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125 lines
3.5 KiB
C++
125 lines
3.5 KiB
C++
// g++ -DNDEBUG -O3 -I.. benchCholesky.cpp -o benchCholesky && ./benchCholesky
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// options:
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// -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
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// -DEIGEN_DONT_VECTORIZE
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// -msse2
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// -DREPEAT=100
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// -DTRIES=10
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// -DSCALAR=double
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#include <iostream>
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#include <Eigen/Core>
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#include <Eigen/Cholesky>
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#include <bench/BenchUtil.h>
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using namespace Eigen;
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#ifndef REPEAT
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#define REPEAT 10000
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#endif
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#ifndef TRIES
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#define TRIES 10
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#endif
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typedef float Scalar;
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template <typename MatrixType>
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__attribute__((noinline)) void benchLLT(const MatrixType& m) {
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int rows = m.rows();
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int cols = m.cols();
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double cost = 0;
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for (int j = 0; j < rows; ++j) {
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int r = std::max(rows - j - 1, 0);
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cost += 2 * (r * j + r + j);
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}
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int repeats = (REPEAT * 1000) / (rows * rows);
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
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MatrixType a = MatrixType::Random(rows, cols);
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SquareMatrixType covMat = a * a.adjoint();
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BenchTimer timerNoSqrt, timerSqrt;
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Scalar acc = 0;
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int r = internal::random<int>(0, covMat.rows() - 1);
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int c = internal::random<int>(0, covMat.cols() - 1);
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for (int t = 0; t < TRIES; ++t) {
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timerNoSqrt.start();
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for (int k = 0; k < repeats; ++k) {
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LDLT<SquareMatrixType> cholnosqrt(covMat);
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acc += cholnosqrt.matrixL().coeff(r, c);
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}
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timerNoSqrt.stop();
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}
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for (int t = 0; t < TRIES; ++t) {
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timerSqrt.start();
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for (int k = 0; k < repeats; ++k) {
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LLT<SquareMatrixType> chol(covMat);
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acc += chol.matrixL().coeff(r, c);
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}
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timerSqrt.stop();
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}
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if (MatrixType::RowsAtCompileTime == Dynamic)
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std::cout << "dyn ";
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else
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std::cout << "fixed ";
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std::cout << covMat.rows() << " \t" << (timerNoSqrt.best()) / repeats << "s "
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<< "(" << 1e-9 * cost * repeats / timerNoSqrt.best() << " GFLOPS)\t" << (timerSqrt.best()) / repeats << "s "
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<< "(" << 1e-9 * cost * repeats / timerSqrt.best() << " GFLOPS)\n";
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#ifdef BENCH_GSL
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if (MatrixType::RowsAtCompileTime == Dynamic) {
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timerSqrt.reset();
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gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(), covMat.cols());
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gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(), covMat.cols());
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eiToGsl(covMat, &gslCovMat);
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for (int t = 0; t < TRIES; ++t) {
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timerSqrt.start();
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for (int k = 0; k < repeats; ++k) {
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gsl_matrix_memcpy(gslCopy, gslCovMat);
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gsl_linalg_cholesky_decomp(gslCopy);
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acc += gsl_matrix_get(gslCopy, r, c);
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}
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timerSqrt.stop();
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}
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std::cout << " | \t" << timerSqrt.value() * REPEAT / repeats << "s";
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gsl_matrix_free(gslCovMat);
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}
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#endif
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std::cout << "\n";
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// make sure the compiler does not optimize too much
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if (acc == 123) std::cout << acc;
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}
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int main(int argc, char* argv[]) {
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const int dynsizes[] = {4, 6, 8, 16, 24, 32, 49, 64, 128, 256, 512, 900, 1500, 0};
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std::cout << "size LDLT LLT";
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// #ifdef BENCH_GSL
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// std::cout << " GSL (standard + double + ATLAS) ";
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// #endif
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std::cout << "\n";
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for (int i = 0; dynsizes[i] > 0; ++i) benchLLT(Matrix<Scalar, Dynamic, Dynamic>(dynsizes[i], dynsizes[i]));
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benchLLT(Matrix<Scalar, 2, 2>());
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benchLLT(Matrix<Scalar, 3, 3>());
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benchLLT(Matrix<Scalar, 4, 4>());
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benchLLT(Matrix<Scalar, 5, 5>());
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benchLLT(Matrix<Scalar, 6, 6>());
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benchLLT(Matrix<Scalar, 7, 7>());
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benchLLT(Matrix<Scalar, 8, 8>());
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benchLLT(Matrix<Scalar, 12, 12>());
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benchLLT(Matrix<Scalar, 16, 16>());
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return 0;
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}
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