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author | Cedric Nugteren <web@cedricnugteren.nl> | 2016-02-08 20:06:02 +0100 |
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committer | Cedric Nugteren <web@cedricnugteren.nl> | 2016-02-08 20:06:02 +0100 |
commit | bf84463ab20f2f39071719fad9bd28a6bb13fc24 (patch) | |
tree | df4a6fff31d178186bd36538da3705ccf3353eb3 /src/kernels/level3/xgemm_part1.opencl | |
parent | 38c56bbde2ed108d47bd058ba239725b3396475d (diff) |
Separated the GEMM kernel in two parts to reduce string length for MSVC
Diffstat (limited to 'src/kernels/level3/xgemm_part1.opencl')
-rw-r--r-- | src/kernels/level3/xgemm_part1.opencl | 329 |
1 files changed, 329 insertions, 0 deletions
diff --git a/src/kernels/level3/xgemm_part1.opencl b/src/kernels/level3/xgemm_part1.opencl new file mode 100644 index 00000000..4cb0585b --- /dev/null +++ b/src/kernels/level3/xgemm_part1.opencl @@ -0,0 +1,329 @@ + +// ================================================================================================= +// 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 an optimized matrix-multiplication kernel according to the paper by Matsumoto +// et al. and the tutorial on http://www.cedricnugteren.nl/tutorial.php. It is fully configurable +// (and tunable!) using more or less the same parameters/naming conventions as in the paper. It +// supports single and double precision (SGEMM/DGEMM) through a pre-processor define. +// +// Matrices are accessed as follows: +// A: [k*M + m], with 'k' ranging from 0:K and 'm' from 0:M (m,k,m) +// B: [k*N + n], with 'k' ranging from 0:K and 'n' from 0:N (n,k,n) +// C: [n*M + m], with 'n' ranging from 0:N and 'm' from 0:M (m,n,m) +// +// Or as an image (assuming column-major) +// K +// o-------o +// | | +// N | [B^T] | +// | | +// o-------o +// K N +// o-------o o-----o +// M | [A] | M | [C] | +// | | | | +// o-------o o-----o +// +// +// This kernel is seperated into two files. This is part 1 out of 2, +// +// ================================================================================================= + +// Enables loading of this file using the C++ pre-processor's #include (C++11 standard raw string +// literal). Comment-out this line for syntax-highlighting when developing. +R"( + +// ================================================================================================= + +// Parameters set by the tuner or by the database. Here they are given a basic default value in case +// this kernel file is used outside of the CLBlast library. +#ifndef MWG + #define MWG 8 // Tile-size in dimension M (e.g. 64, 128) +#endif +#ifndef NWG + #define NWG 8 // Tile-size in dimension N (e.g. 64, 128) +#endif +#ifndef KWG + #define KWG 8 // Tile-size in dimension K (e.g. 8, 16) +#endif +#ifndef MDIMC + #define MDIMC 8 // Threads per workgroup in M-dimension (e.g. 8, 16, 32) +#endif +#ifndef NDIMC + #define NDIMC 8 // Threads per workgroup in N-dimension (e.g. 8, 16, 32) +#endif +#ifndef MDIMA + #define MDIMA 8 // Re-shaped tile dimension of matrix A: KDIMA * MDIMA +#endif +#ifndef NDIMB + #define NDIMB 8 // Re-shaped tile dimension of matrix B: KDIMB * NDIMB +#endif +#ifndef KWI + #define KWI 1 // Unroll factor of the KWG loop (smaller or equal than KWG) +#endif +#ifndef VWM + #define VWM 1 // Vector width of matrices A and C +#endif +#ifndef VWN + #define VWN 1 // Vector width of matrix B +#endif +#ifndef STRM + #define STRM 0 // Use strided access within a thread in the M-dimension (1) or not (0) +#endif +#ifndef STRN + #define STRN 0 // Use strided access within a thread in the N-dimension (1) or not (0) +#endif +#ifndef SA + #define SA 0 // Use local/shared memory to cache matrix A (1) or not (0) +#endif +#ifndef SB + #define SB 0 // Use local/shared memory to cache matrix B (1) or not (0) +#endif + +// Helper parameters based on the above tuning parameters +#define MWI (MWG/MDIMC) // Work per work-item (M-dimension) +#define NWI (NWG/NDIMC) // Work per work-item (N-dimension) +#define KDIMA ((MDIMC*NDIMC)/(MDIMA)) // Re-shaped tile dimension of matrix A: KDIMA * MDIMA +#define KDIMB ((MDIMC*NDIMC)/(NDIMB)) // Re-shaped tile dimension of matrix B: KDIMB * NDIMB +#define MWA (MWG/MDIMA) // Amount of loads-per-thread for matrix A (M-dimension) +#define KWA (KWG/KDIMA) // Amount of loads-per-thread for matrix A (K-dimension) +#define KWB (KWG/KDIMB) // Amount of loads-per-thread for matrix B (K-dimension) +#define NWB (NWG/NDIMB) // Amount of loads-per-thread for matrix B (N-dimension) + +// Settings +#define USE_VECTOR_MAD 0 // Unroll (0) or don't (1) unroll the vector MAD manually + +// ================================================================================================= + +// Data-widths in dimension M +#if VWM == 1 + typedef real realM; +#elif VWM == 2 + typedef real2 realM; +#elif VWM == 4 + typedef real4 realM; +#elif VWM == 8 + typedef real8 realM; +#elif VWM == 16 + typedef real16 realM; +#endif + +// Data-widths in dimension N +#if VWN == 1 + typedef real realN; +#elif VWN == 2 + typedef real2 realN; +#elif VWN == 4 + typedef real4 realN; +#elif VWN == 8 + typedef real8 realN; +#elif VWN == 16 + typedef real16 realN; +#endif + +// ================================================================================================= + +// Initializes the accumulation registers to zero +inline void InitAccRegisters(realM cpm[NWI][MWI/VWM]) { + #pragma unroll + for (int mi=0; mi<MWI/VWM; ++mi) { + #pragma unroll + for (int ni=0; ni<NWI; ++ni) { + #if VWM == 1 + SetToZero(cpm[ni][mi]); + #elif VWM == 2 + SetToZero(cpm[ni][mi].x); + SetToZero(cpm[ni][mi].y); + #elif VWM == 4 + SetToZero(cpm[ni][mi].x); + SetToZero(cpm[ni][mi].y); + SetToZero(cpm[ni][mi].z); + SetToZero(cpm[ni][mi].w); + #elif VWM == 8 + SetToZero(cpm[ni][mi].s0); + SetToZero(cpm[ni][mi].s1); + SetToZero(cpm[ni][mi].s2); + SetToZero(cpm[ni][mi].s3); + SetToZero(cpm[ni][mi].s4); + SetToZero(cpm[ni][mi].s5); + SetToZero(cpm[ni][mi].s6); + SetToZero(cpm[ni][mi].s7); + #elif VWM == 16 + SetToZero(cpm[ni][mi].s0); + SetToZero(cpm[ni][mi].s1); + SetToZero(cpm[ni][mi].s2); + SetToZero(cpm[ni][mi].s3); + SetToZero(cpm[ni][mi].s4); + SetToZero(cpm[ni][mi].s5); + SetToZero(cpm[ni][mi].s6); + SetToZero(cpm[ni][mi].s7); + SetToZero(cpm[ni][mi].s8); + SetToZero(cpm[ni][mi].s9); + SetToZero(cpm[ni][mi].sA); + SetToZero(cpm[ni][mi].sB); + SetToZero(cpm[ni][mi].sC); + SetToZero(cpm[ni][mi].sD); + SetToZero(cpm[ni][mi].sE); + SetToZero(cpm[ni][mi].sF); + #endif + } + } +} + +// ================================================================================================= + +// Caches global off-chip memory into local (shared) memory on-chip. This function is specific for +// caching the A input matrix. +#if SA == 1 +inline void GlobalToLocalA(const __global realM* restrict agm, __local realM* alm, + const int kSizeM, const int tid, const int kwg) { + const int la0 = tid % MDIMA; + const int la1 = tid / MDIMA; + #pragma unroll + for (int mia=0; mia<MWA/VWM; ++mia) { + #pragma unroll + for (int kia=0; kia<KWA; ++kia) { + + // Computes the indices based on strided/non-strided access + #if STRM == 0 + int mg = mia + la0*(MWA/VWM); + #elif STRM == 1 + int mg = la0 + mia*MDIMA; + #endif + + // Computes the indices for the global memory + int kg = kia + la1*KWA; + int idm = mg + get_group_id(0)*(MWG/VWM); + int idk = kg + kwg; + + // Loads the data from global memory (not transposed) into the local memory + alm[kg*(MWG/VWM) + mg] = agm[idk*(kSizeM/VWM) + idm]; + } + } +} +#endif + +// Same as above, but now for the B input matrix +#if SB == 1 +inline void GlobalToLocalB(const __global realN* restrict bgm, __local realN* blm, + const int kSizeN, const int tid, const int kwg) { + const int lb0 = tid % NDIMB; + const int lb1 = tid / NDIMB; + #pragma unroll + for (int kib=0; kib<KWB; ++kib) { + #pragma unroll + for (int nib=0; nib<NWB/VWN; ++nib) { + + // Computes the indices based on strided/non-strided access + #if STRN == 0 + int ng = nib + lb0*(NWB/VWN); + #elif STRN == 1 + int ng = lb0 + nib*NDIMB; + #endif + + // Computes the indices for the global memory + int kg = kib + lb1*KWB; + int idn = ng + get_group_id(1)*(NWG/VWN); + int idk = kg + kwg; + + // Loads the data from global memory (transposed) into the local memory + blm[kg*(NWG/VWN) + ng] = bgm[idk*(kSizeN/VWN) + idn]; + } + } +} +#endif + +// ================================================================================================= + +// Caches global off-chip memory directly into per-thread private memory (registers). This function +// is specific for caching the A input matrix. +#if SA == 0 +inline void GlobalToPrivateA(const __global realM* restrict agm, realM apm[MWI/VWM], + const int kSizeM, const int idk, const int kwg) { + #pragma unroll + for (int mi=0; mi<MWI/VWM; ++mi) { + + // Computes the indices based on strided/non-strided access + #if STRM == 0 + int mg = mi + get_local_id(0)*(MWI/VWM); + #elif STRM == 1 + int mg = get_local_id(0) + mi*MDIMC; + #endif + + // Computes the indices for the global memory + int idm = mg + get_group_id(0)*(MWG/VWM); + + // Loads the data from global memory (not transposed) and stores into registers + apm[mi] = agm[idk*(kSizeM/VWM) + idm]; + } +} +#endif + +// Same as above, but now for the B input matrix +#if SB == 0 +inline void GlobalToPrivateB(const __global realN* restrict bgm, realN bpm[NWI/VWN], + const int kSizeN, const int idk) { + #pragma unroll + for (int ni=0; ni<NWI/VWN; ++ni) { + + // Computes the indices based on strided/non-strided access + #if STRN == 0 + int ng = ni + get_local_id(1)*(NWI/VWN); + #elif STRN == 1 + int ng = get_local_id(1) + ni*NDIMC; + #endif + + // Computes the indices for the global memory + int idn = ng + get_group_id(1)*(NWG/VWN); + + // Loads the data from global memory (transposed) and stores into registers + bpm[ni] = bgm[idk*(kSizeN/VWN) + idn]; + } +} +#endif + +// ================================================================================================= + +// Caches on-chip local memory into per-thread private memory (registers). This function is specific +// for caching the A input matrix. +#if SA == 1 +inline void LocalToPrivateA(__local realM* alm, realM apm[MWI/VWM], const int kg) { + #pragma unroll + for (int mi=0; mi<MWI/VWM; ++mi) { + #if STRM == 0 + int mg = mi + get_local_id(0)*(MWI/VWM); + #elif STRM == 1 + int mg = get_local_id(0) + mi*MDIMC; + #endif + apm[mi] = alm[kg*(MWG/VWM) + mg]; + } +} +#endif + +// Same as above, but now for the B input matrix +#if SB == 1 +inline void LocalToPrivateB(__local realN* blm, realN bpm[NWI/VWN], const int kg) { + #pragma unroll + for (int ni=0; ni<NWI/VWN; ++ni) { + #if STRN == 0 + int ng = ni + get_local_id(1)*(NWI/VWN); + #elif STRN == 1 + int ng = get_local_id(1) + ni*NDIMC; + #endif + bpm[ni] = blm[kg*(NWG/VWN) + ng]; + } +} +#endif + +// ================================================================================================= + +// End of the C++11 raw string literal +)" + +// ================================================================================================= |