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clblast.h
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// =================================================================================================
// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
// width of 100 characters per line.
//
// Author(s):
// Cedric Nugteren <www.cedricnugteren.nl>
//
// This file contains the interface to the CLBlast BLAS routines. It also contains the definitions
// of the returned status codes and the layout and transpose types. This is the only header users
// of CLBlast should include and use.
//
// =================================================================================================
#ifndef CLBLAST_CLBLAST_H_
#define CLBLAST_CLBLAST_H_
#include <cstdlib> // For size_t
#include <string> // For OverrideParameters function
#include <unordered_map> // For OverrideParameters function
// Includes the normal OpenCL C header
#if defined(__APPLE__) || defined(__MACOSX)
#include <OpenCL/opencl.h>
#else
#include <CL/opencl.h>
#endif
// Exports library functions under Windows when building a DLL. See also:
// https://msdn.microsoft.com/en-us/library/a90k134d.aspx
#if defined(_WIN32) && defined(CLBLAST_DLL)
#if defined(COMPILING_DLL)
#define PUBLIC_API __declspec(dllexport)
#else
#define PUBLIC_API __declspec(dllimport)
#endif
#else
#define PUBLIC_API
#endif
// Version numbering (v1.6.1)
#define CLBLAST_VERSION_MAJOR 1
#define CLBLAST_VERSION_MINOR 6
#define CLBLAST_VERSION_PATCH 1
namespace clblast {
// =================================================================================================
// Status codes. These codes can be returned by functions declared in this header file. The error
// codes match either the standard OpenCL error codes or the clBLAS error codes.
enum class StatusCode {
// Status codes in common with the OpenCL standard
kSuccess = 0, // CL_SUCCESS
kOpenCLCompilerNotAvailable= -3, // CL_COMPILER_NOT_AVAILABLE
kTempBufferAllocFailure = -4, // CL_MEM_OBJECT_ALLOCATION_FAILURE
kOpenCLOutOfResources = -5, // CL_OUT_OF_RESOURCES
kOpenCLOutOfHostMemory = -6, // CL_OUT_OF_HOST_MEMORY
kOpenCLBuildProgramFailure = -11, // CL_BUILD_PROGRAM_FAILURE: OpenCL compilation error
kInvalidValue = -30, // CL_INVALID_VALUE
kInvalidCommandQueue = -36, // CL_INVALID_COMMAND_QUEUE
kInvalidMemObject = -38, // CL_INVALID_MEM_OBJECT
kInvalidBinary = -42, // CL_INVALID_BINARY
kInvalidBuildOptions = -43, // CL_INVALID_BUILD_OPTIONS
kInvalidProgram = -44, // CL_INVALID_PROGRAM
kInvalidProgramExecutable = -45, // CL_INVALID_PROGRAM_EXECUTABLE
kInvalidKernelName = -46, // CL_INVALID_KERNEL_NAME
kInvalidKernelDefinition = -47, // CL_INVALID_KERNEL_DEFINITION
kInvalidKernel = -48, // CL_INVALID_KERNEL
kInvalidArgIndex = -49, // CL_INVALID_ARG_INDEX
kInvalidArgValue = -50, // CL_INVALID_ARG_VALUE
kInvalidArgSize = -51, // CL_INVALID_ARG_SIZE
kInvalidKernelArgs = -52, // CL_INVALID_KERNEL_ARGS
kInvalidLocalNumDimensions = -53, // CL_INVALID_WORK_DIMENSION: Too many thread dimensions
kInvalidLocalThreadsTotal = -54, // CL_INVALID_WORK_GROUP_SIZE: Too many threads in total
kInvalidLocalThreadsDim = -55, // CL_INVALID_WORK_ITEM_SIZE: ... or for a specific dimension
kInvalidGlobalOffset = -56, // CL_INVALID_GLOBAL_OFFSET
kInvalidEventWaitList = -57, // CL_INVALID_EVENT_WAIT_LIST
kInvalidEvent = -58, // CL_INVALID_EVENT
kInvalidOperation = -59, // CL_INVALID_OPERATION
kInvalidBufferSize = -61, // CL_INVALID_BUFFER_SIZE
kInvalidGlobalWorkSize = -63, // CL_INVALID_GLOBAL_WORK_SIZE
// Status codes in common with the clBLAS library
kNotImplemented = -1024, // Routine or functionality not implemented yet
kInvalidMatrixA = -1022, // Matrix A is not a valid OpenCL buffer
kInvalidMatrixB = -1021, // Matrix B is not a valid OpenCL buffer
kInvalidMatrixC = -1020, // Matrix C is not a valid OpenCL buffer
kInvalidVectorX = -1019, // Vector X is not a valid OpenCL buffer
kInvalidVectorY = -1018, // Vector Y is not a valid OpenCL buffer
kInvalidDimension = -1017, // Dimensions M, N, and K have to be larger than zero
kInvalidLeadDimA = -1016, // LD of A is smaller than the matrix's first dimension
kInvalidLeadDimB = -1015, // LD of B is smaller than the matrix's first dimension
kInvalidLeadDimC = -1014, // LD of C is smaller than the matrix's first dimension
kInvalidIncrementX = -1013, // Increment of vector X cannot be zero
kInvalidIncrementY = -1012, // Increment of vector Y cannot be zero
kInsufficientMemoryA = -1011, // Matrix A's OpenCL buffer is too small
kInsufficientMemoryB = -1010, // Matrix B's OpenCL buffer is too small
kInsufficientMemoryC = -1009, // Matrix C's OpenCL buffer is too small
kInsufficientMemoryX = -1008, // Vector X's OpenCL buffer is too small
kInsufficientMemoryY = -1007, // Vector Y's OpenCL buffer is too small
// Custom additional status codes for CLBlast
kInsufficientMemoryTemp = -2050, // Temporary buffer provided to GEMM routine is too small
kInvalidBatchCount = -2049, // The batch count needs to be positive
kInvalidOverrideKernel = -2048, // Trying to override parameters for an invalid kernel
kMissingOverrideParameter = -2047, // Missing override parameter(s) for the target kernel
kInvalidLocalMemUsage = -2046, // Not enough local memory available on this device
kNoHalfPrecision = -2045, // Half precision (16-bits) not supported by the device
kNoDoublePrecision = -2044, // Double precision (64-bits) not supported by the device
kInvalidVectorScalar = -2043, // The unit-sized vector is not a valid OpenCL buffer
kInsufficientMemoryScalar = -2042, // The unit-sized vector's OpenCL buffer is too small
kDatabaseError = -2041, // Entry for the device was not found in the database
kUnknownError = -2040, // A catch-all error code representing an unspecified error
kUnexpectedError = -2039, // A catch-all error code representing an unexpected exception
};
// Matrix layout and transpose types
enum class Layout { kRowMajor = 101, kColMajor = 102 };
enum class Transpose { kNo = 111, kYes = 112, kConjugate = 113 };
enum class Triangle { kUpper = 121, kLower = 122 };
enum class Diagonal { kNonUnit = 131, kUnit = 132 };
enum class Side { kLeft = 141, kRight = 142 };
enum class KernelMode { kCrossCorrelation = 151, kConvolution = 152 };
// Precision scoped enum (values in bits)
enum class Precision { kHalf = 16, kSingle = 32, kDouble = 64,
kComplexSingle = 3232, kComplexDouble = 6464, kAny = -1 };
// =================================================================================================
// BLAS level-1 (vector-vector) routines
// =================================================================================================
// Generate givens plane rotation: SROTG/DROTG
template <typename T>
StatusCode Rotg(cl_mem sa_buffer, const size_t sa_offset,
cl_mem sb_buffer, const size_t sb_offset,
cl_mem sc_buffer, const size_t sc_offset,
cl_mem ss_buffer, const size_t ss_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Generate modified givens plane rotation: SROTMG/DROTMG
template <typename T>
StatusCode Rotmg(cl_mem sd1_buffer, const size_t sd1_offset,
cl_mem sd2_buffer, const size_t sd2_offset,
cl_mem sx1_buffer, const size_t sx1_offset,
const cl_mem sy1_buffer, const size_t sy1_offset,
cl_mem sparam_buffer, const size_t sparam_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Apply givens plane rotation: SROT/DROT
template <typename T>
StatusCode Rot(const size_t n,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
const T cos,
const T sin,
cl_command_queue* queue, cl_event* event = nullptr);
// Apply modified givens plane rotation: SROTM/DROTM
template <typename T>
StatusCode Rotm(const size_t n,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem sparam_buffer, const size_t sparam_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Swap two vectors: SSWAP/DSWAP/CSWAP/ZSWAP/HSWAP
template <typename T>
StatusCode Swap(const size_t n,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Vector scaling: SSCAL/DSCAL/CSCAL/ZSCAL/HSCAL
template <typename T>
StatusCode Scal(const size_t n,
const T alpha,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Vector copy: SCOPY/DCOPY/CCOPY/ZCOPY/HCOPY
template <typename T>
StatusCode Copy(const size_t n,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Vector-times-constant plus vector: SAXPY/DAXPY/CAXPY/ZAXPY/HAXPY
template <typename T>
StatusCode Axpy(const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Dot product of two vectors: SDOT/DDOT/HDOT
template <typename T>
StatusCode Dot(const size_t n,
cl_mem dot_buffer, const size_t dot_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Dot product of two complex vectors: CDOTU/ZDOTU
template <typename T>
StatusCode Dotu(const size_t n,
cl_mem dot_buffer, const size_t dot_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Dot product of two complex vectors, one conjugated: CDOTC/ZDOTC
template <typename T>
StatusCode Dotc(const size_t n,
cl_mem dot_buffer, const size_t dot_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Euclidian norm of a vector: SNRM2/DNRM2/ScNRM2/DzNRM2/HNRM2
template <typename T>
StatusCode Nrm2(const size_t n,
cl_mem nrm2_buffer, const size_t nrm2_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Absolute sum of values in a vector: SASUM/DASUM/ScASUM/DzASUM/HASUM
template <typename T>
StatusCode Asum(const size_t n,
cl_mem asum_buffer, const size_t asum_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Sum of values in a vector (non-BLAS function): SSUM/DSUM/ScSUM/DzSUM/HSUM
template <typename T>
StatusCode Sum(const size_t n,
cl_mem sum_buffer, const size_t sum_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Index of absolute maximum value in a vector: iSAMAX/iDAMAX/iCAMAX/iZAMAX/iHAMAX
template <typename T>
StatusCode Amax(const size_t n,
cl_mem imax_buffer, const size_t imax_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Index of absolute minimum value in a vector (non-BLAS function): iSAMIN/iDAMIN/iCAMIN/iZAMIN/iHAMIN
template <typename T>
StatusCode Amin(const size_t n,
cl_mem imin_buffer, const size_t imin_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Index of maximum value in a vector (non-BLAS function): iSMAX/iDMAX/iCMAX/iZMAX/iHMAX
template <typename T>
StatusCode Max(const size_t n,
cl_mem imax_buffer, const size_t imax_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Index of minimum value in a vector (non-BLAS function): iSMIN/iDMIN/iCMIN/iZMIN/iHMIN
template <typename T>
StatusCode Min(const size_t n,
cl_mem imin_buffer, const size_t imin_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// =================================================================================================
// BLAS level-2 (matrix-vector) routines
// =================================================================================================
// General matrix-vector multiplication: SGEMV/DGEMV/CGEMV/ZGEMV/HGEMV
template <typename T>
StatusCode Gemv(const Layout layout, const Transpose a_transpose,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// General banded matrix-vector multiplication: SGBMV/DGBMV/CGBMV/ZGBMV/HGBMV
template <typename T>
StatusCode Gbmv(const Layout layout, const Transpose a_transpose,
const size_t m, const size_t n, const size_t kl, const size_t ku,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian matrix-vector multiplication: CHEMV/ZHEMV
template <typename T>
StatusCode Hemv(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian banded matrix-vector multiplication: CHBMV/ZHBMV
template <typename T>
StatusCode Hbmv(const Layout layout, const Triangle triangle,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian packed matrix-vector multiplication: CHPMV/ZHPMV
template <typename T>
StatusCode Hpmv(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem ap_buffer, const size_t ap_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric matrix-vector multiplication: SSYMV/DSYMV/HSYMV
template <typename T>
StatusCode Symv(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric banded matrix-vector multiplication: SSBMV/DSBMV/HSBMV
template <typename T>
StatusCode Sbmv(const Layout layout, const Triangle triangle,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric packed matrix-vector multiplication: SSPMV/DSPMV/HSPMV
template <typename T>
StatusCode Spmv(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem ap_buffer, const size_t ap_offset,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const T beta,
cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Triangular matrix-vector multiplication: STRMV/DTRMV/CTRMV/ZTRMV/HTRMV
template <typename T>
StatusCode Trmv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Triangular banded matrix-vector multiplication: STBMV/DTBMV/CTBMV/ZTBMV/HTBMV
template <typename T>
StatusCode Tbmv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n, const size_t k,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Triangular packed matrix-vector multiplication: STPMV/DTPMV/CTPMV/ZTPMV/HTPMV
template <typename T>
StatusCode Tpmv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n,
const cl_mem ap_buffer, const size_t ap_offset,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Solves a triangular system of equations: STRSV/DTRSV/CTRSV/ZTRSV
template <typename T>
StatusCode Trsv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Solves a banded triangular system of equations: STBSV/DTBSV/CTBSV/ZTBSV
template <typename T>
StatusCode Tbsv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n, const size_t k,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Solves a packed triangular system of equations: STPSV/DTPSV/CTPSV/ZTPSV
template <typename T>
StatusCode Tpsv(const Layout layout, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t n,
const cl_mem ap_buffer, const size_t ap_offset,
cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// General rank-1 matrix update: SGER/DGER/HGER
template <typename T>
StatusCode Ger(const Layout layout,
const size_t m, const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// General rank-1 complex matrix update: CGERU/ZGERU
template <typename T>
StatusCode Geru(const Layout layout,
const size_t m, const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// General rank-1 complex conjugated matrix update: CGERC/ZGERC
template <typename T>
StatusCode Gerc(const Layout layout,
const size_t m, const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian rank-1 matrix update: CHER/ZHER
template <typename T>
StatusCode Her(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian packed rank-1 matrix update: CHPR/ZHPR
template <typename T>
StatusCode Hpr(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem ap_buffer, const size_t ap_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian rank-2 matrix update: CHER2/ZHER2
template <typename T>
StatusCode Her2(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian packed rank-2 matrix update: CHPR2/ZHPR2
template <typename T>
StatusCode Hpr2(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem ap_buffer, const size_t ap_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric rank-1 matrix update: SSYR/DSYR/HSYR
template <typename T>
StatusCode Syr(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric packed rank-1 matrix update: SSPR/DSPR/HSPR
template <typename T>
StatusCode Spr(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
cl_mem ap_buffer, const size_t ap_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric rank-2 matrix update: SSYR2/DSYR2/HSYR2
template <typename T>
StatusCode Syr2(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Symmetric packed rank-2 matrix update: SSPR2/DSPR2/HSPR2
template <typename T>
StatusCode Spr2(const Layout layout, const Triangle triangle,
const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
cl_mem ap_buffer, const size_t ap_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// =================================================================================================
// BLAS level-3 (matrix-matrix) routines
// =================================================================================================
// General matrix-matrix multiplication: SGEMM/DGEMM/CGEMM/ZGEMM/HGEMM
template <typename T>
StatusCode Gemm(const Layout layout, const Transpose a_transpose, const Transpose b_transpose,
const size_t m, const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr,
cl_mem temp_buffer = nullptr);
// Symmetric matrix-matrix multiplication: SSYMM/DSYMM/CSYMM/ZSYMM/HSYMM
template <typename T>
StatusCode Symm(const Layout layout, const Side side, const Triangle triangle,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Hermitian matrix-matrix multiplication: CHEMM/ZHEMM
template <typename T>
StatusCode Hemm(const Layout layout, const Side side, const Triangle triangle,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Rank-K update of a symmetric matrix: SSYRK/DSYRK/CSYRK/ZSYRK/HSYRK
template <typename T>
StatusCode Syrk(const Layout layout, const Triangle triangle, const Transpose a_transpose,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Rank-K update of a hermitian matrix: CHERK/ZHERK
template <typename T>
StatusCode Herk(const Layout layout, const Triangle triangle, const Transpose a_transpose,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Rank-2K update of a symmetric matrix: SSYR2K/DSYR2K/CSYR2K/ZSYR2K/HSYR2K
template <typename T>
StatusCode Syr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Rank-2K update of a hermitian matrix: CHER2K/ZHER2K
template <typename T, typename U>
StatusCode Her2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose,
const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
const U beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Triangular matrix-matrix multiplication: STRMM/DTRMM/CTRMM/ZTRMM/HTRMM
template <typename T>
StatusCode Trmm(const Layout layout, const Side side, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Solves a triangular system of equations: STRSM/DTRSM/CTRSM/ZTRSM
template <typename T>
StatusCode Trsm(const Layout layout, const Side side, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// =================================================================================================
// Extra non-BLAS routines (level-X)
// =================================================================================================
// Element-wise vector product (Hadamard): SHAD/DHAD/CHAD/ZHAD/HHAD
template <typename T>
StatusCode Had(const size_t n,
const T alpha,
const cl_mem x_buffer, const size_t x_offset, const size_t x_inc,
const cl_mem y_buffer, const size_t y_offset, const size_t y_inc,
const T beta,
cl_mem z_buffer, const size_t z_offset, const size_t z_inc,
cl_command_queue* queue, cl_event* event = nullptr);
// Scaling and out-place transpose/copy (non-BLAS function): SOMATCOPY/DOMATCOPY/COMATCOPY/ZOMATCOPY/HOMATCOPY
template <typename T>
StatusCode Omatcopy(const Layout layout, const Transpose a_transpose,
const size_t m, const size_t n,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld,
cl_mem b_buffer, const size_t b_offset, const size_t b_ld,
cl_command_queue* queue, cl_event* event = nullptr);
// Im2col function (non-BLAS function): SIM2COL/DIM2COL/CIM2COL/ZIM2COL/HIM2COL
template <typename T>
StatusCode Im2col(const KernelMode kernel_mode,
const size_t channels, const size_t height, const size_t width, const size_t kernel_h, const size_t kernel_w, const size_t pad_h, const size_t pad_w, const size_t stride_h, const size_t stride_w, const size_t dilation_h, const size_t dilation_w,
const cl_mem im_buffer, const size_t im_offset,
cl_mem col_buffer, const size_t col_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Col2im function (non-BLAS function): SCOL2IM/DCOL2IM/CCOL2IM/ZCOL2IM/HCOL2IM
template <typename T>
StatusCode Col2im(const KernelMode kernel_mode,
const size_t channels, const size_t height, const size_t width, const size_t kernel_h, const size_t kernel_w, const size_t pad_h, const size_t pad_w, const size_t stride_h, const size_t stride_w, const size_t dilation_h, const size_t dilation_w,
const cl_mem col_buffer, const size_t col_offset,
cl_mem im_buffer, const size_t im_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Batched convolution as GEMM (non-BLAS function): SCONVGEMM/DCONVGEMM/HCONVGEMM
template <typename T>
StatusCode Convgemm(const KernelMode kernel_mode,
const size_t channels, const size_t height, const size_t width, const size_t kernel_h, const size_t kernel_w, const size_t pad_h, const size_t pad_w, const size_t stride_h, const size_t stride_w, const size_t dilation_h, const size_t dilation_w, const size_t num_kernels, const size_t batch_count,
const cl_mem im_buffer, const size_t im_offset,
const cl_mem kernel_buffer, const size_t kernel_offset,
cl_mem result_buffer, const size_t result_offset,
cl_command_queue* queue, cl_event* event = nullptr);
// Batched version of AXPY: SAXPYBATCHED/DAXPYBATCHED/CAXPYBATCHED/ZAXPYBATCHED/HAXPYBATCHED
template <typename T>
StatusCode AxpyBatched(const size_t n,
const T *alphas,
const cl_mem x_buffer, const size_t *x_offsets, const size_t x_inc,
cl_mem y_buffer, const size_t *y_offsets, const size_t y_inc,
const size_t batch_count,
cl_command_queue* queue, cl_event* event = nullptr);
// Batched version of GEMM: SGEMMBATCHED/DGEMMBATCHED/CGEMMBATCHED/ZGEMMBATCHED/HGEMMBATCHED
template <typename T>
StatusCode GemmBatched(const Layout layout, const Transpose a_transpose, const Transpose b_transpose,
const size_t m, const size_t n, const size_t k,
const T *alphas,
const cl_mem a_buffer, const size_t *a_offsets, const size_t a_ld,
const cl_mem b_buffer, const size_t *b_offsets, const size_t b_ld,
const T *betas,
cl_mem c_buffer, const size_t *c_offsets, const size_t c_ld,
const size_t batch_count,
cl_command_queue* queue, cl_event* event = nullptr);
// StridedBatched version of GEMM: SGEMMSTRIDEDBATCHED/DGEMMSTRIDEDBATCHED/CGEMMSTRIDEDBATCHED/ZGEMMSTRIDEDBATCHED/HGEMMSTRIDEDBATCHED
template <typename T>
StatusCode GemmStridedBatched(const Layout layout, const Transpose a_transpose, const Transpose b_transpose,
const size_t m, const size_t n, const size_t k,
const T alpha,
const cl_mem a_buffer, const size_t a_offset, const size_t a_ld, const size_t a_stride,
const cl_mem b_buffer, const size_t b_offset, const size_t b_ld, const size_t b_stride,
const T beta,
cl_mem c_buffer, const size_t c_offset, const size_t c_ld, const size_t c_stride,
const size_t batch_count,
cl_command_queue* queue, cl_event* event = nullptr);
// =================================================================================================
// Retrieves the required size of the temporary buffer for the GEMM kernel (optional)
template <typename T>
StatusCode GemmTempBufferSize(const Layout layout, const Transpose a_transpose, const Transpose b_transpose,
const size_t m, const size_t n, const size_t k,
const size_t a_offset, const size_t a_ld,
const size_t b_offset, const size_t b_ld,
const size_t c_offset, const size_t c_ld,
cl_command_queue* queue, size_t& temp_buffer_size);
// =================================================================================================
// CLBlast stores binaries of compiled kernels into a cache in case the same kernel is used later on
// for the same device. This cache can be cleared to free up system memory or in case of debugging.
StatusCode PUBLIC_API ClearCache();
// The cache can also be pre-initialized for a specific device with all possible CLBlast kernels.
// Further CLBlast routine calls will then run at maximum speed.
StatusCode PUBLIC_API FillCache(const cl_device_id device);
// =================================================================================================
// Retrieves current tuning parameters for a specific device-precision-kernel combination
StatusCode PUBLIC_API RetrieveParameters(const cl_device_id device, const std::string &kernel_name,
const Precision precision,
std::unordered_map<std::string,size_t> ¶meters);
// Overrides tuning parameters for a specific device-precision-kernel combination. The next time
// the target routine is called it will re-compile and use the new parameters from then on.
StatusCode PUBLIC_API OverrideParameters(const cl_device_id device, const std::string &kernel_name,
const Precision precision,
const std::unordered_map<std::string,size_t> ¶meters);
// =================================================================================================
// Tunes the "Xaxpy" kernel, used for many level-1 routines such as XAXPY, XCOPY, and XSWAP
template <typename T>
StatusCode TuneXaxpy(cl_command_queue* queue, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Xdot" kernel, used for level-1 reduction routines such as XDOT, XMAX, and XSUM
template <typename T>
StatusCode TuneXdot(cl_command_queue* queue, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Xgemv" kernel, used for matrix-vector level-2 routines such as XGEMV, XGBMV, and XHEMV
template <typename T>
StatusCode TuneXgemv(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Xger" kernel, used for matrix update level-2 routines such as XGER, XHER, and XSYR2
template <typename T>
StatusCode TuneXger(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Xgemm" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TuneXgemm(cl_command_queue* queue, const size_t m, const size_t n, const size_t k,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "XgemmDiret" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TuneXgemmDirect(cl_command_queue* queue, const size_t m, const size_t n, const size_t k,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Copy" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TuneCopy(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Pad" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TunePad(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Transpose" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TuneTranspose(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Padtranspose" kernel, used for most level-3 routines such as XGEMM, XSYMM, and XHER2K
template <typename T>
StatusCode TunePadtranspose(cl_command_queue* queue, const size_t m, const size_t n,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// Tunes the "Xgemm" kernel, used for the level-3 routine XTRSM
template <typename T>
StatusCode TuneInvert(cl_command_queue* queue, const size_t m, const size_t n, const size_t k,
const double fraction, std::unordered_map<std::string,size_t> ¶meters);
// =================================================================================================
} // namespace clblast
// CLBLAST_CLBLAST_H_
#endif