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| 2 | // g++-4.4 bench_gemm.cpp -I .. -O2 -DNDEBUG -lrt -fopenmp && OMP_NUM_THREADS=2 ./a.out
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| 3 | // icpc bench_gemm.cpp -I .. -O3 -DNDEBUG -lrt -openmp && OMP_NUM_THREADS=2 ./a.out
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| 4 |
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| 5 | #include <iostream>
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| 6 | #include <Eigen/Core>
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| 7 | #include <bench/BenchTimer.h>
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| 8 |
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| 9 | using namespace std;
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| 10 | using namespace Eigen;
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| 11 |
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| 12 | #ifndef SCALAR
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| 13 | // #define SCALAR std::complex<float>
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| 14 | #define SCALAR float
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| 15 | #endif
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| 16 |
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| 17 | typedef SCALAR Scalar;
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| 18 | typedef NumTraits<Scalar>::Real RealScalar;
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| 19 | typedef Matrix<RealScalar,Dynamic,Dynamic> A;
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| 20 | typedef Matrix</*Real*/Scalar,Dynamic,Dynamic> B;
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| 21 | typedef Matrix<Scalar,Dynamic,Dynamic> C;
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| 22 | typedef Matrix<RealScalar,Dynamic,Dynamic> M;
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| 23 |
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| 24 | #ifdef HAVE_BLAS
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| 25 |
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| 26 | extern "C" {
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| 27 | #include <Eigen/src/misc/blas.h>
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| 28 | }
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| 29 |
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| 30 | static float fone = 1;
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| 31 | static float fzero = 0;
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| 32 | static double done = 1;
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| 33 | static double szero = 0;
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| 34 | static std::complex<float> cfone = 1;
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| 35 | static std::complex<float> cfzero = 0;
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| 36 | static std::complex<double> cdone = 1;
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| 37 | static std::complex<double> cdzero = 0;
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| 38 | static char notrans = 'N';
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| 39 | static char trans = 'T';
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| 40 | static char nonunit = 'N';
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| 41 | static char lower = 'L';
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| 42 | static char right = 'R';
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| 43 | static int intone = 1;
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| 44 |
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| 45 | void blas_gemm(const MatrixXf& a, const MatrixXf& b, MatrixXf& c)
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| 46 | {
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| 47 | int M = c.rows(); int N = c.cols(); int K = a.cols();
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| 48 | int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
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| 49 |
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| 50 | sgemm_(¬rans,¬rans,&M,&N,&K,&fone,
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| 51 | const_cast<float*>(a.data()),&lda,
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| 52 | const_cast<float*>(b.data()),&ldb,&fone,
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| 53 | c.data(),&ldc);
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| 54 | }
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| 55 |
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| 56 | EIGEN_DONT_INLINE void blas_gemm(const MatrixXd& a, const MatrixXd& b, MatrixXd& c)
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| 57 | {
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| 58 | int M = c.rows(); int N = c.cols(); int K = a.cols();
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| 59 | int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
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| 60 |
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| 61 | dgemm_(¬rans,¬rans,&M,&N,&K,&done,
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| 62 | const_cast<double*>(a.data()),&lda,
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| 63 | const_cast<double*>(b.data()),&ldb,&done,
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| 64 | c.data(),&ldc);
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| 65 | }
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| 66 |
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| 67 | void blas_gemm(const MatrixXcf& a, const MatrixXcf& b, MatrixXcf& c)
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| 68 | {
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| 69 | int M = c.rows(); int N = c.cols(); int K = a.cols();
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| 70 | int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
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| 71 |
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| 72 | cgemm_(¬rans,¬rans,&M,&N,&K,(float*)&cfone,
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| 73 | const_cast<float*>((const float*)a.data()),&lda,
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| 74 | const_cast<float*>((const float*)b.data()),&ldb,(float*)&cfone,
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| 75 | (float*)c.data(),&ldc);
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| 76 | }
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| 77 |
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| 78 | void blas_gemm(const MatrixXcd& a, const MatrixXcd& b, MatrixXcd& c)
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| 79 | {
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| 80 | int M = c.rows(); int N = c.cols(); int K = a.cols();
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| 81 | int lda = a.rows(); int ldb = b.rows(); int ldc = c.rows();
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| 82 |
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| 83 | zgemm_(¬rans,¬rans,&M,&N,&K,(double*)&cdone,
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| 84 | const_cast<double*>((const double*)a.data()),&lda,
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| 85 | const_cast<double*>((const double*)b.data()),&ldb,(double*)&cdone,
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| 86 | (double*)c.data(),&ldc);
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| 87 | }
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| 88 |
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| 89 |
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| 90 |
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| 91 | #endif
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| 92 |
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| 93 | void matlab_cplx_cplx(const M& ar, const M& ai, const M& br, const M& bi, M& cr, M& ci)
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| 94 | {
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| 95 | cr.noalias() += ar * br;
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| 96 | cr.noalias() -= ai * bi;
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| 97 | ci.noalias() += ar * bi;
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| 98 | ci.noalias() += ai * br;
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| 99 | }
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| 100 |
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| 101 | void matlab_real_cplx(const M& a, const M& br, const M& bi, M& cr, M& ci)
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| 102 | {
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| 103 | cr.noalias() += a * br;
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| 104 | ci.noalias() += a * bi;
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| 105 | }
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| 106 |
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| 107 | void matlab_cplx_real(const M& ar, const M& ai, const M& b, M& cr, M& ci)
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| 108 | {
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| 109 | cr.noalias() += ar * b;
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| 110 | ci.noalias() += ai * b;
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| 111 | }
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| 112 |
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| 113 | template<typename A, typename B, typename C>
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| 114 | EIGEN_DONT_INLINE void gemm(const A& a, const B& b, C& c)
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| 115 | {
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| 116 | c.noalias() += a * b;
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| 117 | }
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| 118 |
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| 119 | int main(int argc, char ** argv)
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| 120 | {
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| 121 | std::ptrdiff_t l1 = internal::queryL1CacheSize();
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| 122 | std::ptrdiff_t l2 = internal::queryTopLevelCacheSize();
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| 123 | std::cout << "L1 cache size = " << (l1>0 ? l1/1024 : -1) << " KB\n";
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| 124 | std::cout << "L2/L3 cache size = " << (l2>0 ? l2/1024 : -1) << " KB\n";
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| 125 | typedef internal::gebp_traits<Scalar,Scalar> Traits;
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| 126 | std::cout << "Register blocking = " << Traits::mr << " x " << Traits::nr << "\n";
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| 127 |
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| 128 | int rep = 1; // number of repetitions per try
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| 129 | int tries = 2; // number of tries, we keep the best
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| 130 |
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| 131 | int s = 2048;
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| 132 | int cache_size = -1;
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| 133 |
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| 134 | bool need_help = false;
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| 135 | for (int i=1; i<argc; ++i)
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| 136 | {
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| 137 | if(argv[i][0]=='s')
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| 138 | s = atoi(argv[i]+1);
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| 139 | else if(argv[i][0]=='c')
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| 140 | cache_size = atoi(argv[i]+1);
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| 141 | else if(argv[i][0]=='t')
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| 142 | tries = atoi(argv[i]+1);
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| 143 | else if(argv[i][0]=='p')
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| 144 | rep = atoi(argv[i]+1);
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| 145 | else
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| 146 | need_help = true;
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| 147 | }
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| 148 |
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| 149 | if(need_help)
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| 150 | {
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| 151 | std::cout << argv[0] << " s<matrix size> c<cache size> t<nb tries> p<nb repeats>\n";
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| 152 | return 1;
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| 153 | }
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| 154 |
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| 155 | if(cache_size>0)
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| 156 | setCpuCacheSizes(cache_size,96*cache_size);
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| 157 |
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| 158 | int m = s;
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| 159 | int n = s;
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| 160 | int p = s;
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| 161 | A a(m,p); a.setRandom();
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| 162 | B b(p,n); b.setRandom();
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| 163 | C c(m,n); c.setOnes();
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| 164 | C rc = c;
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| 165 |
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| 166 | std::cout << "Matrix sizes = " << m << "x" << p << " * " << p << "x" << n << "\n";
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| 167 | std::ptrdiff_t mc(m), nc(n), kc(p);
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| 168 | internal::computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
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| 169 | std::cout << "blocking size (mc x kc) = " << mc << " x " << kc << "\n";
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| 170 |
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| 171 | C r = c;
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| 172 |
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| 173 | // check the parallel product is correct
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| 174 | #if defined EIGEN_HAS_OPENMP
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| 175 | int procs = omp_get_max_threads();
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| 176 | if(procs>1)
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| 177 | {
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| 178 | #ifdef HAVE_BLAS
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| 179 | blas_gemm(a,b,r);
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| 180 | #else
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| 181 | omp_set_num_threads(1);
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| 182 | r.noalias() += a * b;
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| 183 | omp_set_num_threads(procs);
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| 184 | #endif
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| 185 | c.noalias() += a * b;
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| 186 | if(!r.isApprox(c)) std::cerr << "Warning, your parallel product is crap!\n\n";
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| 187 | }
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| 188 | #elif defined HAVE_BLAS
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| 189 | blas_gemm(a,b,r);
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| 190 | c.noalias() += a * b;
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| 191 | if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
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| 192 | #else
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| 193 | gemm(a,b,c);
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| 194 | r.noalias() += a.cast<Scalar>() * b.cast<Scalar>();
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| 195 | if(!r.isApprox(c)) std::cerr << "Warning, your product is crap!\n\n";
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| 196 | #endif
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| 197 |
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| 198 | #ifdef HAVE_BLAS
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| 199 | BenchTimer tblas;
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| 200 | c = rc;
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| 201 | BENCH(tblas, tries, rep, blas_gemm(a,b,c));
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| 202 | 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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| 203 | 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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| 204 | #endif
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| 205 |
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| 206 | BenchTimer tmt;
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| 207 | c = rc;
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| 208 | BENCH(tmt, tries, rep, gemm(a,b,c));
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| 209 | 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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| 210 | 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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| 211 |
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| 212 | #ifdef EIGEN_HAS_OPENMP
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| 213 | if(procs>1)
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| 214 | {
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| 215 | BenchTimer tmono;
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| 216 | omp_set_num_threads(1);
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| 217 | Eigen::internal::setNbThreads(1);
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| 218 | c = rc;
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| 219 | BENCH(tmono, tries, rep, gemm(a,b,c));
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| 220 | 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";
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| 221 | 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";
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| 222 | 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";
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| 223 | }
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| 224 | #endif
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| 225 |
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| 226 | #ifdef DECOUPLED
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| 227 | if((NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
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| 228 | {
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| 229 | M ar(m,p); ar.setRandom();
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| 230 | M ai(m,p); ai.setRandom();
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| 231 | M br(p,n); br.setRandom();
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| 232 | M bi(p,n); bi.setRandom();
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| 233 | M cr(m,n); cr.setRandom();
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| 234 | M ci(m,n); ci.setRandom();
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| 235 |
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| 236 | BenchTimer t;
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| 237 | BENCH(t, tries, rep, matlab_cplx_cplx(ar,ai,br,bi,cr,ci));
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| 238 | 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";
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| 239 | 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";
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| 240 | }
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| 241 | if((!NumTraits<A::Scalar>::IsComplex) && (NumTraits<B::Scalar>::IsComplex))
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| 242 | {
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| 243 | M a(m,p); a.setRandom();
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| 244 | M br(p,n); br.setRandom();
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| 245 | M bi(p,n); bi.setRandom();
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| 246 | M cr(m,n); cr.setRandom();
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| 247 | M ci(m,n); ci.setRandom();
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| 248 |
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| 249 | BenchTimer t;
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| 250 | BENCH(t, tries, rep, matlab_real_cplx(a,br,bi,cr,ci));
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| 251 | 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";
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| 252 | 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";
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| 253 | }
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| 254 | if((NumTraits<A::Scalar>::IsComplex) && (!NumTraits<B::Scalar>::IsComplex))
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| 255 | {
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| 256 | M ar(m,p); ar.setRandom();
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| 257 | M ai(m,p); ai.setRandom();
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| 258 | M b(p,n); b.setRandom();
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| 259 | M cr(m,n); cr.setRandom();
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| 260 | M ci(m,n); ci.setRandom();
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| 261 |
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| 262 | BenchTimer t;
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| 263 | BENCH(t, tries, rep, matlab_cplx_real(ar,ai,b,cr,ci));
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| 264 | 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";
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| 265 | 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";
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| 266 | }
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| 267 | #endif
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| 268 |
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| 269 | return 0;
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| 270 | }
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| 271 |
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