Actual source code: vecs.c

slepc-3.17.0 2022-03-31
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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:    BV implemented as an array of independent Vecs
 12: */

 14: #include <slepc/private/bvimpl.h>

 16: typedef struct {
 17:   Vec      *V;
 18:   PetscInt vmip;   /* Version of BVMultInPlace:
 19:        0: memory-efficient version, uses VecGetArray (default in CPU)
 20:        1: version that allocates (e-s) work vectors in every call (default in GPU) */
 21: } BV_VECS;

 23: PetscErrorCode BVMult_Vecs(BV Y,PetscScalar alpha,PetscScalar beta,BV X,Mat Q)
 24: {
 25:   BV_VECS           *y = (BV_VECS*)Y->data,*x = (BV_VECS*)X->data;
 26:   PetscScalar       *s=NULL;
 27:   const PetscScalar *q;
 28:   PetscInt          i,j,ldq;
 29:   PetscBool         trivial=(alpha==1.0)?PETSC_TRUE:PETSC_FALSE;

 31:   if (Q) {
 32:     MatDenseGetLDA(Q,&ldq);
 33:     if (!trivial) {
 34:       BVAllocateWork_Private(Y,X->k-X->l);
 35:       s = Y->work;
 36:     }
 37:     MatDenseGetArrayRead(Q,&q);
 38:     for (j=Y->l;j<Y->k;j++) {
 39:       VecScale(y->V[Y->nc+j],beta);
 40:       if (!trivial) {
 41:         for (i=X->l;i<X->k;i++) s[i-X->l] = alpha*q[i+j*ldq];
 42:       } else s = (PetscScalar*)(q+j*ldq+X->l);
 43:       VecMAXPY(y->V[Y->nc+j],X->k-X->l,s,x->V+X->nc+X->l);
 44:     }
 45:     MatDenseRestoreArrayRead(Q,&q);
 46:   } else {
 47:     for (j=0;j<Y->k-Y->l;j++) {
 48:       VecScale(y->V[Y->nc+Y->l+j],beta);
 49:       VecAXPY(y->V[Y->nc+Y->l+j],alpha,x->V[X->nc+X->l+j]);
 50:     }
 51:   }
 52:   PetscFunctionReturn(0);
 53: }

 55: PetscErrorCode BVMultVec_Vecs(BV X,PetscScalar alpha,PetscScalar beta,Vec y,PetscScalar *q)
 56: {
 57:   BV_VECS        *x = (BV_VECS*)X->data;
 58:   PetscScalar    *s=NULL,*qq=q;
 59:   PetscInt       i;
 60:   PetscBool      trivial=(alpha==1.0)?PETSC_TRUE:PETSC_FALSE;

 62:   if (!trivial) {
 63:     BVAllocateWork_Private(X,X->k-X->l);
 64:     s = X->work;
 65:   }
 66:   if (!q) VecGetArray(X->buffer,&qq);
 67:   VecScale(y,beta);
 68:   if (!trivial) {
 69:     for (i=0;i<X->k-X->l;i++) s[i] = alpha*qq[i];
 70:   } else s = qq;
 71:   VecMAXPY(y,X->k-X->l,s,x->V+X->nc+X->l);
 72:   if (!q) VecRestoreArray(X->buffer,&qq);
 73:   PetscFunctionReturn(0);
 74: }

 76: /*
 77:    BVMultInPlace_Vecs_ME - V(:,s:e-1) = V*Q(:,s:e-1) for regular vectors.

 79:    Memory-efficient version, uses VecGetArray (default in CPU)

 81:    Writing V = [ V1 V2 V3 ] and Q(:,s:e-1) = [ Q1 Q2 Q3 ]', where V2
 82:    corresponds to the columns s:e-1, the computation is done as
 83:                   V2 := V2*Q2 + V1*Q1 + V3*Q3
 84: */
 85: PetscErrorCode BVMultInPlace_Vecs_ME(BV V,Mat Q,PetscInt s,PetscInt e)
 86: {
 87:   BV_VECS           *ctx = (BV_VECS*)V->data;
 88:   const PetscScalar *q;
 89:   PetscInt          i,ldq;

 91:   MatDenseGetLDA(Q,&ldq);
 92:   MatDenseGetArrayRead(Q,&q);
 93:   /* V2 := V2*Q2 */
 94:   BVMultInPlace_Vecs_Private(V,V->n,e-s,ldq,ctx->V+V->nc+s,q+s*ldq+s,PETSC_FALSE);
 95:   /* V2 += V1*Q1 + V3*Q3 */
 96:   for (i=s;i<e;i++) {
 97:     if (PetscUnlikely(s>V->l)) VecMAXPY(ctx->V[V->nc+i],s-V->l,q+i*ldq+V->l,ctx->V+V->nc+V->l);
 98:     if (V->k>e) VecMAXPY(ctx->V[V->nc+i],V->k-e,q+i*ldq+e,ctx->V+V->nc+e);
 99:   }
100:   MatDenseRestoreArrayRead(Q,&q);
101:   PetscFunctionReturn(0);
102: }

104: /*
105:    BVMultInPlace_Vecs_Alloc - V(:,s:e-1) = V*Q(:,s:e-1) for regular vectors.

107:    Version that allocates (e-s) work vectors in every call (default in GPU)
108: */
109: PetscErrorCode BVMultInPlace_Vecs_Alloc(BV V,Mat Q,PetscInt s,PetscInt e)
110: {
111:   BV_VECS           *ctx = (BV_VECS*)V->data;
112:   const PetscScalar *q;
113:   PetscInt          i,ldq;
114:   Vec               *W;

116:   MatDenseGetLDA(Q,&ldq);
117:   MatDenseGetArrayRead(Q,&q);
118:   VecDuplicateVecs(V->t,e-s,&W);
119:   for (i=s;i<e;i++) VecMAXPY(W[i-s],V->k-V->l,q+i*ldq+V->l,ctx->V+V->nc+V->l);
120:   for (i=s;i<e;i++) VecCopy(W[i-s],ctx->V[V->nc+i]);
121:   VecDestroyVecs(e-s,&W);
122:   MatDenseRestoreArrayRead(Q,&q);
123:   PetscFunctionReturn(0);
124: }

126: /*
127:    BVMultInPlaceHermitianTranspose_Vecs - V(:,s:e-1) = V*Q'(:,s:e-1) for regular vectors.
128: */
129: PetscErrorCode BVMultInPlaceHermitianTranspose_Vecs(BV V,Mat Q,PetscInt s,PetscInt e)
130: {
131:   BV_VECS           *ctx = (BV_VECS*)V->data;
132:   const PetscScalar *q;
133:   PetscInt          i,j,ldq,n;

135:   MatGetSize(Q,NULL,&n);
136:   MatDenseGetLDA(Q,&ldq);
137:   MatDenseGetArrayRead(Q,&q);
138:   /* V2 := V2*Q2' */
139:   BVMultInPlace_Vecs_Private(V,V->n,e-s,ldq,ctx->V+V->nc+s,q+s*ldq+s,PETSC_TRUE);
140:   /* V2 += V1*Q1' + V3*Q3' */
141:   for (i=s;i<e;i++) {
142:     for (j=V->l;j<s;j++) VecAXPY(ctx->V[V->nc+i],q[i+j*ldq],ctx->V[V->nc+j]);
143:     for (j=e;j<n;j++) VecAXPY(ctx->V[V->nc+i],q[i+j*ldq],ctx->V[V->nc+j]);
144:   }
145:   MatDenseRestoreArrayRead(Q,&q);
146:   PetscFunctionReturn(0);
147: }

149: PetscErrorCode BVDot_Vecs(BV X,BV Y,Mat M)
150: {
151:   BV_VECS        *x = (BV_VECS*)X->data,*y = (BV_VECS*)Y->data;
152:   PetscScalar    *m;
153:   PetscInt       j,ldm;

155:   MatDenseGetLDA(M,&ldm);
156:   MatDenseGetArray(M,&m);
157:   for (j=X->l;j<X->k;j++) VecMDot(x->V[X->nc+j],Y->k-Y->l,y->V+Y->nc+Y->l,m+j*ldm+Y->l);
158:   MatDenseRestoreArray(M,&m);
159:   PetscFunctionReturn(0);
160: }

162: PetscErrorCode BVDotVec_Vecs(BV X,Vec y,PetscScalar *q)
163: {
164:   BV_VECS        *x = (BV_VECS*)X->data;
165:   Vec            z = y;
166:   PetscScalar    *qq=q;

168:   if (PetscUnlikely(X->matrix)) {
169:     BV_IPMatMult(X,y);
170:     z = X->Bx;
171:   }
172:   if (!q) VecGetArray(X->buffer,&qq);
173:   VecMDot(z,X->k-X->l,x->V+X->nc+X->l,qq);
174:   if (!q) VecRestoreArray(X->buffer,&qq);
175:   PetscFunctionReturn(0);
176: }

178: PetscErrorCode BVDotVec_Begin_Vecs(BV X,Vec y,PetscScalar *m)
179: {
180:   BV_VECS        *x = (BV_VECS*)X->data;
181:   Vec            z = y;

183:   if (PetscUnlikely(X->matrix)) {
184:     BV_IPMatMult(X,y);
185:     z = X->Bx;
186:   }
187:   VecMDotBegin(z,X->k-X->l,x->V+X->nc+X->l,m);
188:   PetscFunctionReturn(0);
189: }

191: PetscErrorCode BVDotVec_End_Vecs(BV X,Vec y,PetscScalar *m)
192: {
193:   BV_VECS        *x = (BV_VECS*)X->data;

195:   VecMDotEnd(y,X->k-X->l,x->V+X->nc+X->l,m);
196:   PetscFunctionReturn(0);
197: }

199: PetscErrorCode BVScale_Vecs(BV bv,PetscInt j,PetscScalar alpha)
200: {
201:   PetscInt       i;
202:   BV_VECS        *ctx = (BV_VECS*)bv->data;

204:   if (PetscUnlikely(j<0)) {
205:     for (i=bv->l;i<bv->k;i++) VecScale(ctx->V[bv->nc+i],alpha);
206:   } else VecScale(ctx->V[bv->nc+j],alpha);
207:   PetscFunctionReturn(0);
208: }

210: PetscErrorCode BVNorm_Vecs(BV bv,PetscInt j,NormType type,PetscReal *val)
211: {
212:   PetscInt       i;
213:   PetscReal      nrm;
214:   BV_VECS        *ctx = (BV_VECS*)bv->data;

216:   if (PetscUnlikely(j<0)) {
218:     *val = 0.0;
219:     for (i=bv->l;i<bv->k;i++) {
220:       VecNorm(ctx->V[bv->nc+i],NORM_2,&nrm);
221:       *val += nrm*nrm;
222:     }
223:     *val = PetscSqrtReal(*val);
224:   } else VecNorm(ctx->V[bv->nc+j],type,val);
225:   PetscFunctionReturn(0);
226: }

228: PetscErrorCode BVNorm_Begin_Vecs(BV bv,PetscInt j,NormType type,PetscReal *val)
229: {
230:   BV_VECS        *ctx = (BV_VECS*)bv->data;

233:   VecNormBegin(ctx->V[bv->nc+j],type,val);
234:   PetscFunctionReturn(0);
235: }

237: PetscErrorCode BVNorm_End_Vecs(BV bv,PetscInt j,NormType type,PetscReal *val)
238: {
239:   BV_VECS        *ctx = (BV_VECS*)bv->data;

242:   VecNormEnd(ctx->V[bv->nc+j],type,val);
243:   PetscFunctionReturn(0);
244: }

246: PetscErrorCode BVMatMult_Vecs(BV V,Mat A,BV W)
247: {
248:   BV_VECS        *v = (BV_VECS*)V->data,*w = (BV_VECS*)W->data;
249:   PetscInt       j;
250:   Mat            Vmat,Wmat;

252:   if (V->vmm) {
253:     BVGetMat(V,&Vmat);
254:     BVGetMat(W,&Wmat);
255:     MatProductCreateWithMat(A,Vmat,NULL,Wmat);
256:     MatProductSetType(Wmat,MATPRODUCT_AB);
257:     MatProductSetFromOptions(Wmat);
258:     MatProductSymbolic(Wmat);
259:     MatProductNumeric(Wmat);
260:     MatProductClear(Wmat);
261:     BVRestoreMat(V,&Vmat);
262:     BVRestoreMat(W,&Wmat);
263:   } else {
264:     for (j=0;j<V->k-V->l;j++) MatMult(A,v->V[V->nc+V->l+j],w->V[W->nc+W->l+j]);
265:   }
266:   PetscFunctionReturn(0);
267: }

269: PetscErrorCode BVCopy_Vecs(BV V,BV W)
270: {
271:   BV_VECS        *v = (BV_VECS*)V->data,*w = (BV_VECS*)W->data;
272:   PetscInt       j;

274:   for (j=0;j<V->k-V->l;j++) VecCopy(v->V[V->nc+V->l+j],w->V[W->nc+W->l+j]);
275:   PetscFunctionReturn(0);
276: }

278: PetscErrorCode BVCopyColumn_Vecs(BV V,PetscInt j,PetscInt i)
279: {
280:   BV_VECS        *v = (BV_VECS*)V->data;

282:   VecCopy(v->V[V->nc+j],v->V[V->nc+i]);
283:   PetscFunctionReturn(0);
284: }

286: PetscErrorCode BVResize_Vecs(BV bv,PetscInt m,PetscBool copy)
287: {
288:   BV_VECS        *ctx = (BV_VECS*)bv->data;
289:   Vec            *newV;
290:   PetscInt       j;
291:   char           str[50];

293:   VecDuplicateVecs(bv->t,m,&newV);
294:   PetscLogObjectParents(bv,m,newV);
295:   if (((PetscObject)bv)->name) {
296:     for (j=0;j<m;j++) {
297:       PetscSNPrintf(str,sizeof(str),"%s_%" PetscInt_FMT,((PetscObject)bv)->name,j);
298:       PetscObjectSetName((PetscObject)newV[j],str);
299:     }
300:   }
301:   if (copy) {
302:     for (j=0;j<PetscMin(m,bv->m);j++) VecCopy(ctx->V[j],newV[j]);
303:   }
304:   VecDestroyVecs(bv->m,&ctx->V);
305:   ctx->V = newV;
306:   PetscFunctionReturn(0);
307: }

309: PetscErrorCode BVGetColumn_Vecs(BV bv,PetscInt j,Vec *v)
310: {
311:   BV_VECS  *ctx = (BV_VECS*)bv->data;
312:   PetscInt l;

314:   l = BVAvailableVec;
315:   bv->cv[l] = ctx->V[bv->nc+j];
316:   PetscFunctionReturn(0);
317: }

319: PetscErrorCode BVGetArray_Vecs(BV bv,PetscScalar **a)
320: {
321:   BV_VECS           *ctx = (BV_VECS*)bv->data;
322:   PetscInt          j;
323:   const PetscScalar *p;

325:   PetscMalloc1((bv->nc+bv->m)*bv->n,a);
326:   for (j=0;j<bv->nc+bv->m;j++) {
327:     VecGetArrayRead(ctx->V[j],&p);
328:     PetscArraycpy(*a+j*bv->n,p,bv->n);
329:     VecRestoreArrayRead(ctx->V[j],&p);
330:   }
331:   PetscFunctionReturn(0);
332: }

334: PetscErrorCode BVRestoreArray_Vecs(BV bv,PetscScalar **a)
335: {
336:   BV_VECS        *ctx = (BV_VECS*)bv->data;
337:   PetscInt       j;
338:   PetscScalar    *p;

340:   for (j=0;j<bv->nc+bv->m;j++) {
341:     VecGetArray(ctx->V[j],&p);
342:     PetscArraycpy(p,*a+j*bv->n,bv->n);
343:     VecRestoreArray(ctx->V[j],&p);
344:   }
345:   PetscFree(*a);
346:   PetscFunctionReturn(0);
347: }

349: PetscErrorCode BVGetArrayRead_Vecs(BV bv,const PetscScalar **a)
350: {
351:   BV_VECS           *ctx = (BV_VECS*)bv->data;
352:   PetscInt          j;
353:   const PetscScalar *p;

355:   PetscMalloc1((bv->nc+bv->m)*bv->n,(PetscScalar**)a);
356:   for (j=0;j<bv->nc+bv->m;j++) {
357:     VecGetArrayRead(ctx->V[j],&p);
358:     PetscArraycpy((PetscScalar*)*a+j*bv->n,p,bv->n);
359:     VecRestoreArrayRead(ctx->V[j],&p);
360:   }
361:   PetscFunctionReturn(0);
362: }

364: PetscErrorCode BVRestoreArrayRead_Vecs(BV bv,const PetscScalar **a)
365: {
366:   PetscFree(*a);
367:   PetscFunctionReturn(0);
368: }

370: /*
371:    Sets the value of vmip flag and resets ops->multinplace accordingly
372:  */
373: static inline PetscErrorCode BVVecsSetVmip(BV bv,PetscInt vmip)
374: {
375:   typedef PetscErrorCode (*fmultinplace)(BV,Mat,PetscInt,PetscInt);
376:   fmultinplace multinplace[2] = {BVMultInPlace_Vecs_ME, BVMultInPlace_Vecs_Alloc};
377:   BV_VECS      *ctx = (BV_VECS*)bv->data;

379:   ctx->vmip            = vmip;
380:   bv->ops->multinplace = multinplace[vmip];
381:   PetscFunctionReturn(0);
382: }

384: PetscErrorCode BVSetFromOptions_Vecs(PetscOptionItems *PetscOptionsObject,BV bv)
385: {
386:   BV_VECS        *ctx = (BV_VECS*)bv->data;

388:   PetscOptionsHead(PetscOptionsObject,"BV Vecs Options");

390:     PetscOptionsRangeInt("-bv_vecs_vmip","Version of BVMultInPlace operation","",ctx->vmip,&ctx->vmip,NULL,0,1);
391:     BVVecsSetVmip(bv,ctx->vmip);

393:   PetscOptionsTail();
394:   PetscFunctionReturn(0);
395: }

397: PetscErrorCode BVView_Vecs(BV bv,PetscViewer viewer)
398: {
399:   BV_VECS           *ctx = (BV_VECS*)bv->data;
400:   PetscInt          j;
401:   PetscViewerFormat format;
402:   PetscBool         isascii,ismatlab=PETSC_FALSE;
403:   const char        *bvname,*name;

405:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
406:   if (isascii) {
407:     PetscViewerGetFormat(viewer,&format);
408:     if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) PetscFunctionReturn(0);
409:     if (format == PETSC_VIEWER_ASCII_MATLAB) ismatlab = PETSC_TRUE;
410:   }
411:   if (ismatlab) {
412:     PetscObjectGetName((PetscObject)bv,&bvname);
413:     PetscViewerASCIIPrintf(viewer,"%s=[];\n",bvname);
414:   }
415:   for (j=bv->nc;j<bv->nc+bv->m;j++) {
416:     VecView(ctx->V[j],viewer);
417:     if (ismatlab) {
418:       PetscObjectGetName((PetscObject)ctx->V[j],&name);
419:       PetscViewerASCIIPrintf(viewer,"%s=[%s,%s];clear %s\n",bvname,bvname,name,name);
420:     }
421:   }
422:   PetscFunctionReturn(0);
423: }

425: PetscErrorCode BVDestroy_Vecs(BV bv)
426: {
427:   BV_VECS        *ctx = (BV_VECS*)bv->data;

429:   if (!bv->issplit) VecDestroyVecs(bv->nc+bv->m,&ctx->V);
430:   PetscFree(bv->data);
431:   PetscFunctionReturn(0);
432: }

434: PetscErrorCode BVDuplicate_Vecs(BV V,BV W)
435: {
436:   BV_VECS        *ctx = (BV_VECS*)V->data;

438:   BVVecsSetVmip(W,ctx->vmip);
439:   PetscFunctionReturn(0);
440: }

442: SLEPC_EXTERN PetscErrorCode BVCreate_Vecs(BV bv)
443: {
445:   BV_VECS        *ctx;
446:   PetscInt       j,lsplit;
447:   PetscBool      isgpu;
448:   char           str[50];
449:   BV             parent;
450:   Vec            *Vpar;

452:   PetscNewLog(bv,&ctx);
453:   bv->data = (void*)ctx;

455:   if (PetscUnlikely(bv->issplit)) {
456:     /* split BV: share the Vecs of the parent BV */
457:     parent = bv->splitparent;
458:     lsplit = parent->lsplit;
459:     Vpar   = ((BV_VECS*)parent->data)->V;
460:     ctx->V = (bv->issplit==1)? Vpar: Vpar+lsplit;
461:   } else {
462:     /* regular BV: create array of Vecs to store the BV columns */
463:     VecDuplicateVecs(bv->t,bv->m,&ctx->V);
464:     PetscLogObjectParents(bv,bv->m,ctx->V);
465:     if (((PetscObject)bv)->name) {
466:       for (j=0;j<bv->m;j++) {
467:         PetscSNPrintf(str,sizeof(str),"%s_%" PetscInt_FMT,((PetscObject)bv)->name,j);
468:         PetscObjectSetName((PetscObject)ctx->V[j],str);
469:       }
470:     }
471:   }

473:   if (PetscUnlikely(bv->Acreate)) {
474:     for (j=0;j<bv->m;j++) MatGetColumnVector(bv->Acreate,ctx->V[j],j);
475:     MatDestroy(&bv->Acreate);
476:   }

478:   /* Default version of BVMultInPlace */
479:   PetscObjectTypeCompareAny((PetscObject)bv->t,&isgpu,VECSEQCUDA,VECMPICUDA,"");
480:   ctx->vmip = isgpu? 1: 0;

482:   /* Default BVMatMult method */
483:   bv->vmm = BV_MATMULT_VECS;

485:   /* Deferred call to setfromoptions */
486:   if (bv->defersfo) {
487:     ierr = PetscObjectOptionsBegin((PetscObject)bv);
488:     BVSetFromOptions_Vecs(PetscOptionsObject,bv);
489:     ierr = PetscOptionsEnd();
490:   }
491:   BVVecsSetVmip(bv,ctx->vmip);

493:   bv->ops->mult             = BVMult_Vecs;
494:   bv->ops->multvec          = BVMultVec_Vecs;
495:   bv->ops->multinplacetrans = BVMultInPlaceHermitianTranspose_Vecs;
496:   bv->ops->dot              = BVDot_Vecs;
497:   bv->ops->dotvec           = BVDotVec_Vecs;
498:   bv->ops->dotvec_begin     = BVDotVec_Begin_Vecs;
499:   bv->ops->dotvec_end       = BVDotVec_End_Vecs;
500:   bv->ops->scale            = BVScale_Vecs;
501:   bv->ops->norm             = BVNorm_Vecs;
502:   bv->ops->norm_begin       = BVNorm_Begin_Vecs;
503:   bv->ops->norm_end         = BVNorm_End_Vecs;
504:   bv->ops->matmult          = BVMatMult_Vecs;
505:   bv->ops->copy             = BVCopy_Vecs;
506:   bv->ops->copycolumn       = BVCopyColumn_Vecs;
507:   bv->ops->resize           = BVResize_Vecs;
508:   bv->ops->getcolumn        = BVGetColumn_Vecs;
509:   bv->ops->getarray         = BVGetArray_Vecs;
510:   bv->ops->restorearray     = BVRestoreArray_Vecs;
511:   bv->ops->getarrayread     = BVGetArrayRead_Vecs;
512:   bv->ops->restorearrayread = BVRestoreArrayRead_Vecs;
513:   bv->ops->destroy          = BVDestroy_Vecs;
514:   bv->ops->duplicate        = BVDuplicate_Vecs;
515:   bv->ops->setfromoptions   = BVSetFromOptions_Vecs;
516:   bv->ops->view             = BVView_Vecs;
517:   PetscFunctionReturn(0);
518: }