modif de la convergence c'est mieux

LSQR est parfois plus rapide que CGLS

diff --git a/code/ex15.c b/code/ex15.c
index 94c93659b6acb2e0ca63c874f44ed14e79f649c4..7dc050b2182c492dfb6e054cda07c547033293ca 100644 (file)
--- a/code/ex15.c
+++ b/code/ex15.c
@@ -120,7 +120,7 @@ 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, 16); CHKERRQ(ierr);
   ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr);
 
 
@@ -146,11 +146,13 @@ 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);
@@ -335,11 +337,14 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) {
 
 
 
+      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);
@@ -641,7 +646,7 @@ int main(int argc,char **args)
 
   }
 
-
+  
 
   /*
      Free work space.  All PETSc objects should be destroyed when they

diff --git a/code/ex29.c b/code/ex29.c
index ede23559af1f7c1b3857d7b638259ae9ee7f9878..910237b77bac14c73917846df21458125b778461 100644 (file)
--- a/code/ex29.c
+++ b/code/ex29.c
@@ -1,6 +1,6 @@
 
 
-//  /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 3 ex29 -da_grid_x 900 -da_grid_y 900 -ksp_type fgmres
+//  /home/couturie/work/petsc-3.5.1/arch-linux2-c-debug/bin/mpirun -np 3 ex29 -da_grid_x 600 -da_grid_y 600 -ksp_type fgmres
 
 
 
@@ -64,7 +64,7 @@ int KrylovMinimize(Mat A, Vec b, Vec x) {
   //Variables
 
   PetscScalar  gamma, alpha, oldgamma, beta;
-  PetscReal norm=20, Eprecision=1e-5, cgprec=1e-40;     
+  PetscReal norm=20, Eprecision=1e-7, cgprec=1e-40;     
   PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0;
   PetscErrorCode ierr;
   PetscScalar T1, T2;
@@ -128,7 +128,7 @@ 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, 16); CHKERRQ(ierr);
   ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr);
 
 
@@ -154,11 +154,13 @@ 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);
@@ -239,7 +241,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) {
   //Variables
 
   PetscScalar  alpha, beta;
-  PetscReal norm=20, Eprecision=1e-5, tol=1e-40;     
+  PetscReal norm=20, Eprecision=1e-7, tol=1e-40;     
   PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=20, Iiter=0;
   PetscErrorCode ierr;
   PetscScalar T1, T2;
@@ -316,7 +318,7 @@ 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, 16); CHKERRQ(ierr);
   ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr);
 
 
@@ -342,12 +344,14 @@ 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);
@@ -497,7 +501,7 @@ int main(int argc,char **argv)
   ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr);
   ierr = KSPSetUp(ksp);CHKERRQ(ierr);
 
-  ierr = KSPSetTolerances(ksp, 1e-5, 1e-5, PETSC_DEFAULT, 50000000); CHKERRQ(ierr);
+  ierr = KSPSetTolerances(ksp, 1e-7, 1e-7, PETSC_DEFAULT, 50000000); CHKERRQ(ierr);
   T1 = MPI_Wtime();
   ierr = KSPSolve(ksp,NULL,NULL);CHKERRQ(ierr);
   T2 = MPI_Wtime();

diff --git a/code/ex45.c b/code/ex45.c
index 11fd5c28340202ee669d6fea574e220a1d8a771d..dd3f3a6ac478800f9d135c85072a1c8823e2148f 100644 (file)
--- a/code/ex45.c
+++ b/code/ex45.c
@@ -44,7 +44,7 @@ int KrylovMinimize(Mat A, Vec b, Vec x) {
   //Variables
 
   PetscScalar  gamma, alpha, oldgamma, beta;
-  PetscReal norm=20, Eprecision=5e-5, cgprec=1e-40;     
+  PetscReal norm=20, Eprecision=1e-8, cgprec=1e-40;     
   PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0;
   PetscErrorCode ierr;
   PetscScalar T1, T2;
@@ -108,7 +108,7 @@ 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, 16); CHKERRQ(ierr);
   ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr);
 
 
@@ -134,11 +134,12 @@ 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);
@@ -219,7 +220,7 @@ int KrylovMinimizeLSQR(Mat A, Vec b, Vec x) {
   //Variables
 
   PetscScalar  alpha, beta;
-  PetscReal norm=20, Eprecision=5e-5, tol=1e-40;     
+  PetscReal norm=20, Eprecision=1e-8, tol=1e-40;     
   PetscInt giter=0, ColS=12, col=0, Emaxiter=50000000, iter=0, iterations=15, Iiter=0;
   PetscErrorCode ierr;
   PetscScalar T1, T2;
@@ -296,7 +297,7 @@ 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, 16); CHKERRQ(ierr);
   ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE); CHKERRQ(ierr);
 
 
@@ -322,12 +323,14 @@ 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);
@@ -463,7 +466,7 @@ int main(int argc,char **argv)
   ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr);
 
 
-  ierr = KSPSetTolerances(ksp, 1e-7, 1e-7, PETSC_DEFAULT, 50000000); CHKERRQ(ierr);
+  ierr = KSPSetTolerances(ksp, 1e-10, 1e-10, PETSC_DEFAULT, 50000000); CHKERRQ(ierr);
   T1 = MPI_Wtime();
   ierr = KSPSolve(ksp,NULL,NULL);CHKERRQ(ierr);
   T2 = MPI_Wtime();