Date: 2016-07-24T17:06:53+00:00

Actual source code: rich.c
petsc-3.7.3 2016-07-24
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      2: /*
      3:             This implements Richardson Iteration.
      4: */
      5: #include <petsc/private/kspimpl.h>              /*I "petscksp.h" I*/
      6: #include <../src/ksp/ksp/impls/rich/richardsonimpl.h>

     10: PetscErrorCode KSPSetUp_Richardson(KSP ksp)
     11: {
     13:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;

     16:   if (richardsonP->selfscale) {
     17:     KSPSetWorkVecs(ksp,4);
     18:   } else {
     19:     KSPSetWorkVecs(ksp,2);
     20:   }
     21:   return(0);
     22: }

     26: PetscErrorCode  KSPSolve_Richardson(KSP ksp)
     27: {
     29:   PetscInt       i,maxit;
     30:   PetscReal      rnorm = 0.0,abr;
     31:   PetscScalar    scale,rdot;
     32:   Vec            x,b,r,z,w = NULL,y = NULL;
     33:   PetscInt       xs, ws;
     34:   Mat            Amat,Pmat;
     35:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;
     36:   PetscBool      exists,diagonalscale;
     37:   MatNullSpace   nullsp;

     40:   PCGetDiagonalScale(ksp->pc,&diagonalscale);
     41:   if (diagonalscale) SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"Krylov method %s does not support diagonal scaling",((PetscObject)ksp)->type_name);

     43:   ksp->its = 0;

     45:   PCGetOperators(ksp->pc,&Amat,&Pmat);
     46:   x    = ksp->vec_sol;
     47:   b    = ksp->vec_rhs;
     48:   VecGetSize(x,&xs);
     49:   VecGetSize(ksp->work[0],&ws);
     50:   if (xs != ws) {
     51:     if (richardsonP->selfscale) {
     52:       KSPSetWorkVecs(ksp,4);
     53:     } else {
     54:       KSPSetWorkVecs(ksp,2);
     55:     }
     56:   }
     57:   r = ksp->work[0];
     58:   z = ksp->work[1];
     59:   if (richardsonP->selfscale) {
     60:     w = ksp->work[2];
     61:     y = ksp->work[3];
     62:   }
     63:   maxit = ksp->max_it;

     65:   /* if user has provided fast Richardson code use that */
     66:   PCApplyRichardsonExists(ksp->pc,&exists);
     67:   MatGetNullSpace(Pmat,&nullsp);
     68:   if (exists && richardsonP->scale == 1.0 && !ksp->numbermonitors && !ksp->transpose_solve & !nullsp) {
     69:     PCRichardsonConvergedReason reason;
     70:     PCApplyRichardson(ksp->pc,b,x,r,ksp->rtol,ksp->abstol,ksp->divtol,maxit,ksp->guess_zero,&ksp->its,&reason);
     71:     ksp->reason = (KSPConvergedReason)reason;
     72:     return(0);
     73:   } else if (exists && !ksp->numbermonitors && !ksp->transpose_solve & !nullsp) {
     74:     PetscInfo(ksp,"KSPSolve_Richardson: Warning, skipping optimized PCApplyRichardson() because scale factor is not 1.0\n");
     75:   }

     77:   scale = richardsonP->scale;

     79:   if (!ksp->guess_zero) {                          /*   r <- b - A x     */
     80:     KSP_MatMult(ksp,Amat,x,r);
     81:     VecAYPX(r,-1.0,b);
     82:   } else {
     83:     VecCopy(b,r);
     84:   }

     86:   ksp->its = 0;
     87:   if (richardsonP->selfscale) {
     88:     KSP_PCApply(ksp,r,z);         /*   z <- B r          */
     89:     for (i=0; i<maxit; i++) {

     91:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
     92:         VecNorm(r,NORM_2,&rnorm); /*   rnorm <- r'*r     */
     93:         KSPMonitor(ksp,i,rnorm);
     94:         ksp->rnorm = rnorm;
     95:         KSPLogResidualHistory(ksp,rnorm);
     96:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
     97:         if (ksp->reason) break;
     98:       } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
     99:         VecNorm(z,NORM_2,&rnorm); /*   rnorm <- z'*z     */
    100:         KSPMonitor(ksp,i,rnorm);
    101:         ksp->rnorm = rnorm;
    102:         KSPLogResidualHistory(ksp,rnorm);
    103:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    104:         if (ksp->reason) break;
    105:       }
    106:       KSP_PCApplyBAorAB(ksp,z,y,w); /* y = BAz = BABr */
    107:       VecDotNorm2(z,y,&rdot,&abr);   /*   rdot = (Br)^T(BABR); abr = (BABr)^T (BABr) */
    108:       scale = rdot/abr;
    109:       PetscInfo1(ksp,"Self-scale factor %g\n",(double)PetscRealPart(scale));
    110:       VecAXPY(x,scale,z);   /*   x  <- x + scale z */
    111:       VecAXPY(r,-scale,w);  /*  r <- r - scale*Az */
    112:       VecAXPY(z,-scale,y);  /*  z <- z - scale*y */
    113:       ksp->its++;
    114:     }
    115:   } else {
    116:     for (i=0; i<maxit; i++) {

    118:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    119:         VecNorm(r,NORM_2,&rnorm); /*   rnorm <- r'*r     */
    120:         KSPMonitor(ksp,i,rnorm);
    121:         ksp->rnorm = rnorm;
    122:         KSPLogResidualHistory(ksp,rnorm);
    123:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    124:         if (ksp->reason) break;
    125:       }

    127:       KSP_PCApply(ksp,r,z);    /*   z <- B r          */

    129:       if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
    130:         VecNorm(z,NORM_2,&rnorm); /*   rnorm <- z'*z     */
    131:         KSPMonitor(ksp,i,rnorm);
    132:         ksp->rnorm = rnorm;
    133:         KSPLogResidualHistory(ksp,rnorm);
    134:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    135:         if (ksp->reason) break;
    136:       }

    138:       VecAXPY(x,scale,z);    /*   x  <- x + scale z */
    139:       ksp->its++;

    141:       if (i+1 < maxit || ksp->normtype != KSP_NORM_NONE) {
    142:         KSP_MatMult(ksp,Amat,x,r);      /*   r  <- b - Ax      */
    143:         VecAYPX(r,-1.0,b);
    144:       }
    145:     }
    146:   }
    147:   if (!ksp->reason) {
    148:     if (ksp->normtype != KSP_NORM_NONE) {
    149:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    150:         VecNorm(r,NORM_2,&rnorm);     /*   rnorm <- r'*r     */
    151:       } else {
    152:         KSP_PCApply(ksp,r,z);   /*   z <- B r          */
    153:         VecNorm(z,NORM_2,&rnorm);     /*   rnorm <- z'*z     */
    154:       }
    155:       ksp->rnorm = rnorm;
    156:       KSPLogResidualHistory(ksp,rnorm);
    157:       KSPMonitor(ksp,i,rnorm);
    158:     }
    159:     if (ksp->its >= ksp->max_it) {
    160:       if (ksp->normtype != KSP_NORM_NONE) {
    161:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    162:         if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
    163:       } else {
    164:         ksp->reason = KSP_CONVERGED_ITS;
    165:       }
    166:     }
    167:   }
    168:   return(0);
    169: }

    173: PetscErrorCode KSPView_Richardson(KSP ksp,PetscViewer viewer)
    174: {
    175:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;
    177:   PetscBool      iascii;

    180:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    181:   if (iascii) {
    182:     if (richardsonP->selfscale) {
    183:       PetscViewerASCIIPrintf(viewer,"  Richardson: using self-scale best computed damping factor\n");
    184:     } else {
    185:       PetscViewerASCIIPrintf(viewer,"  Richardson: damping factor=%g\n",(double)richardsonP->scale);
    186:     }
    187:   }
    188:   return(0);
    189: }

    193: PetscErrorCode KSPSetFromOptions_Richardson(PetscOptionItems *PetscOptionsObject,KSP ksp)
    194: {
    195:   KSP_Richardson *rich = (KSP_Richardson*)ksp->data;
    197:   PetscReal      tmp;
    198:   PetscBool      flg,flg2;

    201:   PetscOptionsHead(PetscOptionsObject,"KSP Richardson Options");
    202:   PetscOptionsReal("-ksp_richardson_scale","damping factor","KSPRichardsonSetScale",rich->scale,&tmp,&flg);
    203:   if (flg) { KSPRichardsonSetScale(ksp,tmp); }
    204:   PetscOptionsBool("-ksp_richardson_self_scale","dynamically determine optimal damping factor","KSPRichardsonSetSelfScale",rich->selfscale,&flg2,&flg);
    205:   if (flg) { KSPRichardsonSetSelfScale(ksp,flg2); }
    206:   PetscOptionsTail();
    207:   return(0);
    208: }

    212: PetscErrorCode KSPDestroy_Richardson(KSP ksp)
    213: {

    217:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetScale_C",NULL);
    218:   KSPDestroyDefault(ksp);
    219:   return(0);
    220: }

    224: static PetscErrorCode  KSPRichardsonSetScale_Richardson(KSP ksp,PetscReal scale)
    225: {
    226:   KSP_Richardson *richardsonP;

    229:   richardsonP        = (KSP_Richardson*)ksp->data;
    230:   richardsonP->scale = scale;
    231:   return(0);
    232: }

    236: static PetscErrorCode  KSPRichardsonSetSelfScale_Richardson(KSP ksp,PetscBool selfscale)
    237: {
    238:   KSP_Richardson *richardsonP;

    241:   richardsonP            = (KSP_Richardson*)ksp->data;
    242:   richardsonP->selfscale = selfscale;
    243:   return(0);
    244: }

    246: /*MC
    247:      KSPRICHARDSON - The preconditioned Richardson iterative method

    249:    Options Database Keys:
    250: .   -ksp_richardson_scale - damping factor on the correction (defaults to 1.0)

    252:    Level: beginner

    254:    Notes: x^{n+1} = x^{n} + scale*B(b - A x^{n})

    256:           Here B is the application of the preconditioner

    258:           This method often (usually) will not converge unless scale is very small.

    260:    Notes: For some preconditioners, currently SOR, the convergence test is skipped to improve speed,
    261:     thus it always iterates the maximum number of iterations you've selected. When -ksp_monitor
    262:     (or any other monitor) is turned on, the norm is computed at each iteration and so the convergence test is run unless
    263:     you specifically call KSPSetNormType(ksp,KSP_NORM_NONE);

    265:          For some preconditioners, currently PCMG and PCHYPRE with BoomerAMG if -ksp_monitor (and also
    266:     any other monitor) is not turned on then the convergence test is done by the preconditioner itself and
    267:     so the solver may run more or fewer iterations then if -ksp_monitor is selected.

    269:     Supports only left preconditioning

    271:   References:
    272: .  1. - L. F. Richardson, "The Approximate Arithmetical Solution by Finite Differences of Physical Problems Involving
    273:    Differential Equations, with an Application to the Stresses in a Masonry Dam",
    274:   Philosophical Transactions of the Royal Society of London. Series A,
    275:   Containing Papers of a Mathematical or Physical Character, Vol. 210, 1911 (1911).

    277: .seealso:  KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP,
    278:            KSPRichardsonSetScale()

    280: M*/

    284: PETSC_EXTERN PetscErrorCode KSPCreate_Richardson(KSP ksp)
    285: {
    287:   KSP_Richardson *richardsonP;

    290:   PetscNewLog(ksp,&richardsonP);
    291:   ksp->data = (void*)richardsonP;

    293:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,3);
    294:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,2);

    296:   ksp->ops->setup          = KSPSetUp_Richardson;
    297:   ksp->ops->solve          = KSPSolve_Richardson;
    298:   ksp->ops->destroy        = KSPDestroy_Richardson;
    299:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
    300:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
    301:   ksp->ops->view           = KSPView_Richardson;
    302:   ksp->ops->setfromoptions = KSPSetFromOptions_Richardson;

    304:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetScale_C",KSPRichardsonSetScale_Richardson);
    305:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetSelfScale_C",KSPRichardsonSetSelfScale_Richardson);

    307:   richardsonP->scale = 1.0;
    308:   return(0);
    309: }