Actual source code: axpy.c

petsc-master 2020-02-22
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  2:  #include <petsc/private/matimpl.h>

  4: static PetscErrorCode MatTransposeAXPY_Private(Mat Y,PetscScalar a,Mat X,MatStructure str,Mat T)
  5: {
  6:   PetscErrorCode ierr,(*f)(Mat,Mat*);
  7:   Mat            A,F;

 10:   PetscObjectQueryFunction((PetscObject)T,"MatTransposeGetMat_C",&f);
 11:   if (f) {
 12:     MatTransposeGetMat(T,&A);
 13:     if (T == X) {
 14:       PetscInfo(NULL,"Explicitly transposing X of type MATTRANSPOSEMAT to perform MatAXPY()\n");
 15:       MatTranspose(A,MAT_INITIAL_MATRIX,&F);
 16:       A = Y;
 17:     } else {
 18:       PetscInfo(NULL,"Transposing X because Y of type MATTRANSPOSEMAT to perform MatAXPY()\n");
 19:       MatTranspose(X,MAT_INITIAL_MATRIX,&F);
 20:     }
 21:   } else {
 22:     MatHermitianTransposeGetMat(T,&A);
 23:     if (T == X) {
 24:       PetscInfo(NULL,"Explicitly Hermitian transposing X of type MATTRANSPOSEMAT to perform MatAXPY()\n");
 25:       MatHermitianTranspose(A,MAT_INITIAL_MATRIX,&F);
 26:       A = Y;
 27:     } else {
 28:       PetscInfo(NULL,"Hermitian transposing X because Y of type MATTRANSPOSEMAT to perform MatAXPY()\n");
 29:       MatHermitianTranspose(X,MAT_INITIAL_MATRIX,&F);
 30:     }
 31:   }
 32:   MatAXPY(A,a,F,str);
 33:   MatDestroy(&F);
 34:   return(0);
 35: }

 37: /*@
 38:    MatAXPY - Computes Y = a*X + Y.

 40:    Logically  Collective on Mat

 42:    Input Parameters:
 43: +  a - the scalar multiplier
 44: .  X - the first matrix
 45: .  Y - the second matrix
 46: -  str - either SAME_NONZERO_PATTERN, DIFFERENT_NONZERO_PATTERN
 47:          or SUBSET_NONZERO_PATTERN (nonzeros of X is a subset of Y's)

 49:    Notes: No operation is performed when a is zero.

 51:    Level: intermediate

 53: .seealso: MatAYPX()
 54:  @*/
 55: PetscErrorCode MatAXPY(Mat Y,PetscScalar a,Mat X,MatStructure str)
 56: {
 58:   PetscInt       M1,M2,N1,N2;
 59:   PetscInt       m1,m2,n1,n2;
 60:   MatType        t1,t2;
 61:   PetscBool      sametype,transpose;

 68:   MatGetSize(X,&M1,&N1);
 69:   MatGetSize(Y,&M2,&N2);
 70:   MatGetLocalSize(X,&m1,&n1);
 71:   MatGetLocalSize(Y,&m2,&n2);
 72:   if (M1 != M2 || N1 != N2) SETERRQ4(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_SIZ,"Non conforming matrix add: global sizes %D x %D, %D x %D",M1,M2,N1,N2);
 73:   if (m1 != m2 || n1 != n2) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Non conforming matrix add: local sizes %D x %D, %D x %D",m1,m2,n1,n2);
 74:   if (!Y->assembled) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix (Y)");
 75:   if (!X->assembled) SETERRQ(PetscObjectComm((PetscObject)X),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix (X)");
 76:   if (a == (PetscScalar)0.0) return(0);
 77:   if (Y == X) {
 78:     MatScale(Y,1.0 + a);
 79:     return(0);
 80:   }
 81:   MatGetType(X,&t1);
 82:   MatGetType(Y,&t2);
 83:   PetscStrcmp(t1,t2,&sametype);
 84:   PetscLogEventBegin(MAT_AXPY,Y,0,0,0);
 85:   if (Y->ops->axpy && sametype) {
 86:     (*Y->ops->axpy)(Y,a,X,str);
 87:   } else {
 88:     PetscStrcmp(t1,MATTRANSPOSEMAT,&transpose);
 89:     if (transpose) {
 90:         MatTransposeAXPY_Private(Y,a,X,str,X);
 91:     } else {
 92:       PetscStrcmp(t2,MATTRANSPOSEMAT,&transpose);
 93:       if (transpose) {
 94:         MatTransposeAXPY_Private(Y,a,X,str,Y);
 95:       } else {
 96:         MatAXPY_Basic(Y,a,X,str);
 97:       }
 98:     }
 99:   }
100:   PetscLogEventEnd(MAT_AXPY,Y,0,0,0);
101:   return(0);
102: }

104: PetscErrorCode MatAXPY_Basic_Preallocate(Mat Y, Mat X, Mat *B)
105: {
107:   PetscErrorCode (*preall)(Mat,Mat,Mat*) = NULL;

110:   /* look for any available faster alternative to the general preallocator */
111:   PetscObjectQueryFunction((PetscObject)Y,"MatAXPYGetPreallocation_C",&preall);
112:   if (preall) {
113:     (*preall)(Y,X,B);
114:   } else { /* Use MatPrellocator, assumes same row-col distribution */
115:     Mat      preallocator;
116:     PetscInt r,rstart,rend;
117:     PetscInt m,n,M,N;

119:     MatGetRowUpperTriangular(Y);
120:     MatGetRowUpperTriangular(X);
121:     MatGetSize(Y,&M,&N);
122:     MatGetLocalSize(Y,&m,&n);
123:     MatCreate(PetscObjectComm((PetscObject)Y),&preallocator);
124:     MatSetType(preallocator,MATPREALLOCATOR);
125:     MatSetSizes(preallocator,m,n,M,N);
126:     MatSetUp(preallocator);
127:     MatGetOwnershipRange(preallocator,&rstart,&rend);
128:     for (r = rstart; r < rend; ++r) {
129:       PetscInt          ncols;
130:       const PetscInt    *row;
131:       const PetscScalar *vals;

133:       MatGetRow(Y,r,&ncols,&row,&vals);
134:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
135:       MatRestoreRow(Y,r,&ncols,&row,&vals);
136:       MatGetRow(X,r,&ncols,&row,&vals);
137:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
138:       MatRestoreRow(X,r,&ncols,&row,&vals);
139:     }
140:     MatAssemblyBegin(preallocator,MAT_FINAL_ASSEMBLY);
141:     MatAssemblyEnd(preallocator,MAT_FINAL_ASSEMBLY);
142:     MatRestoreRowUpperTriangular(Y);
143:     MatRestoreRowUpperTriangular(X);

145:     MatCreate(PetscObjectComm((PetscObject)Y),B);
146:     MatSetType(*B,((PetscObject)Y)->type_name);
147:     MatSetSizes(*B,m,n,M,N);
148:     MatPreallocatorPreallocate(preallocator,PETSC_FALSE,*B);
149:     MatDestroy(&preallocator);
150:   }
151:   return(0);
152: }

154: PetscErrorCode MatAXPY_Basic(Mat Y,PetscScalar a,Mat X,MatStructure str)
155: {
157:   PetscBool      isshell;

160:   PetscObjectTypeCompare((PetscObject)Y,MATSHELL,&isshell);
161:   if (isshell) { /* MatShell has special support for AXPY */
162:     PetscErrorCode (*f)(Mat,PetscScalar,Mat,MatStructure);

164:     MatGetOperation(Y,MATOP_AXPY,(void (**)(void))&f);
165:     if (f) {
166:       (*f)(Y,a,X,str);
167:       return(0);
168:     }
169:   }
170:   if (str != DIFFERENT_NONZERO_PATTERN) {
171:     PetscInt          i,start,end,j,ncols,m,n;
172:     const PetscInt    *row;
173:     PetscScalar       *val;
174:     const PetscScalar *vals;

176:     MatGetSize(X,&m,&n);
177:     MatGetOwnershipRange(X,&start,&end);
178:     MatGetRowUpperTriangular(X);
179:     if (a == 1.0) {
180:       for (i = start; i < end; i++) {
181:         MatGetRow(X,i,&ncols,&row,&vals);
182:         MatSetValues(Y,1,&i,ncols,row,vals,ADD_VALUES);
183:         MatRestoreRow(X,i,&ncols,&row,&vals);
184:       }
185:     } else {
186:       PetscInt vs = 100;
187:       /* realloc if needed, as this function may be used in parallel */
188:       PetscMalloc1(vs,&val);
189:       for (i=start; i<end; i++) {
190:         MatGetRow(X,i,&ncols,&row,&vals);
191:         if (vs < ncols) {
192:           vs   = PetscMin(2*ncols,n);
193:           PetscRealloc(vs*sizeof(*val),&val);
194:         }
195:         for (j=0; j<ncols; j++) val[j] = a*vals[j];
196:         MatSetValues(Y,1,&i,ncols,row,val,ADD_VALUES);
197:         MatRestoreRow(X,i,&ncols,&row,&vals);
198:       }
199:       PetscFree(val);
200:     }
201:     MatRestoreRowUpperTriangular(X);
202:     MatAssemblyBegin(Y,MAT_FINAL_ASSEMBLY);
203:     MatAssemblyEnd(Y,MAT_FINAL_ASSEMBLY);
204:   } else {
205:     Mat B;

207:     MatAXPY_Basic_Preallocate(Y,X,&B);
208:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
209:     MatHeaderReplace(Y,&B);
210:   }
211:   return(0);
212: }

214: PetscErrorCode MatAXPY_BasicWithPreallocation(Mat B,Mat Y,PetscScalar a,Mat X,MatStructure str)
215: {
216:   PetscInt          i,start,end,j,ncols,m,n;
217:   PetscErrorCode    ierr;
218:   const PetscInt    *row;
219:   PetscScalar       *val;
220:   const PetscScalar *vals;

223:   MatGetSize(X,&m,&n);
224:   MatGetOwnershipRange(X,&start,&end);
225:   MatGetRowUpperTriangular(Y);
226:   MatGetRowUpperTriangular(X);
227:   if (a == 1.0) {
228:     for (i = start; i < end; i++) {
229:       MatGetRow(Y,i,&ncols,&row,&vals);
230:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
231:       MatRestoreRow(Y,i,&ncols,&row,&vals);

233:       MatGetRow(X,i,&ncols,&row,&vals);
234:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
235:       MatRestoreRow(X,i,&ncols,&row,&vals);
236:     }
237:   } else {
238:     PetscInt vs = 100;
239:     /* realloc if needed, as this function may be used in parallel */
240:     PetscMalloc1(vs,&val);
241:     for (i=start; i<end; i++) {
242:       MatGetRow(Y,i,&ncols,&row,&vals);
243:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
244:       MatRestoreRow(Y,i,&ncols,&row,&vals);

246:       MatGetRow(X,i,&ncols,&row,&vals);
247:       if (vs < ncols) {
248:         vs   = PetscMin(2*ncols,n);
249:         PetscRealloc(vs*sizeof(*val),&val);
250:       }
251:       for (j=0; j<ncols; j++) val[j] = a*vals[j];
252:       MatSetValues(B,1,&i,ncols,row,val,ADD_VALUES);
253:       MatRestoreRow(X,i,&ncols,&row,&vals);
254:     }
255:     PetscFree(val);
256:   }
257:   MatRestoreRowUpperTriangular(Y);
258:   MatRestoreRowUpperTriangular(X);
259:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
260:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
261:   return(0);
262: }

264: /*@
265:    MatShift - Computes Y =  Y + a I, where a is a PetscScalar and I is the identity matrix.

267:    Neighbor-wise Collective on Mat

269:    Input Parameters:
270: +  Y - the matrices
271: -  a - the PetscScalar

273:    Level: intermediate

275:    Notes:
276:     If the matrix Y is missing some diagonal entries this routine can be very slow. To make it fast one should initially
277:    fill the matrix so that all diagonal entries have a value (with a value of zero for those locations that would not have an
278:    entry). No operation is performed when a is zero.

280:    To form Y = Y + diag(V) use MatDiagonalSet()

282: .seealso: MatDiagonalSet(), MatScale(), MatDiagonalScale()
283:  @*/
284: PetscErrorCode  MatShift(Mat Y,PetscScalar a)
285: {

290:   if (!Y->assembled) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
291:   if (Y->factortype) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
292:   MatCheckPreallocated(Y,1);
293:   if (a == 0.0) return(0);

295:   if (Y->ops->shift) {
296:     (*Y->ops->shift)(Y,a);
297:   } else {
298:     MatShift_Basic(Y,a);
299:   }

301:   PetscObjectStateIncrease((PetscObject)Y);
302:   return(0);
303: }

305: PetscErrorCode  MatDiagonalSet_Default(Mat Y,Vec D,InsertMode is)
306: {
308:   PetscInt       i,start,end;
309:   PetscScalar    *v;

312:   MatGetOwnershipRange(Y,&start,&end);
313:   VecGetArray(D,&v);
314:   for (i=start; i<end; i++) {
315:     MatSetValues(Y,1,&i,1,&i,v+i-start,is);
316:   }
317:   VecRestoreArray(D,&v);
318:   MatAssemblyBegin(Y,MAT_FINAL_ASSEMBLY);
319:   MatAssemblyEnd(Y,MAT_FINAL_ASSEMBLY);
320:   return(0);
321: }

323: /*@
324:    MatDiagonalSet - Computes Y = Y + D, where D is a diagonal matrix
325:    that is represented as a vector. Or Y[i,i] = D[i] if InsertMode is
326:    INSERT_VALUES.

328:    Input Parameters:
329: +  Y - the input matrix
330: .  D - the diagonal matrix, represented as a vector
331: -  i - INSERT_VALUES or ADD_VALUES

333:    Neighbor-wise Collective on Mat

335:    Notes:
336:     If the matrix Y is missing some diagonal entries this routine can be very slow. To make it fast one should initially
337:    fill the matrix so that all diagonal entries have a value (with a value of zero for those locations that would not have an
338:    entry).

340:    Level: intermediate

342: .seealso: MatShift(), MatScale(), MatDiagonalScale()
343: @*/
344: PetscErrorCode  MatDiagonalSet(Mat Y,Vec D,InsertMode is)
345: {
347:   PetscInt       matlocal,veclocal;

352:   MatGetLocalSize(Y,&matlocal,NULL);
353:   VecGetLocalSize(D,&veclocal);
354:   if (matlocal != veclocal) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number local rows of matrix %D does not match that of vector for diagonal %D",matlocal,veclocal);
355:   if (Y->ops->diagonalset) {
356:     (*Y->ops->diagonalset)(Y,D,is);
357:   } else {
358:     MatDiagonalSet_Default(Y,D,is);
359:   }
360:   PetscObjectStateIncrease((PetscObject)Y);
361:   return(0);
362: }

364: /*@
365:    MatAYPX - Computes Y = a*Y + X.

367:    Logically on Mat

369:    Input Parameters:
370: +  a - the PetscScalar multiplier
371: .  Y - the first matrix
372: .  X - the second matrix
373: -  str - either SAME_NONZERO_PATTERN, DIFFERENT_NONZERO_PATTERN or SUBSET_NONZERO_PATTERN

375:    Level: intermediate

377: .seealso: MatAXPY()
378:  @*/
379: PetscErrorCode  MatAYPX(Mat Y,PetscScalar a,Mat X,MatStructure str)
380: {
381:   PetscScalar    one = 1.0;
383:   PetscInt       mX,mY,nX,nY;

389:   MatGetSize(X,&mX,&nX);
390:   MatGetSize(X,&mY,&nY);
391:   if (mX != mY || nX != nY) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Non conforming matrices: %D %D first %D %D second",mX,mY,nX,nY);
392:   MatScale(Y,a);
393:   MatAXPY(Y,one,X,str);
394:   return(0);
395: }

397: /*@
398:     MatComputeOperator - Computes the explicit matrix

400:     Collective on Mat

402:     Input Parameter:
403: +   inmat - the matrix
404: -   mattype - the matrix type for the explicit operator

406:     Output Parameter:
407: .   mat - the explict  operator

409:     Notes:
410:     This computation is done by applying the operators to columns of the identity matrix.
411:     This routine is costly in general, and is recommended for use only with relatively small systems.
412:     Currently, this routine uses a dense matrix format if mattype == NULL.

414:     Level: advanced

416: @*/
417: PetscErrorCode  MatComputeOperator(Mat inmat,MatType mattype,Mat *mat)
418: {

424:   MatConvert_Shell(inmat,mattype ? mattype : MATDENSE,MAT_INITIAL_MATRIX,mat);
425:   return(0);
426: }

428: /*@
429:     MatComputeOperatorTranspose - Computes the explicit matrix representation of
430:         a give matrix that can apply MatMultTranspose()

432:     Collective on Mat

434:     Input Parameter:
435: .   inmat - the matrix

437:     Output Parameter:
438: .   mat - the explict  operator transposed

440:     Notes:
441:     This computation is done by applying the transpose of the operator to columns of the identity matrix.
442:     This routine is costly in general, and is recommended for use only with relatively small systems.
443:     Currently, this routine uses a dense matrix format if mattype == NULL.

445:     Level: advanced

447: @*/
448: PetscErrorCode  MatComputeOperatorTranspose(Mat inmat,MatType mattype,Mat *mat)
449: {
450:   Mat            A;

456:   MatCreateTranspose(inmat,&A);
457:   MatConvert_Shell(A,mattype ? mattype : MATDENSE,MAT_INITIAL_MATRIX,mat);
458:   MatDestroy(&A);
459:   return(0);
460: }

462: /*@
463:   MatChop - Set all values in the matrix less than the tolerance to zero

465:   Input Parameters:
466: + A   - The matrix
467: - tol - The zero tolerance

469:   Output Parameters:
470: . A - The chopped matrix

472:   Level: intermediate

474: .seealso: MatCreate(), MatZeroEntries()
475:  @*/
476: PetscErrorCode MatChop(Mat A, PetscReal tol)
477: {
478:   PetscScalar    *newVals;
479:   PetscInt       *newCols;
480:   PetscInt       rStart, rEnd, numRows, maxRows, r, colMax = 0;

484:   MatGetOwnershipRange(A, &rStart, &rEnd);
485:   for (r = rStart; r < rEnd; ++r) {
486:     PetscInt ncols;

488:     MatGetRow(A, r, &ncols, NULL, NULL);
489:     colMax = PetscMax(colMax, ncols);
490:     MatRestoreRow(A, r, &ncols, NULL, NULL);
491:   }
492:   numRows = rEnd - rStart;
493:   MPIU_Allreduce(&numRows, &maxRows, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)A));
494:   PetscMalloc2(colMax,&newCols,colMax,&newVals);
495:   for (r = rStart; r < rStart+maxRows; ++r) {
496:     const PetscScalar *vals;
497:     const PetscInt    *cols;
498:     PetscInt           ncols, newcols, c;

500:     if (r < rEnd) {
501:       MatGetRow(A, r, &ncols, &cols, &vals);
502:       for (c = 0; c < ncols; ++c) {
503:         newCols[c] = cols[c];
504:         newVals[c] = PetscAbsScalar(vals[c]) < tol ? 0.0 : vals[c];
505:       }
506:       newcols = ncols;
507:       MatRestoreRow(A, r, &ncols, &cols, &vals);
508:       MatSetValues(A, 1, &r, newcols, newCols, newVals, INSERT_VALUES);
509:     }
510:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
511:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
512:   }
513:   PetscFree2(newCols,newVals);
514:   return(0);
515: }