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ggml : add ssm_scan metal impl
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ggml-ci
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@ggerganov
ggerganov committed Jul 18, 2024
1 parent 7e4e98d commit 21c4882
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Showing 4 changed files with 191 additions and 2 deletions.
85 changes: 85 additions & 0 deletions ggml/src/ggml-metal.m
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Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,7 @@
GGML_METAL_KERNEL_TYPE_GROUP_NORM,
GGML_METAL_KERNEL_TYPE_NORM,
GGML_METAL_KERNEL_TYPE_SSM_CONV_F32,
GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32,
GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32,
GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16,
GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32,
Expand Down Expand Up @@ -540,6 +541,7 @@ static void ggml_metal_log(enum ggml_log_level level, const char * format, ...){
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_GROUP_NORM, group_norm, ctx->support_simdgroup_reduction);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_NORM, norm, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SSM_CONV_F32, ssm_conv_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32, ssm_scan_f32, true);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F32_F32, mul_mv_f32_f32, ctx->support_simdgroup_reduction);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F16, mul_mv_f16_f16, ctx->support_simdgroup_reduction);
GGML_METAL_ADD_KERNEL(GGML_METAL_KERNEL_TYPE_MUL_MV_F16_F32, mul_mv_f16_f32, ctx->support_simdgroup_reduction);
Expand Down Expand Up @@ -802,6 +804,7 @@ static bool ggml_metal_supports_op(const struct ggml_metal_context * ctx, const
}
return ctx->support_simdgroup_mm; // TODO: over-restricted for vec-kernels
case GGML_OP_SSM_CONV:
case GGML_OP_SSM_SCAN:
return true;
case GGML_OP_MUL_MAT:
case GGML_OP_MUL_MAT_ID:
Expand Down Expand Up @@ -1568,6 +1571,88 @@ static enum ggml_status ggml_metal_graph_compute(

[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne1, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_SSM_SCAN:
{
struct ggml_tensor * src3 = gf->nodes[i]->src[3];
struct ggml_tensor * src4 = gf->nodes[i]->src[4];
struct ggml_tensor * src5 = gf->nodes[i]->src[5];

GGML_ASSERT(src3);
GGML_ASSERT(src4);
GGML_ASSERT(src5);

size_t offs_src3 = 0;
size_t offs_src4 = 0;
size_t offs_src5 = 0;

id<MTLBuffer> id_src3 = src3 ? ggml_metal_get_buffer(src3, &offs_src3) : nil;
id<MTLBuffer> id_src4 = src4 ? ggml_metal_get_buffer(src4, &offs_src4) : nil;
id<MTLBuffer> id_src5 = src5 ? ggml_metal_get_buffer(src5, &offs_src5) : nil;

const int64_t ne30 = src3->ne[0]; GGML_UNUSED(ne30);
const int64_t ne31 = src3->ne[1]; GGML_UNUSED(ne31);

const uint64_t nb30 = src3->nb[0];
const uint64_t nb31 = src3->nb[1];

const int64_t ne40 = src4->ne[0]; GGML_UNUSED(ne40);
const int64_t ne41 = src4->ne[1]; GGML_UNUSED(ne41);
const int64_t ne42 = src4->ne[2]; GGML_UNUSED(ne42);

const uint64_t nb40 = src4->nb[0];
const uint64_t nb41 = src4->nb[1];
const uint64_t nb42 = src4->nb[2];

const int64_t ne50 = src5->ne[0]; GGML_UNUSED(ne50);
const int64_t ne51 = src5->ne[1]; GGML_UNUSED(ne51);
const int64_t ne52 = src5->ne[2]; GGML_UNUSED(ne52);

const uint64_t nb50 = src5->nb[0];
const uint64_t nb51 = src5->nb[1];
const uint64_t nb52 = src5->nb[2];

const int64_t d_state = ne00;
const int64_t d_inner = ne01;
const int64_t n_seq_tokens = ne11;
const int64_t n_seqs = ne02;

id<MTLComputePipelineState> pipeline = ctx->kernels[GGML_METAL_KERNEL_TYPE_SSM_SCAN_F32].pipeline;

[encoder setComputePipelineState:pipeline];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
[encoder setBuffer:id_src2 offset:offs_src2 atIndex:2];
[encoder setBuffer:id_src3 offset:offs_src3 atIndex:3];
[encoder setBuffer:id_src4 offset:offs_src4 atIndex:4];
[encoder setBuffer:id_src5 offset:offs_src5 atIndex:5];
[encoder setBuffer:id_dst offset:offs_dst atIndex:6];

[encoder setBytes:&d_state length:sizeof(d_state) atIndex:7];
[encoder setBytes:&d_inner length:sizeof(d_inner) atIndex:8];
[encoder setBytes:&n_seq_tokens length:sizeof(n_seq_tokens) atIndex:9];
[encoder setBytes:&n_seqs length:sizeof(n_seqs) atIndex:10];

[encoder setBytes:&nb00 length:sizeof(nb00) atIndex:11];
[encoder setBytes:&nb01 length:sizeof(nb01) atIndex:12];
[encoder setBytes:&nb02 length:sizeof(nb02) atIndex:13];
[encoder setBytes:&nb10 length:sizeof(nb10) atIndex:14];
[encoder setBytes:&nb11 length:sizeof(nb11) atIndex:15];
[encoder setBytes:&nb12 length:sizeof(nb12) atIndex:16];
[encoder setBytes:&nb13 length:sizeof(nb13) atIndex:17];
[encoder setBytes:&nb20 length:sizeof(nb20) atIndex:18];
[encoder setBytes:&nb21 length:sizeof(nb21) atIndex:19];
[encoder setBytes:&nb22 length:sizeof(nb22) atIndex:20];
[encoder setBytes:&nb30 length:sizeof(nb30) atIndex:21];
[encoder setBytes:&nb31 length:sizeof(nb31) atIndex:22];
[encoder setBytes:&nb40 length:sizeof(nb40) atIndex:23];
[encoder setBytes:&nb41 length:sizeof(nb41) atIndex:24];
[encoder setBytes:&nb42 length:sizeof(nb42) atIndex:25];
[encoder setBytes:&nb50 length:sizeof(nb50) atIndex:26];
[encoder setBytes:&nb51 length:sizeof(nb51) atIndex:27];
[encoder setBytes:&nb52 length:sizeof(nb52) atIndex:28];

[encoder dispatchThreadgroups:MTLSizeMake(d_inner, n_seqs, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_MUL_MAT:
{
GGML_ASSERT(ne00 == ne10);
Expand Down
73 changes: 73 additions & 0 deletions ggml/src/ggml-metal.metal
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Original file line number Diff line number Diff line change
Expand Up @@ -715,6 +715,79 @@ kernel void kernel_ssm_conv_f32(
x[0] = sumf;
}

// ref: ggml.c:ggml_compute_forward_ssm_scan_f32
// TODO: optimize
kernel void kernel_ssm_scan_f32(
device const void * src0,
device const void * src1,
device const void * src2,
device const void * src3,
device const void * src4,
device const void * src5,
device float * dst,
constant int64_t & d_state,
constant int64_t & d_inner,
constant int64_t & n_seq_tokens,
constant int64_t & n_seqs,
constant uint64_t & nb00,
constant uint64_t & nb01,
constant uint64_t & nb02,
constant uint64_t & nb10,
constant uint64_t & nb11,
constant uint64_t & nb12,
constant uint64_t & nb13,
constant uint64_t & nb20,
constant uint64_t & nb21,
constant uint64_t & nb22,
constant uint64_t & nb30,
constant uint64_t & nb31,
constant uint64_t & nb40,
constant uint64_t & nb41,
constant uint64_t & nb42,
constant uint64_t & nb50,
constant uint64_t & nb51,
constant uint64_t & nb52,
uint3 tgpig[[threadgroup_position_in_grid]],
uint3 tpitg[[thread_position_in_threadgroup]],
uint3 ntg[[threads_per_threadgroup]]) {
const int64_t ir = tgpig.x;
const int64_t i3 = tgpig.y;

const int64_t nc = d_state;
const int64_t nr = d_inner;
const int64_t n_t = n_seq_tokens;
const int64_t n_s = n_seqs;

for (int64_t i2 = 0; i2 < n_t; ++i2) {
device const float * s0 = (device const float *) ((device const char *) src0 + ir*nb01 + i3*nb02);
device const float * x = (device const float *) ((device const char *) src1 + ir*nb10 + i2*nb11 + i3*nb12);
device const float * dt = (device const float *) ((device const char *) src2 + ir*nb20 + i2*nb21 + i3*nb22);
device const float * A = (device const float *) ((device const char *) src3 + ir*nb31);
device const float * B = (device const float *) ((device const char *) src4 + i2*nb41 + i3*nb42);
device const float * C = (device const float *) ((device const char *) src5 + i2*nb51 + i3*nb52);
device float * y = (device float *) ((device char *) dst + ir*nb10 + i2*nb11 + i3*nb12); // TODO: do not use src1 strides
device float * s = (device float *) ((device char *) dst + ir*nb01 + i3*nb02 + nb13);

if (i2 > 0) {
s0 = s;
}

// i1 == 0
float dt_soft_plus = dt[0] <= 20.0f ? log(1.0f + exp(dt[0])) : dt[0];
float x_dt = x[0] * dt_soft_plus;
float sumf = 0.0f;

for (int64_t i0 = 0; i0 < nc; ++i0) {
int64_t i = i0;
float state = (s0[i] * exp(dt_soft_plus * A[i])) + (B[i0] * x_dt);
sumf += state * C[i0];
s[i] = state;
}

y[0] = sumf;
}
}

kernel void kernel_norm(
device const void * src0,
device float * dst,
Expand Down
4 changes: 2 additions & 2 deletions ggml/src/ggml.c
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Original file line number Diff line number Diff line change
Expand Up @@ -15788,8 +15788,8 @@ static void ggml_compute_forward_ssm_scan_f32(
const float * A = (const float *) ((const char *) src3->data + ir0*(src3->nb[1])); // {d_state, d_inner}
const float * B = (const float *) ((const char *) src4->data + i2*(src4->nb[1]) + i3*(src4->nb[2])); // {d_state, n_t, n_s}
const float * C = (const float *) ((const char *) src5->data + i2*(src5->nb[1]) + i3*(src5->nb[2])); // {d_state, n_t, n_s}
float * y = (float *) ((char *) dst->data + ir0*(src1->nb[0]) + i2*(src1->nb[1]) + i3*(src1->nb[2])); // {d_inner, n_t, n_s}
float * s = (float *) ((char *) dst->data + ir0*(src0->nb[1]) + i3*(src0->nb[2]) + src1->nb[3]); // {d_state, d_inner, n_s}
float * y = ( float *) (( char *) dst->data + ir0*(src1->nb[0]) + i2*(src1->nb[1]) + i3*(src1->nb[2])); // {d_inner, n_t, n_s}
float * s = ( float *) (( char *) dst->data + ir0*(src0->nb[1]) + i3*(src0->nb[2]) + src1->nb[3]); // {d_state, d_inner, n_s}

// use the output as the source for the next token-wise iterations
if (i2 > 0) { s0 = s; }
Expand Down
31 changes: 31 additions & 0 deletions tests/test-backend-ops.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -957,6 +957,35 @@ struct test_ssm_conv : public test_case {
}
};

// GGML_OP_SSM_SCAN
struct test_ssm_scan : public test_case {
const ggml_type type;

const int64_t d_state;
const int64_t d_inner;
const int64_t n_seq_tokens;
const int64_t n_seqs;

std::string vars() override {
return VARS_TO_STR5(type, d_state, d_inner, n_seq_tokens, n_seqs);
}

test_ssm_scan(ggml_type type = GGML_TYPE_F32,
int64_t d_state = 32, int64_t d_inner = 32, int64_t n_seq_tokens = 32, int64_t n_seqs = 32)
: type(type), d_state(d_state), d_inner(d_inner), n_seq_tokens(n_seq_tokens), n_seqs(n_seqs) {}

ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * s = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_state, d_inner, n_seqs, 1 }.data());
ggml_tensor * x = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_inner, n_seq_tokens, n_seqs, 1 }.data());
ggml_tensor * dt = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_inner, n_seq_tokens, n_seqs, 1 }.data());
ggml_tensor * A = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_state, d_inner, 1 , 1 }.data());
ggml_tensor * B = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_state, n_seq_tokens, n_seqs, 1 }.data());
ggml_tensor * C = ggml_new_tensor(ctx, type, 4, std::vector<int64_t>{ d_state, n_seq_tokens, n_seqs, 1 }.data());
ggml_tensor * out = ggml_ssm_scan(ctx, s, x, dt, A, B, C);
return out;
}
};

// GGML_OP_MUL_MAT
struct test_mul_mat : public test_case {
const ggml_type type_a;
Expand Down Expand Up @@ -2228,6 +2257,8 @@ static bool test_backend(ggml_backend_t backend, test_mode mode, const char * op
test_cases.emplace_back(new test_ssm_conv(GGML_TYPE_F32, {8, 1536, 1, 1}, {4, 1536, 1, 1}));
test_cases.emplace_back(new test_ssm_conv(GGML_TYPE_F32, {4, 1536, 4, 1}, {4, 1536, 1, 1}));

test_cases.emplace_back(new test_ssm_scan(GGML_TYPE_F32, 16, 1024, 32, 4));

for (ggml_type type_a : base_types) {
for (ggml_type type_b : {GGML_TYPE_F32, GGML_TYPE_F16}) {
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, { 1, 1}, {1, 1}));
Expand Down

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