/*@
KSPComputeExplicitOperator - Computes the explicit preconditioned operator.
Collective on KSP
Input Parameter:
. ksp - the Krylov subspace context
Output Parameter:
. mat - the explict preconditioned operator
Notes:
This computation is done by applying the operators to columns of the
identity matrix.
Currently, this routine uses a dense matrix format when 1 processor
is used and a sparse format otherwise. This routine is costly in general,
and is recommended for use only with relatively small systems.
Level: advanced
.keywords: KSP, compute, explicit, operator
.seealso: KSPComputeEigenvaluesExplicitly(), PCComputeExplicitOperator()
@*/
PetscErrorCode KSPComputeExplicitOperator(KSP ksp,Mat *mat)
{
Vec in,out;
PetscErrorCode ierr;
PetscMPIInt size;
PetscInt i,M,m,*rows,start,end;
Mat A;
MPI_Comm comm;
PetscScalar *array,one = 1.0;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
PetscValidPointer(mat,2);
comm = ((PetscObject)ksp)->comm;
ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
ierr = VecDuplicate(ksp->vec_sol,&in);CHKERRQ(ierr);
ierr = VecDuplicate(ksp->vec_sol,&out);CHKERRQ(ierr);
ierr = VecGetSize(in,&M);CHKERRQ(ierr);
ierr = VecGetLocalSize(in,&m);CHKERRQ(ierr);
ierr = VecGetOwnershipRange(in,&start,&end);CHKERRQ(ierr);
ierr = PetscMalloc(m*sizeof(PetscInt),&rows);CHKERRQ(ierr);
for (i=0; i<m; i++) {rows[i] = start + i;}
ierr = MatCreate(comm,mat);CHKERRQ(ierr);
ierr = MatSetSizes(*mat,m,m,M,M);CHKERRQ(ierr);
if (size == 1) {
ierr = MatSetType(*mat,MATSEQDENSE);CHKERRQ(ierr);
ierr = MatSeqDenseSetPreallocation(*mat,PETSC_NULL);CHKERRQ(ierr);
} else {
ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr);
ierr = MatMPIAIJSetPreallocation(*mat,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr);
}
ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCGetOperators(ksp->pc,&A,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr);
for (i=0; i<M; i++) {
ierr = VecSet(in,0.0);CHKERRQ(ierr);
ierr = VecSetValues(in,1,&i,&one,INSERT_VALUES);CHKERRQ(ierr);
ierr = VecAssemblyBegin(in);CHKERRQ(ierr);
ierr = VecAssemblyEnd(in);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,A,in,out);CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,out,in);CHKERRQ(ierr);
ierr = VecGetArray(in,&array);CHKERRQ(ierr);
ierr = MatSetValues(*mat,m,rows,1,&i,array,INSERT_VALUES);CHKERRQ(ierr);
ierr = VecRestoreArray(in,&array);CHKERRQ(ierr);
}
ierr = PetscFree(rows);CHKERRQ(ierr);
ierr = VecDestroy(&in);CHKERRQ(ierr);
ierr = VecDestroy(&out);CHKERRQ(ierr);
ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPInitialResidual(KSP ksp,Vec vsoln,Vec vt1,Vec vt2,Vec vres,Vec vb)
{
Mat Amat,Pmat;
PetscErrorCode ierr;
PetscFunctionBegin;
PetscValidHeaderSpecific(ksp,KSP_CLASSID,1);
PetscValidHeaderSpecific(vsoln,VEC_CLASSID,2);
PetscValidHeaderSpecific(vres,VEC_CLASSID,5);
PetscValidHeaderSpecific(vb,VEC_CLASSID,6);
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
if (!ksp->guess_zero) {
/* skip right scaling since current guess already has it */
ierr = KSP_MatMult(ksp,Amat,vsoln,vt1);CHKERRQ(ierr);
ierr = VecCopy(vb,vt2);CHKERRQ(ierr);
ierr = VecAXPY(vt2,-1.0,vt1);CHKERRQ(ierr);
ierr = (ksp->pc_side == PC_RIGHT) ? (VecCopy(vt2,vres)) : (KSP_PCApply(ksp,vt2,vres));CHKERRQ(ierr);
ierr = PCDiagonalScaleLeft(ksp->pc,vres,vres);CHKERRQ(ierr);
} else {
ierr = VecCopy(vb,vt2);CHKERRQ(ierr);
if (ksp->pc_side == PC_RIGHT) {
ierr = PCDiagonalScaleLeft(ksp->pc,vb,vres);CHKERRQ(ierr);
} else if (ksp->pc_side == PC_LEFT) {
ierr = KSP_PCApply(ksp,vb,vres);CHKERRQ(ierr);
ierr = PCDiagonalScaleLeft(ksp->pc,vres,vres);CHKERRQ(ierr);
} else if (ksp->pc_side == PC_SYMMETRIC) {
ierr = PCApplySymmetricLeft(ksp->pc, vb, vres);CHKERRQ(ierr);
} else SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP, "Invalid preconditioning side %d", (int)ksp->pc_side);
}
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_GCR(KSP ksp)
{
KSP_GCR *ctx = (KSP_GCR*)ksp->data;
PetscErrorCode ierr;
Mat A, B;
Vec r,b,x;
PetscReal norm_r;
PetscFunctionBegin;
ierr = KSPGetOperators(ksp, &A, &B);CHKERRQ(ierr);
x = ksp->vec_sol;
b = ksp->vec_rhs;
r = ctx->R;
/* compute initial residual */
ierr = KSP_MatMult(ksp,A, x, r);CHKERRQ(ierr);
ierr = VecAYPX(r, -1.0, b);CHKERRQ(ierr); /* r = b - A x */
ierr = VecNorm(r, NORM_2, &norm_r);CHKERRQ(ierr);
KSPCheckNorm(ksp,norm_r);
ksp->its = 0;
ksp->rnorm0 = norm_r;
ierr = KSPLogResidualHistory(ksp,ksp->rnorm0);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,ksp->rnorm0);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,ksp->rnorm0,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
do {
ierr = KSPSolve_GCR_cycle(ksp);CHKERRQ(ierr);
if (ksp->reason) break; /* catch case when convergence occurs inside the cycle */
} while (ksp->its < ksp->max_it);CHKERRQ(ierr);
if (ksp->its >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPFischerGuessUpdate_Method1(KSPFischerGuess_Method1 *itg,Vec x)
{
PetscReal norm;
PetscErrorCode ierr;
int curl = itg->curl,i;
PetscFunctionBegin;
PetscValidHeaderSpecific(x,VEC_CLASSID,2);
PetscValidPointer(itg,3);
if (curl == itg->maxl) {
ierr = KSP_MatMult(itg->ksp,itg->mat,x,itg->btilde[0]);CHKERRQ(ierr);
ierr = VecNormalize(itg->btilde[0],&norm);CHKERRQ(ierr);
ierr = VecCopy(x,itg->xtilde[0]);CHKERRQ(ierr);
ierr = VecScale(itg->xtilde[0],1.0/norm);CHKERRQ(ierr);
itg->curl = 1;
} else {
if (!curl) {
ierr = VecCopy(x,itg->xtilde[curl]);CHKERRQ(ierr);
} else {
ierr = VecWAXPY(itg->xtilde[curl],-1.0,itg->guess,x);CHKERRQ(ierr);
}
ierr = KSP_MatMult(itg->ksp,itg->mat,itg->xtilde[curl],itg->btilde[curl]);CHKERRQ(ierr);
ierr = VecMDot(itg->btilde[curl],curl,itg->btilde,itg->alpha);CHKERRQ(ierr);
for (i=0; i<curl; i++) itg->alpha[i] = -itg->alpha[i];
ierr = VecMAXPY(itg->btilde[curl],curl,itg->alpha,itg->btilde);CHKERRQ(ierr);
ierr = VecMAXPY(itg->xtilde[curl],curl,itg->alpha,itg->xtilde);CHKERRQ(ierr);
ierr = VecNormalize(itg->btilde[curl],&norm);CHKERRQ(ierr);
if (norm) {
ierr = VecScale(itg->xtilde[curl],1.0/norm);CHKERRQ(ierr);
itg->curl++;
} else {
ierr = PetscInfo(itg->ksp,"Not increasing dimension of Fischer space because new direction is identical to previous\n");CHKERRQ(ierr);
}
}
PetscFunctionReturn(0);
}
/*
KSPBuildResidualDefault - Default code to compute the residual.
Input Parameters:
. ksp - iterative context
. t - pointer to temporary vector
. v - pointer to user vector
Output Parameter:
. V - pointer to a vector containing the residual
Level: advanced
Developers Note: This is PETSC_EXTERN because it may be used by user written plugin KSP implementations
.keywords: KSP, build, residual, default
.seealso: KSPBuildSolutionDefault()
*/
PetscErrorCode KSPBuildResidualDefault(KSP ksp,Vec t,Vec v,Vec *V)
{
PetscErrorCode ierr;
Mat Amat,Pmat;
PetscFunctionBegin;
if (!ksp->pc) {ierr = KSPGetPC(ksp,&ksp->pc);CHKERRQ(ierr);}
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ierr = KSPBuildSolution(ksp,t,NULL);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,t,v);CHKERRQ(ierr);
ierr = VecAYPX(v,-1.0,ksp->vec_rhs);CHKERRQ(ierr);
*V = v;
PetscFunctionReturn(0);
}
/*
KSPFGMRESResidual - This routine computes the initial residual (NOT PRECONDITIONED)
*/
static PetscErrorCode KSPFGMRESResidual(KSP ksp)
{
KSP_FGMRES *fgmres = (KSP_FGMRES*)(ksp->data);
Mat Amat,Pmat;
PetscErrorCode ierr;
PetscFunctionBegin;
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
/* put A*x into VEC_TEMP */
ierr = KSP_MatMult(ksp,Amat,ksp->vec_sol,VEC_TEMP);CHKERRQ(ierr);
/* now put residual (-A*x + f) into vec_vv(0) */
ierr = VecWAXPY(VEC_VV(0),-1.0,VEC_TEMP,ksp->vec_rhs);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_LCD(KSP ksp)
{
PetscErrorCode ierr;
PetscInt it,j,max_k;
PetscScalar alfa, beta, num, den, mone;
PetscReal rnorm;
Vec X,B,R,Z;
KSP_LCD *lcd;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);
CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
lcd = (KSP_LCD*)ksp->data;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
max_k = lcd->restart;
mone = -1;
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);
CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,Z);
CHKERRQ(ierr); /* z <- b - Ax */
ierr = VecAYPX(Z,mone,B);
CHKERRQ(ierr);
} else {
ierr = VecCopy(B,Z);
CHKERRQ(ierr); /* z <- b (x is 0) */
}
ierr = KSP_PCApply(ksp,Z,R);
CHKERRQ(ierr); /* r <- M^-1z */
ierr = VecNorm(R,NORM_2,&rnorm);
CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnorm);
CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,rnorm);
CHKERRQ(ierr);
ksp->rnorm = rnorm;
/* test for convergence */
ierr = (*ksp->converged)(ksp,0,rnorm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
it = 0;
VecCopy(R,lcd->P[0]);
while (!ksp->reason && ksp->its < ksp->max_it) {
it = 0;
ierr = KSP_MatMult(ksp,Amat,lcd->P[it],Z);
CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,Z,lcd->Q[it]);
CHKERRQ(ierr);
while (!ksp->reason && it < max_k && ksp->its < ksp->max_it) {
ksp->its++;
ierr = VecDot(lcd->P[it],R,&num);
CHKERRQ(ierr);
ierr = VecDot(lcd->P[it],lcd->Q[it], &den);
CHKERRQ(ierr);
alfa = num/den;
ierr = VecAXPY(X,alfa,lcd->P[it]);
CHKERRQ(ierr);
ierr = VecAXPY(R,-alfa,lcd->Q[it]);
CHKERRQ(ierr);
ierr = VecNorm(R,NORM_2,&rnorm);
CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);
CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,rnorm);
CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,rnorm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
if (ksp->reason) break;
ierr = VecCopy(R,lcd->P[it+1]);
CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,lcd->P[it+1],Z);
CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,Z,lcd->Q[it+1]);
CHKERRQ(ierr);
for (j = 0; j <= it; j++) {
ierr = VecDot(lcd->P[j],lcd->Q[it+1],&num);
CHKERRQ(ierr);
ierr = VecDot(lcd->P[j],lcd->Q[j],&den);
CHKERRQ(ierr);
beta = -num/den;
ierr = VecAXPY(lcd->P[it+1],beta,lcd->P[j]);
CHKERRQ(ierr);
ierr = VecAXPY(lcd->Q[it+1],beta,lcd->Q[j]);
CHKERRQ(ierr);
}
it++;
}
ierr = VecCopy(lcd->P[it],lcd->P[0]);
CHKERRQ(ierr);
}
if (ksp->its >= ksp->max_it && !ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
ierr = VecCopy(X,ksp->vec_sol);
CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_GROPPCG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscScalar alpha,beta = 0.0,gamma,gammaNew,t;
PetscReal dp = 0.0;
Vec x,b,r,p,s,S,z,Z;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
x = ksp->vec_sol;
b = ksp->vec_rhs;
r = ksp->work[0];
p = ksp->work[1];
s = ksp->work[2];
S = ksp->work[3];
z = ksp->work[4];
Z = ksp->work[5];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,x,r);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
} else {
ierr = VecCopy(b,r);CHKERRQ(ierr); /* r <- b (x is 0) */
}
ierr = KSP_PCApply(ksp,r,z);CHKERRQ(ierr); /* z <- Br */
ierr = VecCopy(z,p);CHKERRQ(ierr); /* p <- z */
ierr = VecDotBegin(r,z,&gamma);CHKERRQ(ierr); /* gamma <- z'*r */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)r));CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,p,s);CHKERRQ(ierr); /* s <- Ap */
ierr = VecDotEnd(r,z,&gamma);CHKERRQ(ierr); /* gamma <- z'*r */
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
/* This could be merged with the computation of gamma above */
ierr = VecNorm(z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z = e'*A'*B'*B*A'*e' */
break;
case KSP_NORM_UNPRECONDITIONED:
/* This could be merged with the computation of gamma above */
ierr = VecNorm(r,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r = e'*A'*A*e */
break;
case KSP_NORM_NATURAL:
if (PetscIsInfOrNanScalar(gamma)) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_FP,"Infinite or not-a-number generated in dot product");
dp = PetscSqrtReal(PetscAbsScalar(gamma)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
i = 0;
do {
ksp->its = i+1;
i++;
ierr = VecDotBegin(p,s,&t);CHKERRQ(ierr);
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)p));CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,s,S);CHKERRQ(ierr); /* S <- Bs */
ierr = VecDotEnd(p,s,&t);CHKERRQ(ierr);
alpha = gamma / t;
ierr = VecAXPY(x, alpha,p);CHKERRQ(ierr); /* x <- x + alpha * p */
ierr = VecAXPY(r,-alpha,s);CHKERRQ(ierr); /* r <- r - alpha * s */
ierr = VecAXPY(z,-alpha,S);CHKERRQ(ierr); /* z <- z - alpha * S */
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNormBegin(r,NORM_2,&dp);CHKERRQ(ierr);
} else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormBegin(z,NORM_2,&dp);CHKERRQ(ierr);
}
ierr = VecDotBegin(r,z,&gammaNew);CHKERRQ(ierr);
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)r));CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,z,Z);CHKERRQ(ierr); /* Z <- Az */
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNormEnd(r,NORM_2,&dp);CHKERRQ(ierr);
} else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormEnd(z,NORM_2,&dp);CHKERRQ(ierr);
}
ierr = VecDotEnd(r,z,&gammaNew);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_NATURAL) {
if (PetscIsInfOrNanScalar(gammaNew)) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_FP,"Infinite or not-a-number generated in dot product");
dp = PetscSqrtReal(PetscAbsScalar(gammaNew)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
} else if (ksp->normtype == KSP_NORM_NONE) {
dp = 0.0;
}
ksp->rnorm = dp;
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
beta = gammaNew / gamma;
gamma = gammaNew;
ierr = VecAYPX(p,beta,z);CHKERRQ(ierr); /* p <- z + beta * p */
ierr = VecAYPX(s,beta,Z);CHKERRQ(ierr); /* s <- Z + beta * s */
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_GCR_cycle(KSP ksp)
{
KSP_GCR *ctx = (KSP_GCR*)ksp->data;
PetscErrorCode ierr;
PetscScalar r_dot_v;
Mat A, B;
PC pc;
Vec s,v,r;
/*
The residual norm will not be computed when ksp->its > ksp->chknorm hence need to initialize norm_r with some dummy value
*/
PetscReal norm_r = 0.0,nrm;
PetscInt k, i, restart;
Vec x;
PetscFunctionBegin;
restart = ctx->restart;
ierr = KSPGetPC(ksp, &pc);CHKERRQ(ierr);
ierr = KSPGetOperators(ksp, &A, &B);CHKERRQ(ierr);
x = ksp->vec_sol;
r = ctx->R;
for (k=0; k<restart; k++) {
v = ctx->VV[k];
s = ctx->SS[k];
if (ctx->modifypc) {
ierr = (*ctx->modifypc)(ksp,ksp->its,ksp->rnorm,ctx->modifypc_ctx);CHKERRQ(ierr);
}
ierr = KSP_PCApply(ksp, r, s);CHKERRQ(ierr); /* s = B^{-1} r */
ierr = KSP_MatMult(ksp,A, s, v);CHKERRQ(ierr); /* v = A s */
ierr = VecMDot(v,k, ctx->VV, ctx->val);CHKERRQ(ierr);
for (i=0; i<k; i++) ctx->val[i] = -ctx->val[i];
ierr = VecMAXPY(v,k,ctx->val,ctx->VV);CHKERRQ(ierr); /* v = v - sum_{i=0}^{k-1} alpha_i v_i */
ierr = VecMAXPY(s,k,ctx->val,ctx->SS);CHKERRQ(ierr); /* s = s - sum_{i=0}^{k-1} alpha_i s_i */
ierr = VecDotNorm2(r,v,&r_dot_v,&nrm);CHKERRQ(ierr);
nrm = PetscSqrtReal(nrm);
r_dot_v = r_dot_v/nrm;
ierr = VecScale(v, 1.0/nrm);CHKERRQ(ierr);
ierr = VecScale(s, 1.0/nrm);CHKERRQ(ierr);
ierr = VecAXPY(x, r_dot_v, s);CHKERRQ(ierr);
ierr = VecAXPY(r, -r_dot_v, v);CHKERRQ(ierr);
if (ksp->its > ksp->chknorm) {
ierr = VecNorm(r, NORM_2, &norm_r);CHKERRQ(ierr);
KSPCheckNorm(ksp,norm_r);
}
/* update the local counter and the global counter */
ksp->its++;
ksp->rnorm = norm_r;
ierr = KSPLogResidualHistory(ksp,norm_r);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,norm_r);CHKERRQ(ierr);
if (ksp->its-1 > ksp->chknorm) {
ierr = (*ksp->converged)(ksp,ksp->its,norm_r,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
if (ksp->its >= ksp->max_it) {
ksp->reason = KSP_CONVERGED_ITS;
break;
}
}
ctx->n_restarts++;
PetscFunctionReturn(0);
}
PetscErrorCode MyKSPFGMRESCycle(PetscInt *itcount,KSP ksp)
{
KSP_FGMRES *fgmres = (KSP_FGMRES*)(ksp->data);
PetscReal res_norm;
PetscReal hapbnd,tt;
PetscBool hapend = PETSC_FALSE; /* indicates happy breakdown ending */
PetscErrorCode ierr;
PetscInt loc_it; /* local count of # of dir. in Krylov space */
PetscInt max_k = fgmres->max_k; /* max # of directions Krylov space */
Mat Amat,Pmat;
PetscFunctionBegin;
/* Number of pseudo iterations since last restart is the number
of prestart directions */
loc_it = 0;
/* note: (fgmres->it) is always set one less than (loc_it) It is used in
KSPBUILDSolution_FGMRES, where it is passed to KSPFGMRESBuildSoln.
Note that when KSPFGMRESBuildSoln is called from this function,
(loc_it -1) is passed, so the two are equivalent */
fgmres->it = (loc_it - 1);
/* initial residual is in VEC_VV(0) - compute its norm*/
ierr = VecNorm(VEC_VV(0),NORM_2,&res_norm);CHKERRQ(ierr);
/* first entry in right-hand-side of hessenberg system is just
the initial residual norm */
*RS(0) = res_norm;
ksp->rnorm = res_norm;
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
/* check for the convergence - maybe the current guess is good enough */
ierr = (*ksp->converged)(ksp,ksp->its,res_norm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) {
if (itcount) *itcount = 0;
PetscFunctionReturn(0);
}
/* scale VEC_VV (the initial residual) */
ierr = VecScale(VEC_VV(0),1.0/res_norm);CHKERRQ(ierr);
/* MAIN ITERATION LOOP BEGINNING*/
/* keep iterating until we have converged OR generated the max number
of directions OR reached the max number of iterations for the method */
while (!ksp->reason && loc_it < max_k && ksp->its < ksp->max_it) {
if (loc_it) {
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
}
fgmres->it = (loc_it - 1);
/* see if more space is needed for work vectors */
if (fgmres->vv_allocated <= loc_it + VEC_OFFSET + 1) {
ierr = MyKSPFGMRESGetNewVectors(ksp,loc_it+1);CHKERRQ(ierr);
/* (loc_it+1) is passed in as number of the first vector that should
be allocated */
}
/* CHANGE THE PRECONDITIONER? */
/* ModifyPC is the callback function that can be used to
change the PC or its attributes before its applied */
(*fgmres->modifypc)(ksp,ksp->its,loc_it,res_norm,fgmres->modifyctx);
/* apply PRECONDITIONER to direction vector and store with
preconditioned vectors in prevec */
ierr = KSP_PCApply(ksp,VEC_VV(loc_it),PREVEC(loc_it));CHKERRQ(ierr);
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
/* Multiply preconditioned vector by operator - put in VEC_VV(loc_it+1) */
ierr = KSP_MatMult(ksp,Amat,PREVEC(loc_it),VEC_VV(1+loc_it));CHKERRQ(ierr);
/* update hessenberg matrix and do Gram-Schmidt - new direction is in
VEC_VV(1+loc_it)*/
ierr = (*fgmres->orthog)(ksp,loc_it);CHKERRQ(ierr);
/* new entry in hessenburg is the 2-norm of our new direction */
ierr = VecNorm(VEC_VV(loc_it+1),NORM_2,&tt);CHKERRQ(ierr);
*HH(loc_it+1,loc_it) = tt;
*HES(loc_it+1,loc_it) = tt;
/* Happy Breakdown Check */
hapbnd = PetscAbsScalar((tt) / *RS(loc_it));
/* RS(loc_it) contains the res_norm from the last iteration */
hapbnd = PetscMin(fgmres->haptol,hapbnd);
if (tt > hapbnd) {
/* scale new direction by its norm */
ierr = VecScale(VEC_VV(loc_it+1),1.0/tt);CHKERRQ(ierr);
} else {
/* This happens when the solution is exactly reached. */
/* So there is no new direction... */
ierr = VecSet(VEC_TEMP,0.0);CHKERRQ(ierr); /* set VEC_TEMP to 0 */
hapend = PETSC_TRUE;
}
/* note that for FGMRES we could get HES(loc_it+1, loc_it) = 0 and the
current solution would not be exact if HES was singular. Note that
HH non-singular implies that HES is no singular, and HES is guaranteed
to be nonsingular when PREVECS are linearly independent and A is
nonsingular (in GMRES, the nonsingularity of A implies the nonsingularity
of HES). So we should really add a check to verify that HES is nonsingular.*/
/* Now apply rotations to new col of hessenberg (and right side of system),
calculate new rotation, and get new residual norm at the same time*/
ierr = MyKSPFGMRESUpdateHessenberg(ksp,loc_it,hapend,&res_norm);CHKERRQ(ierr);
if (ksp->reason) break;
loc_it++;
fgmres->it = (loc_it-1); /* Add this here in case it has converged */
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = res_norm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,res_norm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
/* Catch error in happy breakdown and signal convergence and break from loop */
if (hapend) {
if (!ksp->reason) {
if (ksp->errorifnotconverged) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"You reached the happy break down, but convergence was not indicated. Residual norm = %g",(double)res_norm);
else {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
}
}
}
/* END OF ITERATION LOOP */
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
/*
Monitor if we know that we will not return for a restart */
if (loc_it && (ksp->reason || ksp->its >= ksp->max_it)) {
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
}
if (itcount) *itcount = loc_it;
/*
Down here we have to solve for the "best" coefficients of the Krylov
columns, add the solution values together, and possibly unwind the
preconditioning from the solution
*/
/* Form the solution (or the solution so far) */
/* Note: must pass in (loc_it-1) for iteration count so that KSPFGMRESBuildSoln
properly navigates */
ierr = MyKSPFGMRESBuildSoln(RS(0),ksp->vec_sol,ksp->vec_sol,ksp,loc_it-1);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_STCG(KSP ksp)
{
#if defined(PETSC_USE_COMPLEX)
SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP, "STCG is not available for complex systems");
#else
KSP_STCG *cg = (KSP_STCG*)ksp->data;
PetscErrorCode ierr;
MatStructure pflag;
Mat Qmat, Mmat;
Vec r, z, p, d;
PC pc;
PetscReal norm_r, norm_d, norm_dp1, norm_p, dMp;
PetscReal alpha, beta, kappa, rz, rzm1;
PetscReal rr, r2, step;
PetscInt max_cg_its;
PetscBool diagonalscale;
/***************************************************************************/
/* Check the arguments and parameters. */
/***************************************************************************/
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc, &diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP, "Krylov method %s does not support diagonal scaling", ((PetscObject)ksp)->type_name);
if (cg->radius < 0.0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE, "Input error: radius < 0");
/***************************************************************************/
/* Get the workspace vectors and initialize variables */
/***************************************************************************/
r2 = cg->radius * cg->radius;
r = ksp->work[0];
z = ksp->work[1];
p = ksp->work[2];
d = ksp->vec_sol;
pc = ksp->pc;
ierr = PCGetOperators(pc, &Qmat, &Mmat, &pflag);CHKERRQ(ierr);
ierr = VecGetSize(d, &max_cg_its);CHKERRQ(ierr);
max_cg_its = PetscMin(max_cg_its, ksp->max_it);
ksp->its = 0;
/***************************************************************************/
/* Initialize objective function and direction. */
/***************************************************************************/
cg->o_fcn = 0.0;
ierr = VecSet(d, 0.0);CHKERRQ(ierr); /* d = 0 */
cg->norm_d = 0.0;
/***************************************************************************/
/* Begin the conjugate gradient method. Check the right-hand side for */
/* numerical problems. The check for not-a-number and infinite values */
/* need be performed only once. */
/***************************************************************************/
ierr = VecCopy(ksp->vec_rhs, r);CHKERRQ(ierr); /* r = -grad */
ierr = VecDot(r, r, &rr);CHKERRQ(ierr); /* rr = r^T r */
if (PetscIsInfOrNanScalar(rr)) {
/*************************************************************************/
/* The right-hand side contains not-a-number or an infinite value. */
/* The gradient step does not work; return a zero value for the step. */
/*************************************************************************/
ksp->reason = KSP_DIVERGED_NANORINF;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: bad right-hand side: rr=%g\n", rr);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/***************************************************************************/
/* Check the preconditioner for numerical problems and for positive */
/* definiteness. The check for not-a-number and infinite values need be */
/* performed only once. */
/***************************************************************************/
ierr = KSP_PCApply(ksp, r, z);CHKERRQ(ierr); /* z = inv(M) r */
ierr = VecDot(r, z, &rz);CHKERRQ(ierr); /* rz = r^T inv(M) r */
if (PetscIsInfOrNanScalar(rz)) {
/*************************************************************************/
/* The preconditioner contains not-a-number or an infinite value. */
/* Return the gradient direction intersected with the trust region. */
/*************************************************************************/
ksp->reason = KSP_DIVERGED_NANORINF;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: bad preconditioner: rz=%g\n", rz);CHKERRQ(ierr);
if (cg->radius != 0) {
if (r2 >= rr) {
alpha = 1.0;
cg->norm_d = PetscSqrtReal(rr);
} else {
alpha = PetscSqrtReal(r2 / rr);
cg->norm_d = cg->radius;
}
ierr = VecAXPY(d, alpha, r);CHKERRQ(ierr); /* d = d + alpha r */
/***********************************************************************/
/* Compute objective function. */
/***********************************************************************/
ierr = KSP_MatMult(ksp, Qmat, d, z);CHKERRQ(ierr);
ierr = VecAYPX(z, -0.5, ksp->vec_rhs);CHKERRQ(ierr);
ierr = VecDot(d, z, &cg->o_fcn);CHKERRQ(ierr);
cg->o_fcn = -cg->o_fcn;
++ksp->its;
}
PetscFunctionReturn(0);
}
if (rz < 0.0) {
/*************************************************************************/
/* The preconditioner is indefinite. Because this is the first */
/* and we do not have a direction yet, we use the gradient step. Note */
/* that we cannot use the preconditioned norm when computing the step */
/* because the matrix is indefinite. */
/*************************************************************************/
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: indefinite preconditioner: rz=%g\n", rz);CHKERRQ(ierr);
if (cg->radius != 0.0) {
if (r2 >= rr) {
alpha = 1.0;
cg->norm_d = PetscSqrtReal(rr);
} else {
alpha = PetscSqrtReal(r2 / rr);
cg->norm_d = cg->radius;
}
ierr = VecAXPY(d, alpha, r);CHKERRQ(ierr); /* d = d + alpha r */
/***********************************************************************/
/* Compute objective function. */
/***********************************************************************/
ierr = KSP_MatMult(ksp, Qmat, d, z);CHKERRQ(ierr);
ierr = VecAYPX(z, -0.5, ksp->vec_rhs);CHKERRQ(ierr);
ierr = VecDot(d, z, &cg->o_fcn);CHKERRQ(ierr);
cg->o_fcn = -cg->o_fcn;
++ksp->its;
}
PetscFunctionReturn(0);
}
/***************************************************************************/
/* As far as we know, the preconditioner is positive semidefinite. */
/* Compute and log the residual. Check convergence because this */
/* initializes things, but do not terminate until at least one conjugate */
/* gradient iteration has been performed. */
/***************************************************************************/
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = VecNorm(z, NORM_2, &norm_r);CHKERRQ(ierr); /* norm_r = |z| */
break;
case KSP_NORM_UNPRECONDITIONED:
norm_r = PetscSqrtReal(rr); /* norm_r = |r| */
break;
case KSP_NORM_NATURAL:
norm_r = PetscSqrtReal(rz); /* norm_r = |r|_M */
break;
default:
norm_r = 0.0;
break;
}
ierr = KSPLogResidualHistory(ksp, norm_r);CHKERRQ(ierr);
ierr = KSPMonitor(ksp, ksp->its, norm_r);CHKERRQ(ierr);
ksp->rnorm = norm_r;
ierr = (*ksp->converged)(ksp, ksp->its, norm_r, &ksp->reason, ksp->cnvP);CHKERRQ(ierr);
/***************************************************************************/
/* Compute the first direction and update the iteration. */
/***************************************************************************/
ierr = VecCopy(z, p);CHKERRQ(ierr); /* p = z */
ierr = KSP_MatMult(ksp, Qmat, p, z);CHKERRQ(ierr); /* z = Q * p */
++ksp->its;
/***************************************************************************/
/* Check the matrix for numerical problems. */
/***************************************************************************/
ierr = VecDot(p, z, &kappa);CHKERRQ(ierr); /* kappa = p^T Q p */
if (PetscIsInfOrNanScalar(kappa)) {
/*************************************************************************/
/* The matrix produced not-a-number or an infinite value. In this case, */
/* we must stop and use the gradient direction. This condition need */
/* only be checked once. */
/*************************************************************************/
ksp->reason = KSP_DIVERGED_NANORINF;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: bad matrix: kappa=%g\n", kappa);CHKERRQ(ierr);
if (cg->radius) {
if (r2 >= rr) {
alpha = 1.0;
cg->norm_d = PetscSqrtReal(rr);
} else {
alpha = PetscSqrtReal(r2 / rr);
cg->norm_d = cg->radius;
}
ierr = VecAXPY(d, alpha, r);CHKERRQ(ierr); /* d = d + alpha r */
/***********************************************************************/
/* Compute objective function. */
/***********************************************************************/
ierr = KSP_MatMult(ksp, Qmat, d, z);CHKERRQ(ierr);
ierr = VecAYPX(z, -0.5, ksp->vec_rhs);CHKERRQ(ierr);
ierr = VecDot(d, z, &cg->o_fcn);CHKERRQ(ierr);
cg->o_fcn = -cg->o_fcn;
++ksp->its;
}
PetscFunctionReturn(0);
}
/***************************************************************************/
/* Initialize variables for calculating the norm of the direction. */
/***************************************************************************/
dMp = 0.0;
norm_d = 0.0;
switch (cg->dtype) {
case STCG_PRECONDITIONED_DIRECTION:
norm_p = rz;
break;
default:
ierr = VecDot(p, p, &norm_p);CHKERRQ(ierr);
break;
}
/***************************************************************************/
/* Check for negative curvature. */
/***************************************************************************/
if (kappa <= 0.0) {
/*************************************************************************/
/* In this case, the matrix is indefinite and we have encountered a */
/* direction of negative curvature. Because negative curvature occurs */
/* during the first step, we must follow a direction. */
/*************************************************************************/
ksp->reason = KSP_CONVERGED_CG_NEG_CURVE;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: negative curvature: kappa=%g\n", kappa);CHKERRQ(ierr);
if (cg->radius != 0.0 && norm_p > 0.0) {
/***********************************************************************/
/* Follow direction of negative curvature to the boundary of the */
/* trust region. */
/***********************************************************************/
step = PetscSqrtReal(r2 / norm_p);
cg->norm_d = cg->radius;
ierr = VecAXPY(d, step, p);CHKERRQ(ierr); /* d = d + step p */
/***********************************************************************/
/* Update objective function. */
/***********************************************************************/
cg->o_fcn += step * (0.5 * step * kappa - rz);
} else if (cg->radius != 0.0) {
/***********************************************************************/
/* The norm of the preconditioned direction is zero; use the gradient */
/* step. */
/***********************************************************************/
if (r2 >= rr) {
alpha = 1.0;
cg->norm_d = PetscSqrtReal(rr);
} else {
alpha = PetscSqrtReal(r2 / rr);
cg->norm_d = cg->radius;
}
ierr = VecAXPY(d, alpha, r);CHKERRQ(ierr); /* d = d + alpha r */
/***********************************************************************/
/* Compute objective function. */
/***********************************************************************/
ierr = KSP_MatMult(ksp, Qmat, d, z);CHKERRQ(ierr);
ierr = VecAYPX(z, -0.5, ksp->vec_rhs);CHKERRQ(ierr);
ierr = VecDot(d, z, &cg->o_fcn);CHKERRQ(ierr);
cg->o_fcn = -cg->o_fcn;
++ksp->its;
}
PetscFunctionReturn(0);
}
/***************************************************************************/
/* Run the conjugate gradient method until either the problem is solved, */
/* we encounter the boundary of the trust region, or the conjugate */
/* gradient method breaks down. */
/***************************************************************************/
while (1) {
/*************************************************************************/
/* Know that kappa is nonzero, because we have not broken down, so we */
/* can compute the steplength. */
/*************************************************************************/
alpha = rz / kappa;
/*************************************************************************/
/* Compute the steplength and check for intersection with the trust */
/* region. */
/*************************************************************************/
norm_dp1 = norm_d + alpha*(2.0*dMp + alpha*norm_p);
if (cg->radius != 0.0 && norm_dp1 >= r2) {
/***********************************************************************/
/* In this case, the matrix is positive definite as far as we know. */
/* However, the full step goes beyond the trust region. */
/***********************************************************************/
ksp->reason = KSP_CONVERGED_CG_CONSTRAINED;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: constrained step: radius=%g\n", cg->radius);CHKERRQ(ierr);
if (norm_p > 0.0) {
/*********************************************************************/
/* Follow the direction to the boundary of the trust region. */
/*********************************************************************/
step = (PetscSqrtReal(dMp*dMp+norm_p*(r2-norm_d))-dMp)/norm_p;
cg->norm_d = cg->radius;
ierr = VecAXPY(d, step, p);CHKERRQ(ierr); /* d = d + step p */
/*********************************************************************/
/* Update objective function. */
/*********************************************************************/
cg->o_fcn += step * (0.5 * step * kappa - rz);
} else {
/*********************************************************************/
/* The norm of the direction is zero; there is nothing to follow. */
/*********************************************************************/
}
break;
}
/*************************************************************************/
/* Now we can update the direction and residual. */
/*************************************************************************/
ierr = VecAXPY(d, alpha, p);CHKERRQ(ierr); /* d = d + alpha p */
ierr = VecAXPY(r, -alpha, z);CHKERRQ(ierr); /* r = r - alpha Q p */
ierr = KSP_PCApply(ksp, r, z);CHKERRQ(ierr); /* z = inv(M) r */
switch (cg->dtype) {
case STCG_PRECONDITIONED_DIRECTION:
norm_d = norm_dp1;
break;
default:
ierr = VecDot(d, d, &norm_d);CHKERRQ(ierr);
break;
}
cg->norm_d = PetscSqrtReal(norm_d);
/*************************************************************************/
/* Update objective function. */
/*************************************************************************/
cg->o_fcn -= 0.5 * alpha * rz;
/*************************************************************************/
/* Check that the preconditioner appears positive semidefinite. */
/*************************************************************************/
rzm1 = rz;
ierr = VecDot(r, z, &rz);CHKERRQ(ierr); /* rz = r^T z */
if (rz < 0.0) {
/***********************************************************************/
/* The preconditioner is indefinite. */
/***********************************************************************/
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: cg indefinite preconditioner: rz=%g\n", rz);CHKERRQ(ierr);
break;
}
/*************************************************************************/
/* As far as we know, the preconditioner is positive semidefinite. */
/* Compute the residual and check for convergence. */
/*************************************************************************/
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = VecNorm(z, NORM_2, &norm_r);CHKERRQ(ierr); /* norm_r = |z| */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(r, NORM_2, &norm_r);CHKERRQ(ierr); /* norm_r = |r| */
break;
case KSP_NORM_NATURAL:
norm_r = PetscSqrtReal(rz); /* norm_r = |r|_M */
break;
default:
norm_r = 0.0;
break;
}
ierr = KSPLogResidualHistory(ksp, norm_r);CHKERRQ(ierr);
ierr = KSPMonitor(ksp, ksp->its, norm_r);CHKERRQ(ierr);
ksp->rnorm = norm_r;
ierr = (*ksp->converged)(ksp, ksp->its, norm_r, &ksp->reason, ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) {
/***********************************************************************/
/* The method has converged. */
/***********************************************************************/
ierr = PetscInfo2(ksp, "KSPSolve_STCG: truncated step: rnorm=%g, radius=%g\n", norm_r, cg->radius);CHKERRQ(ierr);
break;
}
/*************************************************************************/
/* We have not converged yet. Check for breakdown. */
/*************************************************************************/
beta = rz / rzm1;
if (fabs(beta) <= 0.0) {
/***********************************************************************/
/* Conjugate gradients has broken down. */
/***********************************************************************/
ksp->reason = KSP_DIVERGED_BREAKDOWN;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: breakdown: beta=%g\n", beta);CHKERRQ(ierr);
break;
}
/*************************************************************************/
/* Check iteration limit. */
/*************************************************************************/
if (ksp->its >= max_cg_its) {
ksp->reason = KSP_DIVERGED_ITS;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: iterlim: its=%d\n", ksp->its);CHKERRQ(ierr);
break;
}
/*************************************************************************/
/* Update p and the norms. */
/*************************************************************************/
ierr = VecAYPX(p, beta, z);CHKERRQ(ierr); /* p = z + beta p */
switch (cg->dtype) {
case STCG_PRECONDITIONED_DIRECTION:
dMp = beta*(dMp + alpha*norm_p);
norm_p = beta*(rzm1 + beta*norm_p);
break;
default:
ierr = VecDot(d, p, &dMp);CHKERRQ(ierr);
ierr = VecDot(p, p, &norm_p);CHKERRQ(ierr);
break;
}
/*************************************************************************/
/* Compute the new direction and update the iteration. */
/*************************************************************************/
ierr = KSP_MatMult(ksp, Qmat, p, z);CHKERRQ(ierr); /* z = Q * p */
ierr = VecDot(p, z, &kappa);CHKERRQ(ierr); /* kappa = p^T Q p */
++ksp->its;
/*************************************************************************/
/* Check for negative curvature. */
/*************************************************************************/
if (kappa <= 0.0) {
/***********************************************************************/
/* In this case, the matrix is indefinite and we have encountered */
/* a direction of negative curvature. Follow the direction to the */
/* boundary of the trust region. */
/***********************************************************************/
ksp->reason = KSP_CONVERGED_CG_NEG_CURVE;
ierr = PetscInfo1(ksp, "KSPSolve_STCG: negative curvature: kappa=%g\n", kappa);CHKERRQ(ierr);
if (cg->radius != 0.0 && norm_p > 0.0) {
/*********************************************************************/
/* Follow direction of negative curvature to boundary. */
/*********************************************************************/
step = (PetscSqrtReal(dMp*dMp+norm_p*(r2-norm_d))-dMp)/norm_p;
cg->norm_d = cg->radius;
ierr = VecAXPY(d, step, p);CHKERRQ(ierr); /* d = d + step p */
/*********************************************************************/
/* Update objective function. */
/*********************************************************************/
cg->o_fcn += step * (0.5 * step * kappa - rz);
} else if (cg->radius != 0.0) {
/*********************************************************************/
/* The norm of the direction is zero; there is nothing to follow. */
/*********************************************************************/
}
break;
}
}
PetscFunctionReturn(0);
#endif
}
static PetscErrorCode KSPSolve_FBCGSR(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,j,N;
PetscScalar tau,sigma,alpha,omega,beta;
PetscReal rho;
PetscScalar xi1,xi2,xi3,xi4;
Vec X,B,P,P2,RP,R,V,S,T,S2;
PetscScalar *PETSC_RESTRICT rp, *PETSC_RESTRICT r, *PETSC_RESTRICT p;
PetscScalar *PETSC_RESTRICT v, *PETSC_RESTRICT s, *PETSC_RESTRICT t, *PETSC_RESTRICT s2;
PetscScalar insums[4],outsums[4];
KSP_BCGS *bcgs = (KSP_BCGS*)ksp->data;
PC pc;
Mat mat;
PetscFunctionBegin;
if (!ksp->vec_rhs->petscnative) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Only coded for PETSc vectors");
ierr = VecGetLocalSize(ksp->vec_sol,&N);CHKERRQ(ierr);
X = ksp->vec_sol;
B = ksp->vec_rhs;
P2 = ksp->work[0];
/* The followings are involved in modified inner product calculations and vector updates */
RP = ksp->work[1]; ierr = VecGetArray(RP,(PetscScalar**)&rp);CHKERRQ(ierr); ierr = VecRestoreArray(RP,NULL);CHKERRQ(ierr);
R = ksp->work[2]; ierr = VecGetArray(R,(PetscScalar**)&r);CHKERRQ(ierr); ierr = VecRestoreArray(R,NULL);CHKERRQ(ierr);
P = ksp->work[3]; ierr = VecGetArray(P,(PetscScalar**)&p);CHKERRQ(ierr); ierr = VecRestoreArray(P,NULL);CHKERRQ(ierr);
V = ksp->work[4]; ierr = VecGetArray(V,(PetscScalar**)&v);CHKERRQ(ierr); ierr = VecRestoreArray(V,NULL);CHKERRQ(ierr);
S = ksp->work[5]; ierr = VecGetArray(S,(PetscScalar**)&s);CHKERRQ(ierr); ierr = VecRestoreArray(S,NULL);CHKERRQ(ierr);
T = ksp->work[6]; ierr = VecGetArray(T,(PetscScalar**)&t);CHKERRQ(ierr); ierr = VecRestoreArray(T,NULL);CHKERRQ(ierr);
S2 = ksp->work[7]; ierr = VecGetArray(S2,(PetscScalar**)&s2);CHKERRQ(ierr); ierr = VecRestoreArray(S2,NULL);CHKERRQ(ierr);
/* Only supports right preconditioning */
if (ksp->pc_side != PC_RIGHT) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"KSP fbcgsr does not support %s",PCSides[ksp->pc_side]);
if (!ksp->guess_zero) {
if (!bcgs->guess) {
ierr = VecDuplicate(X,&bcgs->guess);CHKERRQ(ierr);
}
ierr = VecCopy(X,bcgs->guess);CHKERRQ(ierr);
} else {
ierr = VecSet(X,0.0);CHKERRQ(ierr);
}
/* Compute initial residual */
ierr = KSPGetPC(ksp,&pc);CHKERRQ(ierr);
ierr = PCSetUp(pc);CHKERRQ(ierr);
ierr = PCGetOperators(pc,&mat,NULL);CHKERRQ(ierr);
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,mat,X,P2);CHKERRQ(ierr); /* P2 is used as temporary storage */
ierr = VecCopy(B,R);CHKERRQ(ierr);
ierr = VecAXPY(R,-1.0,P2);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr);
}
/* Test for nothing to do */
ierr = VecNorm(R,NORM_2,&rho);CHKERRQ(ierr);
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ksp->rnorm = rho;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rho);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,rho);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,rho,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
/* Initialize iterates */
ierr = VecCopy(R,RP);CHKERRQ(ierr); /* rp <- r */
ierr = VecCopy(R,P);CHKERRQ(ierr); /* p <- r */
/* Big loop */
for (i=0; i<ksp->max_it; i++) {
/* matmult and pc */
ierr = KSP_PCApply(ksp,P,P2);CHKERRQ(ierr); /* p2 <- K p */
ierr = KSP_MatMult(ksp,mat,P2,V);CHKERRQ(ierr); /* v <- A p2 */
/* inner prodcuts */
if (i==0) {
tau = rho*rho;
ierr = VecDot(V,RP,&sigma);CHKERRQ(ierr); /* sigma <- (v,rp) */
} else {
ierr = PetscLogEventBegin(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
tau = sigma = 0.0;
for (j=0; j<N; j++) {
tau += r[j]*rp[j]; /* tau <- (r,rp) */
sigma += v[j]*rp[j]; /* sigma <- (v,rp) */
}
ierr = PetscLogFlops(4.0*N);CHKERRQ(ierr);
ierr = PetscLogEventEnd(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
insums[0] = tau;
insums[1] = sigma;
ierr = PetscLogEventBegin(VEC_ReduceCommunication,0,0,0,0);CHKERRQ(ierr);
ierr = MPIU_Allreduce(insums,outsums,2,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)ksp));CHKERRQ(ierr);
ierr = PetscLogEventEnd(VEC_ReduceCommunication,0,0,0,0);CHKERRQ(ierr);
tau = outsums[0];
sigma = outsums[1];
}
/* scalar update */
alpha = tau / sigma;
/* vector update */
ierr = VecWAXPY(S,-alpha,V,R);CHKERRQ(ierr); /* s <- r - alpha v */
/* matmult and pc */
ierr = KSP_PCApply(ksp,S,S2);CHKERRQ(ierr); /* s2 <- K s */
ierr = KSP_MatMult(ksp,mat,S2,T);CHKERRQ(ierr); /* t <- A s2 */
/* inner prodcuts */
ierr = PetscLogEventBegin(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
xi1 = xi2 = xi3 = xi4 = 0.0;
for (j=0; j<N; j++) {
xi1 += s[j]*s[j]; /* xi1 <- (s,s) */
xi2 += t[j]*s[j]; /* xi2 <- (t,s) */
xi3 += t[j]*t[j]; /* xi3 <- (t,t) */
xi4 += t[j]*rp[j]; /* xi4 <- (t,rp) */
}
ierr = PetscLogFlops(8.0*N);CHKERRQ(ierr);
ierr = PetscLogEventEnd(VEC_ReduceArithmetic,0,0,0,0);CHKERRQ(ierr);
insums[0] = xi1;
insums[1] = xi2;
insums[2] = xi3;
insums[3] = xi4;
ierr = PetscLogEventBegin(VEC_ReduceCommunication,0,0,0,0);CHKERRQ(ierr);
ierr = MPIU_Allreduce(insums,outsums,4,MPIU_SCALAR,MPIU_SUM,PetscObjectComm((PetscObject)ksp));CHKERRQ(ierr);
ierr = PetscLogEventEnd(VEC_ReduceCommunication,0,0,0,0);CHKERRQ(ierr);
xi1 = outsums[0];
xi2 = outsums[1];
xi3 = outsums[2];
xi4 = outsums[3];
/* test denominator */
if (xi3 == 0.0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Divide by zero");
if (sigma == 0.0) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Divide by zero");
/* scalar updates */
omega = xi2 / xi3;
beta = -xi4 / sigma;
rho = PetscSqrtReal(PetscAbsScalar(xi1 - omega * xi2)); /* residual norm */
/* vector updates */
ierr = VecAXPBYPCZ(X,alpha,omega,1.0,P2,S2);CHKERRQ(ierr); /* x <- alpha * p2 + omega * s2 + x */
/* convergence test */
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = rho;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rho);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,rho);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,rho,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
/* vector updates */
ierr = PetscLogEventBegin(VEC_Ops,0,0,0,0);CHKERRQ(ierr);
for (j=0; j<N; j++) {
r[j] = s[j] - omega * t[j]; /* r <- s - omega t */
p[j] = r[j] + beta * (p[j] - omega * v[j]); /* p <- r + beta * (p - omega v) */
}
ierr = PetscLogFlops(6.0*N);CHKERRQ(ierr);
ierr = PetscLogEventEnd(VEC_Ops,0,0,0,0);CHKERRQ(ierr);
}
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_PIPECG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscScalar alpha = 0.0,beta = 0.0,gamma = 0.0,gammaold = 0.0,delta = 0.0;
PetscReal dp = 0.0;
Vec X,B,Z,P,W,Q,U,M,N,R,S;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
X = ksp->vec_sol;
B = ksp->vec_rhs;
M = ksp->work[0];
Z = ksp->work[1];
P = ksp->work[2];
N = ksp->work[3];
W = ksp->work[4];
Q = ksp->work[5];
U = ksp->work[6];
R = ksp->work[7];
S = ksp->work[8];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
ierr = KSP_PCApply(ksp,R,U);CHKERRQ(ierr); /* u <- Br */
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = VecNormBegin(U,NORM_2,&dp);CHKERRQ(ierr); /* dp <- u'*u = e'*A'*B'*B*A'*e' */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)U));CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,U,W);CHKERRQ(ierr); /* w <- Au */
ierr = VecNormEnd(U,NORM_2,&dp);CHKERRQ(ierr);
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNormBegin(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r = e'*A'*A*e */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,U,W);CHKERRQ(ierr); /* w <- Au */
ierr = VecNormEnd(R,NORM_2,&dp);CHKERRQ(ierr);
break;
case KSP_NORM_NATURAL:
ierr = VecDotBegin(R,U,&gamma);CHKERRQ(ierr); /* gamma <- u'*r */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,U,W);CHKERRQ(ierr); /* w <- Au */
ierr = VecDotEnd(R,U,&gamma);CHKERRQ(ierr);
KSPCheckDot(ksp,gamma);
dp = PetscSqrtReal(PetscAbsScalar(gamma)); /* dp <- r'*u = r'*B*r = e'*A'*B*A*e */
break;
case KSP_NORM_NONE:
ierr = KSP_MatMult(ksp,Amat,U,W);CHKERRQ(ierr);
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
i = 0;
do {
if (i > 0 && ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNormBegin(R,NORM_2,&dp);CHKERRQ(ierr);
} else if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormBegin(U,NORM_2,&dp);CHKERRQ(ierr);
}
if (!(i == 0 && ksp->normtype == KSP_NORM_NATURAL)) {
ierr = VecDotBegin(R,U,&gamma);CHKERRQ(ierr);
}
ierr = VecDotBegin(W,U,&delta);CHKERRQ(ierr);
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,W,M);CHKERRQ(ierr); /* m <- Bw */
ierr = KSP_MatMult(ksp,Amat,M,N);CHKERRQ(ierr); /* n <- Am */
if (i > 0 && ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNormEnd(R,NORM_2,&dp);CHKERRQ(ierr);
} else if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormEnd(U,NORM_2,&dp);CHKERRQ(ierr);
}
if (!(i == 0 && ksp->normtype == KSP_NORM_NATURAL)) {
ierr = VecDotEnd(R,U,&gamma);CHKERRQ(ierr);
}
ierr = VecDotEnd(W,U,&delta);CHKERRQ(ierr);
if (i > 0) {
if (ksp->normtype == KSP_NORM_NATURAL) dp = PetscSqrtReal(PetscAbsScalar(gamma));
else if (ksp->normtype == KSP_NORM_NONE) dp = 0.0;
ksp->rnorm = dp;
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
if (i == 0) {
alpha = gamma / delta;
ierr = VecCopy(N,Z);CHKERRQ(ierr); /* z <- n */
ierr = VecCopy(M,Q);CHKERRQ(ierr); /* q <- m */
ierr = VecCopy(U,P);CHKERRQ(ierr); /* p <- u */
ierr = VecCopy(W,S);CHKERRQ(ierr); /* s <- w */
} else {
beta = gamma / gammaold;
alpha = gamma / (delta - beta / alpha * gamma);
ierr = VecAYPX(Z,beta,N);CHKERRQ(ierr); /* z <- n + beta * z */
ierr = VecAYPX(Q,beta,M);CHKERRQ(ierr); /* q <- m + beta * q */
ierr = VecAYPX(P,beta,U);CHKERRQ(ierr); /* p <- u + beta * p */
ierr = VecAYPX(S,beta,W);CHKERRQ(ierr); /* s <- w + beta * s */
}
ierr = VecAXPY(X, alpha,P);CHKERRQ(ierr); /* x <- x + alpha * p */
ierr = VecAXPY(U,-alpha,Q);CHKERRQ(ierr); /* u <- u - alpha * q */
ierr = VecAXPY(W,-alpha,Z);CHKERRQ(ierr); /* w <- w - alpha * z */
ierr = VecAXPY(R,-alpha,S);CHKERRQ(ierr); /* r <- r - alpha * s */
gammaold = gamma;
i++;
ksp->its = i;
/* if (i%50 == 0) { */
/* ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /\* w <- b - Ax *\/ */
/* ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr); */
/* ierr = KSP_PCApply(ksp,R,U);CHKERRQ(ierr); */
/* ierr = KSP_MatMult(ksp,Amat,U,W);CHKERRQ(ierr); */
/* } */
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_QCG(KSP ksp)
{
/*
Correpondence with documentation above:
B = g = gradient,
X = s = step
Note: This is not coded correctly for complex arithmetic!
*/
KSP_QCG *pcgP = (KSP_QCG*)ksp->data;
Mat Amat,Pmat;
Vec W,WA,WA2,R,P,ASP,BS,X,B;
PetscScalar scal,beta,rntrn,step;
PetscReal q1,q2,xnorm,step1,step2,rnrm,btx,xtax;
PetscReal ptasp,rtr,wtasp,bstp;
PetscReal dzero = 0.0,bsnrm;
PetscErrorCode ierr;
PetscInt i,maxit;
PC pc = ksp->pc;
PCSide side;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
if (ksp->transpose_solve) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Currently does not support transpose solve");
ksp->its = 0;
maxit = ksp->max_it;
WA = ksp->work[0];
R = ksp->work[1];
P = ksp->work[2];
ASP = ksp->work[3];
BS = ksp->work[4];
W = ksp->work[5];
WA2 = ksp->work[6];
X = ksp->vec_sol;
B = ksp->vec_rhs;
if (pcgP->delta <= dzero) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Input error: delta <= 0");
ierr = KSPGetPCSide(ksp,&side);CHKERRQ(ierr);
if (side != PC_SYMMETRIC) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_ARG_OUTOFRANGE,"Requires symmetric preconditioner!");
/* Initialize variables */
ierr = VecSet(W,0.0);CHKERRQ(ierr); /* W = 0 */
ierr = VecSet(X,0.0);CHKERRQ(ierr); /* X = 0 */
ierr = PCGetOperators(pc,&Amat,&Pmat);CHKERRQ(ierr);
/* Compute: BS = D^{-1} B */
ierr = PCApplySymmetricLeft(pc,B,BS);CHKERRQ(ierr);
ierr = VecNorm(BS,NORM_2,&bsnrm);CHKERRQ(ierr);
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ksp->rnorm = bsnrm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,bsnrm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,bsnrm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,bsnrm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
/* Compute the initial scaled direction and scaled residual */
ierr = VecCopy(BS,R);CHKERRQ(ierr);
ierr = VecScale(R,-1.0);CHKERRQ(ierr);
ierr = VecCopy(R,P);CHKERRQ(ierr);
ierr = VecDotRealPart(R,R,&rtr);CHKERRQ(ierr);
for (i=0; i<=maxit; i++) {
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
/* Compute: asp = D^{-T}*A*D^{-1}*p */
ierr = PCApplySymmetricRight(pc,P,WA);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,WA,WA2);CHKERRQ(ierr);
ierr = PCApplySymmetricLeft(pc,WA2,ASP);CHKERRQ(ierr);
/* Check for negative curvature */
ierr = VecDotRealPart(P,ASP,&ptasp);CHKERRQ(ierr);
if (ptasp <= dzero) {
/* Scaled negative curvature direction: Compute a step so that
||w + step*p|| = delta and QS(w + step*p) is least */
if (!i) {
ierr = VecCopy(P,X);CHKERRQ(ierr);
ierr = VecNorm(X,NORM_2,&xnorm);CHKERRQ(ierr);
scal = pcgP->delta / xnorm;
ierr = VecScale(X,scal);CHKERRQ(ierr);
} else {
/* Compute roots of quadratic */
ierr = KSPQCGQuadraticRoots(W,P,pcgP->delta,&step1,&step2);CHKERRQ(ierr);
ierr = VecDotRealPart(W,ASP,&wtasp);CHKERRQ(ierr);
ierr = VecDotRealPart(BS,P,&bstp);CHKERRQ(ierr);
ierr = VecCopy(W,X);CHKERRQ(ierr);
q1 = step1*(bstp + wtasp + .5*step1*ptasp);
q2 = step2*(bstp + wtasp + .5*step2*ptasp);
if (q1 <= q2) {
ierr = VecAXPY(X,step1,P);CHKERRQ(ierr);
} else {
ierr = VecAXPY(X,step2,P);CHKERRQ(ierr);
}
}
pcgP->ltsnrm = pcgP->delta; /* convergence in direction of */
ksp->reason = KSP_CONVERGED_CG_NEG_CURVE; /* negative curvature */
if (!i) {
ierr = PetscInfo1(ksp,"negative curvature: delta=%g\n",(double)pcgP->delta);CHKERRQ(ierr);
} else {
ierr = PetscInfo3(ksp,"negative curvature: step1=%g, step2=%g, delta=%g\n",(double)step1,(double)step2,(double)pcgP->delta);CHKERRQ(ierr);
}
} else {
/* Compute step along p */
step = rtr/ptasp;
ierr = VecCopy(W,X);CHKERRQ(ierr); /* x = w */
ierr = VecAXPY(X,step,P);CHKERRQ(ierr); /* x <- step*p + x */
ierr = VecNorm(X,NORM_2,&pcgP->ltsnrm);CHKERRQ(ierr);
if (pcgP->ltsnrm > pcgP->delta) {
/* Since the trial iterate is outside the trust region,
evaluate a constrained step along p so that
||w + step*p|| = delta
The positive step is always better in this case. */
if (!i) {
scal = pcgP->delta / pcgP->ltsnrm;
ierr = VecScale(X,scal);CHKERRQ(ierr);
} else {
/* Compute roots of quadratic */
ierr = KSPQCGQuadraticRoots(W,P,pcgP->delta,&step1,&step2);CHKERRQ(ierr);
ierr = VecCopy(W,X);CHKERRQ(ierr);
ierr = VecAXPY(X,step1,P);CHKERRQ(ierr); /* x <- step1*p + x */
}
pcgP->ltsnrm = pcgP->delta;
ksp->reason = KSP_CONVERGED_CG_CONSTRAINED; /* convergence along constrained step */
if (!i) {
ierr = PetscInfo1(ksp,"constrained step: delta=%g\n",(double)pcgP->delta);CHKERRQ(ierr);
} else {
ierr = PetscInfo3(ksp,"constrained step: step1=%g, step2=%g, delta=%g\n",(double)step1,(double)step2,(double)pcgP->delta);CHKERRQ(ierr);
}
} else {
/* Evaluate the current step */
ierr = VecCopy(X,W);CHKERRQ(ierr); /* update interior iterate */
ierr = VecAXPY(R,-step,ASP);CHKERRQ(ierr); /* r <- -step*asp + r */
ierr = VecNorm(R,NORM_2,&rnrm);CHKERRQ(ierr);
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = rnrm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnrm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,rnrm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,rnrm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) { /* convergence for */
ierr = PetscInfo3(ksp,"truncated step: step=%g, rnrm=%g, delta=%g\n",(double)PetscRealPart(step),(double)rnrm,(double)pcgP->delta);CHKERRQ(ierr);
}
}
}
if (ksp->reason) break; /* Convergence has been attained */
else { /* Compute a new AS-orthogonal direction */
ierr = VecDot(R,R,&rntrn);CHKERRQ(ierr);
beta = rntrn/rtr;
ierr = VecAYPX(P,beta,R);CHKERRQ(ierr); /* p <- r + beta*p */
rtr = PetscRealPart(rntrn);
}
}
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
/* Unscale x */
ierr = VecCopy(X,WA2);CHKERRQ(ierr);
ierr = PCApplySymmetricRight(pc,WA2,X);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,X,WA);CHKERRQ(ierr);
ierr = VecDotRealPart(B,X,&btx);CHKERRQ(ierr);
ierr = VecDotRealPart(X,WA,&xtax);CHKERRQ(ierr);
pcgP->quadratic = btx + .5*xtax;
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_PIPEFCG(KSP ksp)
{
PetscErrorCode ierr;
KSP_PIPEFCG *pipefcg;
PetscScalar gamma;
PetscReal dp=0.0;
Vec B,R,Z,X;
Mat Amat,Pmat;
#define VecXDot(x,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecDot (x,y,a) : VecTDot (x,y,a))
PetscFunctionBegin;
ierr = PetscCitationsRegister(citation,&cited);CHKERRQ(ierr);
pipefcg = (KSP_PIPEFCG*)ksp->data;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
/* Compute initial residual needed for convergence check*/
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr);
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr); /* r <- b - Ax */
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- dqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
break;
case KSP_NORM_NATURAL:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecXDot(Z,R,&gamma);CHKERRQ(ierr);
dp = PetscSqrtReal(PetscAbsScalar(gamma)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
/* Initial Convergence Check */
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
if (ksp->normtype == KSP_NORM_NONE) {
ierr = KSPConvergedSkip (ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
} else {
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
}
if (ksp->reason) PetscFunctionReturn(0);
do {
/* A cycle is broken only if a norm breakdown occurs. If not the entire solve happens in a single cycle.
This is coded this way to allow both truncation and truncation-restart strategy
(see KSPFCDGetNumOldDirections()) */
ierr = KSPSolve_PIPEFCG_cycle(ksp);CHKERRQ(ierr);
if (ksp->reason) break;
if (pipefcg->norm_breakdown) {
pipefcg->n_restarts++;
pipefcg->norm_breakdown = PETSC_FALSE;
}
} while (ksp->its < ksp->max_it);
if (ksp->its >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_CG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,stored_max_it,eigs;
PetscScalar dpi = 0.0,a = 1.0,beta,betaold = 1.0,b = 0,*e = 0,*d = 0,delta,dpiold;
PetscReal dp = 0.0;
Vec X,B,Z,R,P,S,W;
KSP_CG *cg;
Mat Amat,Pmat;
MatStructure pflag;
PetscTruth diagonalscale;
PetscFunctionBegin;
ierr = PCDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
cg = (KSP_CG*)ksp->data;
eigs = ksp->calc_sings;
stored_max_it = ksp->max_it;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
P = ksp->work[2];
if (cg->singlereduction) {
S = ksp->work[3];
W = ksp->work[4];
} else {
S = 0; /* unused */
W = Z;
}
#if !defined(PETSC_USE_COMPLEX)
#define VecXDot(x,y,a) VecDot(x,y,a)
#else
#define VecXDot(x,y,a) (((cg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
#endif
if (eigs) {e = cg->e; d = cg->d; e[0] = 0.0; }
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat,&pflag);CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z = e'*A'*B'*B*A'*e' */
} else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r = e'*A'*A*e */
} else if (ksp->normtype == KSP_NORM_NATURAL) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecXDot(Z,S,&delta);CHKERRQ(ierr);
}
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
if PetscIsInfOrNanScalar(beta) SETERRQ(PETSC_ERR_FP,"Infinite or not-a-number generated in dot product");
dp = sqrt(PetscAbsScalar(beta)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
} else dp = 0.0;
PetscErrorCode KSPSolve_SYMMLQ(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscScalar alpha,beta,ibeta,betaold,beta1,ceta = 0,ceta_oold = 0.0, ceta_old = 0.0,ceta_bar;
PetscScalar c = 1.0,cold=1.0,s=0.0,sold=0.0,coold,soold,rho0,rho1,rho2,rho3;
PetscScalar dp = 0.0;
PetscReal np,s_prod;
Vec X,B,R,Z,U,V,W,UOLD,VOLD,Wbar;
Mat Amat,Pmat;
MatStructure pflag;
KSP_SYMMLQ *symmlq = (KSP_SYMMLQ*)ksp->data;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
U = ksp->work[2];
V = ksp->work[3];
W = ksp->work[4];
UOLD = ksp->work[5];
VOLD = ksp->work[6];
Wbar = ksp->work[7];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat,&pflag);CHKERRQ(ierr);
ksp->its = 0;
ierr = VecSet(UOLD,0.0);CHKERRQ(ierr); /* u_old <- zeros; */
ierr = VecCopy(UOLD,VOLD);CHKERRQ(ierr); /* v_old <- u_old; */
ierr = VecCopy(UOLD,W);CHKERRQ(ierr); /* w <- u_old; */
ierr = VecCopy(UOLD,Wbar);CHKERRQ(ierr); /* w_bar <- u_old; */
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - A*x */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- B*r */
ierr = VecDot(R,Z,&dp);CHKERRQ(ierr); /* dp = r'*z; */
if (PetscAbsScalar(dp) < symmlq->haptol) {
ierr = PetscInfo2(ksp,"Detected happy breakdown %G tolerance %G\n",PetscAbsScalar(dp),symmlq->haptol);CHKERRQ(ierr);
ksp->rnorm = 0.0; /* what should we really put here? */
ksp->reason = KSP_CONVERGED_HAPPY_BREAKDOWN; /* bugfix proposed by Lourens ([email protected]) */
PetscFunctionReturn(0);
}
#if !defined(PETSC_USE_COMPLEX)
if (dp < 0.0) {
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
PetscFunctionReturn(0);
}
#endif
dp = PetscSqrtScalar(dp);
beta = dp; /* beta <- sqrt(r'*z) */
beta1 = beta;
s_prod = PetscAbsScalar(beta1);
ierr = VecCopy(R,V);CHKERRQ(ierr); /* v <- r; */
ierr = VecCopy(Z,U);CHKERRQ(ierr); /* u <- z; */
ibeta = 1.0 / beta;
ierr = VecScale(V,ibeta);CHKERRQ(ierr); /* v <- ibeta*v; */
ierr = VecScale(U,ibeta);CHKERRQ(ierr); /* u <- ibeta*u; */
ierr = VecCopy(U,Wbar);CHKERRQ(ierr); /* w_bar <- u; */
ierr = VecNorm(Z,NORM_2,&np);CHKERRQ(ierr); /* np <- ||z|| */
ierr = KSPLogResidualHistory(ksp,np);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,np);CHKERRQ(ierr);
ksp->rnorm = np;
ierr = (*ksp->converged)(ksp,0,np,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
i = 0; ceta = 0.;
do {
ksp->its = i+1;
/* Update */
if (ksp->its > 1) {
ierr = VecCopy(V,VOLD);CHKERRQ(ierr); /* v_old <- v; */
ierr = VecCopy(U,UOLD);CHKERRQ(ierr); /* u_old <- u; */
ierr = VecCopy(R,V);CHKERRQ(ierr);
ierr = VecScale(V,1.0/beta);CHKERRQ(ierr); /* v <- ibeta*r; */
ierr = VecCopy(Z,U);CHKERRQ(ierr);
ierr = VecScale(U,1.0/beta);CHKERRQ(ierr); /* u <- ibeta*z; */
ierr = VecCopy(Wbar,W);CHKERRQ(ierr);
ierr = VecScale(W,c);CHKERRQ(ierr);
ierr = VecAXPY(W,s,U);CHKERRQ(ierr); /* w <- c*w_bar + s*u; (w_k) */
ierr = VecScale(Wbar,-s);CHKERRQ(ierr);
ierr = VecAXPY(Wbar,c,U);CHKERRQ(ierr); /* w_bar <- -s*w_bar + c*u; (w_bar_(k+1)) */
ierr = VecAXPY(X,ceta,W);CHKERRQ(ierr); /* x <- x + ceta * w; (xL_k) */
ceta_oold = ceta_old;
ceta_old = ceta;
}
/* Lanczos */
ierr = KSP_MatMult(ksp,Amat,U,R);CHKERRQ(ierr); /* r <- Amat*u; */
ierr = VecDot(U,R,&alpha);CHKERRQ(ierr); /* alpha <- u'*r; */
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- B*r; */
ierr = VecAXPY(R,-alpha,V);CHKERRQ(ierr); /* r <- r - alpha* v; */
ierr = VecAXPY(Z,-alpha,U);CHKERRQ(ierr); /* z <- z - alpha* u; */
ierr = VecAXPY(R,-beta,VOLD);CHKERRQ(ierr); /* r <- r - beta * v_old; */
ierr = VecAXPY(Z,-beta,UOLD);CHKERRQ(ierr); /* z <- z - beta * u_old; */
betaold = beta; /* beta_k */
ierr = VecDot(R,Z,&dp);CHKERRQ(ierr); /* dp <- r'*z; */
if (PetscAbsScalar(dp) < symmlq->haptol) {
ierr = PetscInfo2(ksp,"Detected happy breakdown %G tolerance %G\n",PetscAbsScalar(dp),symmlq->haptol);CHKERRQ(ierr);
dp = 0.0;
}
#if !defined(PETSC_USE_COMPLEX)
if (dp < 0.0) {
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
break;
}
#endif
beta = PetscSqrtScalar(dp); /* beta = sqrt(dp); */
/* QR factorization */
coold = cold; cold = c; soold = sold; sold = s;
rho0 = cold * alpha - coold * sold * betaold; /* gamma_bar */
rho1 = PetscSqrtScalar(rho0*rho0 + beta*beta); /* gamma */
rho2 = sold * alpha + coold * cold * betaold; /* delta */
rho3 = soold * betaold; /* epsilon */
/* Givens rotation: [c -s; s c] (different from the Reference!) */
c = rho0 / rho1; s = beta / rho1;
if (ksp->its==1) ceta = beta1/rho1;
else ceta = -(rho2*ceta_old + rho3*ceta_oold)/rho1;
s_prod = s_prod*PetscAbsScalar(s);
if (c == 0.0) np = s_prod*1.e16;
else np = s_prod/PetscAbsScalar(c); /* residual norm for xc_k (CGNORM) */
ksp->rnorm = np;
ierr = KSPLogResidualHistory(ksp,np);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,np);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,np,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) break;
i++;
} while (i<ksp->max_it);
/* move to the CG point: xc_(k+1) */
if (c == 0.0) ceta_bar = ceta*1.e15;
else ceta_bar = ceta/c;
ierr = VecAXPY(X,ceta_bar,Wbar);CHKERRQ(ierr); /* x <- x + ceta_bar*w_bar */
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_TSIRM(KSP ksp)
{
PetscErrorCode ierr;
KSP_TSIRM *tsirm = (KSP_TSIRM*)ksp->data;
KSP sub_ksp;
PC pc;
Mat AS;
Vec x,b;
PetscScalar *array;
PetscReal norm = 20;
PetscInt i,*ind_row,first_iteration = 1,its = 0,total = 0,col = 0;
PetscInt restart = 30;
KSP ksp_min; /* KSP for minimization */
PC pc_min; /* PC for minimization */
PetscFunctionBegin;
x = ksp->vec_sol; /* Solution vector */
b = ksp->vec_rhs; /* Right-hand side vector */
/* Row indexes (these indexes are global) */
ierr = PetscMalloc1(tsirm->Iend-tsirm->Istart,&ind_row);
CHKERRQ(ierr);
for (i=0; i<tsirm->Iend-tsirm->Istart; i++) ind_row[i] = i+tsirm->Istart;
/* Inner solver */
ierr = KSPGetPC(ksp,&pc);
CHKERRQ(ierr);
ierr = PCKSPGetKSP(pc,&sub_ksp);
CHKERRQ(ierr);
ierr = KSPSetTolerances(sub_ksp,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,restart);
CHKERRQ(ierr);
/* previously it seemed good but with SNES it seems not good... */
ierr = KSP_MatMult(sub_ksp,tsirm->A,x,tsirm->r);
CHKERRQ(ierr);
ierr = VecAXPY(tsirm->r,-1,b);
CHKERRQ(ierr);
ierr = VecNorm(tsirm->r,NORM_2,&norm);
CHKERRQ(ierr);
ksp->its = 0;
ierr = KSPConvergedDefault(ksp,ksp->its,norm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
ierr = KSPSetInitialGuessNonzero(sub_ksp,PETSC_TRUE);
CHKERRQ(ierr);
do {
for (col=0; col<tsirm->size_ls && ksp->reason==0; col++) {
/* Solve (inner iteration) */
ierr = KSPSolve(sub_ksp,b,x);
CHKERRQ(ierr);
ierr = KSPGetIterationNumber(sub_ksp,&its);
CHKERRQ(ierr);
total += its;
/* Build S^T */
ierr = VecGetArray(x,&array);
CHKERRQ(ierr);
ierr = MatSetValues(tsirm->S,tsirm->Iend-tsirm->Istart,ind_row,1,&col,array,INSERT_VALUES);
CHKERRQ(ierr);
ierr = VecRestoreArray(x,&array);
CHKERRQ(ierr);
ierr = KSPGetResidualNorm(sub_ksp,&norm);
CHKERRQ(ierr);
ksp->rnorm = norm;
ksp->its ++;
ierr = KSPConvergedDefault(ksp,ksp->its,norm,&ksp->reason,ksp->cnvP);
CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,norm);
CHKERRQ(ierr);
}
/* Minimization step */
if (!ksp->reason) {
ierr = MatAssemblyBegin(tsirm->S,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
ierr = MatAssemblyEnd(tsirm->S,MAT_FINAL_ASSEMBLY);
CHKERRQ(ierr);
if (first_iteration) {
ierr = MatMatMult(tsirm->A,tsirm->S,MAT_INITIAL_MATRIX,PETSC_DEFAULT,&AS);
CHKERRQ(ierr);
first_iteration = 0;
} else {
ierr = MatMatMult(tsirm->A,tsirm->S,MAT_REUSE_MATRIX,PETSC_DEFAULT,&AS);
CHKERRQ(ierr);
}
/* CGLS or LSQR method to minimize the residuals*/
ierr = KSPCreate(PETSC_COMM_WORLD,&ksp_min);
CHKERRQ(ierr);
if (tsirm->cgls) {
ierr = KSPSetType(ksp_min,KSPCGLS);
CHKERRQ(ierr);
} else {
ierr = KSPSetType(ksp_min,KSPLSQR);
CHKERRQ(ierr);
}
ierr = KSPSetOperators(ksp_min,AS,AS);
CHKERRQ(ierr);
ierr = KSPSetTolerances(ksp_min,tsirm->tol_ls,PETSC_DEFAULT,PETSC_DEFAULT,tsirm->maxiter_ls);
CHKERRQ(ierr);
ierr = KSPGetPC(ksp_min,&pc_min);
CHKERRQ(ierr);
ierr = PCSetType(pc_min,PCNONE);
CHKERRQ(ierr);
ierr = KSPSolve(ksp_min,b,tsirm->Alpha);
CHKERRQ(ierr); /* Find Alpha such that ||AS Alpha = b|| */
ierr = KSPDestroy(&ksp_min);
CHKERRQ(ierr);
/* Apply minimization */
ierr = MatMult(tsirm->S,tsirm->Alpha,x);
CHKERRQ(ierr); /* x = S * Alpha */
}
} while (ksp->its<ksp->max_it && !ksp->reason);
ierr = MatDestroy(&AS);
CHKERRQ(ierr);
ierr = PetscFree(ind_row);
CHKERRQ(ierr);
ksp->its = total;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_FCG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,k,idx,mi;
KSP_FCG *fcg = (KSP_FCG*)ksp->data;
PetscScalar alpha=0.0,beta = 0.0,dpi,s;
PetscReal dp=0.0;
Vec B,R,Z,X,Pcurr,Ccurr;
Mat Amat,Pmat;
PetscInt eigs = ksp->calc_sings; /* Variables for eigen estimation - START*/
PetscInt stored_max_it = ksp->max_it;
PetscScalar alphaold = 0,betaold = 1.0,*e = 0,*d = 0;/* Variables for eigen estimation - FINISH */
PetscFunctionBegin;
#define VecXDot(x,y,a) (((fcg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
#define VecXMDot(a,b,c,d) (((fcg->type) == (KSP_CG_HERMITIAN)) ? VecMDot(a,b,c,d) : VecMTDot(a,b,c,d))
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
if (eigs) {e = fcg->e; d = fcg->d; e[0] = 0.0; }
/* Compute initial residual needed for convergence check*/
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr);
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr); /* r <- b - Ax */
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- dqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
break;
case KSP_NORM_NATURAL:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecXDot(R,Z,&s);CHKERRQ(ierr);
dp = PetscSqrtReal(PetscAbsScalar(s)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
/* Initial Convergence Check */
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
if (ksp->normtype == KSP_NORM_NONE) {
ierr = KSPConvergedSkip(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
} else {
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
}
if (ksp->reason) PetscFunctionReturn(0);
/* Apply PC if not already done for convergence check */
if(ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE){
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
}
i = 0;
do {
ksp->its = i+1;
/* If needbe, allocate a new chunk of vectors in P and C */
ierr = KSPAllocateVectors_FCG(ksp,i+1,fcg->vecb);CHKERRQ(ierr);
/* Note that we wrap around and start clobbering old vectors */
idx = i % (fcg->mmax+1);
Pcurr = fcg->Pvecs[idx];
Ccurr = fcg->Cvecs[idx];
/* Compute a new column of P (Currently does not support modified G-S or iterative refinement)*/
switch(fcg->truncstrat){
case KSP_FCG_TRUNC_TYPE_NOTAY :
mi = PetscMax(1,i%(fcg->mmax+1));
break;
case KSP_FCG_TRUNC_TYPE_STANDARD :
mi = fcg->mmax;
break;
default:
SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unrecognized FCG Truncation Strategy");CHKERRQ(ierr);
}
ierr = VecCopy(Z,Pcurr);CHKERRQ(ierr);
{
PetscInt l,ndots;
l = PetscMax(0,i-mi);
ndots = i-l;
if (ndots){
PetscInt j;
Vec *Pold, *Cold;
PetscScalar *dots;
ierr = PetscMalloc3(ndots,&dots,ndots,&Cold,ndots,&Pold);CHKERRQ(ierr);
for(k=l,j=0;j<ndots;++k,++j){
idx = k % (fcg->mmax+1);
Cold[j] = fcg->Cvecs[idx];
Pold[j] = fcg->Pvecs[idx];
}
ierr = VecXMDot(Z,ndots,Cold,dots);CHKERRQ(ierr);
for(k=0;k<ndots;++k){
dots[k] = -dots[k];
}
ierr = VecMAXPY(Pcurr,ndots,dots,Pold);CHKERRQ(ierr);
ierr = PetscFree3(dots,Cold,Pold);CHKERRQ(ierr);
}
}
/* Update X and R */
betaold = beta;
ierr = VecXDot(Pcurr,R,&beta);CHKERRQ(ierr); /* beta <- pi'*r */
ierr = KSP_MatMult(ksp,Amat,Pcurr,Ccurr);CHKERRQ(ierr); /* w <- A*pi (stored in ci) */
ierr = VecXDot(Pcurr,Ccurr,&dpi);CHKERRQ(ierr); /* dpi <- pi'*w */
alphaold = alpha;
alpha = beta / dpi; /* alpha <- beta/dpi */
ierr = VecAXPY(X,alpha,Pcurr);CHKERRQ(ierr); /* x <- x + alpha * pi */
ierr = VecAXPY(R,-alpha,Ccurr);CHKERRQ(ierr); /* r <- r - alpha * wi */
/* Compute norm for convergence check */
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
break;
case KSP_NORM_NATURAL:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecXDot(R,Z,&s);CHKERRQ(ierr);
dp = PetscSqrtReal(PetscAbsScalar(s)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
/* Check for convergence */
ksp->rnorm = dp;
KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
/* Apply PC if not already done for convergence check */
if(ksp->normtype == KSP_NORM_UNPRECONDITIONED || ksp->normtype == KSP_NORM_NONE){
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
}
/* Compute current C (which is W/dpi) */
ierr = VecScale(Ccurr,1.0/dpi);CHKERRQ(ierr); /* w <- ci/dpi */
if (eigs) {
if (i > 0) {
if (ksp->max_it != stored_max_it) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Can not change maxit AND calculate eigenvalues");
e[i] = PetscSqrtReal(PetscAbsScalar(beta/betaold))/alphaold;
d[i] = PetscSqrtReal(PetscAbsScalar(beta/betaold))*e[i] + 1.0/alpha;
} else {
d[i] = PetscSqrtReal(PetscAbsScalar(beta))*e[i] + 1.0/alpha;
}
}
++i;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
if (eigs) fcg->ned = ksp->its-1;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_MINRES(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscScalar alpha,beta,ibeta,betaold,eta,c=1.0,ceta,cold=1.0,coold,s=0.0,sold=0.0,soold;
PetscScalar rho0,rho1,irho1,rho2,mrho2,rho3,mrho3,dp = 0.0;
PetscReal np;
Vec X,B,R,Z,U,V,W,UOLD,VOLD,WOLD,WOOLD;
Mat Amat,Pmat;
KSP_MINRES *minres = (KSP_MINRES*)ksp->data;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
U = ksp->work[2];
V = ksp->work[3];
W = ksp->work[4];
UOLD = ksp->work[5];
VOLD = ksp->work[6];
WOLD = ksp->work[7];
WOOLD = ksp->work[8];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ksp->its = 0;
ierr = VecSet(UOLD,0.0);CHKERRQ(ierr); /* u_old <- 0 */
ierr = VecCopy(UOLD,VOLD);CHKERRQ(ierr); /* v_old <- 0 */
ierr = VecCopy(UOLD,W);CHKERRQ(ierr); /* w <- 0 */
ierr = VecCopy(UOLD,WOLD);CHKERRQ(ierr); /* w_old <- 0 */
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - A*x */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- B*r */
ierr = VecDot(R,Z,&dp);CHKERRQ(ierr);
if (PetscRealPart(dp) < minres->haptol) {
ierr = PetscInfo2(ksp,"Detected indefinite operator %g tolerance %g\n",(double)PetscRealPart(dp),(double)minres->haptol);CHKERRQ(ierr);
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
PetscFunctionReturn(0);
}
dp = PetscAbsScalar(dp);
dp = PetscSqrtScalar(dp);
beta = dp; /* beta <- sqrt(r'*z */
eta = beta;
ierr = VecCopy(R,V);CHKERRQ(ierr);
ierr = VecCopy(Z,U);CHKERRQ(ierr);
ibeta = 1.0 / beta;
ierr = VecScale(V,ibeta);CHKERRQ(ierr); /* v <- r / beta */
ierr = VecScale(U,ibeta);CHKERRQ(ierr); /* u <- z / beta */
ierr = VecNorm(Z,NORM_2,&np);CHKERRQ(ierr); /* np <- ||z|| */
ierr = KSPLogResidualHistory(ksp,np);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,np);CHKERRQ(ierr);
ksp->rnorm = np;
ierr = (*ksp->converged)(ksp,0,np,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
i = 0;
do {
ksp->its = i+1;
/* Lanczos */
ierr = KSP_MatMult(ksp,Amat,U,R);CHKERRQ(ierr); /* r <- A*u */
ierr = VecDot(U,R,&alpha);CHKERRQ(ierr); /* alpha <- r'*u */
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- B*r */
ierr = VecAXPY(R,-alpha,V);CHKERRQ(ierr); /* r <- r - alpha v */
ierr = VecAXPY(Z,-alpha,U);CHKERRQ(ierr); /* z <- z - alpha u */
ierr = VecAXPY(R,-beta,VOLD);CHKERRQ(ierr); /* r <- r - beta v_old */
ierr = VecAXPY(Z,-beta,UOLD);CHKERRQ(ierr); /* z <- z - beta u_old */
betaold = beta;
ierr = VecDot(R,Z,&dp);CHKERRQ(ierr);
if ( PetscRealPart(dp) < minres->haptol) {
ierr = PetscInfo2(ksp,"Detected indefinite operator %g tolerance %g\n",(double)PetscRealPart(dp),(double)minres->haptol);CHKERRQ(ierr);
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
break;
}
dp = PetscAbsScalar(dp);
beta = PetscSqrtScalar(dp); /* beta <- sqrt(r'*z) */
/* QR factorisation */
coold = cold; cold = c; soold = sold; sold = s;
rho0 = cold * alpha - coold * sold * betaold;
rho1 = PetscSqrtScalar(rho0*rho0 + beta*beta);
rho2 = sold * alpha + coold * cold * betaold;
rho3 = soold * betaold;
/* Givens rotation */
c = rho0 / rho1;
s = beta / rho1;
/* Update */
ierr = VecCopy(WOLD,WOOLD);CHKERRQ(ierr); /* w_oold <- w_old */
ierr = VecCopy(W,WOLD);CHKERRQ(ierr); /* w_old <- w */
ierr = VecCopy(U,W);CHKERRQ(ierr); /* w <- u */
mrho2 = -rho2;
ierr = VecAXPY(W,mrho2,WOLD);CHKERRQ(ierr); /* w <- w - rho2 w_old */
mrho3 = -rho3;
ierr = VecAXPY(W,mrho3,WOOLD);CHKERRQ(ierr); /* w <- w - rho3 w_oold */
irho1 = 1.0 / rho1;
ierr = VecScale(W,irho1);CHKERRQ(ierr); /* w <- w / rho1 */
ceta = c * eta;
ierr = VecAXPY(X,ceta,W);CHKERRQ(ierr); /* x <- x + c eta w */
eta = -s * eta;
ierr = VecCopy(V,VOLD);CHKERRQ(ierr);
ierr = VecCopy(U,UOLD);CHKERRQ(ierr);
ierr = VecCopy(R,V);CHKERRQ(ierr);
ierr = VecCopy(Z,U);CHKERRQ(ierr);
ibeta = 1.0 / beta;
ierr = VecScale(V,ibeta);CHKERRQ(ierr); /* v <- r / beta */
ierr = VecScale(U,ibeta);CHKERRQ(ierr); /* u <- z / beta */
np = ksp->rnorm * PetscAbsScalar(s);
ksp->rnorm = np;
ierr = KSPLogResidualHistory(ksp,np);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,np);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,np,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) break;
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_Chebyshev(KSP ksp)
{
KSP_Chebyshev *cheb = (KSP_Chebyshev*)ksp->data;
PetscErrorCode ierr;
PetscInt k,kp1,km1,maxit,ktmp,i;
PetscScalar alpha,omegaprod,mu,omega,Gamma,c[3],scale;
PetscReal rnorm = 0.0;
Vec sol_orig,b,p[3],r;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
if (cheb->kspest && !cheb->estimate_current) {
PetscReal max=0.0,min=0.0;
Vec X,B;
X = ksp->work[0];
if (cheb->random) {
B = ksp->work[1];
ierr = VecSetRandom(B,cheb->random);CHKERRQ(ierr);
} else {
B = ksp->vec_rhs;
}
ierr = KSPSolve(cheb->kspest,B,X);CHKERRQ(ierr);
if (ksp->guess_zero) {
ierr = VecZeroEntries(X);CHKERRQ(ierr);
}
ierr = KSPChebyshevComputeExtremeEigenvalues_Private(cheb->kspest,&min,&max);CHKERRQ(ierr);
cheb->emin = cheb->tform[0]*min + cheb->tform[1]*max;
cheb->emax = cheb->tform[2]*min + cheb->tform[3]*max;
cheb->estimate_current = PETSC_TRUE;
}
ksp->its = 0;
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
maxit = ksp->max_it;
/* These three point to the three active solutions, we
rotate these three at each solution update */
km1 = 0; k = 1; kp1 = 2;
sol_orig = ksp->vec_sol; /* ksp->vec_sol will be asigned to rotating vector p[k], thus save its address */
b = ksp->vec_rhs;
p[km1] = sol_orig;
p[k] = ksp->work[0];
p[kp1] = ksp->work[1];
r = ksp->work[2];
/* use scale*B as our preconditioner */
scale = 2.0/(cheb->emax + cheb->emin);
/* -alpha <= scale*lambda(B^{-1}A) <= alpha */
alpha = 1.0 - scale*(cheb->emin);
Gamma = 1.0;
mu = 1.0/alpha;
omegaprod = 2.0/alpha;
c[km1] = 1.0;
c[k] = mu;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,p[km1],r);CHKERRQ(ierr); /* r = b - A*p[km1] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
} else {
ierr = VecCopy(b,r);CHKERRQ(ierr);
}
ierr = KSP_PCApply(ksp,r,p[k]);CHKERRQ(ierr); /* p[k] = scale B^{-1}r + p[km1] */
ierr = VecAYPX(p[k],scale,p[km1]);CHKERRQ(ierr);
for (i=0; i<maxit; i++) {
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
c[kp1] = 2.0*mu*c[k] - c[km1];
omega = omegaprod*c[k]/c[kp1];
ierr = KSP_MatMult(ksp,Amat,p[k],r);CHKERRQ(ierr); /* r = b - Ap[k] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,r,p[kp1]);CHKERRQ(ierr); /* p[kp1] = B^{-1}r */
ksp->vec_sol = p[k];
/* calculate residual norm if requested */
if (ksp->normtype != KSP_NORM_NONE || ksp->numbermonitors) {
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(p[kp1],NORM_2,&rnorm);CHKERRQ(ierr);
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
/* y^{k+1} = omega(y^{k} - y^{k-1} + Gamma*r^{k}) + y^{k-1} */
ierr = VecAXPBYPCZ(p[kp1],1.0-omega,omega,omega*Gamma*scale,p[km1],p[k]);CHKERRQ(ierr);
ktmp = km1;
km1 = k;
k = kp1;
kp1 = ktmp;
}
if (!ksp->reason) {
if (ksp->normtype != KSP_NORM_NONE) {
ierr = KSP_MatMult(ksp,Amat,p[k],r);CHKERRQ(ierr); /* r = b - Ap[k] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr);
} else {
ierr = KSP_PCApply(ksp,r,p[kp1]);CHKERRQ(ierr); /* p[kp1] = B^{-1}r */
ierr = VecNorm(p[kp1],NORM_2,&rnorm);CHKERRQ(ierr);
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->vec_sol = p[k];
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
}
if (ksp->its >= ksp->max_it) {
if (ksp->normtype != KSP_NORM_NONE) {
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
} else ksp->reason = KSP_CONVERGED_ITS;
}
}
/* make sure solution is in vector x */
ksp->vec_sol = sol_orig;
if (k) {
ierr = VecCopy(p[k],sol_orig);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_Chebyshev(KSP ksp)
{
KSP_Chebyshev *cheb = (KSP_Chebyshev*)ksp->data;
PetscErrorCode ierr;
PetscInt k,kp1,km1,maxit,ktmp,i;
PetscScalar alpha,omegaprod,mu,omega,Gamma,c[3],scale;
PetscReal rnorm = 0.0;
Vec sol_orig,b,p[3],r;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
if (cheb->kspest) {
PetscObjectId amatid, pmatid;
PetscObjectState amatstate, pmatstate;
ierr = PetscObjectGetId((PetscObject)Amat,&amatid);CHKERRQ(ierr);
ierr = PetscObjectGetId((PetscObject)Pmat,&pmatid);CHKERRQ(ierr);
ierr = PetscObjectStateGet((PetscObject)Amat,&amatstate);CHKERRQ(ierr);
ierr = PetscObjectStateGet((PetscObject)Pmat,&pmatstate);CHKERRQ(ierr);
if (amatid != cheb->amatid || pmatid != cheb->pmatid || amatstate != cheb->amatstate || pmatstate != cheb->pmatstate) {
PetscReal max=0.0,min=0.0;
Vec B;
KSPConvergedReason reason;
if (cheb->userandom) {
B = ksp->work[1];
if (!cheb->random) {
ierr = PetscRandomCreate(PetscObjectComm((PetscObject)B),&cheb->random);CHKERRQ(ierr);
}
ierr = VecSetRandom(B,cheb->random);CHKERRQ(ierr);
} else {
B = ksp->vec_rhs;
}
ierr = KSPSolve(cheb->kspest,B,ksp->work[0]);CHKERRQ(ierr);
ierr = KSPGetConvergedReason(cheb->kspest,&reason);CHKERRQ(ierr);
if (reason < 0) {
if (reason == KSP_DIVERGED_ITS) {
ierr = PetscInfo(ksp,"Eigen estimator ran for prescribed number of iterations\n");CHKERRQ(ierr);
} else {
PetscInt its;
ierr = KSPGetIterationNumber(cheb->kspest,&its);CHKERRQ(ierr);
SETERRQ2(PetscObjectComm((PetscObject)ksp),PETSC_ERR_PLIB,"Eigen estimator failed: %s at iteration %D",KSPConvergedReasons[reason],its);
}
} else if (reason==KSP_CONVERGED_RTOL ||reason==KSP_CONVERGED_ATOL) {
ierr = PetscInfo(ksp,"Eigen estimator converged prematurely. Should not happen except for small or low rank problem\n");CHKERRQ(ierr);
} else {
ierr = PetscInfo1(ksp,"Eigen estimator did not converge by iteration: %s\n",KSPConvergedReasons[reason]);CHKERRQ(ierr);
}
ierr = KSPChebyshevComputeExtremeEigenvalues_Private(cheb->kspest,&min,&max);CHKERRQ(ierr);
cheb->emin = cheb->tform[0]*min + cheb->tform[1]*max;
cheb->emax = cheb->tform[2]*min + cheb->tform[3]*max;
cheb->amatid = amatid;
cheb->pmatid = pmatid;
cheb->amatstate = amatstate;
cheb->pmatstate = pmatstate;
}
}
ksp->its = 0;
maxit = ksp->max_it;
/* These three point to the three active solutions, we
rotate these three at each solution update */
km1 = 0; k = 1; kp1 = 2;
sol_orig = ksp->vec_sol; /* ksp->vec_sol will be asigned to rotating vector p[k], thus save its address */
b = ksp->vec_rhs;
p[km1] = sol_orig;
p[k] = ksp->work[0];
p[kp1] = ksp->work[1];
r = ksp->work[2];
/* use scale*B as our preconditioner */
scale = 2.0/(cheb->emax + cheb->emin);
/* -alpha <= scale*lambda(B^{-1}A) <= alpha */
alpha = 1.0 - scale*(cheb->emin);
Gamma = 1.0;
mu = 1.0/alpha;
omegaprod = 2.0/alpha;
c[km1] = 1.0;
c[k] = mu;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,p[km1],r);CHKERRQ(ierr); /* r = b - A*p[km1] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
} else {
ierr = VecCopy(b,r);CHKERRQ(ierr);
}
ierr = KSP_PCApply(ksp,r,p[k]);CHKERRQ(ierr); /* p[k] = scale B^{-1}r + p[km1] */
ierr = VecAYPX(p[k],scale,p[km1]);CHKERRQ(ierr);
for (i=0; i<maxit; i++) {
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
c[kp1] = 2.0*mu*c[k] - c[km1];
omega = omegaprod*c[k]/c[kp1];
ierr = KSP_MatMult(ksp,Amat,p[k],r);CHKERRQ(ierr); /* r = b - Ap[k] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,r,p[kp1]);CHKERRQ(ierr); /* p[kp1] = B^{-1}r */
ksp->vec_sol = p[k];
/* calculate residual norm if requested */
if (ksp->normtype != KSP_NORM_NONE || ksp->numbermonitors) {
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr);
} else {
ierr = VecNorm(p[kp1],NORM_2,&rnorm);CHKERRQ(ierr);
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
/* y^{k+1} = omega(y^{k} - y^{k-1} + Gamma*r^{k}) + y^{k-1} */
ierr = VecAXPBYPCZ(p[kp1],1.0-omega,omega,omega*Gamma*scale,p[km1],p[k]);CHKERRQ(ierr);
ktmp = km1;
km1 = k;
k = kp1;
kp1 = ktmp;
}
if (!ksp->reason) {
if (ksp->normtype != KSP_NORM_NONE) {
ierr = KSP_MatMult(ksp,Amat,p[k],r);CHKERRQ(ierr); /* r = b - Ap[k] */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr);
} else {
ierr = KSP_PCApply(ksp,r,p[kp1]);CHKERRQ(ierr); /* p[kp1] = B^{-1}r */
ierr = VecNorm(p[kp1],NORM_2,&rnorm);CHKERRQ(ierr);
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->vec_sol = p[k];
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
}
if (ksp->its >= ksp->max_it) {
if (ksp->normtype != KSP_NORM_NONE) {
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
} else ksp->reason = KSP_CONVERGED_ITS;
}
}
/* make sure solution is in vector x */
ksp->vec_sol = sol_orig;
if (k) {
ierr = VecCopy(p[k],sol_orig);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
static PetscErrorCode KSPPIPEFGMRESCycle(PetscInt *itcount,KSP ksp)
{
KSP_PIPEFGMRES *pipefgmres = (KSP_PIPEFGMRES*)(ksp->data);
PetscReal res_norm;
PetscReal hapbnd,tt;
PetscScalar *hh,*hes,*lhh,shift = pipefgmres->shift;
PetscBool hapend = PETSC_FALSE; /* indicates happy breakdown ending */
PetscErrorCode ierr;
PetscInt loc_it; /* local count of # of dir. in Krylov space */
PetscInt max_k = pipefgmres->max_k; /* max # of directions Krylov space */
PetscInt i,j,k;
Mat Amat,Pmat;
Vec Q,W; /* Pipelining vectors */
Vec *redux = pipefgmres->redux; /* workspace for single reduction */
PetscFunctionBegin;
if (itcount) *itcount = 0;
/* Assign simpler names to these vectors, allocated as pipelining workspace */
Q = VEC_Q;
W = VEC_W;
/* Allocate memory for orthogonalization work (freed in the GMRES Destroy routine)*/
/* Note that we add an extra value here to allow for a single reduction */
if (!pipefgmres->orthogwork) { ierr = PetscMalloc1(pipefgmres->max_k + 2 ,&pipefgmres->orthogwork);CHKERRQ(ierr);
}
lhh = pipefgmres->orthogwork;
/* Number of pseudo iterations since last restart is the number
of prestart directions */
loc_it = 0;
/* note: (pipefgmres->it) is always set one less than (loc_it) It is used in
KSPBUILDSolution_PIPEFGMRES, where it is passed to KSPPIPEFGMRESBuildSoln.
Note that when KSPPIPEFGMRESBuildSoln is called from this function,
(loc_it -1) is passed, so the two are equivalent */
pipefgmres->it = (loc_it - 1);
/* initial residual is in VEC_VV(0) - compute its norm*/
ierr = VecNorm(VEC_VV(0),NORM_2,&res_norm);CHKERRQ(ierr);
/* first entry in right-hand-side of hessenberg system is just
the initial residual norm */
*RS(0) = res_norm;
ksp->rnorm = res_norm;
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
/* check for the convergence - maybe the current guess is good enough */
ierr = (*ksp->converged)(ksp,ksp->its,res_norm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) {
if (itcount) *itcount = 0;
PetscFunctionReturn(0);
}
/* scale VEC_VV (the initial residual) */
ierr = VecScale(VEC_VV(0),1.0/res_norm);CHKERRQ(ierr);
/* Fill the pipeline */
ierr = KSP_PCApply(ksp,VEC_VV(loc_it),PREVEC(loc_it));CHKERRQ(ierr);
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,PREVEC(loc_it),ZVEC(loc_it));CHKERRQ(ierr);
ierr = VecAXPY(ZVEC(loc_it),-shift,VEC_VV(loc_it));CHKERRQ(ierr); /* Note shift */
/* MAIN ITERATION LOOP BEGINNING*/
/* keep iterating until we have converged OR generated the max number
of directions OR reached the max number of iterations for the method */
while (!ksp->reason && loc_it < max_k && ksp->its < ksp->max_it) {
if (loc_it) {
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
}
pipefgmres->it = (loc_it - 1);
/* see if more space is needed for work vectors */
if (pipefgmres->vv_allocated <= loc_it + VEC_OFFSET + 1) {
ierr = KSPPIPEFGMRESGetNewVectors(ksp,loc_it+1);CHKERRQ(ierr);
/* (loc_it+1) is passed in as number of the first vector that should
be allocated */
}
/* Note that these inner products are with "Z" now, so
in particular, lhh[loc_it] is the 'barred' or 'shifted' value,
not the value from the equivalent FGMRES run (even in exact arithmetic)
That is, the H we need for the Arnoldi relation is different from the
coefficients we use in the orthogonalization process,because of the shift */
/* Do some local twiddling to allow for a single reduction */
for(i=0;i<loc_it+1;i++){
redux[i] = VEC_VV(i);
}
redux[loc_it+1] = ZVEC(loc_it);
/* note the extra dot product which ends up in lh[loc_it+1], which computes ||z||^2 */
ierr = VecMDotBegin(ZVEC(loc_it),loc_it+2,redux,lhh);CHKERRQ(ierr);
/* Start the split reduction (This actually calls the MPI_Iallreduce, otherwise, the reduction is simply delayed until the "end" call)*/
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)ZVEC(loc_it)));CHKERRQ(ierr);
/* The work to be overlapped with the inner products follows.
This is application of the preconditioner and the operator
to compute intermediate quantites which will be combined (locally)
with the results of the inner products.
*/
ierr = KSP_PCApply(ksp,ZVEC(loc_it),Q);CHKERRQ(ierr);
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,Q,W);CHKERRQ(ierr);
/* Compute inner products of the new direction with previous directions,
and the norm of the to-be-orthogonalized direction "Z".
This information is enough to build the required entries
of H. The inner product with VEC_VV(it_loc) is
*different* than in the standard FGMRES and need to be dealt with specially.
That is, for standard FGMRES the orthogonalization coefficients are the same
as the coefficients used in the Arnoldi relation to reconstruct, but here this
is not true (albeit only for the one entry of H which we "unshift" below. */
/* Finish the dot product, retrieving the extra entry */
ierr = VecMDotEnd(ZVEC(loc_it),loc_it+2,redux,lhh);CHKERRQ(ierr);
tt = PetscRealPart(lhh[loc_it+1]);
/* Hessenberg entries, and entries for (naive) classical Graham-Schmidt
Note that the Hessenberg entries require a shift, as these are for the
relation AU = VH, which is wrt unshifted basis vectors */
hh = HH(0,loc_it); hes=HES(0,loc_it);
for (j=0; j<loc_it; j++) {
hh[j] = lhh[j];
hes[j] = lhh[j];
}
hh[loc_it] = lhh[loc_it] + shift;
hes[loc_it] = lhh[loc_it] + shift;
/* we delay applying the shift here */
for (j=0; j<=loc_it; j++) {
lhh[j] = -lhh[j]; /* flip sign */
}
/* Compute the norm of the un-normalized new direction using the rearranged formula
Note that these are shifted ("barred") quantities */
for(k=0;k<=loc_it;k++) tt -= ((PetscReal)(PetscAbsScalar(lhh[k]) * PetscAbsScalar(lhh[k])));
/* On AVX512 this is accumulating roundoff errors for eg: tt=-2.22045e-16 */
if ((tt < 0.0) && tt > -PETSC_SMALL) tt = 0.0 ;
if (tt < 0.0) {
/* If we detect square root breakdown in the norm, we must restart the algorithm.
Here this means we simply break the current loop and reconstruct the solution
using the basis we have computed thus far. Note that by breaking immediately,
we do not update the iteration count, so computation done in this iteration
should be disregarded.
*/
ierr = PetscInfo2(ksp,"Restart due to square root breakdown at it = %D, tt=%g\n",ksp->its,(double)tt);CHKERRQ(ierr);
break;
} else {
tt = PetscSqrtReal(tt);
}
/* new entry in hessenburg is the 2-norm of our new direction */
hh[loc_it+1] = tt;
hes[loc_it+1] = tt;
/* The recurred computation for the new direction
The division by tt is delayed to the happy breakdown check later
Note placement BEFORE the unshift
*/
ierr = VecCopy(ZVEC(loc_it),VEC_VV(loc_it+1));CHKERRQ(ierr);
ierr = VecMAXPY(VEC_VV(loc_it+1),loc_it+1,lhh,&VEC_VV(0));CHKERRQ(ierr);
/* (VEC_VV(loc_it+1) is not normalized yet) */
/* The recurred computation for the preconditioned vector (u) */
ierr = VecCopy(Q,PREVEC(loc_it+1));CHKERRQ(ierr);
ierr = VecMAXPY(PREVEC(loc_it+1),loc_it+1,lhh,&PREVEC(0));CHKERRQ(ierr);
ierr = VecScale(PREVEC(loc_it+1),1.0/tt);CHKERRQ(ierr);
/* Unshift an entry in the GS coefficients ("removing the bar") */
lhh[loc_it] -= shift;
/* The recurred computation for z (Au)
Note placement AFTER the "unshift" */
ierr = VecCopy(W,ZVEC(loc_it+1));CHKERRQ(ierr);
ierr = VecMAXPY(ZVEC(loc_it+1),loc_it+1,lhh,&ZVEC(0));CHKERRQ(ierr);
ierr = VecScale(ZVEC(loc_it+1),1.0/tt);CHKERRQ(ierr);
/* Happy Breakdown Check */
hapbnd = PetscAbsScalar((tt) / *RS(loc_it));
/* RS(loc_it) contains the res_norm from the last iteration */
hapbnd = PetscMin(pipefgmres->haptol,hapbnd);
if (tt > hapbnd) {
/* scale new direction by its norm */
ierr = VecScale(VEC_VV(loc_it+1),1.0/tt);CHKERRQ(ierr);
} else {
/* This happens when the solution is exactly reached. */
/* So there is no new direction... */
ierr = VecSet(VEC_TEMP,0.0);CHKERRQ(ierr); /* set VEC_TEMP to 0 */
hapend = PETSC_TRUE;
}
/* note that for pipefgmres we could get HES(loc_it+1, loc_it) = 0 and the
current solution would not be exact if HES was singular. Note that
HH non-singular implies that HES is not singular, and HES is guaranteed
to be nonsingular when PREVECS are linearly independent and A is
nonsingular (in GMRES, the nonsingularity of A implies the nonsingularity
of HES). So we should really add a check to verify that HES is nonsingular.*/
/* Note that to be thorough, in debug mode, one could call a LAPACK routine
here to check that the hessenberg matrix is indeed non-singular (since
FGMRES does not guarantee this) */
/* Now apply rotations to new col of hessenberg (and right side of system),
calculate new rotation, and get new residual norm at the same time*/
ierr = KSPPIPEFGMRESUpdateHessenberg(ksp,loc_it,&hapend,&res_norm);CHKERRQ(ierr);
if (ksp->reason) break;
loc_it++;
pipefgmres->it = (loc_it-1); /* Add this here in case it has converged */
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = res_norm;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,res_norm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
/* Catch error in happy breakdown and signal convergence and break from loop */
if (hapend) {
if (!ksp->reason) {
if (ksp->errorifnotconverged) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"You reached the happy break down, but convergence was not indicated. Residual norm = %g",(double)res_norm);
else {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
}
}
}
/* END OF ITERATION LOOP */
ierr = KSPLogResidualHistory(ksp,res_norm);CHKERRQ(ierr);
/*
Monitor if we know that we will not return for a restart */
if (loc_it && (ksp->reason || ksp->its >= ksp->max_it)) {
ierr = KSPMonitor(ksp,ksp->its,res_norm);CHKERRQ(ierr);
}
if (itcount) *itcount = loc_it;
/*
Down here we have to solve for the "best" coefficients of the Krylov
columns, add the solution values together, and possibly unwind the
preconditioning from the solution
*/
/* Form the solution (or the solution so far) */
/* Note: must pass in (loc_it-1) for iteration count so that KSPPIPEGMRESIIBuildSoln
properly navigates */
ierr = KSPPIPEFGMRESBuildSoln(RS(0),ksp->vec_sol,ksp->vec_sol,ksp,loc_it-1);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_CG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,stored_max_it,eigs;
PetscScalar dpi = 0.0,a = 1.0,beta,betaold = 1.0,b = 0,*e = 0,*d = 0,delta,dpiold;
PetscReal dp = 0.0;
Vec X,B,Z,R,P,S,W;
KSP_CG *cg;
Mat Amat,Pmat;
PetscBool diagonalscale;
/* Dingwen */
PetscInt itv_d, itv_c;
PetscScalar CKSX1,CKSZ1,CKSR1,CKSP1,CKSS1,CKSW1;
PetscScalar CKSX2,CKSZ2,CKSR2,CKSP2,CKSS2,CKSW2;
Vec CKSAmat1;
Vec CKSAmat2;
Vec C1,C2;
PetscScalar d1,d2;
PetscScalar sumX1,sumR1;
PetscScalar sumX2,sumR2;
Vec CKPX,CKPP;
PetscScalar CKPbetaold;
PetscInt CKPi;
PetscBool flag1 = PETSC_TRUE, flag2 = PETSC_TRUE;
PetscInt pos;
PetscScalar v;
VecScatter ctx;
Vec W_SEQ;
PetscScalar *_W;
/* Dingwen */
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
cg = (KSP_CG*)ksp->data;
eigs = ksp->calc_sings;
stored_max_it = ksp->max_it;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
P = ksp->work[2];
/* Dingwen */
CKPX = ksp->work[3];
CKPP = ksp->work[4];
CKSAmat1 = ksp->work[5];
CKSAmat2 = ksp->work[6];
C1 = ksp->work[7];
C2 = ksp->work[8];
/* Dingwen */
/* Dingwen */
int rank; /* Get MPI variables */
MPI_Comm_rank (MPI_COMM_WORLD,&rank);
/* Dingwen */
#define VecXDot(x,y,a) (((cg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
if (cg->singlereduction) {
S = ksp->work[9];
W = ksp->work[10];
} else {
S = 0; /* unused */
W = Z;
}
if (eigs) {e = cg->e; d = cg->d; e[0] = 0.0; }
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
/* Dingwen */
/* checksum coefficients initialization */
PetscInt size;
ierr = VecGetSize(B,&size);
for (i=0; i<size; i++)
{
v = 1.0;
ierr = VecSetValues(C1,1,&i,&v,INSERT_VALUES);CHKERRQ(ierr);
v = i;
ierr = VecSetValues(C2,1,&i,&v,INSERT_VALUES);CHKERRQ(ierr);
}
d1 = 1.0;
d2 = 2.0;
/* Dingwen */
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z = e'*A'*B'*B*A'*e' */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r = e'*A'*A*e */
break;
case KSP_NORM_NATURAL:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecXDot(Z,S,&delta);CHKERRQ(ierr);
/* Dingwen */
ierr = VecXDot(C1,S,&CKSS1);CHKERRQ(ierr); /* Compute the initial checksum1(S) */
ierr = VecXDot(C2,S,&CKSS2);CHKERRQ(ierr); /* Compute the initial checksum2(S) */
/* Dingwen */
}
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
KSPCheckDot(ksp,beta);
dp = PetscSqrtReal(PetscAbsScalar(beta)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
if (ksp->normtype != KSP_NORM_PRECONDITIONED && (ksp->normtype != KSP_NORM_NATURAL)) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
}
if (ksp->normtype != KSP_NORM_NATURAL) {
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecXDot(Z,S,&delta);CHKERRQ(ierr);
}
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
KSPCheckDot(ksp,beta);
}
/* Dingwen */
/* Checksum Initialization */
ierr = VecXDot(C1,X,&CKSX1);CHKERRQ(ierr); /* Compute the initial checksum1(X) */
ierr = VecXDot(C1,W,&CKSW1);CHKERRQ(ierr); /* Compute the initial checksum1(W) */
ierr = VecXDot(C1,R,&CKSR1);CHKERRQ(ierr); /* Compute the initial checksum1(R) */
ierr = VecXDot(C1,Z,&CKSZ1);CHKERRQ(ierr); /* Compute the initial checksum1(Z) */
ierr = VecXDot(C2,X,&CKSX2);CHKERRQ(ierr); /* Compute the initial checksum2(X) */
ierr = VecXDot(C2,W,&CKSW2);CHKERRQ(ierr); /* Compute the initial checksum2(W) */
ierr = VecXDot(C2,R,&CKSR2);CHKERRQ(ierr); /* Compute the initial checksum2(R) */
ierr = VecXDot(C2,Z,&CKSZ2);CHKERRQ(ierr); /* Compute the initial checksum2(Z) */
ierr = KSP_MatMultTranspose(ksp,Amat,C1,CKSAmat1);CHKERRQ(ierr);
ierr = VecAXPY(CKSAmat1,-d1,C1);CHKERRQ(ierr);
ierr = VecAXPY(CKSAmat1,-d2,C2);CHKERRQ(ierr); /* Compute the initial checksum1(A) */
ierr = KSP_MatMultTranspose(ksp,Amat,C2,CKSAmat2);CHKERRQ(ierr);
ierr = VecAXPY(CKSAmat2,-d2,C1);CHKERRQ(ierr);
ierr = VecAXPY(CKSAmat2,-d1,C2);CHKERRQ(ierr); /* Compute the initial checksum2(A) */
itv_c = 2;
itv_d = 10;
/* Dingwen */
i = 0;
do {
/* Dingwen */
if ((i>0) && (i%itv_d == 0))
{
ierr = VecXDot(C1,X,&sumX1);CHKERRQ(ierr);
ierr = VecXDot(C1,R,&sumR1);CHKERRQ(ierr);
if ((PetscAbsScalar(sumX1-CKSX1) > 1.0e-6) || (PetscAbsScalar(sumR1-CKSR1) > 1.0e-6))
{
/* Rollback and Recovery */
if (rank==0) printf ("Recovery start...\n");
if (rank==0) printf ("Rollback from iteration-%d to iteration-%d\n",i,CKPi);
betaold = CKPbetaold; /* Recovery scalar betaold by checkpoint*/
i = CKPi; /* Recovery integer i by checkpoint */
ierr = VecCopy(CKPP,P);CHKERRQ(ierr); /* Recovery vector P from checkpoint */
ierr = VecXDot(C1,P,&CKSP1);CHKERRQ(ierr); /* Recovery checksum1(P) by P */
ierr = VecXDot(C2,P,&CKSP2);CHKERRQ(ierr); /* Recovery checksum2(P) by P */
ierr = KSP_MatMult(ksp,Amat,P,W);CHKERRQ(ierr); /* Recovery vector W by P */
ierr = VecXDot(P,W,&dpi);CHKERRQ(ierr); /* Recovery scalar dpi by P and W */
ierr = VecCopy(CKPX,X);CHKERRQ(ierr); /* Recovery vector X from checkpoint */
ierr = VecXDot(C1,X,&CKSX1);CHKERRQ(ierr); /* Recovery checksum1(X) by X */
ierr = VecXDot(C2,X,&CKSX2);CHKERRQ(ierr); /* Recovery checksum2(X) by X */
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* Recovery vector R by X */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
ierr = VecXDot(C1,R,&CKSR1);CHKERRQ(ierr); /* Recovery checksum1(R) by R */
ierr = VecXDot(C2,R,&CKSR2);CHKERRQ(ierr); /* Recovery checksum2(R) by R */
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* Recovery vector Z by R */
ierr = VecXDot(C1,Z,&CKSZ1);CHKERRQ(ierr); /* Recovery checksum1(Z) by Z */
ierr = VecXDot(C2,Z,&CKSZ2);CHKERRQ(ierr); /* Recovery checksum2(Z) by Z */
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* Recovery scalar beta by Z and R */
if (rank==0) printf ("Recovery end.\n");
}
else if (i%(itv_c*itv_d) == 0)
{
if (rank==0) printf ("Checkpoint iteration-%d\n",i);
ierr = VecCopy(X,CKPX);CHKERRQ(ierr);
ierr = VecCopy(P,CKPP);CHKERRQ(ierr);
CKPbetaold = betaold;
CKPi = i;
}
}
ksp->its = i+1;
if (beta == 0.0) {
ksp->reason = KSP_CONVERGED_ATOL;
ierr = PetscInfo(ksp,"converged due to beta = 0\n");CHKERRQ(ierr);
break;
#if !defined(PETSC_USE_COMPLEX)
} else if ((i > 0) && (beta*betaold < 0.0)) {
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
ierr = PetscInfo(ksp,"diverging due to indefinite preconditioner\n");CHKERRQ(ierr);
break;
#endif
}
if (!i) {
ierr = VecCopy(Z,P);CHKERRQ(ierr); /* p <- z */
b = 0.0;
/* Dingwen */
ierr = VecXDot(C1,P, &CKSP1);CHKERRQ(ierr); /* Compute the initial checksum1(P) */
ierr = VecXDot(C2,P, &CKSP2);CHKERRQ(ierr); /* Compute the initial checksum2(P) */
/* Dingwen */
} else {
b = beta/betaold;
if (eigs) {
if (ksp->max_it != stored_max_it) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Can not change maxit AND calculate eigenvalues");
e[i] = PetscSqrtReal(PetscAbsScalar(b))/a;
}
ierr = VecAYPX(P,b,Z);CHKERRQ(ierr); /* p <- z + b* p */
/* Dingwen */
CKSP1 = CKSZ1 + b*CKSP1; /* Update checksum1(P) = checksum1(Z) + b*checksum1(P); */
CKSP2 = CKSZ2 + b*CKSP2; /* Update checksum2(P) = checksum2(Z) + b*checksum2(P); */
/* Dingwen */
}
dpiold = dpi;
if (!cg->singlereduction || !i) {
ierr = KSP_MatMult(ksp,Amat,P,W);CHKERRQ(ierr); /* w <- Ap */ /* MVM */
ierr = VecXDot(P,W,&dpi);CHKERRQ(ierr); /* dpi <- p'w */
/* Dingwen */
ierr = VecXDot(CKSAmat1, P, &CKSW1);CHKERRQ(ierr);
CKSW1 = CKSW1 + d1*CKSP1 + d2*CKSP2; /* Update checksum1(W) = checksum1(A)P + d1*checksum1(P) + d2*checksum2(P); */
ierr = VecXDot(CKSAmat2, P, &CKSW2);CHKERRQ(ierr);
CKSW2 = CKSW2 + d2*CKSP1 + d1*CKSP2; /* Update checksum2(W) = checksum2(A)P + d2*checksum1(P) + d1*checksum2(P); */
if((i==41)&&(flag2))
{
pos = 100;
v = 1000;
ierr = VecSetValue(W,pos,v,INSERT_VALUES);CHKERRQ(ierr);
VecAssemblyBegin(W);
VecAssemblyEnd(W);
if (rank==0) printf ("Inject an error in %d-th element of vector W after MVM W=AP at iteration-%d\n", pos,i);
flag2 = PETSC_FALSE;
}
PetscScalar delta1,delta2;
PetscScalar sumW1,sumW2;
ierr = VecXDot(C1,W,&sumW1);CHKERRQ(ierr);
ierr = VecXDot(C2,W,&sumW2);CHKERRQ(ierr);
delta1 = sumW1 - CKSW1;
delta2 = sumW2 - CKSW2;
if (PetscAbsScalar(delta1) > 1.0e-6)
{
VecScatterCreateToAll(W,&ctx,&W_SEQ);
VecScatterBegin(ctx,W,W_SEQ,INSERT_VALUES,SCATTER_FORWARD);
VecScatterEnd(ctx,W,W_SEQ,INSERT_VALUES,SCATTER_FORWARD);
VecGetArray(W_SEQ,&_W);
pos = rint(delta2/delta1);
v = _W[pos];
v = v - delta1;
ierr = VecSetValues(W,1,&pos,&v,INSERT_VALUES);CHKERRQ(ierr);
if (rank==0) printf ("Correct an error of %d-th elements of vector W after MVM W=AP at iteration-%d\n", pos, i);
}
} else {
ierr = VecAYPX(W,beta/betaold,S);CHKERRQ(ierr); /* w <- Ap */
dpi = delta - beta*beta*dpiold/(betaold*betaold); /* dpi <- p'w */
/* Dingwen */
CKSW1 = beta/betaold*CKSW1 + CKSS1; /* Update checksum1(W) = checksum1(S) + beta/betaold*checksum1(W); */
CKSW2 = beta/betaold*CKSW2 + CKSS2; /* Update checksum2(W) = checksum2(S) + beta/betaold*checksum2(W); */
/* Dingwen */
}
betaold = beta;
KSPCheckDot(ksp,beta);
if ((dpi == 0.0) || ((i > 0) && (PetscRealPart(dpi*dpiold) <= 0.0))) {
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
ierr = PetscInfo(ksp,"diverging due to indefinite or negative definite matrix\n");CHKERRQ(ierr);
break;
}
a = beta/dpi; /* a = beta/p'w */
if (eigs) d[i] = PetscSqrtReal(PetscAbsScalar(b))*e[i] + 1.0/a;
ierr = VecAXPY(X,a,P);CHKERRQ(ierr); /* x <- x + ap */
/* Dingwen */
CKSX1 = CKSX1 + a*CKSP1; /* Update checksum1(X) = checksum1(X) + a*checksum1(P); */
CKSX2 = CKSX2 + a*CKSP2; /* Update checksum2(X) = checksum2(X) + a*checksum2(P); */
/* Dingwen */
ierr = VecAXPY(R,-a,W);CHKERRQ(ierr); /* r <- r - aw */
/* Dingwen */
CKSR1 = CKSR1 - a*CKSW1; /* Update checksum1(R) = checksum1(R) - a*checksum1(W); */
CKSR2 = CKSR2 - a*CKSW2; /* Update checksum2(R) = checksum2(R) - a*checksum2(W); */
/* Dingwen */
if (ksp->normtype == KSP_NORM_PRECONDITIONED && ksp->chknorm < i+2) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
/* Dingwen */
ierr = VecXDot(C1,Z, &CKSZ1);CHKERRQ(ierr); /* Update checksum1(Z) */
ierr = VecXDot(C2,Z, &CKSZ2);CHKERRQ(ierr); /* Update checksum2(Z) */
/* Dingwen */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr); /* MVM */
/* Dingwen */
ierr = VecXDot(CKSAmat1, Z, &CKSS1);CHKERRQ(ierr);
CKSS1 = CKSS1 + d1*CKSZ1 + d2*CKSZ2; /* Update checksum1(S) = checksum1(A)Z + d1*chekcsum1(Z) + d2*checksum2(Z); */
ierr = VecXDot(CKSAmat2, Z, &CKSS2);CHKERRQ(ierr);
CKSS2 = CKSS2 + d2*CKSZ1 + d1*CKSZ2; /* Update checksum2(S) = checksum2(A)Z + d2*chekcsum1(Z) + d1*checksum2(Z); */
/* Dingwen */
}
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z */
} else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED && ksp->chknorm < i+2) {
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r */
} else if (ksp->normtype == KSP_NORM_NATURAL) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
/* Dingwen */
ierr = VecXDot(C1,Z, &CKSZ1);CHKERRQ(ierr); /* Update checksum1(Z) */
ierr = VecXDot(C2,Z, &CKSZ2);CHKERRQ(ierr); /* Update checksum2(Z) */
/* Dingwen */
if (cg->singlereduction) {
PetscScalar tmp[2];
Vec vecs[2];
vecs[0] = S; vecs[1] = R;
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecMDot(Z,2,vecs,tmp);CHKERRQ(ierr);
delta = tmp[0]; beta = tmp[1];
} else {
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- r'*z */
}
KSPCheckDot(ksp,beta);
dp = PetscSqrtReal(PetscAbsScalar(beta));
} else {
dp = 0.0;
}
ksp->rnorm = dp;
CHKERRQ(ierr);KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
if ((ksp->normtype != KSP_NORM_PRECONDITIONED && (ksp->normtype != KSP_NORM_NATURAL)) || (ksp->chknorm >= i+2)) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
/* Dingwen */
ierr = VecXDot(C1,Z, &CKSZ1);CHKERRQ(ierr); /* Update checksum1(Z) */
ierr = VecXDot(C2,Z, &CKSZ2);CHKERRQ(ierr); /* Update checksum2(Z) */
/* Dingwen */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
}
}
if ((ksp->normtype != KSP_NORM_NATURAL) || (ksp->chknorm >= i+2)) {
if (cg->singlereduction) {
PetscScalar tmp[2];
Vec vecs[2];
vecs[0] = S; vecs[1] = R;
ierr = VecMDot(Z,2,vecs,tmp);CHKERRQ(ierr);
delta = tmp[0]; beta = tmp[1];
} else {
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
}
KSPCheckDot(ksp,beta);
}
i++;
/* Dingwen */
/* Inject error */
if ((i==50)&&(flag1))
{
pos = 1000;
v = -1;
ierr = VecSetValues(X,1,&pos,&v,INSERT_VALUES);CHKERRQ(ierr);
ierr = VecAssemblyBegin(X);CHKERRQ(ierr);
ierr = VecAssemblyEnd(X);CHKERRQ(ierr);
flag1 = PETSC_FALSE;
if (rank==0)printf ("Inject an error in vector X at the end of iteration-%d\n", i-1);
}
/* Dingwen */
} while (i<ksp->max_it);
/* Dingwen */
ierr = VecXDot(C1,X,&sumX1);CHKERRQ(ierr);
ierr = VecXDot(C1,R,&sumR1);CHKERRQ(ierr);
ierr = VecXDot(C2,X,&sumX2);CHKERRQ(ierr);
ierr = VecXDot(C2,R,&sumR2);CHKERRQ(ierr);
if (rank==0)
{
printf ("sum1 of X = %f\n", sumX1);
printf ("checksum1(X) = %f\n", CKSX1);
printf ("sum2 of X = %f\n", sumX2);
printf ("checksum2(X) = %f\n", CKSX2);
printf ("sum1 of R = %f\n", sumR1);
printf ("checksum1(R) = %f\n", CKSR1);
printf ("sum2 of R = %f\n", sumR2);
printf ("checksum2(R) = %f\n", CKSR2);
}
VecDestroy(&W_SEQ);
VecScatterDestroy(&ctx);
/* Dingwen */
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
if (eigs) cg->ned = ksp->its;
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_LSQR(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,size1,size2;
PetscScalar rho,rhobar,phi,phibar,theta,c,s,tmp,tau;
PetscReal beta,alpha,rnorm;
Vec X,B,V,V1,U,U1,TMP,W,W2,SE,Z = NULL;
Mat Amat,Pmat;
MatStructure pflag;
KSP_LSQR *lsqr = (KSP_LSQR*)ksp->data;
PetscBool diagonalscale,nopreconditioner;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat,&pflag);CHKERRQ(ierr);
ierr = PetscObjectTypeCompare((PetscObject)ksp->pc,PCNONE,&nopreconditioner);CHKERRQ(ierr);
/* nopreconditioner =PETSC_FALSE; */
/* Calculate norm of right hand side */
ierr = VecNorm(ksp->vec_rhs,NORM_2,&lsqr->rhs_norm);CHKERRQ(ierr);
/* mark norm of matrix with negative number to indicate it has not yet been computed */
lsqr->anorm = -1.0;
/* vectors of length m, where system size is mxn */
B = ksp->vec_rhs;
U = lsqr->vwork_m[0];
U1 = lsqr->vwork_m[1];
/* vectors of length n */
X = ksp->vec_sol;
W = lsqr->vwork_n[0];
V = lsqr->vwork_n[1];
V1 = lsqr->vwork_n[2];
W2 = lsqr->vwork_n[3];
if (!nopreconditioner) Z = lsqr->vwork_n[4];
/* standard error vector */
SE = lsqr->se;
if (SE) {
ierr = VecGetSize(SE,&size1);CHKERRQ(ierr);
ierr = VecGetSize(X,&size2);CHKERRQ(ierr);
if (size1 != size2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Standard error vector (size %d) does not match solution vector (size %d)",size1,size2);
ierr = VecSet(SE,0.0);CHKERRQ(ierr);
}
/* Compute initial residual, temporarily use work vector u */
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,U);CHKERRQ(ierr); /* u <- b - Ax */
ierr = VecAYPX(U,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,U);CHKERRQ(ierr); /* u <- b (x is 0) */
}
/* Test for nothing to do */
ierr = VecNorm(U,NORM_2,&rnorm);CHKERRQ(ierr);
ierr = PetscObjectAMSTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ksp->rnorm = rnorm;
ierr = PetscObjectAMSGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
beta = rnorm;
ierr = VecScale(U,1.0/beta);CHKERRQ(ierr);
ierr = KSP_MatMultTranspose(ksp,Amat,U,V);CHKERRQ(ierr);
if (nopreconditioner) {
ierr = VecNorm(V,NORM_2,&alpha);CHKERRQ(ierr);
} else {
ierr = PCApply(ksp->pc,V,Z);CHKERRQ(ierr);
ierr = VecDotRealPart(V,Z,&alpha);CHKERRQ(ierr);
if (alpha <= 0.0) {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
PetscFunctionReturn(0);
}
alpha = PetscSqrtReal(alpha);
ierr = VecScale(Z,1.0/alpha);CHKERRQ(ierr);
}
ierr = VecScale(V,1.0/alpha);CHKERRQ(ierr);
if (nopreconditioner) {
ierr = VecCopy(V,W);CHKERRQ(ierr);
} else {
ierr = VecCopy(Z,W);CHKERRQ(ierr);
}
lsqr->arnorm = alpha * beta;
phibar = beta;
rhobar = alpha;
i = 0;
do {
if (nopreconditioner) {
ierr = KSP_MatMult(ksp,Amat,V,U1);CHKERRQ(ierr);
} else {
ierr = KSP_MatMult(ksp,Amat,Z,U1);CHKERRQ(ierr);
}
ierr = VecAXPY(U1,-alpha,U);CHKERRQ(ierr);
ierr = VecNorm(U1,NORM_2,&beta);CHKERRQ(ierr);
if (beta == 0.0) {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
ierr = VecScale(U1,1.0/beta);CHKERRQ(ierr);
ierr = KSP_MatMultTranspose(ksp,Amat,U1,V1);CHKERRQ(ierr);
ierr = VecAXPY(V1,-beta,V);CHKERRQ(ierr);
if (nopreconditioner) {
ierr = VecNorm(V1,NORM_2,&alpha);CHKERRQ(ierr);
} else {
ierr = PCApply(ksp->pc,V1,Z);CHKERRQ(ierr);
ierr = VecDotRealPart(V1,Z,&alpha);CHKERRQ(ierr);
if (alpha <= 0.0) {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
alpha = PetscSqrtReal(alpha);
ierr = VecScale(Z,1.0/alpha);CHKERRQ(ierr);
}
ierr = VecScale(V1,1.0/alpha);CHKERRQ(ierr);
rho = PetscSqrtScalar(rhobar*rhobar + beta*beta);
c = rhobar / rho;
s = beta / rho;
theta = s * alpha;
rhobar = -c * alpha;
phi = c * phibar;
phibar = s * phibar;
tau = s * phi;
ierr = VecAXPY(X,phi/rho,W);CHKERRQ(ierr); /* x <- x + (phi/rho) w */
if (SE) {
ierr = VecCopy(W,W2);CHKERRQ(ierr);
ierr = VecSquare(W2);CHKERRQ(ierr);
ierr = VecScale(W2,1.0/(rho*rho));CHKERRQ(ierr);
ierr = VecAXPY(SE, 1.0, W2);CHKERRQ(ierr); /* SE <- SE + (w^2/rho^2) */
}
if (nopreconditioner) {
ierr = VecAYPX(W,-theta/rho,V1);CHKERRQ(ierr); /* w <- v - (theta/rho) w */
} else {
ierr = VecAYPX(W,-theta/rho,Z);CHKERRQ(ierr); /* w <- z - (theta/rho) w */
}
lsqr->arnorm = alpha*PetscAbsScalar(tau);
rnorm = PetscRealPart(phibar);
ierr = PetscObjectAMSTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = rnorm;
ierr = PetscObjectAMSGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
SWAP(U1,U,TMP);
SWAP(V1,V,TMP);
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it && !ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
/* Finish off the standard error estimates */
if (SE) {
tmp = 1.0;
ierr = MatGetSize(Amat,&size1,&size2);CHKERRQ(ierr);
if (size1 > size2) tmp = size1 - size2;
tmp = rnorm / PetscSqrtScalar(tmp);
ierr = VecSqrtAbs(SE);CHKERRQ(ierr);
ierr = VecScale(SE,tmp);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_BiCG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscBool diagonalscale;
PetscScalar dpi,a=1.0,beta,betaold=1.0,b,ma;
PetscReal dp;
Vec X,B,Zl,Zr,Rl,Rr,Pl,Pr;
Mat Amat,Pmat;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
X = ksp->vec_sol;
B = ksp->vec_rhs;
Rl = ksp->work[0];
Zl = ksp->work[1];
Pl = ksp->work[2];
Rr = ksp->work[3];
Zr = ksp->work[4];
Pr = ksp->work[5];
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,Rr);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(Rr,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,Rr);CHKERRQ(ierr); /* r <- b (x is 0) */
}
ierr = VecCopy(Rr,Rl);CHKERRQ(ierr);
ierr = KSP_PCApply(ksp,Rr,Zr);CHKERRQ(ierr); /* z <- Br */
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = KSP_PCApplyTranspose(ksp,Rl,Zl);CHKERRQ(ierr);
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = VecConjugate(Zl);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNorm(Zr,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z */
} else {
ierr = VecNorm(Rr,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r */
}
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ksp->rnorm = dp;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
i = 0;
do {
ierr = VecDot(Zr,Rl,&beta);CHKERRQ(ierr); /* beta <- r'z */
if (!i) {
if (beta == 0.0) {
ksp->reason = KSP_DIVERGED_BREAKDOWN_BICG;
PetscFunctionReturn(0);
}
ierr = VecCopy(Zr,Pr);CHKERRQ(ierr); /* p <- z */
ierr = VecCopy(Zl,Pl);CHKERRQ(ierr);
} else {
b = beta/betaold;
ierr = VecAYPX(Pr,b,Zr);CHKERRQ(ierr); /* p <- z + b* p */
b = PetscConj(b);
ierr = VecAYPX(Pl,b,Zl);CHKERRQ(ierr);
}
betaold = beta;
ierr = KSP_MatMult(ksp,Amat,Pr,Zr);CHKERRQ(ierr); /* z <- Kp */
ierr = VecConjugate(Pl);CHKERRQ(ierr);
ierr = KSP_MatMultTranspose(ksp,Amat,Pl,Zl);CHKERRQ(ierr);
ierr = VecConjugate(Pl);CHKERRQ(ierr);
ierr = VecConjugate(Zl);CHKERRQ(ierr);
ierr = VecDot(Zr,Pl,&dpi);CHKERRQ(ierr); /* dpi <- z'p */
a = beta/dpi; /* a = beta/p'z */
ierr = VecAXPY(X,a,Pr);CHKERRQ(ierr); /* x <- x + ap */
ma = -a;
ierr = VecAXPY(Rr,ma,Zr);CHKERRQ(ierr);
ma = PetscConj(ma);
ierr = VecAXPY(Rl,ma,Zl);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = KSP_PCApply(ksp,Rr,Zr);CHKERRQ(ierr); /* z <- Br */
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = KSP_PCApplyTranspose(ksp,Rl,Zl);CHKERRQ(ierr);
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = VecConjugate(Zl);CHKERRQ(ierr);
ierr = VecNorm(Zr,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z */
} else {
ierr = VecNorm(Rr,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r */
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = i+1;
ksp->rnorm = dp;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = KSP_PCApply(ksp,Rr,Zr);CHKERRQ(ierr); /* z <- Br */
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = KSP_PCApplyTranspose(ksp,Rl,Zl);CHKERRQ(ierr);
ierr = VecConjugate(Rl);CHKERRQ(ierr);
ierr = VecConjugate(Zl);CHKERRQ(ierr);
}
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_CG(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,stored_max_it,eigs;
PetscScalar dpi = 0.0,a = 1.0,beta,betaold = 1.0,b = 0,*e = 0,*d = 0,delta,dpiold;
PetscReal dp = 0.0;
Vec X,B,Z,R,P,S,W;
KSP_CG *cg;
Mat Amat,Pmat;
PetscBool diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
cg = (KSP_CG*)ksp->data;
eigs = ksp->calc_sings;
stored_max_it = ksp->max_it;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
P = ksp->work[2];
if (cg->singlereduction) {
S = ksp->work[3];
W = ksp->work[4];
} else {
S = 0; /* unused */
W = Z;
}
#define VecXDot(x,y,a) (((cg->type) == (KSP_CG_HERMITIAN)) ? VecDot(x,y,a) : VecTDot(x,y,a))
if (eigs) {e = cg->e; d = cg->d; e[0] = 0.0; }
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
ksp->its = 0;
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr);
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* r <- b (x is 0) */
}
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z = e'*A'*B'*B*A'*e' */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r = e'*A'*A*e */
break;
case KSP_NORM_NATURAL:
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecXDot(Z,S,&delta);CHKERRQ(ierr);
}
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
if (PetscIsInfOrNanScalar(beta)) {
if (ksp->errorifnotconverged) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged due to Nan or Inf inner product");
else {
ksp->reason = KSP_DIVERGED_NANORINF;
PetscFunctionReturn(0);
}
}
dp = PetscSqrtReal(PetscAbsScalar(beta)); /* dp <- r'*z = r'*B*r = e'*A'*B*A*e */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ksp->rnorm = dp;
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr); /* test for convergence */
if (ksp->reason) PetscFunctionReturn(0);
if (ksp->normtype != KSP_NORM_PRECONDITIONED && (ksp->normtype != KSP_NORM_NATURAL)) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
}
if (ksp->normtype != KSP_NORM_NATURAL) {
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecXDot(Z,S,&delta);CHKERRQ(ierr);
}
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
if (PetscIsInfOrNanScalar(beta)) {
if (ksp->errorifnotconverged) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged due to Nan or Inf inner product");
else {
ksp->reason = KSP_DIVERGED_NANORINF;
PetscFunctionReturn(0);
}
}
}
i = 0;
do {
ksp->its = i+1;
if (beta == 0.0) {
ksp->reason = KSP_CONVERGED_ATOL;
ierr = PetscInfo(ksp,"converged due to beta = 0\n");CHKERRQ(ierr);
break;
#if !defined(PETSC_USE_COMPLEX)
} else if ((i > 0) && (beta*betaold < 0.0)) {
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
ierr = PetscInfo(ksp,"diverging due to indefinite preconditioner\n");CHKERRQ(ierr);
break;
#endif
}
if (!i) {
ierr = VecCopy(Z,P);CHKERRQ(ierr); /* p <- z */
b = 0.0;
} else {
b = beta/betaold;
if (eigs) {
if (ksp->max_it != stored_max_it) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Can not change maxit AND calculate eigenvalues");
e[i] = PetscSqrtReal(PetscAbsScalar(b))/a;
}
ierr = VecAYPX(P,b,Z);CHKERRQ(ierr); /* p <- z + b* p */
}
dpiold = dpi;
if (!cg->singlereduction || !i) {
ierr = KSP_MatMult(ksp,Amat,P,W);CHKERRQ(ierr); /* w <- Ap */
ierr = VecXDot(P,W,&dpi);CHKERRQ(ierr); /* dpi <- p'w */
} else {
ierr = VecAYPX(W,beta/betaold,S);CHKERRQ(ierr); /* w <- Ap */
dpi = delta - beta*beta*dpiold/(betaold*betaold); /* dpi <- p'w */
}
betaold = beta;
if (PetscIsInfOrNanScalar(dpi)) {
if (ksp->errorifnotconverged) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged due to Nan or Inf inner product");
else {
ksp->reason = KSP_DIVERGED_NANORINF;
PetscFunctionReturn(0);
}
}
if ((dpi == 0.0) || ((i > 0) && (PetscRealPart(dpi*dpiold) <= 0.0))) {
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
ierr = PetscInfo(ksp,"diverging due to indefinite or negative definite matrix\n");CHKERRQ(ierr);
break;
}
a = beta/dpi; /* a = beta/p'w */
if (eigs) d[i] = PetscSqrtReal(PetscAbsScalar(b))*e[i] + 1.0/a;
ierr = VecAXPY(X,a,P);CHKERRQ(ierr); /* x <- x + ap */
ierr = VecAXPY(R,-a,W);CHKERRQ(ierr); /* r <- r - aw */
if (ksp->normtype == KSP_NORM_PRECONDITIONED && ksp->chknorm < i+2) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
}
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- z'*z */
} else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED && ksp->chknorm < i+2) {
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- r'*r */
} else if (ksp->normtype == KSP_NORM_NATURAL) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
PetscScalar tmp[2];
Vec vecs[2];
vecs[0] = S; vecs[1] = R;
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
ierr = VecMDot(Z,2,vecs,tmp);CHKERRQ(ierr);
delta = tmp[0]; beta = tmp[1];
} else {
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- r'*z */
}
if (PetscIsInfOrNanScalar(beta)) {
if (ksp->errorifnotconverged) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged due to Nan or Inf inner product");
else {
ksp->reason = KSP_DIVERGED_NANORINF;
PetscFunctionReturn(0);
}
}
dp = PetscSqrtReal(PetscAbsScalar(beta));
} else {
dp = 0.0;
}
ksp->rnorm = dp;
CHKERRQ(ierr);KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
if ((ksp->normtype != KSP_NORM_PRECONDITIONED && (ksp->normtype != KSP_NORM_NATURAL)) || (ksp->chknorm >= i+2)) {
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
if (cg->singlereduction) {
ierr = KSP_MatMult(ksp,Amat,Z,S);CHKERRQ(ierr);
}
}
if ((ksp->normtype != KSP_NORM_NATURAL) || (ksp->chknorm >= i+2)) {
if (cg->singlereduction) {
PetscScalar tmp[2];
Vec vecs[2];
vecs[0] = S; vecs[1] = R;
ierr = VecMDot(Z,2,vecs,tmp);CHKERRQ(ierr);
delta = tmp[0]; beta = tmp[1];
} else {
ierr = VecXDot(Z,R,&beta);CHKERRQ(ierr); /* beta <- z'*r */
}
if (PetscIsInfOrNanScalar(beta)) {
if (ksp->errorifnotconverged) SETERRQ(PetscObjectComm((PetscObject)ksp),PETSC_ERR_NOT_CONVERGED,"KSPSolve has not converged due to Nan or Inf inner product");
else {
ksp->reason = KSP_DIVERGED_NANORINF;
PetscFunctionReturn(0);
}
}
}
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}
PetscErrorCode KSPSolve_Richardson(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,maxit;
PetscReal rnorm = 0.0,abr;
PetscScalar scale,rdot;
Vec x,b,r,z,w = NULL,y = NULL;
PetscInt xs, ws;
Mat Amat,Pmat;
KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;
PetscBool exists,diagonalscale;
PetscFunctionBegin;
ierr = PCGetDiagonalScale(ksp->pc,&diagonalscale);CHKERRQ(ierr);
if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);
ksp->its = 0;
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
x = ksp->vec_sol;
b = ksp->vec_rhs;
ierr = VecGetSize(x,&xs);CHKERRQ(ierr);
ierr = VecGetSize(ksp->work[0],&ws);CHKERRQ(ierr);
if (xs != ws) {
if (richardsonP->selfscale) {
ierr = KSPSetWorkVecs(ksp,4);CHKERRQ(ierr);
} else {
ierr = KSPSetWorkVecs(ksp,2);CHKERRQ(ierr);
}
}
r = ksp->work[0];
z = ksp->work[1];
if (richardsonP->selfscale) {
w = ksp->work[2];
y = ksp->work[3];
}
maxit = ksp->max_it;
/* if user has provided fast Richardson code use that */
ierr = PCApplyRichardsonExists(ksp->pc,&exists);CHKERRQ(ierr);
if (exists && !ksp->numbermonitors && !ksp->transpose_solve & !ksp->nullsp) {
PCRichardsonConvergedReason reason;
ierr = PCApplyRichardson(ksp->pc,b,x,r,ksp->rtol,ksp->abstol,ksp->divtol,maxit,ksp->guess_zero,&ksp->its,&reason);CHKERRQ(ierr);
ksp->reason = (KSPConvergedReason)reason;
PetscFunctionReturn(0);
}
scale = richardsonP->scale;
if (!ksp->guess_zero) { /* r <- b - A x */
ierr = KSP_MatMult(ksp,Amat,x,r);CHKERRQ(ierr);
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
} else {
ierr = VecCopy(b,r);CHKERRQ(ierr);
}
ksp->its = 0;
if (richardsonP->selfscale) {
ierr = KSP_PCApply(ksp,r,z);CHKERRQ(ierr); /* z <- B r */
for (i=0; i<maxit; i++) {
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- r'*r */
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
} else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNorm(z,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- z'*z */
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
ierr = KSP_PCApplyBAorAB(ksp,z,y,w);CHKERRQ(ierr); /* y = BAz = BABr */
ierr = VecDotNorm2(z,y,&rdot,&abr);CHKERRQ(ierr); /* rdot = (Br)^T(BABR); abr = (BABr)^T (BABr) */
scale = rdot/abr;
ierr = PetscInfo1(ksp,"Self-scale factor %g\n",(double)PetscRealPart(scale));CHKERRQ(ierr);
ierr = VecAXPY(x,scale,z);CHKERRQ(ierr); /* x <- x + scale z */
ierr = VecAXPY(r,-scale,w);CHKERRQ(ierr); /* r <- r - scale*Az */
ierr = VecAXPY(z,-scale,y);CHKERRQ(ierr); /* z <- z - scale*y */
ksp->its++;
}
} else {
for (i=0; i<maxit; i++) {
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- r'*r */
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
ierr = KSP_PCApply(ksp,r,z);CHKERRQ(ierr); /* z <- B r */
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNorm(z,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- z'*z */
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
}
ierr = VecAXPY(x,scale,z);CHKERRQ(ierr); /* x <- x + scale z */
ksp->its++;
if (i+1 < maxit || ksp->normtype != KSP_NORM_NONE) {
ierr = KSP_MatMult(ksp,Amat,x,r);CHKERRQ(ierr); /* r <- b - Ax */
ierr = VecAYPX(r,-1.0,b);CHKERRQ(ierr);
}
}
}
if (!ksp->reason) {
if (ksp->normtype != KSP_NORM_NONE) {
if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNorm(r,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- r'*r */
} else {
ierr = KSP_PCApply(ksp,r,z);CHKERRQ(ierr); /* z <- B r */
ierr = VecNorm(z,NORM_2,&rnorm);CHKERRQ(ierr); /* rnorm <- z'*z */
}
ksp->rnorm = rnorm;
ierr = KSPLogResidualHistory(ksp,rnorm);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i,rnorm);CHKERRQ(ierr);
}
if (ksp->its >= ksp->max_it) {
if (ksp->normtype != KSP_NORM_NONE) {
ierr = (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
} else {
ksp->reason = KSP_CONVERGED_ITS;
}
}
}
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_PIPEFCG_cycle(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i,j,k,idx,kdx,mi;
KSP_PIPEFCG *pipefcg;
PetscScalar alpha=0.0,gamma,*betas,*dots;
PetscReal dp=0.0, delta,*eta,*etas;
Vec B,R,Z,X,Qcurr,W,ZETAcurr,M,N,Pcurr,Scurr,*redux;
Mat Amat,Pmat;
PetscFunctionBegin;
/* We have not checked these routines for use with complex numbers. The inner products
are likely not defined correctly for that case */
#if (defined(PETSC_USE_COMPLEX) && !defined(PETSC_SKIP_COMPLEX))
SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"PIPEFGMRES has not been implemented for use with complex scalars");
#endif
#define VecXDot(x,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecDot (x,y,a) : VecTDot (x,y,a))
#define VecXDotBegin(x,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecDotBegin (x,y,a) : VecTDotBegin (x,y,a))
#define VecXDotEnd(x,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecDotEnd (x,y,a) : VecTDotEnd (x,y,a))
#define VecMXDot(x,n,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecMDot (x,n,y,a) : VecMTDot (x,n,y,a))
#define VecMXDotBegin(x,n,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecMDotBegin (x,n,y,a) : VecMTDotBegin (x,n,y,a))
#define VecMXDotEnd(x,n,y,a) (((pipefcg->type) == (KSP_CG_HERMITIAN)) ? VecMDotEnd (x,n,y,a) : VecMTDotEnd (x,n,y,a))
pipefcg = (KSP_PIPEFCG*)ksp->data;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
Z = ksp->work[1];
W = ksp->work[2];
M = ksp->work[3];
N = ksp->work[4];
redux = pipefcg->redux;
dots = pipefcg->dots;
etas = pipefcg->etas;
betas = dots; /* dots takes the result of all dot products of which the betas are a subset */
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat);CHKERRQ(ierr);
/* Compute cycle initial residual */
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr);
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr); /* r <- b - Ax */
ierr = KSP_PCApply(ksp,R,Z);CHKERRQ(ierr); /* z <- Br */
Pcurr = pipefcg->Pvecs[0];
Scurr = pipefcg->Svecs[0];
Qcurr = pipefcg->Qvecs[0];
ZETAcurr = pipefcg->ZETAvecs[0];
ierr = VecCopy(Z,Pcurr);CHKERRQ(ierr);
ierr = KSP_MatMult(ksp,Amat,Pcurr,Scurr);CHKERRQ(ierr); /* S = Ap */
ierr = VecCopy(Scurr,W);CHKERRQ(ierr); /* w = s = Az */
/* Initial state of pipelining intermediates */
redux[0] = R;
redux[1] = W;
ierr = VecMXDotBegin(Z,2,redux,dots);CHKERRQ(ierr);
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)Z));CHKERRQ(ierr); /* perform asynchronous reduction */
ierr = KSP_PCApply(ksp,W,M);CHKERRQ(ierr); /* m = B(w) */
ierr = KSP_MatMult(ksp,Amat,M,N);CHKERRQ(ierr); /* n = Am */
ierr = VecCopy(M,Qcurr);CHKERRQ(ierr); /* q = m */
ierr = VecCopy(N,ZETAcurr);CHKERRQ(ierr); /* zeta = n */
ierr = VecMXDotEnd(Z,2,redux,dots);CHKERRQ(ierr);
gamma = dots[0];
delta = PetscRealPart(dots[1]);
etas[0] = delta;
alpha = gamma/delta;
i = 0;
do {
ksp->its++;
/* Update X, R, Z, W */
ierr = VecAXPY(X,+alpha,Pcurr);CHKERRQ(ierr); /* x <- x + alpha * pi */
ierr = VecAXPY(R,-alpha,Scurr);CHKERRQ(ierr); /* r <- r - alpha * si */
ierr = VecAXPY(Z,-alpha,Qcurr);CHKERRQ(ierr); /* z <- z - alpha * qi */
ierr = VecAXPY(W,-alpha,ZETAcurr);CHKERRQ(ierr); /* w <- w - alpha * zetai */
/* Compute norm for convergence check */
switch (ksp->normtype) {
case KSP_NORM_PRECONDITIONED:
ierr = VecNorm(Z,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(z'*z) = sqrt(e'*A'*B'*B*A*e) */
break;
case KSP_NORM_UNPRECONDITIONED:
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- sqrt(r'*r) = sqrt(e'*A'*A*e) */
break;
case KSP_NORM_NATURAL:
dp = PetscSqrtReal(PetscAbsScalar(gamma)); /* dp <- sqrt(r'*z) = sqrt(e'*A'*B*A*e) */
break;
case KSP_NORM_NONE:
dp = 0.0;
break;
default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
}
/* Check for convergence */
ksp->rnorm = dp;
KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
/* Computations of current iteration done */
++i;
/* If needbe, allocate a new chunk of vectors in P and C */
ierr = KSPAllocateVectors_PIPEFCG(ksp,i+1,pipefcg->vecb);CHKERRQ(ierr);
/* Note that we wrap around and start clobbering old vectors */
idx = i % (pipefcg->mmax+1);
Pcurr = pipefcg->Pvecs[idx];
Scurr = pipefcg->Svecs[idx];
Qcurr = pipefcg->Qvecs[idx];
ZETAcurr = pipefcg->ZETAvecs[idx];
eta = pipefcg->etas+idx;
/* number of old directions to orthogonalize against */
switch(pipefcg->truncstrat){
case KSP_FCD_TRUNC_TYPE_STANDARD:
mi = pipefcg->mmax;
break;
case KSP_FCD_TRUNC_TYPE_NOTAY:
mi = ((i-1) % pipefcg->mmax)+1;
break;
default:
SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unrecognized Truncation Strategy");
}
/* Pick old p,s,q,zeta in a way suitable for VecMDot */
ierr = VecCopy(Z,Pcurr);CHKERRQ(ierr);
for(k=PetscMax(0,i-mi),j=0;k<i;++j,++k){
kdx = k % (pipefcg->mmax+1);
pipefcg->Pold[j] = pipefcg->Pvecs[kdx];
pipefcg->Sold[j] = pipefcg->Svecs[kdx];
pipefcg->Qold[j] = pipefcg->Qvecs[kdx];
pipefcg->ZETAold[j] = pipefcg->ZETAvecs[kdx];
redux[j] = pipefcg->Svecs[kdx];
}
redux[j] = R; /* If the above loop is not executed redux contains only R => all beta_k = 0, only gamma, delta != 0 */
redux[j+1] = W;
ierr = VecMXDotBegin(Z,j+2,redux,betas);CHKERRQ(ierr); /* Start split reductions for beta_k = (z,s_k), gamma = (z,r), delta = (z,w) */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)Z));CHKERRQ(ierr); /* perform asynchronous reduction */
ierr = VecWAXPY(N,-1.0,R,W);CHKERRQ(ierr); /* m = u + B(w-r): (a) ntmp = w-r */
ierr = KSP_PCApply(ksp,N,M);CHKERRQ(ierr); /* m = u + B(w-r): (b) mtmp = B(ntmp) = B(w-r) */
ierr = VecAXPY(M,1.0,Z);CHKERRQ(ierr); /* m = u + B(w-r): (c) m = z + mtmp */
ierr = KSP_MatMult(ksp,Amat,M,N);CHKERRQ(ierr); /* n = Am */
ierr = VecMXDotEnd(Z,j+2,redux,betas);CHKERRQ(ierr); /* Finish split reductions */
gamma = betas[j];
delta = PetscRealPart(betas[j+1]);
*eta = 0.;
for(k=PetscMax(0,i-mi),j=0;k<i;++j,++k){
kdx = k % (pipefcg->mmax+1);
betas[j] /= -etas[kdx]; /* betak /= etak */
*eta -= ((PetscReal)(PetscAbsScalar(betas[j])*PetscAbsScalar(betas[j]))) * etas[kdx];
/* etaitmp = -betaik^2 * etak */
}
*eta += delta; /* etai = delta -betaik^2 * etak */
if(*eta < 0.) {
pipefcg->norm_breakdown = PETSC_TRUE;
ierr = PetscInfo1(ksp,"Restart due to square root breakdown at it = \n",ksp->its);CHKERRQ(ierr);
break;
} else {
alpha= gamma/(*eta); /* alpha = gamma/etai */
}
/* project out stored search directions using classical G-S */
ierr = VecCopy(Z,Pcurr);CHKERRQ(ierr);
ierr = VecCopy(W,Scurr);CHKERRQ(ierr);
ierr = VecCopy(M,Qcurr);CHKERRQ(ierr);
ierr = VecCopy(N,ZETAcurr);CHKERRQ(ierr);
ierr = VecMAXPY(Pcurr ,j,betas,pipefcg->Pold);CHKERRQ(ierr); /* pi <- ui - sum_k beta_k p_k */
ierr = VecMAXPY(Scurr ,j,betas,pipefcg->Sold);CHKERRQ(ierr); /* si <- wi - sum_k beta_k s_k */
ierr = VecMAXPY(Qcurr ,j,betas,pipefcg->Qold);CHKERRQ(ierr); /* qi <- m - sum_k beta_k q_k */
ierr = VecMAXPY(ZETAcurr,j,betas,pipefcg->ZETAold);CHKERRQ(ierr); /* zetai <- n - sum_k beta_k zeta_k */
} while (ksp->its < ksp->max_it);
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_CR(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i = 0;
MatStructure pflag;
PetscReal dp;
PetscScalar ai, bi;
PetscScalar apq,btop, bbot;
Vec X,B,R,RT,P,AP,ART,Q;
Mat Amat, Pmat;
PetscFunctionBegin;
X = ksp->vec_sol;
B = ksp->vec_rhs;
R = ksp->work[0];
RT = ksp->work[1];
P = ksp->work[2];
AP = ksp->work[3];
ART = ksp->work[4];
Q = ksp->work[5];
/* R is the true residual norm, RT is the preconditioned residual norm */
ierr = PCGetOperators(ksp->pc,&Amat,&Pmat,&pflag);CHKERRQ(ierr);
if (!ksp->guess_zero) {
ierr = KSP_MatMult(ksp,Amat,X,R);CHKERRQ(ierr); /* R <- A*X */
ierr = VecAYPX(R,-1.0,B);CHKERRQ(ierr); /* R <- B-R == B-A*X */
} else {
ierr = VecCopy(B,R);CHKERRQ(ierr); /* R <- B (X is 0) */
}
ierr = KSP_PCApply(ksp,R,P);CHKERRQ(ierr); /* P <- B*R */
ierr = KSP_MatMult(ksp,Amat,P,AP);CHKERRQ(ierr); /* AP <- A*P */
ierr = VecCopy(P,RT);CHKERRQ(ierr); /* RT <- P */
ierr = VecCopy(AP,ART);CHKERRQ(ierr); /* ART <- AP */
ierr = VecDotBegin(RT,ART,&btop);CHKERRQ(ierr); /* (RT,ART) */
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormBegin(RT,NORM_2,&dp);CHKERRQ(ierr); /* dp <- RT'*RT */
ierr = VecDotEnd (RT,ART,&btop);CHKERRQ(ierr); /* (RT,ART) */
ierr = VecNormEnd (RT,NORM_2,&dp);CHKERRQ(ierr); /* dp <- RT'*RT */
} else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecNormBegin(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- R'*R */
ierr = VecDotEnd (RT,ART,&btop);CHKERRQ(ierr); /* (RT,ART) */
ierr = VecNormEnd (R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- RT'*RT */
} else if (ksp->normtype == KSP_NORM_NATURAL) {
ierr = VecDotEnd (RT,ART,&btop);CHKERRQ(ierr); /* (RT,ART) */
dp = PetscSqrtReal(PetscAbsScalar(btop)); /* dp = sqrt(R,AR) */
}
if (PetscAbsScalar(btop) < 0.0) {
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
ierr = PetscInfo(ksp,"diverging due to indefinite or negative definite matrix\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
ksp->its = 0;
ierr = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ierr = PetscObjectAMSTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = dp;
ierr = PetscObjectAMSGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
i = 0;
do {
ierr = KSP_PCApply(ksp,AP,Q);CHKERRQ(ierr); /* Q <- B* AP */
ierr = VecDot(AP,Q,&apq);CHKERRQ(ierr);
if (PetscRealPart(apq) <= 0.0) {
ksp->reason = KSP_DIVERGED_INDEFINITE_PC;
ierr = PetscInfo(ksp,"KSPSolve_CR:diverging due to indefinite or negative definite PC\n");CHKERRQ(ierr);
break;
}
ai = btop/apq; /* ai = (RT,ART)/(AP,Q) */
ierr = VecAXPY(X,ai,P);CHKERRQ(ierr); /* X <- X + ai*P */
ierr = VecAXPY(RT,-ai,Q);CHKERRQ(ierr); /* RT <- RT - ai*Q */
ierr = KSP_MatMult(ksp,Amat,RT,ART);CHKERRQ(ierr); /* ART <- A*RT */
bbot = btop;
ierr = VecDotBegin(RT,ART,&btop);CHKERRQ(ierr);
if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
ierr = VecNormBegin(RT,NORM_2,&dp);CHKERRQ(ierr); /* dp <- || RT || */
ierr = VecDotEnd (RT,ART,&btop);CHKERRQ(ierr);
ierr = VecNormEnd (RT,NORM_2,&dp);CHKERRQ(ierr); /* dp <- || RT || */
} else if (ksp->normtype == KSP_NORM_NATURAL) {
ierr = VecDotEnd(RT,ART,&btop);CHKERRQ(ierr);
dp = PetscSqrtReal(PetscAbsScalar(btop)); /* dp = sqrt(R,AR) */
} else if (ksp->normtype == KSP_NORM_NONE) {
ierr = VecDotEnd(RT,ART,&btop);CHKERRQ(ierr);
dp = 0.0;
} else if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
ierr = VecAXPY(R,ai,AP);CHKERRQ(ierr); /* R <- R - ai*AP */
ierr = VecNormBegin(R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- R'*R */
ierr = VecDotEnd (RT,ART,&btop);CHKERRQ(ierr);
ierr = VecNormEnd (R,NORM_2,&dp);CHKERRQ(ierr); /* dp <- R'*R */
} else SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"KSPNormType of %d not supported",(int)ksp->normtype);
if (PetscAbsScalar(btop) < 0.0) {
ksp->reason = KSP_DIVERGED_INDEFINITE_MAT;
ierr = PetscInfo(ksp,"diverging due to indefinite or negative definite PC\n");CHKERRQ(ierr);
break;
}
ierr = PetscObjectAMSTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = dp;
ierr = PetscObjectAMSGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = KSPLogResidualHistory(ksp,dp);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,i+1,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,i+1,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) break;
bi = btop/bbot;
ierr = VecAYPX(P,bi,RT);CHKERRQ(ierr); /* P <- RT + Bi P */
ierr = VecAYPX(AP,bi,ART);CHKERRQ(ierr); /* AP <- ART + Bi AP */
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
PetscFunctionReturn(0);
}