Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/bench/benchEigenSolver.cpp b/bench/benchEigenSolver.cpp
new file mode 100644
index 0000000..dd78c7e
--- /dev/null
+++ b/bench/benchEigenSolver.cpp
@@ -0,0 +1,212 @@
+
+// g++ -DNDEBUG -O3 -I.. benchEigenSolver.cpp -o benchEigenSolver && ./benchEigenSolver
+// options:
+// -DBENCH_GMM
+// -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
+// -DEIGEN_DONT_VECTORIZE
+// -msse2
+// -DREPEAT=100
+// -DTRIES=10
+// -DSCALAR=double
+
+#include <iostream>
+
+#include <Eigen/Core>
+#include <Eigen/QR>
+#include <bench/BenchUtil.h>
+using namespace Eigen;
+
+#ifndef REPEAT
+#define REPEAT 1000
+#endif
+
+#ifndef TRIES
+#define TRIES 4
+#endif
+
+#ifndef SCALAR
+#define SCALAR float
+#endif
+
+typedef SCALAR Scalar;
+
+template <typename MatrixType>
+__attribute__ ((noinline)) void benchEigenSolver(const MatrixType& m)
+{
+ int rows = m.rows();
+ int cols = m.cols();
+
+ int stdRepeats = std::max(1,int((REPEAT*1000)/(rows*rows*sqrt(rows))));
+ int saRepeats = stdRepeats * 4;
+
+ 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 timerSa, timerStd;
+
+ Scalar acc = 0;
+ int r = internal::random<int>(0,covMat.rows()-1);
+ int c = internal::random<int>(0,covMat.cols()-1);
+ {
+ SelfAdjointEigenSolver<SquareMatrixType> ei(covMat);
+ for (int t=0; t<TRIES; ++t)
+ {
+ timerSa.start();
+ for (int k=0; k<saRepeats; ++k)
+ {
+ ei.compute(covMat);
+ acc += ei.eigenvectors().coeff(r,c);
+ }
+ timerSa.stop();
+ }
+ }
+
+ {
+ EigenSolver<SquareMatrixType> ei(covMat);
+ for (int t=0; t<TRIES; ++t)
+ {
+ timerStd.start();
+ for (int k=0; k<stdRepeats; ++k)
+ {
+ ei.compute(covMat);
+ acc += ei.eigenvectors().coeff(r,c);
+ }
+ timerStd.stop();
+ }
+ }
+
+ if (MatrixType::RowsAtCompileTime==Dynamic)
+ std::cout << "dyn ";
+ else
+ std::cout << "fixed ";
+ std::cout << covMat.rows() << " \t"
+ << timerSa.value() * REPEAT / saRepeats << "s \t"
+ << timerStd.value() * REPEAT / stdRepeats << "s";
+
+ #ifdef BENCH_GMM
+ if (MatrixType::RowsAtCompileTime==Dynamic)
+ {
+ timerSa.reset();
+ timerStd.reset();
+
+ gmm::dense_matrix<Scalar> gmmCovMat(covMat.rows(),covMat.cols());
+ gmm::dense_matrix<Scalar> eigvect(covMat.rows(),covMat.cols());
+ std::vector<Scalar> eigval(covMat.rows());
+ eiToGmm(covMat, gmmCovMat);
+ for (int t=0; t<TRIES; ++t)
+ {
+ timerSa.start();
+ for (int k=0; k<saRepeats; ++k)
+ {
+ gmm::symmetric_qr_algorithm(gmmCovMat, eigval, eigvect);
+ acc += eigvect(r,c);
+ }
+ timerSa.stop();
+ }
+ // the non-selfadjoint solver does not compute the eigen vectors
+// for (int t=0; t<TRIES; ++t)
+// {
+// timerStd.start();
+// for (int k=0; k<stdRepeats; ++k)
+// {
+// gmm::implicit_qr_algorithm(gmmCovMat, eigval, eigvect);
+// acc += eigvect(r,c);
+// }
+// timerStd.stop();
+// }
+
+ std::cout << " | \t"
+ << timerSa.value() * REPEAT / saRepeats << "s"
+ << /*timerStd.value() * REPEAT / stdRepeats << "s"*/ " na ";
+ }
+ #endif
+
+ #ifdef BENCH_GSL
+ if (MatrixType::RowsAtCompileTime==Dynamic)
+ {
+ timerSa.reset();
+ timerStd.reset();
+
+ gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(),covMat.cols());
+ gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(),covMat.cols());
+ gsl_matrix* eigvect = gsl_matrix_alloc(covMat.rows(),covMat.cols());
+ gsl_vector* eigval = gsl_vector_alloc(covMat.rows());
+ gsl_eigen_symmv_workspace* eisymm = gsl_eigen_symmv_alloc(covMat.rows());
+
+ gsl_matrix_complex* eigvectz = gsl_matrix_complex_alloc(covMat.rows(),covMat.cols());
+ gsl_vector_complex* eigvalz = gsl_vector_complex_alloc(covMat.rows());
+ gsl_eigen_nonsymmv_workspace* einonsymm = gsl_eigen_nonsymmv_alloc(covMat.rows());
+
+ eiToGsl(covMat, &gslCovMat);
+ for (int t=0; t<TRIES; ++t)
+ {
+ timerSa.start();
+ for (int k=0; k<saRepeats; ++k)
+ {
+ gsl_matrix_memcpy(gslCopy,gslCovMat);
+ gsl_eigen_symmv(gslCopy, eigval, eigvect, eisymm);
+ acc += gsl_matrix_get(eigvect,r,c);
+ }
+ timerSa.stop();
+ }
+ for (int t=0; t<TRIES; ++t)
+ {
+ timerStd.start();
+ for (int k=0; k<stdRepeats; ++k)
+ {
+ gsl_matrix_memcpy(gslCopy,gslCovMat);
+ gsl_eigen_nonsymmv(gslCopy, eigvalz, eigvectz, einonsymm);
+ acc += GSL_REAL(gsl_matrix_complex_get(eigvectz,r,c));
+ }
+ timerStd.stop();
+ }
+
+ std::cout << " | \t"
+ << timerSa.value() * REPEAT / saRepeats << "s \t"
+ << timerStd.value() * REPEAT / stdRepeats << "s";
+
+ gsl_matrix_free(gslCovMat);
+ gsl_vector_free(gslCopy);
+ gsl_matrix_free(eigvect);
+ gsl_vector_free(eigval);
+ gsl_matrix_complex_free(eigvectz);
+ gsl_vector_complex_free(eigvalz);
+ gsl_eigen_symmv_free(eisymm);
+ gsl_eigen_nonsymmv_free(einonsymm);
+ }
+ #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[] = {4,6,8,12,16,24,32,64,128,256,512,0};
+ std::cout << "size selfadjoint generic";
+ #ifdef BENCH_GMM
+ std::cout << " GMM++ ";
+ #endif
+ #ifdef BENCH_GSL
+ std::cout << " GSL (double + ATLAS) ";
+ #endif
+ std::cout << "\n";
+ for (uint i=0; dynsizes[i]>0; ++i)
+ benchEigenSolver(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
+
+ benchEigenSolver(Matrix<Scalar,2,2>());
+ benchEigenSolver(Matrix<Scalar,3,3>());
+ benchEigenSolver(Matrix<Scalar,4,4>());
+ benchEigenSolver(Matrix<Scalar,6,6>());
+ benchEigenSolver(Matrix<Scalar,8,8>());
+ benchEigenSolver(Matrix<Scalar,12,12>());
+ benchEigenSolver(Matrix<Scalar,16,16>());
+ return 0;
+}
+