Actual source code: matutil.c

slepc-main 2024-12-17
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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: */

 11: #include <slepc/private/slepcimpl.h>

 13: static PetscErrorCode MatCreateTile_Seq(PetscScalar a,Mat A,PetscScalar b,Mat B,PetscScalar c,Mat C,PetscScalar d,Mat D,Mat G)
 14: {
 15:   PetscInt          i,j,M1,M2,N1,N2,ncols,*scols;
 16:   PetscScalar       *svals,*buf;
 17:   const PetscInt    *cols;
 18:   const PetscScalar *vals;

 20:   PetscFunctionBegin;
 21:   PetscCall(MatGetSize(A,&M1,&N1));
 22:   PetscCall(MatGetSize(D,&M2,&N2));

 24:   PetscCall(PetscMalloc2(PetscMax(N1,N2),&buf,PetscMax(N1,N2),&scols));
 25:   /* Transfer A */
 26:   if (a!=0.0) {
 27:     for (i=0;i<M1;i++) {
 28:       PetscCall(MatGetRow(A,i,&ncols,&cols,&vals));
 29:       if (a!=1.0) {
 30:         svals=buf;
 31:         for (j=0;j<ncols;j++) svals[j] = vals[j]*a;
 32:       } else svals=(PetscScalar*)vals;
 33:       PetscCall(MatSetValues(G,1,&i,ncols,cols,svals,INSERT_VALUES));
 34:       PetscCall(MatRestoreRow(A,i,&ncols,&cols,&vals));
 35:     }
 36:   }
 37:   /* Transfer B */
 38:   if (b!=0.0) {
 39:     for (i=0;i<M1;i++) {
 40:       PetscCall(MatGetRow(B,i,&ncols,&cols,&vals));
 41:       if (b!=1.0) {
 42:         svals=buf;
 43:         for (j=0;j<ncols;j++) svals[j] = vals[j]*b;
 44:       } else svals=(PetscScalar*)vals;
 45:       for (j=0;j<ncols;j++) scols[j] = cols[j]+N1;
 46:       PetscCall(MatSetValues(G,1,&i,ncols,scols,svals,INSERT_VALUES));
 47:       PetscCall(MatRestoreRow(B,i,&ncols,&cols,&vals));
 48:     }
 49:   }
 50:   /* Transfer C */
 51:   if (c!=0.0) {
 52:     for (i=0;i<M2;i++) {
 53:       PetscCall(MatGetRow(C,i,&ncols,&cols,&vals));
 54:       if (c!=1.0) {
 55:         svals=buf;
 56:         for (j=0;j<ncols;j++) svals[j] = vals[j]*c;
 57:       } else svals=(PetscScalar*)vals;
 58:       j = i+M1;
 59:       PetscCall(MatSetValues(G,1,&j,ncols,cols,svals,INSERT_VALUES));
 60:       PetscCall(MatRestoreRow(C,i,&ncols,&cols,&vals));
 61:     }
 62:   }
 63:   /* Transfer D */
 64:   if (d!=0.0) {
 65:     for (i=0;i<M2;i++) {
 66:       PetscCall(MatGetRow(D,i,&ncols,&cols,&vals));
 67:       if (d!=1.0) {
 68:         svals=buf;
 69:         for (j=0;j<ncols;j++) svals[j] = vals[j]*d;
 70:       } else svals=(PetscScalar*)vals;
 71:       for (j=0;j<ncols;j++) scols[j] = cols[j]+N1;
 72:       j = i+M1;
 73:       PetscCall(MatSetValues(G,1,&j,ncols,scols,svals,INSERT_VALUES));
 74:       PetscCall(MatRestoreRow(D,i,&ncols,&cols,&vals));
 75:     }
 76:   }
 77:   PetscCall(PetscFree2(buf,scols));
 78:   PetscFunctionReturn(PETSC_SUCCESS);
 79: }

 81: static PetscErrorCode MatCreateTile_MPI(PetscScalar a,Mat A,PetscScalar b,Mat B,PetscScalar c,Mat C,PetscScalar d,Mat D,Mat G)
 82: {
 83:   PetscMPIInt       np;
 84:   PetscInt          p,i,j,N1,N2,m1,m2,*map1,*map2;
 85:   PetscInt          ncols,*scols,start,gstart;
 86:   PetscScalar       *svals,*buf;
 87:   const PetscInt    *cols,*mapptr1,*mapptr2;
 88:   const PetscScalar *vals;

 90:   PetscFunctionBegin;
 91:   PetscCall(MatGetSize(A,NULL,&N1));
 92:   PetscCall(MatGetLocalSize(A,&m1,NULL));
 93:   PetscCall(MatGetSize(D,NULL,&N2));
 94:   PetscCall(MatGetLocalSize(D,&m2,NULL));

 96:   /* Create mappings */
 97:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)G),&np));
 98:   PetscCall(MatGetOwnershipRangesColumn(A,&mapptr1));
 99:   PetscCall(MatGetOwnershipRangesColumn(B,&mapptr2));
100:   PetscCall(PetscMalloc4(PetscMax(N1,N2),&buf,PetscMax(N1,N2),&scols,N1,&map1,N2,&map2));
101:   for (p=0;p<np;p++) {
102:     for (i=mapptr1[p];i<mapptr1[p+1];i++) map1[i] = i+mapptr2[p];
103:   }
104:   for (p=0;p<np;p++) {
105:     for (i=mapptr2[p];i<mapptr2[p+1];i++) map2[i] = i+mapptr1[p+1];
106:   }
107:   PetscCall(MatGetOwnershipRange(G,&gstart,NULL));

109:   /* Transfer A */
110:   if (a!=0.0) {
111:     PetscCall(MatGetOwnershipRange(A,&start,NULL));
112:     for (i=0;i<m1;i++) {
113:       PetscCall(MatGetRow(A,i+start,&ncols,&cols,&vals));
114:       if (a!=1.0) {
115:         svals=buf;
116:         for (j=0;j<ncols;j++) svals[j] = vals[j]*a;
117:       } else svals=(PetscScalar*)vals;
118:       for (j=0;j<ncols;j++) scols[j] = map1[cols[j]];
119:       j = gstart+i;
120:       PetscCall(MatSetValues(G,1,&j,ncols,scols,svals,INSERT_VALUES));
121:       PetscCall(MatRestoreRow(A,i+start,&ncols,&cols,&vals));
122:     }
123:   }
124:   /* Transfer B */
125:   if (b!=0.0) {
126:     PetscCall(MatGetOwnershipRange(B,&start,NULL));
127:     for (i=0;i<m1;i++) {
128:       PetscCall(MatGetRow(B,i+start,&ncols,&cols,&vals));
129:       if (b!=1.0) {
130:         svals=buf;
131:         for (j=0;j<ncols;j++) svals[j] = vals[j]*b;
132:       } else svals=(PetscScalar*)vals;
133:       for (j=0;j<ncols;j++) scols[j] = map2[cols[j]];
134:       j = gstart+i;
135:       PetscCall(MatSetValues(G,1,&j,ncols,scols,svals,INSERT_VALUES));
136:       PetscCall(MatRestoreRow(B,i+start,&ncols,&cols,&vals));
137:     }
138:   }
139:   /* Transfer C */
140:   if (c!=0.0) {
141:     PetscCall(MatGetOwnershipRange(C,&start,NULL));
142:     for (i=0;i<m2;i++) {
143:       PetscCall(MatGetRow(C,i+start,&ncols,&cols,&vals));
144:       if (c!=1.0) {
145:         svals=buf;
146:         for (j=0;j<ncols;j++) svals[j] = vals[j]*c;
147:       } else svals=(PetscScalar*)vals;
148:       for (j=0;j<ncols;j++) scols[j] = map1[cols[j]];
149:       j = gstart+m1+i;
150:       PetscCall(MatSetValues(G,1,&j,ncols,scols,svals,INSERT_VALUES));
151:       PetscCall(MatRestoreRow(C,i+start,&ncols,&cols,&vals));
152:     }
153:   }
154:   /* Transfer D */
155:   if (d!=0.0) {
156:     PetscCall(MatGetOwnershipRange(D,&start,NULL));
157:     for (i=0;i<m2;i++) {
158:       PetscCall(MatGetRow(D,i+start,&ncols,&cols,&vals));
159:       if (d!=1.0) {
160:         svals=buf;
161:         for (j=0;j<ncols;j++) svals[j] = vals[j]*d;
162:       } else svals=(PetscScalar*)vals;
163:       for (j=0;j<ncols;j++) scols[j] = map2[cols[j]];
164:       j = gstart+m1+i;
165:       PetscCall(MatSetValues(G,1,&j,ncols,scols,svals,INSERT_VALUES));
166:       PetscCall(MatRestoreRow(D,i+start,&ncols,&cols,&vals));
167:     }
168:   }
169:   PetscCall(PetscFree4(buf,scols,map1,map2));
170:   PetscFunctionReturn(PETSC_SUCCESS);
171: }

173: /*@
174:    MatCreateTile - Explicitly build a matrix from four blocks, G = [ a*A b*B; c*C d*D ].

176:    Collective

178:    Input Parameters:
179: +  A - matrix for top-left block
180: .  a - scaling factor for block A
181: .  B - matrix for top-right block
182: .  b - scaling factor for block B
183: .  C - matrix for bottom-left block
184: .  c - scaling factor for block C
185: .  D - matrix for bottom-right block
186: -  d - scaling factor for block D

188:    Output Parameter:
189: .  G  - the resulting matrix

191:    Notes:
192:    In the case of a parallel matrix, a permuted version of G is returned. The permutation
193:    is a perfect shuffle such that the local parts of A, B, C, D remain in the local part of
194:    G for the same process.

196:    Matrix G must be destroyed by the user.

198:    The blocks can be of different type. They can be either ConstantDiagonal, or a standard
199:    type such as AIJ, or any other type provided that it supports the MatGetRow operation.
200:    The type of the output matrix will be the same as the first block that is not
201:    ConstantDiagonal (checked in the A,B,C,D order).

203:    Level: developer

205: .seealso: MatCreateNest()
206: @*/
207: PetscErrorCode MatCreateTile(PetscScalar a,Mat A,PetscScalar b,Mat B,PetscScalar c,Mat C,PetscScalar d,Mat D,Mat *G)
208: {
209:   PetscInt       i,k,M1,M2,N1,N2,M,N,m1,m2,n1,n2,m,n,bs;
210:   PetscBool      diag[4];
211:   Mat            block[4] = {A,B,C,D};
212:   MatType        type[4];
213:   PetscMPIInt    size;

215:   PetscFunctionBegin;
220:   PetscCheckSameTypeAndComm(A,2,B,4);
221:   PetscCheckSameTypeAndComm(A,2,C,6);
222:   PetscCheckSameTypeAndComm(A,2,D,8);
227:   PetscAssertPointer(G,9);

229:   /* check row 1 */
230:   PetscCall(MatGetSize(A,&M1,NULL));
231:   PetscCall(MatGetLocalSize(A,&m1,NULL));
232:   PetscCall(MatGetSize(B,&M,NULL));
233:   PetscCall(MatGetLocalSize(B,&m,NULL));
234:   PetscCheck(M==M1 && m==m1,PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible dimensions");
235:   /* check row 2 */
236:   PetscCall(MatGetSize(C,&M2,NULL));
237:   PetscCall(MatGetLocalSize(C,&m2,NULL));
238:   PetscCall(MatGetSize(D,&M,NULL));
239:   PetscCall(MatGetLocalSize(D,&m,NULL));
240:   PetscCheck(M==M2 && m==m2,PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible dimensions");
241:   /* check column 1 */
242:   PetscCall(MatGetSize(A,NULL,&N1));
243:   PetscCall(MatGetLocalSize(A,NULL,&n1));
244:   PetscCall(MatGetSize(C,NULL,&N));
245:   PetscCall(MatGetLocalSize(C,NULL,&n));
246:   PetscCheck(N==N1 && n==n1,PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible dimensions");
247:   /* check column 2 */
248:   PetscCall(MatGetSize(B,NULL,&N2));
249:   PetscCall(MatGetLocalSize(B,NULL,&n2));
250:   PetscCall(MatGetSize(D,NULL,&N));
251:   PetscCall(MatGetLocalSize(D,NULL,&n));
252:   PetscCheck(N==N2 && n==n2,PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_INCOMP,"Incompatible dimensions");

254:   /* check matrix types */
255:   for (i=0;i<4;i++) {
256:     PetscCall(MatGetType(block[i],&type[i]));
257:     PetscCall(PetscStrcmp(type[i],MATCONSTANTDIAGONAL,&diag[i]));
258:   }
259:   for (k=0;k<4;k++) if (!diag[k]) break;
260:   PetscCheck(k<4,PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Not implemented for 4 diagonal blocks");

262:   PetscCall(MatGetBlockSize(block[k],&bs));
263:   PetscCall(MatCreate(PetscObjectComm((PetscObject)block[k]),G));
264:   PetscCall(MatSetSizes(*G,m1+m2,n1+n2,M1+M2,N1+N2));
265:   PetscCall(MatSetType(*G,type[k]));
266:   PetscCall(MatSetBlockSize(*G,bs));
267:   PetscCall(MatSetUp(*G));

269:   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)*G),&size));
270:   if (size>1) PetscCall(MatCreateTile_MPI(a,A,b,B,c,C,d,D,*G));
271:   else PetscCall(MatCreateTile_Seq(a,A,b,B,c,C,d,D,*G));
272:   PetscCall(MatAssemblyBegin(*G,MAT_FINAL_ASSEMBLY));
273:   PetscCall(MatAssemblyEnd(*G,MAT_FINAL_ASSEMBLY));
274:   PetscFunctionReturn(PETSC_SUCCESS);
275: }

277: /*@
278:    MatCreateVecsEmpty - Get vector(s) compatible with the matrix, i.e. with the same
279:    parallel layout, but without internal array.

281:    Collective

283:    Input Parameter:
284: .  mat - the matrix

286:    Output Parameters:
287: +  right - (optional) vector that the matrix can be multiplied against
288: -  left - (optional) vector that the matrix vector product can be stored in

290:    Note:
291:    This is similar to MatCreateVecs(), but the new vectors do not have an internal
292:    array, so the intended usage is with VecPlaceArray().

294:    Level: developer

296: .seealso: VecDuplicateEmpty()
297: @*/
298: PetscErrorCode MatCreateVecsEmpty(Mat mat,Vec *right,Vec *left)
299: {
300:   PetscBool      standard,cuda=PETSC_FALSE,hip=PETSC_FALSE,skip=PETSC_FALSE;
301:   PetscInt       M,N,mloc,nloc,rbs,cbs;
302:   PetscMPIInt    size;
303:   Vec            v;

305:   PetscFunctionBegin;

309:   PetscCall(PetscObjectTypeCompareAny((PetscObject)mat,&standard,MATSEQAIJ,MATMPIAIJ,MATSEQBAIJ,MATMPIBAIJ,MATSEQSBAIJ,MATMPISBAIJ,MATSEQDENSE,MATMPIDENSE,""));
310:   PetscCall(PetscObjectTypeCompareAny((PetscObject)mat,&cuda,MATSEQAIJCUSPARSE,MATMPIAIJCUSPARSE,""));
311:   PetscCall(PetscObjectTypeCompareAny((PetscObject)mat,&hip,MATSEQAIJHIPSPARSE,MATMPIAIJHIPSPARSE,""));
312:   if (!standard && !cuda && !hip) {
313:     PetscCall(MatCreateVecs(mat,right,left));
314:     v = right? *right: *left;
315:     if (v) {
316:       PetscCall(PetscObjectTypeCompareAny((PetscObject)v,&standard,VECSEQ,VECMPI,""));
317:       PetscCall(PetscObjectTypeCompareAny((PetscObject)v,&cuda,VECSEQCUDA,VECMPICUDA,""));
318:       PetscCall(PetscObjectTypeCompareAny((PetscObject)v,&hip,VECSEQHIP,VECMPIHIP,""));
319:     }
320:     if (!standard && !cuda && !hip) skip = PETSC_TRUE;
321:     else {
322:       if (right) PetscCall(VecDestroy(right));
323:       if (left) PetscCall(VecDestroy(left));
324:     }
325:   }
326:   if (!skip) {
327:     PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size));
328:     PetscCall(MatGetLocalSize(mat,&mloc,&nloc));
329:     PetscCall(MatGetSize(mat,&M,&N));
330:     PetscCall(MatGetBlockSizes(mat,&rbs,&cbs));
331:     if (right) {
332:       if (cuda) {
333: #if defined(PETSC_HAVE_CUDA)
334:         if (size>1) PetscCall(VecCreateMPICUDAWithArray(PetscObjectComm((PetscObject)mat),cbs,nloc,N,NULL,right));
335:         else PetscCall(VecCreateSeqCUDAWithArray(PetscObjectComm((PetscObject)mat),cbs,N,NULL,right));
336: #endif
337:       } else if (hip) {
338: #if defined(PETSC_HAVE_HIP)
339:         if (size>1) PetscCall(VecCreateMPIHIPWithArray(PetscObjectComm((PetscObject)mat),cbs,nloc,N,NULL,right));
340:         else PetscCall(VecCreateSeqHIPWithArray(PetscObjectComm((PetscObject)mat),cbs,N,NULL,right));
341: #endif
342:       } else {
343:         if (size>1) PetscCall(VecCreateMPIWithArray(PetscObjectComm((PetscObject)mat),cbs,nloc,N,NULL,right));
344:         else PetscCall(VecCreateSeqWithArray(PetscObjectComm((PetscObject)mat),cbs,N,NULL,right));
345:       }
346:     }
347:     if (left) {
348:       if (cuda) {
349: #if defined(PETSC_HAVE_CUDA)
350:         if (size>1) PetscCall(VecCreateMPICUDAWithArray(PetscObjectComm((PetscObject)mat),rbs,mloc,M,NULL,left));
351:         else PetscCall(VecCreateSeqCUDAWithArray(PetscObjectComm((PetscObject)mat),rbs,M,NULL,left));
352: #endif
353:       } else if (hip) {
354: #if defined(PETSC_HAVE_HIP)
355:         if (size>1) PetscCall(VecCreateMPIHIPWithArray(PetscObjectComm((PetscObject)mat),rbs,mloc,M,NULL,left));
356:         else PetscCall(VecCreateSeqHIPWithArray(PetscObjectComm((PetscObject)mat),rbs,M,NULL,left));
357: #endif
358:       } else {
359:         if (size>1) PetscCall(VecCreateMPIWithArray(PetscObjectComm((PetscObject)mat),rbs,mloc,M,NULL,left));
360:         else PetscCall(VecCreateSeqWithArray(PetscObjectComm((PetscObject)mat),rbs,M,NULL,left));
361:       }
362:     }
363:   }
364:   PetscFunctionReturn(PETSC_SUCCESS);
365: }

367: /*@
368:    MatNormEstimate - Estimate the 2-norm of a matrix.

370:    Collective

372:    Input Parameters:
373: +  A   - the matrix
374: .  vrn - random vector with normally distributed entries (can be NULL)
375: -  w   - workspace vector (can be NULL)

377:    Output Parameter:
378: .  nrm - the norm estimate

380:    Notes:
381:    Does not need access to the matrix entries, just performs a matrix-vector product.
382:    Based on work by I. Ipsen and coworkers https://ipsen.math.ncsu.edu/ps/slides_ima.pdf

384:    The input vector vrn must have unit 2-norm.
385:    If vrn is NULL, then it is created internally and filled with VecSetRandomNormal().

387:    Level: developer

389: .seealso: VecSetRandomNormal()
390: @*/
391: PetscErrorCode MatNormEstimate(Mat A,Vec vrn,Vec w,PetscReal *nrm)
392: {
393:   PetscInt       n;
394:   Vec            vv=NULL,ww=NULL;

396:   PetscFunctionBegin;
401:   PetscAssertPointer(nrm,4);

403:   if (!vrn) {
404:     PetscCall(MatCreateVecs(A,&vv,NULL));
405:     vrn = vv;
406:     PetscCall(VecSetRandomNormal(vv,NULL,NULL,NULL));
407:     PetscCall(VecNormalize(vv,NULL));
408:   }
409:   if (!w) {
410:     PetscCall(MatCreateVecs(A,&ww,NULL));
411:     w = ww;
412:   }

414:   PetscCall(MatGetSize(A,&n,NULL));
415:   PetscCall(MatMult(A,vrn,w));
416:   PetscCall(VecNorm(w,NORM_2,nrm));
417:   *nrm *= PetscSqrtReal((PetscReal)n);

419:   PetscCall(VecDestroy(&vv));
420:   PetscCall(VecDestroy(&ww));
421:   PetscFunctionReturn(PETSC_SUCCESS);
422: }