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authorGravatar Desire NUENTSA W. <desire.nuentsa_wakam@inria.fr>2012-07-27 11:36:58 +0200
committerGravatar Desire NUENTSA W. <desire.nuentsa_wakam@inria.fr>2012-07-27 11:36:58 +0200
commitc0fa5811ec233a5a3065cce78b1bca155a9b4fc8 (patch)
treecdad1af9ac4060906676c39ff303d71bdf0b7a71 /bench/spbench
parent925ace196c182759026d3eb3edc06565ab5f01ee (diff)
Refactoring codes for numeric updates
Diffstat (limited to 'bench/spbench')
-rw-r--r--bench/spbench/sp_solver.cpp124
-rw-r--r--bench/spbench/test_sparseLU.cpp4
2 files changed, 126 insertions, 2 deletions
diff --git a/bench/spbench/sp_solver.cpp b/bench/spbench/sp_solver.cpp
new file mode 100644
index 000000000..e18f2d1c3
--- /dev/null
+++ b/bench/spbench/sp_solver.cpp
@@ -0,0 +1,124 @@
+// Small bench routine for Eigen available in Eigen
+// (C) Desire NUENTSA WAKAM, INRIA
+
+#include <iostream>
+#include <fstream>
+#include <iomanip>
+#include <Eigen/Jacobi>
+#include <Eigen/Householder>
+#include <Eigen/IterativeLinearSolvers>
+#include <Eigen/LU>
+#include <unsupported/Eigen/SparseExtra>
+//#include <Eigen/SparseLU>
+#include <Eigen/SuperLUSupport>
+// #include <unsupported/Eigen/src/IterativeSolvers/Scaling.h>
+#include <bench/BenchTimer.h>
+
+using namespace std;
+using namespace Eigen;
+
+int main(int argc, char **args)
+{
+ SparseMatrix<double, ColMajor> A;
+ typedef SparseMatrix<double, ColMajor>::Index Index;
+ typedef Matrix<double, Dynamic, Dynamic> DenseMatrix;
+ typedef Matrix<double, Dynamic, 1> DenseRhs;
+ VectorXd b, x, tmp;
+ BenchTimer timer,totaltime;
+ //SparseLU<SparseMatrix<double, ColMajor> > solver;
+ SuperLU<SparseMatrix<double, ColMajor> > solver;
+ ifstream matrix_file;
+ string line;
+ int n;
+ // Set parameters
+// solver.iparm(IPARM_THREAD_NBR) = 4;
+ /* 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 ");
+
+ timer.start();
+ totaltime.start();
+ 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<double, ColMajor> temp;
+ temp = A;
+ A = temp.selfadjointView<Lower>();
+ }
+ timer.stop();
+
+ n = A.cols();
+ // ====== TESTS FOR SPARSE TUTORIAL ======
+// cout<< "OuterSize " << A.outerSize() << " inner " << A.innerSize() << endl;
+// SparseMatrix<double, RowMajor> mat1(A);
+// SparseMatrix<double, RowMajor> mat2;
+// cout << " norm of A " << mat1.norm() << endl; ;
+// PermutationMatrix<Dynamic, Dynamic, int> perm(n);
+// perm.resize(n,1);
+// perm.indices().setLinSpaced(n, 0, n-1);
+// mat2 = perm * mat1;
+// mat.subrows();
+// mat2.resize(n,n);
+// mat2.reserve(10);
+// mat2.setConstant();
+// std::cout<< "NORM " << mat1.squaredNorm()<< endl;
+
+ cout<< "Time to load the matrix " << timer.value() <<endl;
+ /* Fill the right hand side */
+
+// solver.set_restart(374);
+ 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 ;
+ }
+// Scaling<SparseMatrix<double> > scal;
+// scal.computeRef(A);
+// b = scal.LeftScaling().cwiseProduct(b);
+
+ /* Compute the factorization */
+ cout<< "Starting the factorization "<< endl;
+ timer.reset();
+ timer.start();
+ cout<< "Size of Input Matrix "<< b.size()<<"\n\n";
+ cout<< "Rows and columns "<< A.rows() <<" " <<A.cols() <<"\n";
+ solver.compute(A);
+// solver.analyzePattern(A);
+// solver.factorize(A);
+ if (solver.info() != Success) {
+ std::cout<< "The solver failed \n";
+ return -1;
+ }
+ timer.stop();
+ float time_comp = timer.value();
+ cout <<" Compute Time " << time_comp<< endl;
+
+ timer.reset();
+ timer.start();
+ x = solver.solve(b);
+// x = scal.RightScaling().cwiseProduct(x);
+ timer.stop();
+ float time_solve = timer.value();
+ cout<< " Time to solve " << time_solve << endl;
+
+ /* Check the accuracy */
+ VectorXd tmp2 = b - A*x;
+ double tempNorm = tmp2.norm()/b.norm();
+ cout << "Relative norm of the computed solution : " << tempNorm <<"\n";
+// cout << "Iterations : " << solver.iterations() << "\n";
+
+ totaltime.stop();
+ cout << "Total time " << totaltime.value() << "\n";
+// std::cout<<x.transpose()<<"\n";
+
+ return 0;
+} \ No newline at end of file
diff --git a/bench/spbench/test_sparseLU.cpp b/bench/spbench/test_sparseLU.cpp
index 08b6c926e..ecf254b3d 100644
--- a/bench/spbench/test_sparseLU.cpp
+++ b/bench/spbench/test_sparseLU.cpp
@@ -13,8 +13,8 @@ using namespace Eigen;
int main(int argc, char **args)
{
- typedef complex<double> scalar;
-// typedef double scalar;
+// typedef complex<double> scalar;
+ typedef double scalar;
SparseMatrix<scalar, ColMajor> A;
typedef SparseMatrix<scalar, ColMajor>::Index Index;
typedef Matrix<scalar, Dynamic, Dynamic> DenseMatrix;