X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES2stage.git/blobdiff_plain/877ef102aef5b45478a81fe60764c56a50cbf5f3..94bff40349bba73bd034821805ca870d73d148c9:/code/ex45.c diff --git a/code/ex45.c b/code/ex45.c index a44a2d0..d3e5fb4 100644 --- a/code/ex45.c +++ b/code/ex45.c @@ -44,8 +44,8 @@ int KrylovMinimize(Mat A, Vec b, Vec x) { //Variables PetscScalar gamma, alpha, oldgamma, beta; - PetscReal norm=20, Eprecision=5e-5, cgprec=1e-40; - PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; + PetscReal norm=20, Eprecision=1e-8, cgprec=1e-40; + PetscInt giter=0, ColS=6, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; PetscErrorCode ierr; PetscScalar T1, T2; KSP ksp; @@ -108,13 +108,14 @@ int KrylovMinimize(Mat A, Vec b, Vec x) { //Initializations // ierr = KSPGMRESSetRestart(ksp, 16); CHKERRQ(ierr); - ierr = KSPSetTolerances(ksp, 1e-10, 1e-10, PETSC_DEFAULT, 16); CHKERRQ(ierr); + ierr = KSPSetTolerances(ksp, 1e-13, 1e-13, PETSC_DEFAULT, 30); CHKERRQ(ierr); ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr); //GMRES WITH MINIMIZATION T1 = MPI_Wtime(); + ierr = KSPSetUp(ksp);CHKERRQ(ierr); while(giterEprecision ){ for(col=0; colEprecision; col++){ @@ -134,11 +135,12 @@ int KrylovMinimize(Mat A, Vec b, Vec x) { - //Error + KSPGetResidualNorm(ksp,&norm); + /* //Error ierr = VecCopy(x, residu); CHKERRQ(ierr); ierr = VecAXPY(residu, -1, x_old); CHKERRQ(ierr); ierr = VecNorm(residu, NORM_INFINITY, &norm); CHKERRQ(ierr); - + */ ierr = PetscPrintf(PETSC_COMM_WORLD, "Norm of error %g, outer iteration %D\n", norm, giter); CHKERRQ(ierr); @@ -219,8 +221,8 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { //Variables PetscScalar alpha, beta; - PetscReal norm=20, Eprecision=5e-5, tol=1e-40; - PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; + PetscReal norm=20, Eprecision=1e-8, tol=1e-40; + PetscInt giter=0, ColS=6, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0; PetscErrorCode ierr; PetscScalar T1, T2; KSP ksp; @@ -296,7 +298,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { //Initializations // ierr = KSPGMRESSetRestart(ksp, 16); CHKERRQ(ierr); - ierr = KSPSetTolerances(ksp, 1e-10, 1e-10, PETSC_DEFAULT, 16); CHKERRQ(ierr); + ierr = KSPSetTolerances(ksp, 1e-13, 1e-13, PETSC_DEFAULT, 30); CHKERRQ(ierr); ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr); @@ -304,6 +306,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { //GMRES WITH MINIMIZATION T1 = MPI_Wtime(); + ierr = KSPSetUp(ksp);CHKERRQ(ierr); while(giterEprecision ){ for(col=0; colEprecision; col++){ @@ -322,12 +325,14 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { VecRestoreArray(x, &array); + KSPGetResidualNorm(ksp,&norm); + /* //Error ierr = VecCopy(x, residu); CHKERRQ(ierr); ierr = VecAXPY(residu, -1, x_old); CHKERRQ(ierr); ierr = VecNorm(residu, NORM_INFINITY, &norm); CHKERRQ(ierr); - + */ ierr = PetscPrintf(PETSC_COMM_WORLD, "Norm of error %g, outer iteration %D\n", norm, giter); CHKERRQ(ierr); @@ -408,14 +413,6 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) { VecAYPX(d,1/rho,zero_short); //d=d/ rho; - if (normar/(norma*normr) <= tol) { // check for convergence in min{|b-A*x|} - break; - } - if (normr <= tolb) { // check for convergence in A*x=b - break; - } - - VecAXPY(x_lsqr,phi,d); // x_lsqr=x_lsqr+phi*d normr = abs(s) * normr; MatMultTranspose(AS, u, vt); //vt=A'*u; @@ -471,8 +468,22 @@ int main(int argc,char **argv) ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr); - ierr = KSPSetTolerances(ksp, 1e-7, 1e-7, PETSC_DEFAULT, 50000000); CHKERRQ(ierr); + + PC pc; + ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr); + KSPGetPC(ksp, &pc); + PCType type; + PCGetType(pc, &type); + + PetscPrintf(PETSC_COMM_WORLD, "PC TYPE %s \n", type); + KSPGetType(ksp,&type); + PetscPrintf(PETSC_COMM_WORLD, "SOLVER TYPE %s \n", type); + + + + ierr = KSPSetTolerances(ksp, 1e-10, 1e-10, PETSC_DEFAULT, 50000000); CHKERRQ(ierr); T1 = MPI_Wtime(); + ierr = KSPSetUp(ksp);CHKERRQ(ierr); ierr = KSPSolve(ksp,NULL,NULL);CHKERRQ(ierr); T2 = MPI_Wtime();