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* resurected Flagged::_expression used to optimize m+=(a*b).lazy()
(equivalent to the GEMM blas routine) * added a GEMM benchmark
This commit is contained in:
Gael Guennebaud
parent
95549007b3
commit
9433df83a7
@ -113,6 +113,8 @@ template<typename ExpressionType, unsigned int Added, unsigned int Removed> clas
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m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
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}
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const ExpressionType& _expression() const { return m_matrix; }
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protected:
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ExpressionTypeNested m_matrix;
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};
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232
bench/benchBlasGemm.cpp
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232
bench/benchBlasGemm.cpp
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@ -0,0 +1,232 @@
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// #define EIGEN_DEFAULT_TO_ROW_MAJOR
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#define _FLOAT
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#include <Eigen/Array>
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#include <Eigen/Core>
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#include "BenchTimer.h"
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// include the BLAS headers
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#include <cblas.h>
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#include <string>
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#ifdef _FLOAT
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typedef float Scalar;
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#define CBLAS_GEMM cblas_sgemm
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#else
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typedef double Scalar;
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#define CBLAS_GEMM cblas_dgemm
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#endif
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typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic> MyMatrix;
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void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops);
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void bench_eigengemm_normal(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops);
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void check_product(int M, int N, int K);
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void check_product(void);
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int main(int argc, char *argv[])
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{
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{
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int aux;
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asm(
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"stmxcsr %[aux] \n\t"
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"orl $32832, %[aux] \n\t"
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"ldmxcsr %[aux] \n\t"
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: : [aux] "m" (aux));
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}
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int nbtries=1, nbloops=1, M, N, K;
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if (argc==2)
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{
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if (std::string(argv[1])=="check")
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check_product();
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else
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M = N = K = atoi(argv[1]);
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}
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else if ((argc==3) && (std::string(argv[1])=="auto"))
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{
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M = N = K = atoi(argv[2]);
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nbloops = 1000000000/(M*M*M);
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if (nbloops<1)
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nbloops = 1;
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nbtries = 6;
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}
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else if (argc==4)
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{
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M = N = K = atoi(argv[1]);
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nbloops = atoi(argv[2]);
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nbtries = atoi(argv[3]);
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}
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else if (argc==6)
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{
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M = atoi(argv[1]);
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N = atoi(argv[2]);
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K = atoi(argv[3]);
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nbloops = atoi(argv[4]);
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nbtries = atoi(argv[5]);
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}
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else
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{
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std::cout << "Usage: " << argv[0] << " size nbloops nbtries\n";
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std::cout << "Usage: " << argv[0] << " M N K nbloops nbtries\n";
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exit(1);
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}
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double nbmad = double(M) * double(N) * double(K) * double(nbloops);
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if (!(std::string(argv[1])=="auto"))
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std::cout << M << " x " << N << " x " << K << "\n";
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Scalar alpha, beta;
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MyMatrix ma(M,K), mb(K,N), mc(M,N);
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ma = MyMatrix::random(M,K);
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mb = MyMatrix::random(K,N);
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mc = MyMatrix::random(M,N);
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Eigen::BenchTimer timer;
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// we simply compute c += a*b, so:
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alpha = 1;
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beta = 1;
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// bench cblas
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// ROWS_A, COLS_B, COLS_A, 1.0, A, COLS_A, B, COLS_B, 0.0, C, COLS_B);
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if (!(std::string(argv[1])=="auto"))
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{
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timer.reset();
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for (uint k=0 ; k<nbtries ; ++k)
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{
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timer.start();
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for (uint j=0 ; j<nbloops ; ++j)
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#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
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CBLAS_GEMM(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), K, mb.data(), N, beta, mc.data(), N);
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#else
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CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), M, mb.data(), K, beta, mc.data(), M);
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#endif
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timer.stop();
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}
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if (!(std::string(argv[1])=="auto"))
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std::cout << "cblas: " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
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else
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std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
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}
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// clear
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ma = MyMatrix::random(M,K);
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mb = MyMatrix::random(K,N);
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mc = MyMatrix::random(M,N);
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// eigen fast ?
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// if (!(std::string(argv[1])=="auto"))
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{
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timer.reset();
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for (uint k=0 ; k<nbtries ; ++k)
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{
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timer.start();
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bench_eigengemm(mc, ma, mb, nbloops);
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timer.stop();
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}
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if (!(std::string(argv[1])=="auto"))
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std::cout << "eigen : " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
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else
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std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
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}
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// clear
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ma = MyMatrix::random(M,K);
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mb = MyMatrix::random(K,N);
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mc = MyMatrix::random(M,N);
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// eigen normal
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if (!(std::string(argv[1])=="auto"))
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{
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timer.reset();
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for (uint k=0 ; k<nbtries ; ++k)
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{
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timer.start();
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bench_eigengemm_normal(mc, ma, mb, nbloops);
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timer.stop();
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}
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std::cout << "eigen : " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
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}
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return 0;
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}
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using namespace Eigen;
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void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops)
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{
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for (uint j=0 ; j<nbloops ; ++j)
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#ifdef EIGEN_WIP_PRODUCT_DIRTY
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mc = ma * mb;
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#else
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mc += (ma * mb).lazy();
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/*static_cast<MatrixBase<MyMatrix>& >*//*(mc).operator+=( (ma * mb).lazy() );*/
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// Flagged<Product<MyMatrix,MyMatrix,CacheFriendlyProduct>, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>(
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// Product<MyMatrix,MyMatrix,CacheFriendlyProduct>(ma, mb)));
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#endif
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}
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void bench_eigengemm_normal(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops)
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{
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for (uint j=0 ; j<nbloops ; ++j)
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mc += Product<MyMatrix,MyMatrix,NormalProduct>(ma,mb).lazy();
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}
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#define MYVERIFY(A,M) if (!(A)) { \
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std::cout << "FAIL: " << M << "\n"; \
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}
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void check_product(int M, int N, int K)
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{
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MyMatrix ma(M,K), mb(K,N), mc(M,N), maT(K,M), mbT(N,K), meigen(M,N), mref(M,N);
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ma = MyMatrix::random(M,K);
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mb = MyMatrix::random(K,N);
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maT = ma.transpose();
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mbT = mb.transpose();
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mc = MyMatrix::random(M,N);
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MyMatrix::Scalar eps = 1e-4;
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meigen = mref = mc;
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CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, 1, ma.data(), M, mb.data(), K, 1, mref.data(), M);
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meigen += ma * mb;
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MYVERIFY(meigen.isApprox(mref, eps),". * .");
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// meigen = mref = mc;
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// CBLAS_GEMM(CblasColMajor, CblasTrans, CblasNoTrans, M, N, K, 1, maT.data(), K, mb.data(), K, 1, mref.data(), M);
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// meigen += maT.transpose() * mb;
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// MYVERIFY(meigen.isApprox(mref, eps),"T * .");
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//
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// meigen = mref = mc;
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// CBLAS_GEMM(CblasColMajor, CblasTrans, CblasTrans, M, N, K, 1, maT.data(), K, mbT.data(), N, 1, mref.data(), M);
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// meigen += (maT.transpose()) * (mbT.transpose());
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// MYVERIFY(meigen.isApprox(mref, eps),"T * T");
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//
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// meigen = mref = mc;
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// CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasTrans, M, N, K, 1, ma.data(), M, mbT.data(), N, 1, mref.data(), M);
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// meigen += ma * mbT.transpose();
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// MYVERIFY(meigen.isApprox(mref, eps),". * T");
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}
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void check_product(void)
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{
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int M, N, K;
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for (uint i=0; i<1000; ++i)
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{
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M = ei_random<int>(1,64);
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N = ei_random<int>(1,768);
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K = ei_random<int>(1,768);
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M = (0 + M) * 1;
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std::cout << M << " x " << N << " x " << K << "\n";
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check_product(M, N, K);
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}
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}
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