static PetscErrorCode KSPSolve_CGLS(KSP ksp)
{
PetscErrorCode ierr;
KSP_CGLS *cgls = (KSP_CGLS*)ksp->data;
Mat A;
Vec x,b,r,p,q,ss;
PetscScalar beta;
PetscReal alpha,gamma,oldgamma;
PetscInt maxiter_ls = 15;
PetscFunctionBegin;
ierr = KSPGetOperators(ksp,&A,NULL);CHKERRQ(ierr); /* Matrix of the system */
/* vectors of length n, where system size is mxn */
x = ksp->vec_sol; /* Solution vector */
p = cgls->vwork_n[0];
ss = cgls->vwork_n[1];
/* vectors of length m, where system size is mxn */
b = ksp->vec_rhs; /* Right-hand side vector */
r = cgls->vwork_m[0];
q = cgls->vwork_m[1];
/* Minimization with the CGLS method */
ksp->its = 0;
ierr = MatMult(A,x,r);CHKERRQ(ierr);
ierr = VecAYPX(r,-1,b);CHKERRQ(ierr); /* r_0 = b - A * x_0 */
ierr = MatMultTranspose(A,r,p);CHKERRQ(ierr); /* p_0 = A^T * r_0 */
ierr = VecCopy(p,ss);CHKERRQ(ierr); /* s_0 = p_0 */
ierr = VecNorm(ss,NORM_2,&gamma);CHKERRQ(ierr);
KSPCheckNorm(ksp,gamma);
ksp->rnorm = gamma;
ierr = (*ksp->converged)(ksp,ksp->its,ksp->rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
gamma = gamma*gamma; /* gamma = norm2(s)^2 */
do {
ierr = MatMult(A,p,q);CHKERRQ(ierr); /* q = A * p */
ierr = VecNorm(q,NORM_2,&alpha);CHKERRQ(ierr);
KSPCheckNorm(ksp,alpha);
alpha = alpha*alpha; /* alpha = norm2(q)^2 */
alpha = gamma / alpha; /* alpha = gamma / alpha */
ierr = VecAXPY(x,alpha,p);CHKERRQ(ierr); /* x += alpha * p */
ierr = VecAXPY(r,-alpha,q);CHKERRQ(ierr); /* r -= alpha * q */
ierr = MatMultTranspose(A,r,ss);CHKERRQ(ierr); /* ss = A^T * r */
oldgamma = gamma; /* oldgamma = gamma */
ierr = VecNorm(ss,NORM_2,&gamma);CHKERRQ(ierr);
KSPCheckNorm(ksp,gamma);
ksp->its++;
ksp->rnorm = gamma;
ierr = KSPMonitor(ksp,ksp->its,ksp->rnorm);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,ksp->rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
gamma = gamma*gamma; /* gamma = norm2(s)^2 */
beta = gamma/oldgamma; /* beta = gamma / oldgamma */
ierr = VecAYPX(p,beta,ss);CHKERRQ(ierr); /* p = s + beta * p */
} while (ksp->its<ksp->max_it && !ksp->reason);
if (ksp->its>=maxiter_ls && !ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
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);
}
static PetscErrorCode KSPSolve_AGMRES(KSP ksp)
{
PetscErrorCode ierr;
PetscInt its;
KSP_AGMRES *agmres = (KSP_AGMRES*)ksp->data;
PetscBool guess_zero = ksp->guess_zero;
PetscReal res_old, res;
PetscInt test;
PetscFunctionBegin;
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its = 0;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->reason = KSP_CONVERGED_ITERATING;
if (!agmres->HasShifts) { /* Compute Shifts for the Newton basis */
ierr = KSPComputeShifts_DGMRES(ksp);CHKERRQ(ierr);
}
/* NOTE: At this step, the initial guess is not equal to zero since one cycle of the classical GMRES is performed to compute the shifts */
ierr = (*ksp->converged)(ksp,0,ksp->rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
while (!ksp->reason) {
ierr = KSPInitialResidual(ksp,ksp->vec_sol,VEC_TMP,VEC_TMP_MATOP,VEC_V(0),ksp->vec_rhs);CHKERRQ(ierr);
if ((ksp->pc_side == PC_LEFT) && agmres->r && agmres->DeflPrecond) {
ierr = KSPDGMRESApplyDeflation_DGMRES(ksp, VEC_V(0), VEC_TMP);CHKERRQ(ierr);
ierr = VecCopy(VEC_TMP, VEC_V(0));CHKERRQ(ierr);
agmres->matvecs += 1;
}
ierr = VecNormalize(VEC_V(0),&(ksp->rnorm));CHKERRQ(ierr);
KSPCheckNorm(ksp,ksp->rnorm);
res_old = ksp->rnorm; /* Record the residual norm to test if deflation is needed */
ksp->ops->buildsolution = KSPBuildSolution_AGMRES;
ierr = KSPAGMRESCycle(&its,ksp);CHKERRQ(ierr);
if (ksp->its >= ksp->max_it) {
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
break;
}
/* compute the eigenvectors to augment the subspace : use an adaptive strategy */
res = ksp->rnorm;
if (!ksp->reason && agmres->neig > 0) {
test = agmres->max_k * PetscLogReal(ksp->rtol/res) / PetscLogReal(res/res_old); /* estimate the remaining number of steps */
if ((test > agmres->smv*(ksp->max_it-ksp->its)) || agmres->force) {
if (!agmres->force && ((test > agmres->bgv*(ksp->max_it-ksp->its)) && ((agmres->r + 1) < agmres->max_neig))) {
agmres->neig += 1; /* Augment the number of eigenvalues to deflate if the convergence is too slow */
}
ierr = KSPDGMRESComputeDeflationData_DGMRES(ksp,&agmres->neig);CHKERRQ(ierr);
}
}
ksp->guess_zero = PETSC_FALSE; /* every future call to KSPInitialResidual() will have nonzero guess */
}
ksp->guess_zero = guess_zero; /* restore if user has provided nonzero initial guess */
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_TCQMR(KSP ksp)
{
PetscReal rnorm0,rnorm,dp1,Gamma;
PetscScalar theta,ep,cl1,sl1,cl,sl,sprod,tau_n1,f;
PetscScalar deltmp,rho,beta,eptmp,ta,s,c,tau_n,delta;
PetscScalar dp11,dp2,rhom1,alpha,tmp;
PetscErrorCode ierr;
PetscFunctionBegin;
ksp->its = 0;
ierr = KSPInitialResidual(ksp,x,u,v,r,b);CHKERRQ(ierr);
ierr = VecNorm(r,NORM_2,&rnorm0);CHKERRQ(ierr); /* rnorm0 = ||r|| */
KSPCheckNorm(ksp,rnorm0);
ierr = (*ksp->converged)(ksp,0,rnorm0,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
ierr = VecSet(um1,0.0);CHKERRQ(ierr);
ierr = VecCopy(r,u);CHKERRQ(ierr);
rnorm = rnorm0;
tmp = 1.0/rnorm; ierr = VecScale(u,tmp);CHKERRQ(ierr);
ierr = VecSet(vm1,0.0);CHKERRQ(ierr);
ierr = VecCopy(u,v);CHKERRQ(ierr);
ierr = VecCopy(u,v0);CHKERRQ(ierr);
ierr = VecSet(pvec1,0.0);CHKERRQ(ierr);
ierr = VecSet(pvec2,0.0);CHKERRQ(ierr);
ierr = VecSet(p,0.0);CHKERRQ(ierr);
theta = 0.0;
ep = 0.0;
cl1 = 0.0;
sl1 = 0.0;
cl = 0.0;
sl = 0.0;
sprod = 1.0;
tau_n1= rnorm0;
f = 1.0;
Gamma = 1.0;
rhom1 = 1.0;
/*
CALCULATE SQUARED LANCZOS vectors
*/
ierr = (*ksp->converged)(ksp,ksp->its,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
while (!ksp->reason) {
ierr = KSPMonitor(ksp,ksp->its,rnorm);CHKERRQ(ierr);
ksp->its++;
ierr = KSP_PCApplyBAorAB(ksp,u,y,vtmp);CHKERRQ(ierr); /* y = A*u */
ierr = VecDot(y,v0,&dp11);CHKERRQ(ierr);
KSPCheckDot(ksp,dp11);
ierr = VecDot(u,v0,&dp2);CHKERRQ(ierr);
alpha = dp11 / dp2; /* alpha = v0'*y/v0'*u */
deltmp = alpha;
ierr = VecCopy(y,z);CHKERRQ(ierr);
ierr = VecAXPY(z,-alpha,u);CHKERRQ(ierr); /* z = y - alpha u */
ierr = VecDot(u,v0,&rho);CHKERRQ(ierr);
beta = rho / (f*rhom1);
rhom1 = rho;
ierr = VecCopy(z,utmp);CHKERRQ(ierr); /* up1 = (A-alpha*I)*
(z-2*beta*p) + f*beta*
beta*um1 */
ierr = VecAXPY(utmp,-2.0*beta,p);CHKERRQ(ierr);
ierr = KSP_PCApplyBAorAB(ksp,utmp,up1,vtmp);CHKERRQ(ierr);
ierr = VecAXPY(up1,-alpha,utmp);CHKERRQ(ierr);
ierr = VecAXPY(up1,f*beta*beta,um1);CHKERRQ(ierr);
ierr = VecNorm(up1,NORM_2,&dp1);CHKERRQ(ierr);
KSPCheckNorm(ksp,dp1);
f = 1.0 / dp1;
ierr = VecScale(up1,f);CHKERRQ(ierr);
ierr = VecAYPX(p,-beta,z);CHKERRQ(ierr); /* p = f*(z-beta*p) */
ierr = VecScale(p,f);CHKERRQ(ierr);
ierr = VecCopy(u,um1);CHKERRQ(ierr);
ierr = VecCopy(up1,u);CHKERRQ(ierr);
beta = beta/Gamma;
eptmp = beta;
ierr = KSP_PCApplyBAorAB(ksp,v,vp1,vtmp);CHKERRQ(ierr);
ierr = VecAXPY(vp1,-alpha,v);CHKERRQ(ierr);
ierr = VecAXPY(vp1,-beta,vm1);CHKERRQ(ierr);
ierr = VecNorm(vp1,NORM_2,&Gamma);CHKERRQ(ierr);
KSPCheckNorm(ksp,Gamma);
ierr = VecScale(vp1,1.0/Gamma);CHKERRQ(ierr);
ierr = VecCopy(v,vm1);CHKERRQ(ierr);
ierr = VecCopy(vp1,v);CHKERRQ(ierr);
/*
SOLVE Ax = b
*/
/* Apply last two Given's (Gl-1 and Gl) rotations to (beta,alpha,Gamma) */
if (ksp->its > 2) {
theta = sl1*beta;
eptmp = -cl1*beta;
}
if (ksp->its > 1) {
ep = -cl*eptmp + sl*alpha;
deltmp = -sl*eptmp - cl*alpha;
}
if (PetscAbsReal(Gamma) > PetscAbsScalar(deltmp)) {
ta = -deltmp / Gamma;
s = 1.0 / PetscSqrtScalar(1.0 + ta*ta);
c = s*ta;
} else {
ta = -Gamma/deltmp;
c = 1.0 / PetscSqrtScalar(1.0 + ta*ta);
s = c*ta;
}
delta = -c*deltmp + s*Gamma;
tau_n = -c*tau_n1; tau_n1 = -s*tau_n1;
ierr = VecCopy(vm1,pvec);CHKERRQ(ierr);
ierr = VecAXPY(pvec,-theta,pvec2);CHKERRQ(ierr);
ierr = VecAXPY(pvec,-ep,pvec1);CHKERRQ(ierr);
ierr = VecScale(pvec,1.0/delta);CHKERRQ(ierr);
ierr = VecAXPY(x,tau_n,pvec);CHKERRQ(ierr);
cl1 = cl; sl1 = sl; cl = c; sl = s;
ierr = VecCopy(pvec1,pvec2);CHKERRQ(ierr);
ierr = VecCopy(pvec,pvec1);CHKERRQ(ierr);
/* Compute the upper bound on the residual norm r (See QMR paper p. 13) */
sprod = sprod*PetscAbsScalar(s);
rnorm = rnorm0 * PetscSqrtReal((PetscReal)ksp->its+2.0) * PetscRealPart(sprod);
ierr = (*ksp->converged)(ksp,ksp->its,rnorm,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->its >= ksp->max_it) {
if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
break;
}
}
ierr = KSPMonitor(ksp,ksp->its,rnorm);CHKERRQ(ierr);
ierr = KSPUnwindPreconditioner(ksp,x,vtmp);CHKERRQ(ierr);
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);
}
static PetscErrorCode KSPPGMRESCycle(PetscInt *itcount,KSP ksp)
{
KSP_PGMRES *pgmres = (KSP_PGMRES*)(ksp->data);
PetscReal res_norm,res,newnorm;
PetscErrorCode ierr;
PetscInt it = 0,j,k;
PetscBool hapend = PETSC_FALSE;
PetscFunctionBegin;
if (itcount) *itcount = 0;
ierr = VecNormalize(VEC_VV(0),&res_norm);CHKERRQ(ierr);
KSPCheckNorm(ksp,res_norm);
res = res_norm;
*RS(0) = res_norm;
/* check for the convergence */
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->rnorm = res;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
pgmres->it = it-2;
ierr = KSPLogResidualHistory(ksp,res);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res);CHKERRQ(ierr);
if (!res) {
ksp->reason = KSP_CONVERGED_ATOL;
ierr = PetscInfo(ksp,"Converged due to zero residual norm on entry\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
ierr = (*ksp->converged)(ksp,ksp->its,res,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
for (; !ksp->reason; it++) {
Vec Zcur,Znext;
if (pgmres->vv_allocated <= it + VEC_OFFSET + 1) {
ierr = KSPGMRESGetNewVectors(ksp,it+1);CHKERRQ(ierr);
}
/* VEC_VV(it-1) is orthogonal, it will be normalized once the VecNorm arrives. */
Zcur = VEC_VV(it); /* Zcur is not yet orthogonal, but the VecMDot to orthogonalize it has been started. */
Znext = VEC_VV(it+1); /* This iteration will compute Znext, update with a deferred correction once we know how
* Zcur relates to the previous vectors, and start the reduction to orthogonalize it. */
if (it < pgmres->max_k+1 && ksp->its+1 < PetscMax(2,ksp->max_it)) { /* We don't know whether what we have computed is enough, so apply the matrix. */
ierr = KSP_PCApplyBAorAB(ksp,Zcur,Znext,VEC_TEMP_MATOP);CHKERRQ(ierr);
}
if (it > 1) { /* Complete the pending reduction */
ierr = VecNormEnd(VEC_VV(it-1),NORM_2,&newnorm);CHKERRQ(ierr);
*HH(it-1,it-2) = newnorm;
}
if (it > 0) { /* Finish the reduction computing the latest column of H */
ierr = VecMDotEnd(Zcur,it,&(VEC_VV(0)),HH(0,it-1));CHKERRQ(ierr);
}
if (it > 1) {
/* normalize the base vector from two iterations ago, basis is complete up to here */
ierr = VecScale(VEC_VV(it-1),1./ *HH(it-1,it-2));CHKERRQ(ierr);
ierr = KSPPGMRESUpdateHessenberg(ksp,it-2,&hapend,&res);CHKERRQ(ierr);
pgmres->it = it-2;
ksp->its++;
ksp->rnorm = res;
ierr = (*ksp->converged)(ksp,ksp->its,res,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (it < pgmres->max_k+1 || ksp->reason || ksp->its == ksp->max_it) { /* Monitor if we are done or still iterating, but not before a restart. */
ierr = KSPLogResidualHistory(ksp,res);CHKERRQ(ierr);
ierr = KSPMonitor(ksp,ksp->its,res);CHKERRQ(ierr);
}
if (ksp->reason) break;
/* Catch error in happy breakdown and signal convergence and break from loop */
if (hapend) {
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);
else {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
}
if (!(it < pgmres->max_k+1 && ksp->its < ksp->max_it)) break;
/* The it-2 column of H was not scaled when we computed Zcur, apply correction */
ierr = VecScale(Zcur,1./ *HH(it-1,it-2));CHKERRQ(ierr);
/* And Znext computed in this iteration was computed using the under-scaled Zcur */
ierr = VecScale(Znext,1./ *HH(it-1,it-2));CHKERRQ(ierr);
/* In the previous iteration, we projected an unnormalized Zcur against the Krylov basis, so we need to fix the column of H resulting from that projection. */
for (k=0; k<it; k++) *HH(k,it-1) /= *HH(it-1,it-2);
/* When Zcur was projected against the Krylov basis, VV(it-1) was still not normalized, so fix that too. This
* column is complete except for HH(it,it-1) which we won't know until the next iteration. */
*HH(it-1,it-1) /= *HH(it-1,it-2);
}
if (it > 0) {
PetscScalar *work;
if (!pgmres->orthogwork) {ierr = PetscMalloc1(pgmres->max_k + 2,&pgmres->orthogwork);CHKERRQ(ierr);}
work = pgmres->orthogwork;
/* Apply correction computed by the VecMDot in the last iteration to Znext. The original form is
*
* Znext -= sum_{j=0}^{i-1} Z[j+1] * H[j,i-1]
*
* where
*
* Z[j] = sum_{k=0}^j V[k] * H[k,j-1]
*
* substituting
*
* Znext -= sum_{j=0}^{i-1} sum_{k=0}^{j+1} V[k] * H[k,j] * H[j,i-1]
*
* rearranging the iteration space from row-column to column-row
*
* Znext -= sum_{k=0}^i sum_{j=k-1}^{i-1} V[k] * H[k,j] * H[j,i-1]
*
* Note that column it-1 of HH is correct. For all previous columns, we must look at HES because HH has already
* been transformed to upper triangular form.
*/
for (k=0; k<it+1; k++) {
work[k] = 0;
for (j=PetscMax(0,k-1); j<it-1; j++) work[k] -= *HES(k,j) * *HH(j,it-1);
}
ierr = VecMAXPY(Znext,it+1,work,&VEC_VV(0));CHKERRQ(ierr);
ierr = VecAXPY(Znext,-*HH(it-1,it-1),Zcur);CHKERRQ(ierr);
/* Orthogonalize Zcur against existing basis vectors. */
for (k=0; k<it; k++) work[k] = -*HH(k,it-1);
ierr = VecMAXPY(Zcur,it,work,&VEC_VV(0));CHKERRQ(ierr);
/* Zcur is now orthogonal, and will be referred to as VEC_VV(it) again, though it is still not normalized. */
/* Begin computing the norm of the new vector, will be normalized after the MatMult in the next iteration. */
ierr = VecNormBegin(VEC_VV(it),NORM_2,&newnorm);CHKERRQ(ierr);
}
/* Compute column of H (to the diagonal, but not the subdiagonal) to be able to orthogonalize the newest vector. */
ierr = VecMDotBegin(Znext,it+1,&VEC_VV(0),HH(0,it));CHKERRQ(ierr);
/* Start an asynchronous split-mode reduction, the result of the MDot and Norm will be collected on the next iteration. */
ierr = PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)Znext));CHKERRQ(ierr);
}
if (itcount) *itcount = it-1; /* Number of iterations actually completed. */
/*
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) */
ierr = KSPPGMRESBuildSoln(RS(0),ksp->vec_sol,ksp->vec_sol,ksp,it-2);CHKERRQ(ierr);
PetscFunctionReturn(0);
}
static PetscErrorCode KSPSolve_CGS(KSP ksp)
{
PetscErrorCode ierr;
PetscInt i;
PetscScalar rho,rhoold,a,s,b;
Vec X,B,V,P,R,RP,T,Q,U,AUQ;
PetscReal dp = 0.0;
PetscBool diagonalscale;
PetscFunctionBegin;
/* not sure what residual norm it does use, should use for right preconditioning */
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];
RP = ksp->work[1];
V = ksp->work[2];
T = ksp->work[3];
Q = ksp->work[4];
P = ksp->work[5];
U = ksp->work[6];
AUQ = V;
/* Compute initial preconditioned residual */
ierr = KSPInitialResidual(ksp,X,V,T,R,B);CHKERRQ(ierr);
/* Test for nothing to do */
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr);
KSPCheckNorm(ksp,dp);
if (ksp->normtype == KSP_NORM_NATURAL) dp *= dp;
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 = KSPMonitor(ksp,0,dp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
if (ksp->reason) PetscFunctionReturn(0);
/* Make the initial Rp == R */
ierr = VecCopy(R,RP);CHKERRQ(ierr);
/* added for Fidap */
/* Penalize Startup - Isaac Hasbani Trick for CGS
Since most initial conditions result in a mostly 0 residual,
we change all the 0 values in the vector RP to the maximum.
*/
if (ksp->normtype == KSP_NORM_NATURAL) {
PetscReal vr0max;
PetscScalar *tmp_RP=0;
PetscInt numnp =0, *max_pos=0;
ierr = VecMax(RP, max_pos, &vr0max);CHKERRQ(ierr);
ierr = VecGetArray(RP, &tmp_RP);CHKERRQ(ierr);
ierr = VecGetLocalSize(RP, &numnp);CHKERRQ(ierr);
for (i=0; i<numnp; i++) {
if (tmp_RP[i] == 0.0) tmp_RP[i] = vr0max;
}
ierr = VecRestoreArray(RP, &tmp_RP);CHKERRQ(ierr);
}
/* end of addition for Fidap */
/* Set the initial conditions */
ierr = VecDot(R,RP,&rhoold);CHKERRQ(ierr); /* rhoold = (r,rp) */
ierr = VecCopy(R,U);CHKERRQ(ierr);
ierr = VecCopy(R,P);CHKERRQ(ierr);
ierr = KSP_PCApplyBAorAB(ksp,P,V,T);CHKERRQ(ierr);
i = 0;
do {
ierr = VecDot(V,RP,&s);CHKERRQ(ierr); /* s <- (v,rp) */
KSPCheckDot(ksp,s);
a = rhoold / s; /* a <- rho / s */
ierr = VecWAXPY(Q,-a,V,U);CHKERRQ(ierr); /* q <- u - a v */
ierr = VecWAXPY(T,1.0,U,Q);CHKERRQ(ierr); /* t <- u + q */
ierr = VecAXPY(X,a,T);CHKERRQ(ierr); /* x <- x + a (u + q) */
ierr = KSP_PCApplyBAorAB(ksp,T,AUQ,U);CHKERRQ(ierr);
ierr = VecAXPY(R,-a,AUQ);CHKERRQ(ierr); /* r <- r - a K (u + q) */
ierr = VecDot(R,RP,&rho);CHKERRQ(ierr); /* rho <- (r,rp) */
KSPCheckDot(ksp,rho);
if (ksp->normtype == KSP_NORM_NATURAL) {
dp = PetscAbsScalar(rho);
} else {
ierr = VecNorm(R,NORM_2,&dp);CHKERRQ(ierr);
KSPCheckNorm(ksp,dp);
}
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
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;
b = rho / rhoold; /* b <- rho / rhoold */
ierr = VecWAXPY(U,b,Q,R);CHKERRQ(ierr); /* u <- r + b q */
ierr = VecAXPY(Q,b,P);CHKERRQ(ierr);
ierr = VecWAXPY(P,b,Q,U);CHKERRQ(ierr); /* p <- u + b(q + b p) */
ierr = KSP_PCApplyBAorAB(ksp,P,V,Q);CHKERRQ(ierr); /* v <- K p */
rhoold = rho;
i++;
} while (i<ksp->max_it);
if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
ierr = KSPUnwindPreconditioner(ksp,X,T);CHKERRQ(ierr);
PetscFunctionReturn(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;
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);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; */
KSPCheckDot(ksp,dp);
if (PetscAbsScalar(dp) < symmlq->haptol) {
ierr = PetscInfo2(ksp,"Detected happy breakdown %g tolerance %g\n",(double)PetscAbsScalar(dp),(double)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|| */
KSPCheckNorm(ksp,np);
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; */
KSPCheckDot(ksp,dp);
if (PetscAbsScalar(dp) < symmlq->haptol) {
ierr = PetscInfo2(ksp,"Detected happy breakdown %g tolerance %g\n",(double)PetscAbsScalar(dp),(double)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 KSPLGMRESCycle(PetscInt *itcount,KSP ksp)
{
KSP_LGMRES *lgmres = (KSP_LGMRES*)(ksp->data);
PetscReal res_norm, res;
PetscReal hapbnd, tt;
PetscScalar tmp;
PetscBool hapend = PETSC_FALSE; /* indicates happy breakdown ending */
PetscErrorCode ierr;
PetscInt loc_it; /* local count of # of dir. in Krylov space */
PetscInt max_k = lgmres->max_k; /* max approx space size */
PetscInt max_it = ksp->max_it; /* max # of overall iterations for the method */
/* LGMRES_MOD - new variables*/
PetscInt aug_dim = lgmres->aug_dim;
PetscInt spot = 0;
PetscInt order = 0;
PetscInt it_arnoldi; /* number of arnoldi steps to take */
PetscInt it_total; /* total number of its to take (=approx space size)*/
PetscInt ii, jj;
PetscReal tmp_norm;
PetscScalar inv_tmp_norm;
PetscScalar *avec;
PetscFunctionBegin;
/* Number of pseudo iterations since last restart is the number
of prestart directions */
loc_it = 0;
/* LGMRES_MOD: determine number of arnoldi steps to take */
/* if approx_constant then we keep the space the same size even if
we don't have the full number of aug vectors yet*/
if (lgmres->approx_constant) it_arnoldi = max_k - lgmres->aug_ct;
else it_arnoldi = max_k - aug_dim;
it_total = it_arnoldi + lgmres->aug_ct;
/* initial residual is in VEC_VV(0) - compute its norm*/
ierr = VecNorm(VEC_VV(0),NORM_2,&res_norm);CHKERRQ(ierr);
KSPCheckNorm(ksp,res_norm);
res = res_norm;
/* first entry in right-hand-side of hessenberg system is just
the initial residual norm */
*GRS(0) = res_norm;
/* check for the convergence */
if (!res) {
if (itcount) *itcount = 0;
ksp->reason = KSP_CONVERGED_ATOL;
ierr = PetscInfo(ksp,"Converged due to zero residual norm on entry\n");CHKERRQ(ierr);
PetscFunctionReturn(0);
}
/* scale VEC_VV (the initial residual) */
tmp = 1.0/res_norm; ierr = VecScale(VEC_VV(0),tmp);CHKERRQ(ierr);
ksp->rnorm = res;
/* note: (lgmres->it) is always set one less than (loc_it) It is used in
KSPBUILDSolution_LGMRES, where it is passed to KSPLGMRESBuildSoln.
Note that when KSPLGMRESBuildSoln is called from this function,
(loc_it -1) is passed, so the two are equivalent */
lgmres->it = (loc_it - 1);
/* 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 */
ierr = (*ksp->converged)(ksp,ksp->its,res,&ksp->reason,ksp->cnvP);CHKERRQ(ierr);
while (!ksp->reason && loc_it < it_total && ksp->its < max_it) { /* LGMRES_MOD: changed to it_total */
ierr = KSPLogResidualHistory(ksp,res);CHKERRQ(ierr);
lgmres->it = (loc_it - 1);
ierr = KSPMonitor(ksp,ksp->its,res);CHKERRQ(ierr);
/* see if more space is needed for work vectors */
if (lgmres->vv_allocated <= loc_it + VEC_OFFSET + 1) {
ierr = KSPLGMRESGetNewVectors(ksp,loc_it+1);CHKERRQ(ierr);
/* (loc_it+1) is passed in as number of the first vector that should
be allocated */
}
/*LGMRES_MOD: decide whether this is an arnoldi step or an aug step */
if (loc_it < it_arnoldi) { /* Arnoldi */
ierr = KSP_PCApplyBAorAB(ksp,VEC_VV(loc_it),VEC_VV(1+loc_it),VEC_TEMP_MATOP);CHKERRQ(ierr);
} else { /*aug step */
order = loc_it - it_arnoldi + 1; /* which aug step */
for (ii=0; ii<aug_dim; ii++) {
if (lgmres->aug_order[ii] == order) {
spot = ii;
break; /* must have this because there will be duplicates before aug_ct = aug_dim */
}
}
ierr = VecCopy(A_AUGVEC(spot), VEC_VV(1+loc_it));CHKERRQ(ierr);
/*note: an alternate implementation choice would be to only save the AUGVECS and
not A_AUGVEC and then apply the PC here to the augvec */
}
/* update hessenberg matrix and do Gram-Schmidt - new direction is in
VEC_VV(1+loc_it)*/
ierr = (*lgmres->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;
/* check for the happy breakdown */
hapbnd = PetscAbsScalar(tt / *GRS(loc_it)); /* GRS(loc_it) contains the res_norm from the last iteration */
if (hapbnd > lgmres->haptol) hapbnd = lgmres->haptol;
if (tt > hapbnd) {
tmp = 1.0/tt;
ierr = VecScale(VEC_VV(loc_it+1),tmp);CHKERRQ(ierr); /* scale new direction by its norm */
} else {
ierr = PetscInfo2(ksp,"Detected happy breakdown, current hapbnd = %g tt = %g\n",(double)hapbnd,(double)tt);CHKERRQ(ierr);
hapend = PETSC_TRUE;
}
/* 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 = KSPLGMRESUpdateHessenberg(ksp,loc_it,hapend,&res);CHKERRQ(ierr);
if (ksp->reason) break;
loc_it++;
lgmres->it = (loc_it-1); /* Add this here in case it has converged */
ierr = PetscObjectSAWsTakeAccess((PetscObject)ksp);CHKERRQ(ierr);
ksp->its++;
ksp->rnorm = res;
ierr = PetscObjectSAWsGrantAccess((PetscObject)ksp);CHKERRQ(ierr);
ierr = (*ksp->converged)(ksp,ksp->its,res,&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);
else {
ksp->reason = KSP_DIVERGED_BREAKDOWN;
break;
}
}
}
}
/* END OF ITERATION LOOP */
ierr = KSPLogResidualHistory(ksp,res);CHKERRQ(ierr);
/* Monitor if we know that we will not return for a restart */
if (ksp->reason || ksp->its >= max_it) {
ierr = KSPMonitor(ksp, ksp->its, res);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 KSPLGMRESBuildSoln
properly navigates */
ierr = KSPLGMRESBuildSoln(GRS(0),ksp->vec_sol,ksp->vec_sol,ksp,loc_it-1);CHKERRQ(ierr);
/* LGMRES_MOD collect aug vector and A*augvector for future restarts -
only if we will be restarting (i.e. this cycle performed it_total
iterations) */
if (!ksp->reason && ksp->its < max_it && aug_dim > 0) {
/*AUG_TEMP contains the new augmentation vector (assigned in KSPLGMRESBuildSoln) */
if (!lgmres->aug_ct) {
spot = 0;
lgmres->aug_ct++;
} else if (lgmres->aug_ct < aug_dim) {
spot = lgmres->aug_ct;
lgmres->aug_ct++;
} else { /* truncate */
for (ii=0; ii<aug_dim; ii++) {
if (lgmres->aug_order[ii] == aug_dim) spot = ii;
}
}
ierr = VecCopy(AUG_TEMP, AUGVEC(spot));CHKERRQ(ierr);
/*need to normalize */
ierr = VecNorm(AUGVEC(spot), NORM_2, &tmp_norm);CHKERRQ(ierr);
inv_tmp_norm = 1.0/tmp_norm;
ierr = VecScale(AUGVEC(spot),inv_tmp_norm);CHKERRQ(ierr);
/*set new aug vector to order 1 - move all others back one */
for (ii=0; ii < aug_dim; ii++) AUG_ORDER(ii)++;
AUG_ORDER(spot) = 1;
/*now add the A*aug vector to A_AUGVEC(spot) - this is independ. of preconditioning type*/
/* want V*H*y - y is in GRS, V is in VEC_VV and H is in HES */
/* first do H+*y */
avec = lgmres->hwork;
ierr = PetscMemzero(avec,(it_total+1)*sizeof(*avec));CHKERRQ(ierr);
for (ii=0; ii < it_total + 1; ii++) {
for (jj=0; jj <= ii+1 && jj < it_total+1; jj++) {
avec[jj] += *HES(jj ,ii) * *GRS(ii);
}
}
/*now multiply result by V+ */
ierr = VecSet(VEC_TEMP,0.0);CHKERRQ(ierr);
ierr = VecMAXPY(VEC_TEMP, it_total+1, avec, &VEC_VV(0));CHKERRQ(ierr); /*answer is in VEC_TEMP*/
/*copy answer to aug location and scale*/
ierr = VecCopy(VEC_TEMP, A_AUGVEC(spot));CHKERRQ(ierr);
ierr = VecScale(A_AUGVEC(spot),inv_tmp_norm);CHKERRQ(ierr);
}
PetscFunctionReturn(0);
}
/*
KSPFGMRESCycle - Run fgmres, possibly with restart. Return residual
history if requested.
input parameters:
. fgmres - structure containing parameters and work areas
output parameters:
. itcount - number of iterations used. If null, ignored.
. converged - 0 if not converged
Notes:
On entry, the value in vector VEC_VV(0) should be
the initial residual.
*/
PetscErrorCode KSPFGMRESCycle(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);
KSPCheckNorm(ksp,res_norm);
/* 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 = KSPFGMRESGetNewVectors(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 = KSPFGMRESUpdateHessenberg(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 = KSPFGMRESBuildSoln(RS(0),ksp->vec_sol,ksp->vec_sol,ksp,loc_it-1);CHKERRQ(ierr);
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);
KSPCheckNorm(ksp,bsnrm);
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);
KSPCheckNorm(ksp,xnorm);
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);
KSPCheckNorm(ksp,pcgP->ltsnrm);
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);
KSPCheckNorm(ksp,rnrm);
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);
}
