Actual source code: rich.c

      2: /*
      3:             This implements Richardson Iteration.
      4: */
      5: #include <../src/ksp/ksp/impls/rich/richardsonimpl.h>

      7: PetscErrorCode KSPSetUp_Richardson(KSP ksp)
      8: {
      9:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;

     11:   if (richardsonP->selfscale) {
     12:     KSPSetWorkVecs(ksp,4);
     13:   } else {
     14:     KSPSetWorkVecs(ksp,2);
     15:   }
     16:   return 0;
     17: }

     19: PetscErrorCode  KSPSolve_Richardson(KSP ksp)
     20: {
     21:   PetscInt       i,maxit;
     22:   PetscReal      rnorm = 0.0,abr;
     23:   PetscScalar    scale,rdot;
     24:   Vec            x,b,r,z,w = NULL,y = NULL;
     25:   PetscInt       xs, ws;
     26:   Mat            Amat,Pmat;
     27:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;
     28:   PetscBool      exists,diagonalscale;
     29:   MatNullSpace   nullsp;

     31:   PCGetDiagonalScale(ksp->pc,&diagonalscale);

     34:   ksp->its = 0;

     36:   PCGetOperators(ksp->pc,&Amat,&Pmat);
     37:   x    = ksp->vec_sol;
     38:   b    = ksp->vec_rhs;
     39:   VecGetSize(x,&xs);
     40:   VecGetSize(ksp->work[0],&ws);
     41:   if (xs != ws) {
     42:     if (richardsonP->selfscale) {
     43:       KSPSetWorkVecs(ksp,4);
     44:     } else {
     45:       KSPSetWorkVecs(ksp,2);
     46:     }
     47:   }
     48:   r = ksp->work[0];
     49:   z = ksp->work[1];
     50:   if (richardsonP->selfscale) {
     51:     w = ksp->work[2];
     52:     y = ksp->work[3];
     53:   }
     54:   maxit = ksp->max_it;

     56:   /* if user has provided fast Richardson code use that */
     57:   PCApplyRichardsonExists(ksp->pc,&exists);
     58:   MatGetNullSpace(Pmat,&nullsp);
     59:   if (exists && maxit > 0 && richardsonP->scale == 1.0 && (ksp->converged == KSPConvergedDefault || ksp->converged == KSPConvergedSkip) && !ksp->numbermonitors && !ksp->transpose_solve && !nullsp) {
     60:     PCRichardsonConvergedReason reason;
     61:     PCApplyRichardson(ksp->pc,b,x,r,ksp->rtol,ksp->abstol,ksp->divtol,maxit,ksp->guess_zero,&ksp->its,&reason);
     62:     ksp->reason = (KSPConvergedReason)reason;
     63:     return 0;
     64:   } else {
     65:     PetscInfo(ksp,"KSPSolve_Richardson: Warning, skipping optimized PCApplyRichardson()\n");
     66:   }

     68:   if (!ksp->guess_zero) {                          /*   r <- b - A x     */
     69:     KSP_MatMult(ksp,Amat,x,r);
     70:     VecAYPX(r,-1.0,b);
     71:   } else {
     72:     VecCopy(b,r);
     73:   }

     75:   ksp->its = 0;
     76:   if (richardsonP->selfscale) {
     77:     KSP_PCApply(ksp,r,z);         /*   z <- B r          */
     78:     for (i=0; i<maxit; i++) {

     80:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
     81:         VecNorm(r,NORM_2,&rnorm); /*   rnorm <- r'*r     */
     82:       } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
     83:         VecNorm(z,NORM_2,&rnorm); /*   rnorm <- z'*z     */
     84:       } else rnorm = 0.0;

     86:       KSPCheckNorm(ksp,rnorm);
     87:       ksp->rnorm = rnorm;
     88:       KSPMonitor(ksp,i,rnorm);
     89:       KSPLogResidualHistory(ksp,rnorm);
     90:       (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
     91:       if (ksp->reason) break;
     92:       KSP_PCApplyBAorAB(ksp,z,y,w); /* y = BAz = BABr */
     93:       VecDotNorm2(z,y,&rdot,&abr));   /*   rdot = (Br)^T(BABR; abr = (BABr)^T (BABr) */
     94:       scale = rdot/abr;
     95:       PetscInfo(ksp,"Self-scale factor %g\n",(double)PetscRealPart(scale));
     96:       VecAXPY(x,scale,z);   /*   x  <- x + scale z */
     97:       VecAXPY(r,-scale,w);  /*  r <- r - scale*Az */
     98:       VecAXPY(z,-scale,y);  /*  z <- z - scale*y */
     99:       ksp->its++;
    100:     }
    101:   } else {
    102:     for (i=0; i<maxit; i++) {

    104:       if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    105:         VecNorm(r,NORM_2,&rnorm); /*   rnorm <- r'*r     */
    106:       } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
    107:         KSP_PCApply(ksp,r,z);    /*   z <- B r          */
    108:         VecNorm(z,NORM_2,&rnorm); /*   rnorm <- z'*z     */
    109:       } else rnorm = 0.0;
    110:       ksp->rnorm = rnorm;
    111:       KSPMonitor(ksp,i,rnorm);
    112:       KSPLogResidualHistory(ksp,rnorm);
    113:       (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    114:       if (ksp->reason) break;
    115:       if (ksp->normtype != KSP_NORM_PRECONDITIONED) {
    116:         KSP_PCApply(ksp,r,z);    /*   z <- B r          */
    117:       }

    119:       VecAXPY(x,richardsonP->scale,z);    /*   x  <- x + scale z */
    120:       ksp->its++;

    122:       if (i+1 < maxit || ksp->normtype != KSP_NORM_NONE) {
    123:         KSP_MatMult(ksp,Amat,x,r);      /*   r  <- b - Ax      */
    124:         VecAYPX(r,-1.0,b);
    125:       }
    126:     }
    127:   }
    128:   if (!ksp->reason) {
    129:     if (ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    130:       VecNorm(r,NORM_2,&rnorm);     /*   rnorm <- r'*r     */
    131:     } else if (ksp->normtype == KSP_NORM_PRECONDITIONED) {
    132:       KSP_PCApply(ksp,r,z);   /*   z <- B r          */
    133:       VecNorm(z,NORM_2,&rnorm);     /*   rnorm <- z'*z     */
    134:     } else rnorm = 0.0;

    136:     KSPCheckNorm(ksp,rnorm);
    137:     ksp->rnorm = rnorm;
    138:     KSPLogResidualHistory(ksp,rnorm);
    139:     KSPMonitor(ksp,i,rnorm);
    140:     if (ksp->its >= ksp->max_it) {
    141:       if (ksp->normtype != KSP_NORM_NONE) {
    142:         (*ksp->converged)(ksp,i,rnorm,&ksp->reason,ksp->cnvP);
    143:         if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
    144:       } else {
    145:         ksp->reason = KSP_CONVERGED_ITS;
    146:       }
    147:     }
    148:   }
    149:   return 0;
    150: }

    152: PetscErrorCode KSPView_Richardson(KSP ksp,PetscViewer viewer)
    153: {
    154:   KSP_Richardson *richardsonP = (KSP_Richardson*)ksp->data;
    155:   PetscBool      iascii;

    157:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    158:   if (iascii) {
    159:     if (richardsonP->selfscale) {
    160:       PetscViewerASCIIPrintf(viewer,"  using self-scale best computed damping factor\n");
    161:     } else {
    162:       PetscViewerASCIIPrintf(viewer,"  damping factor=%g\n",(double)richardsonP->scale);
    163:     }
    164:   }
    165:   return 0;
    166: }

    168: PetscErrorCode KSPSetFromOptions_Richardson(PetscOptionItems *PetscOptionsObject,KSP ksp)
    169: {
    170:   KSP_Richardson *rich = (KSP_Richardson*)ksp->data;
    171:   PetscReal      tmp;
    172:   PetscBool      flg,flg2;

    174:   PetscOptionsHead(PetscOptionsObject,"KSP Richardson Options");
    175:   PetscOptionsReal("-ksp_richardson_scale","damping factor","KSPRichardsonSetScale",rich->scale,&tmp,&flg);
    176:   if (flg) KSPRichardsonSetScale(ksp,tmp);
    177:   PetscOptionsBool("-ksp_richardson_self_scale","dynamically determine optimal damping factor","KSPRichardsonSetSelfScale",rich->selfscale,&flg2,&flg);
    178:   if (flg) KSPRichardsonSetSelfScale(ksp,flg2);
    179:   PetscOptionsTail();
    180:   return 0;
    181: }

    183: PetscErrorCode KSPDestroy_Richardson(KSP ksp)
    184: {
    185:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetScale_C",NULL);
    186:   KSPDestroyDefault(ksp);
    187:   return 0;
    188: }

    190: static PetscErrorCode  KSPRichardsonSetScale_Richardson(KSP ksp,PetscReal scale)
    191: {
    192:   KSP_Richardson *richardsonP;

    194:   richardsonP        = (KSP_Richardson*)ksp->data;
    195:   richardsonP->scale = scale;
    196:   return 0;
    197: }

    199: static PetscErrorCode  KSPRichardsonSetSelfScale_Richardson(KSP ksp,PetscBool selfscale)
    200: {
    201:   KSP_Richardson *richardsonP;

    203:   richardsonP            = (KSP_Richardson*)ksp->data;
    204:   richardsonP->selfscale = selfscale;
    205:   return 0;
    206: }

    208: static PetscErrorCode KSPBuildResidual_Richardson(KSP ksp,Vec t,Vec v,Vec *V)
    209: {
    210:   if (ksp->normtype == KSP_NORM_NONE) {
    211:     KSPBuildResidualDefault(ksp,t,v,V);
    212:   } else {
    213:     VecCopy(ksp->work[0],v);
    214:     *V   = v;
    215:   }
    216:   return 0;
    217: }

    219: /*MC
    220:      KSPRICHARDSON - The preconditioned Richardson iterative method

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

    225:    Level: beginner

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

    230:           Here B is the application of the preconditioner

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

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

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

    244:     Supports only left preconditioning

    246:     If using direct solvers such as PCLU and PCCHOLESKY one generally uses KSPPREONLY which uses exactly one iteration

    248: $    -ksp_type richardson -pc_type jacobi gives one classically Jacobi preconditioning

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

    256: .seealso:  KSPCreate(), KSPSetType(), KSPType (for list of available types), KSP,
    257:            KSPRichardsonSetScale(), KSPPREONLY

    259: M*/

    261: PETSC_EXTERN PetscErrorCode KSPCreate_Richardson(KSP ksp)
    262: {
    263:   KSP_Richardson *richardsonP;

    265:   PetscNewLog(ksp,&richardsonP);
    266:   ksp->data = (void*)richardsonP;

    268:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,3);
    269:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,2);
    270:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);

    272:   ksp->ops->setup          = KSPSetUp_Richardson;
    273:   ksp->ops->solve          = KSPSolve_Richardson;
    274:   ksp->ops->destroy        = KSPDestroy_Richardson;
    275:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
    276:   ksp->ops->buildresidual  = KSPBuildResidual_Richardson;
    277:   ksp->ops->view           = KSPView_Richardson;
    278:   ksp->ops->setfromoptions = KSPSetFromOptions_Richardson;

    280:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetScale_C",KSPRichardsonSetScale_Richardson);
    281:   PetscObjectComposeFunction((PetscObject)ksp,"KSPRichardsonSetSelfScale_C",KSPRichardsonSetSelfScale_Richardson);

    283:   richardsonP->scale = 1.0;
    284:   return 0;
    285: }