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// g++ -DNDEBUG -O3 -I.. benchLLT.cpp -o benchLLT && ./benchLLT
// options:
// -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
// -DSTORMEIGEN_DONT_VECTORIZE
// -msse2
// -DREPEAT=100
// -DTRIES=10
// -DSCALAR=double
#include <iostream>
#include <StormEigen/Core>
#include <StormEigen/Cholesky>
#include <bench/BenchUtil.h>
using namespace StormEigen;
#ifndef REPEAT
#define REPEAT 10000
#endif
#ifndef TRIES
#define TRIES 10
#endif
typedef float Scalar;
template <typename MatrixType>
__attribute__ ((noinline)) void benchLLT(const MatrixType& m)
{
int rows = m.rows();
int cols = m.cols();
int cost = 0;
for (int j=0; j<rows; ++j)
{
int r = std::max(rows - j -1,0);
cost += 2*(r*j+r+j);
}
int repeats = (REPEAT*1000)/(rows*rows);
typedef typename MatrixType::Scalar Scalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
MatrixType a = MatrixType::Random(rows,cols);
SquareMatrixType covMat = a * a.adjoint();
BenchTimer timerNoSqrt, timerSqrt;
Scalar acc = 0;
int r = internal::random<int>(0,covMat.rows()-1);
int c = internal::random<int>(0,covMat.cols()-1);
for (int t=0; t<TRIES; ++t)
{
timerNoSqrt.start();
for (int k=0; k<repeats; ++k)
{
LDLT<SquareMatrixType> cholnosqrt(covMat);
acc += cholnosqrt.matrixL().coeff(r,c);
}
timerNoSqrt.stop();
}
for (int t=0; t<TRIES; ++t)
{
timerSqrt.start();
for (int k=0; k<repeats; ++k)
{
LLT<SquareMatrixType> chol(covMat);
acc += chol.matrixL().coeff(r,c);
}
timerSqrt.stop();
}
if (MatrixType::RowsAtCompileTime==Dynamic)
std::cout << "dyn ";
else
std::cout << "fixed ";
std::cout << covMat.rows() << " \t"
<< (timerNoSqrt.value() * REPEAT) / repeats << "s "
<< "(" << 1e-6 * cost*repeats/timerNoSqrt.value() << " MFLOPS)\t"
<< (timerSqrt.value() * REPEAT) / repeats << "s "
<< "(" << 1e-6 * cost*repeats/timerSqrt.value() << " MFLOPS)\n";
#ifdef BENCH_GSL
if (MatrixType::RowsAtCompileTime==Dynamic)
{
timerSqrt.reset();
gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(),covMat.cols());
gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(),covMat.cols());
eiToGsl(covMat, &gslCovMat);
for (int t=0; t<TRIES; ++t)
{
timerSqrt.start();
for (int k=0; k<repeats; ++k)
{
gsl_matrix_memcpy(gslCopy,gslCovMat);
gsl_linalg_cholesky_decomp(gslCopy);
acc += gsl_matrix_get(gslCopy,r,c);
}
timerSqrt.stop();
}
std::cout << " | \t"
<< timerSqrt.value() * REPEAT / repeats << "s";
gsl_matrix_free(gslCovMat);
}
#endif
std::cout << "\n";
// make sure the compiler does not optimize too much
if (acc==123)
std::cout << acc;
}
int main(int argc, char* argv[])
{
const int dynsizes[] = {4,6,8,16,24,32,49,64,128,256,512,900,0};
std::cout << "size no sqrt standard";
// #ifdef BENCH_GSL
// std::cout << " GSL (standard + double + ATLAS) ";
// #endif
std::cout << "\n";
for (uint i=0; dynsizes[i]>0; ++i)
benchLLT(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
benchLLT(Matrix<Scalar,2,2>());
benchLLT(Matrix<Scalar,3,3>());
benchLLT(Matrix<Scalar,4,4>());
benchLLT(Matrix<Scalar,5,5>());
benchLLT(Matrix<Scalar,6,6>());
benchLLT(Matrix<Scalar,7,7>());
benchLLT(Matrix<Scalar,8,8>());
benchLLT(Matrix<Scalar,12,12>());
benchLLT(Matrix<Scalar,16,16>());
return 0;
}