PetscErrorCode BSSCR_KSPConverged(KSP ksp,PetscInt n,PetscReal rnorm,KSPConvergedReason *reason,void *cctx)
{
PetscErrorCode ierr;
#if(PETSC_VERSION_MAJOR == 3)
BSSCR_KSPConverged_Ctx *ctx = (BSSCR_KSPConverged_Ctx *)cctx;
KSP_BSSCR *bsscr = ctx->bsscr;
#else
KSP_BSSCR *bsscr = (KSP_BSSCR*)cctx;
#endif
PetscFunctionBegin;
#if ( (PETSC_VERSION_MAJOR == 3) && (PETSC_VERSION_MINOR >=5 ) )
ierr = KSPConvergedDefault(ksp,n,rnorm,reason,ctx->ctx);CHKERRQ(ierr);
#endif
#if ( (PETSC_VERSION_MAJOR == 3) && (PETSC_VERSION_MINOR <=4 ) )
ierr = KSPDefaultConverged(ksp,n,rnorm,reason,ctx->ctx);CHKERRQ(ierr);
#endif
#if ( PETSC_VERSION_MAJOR < 3)
ierr = KSPDefaultConverged(ksp,n,rnorm,reason,cctx);CHKERRQ(ierr);
#endif
if (*reason) {
ierr = PetscInfo2(ksp,"default convergence test KSP iterations=%D, rnorm=%G\n",n,rnorm);CHKERRQ(ierr);
}
if(ksp->its < bsscr->min_it){
ksp->reason = KSP_CONVERGED_ITERATING;
}
PetscFunctionReturn(0);
}
/*@C
KSPLSQRDefaultConverged - Determines convergence of the LSQR Krylov method. This calls KSPConvergedDefault() and if that does not determine convergence then checks
convergence for the least squares problem.
Collective on KSP
Input Parameters:
+ ksp - iterative context
. n - iteration number
. rnorm - 2-norm residual value (may be estimated)
- ctx - convergence context which must be created by KSPConvergedDefaultCreate()
reason is set to:
+ positive - if the iteration has converged;
. negative - if residual norm exceeds divergence threshold;
- 0 - otherwise.
Notes:
Possible convergence for the least squares problem (which is based on the residual of the normal equations) are KSP_CONVERGED_RTOL_NORMAL norm and KSP_CONVERGED_ATOL_NORMAL.
Level: intermediate
.keywords: KSP, default, convergence, residual
.seealso: KSPSetConvergenceTest(), KSPSetTolerances(), KSPConvergedSkip(), KSPConvergedReason, KSPGetConvergedReason(),
KSPConvergedDefaultSetUIRNorm(), KSPConvergedDefaultSetUMIRNorm(), KSPConvergedDefaultCreate(), KSPConvergedDefaultDestroy(), KSPConvergedDefault()
@*/
PetscErrorCode KSPLSQRDefaultConverged(KSP ksp,PetscInt n,PetscReal rnorm,KSPConvergedReason *reason,void *ctx)
{
PetscErrorCode ierr;
KSP_LSQR *lsqr = (KSP_LSQR*)ksp->data;
PetscFunctionBegin;
ierr = KSPConvergedDefault(ksp,n,rnorm,reason,ctx);CHKERRQ(ierr);
if (!n || *reason) PetscFunctionReturn(0);
if (lsqr->arnorm/lsqr->rhs_norm < ksp->rtol) *reason = KSP_CONVERGED_RTOL_NORMAL;
if (lsqr->arnorm < ksp->abstol) *reason = KSP_CONVERGED_ATOL_NORMAL;
PetscFunctionReturn(0);
}
/*
This convergence test determines if the two norm of the
solution lies outside the trust region, if so it halts.
*/
static PetscErrorCode SNESTR_KSPConverged_Private(KSP ksp,PetscInt n,PetscReal rnorm,KSPConvergedReason *reason,void *cctx)
{
SNES_TR_KSPConverged_Ctx *ctx = (SNES_TR_KSPConverged_Ctx*)cctx;
SNES snes = ctx->snes;
SNES_NEWTONTR *neP = (SNES_NEWTONTR*)snes->data;
Vec x;
PetscReal nrm;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = KSPConvergedDefault(ksp,n,rnorm,reason,ctx->ctx);CHKERRQ(ierr);
if (*reason) {
ierr = PetscInfo2(snes,"default convergence test KSP iterations=%D, rnorm=%g\n",n,(double)rnorm);CHKERRQ(ierr);
}
/* Determine norm of solution */
ierr = KSPBuildSolution(ksp,0,&x);CHKERRQ(ierr);
ierr = VecNorm(x,NORM_2,&nrm);CHKERRQ(ierr);
if (nrm >= neP->delta) {
ierr = PetscInfo2(snes,"Ending linear iteration early, delta=%g, length=%g\n",(double)neP->delta,(double)nrm);CHKERRQ(ierr);
*reason = KSP_CONVERGED_STEP_LENGTH;
}
PetscFunctionReturn(0);
}
PetscErrorCode petscConverged(KSP ksp, PetscInt n, PetscReal rnorm, KSPConvergedReason * reason, void * ctx)
{
// Cast the context pointer coming from PETSc to an FEProblem& and
// get a reference to the System from it.
FEProblem & problem = *static_cast<FEProblem *>(ctx);
// Let's be nice and always check PETSc error codes.
PetscErrorCode ierr = 0;
// We want the default behavior of the KSPDefaultConverged test, but
// we don't want PETSc to die in that function with a CHKERRQ
// call... that is probably extremely unlikely/impossible, but just
// to be on the safe side, we push a different error handler before
// calling KSPDefaultConverged().
ierr = PetscPushErrorHandler(PetscReturnErrorHandler, /*void* ctx=*/ PETSC_NULL);
CHKERRABORT(problem.comm().get(),ierr);
#if PETSC_VERSION_LESS_THAN(3,0,0)
// Prior to PETSc 3.0.0, you could call KSPDefaultConverged with a NULL context
// pointer, as it was unused.
KSPDefaultConverged(ksp, n, rnorm, reason, PETSC_NULL);
#elif PETSC_RELEASE_LESS_THAN(3,5,0)
// As of PETSc 3.0.0, you must call KSPDefaultConverged with a
// non-NULL context pointer which must be created with
// KSPDefaultConvergedCreate(), and destroyed with
// KSPDefaultConvergedDestroy().
void* default_ctx = NULL;
KSPDefaultConvergedCreate(&default_ctx);
KSPDefaultConverged(ksp, n, rnorm, reason, default_ctx);
KSPDefaultConvergedDestroy(default_ctx);
#else
// As of PETSc 3.5.0, use KSPConvergedDefaultXXX
void* default_ctx = NULL;
KSPConvergedDefaultCreate(&default_ctx);
KSPConvergedDefault(ksp, n, rnorm, reason, default_ctx);
KSPConvergedDefaultDestroy(default_ctx);
#endif
// Pop the Error handler we pushed on the stack to go back
// to default PETSc error handling behavior.
ierr = PetscPopErrorHandler();
CHKERRABORT(problem.comm().get(),ierr);
// Get tolerances from the KSP object
PetscReal rtol = 0.;
PetscReal atol = 0.;
PetscReal dtol = 0.;
PetscInt maxits = 0;
ierr = KSPGetTolerances(ksp, &rtol, &atol, &dtol, &maxits);
CHKERRABORT(problem.comm().get(),ierr);
// Now do some additional MOOSE-specific tests...
std::string msg;
MooseLinearConvergenceReason moose_reason = problem.checkLinearConvergence(msg, n, rnorm, rtol, atol, dtol, maxits);
switch (moose_reason)
{
case MOOSE_CONVERGED_RTOL:
*reason = KSP_CONVERGED_RTOL;
break;
case MOOSE_CONVERGED_ITS:
*reason = KSP_CONVERGED_ITS;
break;
default:
{
// If it's not either of the two specific cases we handle, just go
// with whatever PETSc decided in KSPDefaultConverged.
break;
}
}
return 0;
}
PetscErrorCode KSPSolve_TSIRM(KSP ksp)
{
PetscErrorCode ierr;
KSP_TSIRM *tsirm = (KSP_TSIRM*)ksp->data;
KSP sub_ksp;
PC pc;
Mat AS;
Vec x,b;
PetscScalar *array;
PetscReal norm = 20;
PetscInt i,*ind_row,first_iteration = 1,its = 0,total = 0,col = 0;
PetscInt restart = 30;
KSP ksp_min; /* KSP for minimization */
PC pc_min; /* PC for minimization */
PetscFunctionBegin;
x = ksp->vec_sol; /* Solution vector */
b = ksp->vec_rhs; /* Right-hand side vector */
/* Row indexes (these indexes are global) */
ierr = PetscMalloc1(tsirm->Iend-tsirm->Istart,&ind_row);
CHKERRQ(ierr);
for (i=0; i<tsirm->Iend-tsirm->Istart; i++) ind_row[i] = i+tsirm->Istart;
/* Inner solver */
ierr = KSPGetPC(ksp,&pc);
CHKERRQ(ierr);
ierr = PCKSPGetKSP(pc,&sub_ksp);
CHKERRQ(ierr);
ierr = KSPSetTolerances(sub_ksp,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,restart);
CHKERRQ(ierr);
/* previously it seemed good but with SNES it seems not good... */
ierr = KSP_MatMult(sub_ksp,tsirm->A,x,tsirm->r);
CHKERRQ(ierr);
ierr = VecAXPY(tsirm->r,-1,b);
CHKERRQ(ierr);
ierr = VecNorm(tsirm->r,NORM_2,&norm);
CHKERRQ(ierr);
ksp->its = 0;
ierr = KSPConvergedDefault(ksp,ksp->its,norm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(sub_ksp,PETSC_TRUE);
CHKERRQ(ierr);
do {
for (col=0; col<tsirm->size_ls && ksp->reason==0; col++) {
/* Solve (inner iteration) */
ierr = KSPSolve(sub_ksp,b,x);
CHKERRQ(ierr);
ierr = KSPGetIterationNumber(sub_ksp,&its);
CHKERRQ(ierr);
total += its;
/* Build S^T */
ierr = VecGetArray(x,&array);
CHKERRQ(ierr);
ierr = MatSetValues(tsirm->S,tsirm->Iend-tsirm->Istart,ind_row,1,&col,array,INSERT_VALUES);
CHKERRQ(ierr);
ierr = VecRestoreArray(x,&array);
CHKERRQ(ierr);
ierr = KSPGetResidualNorm(sub_ksp,&norm);
CHKERRQ(ierr);
ksp->rnorm = norm;
ksp->its ++;
ierr = KSPConvergedDefault(ksp,ksp->its,norm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,norm);
CHKERRQ(ierr);
}
/* Minimization step */
if (!ksp->reason) {
ierr = MatAssemblyBegin(tsirm->S,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
ierr = MatAssemblyEnd(tsirm->S,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
if (first_iteration) {
ierr = MatMatMult(tsirm->A,tsirm->S,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&AS);
CHKERRQ(ierr);
first_iteration = 0;
} else {
ierr = MatMatMult(tsirm->A,tsirm->S,MAT_REUSE_MATRIX,PETSC_DEFAULT,&AS);
CHKERRQ(ierr);
}
/* CGLS or LSQR method to minimize the residuals*/
ierr = KSPCreate(PETSC_COMM_WORLD,&ksp_min);
CHKERRQ(ierr);
if (tsirm->cgls) {
ierr = KSPSetType(ksp_min,KSPCGLS);
CHKERRQ(ierr);
} else {
ierr = KSPSetType(ksp_min,KSPLSQR);
CHKERRQ(ierr);
}
ierr = KSPSetOperators(ksp_min,AS,AS);
CHKERRQ(ierr);
ierr = KSPSetTolerances(ksp_min,tsirm->tol_ls,PETSC_DEFAULT,PETSC_DEFAULT,tsirm->maxiter_ls);
CHKERRQ(ierr);
ierr = KSPGetPC(ksp_min,&pc_min);
CHKERRQ(ierr);
ierr = PCSetType(pc_min,PCNONE);
CHKERRQ(ierr);
ierr = KSPSolve(ksp_min,b,tsirm->Alpha);
CHKERRQ(ierr); /* Find Alpha such that ||AS Alpha = b|| */
ierr = KSPDestroy(&ksp_min);
CHKERRQ(ierr);
/* Apply minimization */
ierr = MatMult(tsirm->S,tsirm->Alpha,x);
CHKERRQ(ierr); /* x = S * Alpha */
}
} while (ksp->its<ksp->max_it && !ksp->reason);
ierr = MatDestroy(&AS);
CHKERRQ(ierr);
ierr = PetscFree(ind_row);
CHKERRQ(ierr);
ksp->its = total;
PetscFunctionReturn(0);
}
PETSC_EXTERN void kspconvergeddefault_(KSP *ksp,PetscInt *n,PetscReal *rnorm,KSPConvergedReason *flag,void *dummy,PetscErrorCode *ierr)
{
CHKFORTRANNULLOBJECT(dummy);
*ierr = KSPConvergedDefault(*ksp,*n,*rnorm,flag,dummy);
}
