cutlass/tools/test/unit/gemm/splitK_sgemm.cu
Andrew Kerr 877bdcace6
Cutlass 1.3 Release (#42)
CUTLASS 1.3 Release
- Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
2019-03-20 10:49:17 -07:00

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#include "cutlass_unit_test.h"
#include "cutlass/gemm/gemm.h"
#include "cutlass/gemm/sgemm_traits.h"
#include "cutlass/reduction/batched_reduction_traits.h"
#include "tools/test/unit/gemm/gemm_testbed.h"
#include "tools/test/unit/gemm/run_gemm.h"
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x512_nn) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 512;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x512_nt) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 512;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x512_tn) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 512;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x512_tt) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 512;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x500_nn) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 500;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x500_nt) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 500;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x500_tn) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 500;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_128x256x500_tt) {
const int splits_count = 16;
const int m = 128;
const int n = 256;
const int k = 500;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_1024x64x4096_nn) {
const int splits_count = 16;
const int m = 1024;
const int n = 64;
const int k = 4096;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_1024x64x4096_nt) {
const int splits_count = 16;
const int m = 1024;
const int n = 64;
const int k = 4096;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kColumnMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_1024x64x4096_tn) {
const int splits_count = 16;
const int m = 1024;
const int n = 64;
const int k = 4096;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(SplitK_sgemm_128x128x8_splits16, sgemm_1024x64x4096_tt) {
const int splits_count = 16;
const int m = 1024;
const int n = 64;
const int k = 4096;
/*batched sgemm traits*/
typedef cutlass::gemm::SgemmTraits<cutlass::MatrixLayout::kRowMajor,
cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
SgemmTraits;
/*batched reduction traits*/
typedef cutlass::reduction::BatchedReductionTraits<float,
float,
float,
float,
float, /*accumulation type*/
splits_count,
cutlass::Shape<1, 1, 128>,
cutlass::Shape<1, 1, 64>,
cutlass::Shape<1, 1, 2> >
BatchedReductionTraits;
run_splitK_gemm<SgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
}