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Updates corresponding to the latest round of PR feedback

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The major changes are

1. Moving CUDA/PacketMath.h to GPU/PacketMath.h
2. Moving CUDA/MathFunctions.h to GPU/MathFunction.h
3. Moving CUDA/CudaSpecialFunctions.h to GPU/GpuSpecialFunctions.h
    The above three changes effectively enable the Eigen "Packet" layer for the HIP platform

4. Merging the "hip_basic" and "cuda_basic" unit tests into one ("gpu_basic")
5. Updating the "EIGEN_DEVICE_FUNC" marking in some places

The change has been tested on the HIP and CUDA platforms.
This commit is contained in:
Deven Desai
2018-07-11 10:39:54 -04:00
parent 1fe0b74904
commit 876f392c39
18 changed files with 158 additions and 285 deletions
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4
test/CMakeLists.txt
View File

@@ -399,7 +399,7 @@ if(CUDA_FOUND)
cuda_include_directories(${CMAKE_CURRENT_BINARY_DIR})
set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")
ei_add_test(cuda_basic)
ei_add_test(gpu_basic)
unset(EIGEN_ADD_TEST_FILENAME_EXTENSION)
@@ -429,7 +429,7 @@ if (EIGEN_TEST_HIP)
include_directories(${HIP_PATH}/include)
set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")
ei_add_test(hip_basic)
ei_add_test(gpu_basic)
unset(EIGEN_ADD_TEST_FILENAME_EXTENSION)
elseif (${HIP_PLATFORM} STREQUAL "nvcc")

63
test/gpu_basic.cu
View File

@@ -15,13 +15,11 @@
#define EIGEN_TEST_NO_LONGDOUBLE
#define EIGEN_TEST_NO_COMPLEX
#define EIGEN_TEST_FUNC cuda_basic
#define EIGEN_TEST_FUNC gpu_basic
#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
#include <math_constants.h>
#include <cuda.h>
#include "main.h"
#include "cuda_common.h"
#include "gpu_common.h"
// Check that dense modules can be properly parsed by nvcc
#include <Eigen/Dense>
@@ -164,40 +162,51 @@ struct matrix_inverse {
}
};
void test_cuda_basic()
void test_gpu_basic()
{
ei_test_init_cuda();
ei_test_init_gpu();
int nthreads = 100;
Eigen::VectorXf in, out;
#ifndef __CUDA_ARCH__
#if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
int data_size = nthreads * 512;
in.setRandom(data_size);
out.setRandom(data_size);
#endif
CALL_SUBTEST( run_and_compare_to_cuda(coeff_wise<Vector3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(coeff_wise<Array44f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(replicate<Array4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(replicate<Array33f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(redux<Array4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(redux<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(prod_test<Matrix3f,Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(prod_test<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix3f,Vector3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(coeff_wise<Vector3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(coeff_wise<Array44f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(matrix_inverse<Matrix2f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(matrix_inverse<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(matrix_inverse<Matrix4f>(), nthreads, in, out) );
#if !defined(EIGEN_USE_HIP)
// FIXME
// These subtests result in a compile failure on the HIP platform
//
// eigen-upstream/Eigen/src/Core/Replicate.h:61:65: error:
// base class 'internal::dense_xpr_base<Replicate<Array<float, 4, 1, 0, 4, 1>, -1, -1> >::type'
// (aka 'ArrayBase<Eigen::Replicate<Eigen::Array<float, 4, 1, 0, 4, 1>, -1, -1> >') has protected default constructor
CALL_SUBTEST( run_and_compare_to_gpu(replicate<Array4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(replicate<Array33f>(), nthreads, in, out) );
#endif
CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues_direct<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues_direct<Matrix2f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_cuda(eigenvalues<Matrix4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(redux<Array4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(redux<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(prod_test<Matrix3f,Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(prod_test<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(diagonal<Matrix3f,Vector3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(matrix_inverse<Matrix2f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(matrix_inverse<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(matrix_inverse<Matrix4f>(), nthreads, in, out) );
#if !defined(EIGEN_USE_HIP)
// FIXME
// These subtests result in a linking error on the HIP platform
CALL_SUBTEST( run_and_compare_to_gpu(eigenvalues_direct<Matrix3f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(eigenvalues_direct<Matrix2f>(), nthreads, in, out) );
CALL_SUBTEST( run_and_compare_to_gpu(eigenvalues<Matrix4f>(), nthreads, in, out) );
#endif
}

86
test/gpu_common.h
View File

@@ -1,13 +1,22 @@
#ifndef EIGEN_TEST_CUDA_COMMON_H
#define EIGEN_TEST_CUDA_COMMON_H
#ifndef EIGEN_TEST_GPU_COMMON_H
#define EIGEN_TEST_GPU_COMMON_H
#ifdef EIGEN_USE_HIP
#include <hip/hip_runtime.h>
#include <hip/hip_runtime_api.h>
#else
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#endif
#include <cuda.h>
#include <cuda_runtime.h>
#include <cuda_runtime_api.h>
#include <iostream>
#ifndef __CUDACC__
#define EIGEN_USE_GPU
#include <unsupported/Eigen/CXX11/src/Tensor/TensorGpuHipCudaDefines.h>
#if !defined(__CUDACC__) && !defined(__HIPCC__)
dim3 threadIdx, blockDim, blockIdx;
#endif
@@ -21,7 +30,7 @@ void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out)
template<typename Kernel, typename Input, typename Output>
__global__
void run_on_cuda_meta_kernel(const Kernel ker, int n, const Input* in, Output* out)
void run_on_gpu_meta_kernel(const Kernel ker, int n, const Input* in, Output* out)
{
int i = threadIdx.x + blockIdx.x*blockDim.x;
if(i<n) {
@@ -31,61 +40,70 @@ void run_on_cuda_meta_kernel(const Kernel ker, int n, const Input* in, Output* o
template<typename Kernel, typename Input, typename Output>
void run_on_cuda(const Kernel& ker, int n, const Input& in, Output& out)
void run_on_gpu(const Kernel& ker, int n, const Input& in, Output& out)
{
typename Input::Scalar* d_in;
typename Output::Scalar* d_out;
std::ptrdiff_t in_bytes = in.size() * sizeof(typename Input::Scalar);
std::ptrdiff_t out_bytes = out.size() * sizeof(typename Output::Scalar);
cudaMalloc((void**)(&d_in), in_bytes);
cudaMalloc((void**)(&d_out), out_bytes);
gpuMalloc((void**)(&d_in), in_bytes);
gpuMalloc((void**)(&d_out), out_bytes);
cudaMemcpy(d_in, in.data(), in_bytes, cudaMemcpyHostToDevice);
cudaMemcpy(d_out, out.data(), out_bytes, cudaMemcpyHostToDevice);
gpuMemcpy(d_in, in.data(), in_bytes, gpuMemcpyHostToDevice);
gpuMemcpy(d_out, out.data(), out_bytes, gpuMemcpyHostToDevice);
// Simple and non-optimal 1D mapping assuming n is not too large
// That's only for unit testing!
dim3 Blocks(128);
dim3 Grids( (n+int(Blocks.x)-1)/int(Blocks.x) );
cudaThreadSynchronize();
run_on_cuda_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out);
cudaThreadSynchronize();
gpuDeviceSynchronize();
#ifdef EIGEN_USE_HIP
hipLaunchKernelGGL(run_on_gpu_meta_kernel<Kernel,
typename std::decay<decltype(*d_in)>::type,
typename std::decay<decltype(*d_out)>::type>,
dim3(Grids), dim3(Blocks), 0, 0, ker, n, d_in, d_out);
#else
run_on_gpu_meta_kernel<<<Grids,Blocks>>>(ker, n, d_in, d_out);
#endif
gpuDeviceSynchronize();
// check inputs have not been modified
cudaMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, cudaMemcpyDeviceToHost);
cudaMemcpy(out.data(), d_out, out_bytes, cudaMemcpyDeviceToHost);
gpuMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, gpuMemcpyDeviceToHost);
gpuMemcpy(out.data(), d_out, out_bytes, gpuMemcpyDeviceToHost);
cudaFree(d_in);
cudaFree(d_out);
gpuFree(d_in);
gpuFree(d_out);
}
template<typename Kernel, typename Input, typename Output>
void run_and_compare_to_cuda(const Kernel& ker, int n, const Input& in, Output& out)
void run_and_compare_to_gpu(const Kernel& ker, int n, const Input& in, Output& out)
{
Input in_ref, in_cuda;
Output out_ref, out_cuda;
#ifndef __CUDA_ARCH__
in_ref = in_cuda = in;
out_ref = out_cuda = out;
Input in_ref, in_gpu;
Output out_ref, out_gpu;
#if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
in_ref = in_gpu = in;
out_ref = out_gpu = out;
#endif
run_on_cpu (ker, n, in_ref, out_ref);
run_on_cuda(ker, n, in_cuda, out_cuda);
#ifndef __CUDA_ARCH__
VERIFY_IS_APPROX(in_ref, in_cuda);
VERIFY_IS_APPROX(out_ref, out_cuda);
run_on_gpu(ker, n, in_gpu, out_gpu);
#if !defined(__CUDA_ARCH__) && !defined(__HIP_DEVICE_COMPILE__)
VERIFY_IS_APPROX(in_ref, in_gpu);
VERIFY_IS_APPROX(out_ref, out_gpu);
#endif
}
void ei_test_init_cuda()
void ei_test_init_gpu()
{
int device = 0;
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, device);
std::cout << "CUDA device info:\n";
gpuDeviceProp_t deviceProp;
gpuGetDeviceProperties(&deviceProp, device);
std::cout << "GPU device info:\n";
std::cout << " name: " << deviceProp.name << "\n";
std::cout << " capability: " << deviceProp.major << "." << deviceProp.minor << "\n";
std::cout << " multiProcessorCount: " << deviceProp.multiProcessorCount << "\n";
@@ -98,4 +116,4 @@ void ei_test_init_cuda()
std::cout << " computeMode: " << deviceProp.computeMode << "\n";
}
#endif // EIGEN_TEST_CUDA_COMMON_H
#endif // EIGEN_TEST_GPU_COMMON_H