Date: 2013-07-02T14:47:57+00:00

Actual source code: pipecr.c
petsc-3.4.2 2013-07-02

      1: #include <petsc-private/kspimpl.h>

      3: /*
      4:      KSPSetUp_PIPECR - Sets up the workspace needed by the PIPECR method.

      6:       This is called once, usually automatically by KSPSolve() or KSPSetUp()
      7:      but can be called directly by KSPSetUp()
      8: */
     11: PetscErrorCode KSPSetUp_PIPECR(KSP ksp)
     12: {

     16:   /* get work vectors needed by PIPECR */
     17:   KSPSetWorkVecs(ksp,7);
     18:   return(0);
     19: }

     21: /*
     22:  KSPSolve_PIPECR - This routine actually applies the pipelined conjugate residual method

     24:  Input Parameter:
     25:  .     ksp - the Krylov space object that was set to use conjugate gradient, by, for
     26:              example, KSPCreate(MPI_Comm,KSP *ksp); KSPSetType(ksp,KSPCG);
     27: */
     30: PetscErrorCode  KSPSolve_PIPECR(KSP ksp)
     31: {
     33:   PetscInt       i;
     34:   PetscScalar    alpha=0.0,beta=0.0,gamma,gammaold=0.0,delta;
     35:   PetscReal      dp   = 0.0;
     36:   Vec            X,B,Z,P,W,Q,U,M,N;
     37:   Mat            Amat,Pmat;
     38:   MatStructure   pflag;
     39:   PetscBool      diagonalscale;

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

     45:   X = ksp->vec_sol;
     46:   B = ksp->vec_rhs;
     47:   M = ksp->work[0];
     48:   Z = ksp->work[1];
     49:   P = ksp->work[2];
     50:   N = ksp->work[3];
     51:   W = ksp->work[4];
     52:   Q = ksp->work[5];
     53:   U = ksp->work[6];

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

     57:   ksp->its = 0;
     58:   /* we don't have an R vector, so put the (unpreconditioned) residual in w for now */
     59:   if (!ksp->guess_zero) {
     60:     KSP_MatMult(ksp,Amat,X,W);            /*     w <- b - Ax     */
     61:     VecAYPX(W,-1.0,B);
     62:   } else {
     63:     VecCopy(B,W);                         /*     w <- b (x is 0) */
     64:   }
     65:   KSP_PCApply(ksp,W,U);                   /*     u <- Bw   */

     67:   switch (ksp->normtype) {
     68:   case KSP_NORM_PRECONDITIONED:
     69:     VecNormBegin(U,NORM_2,&dp);           /*     dp <- u'*u = e'*A'*B'*B*A'*e'     */
     70:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)U));
     71:     KSP_MatMult(ksp,Amat,U,W);            /*     w <- Au   */
     72:     VecNormEnd(U,NORM_2,&dp);
     73:     break;
     74:   case KSP_NORM_NONE:
     75:     KSP_MatMult(ksp,Amat,U,W);
     76:     dp   = 0.0;
     77:     break;
     78:   default: SETERRQ1(PetscObjectComm((PetscObject)ksp),PETSC_ERR_SUP,"%s",KSPNormTypes[ksp->normtype]);
     79:   }
     80:   KSPLogResidualHistory(ksp,dp);
     81:   KSPMonitor(ksp,0,dp);
     82:   ksp->rnorm = dp;
     83:   (*ksp->converged)(ksp,0,dp,&ksp->reason,ksp->cnvP); /* test for convergence */
     84:   if (ksp->reason) return(0);

     86:   i = 0;
     87:   do {
     88:     KSP_PCApply(ksp,W,M);            /*   m <- Bw       */

     90:     if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
     91:       VecNormBegin(U,NORM_2,&dp);
     92:     }
     93:     VecDotBegin(W,U,&gamma);
     94:     VecDotBegin(M,W,&delta);
     95:     PetscCommSplitReductionBegin(PetscObjectComm((PetscObject)U));

     97:     KSP_MatMult(ksp,Amat,M,N);       /*   n <- Am       */

     99:     if (i > 0 && ksp->normtype == KSP_NORM_PRECONDITIONED) {
    100:       VecNormEnd(U,NORM_2,&dp);
    101:     }
    102:     VecDotEnd(W,U,&gamma);
    103:     VecDotEnd(M,W,&delta);

    105:     if (i > 0) {
    106:       if (ksp->normtype == KSP_NORM_NONE) dp = 0.0;
    107:       ksp->rnorm = dp;
    108:       KSPLogResidualHistory(ksp,dp);
    109:       KSPMonitor(ksp,i,dp);
    110:       (*ksp->converged)(ksp,i,dp,&ksp->reason,ksp->cnvP);
    111:       if (ksp->reason) break;
    112:     }

    114:     if (i == 0) {
    115:       alpha = gamma / delta;
    116:       VecCopy(N,Z);        /*     z <- n          */
    117:       VecCopy(M,Q);        /*     q <- m          */
    118:       VecCopy(U,P);        /*     p <- u          */
    119:     } else {
    120:       beta  = gamma / gammaold;
    121:       alpha = gamma / (delta - beta / alpha * gamma);
    122:       VecAYPX(Z,beta,N);   /*     z <- n + beta * z   */
    123:       VecAYPX(Q,beta,M);   /*     q <- m + beta * q   */
    124:       VecAYPX(P,beta,U);   /*     p <- u + beta * p   */
    125:     }
    126:     VecAXPY(X, alpha,P); /*     x <- x + alpha * p   */
    127:     VecAXPY(U,-alpha,Q); /*     u <- u - alpha * q   */
    128:     VecAXPY(W,-alpha,Z); /*     w <- w - alpha * z   */
    129:     gammaold = gamma;
    130:     i++;
    131:     ksp->its = i;

    133:     /* if (i%50 == 0) { */
    134:     /*   KSP_MatMult(ksp,Amat,X,W);            /\*     w <- b - Ax     *\/ */
    135:     /*   VecAYPX(W,-1.0,B); */
    136:     /*   KSP_PCApply(ksp,W,U); */
    137:     /*   KSP_MatMult(ksp,Amat,U,W); */
    138:     /* } */

    140:   } while (i<ksp->max_it);
    141:   if (i >= ksp->max_it) ksp->reason = KSP_DIVERGED_ITS;
    142:   return(0);
    143: }

    145: /*MC
    146:    KSPPIPECR - Pipelined conjugate residual method

    148:    There method has only a single non-blocking reduction per iteration, compared to 2 blocking for standard CR.  The
    149:    non-blocking reduction is overlapped by the matrix-vector product, but not preconditioner application.

    151:    See also KSPPIPECG, where the reduction is only overlapped with the matrix-vector product.

    153:    Level:
    154:    beginner

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

    160:    Contributed by:
    161:    Pieter Ghysels, Universiteit Antwerpen, Intel Exascience lab Flanders

    163:    Reference:
    164:    P. Ghysels and W. Vanroose, "Hiding global synchronization latency in the preconditioned Conjugate Gradient algorithm",
    165:    Submitted to Parallel Computing, 2012.

    167: .seealso: KSPCreate(), KSPSetType(), KSPPIPECG, KSPGROPPCG, KSPPGMRES, KSPCG, KSPCGUseSingleReduction()
    168: M*/

    172: PETSC_EXTERN PetscErrorCode KSPCreate_PIPECR(KSP ksp)
    173: {

    177:   KSPSetSupportedNorm(ksp,KSP_NORM_PRECONDITIONED,PC_LEFT,1);
    178:   KSPSetSupportedNorm(ksp,KSP_NORM_NONE,PC_LEFT,1);

    180:   ksp->ops->setup          = KSPSetUp_PIPECR;
    181:   ksp->ops->solve          = KSPSolve_PIPECR;
    182:   ksp->ops->destroy        = KSPDestroyDefault;
    183:   ksp->ops->view           = 0;
    184:   ksp->ops->setfromoptions = 0;
    185:   ksp->ops->buildsolution  = KSPBuildSolutionDefault;
    186:   ksp->ops->buildresidual  = KSPBuildResidualDefault;
    187:   return(0);
    188: }