign_epi8(x, x), _mm256_sign_epi8(y, x)); + } +}; +struct UnsignedDot { + DotHelper helper; + inline __m256i compute(__m256i x, __m256i y) const { + return helper.dot(x, y); + } +}; + +template struct Sum4 { + Dot dot; + inline __m256i compute(const __m256i * qx, const Q8 * y) const { + const Q8x4 * y4 = (const Q8x4 *)y; + const __m256i p0 = dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y4->qs+0)); // 8x block 0 + const __m256i p1 = dot.compute(qx[1], _mm256_loadu_si256((const __m256i *)y4->qs+1)); // 8x block 1 + const __m256i p2 = dot.compute(qx[2], _mm256_loadu_si256((const __m256i *)y4->qs+2)); // 8x block 2 + const __m256i p3 = dot.compute(qx[3], _mm256_loadu_si256((const __m256i *)y4->qs+3)); // 8x block 3 + if constexpr (can_pack) { + const __m256i p01 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p0, p1)); // 0,0, 1,1, 0,0, 1,1 + const __m256i p23 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p2, p3)); // 2,2, 3,3, 2,2, 3,3 + return _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p01, p23)); // 0,1,2,3, 0,1,2,3 + } else { + // Note to myself: this is much faster than using _mm256_hadd_epi32() + auto p01 = _mm256_add_epi32(_mm256_unpacklo_epi32(p0, p1), _mm256_unpackhi_epi32(p0, p1)); // 0,1, 0,1, 0,1, 0,1 + auto p23 = _mm256_add_epi32(_mm256_unpacklo_epi32(p2, p3), _mm256_unpackhi_epi32(p2, p3)); // 2,3, 2,3, 2,3, 2,3 + return _mm256_add_epi32(_mm256_unpacklo_epi64(p01, p23), _mm256_unpackhi_epi64(p01, p23)); // 0,1,2,3, 0,1,2,3 + } + } +}; + +struct ScaleHelperQ8_0 { + inline __m128 prepare4(const block_q8_0 * y) { + const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y; + return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)y4->d)); + } + inline __m128 prepare4(__m128 other_scales, const block_q8_0 * y) { + return _mm_mul_ps(other_scales, prepare4(y)); + } + template inline float prepare1(const Q * y) const { return GGML_FP16_TO_FP32(y->d); } + template inline float prepare1(float d, const Q * y) const { return d*prepare1(y); } +}; + +struct ScaleHelperQ_0 { + ggml_half scales8[4]; + template + inline __m128 prepare4(const Q * y) { + for (int j = 0; j < 4; ++j) scales8[j] = y[j].d; + return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)scales8)); + } + template + inline __m128 prepare4(__m128 other_scales, const Q * y) { + return _mm_mul_ps(other_scales, prepare4(y)); + } + template inline float prepare1(const Q * y) const { return GGML_FP16_TO_FP32(y->d); } + template inline float prepare1(float d, const Q * y) const { return d*prepare1(y); } +}; + +template +struct ScaleHelperQ_0_1 { + ggml_half scales8[4]; + template + inline __m256 prepare4(const Q * y) { + for (int j = 0; j < 4; ++j) scales8[j] = y[j].d; + auto s4 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)scales8)); + return _mm256_set_m128(_mm_mul_ps(s4, min), s4); + } + template + inline __m256 prepare4(__m256 other_scales, const Q * y) { + return _mm_mul256_ps(other_scales, prepare4(y)); + } + template inline std::pair prepare1(const Q * y) const { + float d = GGML_FP16_TO_FP32(y->d); + return std::make_pair(d, -d*float(min_value)); + } + std::pair inline prepare1(const std::pair& dm, const block_q8_1 * y) const { + return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->s)); + } + const __m128 min = _mm_set1_ps(float(-min_value)); +}; + +struct ScaleHelperQ8_1 { + template + inline __m256 prepare4(const Q * y) { + const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y; + return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)y4->d)); + } + template + inline __m256 prepare4(__m256 other_scales, const Q * y) { + return _mm256_mul_ps(other_scales, prepare4(y)); + } + template inline std::pair prepare1(const Q * y) const { + return std::make_pair(GGML_FP16_TO_FP32(y->d), GGML_FP16_TO_FP32(y->m)); + } + template inline std::pair prepare1(const std::pair& dm, const Q * y) const { + return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->m)); + } + std::pair inline prepare1(const std::pair& dm, const block_q8_1 * y) const { + return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->s)); + } +}; + +struct ScaleHelperQ_1 { + uint32_t scales8[4]; + const __m128i shuffle = _mm_set_epi16(0x0f0e, 0x0b0a, 0x0706, 0x0302, 0x0d0c, 0x0908, 0x0504, 0x0100); + + template + inline __m256 prepare4(const Q * y) { + for (int j = 0; j < 4; ++j) { + // it is slightly faster to directly dereference (const uint32 *)&y[j].d, but some compilers + // complain that this breaks strict-aliasing rules. + memcpy(scales8 + j, &y[j].d, sizeof(uint32_t)); + } + return _mm256_cvtph_ps(_mm_shuffle_epi8(_mm_loadu_si128((const __m128i *)scales8), shuffle)); + } + + template + inline __m256 prepare4(__m256 other_scales, const Q * y) { + return _mm256_mul_ps(other_scales, prepare4(y)); + } + + template inline std::pair prepare1(const Q * y) const { + return std::make_pair(GGML_FP16_TO_FP32(y->d), GGML_FP16_TO_FP32(y->m)); + } + template inline std::pair prepare1(const std::pair& dm, const Q * y) const { + return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->m)); + } + std::pair inline prepare1(const std::pair& dm, const block_q8_1 * y) const { + return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->s)); + } +}; + +struct MinusType0 { + inline __m256 compute(__m128 d, int) const { return _mm256_set_m128(d, d); } + inline float compute(float d, int) const { return d; } + inline float result(__m256 acc, int) const { return hsum_float_8(acc); } +}; + +template struct MinusType1 { + __m128 accm[nrc_y]; + MinusType1() { for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm_setzero_ps(); } + inline __m256 compute(__m256 dm, int iy) { + const __m128 d = _mm256_castps256_ps128(dm); + const __m128 m = _mm256_extractf128_ps(dm, 1); + accm[iy] = _mm_add_ps(accm[iy], m); + return _mm256_set_m128(d, d); + } + inline float compute(const std::pair& dm, int iy) { + accm[iy] = _mm_add_ps(accm[iy], _mm_set1_ps(dm.second*0.25f)); + return dm.first; + } + inline float result(__m256 acc, int iy) const { + const __m128 sum = _mm_add_ps(_mm256_castps256_ps128(acc), _mm256_extractf128_ps(acc, 1)); + return hsum_float_4(_mm_add_ps(sum, accm[iy])); + } +}; + +template struct AccumT { + __m256 acc[nrc_y]; + Minus accm; + AccumT() { for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = _mm256_setzero_ps(); } + template + inline void compute(int nb, Unpacker& unp, Scales& scales, Sum& sum, const Q8 ** y, const DataInfo& info, int ix) { + auto qx = unp.quants(); + __m256 dall[nrc_y]; + for (int i = 0; i < nb/4; ++i) { + auto other_scales = unp.set_block_4(i); + for (int iy = 0; iy < nrc_y; ++iy) { + auto s12 = scales.prepare4(other_scales, y[iy] + 4*i); + dall[iy] = accm.compute(s12, iy); + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto pall = sum.compute(qx, y[iy] + 4*i); + acc[iy] = _mm256_fmadd_ps(dall[iy], _mm256_cvtepi32_ps(pall), acc[iy]); + } + } + if (!is_multiple_of_4) { + for (int i = 4*(nb/4); i < nb; ++i) { + auto other_scales = unp.set_block(i); + for (int iy = 0; iy < nrc_y; ++iy) { + auto s12 = scales.prepare1(other_scales, y[iy] + i); + auto d = accm.compute(s12, iy); + const __m256i p0 = sum.dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[iy][i].qs)); + acc[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(p0), acc[iy]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, accm.result(acc[iy], iy)); + } + } +}; + +template +using AccumType0 = AccumT; + +template +using AccumType1 = AccumT, nrc_y, is_multiple_of_4>; + +using Sum4Type0 = Sum4; +using Sum4Type1 = Sum4; +using Sum4TypeQ80 = Sum4; +using Sum4TypeQ81 = Sum4; + +template +void mul_mat_qX_q8_Helper(int nb, const void * vx, size_t bx, const DataInfo& info, const Q8 ** y, int nrc_x) { + Unpacker unp(vx, bx); + typename Unpacker::Sum4T sum4; + Scales scales; + for (int ix = 0; ix < nrc_x; ++ix) { + unp.set_row(ix); + AccumType accum; + accum.compute(nb, unp, scales, sum4, y, info, ix); + } +} + +template +void mul_mat_qX_0_q8_0_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n%Unpacker::block_size() == 0); + Q8 q8(info); + int nb = n/Unpacker::block_size(); + if (nb%4 == 0) { + mul_mat_qX_q8_Helper, ScaleHelperQ8_0, block_q8_0, nrc_y>( + nb, vx, bx, info, q8.y, nrc_x + ); + } else { + mul_mat_qX_q8_Helper, ScaleHelperQ8_0, block_q8_0, nrc_y>( + nb, vx, bx, info, q8.y, nrc_x + ); + } +} + +template +void mul_mat_qX_1_q8_1_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n%Unpacker::block_size() == 0); + Q8 q8(info); + int nb = n/Unpacker::block_size(); + if (nb%4 == 0) { + mul_mat_qX_q8_Helper, ScaleHelperQ8_1, block_q8_1, nrc_y>( + nb, vx, bx, info, q8.y, nrc_x + ); + } else { + mul_mat_qX_q8_Helper, ScaleHelperQ8_1, block_q8_1, nrc_y>( + nb, vx, bx, info, q8.y, nrc_x + ); + } +} + +struct Dequantizer4bit { + const __m256i m4 = _mm256_set1_epi8(0xf); + inline __m256i dequant(const uint8_t * qs) const { + const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs); + return _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128), m4); + } +}; + +struct Q8_0_Dequantizer { + inline __m256i dequant(const block_q8_0 * x) const { + return _mm256_loadu_si256((const __m256i *)x->qs); + } +}; + +struct Q8_0_1_Dequantizer { + inline __m256i dequant(const block_q8_0 * x) const { + return _mm256_add_epi8(_mm256_set1_epi8(127), _mm256_loadu_si256((const __m256i *)x->qs)); + } +}; + +struct Q4_0_Dequantizer { + Dequantizer4bit b4; + const __m256i m8 = _mm256_set1_epi8(-8); + inline __m256i dequant(const block_q4_0 * x) const { + return _mm256_add_epi8(b4.dequant(x->qs), m8); + } +}; + +struct Q4_0_1_Dequantizer { + Dequantizer4bit b4; + inline __m256i dequant(const block_q4_0 * x) const { + return b4.dequant(x->qs); + } +}; + +struct IQ4_NL_Dequantizer { + Dequantizer4bit b4; + const __m256i values = load_iq4nl_values_256(); + inline __m256i dequant(const block_iq4_nl * x) const { + return _mm256_shuffle_epi8(values, b4.dequant(x->qs)); + } +}; + +struct Q4_1_Dequantizer { + Dequantizer4bit b4; + inline __m256i dequant(const block_q4_1 * x) const { + return b4.dequant(x->qs); + } +}; + +struct HBitDequantizer { + const __m256i shuffle = _mm256_set_epi64x(0x0303030303030303, 0x0202020202020202, 0x0101010101010101, 0x0000000000000000); + const __m256i mask = _mm256_set1_epi64x(0x7fbfdfeff7fbfdfe); + const __m256i minus1 = _mm256_set1_epi64x(-1); + inline __m256i to_bytes(const uint8_t * bits) const { + // Note: Data in all ggml quants is at least 2-byte aligned. + // => we can cast to uint16_t and use or on two consecutive entries + // which is faster than memcpy + const uint16_t * aux16 = (const uint16_t *)bits; + const uint32_t aux32 = aux16[0] | (aux16[1] << 16); + //uint32_t aux32; memcpy(&aux32, bits, sizeof(uint32_t)); + __m256i bytes = _mm256_shuffle_epi8(_mm256_set1_epi32(aux32), shuffle); + bytes = _mm256_or_si256(bytes, mask); + return _mm256_cmpeq_epi8(bytes, minus1); + } +}; + +struct Q5_0_Dequantizer { + Dequantizer4bit b4; + HBitDequantizer hbit; + const __m256i mh = _mm256_set1_epi8((char)0xF0); + inline __m256i dequant(const block_q5_0 * x) const { + const __m256i vqh = _mm256_andnot_si256(hbit.to_bytes(x->qh), mh); + return _mm256_or_si256(b4.dequant(x->qs), vqh); + } +}; + +template +struct Q5_1_Dequantizer { + Dequantizer4bit b4; + HBitDequantizer hbit; + const __m256i mh = _mm256_set1_epi8(0x10); + inline __m256i dequant(const Q5 * x) const { + const __m256i vqh = _mm256_and_si256(hbit.to_bytes(x->qh), mh); + return _mm256_or_si256(b4.dequant(x->qs), vqh); + } +}; +struct Q6_1_Dequantizer { + Dequantizer4bit b4; + const __m256i mh = _mm256_set1_epi8(0x30); + inline __m256i dequant(const block_q6_0 * x) const { + uint64_t aux64; std::memcpy(&aux64, x->qh, 8); + auto h128 = _mm_set_epi64x(aux64, aux64 << 4); + auto h256 = MM256_SET_M128I(_mm_srli_epi16(h128, 2), h128); + return _mm256_or_si256(b4.dequant(x->qs), _mm256_and_si256(h256, mh)); + } +}; + +template +struct Q_Unpacker { + Q_Unpacker(const void * vx, size_t bx) : cx_0((const char *)vx), x((const Q*)cx_0), bx(bx) {} + + const char * cx_0; + const Q * x; + size_t bx; + + Scales scales; + Dequantizer deq; + + __m256i qx[4]; + + inline const __m256i* quants() const { return qx; } + + inline void set_row(int ix) { x = (const Q*)(cx_0 + ix*bx); } + + inline auto set_block_4(int i) { + for (int j = 0; j < 4; ++j) { + qx[j] = deq.dequant(x + 4*i + j); + } + return scales.prepare4(x + 4*i); + } + inline auto set_block(int i) { + qx[0] = deq.dequant(x + i); + return scales.prepare1(x + i); + } +}; + +struct Q8_0_x4_Unpacker { + using Sum4T = Sum4TypeQ80; + inline static int block_size() { return QK8_0; } + Q8_0_x4_Unpacker(const void * vx, size_t bx) : cx_0((const char *)vx), x((const block_q8_0_x4 *)cx_0), bx(bx) {} + + const char * cx_0; + const block_q8_0_x4 * x; + size_t bx; + + __m256i qx[4]; + + inline const __m256i* quants() const { return qx; } + + inline void set_row(int ix) { x = (const block_q8_0_x4 *)(cx_0 + ix*bx); } + + inline auto set_block_4(int i) { + auto scales = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)x[i].d)); + for (int j = 0; j < 4; ++j) { + qx[j] = _mm256_loadu_si256((const __m256i *)x[i].qs + j); + } + return scales; + } + inline auto set_block(int i) { + auto q8 = (const block_q8_0 *)(x + i); + qx[0] = _mm256_loadu_si256((const __m256i *)q8->qs); + return GGML_FP16_TO_FP32(q8->d); + } +}; + +struct Q8_0_Unpacker final : public Q_Unpacker { + Q8_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ80; + inline static int block_size() { return QK8_0; } +}; +struct Q8_0_1_Unpacker final : public Q_Unpacker, Q8_0_1_Dequantizer> { + Q8_0_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ81; + inline static int block_size() { return QK8_0; } +}; +struct Q4_0_Unpacker final : public Q_Unpacker { + Q4_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ80; + inline static int block_size() { return QK4_0; } +}; +struct Q4_0_1_Unpacker final : public Q_Unpacker, Q4_0_1_Dequantizer> { + Q4_0_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ81; + inline static int block_size() { return QK4_0; } +}; +struct IQ4_NL_Unpacker final : public Q_Unpacker, IQ4_NL_Dequantizer> { + IQ4_NL_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ81; + inline static int block_size() { return QK4_NL; } +}; +struct Q5_0_Unpacker final : public Q_Unpacker { + Q5_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ80; + inline static int block_size() { return QK5_0; } +}; +struct Q5_0_1_Unpacker final : public Q_Unpacker, Q5_1_Dequantizer> { + Q5_0_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ81; + inline static int block_size() { return QK5_0; } +}; +struct Q4_1_Unpacker final : public Q_Unpacker { + Q4_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4Type1; + inline static int block_size() { return QK4_1; } +}; +struct Q5_1_Unpacker final : public Q_Unpacker> { + Q5_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4Type1; + inline static int block_size() { return QK4_1; } +}; +struct Q6_0_1_Unpacker final : public Q_Unpacker, Q6_1_Dequantizer> { + Q6_0_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {} + using Sum4T = Sum4TypeQ81; + inline static int block_size() { return QK5_0; } +}; + +// float matrices - we handle f16, bf16 (if native bf16 support is available) and f32, but only to f32 result + +struct QFBase { +#ifdef __AVX512F__ + constexpr static int k_step = 16; + using Data = __m512; + using Acc = __m512; + static inline Data load(const ggml_half * x) { return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)x)); } + static inline Data load(const float * x) { return _mm512_loadu_ps(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return _mm512_fmadd_ps(y, x, prev); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm512_mul_ps(y, x); + } + static inline float hsum(Acc acc) { + return _mm512_reduce_add_ps(acc); + } + template + static inline Data load4Floats(const Float * x) { + return _mm512_insertf32x4(_mm512_setzero_ps(), load128(x), 0); + } +#else + constexpr static int k_step = 8; + using Data = __m256; + using Acc = __m256; + static inline Data load(const ggml_half * x) { return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)x)); } + static inline Data load(const float * x) { return _mm256_loadu_ps(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return _mm256_fmadd_ps(y, x, prev); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm256_mul_ps(y, x); + } + static inline float hsum(Acc acc) { + return hsum_float_8(acc); + } + template + static inline Data load4Floats(const Float * x) { + return _mm256_insertf128_ps(_mm256_setzero_ps(), load128(x), 0); + } +#endif + static inline __m128 load128(const ggml_half * x) { return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)x)); } + static inline __m128 load128(const float * x) { return _mm_loadu_ps(x); } +}; +template struct QFT final : public QFBase { + constexpr static int nrc = nrc_in; + QFT(const DataInfo& info) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const Float *)info.src1_row(iy); + } + QFT(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const Float *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load4Floats(y[iy] + 4*i); } + const Float * y[nrc]; +}; + +template +IQK_NOINLINE void mul_mat_Qx_Qy_MxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + int nb = n/QFBase::k_step; + int nb4 = n/4; + Qy y(info); + Qx x(cx + ix0*bx, bx); + QFBase::Data xv[Qx::nrc]; + QFBase::Acc acc[Qx::nrc*Qy::nrc]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QFBase::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc(acc[Qx::nrc*iy + ix], yv, xv[ix]); + } + } + for (int i = (QFBase::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < Qx::nrc; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = QFBase::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < Qx::nrc; ++ix) acc[Qx::nrc*iy + ix] = QFBase::acc(acc[Qx::nrc*iy + ix], yv, xv[ix]); + } + } + for (int iy = 0; iy < Qy::nrc; ++iy) for (int ix = 0; ix < Qx::nrc; ++ix) info.store(ix0+ix, iy, QFBase::hsum(acc[Qx::nrc*iy+ix])); +} + +// This will handle any of f16 x f32, f32 x f16, f16 x f16, f32 x f32, with computations done +// in f32 (i.e., f16 is first converted to f32). It is easy to extend to computations done in +// f16, but I don't have a CPU capable of f16 vector arithmetic, so not doing it for now. +template +void mul_mat_fX_fY_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { +#ifdef __AVX512F__ + constexpr int k_nx = 5; +#else + constexpr int k_nx = 2; +#endif + const char * cx = (const char *)vx; + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_MxN, QFT>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN, QFT>(n, cx, bx, last_x, info); break; +#ifdef __AVX512F__ + case 2: mul_mat_Qx_Qy_MxN, QFT>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_MxN, QFT>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_MxN, QFT>(n, cx, bx, last_x, info); break; +#endif + } +} + +#ifdef __AVX512BF16__ +struct QFBaseBF16 { + constexpr static int k_step = 32; + using Data = __m512bh; + using Acc = __m512; + static inline Data load(const ggml_bf16_t * x) { return __m512bh(_mm512_loadu_si512((const __m512i *)x)); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return _mm512_dpbf16_ps(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return _mm512_dpbf16_ps(_mm512_setzero_ps(), y, x); + } + static inline float hsum(Acc acc) { + return _mm512_reduce_add_ps(acc); + } +}; +template struct QFTBF16 final : public QFBaseBF16 { + constexpr static int nrc = nrc_in; + QFTBF16(const DataInfo& info) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const ggml_bf16_t *)info.src1_row(iy); + } + QFTBF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc; ++iy) y[iy] = (const ggml_bf16_t *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + const ggml_bf16_t * y[nrc]; +}; + +template +IQK_NOINLINE void mul_mat_Qx_Qy_MxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + int nb = n/QFBaseBF16::k_step; + QFTBF16 y(info); + QFTBF16 x(cx + ix0*bx, bx); + QFBaseBF16::Data xv[nrc_x]; + QFBaseBF16::Acc acc[nrc_x*nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QFBaseBF16::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QFBaseBF16::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QFBaseBF16::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QFBaseBF16::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + for (int iy = 0; iy < nrc_y; ++iy) for (int ix = 0; ix < nrc_x; ++ix) info.store(ix0+ix, iy, QFBaseBF16::hsum(acc[nrc_x*iy+ix])); +} +template +void mul_mat_fX_fY_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + constexpr int k_nx = nrc_y <= 2 ? 8 : 5; + const char * cx = (const char *)vx; + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_MxN(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + if constexpr (nrc_y <= 2) { + if (nx >= 4) { + mul_mat_Qx_Qy_MxN(n, cx, bx, last_x, info); + last_x += 4; + if (last_x == nrc_x) return; + nx = nrc_x - last_x; + } + } + switch (nx) { + case 1: mul_mat_Qx_Qy_MxN(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_MxN(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_MxN(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_MxN(n, cx, bx, last_x, info); break; + } +} +#endif + +// +// Tiled Q8_0 x Q8_0 implementation. Not used as the templated legacy quant implementation +// above is faster. Left behind so we remember we tried. +// +template struct Q80 { + constexpr static int nrc_y = nrc; + Q80(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_0 *)info.src1_row(iy); + } + IQK_ALWAYS_INLINE __m256i load1(int iy, int i) const { return _mm256_loadu_si256((const __m256i *)y[iy][i].qs); } + IQK_ALWAYS_INLINE float scale(int iy, int i) const { return GGML_FP16_TO_FP32(y[iy][i].d); } + + const block_q8_0 * y[nrc_y]; +}; +inline __m256i mul_q80(__m256i x, __m256i y) { + auto ux = _mm256_sign_epi8(x, x); +#ifdef HAVE_FANCY_SIMD + return _mm256_dpbusd_epi32(_mm256_setzero_si256(), ux, _mm256_sign_epi8(y, x)); +#else + return _mm256_madd_epi16(_mm256_set1_epi16(1), _mm256_maddubs_epi16(ux, _mm256_sign_epi8(y, x))); +#endif +} +template +void mul_mat_q80_q80_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n%QK8_0 == 0); + constexpr int k_nx = 4; + int nb = n/QK8_0; + Q80 q8(info); + const block_q8_0 * x[k_nx]; + float ds[k_nx]; + __m256 acc[k_nx*nrc_y]; + __m256i xv[k_nx]; + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + int ix0 = k_nx*ix; + for (int kx = 0; kx < k_nx; ++kx) { + x[kx] = (const block_q8_0 *)((const char *)vx + (ix0 + kx)*bx); + ds[kx] = GGML_FP16_TO_FP32(x[kx][0].d); + xv[kx] = _mm256_loadu_si256((const __m256i *)x[kx][0].qs); + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto yv = q8.load1(iy, 0); + float d = q8.scale(iy, 0); + for (int kx = 0; kx < k_nx; ++kx) { + auto dot = mul_q80(yv, xv[kx]); + acc[k_nx*iy + kx] = _mm256_mul_ps(_mm256_set1_ps(ds[kx]*d), _mm256_cvtepi32_ps(dot)); + } + } + for (int i = 1; i < nb; ++i) { + for (int kx = 0; kx < k_nx; ++kx) { + ds[kx] = GGML_FP16_TO_FP32(x[kx][i].d); + xv[kx] = _mm256_loadu_si256((const __m256i *)x[kx][i].qs); + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto yv = q8.load1(iy, i); + float d = q8.scale(iy, i); + for (int kx = 0; kx < k_nx; ++kx) { + auto dot = mul_q80(yv, xv[kx]); + acc[k_nx*iy + kx] = _mm256_fmadd_ps(_mm256_set1_ps(ds[kx]*d), _mm256_cvtepi32_ps(dot), acc[k_nx*iy + kx]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + for (int kx = 0; kx < k_nx; ++kx) info.store(ix0+kx, iy, hsum_float_8(acc[k_nx*iy+kx])); + } + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + // TODO: handle remaining rows +} + +template void MulMat::set_functions(MulMat& m) { + if constexpr (std::is_same_v || std::is_same_v || + std::is_same_v) { + m.funcs[0] = mul_mat_qX_0_q8_0_T; + m.funcs[1] = mul_mat_qX_0_q8_0_T; + m.funcs[2] = mul_mat_qX_0_q8_0_T; + m.funcs[3] = mul_mat_qX_0_q8_0_T; + m.funcs[4] = mul_mat_qX_0_q8_0_T; + m.funcs[5] = mul_mat_qX_0_q8_0_T; + m.funcs[6] = mul_mat_qX_0_q8_0_T; + m.funcs[7] = mul_mat_qX_0_q8_0_T; + } + else if constexpr (std::is_same_v || std::is_same_v || + std::is_same_v || std::is_same_v || + std::is_same_v || std::is_same_v || + std::is_same_v) { + m.funcs[0] = mul_mat_qX_1_q8_1_T; + m.funcs[1] = mul_mat_qX_1_q8_1_T; + m.funcs[2] = mul_mat_qX_1_q8_1_T; + m.funcs[3] = mul_mat_qX_1_q8_1_T; + m.funcs[4] = mul_mat_qX_1_q8_1_T; + m.funcs[5] = mul_mat_qX_1_q8_1_T; + m.funcs[6] = mul_mat_qX_1_q8_1_T; + m.funcs[7] = mul_mat_qX_1_q8_1_T; + } + else if constexpr (std::is_same_v || std::is_same_v || + std::is_same_v || std::is_same_v || + std::is_same_v) { + m.funcs[0] = mul_mat_qX_K_q8_K_IQ; + m.funcs[1] = mul_mat_qX_K_q8_K_IQ; + m.funcs[2] = mul_mat_qX_K_q8_K_IQ; + m.funcs[3] = mul_mat_qX_K_q8_K_IQ; + m.funcs[4] = mul_mat_qX_K_q8_K_IQ; + m.funcs[5] = mul_mat_qX_K_q8_K_IQ; + m.funcs[6] = mul_mat_qX_K_q8_K_IQ; + m.funcs[7] = mul_mat_qX_K_q8_K_IQ; + } + else { +#ifdef HAVE_FANCY_SIMD + if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v) { + m.funcs[0] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[1] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[2] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[3] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[4] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[5] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[6] = mul_mat_iqX_k_q8_K_AVX512; + m.funcs[7] = mul_mat_iqX_k_q8_K_AVX512; + } else { + m.funcs[0] = mul_mat_qX_K_q8_K_AVX512_1; + m.funcs[1] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[2] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[3] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[4] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[5] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[6] = mul_mat_qX_K_q8_K_AVX512; + m.funcs[7] = mul_mat_qX_K_q8_K_AVX512; + } +#else + if constexpr (std::is_same_v || + std::is_same_v || + std::is_same_v || + std::is_same_v|| + std::is_same_v|| + std::is_same_v|| + std::is_same_v|| + std::is_same_v) { + m.funcs[0] = mul_mat_qY_K_q8_K_T; + m.funcs[1] = mul_mat_qY_K_q8_K_T; + m.funcs[2] = mul_mat_qY_K_q8_K_T; + m.funcs[3] = mul_mat_qY_K_q8_K_T; + m.funcs[4] = mul_mat_qY_K_q8_K_T; + m.funcs[5] = mul_mat_qY_K_q8_K_T; + m.funcs[6] = mul_mat_qY_K_q8_K_T; + m.funcs[7] = mul_mat_qY_K_q8_K_T; + } else { + m.funcs[0] = mul_mat_qX_K_q8_K_T; + m.funcs[1] = mul_mat_qX_K_q8_K_T; + m.funcs[2] = mul_mat_qX_K_q8_K_T; + m.funcs[3] = mul_mat_qX_K_q8_K_T; + m.funcs[4] = mul_mat_qX_K_q8_K_T; + m.funcs[5] = mul_mat_qX_K_q8_K_T; + m.funcs[6] = mul_mat_qX_K_q8_K_T; + m.funcs[7] = mul_mat_qX_K_q8_K_T; + } +#endif + } +} + +template +void set_mul_mat_f(MulMat& mm) { + for (auto& f : mm.funcs) f = nullptr; + mm.funcs[0] = mul_mat_fX_fY_T<1, FloatX, FloatY>; + mm.funcs[1] = mul_mat_fX_fY_T<2, FloatX, FloatY>; + mm.funcs[2] = mul_mat_fX_fY_T<3, FloatX, FloatY>; + mm.funcs[3] = mul_mat_fX_fY_T<4, FloatX, FloatY>; + mm.funcs[4] = mul_mat_fX_fY_T<5, FloatX, FloatY>; +#ifndef __AVX512F__ + mm.funcs[5] = mul_mat_fX_fY_T<6, FloatX, FloatY>; +#endif +} + +#ifdef __AVX512BF16__ +void set_mul_mat_bf16(MulMat& mm) { + for (auto& f : mm.funcs) f = nullptr; + mm.funcs[0] = mul_mat_fX_fY_T<1>; + mm.funcs[1] = mul_mat_fX_fY_T<2>; + mm.funcs[2] = mul_mat_fX_fY_T<3>; + mm.funcs[3] = mul_mat_fX_fY_T<4>; + mm.funcs[4] = mul_mat_fX_fY_T<5>; +} +#endif + +bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) { + + (void)Ny; + + if (typeA == GGML_TYPE_BF16) { + if (ne00 % 32) return false; + switch (typeB) { +#ifdef __AVX512BF16__ + case GGML_TYPE_BF16: set_mul_mat_bf16(mm); break; +#endif + default: return false; + } + return true; + } + + if (typeA == GGML_TYPE_F16 || typeA == GGML_TYPE_F32) { + if (ne00 % 4) return false; + } + if (typeA == GGML_TYPE_F16) { + switch (typeB) { + case GGML_TYPE_F16: set_mul_mat_f(mm); break; + case GGML_TYPE_F32: set_mul_mat_f(mm); break; + default: return false; + } + return true; + } + if (typeA == GGML_TYPE_F32) { + switch (typeB) { + case GGML_TYPE_F16: set_mul_mat_f(mm); break; + case GGML_TYPE_F32: set_mul_mat_f(mm); break; + default: return false; + } + return true; + } + + auto expected_typeB = GGML_TYPE_Q8_K; + + switch (typeA) { + case GGML_TYPE_Q2_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ2_TN: + assert (ne00 % QK_K == 0); +#ifdef HAVE_FANCY_SIMD + //MulMat::set_functions(mm); + mm.funcs[0] = mul_mat_qX_K_q8_K_AVX512_1; + //mm.funcs[0] = mul_mat_iq2tn_q8_K_AVX512<1>; + mm.funcs[1] = mul_mat_iq2tn_q8_K_AVX512<2>; + mm.funcs[2] = mul_mat_iq2tn_q8_K_AVX512<3>; + mm.funcs[3] = mul_mat_iq2tn_q8_K_AVX512<4>; + mm.funcs[4] = mul_mat_iq2tn_q8_K_AVX512<5>; + mm.funcs[5] = mul_mat_iq2tn_q8_K_AVX512<6>; + mm.funcs[6] = mul_mat_iq2tn_q8_K_AVX512<7>; + mm.funcs[7] = mul_mat_iq2tn_q8_K_AVX512<8>; +#else + mm.funcs[0] = mul_mat_iq2tn_q8_K<1>; + mm.funcs[1] = mul_mat_iq2tn_q8_K<2>; + mm.funcs[2] = mul_mat_iq2tn_q8_K<3>; + mm.funcs[3] = mul_mat_iq2tn_q8_K<4>; + mm.funcs[4] = mul_mat_iq2tn_q8_K<5>; + mm.funcs[5] = mul_mat_iq2tn_q8_K<6>; + mm.funcs[6] = mul_mat_iq2tn_q8_K<7>; + mm.funcs[7] = mul_mat_iq2tn_q8_K<8>; +#endif + break; + case GGML_TYPE_Q3_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_Q4_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_Q5_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_Q6_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ4_XS: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ2_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ3_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ4_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ5_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ6_K: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ3_S: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ3_XXS: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ2_S: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ2_XS: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ2_XXS: + assert (ne00 % QK_K == 0); + MulMat::set_functions(mm); + break; + case GGML_TYPE_IQ1_BN: + assert (ne00 % QK_IQ1BN == 0); + mm.funcs[0] = mul_mat_iq1bn_q8_K64<1, false>; + mm.funcs[1] = mul_mat_iq1bn_q8_K64<2, false>; + mm.funcs[2] = mul_mat_iq1bn_q8_K64<3, false>; + mm.funcs[3] = mul_mat_iq1bn_q8_K64<4, false>; + mm.funcs[4] = mul_mat_iq1bn_q8_K64<5, false>; + mm.funcs[5] = mul_mat_iq1bn_q8_K64<6, false>; + mm.funcs[6] = mul_mat_iq1bn_q8_K64<7, false>; + mm.funcs[7] = mul_mat_iq1bn_q8_K64<8, false>; + expected_typeB = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_IQ1_TN: + assert (ne00 % QK_IQ1BN == 0); + mm.funcs[0] = mul_mat_iq1bn_q8_K64<1, true>; + mm.funcs[1] = mul_mat_iq1bn_q8_K64<2, true>; + mm.funcs[2] = mul_mat_iq1bn_q8_K64<3, true>; + mm.funcs[3] = mul_mat_iq1bn_q8_K64<4, true>; + mm.funcs[4] = mul_mat_iq1bn_q8_K64<5, true>; + mm.funcs[5] = mul_mat_iq1bn_q8_K64<6, true>; + mm.funcs[6] = mul_mat_iq1bn_q8_K64<7, true>; + mm.funcs[7] = mul_mat_iq1bn_q8_K64<8, true>; + expected_typeB = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_IQ2_BN: + assert (ne00 % QK_IQ1BN == 0); + mm.funcs[0] = mul_mat_iq2bn_q8_K64<1>; + mm.funcs[1] = mul_mat_iq2bn_q8_K64<2>; + mm.funcs[2] = mul_mat_iq2bn_q8_K64<3>; + mm.funcs[3] = mul_mat_iq2bn_q8_K64<4>; + mm.funcs[4] = mul_mat_iq2bn_q8_K64<5>; + mm.funcs[5] = mul_mat_iq2bn_q8_K64<6>; + mm.funcs[6] = mul_mat_iq2bn_q8_K64<7>; + mm.funcs[7] = mul_mat_iq2bn_q8_K64<8>; + expected_typeB = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_Q4_0: + assert (ne00 % QK4_0 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q4_1: + assert (ne00 % QK4_1 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q5_0: + assert (ne00 % QK5_0 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q5_1: + assert (ne00 % QK5_1 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q6_0: + assert (ne00 % QK6_0 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q8_0: + assert (ne00 % QK8_0 == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_IQ4_NL: + assert (ne00 % QK4_NL == 0); + MulMat::set_functions(mm); + expected_typeB = GGML_TYPE_Q8_1; + break; + + default: + return false; + } + + return ggml_type(typeB) == expected_typeB; +} + +} // namespace + + +#else // __aarch64__ + +namespace { + +template struct Q8 { + + constexpr static int nrc_y = nrc; + + Q8(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy); + } + + inline int8x16x2_t load_quants(int iy, int i, int j) const { return vld1q_s8_x2(y[iy][i].qs + 32*j); } + inline int8x16x4_t load_quants_64(int iy, int i, int j) const { return vld1q_s8_x4(y[iy][i].qs + 64*j); } + inline int16x8x2_t load_bsums(int iy, int i) const { return vld1q_s16_x2(y[iy][i].bsums); } + inline int16x8_t load_bsums8(int iy, int i) const { + auto q8s = vld1q_s16_x2(y[iy][i].bsums); + return vpaddq_s16(q8s.val[0], q8s.val[1]); + } + inline float scale(int iy, int i) const { return y[iy][i].d; } + + const block_q8 * y[nrc_y]; +}; + +template +inline void compute_8_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8, + const int32x4x2_t& scales, int iy, int i, int j, int32x4_t& sumi) { + auto mzero = vdupq_n_s32(0); + auto q8b_1 = q8.load_quants(iy, i, 4*j+0); + auto p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[0]), q8b_1.val[0]), + vreinterpretq_s8_u8(qx_1.val[1]), q8b_1.val[1]); // block 1 + auto q8b_2 = q8.load_quants(iy, i, 4*j+1); + auto p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[2]), q8b_2.val[0]), + vreinterpretq_s8_u8(qx_1.val[3]), q8b_2.val[1]); // block 2 + auto p12 = vpaddq_s32(p1, p2); + + auto q8b_3 = q8.load_quants(iy, i, 4*j+2); + auto p3 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[0]), q8b_3.val[0]), + vreinterpretq_s8_u8(qx_2.val[1]), q8b_3.val[1]); // block 1 + auto q8b_4 = q8.load_quants(iy, i, 4*j+3); + auto p4 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[2]), q8b_4.val[0]), + vreinterpretq_s8_u8(qx_2.val[3]), q8b_4.val[1]); // block 2 + auto p34 = vpaddq_s32(p3, p4); + + auto pall = vpaddq_s32(p12, p34); + sumi = vmlaq_s32(sumi, scales.val[j], pall); +} + +template +inline void compute_16_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8, + const int32x4x4_t& scales, int iy, int i, int j, int32x4_t& sumi) { + + auto mzero = vdupq_n_s32(0); + auto q8b_1 = q8.load_quants(iy, i, 4*j+0); + auto p1 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[0]), q8b_1.val[0]), + ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[1]), q8b_1.val[1])); // blocks 0, 0, 1, 1, + auto q8b_2 = q8.load_quants(iy, i, 4*j+1); + auto p2 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[2]), q8b_2.val[0]), + ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[3]), q8b_2.val[1])); // blocks 3, 3, 4, 4, + auto p12 = vpaddq_s32(p1, p2); // blocks 0, 1, 2, 3 + sumi = vmlaq_s32(sumi, scales.val[2*j+0], p12); + + auto q8b_3 = q8.load_quants(iy, i, 4*j+2); + auto p3 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[0]), q8b_3.val[0]), + ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[1]), q8b_3.val[1])); // block 4, 4, 5, 5, + auto q8b_4 = q8.load_quants(iy, i, 4*j+3); + auto p4 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[2]), q8b_4.val[0]), + ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[3]), q8b_4.val[1])); // block 6, 6, 7, 7, + auto p34 = vpaddq_s32(p3, p4); // blocks 4, 5, 6, 7 + sumi = vmlaq_s32(sumi, scales.val[2*j+1], p34); +} + +template +inline void accum_mins_8(const int16x8_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto q8s = q8.load_bsums8(iy, i); + int32x4_t b1 = vmull_s16(vget_low_s16(mins), vget_low_s16(q8s)); + int32x4_t b2 = vmull_s16(vget_high_s16(mins), vget_high_s16(q8s)); + float32x4_t prod = vcvtq_f32_s32(vaddq_s32(b1, b2)); + acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i))); + } +} +template +inline void accum_mins_16(const int16x8x2_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto q8s = q8.load_bsums(iy, i); + int32x4_t b1 = vmull_s16(vget_low_s16 (mins.val[0]), vget_low_s16 (q8s.val[0])); + int32x4_t b2 = vmull_s16(vget_high_s16(mins.val[0]), vget_high_s16(q8s.val[0])); + int32x4_t b3 = vmull_s16(vget_low_s16 (mins.val[1]), vget_low_s16 (q8s.val[1])); + int32x4_t b4 = vmull_s16(vget_high_s16(mins.val[1]), vget_high_s16(q8s.val[1])); + float32x4_t prod = vcvtq_f32_s32(vaddq_s32(vaddq_s32(b1, b2), vaddq_s32(b3, b4))); + acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i))); + } +} + +struct Scales8 { + uint32_t utmp[4]; + const uint8_t * sc8 = (const uint8_t *)utmp; + template + inline int32x4x2_t process_scales_mins(const Qx& x, const Q8& q8, int i, float32x4_t * acc) { + make_q4_scales(x.scales, utmp); + int16x8_t mins = vmovl_s8(vld1_s8((const int8_t *)sc8 + 8)); + accum_mins_8(mins, q8, acc, i, -GGML_FP16_TO_FP32(x.dmin)); + + uint8x8_t scales8 = vld1_u8(sc8); + uint16x8_t scales16 = vmovl_u8(scales8); + int32x4x2_t scales = {vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(scales16))), + vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(scales16)))}; + return scales; + } +}; + +struct Q4bits { + const uint8x16_t m4b = vdupq_n_u8(0xf); + uint8x16x4_t b1, b2; + inline void prepare4(uint8x16x4_t& b, const uint8x16_t * val) const { + b.val[0] = vandq_u8(val[0], m4b); + b.val[2] = vshrq_n_u8(val[0], 4); + b.val[1] = vandq_u8(val[1], m4b); + b.val[3] = vshrq_n_u8(val[1], 4); + } + inline void prepare4_16(uint8x16x4_t& b, const uint8x16_t * val) const { + b.val[0] = vandq_u8(val[0], m4b); + b.val[1] = vshrq_n_u8(val[0], 4); + b.val[2] = vandq_u8(val[1], m4b); + b.val[3] = vshrq_n_u8(val[1], 4); + } + inline void prepare(const uint8_t * qs) { + auto q4bits = vld1q_u8_x2(qs); + prepare4(b1, q4bits.val); + q4bits = vld1q_u8_x2(qs+32); + prepare4(b2, q4bits.val); + } + inline void prepare_v2(const uint8_t * qs) { + auto q4bits = vld1q_u8_x4(qs); + prepare4(b1, q4bits.val+0); + prepare4(b2, q4bits.val+2); + } + inline void prepare64(const uint8_t * qs) { + auto q4bits = vld1q_u8_x4(qs); + b1.val[0] = vandq_u8(q4bits.val[0], m4b); + b1.val[1] = vandq_u8(q4bits.val[1], m4b); + b1.val[2] = vandq_u8(q4bits.val[2], m4b); + b1.val[3] = vandq_u8(q4bits.val[3], m4b); + b2.val[0] = vshrq_n_u8(q4bits.val[0], 4); + b2.val[1] = vshrq_n_u8(q4bits.val[1], 4); + b2.val[2] = vshrq_n_u8(q4bits.val[2], 4); + b2.val[3] = vshrq_n_u8(q4bits.val[3], 4); + } + inline void prepare16(const uint8_t * qs) { + auto q4bits = vld1q_u8_x2(qs); + prepare4_16(b1, q4bits.val); + q4bits = vld1q_u8_x2(qs+32); + prepare4_16(b2, q4bits.val); + } + inline void prepare16_v2(const uint8_t * qs) { + auto q4bits = vld1q_u8_x4(qs); + prepare4_16(b1, q4bits.val+0); + prepare4_16(b2, q4bits.val+2); + } +}; + +struct Q2bits { + const uint8x16_t m4b = vdupq_n_u8(0x03); + uint8x16x4_t b1, b2; + inline void prepare(const uint8_t * qs) { + auto q2bits = vld1q_u8_x2(qs); + b1.val[0] = vandq_u8(q2bits.val[0], m4b); + b1.val[1] = vandq_u8(q2bits.val[1], m4b); + + q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2); + q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2); + b1.val[2] = vandq_u8(q2bits.val[0], m4b); + b1.val[3] = vandq_u8(q2bits.val[1], m4b); + + q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2); + q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2); + b2.val[0] = vandq_u8(q2bits.val[0], m4b); + b2.val[1] = vandq_u8(q2bits.val[1], m4b); + + q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2); + q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2); + b2.val[2] = vandq_u8(q2bits.val[0], m4b); + b2.val[3] = vandq_u8(q2bits.val[1], m4b); + } +}; + +template +struct BaseDequantizer { + BaseDequantizer(const void * vx, size_t bx, int nrc) : vx(vx), x(nullptr), bx(bx), nrc(nrc) {} + inline void new_row(int ix) { + if constexpr (has_row_scale) { + const float * dptr = (const float *)((const char *)vx + ix*bx); + d = *dptr; + x = (const block_q *)(dptr + 1); + } else { + x = (const block_q *)((const char *)vx + ix*bx); + } + } + const void * vx; + const block_q * x; + const size_t bx; + const int nrc; + float d; +}; + +struct DequantizerQ4K final : public BaseDequantizer { + DequantizerQ4K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return s8.process_scales_mins(x[i], q8, i, acc); + } + inline void prepare(int i, int j) { + if (nrc == 1) bits.prepare_v2(x[i].qs+64*j); + else bits.prepare(x[i].qs+64*j); + } + + Q4bits bits; + Scales8 s8; + +}; + +struct HighBit5 { + const uint8x16_t mhb = vdupq_n_u8(0x10); + uint8x16x2_t bits; + inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) { + b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 4), mhb)); + b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 4), mhb)); + b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 3), mhb)); + b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 3), mhb)); + + b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb)); + b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb)); + b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb)); + b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb)); + + if (do_shift) { + bits.val[0] = vshrq_n_u8(bits.val[0], 4); + bits.val[1] = vshrq_n_u8(bits.val[1], 4); + } + } +}; + +struct HighBit3 { + const uint8x16_t mhb = vdupq_n_u8(0x04); + uint8x16x2_t bits; + inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) { + b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb)); + b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb)); + b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb)); + b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb)); + + b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(bits.val[0], mhb)); + b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(bits.val[1], mhb)); + b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshrq_n_u8(bits.val[0], 1), mhb)); + b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshrq_n_u8(bits.val[1], 1), mhb)); + + if (do_shift) { + bits.val[0] = vshrq_n_u8(bits.val[0], 4); + bits.val[1] = vshrq_n_u8(bits.val[1], 4); + } + } +}; + +struct DequantizerQ5K final : public BaseDequantizer { + DequantizerQ5K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + h.bits = vld1q_u8_x2(x[i].qh); + return s8.process_scales_mins(x[i], q8, i, acc); + } + inline void prepare(int i, int j) { + if (nrc == 1) bits.prepare_v2(x[i].qs+64*j); + else bits.prepare(x[i].qs+64*j); + h.apply(bits.b1, bits.b2, j == 0); + } + + Q4bits bits; + HighBit5 h; + Scales8 s8; + + uint8x16x2_t hbits; + +}; + +inline int32x4x4_t make_wider(const int16x8x2_t& scales16) { + int32x4x4_t scales = { + vmovl_s16(vget_low_s16 (scales16.val[0])), + vmovl_s16(vget_high_s16(scales16.val[0])), + vmovl_s16(vget_low_s16 (scales16.val[1])), + vmovl_s16(vget_high_s16(scales16.val[1])), + }; + return scales; +} + +template +inline int32x4x4_t process_scales_mins_16(const int8x16_t& scales8, const Q8& q8, float32x4_t * acc, int i, float c) { + int16x8x2_t scales16; + scales16.val[0] = vmovl_s8(vget_low_s8(scales8)); + scales16.val[1] = vmovl_s8(vget_high_s8(scales8)); + accum_mins_16(scales16, q8, acc, i, c); + return make_wider(scales16); +} + +struct DequantizerQ6K final : public BaseDequantizer { + DequantizerQ6K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return process_scales_mins_16(vld1q_s8(x[i].scales), q8, acc, i, -32.f*d); + } + inline void prepare(int i, int j) { + + auto hbits = vld1q_u8_x2(x[i].qh + 32*j); + + bits.prepare64(x[i].ql+64*j); + bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 4), mhb)); + bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 4), mhb)); + bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 2), mhb)); + bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 2), mhb)); + + bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(hbits.val[0], mhb)); + bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(hbits.val[1], mhb)); + bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshrq_n_u8(hbits.val[0], 2), mhb)); + bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshrq_n_u8(hbits.val[1], 2), mhb)); + + } + + Q4bits bits; + + const uint8x16_t mhb = vdupq_n_u8(0x30); + +}; + +struct DequantizerQ3K final : public BaseDequantizer { + DequantizerQ3K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + h.bits = vld1q_u8_x2(x[i].hmask); + mask = vdupq_n_u8(0x01); + const uint16_t * sc16 = (const uint16_t *)x[i].scales; + uint32_t aux0 = sc16[0] | (sc16[1] << 16); + uint32_t aux1 = sc16[2] | (sc16[3] << 16); + uint32_t aux2 = sc16[4] | (sc16[5] << 16); + aux32[0] = (aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030); + aux32[1] = (aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030); + aux32[2] = ((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030); + aux32[3] = ((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030); + auto scales8 = vaddq_s8(vld1q_s8((const int8_t *)aux32), vdupq_n_s8(-32)); + if (nrc > 1) { + return process_scales_mins_16(scales8, q8, acc, i, -4.f*d); + } + int16x8x2_t scales16; + scales16.val[0] = vmovl_s8(vget_low_s8(scales8)); + scales16.val[1] = vmovl_s8(vget_high_s8(scales8)); + return make_wider(scales16); + } + + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+32*j); + if (nrc > 1) { + h.apply(bits.b1, bits.b2, j == 0); + } else { + auto minus4 = vdupq_n_u8(0xfc); + auto zero = vdupq_n_u8(0); + bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[0], mask), zero))); + bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[1], mask), zero))); + mask = vshlq_n_u8(mask, 1); + bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[0], mask), zero))); + bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[1], mask), zero))); + mask = vshlq_n_u8(mask, 1); + bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[0], mask), zero))); + bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[1], mask), zero))); + mask = vshlq_n_u8(mask, 1); + bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[0], mask), zero))); + bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(minus4, vceqq_u8(vandq_u8(h.bits.val[1], mask), zero))); + mask = vshlq_n_u8(mask, 1); + } + } + + uint32_t aux32[4]; + + Q2bits bits; + + uint8x16_t mask; + HighBit3 h; + +}; + +struct DequantizerQ2K final : public BaseDequantizer { + DequantizerQ2K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return true; } + + template + inline void process_scales(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + auto scales_and_mins = vld1q_u8(x[i].scales); + auto mins8 = vreinterpretq_s8_u8(vshrq_n_u8(scales_and_mins, 4)); + int16x8x2_t scales16; + scales16.val[0] = vmovl_s8(vget_low_s8(mins8)); + scales16.val[1] = vmovl_s8(vget_high_s8(mins8)); + accum_mins_16(scales16, q8, acc, i, -GGML_FP16_TO_FP32(x[i].dmin)); + + scales8 = vandq_u8(scales_and_mins, vdupq_n_u8(0xf)); + } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + process_scales(i, q8, acc); + int16x8x2_t scales16; + scales16.val[0] = vmovl_s8(vget_low_s8(vreinterpretq_s8_u8(scales8))); + scales16.val[1] = vmovl_s8(vget_high_s8(vreinterpretq_s8_u8(scales8))); + return make_wider(scales16); + } + + template + inline void compute(const Q8& q8, int i, int j, int32x4_t * sumi) { + auto m1 = vdupq_n_u8(1); + auto shuffle = vdupq_n_u8(8*j); + bits.b1.val[0] = vmulq_u8(bits.b1.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b1.val[1] = vmulq_u8(bits.b1.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b1.val[2] = vmulq_u8(bits.b1.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b1.val[3] = vmulq_u8(bits.b1.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b2.val[0] = vmulq_u8(bits.b2.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b2.val[1] = vmulq_u8(bits.b2.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b2.val[2] = vmulq_u8(bits.b2.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + bits.b2.val[3] = vmulq_u8(bits.b2.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1); + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto q8b_1 = q8.load_quants(iy, i, 4*j+0); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[0]), q8b_1.val[0]), + vreinterpretq_s8_u8(bits.b1.val[1]), q8b_1.val[1]); + + auto q8b_2 = q8.load_quants(iy, i, 4*j+1); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[2]), q8b_2.val[0]), + vreinterpretq_s8_u8(bits.b1.val[3]), q8b_2.val[1]); + + auto q8b_3 = q8.load_quants(iy, i, 4*j+2); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[0]), q8b_3.val[0]), + vreinterpretq_s8_u8(bits.b2.val[1]), q8b_3.val[1]); + + auto q8b_4 = q8.load_quants(iy, i, 4*j+3); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[2]), q8b_4.val[0]), + vreinterpretq_s8_u8(bits.b2.val[3]), q8b_4.val[1]); + } + } + + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+32*j); + } + + uint32_t aux32[4]; + + uint8x16_t scales8; + + Q2bits bits; + +}; + +// ============================= i-quants + +inline int32x4x4_t make_wider_8(const int8x16_t& scales8) { + int16x8x2_t scales16{vmovl_s8(vget_low_s8(scales8)), vmovl_s8(vget_high_s8(scales8))}; + return make_wider(scales16); +} + +struct Scale16Extra { + template + static inline int32x4x4_t new_block(int i, float d, uint16_t extra, uint8_t val, + const int8x16_t& scales8, const Q8& q8, float32x4_t * acc) { + uint8x16_t e8 = vreinterpretq_u8_u16(vdupq_n_u16(extra)); + e8 = vceqq_u8(vandq_u8(e8, emask), emask); + e8 = vqtbl1q_u8(vandq_u8(e8, vdupq_n_u8(val)), eshuff); + int16x8x2_t extra16 = {vmull_s8(vget_low_s8 (e8), vget_low_s8 (scales8)), + vmull_s8(vget_high_s8(e8), vget_high_s8(scales8))}; + accum_mins_16(extra16, q8, acc, i, d); + return make_wider_8(scales8); + } + + constexpr static uint32x4_t emask = {0x02020101, 0x08080404, 0x20201010, 0x80804040}; + constexpr static uint32x4_t eshuff = {0x06040200, 0x0e0c0a08, 0x07050301, 0x0f0d0b09}; +}; + +// Note: on ARM_NEON we cannot use the values shifted into the uint8_t range because +// the ARM_NEON only has vdotq_s32 or vdotq_u32, where both operands need to +// be signed or unsigned. As the Q8_K quants are signed, we need to have the +// iq4_s quants also signed. We can only use unsigned values in k-quants +// because they are all within the valid int8_t range. +struct DequantizerIQ4K final : public BaseDequantizer { + DequantizerIQ4K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(vld1q_s8(iq4k_values)) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return Scale16Extra::new_block(i, d, x[i].extra, 4, make_scales(x[i].scales_l, x[i].scales_h), q8, acc); + } + inline void prepare(int i, int j) { + bits.prepare16(x[i].qs+64*j); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vqtbl1q_s8(values, bits.b1.val[k]); + bits.b2.val[k] = vqtbl1q_s8(values, bits.b2.val[k]); + } + } + inline int8x16_t make_scales(const uint8_t * scales_l, const uint8_t * scales_h) const { + uint8x8_t aux = vld1_u8(scales_l); + uint8x16_t scl8 = vandq_u8(vcombine_u8(aux, vshr_n_u8(aux, 4)), vdupq_n_u8(0xf)); + const uint32_t * aux32 = (const uint32_t *)scales_h; + uint32x4_t sch_32 = {aux32[0] << 4, aux32[0] << 2, aux32[0], aux32[0] >> 2}; + uint8x16_t sch8 = vandq_u8(vreinterpretq_u8_u32(sch_32), vdupq_n_u8(0x30)); + int8x16_t scales8 = vorrq_u8(scl8, vqtbl1q_u8(sch8, hshuff)); + return vaddq_s8(vqtbl1q_s8(scales8, hshuff), vdupq_n_s8(-32)); + } + + Q4bits bits; + const int8x16_t values; + const uint8x16_t hshuff = vreinterpretq_u8_u32(uint32x4_t{0x09010800, 0x0b030a02, 0x0d050c04, 0x0f070e06}); + +}; + +struct DequantizerIQ5K final : public BaseDequantizer { + DequantizerIQ5K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(vld1q_s8_x2(iq5nl_values)) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + hbits = vld1q_u8_x2(x[i].qh); // hbits.val[0] holds 0....15, 32...47, 64...79, 96...111, 128...143, 160...175, 192...207, 224...239 + // hbits.val[1] holds 16...31, 48...63, 80...95, 112..127, 144...159, 176...191, 208...223, 240...255 + return Scale16Extra::new_block(i, d, x[i].extra, 2, make_scales(x[i].scales_l, x[i].scales_h), q8, acc); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+64*j); + if (j == 1) { + for (int k = 0; k < 2; ++k) hbits.val[k] = vshrq_n_u8(hbits.val[k], 4); + } + bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 4), hm)); + bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 4), hm)); + bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 3), hm)); + bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 3), hm)); + bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 2), hm)); + bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 2), hm)); + bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 1), hm)); + bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 1), hm)); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vqtbl2q_s8(values, bits.b1.val[k]); + bits.b2.val[k] = vqtbl2q_s8(values, bits.b2.val[k]); + } + } + inline int8x16_t make_scales(const uint8_t * scales_l, const uint8_t * scales_h) const { + uint8x8_t aux = vld1_u8(scales_l); + uint8x16_t scl8 = vandq_u8(vcombine_u8(aux, vshr_n_u8(aux, 4)), vdupq_n_u8(0xf)); + const uint32_t * aux32 = (const uint32_t *)scales_h; + uint32x4_t sch_32 = {aux32[0] << 4, aux32[0] << 2, aux32[0], aux32[0] >> 2}; + uint8x16_t sch8 = vandq_u8(vreinterpretq_u8_u32(sch_32), vdupq_n_u8(0x30)); + int8x16_t scales8 = vorrq_u8(scl8, vqtbl1q_u8(sch8, hshuff)); + return vaddq_s8(vqtbl1q_s8(scales8, hshuff), vdupq_n_s8(-32)); + } + + Q4bits bits; + const int8x16x2_t values; + const uint8x16_t hshuff = vreinterpretq_u8_u32(uint32x4_t{0x09010800, 0x0b030a02, 0x0d050c04, 0x0f070e06}); + const uint8x16_t hm = vdupq_n_u8(0x10); + uint8x16x2_t hbits; + +}; + +struct DequantizerIQ6K final : public BaseDequantizer { + DequantizerIQ6K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(vld1q_s8_x4(iq6nl_values)) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return Scale16Extra::new_block(i, d, x[i].extra, 1, vld1q_s8(x[i].scales), q8, acc); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+64*j); + auto hbits = vld1q_u8_x2(x[i].qh + 32*j); + bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 4), hm)); + bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 4), hm)); + bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 2), hm)); + bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 2), hm)); + bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(hbits.val[0], hm)); + bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(hbits.val[1], hm)); + bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshrq_n_u8(hbits.val[0], 2), hm)); + bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshrq_n_u8(hbits.val[1], 2), hm)); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vqtbl4q_s8(values, bits.b1.val[k]); + bits.b2.val[k] = vqtbl4q_s8(values, bits.b2.val[k]); + } + } + + Q4bits bits; + const int8x16x4_t values; + const uint8x16_t hm = vdupq_n_u8(0x30); + +}; + +struct DequantizerIQ2K final : public BaseDequantizer { + DequantizerIQ2K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return Scale16Extra::new_block(i, d, x[i].extra, 5, make_scales(x[i].scales), q8, acc); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+32*j); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vqtbl1q_s8(values, bits.b1.val[k]); + bits.b2.val[k] = vqtbl1q_s8(values, bits.b2.val[k]); + } + } + inline int8x16_t make_scales(const uint8_t * scales_l) const { + uint8x8_t aux = vld1_u8(scales_l); + uint8x16_t scl8 = vandq_u8(vcombine_u8(aux, vshr_n_u8(aux, 4)), vdupq_n_u8(0xf)); + int8x16_t scales = vaddq_s8(vreinterpretq_s8_u8(vshlq_n_u8(scl8, 1)), vdupq_n_s8(-15)); + return vqtbl1q_s8(scales, hshuff); + } + + Q2bits bits; + const int8x16_t values = vreinterpretq_s8_u64(vdupq_n_u64(0x000000001101f3e1)); + const uint8x16_t hshuff = vreinterpretq_u8_u32(uint32x4_t{0x09010800, 0x0b030a02, 0x0d050c04, 0x0f070e06}); + +}; + +struct DequantizerIQ3K final : public BaseDequantizer { + DequantizerIQ3K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) { + d = GGML_FP16_TO_FP32(x[i].d); + return Scale16Extra::new_block(i, d, x[i].extra, 4, make_scales(x[i].scales_h, x[i].scales_l), q8, acc); + } + inline void prepare(int i, int j) { + bits.prepare(x[i].qs+32*j); + if (j == 0) { + hbits = vld1q_u8_x2(x[i].qh); + } + else { + hbits.val[0] = vshrq_n_u8(hbits.val[0], 4); + hbits.val[1] = vshrq_n_u8(hbits.val[1], 4); + } + bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 2), hmask)); + bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 2), hmask)); + bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 1), hmask)); + bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 1), hmask)); + bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(hbits.val[0], hmask)); + bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(hbits.val[1], hmask)); + bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshrq_n_u8(hbits.val[0], 1), hmask)); + bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshrq_n_u8(hbits.val[1], 1), hmask)); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vqtbl1q_s8(values, bits.b1.val[k]); + bits.b2.val[k] = vqtbl1q_s8(values, bits.b2.val[k]); + } + } + inline int8x16_t make_scales(uint16_t sign_bits, const uint8_t * scales_l) const { + uint8x8_t aux = vld1_u8(scales_l); + uint8x16_t scl8 = vandq_u8(vcombine_u8(aux, vshr_n_u8(aux, 4)), vdupq_n_u8(0xf)); + int8x16_t scales = vaddq_s8(vreinterpretq_s8_u8(vshlq_n_u8(scl8, 1)), vdupq_n_s8(1)); + uint8x16_t signs = vceqq_u8(vandq_u8(vreinterpretq_u8_u16(vdupq_n_u16(sign_bits)), sign_mask), sign_mask); + signs = vorrq_u8(signs, vdupq_n_u8(1)); + // scales are 0, 2, 4, 6, 8, 10, 12, 14, 1, 3, 5, 7, 9, 11, 13, 15 + // signs are 0, 8, 1, 9, 2, 10, 3, 11, 4, 12, 5, 13, 6, 14, 7, 15 + scales = vmulq_s8(scales, vreinterpretq_s8_u8(vqtbl1q_u8(signs, sign_shuffle))); + return vqtbl1q_s8(scales, hshuff); + } + inline static uint8x16_t load_sign_shuffle() { + static uint8_t k_shuff[16] = {0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15}; + return vld1q_u8(k_shuff); + } + + Q2bits bits; + uint8x16x2_t hbits; + const int8x16_t values = vreinterpretq_s8_u64(vdupq_n_u64(0x2f1c0d01f6e9d8c1)); + const uint8x16_t hshuff = vreinterpretq_u8_u32(uint32x4_t{0x09010800, 0x0b030a02, 0x0d050c04, 0x0f070e06}); + const uint8x16_t hmask = vdupq_n_u8(4); + const uint8x16_t sign_mask = vreinterpretq_u8_u64(uint64x2_t{0x0808040402020101, 0x8080404020201010}); + const uint8x16_t sign_shuffle = load_sign_shuffle(); + +}; + +struct DequantizerIQ4XS final : public BaseDequantizer { + + static int8x16_t load_values() { + static const int8_t iq4nl_values[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113}; + return vld1q_s8(iq4nl_values); + } + + DequantizerIQ4XS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(load_values()) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + inline void new_row(int ix) { x = (const block_iq4_xs *)((const char *)vx + bx*ix); } + + template + inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) { + (void)q8; + (void)acc; + d = GGML_FP16_TO_FP32(x[i].d); + const uint16_t scales_h = x[i].scales_h; + const uint16_t * scales_l = (const uint16_t *)x[i].scales_l; + aux32[0] = scales_l[0] | (scales_l[1] << 16); + aux32[1] = aux32[0] >> 4; + // scl is ordered as 0, 2, 4, 6, 1, 3, 5, 7 + uint8x8_t scl8 = vand_u8(vld1_u8((const uint8_t *)aux32), vdup_n_u8(0xf)); + uint16_t * aux16 = (uint16_t *)aux32; + aux16[0] = scales_h << 4; aux16[1] = scales_h << 2; aux16[2] = scales_h; aux16[3] = scales_h >> 2; + // sch is ordered as 0, 4, 1, 5, 2, 6, 3, 7 + uint8x8_t sch8 = vand_u8(vld1_u8((const uint8_t *)aux16), vdup_n_u8(0x30)); + int8x8_t scales8 = vadd_s8(vreinterpret_s8_u8(vorr_u8(scl8, vtbl1_u8(sch8, vreinterpret_u8_u32(hshuff)))), vdup_n_s8(-32)); + // shuffle 0, 2, 4, 6, 1, 3, 5, 7 -> 0, 1, 2, 3, 4, 5, 6, 7 + scales8 = vtbl1_s8(scales8, vreinterpret_s8_u32(hshuff)); + int16x8_t scales16 = vmovl_s8(scales8); + int32x4x2_t scales = {vmovl_s16(vget_low_s16(scales16)), vmovl_s16(vget_high_s16(scales16))}; + return scales; + } + inline void prepare(int i, int j) { + bits.prepare16(x[i].qs+64*j); + //if (nrc == 1) { + // bits.prepare16_v2(x[i].qs+64*j); + //} else { + // bits.prepare16(x[i].qs+64*j); + //} + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b1.val[k])); + bits.b2.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b2.val[k])); + } + } + + Q4bits bits; + const int8x16_t values; + uint32_t aux32[2]; + + constexpr static uint32x2_t hshuff = {0x05010400, 0x07030602}; + +}; + +struct SimpleBits { + uint8x16x4_t b1; + uint8x16x4_t b2; +}; + +inline int32x4x2_t prepare_scales_8(const uint32x4_t& v1, const uint32x4_t& v2) { + int32x4x2_t scales; + scales.val[0] = vreinterpretq_s32_u32(vorrq_u32(vshlq_n_u32(vshrq_n_u32(v1, 28), 1), vdupq_n_u32(1))); + scales.val[1] = vreinterpretq_s32_u32(vorrq_u32(vshlq_n_u32(vshrq_n_u32(v2, 28), 1), vdupq_n_u32(1))); + return scales; +} + +inline void apply_signs_2(uint8x16_t * b, const uint64_t * signs, uint32_t sidx) { + auto s1 = vcombine_s8(vld1_s8((const int8_t *)(signs + ((sidx >> 0) & 127))), vld1_s8((const int8_t *)(signs + ((sidx >> 7) & 127)))); + auto s2 = vcombine_s8(vld1_s8((const int8_t *)(signs + ((sidx >>14) & 127))), vld1_s8((const int8_t *)(signs + ((sidx >>21) & 127)))); + b[0] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[0]), s1)); + b[1] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[1]), s2)); +} + +struct DequantizerIQ2XXS final : public BaseDequantizer { + DequantizerIQ2XXS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x2_t new_block(int i, const Q8& /*q8*/, float32x4_t * /*acc*/) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + + auto tmp = vld1q_u32_x4((const uint32_t *)x[i].qs); + data.val[0] = vuzp1q_u32(tmp.val[0], tmp.val[1]); // codebook indices for blocks 0...3 + data.val[1] = vuzp2q_u32(tmp.val[0], tmp.val[1]); // scales and signs for blocks 0...3 + data.val[2] = vuzp1q_u32(tmp.val[2], tmp.val[3]); // codebook indices for blocks 4...7 + data.val[3] = vuzp2q_u32(tmp.val[2], tmp.val[3]); // scales and signs for blocks 4...7 + + return prepare_scales_8(data.val[1], data.val[3]); + } + + static inline void prepare2(uint8x16_t * b, const uint8_t * idx, const uint64_t * signs, uint32_t sidx) { + b[0] = vreinterpretq_u8_u64(uint64x2_t{iq2xxs_grid[idx[0]], iq2xxs_grid[idx[1]]}); + b[1] = vreinterpretq_u8_u64(uint64x2_t{iq2xxs_grid[idx[2]], iq2xxs_grid[idx[3]]}); + apply_signs_2(b, signs, sidx); + } + + inline void prepare(int /*i*/, int j) { + const uint8_t * idx = (const uint8_t *)(data.val + 2*j); + const uint32_t * sidx = (const uint32_t *)(data.val + 2*j+1); + prepare2(bits.b1.val + 0, idx, keven_signs, sidx[0]); idx += 4; + prepare2(bits.b1.val + 2, idx, keven_signs, sidx[1]); idx += 4; + prepare2(bits.b2.val + 0, idx, keven_signs, sidx[2]); idx += 4; + prepare2(bits.b2.val + 2, idx, keven_signs, sidx[3]); + } + + uint32x4x4_t data; + SimpleBits bits; + +}; + +inline int32x4x4_t prepare_4bit_scales16(const uint8_t * sc) { + auto aux = vld1_u8(sc); + auto scales_l = vand_u8(aux, vdup_n_u8(0xf)); + auto scales_h = vshr_n_u8(aux, 4); + auto aux1 = vcombine_u8(vzip1_u8(scales_l, scales_h), vzip2_u8(scales_l, scales_h)); + + auto scales8 = vreinterpretq_s8_u8(vorrq_u8(vshlq_n_u8(aux1, 1), vdupq_n_u8(1))); + int16x8x2_t scales16 = { vmovl_s8(vget_low_s8(scales8)), vmovl_s8(vget_high_s8(scales8)) }; + return make_wider(scales16); +} + +struct DequantizerIQ2XS final : public BaseDequantizer { + DequantizerIQ2XS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& /*q8*/, float32x4_t * /*acc*/) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + return prepare_4bit_scales16(x[i].scales); + } + + inline static uint8x16_t make1(const uint16_t * qs) { + auto b = vcombine_u8(vld1_u8((const uint8_t *)(iq2xs_grid + (qs[0] & 511))), vld1_u8((const uint8_t *)(iq2xs_grid + (qs[1] & 511)))); + auto s = vcombine_s8(vld1_s8((const int8_t *)(keven_signs + (qs[0] >> 9))), vld1_s8((const int8_t *)(keven_signs + (qs[1] >> 9)))); + return vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b), s)); + } + + inline static void make4(const uint16_t * qs, uint8x16_t * b) { + b[0] = make1(qs + 0); + b[1] = make1(qs + 2); + b[2] = make1(qs + 4); + b[3] = make1(qs + 6); + } + + inline void prepare(int i, int j) { + make4(x[i].qs + 16*j + 0, bits.b1.val); + make4(x[i].qs + 16*j + 8, bits.b2.val); + } + + SimpleBits bits; + + +}; + +struct SignHelper { + + inline void init() { shuffle = vcombine_u8(vdup_n_u8(0), vdup_n_u8(1)); } + + inline void apply_signs_1(uint8x16_t * b, const uint8x16_t& signs16) { + auto aux = vqtbl1q_u8(signs16, shuffle); + auto s = vreinterpretq_s8_u8(vorrq_u8(vceqq_u8(vandq_u8(aux, smask), smask), m1)); + b[0] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[0]), s)); + shuffle = vaddq_u8(shuffle, step); + } + + const uint8x16_t smask = vreinterpretq_u8_u64(vdupq_n_u64(0x8040201008040201)); + const uint8x16_t m1 = vdupq_n_u8(1); + const uint8x16_t step = vdupq_n_u8(2); + uint8x16_t shuffle; +}; + +struct DequantizerIQ2S final : public BaseDequantizer { + DequantizerIQ2S(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x4_t new_block(int i, const Q8& /*q8*/, float32x4_t * /*acc*/) { + d = 0.125f * GGML_FP16_TO_FP32(x[i].d); + return prepare_4bit_scales16(x[i].scales); + } + + static inline void make4(SignHelper& sh, const uint8x16_t& signs16, const uint8_t * qs, const uint8_t * qh, uint8x16_t * b) { + uint32_t aux32[2]; + const uint16_t * aux16 = (const uint16_t *)aux32; + for (int k = 0; k < 2; ++k) { + aux32[1] = (qh[k] << 4) | (qh[k] << 18); + aux32[0] = (aux32[1] << 4) & 0x03000300; + aux32[1] &= 0x03000300; + b[2*k+0] = vcombine_u8(vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+0] | aux16[0]))), + vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+1] | aux16[1])))); + sh.apply_signs_1(b+2*k+0, signs16); + + b[2*k+1] = vcombine_u8(vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+2] | aux16[2]))), + vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+3] | aux16[3])))); + sh.apply_signs_1(b+2*k+1, signs16); + } + } + + inline void prepare(int i, int j) { + + const auto * qs = x[i].qs + 16*j; + const auto * qh = x[i].qh + 4*j; + const auto signs16 = vld1q_u8(qs + QK_K/8); + + sh.init(); + make4(sh, signs16, qs+0, qh+0, bits.b1.val); + make4(sh, signs16, qs+8, qh+2, bits.b2.val); + } + + SimpleBits bits; + SignHelper sh; + + +}; + +struct DequantizerIQ3XXS final : public BaseDequantizer { + DequantizerIQ3XXS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x2_t new_block(int i, const Q8& /*q8*/, float32x4_t * /*acc*/) { + d = 0.25f * GGML_FP16_TO_FP32(x[i].d); + gas = vld1q_u32_x2((const uint32_t *)(x[i].qs + QK_K/4)); + return prepare_scales_8(gas.val[0], gas.val[1]); + } + + inline static void make2(const uint8_t * q3, uint32_t sidx, uint8x16_t * b) { + b[0] = vreinterpretq_u8_u32(uint32x4_t{iq3xxs_grid[q3[0]], iq3xxs_grid[q3[1]], iq3xxs_grid[q3[2]], iq3xxs_grid[q3[3]]}); + b[1] = vreinterpretq_u8_u32(uint32x4_t{iq3xxs_grid[q3[4]], iq3xxs_grid[q3[5]], iq3xxs_grid[q3[6]], iq3xxs_grid[q3[7]]}); + apply_signs_2(b, keven_signs, sidx); + } + inline void prepare(int i, int j) { + const auto * q3 = x[i].qs + 32*j; + const auto * signs = (const uint32_t *)(gas.val + j); + make2(q3, signs[0], bits.b1.val + 0); q3 += 8; + make2(q3, signs[1], bits.b1.val + 2); q3 += 8; + make2(q3, signs[2], bits.b2.val + 0); q3 += 8; + make2(q3, signs[3], bits.b2.val + 2); + } + + SimpleBits bits; + uint32x4x2_t gas; + +}; + +struct DequantizerIQ3S final : public BaseDequantizer { + DequantizerIQ3S(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 8; } + constexpr static bool should_scale_quants() { return false; } + + template + inline int32x4x2_t new_block(int i, const Q8& /*q8*/, float32x4_t * /*acc*/) { + d = GGML_FP16_TO_FP32(x[i].d); + uint32_t scales32[2]; + std::memcpy(scales32, x[i].scales, 4); + scales32[1] = (((scales32[0] >> 4) & 0x0f0f0f0f) << 1) | 0x01010101; + scales32[0] = ((scales32[0] & 0x0f0f0f0f) << 1) | 0x01010101; + auto scales8 = vld1_u8((const uint8_t *)scales32); // 0, 2, 4, 6, 1, 3, 5, 7 + scales8 = vtbl1_u8(scales8, vreinterpret_u8_u64(vdup_n_u64(0x0703060205010400))); + auto scales16 = vreinterpretq_s16_u16(vmovl_u8(scales8)); + int32x4x2_t scales; + scales.val[0] = vmovl_s16(vget_low_s16(scales16)); + scales.val[1] = vmovl_s16(vget_high_s16(scales16)); + return scales; + } + + static inline void make2(SignHelper& sh, const uint8x16_t& signs16, const uint16x8_t& idx_l, uint8_t qh, + const int8x16_t& hshift, uint8x16_t * b) { + auto vindex = vorrq_u16(idx_l, vandq_u16(vshlq_u16(vdupq_n_u16(qh), hshift), vdupq_n_u16(256))); + const uint16_t * idx = (const uint16_t *)&vindex; + b[0] = vreinterpretq_u8_u32(uint32x4_t{iq3s_grid[idx[0]], iq3s_grid[idx[1]], iq3s_grid[idx[2]], iq3s_grid[idx[3]]}); + b[1] = vreinterpretq_u8_u32(uint32x4_t{iq3s_grid[idx[4]], iq3s_grid[idx[5]], iq3s_grid[idx[6]], iq3s_grid[idx[7]]}); + sh.apply_signs_1(b+0, signs16); + sh.apply_signs_1(b+1, signs16); + } + static inline void make4(SignHelper& sh, const uint8x16_t& signs16, const uint8_t * qs, const uint8_t * qh, + const int8x16_t& hshift, uint8x16_t * b) { + auto idx_l = vld1q_u8(qs); + make2(sh, signs16, vmovl_u8(vget_low_u8 (idx_l)), qh[0], hshift, b+0); + make2(sh, signs16, vmovl_u8(vget_high_u8(idx_l)), qh[1], hshift, b+2); + } + + inline void prepare(int i, int j) { + + static const int16_t k_shift[8] = {8, 7, 6, 5, 4, 3, 2, 1}; + const auto hshift = vld1q_s16(k_shift); + + const auto * qs = x[i].qs + 32*j; + const auto * qh = x[i].qh + 4*j; + const auto signs16 = vld1q_u8(x[i].signs + 16*j); + + sh.init(); + make4(sh, signs16, qs+ 0, qh+0, hshift, bits.b1.val); + make4(sh, signs16, qs+16, qh+2, hshift, bits.b2.val); + } + + SimpleBits bits; + SignHelper sh; + uint32x4x2_t gas; + +}; + +struct DequantizerIQ2TN final : public BaseDequantizer { + DequantizerIQ2TN(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {} + + constexpr static int num_blocks() { return 16; } + constexpr static bool should_scale_quants() { return true; } + + //template + //inline void process_scales(int i, [[maybe_unused]] const Q8& q8, [[maybe_unused]] float32x4_t * acc) { + // d = GGML_FP16_TO_FP32(x[i].d); + //} + + inline void new_block(int) { } + + template + inline void compute(const Q8& q8, int i, int j, int32x4_t * sumi) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto q8b_1 = q8.load_quants(iy, i, 4*j+0); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[0]), q8b_1.val[0]), + vreinterpretq_s8_u8(bits.b1.val[1]), q8b_1.val[1]); + + auto q8b_2 = q8.load_quants(iy, i, 4*j+1); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[2]), q8b_2.val[0]), + vreinterpretq_s8_u8(bits.b1.val[3]), q8b_2.val[1]); + + auto q8b_3 = q8.load_quants(iy, i, 4*j+2); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[0]), q8b_3.val[0]), + vreinterpretq_s8_u8(bits.b2.val[1]), q8b_3.val[1]); + + auto q8b_4 = q8.load_quants(iy, i, 4*j+3); + sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[2]), q8b_4.val[0]), + vreinterpretq_s8_u8(bits.b2.val[3]), q8b_4.val[1]); + } + } + template + inline void compute1(const Q8& q8, int i, int j, int32x4_t * sumi) { + auto q8b_1 = q8.load_quants(0, i, 4*j+0); + sumi[0] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[0], vreinterpretq_s8_u8(bits.b1.val[0]), q8b_1.val[0]), + vreinterpretq_s8_u8(bits.b1.val[1]), q8b_1.val[1]); + + auto q8b_2 = q8.load_quants(0, i, 4*j+1); + sumi[1] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[1], vreinterpretq_s8_u8(bits.b1.val[2]), q8b_2.val[0]), + vreinterpretq_s8_u8(bits.b1.val[3]), q8b_2.val[1]); + + q8b_1 = q8.load_quants(0, i, 4*j+2); + sumi[0] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[0], vreinterpretq_s8_u8(bits.b2.val[0]), q8b_1.val[0]), + vreinterpretq_s8_u8(bits.b2.val[1]), q8b_1.val[1]); + + q8b_2 = q8.load_quants(0, i, 4*j+3); + sumi[1] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[1], vreinterpretq_s8_u8(bits.b2.val[2]), q8b_2.val[0]), + vreinterpretq_s8_u8(bits.b2.val[3]), q8b_2.val[1]); + } + + IQK_ALWAYS_INLINE void prepare(int i, int j) { + bits.prepare(x[i].qs+32*j); + auto m1 = vdupq_n_s8(1); + for (int k = 0; k < 4; ++k) { + bits.b1.val[k] = vsubq_s8(bits.b1.val[k], m1); + bits.b2.val[k] = vsubq_s8(bits.b2.val[k], m1); + } + } + + Q2bits bits; +}; + +template +void mul_mat_iq2tn_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + DequantizerIQ2TN deq(vx, bx, nrc_y); + float32x4_t acc[nrc_y]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + int32x4_t sumi[nrc_y]; + for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = vdupq_n_s32(0); + + deq.new_block(i); + deq.prepare(i, 0); + deq.compute(q8, i, 0, sumi); + deq.prepare(i, 1); + deq.compute(q8, i, 1, sumi); + + if (i > 0) { + for (int iy = 0; iy < nrc_y; ++iy) { + acc[iy] = vmlaq_f32(acc[iy], vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i))); + } + } else { + for (int iy = 0; iy < nrc_y; ++iy) { + acc[iy] = vmulq_f32(vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i))); + } + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, vaddvq_f32(acc[iy])); + } + } +} +void mul_mat_iq2tn_K_q8_K_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8<1, block_q8_K> q8(info); + + DequantizerIQ2TN deq(vx, bx, 1); + + auto m1 = vdup_n_s16(-1); + float32x4_t acc[2]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + for (int i = 0; i < nb; ++i) { + + int32x4_t sumi[2] = {}; + deq.new_block(i); + auto bsums = q8.load_bsums(0, i); + bsums.val[0] = vaddq_s32(bsums.val[0], bsums.val[1]); + sumi[0] = vmlal_s16(sumi[0], vget_low_s16 (bsums.val[0]), m1); + sumi[1] = vmlal_s16(sumi[1], vget_high_s16(bsums.val[0]), m1); + deq.bits.prepare(deq.x[i].qs); + deq.compute1(q8, i, 0, sumi); + deq.bits.prepare(deq.x[i].qs+32); + deq.compute1(q8, i, 1, sumi); + + auto vd = vdupq_n_f32(deq.d*q8.scale(0, i)); + if (i > 0) { + acc[0] = vmlaq_f32(acc[0], vcvtq_f32_s32(sumi[0]), vd); + acc[1] = vmlaq_f32(acc[1], vcvtq_f32_s32(sumi[1]), vd); + } else { + acc[0] = vmulq_f32(vcvtq_f32_s32(sumi[0]), vd); + acc[1] = vmulq_f32(vcvtq_f32_s32(sumi[1]), vd); + } + + } + + acc[0] = vaddq_f32(acc[0], acc[1]); + info.store(ix, 0, vaddvq_f32(acc[0])); + } +} + + +template +void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + assert(n % QK_K == 0); + const int nb = n / QK_K; + + Q8 q8(info); + + Dequantizer deq(vx, bx, nrc_y); + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + float32x4_t acc[nrc_y]; + for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f); + + for (int i = 0; i < nb; ++i) { + + int32x4_t sumi[nrc_y]; + for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = vdupq_n_s32(0); + + if constexpr (nrc_y > 1 && Dequantizer::should_scale_quants()) { + deq.process_scales(i, q8, acc); + deq.prepare(i, 0); + deq.compute(q8, i, 0, sumi); + deq.prepare(i, 1); + deq.compute(q8, i, 1, sumi); + } else { + if constexpr (Dequantizer::num_blocks() == 8) { + auto scales = deq.new_block(i, q8, acc); + deq.prepare(i, 0); + for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]); + deq.prepare(i, 1); + for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]); + } + else if constexpr (Dequantizer::num_blocks() == 16) { + auto scales = deq.new_block(i, q8, acc); + deq.prepare(i, 0); + for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]); + deq.prepare(i, 1); + for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]); + } + else { + GGML_ASSERT(false); + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + acc[iy] = vmlaq_f32(acc[iy], vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i))); + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, vaddvq_f32(acc[iy])); + } + } +} + +// =========================================== Legacy quants + +template +inline float16x4_t load_scales_q0(const Block * x, ggml_half * aux) { + for (int k = 0; k < 4; ++k) aux[k] = x[k].d; + return vld1_f16((const float16_t *)aux); +} + +template +inline float16x8_t load_scales_q1(const Block * x, ggml_half * aux) { + if constexpr (std::is_same_v) { + for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].s; } + } else { + for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].m; } + } + return vld1q_f16((const float16_t *)aux); +} + +struct Q4LegacyBits { + template + inline void prepare(const Block * x) { + for (int i = 0; i < 4; ++i) { + auto q4bits = vld1q_u8(x[i].qs); + b[2*i+0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b)); + b[2*i+1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4)); + } + } + inline void prepare1(const uint8_t * qs, int8x16_t * q) const { + auto q4bits = vld1q_u8(qs); + q[0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b)); + q[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4)); + } + inline void prepare1(const uint8_t * qs) { + prepare1(qs, b); + } + const uint8x16_t m4b = vdupq_n_u8(0xf); + int8x16_t b[8]; +}; + +// One would think this commented out version would do better than the one below +// because it offers more opportunities to execute instructions in parallel. +// Instead, it runs significantly slower. Why? If the compiler is running out of vector registers +// cannot it just do the sequential version below on its own? +//inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) { +// const auto q8b_1 = vld1q_s8_x2(qs + 0); +// auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b_1.val[0]), b[1], q8b_1.val[1]); +// const auto q8b_2 = vld1q_s8_x2(qs + 32); +// auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b_2.val[0]), b[3], q8b_2.val[1]); +// auto p1234 = vpaddq_s32(p12, p34); +// const auto q8b_3 = vld1q_s8_x2(qs + 64); +// auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b_3.val[0]), b[5], q8b_3.val[1]); +// const auto q8b_4 = vld1q_s8_x2(qs + 96); +// auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b_4.val[0]), b[7], q8b_4.val[1]); +// return vpaddq_s32(p1234, vpaddq_s32(p56, p78)); +//} + +inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) { + auto q8b = vld1q_s8_x2(qs + 0); + auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b.val[0]), b[1], q8b.val[1]); + q8b = vld1q_s8_x2(qs + 32); + auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b.val[0]), b[3], q8b.val[1]); + auto p1234 = vpaddq_s32(p12, p34); + q8b = vld1q_s8_x2(qs + 64); + auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b.val[0]), b[5], q8b.val[1]); + q8b = vld1q_s8_x2(qs + 96); + auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b.val[0]), b[7], q8b.val[1]); + return vpaddq_s32(p1234, vpaddq_s32(p56, p78)); +} + +inline int32x4x2_t sum_4_blocks(const int8x16_t * b1, const int8x16_t * b2, const int8_t * qs) { + auto q8b = vld1q_s8_x2(qs + 0); + auto p12_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b1[0], q8b.val[0]), b1[1], q8b.val[1]); + auto p12_2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b2[0], q8b.val[0]), b2[1], q8b.val[1]); + q8b = vld1q_s8_x2(qs + 32); + auto p34_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b1[2], q8b.val[0]), b1[3], q8b.val[1]); + auto p34_2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b2[2], q8b.val[0]), b2[3], q8b.val[1]); + auto p1234_1 = vpaddq_s32(p12_1, p34_1); + auto p1234_2 = vpaddq_s32(p12_2, p34_2); + q8b = vld1q_s8_x2(qs + 64); + auto p56_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b1[4], q8b.val[0]), b1[5], q8b.val[1]); + auto p56_2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b2[4], q8b.val[0]), b2[5], q8b.val[1]); + q8b = vld1q_s8_x2(qs + 96); + auto p78_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b1[6], q8b.val[0]), b1[7], q8b.val[1]); + auto p78_2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b2[6], q8b.val[0]), b2[7], q8b.val[1]); + auto p5678_1 = vpaddq_s32(p56_1, p78_1); + auto p5678_2 = vpaddq_s32(p56_2, p78_2); + return { vpaddq_s32(p1234_1, p5678_1), vpaddq_s32(p1234_2, p5678_2)}; +} + +template struct Q80 { + + constexpr static int nrc_y = nrc; + + Q80(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_0 *)info.src1_row(iy); + } + + inline const int8_t * quant_data(int iy, int i) const { + const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i; + return y4->qs; + } + + inline float16x4_t load_scales(int iy, int i) const { + const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i; + return vld1_f16((const float16_t *)y4->d); + } + + template + inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * /*acc*/) const { + auto qx_scales = deq.new_block(i); + for (int iy = 0; iy < nrc; ++iy) { + auto q8_scales = load_scales(iy, i); + sc16[iy] = vmul_f16(qx_scales, q8_scales); + } + } + + template + inline void process_scales(int i, Dequantizer& deq1, Dequantizer& deq2, float16x4_t * sc16, float32x4_t * /*acc*/) const { + auto qx_scales_1 = deq1.new_block(i); + auto qx_scales_2 = deq2.new_block(i); + for (int iy = 0; iy < nrc; ++iy) { + auto q8_scales = load_scales(iy, i); + sc16[iy ] = vmul_f16(qx_scales_1, q8_scales); + sc16[iy+nrc_y] = vmul_f16(qx_scales_2, q8_scales); + } + } + + template + inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const { + deq.prepare1(i); + float d = GGML_FP16_TO_FP32(deq.x[i].d); + for (int iy = 0; iy < nrc; ++iy) { + auto q8b = vld1q_s8_x2(y[iy][i].qs); + auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]); + acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p)); + } + } + + const block_q8_0 * y[nrc_y]; +}; + +template struct Q81 { + + constexpr static int nrc_y = nrc; + + Q81(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_1 *)info.src1_row(iy); + } + + inline const int8_t * quant_data(int iy, int i) const { + const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i; + return y4->qs; + } + + inline float16x8_t load_scales(int iy, int i) const { + const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i; + return vld1q_f16((const float16_t *)y4->d); + } + + template + inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * acc) const { + auto qx_scales = deq.new_block(i); + for (int iy = 0; iy < nrc; ++iy) { + auto q8_scales = load_scales(iy, i); + auto m = vmul_f16(vget_high_f16(qx_scales), vget_high_f16(q8_scales)); + acc[iy] = vaddq_f32(acc[iy], vcvt_f32_f16(m)); + sc16[iy] = vmul_f16(vget_low_f16(qx_scales), vget_low_f16(q8_scales)); + } + } + + template + inline void process_scales(int i, Dequantizer& deq1, Dequantizer& deq2, float16x4_t * sc16, float32x4_t * acc) const { + auto qx_scales_1 = deq1.new_block(i); + auto qx_scales_2 = deq2.new_block(i); + for (int iy = 0; iy < nrc; ++iy) { + auto q8_scales = load_scales(iy, i); + auto q8_scales_l = vget_low_f16(q8_scales); + auto q8_scales_h = vget_high_f16(q8_scales); + auto m1 = vmul_f16(vget_high_f16(qx_scales_1), q8_scales_h); + auto m2 = vmul_f16(vget_high_f16(qx_scales_2), q8_scales_h); + acc[iy ] = vaddq_f32(acc[iy ], vcvt_f32_f16(m1)); + acc[iy+nrc_y ] = vaddq_f32(acc[iy+nrc_y], vcvt_f32_f16(m2)); + sc16[iy ] = vmul_f16(vget_low_f16(qx_scales_1), q8_scales_l); + sc16[iy+nrc_y] = vmul_f16(vget_low_f16(qx_scales_2), q8_scales_l); + } + } + + template + inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const { + deq.prepare1(i); + float d = GGML_FP16_TO_FP32(deq.x[i].d), m = 0.25f*GGML_FP16_TO_FP32(deq.x[i].m); + for (int iy = 0; iy < nrc; ++iy) { + auto q8b = vld1q_s8_x2(y[iy][i].qs); + auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]); + acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p)); + acc[iy] = vaddq_f32(acc[iy], vdupq_n_f32(m*GGML_FP16_TO_FP32(y[iy][i].s))); + } + } + + const block_q8_1 * y[nrc_y]; +}; + +template +struct BaseLegacyDequantizer { + + BaseLegacyDequantizer(const void * vx, size_t bx) : vx(vx), x(nullptr), bx(bx) {} + + inline void new_row(int ix) { x = (const block_q *)((const char *)vx + bx*ix); } + + Q4LegacyBits bits; + + const void * vx; + const block_q * x; + size_t bx; +}; + +struct DequantizerQ40 final : public BaseLegacyDequantizer { + + DequantizerQ40(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i, int8x16_t * q) const { + bits.prepare1(x[i].qs, q); + q[0] = vaddq_s8(q[0], m8); + q[1] = vaddq_s8(q[1], m8); + } + inline void prepare1(int i) { + prepare1(i, bits.b); + } + + inline float16x4_t new_block(int i) { + ggml_half aux[4]; + for (int k = 0; k < 4; ++k) { + aux[k] = x[4*i+k].d; + prepare1(4*i+k, bits.b + 2*k); + } + return vld1_f16((const float16_t *)aux); + } + + const int8x16_t m8 = vdupq_n_s8(-8); + //ggml_half aux[4]; +}; + +struct DequantizerQ60 final : public BaseLegacyDequantizer { + + DequantizerQ60(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i, int8x16_t * q) const { + bits.prepare1(x[i].qs, q); + auto qh8 = vld1_u8(x[i].qh); + auto qh = vcombine_u8(vshl_n_u8(qh8, 4), qh8); + q[0] = vaddq_s8(vorrq_u8(q[0], vandq_u8(qh, hmask)), m32); + q[1] = vaddq_s8(vorrq_u8(q[1], vandq_u8(vshrq_n_u8(qh, 2), hmask)), m32); + } + inline void prepare1(int i) { + prepare1(i, bits.b); + } + + inline float16x4_t new_block(int i) { + ggml_half aux[4]; + for (int k = 0; k < 4; ++k) { + aux[k] = x[4*i+k].d; + prepare1(4*i+k, bits.b + 2*k); + } + return vld1_f16((const float16_t *)aux); + } + + const int8x16_t m32 = vdupq_n_s8(-32); + const uint8x16_t hmask = vdupq_n_u8(0x30); +}; + +struct DequantizerIQ4NL final : public BaseLegacyDequantizer { + + DequantizerIQ4NL(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i, int8x16_t * q) const { + bits.prepare1(x[i].qs, q); + q[0] = vqtbl1q_s8(values, q[0]); + q[1] = vqtbl1q_s8(values, q[1]); + } + inline void prepare1(int i) { + prepare1(i, bits.b); + } + + inline float16x4_t new_block(int i) { + ggml_half aux[4]; + for (int k = 0; k < 4; ++k) { + aux[k] = x[4*i+k].d; + prepare1(4*i+k, bits.b + 2*k); + } + return vld1_f16((const float16_t *)aux); + } + static int8x16_t load_values() { + static const int8_t iq4nl_values[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113}; + return vld1q_s8(iq4nl_values); + } + + const int8x16_t values = load_values(); +}; + +struct DequantizerQ41 : public BaseLegacyDequantizer { + + DequantizerQ41(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i) { + bits.prepare1(x[i].qs); + } + + inline float16x8_t new_block(int i) { + uint32_t aux32[4]; + const uint32_t * s32 = (const uint32_t *)&x[4*i].d; + for (int k = 0; k < 4; ++k) { + aux32[k] = *s32; s32 += sizeof(block_q4_1)/4; + bits.prepare1(x[4*i+k].qs, bits.b + 2*k); + } + return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle))); + } + // Leaving this commented out attempt to be reminded that I already tried this. + // It has basically the same performance as the version above. + //inline float16x8_t new_block(int i) { + // uint32x4_t scales = {}; + // const block_q4_1 * xi = x + 4*i; + // const uint32_t * s32 = (const uint32_t *)&xi->d; + // scales = vsetq_lane_u32(*s32, scales, 0); s32 += sizeof(block_q4_1)/4; + // bits.prepare1(xi[0].qs, bits.b + 0); + // scales = vsetq_lane_u32(*s32, scales, 1); s32 += sizeof(block_q4_1)/4; + // bits.prepare1(xi[1].qs, bits.b + 2); + // scales = vsetq_lane_u32(*s32, scales, 2); s32 += sizeof(block_q4_1)/4; + // bits.prepare1(xi[2].qs, bits.b + 4); + // scales = vsetq_lane_u32(*s32, scales, 3); + // bits.prepare1(xi[3].qs, bits.b + 6); + // return vreinterpretq_f16_u8(vqtbl1q_u8(vreinterpretq_u8_u32(scales), vreinterpretq_u8_u64(shuffle))); + //} + + const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302}; +}; + +struct HighBit5Legacy { + inline uint8x16_t to_bytes(const uint8_t * qh) const { + uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle); + return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vreinterpretq_u8_u64(mask)); + } + inline uint8x16_t to_negated_bytes(const uint8_t * qh) const { + uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle); + return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vdupq_n_u8(0)); + } + const uint64x2_t mask = vdupq_n_u64(0x8040201008040201); + const uint8x16_t shuffle = vcombine_u8(vdup_n_u8(0), vdup_n_u8(1)); +}; + +struct DequantizerQ50 final : public BaseLegacyDequantizer { + + DequantizerQ50(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i, int8x16_t * q) const { + bits.prepare1(x[i].qs, q); + auto qh = x[i].qh; + q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_negated_bytes(qh+0)))); + q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_negated_bytes(qh+2)))); + } + inline void prepare1(int i) { + prepare1(i, bits.b); + } + + inline float16x4_t new_block(int i) { + ggml_half aux[4]; + for (int k = 0; k < 4; ++k) { + aux[k] = x[4*i+k].d; + prepare1(4*i+k, bits.b + 2*k); + } + return vld1_f16((const float16_t *)aux); + } + + HighBit5Legacy hbits; + + const uint8x16_t mh = vdupq_n_u8(0xf0); + +}; + +struct DequantizerQ80 final : public BaseLegacyDequantizer { + + DequantizerQ80(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i) { + bits.b[0] = vld1q_s8(x[i].qs); + bits.b[1] = vld1q_s8(x[i].qs+16); + } + + inline float16x4_t new_block(int i) { + ggml_half aux[4]; + for (int k = 0; k < 4; ++k) { + aux[k] = x[4*i+k].d; + bits.b[2*k+0] = vld1q_s8(x[4*i+k].qs); + bits.b[2*k+1] = vld1q_s8(x[4*i+k].qs+16); + } + return vld1_f16((const float16_t *)aux); + } + +}; + +// TODO: handle case where row size is not a multiple of 128 +struct DequantizerQ80_x4 final : public BaseLegacyDequantizer { + + DequantizerQ80_x4(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i) { + bits.b[0] = vld1q_s8(x[i].qs); + bits.b[1] = vld1q_s8(x[i].qs+16); + } + + inline float16x4_t new_block(int i) { + auto scale = vld1_f16((const float16_t *)x[i].d); + for (int k = 0; k < 4; ++k) { + bits.b[2*k+0] = vld1q_s8(x[i].qs+32*k); + bits.b[2*k+1] = vld1q_s8(x[i].qs+32*k+16); + } + return scale; + } + +}; + +struct DequantizerQ51 final : public BaseLegacyDequantizer { + + DequantizerQ51(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {} + + inline void prepare1(int i, int8x16_t * q) const { + bits.prepare1(x[i].qs, q); + auto qh = x[i].qh; + q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_bytes(qh+0)))); + q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_bytes(qh+2)))); + } + inline void prepare1(int i) { + bits.prepare1(x[i].qs, bits.b); + } + + inline float16x8_t new_block(int i) { + uint32_t aux32[4]; + const uint32_t * s32 = (const uint32_t *)&x[4*i].d; + for (int k = 0; k < 4; ++k) { + aux32[k] = *s32; s32 += sizeof(block_q5_1)/4; + prepare1(4*i+k, bits.b + 2*k); + } + return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle))); + } + + HighBit5Legacy hbits; + + const uint8x16_t mh = vdupq_n_u8(0x10); + const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302}; + +}; + +template +inline void sum_4(int i, Dequantizer& deq, const Q8& q8, const float16x4_t * sc16, float32x4_t * acc) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto pall = sum_4_blocks(deq.bits.b, q8.quant_data(iy, i)); + auto scale = vcvt_f32_f16(sc16[iy]); + acc[iy] = vmlaq_f32(acc[iy], scale, vcvtq_f32_s32(pall)); + } +} + +template +inline void sum_4(int i, Dequantizer& deq1, Dequantizer& deq2, const Q8& q8, const float16x4_t * sc16, float32x4_t * acc) { + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + auto pall = sum_4_blocks(deq1.bits.b, deq2.bits.b, q8.quant_data(iy, i)); + auto scale1 = vcvt_f32_f16(sc16[iy]); + auto scale2 = vcvt_f32_f16(sc16[iy+Q8::nrc_y]); + acc[iy] = vmlaq_f32(acc[iy], scale1, vcvtq_f32_s32(pall.val[0])); + acc[iy+Q8::nrc_y] = vmlaq_f32(acc[iy+Q8::nrc_y], scale2, vcvtq_f32_s32(pall.val[1])); + } +} + +template +inline void mul_mat_qX_Y_q8_Y(int n, Dequantizer& deq, Q8& q8, const DataInfo& info, int nrc_x) { + const int nb = n / QK4_1; + + float16x4_t sc16[Q8::nrc_y]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq.new_row(ix); + + float32x4_t acc[Q8::nrc_y]; + for (int iy = 0; iy < Q8::nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f); + + for (int i = 0; i < nb/4; ++i) { + q8.process_scales(i, deq, sc16, acc); + sum_4(i, deq, q8, sc16, acc); + } + //for (int i = 4*(nb/4); i < nb; ++i) { + // q8.process_1_block(i, deq, acc); + //} + + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + info.store(ix, iy, vaddvq_f32(acc[iy])); + } + } +} + +template +inline void mul_mat_qX_Y_q8_Y_IK(int n, Dequantizer& deq1, Dequantizer& deq2, Q8& q8, const DataInfo& info, int nrc_x) { + const int nb = n / QK4_1; + + float16x4_t sc16[2*Q8::nrc_y]; + float32x4_t acc[2*Q8::nrc_y]; + + for (int ix = 0; ix < nrc_x; ix += 2) { + + deq1.new_row(ix+0); + deq2.new_row(ix+1); + + for (int iy = 0; iy < 2*Q8::nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f); + + for (int i = 0; i < nb/4; ++i) { + q8.process_scales(i, deq1, deq2, sc16, acc); + sum_4(i, deq1, deq2, q8, sc16, acc); + } + //for (int i = 4*(nb/4); i < nb; ++i) { + // q8.process_1_block(i, deq, acc); + //} + + for (int iy = 0; iy < Q8::nrc_y; ++iy) { + info.store(ix+0, iy, vaddvq_f32(acc[iy])); + info.store(ix+1, iy, vaddvq_f32(acc[iy+Q8::nrc_y])); + } + } +} + +template +inline void mul_mat_qX_Y_q8_Y_1(int n, Dequantizer& deq1, Dequantizer& deq2, Q8& q8, const DataInfo& info, int nrc_x) { + const int nb = n / QK4_1; + + float16x4_t sc16[2]; + + for (int ix = 0; ix < nrc_x; ++ix) { + + deq1.new_row(ix); + deq2.new_row(ix); + + float32x4_t acc[2] = { vdupq_n_f32(0.f), vdupq_n_f32(0.f) }; + + for (int i = 0; i < nb/8; ++i) { + q8.process_scales(2*i+0, deq1, sc16+0, acc+0); + q8.process_scales(2*i+1, deq2, sc16+1, acc+1); + sum_4(2*i+0, deq1, q8, sc16+0, acc+0); + sum_4(2*i+1, deq2, q8, sc16+1, acc+1); + } + for (int i = 2*(nb/8); i < nb/4; ++i) { + q8.process_scales(i, deq1, sc16, acc); + sum_4(i, deq1, q8, sc16, acc); + } + //for (int i = 4*(nb/4); i < nb; ++i) { + // q8.process_1_block(i, deq1, acc); + //} + + info.store(ix, 0, vaddvq_f32(vaddq_f32(acc[0], acc[1]))); + } +} + +template +static void mul_mat_qX_1_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + Q81 q8(info); + if constexpr (nrc_y == 1) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x); + } else { + if (nrc_x%2 == 0) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + mul_mat_qX_Y_q8_Y_IK(n, deq1, deq2, q8, info, nrc_x); + } else { + Dequantizer deq(vx, bx); + mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x); + } + //Dequantizer deq(vx, bx); + //mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x); + } +} + +template +static void mul_mat_qX_0_q8_0(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + Q80 q8(info); + if constexpr (nrc_y == 1) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x); + } else { + if (nrc_x%2 == 0) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + mul_mat_qX_Y_q8_Y_IK(n, deq1, deq2, q8, info, nrc_x); + } else { + Dequantizer deq(vx, bx); + mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x); + } + } +} + +template +static void mul_mat_qX_1_q8_1_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + Q81<1> q8(info); + mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x); +} + +template +static void mul_mat_qX_0_q8_0_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + Dequantizer deq1(vx, bx), deq2(vx, bx); + Q80<1> q8(info); + mul_mat_qX_Y_q8_Y(n, deq1, deq2, q8, info, nrc_x); +} + +struct QF16Base { + constexpr static int k_step = 8; + using Data = float16x8_t; + using Acc = float16x8_t; + static inline Data load(const __fp16 * x) { return vld1q_f16(x); } + static inline Data load4(const __fp16 * x) { return vcombine_f16(vld1_f16(x), vdup_n_f16(0)); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return vfmaq_f16(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return vmulq_f16(y, x); + } + //constexpr static int k_step = 16; + //using Data = float16x8x2_t; + //static inline Data load(const __fp16 * x) { return vld1q_f16_x2(x); } + //static inline Acc acc(Acc prev, const Data& y, const Data& x) { + // return vfmaq_f16(vfmaq_f16(prev, y.val[0], x.val[0]), y.val[1], x.val[1]); + //} + //static inline Acc acc_first(const Data& y, const Data& x) { + // return vfmaq_f16(vmulq_f16(y.val[0], x.val[0]), y.val[1], x.val[1]); + //} + static inline float hsum(Acc acc) { + float32x4_t sum = vcvt_f32_f16(vadd_f16(vget_low_f16(acc), vget_high_f16(acc))); + return vaddvq_f32(sum); + } +}; +template struct QF16 final : public QF16Base { + using Base = QF16Base; + constexpr static int nrc_y = nrc; + QF16(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const __fp16 *)info.src1_row(iy); + } + QF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const __fp16 *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load4(y[iy] + 4*i); } + IQK_ALWAYS_INLINE float16x8x4_t loadx(int iy, int i) const { return vld1q_f16_x4(y[iy] + 4*k_step*i); } + const __fp16 * y[nrc_y]; +}; + +struct QBF16Base { + constexpr static int k_step = 4; + using Data = float32x4_t; + using Acc = float32x4_t; + static inline Data load(const uint16_t * x) { return vreinterpretq_f32_u32(vshlq_n_u32(vmovl_u16(vld1_u16(x)), 16)); } + static inline Data load4(const uint16_t * x) { return load(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { + return vfmaq_f32(prev, y, x); + } + static inline Acc acc_first(const Data& y, const Data& x) { + return vmulq_f32(y, x); + } + static inline float hsum(Acc acc) { return vaddvq_f32(acc); } +}; +template struct QBF16 final : public QBF16Base { + using Base = QBF16Base; + constexpr static int nrc_y = nrc; + QBF16(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const uint16_t *)info.src1_row(iy); + } + QBF16(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const uint16_t *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load(y[iy] + 4*i); } + const uint16_t * y[nrc_y]; +}; + +struct QF32Base { + constexpr static int k_step = 4; + using Data = float32x4_t; + using Acc = float32x4_t; + static inline Data load(const float * x) { return vld1q_f32(x); } + static inline Data load4(const float * x) { return load(x); } + static inline Acc acc(Acc prev, const Data& y, const Data& x) { return vfmaq_f32(prev, y, x); } + static inline Acc acc_first(const Data& y, const Data& x) { return vmulq_f32(y, x); } + static inline float hsum(Acc acc) { return vaddvq_f32(acc); } +}; +template struct QF32 final : public QF32Base { + using Base = QF32Base; + constexpr static int nrc_y = nrc; + QF32(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const float *)info.src1_row(iy); + } + QF32(const char * cx, size_t bx) { + for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const float *)(cx + iy*bx); + } + IQK_ALWAYS_INLINE Data load1(int iy, int i) const { return load(y[iy] + k_step*i); } + IQK_ALWAYS_INLINE Data load_tail(int iy, int i) const { return load(y[iy] + 4*i); } + const float * y[nrc_y]; +}; + +template +IQK_NOINLINE void mul_mat_Qx_Qy_NxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + GGML_ASSERT(Qx::Base::k_step == Qy::Base::k_step); + int nb = n/Qx::Base::k_step; + Qy y(info); + Qx x(cx + ix0*bx, bx); + typename Qx::Base::Data xv[Qx::nrc_y]; + typename Qx::Base::Acc acc[Qx::nrc_y*Qy::nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = Qx::Base::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = Qx::Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc(acc[Qx::nrc_y*iy + ix], yv, xv[ix]); + } + } + if constexpr (Qx::Base::k_step > 4 && !is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (Qx::Base::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = Qx::Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < Qy::nrc_y; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < Qx::nrc_y; ++ix) acc[Qx::nrc_y*iy + ix] = Qx::Base::acc(acc[Qx::nrc_y*iy + ix], yv, xv[ix]); + } + } + } + for (int iy = 0; iy < Qy::nrc_y; ++iy) for (int ix = 0; ix < Qx::nrc_y; ++ix) info.store(ix0+ix, iy, Qx::Base::hsum(acc[Qx::nrc_y*iy+ix])); +} + +template +IQK_NOINLINE void mul_mat_f16_f16_NxN(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + assert(n%QF16Base::k_step == 0); + int nb = n/QF16Base::k_step; + QF16 y(info); + QF16 x(cx + ix0*bx, bx); + QF16Base::Data xv[nrc_x]; + QF16Base::Acc acc[nrc_x*nrc_y]; + auto yv = y.load1(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, 0); + acc[ix] = QF16Base::acc_first(yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, 0); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc_first(yv, xv[ix]); + } + for (int i = 1; i < nb; ++i) { + yv = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load1(ix, i); + acc[ix] = QF16Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load1(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + if constexpr (!is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (QF16Base::k_step/4)*nb; i < nb4; ++i) { + yv = y.load_tail(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + xv[ix] = x.load_tail(ix, i); + acc[ix] = QF16Base::acc(acc[ix], yv, xv[ix]); + } + for (int iy = 1; iy < nrc_y; ++iy) { + yv = y.load_tail(iy, i); + for (int ix = 0; ix < nrc_x; ++ix) acc[nrc_x*iy + ix] = QF16Base::acc(acc[nrc_x*iy + ix], yv, xv[ix]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) for (int ix = 0; ix < nrc_x; ++ix) info.store(ix0+ix, iy, QF16Base::hsum(acc[nrc_x*iy+ix])); +} + +template typename Qx> +void mul_mat_Qx_Qy_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + constexpr int k_nx = 5; + const char * cx = (const char *)vx; + if (n%Qx::Base::k_step == 0) { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_NxN, true>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_Qx_Qy_NxN, true>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_NxN, true>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_NxN, true>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_NxN, true>(n, cx, bx, last_x, info); break; + } + } else { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_Qx_Qy_NxN, false>(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_Qx_Qy_NxN, false>(n, cx, bx, last_x, info); break; + case 2: mul_mat_Qx_Qy_NxN, false>(n, cx, bx, last_x, info); break; + case 3: mul_mat_Qx_Qy_NxN, false>(n, cx, bx, last_x, info); break; + case 4: mul_mat_Qx_Qy_NxN, false>(n, cx, bx, last_x, info); break; + } + } +} + +template +void mul_mat_f16_f16_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + constexpr int k_nx = 5; + const char * cx = (const char *)vx; + if (n%QF16Base::k_step == 0) { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_f16_f16_NxN(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 2: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 3: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 4: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + } + } else { + for (int ix = 0; ix < nrc_x/k_nx; ++ix) { + mul_mat_f16_f16_NxN(n, cx, bx, ix*k_nx, info); + } + int last_x = k_nx*(nrc_x/k_nx); + if (last_x == nrc_x) return; + int nx = nrc_x - last_x; + switch (nx) { + case 1: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 2: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 3: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + case 4: mul_mat_f16_f16_NxN(n, cx, bx, last_x, info); break; + } + } +} + +template +IQK_NOINLINE void mul_mat_f16_f16_Nx1(int n, const char * cx, size_t bx, int ix0, const DataInfo& info) { + assert(n%QF16Base::k_step == 0); + int nb = n/QF16Base::k_step; + QF16<1> y(info); + QF16 x(cx + ix0*bx, bx); + QF16Base::Acc acc[4*nrc_x]; + auto yv = y.loadx(0, 0); + for (int ix = 0; ix < nrc_x; ++ix) { + for (int k = 0; k < 4; ++k) { + auto xv = x.load1(ix, k); + acc[4*ix+k] = QF16Base::acc_first(yv.val[k], xv); + } + } + for (int i = 1; i < nb/4; ++i) { + yv = y.loadx(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + for (int k = 0; k < 4; ++k) { + auto xv = x.load1(ix, 4*i+k); + acc[4*ix+k] = QF16Base::acc(acc[4*ix+k], yv.val[k], xv); + } + } + } + for (int i = 4*(nb/4); i < nb; ++i) { + auto yv1 = y.load1(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + auto xv1 = x.load1(ix, i); + acc[4*ix] = QF16Base::acc(acc[4*ix], yv1, xv1); + } + } + if constexpr (!is_multiple_of_k_step) { + int nb4 = n/4; + for (int i = (QF16Base::k_step/4)*nb; i < nb4; ++i) { + auto yv1 = y.load_tail(0, i); + for (int ix = 0; ix < nrc_x; ++ix) { + auto xv1 = x.load_tail(ix, i); + acc[4*ix] = QF16Base::acc(acc[4*ix], yv1, xv1); + } + } + } + for (int ix = 0; ix < nrc_x; ++ix) { + auto v1 = vaddq_f16(acc[4*ix+0], acc[4*ix+1]); + auto v2 = vaddq_f16(acc[4*ix+2], acc[4*ix+3]); + info.store(ix0+ix, 0, QF16Base::hsum(vaddq_f16(v1, v2))); + } +} + +// At least on my M2-Max the version below, which does the multiplication row-by-row, is faster. +// But let's keep this version commented out for now. +//void mul_mat_f16_f16_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { +// GGML_ASSERT(n%4 == 0); +// constexpr int k_nx = 2; +// const char * cx = (const char *)vx; +// if (n%QF16Base::k_step == 0) { +// for (int ix = 0; ix < nrc_x/k_nx; ++ix) { +// mul_mat_f16_f16_Nx1(n, cx, bx, ix*k_nx, info); +// } +// int last_x = k_nx*(nrc_x/k_nx); +// if (last_x == nrc_x) return; +// int nx = nrc_x - last_x; +// switch (nx) { +// case 1: mul_mat_f16_f16_Nx1<1, true>(n, cx, bx, last_x, info); break; +// //case 2: mul_mat_f16_f16_Nx1<2, true>(n, cx, bx, last_x, info); break; +// //case 3: mul_mat_f16_f16_Nx1<3, true>(n, cx, bx, last_x, info); break; +// } +// } else { +// for (int ix = 0; ix < nrc_x/k_nx; ++ix) { +// mul_mat_f16_f16_Nx1(n, cx, bx, ix*k_nx, info); +// } +// int last_x = k_nx*(nrc_x/k_nx); +// if (last_x == nrc_x) return; +// int nx = nrc_x - last_x; +// switch (nx) { +// case 1: mul_mat_f16_f16_Nx1<1, false>(n, cx, bx, last_x, info); break; +// //case 2: mul_mat_f16_f16_Nx1<2, false>(n, cx, bx, last_x, info); break; +// //case 3: mul_mat_f16_f16_Nx1<3, false>(n, cx, bx, last_x, info); break; +// } +// } +//} + +void mul_mat_f16_f16_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(n%4 == 0); + const char * cx = (const char *)vx; + if (n%QF16Base::k_step == 0) { + for (int ix = 0; ix < nrc_x; ++ix) { + mul_mat_f16_f16_Nx1<1, true>(n, cx, bx, ix, info); + } + } else { + for (int ix = 0; ix < nrc_x; ++ix) { + mul_mat_f16_f16_Nx1<1, false>(n, cx, bx, ix, info); + } + } +} + +template struct Q8_K64 { + + constexpr static int nrc_y = nrc; + + Q8_K64(const DataInfo& info) { + for (int iy = 0; iy < nrc_y; ++iy) { + auto dptr = (const float *)info.src1_row(iy); + std::memcpy(d + 8*iy, dptr, 8*sizeof(float)); + y[iy] = (const int8_t *)(dptr + 8); + } + } + + inline int8x16x4_t load_quants64(int iy, int i, int j) const { return vld1q_s8_x4(y[iy] + 128*i + 64*j); } + inline int8x16x2_t load_quants(int iy, int i, int j) const { return vld1q_s8_x2(y[iy] + 128*i + 32*j); } + inline float32x4_t scale(int iy) const { return vld1q_f32(d + 8*iy); } + inline float32x4_t minus(int iy) const { return vld1q_f32(d + 8*iy + 4); } + + float d[8*nrc_y]; + const int8_t * y[nrc_y]; +}; + +struct DequantizerIQ1BN { + const uint8x16_t m1 = vdupq_n_u8(1); + + static inline uint8x16x4_t load_shuffles() { + static const uint8_t data[64] = {0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 12, + 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 12, + 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 12, + 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 12}; + return vld1q_u8_x4(data); + } + static inline uint8x16x4_t load_mult() { + static const uint8_t data[64] = {81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 81, + 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 27, + 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 9, + 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 81, 27, 9, 3, 1, 3}; + return vld1q_u8_x4(data); + } + const uint8x16x4_t shuff = load_shuffles(); + const uint8x16x4_t mult = load_mult(); + + IQK_ALWAYS_INLINE void prepare_iq1bn_quants(const block_iq1_bn * x, int8x16x4_t& v) const { + auto data = vld1q_u8((const uint8_t *)x); + for (int k = 0; k < 4; ++k) { + auto val = vmulq_u8(vqtbl1q_u8(data, shuff.val[k]), mult.val[k]); + val = vshrq_n_u8(vhaddq_u8(val, vshrq_n_u8(val, 1)), 6); + v.val[k] = vsubq_s8(vreinterpretq_s8_u8(val), m1); + } + } + + IQK_ALWAYS_INLINE void prepare_iq1bn_quants_nosub(const block_iq1_bn * x, int8x16x4_t& v) const { + auto data = vld1q_u8((const uint8_t *)x); + for (int k = 0; k < 4; ++k) { + auto val = vmulq_u8(vqtbl1q_u8(data, shuff.val[k]), mult.val[k]); + v.val[k] = vreinterpretq_s8_u8(vshrq_n_u8(vhaddq_u8(val, vshrq_n_u8(val, 1)), 6)); + } + } +}; + +template +static void mul_mat_iq1bn_q8_K64(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_IQ1BN; + + Q8_K64 q8(info); + DequantizerIQ1BN deq; + + int32x4_t accd[nrc_y]; + int8x16x4_t v1, v2; + + float scale; + + for (int ix = 0; ix < nrc_x; ++ix) { + + const char * cx = ((const char *)vx + ix*bx); + if constexpr (is_iq1_tn) { + scale = GGML_FP16_TO_FP32(*(const ggml_half *)cx); + cx += sizeof(ggml_half); + } + + const block_iq1_bn * x = (const block_iq1_bn *)cx; + + if constexpr (nrc_y == 1) { + int32x4_t acc[4] = {}; + for (int i = 0; i < nb/2; ++i) { + deq.prepare_iq1bn_quants_nosub(x+2*i+0, v1); + auto q = q8.load_quants64(0, i, 0); + for (int j = 0; j < 4; ++j) acc[j] = ggml_vdotq_s32(acc[j], q.val[j], v1.val[j]); + deq.prepare_iq1bn_quants_nosub(x+2*i+1, v2); + q = q8.load_quants64(0, i, 1); + for (int j = 0; j < 4; ++j) acc[j] = ggml_vdotq_s32(acc[j], q.val[j], v2.val[j]); + } + accd[0] = vaddq_s32(vaddq_s32(acc[0], acc[1]), vaddq_s32(acc[2], acc[3])); + } + else { + + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = vdupq_n_s32(0); + + for (int i = 0; i < nb/2; ++i) { + + deq.prepare_iq1bn_quants_nosub(x+2*i+0, v1); + deq.prepare_iq1bn_quants_nosub(x+2*i+1, v2); + + for (int iy = 0; iy < nrc_y; ++iy) { + auto q = q8.load_quants(iy, i, 0); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[0]), q.val[1], v1.val[1]); + q = q8.load_quants(iy, i, 1); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[2]), q.val[1], v1.val[3]); + q = q8.load_quants(iy, i, 2); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v2.val[0]), q.val[1], v2.val[1]); + q = q8.load_quants(iy, i, 3); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v2.val[2]), q.val[1], v2.val[3]); + } + } + } + int i = 2*(nb/2); + if (i < nb) { + deq.prepare_iq1bn_quants_nosub(x+i, v1); + if constexpr (nrc_y == 1) { + auto q = q8.load_quants(0, i/2, 0); + for (int j = 0; j < 4; ++j) { + accd[0] = ggml_vdotq_s32(accd[0], q.val[j], v1.val[j]); + } + } else { + for (int iy = 0; iy < nrc_y; ++iy) { + auto q = q8.load_quants(iy, i/2, 0); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[0]), q.val[1], v1.val[1]); + q = q8.load_quants(iy, i/2, 1); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[2]), q.val[1], v1.val[3]); + } + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + if constexpr (is_iq1_tn) { + info.store(ix, iy, -scale * vaddvq_f32(vfmsq_f32(q8.minus(iy), q8.scale(iy), vcvtq_f32_s32(accd[iy])))); + } else { + info.store(ix, iy, -vaddvq_f32(vfmsq_f32(q8.minus(iy), q8.scale(iy), vcvtq_f32_s32(accd[iy])))); + } + } + + } +} + +template +static void mul_mat_iq2bn_q8_K64(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + const int nb = n / QK_IQ1BN; + + Q8_K64 q8(info); + + int32x4_t accd[nrc_y]; + + const auto mask2 = vdupq_n_s8(3); + + for (int ix = 0; ix < nrc_x; ++ix) { + + const block_iq2_bn * x = (const block_iq2_bn *)((const char *)vx + ix*bx); + + if constexpr (nrc_y == 1) { + int8x16x4_t v1; + int32x4_t acc[4] = {}; + for (int i = 0; i < nb/2; ++i) { + for (int j = 0; j < 2; ++j) { + auto q = q8.load_quants64(0, i, j); + auto q2bits = vld1q_u8(x[2*i+j].qs); + v1.val[0] = vandq_s8(q2bits, mask2); + v1.val[1] = vandq_s8(vshrq_n_u8(q2bits, 2), mask2); + v1.val[2] = vandq_s8(vshrq_n_u8(q2bits, 4), mask2); + v1.val[3] = vshrq_n_u8(q2bits, 6); + acc[0] = ggml_vdotq_s32(acc[0], q.val[0], v1.val[0]); + acc[1] = ggml_vdotq_s32(acc[1], q.val[1], v1.val[1]); + acc[2] = ggml_vdotq_s32(acc[2], q.val[2], v1.val[2]); + acc[3] = ggml_vdotq_s32(acc[3], q.val[3], v1.val[3]); + } + } + accd[0] = vaddq_s32(vaddq_s32(acc[0], acc[1]), vaddq_s32(acc[2], acc[3])); + } else { + int8x16x4_t v1, v2; + for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = vdupq_n_s32(0); + for (int i = 0; i < nb/2; ++i) { + auto q2bits = vld1q_u8(x[2*i+0].qs); + v1.val[0] = vandq_s8(q2bits, mask2); + v1.val[1] = vandq_s8(vshrq_n_u8(q2bits, 2), mask2); + v1.val[2] = vandq_s8(vshrq_n_u8(q2bits, 4), mask2); + v1.val[3] = vshrq_n_u8(q2bits, 6); + q2bits = vld1q_u8(x[2*i+1].qs); + v2.val[0] = vandq_s8(q2bits, mask2); + v2.val[1] = vandq_s8(vshrq_n_u8(q2bits, 2), mask2); + v2.val[2] = vandq_s8(vshrq_n_u8(q2bits, 4), mask2); + v2.val[3] = vshrq_n_u8(q2bits, 6); + for (int iy = 0; iy < nrc_y; ++iy) { + auto q = q8.load_quants(iy, i, 0); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[0]), q.val[1], v1.val[1]); + q = q8.load_quants(iy, i, 1); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[2]), q.val[1], v1.val[3]); + q = q8.load_quants(iy, i, 2); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v2.val[0]), q.val[1], v2.val[1]); + q = q8.load_quants(iy, i, 3); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v2.val[2]), q.val[1], v2.val[3]); + } + } + } + int i = 2*(nb/2); + if (i < nb) { + auto q2bits = vld1q_u8(x[i].qs); + int8x16x4_t v1; + v1.val[0] = vandq_s8(q2bits, mask2); + v1.val[1] = vandq_s8(vshrq_n_u8(q2bits, 2), mask2); + v1.val[2] = vandq_s8(vshrq_n_u8(q2bits, 4), mask2); + v1.val[3] = vshrq_n_u8(q2bits, 6); + for (int iy = 0; iy < nrc_y; ++iy) { + auto q = q8.load_quants(iy, i/2, 0); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[0]), q.val[1], v1.val[1]); + q = q8.load_quants(iy, i/2, 1); + accd[iy] = ggml_vdotq_s32(ggml_vdotq_s32(accd[iy], q.val[0], v1.val[2]), q.val[1], v1.val[3]); + } + } + + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, -vaddvq_f32(vfmsq_f32(q8.minus(iy), q8.scale(iy), vcvtq_f32_s32(accd[iy])))); + } + } +} + +template void MulMat::set_functions(MulMat& m) { + if constexpr (std::is_same_v || std::is_same_v || + std::is_same_v || std::is_same_v || + std::is_same_v) { + m.funcs[0] = mul_mat_qX_0_q8_0; + m.funcs[1] = mul_mat_qX_0_q8_0; + m.funcs[2] = mul_mat_qX_0_q8_0; + m.funcs[3] = mul_mat_qX_0_q8_0; + m.funcs[4] = mul_mat_qX_0_q8_0; + m.funcs[5] = mul_mat_qX_0_q8_0; + m.funcs[6] = mul_mat_qX_0_q8_0; + m.funcs[7] = mul_mat_qX_0_q8_0; + } + else if constexpr (std::is_same_v || std::is_same_v) { + m.funcs[0] = mul_mat_qX_1_q8_1; + m.funcs[1] = mul_mat_qX_1_q8_1; + m.funcs[2] = mul_mat_qX_1_q8_1; + m.funcs[3] = mul_mat_qX_1_q8_1; + m.funcs[4] = mul_mat_qX_1_q8_1; + m.funcs[5] = mul_mat_qX_1_q8_1; + m.funcs[6] = mul_mat_qX_1_q8_1; + m.funcs[7] = mul_mat_qX_1_q8_1; + } + else { + m.funcs[0] = mul_mat_qX_K_q8_K_T<1, Dequantizer>; + m.funcs[1] = mul_mat_qX_K_q8_K_T<2, Dequantizer>; + m.funcs[2] = mul_mat_qX_K_q8_K_T<3, Dequantizer>; + m.funcs[3] = mul_mat_qX_K_q8_K_T<4, Dequantizer>; + m.funcs[4] = mul_mat_qX_K_q8_K_T<5, Dequantizer>; + m.funcs[5] = mul_mat_qX_K_q8_K_T<6, Dequantizer>; + m.funcs[6] = mul_mat_qX_K_q8_K_T<7, Dequantizer>; + m.funcs[7] = mul_mat_qX_K_q8_K_T<8, Dequantizer>; + } +} + +bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) { + + if (typeA == GGML_TYPE_F16 && typeB == GGML_TYPE_F16) { + if (ne00%4) return false; + for (auto& f : m.funcs) f = nullptr; + m.funcs[0] = mul_mat_f16_f16_1; + m.funcs[1] = mul_mat_f16_f16_T<2>; + m.funcs[2] = mul_mat_f16_f16_T<3>; + m.funcs[3] = mul_mat_f16_f16_T<4>; + m.funcs[4] = mul_mat_f16_f16_T<5>; + return true; + } + + if (typeA == GGML_TYPE_BF16 && typeB == GGML_TYPE_F32) { + if (ne00%4) return false; + for (auto& f : m.funcs) f = nullptr; + m.funcs[0] = mul_mat_Qx_Qy_T, QBF16>; + m.funcs[1] = mul_mat_Qx_Qy_T, QBF16>; + m.funcs[2] = mul_mat_Qx_Qy_T, QBF16>; + m.funcs[3] = mul_mat_Qx_Qy_T, QBF16>; + m.funcs[4] = mul_mat_Qx_Qy_T, QBF16>; + return true; + } + + auto expected_Btype = GGML_TYPE_Q8_K; + + switch (typeA) { + case GGML_TYPE_Q2_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ2_TN: + //MulMat::set_functions(m); + m.funcs[0] = mul_mat_iq2tn_K_q8_K_1; + m.funcs[1] = mul_mat_iq2tn_K_q8_K_T<2>; + m.funcs[2] = mul_mat_iq2tn_K_q8_K_T<3>; + m.funcs[3] = mul_mat_iq2tn_K_q8_K_T<4>; + m.funcs[4] = mul_mat_iq2tn_K_q8_K_T<5>; + m.funcs[5] = mul_mat_iq2tn_K_q8_K_T<6>; + m.funcs[6] = mul_mat_iq2tn_K_q8_K_T<7>; + m.funcs[7] = mul_mat_iq2tn_K_q8_K_T<8>; + break; + case GGML_TYPE_Q3_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_Q4_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_Q5_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_Q6_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ4_XS: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ4_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ5_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ6_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ2_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ3_K: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ2_XXS: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ2_XS: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ2_S: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ3_XXS: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ3_S: + MulMat::set_functions(m); + break; + case GGML_TYPE_IQ1_BN: + m.funcs[0] = mul_mat_iq1bn_q8_K64<1, false>; + m.funcs[1] = mul_mat_iq1bn_q8_K64<2, false>; + m.funcs[2] = mul_mat_iq1bn_q8_K64<3, false>; + m.funcs[3] = mul_mat_iq1bn_q8_K64<4, false>; + m.funcs[4] = mul_mat_iq1bn_q8_K64<5, false>; + m.funcs[5] = mul_mat_iq1bn_q8_K64<6, false>; + m.funcs[6] = mul_mat_iq1bn_q8_K64<7, false>; + m.funcs[7] = mul_mat_iq1bn_q8_K64<8, false>; + expected_Btype = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_IQ1_TN: + m.funcs[0] = mul_mat_iq1bn_q8_K64<1, true>; + m.funcs[1] = mul_mat_iq1bn_q8_K64<2, true>; + m.funcs[2] = mul_mat_iq1bn_q8_K64<3, true>; + m.funcs[3] = mul_mat_iq1bn_q8_K64<4, true>; + m.funcs[4] = mul_mat_iq1bn_q8_K64<5, true>; + m.funcs[5] = mul_mat_iq1bn_q8_K64<6, true>; + m.funcs[6] = mul_mat_iq1bn_q8_K64<7, true>; + m.funcs[7] = mul_mat_iq1bn_q8_K64<8, true>; + expected_Btype = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_IQ2_BN: + m.funcs[0] = mul_mat_iq2bn_q8_K64<1>; + m.funcs[1] = mul_mat_iq2bn_q8_K64<2>; + m.funcs[2] = mul_mat_iq2bn_q8_K64<3>; + m.funcs[3] = mul_mat_iq2bn_q8_K64<4>; + m.funcs[4] = mul_mat_iq2bn_q8_K64<5>; + m.funcs[5] = mul_mat_iq2bn_q8_K64<6>; + m.funcs[6] = mul_mat_iq2bn_q8_K64<7>; + m.funcs[7] = mul_mat_iq2bn_q8_K64<8>; + expected_Btype = GGML_TYPE_Q8_K64; + break; + case GGML_TYPE_Q4_0: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_0; + break; + case GGML_TYPE_Q4_1: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q5_0: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_0; + break; + case GGML_TYPE_Q5_1: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_1; + break; + case GGML_TYPE_Q6_0: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_0; + break; + case GGML_TYPE_Q8_0: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_0; + break; + case GGML_TYPE_IQ4_NL: + MulMat::set_functions(m); + expected_Btype = GGML_TYPE_Q8_0; + break; + default: + return false; + } + + return typeB == expected_Btype; +} + +} + +#endif // __aarch64__ + +namespace { + +#if defined(__ARM_NEON) && defined(__aarch64__) +// copy-pasted from Justine Tunney's contribution to llama.cpp +// adapted from arm limited optimized routine +// the maximum error is 1.45358 plus 0.5 ulps +// numbers above 88.38 will flush to infinity +// numbers beneath -103.97 will flush to zero +inline float32x4_t v_expf(float32x4_t x) { + const float32x4_t r = vdupq_n_f32(0x1.8p23f); + const float32x4_t z = vfmaq_f32(r, x, vdupq_n_f32(0x1.715476p+0f)); + const float32x4_t n = vsubq_f32(z, r); + const float32x4_t b = vfmsq_f32(vfmsq_f32(x, n, vdupq_n_f32(0x1.62e4p-1f)), n, + vdupq_n_f32(0x1.7f7d1cp-20f)); + const uint32x4_t e = vshlq_n_u32(vreinterpretq_u32_f32(z), 23); + const float32x4_t k = vreinterpretq_f32_u32(vaddq_u32(e, vreinterpretq_u32_f32(vdupq_n_f32(1)))); + const uint32x4_t c = vcagtq_f32(n, vdupq_n_f32(126)); + const float32x4_t u = vmulq_f32(b, b); + const float32x4_t j = vfmaq_f32( + vmulq_f32(vdupq_n_f32(0x1.ffffecp-1f), b), + vfmaq_f32(vfmaq_f32(vdupq_n_f32(0x1.fffdb6p-2f), vdupq_n_f32(0x1.555e66p-3f), b), + vfmaq_f32(vdupq_n_f32(0x1.573e2ep-5f), vdupq_n_f32(0x1.0e4020p-7f), b), u), u); + if (!vpaddd_u64(vreinterpretq_u64_u32(c))) + return vfmaq_f32(k, j, k); + const uint32x4_t d = vandq_u32(vclezq_f32(n), vdupq_n_u32(0x82000000)); + const float32x4_t s1 = vreinterpretq_f32_u32(vaddq_u32(d, vdupq_n_u32(0x7f000000))); + const float32x4_t s2 = vreinterpretq_f32_u32(vsubq_u32(e, d)); + return vbslq_f32(vcagtq_f32(n, vdupq_n_f32(192)), vmulq_f32(s1, s1), + vbslq_f32(c, vmulq_f32(vfmaq_f32(s2, s2, j), s1), vfmaq_f32(k, k, j))); +} +inline float16x8_t v_expf(float16x8_t x) { + auto val1 = v_expf(vcvt_f32_f16(vget_low_f16(x))); + auto val2 = v_expf(vcvt_f32_f16(vget_high_f16(x))); + return vcombine_f16(vcvt_f16_f32(val1), vcvt_f16_f32(val2)); +} +inline float32x4_t v_tanh(float32x4_t x) { + const float32x4_t one = vdupq_n_f32(1.0f); + const float32x4_t two_x = vmulq_f32(x, vdupq_n_f32(2.f)); + const float32x4_t exp_two_x = v_expf(two_x); + const uint32x4_t mask = vcgtq_f32(x, vdupq_n_f32(10.f)); + const float32x4_t res = vdivq_f32(vsubq_f32(exp_two_x, one), vaddq_f32(exp_two_x, one)); + return vreinterpretq_f32_u32(vorrq_u32(vandq_u32(vreinterpretq_u32_f32(one), mask), vbicq_u32(vreinterpretq_u32_f32(res), mask))); + //return vdivq_f32(vsubq_f32(exp_two_x, one), vaddq_f32(exp_two_x, one)); +} +inline float32x4_t v_tanh(float16x8_t x) { + auto val1 = v_tanh(vcvt_f32_f16(vget_low_f16(x))); + auto val2 = v_tanh(vcvt_f32_f16(vget_high_f16(x))); + return vcombine_f16(vcvt_f16_f32(val1), vcvt_f16_f32(val2)); +} +#endif + +#if defined(__AVX512F__) && defined(__AVX512DQ__) + +// copy-pasted from Justine Tunney's contribution to llama.cpp +// adapted from arm limited optimized routine +// the maximum error is 1.45358 plus 0.5 ulps +// numbers above 88.38 will flush to infinity +// numbers beneath -103.97 will flush to zero +inline __m512 v_expf(__m512 x) { + const __m512 r = _mm512_set1_ps(0x1.8p23f); + const __m512 z = _mm512_fmadd_ps(x, _mm512_set1_ps(0x1.715476p+0f), r); + const __m512 n = _mm512_sub_ps(z, r); + const __m512 b = + _mm512_fnmadd_ps(n, _mm512_set1_ps(0x1.7f7d1cp-20f), + _mm512_fnmadd_ps(n, _mm512_set1_ps(0x1.62e4p-1f), x)); + const __mmask16 d = + _mm512_cmp_ps_mask(_mm512_abs_ps(n), _mm512_set1_ps(192), _CMP_GT_OQ); + const __m512 u = _mm512_mul_ps(b, b); + const __m512 j = _mm512_fmadd_ps( + _mm512_fmadd_ps(_mm512_fmadd_ps(_mm512_set1_ps(0x1.0e4020p-7f), b, + _mm512_set1_ps(0x1.573e2ep-5f)), + u, + _mm512_fmadd_ps(_mm512_set1_ps(0x1.555e66p-3f), b, + _mm512_set1_ps(0x1.fffdb6p-2f))), + u, + _mm512_fmadd_ps(_mm512_set1_ps(0x1.ffffecp-1f), b, _mm512_set1_ps(1.0F))); + const __m512 res = _mm512_scalef_ps(j, n); + if (_mm512_kortestz(d, d)) + return res; + const __m512 zero = _mm512_setzero_ps(); + const __m512 alt = _mm512_mask_blend_ps( + _mm512_cmp_ps_mask(n, zero, _CMP_LE_OQ), _mm512_set1_ps(INFINITY), zero); + return _mm512_mask_blend_ps(d, res, alt); +} +inline __m512 v_tanh(__m512 x) { + const __m512 one = _mm512_set1_ps(1.0f); + const __m512 exp_two_x = v_expf(_mm512_mul_ps(x, _mm512_set1_ps(2.f))); + const __mmask16 mask = _mm512_cmp_ps_mask(x, _mm512_set1_ps(10.f), _CMP_GT_OQ); + const __m512 res = _mm512_div_ps(_mm512_sub_ps(exp_two_x, one), _mm512_add_ps(exp_two_x, one)); + return _mm512_mask_blend_ps(mask, res, one); +} +#endif + +#if defined(__AVX2__) && defined(__FMA__) + +// adapted from arm limited optimized routine +// the maximum error is 1.45358 plus 0.5 ulps +// numbers above 88.38 will flush to infinity +// numbers beneath -103.97 will flush to zero +inline __m256 v_expf(__m256 x) { + const __m256 r = _mm256_set1_ps(0x1.8p23f); + const __m256 z = _mm256_fmadd_ps(x, _mm256_set1_ps(0x1.715476p+0f), r); + const __m256 n = _mm256_sub_ps(z, r); + const __m256 b = _mm256_fnmadd_ps(n, _mm256_set1_ps(0x1.7f7d1cp-20f), + _mm256_fnmadd_ps(n, _mm256_set1_ps(0x1.62e4p-1f), x)); + const __m256i e = _mm256_slli_epi32(_mm256_castps_si256(z), 23); + const __m256 k = _mm256_castsi256_ps( + _mm256_add_epi32(e, _mm256_castps_si256(_mm256_set1_ps(1)))); + const __m256i c = _mm256_castps_si256( + _mm256_cmp_ps(_mm256_andnot_ps(_mm256_set1_ps(-0.f), n), + _mm256_set1_ps(126), _CMP_GT_OQ)); + const __m256 u = _mm256_mul_ps(b, b); + const __m256 j = _mm256_fmadd_ps(_mm256_fmadd_ps(_mm256_fmadd_ps(_mm256_set1_ps(0x1.0e4020p-7f), b, + _mm256_set1_ps(0x1.573e2ep-5f)), u, + _mm256_fmadd_ps(_mm256_set1_ps(0x1.555e66p-3f), b, + _mm256_set1_ps(0x1.fffdb6p-2f))), + u, _mm256_mul_ps(_mm256_set1_ps(0x1.ffffecp-1f), b)); + if (!_mm256_movemask_ps(_mm256_castsi256_ps(c))) + return _mm256_fmadd_ps(j, k, k); + const __m256i g = _mm256_and_si256( + _mm256_castps_si256(_mm256_cmp_ps(n, _mm256_setzero_ps(), _CMP_LE_OQ)), + _mm256_set1_epi32(0x82000000u)); + const __m256 s1 = + _mm256_castsi256_ps(_mm256_add_epi32(g, _mm256_set1_epi32(0x7f000000u))); + const __m256 s2 = _mm256_castsi256_ps(_mm256_sub_epi32(e, g)); + const __m256i d = _mm256_castps_si256( + _mm256_cmp_ps(_mm256_andnot_ps(_mm256_set1_ps(-0.f), n), + _mm256_set1_ps(192), _CMP_GT_OQ)); + return _mm256_or_ps( + _mm256_and_ps(_mm256_castsi256_ps(d), _mm256_mul_ps(s1, s1)), + _mm256_andnot_ps( + _mm256_castsi256_ps(d), + _mm256_or_ps( + _mm256_and_ps(_mm256_castsi256_ps(c), + _mm256_mul_ps(_mm256_fmadd_ps(s2, j, s2), s1)), + _mm256_andnot_ps(_mm256_castsi256_ps(c), _mm256_fmadd_ps(k, j, k))))); +} +inline __m256 v_tanh(__m256 x) { + const __m256 one = _mm256_set1_ps(1.0f); + const __m256 exp_two_x = v_expf(_mm256_mul_ps(x, _mm256_set1_ps(2.f))); + const __m256 res = _mm256_div_ps(_mm256_sub_ps(exp_two_x, one), _mm256_add_ps(exp_two_x, one)); + const __m256 mask = _mm256_cmp_ps(x, _mm256_set1_ps(10.f), _CMP_GT_OQ); + return _mm256_or_ps(_mm256_and_ps(mask, one), _mm256_andnot_ps(mask, res)); +} + +#endif +} // namespace + +namespace { + +template +struct BaseHelper { + BaseHelper(const char * data, int stride) : data(data), block(data), stride(stride) {} + + inline void set_block(int k1) { block = data + k1*k_step*stride; } + inline void reset_block() { block = data; } + inline void next_block() { block += k_step*stride; } + inline const char * lblock(int l1) const { return block + l1*stride; } + + const char * data; + const char * block; + int stride; + +}; + +struct F16 { +#ifdef HAVE_FANCY_SIMD + using Data = __m512; + constexpr static int block_size = 16; + constexpr static int num_registers = 32; + constexpr static int q_step = 8; + static inline Data zero() { return _mm512_setzero_ps(); } + static inline Data load(const char * ptr, int i) { return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)ptr + i)); } + static inline Data set1(float val) { return _mm512_set1_ps(val); } + static inline Data mul(Data v1, Data v2) { return _mm512_mul_ps(v1, v2); } + static inline Data sub(Data v1, Data v2) { return _mm512_sub_ps(v1, v2); } + static inline Data load(const float * ptr) { return _mm512_loadu_ps(ptr); } + static inline void store(float * ptr, Data data) { _mm512_storeu_ps(ptr, data); } + static inline float reduce_max(Data data) { return _mm512_reduce_max_ps(data); } + static inline float reduce_add(Data data) { return _mm512_reduce_add_ps(data); } + static inline Data fmadd(Data prev, Data v1, Data v2) { return _mm512_fmadd_ps(v1, v2, prev); } + template static inline float reduce_max(const Data * data) { + return reduce_T(data); + } + template static inline float reduce_add(const Data * data) { + return reduce_T(data); + } +#elif defined __AVX2__ + using Data = __m256; + constexpr static int block_size = 8; + constexpr static int num_registers = 16; + constexpr static int q_step = 8; + static inline Data zero() { return _mm256_setzero_ps(); } + static inline Data load(const char * ptr, int i) { return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)ptr + i)); } + static inline Data set1(float val) { return _mm256_set1_ps(val); } + static inline Data mul(Data v1, Data v2) { return _mm256_mul_ps(v1, v2); } + static inline Data load(const float * ptr) { return _mm256_loadu_ps(ptr); } + static inline Data sub(Data v1, Data v2) { return _mm256_sub_ps(v1, v2); } + static inline void store(float * ptr, Data data) { _mm256_storeu_ps(ptr, data); } + static inline Data fmadd(Data prev, Data v1, Data v2) { return _mm256_fmadd_ps(v1, v2, prev); } + static inline float reduce_max(Data data) { return hmax_float_8(data); } + static inline float reduce_add(Data data) { return hsum_float_8(data); } + template static inline float reduce_max(const Data * data) { + return reduce_T(data); + } + template static inline float reduce_add(const Data * data) { + return reduce_T(data); + } +#else + using Data = float16x8_t; + constexpr static int block_size = 8; + constexpr static int num_registers = 32; + constexpr static int q_step = 8; + static inline Data zero() { return vdupq_n_f16(0); } + static inline Data load(const char * ptr, int i) { return vld1q_f16((const float16_t *)ptr + block_size*i); } + static inline Data load(const float16_t * ptr, int i) { return vld1q_f16(ptr + block_size*i); } + static inline Data load(const float16_t * ptr) { return vld1q_f16(ptr); } + static inline Data load(const float * ptr) { + auto val1 = vld1q_f32(ptr); + auto val2 = vld1q_f32(ptr+4); + return vcombine_f16(vcvt_f16_f32(val1), vcvt_f16_f32(val2)); + } + static inline Data set1(float val) { return vdupq_n_f16(val); } + static inline Data mul(Data v1, Data v2) { return vmulq_f16(v1, v2); } + static inline Data sub(Data v1, Data v2) { return vsubq_f16(v1, v2); } + static inline void store(float * ptr, Data data) { + vst1q_f32(ptr+0, vcvt_f32_f16(vget_low_f16(data))); + vst1q_f32(ptr+4, vcvt_f32_f16(vget_high_f16(data))); + } + static inline void store(float16_t * ptr, Data data) { vst1q_f16(ptr, data); } + static inline void store(float * ptr, float32x4_t data) { vst1q_f32(ptr, data); } + static inline Data fmadd(Data prev, Data v1, Data v2) { return vfmaq_f16(prev, v1, v2); } + static inline float reduce_max(Data data) { return vmaxvq_f16(data); } + static inline float reduce_add(Data data) { + auto sum = vadd_f16(vget_low_f16(data), vget_high_f16(data)); + return vaddvq_f32(vcvt_f32_f16(sum)); + } + template static inline float reduce_max(const Data * data) { + return reduce_T(data); + } + template static inline float reduce_add(const Data * data) { + return reduce_T(data); + } +#endif + template + static float reduce_T(const Data * data) { + float result; + if constexpr (k_step/block_size == 1) { + result = Op(data[0]); + } + else if constexpr (k_step/block_size == 2) { + result = Op(Op_combine(data[0], data[1])); + } + else { + auto vmax = Op_combine(data[0], data[1]); + for (int l = 2; l < k_step/block_size; ++l) vmax = Op_combine(vmax, data[l]); + result = Op(vmax); + } + return result; + } +}; + +template +struct HelperF16 final : public BaseHelper { + using Base = BaseHelper; + HelperF16(const char * data, int stride) : Base(data, stride) {} + + inline void load(int l1, F16::Data * vk) const { + auto dr = Base::lblock(l1); + for (int i = 0; i < D/F16::block_size; ++i) vk[i] = F16::load(dr, i); + } + + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + //auto dr = (const ggml_half *)Base::lblock(l1); + auto dr = Base::lblock(l1); + v1 = F16::load(dr, i + 0); + v2 = F16::load(dr, i + 1); + } + + inline void load_2(int l1, F16::Data* vk) const { + load(l1+0, vk+0); + load(l1+1, vk+D/16); + } +}; + +void quantize_row_q8_0(const float * x, block_q8_0 * y, int k) { + const int nb = k / QK8_0; + const int nb4 = 4*(nb/4); + +#if defined(__aarch64__) + block_q8_0_x4 * y4 = (block_q8_0_x4 *)y; + for (int i = 0; i < nb; i++) { + int i4 = i/4, ir = i%4; + float32x4_t srcv [8]; + float32x4_t asrcv[8]; + float32x4_t amaxv[8]; + + for (int j = 0; j < 8; j++) srcv[j] = vld1q_f32(x + i*32 + 4*j); + for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[j]); + + for (int j = 0; j < 4; j++) amaxv[2*j] = vmaxq_f32(asrcv[2*j], asrcv[2*j+1]); + for (int j = 0; j < 2; j++) amaxv[4*j] = vmaxq_f32(amaxv[4*j], amaxv[4*j+2]); + for (int j = 0; j < 1; j++) amaxv[8*j] = vmaxq_f32(amaxv[8*j], amaxv[8*j+4]); + + const float amax = vmaxvq_f32(amaxv[0]); + + const float d = amax / ((1 << 7) - 1); + const float id = d ? 1.0f/d : 0.0f; + + if (i < nb4) { + y4[i4].d[ir] = GGML_FP32_TO_FP16(d); + } else { + y[i].d = GGML_FP32_TO_FP16(d); + } + + for (int j = 0; j < 8; j++) { + const float32x4_t v = vmulq_n_f32(srcv[j], id); + const int32x4_t vi = vcvtnq_s32_f32(v); + + if (i < nb4) { + y4[i4].qs[32*ir + 4*j + 0] = vgetq_lane_s32(vi, 0); + y4[i4].qs[32*ir + 4*j + 1] = vgetq_lane_s32(vi, 1); + y4[i4].qs[32*ir + 4*j + 2] = vgetq_lane_s32(vi, 2); + y4[i4].qs[32*ir + 4*j + 3] = vgetq_lane_s32(vi, 3); + } else { + y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0); + y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1); + y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2); + y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3); + } + } + } +#else + block_q8_0_x4 * y4 = (block_q8_0_x4 *)y; + for (int i = 0; i < nb; i++) { + int i4 = i/4, ir = i%4; + // Load elements into 4 AVX vectors + __m256 v0 = _mm256_loadu_ps( x ); + __m256 v1 = _mm256_loadu_ps( x + 8 ); + __m256 v2 = _mm256_loadu_ps( x + 16 ); + __m256 v3 = _mm256_loadu_ps( x + 24 ); + x += 32; + + const __m256 signBit = _mm256_set1_ps( -0.0f ); + __m256 maxAbs = _mm256_andnot_ps( signBit, v0 ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v1 ) ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v2 ) ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v3 ) ); + + __m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) ); + max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) ); + max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) ); + const float maxScalar = _mm_cvtss_f32( max4 ); + + const float d = maxScalar / 127.f; + if (i < nb4) { + y4[i4].d[ir] = GGML_FP32_TO_FP16(d); + } else { + y[i].d = GGML_FP32_TO_FP16(d); + } + const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f; + const __m256 mul = _mm256_set1_ps( id ); + + v0 = _mm256_mul_ps( v0, mul ); + v1 = _mm256_mul_ps( v1, mul ); + v2 = _mm256_mul_ps( v2, mul ); + v3 = _mm256_mul_ps( v3, mul ); + + v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST ); + v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST ); + v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST ); + v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST ); + + __m256i i0 = _mm256_cvtps_epi32( v0 ); + __m256i i1 = _mm256_cvtps_epi32( v1 ); + __m256i i2 = _mm256_cvtps_epi32( v2 ); + __m256i i3 = _mm256_cvtps_epi32( v3 ); + + // Convert int32 to int16 + i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15 + i2 = _mm256_packs_epi32( i2, i3 ); // 16, 17, 18, 19, 24, 25, 26, 27, 20, 21, 22, 23, 28, 29, 30, 31 + // Convert int16 to int8 + i0 = _mm256_packs_epi16( i0, i2 ); // 0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27, 4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31 + + // We got our precious signed bytes, but the order is now wrong + // These AVX2 pack instructions process 16-byte pieces independently + // The following instruction is fixing the order + const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 ); + i0 = _mm256_permutevar8x32_epi32( i0, perm ); + + if (i < nb4) { + _mm256_storeu_si256((__m256i *)y4[i4].qs + ir, i0); + } else { + _mm256_storeu_si256((__m256i *)y[i].qs, i0); + } + } +#endif +} + +void quantize_row_q8_1(const float * x, block_q8_1 * y, int k) { + assert(k % QK8_1 == 0); + const int nb = k / QK8_1; + + const int nb4 = 4*(nb/4); + block_q8_1_x4 * y4 = (block_q8_1_x4 *)y; +#if defined(__aarch64__) + for (int i = 0; i < nb; i++) { + int i4 = i/4, ir = i%4; + float32x4_t srcv [8]; + float32x4_t asrcv[8]; + float32x4_t amaxv[8]; + + for (int j = 0; j < 8; j++) srcv[j] = vld1q_f32(x + i*32 + 4*j); + for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[j]); + + for (int j = 0; j < 4; j++) amaxv[2*j] = vmaxq_f32(asrcv[2*j], asrcv[2*j+1]); + for (int j = 0; j < 2; j++) amaxv[4*j] = vmaxq_f32(amaxv[4*j], amaxv[4*j+2]); + for (int j = 0; j < 1; j++) amaxv[8*j] = vmaxq_f32(amaxv[8*j], amaxv[8*j+4]); + + const float amax = vmaxvq_f32(amaxv[0]); + + const float d = amax / ((1 << 7) - 1); + const float id = d ? 1.0f/d : 0.0f; + + if (i < nb4) { + y4[i4].d[ir] = GGML_FP32_TO_FP16(d); + } else { + y[i].d = GGML_FP32_TO_FP16(d); + } + + int32x4_t accv = vdupq_n_s32(0); + + for (int j = 0; j < 8; j++) { + const float32x4_t v = vmulq_n_f32(srcv[j], id); + const int32x4_t vi = vcvtnq_s32_f32(v); + + if (i < nb4) { + y4[i4].qs[QK8_1*ir + 4*j + 0] = vgetq_lane_s32(vi, 0); + y4[i4].qs[QK8_1*ir + 4*j + 1] = vgetq_lane_s32(vi, 1); + y4[i4].qs[QK8_1*ir + 4*j + 2] = vgetq_lane_s32(vi, 2); + y4[i4].qs[QK8_1*ir + 4*j + 3] = vgetq_lane_s32(vi, 3); + } else { + y[i].qs[4*j + 0] = vgetq_lane_s32(vi, 0); + y[i].qs[4*j + 1] = vgetq_lane_s32(vi, 1); + y[i].qs[4*j + 2] = vgetq_lane_s32(vi, 2); + y[i].qs[4*j + 3] = vgetq_lane_s32(vi, 3); + } + + accv = vaddq_s32(accv, vi); + } + + if (i < nb4) { + y4[i4].d[ir+4] = GGML_FP32_TO_FP16(d * vaddvq_s32(accv)); + } else { + y[i].s = GGML_FP32_TO_FP16(d * vaddvq_s32(accv)); + } + } +#else + for (int i = 0; i < nb; i++) { + int i4 = i/4, ir = i%4; + // Load elements into 4 AVX vectors + __m256 v0 = _mm256_loadu_ps( x ); + __m256 v1 = _mm256_loadu_ps( x + 8 ); + __m256 v2 = _mm256_loadu_ps( x + 16 ); + __m256 v3 = _mm256_loadu_ps( x + 24 ); + x += 32; + + // Compute max(abs(e)) for the block + const __m256 signBit = _mm256_set1_ps( -0.0f ); + __m256 maxAbs = _mm256_andnot_ps( signBit, v0 ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v1 ) ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v2 ) ); + maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v3 ) ); + + __m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) ); + max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) ); + max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) ); + const float max_scalar = _mm_cvtss_f32( max4 ); + + // Quantize these floats + const float d = max_scalar / 127.f; + if (i < nb4) { + y4[i4].d[ir] = GGML_FP32_TO_FP16(d); + } else { + y[i].d = GGML_FP32_TO_FP16(d); + } + const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f; + const __m256 mul = _mm256_set1_ps( id ); + + // Apply the multiplier + v0 = _mm256_mul_ps( v0, mul ); + v1 = _mm256_mul_ps( v1, mul ); + v2 = _mm256_mul_ps( v2, mul ); + v3 = _mm256_mul_ps( v3, mul ); + + // Round to nearest integer + v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST ); + v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST ); + v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST ); + v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST ); + + // Convert floats to integers + __m256i i0 = _mm256_cvtps_epi32( v0 ); + __m256i i1 = _mm256_cvtps_epi32( v1 ); + __m256i i2 = _mm256_cvtps_epi32( v2 ); + __m256i i3 = _mm256_cvtps_epi32( v3 ); + + // Compute the sum of the quants and set y[i].s + if (i < nb4) { + y4[i4].d[ir+4] = GGML_FP32_TO_FP16(d * hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)))); + } else { + y[i].s = GGML_FP32_TO_FP16(d * hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3)))); + } + + // Convert int32 to int16 + i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15 + i2 = _mm256_packs_epi32( i2, i3 ); // 16, 17, 18, 19, 24, 25, 26, 27, 20, 21, 22, 23, 28, 29, 30, 31 + // Convert int16 to int8 + i0 = _mm256_packs_epi16( i0, i2 ); // 0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27, 4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31 + + // We got our precious signed bytes, but the order is now wrong + // These AVX2 pack instructions process 16-byte pieces independently + // The following instruction is fixing the order + const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 ); + i0 = _mm256_permutevar8x32_epi32( i0, perm ); + + if (i < nb4) { + _mm256_storeu_si256((__m256i *)y4[i4].qs + ir, i0); + } else { + _mm256_storeu_si256((__m256i *)y[i].qs, i0); + } + } +#endif +} + +template +struct HelperQ80 final : public BaseHelper { + using Base = BaseHelper; + using block_q8 = block_q8_0; + HelperQ80(const char * data, int stride) : Base(data, stride) {} + + // Needed for v * softmax(k * q) + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + int j = F16::block_size*i; + auto dl = (const block_q8_0_x4 *)Base::lblock(l1) + j/(4*QK8_0); + int ii = (j/QK8_0)%4; +#ifdef __aarch64__ + const float16_t * d = (const float16_t *)dl->d; + auto vd = F16::set1(d[ii]); + auto qs = vld1_s8_x2(dl->qs + 32*ii + j%32); + v1 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(qs.val[0]))); + v2 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(qs.val[1]))); +#else + auto vd = F16::set1(GGML_FP16_TO_FP32(dl->d[ii])); +#ifdef HAVE_FANCY_SIMD + v1 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)dl->qs+2*ii+0)))); + v2 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(_mm_loadu_si128((const __m128i *)dl->qs+2*ii+1)))); +#else + v1 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm_loadl_epi64((const __m128i *)(dl->qs+32*ii+j%32))))); + v2 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi8_epi32(_mm_loadl_epi64((const __m128i *)(dl->qs+32*ii+j%32+8))))); +#endif +#endif + } + + static inline void convert(int nq, int stride_q, const float * q, block_q8_0 * y) { + GGML_ASSERT(nq <= step); + for (int i = 0; i < nq; ++i) { + quantize_row_q8_0(q, y, D); + q += stride_q; + y += D/QK8_0; + } + } + + static inline void convert(int nq, int stride_q, const float * q, block_q8_1 * y) { + GGML_ASSERT(nq <= step); + for (int i = 0; i < nq; ++i) { + quantize_row_q8_1(q, y, D); + q += stride_q; + y += D/QK8_1; + } + } +}; + +template +struct HelperQ40 final : public BaseHelper { + using Base = BaseHelper; + using block_q8 = block_q8_0; + HelperQ40(const char * data, int stride) : Base(data, stride) {} + + // Needed for v * softmax(k * q) + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + int j = F16::block_size*i; + auto dl = (const block_q4_0 *)Base::lblock(l1) + j/QK4_0; +#ifdef __aarch64__ + auto vd = F16::set1(*(const float16_t *)&dl->d); + auto q = vld1q_u8(dl->qs); + q = j%QK4_0 ? vshrq_n_u8(q, 4) : vandq_u8(q, mask); + q = vaddq_s8(q, m8); + v1 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_low_s8(q)))); + v2 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_high_s8(q)))); +#else + auto vd = F16::set1(GGML_FP16_TO_FP32(dl->d)); + auto q = _mm_loadu_si128((const __m128i *)dl->qs); +#ifdef HAVE_FANCY_SIMD + auto ql = _mm_add_epi8(_mm_and_si128(q, mask), m8); + auto qh = _mm_add_epi8(_mm_and_si128(_mm_srli_epi16(q, 4), mask), m8); + v1 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(ql))); + v2 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(qh))); +#else + if (j%QK4_0) q = _mm_srli_epi16(q, 4); + auto q16 = _mm256_cvtepi8_epi16(_mm_add_epi8(_mm_and_si128(q, mask), m8)); + v1 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_castsi256_si128(q16)))); + v2 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_extracti128_si256(q16, 1)))); +#endif +#endif + } + +#ifdef __AVX2__ + const __m128i mask = _mm_set1_epi8(0xf); + const __m128i m8 = _mm_set1_epi8(-8); +#else + const uint8x16_t mask = vdupq_n_u8(0xf); + const int8x16_t m8 = vdupq_n_s8(-8); +#endif +}; + +template +struct HelperQ41 final : public BaseHelper { + using Base = BaseHelper; + using block_q8 = block_q8_1; + HelperQ41(const char * data, int stride) : Base(data, stride) {} + + // Needed for v * softmax(k * q) + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + int j = F16::block_size*i; + auto dl = (const block_q4_1 *)Base::lblock(l1) + j/QK4_1; +#ifdef __aarch64__ + auto vd = F16::set1(*(const float16_t *)&dl->d); + auto vm = F16::set1(*(const float16_t *)&dl->m); + auto q = vld1q_u8(dl->qs); + q = (j%QK4_1) ? vshrq_n_u8(q, 4) : vandq_u8(q, mask); + v1 = vfmaq_f16(vm, vd, vcvtq_f16_u16(vmovl_u8(vget_low_u8(q)))); + v2 = vfmaq_f16(vm, vd, vcvtq_f16_u16(vmovl_u8(vget_high_u8(q)))); +#else + auto vd = F16::set1(GGML_FP16_TO_FP32(dl->d)); + auto vm = F16::set1(GGML_FP16_TO_FP32(dl->m)); + auto q = _mm_loadu_si128((const __m128i *)dl->qs); +#ifdef HAVE_FANCY_SIMD + auto ql = _mm_and_si128(q, mask); + auto qh = _mm_and_si128(_mm_srli_epi16(q, 4), mask); + v1 = _mm512_fmadd_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(ql)), vm); + v2 = _mm512_fmadd_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(qh)), vm); +#else + if (j%QK4_1) q = _mm_srli_epi16(q, 4); + auto q16 = _mm256_cvtepi8_epi16(_mm_and_si128(q, mask)); + v1 = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_castsi256_si128(q16))), vm); + v2 = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_extracti128_si256(q16, 1))), vm); +#endif +#endif + } + +#ifdef __aarch64__ + const uint8x16_t mask = vdupq_n_u8(0xf); +#else + const __m128i mask = _mm_set1_epi8(0xf); +#endif +}; + +template +struct HelperIQ4nl final : public BaseHelper { + using Base = BaseHelper; +#ifdef __aarch64__ + using block_q8 = block_q8_0; + HelperIQ4nl(const char * data, int stride) : Base(data, stride), values(vld1q_s8(iq4k_values)) {} +#else + HelperIQ4nl(const char * data, int stride) : Base(data, stride) {} + using block_q8 = block_q8_1; +#endif + + // Needed for v * softmax(k * q) + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + int j = F16::block_size*i; + auto dl = (const block_iq4_nl *)Base::lblock(l1) + j/QK4_0; +#ifdef __aarch64__ + auto vd = F16::set1(*(const float16_t *)&dl->d); + auto q = vld1q_u8(dl->qs); + q = j%QK4_0 ? vshrq_n_u8(q, 4) : vandq_u8(q, mask); + q = vqtbl1q_s8(values, q); + v1 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_low_s8(q)))); + v2 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_high_s8(q)))); +#else + auto vd = F16::set1(GGML_FP16_TO_FP32(dl->d)); + auto q = _mm_loadu_si128((const __m128i *)dl->qs); +#ifdef HAVE_FANCY_SIMD + auto ql = _mm_shuffle_epi8(values, _mm_and_si128(q, mask)); + auto qh = _mm_shuffle_epi8(values, _mm_and_si128(_mm_srli_epi16(q, 4), mask)); + v1 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(ql))); + v2 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(qh))); +#else + if (j%QK4_0) q = _mm_srli_epi16(q, 4); + auto q16 = _mm256_cvtepi8_epi16(_mm_shuffle_epi8(values, _mm_and_si128(q, mask))); + v1 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_castsi256_si128(q16)))); + v2 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_extracti128_si256(q16, 1)))); +#endif +#endif + } + +#ifdef __aarch64__ + const uint8x16_t mask = vdupq_n_u8(0xf); + const int8x16_t values; +#else + const __m128i mask = _mm_set1_epi8(0xf); + const __m128i values = _mm_loadu_si128((const __m128i *)iq4k_values); +#endif +}; + +template +struct HelperQ60 final : public BaseHelper { +#ifdef __aarch64__ + using block_q8 = block_q8_0; +#else + using block_q8 = block_q8_1; +#endif + using Base = BaseHelper; + HelperQ60(const char * data, int stride) : Base(data, stride) {} + + // Needed for v * softmax(k * q) + inline void load(int l1, int i, F16::Data& v1, F16::Data& v2) const { + int j = F16::block_size*i; + auto dl = (const block_q6_0 *)Base::lblock(l1) + j/QK6_0; +#ifdef __aarch64__ + // TODO + auto vd = F16::set1(*(const float16_t *)&dl->d); + auto qh8 = vld1_u8(dl->qh); + auto qh = vcombine_u8(vshl_n_u8(qh8, 4), qh8); + auto qs = vld1q_u8(dl->qs); + qs = j%QK4_0 ? vshrq_n_u8(qs, 4) : vandq_u8(qs, mask_l); + qs = vorrq_u8(qs, vandq_u8(mask_h, j%QK4_0 ? vshrq_n_u8(qh, 2) : qh)); + qs = vaddq_s8(qs, m32); + v1 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_low_s8(qs)))); + v2 = vmulq_f16(vd, vcvtq_f16_s16(vmovl_s8(vget_high_s8(qs)))); +#else + auto vd = F16::set1(GGML_FP16_TO_FP32(dl->d)); + auto bl = _mm_loadu_si128((const __m128i *)dl->qs); + uint64_t aux64; std::memcpy(&aux64, dl->qh, 8); + auto bh = _mm_set_epi64x(aux64, aux64 << 4); +#ifdef HAVE_FANCY_SIMD + auto ql = _mm_add_epi8(_mm_or_si128(_mm_and_si128(bl, mask_l), _mm_and_si128(bh, mask_h)), m32); + auto qh = _mm_add_epi8(_mm_or_si128(_mm_and_si128(_mm_srli_epi16(bl, 4), mask_l), _mm_and_si128(_mm_srli_epi16(bh, 2), mask_h)), m32); + v1 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(ql))); + v2 = _mm512_mul_ps(vd, _mm512_cvtepi32_ps(_mm512_cvtepi8_epi32(qh))); +#else + if (j%QK4_0) { + bl = _mm_srli_epi16(bl, 4); + bh = _mm_srli_epi16(bh, 2); + } + auto q16 = _mm256_cvtepi8_epi16(_mm_add_epi8(_mm_or_si128(_mm_and_si128(bl, mask_l), _mm_and_si128(bh, mask_h)), m32)); + v1 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_castsi256_si128(q16)))); + v2 = _mm256_mul_ps(vd, _mm256_cvtepi32_ps(_mm256_cvtepi16_epi32(_mm256_extracti128_si256(q16, 1)))); +#endif +#endif + } + +#ifdef __AVX2__ + const __m128i mask_l = _mm_set1_epi8(0x0f); + const __m128i mask_h = _mm_set1_epi8(0x30); + const __m128i m32 = _mm_set1_epi8(-32); +#else + const uint8x16_t mask_l = vdupq_n_u8(0x0f); + const uint8x16_t mask_h = vdupq_n_u8(0x30); + const int8x16_t m32 = vdupq_n_s8(-32); +#endif +}; + +template +struct FlashMS { +// Something goes wrong when storing and manipulating K*Q as fp16. +// It works for some models (e.g., Gemma-2), but not for others (e.g., LLaMA-3.1-8B). +// As I wasn't able to find where we lose precision, let's comment this out +// for now and do the K*Q part in fp32. +//#ifdef __aarch64__ +// using cache_t = float16_t; +//#else +// using cache_t = float; +//#endif + using cache_t = float; + + FlashMS(float scale, float softcap) : vscale(F16::set1(scale)), softcap(softcap), h_inf(GGML_FP32_TO_FP16(-INFINITY)) {} + + inline void init_qstep() { + for (int j = 0; j < q_step; ++j) { + S[j] = 0; M[j] = -INFINITY; + } + } + + inline void update_M(int j, float smax) { + if (smax == -INFINITY) { + std::memset(cache + k_step*j, 0, k_step*sizeof(float)); + need_scaling[j] = M[j] == -INFINITY ? 2 : 0; + return; + } + need_scaling[j] = 0; + if (smax > M[j]) { + if (M[j] > -INFINITY) { + float m = expf(M[j] - smax); + vms[j] = F16::set1(m); + need_scaling[j] = 1; + S[j] *= m; + } else { + need_scaling[j] = 2; + S[j] = 0; + } + M[j] = smax; + } + } + +#ifdef __aarch64__ + inline void update_S(int j, float32x4_t * vk) { + auto vm = vdupq_n_f32(M[j]); + auto vsum = vdupq_n_f32(0); + for (int l = 0; l < k_step/4; ++l) { + vk[l] = v_expf(vsubq_f32(vk[l], vm)); + vsum = vaddq_f32(vsum, vk[l]); + F16::store(cache + k_step*j + 4*l, vk[l]); + } + S[j] += vaddvq_f32(vsum); + } +#else + inline void update_S(int j, F16::Data * vk) { + auto vm = F16::set1(M[j]); + for (int l = 0; l < k_step/F16::block_size; ++l) { + vk[l] = v_expf(F16::sub(vk[l], vm)); + F16::store(cache + k_step*j + F16::block_size*l, vk[l]); + } + S[j] += F16::reduce_add(vk); + } +#endif + +#ifdef __aarch64__ + inline float load_and_scale(int j, float32x4_t * vk) { + float32x4_t vmax = vdupq_n_f32(-INFINITY); + // Something goes wrong when storing and manipulating K*Q as fp16. + // It works for some models (e.g., Gemma-2), but not for others (e.g., LLaMA-3.1-8B). + // As I wasn't able to find where we lose precision, let's comment this out + // for now and do the K*Q part in fp32. + //if (softcap <= 0.0f) { + // for (int l = 0; l < k_step/F16::block_size; ++l) { + // auto val = F16::mul(vscale, F16::load(cache + k_step*j + F16::block_size*l)); + // vk[2*l+0] = vcvt_f32_f16(vget_low_f16(val)); + // vk[2*l+1] = vcvt_f32_f16(vget_high_f16(val)); + // vmax = vmaxq_f32(vmax, vmaxq_f32(vk[2*l+0], vk[2*l+1])); + // } + //} else { + // auto v_softcap = vdupq_n_f32(softcap); + // for (int l = 0; l < k_step/F16::block_size; ++l) { + // auto val = F16::mul(vscale, F16::load(cache + k_step*j + F16::block_size*l)); + // vk[2*l+0] = vcvt_f32_f16(vget_low_f16(val)); + // vk[2*l+1] = vcvt_f32_f16(vget_high_f16(val)); + // vk[2*l+0] = vmulq_f32(v_softcap, v_tanh(vk[2*l+0])); + // vk[2*l+1] = vmulq_f32(v_softcap, v_tanh(vk[2*l+1])); + // vmax = vmaxq_f32(vmax, vmaxq_f32(vk[2*l+0], vk[2*l+1])); + // } + //} + auto vscale32 = vcvt_f32_f16(vget_low_f16(vscale)); + if (softcap <= 0.0f) { + for (int l = 0; l < k_step/4; ++l) { + vk[l] = vmulq_f32(vscale32, vld1q_f32(cache + k_step*j + 4*l)); + vmax = vmaxq_f32(vmax, vk[l]); + } + } else { + auto v_softcap = vdupq_n_f32(softcap); + for (int l = 0; l < k_step/4; ++l) { + vk[l] = vmulq_f32(vscale32, vld1q_f32(cache + k_step*j + 4*l)); + vk[l] = vmulq_f32(v_softcap, v_tanh(vk[l])); + vmax = vmaxq_f32(vmax, vk[l]); + } + } + return vmaxvq_f32(vmax); + } + inline float load_apply_mask_and_scale(int j, float32x4_t * vk, const char * mask) { + auto vzero = vdupq_n_f32(0); + auto vinf = vdupq_n_f32(-INFINITY); + for (int l = 0; l < k_step/8; ++l) { + auto vm = vceqq_f16(vzero, vld1q_f16((const float16_t *)mask + 8*l)); + auto vm1 = vzip1q_u16(vm, vm); + auto vm2 = vzip2q_u16(vm, vm); + auto kq = vld1q_f32_x2(cache + k_step*j + 8*l); + vk[2*l+0] = vreinterpretq_f32_u32(vorrq_u32(vandq_u32(vreinterpretq_u32_f32(kq.val[0]), vm1), + vbicq_u32(vinf, vm1))); + vk[2*l+1] = vreinterpretq_f32_u32(vorrq_u32(vandq_u32(vreinterpretq_u32_f32(kq.val[1]), vm2), + vbicq_u32(vinf, vm2))); + } + float32x4_t vmax = vdupq_n_f32(-INFINITY); + auto vscale32 = vcvt_f32_f16(vget_low_f16(vscale)); + if (softcap <= 0.0f) { + for (int l = 0; l < k_step/4; ++l) { + vk[l] = vmulq_f32(vscale32, vk[l]); + vmax = vmaxq_f32(vmax, vk[l]); + } + } else { + auto v_softcap = vdupq_n_f32(softcap); + for (int l = 0; l < k_step/4; ++l) { + vk[l] = vmulq_f32(vscale32, vk[l]); + vk[l] = vmulq_f32(v_softcap, v_tanh(vk[l])); + vmax = vmaxq_f32(vmax, vk[l]); + } + } + return vmaxvq_f32(vmax); + } +#else + inline float load_and_scale(int j, F16::Data * vk) { + if (softcap <= 0.0f) { + for (int l = 0; l < k_step/F16::block_size; ++l) vk[l] = F16::mul(vscale, F16::load(cache + k_step*j + F16::block_size*l)); + } else { + auto v_softcap = F16::set1(softcap); + for (int l = 0; l < k_step/F16::block_size; ++l) { + auto val = F16::load(cache + k_step*j + F16::block_size*l); + vk[l] = F16::mul(v_softcap, v_tanh(F16::mul(vscale, val))); + } + } + return F16::reduce_max(vk); + } + inline float load_apply_mask_and_scale(int j, F16::Data * vk, const char * mask) { +#ifdef HAVE_FANCY_SIMD + auto vzero = _mm256_set1_epi16(0); + auto vinf = _mm512_set1_ps(-INFINITY); + if (softcap <= 0) { + for (int l = 0; l < k_step/F16::block_size; ++l) { + auto m16 = _mm256_cmpeq_epi16_mask(_mm256_loadu_si256((const __m256i *)mask + l), vzero); + vk[l] = _mm512_mask_mul_ps(vinf, m16, vscale, F16::load(cache + k_step*j + F16::block_size*l)); + } + } else { + auto v_softcap = F16::set1(softcap); + for (int l = 0; l < k_step/F16::block_size; ++l) { + auto m16 = _mm256_cmpeq_epi16_mask(_mm256_loadu_si256((const __m256i *)mask + l), vzero); + vk[l] = _mm512_mask_mul_ps(vinf, m16, v_softcap, v_tanh(F16::mul(vscale, F16::load(cache + k_step*j + F16::block_size*l)))); + } + } +#else + auto vzero = _mm_set1_epi16(0); + auto vinf = F16::set1(-INFINITY); + for (int l = 0; l < k_step/F16::block_size; ++l) { + auto m128 = _mm_loadu_si128((const __m128i *)mask + l); + m128 = _mm_cmpeq_epi16(m128, vzero); + auto m256 = _mm256_cvtepi16_epi32(m128); + auto mf = _mm256_castsi256_ps(_mm256_or_si256(m256, _mm256_slli_epi32(m256, 16))); + auto val = _mm256_loadu_ps(cache + k_step*j + F16::block_size*l); + vk[l] = _mm256_or_ps(_mm256_and_ps(mf, val), _mm256_andnot_ps(mf, vinf)); + } + if (softcap <= 0) { + for (int l = 0; l < k_step/F16::block_size; ++l) vk[l] = F16::mul(vscale, vk[l]); + } else { + auto v_softcap = F16::set1(softcap); + for (int l = 0; l < k_step/F16::block_size; ++l) vk[l] = F16::mul(v_softcap, v_tanh(F16::mul(vscale, vk[l]))); + } +#endif + return F16::reduce_max(vk); + } +#endif + +#ifdef __aarch64__ + inline void update_M_S(int j, float32x4_t * vk) { + float smax = load_and_scale(j, vk); + update_M(j, smax); + update_S(j, vk); + } + inline void update_M_S(int j, float32x4_t * vk, const char * mask) { + float smax = load_apply_mask_and_scale(j, vk, mask); + update_M(j, smax); + update_S(j, vk); + } +#else + inline void update_M_S(int j, F16::Data * vk) { + float smax = load_and_scale(j, vk); + update_M(j, smax); + update_S(j, vk); + } + inline void update_M_S(int j, F16::Data * vk, const char * mask) { + float smax = load_apply_mask_and_scale(j, vk, mask); + update_M(j, smax); + update_S(j, vk); + } +#endif + + cache_t cache[q_step*k_step]; + float S[q_step], M[q_step]; + int need_scaling[q_step]; + F16::Data vms[q_step]; + const F16::Data vscale; + const float softcap; + const ggml_half h_inf; + +}; + +template +struct FlashQKV { + +#ifdef __aarch64__ + using qkv_cache_t = float16_t; +#else + using qkv_cache_t = float; +#endif + + // This fails for head sizes of 80 and 112 as D/16 is odd, so we cannot do steps of 2 + // Hence, for now, we will not handle head sizes of 80 and 112 + template + inline void accumulate_qkv(const VHelper& vh, const FlashMS& fms) { + F16::Data vk[2*q_step]; + for (int i = 0; i < D/F16::block_size; i += 2) { + for (int j = 0; j < q_step; ++j) { + if (fms.need_scaling[j] == 2) { + vk[2*j+0] = vk[2*j+1] = F16::zero(); + } else { + auto R = qkv_cache + D*j; + vk[2*j+0] = F16::load(R + F16::block_size*i); + vk[2*j+1] = F16::load(R + F16::block_size*(i + 1)); + if (fms.need_scaling[j] == 1) { + vk[2*j+0] = F16::mul(vk[2*j+0], fms.vms[j]); + vk[2*j+1] = F16::mul(vk[2*j+1], fms.vms[j]); + } + } + } + F16::Data v1, v2; + for (int l1 = 0; l1 < k_step; ++l1) { + vh.load(l1, i, v1, v2); + for (int j = 0; j < q_step; ++j) { + auto vs = F16::set1(fms.cache[k_step*j + l1]); + vk[2*j+0] = F16::fmadd(vk[2*j+0], v1, vs); + vk[2*j+1] = F16::fmadd(vk[2*j+1], v2, vs); + } + } + for (int j = 0; j < q_step; ++j) { + auto R = qkv_cache + D*j; + F16::store(R + F16::block_size*(i + 0), vk[2*j+0]); + F16::store(R + F16::block_size*(i + 1), vk[2*j+1]); + } + } + } + + template = 2>> + inline void accumulate_qkv(int nq1, const VHelper& vh, const FlashMS& fms) { + F16::Data vk[2*q_step]; + for (int i = 0; i < D/F16::block_size; i += 2) { + for (int j = 0; j < nq1; ++j) { + if (fms.need_scaling[j] == 2) { + vk[2*j+0] = vk[2*j+1] = F16::zero(); + } else { + auto R = qkv_cache + D*j; + vk[2*j+0] = F16::load(R + F16::block_size*i); + vk[2*j+1] = F16::load(R + F16::block_size*(i + 1)); + if (fms.need_scaling[j] == 1) { + vk[2*j+0] = F16::mul(vk[2*j+0], fms.vms[j]); + vk[2*j+1] = F16::mul(vk[2*j+1], fms.vms[j]); + } + } + } + F16::Data v1, v2; + for (int l1 = 0; l1 < k_step; ++l1) { + vh.load(l1, i, v1, v2); + for (int j = 0; j < nq1; ++j) { + auto vs = F16::set1(fms.cache[k_step*j + l1]); + vk[2*j+0] = F16::fmadd(vk[2*j+0], v1, vs); + vk[2*j+1] = F16::fmadd(vk[2*j+1], v2, vs); + } + } + for (int j = 0; j < nq1; ++j) { + auto R = qkv_cache + D*j; + F16::store(R + F16::block_size*(i + 0), vk[2*j+0]); + F16::store(R + F16::block_size*(i + 1), vk[2*j+1]); + } + } + } + + inline void normalize_and_store(const FlashMS& fms, int j, const qkv_cache_t * R, float * qkv) const { + GGML_ASSERT(fms.S[j] > 0); + auto norm = F16::set1(1/fms.S[j]); + for (int i = 0; i < D/F16::block_size; ++i) { + auto r = F16::load(R + F16::block_size*i); + F16::store(qkv + F16::block_size*i, F16::mul(norm, r)); + } + } + + inline void normalize_and_store(const FlashMS& fms, int nq1, int stride_qkv, float * qkv) const { + auto R = qkv_cache; + for (int j = 0; j < nq1; ++j) { + normalize_and_store(fms, j, R, qkv); + qkv += stride_qkv; + R += D; + } + } + + inline void normalize_and_store(const FlashMS& fms, int stride_qkv, float * qkv) const { + auto R = qkv_cache; + for (int j = 0; j < q_step; ++j) { + normalize_and_store(fms, j, R, qkv); + qkv += stride_qkv; + R += D; + } + } + + qkv_cache_t qkv_cache[D*q_step]; +}; + +template +struct FlashQKfp32 { + static_assert(D%F16::block_size == 0 && D <= 256); + static_assert(k_step%F16::block_size == 0); + static_assert(q_step <= 4 || q_step%4 == 0); + +#ifdef __aarch64__ + constexpr static bool is_small_head = false; +#else + constexpr static bool is_small_head = D <= (F16::num_registers/2)*F16::block_size; +#endif + + template , typename q_float> + static inline void mult_mask_kq_one(int l1, int m1, int stride_q, int stride_m, const q_float * q, const char * mask, + F16::Data * qv, F16::Data * vk, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + fms.cache[k_step*m1 + l1 + 0] = fms.cache[k_step*m1 + l1 + 1] = -INFINITY; + if (mp[l1+0] == fms.h_inf && mp[l1+1] == fms.h_inf) { + return; + } + auto qr = q + m1*stride_q; + for (int i = 0; i < D/F16::block_size; ++i) qv[i] = F16::load(qr + F16::block_size*i); + if (mp[l1+0] != fms.h_inf) { + auto vsum = F16::zero(); + for (int i = 0; i < D/F16::block_size; ++i) vsum = F16::fmadd(vsum, vk[i], qv[i]); + fms.cache[k_step*m1 + l1 + 0] = F16::reduce_add(vsum); + } + if (mp[l1+1] != fms.h_inf) { + auto vsum = F16::zero(); + for (int i = 0; i < D/F16::block_size; ++i) vsum = F16::fmadd(vsum, vk[i+D/16], qv[i]); + fms.cache[k_step*m1 + l1 + 1] = F16::reduce_add(vsum); + } + } + + template , typename q_float> + static inline void mult_mask_kq_one(int l1, int m1, int stride_q, int stride_m, const q_float * q, const char * mask, + F16::Data * vk, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + if (mp[l1] == fms.h_inf) { + fms.cache[k_step*m1 + l1] = -INFINITY; + return; + } + auto qr = q + m1*stride_q; + auto vsum = F16::zero(); + for (int i = 0; i < D/F16::block_size; ++i) { + vsum = F16::fmadd(vsum, vk[i], F16::load(qr + F16::block_size*i)); + } + fms.cache[k_step*m1 + l1] = F16::reduce_add(vsum); + } + + template , typename q_float> + static inline void mult_mask_kq(const KHelper& kh, int stride_q, int stride_m, const q_float * q, const char * mask, + FlashMS& fms) { + F16::Data qv[D/F16::block_size]; + F16::Data vk[D/(F16::block_size/2)]; + for (int l1 = 0; l1 < k_step; l1 += 2) { + kh.load_2(l1, vk); + for (int m1 = 0; m1 < q_step; ++m1) { + mult_mask_kq_one(l1, m1, stride_q, stride_m, q, mask, qv, vk, fms); + } + } + } + + template , typename q_float> + static inline void mult_mask_kq_l(const KHelper& kh, int stride_q, int stride_m, + const q_float * q, const char * mask, FlashMS& fms) { + F16::Data vk[D/F16::block_size]; + for (int l1 = 0; l1 < k_step; ++l1) { + kh.load(l1, vk); + for (int m1 = 0; m1 < q_step; ++m1) { + mult_mask_kq_one(l1, m1, stride_q, stride_m, q, mask, vk, fms); + } + } + } + + template , typename q_float> + static inline void mult_mask_kq(int nq, const KHelper& kh, int stride_q, int stride_m, const q_float * q, const char * mask, + FlashMS& fms) { + F16::Data qv[D/F16::block_size]; + F16::Data vk[D/(F16::block_size/2)]; + for (int l1 = 0; l1 < k_step; l1 += 2) { + kh.load_2(l1, vk); + for (int m1 = 0; m1 < nq; ++m1) { + mult_mask_kq_one(l1, m1, stride_q, stride_m, q, mask, qv, vk, fms); + } + } + } + + template , typename q_float> + static inline void mult_mask_kq_l(int nq, const KHelper& kh, int stride_q, int stride_m, + const q_float * q, const char * mask, FlashMS& fms) { + F16::Data vk[D/F16::block_size]; + for (int l1 = 0; l1 < k_step; ++l1) { + kh.load(l1, vk); + for (int m1 = 0; m1 < nq; ++m1) { + mult_mask_kq_one(l1, m1, stride_q, stride_m, q, mask, vk, fms); + } + } + } + + template + static inline void multiply_mask_kq(const KHelper& kh, int stride_q, int stride_m, const q_float * q, const char * mask, + FlashMS& fms) { + if constexpr (is_small_head) { + mult_mask_kq(kh, stride_q, stride_m, q, mask, fms); + } + else { + mult_mask_kq_l(kh, stride_q, stride_m, q, mask, fms); + } +#ifdef __aarch64__ + float32x4_t vk[k_step/4]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk); + } +#else + F16::Data vk[k_step/F16::block_size]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk); + } +#endif + } + + template + static inline void multiply_mask_kq(int nq, const KHelper& kh, int stride_q, int stride_m, const q_float * q, const char * mask, + FlashMS& fms) { + if constexpr (is_small_head) { + mult_mask_kq(nq, kh, stride_q, stride_m, q, mask, fms); + } + else { + mult_mask_kq_l(nq, kh, stride_q, stride_m, q, mask, fms); + } +#ifdef __aarch64__ + float32x4_t vk[k_step/4]; + for (int j = 0; j < nq; ++j) { + fms.update_M_S(j, vk); + } +#else + F16::Data vk[k_step/F16::block_size]; + for (int j = 0; j < nq; ++j) { + fms.update_M_S(j, vk); + } +#endif + } + +#ifdef __aarch64__ + static inline void convert(int nq, int stride_q, const float * q, float16_t * q_f16) { + for (int i = 0; i < nq; ++i) { + for (int j = 0; j < D; j += 8) { + auto val1_f32 = vld1q_f32(q + j + 0); + auto val2_f32 = vld1q_f32(q + j + 4); + auto val_f16 = vcombine_f16(vcvt_f16_f32(val1_f32), vcvt_f16_f32(val2_f32)); + vst1q_f16(q_f16 + j, val_f16); + } + q += stride_q; + q_f16 += D; + } + } +#endif + + template + static inline void mul_mask_kq(const KHelper& kh, int stride_m, + const block_q8 * q, const char * mask, FlashMS& fms) { + static_assert(q_step <= 8); + if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_0)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); +#else + mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); +#endif + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_0)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); +#else + if constexpr (D >= 128) { + mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); + } else { + mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); + } +#endif + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); +#else + mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); +#endif + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); +#else + mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); +#endif + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); +#else + mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); +#endif + } + else { + GGML_ASSERT(false); + } +#ifdef __aarch64__ + float32x4_t vk[k_step/4]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk, mask + stride_m*j); + } +#else + F16::Data vk[k_step/F16::block_size]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk, mask + stride_m*j); + } +#endif + } + template + static inline void mul_mask_kq(int nq, const KHelper& kh, int stride_m, + const block_q8 * q, const char * mask, FlashMS& fms) { + GGML_ASSERT(nq < 8); + if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_0)*sizeof(block_q8), 0, 1, nullptr}; + switch (nq) { +#ifdef __aarch64__ + case 1: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; +#else + case 1: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; +#endif + } + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_0)*sizeof(block_q8), 0, 1, nullptr}; +#ifdef __aarch64__ + switch (nq) { + case 1: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + } +#else + if constexpr (D >= 128) { + switch (nq) { + case 1: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + } + } else { + switch (nq) { + case 1: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0_T(D, kh.block, kh.stride, info, k_step); break; + } + } +#endif + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; + switch (nq) { +#ifdef __aarch64__ + case 1: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_1_q8_1(D, kh.block, kh.stride, info, k_step); break; +#else + case 1: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; +#endif + } + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; + switch (nq) { +#ifdef __aarch64__ + case 1: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; +#else + case 1: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; +#endif + } + } + else if constexpr (std::is_same_v>) { + DataInfo info{fms.cache, (const char *)q, k_step, (D/QK8_1)*sizeof(block_q8), 0, 1, nullptr}; + switch (nq) { +#ifdef __aarch64__ + case 1: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_0_q8_0(D, kh.block, kh.stride, info, k_step); break; +#else + case 1: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 2: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 3: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 4: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 5: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 6: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; + case 7: mul_mat_qX_1_q8_1_T(D, kh.block, kh.stride, info, k_step); break; +#endif + } + } + else { + GGML_ASSERT(false); + } +#ifdef __aarch64__ + float32x4_t vk[k_step/4]; + for (int j = 0; j < nq; ++j) { + fms.update_M_S(j, vk, mask + stride_m*j); + } +#else + F16::Data vk[k_step/F16::block_size]; + for (int j = 0; j < nq; ++j) { + fms.update_M_S(j, vk, mask + stride_m*j); + } +#endif + } +}; + +template +void compute_helper(KHelper& kh, VHelper& vh, int nq1, int nk1, int stride_q, int stride_m, int stride_qkv, + FlashMS& fms, + FlashQKV& fqkv, + const float * q, const char * mask, float * qkv) { +#ifdef __aarch64__ + float16_t q_f16[D*q_step]; +#endif + for (int i1 = 0; i1 < nq1/q_step; ++i1) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); +#ifdef __aarch64__ + KQHelper::convert(q_step, stride_q, q, q_f16); +#endif + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { +#ifdef __aarch64__ + KQHelper::multiply_mask_kq(kh, D, stride_m, q_f16, mr, fms); +#else + KQHelper::multiply_mask_kq(kh, stride_q, stride_m, q, mr, fms); +#endif + fqkv.accumulate_qkv(vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, stride_qkv, qkv); + + q += q_step*stride_q; + mask += q_step*stride_m; + qkv += q_step*stride_qkv; + } + int n_left = nq1 - q_step*(nq1/q_step); + if (n_left > 0) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); +#ifdef __aarch64__ + KQHelper::convert(n_left, stride_q, q, q_f16); +#endif + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { +#ifdef __aarch64__ + KQHelper::multiply_mask_kq(n_left, kh, D, stride_m, q_f16, mr, fms); +#else + KQHelper::multiply_mask_kq(n_left, kh, stride_q, stride_m, q, mr, fms); +#endif + fqkv.accumulate_qkv(n_left, vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, n_left, stride_qkv, qkv); + } +} + +template +void compute_helper_q(KHelper& kh, VHelper& vh, int nq1, int nk1, int stride_q, int stride_m, int stride_qkv, + FlashMS& fms, + FlashQKV& fqkv, + const float * q, const char * mask, float * qkv) { + typename KHelper::block_q8 q8[q_step*(D/QK8_0)]; + for (int i1 = 0; i1 < nq1/q_step; ++i1) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); + HelperQ80::convert(q_step, stride_q, q, q8); + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { + KQHelper::mul_mask_kq(kh, stride_m, q8, mr, fms); + fqkv.accumulate_qkv(vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, stride_qkv, qkv); + + q += q_step*stride_q; + mask += q_step*stride_m; + qkv += q_step*stride_qkv; + } + int n_left = nq1 - q_step*(nq1/q_step); + if (n_left > 0) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); + HelperQ80::convert(n_left, stride_q, q, q8); + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { + KQHelper::mul_mask_kq(n_left, kh, stride_m, q8, mr, fms); + fqkv.accumulate_qkv(n_left, vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, n_left, stride_qkv, qkv); + } +} + +// Some of the methods in FlashAttn have two identical implementations that only differ by +// one version using a loop over the template parameter q_step, while the other using a loop +// over an input parameter nq (these are loops over the rows of q^T). I dislike this a lot, +// but performance drops signficantly if I remove the version with fixed q_step iterations. +// We only instantiate FlashAttn with q_step = 1 and q_step = 4 or 8 (depending on head size D), +// so when we have to process Nq rows, we process q_step*(Nq/q_step) using fixed q_step loops, +// and use the variable nq version (with lower performance) only for the remaining i1...q_step-1 +// rows (if Nq is not a multiple of q_step). One could have made the number of q^T rows to +// process template parameter of such functions, but this would result in the compiler generating +// q_step-1 versions of these functions for us, which I though was too much with q_step = 8. +template +struct FlashAttn { + static_assert(D%F16::block_size == 0 && D <= 256); + static_assert(k_step%F16::block_size == 0); + static_assert(q_step <= 4 || q_step%4 == 0); + + FlashAttn(float scale, float softcap) : fms(scale, softcap) {} + + template + void compute(KHelper& kh, VHelper& vh, int nq1, int nk1, int stride_q, int stride_m, int stride_qkv, + const float * q, const char * mask, float * qkv) { + if constexpr (std::is_same_v> || std::is_same_v> || + std::is_same_v> || std::is_same_v> || + std::is_same_v>) { + compute_helper_q>( + kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, fms, fqkv, q, mask, qkv); + } else { + compute_helper>( + kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, fms, fqkv, q, mask, qkv); + } + } + + FlashMS fms; + FlashQKV fqkv; + +}; + +#ifdef __AVX512BF16__ + +template +struct HelperBF16 final : public BaseHelper { + using Base = BaseHelper; + HelperBF16(const char * data, int stride) : Base(data, stride) {} + inline void load(int l1, __m512bh * vk) const { + auto dr = Base::lblock(l1); + for (int i = 0; i < D/32; ++i) vk[i] = __m512bh(_mm512_loadu_si512((const __m512i*)dr + i)); + } + + inline void load(int l1, int i, __m512& v1, __m512& v2) const { + auto dr = Base::lblock(l1); + v1 = _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)dr + i + 0)), 16)); + v2 = _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)dr + i + 1)), 16)); + } + + inline void load_2(int l1, __m512bh * vk) const { + load(l1+0, vk+0); + load(l1+1, vk+D/32); + } + + inline void load_4(int l1, __m512bh * vk) const { + load(l1+0, vk+0); + load(l1+1, vk+1*D/32); + load(l1+2, vk+2*D/32); + load(l1+3, vk+3*D/32); + } +}; + +template +struct FlashQKbf16 { + static_assert(D%32 == 0 && D <= 256); + static_assert(k_step%32 == 0); + static_assert(q_step <= 4 || q_step%4 == 0); + + static inline void mult_mask_kq_one(int l1, int m1, int stride_q, int stride_m, const float * q, const char * mask, + __m512bh * qv, const __m512bh * vkh, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + fms.cache[k_step*m1 + l1 + 0] = fms.cache[k_step*m1 + l1 + 1] = -INFINITY; + if (mp[l1+0] == fms.h_inf && mp[l1+1] == fms.h_inf) { + return; + } + auto qr = q + m1*stride_q; + for (int i = 0; i < D/32; ++i) { + auto val1 = _mm512_loadu_ps(qr + 32*i); + auto val2 = _mm512_loadu_ps(qr + 32*i + 16); + qv[i] = _mm512_cvtne2ps_pbh(val2, val1); + } + if (mp[l1+0] != fms.h_inf) { + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i], qv[i]); + fms.cache[k_step*m1 + l1 + 0] = _mm512_reduce_add_ps(vsum); + } + if (mp[l1+1] != fms.h_inf) { + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i+D/32], qv[i]); + fms.cache[k_step*m1 + l1 + 1] = _mm512_reduce_add_ps(vsum); + } + } + + static inline void mult_mask_kq_one(int l1, int m1, int stride_m, const ggml_bf16_t * q, const char * mask, + __m512bh * qv, const __m512bh * vkh, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + fms.cache[k_step*m1 + l1 + 0] = fms.cache[k_step*m1 + l1 + 1] = -INFINITY; + if (mp[l1+0] == fms.h_inf && mp[l1+1] == fms.h_inf) { + return; + } + auto qr = q + m1*D; + for (int i = 0; i < D/32; ++i) qv[i] = __m512bh(_mm512_loadu_si512((const __m512i*)qr + i)); + if (mp[l1+0] != fms.h_inf) { + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i], qv[i]); + fms.cache[k_step*m1 + l1 + 0] = _mm512_reduce_add_ps(vsum); + } + if (mp[l1+1] != fms.h_inf) { + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i+D/32], qv[i]); + fms.cache[k_step*m1 + l1 + 1] = _mm512_reduce_add_ps(vsum); + } + } + + static inline void mult_mask_kq_4(int l1, int m1, int stride_q, int stride_m, const float * q, const char * mask, + __m512bh * qv, const __m512bh * vkh, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + fms.cache[k_step*m1 + l1 + 0] = fms.cache[k_step*m1 + l1 + 1] = + fms.cache[k_step*m1 + l1 + 2] = fms.cache[k_step*m1 + l1 + 3] = -INFINITY; + if (mp[l1+0] == fms.h_inf && mp[l1+1] == fms.h_inf && mp[l1+2] == fms.h_inf && mp[l1+3] == fms.h_inf) { + return; + } + auto qr = q + m1*stride_q; + for (int i = 0; i < D/32; ++i) { + auto val1 = _mm512_loadu_ps(qr + 32*i); + auto val2 = _mm512_loadu_ps(qr + 32*i + 16); + qv[i] = _mm512_cvtne2ps_pbh(val2, val1); + } + for (int k = 0; k < 4; ++k) { + if (mp[l1+k] == fms.h_inf) continue; + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i+k*(D/32)], qv[i]); + fms.cache[k_step*m1 + l1 + k] = _mm512_reduce_add_ps(vsum); + } + } + + static inline void mult_mask_kq_4(int l1, int m1, int stride_m, const ggml_bf16_t * q, const char * mask, + __m512bh * qv, const __m512bh * vkh, FlashMS& fms) { + // q index is q_step*i1 + m1 + // k index is k_step*k1 + l1 + const ggml_half * mp = (const ggml_half *)(mask + stride_m*m1); + fms.cache[k_step*m1 + l1 + 0] = fms.cache[k_step*m1 + l1 + 1] = + fms.cache[k_step*m1 + l1 + 2] = fms.cache[k_step*m1 + l1 + 3] = -INFINITY; + if (mp[l1+0] == fms.h_inf && mp[l1+1] == fms.h_inf && mp[l1+2] == fms.h_inf && mp[l1+3] == fms.h_inf) { + return; + } + auto qr = q + m1*D; + for (int i = 0; i < D/32; ++i) qv[i] = __m512bh(_mm512_loadu_si512((const __m512i *)qr + i)); + for (int k = 0; k < 4; ++k) { + if (mp[l1+k] == fms.h_inf) continue; + auto vsum = _mm512_setzero_ps(); + for (int i = 0; i < D/32; ++i) vsum = _mm512_dpbf16_ps(vsum, vkh[i+k*(D/32)], qv[i]); + fms.cache[k_step*m1 + l1 + k] = _mm512_reduce_add_ps(vsum); + } + } + + template + static inline void multiply_mask_kq(const KHelper& kh, int stride_q, int stride_m, const float * q, + const char * mask, FlashMS& fms) { + { + __m512bh qv[D/32]; + if constexpr (D <= 128) { + __m512bh vkh[D/8]; + for (int l1 = 0; l1 < k_step; l1 += 4) { + kh.load_4(l1, vkh); + for (int j = 0; j < q_step; ++j) { + mult_mask_kq_4(l1, j, stride_q, stride_m, q, mask, qv, vkh, fms); + } + } + } else { + __m512bh vkh[D/16]; + for (int l1 = 0; l1 < k_step; l1 += 2) { + kh.load_2(l1, vkh); + for (int j = 0; j < q_step; ++j) { + mult_mask_kq_one(l1, j, stride_q, stride_m, q, mask, qv, vkh, fms); + } + } + } + } + __m512 vk[k_step/16]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk); + } + } + + template + static inline void multiply_mask_kq(const KHelper& kh, int stride_m, const ggml_bf16_t * q, + const char * mask, FlashMS& fms) { + { + __m512bh qv[D/32]; + if constexpr (D <= 128) { + __m512bh vkh[D/8]; + for (int l1 = 0; l1 < k_step; l1 += 4) { + kh.load_4(l1, vkh); + for (int j = 0; j < q_step; ++j) { + mult_mask_kq_4(l1, j, stride_m, q, mask, qv, vkh, fms); + } + } + } else { + __m512bh vkh[D/16]; + for (int l1 = 0; l1 < k_step; l1 += 2) { + kh.load_2(l1, vkh); + for (int j = 0; j < q_step; ++j) { + mult_mask_kq_one(l1, j, stride_m, q, mask, qv, vkh, fms); + } + } + } + } + __m512 vk[k_step/16]; + for (int j = 0; j < q_step; ++j) { + fms.update_M_S(j, vk); + } + } + + template + static inline void multiply_mask_kq(int nq, const KHelper& kh, int stride_q, int stride_m, const float * q, + const char * mask, FlashMS& fms) { + { + __m512bh qv[D/32]; + __m512bh vkh[D/16]; + for (int l1 = 0; l1 < k_step; l1 += 2) { + kh.load_2(l1, vkh); + for (int m1 = 0; m1 < nq; ++m1) { + mult_mask_kq_one(l1, m1, stride_q, stride_m, q, mask, qv, vkh, fms); + } + } + } + __m512 vk[k_step/16]; + for (int j = 0; j < nq; ++j) { + fms.update_M_S(j, vk); + } + } + + static inline void convert(int stride_q, const float * q, ggml_bf16_t * bf16) { + auto qr = q; + for (int j = 0; j < q_step; ++j) { + for (int i = 0; i < D/32; ++i) { + auto val1 = _mm512_loadu_ps(qr + 32*i); + auto val2 = _mm512_loadu_ps(qr + 32*i + 16); + _mm512_storeu_si512((__m512i *)bf16 + i, (__m512i)_mm512_cvtne2ps_pbh(val2, val1)); + } + qr += stride_q; + bf16 += D; + } + } +}; + +template +struct FlashAttnBF16 { + static_assert(D%32 == 0 && D <= 256); + static_assert(k_step%32 == 0); + static_assert(q_step <= 4 || q_step%4 == 0); + + FlashAttnBF16(float scale, float softcap) : fms(scale, softcap) {} + + template + void compute(KHelper& kh, VHelper& vh, int nq1, int nk1, int stride_q, int stride_m, int stride_qkv, + const float * q, const char * mask, float * qkv) { + ggml_bf16_t q_bf16[q_step*D]; + for (int i1 = 0; i1 < nq1/q_step; ++i1) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); + FlashQKbf16::convert(stride_q, q, q_bf16); + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { + FlashQKbf16::multiply_mask_kq(kh, stride_m, q_bf16, mr, fms); + fqkv.accumulate_qkv(vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, stride_qkv, qkv); + + q += q_step*stride_q; + mask += q_step*stride_m; + qkv += q_step*stride_qkv; + } + int n_left = nq1 - q_step*(nq1/q_step); + if (n_left > 0) { + fms.init_qstep(); + kh.reset_block(); + vh.reset_block(); + auto mr = mask; + for (int k1 = 0; k1 < nk1/k_step; ++k1) { + FlashQKbf16::multiply_mask_kq(n_left, kh, stride_q, stride_m, q, mr, fms); + fqkv.accumulate_qkv(n_left, vh, fms); + kh.next_block(); + vh.next_block(); + mr += k_step*sizeof(ggml_half); + } + fqkv.normalize_and_store(fms, n_left, stride_qkv, qkv); + } + } + + FlashMS fms; + FlashQKV fqkv; +}; +#endif + +template +inline void iqk_flash_helper(KHelper& kh, VHelper& vh, int nq1, int nk1, int stride_q, int stride_m, int stride_qkv, + const float * q, const char * mask, float scale, float softcap, float * qkv) { + + if (nq1 >= q_step) { + FlashAttn fa(scale, softcap); + fa.compute(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, (const char *)mask, qkv); + } else { + FlashAttn fa(scale, softcap); + fa.compute(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, (const char *)mask, qkv); + } +} + +#ifdef __AVX512BF16__ +template +inline void iqk_flash_helper_T(int nq1, int nk1, int stride_q, int stride_k, int stride_v, int stride_m, int stride_qkv, + const float * q, const char * k, const char * v, const char * mask, + float scale, float softcap, float * qkv) { + HelperBF16 kh(k, stride_k); + HelperBF16 vh(v, stride_v); + if (nq1 >= q_step) { + FlashAttnBF16 fa(scale, softcap); + fa.compute(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, (const char *)mask, qkv); + } else { + FlashAttnBF16 fa(scale, softcap); + fa.compute(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, (const char *)mask, qkv); + } +} +#endif + +template +inline void iqk_flash_helper_T(KHelper& kh, ggml_type type_v, + int nq1, int nk1, int stride_q, int stride_v, int stride_m, int stride_qkv, + const float * q, const char * v, const char * mask, + float scale, float softcap, float * qkv) { + + switch (type_v) { + case GGML_TYPE_F16: { + HelperF16 vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q8_0: { + HelperQ80 vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q4_0: { + HelperQ40 vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q4_1: { + HelperQ41 vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_IQ4_NL: { + HelperIQ4nl vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q6_0: { + HelperQ60 vh(v, stride_v); + iqk_flash_helper(kh, vh, nq1, nk1, stride_q, stride_m, stride_qkv, q, mask, scale, softcap, qkv); + } break; + default: break; + } +} + +template +inline void iqk_flash_helper_T(ggml_type type_k, ggml_type type_v, + int nq1, int nk1, int stride_q, int stride_k, int stride_v, int stride_m, int stride_qkv, + const float * q, const char * k, const char * v, const char * mask, + float scale, float softcap, float * qkv) { + + switch (type_k) { + case GGML_TYPE_F16: { + HelperF16 kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q8_0: { + HelperQ80 kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q4_0: { + HelperQ40 kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q4_1: { + HelperQ41 kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_IQ4_NL: { + HelperIQ4nl kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + case GGML_TYPE_Q6_0: { + HelperQ60 kh(k, stride_k); + iqk_flash_helper_T(kh, type_v, nq1, nk1, stride_q, stride_v, stride_m, stride_qkv, q, v, mask, scale, softcap, qkv); + } break; + default: break; + } + +} + +inline bool flash_attn_is_supported(ggml_type type) { +#ifdef __AVX512BF16__ + if (type == GGML_TYPE_BF16) return true; +#endif + if (type == GGML_TYPE_F16 || type == GGML_TYPE_Q8_0 || type == GGML_TYPE_Q4_0 || type == GGML_TYPE_Q4_1 || + type == GGML_TYPE_Q6_0 || type == GGML_TYPE_IQ4_NL) return true; + return false; +} +} + +bool iqk_flash_attn_noalibi(int int_type_k, // type of k + int int_type_v, // type of v + int D, // head size + int nq1, // number of columns in q + int nk1, // number of rows in k + int stride_q, // distance between q columns in bytes + int stride_k, // distance between k rows in bytes + int stride_v, // distance between v rows in bytes + int stride_m, // distance between mask rows (in bytes + int stride_qkv, // distance between rows in mask (in bytes) + const float * q, // q matrix. + const void * k, // k matrix. Assumed to be fp16, nq x nk elements + const void * v, // v matrix. Assumed to be fp16, nq x nk elements + const void * mask, // mask. If not null, assumed to be fp16. nq x nk elements + float scale, // scale applied before softmax + float softcap, // if > 0, a "soft-cap" operation is applied before softmax + float * qkv) { // v*softmax(scale*(k*q)) + + auto type_k = ggml_type(int_type_k); + auto type_v = ggml_type(int_type_v); + if (!flash_attn_is_supported(type_k) || !flash_attn_is_supported(type_v)) return false; + if (!mask || nk1%32 != 0) return false; // the implementation assumes mask is not null and nk is a multiple of 32 + + auto ck = (const char *)k; + auto cv = (const char *)v; + auto cm = (const char *)mask; + + stride_q /= sizeof(float); // q stride as float + +#ifdef __AVX512BF16__ + if (type_k == GGML_TYPE_BF16 || type_v == GGML_TYPE_BF16) { + if (type_k != GGML_TYPE_BF16 || type_v != GGML_TYPE_BF16) return false; // we do not support mixing bf16 with other types + switch (D) { + case 64: + iqk_flash_helper_T< 64, 8, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 96: + iqk_flash_helper_T< 96, 8, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 128: + iqk_flash_helper_T<128, 8, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 256: + iqk_flash_helper_T<256, 8, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + default: + return false; + } + + return true; + } +#endif + + switch (D) { + case 64: + iqk_flash_helper_T< 64, F16::q_step, 32>(type_k, type_v, nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + // Disable until we fix accumulate_qkv for odd D/16 + //case 80: + // iqk_flash_helper_T< 80, 4, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 96: + iqk_flash_helper_T< 96, F16::q_step, 32>(type_k, type_v, nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + // Disable until we fix accumulate_qkv for odd D/16 + //case 112: + // iqk_flash_helper_T<112, 4, 32>(nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 128: + iqk_flash_helper_T<128, F16::q_step, 32>(type_k, type_v, nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + case 256: + iqk_flash_helper_T<256, F16::q_step, 32>(type_k, type_v, nq1, nk1, stride_q, stride_k, stride_v, stride_m, stride_qkv, q, ck, cv, cm, scale, softcap, qkv); break; + default: + return false; + } + + return true; +} + +#else // IQK_IMPLEMENT + +bool iqk_mul_mat(int, long, long, long, int, const void *, long, int, const void *, long, float *, long, int, int) { + return false; +} + +bool iqk_mul_mat_moe(long, long, long, int, int, const void *, long, int, const void *, long, float *, long, long, + const void *, int, int) { + return false; +} + +bool iqk_flash_attn_noalibi([[maybe_unused]] int int_type_k, // type of k + [[maybe_unused]] int int_type_v, // type of v + [[maybe_unused]] int D, // head size + [[maybe_unused]] int nq, // number of columns in q + [[maybe_unused]] int nk, // number of rows in k + [[maybe_unused]] int stride_q, // distance between q columns in bytes + [[maybe_unused]] int stride_k, // distance between k rows in bytes + [[maybe_unused]] int stride_v, // distance between v rows in bytes + [[maybe_unused]] int stride_m, // distance between mask rows (in bytes + [[maybe_unused]] int stride_qkv, // distance between rows in mask (in bytes) + [[maybe_unused]] const float * q, // q matrix. + [[maybe_unused]] const void * k, // k matrix. Assumed to be fp16, nq x nk elements + [[maybe_unused]] const void * v, // v matrix. Assumed to be fp16, nq x nk elements + [[maybe_unused]] const void * mask, // mask. If not null, assumed to be fp16. nq x nk elements + [[maybe_unused]] float scale, // scale applied before softmax + [[maybe_unused]] float softcap, // if > 0, a "soft-cap" operation is applied before softmax + [[maybe_unused]] float * qkv) { // v*softmax(scale*(k*q)) + return false; +} + +#endif diff --git a/include/llama.h b/include/llama.h index 3615e88657f0e..6503d68b7fab8 100644 --- a/include/llama.h +++ b/include/llama.h @@ -175,6 +175,8 @@ extern "C" { LLAMA_FTYPE_MOSTLY_Q4_0_8_8 = 35, // except 1d tensors LLAMA_FTYPE_MOSTLY_TQ1_0 = 36, // except 1d tensors LLAMA_FTYPE_MOSTLY_TQ2_0 = 37, // except 1d tensors + // + LLAMA_FTYPE_MOSTLY_Q6_0 = 135, // except 1d tensors LLAMA_FTYPE_GUESSED = 1024, // not specified in the model file }; diff --git a/src/llama.cpp b/src/llama.cpp index bd17e59c07461..55a94951c4fc8 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -4500,6 +4500,7 @@ struct llama_model_loader { case GGML_TYPE_Q4_1: ftype = LLAMA_FTYPE_MOSTLY_Q4_1; break; case GGML_TYPE_Q5_0: ftype = LLAMA_FTYPE_MOSTLY_Q5_0; break; case GGML_TYPE_Q5_1: ftype = LLAMA_FTYPE_MOSTLY_Q5_1; break; + case GGML_TYPE_Q6_0: ftype = LLAMA_FTYPE_MOSTLY_Q6_0; break; case GGML_TYPE_Q8_0: ftype = LLAMA_FTYPE_MOSTLY_Q8_0; break; case GGML_TYPE_Q2_K: ftype = LLAMA_FTYPE_MOSTLY_Q2_K; break; case GGML_TYPE_Q3_K: ftype = LLAMA_FTYPE_MOSTLY_Q3_K_M; break; @@ -5299,6 +5300,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) { case LLAMA_FTYPE_MOSTLY_Q4_1: return "Q4_1"; case LLAMA_FTYPE_MOSTLY_Q5_0: return "Q5_0"; case LLAMA_FTYPE_MOSTLY_Q5_1: return "Q5_1"; + case LLAMA_FTYPE_MOSTLY_Q6_0: return "Q6_0"; case LLAMA_FTYPE_MOSTLY_Q8_0: return "Q8_0"; case LLAMA_FTYPE_MOSTLY_Q2_K: return "Q2_K - Medium"; case LLAMA_FTYPE_MOSTLY_Q2_K_S: return "Q2_K - Small"; @@ -18442,6 +18444,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s case LLAMA_FTYPE_MOSTLY_Q4_1: default_type = GGML_TYPE_Q4_1; break; case LLAMA_FTYPE_MOSTLY_Q5_0: default_type = GGML_TYPE_Q5_0; break; case LLAMA_FTYPE_MOSTLY_Q5_1: default_type = GGML_TYPE_Q5_1; break; + case LLAMA_FTYPE_MOSTLY_Q6_0: default_type = GGML_TYPE_Q6_0; break; case LLAMA_FTYPE_MOSTLY_Q8_0: default_type = GGML_TYPE_Q8_0; break; case LLAMA_FTYPE_MOSTLY_F16: default_type = GGML_TYPE_F16; break; case LLAMA_FTYPE_MOSTLY_BF16: default_type = GGML_TYPE_BF16; break;