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-rw-r--r--unsupported/test/cxx11_tensor_contract_cuda.cu66
1 files changed, 65 insertions, 1 deletions
diff --git a/unsupported/test/cxx11_tensor_contract_cuda.cu b/unsupported/test/cxx11_tensor_contract_cuda.cu
index 6d1ef07f9..767e9c678 100644
--- a/unsupported/test/cxx11_tensor_contract_cuda.cu
+++ b/unsupported/test/cxx11_tensor_contract_cuda.cu
@@ -14,7 +14,9 @@
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
#define EIGEN_USE_GPU
-
+#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500
+#include <cuda_fp16.h>
+#endif
#include "main.h"
#include <unsupported/Eigen/CXX11/Tensor>
@@ -84,6 +86,65 @@ void test_cuda_contraction(int m_size, int k_size, int n_size)
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>
void test_cuda_contraction_m() {
for (int k = 32; k < 256; k++) {
@@ -138,6 +199,9 @@ void test_cxx11_tensor_cuda()
CALL_SUBTEST_1(test_cuda_contraction<ColMajor>(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_3(test_cuda_contraction_m<RowMajor>());