Actual source code: axpy.c


  2: #include <petsc/private/matimpl.h>

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

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

 36: /*@
 37:    MatAXPY - Computes Y = a*X + Y.

 39:    Logically  Collective on Mat

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

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

 49:    Level: intermediate

 51: .seealso: MatAYPX()
 52:  @*/
 53: PetscErrorCode MatAXPY(Mat Y,PetscScalar a,Mat X,MatStructure str)
 54: {
 55:   PetscInt       M1,M2,N1,N2;
 56:   PetscInt       m1,m2,n1,n2;
 57:   MatType        t1,t2;
 58:   PetscBool      sametype,transpose;

 64:   MatGetSize(X,&M1,&N1);
 65:   MatGetSize(Y,&M2,&N2);
 66:   MatGetLocalSize(X,&m1,&n1);
 67:   MatGetLocalSize(Y,&m2,&n2);
 72:   if (a == (PetscScalar)0.0) return 0;
 73:   if (Y == X) {
 74:     MatScale(Y,1.0 + a);
 75:     return 0;
 76:   }
 77:   MatGetType(X,&t1);
 78:   MatGetType(Y,&t2);
 79:   PetscStrcmp(t1,t2,&sametype);
 80:   PetscLogEventBegin(MAT_AXPY,Y,0,0,0);
 81:   if (Y->ops->axpy && (sametype || X->ops->axpy == Y->ops->axpy)) {
 82:     (*Y->ops->axpy)(Y,a,X,str);
 83:   } else {
 84:     PetscStrcmp(t1,MATTRANSPOSEMAT,&transpose);
 85:     if (transpose) {
 86:       MatTransposeAXPY_Private(Y,a,X,str,X);
 87:     } else {
 88:       PetscStrcmp(t2,MATTRANSPOSEMAT,&transpose);
 89:       if (transpose) {
 90:         MatTransposeAXPY_Private(Y,a,X,str,Y);
 91:       } else {
 92:         MatAXPY_Basic(Y,a,X,str);
 93:       }
 94:     }
 95:   }
 96:   PetscLogEventEnd(MAT_AXPY,Y,0,0,0);
 97:   return 0;
 98: }

100: PetscErrorCode MatAXPY_Basic_Preallocate(Mat Y, Mat X, Mat *B)
101: {
102:   PetscErrorCode (*preall)(Mat,Mat,Mat*) = NULL;

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

113:     MatGetRowUpperTriangular(Y);
114:     MatGetRowUpperTriangular(X);
115:     MatGetSize(Y,&M,&N);
116:     MatGetLocalSize(Y,&m,&n);
117:     MatCreate(PetscObjectComm((PetscObject)Y),&preallocator);
118:     MatSetType(preallocator,MATPREALLOCATOR);
119:     MatSetLayouts(preallocator,Y->rmap,Y->cmap);
120:     MatSetUp(preallocator);
121:     MatGetOwnershipRange(preallocator,&rstart,&rend);
122:     for (r = rstart; r < rend; ++r) {
123:       PetscInt          ncols;
124:       const PetscInt    *row;
125:       const PetscScalar *vals;

127:       MatGetRow(Y,r,&ncols,&row,&vals);
128:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
129:       MatRestoreRow(Y,r,&ncols,&row,&vals);
130:       MatGetRow(X,r,&ncols,&row,&vals);
131:       MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
132:       MatRestoreRow(X,r,&ncols,&row,&vals);
133:     }
134:     MatSetOption(preallocator,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
135:     MatAssemblyBegin(preallocator,MAT_FINAL_ASSEMBLY);
136:     MatAssemblyEnd(preallocator,MAT_FINAL_ASSEMBLY);
137:     MatRestoreRowUpperTriangular(Y);
138:     MatRestoreRowUpperTriangular(X);

140:     MatCreate(PetscObjectComm((PetscObject)Y),B);
141:     MatSetType(*B,((PetscObject)Y)->type_name);
142:     MatSetLayouts(*B,Y->rmap,Y->cmap);
143:     MatPreallocatorPreallocate(preallocator,PETSC_FALSE,*B);
144:     MatDestroy(&preallocator);
145:   }
146:   return 0;
147: }

149: PetscErrorCode MatAXPY_Basic(Mat Y,PetscScalar a,Mat X,MatStructure str)
150: {
151:   PetscBool      isshell,isdense,isnest;

153:   MatIsShell(Y,&isshell);
154:   if (isshell) { /* MatShell has special support for AXPY */
155:     PetscErrorCode (*f)(Mat,PetscScalar,Mat,MatStructure);

157:     MatGetOperation(Y,MATOP_AXPY,(void (**)(void))&f);
158:     if (f) {
159:       (*f)(Y,a,X,str);
160:       return 0;
161:     }
162:   }
163:   /* no need to preallocate if Y is dense */
164:   PetscObjectBaseTypeCompareAny((PetscObject)Y,&isdense,MATSEQDENSE,MATMPIDENSE,"");
165:   if (isdense) {
166:     PetscObjectTypeCompare((PetscObject)X,MATNEST,&isnest);
167:     if (isnest) {
168:       MatAXPY_Dense_Nest(Y,a,X);
169:       return 0;
170:     }
171:     if (str == DIFFERENT_NONZERO_PATTERN || str == UNKNOWN_NONZERO_PATTERN) str = SUBSET_NONZERO_PATTERN;
172:   }
173:   if (str != DIFFERENT_NONZERO_PATTERN && str != UNKNOWN_NONZERO_PATTERN) {
174:     PetscInt          i,start,end,j,ncols,m,n;
175:     const PetscInt    *row;
176:     PetscScalar       *val;
177:     const PetscScalar *vals;

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

210:     MatAXPY_Basic_Preallocate(Y,X,&B);
211:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
212:     MatHeaderMerge(Y,&B);
213:   }
214:   return 0;
215: }

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

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

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

247:       MatGetRow(X,i,&ncols,&row,&vals);
248:       if (vs < ncols) {
249:         vs   = PetscMin(2*ncols,n);
250:         PetscRealloc(vs*sizeof(*val),&val);
251:       }
252:       for (j=0; j<ncols; j++) val[j] = a*vals[j];
253:       MatSetValues(B,1,&i,ncols,row,val,ADD_VALUES);
254:       MatRestoreRow(X,i,&ncols,&row,&vals);
255:     }
256:     PetscFree(val);
257:   }
258:   MatRestoreRowUpperTriangular(Y);
259:   MatRestoreRowUpperTriangular(X);
260:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
261:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
262:   return 0;
263: }

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

268:    Neighbor-wise Collective on Mat

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

274:    Level: intermediate

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

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

283: .seealso: MatDiagonalSet(), MatScale(), MatDiagonalScale()
284:  @*/
285: PetscErrorCode  MatShift(Mat Y,PetscScalar a)
286: {
290:   MatCheckPreallocated(Y,1);
291:   if (a == 0.0) return 0;

293:   if (Y->ops->shift) (*Y->ops->shift)(Y,a);
294:   else MatShift_Basic(Y,a);

296:   PetscObjectStateIncrease((PetscObject)Y);
297:   return 0;
298: }

300: PetscErrorCode  MatDiagonalSet_Default(Mat Y,Vec D,InsertMode is)
301: {
302:   PetscInt          i,start,end;
303:   const PetscScalar *v;

305:   MatGetOwnershipRange(Y,&start,&end);
306:   VecGetArrayRead(D,&v);
307:   for (i=start; i<end; i++) {
308:     MatSetValues(Y,1,&i,1,&i,v+i-start,is);
309:   }
310:   VecRestoreArrayRead(D,&v);
311:   MatAssemblyBegin(Y,MAT_FINAL_ASSEMBLY);
312:   MatAssemblyEnd(Y,MAT_FINAL_ASSEMBLY);
313:   return 0;
314: }

316: /*@
317:    MatDiagonalSet - Computes Y = Y + D, where D is a diagonal matrix
318:    that is represented as a vector. Or Y[i,i] = D[i] if InsertMode is
319:    INSERT_VALUES.

321:    Neighbor-wise Collective on Mat

323:    Input Parameters:
324: +  Y - the input matrix
325: .  D - the diagonal matrix, represented as a vector
326: -  i - INSERT_VALUES or ADD_VALUES

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

333:    Level: intermediate

335: .seealso: MatShift(), MatScale(), MatDiagonalScale()
336: @*/
337: PetscErrorCode  MatDiagonalSet(Mat Y,Vec D,InsertMode is)
338: {
339:   PetscInt       matlocal,veclocal;

343:   MatGetLocalSize(Y,&matlocal,NULL);
344:   VecGetLocalSize(D,&veclocal);
346:   if (Y->ops->diagonalset) {
347:     (*Y->ops->diagonalset)(Y,D,is);
348:   } else {
349:     MatDiagonalSet_Default(Y,D,is);
350:   }
351:   PetscObjectStateIncrease((PetscObject)Y);
352:   return 0;
353: }

355: /*@
356:    MatAYPX - Computes Y = a*Y + X.

358:    Logically on Mat

360:    Input Parameters:
361: +  a - the PetscScalar multiplier
362: .  Y - the first matrix
363: .  X - the second matrix
364: -  str - either SAME_NONZERO_PATTERN, DIFFERENT_NONZERO_PATTERN, UNKNOWN_NONZERO_PATTERN, or SUBSET_NONZERO_PATTERN (nonzeros of X is a subset of Y's)

366:    Level: intermediate

368: .seealso: MatAXPY()
369:  @*/
370: PetscErrorCode  MatAYPX(Mat Y,PetscScalar a,Mat X,MatStructure str)
371: {
372:   MatScale(Y,a);
373:   MatAXPY(Y,1.0,X,str);
374:   return 0;
375: }

377: /*@
378:     MatComputeOperator - Computes the explicit matrix

380:     Collective on Mat

382:     Input Parameters:
383: +   inmat - the matrix
384: -   mattype - the matrix type for the explicit operator

386:     Output Parameter:
387: .   mat - the explicit  operator

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

394:     Level: advanced

396: @*/
397: PetscErrorCode  MatComputeOperator(Mat inmat,MatType mattype,Mat *mat)
398: {
401:   MatConvert_Shell(inmat,mattype ? mattype : MATDENSE,MAT_INITIAL_MATRIX,mat);
402:   return 0;
403: }

405: /*@
406:     MatComputeOperatorTranspose - Computes the explicit matrix representation of
407:         a give matrix that can apply MatMultTranspose()

409:     Collective on Mat

411:     Input Parameters:
412: +   inmat - the matrix
413: -   mattype - the matrix type for the explicit operator

415:     Output Parameter:
416: .   mat - the explicit  operator transposed

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

423:     Level: advanced

425: @*/
426: PetscErrorCode  MatComputeOperatorTranspose(Mat inmat,MatType mattype,Mat *mat)
427: {
428:   Mat            A;

432:   MatCreateTranspose(inmat,&A);
433:   MatConvert_Shell(A,mattype ? mattype : MATDENSE,MAT_INITIAL_MATRIX,mat);
434:   MatDestroy(&A);
435:   return 0;
436: }

438: /*@
439:   MatChop - Set all values in the matrix less than the tolerance to zero

441:   Input Parameters:
442: + A   - The matrix
443: - tol - The zero tolerance

445:   Output Parameters:
446: . A - The chopped matrix

448:   Level: intermediate

450: .seealso: MatCreate(), MatZeroEntries()
451:  @*/
452: PetscErrorCode MatChop(Mat A, PetscReal tol)
453: {
454:   Mat            a;
455:   PetscScalar    *newVals;
456:   PetscInt       *newCols, rStart, rEnd, numRows, maxRows, r, colMax = 0;
457:   PetscBool      flg;

459:   PetscObjectBaseTypeCompareAny((PetscObject)A, &flg, MATSEQDENSE, MATMPIDENSE, "");
460:   if (flg) {
461:     MatDenseGetLocalMatrix(A, &a);
462:     MatDenseGetLDA(a, &r);
463:     MatGetSize(a, &rStart, &rEnd);
464:     MatDenseGetArray(a, &newVals);
465:     for (; colMax < rEnd; ++colMax) {
466:       for (maxRows = 0; maxRows < rStart; ++maxRows) {
467:         newVals[maxRows + colMax * r] = PetscAbsScalar(newVals[maxRows + colMax * r]) < tol ? 0.0 : newVals[maxRows + colMax * r];
468:       }
469:     }
470:     MatDenseRestoreArray(a, &newVals);
471:   } else {
472:     MatGetOwnershipRange(A, &rStart, &rEnd);
473:     MatGetRowUpperTriangular(A);
474:     for (r = rStart; r < rEnd; ++r) {
475:       PetscInt ncols;

477:       MatGetRow(A, r, &ncols, NULL, NULL);
478:       colMax = PetscMax(colMax, ncols);
479:       MatRestoreRow(A, r, &ncols, NULL, NULL);
480:     }
481:     numRows = rEnd - rStart;
482:     MPIU_Allreduce(&numRows, &maxRows, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)A));
483:     PetscMalloc2(colMax, &newCols, colMax, &newVals);
484:     MatGetOption(A, MAT_NO_OFF_PROC_ENTRIES, &flg); /* cache user-defined value */
485:     MatSetOption(A, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE);
486:     /* short-circuit code in MatAssemblyBegin() and MatAssemblyEnd()             */
487:     /* that are potentially called many times depending on the distribution of A */
488:     for (r = rStart; r < rStart+maxRows; ++r) {
489:       const PetscScalar *vals;
490:       const PetscInt    *cols;
491:       PetscInt           ncols, newcols, c;

493:       if (r < rEnd) {
494:         MatGetRow(A, r, &ncols, &cols, &vals);
495:         for (c = 0; c < ncols; ++c) {
496:           newCols[c] = cols[c];
497:           newVals[c] = PetscAbsScalar(vals[c]) < tol ? 0.0 : vals[c];
498:         }
499:         newcols = ncols;
500:         MatRestoreRow(A, r, &ncols, &cols, &vals);
501:         MatSetValues(A, 1, &r, newcols, newCols, newVals, INSERT_VALUES);
502:       }
503:       MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
504:       MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
505:     }
506:     MatRestoreRowUpperTriangular(A);
507:     PetscFree2(newCols, newVals);
508:     MatSetOption(A, MAT_NO_OFF_PROC_ENTRIES, flg); /* reset option to its user-defined value */
509:   }
510:   return 0;
511: }