int main(int argc, char *argv[])
{
PetscErrorCode ierr;
DM dau,dak,pack;
const PetscInt *lxu;
PetscInt *lxk,m,sizes;
User user;
SNES snes;
Vec X,F,Xu,Xk,Fu,Fk;
Mat B;
IS *isg;
PetscBool view_draw,pass_dm;
PetscInitialize(&argc,&argv,0,help);
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,-10,1,1,NULL,&dau);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(dau,"u_");CHKERRQ(ierr);
ierr = DMSetFromOptions(dau);CHKERRQ(ierr);
ierr = DMDAGetOwnershipRanges(dau,&lxu,0,0);CHKERRQ(ierr);
ierr = DMDAGetInfo(dau,0, &m,0,0, &sizes,0,0, 0,0,0,0,0,0);CHKERRQ(ierr);
ierr = PetscMalloc1(sizes,&lxk);CHKERRQ(ierr);
ierr = PetscMemcpy(lxk,lxu,sizes*sizeof(*lxk));CHKERRQ(ierr);
lxk[0]--;
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,m-1,1,1,lxk,&dak);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(dak,"k_");CHKERRQ(ierr);
ierr = DMSetFromOptions(dak);CHKERRQ(ierr);
ierr = PetscFree(lxk);CHKERRQ(ierr);
ierr = DMCompositeCreate(PETSC_COMM_WORLD,&pack);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(pack,"pack_");CHKERRQ(ierr);
ierr = DMCompositeAddDM(pack,dau);CHKERRQ(ierr);
ierr = DMCompositeAddDM(pack,dak);CHKERRQ(ierr);
ierr = DMDASetFieldName(dau,0,"u");CHKERRQ(ierr);
ierr = DMDASetFieldName(dak,0,"k");CHKERRQ(ierr);
ierr = DMSetFromOptions(pack);CHKERRQ(ierr);
ierr = DMCreateGlobalVector(pack,&X);CHKERRQ(ierr);
ierr = VecDuplicate(X,&F);CHKERRQ(ierr);
ierr = PetscNew(&user);CHKERRQ(ierr);
user->pack = pack;
ierr = DMCompositeGetGlobalISs(pack,&isg);CHKERRQ(ierr);
ierr = DMCompositeGetLocalVectors(pack,&user->Uloc,&user->Kloc);CHKERRQ(ierr);
ierr = DMCompositeScatter(pack,X,user->Uloc,user->Kloc);CHKERRQ(ierr);
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"Coupled problem options","SNES");CHKERRQ(ierr);
{
user->ptype = 0; view_draw = PETSC_FALSE; pass_dm = PETSC_TRUE;
ierr = PetscOptionsInt("-problem_type","0: solve for u only, 1: solve for k only, 2: solve for both",0,user->ptype,&user->ptype,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-view_draw","Draw the final coupled solution regardless of whether only one physics was solved",0,view_draw,&view_draw,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-pass_dm","Pass the packed DM to SNES to use when determining splits and forward into splits",0,pass_dm,&pass_dm,NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ierr = FormInitial_Coupled(user,X);CHKERRQ(ierr);
ierr = SNESCreate(PETSC_COMM_WORLD,&snes);CHKERRQ(ierr);
switch (user->ptype) {
case 0:
ierr = DMCompositeGetAccess(pack,X,&Xu,0);CHKERRQ(ierr);
ierr = DMCompositeGetAccess(pack,F,&Fu,0);CHKERRQ(ierr);
ierr = DMCreateMatrix(dau,&B);CHKERRQ(ierr);
ierr = SNESSetFunction(snes,Fu,FormFunction_All,user);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes,B,B,FormJacobian_All,user);CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes);CHKERRQ(ierr);
ierr = SNESSetDM(snes,dau);CHKERRQ(ierr);
ierr = SNESSolve(snes,NULL,Xu);CHKERRQ(ierr);
ierr = DMCompositeRestoreAccess(pack,X,&Xu,0);CHKERRQ(ierr);
ierr = DMCompositeRestoreAccess(pack,F,&Fu,0);CHKERRQ(ierr);
break;
case 1:
ierr = DMCompositeGetAccess(pack,X,0,&Xk);CHKERRQ(ierr);
ierr = DMCompositeGetAccess(pack,F,0,&Fk);CHKERRQ(ierr);
ierr = DMCreateMatrix(dak,&B);CHKERRQ(ierr);
ierr = SNESSetFunction(snes,Fk,FormFunction_All,user);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes,B,B,FormJacobian_All,user);CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes);CHKERRQ(ierr);
ierr = SNESSetDM(snes,dak);CHKERRQ(ierr);
ierr = SNESSolve(snes,NULL,Xk);CHKERRQ(ierr);
ierr = DMCompositeRestoreAccess(pack,X,0,&Xk);CHKERRQ(ierr);
ierr = DMCompositeRestoreAccess(pack,F,0,&Fk);CHKERRQ(ierr);
break;
case 2:
ierr = DMCreateMatrix(pack,&B);CHKERRQ(ierr);
/* This example does not correctly allocate off-diagonal blocks. These options allows new nonzeros (slow). */
ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
ierr = SNESSetFunction(snes,F,FormFunction_All,user);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes,B,B,FormJacobian_All,user);CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes);CHKERRQ(ierr);
if (!pass_dm) { /* Manually provide index sets and names for the splits */
KSP ksp;
PC pc;
ierr = SNESGetKSP(snes,&ksp);CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCFieldSplitSetIS(pc,"u",isg[0]);CHKERRQ(ierr);
ierr = PCFieldSplitSetIS(pc,"k",isg[1]);CHKERRQ(ierr);
} else {
/* The same names come from the options prefix for dau and dak. This option can support geometric multigrid inside
* of splits, but it requires using a DM (perhaps your own implementation). */
ierr = SNESSetDM(snes,pack);CHKERRQ(ierr);
}
ierr = SNESSolve(snes,NULL,X);CHKERRQ(ierr);
break;
}
if (view_draw) {ierr = VecView(X,PETSC_VIEWER_DRAW_WORLD);CHKERRQ(ierr);}
if (0) {
PetscInt col = 0;
PetscBool mult_dup = PETSC_FALSE,view_dup = PETSC_FALSE;
Mat D;
Vec Y;
ierr = PetscOptionsGetInt(0,"-col",&col,0);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(0,"-mult_dup",&mult_dup,0);CHKERRQ(ierr);
ierr = PetscOptionsGetBool(0,"-view_dup",&view_dup,0);CHKERRQ(ierr);
ierr = VecDuplicate(X,&Y);CHKERRQ(ierr);
/* ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); */
/* ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); */
ierr = MatConvert(B,MATAIJ,MAT_INITIAL_MATRIX,&D);CHKERRQ(ierr);
ierr = VecZeroEntries(X);CHKERRQ(ierr);
ierr = VecSetValue(X,col,1.0,INSERT_VALUES);CHKERRQ(ierr);
ierr = VecAssemblyBegin(X);CHKERRQ(ierr);
ierr = VecAssemblyEnd(X);CHKERRQ(ierr);
ierr = MatMult(mult_dup ? D : B,X,Y);CHKERRQ(ierr);
ierr = MatView(view_dup ? D : B,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
/* ierr = VecView(X,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr); */
ierr = VecView(Y,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
ierr = MatDestroy(&D);CHKERRQ(ierr);
ierr = VecDestroy(&Y);CHKERRQ(ierr);
}
ierr = DMCompositeRestoreLocalVectors(pack,&user->Uloc,&user->Kloc);CHKERRQ(ierr);
ierr = PetscFree(user);CHKERRQ(ierr);
ierr = ISDestroy(&isg[0]);CHKERRQ(ierr);
ierr = ISDestroy(&isg[1]);CHKERRQ(ierr);
ierr = PetscFree(isg);CHKERRQ(ierr);
ierr = VecDestroy(&X);CHKERRQ(ierr);
ierr = VecDestroy(&F);CHKERRQ(ierr);
ierr = MatDestroy(&B);CHKERRQ(ierr);
ierr = DMDestroy(&dau);CHKERRQ(ierr);
ierr = DMDestroy(&dak);CHKERRQ(ierr);
ierr = DMDestroy(&pack);CHKERRQ(ierr);
ierr = SNESDestroy(&snes);CHKERRQ(ierr);
PetscFinalize();
return 0;
}
PetscErrorCode PCSetFromOptions_MG(PC pc)
{
PetscErrorCode ierr;
PetscInt m,levels = 1,cycles;
PetscBool flg,set;
PC_MG *mg = (PC_MG*)pc->data;
PC_MG_Levels **mglevels = mg->levels;
PCMGType mgtype;
PCMGCycleType mgctype;
PetscFunctionBegin;
ierr = PetscOptionsHead("Multigrid options");
CHKERRQ(ierr);
if (!mg->levels) {
ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);
CHKERRQ(ierr);
if (!flg && pc->dm) {
ierr = DMGetRefineLevel(pc->dm,&levels);
CHKERRQ(ierr);
levels++;
mg->usedmfornumberoflevels = PETSC_TRUE;
}
ierr = PCMGSetLevels(pc,levels,NULL);
CHKERRQ(ierr);
}
mglevels = mg->levels;
mgctype = (PCMGCycleType) mglevels[0]->cycles;
ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PCMGSetCycleType(pc,mgctype);
CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,&set);
CHKERRQ(ierr);
if (set) {
ierr = PCMGSetGalerkin(pc,flg);
CHKERRQ(ierr);
}
ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PCMGSetNumberSmoothUp(pc,m);
CHKERRQ(ierr);
}
ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PCMGSetNumberSmoothDown(pc,m);
CHKERRQ(ierr);
}
mgtype = mg->am;
ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PCMGSetType(pc,mgtype);
CHKERRQ(ierr);
}
if (mg->am == PC_MG_MULTIPLICATIVE) {
ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg->cyclesperpcapply,&cycles,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PCMGMultiplicativeSetCycles(pc,cycles);
CHKERRQ(ierr);
}
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,NULL);
CHKERRQ(ierr);
if (flg) {
PetscInt i;
char eventname[128];
if (!mglevels) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling");
levels = mglevels[0]->levels;
for (i=0; i<levels; i++) {
sprintf(eventname,"MGSetup Level %d",(int)i);
ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsetup);
CHKERRQ(ierr);
sprintf(eventname,"MGSmooth Level %d",(int)i);
ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventsmoothsolve);
CHKERRQ(ierr);
if (i) {
sprintf(eventname,"MGResid Level %d",(int)i);
ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventresidual);
CHKERRQ(ierr);
sprintf(eventname,"MGInterp Level %d",(int)i);
ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->classid,&mglevels[i]->eventinterprestrict);
CHKERRQ(ierr);
}
}
#if defined(PETSC_USE_LOG)
{
const char *sname = "MG Apply";
PetscStageLog stageLog;
PetscInt st;
PetscFunctionBegin;
ierr = PetscLogGetStageLog(&stageLog);
CHKERRQ(ierr);
for (st = 0; st < stageLog->numStages; ++st) {
PetscBool same;
ierr = PetscStrcmp(stageLog->stageInfo[st].name, sname, &same);
CHKERRQ(ierr);
if (same) mg->stageApply = st;
}
if (!mg->stageApply) {
ierr = PetscLogStageRegister(sname, &mg->stageApply);
CHKERRQ(ierr);
}
}
#endif
}
ierr = PetscOptionsTail();
CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
KSPSetFromOptions - Sets KSP options from the options database.
This routine must be called before KSPSetUp() if the user is to be
allowed to set the Krylov type.
Collective on KSP
Input Parameters:
. ksp - the Krylov space context
Options Database Keys:
+ -ksp_max_it - maximum number of linear iterations
. -ksp_rtol rtol - relative tolerance used in default determination of convergence, i.e.
if residual norm decreases by this factor than convergence is declared
. -ksp_atol abstol - absolute tolerance used in default convergence test, i.e. if residual
norm is less than this then convergence is declared
. -ksp_divtol tol - if residual norm increases by this factor than divergence is declared
. -ksp_converged_use_initial_residual_norm - see KSPConvergedDefaultSetUIRNorm()
. -ksp_converged_use_min_initial_residual_norm - see KSPConvergedDefaultSetUMIRNorm()
. -ksp_norm_type - none - skip norms used in convergence tests (useful only when not using
convergence test (say you always want to run with 5 iterations) to
save on communication overhead
preconditioned - default for left preconditioning
unpreconditioned - see KSPSetNormType()
natural - see KSPSetNormType()
. -ksp_check_norm_iteration it - do not compute residual norm until iteration number it (does compute at 0th iteration)
works only for PCBCGS, PCIBCGS and and PCCG
. -ksp_lag_norm - compute the norm of the residual for the ith iteration on the i+1 iteration; this means that one can use
the norm of the residual for convergence test WITHOUT an extra MPI_Allreduce() limiting global synchronizations.
This will require 1 more iteration of the solver than usual.
. -ksp_fischer_guess <model,size> - uses the Fischer initial guess generator for repeated linear solves
. -ksp_constant_null_space - assume the operator (matrix) has the constant vector in its null space
. -ksp_test_null_space - tests the null space set with KSPSetNullSpace() to see if it truly is a null space
. -ksp_knoll - compute initial guess by applying the preconditioner to the right hand side
. -ksp_monitor_cancel - cancel all previous convergene monitor routines set
. -ksp_monitor <optional filename> - print residual norm at each iteration
. -ksp_monitor_lg_residualnorm - plot residual norm at each iteration
. -ksp_monitor_solution - plot solution at each iteration
- -ksp_monitor_singular_value - monitor extremem singular values at each iteration
Notes:
To see all options, run your program with the -help option
or consult Users-Manual: ch_ksp
Level: beginner
.keywords: KSP, set, from, options, database
.seealso: KSPSetUseFischerGuess()
@*/
PetscErrorCode KSPSetFromOptions(KSP ksp)
{
PetscErrorCode ierr;
PetscInt indx;
const char *convtests[] = {"default","skip"};
char type[256], monfilename[PETSC_MAX_PATH_LEN];
PetscViewer monviewer;
PetscBool flg,flag,reuse;
PetscInt model[2]={0,0},nmax;
KSPNormType normtype;
PCSide pcside;
void *ctx;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCSetFromOptions(ksp->pc);CHKERRQ(ierr);
if (!KSPRegisterAllCalled) {ierr = KSPRegisterAll();CHKERRQ(ierr);}
ierr = PetscObjectOptionsBegin((PetscObject)ksp);CHKERRQ(ierr);
ierr = PetscOptionsFList("-ksp_type","Krylov method","KSPSetType",KSPList,(char*)(((PetscObject)ksp)->type_name ? ((PetscObject)ksp)->type_name : KSPGMRES),type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetType(ksp,type);CHKERRQ(ierr);
}
/*
Set the type if it was never set.
*/
if (!((PetscObject)ksp)->type_name) {
ierr = KSPSetType(ksp,KSPGMRES);CHKERRQ(ierr);
}
ierr = PetscOptionsInt("-ksp_max_it","Maximum number of iterations","KSPSetTolerances",ksp->max_it,&ksp->max_it,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_rtol","Relative decrease in residual norm","KSPSetTolerances",ksp->rtol,&ksp->rtol,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_atol","Absolute value of residual norm","KSPSetTolerances",ksp->abstol,&ksp->abstol,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-ksp_divtol","Residual norm increase cause divergence","KSPSetTolerances",ksp->divtol,&ksp->divtol,NULL);CHKERRQ(ierr);
flag = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_use_initial_residual_norm","Use initial residual residual norm for computing relative convergence","KSPConvergedDefaultSetUIRNorm",flag,&flag,NULL);CHKERRQ(ierr);
if (flag) {ierr = KSPConvergedDefaultSetUIRNorm(ksp);CHKERRQ(ierr);}
flag = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_use_min_initial_residual_norm","Use minimum of initial residual norm and b for computing relative convergence","KSPConvergedDefaultSetUMIRNorm",flag,&flag,NULL);CHKERRQ(ierr);
if (flag) {ierr = KSPConvergedDefaultSetUMIRNorm(ksp);CHKERRQ(ierr);}
ierr = KSPGetInitialGuessNonzero(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_initial_guess_nonzero","Use the contents of the solution vector for initial guess","KSPSetInitialNonzero",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetInitialGuessNonzero(ksp,flag);CHKERRQ(ierr);
}
ierr = PCGetReusePreconditioner(ksp->pc,&reuse);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_reuse_preconditioner","Use initial preconditioner and don't ever compute a new one ","KSPReusePreconditioner",reuse,&reuse,NULL);CHKERRQ(ierr);
ierr = KSPSetReusePreconditioner(ksp,reuse);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_knoll","Use preconditioner applied to b for initial guess","KSPSetInitialGuessKnoll",ksp->guess_knoll,&ksp->guess_knoll,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_error_if_not_converged","Generate error if solver does not converge","KSPSetErrorIfNotConverged",ksp->errorifnotconverged,&ksp->errorifnotconverged,NULL);CHKERRQ(ierr);
nmax = 2;
ierr = PetscOptionsIntArray("-ksp_fischer_guess","Use Paul Fischer's algorithm for initial guess","KSPSetUseFischerGuess",model,&nmax,&flag);CHKERRQ(ierr);
if (flag) {
if (nmax != 2) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Must pass in model,size as arguments");
ierr = KSPSetUseFischerGuess(ksp,model[0],model[1]);CHKERRQ(ierr);
}
ierr = PetscOptionsEList("-ksp_convergence_test","Convergence test","KSPSetConvergenceTest",convtests,2,"default",&indx,&flg);CHKERRQ(ierr);
if (flg) {
switch (indx) {
case 0:
ierr = KSPConvergedDefaultCreate(&ctx);CHKERRQ(ierr);
ierr = KSPSetConvergenceTest(ksp,KSPConvergedDefault,ctx,KSPConvergedDefaultDestroy);CHKERRQ(ierr);
break;
case 1: ierr = KSPSetConvergenceTest(ksp,KSPConvergedSkip,NULL,NULL);CHKERRQ(ierr); break;
}
}
ierr = KSPSetUpNorms_Private(ksp,&normtype,&pcside);CHKERRQ(ierr);
ierr = PetscOptionsEnum("-ksp_norm_type","KSP Norm type","KSPSetNormType",KSPNormTypes,(PetscEnum)normtype,(PetscEnum*)&normtype,&flg);CHKERRQ(ierr);
if (flg) { ierr = KSPSetNormType(ksp,normtype);CHKERRQ(ierr); }
ierr = PetscOptionsInt("-ksp_check_norm_iteration","First iteration to compute residual norm","KSPSetCheckNormIteration",ksp->chknorm,&ksp->chknorm,NULL);CHKERRQ(ierr);
flag = ksp->lagnorm;
ierr = PetscOptionsBool("-ksp_lag_norm","Lag the calculation of the residual norm","KSPSetLagNorm",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetLagNorm(ksp,flag);CHKERRQ(ierr);
}
ierr = KSPGetDiagonalScale(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_diagonal_scale","Diagonal scale matrix before building preconditioner","KSPSetDiagonalScale",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetDiagonalScale(ksp,flag);CHKERRQ(ierr);
}
ierr = KSPGetDiagonalScaleFix(ksp,&flag);CHKERRQ(ierr);
ierr = PetscOptionsBool("-ksp_diagonal_scale_fix","Fix diagonally scaled matrix after solve","KSPSetDiagonalScaleFix",flag,&flag,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetDiagonalScaleFix(ksp,flag);CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_constant_null_space","Add constant null space to Krylov solver","KSPSetNullSpace",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
MatNullSpace nsp;
ierr = MatNullSpaceCreate(PetscObjectComm((PetscObject)ksp),PETSC_TRUE,0,0,&nsp);CHKERRQ(ierr);
ierr = KSPSetNullSpace(ksp,nsp);CHKERRQ(ierr);
ierr = MatNullSpaceDestroy(&nsp);CHKERRQ(ierr);
}
/* option is actually checked in KSPSetUp(), just here so goes into help message */
if (ksp->nullsp) {
ierr = PetscOptionsName("-ksp_test_null_space","Is provided null space correct","None",&flg);CHKERRQ(ierr);
}
/*
Prints reason for convergence or divergence of each linear solve
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_converged_reason","Print reason for converged or diverged","KSPSolve",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) ksp->printreason = PETSC_TRUE;
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_cancel","Remove any hardwired monitor routines","KSPMonitorCancel",flg,&flg,NULL);CHKERRQ(ierr);
/* -----------------------------------------------------------------------*/
/*
Cancels all monitors hardwired into code before call to KSPSetFromOptions()
*/
if (flg) {
ierr = KSPMonitorCancel(ksp);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor","Monitor preconditioned residual norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDefault,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_range","Monitor percent of residual entries more than 10 percent of max","KSPMonitorRange","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorRange,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
ierr = PetscObjectTypeCompare((PetscObject)ksp->pc,PCKSP,&flg);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)ksp->pc,PCBJACOBI,&flag);CHKERRQ(ierr);
if (flg || flag) {
/* A hack for using dynamic tolerance in preconditioner */
ierr = PetscOptionsString("-sub_ksp_dynamic_tolerance","Use dynamic tolerance for PC if PC is a KSP","KSPMonitorDynamicTolerance","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
KSPDynTolCtx *scale = NULL;
PetscReal defaultv = 1.0;
ierr = PetscMalloc1(1,&scale);CHKERRQ(ierr);
scale->bnrm = -1.0;
scale->coef = defaultv;
ierr = PetscOptionsReal("-sub_ksp_dynamic_tolerance_param","Parameter of dynamic tolerance for inner PCKSP","KSPMonitorDynamicToleranceParam",defaultv,&(scale->coef),&flg);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDynamicTolerance,scale,KSPMonitorDynamicToleranceDestroy);CHKERRQ(ierr);
}
}
/*
Plots the vector solution
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_solution","Monitor solution graphically","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
ierr = KSPMonitorSet(ksp,KSPMonitorSolution,NULL,NULL);CHKERRQ(ierr);
}
/*
Prints preconditioned and true residual norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_true_residual","Monitor true residual norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorTrueResidualNorm,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints with max norm at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_max","Monitor true residual max norm","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorTrueResidualMaxNorm,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints extreme eigenvalue estimates at each iteration
*/
ierr = PetscOptionsString("-ksp_monitor_singular_value","Monitor singular values","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr);
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorSingularValue,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Prints preconditioned residual norm with fewer digits
*/
ierr = PetscOptionsString("-ksp_monitor_short","Monitor preconditioned residual norm with fewer digits","KSPMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)ksp),monfilename,&monviewer);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorDefaultShort,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
/*
Calls Python function
*/
ierr = PetscOptionsString("-ksp_monitor_python","Use Python function","KSPMonitorSet",0,monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {ierr = PetscPythonMonitorSet((PetscObject)ksp,monfilename);CHKERRQ(ierr);}
/*
Graphically plots preconditioned residual norm
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_residualnorm","Monitor graphically preconditioned residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGResidualNormCreate(0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGResidualNorm,ctx,(PetscErrorCode (*)(void**))KSPMonitorLGResidualNormDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned and true residual norm
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_true_residualnorm","Monitor graphically true residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscDrawLG ctx;
ierr = KSPMonitorLGTrueResidualNormCreate(PetscObjectComm((PetscObject)ksp),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGTrueResidualNorm,ctx,(PetscErrorCode (*)(void**))KSPMonitorLGTrueResidualNormDestroy);CHKERRQ(ierr);
}
/*
Graphically plots preconditioned residual norm and range of residual element values
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_lg_range","Monitor graphically range of preconditioned residual norm","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
PetscViewer ctx;
ierr = PetscViewerDrawOpen(PetscObjectComm((PetscObject)ksp),0,0,PETSC_DECIDE,PETSC_DECIDE,300,300,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorLGRange,ctx,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
#if defined(PETSC_HAVE_SAWS)
/*
Publish convergence information using AMS
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_monitor_saws","Publish KSP progress using SAWs","KSPMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
void *ctx;
ierr = KSPMonitorSAWsCreate(ksp,&ctx);CHKERRQ(ierr);
ierr = KSPMonitorSet(ksp,KSPMonitorSAWs,ctx,KSPMonitorSAWsDestroy);CHKERRQ(ierr);
ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr);
}
#endif
/* -----------------------------------------------------------------------*/
ierr = KSPSetUpNorms_Private(ksp,&normtype,&pcside);CHKERRQ(ierr);
ierr = PetscOptionsEnum("-ksp_pc_side","KSP preconditioner side","KSPSetPCSide",PCSides,(PetscEnum)pcside,(PetscEnum*)&pcside,&flg);CHKERRQ(ierr);
if (flg) {ierr = KSPSetPCSide(ksp,pcside);CHKERRQ(ierr);}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_compute_singularvalues","Compute singular values of preconditioned operator","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_compute_eigenvalues","Compute eigenvalues of preconditioned operator","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_plot_eigenvalues","Scatter plot extreme eigenvalues","KSPSetComputeSingularValues",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) { ierr = KSPSetComputeSingularValues(ksp,PETSC_TRUE);CHKERRQ(ierr); }
#if defined(PETSC_HAVE_SAWS)
{
PetscBool set;
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-ksp_saws_block","Block for SAWs at end of KSPSolve","PetscObjectSAWsBlock",((PetscObject)ksp)->amspublishblock,&flg,&set);CHKERRQ(ierr);
if (set) {
ierr = PetscObjectSAWsSetBlock((PetscObject)ksp,flg);CHKERRQ(ierr);
}
}
#endif
if (ksp->ops->setfromoptions) {
ierr = (*ksp->ops->setfromoptions)(ksp);CHKERRQ(ierr);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)ksp);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
PetscFunctionReturn(0);
}
int main(int argc,char *argv[])
{
char mat_type[256] = "aij"; /* default matrix type */
PetscErrorCode ierr;
MPI_Comm comm;
PetscMPIInt rank,size;
Sliced slice;
PetscInt i,bs=1,N=5,n,m,rstart,ghosts[2],*d_nnz,*o_nnz,dfill[4]={1,0,0,1},ofill[4]={1,1,1,1};
PetscReal alpha=1,K=1,rho0=1,u0=0,sigma=0.2;
PetscTruth useblock=PETSC_TRUE;
PetscScalar *xx;
Mat A;
Vec x,b,lf;
ierr = PetscInitialize(&argc,&argv,0,help);CHKERRQ(ierr);
comm = PETSC_COMM_WORLD;
ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
ierr = PetscOptionsBegin(comm,0,"Options for Sliced test",0);CHKERRQ(ierr);
{
ierr = PetscOptionsInt("-n","Global number of nodes","",N,&N,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-bs","Block size (1 or 2)","",bs,&bs,PETSC_NULL);CHKERRQ(ierr);
if (bs != 1) {
if (bs != 2) SETERRQ(1,"Block size must be 1 or 2");
ierr = PetscOptionsReal("-alpha","Inverse time step for wave operator","",alpha,&alpha,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-K","Bulk modulus of compressibility","",K,&K,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-rho0","Reference density","",rho0,&rho0,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-u0","Reference velocity","",u0,&u0,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-sigma","Width of Gaussian density perturbation","",sigma,&sigma,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsTruth("-block","Use block matrix assembly","",useblock,&useblock,PETSC_NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsString("-sliced_mat_type","Matrix type to use (aij or baij)","",mat_type,mat_type,sizeof mat_type,PETSC_NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
/* Split ownership, set up periodic grid in 1D */
n = PETSC_DECIDE;
ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr);
rstart = 0;
ierr = MPI_Scan(&n,&rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr);
rstart -= n;
ghosts[0] = (N+rstart-1)%N;
ghosts[1] = (rstart+n)%N;
ierr = SlicedCreate(comm,&slice);CHKERRQ(ierr);
ierr = SlicedSetGhosts(slice,bs,n,2,ghosts);CHKERRQ(ierr);
ierr = PetscMalloc2(n,PetscInt,&d_nnz,n,PetscInt,&o_nnz);CHKERRQ(ierr);
for (i=0; i<n; i++) {
if (size > 1 && (i==0 || i==n-1)) {
d_nnz[i] = 2;
o_nnz[i] = 1;
} else {
d_nnz[i] = 3;
o_nnz[i] = 0;
}
}
ierr = SlicedSetPreallocation(slice,0,d_nnz,0,o_nnz);CHKERRQ(ierr); /* Currently does not copy X_nnz so we can't free them until after SlicedGetMatrix */
if (!useblock) {ierr = SlicedSetBlockFills(slice,dfill,ofill);CHKERRQ(ierr);} /* Irrelevant for baij formats */
ierr = SlicedGetMatrix(slice,mat_type,&A);CHKERRQ(ierr);
ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr);
ierr = MatSetOption(A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);
ierr = SlicedCreateGlobalVector(slice,&x);CHKERRQ(ierr);
ierr = VecDuplicate(x,&b);CHKERRQ(ierr);
ierr = VecGhostGetLocalForm(x,&lf);CHKERRQ(ierr);
ierr = VecGetSize(lf,&m);CHKERRQ(ierr);
if (m != (n+2)*bs) SETERRQ2(1,"size of local form %D, expected %D",m,(n+2)*bs);
ierr = VecGetArray(lf,&xx);CHKERRQ(ierr);
for (i=0; i<n; i++) {
PetscInt row[2],col[9],im,ip;
PetscScalar v[12];
const PetscReal xref = 2.0*(rstart+i)/N - 1; /* [-1,1] */
const PetscReal h = 1.0/N; /* grid spacing */
im = (i==0) ? n : i-1;
ip = (i==n-1) ? n+1 : i+1;
switch (bs) {
case 1: /* Laplacian with periodic boundaries */
col[0] = im; col[1] = i; col[2] = ip;
v[0] = -h; v[1] = 2*h; v[2] = -h;
ierr = MatSetValuesLocal(A,1,&i,3,col,v,INSERT_VALUES);CHKERRQ(ierr);
xx[i] = sin(xref*PETSC_PI);
break;
case 2: /* Linear acoustic wave operator in variables [rho, u], central differences, periodic, timestep 1/alpha */
v[0] = -0.5*u0; v[1] = -0.5*K; v[2] = alpha; v[3] = 0; v[4] = 0.5*u0; v[5] = 0.5*K;
v[6] = -0.5/rho0; v[7] = -0.5*u0; v[8] = 0; v[9] = alpha; v[10] = 0.5/rho0; v[11] = 0.5*u0;
if (useblock) {
row[0] = i; col[0] = im; col[1] = i; col[2] = ip;
ierr = MatSetValuesBlockedLocal(A,1,row,3,col,v,INSERT_VALUES);CHKERRQ(ierr);
} else {
row[0] = 2*i; row[1] = 2*i+1;
col[0] = 2*im; col[1] = 2*im+1; col[2] = 2*i; col[3] = 2*ip; col[4] = 2*ip+1;
v[3] = v[4]; v[4] = v[5]; /* pack values in first row */
ierr = MatSetValuesLocal(A,1,row,5,col,v,INSERT_VALUES);CHKERRQ(ierr);
col[2] = 2*i+1;
v[8] = v[9]; v[9] = v[10]; v[10] = v[11]; /* pack values in second row */
ierr = MatSetValuesLocal(A,1,row+1,5,col,v+6,INSERT_VALUES);CHKERRQ(ierr);
}
/* Set current state (gaussian density perturbation) */
xx[2*i] = 0.2*exp(-PetscSqr(xref)/(2*PetscSqr(sigma)));
xx[2*i+1] = 0;
break;
default: SETERRQ1(1,"not implemented for block size %D",bs);
}
}
ierr = VecRestoreArray(lf,&xx);CHKERRQ(ierr);
ierr = VecGhostRestoreLocalForm(x,&lf);CHKERRQ(ierr);
ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatMult(A,x,b);CHKERRQ(ierr);
ierr = MatView(A,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
ierr = VecView(x,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
ierr = VecView(b,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
/* Update the ghosted values, view the result on rank 0. */
ierr = VecGhostUpdateBegin(b,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
ierr = VecGhostUpdateEnd(b,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
if (!rank) {
ierr = VecGhostGetLocalForm(b,&lf);CHKERRQ(ierr);
ierr = PetscViewerASCIIPrintf(PETSC_VIEWER_STDOUT_SELF,"Local form of b on rank 0, last two nodes are ghost nodes\n");CHKERRQ(ierr);
ierr = VecView(lf,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr);
ierr = VecGhostRestoreLocalForm(b,&lf);CHKERRQ(ierr);
}
ierr = SlicedDestroy(slice);CHKERRQ(ierr);
ierr = VecDestroy(x);CHKERRQ(ierr);
ierr = VecDestroy(b);CHKERRQ(ierr);
ierr = MatDestroy(A);CHKERRQ(ierr);
ierr = PetscFinalize();CHKERRQ(ierr);
return 0;
}
int main(int argc,char **argv) {
PetscErrorCode ierr;
PetscBool view = PETSC_FALSE,
viewsoln = PETSC_FALSE,
noprealloc = PETSC_FALSE;
char root[256] = "", nodesname[256], issname[256], solnname[256];
UM mesh;
unfemCtx user;
SNES snes;
KSP ksp;
PC pc;
Mat A;
Vec r, u, uexact;
double err, h_max;
PetscInitialize(&argc,&argv,NULL,help);
ierr = PetscLogStageRegister("Read mesh ", &user.readstage); CHKERRQ(ierr); //STRIP
ierr = PetscLogStageRegister("Set-up ", &user.setupstage); CHKERRQ(ierr); //STRIP
ierr = PetscLogStageRegister("Solver ", &user.solverstage); CHKERRQ(ierr); //STRIP
ierr = PetscLogStageRegister("Residual eval ", &user.resstage); CHKERRQ(ierr); //STRIP
ierr = PetscLogStageRegister("Jacobian eval ", &user.jacstage); CHKERRQ(ierr); //STRIP
user.quaddeg = 1;
user.solncase = 0;
ierr = PetscOptionsBegin(PETSC_COMM_WORLD, "un_", "options for unfem", ""); CHKERRQ(ierr);
ierr = PetscOptionsInt("-case",
"exact solution cases: 0=linear, 1=nonlinear, 2=nonhomoNeumann, 3=chapter3, 4=koch",
"unfem.c",user.solncase,&(user.solncase),NULL); CHKERRQ(ierr);
ierr = PetscOptionsString("-mesh",
"file name root of mesh stored in PETSc binary with .vec,.is extensions",
"unfem.c",root,root,sizeof(root),NULL); CHKERRQ(ierr);
ierr = PetscOptionsInt("-quaddeg",
"quadrature degree (1,2,3)",
"unfem.c",user.quaddeg,&(user.quaddeg),NULL); CHKERRQ(ierr);
ierr = PetscOptionsBool("-view",
"view loaded nodes and elements at stdout",
"unfem.c",view,&view,NULL); CHKERRQ(ierr);
ierr = PetscOptionsBool("-view_solution",
"view solution u(x,y) to binary file; uses root name of mesh plus .soln\nsee petsc2tricontour.py to view graphically",
"unfem.c",viewsoln,&viewsoln,NULL); CHKERRQ(ierr);
ierr = PetscOptionsBool("-noprealloc",
"do not perform preallocation before matrix assembly",
"unfem.c",noprealloc,&noprealloc,NULL); CHKERRQ(ierr);
ierr = PetscOptionsEnd(); CHKERRQ(ierr);
// set parameters and exact solution
user.a_fcn = &a_lin;
user.f_fcn = &f_lin;
user.uexact_fcn = &uexact_lin;
user.gD_fcn = &gD_lin;
user.gN_fcn = &gN_lin;
switch (user.solncase) {
case 0 :
break;
case 1 :
user.a_fcn = &a_nonlin;
user.f_fcn = &f_nonlin;
break;
case 2 :
user.gN_fcn = &gN_linneu;
break;
case 3 :
user.a_fcn = &a_square;
user.f_fcn = &f_square;
user.uexact_fcn = &uexact_square;
user.gD_fcn = &gD_square;
user.gN_fcn = NULL; // seg fault if ever called
break;
case 4 :
user.a_fcn = &a_koch;
user.f_fcn = &f_koch;
user.uexact_fcn = NULL;
user.gD_fcn = &gD_koch;
user.gN_fcn = NULL; // seg fault if ever called
break;
default :
SETERRQ(PETSC_COMM_WORLD,1,"other solution cases not implemented");
}
// determine filenames
strcpy(nodesname, root);
strncat(nodesname, ".vec", 4);
strcpy(issname, root);
strncat(issname, ".is", 3);
//STARTMAININITIAL
PetscLogStagePush(user.readstage); //STRIP
// read mesh object of type UM
ierr = UMInitialize(&mesh); CHKERRQ(ierr);
ierr = UMReadNodes(&mesh,nodesname); CHKERRQ(ierr);
ierr = UMReadISs(&mesh,issname); CHKERRQ(ierr);
ierr = UMStats(&mesh, &h_max, NULL, NULL, NULL); CHKERRQ(ierr);
if (view) { //STRIP
PetscViewer stdoutviewer; //STRIP
ierr = PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&stdoutviewer); CHKERRQ(ierr); //STRIP
ierr = UMViewASCII(&mesh,stdoutviewer); CHKERRQ(ierr); //STRIP
} //STRIP
user.mesh = &mesh;
PetscLogStagePop(); //STRIP
// configure Vecs and SNES
PetscLogStagePush(user.setupstage); //STRIP
ierr = VecCreate(PETSC_COMM_WORLD,&r); CHKERRQ(ierr);
ierr = VecSetSizes(r,PETSC_DECIDE,mesh.N); CHKERRQ(ierr);
ierr = VecSetFromOptions(r); CHKERRQ(ierr);
ierr = VecDuplicate(r,&u); CHKERRQ(ierr);
ierr = VecSet(u,0.0); CHKERRQ(ierr);
ierr = SNESCreate(PETSC_COMM_WORLD,&snes); CHKERRQ(ierr);
ierr = SNESSetFunction(snes,r,FormFunction,&user); CHKERRQ(ierr);
// reset default KSP and PC
ierr = SNESGetKSP(snes,&ksp); CHKERRQ(ierr);
ierr = KSPSetType(ksp,KSPCG); CHKERRQ(ierr);
ierr = KSPGetPC(ksp,&pc); CHKERRQ(ierr);
ierr = PCSetType(pc,PCICC); CHKERRQ(ierr);
// setup matrix for Picard iteration, including preallocation
ierr = MatCreate(PETSC_COMM_WORLD,&A); CHKERRQ(ierr);
ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,mesh.N,mesh.N); CHKERRQ(ierr);
ierr = MatSetFromOptions(A); CHKERRQ(ierr);
ierr = MatSetOption(A,MAT_SYMMETRIC,PETSC_TRUE); CHKERRQ(ierr);
if (noprealloc) {
ierr = MatSetUp(A); CHKERRQ(ierr);
} else {
ierr = Preallocation(A,&user); CHKERRQ(ierr);
}
ierr = SNESSetJacobian(snes,A,A,FormPicard,&user); CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes); CHKERRQ(ierr);
PetscLogStagePop(); //STRIP
// solve
PetscLogStagePush(user.solverstage); //STRIP
ierr = SNESSolve(snes,NULL,u);CHKERRQ(ierr);
PetscLogStagePop(); //STRIP
//ENDMAININITIAL
if (viewsoln) {
strcpy(solnname, root);
strncat(solnname, ".soln", 5);
ierr = UMViewSolutionBinary(&mesh,solnname,u); CHKERRQ(ierr);
}
if (user.uexact_fcn) {
// measure error relative to exact solution
ierr = VecDuplicate(r,&uexact); CHKERRQ(ierr);
ierr = FillExact(uexact,&user); CHKERRQ(ierr);
ierr = VecAXPY(u,-1.0,uexact); CHKERRQ(ierr); // u <- u + (-1.0) uexact
ierr = VecNorm(u,NORM_INFINITY,&err); CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,
"case %d result for N=%d nodes with h = %.3e : |u-u_ex|_inf = %g\n",
user.solncase,mesh.N,h_max,err); CHKERRQ(ierr);
VecDestroy(&uexact);
} else {
ierr = PetscPrintf(PETSC_COMM_WORLD,
"case %d completed for N=%d nodes with h = %.3e (no exact solution)\n",
user.solncase,mesh.N,h_max); CHKERRQ(ierr);
}
// clean-up
SNESDestroy(&snes);
MatDestroy(&A);
VecDestroy(&u); VecDestroy(&r);
UMDestroy(&mesh);
PetscFinalize();
return 0;
}
int main(int argc,char **argv)
{
TS ts;
SNES snes_alg;
PetscErrorCode ierr;
PetscMPIInt size;
Userctx user;
PetscViewer Xview,Ybusview;
Vec X;
Mat J;
PetscInt i;
/* sensitivity context */
PetscScalar *y_ptr;
Vec lambda[1];
PetscInt *idx2;
Vec Xdot;
Vec F_alg;
PetscInt row_loc,col_loc;
PetscScalar val;
ierr = PetscInitialize(&argc,&argv,"petscoptions",help);CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size > 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"Only for sequential runs");
user.neqs_gen = 9*ngen; /* # eqs. for generator subsystem */
user.neqs_net = 2*nbus; /* # eqs. for network subsystem */
user.neqs_pgrid = user.neqs_gen + user.neqs_net;
/* Create indices for differential and algebraic equations */
ierr = PetscMalloc1(7*ngen,&idx2);CHKERRQ(ierr);
for (i=0; i<ngen; i++) {
idx2[7*i] = 9*i; idx2[7*i+1] = 9*i+1; idx2[7*i+2] = 9*i+2; idx2[7*i+3] = 9*i+3;
idx2[7*i+4] = 9*i+6; idx2[7*i+5] = 9*i+7; idx2[7*i+6] = 9*i+8;
}
ierr = ISCreateGeneral(PETSC_COMM_WORLD,7*ngen,idx2,PETSC_COPY_VALUES,&user.is_diff);CHKERRQ(ierr);
ierr = ISComplement(user.is_diff,0,user.neqs_pgrid,&user.is_alg);CHKERRQ(ierr);
ierr = PetscFree(idx2);CHKERRQ(ierr);
/* Read initial voltage vector and Ybus */
ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD,"X.bin",FILE_MODE_READ,&Xview);CHKERRQ(ierr);
ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD,"Ybus.bin",FILE_MODE_READ,&Ybusview);CHKERRQ(ierr);
ierr = VecCreate(PETSC_COMM_WORLD,&user.V0);CHKERRQ(ierr);
ierr = VecSetSizes(user.V0,PETSC_DECIDE,user.neqs_net);CHKERRQ(ierr);
ierr = VecLoad(user.V0,Xview);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&user.Ybus);CHKERRQ(ierr);
ierr = MatSetSizes(user.Ybus,PETSC_DECIDE,PETSC_DECIDE,user.neqs_net,user.neqs_net);CHKERRQ(ierr);
ierr = MatSetType(user.Ybus,MATBAIJ);CHKERRQ(ierr);
/* ierr = MatSetBlockSize(user.Ybus,2);CHKERRQ(ierr); */
ierr = MatLoad(user.Ybus,Ybusview);CHKERRQ(ierr);
/* Set run time options */
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"Transient stability fault options","");CHKERRQ(ierr);
{
user.tfaulton = 1.0;
user.tfaultoff = 1.2;
user.Rfault = 0.0001;
user.faultbus = 8;
ierr = PetscOptionsReal("-tfaulton","","",user.tfaulton,&user.tfaulton,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tfaultoff","","",user.tfaultoff,&user.tfaultoff,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-faultbus","","",user.faultbus,&user.faultbus,NULL);CHKERRQ(ierr);
user.t0 = 0.0;
user.tmax = 5.0;
ierr = PetscOptionsReal("-t0","","",user.t0,&user.t0,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tmax","","",user.tmax,&user.tmax,NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ierr = PetscViewerDestroy(&Xview);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&Ybusview);CHKERRQ(ierr);
/* Create DMs for generator and network subsystems */
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,user.neqs_gen,1,1,NULL,&user.dmgen);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmgen,"dmgen_");CHKERRQ(ierr);
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,user.neqs_net,1,1,NULL,&user.dmnet);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmnet,"dmnet_");CHKERRQ(ierr);
/* Create a composite DM packer and add the two DMs */
ierr = DMCompositeCreate(PETSC_COMM_WORLD,&user.dmpgrid);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmpgrid,"pgrid_");CHKERRQ(ierr);
ierr = DMCompositeAddDM(user.dmpgrid,user.dmgen);CHKERRQ(ierr);
ierr = DMCompositeAddDM(user.dmpgrid,user.dmnet);CHKERRQ(ierr);
ierr = DMCreateGlobalVector(user.dmpgrid,&X);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&J);CHKERRQ(ierr);
ierr = MatSetSizes(J,PETSC_DECIDE,PETSC_DECIDE,user.neqs_pgrid,user.neqs_pgrid);CHKERRQ(ierr);
ierr = MatSetFromOptions(J);CHKERRQ(ierr);
ierr = PreallocateJacobian(J,&user);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create timestepping solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
ierr = TSSetType(ts,TSCN);CHKERRQ(ierr);
ierr = TSSetIFunction(ts,NULL,(TSIFunction) IFunction,&user);CHKERRQ(ierr);
ierr = TSSetIJacobian(ts,J,J,(TSIJacobian)IJacobian,&user);CHKERRQ(ierr);
ierr = TSSetApplicationContext(ts,&user);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set initial conditions
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = SetInitialGuess(X,&user);CHKERRQ(ierr);
/* Just to set up the Jacobian structure */
ierr = VecDuplicate(X,&Xdot);CHKERRQ(ierr);
ierr = IJacobian(ts,0.0,X,Xdot,0.0,J,J,&user);CHKERRQ(ierr);
ierr = VecDestroy(&Xdot);CHKERRQ(ierr);
/*
Save trajectory of solution so that TSAdjointSolve() may be used
*/
ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);
ierr = TSSetDuration(ts,1000,user.tfaulton);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,0.0,0.01);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
user.alg_flg = PETSC_FALSE;
/* Prefault period */
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* Create the nonlinear solver for solving the algebraic system */
/* Note that although the algebraic system needs to be solved only for
Idq and V, we reuse the entire system including xgen. The xgen
variables are held constant by setting their residuals to 0 and
putting a 1 on the Jacobian diagonal for xgen rows
*/
ierr = VecDuplicate(X,&F_alg);CHKERRQ(ierr);
ierr = SNESCreate(PETSC_COMM_WORLD,&snes_alg);CHKERRQ(ierr);
ierr = SNESSetFunction(snes_alg,F_alg,AlgFunction,&user);CHKERRQ(ierr);
ierr = MatZeroEntries(J);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes_alg,J,J,AlgJacobian,&user);CHKERRQ(ierr);
ierr = SNESSetOptionsPrefix(snes_alg,"alg_");CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes_alg);CHKERRQ(ierr);
/* Apply disturbance - resistive fault at user.faultbus */
/* This is done by adding shunt conductance to the diagonal location
in the Ybus matrix */
row_loc = 2*user.faultbus; col_loc = 2*user.faultbus+1; /* Location for G */
val = 1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
row_loc = 2*user.faultbus+1; col_loc = 2*user.faultbus; /* Location for G */
val = 1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
ierr = MatAssemblyBegin(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
/* Disturbance period */
ierr = TSSetDuration(ts,1000,user.tfaultoff);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,user.tfaulton,.01);CHKERRQ(ierr);
user.alg_flg = PETSC_FALSE;
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* Remove the fault */
row_loc = 2*user.faultbus; col_loc = 2*user.faultbus+1;
val = -1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
row_loc = 2*user.faultbus+1; col_loc = 2*user.faultbus;
val = -1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
ierr = MatAssemblyBegin(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatZeroEntries(J);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
/* Post-disturbance period */
ierr = TSSetDuration(ts,1000,user.tmax);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,user.tfaultoff,.01);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Adjoint model starts here
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetPostStep(ts,NULL);CHKERRQ(ierr);
ierr = MatCreateVecs(J,&lambda[0],NULL);CHKERRQ(ierr);
/* Set initial conditions for the adjoint integration */
ierr = VecZeroEntries(lambda[0]);CHKERRQ(ierr);
ierr = VecGetArray(lambda[0],&y_ptr);CHKERRQ(ierr);
y_ptr[0] = 1.0;
ierr = VecRestoreArray(lambda[0],&y_ptr);CHKERRQ(ierr);
ierr = TSSetCostGradients(ts,1,lambda,NULL);CHKERRQ(ierr);
ierr = TSAdjointSolve(ts);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD,"\n sensitivity wrt initial conditions: \n");CHKERRQ(ierr);
ierr = VecView(lambda[0],PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);
ierr = VecDestroy(&lambda[0]);CHKERRQ(ierr);
ierr = SNESDestroy(&snes_alg);CHKERRQ(ierr);
ierr = VecDestroy(&F_alg);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr);
ierr = MatDestroy(&user.Ybus);CHKERRQ(ierr);
ierr = VecDestroy(&X);CHKERRQ(ierr);
ierr = VecDestroy(&user.V0);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmgen);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmnet);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmpgrid);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_diff);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_alg);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
EXTERN_C_END
/*MC
MATSOLVERSUPERLU = "superlu" - A solver package providing solvers LU and ILU for sequential matrices
via the external package SuperLU.
Use ./configure --download-superlu to have PETSc installed with SuperLU
Options Database Keys:
+ -mat_superlu_equil <FALSE> - Equil (None)
. -mat_superlu_colperm <COLAMD> - (choose one of) NATURAL MMD_ATA MMD_AT_PLUS_A COLAMD
. -mat_superlu_iterrefine <NOREFINE> - (choose one of) NOREFINE SINGLE DOUBLE EXTRA
. -mat_superlu_symmetricmode: <FALSE> - SymmetricMode (None)
. -mat_superlu_diagpivotthresh <1> - DiagPivotThresh (None)
. -mat_superlu_pivotgrowth <FALSE> - PivotGrowth (None)
. -mat_superlu_conditionnumber <FALSE> - ConditionNumber (None)
. -mat_superlu_rowperm <NOROWPERM> - (choose one of) NOROWPERM LargeDiag
. -mat_superlu_replacetinypivot <FALSE> - ReplaceTinyPivot (None)
. -mat_superlu_printstat <FALSE> - PrintStat (None)
. -mat_superlu_lwork <0> - size of work array in bytes used by factorization (None)
. -mat_superlu_ilu_droptol <0> - ILU_DropTol (None)
. -mat_superlu_ilu_filltol <0> - ILU_FillTol (None)
. -mat_superlu_ilu_fillfactor <0> - ILU_FillFactor (None)
. -mat_superlu_ilu_droprull <0> - ILU_DropRule (None)
. -mat_superlu_ilu_norm <0> - ILU_Norm (None)
- -mat_superlu_ilu_milu <0> - ILU_MILU (None)
Notes: Do not confuse this with MATSOLVERSUPERLU_DIST which is for parallel sparse solves
Level: beginner
.seealso: PCLU, PCILU, MATSOLVERSUPERLU_DIST, MATSOLVERMUMPS, MATSOLVERSPOOLES, PCFactorSetMatSolverPackage(), MatSolverPackage
M*/
EXTERN_C_BEGIN
#undef __FUNCT__
#define __FUNCT__ "MatGetFactor_seqaij_superlu"
PetscErrorCode MatGetFactor_seqaij_superlu(Mat A,MatFactorType ftype,Mat *F)
{
Mat B;
Mat_SuperLU *lu;
PetscErrorCode ierr;
PetscInt indx,m=A->rmap->n,n=A->cmap->n;
PetscBool flg;
const char *colperm[]={"NATURAL","MMD_ATA","MMD_AT_PLUS_A","COLAMD"}; /* MY_PERMC - not supported by the petsc interface yet */
const char *iterrefine[]={"NOREFINE", "SINGLE", "DOUBLE", "EXTRA"};
const char *rowperm[]={"NOROWPERM", "LargeDiag"}; /* MY_PERMC - not supported by the petsc interface yet */
PetscFunctionBegin;
ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr);
ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr);
ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr);
if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU){
B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU;
B->ops->ilufactorsymbolic = MatLUFactorSymbolic_SuperLU;
} else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
B->ops->destroy = MatDestroy_SuperLU;
B->ops->view = MatView_SuperLU;
B->factortype = ftype;
B->assembled = PETSC_TRUE; /* required by -ksp_view */
B->preallocated = PETSC_TRUE;
ierr = PetscNewLog(B,Mat_SuperLU,&lu);CHKERRQ(ierr);
if (ftype == MAT_FACTOR_LU){
set_default_options(&lu->options);
/* Comments from SuperLU_4.0/SRC/dgssvx.c:
"Whether or not the system will be equilibrated depends on the
scaling of the matrix A, but if equilibration is used, A is
overwritten by diag(R)*A*diag(C) and B by diag(R)*B
(if options->Trans=NOTRANS) or diag(C)*B (if options->Trans = TRANS or CONJ)."
We set 'options.Equil = NO' as default because additional space is needed for it.
*/
lu->options.Equil = NO;
} else if (ftype == MAT_FACTOR_ILU){
/* Set the default input options of ilu: */
ilu_set_default_options(&lu->options);
}
lu->options.PrintStat = NO;
/* Initialize the statistics variables. */
StatInit(&lu->stat);
lu->lwork = 0; /* allocate space internally by system malloc */
ierr = PetscOptionsBegin(((PetscObject)A)->comm,((PetscObject)A)->prefix,"SuperLU Options","Mat");CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_superlu_equil","Equil","None",(PetscBool)lu->options.Equil,(PetscBool*)&lu->options.Equil,0);CHKERRQ(ierr);
ierr = PetscOptionsEList("-mat_superlu_colperm","ColPerm","None",colperm,4,colperm[3],&indx,&flg);CHKERRQ(ierr);
if (flg) {lu->options.ColPerm = (colperm_t)indx;}
ierr = PetscOptionsEList("-mat_superlu_iterrefine","IterRefine","None",iterrefine,4,iterrefine[0],&indx,&flg);CHKERRQ(ierr);
if (flg) { lu->options.IterRefine = (IterRefine_t)indx;}
ierr = PetscOptionsBool("-mat_superlu_symmetricmode","SymmetricMode","None",(PetscBool)lu->options.SymmetricMode,&flg,0);CHKERRQ(ierr);
if (flg) lu->options.SymmetricMode = YES;
ierr = PetscOptionsReal("-mat_superlu_diagpivotthresh","DiagPivotThresh","None",lu->options.DiagPivotThresh,&lu->options.DiagPivotThresh,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_superlu_pivotgrowth","PivotGrowth","None",(PetscBool)lu->options.PivotGrowth,&flg,0);CHKERRQ(ierr);
if (flg) lu->options.PivotGrowth = YES;
ierr = PetscOptionsBool("-mat_superlu_conditionnumber","ConditionNumber","None",(PetscBool)lu->options.ConditionNumber,&flg,0);CHKERRQ(ierr);
if (flg) lu->options.ConditionNumber = YES;
ierr = PetscOptionsEList("-mat_superlu_rowperm","rowperm","None",rowperm,2,rowperm[lu->options.RowPerm],&indx,&flg);CHKERRQ(ierr);
if (flg) {lu->options.RowPerm = (rowperm_t)indx;}
ierr = PetscOptionsBool("-mat_superlu_replacetinypivot","ReplaceTinyPivot","None",(PetscBool)lu->options.ReplaceTinyPivot,&flg,0);CHKERRQ(ierr);
if (flg) lu->options.ReplaceTinyPivot = YES;
ierr = PetscOptionsBool("-mat_superlu_printstat","PrintStat","None",(PetscBool)lu->options.PrintStat,&flg,0);CHKERRQ(ierr);
if (flg) lu->options.PrintStat = YES;
ierr = PetscOptionsInt("-mat_superlu_lwork","size of work array in bytes used by factorization","None",lu->lwork,&lu->lwork,PETSC_NULL);CHKERRQ(ierr);
if (lu->lwork > 0 ){
ierr = PetscMalloc(lu->lwork,&lu->work);CHKERRQ(ierr);
} else if (lu->lwork != 0 && lu->lwork != -1){
ierr = PetscPrintf(PETSC_COMM_SELF," Warning: lwork %D is not supported by SUPERLU. The default lwork=0 is used.\n",lu->lwork);
lu->lwork = 0;
}
/* ilu options */
ierr = PetscOptionsReal("-mat_superlu_ilu_droptol","ILU_DropTol","None",lu->options.ILU_DropTol,&lu->options.ILU_DropTol,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_superlu_ilu_filltol","ILU_FillTol","None",lu->options.ILU_FillTol,&lu->options.ILU_FillTol,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_superlu_ilu_fillfactor","ILU_FillFactor","None",lu->options.ILU_FillFactor,&lu->options.ILU_FillFactor,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_superlu_ilu_droprull","ILU_DropRule","None",lu->options.ILU_DropRule,&lu->options.ILU_DropRule,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_superlu_ilu_norm","ILU_Norm","None",lu->options.ILU_Norm,&indx,&flg);CHKERRQ(ierr);
if (flg){
lu->options.ILU_Norm = (norm_t)indx;
}
ierr = PetscOptionsInt("-mat_superlu_ilu_milu","ILU_MILU","None",lu->options.ILU_MILU,&indx,&flg);CHKERRQ(ierr);
if (flg){
lu->options.ILU_MILU = (milu_t)indx;
}
PetscOptionsEnd();
if (lu->options.Equil == YES) {
/* superlu overwrites input matrix and rhs when Equil is used, thus create A_dup to keep user's A unchanged */
ierr = MatDuplicate_SeqAIJ(A,MAT_COPY_VALUES,&lu->A_dup);CHKERRQ(ierr);
}
/* Allocate spaces (notice sizes are for the transpose) */
ierr = PetscMalloc(m*sizeof(PetscInt),&lu->etree);CHKERRQ(ierr);
ierr = PetscMalloc(n*sizeof(PetscInt),&lu->perm_r);CHKERRQ(ierr);
ierr = PetscMalloc(m*sizeof(PetscInt),&lu->perm_c);CHKERRQ(ierr);
ierr = PetscMalloc(n*sizeof(PetscScalar),&lu->R);CHKERRQ(ierr);
ierr = PetscMalloc(m*sizeof(PetscScalar),&lu->C);CHKERRQ(ierr);
/* create rhs and solution x without allocate space for .Store */
#if defined(PETSC_USE_COMPLEX)
zCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
zCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_Z, SLU_GE);
#else
dCreate_Dense_Matrix(&lu->B, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
dCreate_Dense_Matrix(&lu->X, m, 1, PETSC_NULL, m, SLU_DN, SLU_D, SLU_GE);
#endif
#ifdef SUPERLU2
ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatCreateNull","MatCreateNull_SuperLU",(void(*)(void))MatCreateNull_SuperLU);CHKERRQ(ierr);
#endif
ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatFactorGetSolverPackage_C","MatFactorGetSolverPackage_seqaij_superlu",MatFactorGetSolverPackage_seqaij_superlu);CHKERRQ(ierr);
ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSuperluSetILUDropTol_C","MatSuperluSetILUDropTol_SuperLU",MatSuperluSetILUDropTol_SuperLU);CHKERRQ(ierr);
B->spptr = lu;
*F = B;
PetscFunctionReturn(0);
}
int main(int argc,char **argv)
{
TS ts; /* ODE integrator */
Vec U,V; /* solution will be stored here */
Vec F; /* residual vector */
Mat J; /* Jacobian matrix */
PetscMPIInt rank;
PetscScalar *u,*v;
AppCtx app;
PetscInt direction[2];
PetscBool terminate[2];
TSAdapt adapt;
PetscErrorCode ierr;
ierr = PetscInitialize(&argc,&argv,NULL,help);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
app.Cd = 0.0;
app.Cr = 0.9;
app.bounces = 0;
app.maxbounces = 10;
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"ex44 options","");CHKERRQ(ierr);
ierr = PetscOptionsReal("-Cd","Drag coefficient","",app.Cd,&app.Cd,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-Cr","Restitution coefficient","",app.Cr,&app.Cr,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-maxbounces","Maximum number of bounces","",app.maxbounces,&app.maxbounces,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
/*ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);*/
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
ierr = TSSetType(ts,TSALPHA2);CHKERRQ(ierr);
ierr = TSSetDuration(ts,PETSC_MAX_INT,PETSC_MAX_REAL);CHKERRQ(ierr);
ierr = TSSetTimeStep(ts,0.1);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
ierr = TSAdaptSetStepLimits(adapt,0.0,0.5);CHKERRQ(ierr);
direction[0] = -1; terminate[0] = PETSC_FALSE;
direction[1] = -1; terminate[1] = PETSC_TRUE;
ierr = TSSetEventHandler(ts,2,direction,terminate,Event,PostEvent,&app);CHKERRQ(ierr);
ierr = MatCreateAIJ(PETSC_COMM_WORLD,1,1,PETSC_DECIDE,PETSC_DECIDE,1,NULL,0,NULL,&J);CHKERRQ(ierr);
ierr = MatSetFromOptions(J);CHKERRQ(ierr);
ierr = MatSetUp(J);CHKERRQ(ierr);
ierr = MatCreateVecs(J,NULL,&F);CHKERRQ(ierr);
ierr = TSSetI2Function(ts,F,I2Function,&app);CHKERRQ(ierr);
ierr = TSSetI2Jacobian(ts,J,J,I2Jacobian,&app);CHKERRQ(ierr);
ierr = VecDestroy(&F);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr);
ierr = TSGetI2Jacobian(ts,&J,NULL,NULL,NULL);CHKERRQ(ierr);
ierr = MatCreateVecs(J,&U,NULL);CHKERRQ(ierr);
ierr = MatCreateVecs(J,&V,NULL);CHKERRQ(ierr);
ierr = VecGetArray(U,&u);CHKERRQ(ierr);
ierr = VecGetArray(V,&v);CHKERRQ(ierr);
u[0] = 5.0*rank; v[0] = 20.0;
ierr = VecRestoreArray(U,&u);CHKERRQ(ierr);
ierr = VecRestoreArray(V,&v);CHKERRQ(ierr);
ierr = TS2SetSolution(ts,U,V);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
ierr = TSSolve(ts,NULL);CHKERRQ(ierr);
ierr = VecDestroy(&U);CHKERRQ(ierr);
ierr = VecDestroy(&V);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
-pc_gasm_print_subdomains\n \n";
/*
Note: This example focuses on setting the subdomains for the GASM
preconditioner for a problem on a 2D rectangular grid. See ex1.c
and ex2.c for more detailed comments on the basic usage of KSP
(including working with matrices and vectors).
The GASM preconditioner is fully parallel. The user-space routine
CreateSubdomains2D that computes the domain decomposition is also parallel
and attempts to generate both subdomains straddling processors and multiple
domains per processor.
This matrix in this linear system arises from the discretized Laplacian,
and thus is not very interesting in terms of experimenting with variants
of the GASM preconditioner.
*/
/*T
Concepts: KSP^Additive Schwarz Method (GASM) with user-defined subdomains
Processors: n
T*/
/*
Include "petscksp.h" so that we can use KSP solvers. Note that this file
automatically includes:
petscsys.h - base PETSc routines petscvec.h - vectors
petscmat.h - matrices
petscis.h - index sets petscksp.h - Krylov subspace methods
petscviewer.h - viewers petscpc.h - preconditioners
*/
#include <petscksp.h>
#include <petscmat.h>
int main(int argc,char **args)
{
Vec x,b,u; /* approx solution, RHS, exact solution */
Mat A,perA; /* linear system matrix */
KSP ksp; /* linear solver context */
PC pc; /* PC context */
PetscInt overlap; /* width of subdomain overlap */
PetscInt m,n; /* mesh dimensions in x- and y- directions */
PetscInt M,N; /* number of subdomains in x- and y- directions */
PetscInt i,j,Ii,J,Istart,Iend;
PetscErrorCode ierr;
PetscMPIInt size;
PetscBool flg;
PetscBool user_set_subdomains;
PetscScalar v, one = 1.0;
MatPartitioning part;
IS coarseparts,fineparts;
IS is,isn,isrows;
MPI_Comm comm;
PetscReal e;
ierr = PetscInitialize(&argc,&args,(char*)0,help);
if (ierr) return ierr;
comm = PETSC_COMM_WORLD;
ierr = MPI_Comm_size(comm,&size);
CHKERRQ(ierr);
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"ex62","PC");
CHKERRQ(ierr);
m = 15;
ierr = PetscOptionsInt("-M", "Number of mesh points in the x-direction","PCGASMCreateSubdomains2D",m,&m,NULL);
CHKERRQ(ierr);
n = 17;
ierr = PetscOptionsInt("-N","Number of mesh points in the y-direction","PCGASMCreateSubdomains2D",n,&n,NULL);
CHKERRQ(ierr);
user_set_subdomains = PETSC_FALSE;
ierr = PetscOptionsBool("-user_set_subdomains","Use the user-specified 2D tiling of mesh by subdomains","PCGASMCreateSubdomains2D",user_set_subdomains,&user_set_subdomains,NULL);
CHKERRQ(ierr);
M = 2;
ierr = PetscOptionsInt("-Mdomains","Number of subdomain tiles in the x-direction","PCGASMSetSubdomains2D",M,&M,NULL);
CHKERRQ(ierr);
N = 1;
ierr = PetscOptionsInt("-Ndomains","Number of subdomain tiles in the y-direction","PCGASMSetSubdomains2D",N,&N,NULL);
CHKERRQ(ierr);
overlap = 1;
ierr = PetscOptionsInt("-overlap","Size of tile overlap.","PCGASMSetSubdomains2D",overlap,&overlap,NULL);
CHKERRQ(ierr);
ierr = PetscOptionsEnd();
CHKERRQ(ierr);
/* -------------------------------------------------------------------
Compute the matrix and right-hand-side vector that define
the linear system, Ax = b.
------------------------------------------------------------------- */
/*
Assemble the matrix for the five point stencil, YET AGAIN
*/
ierr = MatCreate(comm,&A);
CHKERRQ(ierr);
ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m*n,m*n);
CHKERRQ(ierr);
ierr = MatSetFromOptions(A);
CHKERRQ(ierr);
ierr = MatSetUp(A);
CHKERRQ(ierr);
ierr = MatGetOwnershipRange(A,&Istart,&Iend);
CHKERRQ(ierr);
for (Ii=Istart; Ii<Iend; Ii++) {
v = -1.0;
i = Ii/n;
j = Ii - i*n;
if (i>0) {
J = Ii - n;
ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);
CHKERRQ(ierr);
}
if (i<m-1) {
J = Ii + n;
ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);
CHKERRQ(ierr);
}
if (j>0) {
J = Ii - 1;
ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);
CHKERRQ(ierr);
}
if (j<n-1) {
J = Ii + 1;
ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);
CHKERRQ(ierr);
}
v = 4.0;
ierr = MatSetValues(A,1,&Ii,1,&Ii,&v,INSERT_VALUES);
CHKERRQ(ierr);
}
ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
/*
Partition the graph of the matrix
*/
ierr = MatPartitioningCreate(comm,&part);
CHKERRQ(ierr);
ierr = MatPartitioningSetAdjacency(part,A);
CHKERRQ(ierr);
ierr = MatPartitioningSetType(part,MATPARTITIONINGHIERARCH);
CHKERRQ(ierr);
ierr = MatPartitioningHierarchicalSetNcoarseparts(part,2);
CHKERRQ(ierr);
ierr = MatPartitioningHierarchicalSetNfineparts(part,2);
CHKERRQ(ierr);
ierr = MatPartitioningSetFromOptions(part);
CHKERRQ(ierr);
/* get new processor owner number of each vertex */
ierr = MatPartitioningApply(part,&is);
CHKERRQ(ierr);
/* get coarse parts according to which we rearrange the matrix */
ierr = MatPartitioningHierarchicalGetCoarseparts(part,&coarseparts);
CHKERRQ(ierr);
/* fine parts are used with coarse parts */
ierr = MatPartitioningHierarchicalGetFineparts(part,&fineparts);
CHKERRQ(ierr);
/* get new global number of each old global number */
ierr = ISPartitioningToNumbering(is,&isn);
CHKERRQ(ierr);
ierr = ISBuildTwoSided(is,NULL,&isrows);
CHKERRQ(ierr);
ierr = MatGetSubMatrix(A,isrows,isrows,MAT_INITIAL_MATRIX,&perA);
CHKERRQ(ierr);
ierr = MatCreateVecs(perA,&b,NULL);
CHKERRQ(ierr);
ierr = VecSetFromOptions(b);
CHKERRQ(ierr);
ierr = VecDuplicate(b,&u);
CHKERRQ(ierr);
ierr = VecDuplicate(b,&x);
CHKERRQ(ierr);
ierr = VecSet(u,one);
CHKERRQ(ierr);
ierr = MatMult(perA,u,b);
CHKERRQ(ierr);
ierr = KSPCreate(comm,&ksp);
CHKERRQ(ierr);
/*
Set operators. Here the matrix that defines the linear system
also serves as the preconditioning matrix.
*/
ierr = KSPSetOperators(ksp,perA,perA);
CHKERRQ(ierr);
/*
Set the default preconditioner for this program to be GASM
*/
ierr = KSPGetPC(ksp,&pc);
CHKERRQ(ierr);
ierr = PCSetType(pc,PCGASM);
CHKERRQ(ierr);
ierr = KSPSetFromOptions(ksp);
CHKERRQ(ierr);
/* -------------------------------------------------------------------
Solve the linear system
------------------------------------------------------------------- */
ierr = KSPSolve(ksp,b,x);
CHKERRQ(ierr);
/* -------------------------------------------------------------------
Compare result to the exact solution
------------------------------------------------------------------- */
ierr = VecAXPY(x,-1.0,u);
CHKERRQ(ierr);
ierr = VecNorm(x,NORM_INFINITY, &e);
CHKERRQ(ierr);
flg = PETSC_FALSE;
ierr = PetscOptionsGetBool(NULL,NULL,"-print_error",&flg,NULL);
CHKERRQ(ierr);
if (flg) {
ierr = PetscPrintf(PETSC_COMM_WORLD, "Infinity norm of the error: %g\n", (double)e);
CHKERRQ(ierr);
}
/*
Free work space. All PETSc objects should be destroyed when they
are no longer needed.
*/
ierr = KSPDestroy(&ksp);
CHKERRQ(ierr);
ierr = VecDestroy(&u);
CHKERRQ(ierr);
ierr = VecDestroy(&x);
CHKERRQ(ierr);
ierr = VecDestroy(&b);
CHKERRQ(ierr);
ierr = MatDestroy(&A);
CHKERRQ(ierr);
ierr = MatDestroy(&perA);
CHKERRQ(ierr);
ierr = ISDestroy(&is);
CHKERRQ(ierr);
ierr = ISDestroy(&coarseparts);
CHKERRQ(ierr);
ierr = ISDestroy(&fineparts);
CHKERRQ(ierr);
ierr = ISDestroy(&isrows);
CHKERRQ(ierr);
ierr = ISDestroy(&isn);
CHKERRQ(ierr);
ierr = MatPartitioningDestroy(&part);
CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
/*@C
TSSetEventHandler - Sets a monitoring function used for detecting events
Logically Collective on TS
Input Parameters:
+ ts - the TS context obtained from TSCreate()
. nevents - number of local events
. direction - direction of zero crossing to be detected. -1 => Zero crossing in negative direction,
+1 => Zero crossing in positive direction, 0 => both ways (one for each event)
. terminate - flag to indicate whether time stepping should be terminated after
event is detected (one for each event)
. eventhandler - event monitoring routine
. postevent - [optional] post-event function
- ctx - [optional] user-defined context for private data for the
event monitor and post event routine (use NULL if no
context is desired)
Calling sequence of eventhandler:
PetscErrorCode PetscEventHandler(TS ts,PetscReal t,Vec U,PetscScalar fvalue[],void* ctx)
Input Parameters:
+ ts - the TS context
. t - current time
. U - current iterate
- ctx - [optional] context passed with eventhandler
Output parameters:
. fvalue - function value of events at time t
Calling sequence of postevent:
PetscErrorCode PostEvent(TS ts,PetscInt nevents_zero,PetscInt events_zero[],PetscReal t,Vec U,PetscBool forwardsolve,void* ctx)
Input Parameters:
+ ts - the TS context
. nevents_zero - number of local events whose event function is zero
. events_zero - indices of local events which have reached zero
. t - current time
. U - current solution
. forwardsolve - Flag to indicate whether TS is doing a forward solve (1) or adjoint solve (0)
- ctx - the context passed with eventhandler
Level: intermediate
.keywords: TS, event, set
.seealso: TSCreate(), TSSetTimeStep(), TSSetConvergedReason()
@*/
PetscErrorCode TSSetEventHandler(TS ts,PetscInt nevents,PetscInt direction[],PetscBool terminate[],PetscErrorCode (*eventhandler)(TS,PetscReal,Vec,PetscScalar[],void*),PetscErrorCode (*postevent)(TS,PetscInt,PetscInt[],PetscReal,Vec,PetscBool,void*),void *ctx)
{
PetscErrorCode ierr;
TSEvent event;
PetscInt i;
PetscBool flg;
#if defined PETSC_USE_REAL_SINGLE
PetscReal tol=1e-4;
#else
PetscReal tol=1e-6;
#endif
PetscFunctionBegin;
PetscValidHeaderSpecific(ts,TS_CLASSID,1);
if(nevents) {
PetscValidIntPointer(direction,2);
PetscValidIntPointer(terminate,3);
}
ierr = PetscNewLog(ts,&event);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->fvalue);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->fvalue_prev);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->fvalue_right);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->zerocrossing);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->side);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->direction);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->terminate);CHKERRQ(ierr);
ierr = PetscMalloc1(nevents,&event->vtol);CHKERRQ(ierr);
for (i=0; i < nevents; i++) {
event->direction[i] = direction[i];
event->terminate[i] = terminate[i];
event->zerocrossing[i] = PETSC_FALSE;
event->side[i] = 0;
}
ierr = PetscMalloc1(nevents,&event->events_zero);CHKERRQ(ierr);
event->nevents = nevents;
event->eventhandler = eventhandler;
event->postevent = postevent;
event->ctx = ctx;
event->recsize = 8; /* Initial size of the recorder */
ierr = PetscOptionsBegin(((PetscObject)ts)->comm,"","TS Event options","");CHKERRQ(ierr);
{
ierr = PetscOptionsReal("-ts_event_tol","Scalar event tolerance for zero crossing check","TSSetEventTolerances",tol,&tol,NULL);CHKERRQ(ierr);
ierr = PetscOptionsName("-ts_event_monitor","Print choices made by event handler","",&flg);CHKERRQ(ierr);
ierr = PetscOptionsInt("-ts_event_recorder_initial_size","Initial size of event recorder","",event->recsize,&event->recsize,NULL);CHKERRQ(ierr);
}
PetscOptionsEnd();
ierr = PetscMalloc1(event->recsize,&event->recorder.time);CHKERRQ(ierr);
ierr = PetscMalloc1(event->recsize,&event->recorder.stepnum);CHKERRQ(ierr);
ierr = PetscMalloc1(event->recsize,&event->recorder.nevents);CHKERRQ(ierr);
ierr = PetscMalloc1(event->recsize,&event->recorder.eventidx);CHKERRQ(ierr);
for (i=0; i < event->recsize; i++) {
ierr = PetscMalloc1(event->nevents,&event->recorder.eventidx[i]);CHKERRQ(ierr);
}
/* Initialize the event recorder */
event->recorder.ctr = 0;
for (i=0; i < event->nevents; i++) event->vtol[i] = tol;
if (flg) {ierr = PetscViewerASCIIOpen(PETSC_COMM_SELF,"stdout",&event->monitor);CHKERRQ(ierr);}
ierr = TSEventDestroy(&ts->event);CHKERRQ(ierr);
ts->event = event;
ts->event->refct = 1;
PetscFunctionReturn(0);
}
int main(int argc,char **argv)
{
TS ts;
SNES snes_alg;
PetscErrorCode ierr;
PetscMPIInt size;
Userctx user;
PetscViewer Xview,Ybusview;
Vec X;
Mat J;
PetscInt i;
ierr = PetscInitialize(&argc,&argv,"petscoptions",help);CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size > 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"Only for sequential runs");
user.neqs_gen = 9*ngen; /* # eqs. for generator subsystem */
user.neqs_net = 2*nbus; /* # eqs. for network subsystem */
user.neqs_pgrid = user.neqs_gen + user.neqs_net;
/* Create indices for differential and algebraic equations */
PetscInt *idx2;
ierr = PetscMalloc1(7*ngen,&idx2);CHKERRQ(ierr);
for (i=0; i<ngen; i++) {
idx2[7*i] = 9*i; idx2[7*i+1] = 9*i+1; idx2[7*i+2] = 9*i+2; idx2[7*i+3] = 9*i+3;
idx2[7*i+4] = 9*i+6; idx2[7*i+5] = 9*i+7; idx2[7*i+6] = 9*i+8;
}
ierr = ISCreateGeneral(PETSC_COMM_WORLD,7*ngen,idx2,PETSC_COPY_VALUES,&user.is_diff);CHKERRQ(ierr);
ierr = ISComplement(user.is_diff,0,user.neqs_pgrid,&user.is_alg);CHKERRQ(ierr);
ierr = PetscFree(idx2);CHKERRQ(ierr);
/* Read initial voltage vector and Ybus */
ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD,"X.bin",FILE_MODE_READ,&Xview);CHKERRQ(ierr);
ierr = PetscViewerBinaryOpen(PETSC_COMM_WORLD,"Ybus.bin",FILE_MODE_READ,&Ybusview);CHKERRQ(ierr);
ierr = VecCreate(PETSC_COMM_WORLD,&user.V0);CHKERRQ(ierr);
ierr = VecSetSizes(user.V0,PETSC_DECIDE,user.neqs_net);CHKERRQ(ierr);
ierr = VecLoad(user.V0,Xview);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&user.Ybus);CHKERRQ(ierr);
ierr = MatSetSizes(user.Ybus,PETSC_DECIDE,PETSC_DECIDE,user.neqs_net,user.neqs_net);CHKERRQ(ierr);
ierr = MatSetType(user.Ybus,MATBAIJ);CHKERRQ(ierr);
/* ierr = MatSetBlockSize(user.Ybus,2);CHKERRQ(ierr); */
ierr = MatLoad(user.Ybus,Ybusview);CHKERRQ(ierr);
/* Set run time options */
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"Transient stability fault options","");CHKERRQ(ierr);
{
user.tfaulton = 1.0;
user.tfaultoff = 1.2;
user.Rfault = 0.0001;
user.faultbus = 8;
ierr = PetscOptionsReal("-tfaulton","","",user.tfaulton,&user.tfaulton,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tfaultoff","","",user.tfaultoff,&user.tfaultoff,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-faultbus","","",user.faultbus,&user.faultbus,NULL);CHKERRQ(ierr);
user.t0 = 0.0;
user.tmax = 5.0;
ierr = PetscOptionsReal("-t0","","",user.t0,&user.t0,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tmax","","",user.tmax,&user.tmax,NULL);CHKERRQ(ierr);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ierr = PetscViewerDestroy(&Xview);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&Ybusview);CHKERRQ(ierr);
/* Create DMs for generator and network subsystems */
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,user.neqs_gen,1,1,NULL,&user.dmgen);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmgen,"dmgen_");CHKERRQ(ierr);
ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,user.neqs_net,1,1,NULL,&user.dmnet);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmnet,"dmnet_");CHKERRQ(ierr);
/* Create a composite DM packer and add the two DMs */
ierr = DMCompositeCreate(PETSC_COMM_WORLD,&user.dmpgrid);CHKERRQ(ierr);
ierr = DMSetOptionsPrefix(user.dmpgrid,"pgrid_");CHKERRQ(ierr);
ierr = DMCompositeAddDM(user.dmpgrid,user.dmgen);CHKERRQ(ierr);
ierr = DMCompositeAddDM(user.dmpgrid,user.dmnet);CHKERRQ(ierr);
ierr = DMCreateGlobalVector(user.dmpgrid,&X);CHKERRQ(ierr);
ierr = MatCreate(PETSC_COMM_WORLD,&J);CHKERRQ(ierr);
ierr = MatSetSizes(J,PETSC_DECIDE,PETSC_DECIDE,user.neqs_pgrid,user.neqs_pgrid);CHKERRQ(ierr);
ierr = MatSetFromOptions(J);CHKERRQ(ierr);
ierr = PreallocateJacobian(J,&user);CHKERRQ(ierr);
/* Create matrix to save solutions at each time step */
user.stepnum = 0;
ierr = MatCreateSeqDense(PETSC_COMM_SELF,user.neqs_pgrid+1,1002,NULL,&user.Sol);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create timestepping solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
ierr = TSSetEquationType(ts,TS_EQ_DAE_IMPLICIT_INDEX1);CHKERRQ(ierr);
ierr = TSARKIMEXSetFullyImplicit(ts,PETSC_TRUE);CHKERRQ(ierr);
ierr = TSSetIFunction(ts,NULL,(TSIFunction) IFunction,&user);CHKERRQ(ierr);
ierr = TSSetIJacobian(ts,J,J,(TSIJacobian)IJacobian,&user);CHKERRQ(ierr);
ierr = TSSetApplicationContext(ts,&user);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set initial conditions
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = SetInitialGuess(X,&user);CHKERRQ(ierr);
/* Just to set up the Jacobian structure */
Vec Xdot;
MatStructure flg;
ierr = VecDuplicate(X,&Xdot);CHKERRQ(ierr);
ierr = IJacobian(ts,0.0,X,Xdot,0.0,J,J,&flg,&user);CHKERRQ(ierr);
ierr = VecDestroy(&Xdot);CHKERRQ(ierr);
/* Save initial solution */
PetscScalar *x,*mat;
PetscInt idx=user.stepnum*(user.neqs_pgrid+1);
ierr = MatDenseGetArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecGetArray(X,&x);CHKERRQ(ierr);
mat[idx] = 0.0;
ierr = PetscMemcpy(mat+idx+1,x,user.neqs_pgrid*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = MatDenseRestoreArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecRestoreArray(X,&x);CHKERRQ(ierr);
user.stepnum++;
ierr = TSSetDuration(ts,1000,user.tfaulton);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,0.0,0.01);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
ierr = TSSetPostStep(ts,SaveSolution);CHKERRQ(ierr);
user.alg_flg = PETSC_FALSE;
/* Prefault period */
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* Create the nonlinear solver for solving the algebraic system */
/* Note that although the algebraic system needs to be solved only for
Idq and V, we reuse the entire system including xgen. The xgen
variables are held constant by setting their residuals to 0 and
putting a 1 on the Jacobian diagonal for xgen rows
*/
Vec F_alg;
ierr = VecDuplicate(X,&F_alg);CHKERRQ(ierr);
ierr = SNESCreate(PETSC_COMM_WORLD,&snes_alg);CHKERRQ(ierr);
ierr = SNESSetFunction(snes_alg,F_alg,AlgFunction,&user);CHKERRQ(ierr);
ierr = MatZeroEntries(J);CHKERRQ(ierr);
ierr = SNESSetJacobian(snes_alg,J,J,AlgJacobian,&user);CHKERRQ(ierr);
ierr = SNESSetOptionsPrefix(snes_alg,"alg_");CHKERRQ(ierr);
ierr = SNESSetFromOptions(snes_alg);CHKERRQ(ierr);
/* Apply disturbance - resistive fault at user.faultbus */
/* This is done by adding shunt conductance to the diagonal location
in the Ybus matrix */
PetscInt row_loc,col_loc;
PetscScalar val;
row_loc = 2*user.faultbus; col_loc = 2*user.faultbus+1; /* Location for G */
val = 1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
row_loc = 2*user.faultbus+1; col_loc = 2*user.faultbus; /* Location for G */
val = 1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
ierr = MatAssemblyBegin(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
/* Save fault-on solution */
idx = user.stepnum*(user.neqs_pgrid+1);
ierr = MatDenseGetArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecGetArray(X,&x);CHKERRQ(ierr);
mat[idx] = user.tfaulton;
ierr = PetscMemcpy(mat+idx+1,x,user.neqs_pgrid*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = MatDenseRestoreArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecRestoreArray(X,&x);CHKERRQ(ierr);
user.stepnum++;
/* Disturbance period */
ierr = TSSetDuration(ts,1000,user.tfaultoff);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,user.tfaulton,.01);CHKERRQ(ierr);
user.alg_flg = PETSC_FALSE;
ierr = TSSolve(ts,X);CHKERRQ(ierr);
/* Remove the fault */
row_loc = 2*user.faultbus; col_loc = 2*user.faultbus+1;
val = -1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
row_loc = 2*user.faultbus+1; col_loc = 2*user.faultbus;
val = -1/user.Rfault;
ierr = MatSetValues(user.Ybus,1,&row_loc,1,&col_loc,&val,ADD_VALUES);CHKERRQ(ierr);
ierr = MatAssemblyBegin(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(user.Ybus,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatZeroEntries(J);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
/* Solve the algebraic equations */
ierr = SNESSolve(snes_alg,NULL,X);CHKERRQ(ierr);
/* Save tfault off solution */
idx = user.stepnum*(user.neqs_pgrid+1);
ierr = MatDenseGetArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecGetArray(X,&x);CHKERRQ(ierr);
mat[idx] = user.tfaultoff;
ierr = PetscMemcpy(mat+idx+1,x,user.neqs_pgrid*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = MatDenseRestoreArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = VecRestoreArray(X,&x);CHKERRQ(ierr);
user.stepnum++;
/* Post-disturbance period */
ierr = TSSetDuration(ts,1000,user.tmax);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,user.tfaultoff,.01);CHKERRQ(ierr);
user.alg_flg = PETSC_TRUE;
ierr = TSSolve(ts,X);CHKERRQ(ierr);
ierr = MatAssemblyBegin(user.Sol,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(user.Sol,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
Mat A;
PetscScalar *amat;
ierr = MatCreateSeqDense(PETSC_COMM_SELF,user.neqs_pgrid+1,user.stepnum,NULL,&A);CHKERRQ(ierr);
ierr = MatDenseGetArray(user.Sol,&mat);CHKERRQ(ierr);
ierr = MatDenseGetArray(A,&amat);CHKERRQ(ierr);
ierr = PetscMemcpy(amat,mat,(user.stepnum*(user.neqs_pgrid+1))*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = MatDenseRestoreArray(A,&amat);CHKERRQ(ierr);
ierr = MatDenseRestoreArray(user.Sol,&mat);CHKERRQ(ierr);
PetscViewer viewer;
ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,"out.bin",FILE_MODE_WRITE,&viewer);CHKERRQ(ierr);
ierr = MatView(A,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = MatDestroy(&A);CHKERRQ(ierr);
ierr = SNESDestroy(&snes_alg);CHKERRQ(ierr);
ierr = VecDestroy(&F_alg);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr);
ierr = MatDestroy(&user.Ybus);CHKERRQ(ierr);
ierr = MatDestroy(&user.Sol);CHKERRQ(ierr);
ierr = VecDestroy(&X);CHKERRQ(ierr);
ierr = VecDestroy(&user.V0);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmgen);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmnet);CHKERRQ(ierr);
ierr = DMDestroy(&user.dmpgrid);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_diff);CHKERRQ(ierr);
ierr = ISDestroy(&user.is_alg);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = PetscFinalize();
return(0);
}
int main(int argc, char *argv[]) {
PetscErrorCode ierr;
PetscMPIInt rank;
AppCtx user;
PetscInt p=2,N=64,C=1;
PetscInt ng = p+2; /* integration in each direction */
PetscInt Nx,Ny;
Vec U; /* solution vector */
Mat J;
TS ts;
PetscInt steps;
PetscReal ftime;
/* This code solve the dimensionless form of the isothermal
Navier-Stokes-Korteweg equations as presented in:
Gomez, Hughes, Nogueira, Calo
Isogeometric analysis of the isothermal Navier-Stokes-Korteweg equations
CMAME, 2010
Equation/section numbers reflect this publication.
*/
// Petsc Initialization rite of passage
ierr = PetscInitialize(&argc,&argv,0,help);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD, &rank);CHKERRQ(ierr);
// Define simulation specific parameters
user.L0 = 1.0; // length scale
user.C1x = 0.75; user.C1y = 0.50; // bubble centers
user.C2x = 0.25; user.C2y = 0.50;
user.C3x = 0.40; user.C3y = 0.75;
user.R1 = 0.10; user.R2 = 0.15; user.R3 = 0.08; // bubble radii
user.alpha = 2.0; // (Eq. 41)
user.theta = 0.85; // temperature parameter (just before section 5.1)
// Set discretization options
ierr = PetscOptionsBegin(PETSC_COMM_WORLD, "", "NavierStokesKorteweg Options", "IGA");CHKERRQ(ierr);
ierr = PetscOptionsInt("-p", "polynomial order", __FILE__, p, &p, PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-C", "global continuity order", __FILE__, C, &C, PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-N", "number of elements (along one dimension)", __FILE__, N, &N, PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
// Compute simulation parameters
user.h = user.L0/N; // characteristic length scale of mesh (Eq. 43, simplified for uniform elements)
user.Ca = user.h/user.L0; // capillarity number (Eq. 38)
user.Re = user.alpha/user.Ca; // Reynolds number (Eq. 39)
// Test C < p
if(p <= C){
SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_ARG_OUTOFRANGE, "Discretization inconsistent: polynomial order must be greater than degree of continuity");
}
Nx=Ny=N;
// Initialize B-spline space
ierr = DMCreate(PETSC_COMM_WORLD,&user.iga);CHKERRQ(ierr);
ierr = DMSetType(user.iga, DMIGA);CHKERRQ(ierr);
ierr = DMIGAInitializeUniform2d(user.iga,PETSC_FALSE,2,3,
p,Nx,C,0.0,1.0,PETSC_TRUE,ng,
p,Ny,C,0.0,1.0,PETSC_TRUE,ng);CHKERRQ(ierr);
ierr = DMCreateGlobalVector(user.iga,&U);CHKERRQ(ierr);
ierr = FormInitialCondition(&user,U);CHKERRQ(ierr);
ierr = DMIGASetFieldName(user.iga, 0, "density");CHKERRQ(ierr);
ierr = DMIGASetFieldName(user.iga, 1, "velocity-u");CHKERRQ(ierr);
ierr = DMIGASetFieldName(user.iga, 2, "velocity-v");CHKERRQ(ierr);
ierr = DMCreateMatrix(user.iga, MATAIJ, &J);CHKERRQ(ierr);
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetType(ts,TSALPHA);CHKERRQ(ierr);
ierr = TSAlphaSetRadius(ts,0.5);CHKERRQ(ierr);
ierr = TSSetDM(ts,user.iga);CHKERRQ(ierr);
ierr = TSSetSolution(ts,U);CHKERRQ(ierr);
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
ierr = TSSetIFunction(ts,PETSC_NULL,FormResidual,&user);CHKERRQ(ierr);
ierr = TSSetIJacobian(ts,J,J,FormTangent,&user);CHKERRQ(ierr);
ierr = TSSetDuration(ts,1000000,1000.0);CHKERRQ(ierr);
ierr = TSSetInitialTimeStep(ts,0.0,0.001);CHKERRQ(ierr);
ierr = TSAlphaSetAdapt(ts,TSAlphaAdaptDefault,PETSC_NULL);CHKERRQ(ierr);
ierr = TSMonitorSet(ts,OutputMonitor,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
ierr = TSSolve(ts,U,&ftime);CHKERRQ(ierr);
ierr = TSGetTimeStepNumber(ts,&steps);CHKERRQ(ierr);
// Cleanup
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = DMDestroy(&user.iga);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
int main(int argc,char **argv)
{
TS ts; /* ODE integrator */
Vec U; /* solution will be stored here */
PetscErrorCode ierr;
PetscMPIInt size;
PetscInt n = 2;
PetscScalar *u;
AppCtx app;
PetscInt direction[2];
PetscBool terminate[2];
PetscBool rhs_form=PETSC_FALSE,hist=PETSC_TRUE;
TSAdapt adapt;
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Initialize program
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;
ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr);
if (size > 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"Only for sequential runs");
app.nbounces = 0;
app.maxbounces = 10;
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"ex40 options","");CHKERRQ(ierr);
ierr = PetscOptionsInt("-maxbounces","","",app.maxbounces,&app.maxbounces,NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-test_adapthistory","","",hist,&hist,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Create timestepping solver context
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
ierr = TSSetType(ts,TSROSW);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set ODE routines
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
/* Users are advised against the following branching and code duplication.
For problems without a mass matrix like the one at hand, the RHSFunction
(and companion RHSJacobian) interface is enough to support both explicit
and implicit timesteppers. This tutorial example also deals with the
IFunction/IJacobian interface for demonstration and testing purposes. */
ierr = PetscOptionsGetBool(NULL,NULL,"-rhs-form",&rhs_form,NULL);CHKERRQ(ierr);
if (rhs_form) {
ierr = TSSetRHSFunction(ts,NULL,RHSFunction,NULL);CHKERRQ(ierr);
ierr = TSSetRHSJacobian(ts,NULL,NULL,RHSJacobian,NULL);CHKERRQ(ierr);
} else {
Mat A; /* Jacobian matrix */
ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
ierr = MatSetSizes(A,n,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
ierr = MatSetType(A,MATDENSE);CHKERRQ(ierr);
ierr = MatSetFromOptions(A);CHKERRQ(ierr);
ierr = MatSetUp(A);CHKERRQ(ierr);
ierr = TSSetIFunction(ts,NULL,IFunction,NULL);CHKERRQ(ierr);
ierr = TSSetIJacobian(ts,A,A,IJacobian,NULL);CHKERRQ(ierr);
ierr = MatDestroy(&A);CHKERRQ(ierr);
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set initial conditions
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = VecCreate(PETSC_COMM_WORLD,&U);CHKERRQ(ierr);
ierr = VecSetSizes(U,n,PETSC_DETERMINE);CHKERRQ(ierr);
ierr = VecSetUp(U);CHKERRQ(ierr);
ierr = VecGetArray(U,&u);CHKERRQ(ierr);
u[0] = 0.0;
u[1] = 20.0;
ierr = VecRestoreArray(U,&u);CHKERRQ(ierr);
ierr = TSSetSolution(ts,U);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Set solver options
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSetSaveTrajectory(ts);CHKERRQ(ierr);
ierr = TSSetMaxTime(ts,30.0);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
ierr = TSSetTimeStep(ts,0.1);CHKERRQ(ierr);
/* The adapative time step controller could take very large timesteps resulting in
the same event occuring multiple times in the same interval. A maximum step size
limit is enforced here to avoid this issue. */
ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
ierr = TSAdaptSetStepLimits(adapt,0.0,0.5);CHKERRQ(ierr);
/* Set directions and terminate flags for the two events */
direction[0] = -1; direction[1] = -1;
terminate[0] = PETSC_FALSE; terminate[1] = PETSC_TRUE;
ierr = TSSetEventHandler(ts,2,direction,terminate,EventFunction,PostEventFunction,(void*)&app);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Run timestepping solver
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = TSSolve(ts,U);CHKERRQ(ierr);
if (hist) { /* replay following history */
TSTrajectory tj;
PetscReal tf,t0,dt;
app.nbounces = 0;
ierr = TSGetTime(ts,&tf);CHKERRQ(ierr);
ierr = TSSetMaxTime(ts,tf);CHKERRQ(ierr);
ierr = TSSetStepNumber(ts,0);CHKERRQ(ierr);
ierr = TSRestartStep(ts);CHKERRQ(ierr);
ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_MATCHSTEP);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr);
ierr = TSAdaptSetType(adapt,TSADAPTHISTORY);CHKERRQ(ierr);
ierr = TSGetTrajectory(ts,&tj);CHKERRQ(ierr);
ierr = TSAdaptHistorySetTrajectory(adapt,tj,PETSC_FALSE);CHKERRQ(ierr);
ierr = TSAdaptHistoryGetStep(adapt,0,&t0,&dt);CHKERRQ(ierr);
/* this example fails with single (or smaller) precision */
#if defined(PETSC_USE_REAL_SINGLE) || defined(PETSC_USE_REAL__FP16)
ierr = TSAdaptSetType(adapt,TSADAPTBASIC);CHKERRQ(ierr);
ierr = TSAdaptSetStepLimits(adapt,0.0,0.5);CHKERRQ(ierr);
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
#endif
ierr = TSSetTime(ts,t0);CHKERRQ(ierr);
ierr = TSSetTimeStep(ts,dt);CHKERRQ(ierr);
ierr = TSResetTrajectory(ts);CHKERRQ(ierr);
ierr = VecGetArray(U,&u);CHKERRQ(ierr);
u[0] = 0.0;
u[1] = 20.0;
ierr = VecRestoreArray(U,&u);CHKERRQ(ierr);
ierr = TSSolve(ts,U);CHKERRQ(ierr);
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Free work space. All PETSc objects should be destroyed when they are no longer needed.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
ierr = VecDestroy(&U);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
PetscErrorCode SNESSetFromOptions_FAS(SNES snes)
{
SNES_FAS *fas = (SNES_FAS *) snes->data;
PetscInt levels = 1;
PetscBool flg = PETSC_FALSE, upflg = PETSC_FALSE, downflg = PETSC_FALSE, monflg = PETSC_FALSE, galerkinflg = PETSC_FALSE;
PetscErrorCode ierr;
char monfilename[PETSC_MAX_PATH_LEN];
SNESFASType fastype;
const char *optionsprefix;
SNESLineSearch linesearch;
PetscInt m, n_up, n_down;
SNES next;
PetscBool isFine;
PetscFunctionBegin;
ierr = SNESFASCycleIsFine(snes, &isFine);CHKERRQ(ierr);
ierr = PetscOptionsHead("SNESFAS Options-----------------------------------");CHKERRQ(ierr);
/* number of levels -- only process most options on the finest level */
if (isFine) {
ierr = PetscOptionsInt("-snes_fas_levels", "Number of Levels", "SNESFASSetLevels", levels, &levels, &flg);CHKERRQ(ierr);
if (!flg && snes->dm) {
ierr = DMGetRefineLevel(snes->dm,&levels);CHKERRQ(ierr);
levels++;
fas->usedmfornumberoflevels = PETSC_TRUE;
}
ierr = SNESFASSetLevels(snes, levels, PETSC_NULL);CHKERRQ(ierr);
fastype = fas->fastype;
ierr = PetscOptionsEnum("-snes_fas_type","FAS correction type","SNESFASSetType",SNESFASTypes,(PetscEnum)fastype,(PetscEnum*)&fastype,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetType(snes, fastype);CHKERRQ(ierr);
}
ierr = SNESGetOptionsPrefix(snes, &optionsprefix);CHKERRQ(ierr);
ierr = PetscOptionsInt("-snes_fas_cycles","Number of cycles","SNESFASSetCycles",fas->n_cycles,&m,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetCycles(snes, m);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-snes_fas_galerkin", "Form coarse problems with Galerkin","SNESFASSetGalerkin",fas->galerkin,&galerkinflg,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetGalerkin(snes, galerkinflg);CHKERRQ(ierr);
}
ierr = PetscOptionsInt("-snes_fas_smoothup","Number of post-smoothing steps","SNESFASSetNumberSmoothUp",fas->max_up_it,&n_up,&upflg);CHKERRQ(ierr);
ierr = PetscOptionsInt("-snes_fas_smoothdown","Number of pre-smoothing steps","SNESFASSetNumberSmoothDown",fas->max_down_it,&n_down,&downflg);CHKERRQ(ierr);
ierr = PetscOptionsString("-snes_fas_monitor","Monitor FAS progress","SNESFASSetMonitor","stdout",monfilename,PETSC_MAX_PATH_LEN,&monflg);CHKERRQ(ierr);
if (monflg) ierr = SNESFASSetMonitor(snes, PETSC_TRUE);CHKERRQ(ierr);
}
ierr = PetscOptionsTail();CHKERRQ(ierr);
/* setup from the determined types if there is no pointwise procedure or smoother defined */
if (upflg) {
ierr = SNESFASSetNumberSmoothUp(snes,n_up);CHKERRQ(ierr);
}
if (downflg) {
ierr = SNESFASSetNumberSmoothDown(snes,n_down);CHKERRQ(ierr);
}
/* set up the default line search for coarse grid corrections */
if (fas->fastype == SNES_FAS_ADDITIVE) {
if (!snes->linesearch) {
ierr = SNESGetSNESLineSearch(snes, &linesearch);CHKERRQ(ierr);
ierr = SNESLineSearchSetType(linesearch, SNESLINESEARCHL2);CHKERRQ(ierr);
}
}
ierr = SNESFASCycleGetCorrection(snes, &next);CHKERRQ(ierr);
/* recursive option setting for the smoothers */
if (next) {ierr = SNESSetFromOptions(next);CHKERRQ(ierr);}
PetscFunctionReturn(0);
}
PetscErrorCode SetSpoolesOptions(Mat A, Spooles_options *options)
{
PetscErrorCode ierr;
int indx;
const char *ordertype[]={"BestOfNDandMS","MMD","MS","ND"};
PetscTruth flg;
PetscFunctionBegin;
/* set default input parameters */
#if defined(PETSC_USE_COMPLEX)
options->typeflag = SPOOLES_COMPLEX;
#else
options->typeflag = SPOOLES_REAL;
#endif
options->msglvl = 0;
options->msgFile = 0;
options->tau = 100.;
options->seed = 10101;
options->ordering = 1; /* MMD */
options->maxdomainsize = 500;
options->maxzeros = 1000;
options->maxsize = 96;
options->FrontMtxInfo = PETSC_FALSE;
if ( options->symflag == SPOOLES_SYMMETRIC ) { /* || SPOOLES_HERMITIAN */
options->patchAndGoFlag = 0; /* no patch */
options->storeids = 1;
options->storevalues = 1;
options->toosmall = 1.e-9;
options->fudge = 1.e-9;
}
/* get runtime input parameters */
ierr = PetscOptionsBegin(((PetscObject)A)->comm,((PetscObject)A)->prefix,"Spooles Options","Mat");CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_spooles_tau","tau (used for pivoting; \n\
all entries in L and U have magnitude no more than tau)","None",
options->tau,&options->tau,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_seed","random number seed, used for ordering","None",
options->seed,&options->seed,PETSC_NULL);CHKERRQ(ierr);
if (PetscLogPrintInfo) options->msglvl = 1;
ierr = PetscOptionsInt("-mat_spooles_msglvl","msglvl","None",
options->msglvl,&options->msglvl,0);CHKERRQ(ierr);
if (options->msglvl > 0) {
options->msgFile = fopen("spooles.msgFile", "a");
PetscPrintf(PETSC_COMM_SELF,"\n Spooles' output is written into the file 'spooles.msgFile' \n\n");
}
ierr = PetscOptionsEList("-mat_spooles_ordering","ordering type","None",ordertype,4,ordertype[1],&indx,&flg);CHKERRQ(ierr);
if (flg) options->ordering = indx;
ierr = PetscOptionsInt("-mat_spooles_maxdomainsize","maxdomainsize","None",\
options->maxdomainsize,&options->maxdomainsize,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_maxzeros ","maxzeros","None",\
options->maxzeros,&options->maxzeros,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_maxsize","maxsize","None",\
options->maxsize,&options->maxsize,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsTruth("-mat_spooles_FrontMtxInfo","FrontMtxInfo","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
if (flg) options->FrontMtxInfo = PETSC_TRUE;
if ( options->symflag == SPOOLES_SYMMETRIC ) {
ierr = PetscOptionsInt("-mat_spooles_symmetryflag","matrix type","None", \
options->symflag,&options->symflag,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_patchAndGoFlag","patchAndGoFlag","None", \
options->patchAndGoFlag,&options->patchAndGoFlag,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_spooles_fudge","fudge","None", \
options->fudge,&options->fudge,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_spooles_toosmall","toosmall","None", \
options->toosmall,&options->toosmall,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_storeids","storeids","None", \
options->storeids,&options->storeids,PETSC_NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_spooles_storevalues","storevalues","None", \
options->storevalues,&options->storevalues,PETSC_NULL);CHKERRQ(ierr);
}
PetscOptionsEnd();
PetscFunctionReturn(0);
}
/*
convert Petsc seqaij matrix to CSC: colptr[n], row[nz], val[nz]
input:
A - matrix in seqaij or mpisbaij (bs=1) format
valOnly - FALSE: spaces are allocated and values are set for the CSC
TRUE: Only fill values
output:
n - Size of the matrix
colptr - Index of first element of each column in row and val
row - Row of each element of the matrix
values - Value of each element of the matrix
*/
PetscErrorCode MatConvertToCSC(Mat A,PetscBool valOnly,PetscInt *n,PetscInt **colptr,PetscInt **row,PetscScalar **values)
{
Mat_SeqAIJ *aa = (Mat_SeqAIJ*)A->data;
PetscInt *rowptr = aa->i;
PetscInt *col = aa->j;
PetscScalar *rvalues = aa->a;
PetscInt m = A->rmap->N;
PetscInt nnz;
PetscInt i,j, k;
PetscInt base = 1;
PetscInt idx;
PetscErrorCode ierr;
PetscInt colidx;
PetscInt *colcount;
PetscBool isSBAIJ;
PetscBool isSeqSBAIJ;
PetscBool isMpiSBAIJ;
PetscBool isSym;
PetscBool flg;
PetscInt icntl;
PetscInt verb;
PetscInt check;
PetscFunctionBegin;
ierr = MatIsSymmetric(A,0.0,&isSym);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)A,MATSBAIJ,&isSBAIJ);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)A,MATMPISBAIJ,&isMpiSBAIJ);CHKERRQ(ierr);
*n = A->cmap->N;
/* PaStiX only needs triangular matrix if matrix is symmetric
*/
if (isSym && !(isSBAIJ || isSeqSBAIJ || isMpiSBAIJ)) {
nnz = (aa->nz - *n)/2 + *n;
}
else {
nnz = aa->nz;
}
if (!valOnly){
ierr = PetscMalloc(((*n)+1) *sizeof(PetscInt) ,colptr );CHKERRQ(ierr);
ierr = PetscMalloc( nnz *sizeof(PetscInt) ,row);CHKERRQ(ierr);
ierr = PetscMalloc( nnz *sizeof(PetscScalar),values);CHKERRQ(ierr);
if (isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) {
ierr = PetscMemcpy (*colptr, rowptr, ((*n)+1)*sizeof(PetscInt));CHKERRQ(ierr);
for (i = 0; i < *n+1; i++)
(*colptr)[i] += base;
ierr = PetscMemcpy (*row, col, (nnz)*sizeof(PetscInt));CHKERRQ(ierr);
for (i = 0; i < nnz; i++)
(*row)[i] += base;
ierr = PetscMemcpy (*values, rvalues, (nnz)*sizeof(PetscScalar));CHKERRQ(ierr);
} else {
ierr = PetscMalloc((*n)*sizeof(PetscInt) ,&colcount);CHKERRQ(ierr);
for (i = 0; i < m; i++) colcount[i] = 0;
/* Fill-in colptr */
for (i = 0; i < m; i++) {
for (j = rowptr[i]; j < rowptr[i+1]; j++) {
if (!isSym || col[j] <= i) colcount[col[j]]++;
}
}
(*colptr)[0] = base;
for (j = 0; j < *n; j++) {
(*colptr)[j+1] = (*colptr)[j] + colcount[j];
/* in next loop we fill starting from (*colptr)[colidx] - base */
colcount[j] = -base;
}
/* Fill-in rows and values */
for (i = 0; i < m; i++) {
for (j = rowptr[i]; j < rowptr[i+1]; j++) {
if (!isSym || col[j] <= i) {
colidx = col[j];
idx = (*colptr)[colidx] + colcount[colidx];
(*row)[idx] = i + base;
(*values)[idx] = rvalues[j];
colcount[colidx]++;
}
}
}
ierr = PetscFree(colcount);CHKERRQ(ierr);
}
} else {
/* Fill-in only values */
for (i = 0; i < m; i++) {
for (j = rowptr[i]; j < rowptr[i+1]; j++) {
colidx = col[j];
if ((isSBAIJ || isSeqSBAIJ || isMpiSBAIJ) ||!isSym || col[j] <= i)
{
/* look for the value to fill */
for (k = (*colptr)[colidx] - base; k < (*colptr)[colidx + 1] - base; k++) {
if (((*row)[k]-base) == i) {
(*values)[k] = rvalues[j];
break;
}
}
/* data structure of sparse matrix has changed */
if (k == (*colptr)[colidx + 1] - base) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"overflow on k %D",k);
}
}
}
}
icntl=-1;
check = 0;
ierr = PetscOptionsInt("-mat_pastix_check","Check the matrix 0 : no, 1 : yes)","None",check,&icntl,&flg);CHKERRQ(ierr);
if ((flg && icntl >= 0) || PetscLogPrintInfo) {
check = icntl;
}
if (check == 1) {
PetscScalar *tmpvalues;
PetscInt *tmprows,*tmpcolptr;
tmpvalues = (PetscScalar*)malloc(nnz*sizeof(PetscScalar)); if (!tmpvalues) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");
tmprows = (PetscInt*) malloc(nnz*sizeof(PetscInt)); if (!tmprows) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");
tmpcolptr = (PetscInt*) malloc((*n+1)*sizeof(PetscInt)); if (!tmpcolptr) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MEM,"Unable to allocate memory");
ierr = PetscMemcpy(tmpcolptr,*colptr,(*n+1)*sizeof(PetscInt));CHKERRQ(ierr);
ierr = PetscMemcpy(tmprows,*row,nnz*sizeof(PetscInt));CHKERRQ(ierr);
ierr = PetscMemcpy(tmpvalues,*values,nnz*sizeof(PetscScalar));CHKERRQ(ierr);
ierr = PetscFree(*row);CHKERRQ(ierr);
ierr = PetscFree(*values);CHKERRQ(ierr);
icntl=-1;
verb = API_VERBOSE_NOT;
ierr = PetscOptionsInt("-mat_pastix_verbose","iparm[IPARM_VERBOSE] : level of printing (0 to 2)","None",verb,&icntl,&flg);CHKERRQ(ierr);
if ((flg && icntl >= 0) || PetscLogPrintInfo) {
verb = icntl;
}
PASTIX_CHECKMATRIX(MPI_COMM_WORLD,verb,((isSym != 0) ? API_SYM_YES : API_SYM_NO),API_YES,*n,&tmpcolptr,&tmprows,(PastixScalar**)&tmpvalues,NULL,1);
ierr = PetscMemcpy(*colptr,tmpcolptr,(*n+1)*sizeof(PetscInt));CHKERRQ(ierr);
ierr = PetscMalloc(((*colptr)[*n]-1)*sizeof(PetscInt),row);CHKERRQ(ierr);
ierr = PetscMemcpy(*row,tmprows,((*colptr)[*n]-1)*sizeof(PetscInt));CHKERRQ(ierr);
ierr = PetscMalloc(((*colptr)[*n]-1)*sizeof(PetscScalar),values);CHKERRQ(ierr);
ierr = PetscMemcpy(*values,tmpvalues,((*colptr)[*n]-1)*sizeof(PetscScalar));CHKERRQ(ierr);
free(tmpvalues);
free(tmprows);
free(tmpcolptr);
}
PetscFunctionReturn(0);
}
/*@C
MatCreateLMVM - Creates a limited memory matrix for lmvm algorithms.
Collective on A
Input Parameters:
+ comm - MPI Communicator
. n - local size of vectors
- N - global size of vectors
Output Parameters:
. A - New LMVM matrix
Level: developer
@*/
extern PetscErrorCode MatCreateLMVM(MPI_Comm comm, PetscInt n, PetscInt N, Mat *A)
{
MatLMVMCtx *ctx;
PetscErrorCode ierr;
PetscInt nhistory;
PetscFunctionBegin;
/* create data structure and populate with default values */
ierr = PetscNew(&ctx);CHKERRQ(ierr);
ctx->lm=5;
ctx->eps=0.0;
ctx->limitType=MatLMVM_Limit_None;
ctx->scaleType=MatLMVM_Scale_Broyden;
ctx->rScaleType = MatLMVM_Rescale_Scalar;
ctx->s_alpha = 1.0;
ctx->r_alpha = 1.0;
ctx->r_beta = 0.5;
ctx->mu = 1.0;
ctx->nu = 100.0;
ctx->phi = 0.125;
ctx->scalar_history = 1;
ctx->rescale_history = 1;
ctx->delta_min = 1e-7;
ctx->delta_max = 100.0;
/* Begin configuration */
ierr = PetscOptionsInt("-tao_lmm_vectors", "vectors to use for approximation", "", ctx->lm, &ctx->lm, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_limit_mu", "mu limiting factor", "", ctx->mu, &ctx->mu, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_limit_nu", "nu limiting factor", "", ctx->nu, &ctx->nu, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_broyden_phi", "phi factor for Broyden scaling", "", ctx->phi, &ctx->phi, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_scalar_alpha", "alpha factor for scalar scaling", "",ctx->s_alpha, &ctx->s_alpha, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_rescale_alpha", "alpha factor for rescaling diagonal", "", ctx->r_alpha, &ctx->r_alpha, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_rescale_beta", "beta factor for rescaling diagonal", "", ctx->r_beta, &ctx->r_beta, 0);CHKERRQ(ierr);
ierr = PetscOptionsInt("-tao_lmm_scalar_history", "amount of history for scalar scaling", "", ctx->scalar_history, &ctx->scalar_history, 0);CHKERRQ(ierr);
ierr = PetscOptionsInt("-tao_lmm_rescale_history", "amount of history for rescaling diagonal", "", ctx->rescale_history, &ctx->rescale_history, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_eps", "rejection tolerance", "", ctx->eps, &ctx->eps, 0);CHKERRQ(ierr);
ierr = PetscOptionsEList("-tao_lmm_scale_type", "scale type", "", Scale_Table, MatLMVM_Scale_Types, Scale_Table[ctx->scaleType], &ctx->scaleType, 0);CHKERRQ(ierr);
ierr = PetscOptionsEList("-tao_lmm_rescale_type", "rescale type", "", Rescale_Table, MatLMVM_Rescale_Types, Rescale_Table[ctx->rScaleType], &ctx->rScaleType, 0);CHKERRQ(ierr);
ierr = PetscOptionsEList("-tao_lmm_limit_type", "limit type", "", Limit_Table, MatLMVM_Limit_Types, Limit_Table[ctx->limitType], &ctx->limitType, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_delta_min", "minimum delta value", "", ctx->delta_min, &ctx->delta_min, 0);CHKERRQ(ierr);
ierr = PetscOptionsReal("-tao_lmm_delta_max", "maximum delta value", "", ctx->delta_max, &ctx->delta_max, 0);CHKERRQ(ierr);
/* Complete configuration */
ctx->rescale_history = PetscMin(ctx->rescale_history, ctx->lm);
ierr = PetscMalloc1(ctx->lm+1,&ctx->rho);CHKERRQ(ierr);
ierr = PetscMalloc1(ctx->lm+1,&ctx->beta);CHKERRQ(ierr);
nhistory = PetscMax(ctx->scalar_history,1);
ierr = PetscMalloc1(nhistory,&ctx->yy_history);CHKERRQ(ierr);
ierr = PetscMalloc1(nhistory,&ctx->ys_history);CHKERRQ(ierr);
ierr = PetscMalloc1(nhistory,&ctx->ss_history);CHKERRQ(ierr);
nhistory = PetscMax(ctx->rescale_history,1);
ierr = PetscMalloc1(nhistory,&ctx->yy_rhistory);CHKERRQ(ierr);
ierr = PetscMalloc1(nhistory,&ctx->ys_rhistory);CHKERRQ(ierr);
ierr = PetscMalloc1(nhistory,&ctx->ss_rhistory);CHKERRQ(ierr);
/* Finish initializations */
ctx->lmnow = 0;
ctx->iter = 0;
ctx->nupdates = 0;
ctx->nrejects = 0;
ctx->delta = 1.0;
ctx->Gprev = 0;
ctx->Xprev = 0;
ctx->scale = 0;
ctx->useScale = PETSC_FALSE;
ctx->H0 = 0;
ctx->useDefaultH0=PETSC_TRUE;
ierr = MatCreateShell(comm, n, n, N, N, ctx, A);CHKERRQ(ierr);
ierr = MatShellSetOperation(*A,MATOP_DESTROY,(void(*)(void))MatDestroy_LMVM);CHKERRQ(ierr);
ierr = MatShellSetOperation(*A,MATOP_VIEW,(void(*)(void))MatView_LMVM);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/*@
EPSSetFromOptions - Sets EPS options from the options database.
This routine must be called before EPSSetUp() if the user is to be
allowed to set the solver type.
Collective on EPS
Input Parameters:
. eps - the eigensolver context
Notes:
To see all options, run your program with the -help option.
Level: beginner
@*/
PetscErrorCode EPSSetFromOptions(EPS eps)
{
PetscErrorCode ierr;
char type[256],monfilename[PETSC_MAX_PATH_LEN];
PetscBool flg,flg1,flg2,flg3;
PetscReal r,array[2]={0,0};
PetscScalar s;
PetscInt i,j,k;
PetscViewer monviewer;
SlepcConvMonitor ctx;
PetscFunctionBegin;
PetscValidHeaderSpecific(eps,EPS_CLASSID,1);
if (!EPSRegisterAllCalled) { ierr = EPSRegisterAll();CHKERRQ(ierr); }
ierr = PetscObjectOptionsBegin((PetscObject)eps);CHKERRQ(ierr);
ierr = PetscOptionsFList("-eps_type","Eigenvalue Problem Solver method","EPSSetType",EPSList,(char*)(((PetscObject)eps)->type_name?((PetscObject)eps)->type_name:EPSKRYLOVSCHUR),type,256,&flg);CHKERRQ(ierr);
if (flg) {
ierr = EPSSetType(eps,type);CHKERRQ(ierr);
}
/*
Set the type if it was never set.
*/
if (!((PetscObject)eps)->type_name) {
ierr = EPSSetType(eps,EPSKRYLOVSCHUR);CHKERRQ(ierr);
}
ierr = PetscOptionsBoolGroupBegin("-eps_hermitian","hermitian eigenvalue problem","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_HEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_gen_hermitian","generalized hermitian eigenvalue problem","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_GHEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_non_hermitian","non-hermitian eigenvalue problem","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_NHEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_gen_non_hermitian","generalized non-hermitian eigenvalue problem","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_GNHEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_pos_gen_non_hermitian","generalized non-hermitian eigenvalue problem with positive semi-definite B","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_PGNHEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroupEnd("-eps_gen_indefinite","generalized hermitian-indefinite eigenvalue problem","EPSSetProblemType",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetProblemType(eps,EPS_GHIEP);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroupBegin("-eps_ritz","Rayleigh-Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_RITZ);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_harmonic","harmonic Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_HARMONIC);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_harmonic_relative","relative harmonic Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_HARMONIC_RELATIVE);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_harmonic_right","right harmonic Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_HARMONIC_RIGHT);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_harmonic_largest","largest harmonic Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_HARMONIC_LARGEST);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_refined","refined Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_REFINED);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroupEnd("-eps_refined_harmonic","refined harmonic Ritz extraction","EPSSetExtraction",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetExtraction(eps,EPS_REFINED_HARMONIC);CHKERRQ(ierr); }
ierr = PetscOptionsEnum("-eps_balance","Balancing method","EPSSetBalance",EPSBalanceTypes,(PetscEnum)eps->balance,(PetscEnum*)&eps->balance,NULL);CHKERRQ(ierr);
j = eps->balance_its;
ierr = PetscOptionsInt("-eps_balance_its","Number of iterations in balancing","EPSSetBalance",eps->balance_its,&j,&flg1);CHKERRQ(ierr);
r = eps->balance_cutoff;
ierr = PetscOptionsReal("-eps_balance_cutoff","Cutoff value in balancing","EPSSetBalance",eps->balance_cutoff,&r,&flg2);CHKERRQ(ierr);
if (flg1 || flg2) {
ierr = EPSSetBalance(eps,eps->balance,j,r);CHKERRQ(ierr);
}
i = eps->max_it? eps->max_it: PETSC_DEFAULT;
ierr = PetscOptionsInt("-eps_max_it","Maximum number of iterations","EPSSetTolerances",eps->max_it,&i,&flg1);CHKERRQ(ierr);
r = eps->tol;
ierr = PetscOptionsReal("-eps_tol","Tolerance","EPSSetTolerances",eps->tol==PETSC_DEFAULT?SLEPC_DEFAULT_TOL:eps->tol,&r,&flg2);CHKERRQ(ierr);
if (flg1 || flg2) {
ierr = EPSSetTolerances(eps,r,i);CHKERRQ(ierr);
}
ierr = PetscOptionsBoolGroupBegin("-eps_conv_eig","Relative error convergence test","EPSSetConvergenceTest",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetConvergenceTest(eps,EPS_CONV_EIG);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_conv_norm","Convergence test relative to the eigenvalue and the matrix norms","EPSSetConvergenceTest",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetConvergenceTest(eps,EPS_CONV_NORM);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_conv_abs","Absolute error convergence test","EPSSetConvergenceTest",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetConvergenceTest(eps,EPS_CONV_ABS);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroupEnd("-eps_conv_user","User-defined convergence test","EPSSetConvergenceTest",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetConvergenceTest(eps,EPS_CONV_USER);CHKERRQ(ierr); }
i = eps->nev;
ierr = PetscOptionsInt("-eps_nev","Number of eigenvalues to compute","EPSSetDimensions",eps->nev,&i,&flg1);CHKERRQ(ierr);
j = eps->ncv? eps->ncv: PETSC_DEFAULT;
ierr = PetscOptionsInt("-eps_ncv","Number of basis vectors","EPSSetDimensions",eps->ncv,&j,&flg2);CHKERRQ(ierr);
k = eps->mpd? eps->mpd: PETSC_DEFAULT;
ierr = PetscOptionsInt("-eps_mpd","Maximum dimension of projected problem","EPSSetDimensions",eps->mpd,&k,&flg3);CHKERRQ(ierr);
if (flg1 || flg2 || flg3) {
ierr = EPSSetDimensions(eps,i,j,k);CHKERRQ(ierr);
}
/* -----------------------------------------------------------------------*/
/*
Cancels all monitors hardwired into code before call to EPSSetFromOptions()
*/
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-eps_monitor_cancel","Remove any hardwired monitor routines","EPSMonitorCancel",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
ierr = EPSMonitorCancel(eps);CHKERRQ(ierr);
}
/*
Prints approximate eigenvalues and error estimates at each iteration
*/
ierr = PetscOptionsString("-eps_monitor","Monitor first unconverged approximate eigenvalue and error estimate","EPSMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)eps),monfilename,&monviewer);CHKERRQ(ierr);
ierr = EPSMonitorSet(eps,EPSMonitorFirst,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
}
ierr = PetscOptionsString("-eps_monitor_conv","Monitor approximate eigenvalues and error estimates as they converge","EPSMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscNew(&ctx);CHKERRQ(ierr);
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)eps),monfilename,&ctx->viewer);CHKERRQ(ierr);
ierr = EPSMonitorSet(eps,EPSMonitorConverged,ctx,(PetscErrorCode (*)(void**))SlepcConvMonitorDestroy);CHKERRQ(ierr);
}
ierr = PetscOptionsString("-eps_monitor_all","Monitor approximate eigenvalues and error estimates","EPSMonitorSet","stdout",monfilename,PETSC_MAX_PATH_LEN,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscViewerASCIIOpen(PetscObjectComm((PetscObject)eps),monfilename,&monviewer);CHKERRQ(ierr);
ierr = EPSMonitorSet(eps,EPSMonitorAll,monviewer,(PetscErrorCode (*)(void**))PetscViewerDestroy);CHKERRQ(ierr);
ierr = EPSSetTrackAll(eps,PETSC_TRUE);CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-eps_monitor_lg","Monitor first unconverged approximate eigenvalue and error estimate graphically","EPSMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
ierr = EPSMonitorSet(eps,EPSMonitorLG,NULL,NULL);CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-eps_monitor_lg_all","Monitor error estimates graphically","EPSMonitorSet",flg,&flg,NULL);CHKERRQ(ierr);
if (flg) {
ierr = EPSMonitorSet(eps,EPSMonitorLGAll,NULL,NULL);CHKERRQ(ierr);
ierr = EPSSetTrackAll(eps,PETSC_TRUE);CHKERRQ(ierr);
}
/* -----------------------------------------------------------------------*/
ierr = PetscOptionsBoolGroupBegin("-eps_largest_magnitude","compute largest eigenvalues in magnitude","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_LARGEST_MAGNITUDE);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_smallest_magnitude","compute smallest eigenvalues in magnitude","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_SMALLEST_MAGNITUDE);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_largest_real","compute largest real parts","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_LARGEST_REAL);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_smallest_real","compute smallest real parts","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_SMALLEST_REAL);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_largest_imaginary","compute largest imaginary parts","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_LARGEST_IMAGINARY);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_smallest_imaginary","compute smallest imaginary parts","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_SMALLEST_IMAGINARY);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_target_magnitude","compute nearest eigenvalues to target","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_TARGET_MAGNITUDE);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_target_real","compute eigenvalues with real parts close to target","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_TARGET_REAL);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroup("-eps_target_imaginary","compute eigenvalues with imaginary parts close to target","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_TARGET_IMAGINARY);CHKERRQ(ierr); }
ierr = PetscOptionsBoolGroupEnd("-eps_all","compute all eigenvalues in an interval","EPSSetWhichEigenpairs",&flg);CHKERRQ(ierr);
if (flg) { ierr = EPSSetWhichEigenpairs(eps,EPS_ALL);CHKERRQ(ierr); }
ierr = PetscOptionsScalar("-eps_target","Value of the target","EPSSetTarget",eps->target,&s,&flg);CHKERRQ(ierr);
if (flg) {
if (eps->which!=EPS_TARGET_REAL && eps->which!=EPS_TARGET_IMAGINARY) {
ierr = EPSSetWhichEigenpairs(eps,EPS_TARGET_MAGNITUDE);CHKERRQ(ierr);
}
ierr = EPSSetTarget(eps,s);CHKERRQ(ierr);
}
k = 2;
ierr = PetscOptionsRealArray("-eps_interval","Computational interval (two real values separated with a comma without spaces)","EPSSetInterval",array,&k,&flg);CHKERRQ(ierr);
if (flg) {
if (k<2) SETERRQ(PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_SIZ,"Must pass two values in -eps_interval (comma-separated without spaces)");
ierr = EPSSetWhichEigenpairs(eps,EPS_ALL);CHKERRQ(ierr);
ierr = EPSSetInterval(eps,array[0],array[1]);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-eps_true_residual","Compute true residuals explicitly","EPSSetTrueResidual",eps->trueres,&eps->trueres,NULL);CHKERRQ(ierr);
ierr = PetscOptionsName("-eps_view","Print detailed information on solver used","EPSView",0);CHKERRQ(ierr);
ierr = PetscOptionsName("-eps_plot_eigs","Make a plot of the computed eigenvalues","EPSSolve",0);CHKERRQ(ierr);
if (eps->ops->setfromoptions) {
ierr = (*eps->ops->setfromoptions)(eps);CHKERRQ(ierr);
}
ierr = PetscObjectProcessOptionsHandlers((PetscObject)eps);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
if (!eps->V) { ierr = EPSGetBV(eps,&eps->V);CHKERRQ(ierr); }
ierr = BVSetFromOptions(eps->V);CHKERRQ(ierr);
if (!eps->rg) { ierr = EPSGetRG(eps,&eps->rg);CHKERRQ(ierr); }
ierr = RGSetFromOptions(eps->rg);CHKERRQ(ierr);
if (!eps->ds) { ierr = EPSGetDS(eps,&eps->ds);CHKERRQ(ierr); }
ierr = DSSetFromOptions(eps->ds);CHKERRQ(ierr);
ierr = STSetFromOptions(eps->st);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(eps->rand);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode MatFactorNumeric_PaStiX(Mat F,Mat A,const MatFactorInfo *info)
{
Mat_Pastix *lu =(Mat_Pastix*)(F)->spptr;
Mat *tseq;
PetscErrorCode ierr = 0;
PetscInt icntl;
PetscInt M=A->rmap->N;
PetscBool valOnly,flg, isSym;
Mat F_diag;
IS is_iden;
Vec b;
IS isrow;
PetscBool isSeqAIJ,isSeqSBAIJ,isMPIAIJ;
PetscFunctionBegin;
ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr);
if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
(F)->ops->solve = MatSolve_PaStiX;
/* Initialize a PASTIX instance */
ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->pastix_comm));CHKERRQ(ierr);
ierr = MPI_Comm_rank(lu->pastix_comm, &lu->commRank);CHKERRQ(ierr);
ierr = MPI_Comm_size(lu->pastix_comm, &lu->commSize);CHKERRQ(ierr);
/* Set pastix options */
lu->iparm[IPARM_MODIFY_PARAMETER] = API_NO;
lu->iparm[IPARM_START_TASK] = API_TASK_INIT;
lu->iparm[IPARM_END_TASK] = API_TASK_INIT;
lu->rhsnbr = 1;
/* Call to set default pastix options */
PASTIX_CALL(&(lu->pastix_data),
lu->pastix_comm,
lu->n,
lu->colptr,
lu->row,
(PastixScalar*)lu->val,
lu->perm,
lu->invp,
(PastixScalar*)lu->rhs,
lu->rhsnbr,
lu->iparm,
lu->dparm);
ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"PaStiX Options","Mat");CHKERRQ(ierr);
icntl = -1;
lu->iparm[IPARM_VERBOSE] = API_VERBOSE_NOT;
ierr = PetscOptionsInt("-mat_pastix_verbose","iparm[IPARM_VERBOSE] : level of printing (0 to 2)","None",lu->iparm[IPARM_VERBOSE],&icntl,&flg);CHKERRQ(ierr);
if ((flg && icntl >= 0) || PetscLogPrintInfo) {
lu->iparm[IPARM_VERBOSE] = icntl;
}
icntl=-1;
ierr = PetscOptionsInt("-mat_pastix_threadnbr","iparm[IPARM_THREAD_NBR] : Number of thread by MPI node","None",lu->iparm[IPARM_THREAD_NBR],&icntl,&flg);CHKERRQ(ierr);
if ((flg && icntl > 0)) {
lu->iparm[IPARM_THREAD_NBR] = icntl;
}
PetscOptionsEnd();
valOnly = PETSC_FALSE;
} else {
if (isSeqAIJ || isMPIAIJ) {
ierr = PetscFree(lu->colptr);CHKERRQ(ierr);
ierr = PetscFree(lu->row);CHKERRQ(ierr);
ierr = PetscFree(lu->val);CHKERRQ(ierr);
valOnly = PETSC_FALSE;
} else valOnly = PETSC_TRUE;
}
lu->iparm[IPARM_MATRIX_VERIFICATION] = API_YES;
/* convert mpi A to seq mat A */
ierr = ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);CHKERRQ(ierr);
ierr = MatGetSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);CHKERRQ(ierr);
ierr = ISDestroy(&isrow);CHKERRQ(ierr);
ierr = MatConvertToCSC(*tseq,valOnly, &lu->n, &lu->colptr, &lu->row, &lu->val);CHKERRQ(ierr);
ierr = MatIsSymmetric(*tseq,0.0,&isSym);CHKERRQ(ierr);
ierr = MatDestroyMatrices(1,&tseq);CHKERRQ(ierr);
if (!lu->perm) {
ierr = PetscMalloc1((lu->n),&(lu->perm));CHKERRQ(ierr);
ierr = PetscMalloc1((lu->n),&(lu->invp));CHKERRQ(ierr);
}
if (isSym) {
/* On symmetric matrix, LLT */
lu->iparm[IPARM_SYM] = API_SYM_YES;
lu->iparm[IPARM_FACTORIZATION] = API_FACT_LDLT;
} else {
/* On unsymmetric matrix, LU */
lu->iparm[IPARM_SYM] = API_SYM_NO;
lu->iparm[IPARM_FACTORIZATION] = API_FACT_LU;
}
/*----------------*/
if (lu->matstruc == DIFFERENT_NONZERO_PATTERN) {
if (!(isSeqAIJ || isSeqSBAIJ)) {
/* PaStiX only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */
ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&lu->b_seq);CHKERRQ(ierr);
ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr);
ierr = MatCreateVecs(A,NULL,&b);CHKERRQ(ierr);
ierr = VecScatterCreate(b,is_iden,lu->b_seq,is_iden,&lu->scat_rhs);CHKERRQ(ierr);
ierr = VecScatterCreate(lu->b_seq,is_iden,b,is_iden,&lu->scat_sol);CHKERRQ(ierr);
ierr = ISDestroy(&is_iden);CHKERRQ(ierr);
ierr = VecDestroy(&b);CHKERRQ(ierr);
}
lu->iparm[IPARM_START_TASK] = API_TASK_ORDERING;
lu->iparm[IPARM_END_TASK] = API_TASK_NUMFACT;
PASTIX_CALL(&(lu->pastix_data),
lu->pastix_comm,
lu->n,
lu->colptr,
lu->row,
(PastixScalar*)lu->val,
lu->perm,
lu->invp,
(PastixScalar*)lu->rhs,
lu->rhsnbr,
lu->iparm,
lu->dparm);
if (lu->iparm[IPARM_ERROR_NUMBER] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by PaStiX in analysis phase: iparm(IPARM_ERROR_NUMBER)=%d\n",lu->iparm[IPARM_ERROR_NUMBER]);
} else {
lu->iparm[IPARM_START_TASK] = API_TASK_NUMFACT;
lu->iparm[IPARM_END_TASK] = API_TASK_NUMFACT;
PASTIX_CALL(&(lu->pastix_data),
lu->pastix_comm,
lu->n,
lu->colptr,
lu->row,
(PastixScalar*)lu->val,
lu->perm,
lu->invp,
(PastixScalar*)lu->rhs,
lu->rhsnbr,
lu->iparm,
lu->dparm);
if (lu->iparm[IPARM_ERROR_NUMBER] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by PaStiX in analysis phase: iparm(IPARM_ERROR_NUMBER)=%d\n",lu->iparm[IPARM_ERROR_NUMBER]);
}
if (lu->commSize > 1) {
if ((F)->factortype == MAT_FACTOR_LU) {
F_diag = ((Mat_MPIAIJ*)(F)->data)->A;
} else {
F_diag = ((Mat_MPISBAIJ*)(F)->data)->A;
}
F_diag->assembled = PETSC_TRUE;
}
(F)->assembled = PETSC_TRUE;
lu->matstruc = SAME_NONZERO_PATTERN;
lu->CleanUpPastix = PETSC_TRUE;
PetscFunctionReturn(0);
}
int main(int argc, char** argv)
{
PC pc;
PetscErrorCode ierr;
PetscInt m, nn, M, j, k, ne = 4;
PetscReal* coords;
Vec x, rhs;
Mat A;
KSP ksp;
PetscMPIInt npe, rank;
PetscInitialize(&argc, &argv, NULL, NULL);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD, &rank);
CHKERRQ(ierr);
ierr = MPI_Comm_size(PETSC_COMM_WORLD, &npe);
CHKERRQ(ierr);
ierr = PetscOptionsBegin(PETSC_COMM_WORLD, NULL, "Linear elasticity in 3D", "");
{
char nestring[256];
ierr = PetscSNPrintf(nestring, sizeof nestring, "number of elements in each direction, ne+1 must be a multiple of %D (sizes^{1/3})",
(PetscInt)(PetscPowReal((PetscReal)npe, 1.0 / 3.0) + 0.5));
ierr = PetscOptionsInt("-ne", nestring, "", ne, &ne, NULL);
}
ierr = PetscOptionsEnd();
CHKERRQ(ierr);
const HpddmOption* const opt = HpddmOptionGet();
{
HpddmOptionParse(opt, argc, argv, rank == 0);
if (rank) HpddmOptionRemove(opt, "verbosity");
}
nn = ne + 1;
M = 3 * nn * nn * nn;
if (npe == 2) {
if (rank == 1)
m = 0;
else
m = nn * nn * nn;
npe = 1;
}
else {
m = nn * nn * nn / npe;
if (rank == npe - 1) m = nn * nn * nn - (npe - 1) * m;
}
m *= 3;
ierr = KSPCreate(PETSC_COMM_WORLD, &ksp);
CHKERRQ(ierr);
ierr = KSPSetFromOptions(ksp);
CHKERRQ(ierr);
int i;
{
PetscInt Istart, Iend, jj, ic;
const PetscInt NP = (PetscInt)(PetscPowReal((PetscReal)npe, 1.0 / 3.0) + 0.5);
const PetscInt ipx = rank % NP, ipy = (rank % (NP * NP)) / NP, ipz = rank / (NP * NP);
const PetscInt Ni0 = ipx * (nn / NP), Nj0 = ipy * (nn / NP), Nk0 = ipz * (nn / NP);
const PetscInt Ni1 = Ni0 + (m > 0 ? (nn / NP) : 0), Nj1 = Nj0 + (nn / NP), Nk1 = Nk0 + (nn / NP);
PetscInt *d_nnz, *o_nnz, osz[4] = {0, 9, 15, 19}, nbc;
if (npe != NP * NP * NP) SETERRQ1(PETSC_COMM_WORLD, PETSC_ERR_ARG_WRONG, "npe=%d: npe^{1/3} must be integer", npe);
if (nn != NP * (nn / NP)) SETERRQ1(PETSC_COMM_WORLD, PETSC_ERR_ARG_WRONG, "-ne %d: (ne+1)%(npe^{1/3}) must equal zero", ne);
ierr = PetscMalloc1(m + 1, &d_nnz);
CHKERRQ(ierr);
ierr = PetscMalloc1(m + 1, &o_nnz);
CHKERRQ(ierr);
for (i = Ni0, ic = 0; i < Ni1; i++) {
for (j = Nj0; j < Nj1; j++) {
for (k = Nk0; k < Nk1; k++) {
nbc = 0;
if (i == Ni0 || i == Ni1 - 1) nbc++;
if (j == Nj0 || j == Nj1 - 1) nbc++;
if (k == Nk0 || k == Nk1 - 1) nbc++;
for (jj = 0; jj < 3; jj++, ic++) {
d_nnz[ic] = 3 * (27 - osz[nbc]);
o_nnz[ic] = 3 * osz[nbc];
}
}
}
}
if (ic != m) SETERRQ2(PETSC_COMM_SELF, PETSC_ERR_PLIB, "ic %D does not equal m %D", ic, m);
ierr = MatCreate(PETSC_COMM_WORLD, &A);
CHKERRQ(ierr);
ierr = MatSetSizes(A, m, m, M, M);
CHKERRQ(ierr);
ierr = MatSetBlockSize(A, 3);
CHKERRQ(ierr);
ierr = MatSetType(A, MATAIJ);
CHKERRQ(ierr);
ierr = MatSeqAIJSetPreallocation(A, 0, d_nnz);
CHKERRQ(ierr);
ierr = MatMPIAIJSetPreallocation(A, 0, d_nnz, 0, o_nnz);
CHKERRQ(ierr);
ierr = PetscFree(d_nnz);
CHKERRQ(ierr);
ierr = PetscFree(o_nnz);
CHKERRQ(ierr);
ierr = MatGetOwnershipRange(A, &Istart, &Iend);
CHKERRQ(ierr);
if (m != Iend - Istart) SETERRQ3(PETSC_COMM_SELF, PETSC_ERR_PLIB, "m %D does not equal Iend %D - Istart %D", m, Iend, Istart);
ierr = VecCreate(PETSC_COMM_WORLD, &x);
CHKERRQ(ierr);
ierr = VecSetSizes(x, m, M);
CHKERRQ(ierr);
ierr = VecSetBlockSize(x, 3);
CHKERRQ(ierr);
ierr = VecSetFromOptions(x);
CHKERRQ(ierr);
ierr = VecDuplicate(x, &rhs);
CHKERRQ(ierr);
ierr = PetscMalloc1(m + 1, &coords);
CHKERRQ(ierr);
coords[m] = -99.0;
PetscReal h = 1.0 / ne;
for (i = Ni0, ic = 0; i < Ni1; i++) {
for (j = Nj0; j < Nj1; j++) {
for (k = Nk0; k < Nk1; k++, ic++) {
coords[3 * ic] = h * (PetscReal)i;
coords[3 * ic + 1] = h * (PetscReal)j;
coords[3 * ic + 2] = h * (PetscReal)k;
}
}
}
}
PetscReal s_r[SIZE_ARRAY_R] = {30, 0.1, 20, 10};
PetscReal x_r[SIZE_ARRAY_R] = {0.5, 0.4, 0.4, 0.4};
PetscReal y_r[SIZE_ARRAY_R] = {0.5, 0.5, 0.4, 0.4};
PetscReal z_r[SIZE_ARRAY_R] = {0.5, 0.45, 0.4, 0.35};
PetscReal r[SIZE_ARRAY_R] = {0.5, 0.5, 0.4, 0.4};
AssembleSystem(A, rhs, s_r[0], x_r[0], y_r[0], z_r[0], r[0], ne, npe, rank, nn, m);
ierr = KSPSetOperators(ksp, A, A);
CHKERRQ(ierr);
MatNullSpace matnull;
Vec vec_coords;
PetscScalar* c;
ierr = VecCreate(MPI_COMM_WORLD, &vec_coords);
CHKERRQ(ierr);
ierr = VecSetBlockSize(vec_coords, 3);
CHKERRQ(ierr);
ierr = VecSetSizes(vec_coords, m, PETSC_DECIDE);
CHKERRQ(ierr);
ierr = VecSetUp(vec_coords);
CHKERRQ(ierr);
ierr = VecGetArray(vec_coords, &c);
CHKERRQ(ierr);
for (i = 0; i < m; i++) c[i] = coords[i];
ierr = VecRestoreArray(vec_coords, &c);
CHKERRQ(ierr);
ierr = MatNullSpaceCreateRigidBody(vec_coords, &matnull);
CHKERRQ(ierr);
ierr = MatSetNearNullSpace(A, matnull);
CHKERRQ(ierr);
ierr = MatNullSpaceDestroy(&matnull);
CHKERRQ(ierr);
ierr = VecDestroy(&vec_coords);
CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE);
CHKERRQ(ierr);
MPI_Barrier(PETSC_COMM_WORLD);
double time = MPI_Wtime();
ierr = KSPSetUp(ksp);
CHKERRQ(ierr);
MPI_Barrier(PETSC_COMM_WORLD);
time = MPI_Wtime() - time;
ierr = PetscPrintf(PETSC_COMM_WORLD, "--- PC setup = %f\n", time);
CHKERRQ(ierr);
float t_time[SIZE_ARRAY_R];
int t_its[SIZE_ARRAY_R];
{
{
ierr = KSPSolve(ksp, rhs, x);
CHKERRQ(ierr);
ierr = KSPReset(ksp);
CHKERRQ(ierr);
ierr = KSPSetOperators(ksp, A, A);
CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE);
CHKERRQ(ierr);
ierr = KSPSetUp(ksp);
CHKERRQ(ierr);
}
for (i = 0; i < SIZE_ARRAY_R; ++i) {
ierr = VecZeroEntries(x);
CHKERRQ(ierr);
MPI_Barrier(PETSC_COMM_WORLD);
time = MPI_Wtime();
ierr = KSPSolve(ksp, rhs, x);
CHKERRQ(ierr);
MPI_Barrier(PETSC_COMM_WORLD);
t_time[i] = MPI_Wtime() - time;
PetscInt its;
ierr = KSPGetIterationNumber(ksp, &its);
CHKERRQ(ierr);
t_its[i] = its;
ierr = ComputeError(A, rhs, x);
CHKERRQ(ierr);
if (i == (SIZE_ARRAY_R - 1))
AssembleSystem(A, rhs, s_r[0], x_r[0], y_r[0], z_r[0], r[0], ne, npe, rank, nn, m);
else
AssembleSystem(A, rhs, s_r[i + 1], x_r[i + 1], y_r[i + 1], z_r[i + 1], r[i + 1], ne, npe, rank, nn, m);
ierr = KSPSetOperators(ksp, A, A);
CHKERRQ(ierr);
ierr = KSPSetUp(ksp);
CHKERRQ(ierr);
}
for (i = 0; i < SIZE_ARRAY_R; ++i) {
ierr = PetscPrintf(PETSC_COMM_WORLD, "%d\t%d\t%f\n", i + 1, t_its[i], t_time[i]);
CHKERRQ(ierr);
if (i > 0) {
t_its[0] += t_its[i];
t_time[0] += t_time[i];
}
}
if (SIZE_ARRAY_R > 1) {
ierr = PetscPrintf(PETSC_COMM_WORLD, "------------------------\n\t%d\t%f\n", t_its[0], t_time[0]);
CHKERRQ(ierr);
}
}
{
ierr = KSPGetPC(ksp, &pc);
CHKERRQ(ierr);
HpddmCustomOperator H;
H._A = A;
H._M = pc;
H._mv = mv;
H._precond = precond;
H._b = rhs;
H._x = x;
int n;
MatGetLocalSize(A, &n, NULL);
{
ierr = VecZeroEntries(x);
K* pt_rhs;
K* pt_x;
VecGetArray(rhs, &pt_rhs);
VecGetArray(x, &pt_x);
int previous = HpddmOptionVal(opt, "verbosity");
if (previous > 0) HpddmOptionRemove(opt, "verbosity");
HpddmCustomOperatorSolve(&H, n, H._mv, H._precond, pt_rhs, pt_x, 1, &PETSC_COMM_WORLD);
if (previous > 0) {
char buffer[20];
snprintf(buffer, 20, "%d", previous);
char* concat = malloc(strlen("-hpddm_verbosity ") + strlen(buffer) + 1);
strcpy(concat, "-hpddm_verbosity ");
strcat(concat, buffer);
HpddmOptionParseString(opt, concat);
free(concat);
}
VecRestoreArray(x, &pt_x);
VecRestoreArray(rhs, &pt_rhs);
previous = HpddmOptionVal(opt, "krylov_method");
if(previous == 4 || previous == 5) HpddmDestroyRecycling();
ierr = KSPReset(ksp);
CHKERRQ(ierr);
ierr = KSPSetOperators(ksp, A, A);
CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(ksp, PETSC_TRUE);
CHKERRQ(ierr);
ierr = KSPSetUp(ksp);
CHKERRQ(ierr);
}
for (i = 0; i < SIZE_ARRAY_R; ++i) {
ierr = VecZeroEntries(x);
CHKERRQ(ierr);
K* pt_rhs;
K* pt_x;
VecGetArray(rhs, &pt_rhs);
VecGetArray(x, &pt_x);
MPI_Barrier(PETSC_COMM_WORLD);
time = MPI_Wtime();
t_its[i] = HpddmCustomOperatorSolve(&H, n, H._mv, H._precond, pt_rhs, pt_x, 1, &PETSC_COMM_WORLD);
MPI_Barrier(PETSC_COMM_WORLD);
t_time[i] = MPI_Wtime() - time;
VecRestoreArray(x, &pt_x);
VecRestoreArray(rhs, &pt_rhs);
ierr = ComputeError(A, rhs, x);
CHKERRQ(ierr);
if (i != (SIZE_ARRAY_R - 1)) {
AssembleSystem(A, rhs, s_r[i + 1], x_r[i + 1], y_r[i + 1], z_r[i + 1], r[i + 1], ne, npe, rank, nn, m);
ierr = KSPSetOperators(ksp, A, A);
CHKERRQ(ierr);
ierr = KSPSetUp(ksp);
CHKERRQ(ierr);
}
}
for (i = 0; i < SIZE_ARRAY_R; ++i) {
ierr = PetscPrintf(PETSC_COMM_WORLD, "%d\t%d\t%f\n", i + 1, t_its[i], t_time[i]);
CHKERRQ(ierr);
if (i > 0) {
t_its[0] += t_its[i];
t_time[0] += t_time[i];
}
}
if (SIZE_ARRAY_R > 1) {
ierr = PetscPrintf(PETSC_COMM_WORLD, "------------------------\n\t%d\t%f\n", t_its[0], t_time[0]);
CHKERRQ(ierr);
}
}
ierr = KSPDestroy(&ksp);
CHKERRQ(ierr);
ierr = VecDestroy(&x);
CHKERRQ(ierr);
ierr = VecDestroy(&rhs);
CHKERRQ(ierr);
ierr = MatDestroy(&A);
CHKERRQ(ierr);
ierr = PetscFree(coords);
CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
PetscErrorCode DMSetFromOptions_DA(PetscOptionItems *PetscOptionsObject,DM da)
{
PetscErrorCode ierr;
DM_DA *dd = (DM_DA*)da->data;
PetscInt refine = 0,dim = da->dim,maxnlevels = 100,refx[100],refy[100],refz[100],n,i;
PetscBool flg;
PetscFunctionBegin;
PetscValidHeaderSpecific(da,DM_CLASSID,1);
if (dd->M < 0) SETERRQ(PetscObjectComm((PetscObject)da),PETSC_ERR_ARG_OUTOFRANGE,"Dimension must be non-negative, call DMSetFromOptions() if you want to change the value at runtime");
if (dd->N < 0) SETERRQ(PetscObjectComm((PetscObject)da),PETSC_ERR_ARG_OUTOFRANGE,"Dimension must be non-negative, call DMSetFromOptions() if you want to change the value at runtime");
if (dd->P < 0) SETERRQ(PetscObjectComm((PetscObject)da),PETSC_ERR_ARG_OUTOFRANGE,"Dimension must be non-negative, call DMSetFromOptions() if you want to change the value at runtime");
ierr = PetscOptionsHead(PetscOptionsObject,"DMDA Options");CHKERRQ(ierr);
ierr = PetscOptionsInt("-da_grid_x","Number of grid points in x direction","DMDASetSizes",dd->M,&dd->M,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-da_grid_y","Number of grid points in y direction","DMDASetSizes",dd->N,&dd->N,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-da_grid_z","Number of grid points in z direction","DMDASetSizes",dd->P,&dd->P,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-da_overlap","Decomposition overlap in all directions","DMDASetOverlap",dd->xol,&dd->xol,&flg);CHKERRQ(ierr);
if (flg) {ierr = DMDASetOverlap(da,dd->xol,dd->xol,dd->xol);CHKERRQ(ierr);}
ierr = PetscOptionsInt("-da_overlap_x","Decomposition overlap in x direction","DMDASetOverlap",dd->xol,&dd->xol,NULL);CHKERRQ(ierr);
if (dim > 1) {ierr = PetscOptionsInt("-da_overlap_y","Decomposition overlap in y direction","DMDASetOverlap",dd->yol,&dd->yol,NULL);CHKERRQ(ierr);}
if (dim > 2) {ierr = PetscOptionsInt("-da_overlap_z","Decomposition overlap in z direction","DMDASetOverlap",dd->zol,&dd->zol,NULL);CHKERRQ(ierr);}
ierr = PetscOptionsInt("-da_local_subdomains","","DMDASetNumLocalSubdomains",dd->Nsub,&dd->Nsub,&flg);CHKERRQ(ierr);
if (flg) {ierr = DMDASetNumLocalSubDomains(da,dd->Nsub);CHKERRQ(ierr);}
/* Handle DMDA parallel distibution */
ierr = PetscOptionsInt("-da_processors_x","Number of processors in x direction","DMDASetNumProcs",dd->m,&dd->m,NULL);CHKERRQ(ierr);
if (dim > 1) {ierr = PetscOptionsInt("-da_processors_y","Number of processors in y direction","DMDASetNumProcs",dd->n,&dd->n,NULL);CHKERRQ(ierr);}
if (dim > 2) {ierr = PetscOptionsInt("-da_processors_z","Number of processors in z direction","DMDASetNumProcs",dd->p,&dd->p,NULL);CHKERRQ(ierr);}
/* Handle DMDA refinement */
ierr = PetscOptionsInt("-da_refine_x","Refinement ratio in x direction","DMDASetRefinementFactor",dd->refine_x,&dd->refine_x,NULL);CHKERRQ(ierr);
if (dim > 1) {ierr = PetscOptionsInt("-da_refine_y","Refinement ratio in y direction","DMDASetRefinementFactor",dd->refine_y,&dd->refine_y,NULL);CHKERRQ(ierr);}
if (dim > 2) {ierr = PetscOptionsInt("-da_refine_z","Refinement ratio in z direction","DMDASetRefinementFactor",dd->refine_z,&dd->refine_z,NULL);CHKERRQ(ierr);}
dd->coarsen_x = dd->refine_x; dd->coarsen_y = dd->refine_y; dd->coarsen_z = dd->refine_z;
/* Get refinement factors, defaults taken from the coarse DMDA */
ierr = DMDAGetRefinementFactor(da,&refx[0],&refy[0],&refz[0]);CHKERRQ(ierr);
for (i=1; i<maxnlevels; i++) {
refx[i] = refx[0];
refy[i] = refy[0];
refz[i] = refz[0];
}
n = maxnlevels;
ierr = PetscOptionsIntArray("-da_refine_hierarchy_x","Refinement factor for each level","None",refx,&n,&flg);CHKERRQ(ierr);
if (flg) {
dd->refine_x = refx[0];
dd->refine_x_hier_n = n;
ierr = PetscMalloc1(n,&dd->refine_x_hier);CHKERRQ(ierr);
ierr = PetscMemcpy(dd->refine_x_hier,refx,n*sizeof(PetscInt));CHKERRQ(ierr);
}
if (dim > 1) {
n = maxnlevels;
ierr = PetscOptionsIntArray("-da_refine_hierarchy_y","Refinement factor for each level","None",refy,&n,&flg);CHKERRQ(ierr);
if (flg) {
dd->refine_y = refy[0];
dd->refine_y_hier_n = n;
ierr = PetscMalloc1(n,&dd->refine_y_hier);CHKERRQ(ierr);
ierr = PetscMemcpy(dd->refine_y_hier,refy,n*sizeof(PetscInt));CHKERRQ(ierr);
}
}
if (dim > 2) {
n = maxnlevels;
ierr = PetscOptionsIntArray("-da_refine_hierarchy_z","Refinement factor for each level","None",refz,&n,&flg);CHKERRQ(ierr);
if (flg) {
dd->refine_z = refz[0];
dd->refine_z_hier_n = n;
ierr = PetscMalloc1(n,&dd->refine_z_hier);CHKERRQ(ierr);
ierr = PetscMemcpy(dd->refine_z_hier,refz,n*sizeof(PetscInt));CHKERRQ(ierr);
}
}
ierr = PetscOptionsInt("-da_refine","Uniformly refine DA one or more times","None",refine,&refine,NULL);CHKERRQ(ierr);
ierr = PetscOptionsTail();CHKERRQ(ierr);
while (refine--) {
if (dd->bx == DM_BOUNDARY_PERIODIC || dd->interptype == DMDA_Q0) {
dd->M = dd->refine_x*dd->M;
} else {
dd->M = 1 + dd->refine_x*(dd->M - 1);
}
if (dd->by == DM_BOUNDARY_PERIODIC || dd->interptype == DMDA_Q0) {
dd->N = dd->refine_y*dd->N;
} else {
dd->N = 1 + dd->refine_y*(dd->N - 1);
}
if (dd->bz == DM_BOUNDARY_PERIODIC || dd->interptype == DMDA_Q0) {
dd->P = dd->refine_z*dd->P;
} else {
dd->P = 1 + dd->refine_z*(dd->P - 1);
}
da->levelup++;
if (da->levelup - da->leveldown >= 0) {
dd->refine_x = refx[da->levelup - da->leveldown];
dd->refine_y = refy[da->levelup - da->leveldown];
dd->refine_z = refz[da->levelup - da->leveldown];
}
if (da->levelup - da->leveldown >= 1) {
dd->coarsen_x = refx[da->levelup - da->leveldown - 1];
dd->coarsen_y = refy[da->levelup - da->leveldown - 1];
dd->coarsen_z = refz[da->levelup - da->leveldown - 1];
}
}
PetscFunctionReturn(0);
}
int main(int argc,char **argv)
{
PetscErrorCode ierr;
PetscViewer viewer;
DM da;
Vec global,local,global2;
PetscMPIInt rank;
PetscBool flg;
PetscInt ndof;
/*
Every PETSc routine should begin with the PetscInitialize() routine.
argc, argv - These command line arguments are taken to extract the options
supplied to PETSc and options supplied to MPI.
help - When PETSc executable is invoked with the option -help,
it prints the various options that can be applied at
runtime. The user can use the "help" variable place
additional help messages in this printout.
*/
ierr = PetscInitialize(&argc,&argv,(char*)0,help);CHKERRQ(ierr);
/* Get number of DOF's from command line */
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,NULL,"DMDA VecView/VecLoad example","");CHKERRQ(ierr);
{
ndof = 1;
PetscOptionsInt("-ndof","Number of DOF's in DMDA","",ndof,&ndof,NULL);
}
ierr = PetscOptionsEnd();CHKERRQ(ierr);
/* Create a DMDA and an associated vector */
ierr = DMDACreate2d(PETSC_COMM_WORLD, DM_BOUNDARY_NONE, DM_BOUNDARY_NONE,DMDA_STENCIL_BOX,100,90,PETSC_DECIDE,PETSC_DECIDE,ndof,1,NULL,NULL,&da);CHKERRQ(ierr);
ierr = DMCreateGlobalVector(da,&global);CHKERRQ(ierr);
ierr = DMCreateLocalVector(da,&local);CHKERRQ(ierr);
ierr = VecSet(global,-1.0);CHKERRQ(ierr);
ierr = DMGlobalToLocalBegin(da,global,INSERT_VALUES,local);CHKERRQ(ierr);
ierr = DMGlobalToLocalEnd(da,global,INSERT_VALUES,local);CHKERRQ(ierr);
ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr);
ierr = VecScale(local,rank+1);CHKERRQ(ierr);
ierr = DMLocalToGlobalBegin(da,local,ADD_VALUES,global);CHKERRQ(ierr);
ierr = DMLocalToGlobalEnd(da,local,ADD_VALUES,global);CHKERRQ(ierr);
/* Create the HDF5 viewer for writing */
ierr = PetscViewerHDF5Open(PETSC_COMM_WORLD,"hdf5output.h5",FILE_MODE_WRITE,&viewer);CHKERRQ(ierr);
ierr = PetscViewerSetFromOptions(viewer);CHKERRQ(ierr);
/* Write the Vec without one extra dimension for BS */
ierr = PetscViewerHDF5SetBaseDimension2(viewer, PETSC_FALSE);
ierr = PetscObjectSetName((PetscObject) global, "noBsDim");CHKERRQ(ierr);
ierr = VecView(global,viewer);CHKERRQ(ierr);
/* Write the Vec with one extra, 1-sized, dimension for BS */
ierr = PetscViewerHDF5SetBaseDimension2(viewer, PETSC_TRUE);
ierr = PetscObjectSetName((PetscObject) global, "bsDim");CHKERRQ(ierr);
ierr = VecView(global,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = MPI_Barrier(PETSC_COMM_WORLD);CHKERRQ(ierr);
ierr = VecDuplicate(global,&global2);CHKERRQ(ierr);
/* Create the HDF5 viewer for reading */
ierr = PetscViewerHDF5Open(PETSC_COMM_WORLD,"hdf5output.h5",FILE_MODE_READ,&viewer);CHKERRQ(ierr);
ierr = PetscViewerSetFromOptions(viewer);CHKERRQ(ierr);
/* Load the Vec without the BS dim and compare */
ierr = PetscObjectSetName((PetscObject) global2, "noBsDim");CHKERRQ(ierr);
ierr = VecLoad(global2,viewer);CHKERRQ(ierr);
ierr = VecEqual(global,global2,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscPrintf(PETSC_COMM_WORLD,"Vectors are equal\n");CHKERRQ(ierr);
} else {
ierr = PetscPrintf(PETSC_COMM_WORLD,"Vectors are not equal\n");CHKERRQ(ierr);
}
/* Load the Vec with one extra, 1-sized, BS dim and compare */
ierr = PetscObjectSetName((PetscObject) global2, "bsDim");CHKERRQ(ierr);
ierr = VecLoad(global2,viewer);CHKERRQ(ierr);
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = VecEqual(global,global2,&flg);CHKERRQ(ierr);
if (flg) {
ierr = PetscPrintf(PETSC_COMM_WORLD,"Vectors are equal\n");CHKERRQ(ierr);
} else {
ierr = PetscPrintf(PETSC_COMM_WORLD,"Vectors are not equal\n");CHKERRQ(ierr);
}
/* clean up and exit */
ierr = VecDestroy(&local);CHKERRQ(ierr);
ierr = VecDestroy(&global);CHKERRQ(ierr);
ierr = VecDestroy(&global2);CHKERRQ(ierr);
ierr = DMDestroy(&da);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
PETSC_EXTERN PetscErrorCode MatGetFactor_aij_superlu_dist(Mat A,MatFactorType ftype,Mat *F)
{
Mat B;
Mat_SuperLU_DIST *lu;
PetscErrorCode ierr;
PetscInt M=A->rmap->N,N=A->cmap->N,indx;
PetscMPIInt size;
superlu_options_t options;
PetscBool flg;
const char *colperm[] = {"NATURAL","MMD_AT_PLUS_A","MMD_ATA","METIS_AT_PLUS_A","PARMETIS"};
const char *rowperm[] = {"LargeDiag","NATURAL"};
const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm"};
PetscFunctionBegin;
/* Create the factorization matrix */
ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,M,N);CHKERRQ(ierr);
ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr);
ierr = MatSeqAIJSetPreallocation(B,0,NULL);
ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr);
B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST;
B->ops->view = MatView_SuperLU_DIST;
B->ops->destroy = MatDestroy_SuperLU_DIST;
ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_aij_superlu_dist);CHKERRQ(ierr);
B->factortype = MAT_FACTOR_LU;
ierr = PetscNewLog(B,&lu);CHKERRQ(ierr);
B->spptr = lu;
/* Set the default input options:
options.Fact = DOFACT;
options.Equil = YES;
options.ParSymbFact = NO;
options.ColPerm = METIS_AT_PLUS_A;
options.RowPerm = LargeDiag;
options.ReplaceTinyPivot = YES;
options.IterRefine = DOUBLE;
options.Trans = NOTRANS;
options.SolveInitialized = NO; -hold the communication pattern used MatSolve() and MatMatSolve()
options.RefineInitialized = NO;
options.PrintStat = YES;
*/
set_default_options_dist(&options);
ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->comm_superlu));CHKERRQ(ierr);
ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr);
/* Default num of process columns and rows */
lu->npcol = (int_t) (0.5 + PetscSqrtReal((PetscReal)size));
if (!lu->npcol) lu->npcol = 1;
while (lu->npcol > 0) {
lu->nprow = (int_t) (size/lu->npcol);
if (size == lu->nprow * lu->npcol) break;
lu->npcol--;
}
ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,(PetscInt*)&lu->nprow,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,(PetscInt*)&lu->npcol,NULL);CHKERRQ(ierr);
if (size != lu->nprow * lu->npcol) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol);
lu->MatInputMode = DISTRIBUTED;
ierr = PetscOptionsEnum("-mat_superlu_dist_matinput","Matrix input mode (global or distributed)","None",SuperLU_MatInputModes,(PetscEnum)lu->MatInputMode,(PetscEnum*)&lu->MatInputMode,NULL);CHKERRQ(ierr);
if (lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL;
ierr = PetscOptionsBool("-mat_superlu_dist_equil","Equilibrate matrix","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr);
if (!flg) options.Equil = NO;
ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",rowperm,2,rowperm[0],&indx,&flg);CHKERRQ(ierr);
if (flg) {
switch (indx) {
case 0:
options.RowPerm = LargeDiag;
break;
case 1:
options.RowPerm = NOROWPERM;
break;
}
}
ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",colperm,5,colperm[3],&indx,&flg);CHKERRQ(ierr);
if (flg) {
switch (indx) {
case 0:
options.ColPerm = NATURAL;
break;
case 1:
options.ColPerm = MMD_AT_PLUS_A;
break;
case 2:
options.ColPerm = MMD_ATA;
break;
case 3:
options.ColPerm = METIS_AT_PLUS_A;
break;
case 4:
options.ColPerm = PARMETIS; /* only works for np>1 */
break;
default:
SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation");
}
}
ierr = PetscOptionsBool("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr);
if (!flg) options.ReplaceTinyPivot = NO;
options.ParSymbFact = NO;
ierr = PetscOptionsBool("-mat_superlu_dist_parsymbfact","Parallel symbolic factorization","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
if (flg) {
#if defined(PETSC_HAVE_PARMETIS)
options.ParSymbFact = YES;
options.ColPerm = PARMETIS; /* in v2.2, PARMETIS is forced for ParSymbFact regardless of user ordering setting */
#else
printf("parsymbfact needs PARMETIS");
#endif
}
lu->FactPattern = SamePattern_SameRowPerm;
ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,2,factPattern[1],&indx,&flg);CHKERRQ(ierr);
if (flg) {
switch (indx) {
case 0:
lu->FactPattern = SamePattern;
break;
case 1:
lu->FactPattern = SamePattern_SameRowPerm;
break;
}
}
options.IterRefine = NOREFINE;
ierr = PetscOptionsBool("-mat_superlu_dist_iterrefine","Use iterative refinement","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr);
if (flg) options.IterRefine = SLU_DOUBLE;
if (PetscLogPrintInfo) options.PrintStat = YES;
else options.PrintStat = NO;
ierr = PetscOptionsBool("-mat_superlu_dist_statprint","Print factorization information","None",
(PetscBool)options.PrintStat,(PetscBool*)&options.PrintStat,0);CHKERRQ(ierr);
PetscOptionsEnd();
lu->options = options;
lu->options.Fact = DOFACT;
lu->matsolve_iscalled = PETSC_FALSE;
lu->matmatsolve_iscalled = PETSC_FALSE;
*F = B;
PetscFunctionReturn(0);
}
PetscErrorCode SNESSetFromOptions_FAS(PetscOptionItems *PetscOptionsObject,SNES snes)
{
SNES_FAS *fas = (SNES_FAS*) snes->data;
PetscInt levels = 1;
PetscBool flg = PETSC_FALSE, upflg = PETSC_FALSE, downflg = PETSC_FALSE, monflg = PETSC_FALSE, galerkinflg = PETSC_FALSE,continuationflg = PETSC_FALSE;
PetscErrorCode ierr;
SNESFASType fastype;
const char *optionsprefix;
SNESLineSearch linesearch;
PetscInt m, n_up, n_down;
SNES next;
PetscBool isFine;
PetscFunctionBegin;
ierr = SNESFASCycleIsFine(snes, &isFine);CHKERRQ(ierr);
ierr = PetscOptionsHead(PetscOptionsObject,"SNESFAS Options-----------------------------------");CHKERRQ(ierr);
/* number of levels -- only process most options on the finest level */
if (isFine) {
ierr = PetscOptionsInt("-snes_fas_levels", "Number of Levels", "SNESFASSetLevels", levels, &levels, &flg);CHKERRQ(ierr);
if (!flg && snes->dm) {
ierr = DMGetRefineLevel(snes->dm,&levels);CHKERRQ(ierr);
levels++;
fas->usedmfornumberoflevels = PETSC_TRUE;
}
ierr = SNESFASSetLevels(snes, levels, NULL);CHKERRQ(ierr);
fastype = fas->fastype;
ierr = PetscOptionsEnum("-snes_fas_type","FAS correction type","SNESFASSetType",SNESFASTypes,(PetscEnum)fastype,(PetscEnum*)&fastype,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetType(snes, fastype);CHKERRQ(ierr);
}
ierr = SNESGetOptionsPrefix(snes, &optionsprefix);CHKERRQ(ierr);
ierr = PetscOptionsInt("-snes_fas_cycles","Number of cycles","SNESFASSetCycles",fas->n_cycles,&m,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetCycles(snes, m);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-snes_fas_continuation","Corrected grid-sequence continuation","SNESFASSetContinuation",fas->continuation,&continuationflg,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetContinuation(snes,continuationflg);CHKERRQ(ierr);
}
ierr = PetscOptionsBool("-snes_fas_galerkin", "Form coarse problems with Galerkin","SNESFASSetGalerkin",fas->galerkin,&galerkinflg,&flg);CHKERRQ(ierr);
if (flg) {
ierr = SNESFASSetGalerkin(snes, galerkinflg);CHKERRQ(ierr);
}
if (fas->fastype == SNES_FAS_FULL) {
ierr = PetscOptionsBool("-snes_fas_full_downsweep","Smooth on the initial upsweep for full FAS cycles","SNESFASFullSetDownSweep",fas->full_downsweep,&fas->full_downsweep,&flg);CHKERRQ(ierr);
if (flg) {SNESFASFullSetDownSweep(snes,fas->full_downsweep);CHKERRQ(ierr);}
}
ierr = PetscOptionsInt("-snes_fas_smoothup","Number of post-smoothing steps","SNESFASSetNumberSmoothUp",fas->max_up_it,&n_up,&upflg);CHKERRQ(ierr);
ierr = PetscOptionsInt("-snes_fas_smoothdown","Number of pre-smoothing steps","SNESFASSetNumberSmoothDown",fas->max_down_it,&n_down,&downflg);CHKERRQ(ierr);
{
PetscViewer viewer;
PetscViewerFormat format;
ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)snes),((PetscObject)snes)->prefix,
"-snes_fas_monitor",&viewer,&format,&monflg);CHKERRQ(ierr);
if (monflg) {
PetscViewerAndFormat *vf;
ierr = PetscViewerAndFormatCreate(viewer,format,&vf);CHKERRQ(ierr);
ierr = PetscObjectDereference((PetscObject)viewer);CHKERRQ(ierr);
ierr = SNESFASSetMonitor(snes,vf,PETSC_TRUE);CHKERRQ(ierr);
}
}
flg = PETSC_FALSE;
monflg = PETSC_TRUE;
ierr = PetscOptionsBool("-snes_fas_log","Log times for each FAS level","SNESFASSetLog",monflg,&monflg,&flg);CHKERRQ(ierr);
if (flg) {ierr = SNESFASSetLog(snes,monflg);CHKERRQ(ierr);}
}
ierr = PetscOptionsTail();CHKERRQ(ierr);
/* setup from the determined types if there is no pointwise procedure or smoother defined */
if (upflg) {
ierr = SNESFASSetNumberSmoothUp(snes,n_up);CHKERRQ(ierr);
}
if (downflg) {
ierr = SNESFASSetNumberSmoothDown(snes,n_down);CHKERRQ(ierr);
}
/* set up the default line search for coarse grid corrections */
if (fas->fastype == SNES_FAS_ADDITIVE) {
if (!snes->linesearch) {
ierr = SNESGetLineSearch(snes, &linesearch);CHKERRQ(ierr);
ierr = SNESLineSearchSetType(linesearch, SNESLINESEARCHL2);CHKERRQ(ierr);
}
}
ierr = SNESFASCycleGetCorrection(snes, &next);CHKERRQ(ierr);
/* recursive option setting for the smoothers */
if (next) {ierr = SNESSetFromOptions(next);CHKERRQ(ierr);}
PetscFunctionReturn(0);
}
/*@
MatSetFromOptions - Creates a matrix where the type is determined
from the options database. Generates a parallel MPI matrix if the
communicator has more than one processor. The default matrix type is
AIJ, using the routines MatCreateSeqAIJ() and MatCreateAIJ() if
you do not select a type in the options database.
Collective on Mat
Input Parameter:
. A - the matrix
Options Database Keys:
+ -mat_type seqaij - AIJ type, uses MatCreateSeqAIJ()
. -mat_type mpiaij - AIJ type, uses MatCreateAIJ()
. -mat_type seqdense - dense type, uses MatCreateSeqDense()
. -mat_type mpidense - dense type, uses MatCreateDense()
. -mat_type seqbaij - block AIJ type, uses MatCreateSeqBAIJ()
- -mat_type mpibaij - block AIJ type, uses MatCreateBAIJ()
Even More Options Database Keys:
See the manpages for particular formats (e.g., MatCreateSeqAIJ())
for additional format-specific options.
Level: beginner
.keywords: matrix, create
.seealso: MatCreateSeqAIJ((), MatCreateAIJ(),
MatCreateSeqDense(), MatCreateDense(),
MatCreateSeqBAIJ(), MatCreateBAIJ(),
MatCreateSeqSBAIJ(), MatCreateSBAIJ(),
MatConvert()
@*/
PetscErrorCode MatSetFromOptions(Mat B)
{
PetscErrorCode ierr;
const char *deft = MATAIJ;
char type[256];
PetscBool flg,set;
PetscFunctionBegin;
PetscValidHeaderSpecific(B,MAT_CLASSID,1);
ierr = PetscObjectOptionsBegin((PetscObject)B);
CHKERRQ(ierr);
if (B->rmap->bs < 0) {
PetscInt newbs = -1;
ierr = PetscOptionsInt("-mat_block_size","Set the blocksize used to store the matrix","MatSetBlockSize",newbs,&newbs,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = PetscLayoutSetBlockSize(B->rmap,newbs);
CHKERRQ(ierr);
ierr = PetscLayoutSetBlockSize(B->cmap,newbs);
CHKERRQ(ierr);
}
}
ierr = PetscOptionsFList("-mat_type","Matrix type","MatSetType",MatList,deft,type,256,&flg);
CHKERRQ(ierr);
if (flg) {
ierr = MatSetType(B,type);
CHKERRQ(ierr);
} else if (!((PetscObject)B)->type_name) {
ierr = MatSetType(B,deft);
CHKERRQ(ierr);
}
ierr = PetscOptionsName("-mat_is_symmetric","Checks if mat is symmetric on MatAssemblyEnd()","MatIsSymmetric",&B->checksymmetryonassembly);
CHKERRQ(ierr);
ierr = PetscOptionsReal("-mat_is_symmetric","Checks if mat is symmetric on MatAssemblyEnd()","MatIsSymmetric",0.0,&B->checksymmetrytol,NULL);
CHKERRQ(ierr);
ierr = PetscOptionsBool("-mat_null_space_test","Checks if provided null space is correct in MatAssemblyEnd()","MatSetNullSpaceTest",PETSC_FALSE,&B->checknullspaceonassembly,NULL);
CHKERRQ(ierr);
if (B->ops->setfromoptions) {
ierr = (*B->ops->setfromoptions)(B);
CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-mat_new_nonzero_location_err","Generate an error if new nonzeros are created in the matrix structure (useful to test preallocation)","MatSetOption",flg,&flg,&set);
CHKERRQ(ierr);
if (set) {
ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,flg);
CHKERRQ(ierr);
}
flg = PETSC_FALSE;
ierr = PetscOptionsBool("-mat_new_nonzero_allocation_err","Generate an error if new nonzeros are allocated in the matrix structure (useful to test preallocation)","MatSetOption",flg,&flg,&set);
CHKERRQ(ierr);
if (set) {
ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,flg);
CHKERRQ(ierr);
}
/* process any options handlers added with PetscObjectAddOptionsHandler() */
ierr = PetscObjectProcessOptionsHandlers((PetscObject)B);
CHKERRQ(ierr);
ierr = PetscOptionsEnd();
CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode ProcessOptions(MPI_Comm comm, AppCtx *options)
{
const char *bcTypes[3] = {"neumann", "dirichlet", "none"};
const char *runTypes[3] = {"full", "test", "perf"};
const char *coeffTypes[4] = {"none", "analytic", "field", "nonlinear"};
PetscInt bc, run, coeff;
PetscBool flg;
PetscErrorCode ierr;
PetscFunctionBeginUser;
options->debug = 0;
options->runType = RUN_FULL;
options->dim = 2;
options->filename[0] = '\0';
options->interpolate = PETSC_FALSE;
options->refinementLimit = 0.0;
options->refinementUniform = PETSC_FALSE;
options->refinementRounds = 1;
options->bcType = DIRICHLET;
options->variableCoefficient = COEFF_NONE;
options->jacobianMF = PETSC_FALSE;
options->showInitial = PETSC_FALSE;
options->showSolution = PETSC_FALSE;
options->restart = PETSC_FALSE;
options->checkpoint = NULL;
options->fem.f0Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->f0Funcs;
options->fem.f1Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->f1Funcs;
options->fem.g0Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->g0Funcs;
options->fem.g1Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->g1Funcs;
options->fem.g2Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->g2Funcs;
options->fem.g3Funcs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], PetscScalar[])) &options->g3Funcs;
options->fem.f0BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->f0BdFuncs;
options->fem.f1BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->f1BdFuncs;
options->fem.g0BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->g0BdFuncs;
options->fem.g1BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->g1BdFuncs;
options->fem.g2BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->g2BdFuncs;
options->fem.g3BdFuncs = (void (**)(const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscScalar[], const PetscReal[], const PetscReal[], PetscScalar[])) &options->g3BdFuncs;
ierr = MPI_Comm_size(comm, &options->numProcs);CHKERRQ(ierr);
ierr = MPI_Comm_rank(comm, &options->rank);CHKERRQ(ierr);
ierr = PetscOptionsBegin(comm, "", "Poisson Problem Options", "DMPLEX");CHKERRQ(ierr);
ierr = PetscOptionsInt("-debug", "The debugging level", "ex12.c", options->debug, &options->debug, NULL);CHKERRQ(ierr);
run = options->runType;
ierr = PetscOptionsEList("-run_type", "The run type", "ex12.c", runTypes, 3, runTypes[options->runType], &run, NULL);CHKERRQ(ierr);
options->runType = (RunType) run;
ierr = PetscOptionsInt("-dim", "The topological mesh dimension", "ex12.c", options->dim, &options->dim, NULL);CHKERRQ(ierr);
spatialDim = options->dim;
ierr = PetscOptionsString("-f", "Exodus.II filename to read", "ex12.c", options->filename, options->filename, sizeof(options->filename), &flg);CHKERRQ(ierr);
#if !defined(PETSC_HAVE_EXODUSII)
if (flg) SETERRQ(comm, PETSC_ERR_ARG_WRONG, "This option requires ExodusII support. Reconfigure using --download-exodusii");
#endif
ierr = PetscOptionsBool("-interpolate", "Generate intermediate mesh elements", "ex12.c", options->interpolate, &options->interpolate, NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-refinement_limit", "The largest allowable cell volume", "ex12.c", options->refinementLimit, &options->refinementLimit, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-refinement_uniform", "Uniformly refine the mesh", "ex52.c", options->refinementUniform, &options->refinementUniform, NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-refinement_rounds", "The number of uniform refinements", "ex52.c", options->refinementRounds, &options->refinementRounds, NULL);CHKERRQ(ierr);
ierr = PetscStrcpy(options->partitioner, "chaco");CHKERRQ(ierr);
ierr = PetscOptionsString("-partitioner", "The graph partitioner", "pflotran.cxx", options->partitioner, options->partitioner, 2048, NULL);CHKERRQ(ierr);
bc = options->bcType;
ierr = PetscOptionsEList("-bc_type","Type of boundary condition","ex12.c",bcTypes,3,bcTypes[options->bcType],&bc,NULL);CHKERRQ(ierr);
options->bcType = (BCType) bc;
coeff = options->variableCoefficient;
ierr = PetscOptionsEList("-variable_coefficient","Type of variable coefficent","ex12.c",coeffTypes,4,coeffTypes[options->variableCoefficient],&coeff,NULL);CHKERRQ(ierr);
options->variableCoefficient = (CoeffType) coeff;
ierr = PetscOptionsBool("-jacobian_mf", "Calculate the action of the Jacobian on the fly", "ex12.c", options->jacobianMF, &options->jacobianMF, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-show_initial", "Output the initial guess for verification", "ex12.c", options->showInitial, &options->showInitial, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-show_solution", "Output the solution for verification", "ex12.c", options->showSolution, &options->showSolution, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-restart", "Read in the mesh and solution from a file", "ex12.c", options->restart, &options->restart, NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();
ierr = PetscLogEventRegister("CreateMesh", DM_CLASSID, &options->createMeshEvent);CHKERRQ(ierr);
if (options->restart) {
ierr = PetscViewerCreate(comm, &options->checkpoint);CHKERRQ(ierr);
ierr = PetscViewerSetType(options->checkpoint, PETSCVIEWERHDF5);CHKERRQ(ierr);
ierr = PetscViewerFileSetMode(options->checkpoint, FILE_MODE_READ);CHKERRQ(ierr);
ierr = PetscViewerFileSetName(options->checkpoint, options->filename);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
int main(int argc, char **argv)
{
MPI_Comm comm;
DM base, preForest, postForest;
PetscInt dim = 2;
PetscInt preCount, postCount;
Vec preVec, postVecTransfer, postVecExact;
PetscErrorCode (*funcs[1]) (PetscInt,PetscReal,const PetscReal [],PetscInt,PetscScalar [], void *) = {MultiaffineFunction};
void *ctxs[1] = {NULL};
const PetscInt cells[] = {3, 3, 3};
PetscReal diff, tol = PETSC_SMALL;
PetscBool linear = PETSC_FALSE;
PetscBool useFV = PETSC_FALSE;
PetscDS ds;
bc_func_ctx bcCtx;
DMLabel adaptLabel;
PetscErrorCode ierr;
ierr = PetscInitialize(&argc, &argv, NULL,help);if (ierr) return ierr;
comm = PETSC_COMM_WORLD;
ierr = PetscOptionsBegin(comm, "", "DMForestTransferVec() Test Options", "DMFOREST");CHKERRQ(ierr);
ierr = PetscOptionsInt("-dim", "The dimension (2 or 3)", "ex2.c", dim, &dim, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-linear","Transfer a simple linear function", "ex2.c", linear, &linear, NULL);CHKERRQ(ierr);
ierr = PetscOptionsBool("-use_fv","Use a finite volume approximation", "ex2.c", useFV, &useFV, NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
if (linear) {
funcs[0] = LinearFunction;
}
bcCtx.func = funcs[0];
bcCtx.dim = dim;
bcCtx.Nf = 1;
bcCtx.ctx = NULL;
/* the base mesh */
ierr = DMPlexCreateHexBoxMesh(comm, dim, cells, DM_BOUNDARY_NONE, DM_BOUNDARY_NONE, DM_BOUNDARY_NONE, &base);CHKERRQ(ierr);
if (useFV) {
PetscFV fv;
PetscLimiter limiter;
DM baseFV;
ierr = DMPlexConstructGhostCells(base,NULL,NULL,&baseFV);CHKERRQ(ierr);
ierr = DMDestroy(&base);CHKERRQ(ierr);
base = baseFV;
ierr = PetscFVCreate(comm, &fv);CHKERRQ(ierr);
ierr = PetscFVSetSpatialDimension(fv,dim);CHKERRQ(ierr);
ierr = PetscFVSetType(fv,PETSCFVLEASTSQUARES);CHKERRQ(ierr);
ierr = PetscFVSetNumComponents(fv,1);CHKERRQ(ierr);
ierr = PetscLimiterCreate(comm,&limiter);CHKERRQ(ierr);
ierr = PetscLimiterSetType(limiter,PETSCLIMITERNONE);CHKERRQ(ierr);
ierr = PetscFVSetLimiter(fv,limiter);CHKERRQ(ierr);
ierr = PetscLimiterDestroy(&limiter);CHKERRQ(ierr);
ierr = PetscFVSetFromOptions(fv);CHKERRQ(ierr);
ierr = DMSetField(base,0,(PetscObject)fv);CHKERRQ(ierr);
ierr = PetscFVDestroy(&fv);CHKERRQ(ierr);
} else {
PetscFE fe;
ierr = PetscFECreateDefault(base,dim,1,PETSC_FALSE,NULL,PETSC_DEFAULT,&fe);CHKERRQ(ierr);
ierr = DMSetField(base,0,(PetscObject)fe);CHKERRQ(ierr);
ierr = PetscFEDestroy(&fe);CHKERRQ(ierr);
}
{
PetscDS prob;
PetscInt comps[] = {0};
PetscInt ids[] = {1, 2, 3, 4, 5, 6};
ierr = DMGetDS(base,&prob);CHKERRQ(ierr);
ierr = PetscDSAddBoundary(prob,PETSC_TRUE, "bc", "marker", 0, 1, comps, useFV ? (void(*)()) bc_func_fv : (void(*)()) funcs[0], 2 * dim, ids, useFV ? (void *) &bcCtx : NULL);CHKERRQ(ierr);
}
ierr = AddIdentityLabel(base);CHKERRQ(ierr);
ierr = DMViewFromOptions(base,NULL,"-dm_base_view");CHKERRQ(ierr);
/* the pre adaptivity forest */
ierr = DMCreate(comm,&preForest);CHKERRQ(ierr);
ierr = DMSetType(preForest,(dim == 2) ? DMP4EST : DMP8EST);CHKERRQ(ierr);
ierr = DMGetDS(base,&ds);CHKERRQ(ierr);
ierr = DMSetDS(preForest,ds);CHKERRQ(ierr);
ierr = DMForestSetBaseDM(preForest,base);CHKERRQ(ierr);
ierr = DMForestSetMinimumRefinement(preForest,1);CHKERRQ(ierr);
ierr = DMForestSetInitialRefinement(preForest,1);CHKERRQ(ierr);
ierr = DMSetFromOptions(preForest);CHKERRQ(ierr);
ierr = DMSetUp(preForest);CHKERRQ(ierr);
ierr = DMViewFromOptions(preForest,NULL,"-dm_pre_view");CHKERRQ(ierr);
/* the pre adaptivity field */
ierr = DMCreateGlobalVector(preForest,&preVec);CHKERRQ(ierr);
ierr = DMProjectFunction(preForest,0.,funcs,ctxs,INSERT_VALUES,preVec);CHKERRQ(ierr);
ierr = VecViewFromOptions(preVec,NULL,"-vec_pre_view");CHKERRQ(ierr);
ierr = PetscObjectGetReference((PetscObject)preForest,&preCount);CHKERRQ(ierr);
/* adapt */
ierr = CreateAdaptivityLabel(preForest,&adaptLabel);CHKERRQ(ierr);
ierr = DMForestTemplate(preForest,comm,&postForest);CHKERRQ(ierr);
ierr = DMForestSetMinimumRefinement(postForest,0);CHKERRQ(ierr);
ierr = DMForestSetInitialRefinement(postForest,0);CHKERRQ(ierr);
ierr = DMForestSetAdaptivityLabel(postForest,adaptLabel);CHKERRQ(ierr);
ierr = DMLabelDestroy(&adaptLabel);CHKERRQ(ierr);
ierr = DMSetUp(postForest);CHKERRQ(ierr);
ierr = DMViewFromOptions(postForest,NULL,"-dm_post_view");CHKERRQ(ierr);
/* transfer */
ierr = DMCreateGlobalVector(postForest,&postVecTransfer);CHKERRQ(ierr);
ierr = DMForestTransferVec(preForest,preVec,postForest,postVecTransfer,PETSC_TRUE,0.0);CHKERRQ(ierr);
ierr = VecViewFromOptions(postVecTransfer,NULL,"-vec_post_transfer_view");CHKERRQ(ierr);
/* the exact post adaptivity field */
ierr = DMCreateGlobalVector(postForest,&postVecExact);CHKERRQ(ierr);
ierr = DMProjectFunction(postForest,0.,funcs,ctxs,INSERT_VALUES,postVecExact);CHKERRQ(ierr);
ierr = VecViewFromOptions(postVecExact,NULL,"-vec_post_exact_view");CHKERRQ(ierr);
/* compare */
ierr = VecAXPY(postVecTransfer,-1.,postVecExact);CHKERRQ(ierr);
ierr = VecViewFromOptions(postVecTransfer,NULL,"-vec_diff_view");CHKERRQ(ierr);
ierr = VecNorm(postVecTransfer,NORM_2,&diff);CHKERRQ(ierr);
/* output */
if (diff < tol) {
ierr = PetscPrintf(comm,"DMForestTransferVec() passes.\n");CHKERRQ(ierr);
} else {
ierr = PetscPrintf(comm,"DMForestTransferVec() fails with error %g and tolerance %g\n",diff,tol);CHKERRQ(ierr);
}
/* disconnect preForest from postForest */
ierr = DMForestSetAdaptivityForest(postForest,NULL);CHKERRQ(ierr);
ierr = PetscObjectGetReference((PetscObject)preForest,&postCount);CHKERRQ(ierr);
if (postCount != preCount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Adaptation not memory neutral: reference count increase from %d to %d\n",preCount,postCount);
/* cleanup */
ierr = VecDestroy(&postVecExact);CHKERRQ(ierr);
ierr = VecDestroy(&postVecTransfer);CHKERRQ(ierr);
ierr = DMDestroy(&postForest);CHKERRQ(ierr);
ierr = VecDestroy(&preVec);CHKERRQ(ierr);
ierr = DMDestroy(&preForest);CHKERRQ(ierr);
ierr = DMDestroy(&base);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
int main(int argc, char **argv)
{
Vec vec, tagged, untagged;
VecScatter taggedScatter, untaggedScatter;
PetscInt bs;
PetscInt n, nloc, nint, i, j, k, localStart, localEnd, ntagged, nuntagged;
MPI_Comm comm;
VecTagger tagger;
PetscScalar *array;
PetscRandom rand;
VecTaggerBox *defaultBox;
VecTaggerBox *boxes;
IS is, isBlockGlobal, isComp;
PetscErrorCode ierr;
ierr = PetscInitialize(&argc,&argv,NULL,help);if (ierr) return ierr;
n = 10.;
bs = 1;
comm = PETSC_COMM_WORLD;
ierr = PetscOptionsBegin(comm, "" , "VecTagger Test Options", "Vec");CHKERRQ(ierr);
ierr = PetscOptionsInt("-bs","The block size of the vector","ex1.c",bs,&bs,NULL);CHKERRQ(ierr);
ierr = PetscOptionsInt("-n","The size of the vector (in blocks)","ex1.c",n,&n,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();CHKERRQ(ierr);
ierr = PetscRandomCreate(comm,&rand);CHKERRQ(ierr);
ierr = PetscRandomSetFromOptions(rand);CHKERRQ(ierr);
ierr = VecCreate(comm,&vec);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)vec,"Vec to Tag");CHKERRQ(ierr);
ierr = VecSetBlockSize(vec,bs);CHKERRQ(ierr);
ierr = VecSetSizes(vec,PETSC_DECIDE,n);CHKERRQ(ierr);
ierr = VecSetUp(vec);CHKERRQ(ierr);
ierr = VecGetLocalSize(vec,&nloc);CHKERRQ(ierr);
ierr = VecGetArray(vec,&array);CHKERRQ(ierr);
for (i = 0; i < nloc; i++) {
PetscScalar val;
ierr = PetscRandomGetValue(rand,&val);CHKERRQ(ierr);
array[i] = val;
}
ierr = VecRestoreArray(vec,&array);CHKERRQ(ierr);
ierr = PetscRandomDestroy(&rand);CHKERRQ(ierr);
ierr = VecViewFromOptions(vec,NULL,"-vec_view");CHKERRQ(ierr);
ierr = VecTaggerCreate(comm,&tagger);CHKERRQ(ierr);
ierr = VecTaggerSetBlockSize(tagger,bs);CHKERRQ(ierr);
ierr = VecTaggerSetType(tagger,VECTAGGERABSOLUTE);CHKERRQ(ierr);
ierr = PetscMalloc1(bs,&defaultBox);CHKERRQ(ierr);
for (i = 0; i < bs; i++) {
#if !defined(PETSC_USE_COMPLEX)
defaultBox[i].min = 0.1;
defaultBox[i].max = 1.5;
#else
defaultBox[i].min = PetscCMPLX(0.1,0.1);
defaultBox[i].max = PetscCMPLX(1.5,1.5);
#endif
}
ierr = VecTaggerAbsoluteSetBox(tagger,defaultBox);CHKERRQ(ierr);
ierr = PetscFree(defaultBox);CHKERRQ(ierr);
ierr = VecTaggerSetFromOptions(tagger);CHKERRQ(ierr);
ierr = VecTaggerSetUp(tagger);CHKERRQ(ierr);
ierr = PetscObjectViewFromOptions((PetscObject)tagger,NULL,"-vec_tagger_view");CHKERRQ(ierr);
ierr = VecTaggerGetBlockSize(tagger,&bs);CHKERRQ(ierr);
ierr = VecTaggerComputeBoxes(tagger,vec,&nint,&boxes);
if (ierr && ierr != PETSC_ERR_SUP) CHKERRQ(ierr);
else {
PetscViewer viewer = NULL;
ierr = PetscOptionsGetViewer(comm,NULL,NULL,"-vec_tagger_boxes_view",&viewer,NULL,NULL);CHKERRQ(ierr);
if (viewer) {
PetscBool iascii;
ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
if (iascii) {
ierr = PetscViewerASCIIPrintf(viewer,"Num boxes: %D\n",nint);CHKERRQ(ierr);
ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr);
for (i = 0, k = 0; i < nint; i++) {
ierr = PetscViewerASCIIPrintf(viewer,"%D: ",i);CHKERRQ(ierr);
for (j = 0; j < bs; j++, k++) {
if (j) {ierr = PetscViewerASCIIPrintf(viewer," x ");CHKERRQ(ierr);}
#if !defined(PETSC_USE_COMPLEX)
ierr = PetscViewerASCIIPrintf(viewer,"[%g,%g]",(double)boxes[k].min,(double)boxes[k].max);CHKERRQ(ierr);
#else
ierr = PetscViewerASCIIPrintf(viewer,"[%g+%gi,%g+%gi]",(double)PetscRealPart(boxes[k].min),(double)PetscImaginaryPart(boxes[k].min),(double)PetscRealPart(boxes[k].max),(double)PetscImaginaryPart(boxes[k].max));CHKERRQ(ierr);
#endif
}
ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr);
}
ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr);
}
}
ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
ierr = PetscFree(boxes);CHKERRQ(ierr);
}
ierr = VecTaggerComputeIS(tagger,vec,&is);CHKERRQ(ierr);
ierr = ISGetBlockGlobalIS(is,vec,bs,&isBlockGlobal);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)isBlockGlobal,"Tagged IS (block global)");CHKERRQ(ierr);
ierr = ISViewFromOptions(isBlockGlobal,NULL,"-tagged_is_view");CHKERRQ(ierr);
ierr = VecGetOwnershipRange(vec,&localStart,&localEnd);CHKERRQ(ierr);
ierr = ISComplement(isBlockGlobal,localStart,localEnd,&isComp);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)isComp,"Untagged IS (global)");CHKERRQ(ierr);
ierr = ISViewFromOptions(isComp,NULL,"-untagged_is_view");CHKERRQ(ierr);
ierr = ISGetLocalSize(isBlockGlobal,&ntagged);CHKERRQ(ierr);
ierr = ISGetLocalSize(isComp,&nuntagged);CHKERRQ(ierr);
ierr = VecCreate(comm,&tagged);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)tagged,"Tagged selection");CHKERRQ(ierr);
ierr = VecSetSizes(tagged,ntagged,PETSC_DETERMINE);CHKERRQ(ierr);
ierr = VecSetUp(tagged);CHKERRQ(ierr);
ierr = VecCreate(comm,&untagged);CHKERRQ(ierr);
ierr = PetscObjectSetName((PetscObject)untagged,"Untagged selection");CHKERRQ(ierr);
ierr = VecSetSizes(untagged,nuntagged,PETSC_DETERMINE);CHKERRQ(ierr);
ierr = VecSetUp(untagged);CHKERRQ(ierr);
ierr = VecScatterCreate(vec,isBlockGlobal,tagged,NULL,&taggedScatter);CHKERRQ(ierr);
ierr = VecScatterCreate(vec,isComp,untagged,NULL,&untaggedScatter);CHKERRQ(ierr);
ierr = VecScatterBegin(taggedScatter,vec,tagged,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
ierr = VecScatterEnd(taggedScatter,vec,tagged,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
ierr = VecScatterBegin(untaggedScatter,vec,untagged,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
ierr = VecScatterEnd(untaggedScatter,vec,untagged,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
ierr = VecViewFromOptions(tagged,NULL,"-tagged_vec_view");CHKERRQ(ierr);
ierr = VecViewFromOptions(untagged,NULL,"-untagged_vec_view");CHKERRQ(ierr);
ierr = VecScatterDestroy(&untaggedScatter);CHKERRQ(ierr);
ierr = VecScatterDestroy(&taggedScatter);CHKERRQ(ierr);
ierr = VecDestroy(&untagged);CHKERRQ(ierr);
ierr = VecDestroy(&tagged);CHKERRQ(ierr);
ierr = ISDestroy(&isComp);CHKERRQ(ierr);
ierr = ISDestroy(&isBlockGlobal);CHKERRQ(ierr);
ierr = ISDestroy(&is);CHKERRQ(ierr);
ierr = VecTaggerDestroy(&tagger);CHKERRQ(ierr);
ierr = VecDestroy(&vec);CHKERRQ(ierr);
ierr = PetscFinalize();
return ierr;
}
int main(int argc, char **argv)
{
const PetscInt digits = 14;
const PetscReal epsilon = 1.0e-14;
const PetscReal bounds[28] =
{
0.0, 1.0,
0.0, 1.0,
0.0, PETSC_PI/2.,
0.0, 1.0,
0.0, 1.0,
0.0, 1.0,
0.0, 1.0,
0.0, 1.0,
0.0, PETSC_PI/2.,
0.0, PETSC_PI/2.,
0.0, 1.0,
0.0, 1.0,
0.0, 1.0,
0.0, 1.0
};
const PetscReal analytic[14] =
{
0.250000000000000,
0.210657251225806988108092302182988001695680805674,
1.905238690482675827736517833351916563195085437332,
0.514041895890070761397629739576882871630921844127,
-.444444444444444444444444444444444444444444444444,
0.785398163397448309615660845819875721049292349843,
1.198140234735592207439922492280323878227212663216,
2.000000000000000000000000000000000000000000000000,
-1.08879304515180106525034444911880697366929185018,
2.221441469079183123507940495030346849307310844687,
1.570796326794896619231321691639751442098584699687,
1.772453850905516027298167483341145182797549456122,
1.253314137315500251207882642405522626503493370304,
0.500000000000000000000000000000000000000000000000
};
void (*funcs[14])(PetscReal, PetscReal *) = {func1, func2, func3, func4, func5, func6, func7, func8, func9, func10, func11, func12, func13, func14};
PetscInt mdigits = 14, f;
PetscErrorCode ierr;
ierr = PetscInitialize(&argc, &argv, PETSC_NULL, help);CHKERRQ(ierr);
ierr = PetscOptionsBegin(PETSC_COMM_WORLD,"","Test Options","none");CHKERRQ(ierr);
ierr = PetscOptionsInt("-digits", "The number of significant digits for the integral","ex3.c",mdigits,&mdigits,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();
/* Integrate each function */
for (f = 0; f < 14; ++f) {
PetscReal integral;
ierr = PetscDTTanhSinhIntegrate(funcs[f], bounds[f*2+0], bounds[f*2+1], digits, &integral);CHKERRQ(ierr);
if (PetscAbsReal(integral - analytic[f]) < epsilon) {ierr = PetscPrintf(PETSC_COMM_SELF, "The integral of func%2d is correct\n", f+1);CHKERRQ(ierr);}
else {ierr = PetscPrintf(PETSC_COMM_SELF, "The integral of func%2d is wrong: %15.15f (%15.15f)\n", f+1, integral, PetscAbsReal(integral - analytic[f]));CHKERRQ(ierr);}
}
#ifdef PETSC_HAVE_MPFR
for (f = 0; f < 14; ++f) {
PetscReal integral;
ierr = PetscDTTanhSinhIntegrateMPFR(funcs[f], bounds[f*2+0], bounds[f*2+1], mdigits, &integral);CHKERRQ(ierr);
if (PetscAbsReal(integral - analytic[f]) < epsilon) {ierr = PetscPrintf(PETSC_COMM_SELF, "The integral of func%2d is correct\n", f+1);CHKERRQ(ierr);}
else {ierr = PetscPrintf(PETSC_COMM_SELF, "The integral of func%2d is wrong: %15.15f (%15.15f)\n", f+1, integral, PetscAbsReal(integral - analytic[f]));CHKERRQ(ierr);}
}
#endif
PetscFinalize();
return 0;
}
int main(int argc, char **argv)
{
TS ts; /* time-stepping context */
Vec x; /* State vector */
Mat J; /* Jacobian matrix */
AppCtx user; /* user-defined context */
PetscErrorCode ierr;
PetscReal ftime;
PetscInt its;
PetscMPIInt size;
PetscInitialize(&argc, &argv, NULL, help);
ierr = MPI_Comm_size(PETSC_COMM_WORLD, &size);
if(size != 1) SETERRQ(PETSC_COMM_WORLD, PETSC_ERR_SUP, "This is a uniprocessor example only");
/*
* Allow user to set the grid dimensions and the equations parameters
*/
user.nb_cells = 50;
user.alpha = 10.;
user.beta = 1.;
user.rho_a = 1.;
user.rho_h = 2.;
user.mu_a = 2.;
user.mu_h = 3.;
user.D_a = 0.;
user.D_h = 30.;
ierr = PetscOptionsBegin(PETSC_COMM_WORLD, "", "Problem settings", "PROBLEM");
ierr = PetscOptionsInt("-nb_cells", "Number of cells", "ex42.c",user.nb_cells, &user.nb_cells,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-alpha", "Autocatalysis factor", "ex42.c",user.alpha, &user.alpha,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-beta", "Inhibition factor", "ex42.c",user.beta, &user.beta,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-rho_a", "Default production of the activator", "ex42.c",user.rho_a, &user.rho_a,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mu_a", "Degradation rate of the activator", "ex42.c",user.mu_a, &user.mu_a,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-D_a", "Diffusion rate of the activator", "ex42.c",user.D_a, &user.D_a,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-rho_h", "Default production of the inhibitor", "ex42.c",user.rho_h, &user.rho_h,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-mu_h", "Degradation rate of the inhibitor", "ex42.c",user.mu_h, &user.mu_h,NULL);CHKERRQ(ierr);
ierr = PetscOptionsReal("-D_h", "Diffusion rate of the inhibitor", "ex42.c",user.D_h, &user.D_h,NULL);CHKERRQ(ierr);
ierr = PetscOptionsEnd();
ierr = PetscPrintf(PETSC_COMM_WORLD, "nb_cells: %D\n", user.nb_cells);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "alpha: %5.5g\n", user.alpha);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "beta: %5.5g\n", user.beta);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "rho_a: %5.5g\n", user.rho_a);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "mu_a: %5.5g\n", user.mu_a);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "D_a: %5.5g\n", user.D_a);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "rho_h: %5.5g\n", user.rho_h);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "mu_h: %5.5g\n", user.mu_h);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "D_h: %5.5g\n", user.D_h);CHKERRQ(ierr);
/*
* Create vector to hold the solution
*/
ierr = VecCreateSeq(PETSC_COMM_WORLD, 2*user.nb_cells, &x);CHKERRQ(ierr);
/*
* Create time-stepper context
*/
ierr = TSCreate(PETSC_COMM_WORLD, &ts);CHKERRQ(ierr);
ierr = TSSetProblemType(ts, TS_NONLINEAR);CHKERRQ(ierr);
/*
* Tell the time-stepper context where to compute the solution
*/
ierr = TSSetSolution(ts, x);CHKERRQ(ierr);
/*
* Allocate the jacobian matrix
*/
ierr = MatCreateSeqAIJ(PETSC_COMM_WORLD, 2*user.nb_cells, 2*user.nb_cells, 4, 0, &J);CHKERRQ(ierr);
/*
* Provide the call-back for the non-linear function we are evaluating.
*/
ierr = TSSetRHSFunction(ts, NULL, RHSFunction, &user);CHKERRQ(ierr);
/*
* Set the Jacobian matrix and the function user to compute Jacobians
*/
ierr = TSSetRHSJacobian(ts, J, J, RHSJacobian, &user);CHKERRQ(ierr);
/*
* Set the function checking the domain
*/
ierr = TSSetFunctionDomainError(ts, &DomainErrorFunction);CHKERRQ(ierr);
/*
* Initialize the problem with random values
*/
ierr = FormInitialState(x, &user);CHKERRQ(ierr);
/*
* Read the solver type from options
*/
ierr = TSSetType(ts, TSPSEUDO);CHKERRQ(ierr);
/*
* Set a large number of timesteps and final duration time to insure
* convergenge to steady state
*/
ierr = TSSetDuration(ts, 5000, 1e12);
/*
* Set a larger number of potential errors
*/
ierr = TSSetMaxStepRejections(ts, 50);CHKERRQ(ierr);
/*
* Also start with a very small dt
*/
ierr = TSSetTimeStep(ts, 0.05);CHKERRQ(ierr);
/*
* Set a larger time step increment
*/
ierr = TSPseudoSetTimeStepIncrement(ts, 1.5);CHKERRQ(ierr);
/*
* Let the user personalise TS
*/
ierr = TSSetFromOptions(ts);CHKERRQ(ierr);
/*
* Set the context for the time stepper
*/
ierr = TSSetApplicationContext(ts, &user);CHKERRQ(ierr);
/*
* Setup the time stepper, ready for evaluation
*/
ierr = TSSetUp(ts);CHKERRQ(ierr);
/*
* Perform the solve.
*/
ierr = TSSolve(ts, x);CHKERRQ(ierr);
ierr = TSGetSolveTime(ts, &ftime);CHKERRQ(ierr);
ierr = TSGetTimeStepNumber(ts,&its);CHKERRQ(ierr);
ierr = PetscPrintf(PETSC_COMM_WORLD, "Number of time steps = %D, final time: %4.2e\nResult:\n\n", its, (double)ftime);CHKERRQ(ierr);
ierr = PrintSolution(x, &user);CHKERRQ(ierr);
/*
* Free the data structures
*/
ierr = VecDestroy(&x);CHKERRQ(ierr);
ierr = MatDestroy(&J);CHKERRQ(ierr);
ierr = TSDestroy(&ts);CHKERRQ(ierr);
ierr = PetscFinalize();
return 0;
}
