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Started to work on contractions and reductions using half floats

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This commit is contained in:
Benoit Steiner 2016-02-19 15:59:59 +00:00
parent f3352e0fb0
commit a08d2ff0c9
1 changed files with 94 additions and 1 deletions
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95
unsupported/test/cxx11_tensor_of_float16_cuda.cu
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@ -94,6 +94,97 @@ void test_cuda_elementwise() {
gpu_device.deallocate(d_res_float);
}
/*
void test_cuda_contractions() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
int rows = 101;
int cols = 101;
int num_elem = rows*cols;
float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_half = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float1(
d_float1, rows, cols);
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float2(
d_float2, rows, cols);
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_res_half(
d_res_half, rows, cols);
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_res_float(
d_res_float, rows, cols);
gpu_float1.device(gpu_device) = gpu_float1.random();
gpu_float2.device(gpu_device) = gpu_float2.random();
typedef Tensor<float, 2>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims(DimPair(1, 0));
gpu_res_float.device(gpu_device) = gpu_float1.contract(gpu_float2, dims);
gpu_res_half.device(gpu_device) = gpu_float1.cast<half>().contract(gpu_float2.cast<half>(), dims).cast<float>();
Tensor<float, 2> half_prec(rows, cols);
Tensor<float, 2> full_prec(rows, cols);
gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(float));
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
VERIFY_IS_APPROX(full_prec(i, j), half_prec(i, j));
}
}
gpu_device.deallocate(d_float1);
gpu_device.deallocate(d_float2);
gpu_device.deallocate(d_res_half);
gpu_device.deallocate(d_res_float);
}
void test_cuda_reductions() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
int size = 101;
int num_elem = size*size;
float* d_float1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_float2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_half = (float*)gpu_device.allocate(size * sizeof(float));
float* d_res_float = (float*)gpu_device.allocate(size * sizeof(float));
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float1(
d_float1, size, size);
Eigen::TensorMap<Eigen::Tensor<float, 2>, Eigen::Aligned> gpu_float2(
d_float2, size, size);
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half(
d_res_half, size);
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
d_res_float, size);
gpu_float1.device(gpu_device) = gpu_float1.random();
gpu_float2.device(gpu_device) = gpu_float2.random();
Eigen::array<int, 1> redux_dim = {{0}};
gpu_res_float.device(gpu_device) = gpu_float1.sum(redux_dim);
gpu_res_half.device(gpu_device) = gpu_float1.cast<half>().sum(redux_dim).cast<float>();
Tensor<float, 1> half_prec(size);
Tensor<float, 1> full_prec(size);
gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(float));
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
for (int i = 0; i < size; ++i) {
VERIFY_IS_APPROX(full_prec(i), half_prec(i));
}
gpu_device.deallocate(d_float1);
gpu_device.deallocate(d_float2);
gpu_device.deallocate(d_res_half);
gpu_device.deallocate(d_res_float);
}
*/
#endif
@ -101,6 +192,8 @@ void test_cxx11_tensor_of_float16_cuda()
{
#ifdef EIGEN_HAS_CUDA_FP16
CALL_SUBTEST_1(test_cuda_conversion());
CALL_SUBTEST_1(test_cuda_element_wise());
CALL_SUBTEST_1(test_cuda_elementwise());
// CALL_SUBTEST_2(test_cuda_contractions());
// CALL_SUBTEST_3(test_cuda_reductions());
#endif
}