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releaase 2.11 (#703)

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This commit is contained in:
Aditya Atluri
2022-11-19 06:02:15 -08:00
committed by GitHub
parent 3c90f6aea6
commit c975e2ccbb
329 changed files with 47332 additions and 10607 deletions
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28
test/unit/conv/device/conv2d_testbed.h
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@ -192,7 +192,7 @@ public:
// Determine SMEM requirements and waive if not satisfied
//
int smem_size = int(sizeof(typename Conv2d::ImplicitGemmKernel::SharedStorage));
int smem_size = int(sizeof(typename Conv2d::UnderlyingKernel::SharedStorage));
cudaDeviceProp properties;
int device_idx;
@ -208,7 +208,7 @@ public:
throw std::runtime_error("cudaGetDeviceProperties() failed");
}
if (properties.sharedMemPerMultiprocessor < smem_size) {
if (properties.sharedMemPerBlockOptin < smem_size) {
return false;
}
@ -305,15 +305,15 @@ public:
cutlass::conv::implicit_gemm_tensor_c_size(kConvolutionalOperator, problem_size),
{
reinterpret_cast<ElementAccumulator*> (workspace.get()),
ReductionStrideIndex(tensor_C.stride()[Conv2d::ImplicitGemmKernel::kTensorCStrideIdx])
ReductionStrideIndex(tensor_C.stride()[Conv2d::UnderlyingKernel::kTensorCStrideIdx])
},
{
tensor_D_computed.device_data(),
ReductionStrideIndex(tensor_C.stride()[Conv2d::ImplicitGemmKernel::kTensorCStrideIdx])
ReductionStrideIndex(tensor_C.stride()[Conv2d::UnderlyingKernel::kTensorCStrideIdx])
},
{
tensor_C.device_data(),
ReductionStrideIndex(tensor_C.stride()[Conv2d::ImplicitGemmKernel::kTensorCStrideIdx])
ReductionStrideIndex(tensor_C.stride()[Conv2d::UnderlyingKernel::kTensorCStrideIdx])
},
// apply alpha, beta to obtain the following equation alpha * ReduceAdd(A * B) + beta * C
{alpha, beta}
@ -637,7 +637,7 @@ bool TestAllConv2d(
// CUTLASS DGRAD's *unity* stride specialization only support stride {1, 1}
if ((ImplicitGemm::kConvolutionalOperator ==
cutlass::conv::Operator::kDgrad) &&
(ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kStrideSupport ==
(ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kStrideSupport ==
cutlass::conv::StrideSupport::kUnity)) {
if (!((conv_problem.stride_h == 1) && (conv_problem.stride_w == 1))) {
continue;
@ -645,17 +645,17 @@ bool TestAllConv2d(
}
// Fixed channels algorithm requires channel count to match access size
if (ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kIteratorAlgorithm ==
if (ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kIteratorAlgorithm ==
cutlass::conv::IteratorAlgorithm::kFixedChannels) {
if (conv_problem.C != ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::AccessType::kElements) {
if (conv_problem.C != ImplicitGemm::UnderlyingKernel::Mma::IteratorA::AccessType::kElements) {
continue;
}
}
// Few channels algorithm requires channel count to match access size
if (ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kIteratorAlgorithm ==
if (ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kIteratorAlgorithm ==
cutlass::conv::IteratorAlgorithm::kFewChannels) {
if (conv_problem.C % ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::AccessType::kElements) {
if (conv_problem.C % ImplicitGemm::UnderlyingKernel::Mma::IteratorA::AccessType::kElements) {
continue;
}
}
@ -665,7 +665,7 @@ bool TestAllConv2d(
// to run strided dgrad for non-unity strides
if ((ImplicitGemm::kConvolutionalOperator ==
cutlass::conv::Operator::kDgrad) &&
(ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kStrideSupport ==
(ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kStrideSupport ==
cutlass::conv::StrideSupport::kStrided)) {
if (((conv_problem.stride_h == 1) && (conv_problem.stride_w == 1))) {
continue;
@ -704,14 +704,14 @@ bool TestAllConv2d(
}
// Small-channels convolution can't run here.
if (ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kIteratorAlgorithm ==
if (ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kIteratorAlgorithm ==
cutlass::conv::IteratorAlgorithm::kFixedChannels) {
return true;
}
// Small-channels convolution can't run here.
if (ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kIteratorAlgorithm ==
if (ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kIteratorAlgorithm ==
cutlass::conv::IteratorAlgorithm::kFewChannels) {
return true;
@ -720,7 +720,7 @@ bool TestAllConv2d(
// CUTLASS DGRAD's *strided* specialization does not support split-k mode
if ((ImplicitGemm::kConvolutionalOperator ==
cutlass::conv::Operator::kDgrad) &&
(ImplicitGemm::ImplicitGemmKernel::Mma::IteratorA::kStrideSupport ==
(ImplicitGemm::UnderlyingKernel::Mma::IteratorA::kStrideSupport ==
cutlass::conv::StrideSupport::kStrided)) {
passed = testbed.run(