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Updated the tensor sum and mean reducer to enable them to process complex numbers on cuda gpus.

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This commit is contained in:
Benoit Steiner 2016-09-28 17:08:41 -07:00
parent f3a00dd2b5
commit 2bda1b0d93
2 changed files with 41 additions and 2 deletions
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6
unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
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@ -99,7 +99,8 @@ template <typename T> struct SumReducer
static const bool IsStateful = false; static const bool IsStateful = false;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const { 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> template <typename Packet>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const { 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) { } MeanReducer() : scalarCount_(0), packetCount_(0) { }
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) { 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_++; scalarCount_++;
} }
template <typename Packet> template <typename Packet>

37
unsupported/test/cxx11_tensor_complex_cuda.cu
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@ -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() void test_cxx11_tensor_complex()
{ {
CALL_SUBTEST(test_cuda_nullary()); CALL_SUBTEST(test_cuda_nullary());
CALL_SUBTEST(test_cuda_sum_reductions());
} }