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Added tests for full contractions using thread pools and gpu devices.

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Fixed a couple of issues in the corresponding code.
This commit is contained in:
Benoit Steiner 2016-05-05 09:05:45 -07:00
parent 06d774bf58
commit f363e533aa
5 changed files with 109 additions and 8 deletions
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4
unsupported/Eigen/CXX11/src/Tensor/TensorContraction.h
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@ -143,8 +143,8 @@ struct TensorContractionEvaluatorBase
static const int NumDims = LDims + RDims - 2 * ContractDims; static const int NumDims = LDims + RDims - 2 * ContractDims;
typedef array<Index, ContractDims> contract_t; typedef array<Index, ContractDims> contract_t;
typedef array<Index, max_n_1<LDims - ContractDims>::size> left_nocontract_t; typedef array<Index, LDims - ContractDims> left_nocontract_t;
typedef array<Index, max_n_1<RDims - ContractDims>::size> right_nocontract_t; typedef array<Index, RDims - ContractDims> right_nocontract_t;
typedef DSizes<Index, NumDims> Dimensions; typedef DSizes<Index, NumDims> Dimensions;

6
unsupported/Eigen/CXX11/src/Tensor/TensorContractionCuda.h
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@ -1240,10 +1240,10 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
typedef array<Index, RDims> right_dim_mapper_t; typedef array<Index, RDims> right_dim_mapper_t;
typedef array<Index, ContractDims> contract_t; typedef array<Index, ContractDims> contract_t;
typedef array<Index, max_n_1<LDims - ContractDims>::size> left_nocontract_t; typedef array<Index, LDims - ContractDims> left_nocontract_t;
typedef array<Index, max_n_1<RDims - ContractDims>::size> right_nocontract_t; typedef array<Index, RDims - ContractDims> right_nocontract_t;
static const int NumDims = max_n_1<LDims + RDims - 2 * ContractDims>::size; static const int NumDims = LDims + RDims - 2 * ContractDims;
typedef DSizes<Index, NumDims> Dimensions; typedef DSizes<Index, NumDims> Dimensions;

6
unsupported/Eigen/CXX11/src/Tensor/TensorContractionThreadPool.h
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@ -92,10 +92,10 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
typedef array<Index, RDims> right_dim_mapper_t; typedef array<Index, RDims> right_dim_mapper_t;
typedef array<Index, ContractDims> contract_t; typedef array<Index, ContractDims> contract_t;
typedef array<Index, max_n_1<LDims - ContractDims>::size> left_nocontract_t; typedef array<Index, LDims - ContractDims> left_nocontract_t;
typedef array<Index, max_n_1<RDims - ContractDims>::size> right_nocontract_t; typedef array<Index, RDims - ContractDims> right_nocontract_t;
static const int NumDims = max_n_1<LDims + RDims - 2 * ContractDims>::size; static const int NumDims = LDims + RDims - 2 * ContractDims;
typedef DSizes<Index, NumDims> Dimensions; typedef DSizes<Index, NumDims> Dimensions;

62
unsupported/test/cxx11_tensor_contract_cuda.cu
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@ -84,6 +84,65 @@ void test_cuda_contraction(int m_size, int k_size, int n_size)
cudaFree((void*)d_t_result); cudaFree((void*)d_t_result);
} }
template<int DataLayout>
void test_scalar(int m_size, int k_size, int n_size)
{
std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
// with these dimensions, the output has 300 * 140 elements, which is
// more than 30 * 1024, which is the number of threads in blocks on
// a 15 SM GK110 GPU
Tensor<float, 2, DataLayout> t_left(m_size, k_size);
Tensor<float, 2, DataLayout> t_right(k_size, n_size);
Tensor<float, 0, DataLayout> t_result;
Tensor<float, 0, DataLayout> t_result_gpu;
Eigen::array<DimPair, 2> dims(DimPair(0, 0), DimPair(1, 1));
t_left.setRandom();
t_right.setRandom();
std::size_t t_left_bytes = t_left.size() * sizeof(float);
std::size_t t_right_bytes = t_right.size() * sizeof(float);
std::size_t t_result_bytes = sizeof(float);
float* d_t_left;
float* d_t_right;
float* d_t_result;
cudaMalloc((void**)(&d_t_left), t_left_bytes);
cudaMalloc((void**)(&d_t_right), t_right_bytes);
cudaMalloc((void**)(&d_t_result), t_result_bytes);
cudaMemcpy(d_t_left, t_left.data(), t_left_bytes, cudaMemcpyHostToDevice);
cudaMemcpy(d_t_right, t_right.data(), t_right_bytes, cudaMemcpyHostToDevice);
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
gpu_t_left(d_t_left, m_size, k_size);
Eigen::TensorMap<Eigen::Tensor<float, 2, DataLayout> >
gpu_t_right(d_t_right, k_size, n_size);
Eigen::TensorMap<Eigen::Tensor<float, 0, DataLayout> >
gpu_t_result(d_t_result);
gpu_t_result.device(gpu_device) = gpu_t_left.contract(gpu_t_right, dims);
t_result = t_left.contract(t_right, dims);
cudaMemcpy(t_result_gpu.data(), d_t_result, t_result_bytes, cudaMemcpyDeviceToHost);
if (fabs(t_result() - t_result_gpu()) > 1e-4f &&
!Eigen::internal::isApprox(t_result(), t_result_gpu(), 1e-4f)) {
std::cout << "mismatch detected: " << t_result()
<< " vs " << t_result_gpu() << std::endl;
assert(false);
}
cudaFree((void*)d_t_left);
cudaFree((void*)d_t_right);
cudaFree((void*)d_t_result);
}
template<int DataLayout> template<int DataLayout>
void test_cuda_contraction_m() { void test_cuda_contraction_m() {
for (int k = 32; k < 256; k++) { for (int k = 32; k < 256; k++) {
@ -138,6 +197,9 @@ void test_cxx11_tensor_cuda()
CALL_SUBTEST_1(test_cuda_contraction<ColMajor>(128, 128, 128)); CALL_SUBTEST_1(test_cuda_contraction<ColMajor>(128, 128, 128));
CALL_SUBTEST_1(test_cuda_contraction<RowMajor>(128, 128, 128)); CALL_SUBTEST_1(test_cuda_contraction<RowMajor>(128, 128, 128));
CALL_SUBTEST_1(test_scalar<ColMajor>(128, 128, 128));
CALL_SUBTEST_1(test_scalar<RowMajor>(128, 128, 128));
CALL_SUBTEST_2(test_cuda_contraction_m<ColMajor>()); CALL_SUBTEST_2(test_cuda_contraction_m<ColMajor>());
CALL_SUBTEST_3(test_cuda_contraction_m<RowMajor>()); CALL_SUBTEST_3(test_cuda_contraction_m<RowMajor>());

39
unsupported/test/cxx11_tensor_thread_pool.cpp
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@ -233,6 +233,42 @@ void test_multithread_contraction_agrees_with_singlethread() {
} }
template<int DataLayout>
void test_full_contraction() {
int contract_size1 = internal::random<int>(1, 500);
int contract_size2 = internal::random<int>(1, 500);
Tensor<float, 2, DataLayout> left(contract_size1,
contract_size2);
Tensor<float, 2, DataLayout> right(contract_size1,
contract_size2);
left.setRandom();
right.setRandom();
// add constants to shift values away from 0 for more precision
left += left.constant(1.5f);
right += right.constant(1.5f);
typedef Tensor<float, 2>::DimensionPair DimPair;
Eigen::array<DimPair, 2> dims({{DimPair(0, 0), DimPair(1, 1)}});
Eigen::ThreadPool tp(internal::random<int>(2, 11));
Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(2, 11));
Tensor<float, 0, DataLayout> st_result;
st_result = left.contract(right, dims);
Tensor<float, 0, DataLayout> tp_result;
tp_result.device(thread_pool_device) = left.contract(right, dims);
VERIFY(dimensions_match(st_result.dimensions(), tp_result.dimensions()));
// if both of the values are very small, then do nothing (because the test will fail
// due to numerical precision issues when values are small)
if (fabs(st_result() - tp_result()) >= 1e-4) {
VERIFY_IS_APPROX(st_result(), tp_result());
}
}
template<int DataLayout> template<int DataLayout>
void test_multithreaded_reductions() { void test_multithreaded_reductions() {
const int num_threads = internal::random<int>(3, 11); const int num_threads = internal::random<int>(3, 11);
@ -324,6 +360,9 @@ void test_cxx11_tensor_thread_pool()
CALL_SUBTEST_4(test_contraction_corner_cases<ColMajor>()); CALL_SUBTEST_4(test_contraction_corner_cases<ColMajor>());
CALL_SUBTEST_4(test_contraction_corner_cases<RowMajor>()); CALL_SUBTEST_4(test_contraction_corner_cases<RowMajor>());
CALL_SUBTEST_4(test_full_contraction<ColMajor>());
CALL_SUBTEST_4(test_full_contraction<RowMajor>());
CALL_SUBTEST_5(test_multithreaded_reductions<ColMajor>()); CALL_SUBTEST_5(test_multithreaded_reductions<ColMajor>());
CALL_SUBTEST_5(test_multithreaded_reductions<RowMajor>()); CALL_SUBTEST_5(test_multithreaded_reductions<RowMajor>());