cutlass/tools/test/unit/reduction/batched_reduction.cu

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#include "cutlass_unit_test.h"
#include "cutlass/shape.h"
#include "tools/util/host_tensor.h"
#include "cutlass/reduction/batched_reduction.h"
#include "cutlass/reduction/batched_reduction_traits.h"
#include "tools/test/unit/reduction/test_batched_reduction.h"
#include "tools/test/unit/reduction/batched_reduction_testbed.h"

////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_float, batched_reduction_128x256x16) {
  /*
  The output matrix is 128x256
  The input matrix is 128x256x16
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 16;
  typedef cutlass::reduction::BatchedReductionTraits<float, /*A*/
    float, /*C*/
    float, /*D*/
    float, /*alpha and beta*/
    float, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
  BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_double, batched_reduction_128x256x16) {
  /*
  D = alpha * Reduction(A) + beta * C
  The output matrix D is 128x256
  The input matrix A is 128x256x16
  The input matrix C is 128x256
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 16;
  typedef cutlass::reduction::BatchedReductionTraits<double,
    double,
    double,
    double,
    double, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
    BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(Batched_reduction_half, batched_reduction_128x256x16) {
  /*
  The output matrix is 128x256
  The input matrix is 128x256x16
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 16;
  typedef cutlass::reduction::BatchedReductionTraits<half,
    half,
    half,
    half,
    half, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
    BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}
////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_float, batched_reduction_128x64x80) {
  /*
  The output matrix is 128x64
  The input matrix is 128x64x80
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 64;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 80;
  typedef cutlass::reduction::BatchedReductionTraits<float,
    float,
    float,
    float,
    float, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
    BatchedReductionTraits_80;

  test_batched_reduction<BatchedReductionTraits_80>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_double, batched_reduction_128x64x80) {
  /*
  The output matrix is 128x64
  The input matrix is 128x64x80
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 64;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 80;
  typedef cutlass::reduction::BatchedReductionTraits<double,
    double,
    double,
    double,
    double, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
    BatchedReductionTraits_80;

  test_batched_reduction<BatchedReductionTraits_80>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(Batched_reduction_half, batched_reduction_128x64x80) {
  /*
  The output matrix is 128x64
  The input matrix is 128x64x80
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 64;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 80;
  typedef cutlass::reduction::BatchedReductionTraits<half,
    half,
    half,
    half,
    half, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 2> >
    BatchedReductionTraits_80;

  test_batched_reduction<BatchedReductionTraits_80>(m, n, lda, ldc, ldd);

}
////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_float_threadShape1, batched_reduction_128x256x90) {
  /*
  The output matrix is 128x256
  The input matrix is 128x256x90
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 90;
  typedef cutlass::reduction::BatchedReductionTraits<float, /*A*/
    float, /*C*/
    float, /*D*/
    float, /*alpha and beta*/
    float, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 1> >
    BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////

TEST(Batched_reduction_double_threadShape1, batched_reduction_128x256x90) {
  /*
  The output matrix is 128x256
  The input matrix is 128x256x90
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 90;
  typedef cutlass::reduction::BatchedReductionTraits<double, /*A*/
    double, /*C*/
    double, /*D*/
    double, /*alpha and beta*/
    double, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 1> >
    BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}

////////////////////////////////////////////////////////////////////////////////////////////////////
TEST(Batched_reduction_half_threadShape1, batched_reduction_128x256x90) {
  /*
  The output matrix is 128x256
  The input matrix is 128x256x90
  The reduction will be applied at the third dim of input matrix
  */


  const int m = 128;
  const int n = 256;
  const int lda = 128;
  const int ldc = 128;
  const int ldd = 128;
  const int reduction_size = 90;
  typedef cutlass::reduction::BatchedReductionTraits<half, /*A*/
    half, /*C*/
    half, /*D*/
    half, /*alpha and beta*/
    half, /*accumulation type*/
    reduction_size,
    cutlass::Shape<1, 1, 128>,
    cutlass::Shape<1, 1, 64>,
    cutlass::Shape<1, 1, 1> >
    BatchedReductionTraits_16;

  test_batched_reduction<BatchedReductionTraits_16>(m, n, lda, ldc, ldd);

}