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/spbench/test_sparseLU.cpp b/bench/spbench/test_sparseLU.cpp
new file mode 100644
index 0000000..f8ecbe6
--- /dev/null
+++ b/bench/spbench/test_sparseLU.cpp
@@ -0,0 +1,93 @@
+// Small bench routine for Eigen available in Eigen
+// (C) Desire NUENTSA WAKAM, INRIA
+
+#include <iostream>
+#include <fstream>
+#include <iomanip>
+#include <unsupported/Eigen/SparseExtra>
+#include <Eigen/SparseLU>
+#include <bench/BenchTimer.h>
+#ifdef EIGEN_METIS_SUPPORT
+#include <Eigen/MetisSupport>
+#endif
+
+using namespace std;
+using namespace Eigen;
+
+int main(int argc, char **args)
+{
+// typedef complex<double> scalar;
+ typedef double scalar;
+ SparseMatrix<scalar, ColMajor> A;
+ typedef SparseMatrix<scalar, ColMajor>::Index Index;
+ typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;
+ typedef Matrix<scalar, Dynamic, 1> DenseRhs;
+ Matrix<scalar, Dynamic, 1> b, x, tmp;
+// SparseLU<SparseMatrix<scalar, ColMajor>, AMDOrdering<int> > solver;
+// #ifdef EIGEN_METIS_SUPPORT
+// SparseLU<SparseMatrix<scalar, ColMajor>, MetisOrdering<int> > solver;
+// std::cout<< "ORDERING : METIS\n";
+// #else
+ SparseLU<SparseMatrix<scalar, ColMajor>, COLAMDOrdering<int> > solver;
+ std::cout<< "ORDERING : COLAMD\n";
+// #endif
+
+ ifstream matrix_file;
+ string line;
+ int n;
+ BenchTimer timer;
+
+ // Set parameters
+ /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
+ if (argc < 2) assert(false && "please, give the matrix market file ");
+ loadMarket(A, args[1]);
+ cout << "End charging matrix " << endl;
+ bool iscomplex=false, isvector=false;
+ int sym;
+ getMarketHeader(args[1], sym, iscomplex, isvector);
+// if (iscomplex) { cout<< " Not for complex matrices \n"; return -1; }
+ if (isvector) { cout << "The provided file is not a matrix file\n"; return -1;}
+ if (sym != 0) { // symmetric matrices, only the lower part is stored
+ SparseMatrix<scalar, ColMajor> temp;
+ temp = A;
+ A = temp.selfadjointView<Lower>();
+ }
+ n = A.cols();
+ /* Fill the right hand side */
+
+ if (argc > 2)
+ loadMarketVector(b, args[2]);
+ else
+ {
+ b.resize(n);
+ tmp.resize(n);
+// tmp.setRandom();
+ for (int i = 0; i < n; i++) tmp(i) = i;
+ b = A * tmp ;
+ }
+
+ /* Compute the factorization */
+// solver.isSymmetric(true);
+ timer.start();
+// solver.compute(A);
+ solver.analyzePattern(A);
+ timer.stop();
+ cout << "Time to analyze " << timer.value() << std::endl;
+ timer.reset();
+ timer.start();
+ solver.factorize(A);
+ timer.stop();
+ cout << "Factorize Time " << timer.value() << std::endl;
+ timer.reset();
+ timer.start();
+ x = solver.solve(b);
+ timer.stop();
+ cout << "solve time " << timer.value() << std::endl;
+ /* Check the accuracy */
+ Matrix<scalar, Dynamic, 1> tmp2 = b - A*x;
+ scalar tempNorm = tmp2.norm()/b.norm();
+ cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+ cout << "Number of nonzeros in the factor : " << solver.nnzL() + solver.nnzU() << std::endl;
+
+ return 0;
+}
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