Actual source code: lobpcg.c
slepc-3.21.1 2024-04-26
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    SLEPc eigensolver: "lobpcg"

     13:    Method: Locally Optimal Block Preconditioned Conjugate Gradient

     15:    Algorithm:

     17:        LOBPCG with soft and hard locking. Follows the implementation
     18:        in BLOPEX [2].

     20:    References:

     22:        [1] A. V. Knyazev, "Toward the optimal preconditioned eigensolver:
     23:            locally optimal block preconditioned conjugate gradient method",
     24:            SIAM J. Sci. Comput. 23(2):517-541, 2001.

     26:        [2] A. V. Knyazev et al., "Block Locally Optimal Preconditioned
     27:            Eigenvalue Xolvers (BLOPEX) in Hypre and PETSc", SIAM J. Sci.
     28:            Comput. 29(5):2224-2239, 2007.
     29: */

     31: #include <slepc/private/epsimpl.h>

     33: typedef struct {
     34:   PetscInt  bs;        /* block size */
     35:   PetscBool lock;      /* soft locking active/inactive */
     36:   PetscReal restart;   /* restart parameter */
     37:   PetscInt  guard;     /* number of guard vectors */
     38: } EPS_LOBPCG;

     40: static PetscErrorCode EPSSetDimensions_LOBPCG(EPS eps,PetscInt nev,PetscInt *ncv,PetscInt *mpd)
     41: {
     42:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;
     43:   PetscInt   k;

     45:   PetscFunctionBegin;
     46:   k = PetscMax(3*ctx->bs,((eps->nev-1)/ctx->bs+3)*ctx->bs);
     47:   if (*ncv!=PETSC_DEFAULT) { /* ncv set */
     48:     PetscCheck(*ncv>=k,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"The value of ncv is not sufficiently large");
     49:   } else *ncv = k;
     50:   if (*mpd==PETSC_DEFAULT) *mpd = 3*ctx->bs;
     51:   else PetscCheck(*mpd==3*ctx->bs,PetscObjectComm((PetscObject)eps),PETSC_ERR_USER_INPUT,"This solver does not allow a value of mpd different from 3*blocksize");
     52:   PetscFunctionReturn(PETSC_SUCCESS);
     53: }

     55: static PetscErrorCode EPSSetUp_LOBPCG(EPS eps)
     56: {
     57:   EPS_LOBPCG     *ctx = (EPS_LOBPCG*)eps->data;

     59:   PetscFunctionBegin;
     60:   EPSCheckHermitianDefinite(eps);
     61:   if (!ctx->bs) ctx->bs = PetscMin(16,eps->nev);
     62:   PetscCheck(eps->n-eps->nds>=5*ctx->bs,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"The problem size is too small relative to the block size");
     63:   PetscCall(EPSSetDimensions_LOBPCG(eps,eps->nev,&eps->ncv,&eps->mpd));
     64:   if (eps->max_it==PETSC_DEFAULT) eps->max_it = PetscMax(100,2*eps->n/eps->ncv);
     65:   if (!eps->which) eps->which = EPS_SMALLEST_REAL;
     66:   PetscCheck(eps->which==EPS_SMALLEST_REAL || eps->which==EPS_LARGEST_REAL,PetscObjectComm((PetscObject)eps),PETSC_ERR_SUP,"This solver supports only smallest real or largest real eigenvalues");
     67:   EPSCheckUnsupported(eps,EPS_FEATURE_ARBITRARY | EPS_FEATURE_REGION | EPS_FEATURE_EXTRACTION);
     68:   EPSCheckIgnored(eps,EPS_FEATURE_BALANCE);

     70:   if (!ctx->restart) ctx->restart = 0.9;

     72:   /* number of guard vectors */
     73:   if (ctx->bs==1) ctx->guard = 0;
     74:   else ctx->guard = PetscMin((PetscInt)((1.0-ctx->restart)*ctx->bs+0.45),ctx->bs-1);

     76:   PetscCall(EPSAllocateSolution(eps,0));
     77:   PetscCall(EPS_SetInnerProduct(eps));
     78:   PetscCall(DSSetType(eps->ds,DSGHEP));
     79:   PetscCall(DSAllocate(eps->ds,eps->mpd));
     80:   PetscCall(EPSSetWorkVecs(eps,1));
     81:   PetscFunctionReturn(PETSC_SUCCESS);
     82: }

     84: static PetscErrorCode EPSSolve_LOBPCG(EPS eps)
     85: {
     86:   EPS_LOBPCG     *ctx = (EPS_LOBPCG*)eps->data;
     87:   PetscInt       i,j,k,nv,ini,nmat,nc,nconv,locked,its,prev=0;
     88:   PetscReal      norm;
     89:   PetscScalar    *eigr,dot;
     90:   PetscBool      breakdown,countc,flip=PETSC_FALSE,checkprecond=PETSC_FALSE;
     91:   Mat            A,B,M,V=NULL,W=NULL;
     92:   Vec            v,z,w=eps->work[0];
     93:   BV             X,Y=NULL,Z,R,P,AX,BX;
     94:   SlepcSC        sc;

     96:   PetscFunctionBegin;
     97:   PetscCall(STGetNumMatrices(eps->st,&nmat));
     98:   PetscCall(STGetMatrix(eps->st,0,&A));
     99:   if (nmat>1) PetscCall(STGetMatrix(eps->st,1,&B));
    100:   else B = NULL;

    102:   if (eps->which==EPS_LARGEST_REAL) {  /* flip spectrum */
    103:     flip = PETSC_TRUE;
    104:     PetscCall(DSGetSlepcSC(eps->ds,&sc));
    105:     sc->comparison = SlepcCompareSmallestReal;
    106:   }

    108:   /* undocumented option to check for a positive-definite preconditioner (turn-off by default) */
    109:   PetscCall(PetscOptionsGetBool(NULL,NULL,"-eps_lobpcg_checkprecond",&checkprecond,NULL));

    111:   /* 1. Allocate memory */
    112:   PetscCall(PetscCalloc1(3*ctx->bs,&eigr));
    113:   PetscCall(BVDuplicateResize(eps->V,3*ctx->bs,&Z));
    114:   PetscCall(BVDuplicateResize(eps->V,ctx->bs,&X));
    115:   PetscCall(BVDuplicateResize(eps->V,ctx->bs,&R));
    116:   PetscCall(BVDuplicateResize(eps->V,ctx->bs,&P));
    117:   PetscCall(BVDuplicateResize(eps->V,ctx->bs,&AX));
    118:   if (B) PetscCall(BVDuplicateResize(eps->V,ctx->bs,&BX));
    119:   nc = eps->nds;
    120:   if (nc>0 || eps->nev>ctx->bs-ctx->guard) PetscCall(BVDuplicateResize(eps->V,nc+eps->nev,&Y));
    121:   if (nc>0) {
    122:     for (j=0;j<nc;j++) {
    123:       PetscCall(BVGetColumn(eps->V,-nc+j,&v));
    124:       PetscCall(BVInsertVec(Y,j,v));
    125:       PetscCall(BVRestoreColumn(eps->V,-nc+j,&v));
    126:     }
    127:     PetscCall(BVSetActiveColumns(Y,0,nc));
    128:   }

    130:   /* 2. Apply the constraints to the initial vectors */
    131:   /* 3. B-orthogonalize initial vectors */
    132:   for (k=eps->nini;k<eps->ncv-ctx->bs;k++) { /* Generate more initial vectors if necessary */
    133:     PetscCall(BVSetRandomColumn(eps->V,k));
    134:     PetscCall(BVOrthonormalizeColumn(eps->V,k,PETSC_TRUE,NULL,NULL));
    135:   }
    136:   nv = ctx->bs;
    137:   PetscCall(BVSetActiveColumns(eps->V,0,nv));
    138:   PetscCall(BVSetActiveColumns(Z,0,nv));
    139:   PetscCall(BVCopy(eps->V,Z));
    140:   PetscCall(BVCopy(Z,X));

    142:   /* 4. Compute initial Ritz vectors */
    143:   PetscCall(BVMatMult(X,A,AX));
    144:   PetscCall(DSSetDimensions(eps->ds,nv,0,0));
    145:   PetscCall(DSGetMat(eps->ds,DS_MAT_A,&M));
    146:   PetscCall(BVMatProject(AX,NULL,X,M));
    147:   if (flip) PetscCall(MatScale(M,-1.0));
    148:   PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&M));
    149:   PetscCall(DSSetIdentity(eps->ds,DS_MAT_B));
    150:   PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    151:   PetscCall(DSSolve(eps->ds,eigr,NULL));
    152:   PetscCall(DSSort(eps->ds,eigr,NULL,NULL,NULL,NULL));
    153:   PetscCall(DSSynchronize(eps->ds,eigr,NULL));
    154:   for (j=0;j<nv;j++) eps->eigr[j] = flip? -eigr[j]: eigr[j];
    155:   PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    156:   PetscCall(DSGetMat(eps->ds,DS_MAT_X,&M));
    157:   PetscCall(BVMultInPlace(X,M,0,nv));
    158:   PetscCall(BVMultInPlace(AX,M,0,nv));
    159:   PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&M));

    161:   /* 5. Initialize range of active iterates */
    162:   locked = 0;  /* hard-locked vectors, the leading locked columns of V are eigenvectors */
    163:   nconv  = 0;  /* number of converged eigenvalues in the current block */
    164:   its    = 0;  /* iterations for the current block */

    166:   /* 6. Main loop */
    167:   while (eps->reason == EPS_CONVERGED_ITERATING) {

    169:     if (ctx->lock) {
    170:       PetscCall(BVSetActiveColumns(R,nconv,ctx->bs));
    171:       PetscCall(BVSetActiveColumns(AX,nconv,ctx->bs));
    172:       if (B) PetscCall(BVSetActiveColumns(BX,nconv,ctx->bs));
    173:     }

    175:     /* 7. Compute residuals */
    176:     ini = (ctx->lock)? nconv: 0;
    177:     PetscCall(BVCopy(AX,R));
    178:     if (B) PetscCall(BVMatMult(X,B,BX));
    179:     for (j=ini;j<ctx->bs;j++) {
    180:       PetscCall(BVGetColumn(R,j,&v));
    181:       PetscCall(BVGetColumn(B?BX:X,j,&z));
    182:       PetscCall(VecAXPY(v,-eps->eigr[locked+j],z));
    183:       PetscCall(BVRestoreColumn(R,j,&v));
    184:       PetscCall(BVRestoreColumn(B?BX:X,j,&z));
    185:     }

    187:     /* 8. Compute residual norms and update index set of active iterates */
    188:     k = ini;
    189:     countc = PETSC_TRUE;
    190:     for (j=ini;j<ctx->bs;j++) {
    191:       i = locked+j;
    192:       PetscCall(BVGetColumn(R,j,&v));
    193:       PetscCall(VecNorm(v,NORM_2,&norm));
    194:       PetscCall(BVRestoreColumn(R,j,&v));
    195:       PetscCall((*eps->converged)(eps,eps->eigr[i],eps->eigi[i],norm,&eps->errest[i],eps->convergedctx));
    196:       if (countc) {
    197:         if (eps->errest[i] < eps->tol) k++;
    198:         else countc = PETSC_FALSE;
    199:       }
    200:       if (!countc && !eps->trackall) break;
    201:     }
    202:     nconv = k;
    203:     eps->nconv = locked + nconv;
    204:     if (its) PetscCall(EPSMonitor(eps,eps->its+its,eps->nconv,eps->eigr,eps->eigi,eps->errest,locked+ctx->bs));
    205:     PetscCall((*eps->stopping)(eps,eps->its+its,eps->max_it,eps->nconv,eps->nev,&eps->reason,eps->stoppingctx));
    206:     if (eps->reason != EPS_CONVERGED_ITERATING || nconv >= ctx->bs-ctx->guard) {
    207:       PetscCall(BVSetActiveColumns(eps->V,locked,eps->nconv));
    208:       PetscCall(BVSetActiveColumns(X,0,nconv));
    209:       PetscCall(BVCopy(X,eps->V));
    210:     }
    211:     if (eps->reason != EPS_CONVERGED_ITERATING) {
    212:       break;
    213:     } else if (nconv >= ctx->bs-ctx->guard) {
    214:       eps->its += its-1;
    215:       its = 0;
    216:     } else its++;

    218:     if (nconv >= ctx->bs-ctx->guard) {  /* force hard locking of vectors and compute new R */

    220:       /* extend constraints */
    221:       PetscCall(BVSetActiveColumns(Y,nc+locked,nc+locked+nconv));
    222:       PetscCall(BVCopy(X,Y));
    223:       PetscCall(BVSetActiveColumns(Y,0,nc+locked+nconv));

    225:       /* shift work BV's */
    226:       for (j=nconv;j<ctx->bs;j++) {
    227:         PetscCall(BVCopyColumn(X,j,j-nconv));
    228:         PetscCall(BVCopyColumn(R,j,j-nconv));
    229:         PetscCall(BVCopyColumn(P,j,j-nconv));
    230:         PetscCall(BVCopyColumn(AX,j,j-nconv));
    231:         if (B) PetscCall(BVCopyColumn(BX,j,j-nconv));
    232:       }

    234:       /* set new initial vectors */
    235:       PetscCall(BVSetActiveColumns(eps->V,locked+ctx->bs,locked+ctx->bs+nconv));
    236:       PetscCall(BVSetActiveColumns(X,ctx->bs-nconv,ctx->bs));
    237:       PetscCall(BVCopy(eps->V,X));
    238:       for (j=ctx->bs-nconv;j<ctx->bs;j++) {
    239:         PetscCall(BVGetColumn(X,j,&v));
    240:         PetscCall(BVOrthogonalizeVec(Y,v,NULL,&norm,&breakdown));
    241:         if (norm>0.0 && !breakdown) PetscCall(VecScale(v,1.0/norm));
    242:         else {
    243:           PetscCall(PetscInfo(eps,"Orthogonalization of initial vector failed\n"));
    244:           eps->reason = EPS_DIVERGED_BREAKDOWN;
    245:           goto diverged;
    246:         }
    247:         PetscCall(BVRestoreColumn(X,j,&v));
    248:       }
    249:       locked += nconv;
    250:       nconv = 0;
    251:       PetscCall(BVSetActiveColumns(X,nconv,ctx->bs));

    253:       /* B-orthogonalize initial vectors */
    254:       PetscCall(BVOrthogonalize(X,NULL));
    255:       PetscCall(BVSetActiveColumns(Z,nconv,ctx->bs));
    256:       PetscCall(BVSetActiveColumns(AX,nconv,ctx->bs));
    257:       PetscCall(BVCopy(X,Z));

    259:       /* compute initial Ritz vectors */
    260:       nv = ctx->bs;
    261:       PetscCall(BVMatMult(X,A,AX));
    262:       PetscCall(DSSetDimensions(eps->ds,nv,0,0));
    263:       PetscCall(DSGetMat(eps->ds,DS_MAT_A,&M));
    264:       PetscCall(BVMatProject(AX,NULL,X,M));
    265:       if (flip) PetscCall(MatScale(M,-1.0));
    266:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&M));
    267:       PetscCall(DSSetIdentity(eps->ds,DS_MAT_B));
    268:       PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    269:       PetscCall(DSSolve(eps->ds,eigr,NULL));
    270:       PetscCall(DSSort(eps->ds,eigr,NULL,NULL,NULL,NULL));
    271:       PetscCall(DSSynchronize(eps->ds,eigr,NULL));
    272:       for (j=0;j<nv;j++) if (locked+j<eps->ncv) eps->eigr[locked+j] = flip? -eigr[j]: eigr[j];
    273:       PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));
    274:       PetscCall(DSGetMat(eps->ds,DS_MAT_X,&M));
    275:       PetscCall(BVMultInPlace(X,M,0,nv));
    276:       PetscCall(BVMultInPlace(AX,M,0,nv));
    277:       PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&M));

    279:       continue;   /* skip the rest of the iteration */
    280:     }

    282:     ini = (ctx->lock)? nconv: 0;
    283:     if (ctx->lock) {
    284:       PetscCall(BVSetActiveColumns(R,nconv,ctx->bs));
    285:       PetscCall(BVSetActiveColumns(P,nconv,ctx->bs));
    286:       PetscCall(BVSetActiveColumns(AX,nconv,ctx->bs));
    287:       if (B) PetscCall(BVSetActiveColumns(BX,nconv,ctx->bs));
    288:     }

    290:     /* 9. Apply preconditioner to the residuals */
    291:     PetscCall(BVGetMat(R,&V));
    292:     if (prev != ctx->bs-ini) {
    293:       prev = ctx->bs-ini;
    294:       PetscCall(MatDestroy(&W));
    295:       PetscCall(MatDuplicate(V,MAT_SHARE_NONZERO_PATTERN,&W));
    296:     }
    297:     PetscCall(STApplyMat(eps->st,V,W));
    298:     if (checkprecond) {
    299:       for (j=ini;j<ctx->bs;j++) {
    300:         PetscCall(MatDenseGetColumnVecRead(V,j-ini,&v));
    301:         PetscCall(MatDenseGetColumnVecRead(W,j-ini,&w));
    302:         PetscCall(VecDot(v,w,&dot));
    303:         PetscCall(MatDenseRestoreColumnVecRead(W,j-ini,&w));
    304:         PetscCall(MatDenseRestoreColumnVecRead(V,j-ini,&v));
    305:         if (PetscRealPart(dot)<0.0) {
    306:           PetscCall(PetscInfo(eps,"The preconditioner is not positive-definite\n"));
    307:           eps->reason = EPS_DIVERGED_BREAKDOWN;
    308:           goto diverged;
    309:         }
    310:       }
    311:     }
    312:     if (nc+locked>0) {
    313:       for (j=ini;j<ctx->bs;j++) {
    314:         PetscCall(MatDenseGetColumnVecWrite(W,j-ini,&w));
    315:         PetscCall(BVOrthogonalizeVec(Y,w,NULL,&norm,&breakdown));
    316:         if (norm>0.0 && !breakdown) PetscCall(VecScale(w,1.0/norm));
    317:         PetscCall(MatDenseRestoreColumnVecWrite(W,j-ini,&w));
    318:         if (norm<=0.0 || breakdown) {
    319:           PetscCall(PetscInfo(eps,"Orthogonalization of preconditioned residual failed\n"));
    320:           eps->reason = EPS_DIVERGED_BREAKDOWN;
    321:           goto diverged;
    322:         }
    323:       }
    324:     }
    325:     PetscCall(MatCopy(W,V,SAME_NONZERO_PATTERN));
    326:     PetscCall(BVRestoreMat(R,&V));

    328:     /* 11. B-orthonormalize preconditioned residuals */
    329:     PetscCall(BVOrthogonalize(R,NULL));

    331:     /* 13-16. B-orthonormalize conjugate directions */
    332:     if (its>1) PetscCall(BVOrthogonalize(P,NULL));

    334:     /* 17-23. Compute symmetric Gram matrices */
    335:     PetscCall(BVSetActiveColumns(Z,0,ctx->bs));
    336:     PetscCall(BVSetActiveColumns(X,0,ctx->bs));
    337:     PetscCall(BVCopy(X,Z));
    338:     PetscCall(BVSetActiveColumns(Z,ctx->bs,2*ctx->bs-ini));
    339:     PetscCall(BVCopy(R,Z));
    340:     if (its>1) {
    341:       PetscCall(BVSetActiveColumns(Z,2*ctx->bs-ini,3*ctx->bs-2*ini));
    342:       PetscCall(BVCopy(P,Z));
    343:     }

    345:     if (its>1) nv = 3*ctx->bs-2*ini;
    346:     else nv = 2*ctx->bs-ini;

    348:     PetscCall(BVSetActiveColumns(Z,0,nv));
    349:     PetscCall(DSSetDimensions(eps->ds,nv,0,0));
    350:     PetscCall(DSGetMat(eps->ds,DS_MAT_A,&M));
    351:     PetscCall(BVMatProject(Z,A,Z,M));
    352:     if (flip) PetscCall(MatScale(M,-1.0));
    353:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_A,&M));
    354:     PetscCall(DSGetMat(eps->ds,DS_MAT_B,&M));
    355:     PetscCall(BVMatProject(Z,B,Z,M)); /* covers also the case B=NULL */
    356:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_B,&M));

    358:     /* 24. Solve the generalized eigenvalue problem */
    359:     PetscCall(DSSetState(eps->ds,DS_STATE_RAW));
    360:     PetscCall(DSSolve(eps->ds,eigr,NULL));
    361:     PetscCall(DSSort(eps->ds,eigr,NULL,NULL,NULL,NULL));
    362:     PetscCall(DSSynchronize(eps->ds,eigr,NULL));
    363:     for (j=0;j<nv;j++) if (locked+j<eps->ncv) eps->eigr[locked+j] = flip? -eigr[j]: eigr[j];
    364:     PetscCall(DSVectors(eps->ds,DS_MAT_X,NULL,NULL));

    366:     /* 25-33. Compute Ritz vectors */
    367:     PetscCall(DSGetMat(eps->ds,DS_MAT_X,&M));
    368:     PetscCall(BVSetActiveColumns(Z,ctx->bs,nv));
    369:     if (ctx->lock) PetscCall(BVSetActiveColumns(P,0,ctx->bs));
    370:     PetscCall(BVMult(P,1.0,0.0,Z,M));
    371:     PetscCall(BVCopy(P,X));
    372:     if (ctx->lock) PetscCall(BVSetActiveColumns(P,nconv,ctx->bs));
    373:     PetscCall(BVSetActiveColumns(Z,0,ctx->bs));
    374:     PetscCall(BVMult(X,1.0,1.0,Z,M));
    375:     if (ctx->lock) PetscCall(BVSetActiveColumns(X,nconv,ctx->bs));
    376:     PetscCall(BVMatMult(X,A,AX));
    377:     PetscCall(DSRestoreMat(eps->ds,DS_MAT_X,&M));
    378:   }

    380: diverged:
    381:   eps->its += its;

    383:   if (flip) sc->comparison = SlepcCompareLargestReal;
    384:   PetscCall(PetscFree(eigr));
    385:   PetscCall(MatDestroy(&W));
    386:   if (V) PetscCall(BVRestoreMat(R,&V)); /* only needed when goto diverged is reached */
    387:   PetscCall(BVDestroy(&Z));
    388:   PetscCall(BVDestroy(&X));
    389:   PetscCall(BVDestroy(&R));
    390:   PetscCall(BVDestroy(&P));
    391:   PetscCall(BVDestroy(&AX));
    392:   if (B) PetscCall(BVDestroy(&BX));
    393:   if (nc>0 || eps->nev>ctx->bs-ctx->guard) PetscCall(BVDestroy(&Y));
    394:   PetscFunctionReturn(PETSC_SUCCESS);
    395: }

    397: static PetscErrorCode EPSLOBPCGSetBlockSize_LOBPCG(EPS eps,PetscInt bs)
    398: {
    399:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    401:   PetscFunctionBegin;
    402:   if (bs == PETSC_DEFAULT || bs == PETSC_DECIDE) bs = 0;
    403:   else PetscCheck(bs>0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size %" PetscInt_FMT,bs);
    404:   if (ctx->bs != bs) {
    405:     ctx->bs = bs;
    406:     eps->state = EPS_STATE_INITIAL;
    407:   }
    408:   PetscFunctionReturn(PETSC_SUCCESS);
    409: }

    411: /*@
    412:    EPSLOBPCGSetBlockSize - Sets the block size of the LOBPCG method.

    414:    Logically Collective

    416:    Input Parameters:
    417: +  eps - the eigenproblem solver context
    418: -  bs  - the block size

    420:    Options Database Key:
    421: .  -eps_lobpcg_blocksize - Sets the block size

    423:    Level: advanced

    425: .seealso: EPSLOBPCGGetBlockSize()
    426: @*/
    427: PetscErrorCode EPSLOBPCGSetBlockSize(EPS eps,PetscInt bs)
    428: {
    429:   PetscFunctionBegin;
    432:   PetscTryMethod(eps,"EPSLOBPCGSetBlockSize_C",(EPS,PetscInt),(eps,bs));
    433:   PetscFunctionReturn(PETSC_SUCCESS);
    434: }

    436: static PetscErrorCode EPSLOBPCGGetBlockSize_LOBPCG(EPS eps,PetscInt *bs)
    437: {
    438:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    440:   PetscFunctionBegin;
    441:   *bs = ctx->bs;
    442:   PetscFunctionReturn(PETSC_SUCCESS);
    443: }

    445: /*@
    446:    EPSLOBPCGGetBlockSize - Gets the block size used in the LOBPCG method.

    448:    Not Collective

    450:    Input Parameter:
    451: .  eps - the eigenproblem solver context

    453:    Output Parameter:
    454: .  bs - the block size

    456:    Level: advanced

    458: .seealso: EPSLOBPCGSetBlockSize()
    459: @*/
    460: PetscErrorCode EPSLOBPCGGetBlockSize(EPS eps,PetscInt *bs)
    461: {
    462:   PetscFunctionBegin;
    464:   PetscAssertPointer(bs,2);
    465:   PetscUseMethod(eps,"EPSLOBPCGGetBlockSize_C",(EPS,PetscInt*),(eps,bs));
    466:   PetscFunctionReturn(PETSC_SUCCESS);
    467: }

    469: static PetscErrorCode EPSLOBPCGSetRestart_LOBPCG(EPS eps,PetscReal restart)
    470: {
    471:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    473:   PetscFunctionBegin;
    474:   if (restart==(PetscReal)PETSC_DEFAULT) restart = 0.9;
    475:   PetscCheck(restart>=0.1 && restart<=1.0,PetscObjectComm((PetscObject)eps),PETSC_ERR_ARG_OUTOFRANGE,"The restart argument %g must be in the range [0.1,1.0]",(double)restart);
    476:   if (restart != ctx->restart) {
    477:     ctx->restart = restart;
    478:     eps->state = EPS_STATE_INITIAL;
    479:   }
    480:   PetscFunctionReturn(PETSC_SUCCESS);
    481: }

    483: /*@
    484:    EPSLOBPCGSetRestart - Sets the restart parameter for the LOBPCG method.

    486:    Logically Collective

    488:    Input Parameters:
    489: +  eps - the eigenproblem solver context
    490: -  restart - the percentage of the block of vectors to force a restart

    492:    Options Database Key:
    493: .  -eps_lobpcg_restart - Sets the restart parameter

    495:    Notes:
    496:    The meaning of this parameter is the proportion of vectors within the
    497:    current block iterate that must have converged in order to force a
    498:    restart with hard locking.
    499:    Allowed values are in the range [0.1,1.0]. The default is 0.9.

    501:    Level: advanced

    503: .seealso: EPSLOBPCGGetRestart()
    504: @*/
    505: PetscErrorCode EPSLOBPCGSetRestart(EPS eps,PetscReal restart)
    506: {
    507:   PetscFunctionBegin;
    510:   PetscTryMethod(eps,"EPSLOBPCGSetRestart_C",(EPS,PetscReal),(eps,restart));
    511:   PetscFunctionReturn(PETSC_SUCCESS);
    512: }

    514: static PetscErrorCode EPSLOBPCGGetRestart_LOBPCG(EPS eps,PetscReal *restart)
    515: {
    516:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    518:   PetscFunctionBegin;
    519:   *restart = ctx->restart;
    520:   PetscFunctionReturn(PETSC_SUCCESS);
    521: }

    523: /*@
    524:    EPSLOBPCGGetRestart - Gets the restart parameter used in the LOBPCG method.

    526:    Not Collective

    528:    Input Parameter:
    529: .  eps - the eigenproblem solver context

    531:    Output Parameter:
    532: .  restart - the restart parameter

    534:    Level: advanced

    536: .seealso: EPSLOBPCGSetRestart()
    537: @*/
    538: PetscErrorCode EPSLOBPCGGetRestart(EPS eps,PetscReal *restart)
    539: {
    540:   PetscFunctionBegin;
    542:   PetscAssertPointer(restart,2);
    543:   PetscUseMethod(eps,"EPSLOBPCGGetRestart_C",(EPS,PetscReal*),(eps,restart));
    544:   PetscFunctionReturn(PETSC_SUCCESS);
    545: }

    547: static PetscErrorCode EPSLOBPCGSetLocking_LOBPCG(EPS eps,PetscBool lock)
    548: {
    549:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    551:   PetscFunctionBegin;
    552:   ctx->lock = lock;
    553:   PetscFunctionReturn(PETSC_SUCCESS);
    554: }

    556: /*@
    557:    EPSLOBPCGSetLocking - Choose between locking and non-locking variants of
    558:    the LOBPCG method.

    560:    Logically Collective

    562:    Input Parameters:
    563: +  eps  - the eigenproblem solver context
    564: -  lock - true if the locking variant must be selected

    566:    Options Database Key:
    567: .  -eps_lobpcg_locking - Sets the locking flag

    569:    Notes:
    570:    This flag refers to soft locking (converged vectors within the current
    571:    block iterate), since hard locking is always used (when nev is larger
    572:    than the block size).

    574:    Level: advanced

    576: .seealso: EPSLOBPCGGetLocking()
    577: @*/
    578: PetscErrorCode EPSLOBPCGSetLocking(EPS eps,PetscBool lock)
    579: {
    580:   PetscFunctionBegin;
    583:   PetscTryMethod(eps,"EPSLOBPCGSetLocking_C",(EPS,PetscBool),(eps,lock));
    584:   PetscFunctionReturn(PETSC_SUCCESS);
    585: }

    587: static PetscErrorCode EPSLOBPCGGetLocking_LOBPCG(EPS eps,PetscBool *lock)
    588: {
    589:   EPS_LOBPCG *ctx = (EPS_LOBPCG*)eps->data;

    591:   PetscFunctionBegin;
    592:   *lock = ctx->lock;
    593:   PetscFunctionReturn(PETSC_SUCCESS);
    594: }

    596: /*@
    597:    EPSLOBPCGGetLocking - Gets the locking flag used in the LOBPCG method.

    599:    Not Collective

    601:    Input Parameter:
    602: .  eps - the eigenproblem solver context

    604:    Output Parameter:
    605: .  lock - the locking flag

    607:    Level: advanced

    609: .seealso: EPSLOBPCGSetLocking()
    610: @*/
    611: PetscErrorCode EPSLOBPCGGetLocking(EPS eps,PetscBool *lock)
    612: {
    613:   PetscFunctionBegin;
    615:   PetscAssertPointer(lock,2);
    616:   PetscUseMethod(eps,"EPSLOBPCGGetLocking_C",(EPS,PetscBool*),(eps,lock));
    617:   PetscFunctionReturn(PETSC_SUCCESS);
    618: }

    620: static PetscErrorCode EPSView_LOBPCG(EPS eps,PetscViewer viewer)
    621: {
    622:   EPS_LOBPCG     *ctx = (EPS_LOBPCG*)eps->data;
    623:   PetscBool      isascii;

    625:   PetscFunctionBegin;
    626:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii));
    627:   if (isascii) {
    628:     PetscCall(PetscViewerASCIIPrintf(viewer,"  block size %" PetscInt_FMT "\n",ctx->bs));
    629:     PetscCall(PetscViewerASCIIPrintf(viewer,"  restart parameter=%g (using %" PetscInt_FMT " guard vectors)\n",(double)ctx->restart,ctx->guard));
    630:     PetscCall(PetscViewerASCIIPrintf(viewer,"  soft locking %sactivated\n",ctx->lock?"":"de"));
    631:   }
    632:   PetscFunctionReturn(PETSC_SUCCESS);
    633: }

    635: static PetscErrorCode EPSSetFromOptions_LOBPCG(EPS eps,PetscOptionItems *PetscOptionsObject)
    636: {
    637:   PetscBool      lock,flg;
    638:   PetscInt       bs;
    639:   PetscReal      restart;

    641:   PetscFunctionBegin;
    642:   PetscOptionsHeadBegin(PetscOptionsObject,"EPS LOBPCG Options");

    644:     PetscCall(PetscOptionsInt("-eps_lobpcg_blocksize","Block size","EPSLOBPCGSetBlockSize",20,&bs,&flg));
    645:     if (flg) PetscCall(EPSLOBPCGSetBlockSize(eps,bs));

    647:     PetscCall(PetscOptionsReal("-eps_lobpcg_restart","Percentage of the block of vectors to force a restart","EPSLOBPCGSetRestart",0.5,&restart,&flg));
    648:     if (flg) PetscCall(EPSLOBPCGSetRestart(eps,restart));

    650:     PetscCall(PetscOptionsBool("-eps_lobpcg_locking","Choose between locking and non-locking variants","EPSLOBPCGSetLocking",PETSC_TRUE,&lock,&flg));
    651:     if (flg) PetscCall(EPSLOBPCGSetLocking(eps,lock));

    653:   PetscOptionsHeadEnd();
    654:   PetscFunctionReturn(PETSC_SUCCESS);
    655: }

    657: static PetscErrorCode EPSDestroy_LOBPCG(EPS eps)
    658: {
    659:   PetscFunctionBegin;
    660:   PetscCall(PetscFree(eps->data));
    661:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetBlockSize_C",NULL));
    662:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetBlockSize_C",NULL));
    663:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetRestart_C",NULL));
    664:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetRestart_C",NULL));
    665:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetLocking_C",NULL));
    666:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetLocking_C",NULL));
    667:   PetscFunctionReturn(PETSC_SUCCESS);
    668: }

    670: SLEPC_EXTERN PetscErrorCode EPSCreate_LOBPCG(EPS eps)
    671: {
    672:   EPS_LOBPCG     *lobpcg;

    674:   PetscFunctionBegin;
    675:   PetscCall(PetscNew(&lobpcg));
    676:   eps->data = (void*)lobpcg;
    677:   lobpcg->lock = PETSC_TRUE;

    679:   eps->useds = PETSC_TRUE;
    680:   eps->categ = EPS_CATEGORY_PRECOND;

    682:   eps->ops->solve          = EPSSolve_LOBPCG;
    683:   eps->ops->setup          = EPSSetUp_LOBPCG;
    684:   eps->ops->setupsort      = EPSSetUpSort_Default;
    685:   eps->ops->setfromoptions = EPSSetFromOptions_LOBPCG;
    686:   eps->ops->destroy        = EPSDestroy_LOBPCG;
    687:   eps->ops->view           = EPSView_LOBPCG;
    688:   eps->ops->backtransform  = EPSBackTransform_Default;
    689:   eps->ops->setdefaultst   = EPSSetDefaultST_GMRES;

    691:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetBlockSize_C",EPSLOBPCGSetBlockSize_LOBPCG));
    692:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetBlockSize_C",EPSLOBPCGGetBlockSize_LOBPCG));
    693:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetRestart_C",EPSLOBPCGSetRestart_LOBPCG));
    694:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetRestart_C",EPSLOBPCGGetRestart_LOBPCG));
    695:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGSetLocking_C",EPSLOBPCGSetLocking_LOBPCG));
    696:   PetscCall(PetscObjectComposeFunction((PetscObject)eps,"EPSLOBPCGGetLocking_C",EPSLOBPCGGetLocking_LOBPCG));
    697:   PetscFunctionReturn(PETSC_SUCCESS);
    698: }