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// g++-4.2 -O3 -DNDEBUG -I.. benchBlasGemm.cpp /usr/lib/libcblas.so.3 - o benchBlasGemm
// possible options:
// -DEIGEN_DONT_VECTORIZE
// -msse2
// #define EIGEN_DEFAULT_TO_ROW_MAJOR
#define _FLOAT
#include <Eigen/Array>
#include <Eigen/Core>
#include "BenchTimer.h"
// include the BLAS headers
#include <cblas.h>
#include <string>
#ifdef _FLOAT
typedef float Scalar;
#define CBLAS_GEMM cblas_sgemm
#else
typedef double Scalar;
#define CBLAS_GEMM cblas_dgemm
#endif
typedef Eigen::Matrix<Scalar,Eigen::Dynamic,Eigen::Dynamic> MyMatrix;
void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops);
void bench_eigengemm_normal(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops);
void check_product(int M, int N, int K);
void check_product(void);
int main(int argc, char *argv[])
{
// disable SSE exceptions
#ifdef __GNUC__
{
int aux;
asm(
"stmxcsr %[aux] \n\t"
"orl $32832, %[aux] \n\t"
"ldmxcsr %[aux] \n\t"
: : [aux] "m" (aux));
}
#endif
int nbtries=1, nbloops=1, M, N, K;
if (argc==2)
{
if (std::string(argv[1])=="check")
check_product();
else
M = N = K = atoi(argv[1]);
}
else if ((argc==3) && (std::string(argv[1])=="auto"))
{
M = N = K = atoi(argv[2]);
nbloops = 1000000000/(M*M*M);
if (nbloops<1)
nbloops = 1;
nbtries = 6;
}
else if (argc==4)
{
M = N = K = atoi(argv[1]);
nbloops = atoi(argv[2]);
nbtries = atoi(argv[3]);
}
else if (argc==6)
{
M = atoi(argv[1]);
N = atoi(argv[2]);
K = atoi(argv[3]);
nbloops = atoi(argv[4]);
nbtries = atoi(argv[5]);
}
else
{
std::cout << "Usage: " << argv[0] << " size \n";
std::cout << "Usage: " << argv[0] << " auto size\n";
std::cout << "Usage: " << argv[0] << " size nbloops nbtries\n";
std::cout << "Usage: " << argv[0] << " M N K nbloops nbtries\n";
std::cout << "Usage: " << argv[0] << " check\n";
std::cout << "Options:\n";
std::cout << " size unique size of the 2 matrices (integer)\n";
std::cout << " auto automatically set the number of repetitions and tries\n";
std::cout << " nbloops number of times the GEMM routines is executed\n";
std::cout << " nbtries number of times the loop is benched (return the best try)\n";
std::cout << " M N K sizes of the matrices: MxN = MxK * KxN (integers)\n";
std::cout << " check check eigen product using cblas as a reference\n";
exit(1);
}
double nbmad = double(M) * double(N) * double(K) * double(nbloops);
if (!(std::string(argv[1])=="auto"))
std::cout << M << " x " << N << " x " << K << "\n";
Scalar alpha, beta;
MyMatrix ma(M,K), mb(K,N), mc(M,N);
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
mc = MyMatrix::Random(M,N);
Eigen::BenchTimer timer;
// we simply compute c += a*b, so:
alpha = 1;
beta = 1;
// bench cblas
// ROWS_A, COLS_B, COLS_A, 1.0, A, COLS_A, B, COLS_B, 0.0, C, COLS_B);
if (!(std::string(argv[1])=="auto"))
{
timer.reset();
for (uint k=0 ; k<nbtries ; ++k)
{
timer.start();
for (uint j=0 ; j<nbloops ; ++j)
#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
CBLAS_GEMM(CblasRowMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), K, mb.data(), N, beta, mc.data(), N);
#else
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, alpha, ma.data(), M, mb.data(), K, beta, mc.data(), M);
#endif
timer.stop();
}
if (!(std::string(argv[1])=="auto"))
std::cout << "cblas: " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
else
std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
}
// clear
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
mc = MyMatrix::Random(M,N);
// eigen
// if (!(std::string(argv[1])=="auto"))
{
timer.reset();
for (uint k=0 ; k<nbtries ; ++k)
{
timer.start();
bench_eigengemm(mc, ma, mb, nbloops);
timer.stop();
}
if (!(std::string(argv[1])=="auto"))
std::cout << "eigen : " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
else
std::cout << M << " : " << timer.value() << " ; " << 1e-3*floor(1e-6*nbmad/timer.value()) << "\n";
}
// clear
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
mc = MyMatrix::Random(M,N);
// eigen normal
if (!(std::string(argv[1])=="auto"))
{
timer.reset();
for (uint k=0 ; k<nbtries ; ++k)
{
timer.start();
bench_eigengemm_normal(mc, ma, mb, nbloops);
timer.stop();
}
std::cout << "eigen : " << timer.value() << " (" << 1e-3*floor(1e-6*nbmad/timer.value()) << " GFlops/s)\n";
}
return 0;
}
using namespace Eigen;
void bench_eigengemm(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops)
{
for (uint j=0 ; j<nbloops ; ++j)
mc += (ma * mb).lazy();
}
void bench_eigengemm_normal(MyMatrix& mc, const MyMatrix& ma, const MyMatrix& mb, int nbloops)
{
for (uint j=0 ; j<nbloops ; ++j)
mc += Product<MyMatrix,MyMatrix,NormalProduct>(ma,mb).lazy();
}
#define MYVERIFY(A,M) if (!(A)) { \
std::cout << "FAIL: " << M << "\n"; \
}
void check_product(int M, int N, int K)
{
MyMatrix ma(M,K), mb(K,N), mc(M,N), maT(K,M), mbT(N,K), meigen(M,N), mref(M,N);
ma = MyMatrix::Random(M,K);
mb = MyMatrix::Random(K,N);
maT = ma.transpose();
mbT = mb.transpose();
mc = MyMatrix::Random(M,N);
MyMatrix::Scalar eps = 1e-4;
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasNoTrans, M, N, K, 1, ma.data(), M, mb.data(), K, 1, mref.data(), M);
meigen += ma * mb;
MYVERIFY(meigen.isApprox(mref, eps),". * .");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasTrans, CblasNoTrans, M, N, K, 1, maT.data(), K, mb.data(), K, 1, mref.data(), M);
meigen += maT.transpose() * mb;
MYVERIFY(meigen.isApprox(mref, eps),"T * .");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasTrans, CblasTrans, M, N, K, 1, maT.data(), K, mbT.data(), N, 1, mref.data(), M);
meigen += (maT.transpose()) * (mbT.transpose());
MYVERIFY(meigen.isApprox(mref, eps),"T * T");
meigen = mref = mc;
CBLAS_GEMM(CblasColMajor, CblasNoTrans, CblasTrans, M, N, K, 1, ma.data(), M, mbT.data(), N, 1, mref.data(), M);
meigen += ma * mbT.transpose();
MYVERIFY(meigen.isApprox(mref, eps),". * T");
}
void check_product(void)
{
int M, N, K;
for (uint i=0; i<1000; ++i)
{
M = ei_random<int>(1,64);
N = ei_random<int>(1,768);
K = ei_random<int>(1,768);
M = (0 + M) * 1;
std::cout << M << " x " << N << " x " << K << "\n";
check_product(M, N, K);
}
}
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