deleting hip specific files that are no longer required
diff --git a/test/hip_basic.cu b/test/hip_basic.cu
deleted file mode 100644
index 2e1bf94..0000000
--- a/test/hip_basic.cu
+++ /dev/null
@@ -1,172 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2015-2016 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-// workaround issue between gcc >= 4.7 and cuda 5.5
-#if (defined __GNUC__) && (__GNUC__>4 || __GNUC_MINOR__>=7)
- #undef _GLIBCXX_ATOMIC_BUILTINS
- #undef _GLIBCXX_USE_INT128
-#endif
-
-#define EIGEN_TEST_NO_LONGDOUBLE
-#define EIGEN_TEST_NO_COMPLEX
-#define EIGEN_TEST_FUNC hip_basic
-#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
-
-#include <hip/hip_runtime.h>
-
-#include "main.h"
-#include "hip_common.h"
-
-// Check that dense modules can be properly parsed by hipcc
-#include <Eigen/Dense>
-
-// struct Foo{
-// EIGEN_DEVICE_FUNC
-// void operator()(int i, const float* mats, float* vecs) const {
-// using namespace Eigen;
-// // Matrix3f M(data);
-// // Vector3f x(data+9);
-// // Map<Vector3f>(data+9) = M.inverse() * x;
-// Matrix3f M(mats+i/16);
-// Vector3f x(vecs+i*3);
-// // using std::min;
-// // using std::sqrt;
-// Map<Vector3f>(vecs+i*3) << x.minCoeff(), 1, 2;// / x.dot(x);//(M.inverse() * x) / x.x();
-// //x = x*2 + x.y() * x + x * x.maxCoeff() - x / x.sum();
-// }
-// };
-
-template<typename T>
-struct coeff_wise {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
- {
- using namespace Eigen;
- T x1(in+i);
- T x2(in+i+1);
- T x3(in+i+2);
- Map<T> res(out+i*T::MaxSizeAtCompileTime);
-
- res.array() += (in[0] * x1 + x2).array() * x3.array();
- }
-};
-
-template<typename T>
-struct replicate {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
- {
- using namespace Eigen;
- T x1(in+i);
- int step = x1.size() * 4;
- int stride = 3 * step;
-
- typedef Map<Array<typename T::Scalar,Dynamic,Dynamic> > MapType;
- MapType(out+i*stride+0*step, x1.rows()*2, x1.cols()*2) = x1.replicate(2,2);
- MapType(out+i*stride+1*step, x1.rows()*3, x1.cols()) = in[i] * x1.colwise().replicate(3);
- MapType(out+i*stride+2*step, x1.rows(), x1.cols()*3) = in[i] * x1.rowwise().replicate(3);
- }
-};
-
-template<typename T>
-struct redux {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
- {
- using namespace Eigen;
- int N = 10;
- T x1(in+i);
- out[i*N+0] = x1.minCoeff();
- out[i*N+1] = x1.maxCoeff();
- out[i*N+2] = x1.sum();
- out[i*N+3] = x1.prod();
- out[i*N+4] = x1.matrix().squaredNorm();
- out[i*N+5] = x1.matrix().norm();
- out[i*N+6] = x1.colwise().sum().maxCoeff();
- out[i*N+7] = x1.rowwise().maxCoeff().sum();
- out[i*N+8] = x1.matrix().colwise().squaredNorm().sum();
- }
-};
-
-template<typename T1, typename T2>
-struct prod_test {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T1::Scalar* in, typename T1::Scalar* out) const
- {
- using namespace Eigen;
- typedef Matrix<typename T1::Scalar, T1::RowsAtCompileTime, T2::ColsAtCompileTime> T3;
- T1 x1(in+i);
- T2 x2(in+i+1);
- Map<T3> res(out+i*T3::MaxSizeAtCompileTime);
- res += in[i] * x1 * x2;
- }
-};
-
-template<typename T1, typename T2>
-struct diagonal {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T1::Scalar* in, typename T1::Scalar* out) const
- {
- using namespace Eigen;
- T1 x1(in+i);
- Map<T2> res(out+i*T2::MaxSizeAtCompileTime);
- res += x1.diagonal();
- }
-};
-
-template<typename T>
-struct eigenvalues {
- EIGEN_DEVICE_FUNC
- void operator()(int i, const typename T::Scalar* in, typename T::Scalar* out) const
- {
- using namespace Eigen;
- typedef Matrix<typename T::Scalar, T::RowsAtCompileTime, 1> Vec;
- T M(in+i);
- Map<Vec> res(out+i*Vec::MaxSizeAtCompileTime);
- T A = M*M.adjoint();
- SelfAdjointEigenSolver<T> eig;
- eig.computeDirect(M);
- res = eig.eigenvalues();
- }
-};
-
-void test_hip_basic()
-{
- ei_test_init_hip();
-
- int nthreads = 100;
- Eigen::VectorXf in, out;
-
- #ifndef __HIP_DEVICE_COMPILE__
- int data_size = nthreads * 512;
- in.setRandom(data_size);
- out.setRandom(data_size);
- #endif
-
- CALL_SUBTEST( run_and_compare_to_hip(coeff_wise<Vector3f>(), nthreads, in, out) );
- CALL_SUBTEST( run_and_compare_to_hip(coeff_wise<Array44f>(), nthreads, in, out) );
-
- // FIXME compile fails when we uncomment the followig two tests
- // CALL_SUBTEST( run_and_compare_to_hip(replicate<Array4f>(), nthreads, in, out) );
- // CALL_SUBTEST( run_and_compare_to_hip(replicate<Array33f>(), nthreads, in, out) );
-
- CALL_SUBTEST( run_and_compare_to_hip(redux<Array4f>(), nthreads, in, out) );
- CALL_SUBTEST( run_and_compare_to_hip(redux<Matrix3f>(), nthreads, in, out) );
-
- CALL_SUBTEST( run_and_compare_to_hip(prod_test<Matrix3f,Matrix3f>(), nthreads, in, out) );
- CALL_SUBTEST( run_and_compare_to_hip(prod_test<Matrix4f,Vector4f>(), nthreads, in, out) );
-
- CALL_SUBTEST( run_and_compare_to_hip(diagonal<Matrix3f,Vector3f>(), nthreads, in, out) );
- CALL_SUBTEST( run_and_compare_to_hip(diagonal<Matrix4f,Vector4f>(), nthreads, in, out) );
-
- // FIXME : Runtime failure occurs when we uncomment the following two tests
- // CALL_SUBTEST( run_and_compare_to_hip(eigenvalues<Matrix3f>(), nthreads, in, out) );
- // CALL_SUBTEST( run_and_compare_to_hip(eigenvalues<Matrix2f>(), nthreads, in, out) );
-
-}
diff --git a/test/hip_common.h b/test/hip_common.h
deleted file mode 100644
index 251585c..0000000
--- a/test/hip_common.h
+++ /dev/null
@@ -1,103 +0,0 @@
-
-#ifndef EIGEN_TEST_HIP_COMMON_H
-#define EIGEN_TEST_HIP_COMMON_H
-
-#include "hip/hip_runtime.h"
-#include "hip/hip_runtime_api.h"
-#include <iostream>
-
-#ifndef __HIPCC__
-dim3 threadIdx, blockDim, blockIdx;
-#endif
-
-template<typename Kernel, typename Input, typename Output>
-void run_on_cpu(const Kernel& ker, int n, const Input& in, Output& out)
-{
- for(int i=0; i<n; i++)
- ker(i, in.data(), out.data());
-}
-
-
-template<typename Kernel, typename Input, typename Output>
-__global__ __attribute__((used))
-void run_on_hip_meta_kernel(const Kernel ker, int n, const Input* in, Output* out)
-{
- int i = hipThreadIdx_x + hipBlockIdx_x*hipBlockDim_x;
- if(i<n) {
- ker(i, in, out);
- }
-}
-
-
-template<typename Kernel, typename Input, typename Output>
-void run_on_hip(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);
-
- hipMalloc((void**)(&d_in), in_bytes);
- hipMalloc((void**)(&d_out), out_bytes);
-
- hipMemcpy(d_in, in.data(), in_bytes, hipMemcpyHostToDevice);
- hipMemcpy(d_out, out.data(), out_bytes, hipMemcpyHostToDevice);
-
- // 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) );
-
- hipDeviceSynchronize();
- hipLaunchKernelGGL(HIP_KERNEL_NAME(run_on_hip_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);
- hipDeviceSynchronize();
-
- // check inputs have not been modified
- hipMemcpy(const_cast<typename Input::Scalar*>(in.data()), d_in, in_bytes, hipMemcpyDeviceToHost);
- hipMemcpy(out.data(), d_out, out_bytes, hipMemcpyDeviceToHost);
-
- hipFree(d_in);
- hipFree(d_out);
-}
-
-
-template<typename Kernel, typename Input, typename Output>
-void run_and_compare_to_hip(const Kernel& ker, int n, const Input& in, Output& out)
-{
- Input in_ref, in_hip;
- Output out_ref, out_hip;
- #ifndef __HIP_DEVICE_COMPILE__
- in_ref = in_hip = in;
- out_ref = out_hip = out;
- #endif
- run_on_cpu (ker, n, in_ref, out_ref);
- run_on_hip(ker, n, in_hip, out_hip);
- #ifndef __HIP_DEVICE_COMPILE__
- VERIFY_IS_APPROX(in_ref, in_hip);
- VERIFY_IS_APPROX(out_ref, out_hip);
- #endif
-}
-
-
-void ei_test_init_hip()
-{
- int device = 0;
- hipDeviceProp_t deviceProp;
- hipGetDeviceProperties(&deviceProp, device);
- std::cout << "HIP device info:\n";
- std::cout << " name: " << deviceProp.name << "\n";
- std::cout << " capability: " << deviceProp.major << "." << deviceProp.minor << "\n";
- std::cout << " multiProcessorCount: " << deviceProp.multiProcessorCount << "\n";
- std::cout << " maxThreadsPerMultiProcessor: " << deviceProp.maxThreadsPerMultiProcessor << "\n";
- std::cout << " warpSize: " << deviceProp.warpSize << "\n";
- std::cout << " regsPerBlock: " << deviceProp.regsPerBlock << "\n";
- std::cout << " concurrentKernels: " << deviceProp.concurrentKernels << "\n";
- std::cout << " clockRate: " << deviceProp.clockRate << "\n";
- std::cout << " canMapHostMemory: " << deviceProp.canMapHostMemory << "\n";
- std::cout << " computeMode: " << deviceProp.computeMode << "\n";
-}
-
-#endif // EIGEN_TEST_HIP_COMMON_H
