mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-03-07 18:27:40 +08:00
Updated the tensor sum and mean reducer to enable them to process complex numbers on cuda gpus.
This commit is contained in:
parent
f3a00dd2b5
commit
2bda1b0d93
@ -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>
|
||||
|
@ -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());
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user