Date: 2022-03-04T17:39:02+00:00

Actual source code: pipecgrr.c

      2: #include <petsc/private/kspimpl.h>

      4: /*
      5:      KSPSetUp_PIPECGRR - Sets up the workspace needed by the PIPECGRR method.

      7:       This is called once, usually automatically by KSPSolve() or KSPSetUp()
      8:      but can be called directly by KSPSetUp()
      9: */
     10: static PetscErrorCode KSPSetUp_PIPECGRR(KSP ksp)
     11: {

     15:   /* get work vectors needed by PIPECGRR */
     16:   KSPSetWorkVecs(ksp,9);
     17:   return(0);
     18: }

     20: /*
     21:  KSPSolve_PIPECGRR - This routine actually applies the pipelined conjugate gradient method with automated residual replacement
     22: */
     23: static PetscErrorCode  KSPSolve_PIPECGRR(KSP ksp)
     24: {
     26:   PetscInt       i = 0,replace = 0,totreplaces = 0,nsize;
     27:   PetscScalar    alpha = 0.0,beta = 0.0,gamma = 0.0,gammaold = 0.0,delta = 0.0,alphap = 0.0,betap = 0.0;
     28:   PetscReal      dp = 0.0,nsi = 0.0,sqn = 0.0,Anorm = 0.0,rnp = 0.0,pnp = 0.0,snp = 0.0,unp = 0.0,wnp = 0.0,xnp = 0.0,qnp = 0.0,znp = 0.0,mnz = 5.0,tol = PETSC_SQRT_MACHINE_EPSILON,eps = PETSC_MACHINE_EPSILON;
     29:   PetscReal      ds = 0.0,dz = 0.0,dx = 0.0,dpp = 0.0,dq = 0.0,dm = 0.0,du = 0.0,dw = 0.0,db = 0.0,errr = 0.0,errrprev = 0.0,errs = 0.0,errw = 0.0,errz = 0.0,errncr = 0.0,errncs = 0.0,errncw = 0.0,errncz = 0.0;
     30:   Vec            X,B,Z,P,W,Q,U,M,N,R,S;
     31:   Mat            Amat,Pmat;
     32:   PetscBool      diagonalscale;

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

     38:   X = ksp->vec_sol;
     39:   B = ksp->vec_rhs;
     40:   M = ksp->work[0];
     41:   Z = ksp->work[1];
     42:   P = ksp->work[2];
     43:   N = ksp->work[3];
     44:   W = ksp->work[4];
     45:   Q = ksp->work[5];
     46:   U = ksp->work[6];
     47:   R = ksp->work[7];
     48:   S = ksp->work[8];

     50:   PCGetOperators(ksp->pc,&Amat,&Pmat);

     52:   ksp->its = 0;
     53:   if (!ksp->guess_zero) {
     54:     KSP_MatMult(ksp,Amat,X,R);  /*  r <- b - Ax  */
     55:     VecAYPX(R,-1.0,B);
     56:   } else {
     57:     VecCopy(B,R);               /*  r <- b (x is 0)  */
     58:   }

     60:   KSP_PCApply(ksp,R,U);         /*  u <- Br  */

     62:   switch (ksp->normtype) {
     63:   case KSP_NORM_PRECONDITIONED:
     64:     VecNormBegin(U,NORM_2,&dp); /*  dp <- u'*u = e'*A'*B'*B*A'*e'  */
     65:     VecNormBegin(B,NORM_2,&db);
     66:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)U));
     67:     KSP_MatMult(ksp,Amat,U,W);  /*  w <- Au  */
     68:     VecNormEnd(U,NORM_2,&dp);
     69:     VecNormEnd(B,NORM_2,&db);
     70:     break;
     71:   case KSP_NORM_UNPRECONDITIONED:
     72:     VecNormBegin(R,NORM_2,&dp); /*  dp <- r'*r = e'*A'*A*e  */
     73:     VecNormBegin(B,NORM_2,&db);
     74:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));
     75:     KSP_MatMult(ksp,Amat,U,W);  /*  w <- Au  */
     76:     VecNormEnd(R,NORM_2,&dp);
     77:     VecNormEnd(B,NORM_2,&db);
     78:     break;
     79:   case KSP_NORM_NATURAL:
     80:     VecDotBegin(R,U,&gamma);    /*  gamma <- u'*r  */
     81:     VecNormBegin(B,NORM_2,&db);
     82:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));
     83:     KSP_MatMult(ksp,Amat,U,W);  /*  w <- Au  */
     84:     VecDotEnd(R,U,&gamma);
     85:     VecNormEnd(B,NORM_2,&db);
     86:     KSPCheckDot(ksp,gamma);
     87:     dp = PetscSqrtReal(PetscAbsScalar(gamma));       /*  dp <- r'*u = r'*B*r = e'*A'*B*A*e  */
     88:     break;
     89:   case KSP_NORM_NONE:
     90:     KSP_MatMult(ksp,Amat,U,W);
     91:     dp   = 0.0;
     92:     break;
     93:   default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
     94:   }
     95:   KSPLogResidualHistory(ksp,dp);
     96:   KSPMonitor(ksp,0,dp);
     97:   ksp->rnorm = dp;
     98:   (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP); /*  test for convergence  */
     99:   if (ksp->reason) return(0);

    101:   MatNorm(Amat,NORM_INFINITY,&Anorm);
    102:   VecGetSize(B,&nsize);
    103:   nsi = (PetscReal) nsize;
    104:   sqn = PetscSqrtReal(nsi);

    106:   do {
    107:     if (i > 1) {
    108:       pnp = dpp;
    109:       snp = ds;
    110:       qnp = dq;
    111:       znp = dz;
    112:     }
    113:     if (i > 0) {
    114:       rnp = dp;
    115:       unp = du;
    116:       wnp = dw;
    117:       xnp = dx;
    118:       alphap = alpha;
    119:       betap = beta;
    120:     }

    122:     if (i > 0 && ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    123:       VecNormBegin(R,NORM_2,&dp);
    124:     } else if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
    125:       VecNormBegin(U,NORM_2,&dp);
    126:     }
    127:     if (!(i == 0 && ksp->normtype == KSP_NORM_NATURAL)) {
    128:       VecDotBegin(R,U,&gamma);
    129:     }
    130:     VecDotBegin(W,U,&delta);

    132:     if (i > 0) {
    133:       VecNormBegin(S,NORM_2,&ds);
    134:       VecNormBegin(Z,NORM_2,&dz);
    135:       VecNormBegin(P,NORM_2,&dpp);
    136:       VecNormBegin(Q,NORM_2,&dq);
    137:       VecNormBegin(M,NORM_2,&dm);
    138:     }
    139:     VecNormBegin(X,NORM_2,&dx);
    140:     VecNormBegin(U,NORM_2,&du);
    141:     VecNormBegin(W,NORM_2,&dw);

    143:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)R));
    144:     KSP_PCApply(ksp,W,M);           /*   m <- Bw       */
    145:     KSP_MatMult(ksp,Amat,M,N);      /*   n <- Am       */

    147:     if (i > 0 && ksp->normtype == KSP_NORM_UNPRECONDITIONED) {
    148:       VecNormEnd(R,NORM_2,&dp);
    149:     } else if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
    150:       VecNormEnd(U,NORM_2,&dp);
    151:     }
    152:     if (!(i == 0 && ksp->normtype == KSP_NORM_NATURAL)) {
    153:       VecDotEnd(R,U,&gamma);
    154:     }
    155:     VecDotEnd(W,U,&delta);

    157:     if (i > 0) {
    158:       VecNormEnd(S,NORM_2,&ds);
    159:       VecNormEnd(Z,NORM_2,&dz);
    160:       VecNormEnd(P,NORM_2,&dpp);
    161:       VecNormEnd(Q,NORM_2,&dq);
    162:       VecNormEnd(M,NORM_2,&dm);
    163:     }
    164:     VecNormEnd(X,NORM_2,&dx);
    165:     VecNormEnd(U,NORM_2,&du);
    166:     VecNormEnd(W,NORM_2,&dw);

    168:     if (i > 0) {
    169:       if (ksp->normtype == KSP_NORM_NATURAL) dp = PetscSqrtReal(PetscAbsScalar(gamma));
    170:       else if (ksp->normtype == KSP_NORM_NONE) dp = 0.0;

    172:       ksp->rnorm = dp;
    173:       KSPLogResidualHistory(ksp,dp);
    174:       KSPMonitor(ksp,i,dp);
    175:       (*ksp->converged)(ksp,i,dp,&ksp->reason,ksp->cnvP);
    176:       if (ksp->reason) return(0);
    177:     }

    179:     if (i == 0) {
    180:       alpha = gamma / delta;
    181:       VecCopy(N,Z);          /*  z <- n  */
    182:       VecCopy(M,Q);          /*  q <- m  */
    183:       VecCopy(U,P);          /*  p <- u  */
    184:       VecCopy(W,S);          /*  s <- w  */
    185:     } else {
    186:       beta = gamma / gammaold;
    187:       alpha = gamma / (delta - beta / alpha * gamma);
    188:       VecAYPX(Z,beta,N);     /*  z <- n + beta * z  */
    189:       VecAYPX(Q,beta,M);     /*  q <- m + beta * q  */
    190:       VecAYPX(P,beta,U);     /*  p <- u + beta * p  */
    191:       VecAYPX(S,beta,W);     /*  s <- w + beta * s  */
    192:     }
    193:     VecAXPY(X, alpha,P);     /*  x <- x + alpha * p  */
    194:     VecAXPY(U,-alpha,Q);     /*  u <- u - alpha * q  */
    195:     VecAXPY(W,-alpha,Z);     /*  w <- w - alpha * z  */
    196:     VecAXPY(R,-alpha,S);     /*  r <- r - alpha * s  */
    197:     gammaold = gamma;

    199:     if (i > 0) {
    200:       errncr = PetscSqrtReal(Anorm*xnp+2.0*Anorm*PetscAbsScalar(alphap)*dpp+rnp+2.0*PetscAbsScalar(alphap)*ds)*eps;
    201:       errncw = PetscSqrtReal(Anorm*unp+2.0*Anorm*PetscAbsScalar(alphap)*dq+wnp+2.0*PetscAbsScalar(alphap)*dz)*eps;
    202:     }
    203:     if (i > 1) {
    204:       errncs = PetscSqrtReal(Anorm*unp+2.0*Anorm*PetscAbsScalar(betap)*pnp+wnp+2.0*PetscAbsScalar(betap)*snp)*eps;
    205:       errncz = PetscSqrtReal((mnz*sqn+2)*Anorm*dm+2.0*Anorm*PetscAbsScalar(betap)*qnp+2.0*PetscAbsScalar(betap)*znp)*eps;
    206:     }

    208:     if (i > 0) {
    209:       if (i == 1) {
    210:         errr = PetscSqrtReal((mnz*sqn+1)*Anorm*xnp+db)*eps+PetscSqrtReal(PetscAbsScalar(alphap)*mnz*sqn*Anorm*dpp)*eps+errncr;
    211:         errs = PetscSqrtReal(mnz*sqn*Anorm*dpp)*eps;
    212:         errw = PetscSqrtReal(mnz*sqn*Anorm*unp)*eps+PetscSqrtReal(PetscAbsScalar(alphap)*mnz*sqn*Anorm*dq)*eps+errncw;
    213:         errz = PetscSqrtReal(mnz*sqn*Anorm*dq)*eps;
    214:       } else if (replace == 1) {
    215:         errrprev = errr;
    216:         errr = PetscSqrtReal((mnz*sqn+1)*Anorm*dx+db)*eps;
    217:         errs = PetscSqrtReal(mnz*sqn*Anorm*dpp)*eps;
    218:         errw = PetscSqrtReal(mnz*sqn*Anorm*du)*eps;
    219:         errz = PetscSqrtReal(mnz*sqn*Anorm*dq)*eps;
    220:         replace = 0;
    221:       } else {
    222:         errrprev = errr;
    223:         errr = errr+PetscAbsScalar(alphap)*PetscAbsScalar(betap)*errs+PetscAbsScalar(alphap)*errw+errncr+PetscAbsScalar(alphap)*errncs;
    224:         errs = errw+PetscAbsScalar(betap)*errs+errncs;
    225:         errw = errw+PetscAbsScalar(alphap)*PetscAbsScalar(betap)*errz+errncw+PetscAbsScalar(alphap)*errncz;
    226:         errz = PetscAbsScalar(betap)*errz+errncz;
    227:       }
    228:       if (i > 1 && errrprev <= (tol * rnp) && errr > (tol * dp)) {
    229:         KSP_MatMult(ksp,Amat,X,R);        /*  r <- Ax - b  */
    230:         VecAYPX(R,-1.0,B);
    231:         KSP_PCApply(ksp,R,U);             /*  u <- Br  */
    232:         KSP_MatMult(ksp,Amat,U,W);        /*  w <- Au  */
    233:         KSP_MatMult(ksp,Amat,P,S);        /*  s <- Ap  */
    234:         KSP_PCApply(ksp,S,Q);             /*  q <- Bs  */
    235:         KSP_MatMult(ksp,Amat,Q,Z);        /*  z <- Aq  */
    236:         replace = 1;
    237:         totreplaces++;
    238:       }
    239:     }

    241:     i++;
    242:     ksp->its = i;

    244:   } while (i<=ksp->max_it);
    245:   if (!ksp->reason) ksp->reason = KSP_DIVERGED_ITS;
    246:   return(0);
    247: }

    249: /*MC
    250:    KSPPIPECGRR - Pipelined conjugate gradient method with automated residual replacements.

    252:    This method has only a single non-blocking reduction per iteration, compared to 2 blocking for standard CG.  The
    253:    non-blocking reduction is overlapped by the matrix-vector product and preconditioner application.

    255:    KSPPIPECGRR improves the robustness of KSPPIPECG by adding an automated residual replacement strategy.
    256:    True residual and other auxiliary variables are computed explicitly in a number of dynamically determined
    257:    iterations to counteract the accumulation of rounding errors and thus attain a higher maximal final accuracy.

    259:    See also KSPPIPECG, which is identical to KSPPIPECGRR without residual replacements.
    260:    See also KSPPIPECR, where the reduction is only overlapped with the matrix-vector product.

    262:    Level: intermediate

    264:    Notes:
    265:    MPI configuration may be necessary for reductions to make asynchronous progress, which is important for
    266:    performance of pipelined methods. See the FAQ on the PETSc website for details.

    268:    Contributed by:
    269:    Siegfried Cools, Universiteit Antwerpen, Dept. Mathematics & Computer Science,
    270:    European FP7 Project on EXascale Algorithms and Advanced Computational Techniques (EXA2CT) / Research Foundation Flanders (FWO)

    272:    Reference:
    273:    S. Cools, E.F. Yetkin, E. Agullo, L. Giraud, W. Vanroose, "Analyzing the effect of local rounding error
    274:    propagation on the maximal attainable accuracy of the pipelined Conjugate Gradients method",
    275:    SIAM Journal on Matrix Analysis and Applications (SIMAX), 39(1):426--450, 2018.

    277: .seealso: KSPCreate(), KSPSetType(), KSPPIPECR, KSPGROPPCG, KSPPIPECG, KSPPGMRES, KSPCG, KSPPIPEBCGS, KSPCGUseSingleReduction()
    278: M*/
    279: PETSC_EXTERN PetscErrorCode KSPCreate_PIPECGRR(KSP ksp)
    280: {

    284:   KSPSetSupportedNorm(ksp,KSP_NORM_UNPRECONDITIONED,PC_LEFT,2);
    285:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,2);
    286:   KSPSetSupportedNorm(ksp,KSP_NORM_NATURAL,PC_LEFT,2);
    287:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);

    289:   ksp->ops->setup          = KSPSetUp_PIPECGRR;
    290:   ksp->ops->solve          = KSPSolve_PIPECGRR;
    291:   ksp->ops->destroy        = KSPDestroyDefault;
    292:   ksp->ops->view           = NULL;
    293:   ksp->ops->setfromoptions = NULL;
    294:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
    295:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
    296:   return(0);
    297: }