Date: 2017-05-17T08:27:36+00:00

Actual source code: mfnkrylov.c
slepc-3.7.4 2017-05-17
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      1: /*

      3:    SLEPc matrix function solver: "krylov"

      5:    Method: Arnoldi with Eiermann-Ernst restart

      7:    Algorithm:

      9:        Build Arnoldi approximations using f(H) for the Hessenberg matrix H,
     10:        restart by discarding the Krylov basis but keeping H.

     12:    References:

     14:        [1] M. Eiermann and O. Ernst, "A restarted Krylov subspace method
     15:            for the evaluation of matrix functions", SIAM J. Numer. Anal.
     16:            44(6):2481-2504, 2006.

     18:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     19:    SLEPc - Scalable Library for Eigenvalue Problem Computations
     20:    Copyright (c) 2002-2016, Universitat Politecnica de Valencia, Spain

     22:    This file is part of SLEPc.

     24:    SLEPc is free software: you can redistribute it and/or modify it under  the
     25:    terms of version 3 of the GNU Lesser General Public License as published by
     26:    the Free Software Foundation.

     28:    SLEPc  is  distributed in the hope that it will be useful, but WITHOUT  ANY
     29:    WARRANTY;  without even the implied warranty of MERCHANTABILITY or  FITNESS
     30:    FOR  A  PARTICULAR PURPOSE. See the GNU Lesser General Public  License  for
     31:    more details.

     33:    You  should have received a copy of the GNU Lesser General  Public  License
     34:    along with SLEPc. If not, see <http://www.gnu.org/licenses/>.
     35:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     36: */

     38: #include <slepc/private/mfnimpl.h>
     39: #include <slepcblaslapack.h>

     43: PetscErrorCode MFNSetUp_Krylov(MFN mfn)
     44: {
     46:   PetscInt       N;

     49:   MatGetSize(mfn->A,&N,NULL);
     50:   if (!mfn->ncv) mfn->ncv = PetscMin(30,N);
     51:   if (!mfn->max_it) mfn->max_it = 100;
     52:   MFNAllocateSolution(mfn,1);
     53:   return(0);
     54: }

     58: PetscErrorCode MFNBasicArnoldi(MFN mfn,PetscScalar *H,PetscInt ldh,PetscInt k,PetscInt *M,PetscReal *beta,PetscBool *breakdown)
     59: {
     61:   PetscInt       j,m = *M;
     62:   Vec            vj,vj1;

     65:   BVSetActiveColumns(mfn->V,0,m);
     66:   for (j=k;j<m;j++) {
     67:     BVGetColumn(mfn->V,j,&vj);
     68:     BVGetColumn(mfn->V,j+1,&vj1);
     69:     MatMult(mfn->A,vj,vj1);
     70:     BVRestoreColumn(mfn->V,j,&vj);
     71:     BVRestoreColumn(mfn->V,j+1,&vj1);
     72:     BVOrthogonalizeColumn(mfn->V,j+1,H+ldh*j,beta,breakdown);
     73:     H[j+1+ldh*j] = *beta;
     74:     if (*breakdown) {
     75:       *M = j+1;
     76:       break;
     77:     } else {
     78:       BVScaleColumn(mfn->V,j+1,1.0/(*beta));
     79:     }
     80:   }
     81:   return(0);
     82: }

     86: PetscErrorCode MFNSolve_Krylov(MFN mfn,Vec b,Vec x)
     87: {
     89:   PetscInt       n=0,m,ld,ldh,j;
     90:   PetscBLASInt   m_,inc=1;
     91:   Mat            G=NULL,H=NULL;
     92:   Vec            F=NULL;
     93:   PetscScalar    *array,*farray,*garray,*harray;
     94:   PetscReal      beta,betaold=0.0,nrm=1.0;
     95:   PetscBool      breakdown,set,flg,symm=PETSC_FALSE;

     98:   m  = mfn->ncv;
     99:   ld = m+1;
    100:   PetscCalloc1(ld*ld,&array);

    102:   /* set initial vector to b/||b|| */
    103:   BVInsertVec(mfn->V,0,b);
    104:   BVScaleColumn(mfn->V,0,1.0/mfn->bnorm);
    105:   VecSet(x,0.0);

    107:   /* Restart loop */
    108:   while (mfn->reason == MFN_CONVERGED_ITERATING) {
    109:     mfn->its++;

    111:     /* compute Arnoldi factorization */
    112:     MFNBasicArnoldi(mfn,array,ld,0,&m,&beta,&breakdown);

    114:     /* save previous Hessenberg matrix in G; allocate new storage for H and f(H) */
    115:     if (mfn->its>1) { G = H; H = NULL; }
    116:     ldh = n+m;
    117:     MFN_CreateVec(ldh,&F);
    118:     MFN_CreateDenseMat(ldh,&H);

    120:     /* glue together the previous H and the new H obtained with Arnoldi */
    121:     MatDenseGetArray(H,&harray);
    122:     for (j=0;j<m;j++) {
    123:       PetscMemcpy(harray+n+(j+n)*ldh,array+j*ld,m*sizeof(PetscScalar));
    124:     }
    125:     if (mfn->its>1) {
    126:       MatDenseGetArray(G,&garray);
    127:       for (j=0;j<n;j++) {
    128:         PetscMemcpy(harray+j*ldh,garray+j*n,n*sizeof(PetscScalar));
    129:       }
    130:       MatDenseRestoreArray(G,&garray);
    131:       MatDestroy(&G);
    132:       harray[n+(n-1)*ldh] = betaold;
    133:     }
    134:     MatDenseRestoreArray(H,&harray);

    136:     if (mfn->its==1) {
    137:       /* set symmetry flag of H from A */
    138:       MatIsHermitianKnown(mfn->A,&set,&flg);
    139:       symm = set? flg: PETSC_FALSE;
    140:       if (symm) {
    141:         MatSetOption(H,MAT_HERMITIAN,PETSC_TRUE);
    142:       }
    143:     }

    145:     /* evaluate f(H) */
    146:     FNEvaluateFunctionMatVec(mfn->fn,H,F);

    148:     /* x += ||b||*V*f(H)*e_1 */
    149:     VecGetArray(F,&farray);
    150:     PetscBLASIntCast(m,&m_);
    151:     nrm = BLASnrm2_(&m_,farray+n,&inc);   /* relative norm of the update ||u||/||b|| */
    152:     MFNMonitor(mfn,mfn->its,nrm);
    153:     for (j=0;j<m;j++) farray[j+n] *= mfn->bnorm;
    154:     BVSetActiveColumns(mfn->V,0,m);
    155:     BVMultVec(mfn->V,1.0,1.0,x,farray+n);
    156:     VecRestoreArray(F,&farray);

    158:     /* check convergence */
    159:     if (mfn->its>1) {
    160:       if (mfn->its >= mfn->max_it) mfn->reason = MFN_DIVERGED_ITS;
    161:       if (m<mfn->ncv || breakdown || beta==0.0 || nrm<mfn->tol) mfn->reason = MFN_CONVERGED_TOL;
    162:     }

    164:     /* restart with vector v_{m+1} */
    165:     if (mfn->reason == MFN_CONVERGED_ITERATING) {
    166:       BVCopyColumn(mfn->V,m,0);
    167:       n += m;
    168:       betaold = beta;
    169:     }
    170:   }

    172:   MatDestroy(&H);
    173:   MatDestroy(&G);
    174:   VecDestroy(&F);
    175:   PetscFree(array);
    176:   return(0);
    177: }

    181: PETSC_EXTERN PetscErrorCode MFNCreate_Krylov(MFN mfn)
    182: {
    184:   mfn->ops->solve          = MFNSolve_Krylov;
    185:   mfn->ops->setup          = MFNSetUp_Krylov;
    186:   return(0);
    187: }