diff options
author | Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-09-28 17:08:41 -0700 |
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committer | Benoit Steiner <benoit.steiner.goog@gmail.com> | 2016-09-28 17:08:41 -0700 |
commit | 2bda1b0d93fb627d0c500ec48b20302d44c32cb7 (patch) | |
tree | db17aeb9cfb9798167621269612669c168d7e5ef /unsupported | |
parent | f3a00dd2b5faf6037b72dee50213e4d4538dd77a (diff) |
Updated the tensor sum and mean reducer to enable them to process complex numbers on cuda gpus.
Diffstat (limited to 'unsupported')
-rw-r--r-- | unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h | 6 | ||||
-rw-r--r-- | unsupported/test/cxx11_tensor_complex_cuda.cu | 37 |
2 files changed, 41 insertions, 2 deletions
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h index 760074622..eddb86597 100644 --- a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h +++ b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h @@ -99,7 +99,8 @@ template <typename T> struct SumReducer static const bool IsStateful = false; EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const { - (*accum) += t; + internal::scalar_sum_op<T> sum_op; + *accum = sum_op(*accum, t); } template <typename Packet> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const { @@ -145,7 +146,8 @@ template <typename T> struct MeanReducer MeanReducer() : scalarCount_(0), packetCount_(0) { } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) { - (*accum) += t; + internal::scalar_sum_op<T> sum_op; + *accum = sum_op(*accum, t); scalarCount_++; } template <typename Packet> diff --git a/unsupported/test/cxx11_tensor_complex_cuda.cu b/unsupported/test/cxx11_tensor_complex_cuda.cu index 74befe670..f895efd01 100644 --- a/unsupported/test/cxx11_tensor_complex_cuda.cu +++ b/unsupported/test/cxx11_tensor_complex_cuda.cu @@ -71,8 +71,45 @@ void test_cuda_nullary() { } +static void test_cuda_sum_reductions() { + + Eigen::CudaStreamDevice stream; + Eigen::GpuDevice gpu_device(&stream); + + const int num_rows = internal::random<int>(1024, 5*1024); + const int num_cols = internal::random<int>(1024, 5*1024); + + Tensor<std::complex<float>, 2> in(num_rows, num_cols); + in.setRandom(); + + Tensor<std::complex<float>, 0> full_redux; + full_redux = in.sum(); + + std::size_t in_bytes = in.size() * sizeof(std::complex<float>); + std::size_t out_bytes = full_redux.size() * sizeof(std::complex<float>); + std::complex<float>* gpu_in_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(in_bytes)); + std::complex<float>* gpu_out_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(out_bytes)); + gpu_device.memcpyHostToDevice(gpu_in_ptr, in.data(), in_bytes); + + TensorMap<Tensor<std::complex<float>, 2> > in_gpu(gpu_in_ptr, num_rows, num_cols); + TensorMap<Tensor<std::complex<float>, 0> > out_gpu(gpu_out_ptr); + + out_gpu.device(gpu_device) = in_gpu.sum(); + + Tensor<std::complex<float>, 0> full_redux_gpu; + gpu_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_ptr, out_bytes); + gpu_device.synchronize(); + + // Check that the CPU and GPU reductions return the same result. + VERIFY_IS_APPROX(full_redux(), full_redux_gpu()); + + gpu_device.deallocate(gpu_in_ptr); + gpu_device.deallocate(gpu_out_ptr); +} + void test_cxx11_tensor_complex() { CALL_SUBTEST(test_cuda_nullary()); + CALL_SUBTEST(test_cuda_sum_reductions()); } |