mirror of
https://gitlab.com/libeigen/eigen.git
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Clang-format tests, examples, libraries, benchmarks, etc.
This commit is contained in:
Antonio Sánchez
committed by
Rasmus Munk Larsen
Rasmus Munk Larsen
parent
3252ecc7a4
commit
46e9cdb7fe
@@ -3,7 +3,7 @@
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// icpc bench_gemm.cpp -I .. -O3 -DNDEBUG -lrt -openmp && OMP_NUM_THREADS=2 ./a.out
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// Compilation options:
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//
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//
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// -DSCALAR=std::complex<double>
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// -DSCALARA=double or -DSCALARB=double
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// -DHAVE_BLAS
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@@ -14,7 +14,6 @@
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#include <bench/BenchTimer.h>
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#include <Eigen/Core>
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using namespace std;
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using namespace Eigen;
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@@ -45,15 +44,15 @@ const int opt_B = ColMajor;
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typedef SCALAR Scalar;
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typedef NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<SCALARA,Dynamic,Dynamic,opt_A> A;
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typedef Matrix<SCALARB,Dynamic,Dynamic,opt_B> B;
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typedef Matrix<Scalar,Dynamic,Dynamic> C;
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typedef Matrix<RealScalar,Dynamic,Dynamic> M;
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typedef Matrix<SCALARA, Dynamic, Dynamic, opt_A> A;
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typedef Matrix<SCALARB, Dynamic, Dynamic, opt_B> B;
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typedef Matrix<Scalar, Dynamic, Dynamic> C;
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typedef Matrix<RealScalar, Dynamic, Dynamic> M;
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#ifdef HAVE_BLAS
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extern "C" {
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#include <Eigen/src/misc/blas.h>
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#include <Eigen/src/misc/blas.h>
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}
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static float fone = 1;
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@@ -65,7 +64,7 @@ static std::complex<float> cfzero = 0;
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static std::complex<double> cdone = 1;
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static std::complex<double> cdzero = 0;
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static char notrans = 'N';
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static char trans = 'T';
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static char trans = 'T';
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static char nonunit = 'N';
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static char lower = 'L';
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static char right = 'R';
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@@ -83,60 +82,61 @@ const char transB = trans;
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const char transB = notrans;
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#endif
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template<typename A,typename B>
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void blas_gemm(const A& a, const B& b, MatrixXf& c)
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{
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int M = c.rows(); int N = c.cols(); int K = a.cols();
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int lda = a.outerStride(); int ldb = b.outerStride(); int ldc = c.rows();
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template <typename A, typename B>
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void blas_gemm(const A& a, const B& b, MatrixXf& c) {
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int M = c.rows();
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int N = c.cols();
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int K = a.cols();
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int lda = a.outerStride();
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int ldb = b.outerStride();
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int ldc = c.rows();
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sgemm_(&transA,&transB,&M,&N,&K,&fone,
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const_cast<float*>(a.data()),&lda,
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const_cast<float*>(b.data()),&ldb,&fone,
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c.data(),&ldc);
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sgemm_(&transA, &transB, &M, &N, &K, &fone, const_cast<float*>(a.data()), &lda, const_cast<float*>(b.data()), &ldb,
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&fone, c.data(), &ldc);
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}
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template<typename A,typename B>
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void blas_gemm(const A& a, const B& b, MatrixXd& c)
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{
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int M = c.rows(); int N = c.cols(); int K = a.cols();
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int lda = a.outerStride(); int ldb = b.outerStride(); int ldc = c.rows();
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template <typename A, typename B>
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void blas_gemm(const A& a, const B& b, MatrixXd& c) {
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int M = c.rows();
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int N = c.cols();
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int K = a.cols();
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int lda = a.outerStride();
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int ldb = b.outerStride();
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int ldc = c.rows();
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dgemm_(&transA,&transB,&M,&N,&K,&done,
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const_cast<double*>(a.data()),&lda,
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const_cast<double*>(b.data()),&ldb,&done,
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c.data(),&ldc);
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dgemm_(&transA, &transB, &M, &N, &K, &done, const_cast<double*>(a.data()), &lda, const_cast<double*>(b.data()), &ldb,
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&done, c.data(), &ldc);
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}
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template<typename A,typename B>
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void blas_gemm(const A& a, const B& b, MatrixXcf& c)
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{
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int M = c.rows(); int N = c.cols(); int K = a.cols();
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int lda = a.outerStride(); int ldb = b.outerStride(); int ldc = c.rows();
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template <typename A, typename B>
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void blas_gemm(const A& a, const B& b, MatrixXcf& c) {
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int M = c.rows();
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int N = c.cols();
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int K = a.cols();
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int lda = a.outerStride();
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int ldb = b.outerStride();
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int ldc = c.rows();
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cgemm_(&transA,&transB,&M,&N,&K,(float*)&cfone,
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const_cast<float*>((const float*)a.data()),&lda,
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const_cast<float*>((const float*)b.data()),&ldb,(float*)&cfone,
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(float*)c.data(),&ldc);
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cgemm_(&transA, &transB, &M, &N, &K, (float*)&cfone, const_cast<float*>((const float*)a.data()), &lda,
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const_cast<float*>((const float*)b.data()), &ldb, (float*)&cfone, (float*)c.data(), &ldc);
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}
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template<typename A,typename B>
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void blas_gemm(const A& a, const B& b, MatrixXcd& c)
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{
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int M = c.rows(); int N = c.cols(); int K = a.cols();
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int lda = a.outerStride(); int ldb = b.outerStride(); int ldc = c.rows();
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template <typename A, typename B>
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void blas_gemm(const A& a, const B& b, MatrixXcd& c) {
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int M = c.rows();
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int N = c.cols();
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int K = a.cols();
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int lda = a.outerStride();
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int ldb = b.outerStride();
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int ldc = c.rows();
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zgemm_(&transA,&transB,&M,&N,&K,(double*)&cdone,
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const_cast<double*>((const double*)a.data()),&lda,
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const_cast<double*>((const double*)b.data()),&ldb,(double*)&cdone,
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(double*)c.data(),&ldc);
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zgemm_(&transA, &transB, &M, &N, &K, (double*)&cdone, const_cast<double*>((const double*)a.data()), &lda,
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const_cast<double*>((const double*)b.data()), &ldb, (double*)&cdone, (double*)c.data(), &ldc);
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}
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#endif
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void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr, M& ci)
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{
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void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr, M& ci) {
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cr.noalias() += ar * br;
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cr.noalias() -= ai * bi;
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ci.noalias() += ar * bi;
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@@ -144,33 +144,27 @@ void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr,
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// [cr ci] += [ar ai] * br + [-ai ar] * bi
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}
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void matlab_real_cplx(const M& a, const M& br, const M& bi, M& cr, M& ci)
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{
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void matlab_real_cplx(const M& a, const M& br, const M& bi, M& cr, M& ci) {
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cr.noalias() += a * br;
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ci.noalias() += a * bi;
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}
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void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci)
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{
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void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci) {
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cr.noalias() += ar * b;
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ci.noalias() += ai * b;
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}
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template<typename A, typename B, typename C>
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EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c)
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{
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template <typename A, typename B, typename C>
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EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c) {
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c.noalias() += a * b;
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}
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int main(int argc, char ** argv)
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{
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int main(int argc, char** argv) {
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std::ptrdiff_t l1 = internal::queryL1CacheSize();
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std::ptrdiff_t l2 = internal::queryTopLevelCacheSize();
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std::cout << "L1 cache size = " << (l1>0 ? l1/1024 : -1) << " KB\n";
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std::cout << "L2/L3 cache size = " << (l2>0 ? l2/1024 : -1) << " KB\n";
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typedef internal::gebp_traits<Scalar,Scalar> Traits;
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std::cout << "L1 cache size = " << (l1 > 0 ? l1 / 1024 : -1) << " KB\n";
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std::cout << "L2/L3 cache size = " << (l2 > 0 ? l2 / 1024 : -1) << " KB\n";
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typedef internal::gebp_traits<Scalar, Scalar> Traits;
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std::cout << "Register blocking = " << Traits::mr << " x " << Traits::nr << "\n";
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int rep = 1; // number of repetitions per try
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@@ -180,196 +174,220 @@ int main(int argc, char ** argv)
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int m = s;
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int n = s;
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int p = s;
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int cache_size1=-1, cache_size2=l2, cache_size3 = 0;
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int cache_size1 = -1, cache_size2 = l2, cache_size3 = 0;
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bool need_help = false;
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for (int i=1; i<argc;)
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{
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if(argv[i][0]=='-')
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{
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if(argv[i][1]=='s')
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{
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for (int i = 1; i < argc;) {
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if (argv[i][0] == '-') {
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if (argv[i][1] == 's') {
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++i;
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s = atoi(argv[i++]);
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m = n = p = s;
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if(argv[i][0]!='-')
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{
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if (argv[i][0] != '-') {
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n = atoi(argv[i++]);
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p = atoi(argv[i++]);
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}
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}
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else if(argv[i][1]=='c')
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{
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} else if (argv[i][1] == 'c') {
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++i;
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cache_size1 = atoi(argv[i++]);
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if(argv[i][0]!='-')
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{
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if (argv[i][0] != '-') {
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cache_size2 = atoi(argv[i++]);
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if(argv[i][0]!='-')
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cache_size3 = atoi(argv[i++]);
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if (argv[i][0] != '-') cache_size3 = atoi(argv[i++]);
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}
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}
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else if(argv[i][1]=='t')
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{
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} else if (argv[i][1] == 't') {
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tries = atoi(argv[++i]);
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++i;
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}
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else if(argv[i][1]=='p')
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{
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} else if (argv[i][1] == 'p') {
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++i;
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rep = atoi(argv[i++]);
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}
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}
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else
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{
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} else {
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need_help = true;
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break;
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}
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}
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if(need_help)
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{
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if (need_help) {
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std::cout << argv[0] << " -s <matrix sizes> -c <cache sizes> -t <nb tries> -p <nb repeats>\n";
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std::cout << " <matrix sizes> : size\n";
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std::cout << " <matrix sizes> : rows columns depth\n";
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return 1;
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}
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#if EIGEN_VERSION_AT_LEAST(3,2,90)
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if(cache_size1>0)
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setCpuCacheSizes(cache_size1,cache_size2,cache_size3);
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#if EIGEN_VERSION_AT_LEAST(3, 2, 90)
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if (cache_size1 > 0) setCpuCacheSizes(cache_size1, cache_size2, cache_size3);
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#endif
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A a(m,p); a.setRandom();
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B b(p,n); b.setRandom();
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C c(m,n); c.setOnes();
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A a(m, p);
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a.setRandom();
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B b(p, n);
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b.setRandom();
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C c(m, n);
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c.setOnes();
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C rc = c;
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std::cout << "Matrix sizes = " << m << "x" << p << " * " << p << "x" << n << "\n";
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std::ptrdiff_t mc(m), nc(n), kc(p);
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internal::computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
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internal::computeProductBlockingSizes<Scalar, Scalar>(kc, mc, nc);
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std::cout << "blocking size (mc x kc) = " << mc << " x " << kc << " x " << nc << "\n";
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C r = c;
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// check the parallel product is correct
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#if defined EIGEN_HAS_OPENMP
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// check the parallel product is correct
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#if defined EIGEN_HAS_OPENMP
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Eigen::initParallel();
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int procs = omp_get_max_threads();
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if(procs>1)
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{
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#ifdef HAVE_BLAS
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blas_gemm(a,b,r);
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#else
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if (procs > 1) {
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#ifdef HAVE_BLAS
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blas_gemm(a, b, r);
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#else
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omp_set_num_threads(1);
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r.noalias() += a * b;
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omp_set_num_threads(procs);
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#endif
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#endif
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c.noalias() += a * b;
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if(!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
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if (!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
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}
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#elif defined HAVE_BLAS
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blas_gemm(a,b,r);
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c.noalias() += a * b;
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if(!r.isApprox(c)) {
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std::cout << (r - c).norm()/r.norm() << "\n";
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#elif defined HAVE_BLAS
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blas_gemm(a, b, r);
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c.noalias() += a * b;
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if (!r.isApprox(c)) {
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std::cout << (r - c).norm() / r.norm() << "\n";
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std::cerr << "Warning, your product is crap!\n\n";
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}
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#else
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if (1. * m * n * p < 2000. * 2000 * 2000) {
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gemm(a, b, c);
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r.noalias() += a.cast<Scalar>().lazyProduct(b.cast<Scalar>());
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if (!r.isApprox(c)) {
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std::cout << (r - c).norm() / r.norm() << "\n";
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std::cerr << "Warning, your product is crap!\n\n";
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}
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#else
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if(1.*m*n*p<2000.*2000*2000)
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{
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gemm(a,b,c);
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r.noalias() += a.cast<Scalar>() .lazyProduct( b.cast<Scalar>() );
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if(!r.isApprox(c)) {
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std::cout << (r - c).norm()/r.norm() << "\n";
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std::cerr << "Warning, your product is crap!\n\n";
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}
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}
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#endif
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}
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#endif
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#ifdef HAVE_BLAS
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#ifdef HAVE_BLAS
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BenchTimer tblas;
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c = rc;
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BENCH(tblas, tries, rep, blas_gemm(a,b,c));
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std::cout << "blas cpu " << tblas.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(CPU_TIMER) << "s)\n";
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std::cout << "blas real " << tblas.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tblas.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tblas.total(REAL_TIMER) << "s)\n";
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#endif
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BENCH(tblas, tries, rep, blas_gemm(a, b, c));
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std::cout << "blas cpu " << tblas.best(CPU_TIMER) / rep << "s \t"
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<< (double(m) * n * p * rep * 2 / tblas.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << tblas.total(CPU_TIMER)
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<< "s)\n";
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std::cout << "blas real " << tblas.best(REAL_TIMER) / rep << "s \t"
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<< (double(m) * n * p * rep * 2 / tblas.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << tblas.total(REAL_TIMER)
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<< "s)\n";
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#endif
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// warm start
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if(b.norm()+a.norm()==123.554) std::cout << "\n";
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if (b.norm() + a.norm() == 123.554) std::cout << "\n";
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BenchTimer tmt;
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c = rc;
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BENCH(tmt, tries, rep, gemm(a,b,c));
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std::cout << "eigen cpu " << tmt.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER) << "s)\n";
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std::cout << "eigen real " << tmt.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n";
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BENCH(tmt, tries, rep, gemm(a, b, c));
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std::cout << "eigen cpu " << tmt.best(CPU_TIMER) / rep << "s \t"
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<< (double(m) * n * p * rep * 2 / tmt.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER)
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<< "s)\n";
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std::cout << "eigen real " << tmt.best(REAL_TIMER) / rep << "s \t"
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<< (double(m) * n * p * rep * 2 / tmt.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER)
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<< "s)\n";
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#ifdef EIGEN_HAS_OPENMP
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if(procs>1)
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{
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#ifdef EIGEN_HAS_OPENMP
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if (procs > 1) {
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BenchTimer tmono;
|
||||
omp_set_num_threads(1);
|
||||
Eigen::setNbThreads(1);
|
||||
c = rc;
|
||||
BENCH(tmono, tries, rep, gemm(a,b,c));
|
||||
std::cout << "eigen mono cpu " << tmono.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(CPU_TIMER) << "s)\n";
|
||||
std::cout << "eigen mono real " << tmono.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmono.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmono.total(REAL_TIMER) << "s)\n";
|
||||
std::cout << "mt speed up x" << tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER) << " => " << (100.0*tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER))/procs << "%\n";
|
||||
BENCH(tmono, tries, rep, gemm(a, b, c));
|
||||
std::cout << "eigen mono cpu " << tmono.best(CPU_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / tmono.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << tmono.total(CPU_TIMER)
|
||||
<< "s)\n";
|
||||
std::cout << "eigen mono real " << tmono.best(REAL_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / tmono.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t("
|
||||
<< tmono.total(REAL_TIMER) << "s)\n";
|
||||
std::cout << "mt speed up x" << tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER) << " => "
|
||||
<< (100.0 * tmono.best(CPU_TIMER) / tmt.best(REAL_TIMER)) / procs << "%\n";
|
||||
}
|
||||
#endif
|
||||
|
||||
if(1.*m*n*p<30*30*30)
|
||||
{
|
||||
#endif
|
||||
|
||||
if (1. * m * n * p < 30 * 30 * 30) {
|
||||
BenchTimer tmt;
|
||||
c = rc;
|
||||
BENCH(tmt, tries, rep, c.noalias()+=a.lazyProduct(b));
|
||||
std::cout << "lazy cpu " << tmt.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER) << "s)\n";
|
||||
std::cout << "lazy real " << tmt.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/tmt.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER) << "s)\n";
|
||||
BENCH(tmt, tries, rep, c.noalias() += a.lazyProduct(b));
|
||||
std::cout << "lazy cpu " << tmt.best(CPU_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / tmt.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << tmt.total(CPU_TIMER)
|
||||
<< "s)\n";
|
||||
std::cout << "lazy real " << tmt.best(REAL_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / tmt.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << tmt.total(REAL_TIMER)
|
||||
<< "s)\n";
|
||||
}
|
||||
|
||||
#ifdef DECOUPLED
|
||||
if((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
|
||||
{
|
||||
M ar(m,p); ar.setRandom();
|
||||
M ai(m,p); ai.setRandom();
|
||||
M br(p,n); br.setRandom();
|
||||
M bi(p,n); bi.setRandom();
|
||||
M cr(m,n); cr.setRandom();
|
||||
M ci(m,n); ci.setRandom();
|
||||
|
||||
|
||||
#ifdef DECOUPLED
|
||||
if ((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex)) {
|
||||
M ar(m, p);
|
||||
ar.setRandom();
|
||||
M ai(m, p);
|
||||
ai.setRandom();
|
||||
M br(p, n);
|
||||
br.setRandom();
|
||||
M bi(p, n);
|
||||
bi.setRandom();
|
||||
M cr(m, n);
|
||||
cr.setRandom();
|
||||
M ci(m, n);
|
||||
ci.setRandom();
|
||||
|
||||
BenchTimer t;
|
||||
BENCH(t, tries, rep, matlab_cplx_cplx(ar,ai,br,bi,cr,ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
|
||||
BENCH(t, tries, rep, matlab_cplx_cplx(ar, ai, br, bi, cr, ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER)
|
||||
<< "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER)
|
||||
<< "s)\n";
|
||||
}
|
||||
if((!NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
|
||||
{
|
||||
M a(m,p); a.setRandom();
|
||||
M br(p,n); br.setRandom();
|
||||
M bi(p,n); bi.setRandom();
|
||||
M cr(m,n); cr.setRandom();
|
||||
M ci(m,n); ci.setRandom();
|
||||
|
||||
if ((!NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex)) {
|
||||
M a(m, p);
|
||||
a.setRandom();
|
||||
M br(p, n);
|
||||
br.setRandom();
|
||||
M bi(p, n);
|
||||
bi.setRandom();
|
||||
M cr(m, n);
|
||||
cr.setRandom();
|
||||
M ci(m, n);
|
||||
ci.setRandom();
|
||||
|
||||
BenchTimer t;
|
||||
BENCH(t, tries, rep, matlab_real_cplx(a,br,bi,cr,ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
|
||||
BENCH(t, tries, rep, matlab_real_cplx(a, br, bi, cr, ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER)
|
||||
<< "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER)
|
||||
<< "s)\n";
|
||||
}
|
||||
if((NumTraits<A::Scalar>::IsComplex) && (!NumTraits<B::Scalar>::IsComplex))
|
||||
{
|
||||
M ar(m,p); ar.setRandom();
|
||||
M ai(m,p); ai.setRandom();
|
||||
M b(p,n); b.setRandom();
|
||||
M cr(m,n); cr.setRandom();
|
||||
M ci(m,n); ci.setRandom();
|
||||
|
||||
if ((NumTraits<A::Scalar>::IsComplex) && (!NumTraits<B::Scalar>::IsComplex)) {
|
||||
M ar(m, p);
|
||||
ar.setRandom();
|
||||
M ai(m, p);
|
||||
ai.setRandom();
|
||||
M b(p, n);
|
||||
b.setRandom();
|
||||
M cr(m, n);
|
||||
cr.setRandom();
|
||||
M ci(m, n);
|
||||
ci.setRandom();
|
||||
|
||||
BenchTimer t;
|
||||
BENCH(t, tries, rep, matlab_cplx_real(ar,ai,b,cr,ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(CPU_TIMER))*1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER) << "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER)/rep << "s \t" << (double(m)*n*p*rep*2/t.best(REAL_TIMER))*1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER) << "s)\n";
|
||||
BENCH(t, tries, rep, matlab_cplx_real(ar, ai, b, cr, ci));
|
||||
std::cout << "\"matlab\" cpu " << t.best(CPU_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(CPU_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(CPU_TIMER)
|
||||
<< "s)\n";
|
||||
std::cout << "\"matlab\" real " << t.best(REAL_TIMER) / rep << "s \t"
|
||||
<< (double(m) * n * p * rep * 2 / t.best(REAL_TIMER)) * 1e-9 << " GFLOPS \t(" << t.total(REAL_TIMER)
|
||||
<< "s)\n";
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user