Actual source code: axpy.c

petsc-3.6.1 2015-07-22
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  2: #include <petsc/private/matimpl.h>  /*I   "petscmat.h"  I*/

  6: /*@
  7:    MatAXPY - Computes Y = a*X + Y.

  9:    Logically  Collective on Mat

 11:    Input Parameters:
 12: +  a - the scalar multiplier
 13: .  X - the first matrix
 14: .  Y - the second matrix
 15: -  str - either SAME_NONZERO_PATTERN, DIFFERENT_NONZERO_PATTERN
 16:          or SUBSET_NONZERO_PATTERN (nonzeros of X is a subset of Y's)

 18:    Level: intermediate

 20: .keywords: matrix, add

 22: .seealso: MatAYPX()
 23:  @*/
 24: PetscErrorCode MatAXPY(Mat Y,PetscScalar a,Mat X,MatStructure str)
 25: {
 27:   PetscInt       m1,m2,n1,n2;

 33:   MatGetSize(X,&m1,&n1);
 34:   MatGetSize(Y,&m2,&n2);
 35:   if (m1 != m2 || n1 != n2) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Non conforming matrix add: %D %D %D %D",m1,m2,n1,n2);

 37:   PetscLogEventBegin(MAT_AXPY,Y,0,0,0);
 38:   if (Y->ops->axpy) {
 39:     (*Y->ops->axpy)(Y,a,X,str);
 40:   } else {
 41:     MatAXPY_Basic(Y,a,X,str);
 42:   }
 43:   PetscLogEventEnd(MAT_AXPY,Y,0,0,0);
 44: #if defined(PETSC_HAVE_CUSP)
 45:   if (Y->valid_GPU_matrix != PETSC_CUSP_UNALLOCATED) {
 46:     Y->valid_GPU_matrix = PETSC_CUSP_CPU;
 47:   }
 48: #endif
 49: #if defined(PETSC_HAVE_VIENNACL)
 50:   if (Y->valid_GPU_matrix != PETSC_VIENNACL_UNALLOCATED) {
 51:     Y->valid_GPU_matrix = PETSC_VIENNACL_CPU;
 52:   }
 53: #endif
 54:   return(0);
 55: }

 59: PetscErrorCode MatAXPY_Basic(Mat Y,PetscScalar a,Mat X,MatStructure str)
 60: {
 61:   PetscInt          i,start,end,j,ncols,m,n;
 62:   PetscErrorCode    ierr;
 63:   const PetscInt    *row;
 64:   PetscScalar       *val;
 65:   const PetscScalar *vals;

 68:   MatGetSize(X,&m,&n);
 69:   MatGetOwnershipRange(X,&start,&end);
 70:   if (a == 1.0) {
 71:     for (i = start; i < end; i++) {
 72:       MatGetRow(X,i,&ncols,&row,&vals);
 73:       MatSetValues(Y,1,&i,ncols,row,vals,ADD_VALUES);
 74:       MatRestoreRow(X,i,&ncols,&row,&vals);
 75:     }
 76:   } else {
 77:     PetscMalloc1(n+1,&val);
 78:     for (i=start; i<end; i++) {
 79:       MatGetRow(X,i,&ncols,&row,&vals);
 80:       for (j=0; j<ncols; j++) {
 81:         val[j] = a*vals[j];
 82:       }
 83:       MatSetValues(Y,1,&i,ncols,row,val,ADD_VALUES);
 84:       MatRestoreRow(X,i,&ncols,&row,&vals);
 85:     }
 86:     PetscFree(val);
 87:   }
 88:   MatAssemblyBegin(Y,MAT_FINAL_ASSEMBLY);
 89:   MatAssemblyEnd(Y,MAT_FINAL_ASSEMBLY);
 90:   return(0);
 91: }

 95: PetscErrorCode MatAXPY_BasicWithPreallocation(Mat B,Mat Y,PetscScalar a,Mat X,MatStructure str)
 96: {
 97:   PetscInt          i,start,end,j,ncols,m,n;
 98:   PetscErrorCode    ierr;
 99:   const PetscInt    *row;
100:   PetscScalar       *val;
101:   const PetscScalar *vals;

104:   MatGetSize(X,&m,&n);
105:   MatGetOwnershipRange(X,&start,&end);
106:   if (a == 1.0) {
107:     for (i = start; i < end; i++) {
108:       MatGetRow(Y,i,&ncols,&row,&vals);
109:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
110:       MatRestoreRow(Y,i,&ncols,&row,&vals);

112:       MatGetRow(X,i,&ncols,&row,&vals);
113:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
114:       MatRestoreRow(X,i,&ncols,&row,&vals);
115:     }
116:   } else {
117:     PetscMalloc1(n+1,&val);
118:     for (i=start; i<end; i++) {
119:       MatGetRow(Y,i,&ncols,&row,&vals);
120:       MatSetValues(B,1,&i,ncols,row,vals,ADD_VALUES);
121:       MatRestoreRow(Y,i,&ncols,&row,&vals);

123:       MatGetRow(X,i,&ncols,&row,&vals);
124:       for (j=0; j<ncols; j++) {
125:         val[j] = a*vals[j];
126:       }
127:       MatSetValues(B,1,&i,ncols,row,val,ADD_VALUES);
128:       MatRestoreRow(X,i,&ncols,&row,&vals);
129:     }
130:     PetscFree(val);
131:   }
132:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
133:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
134:   return(0);
135: }

139: /*@
140:    MatShift - Computes Y =  Y + a I, where a is a PetscScalar and I is the identity matrix.

142:    Neighbor-wise Collective on Mat

144:    Input Parameters:
145: +  Y - the matrices
146: -  a - the PetscScalar

148:    Level: intermediate

150: .keywords: matrix, add, shift

152: .seealso: MatDiagonalSet()
153:  @*/
154: PetscErrorCode  MatShift(Mat Y,PetscScalar a)
155: {

160:   if (!Y->assembled) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
161:   if (Y->factortype) SETERRQ(PetscObjectComm((PetscObject)Y),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
162:   MatCheckPreallocated(Y,1);

164:   (*Y->ops->shift)(Y,a);

166: #if defined(PETSC_HAVE_CUSP)
167:   if (Y->valid_GPU_matrix != PETSC_CUSP_UNALLOCATED) {
168:     Y->valid_GPU_matrix = PETSC_CUSP_CPU;
169:   }
170: #endif
171: #if defined(PETSC_HAVE_VIENNACL)
172:   if (Y->valid_GPU_matrix != PETSC_VIENNACL_UNALLOCATED) {
173:     Y->valid_GPU_matrix = PETSC_VIENNACL_CPU;
174:   }
175: #endif
176:   return(0);
177: }

181: PetscErrorCode  MatDiagonalSet_Default(Mat Y,Vec D,InsertMode is)
182: {
184:   PetscInt       i,start,end;
185:   PetscScalar    *v;

188:   MatGetOwnershipRange(Y,&start,&end);
189:   VecGetArray(D,&v);
190:   for (i=start; i<end; i++) {
191:     MatSetValues(Y,1,&i,1,&i,v+i-start,is);
192:   }
193:   VecRestoreArray(D,&v);
194:   MatAssemblyBegin(Y,MAT_FINAL_ASSEMBLY);
195:   MatAssemblyEnd(Y,MAT_FINAL_ASSEMBLY);
196:   return(0);
197: }

201: /*@
202:    MatDiagonalSet - Computes Y = Y + D, where D is a diagonal matrix
203:    that is represented as a vector. Or Y[i,i] = D[i] if InsertMode is
204:    INSERT_VALUES.

206:    Input Parameters:
207: +  Y - the input matrix
208: .  D - the diagonal matrix, represented as a vector
209: -  i - INSERT_VALUES or ADD_VALUES

211:    Neighbor-wise Collective on Mat and Vec

213:    Level: intermediate

215: .keywords: matrix, add, shift, diagonal

217: .seealso: MatShift()
218: @*/
219: PetscErrorCode  MatDiagonalSet(Mat Y,Vec D,InsertMode is)
220: {
222:   PetscInt       matlocal,veclocal;

227:   MatGetLocalSize(Y,&matlocal,NULL);
228:   VecGetLocalSize(D,&veclocal);
229:   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);
230:   if (Y->ops->diagonalset) {
231:     (*Y->ops->diagonalset)(Y,D,is);
232:   } else {
233:     MatDiagonalSet_Default(Y,D,is);
234:   }
235:   return(0);
236: }

240: /*@
241:    MatAYPX - Computes Y = a*Y + X.

243:    Logically on Mat

245:    Input Parameters:
246: +  a - the PetscScalar multiplier
247: .  Y - the first matrix
248: .  X - the second matrix
249: -  str - either SAME_NONZERO_PATTERN, DIFFERENT_NONZERO_PATTERN or SUBSET_NONZERO_PATTERN

251:    Level: intermediate

253: .keywords: matrix, add

255: .seealso: MatAXPY()
256:  @*/
257: PetscErrorCode  MatAYPX(Mat Y,PetscScalar a,Mat X,MatStructure str)
258: {
259:   PetscScalar    one = 1.0;
261:   PetscInt       mX,mY,nX,nY;

267:   MatGetSize(X,&mX,&nX);
268:   MatGetSize(X,&mY,&nY);
269:   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);

271:   MatScale(Y,a);
272:   MatAXPY(Y,one,X,str);
273:   return(0);
274: }

278: /*@
279:     MatComputeExplicitOperator - Computes the explicit matrix

281:     Collective on Mat

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

286:     Output Parameter:
287: .   mat - the explict preconditioned operator

289:     Notes:
290:     This computation is done by applying the operators to columns of the
291:     identity matrix.

293:     Currently, this routine uses a dense matrix format when 1 processor
294:     is used and a sparse format otherwise.  This routine is costly in general,
295:     and is recommended for use only with relatively small systems.

297:     Level: advanced

299: .keywords: Mat, compute, explicit, operator
300: @*/
301: PetscErrorCode  MatComputeExplicitOperator(Mat inmat,Mat *mat)
302: {
303:   Vec            in,out;
305:   PetscInt       i,m,n,M,N,*rows,start,end;
306:   MPI_Comm       comm;
307:   PetscScalar    *array,zero = 0.0,one = 1.0;
308:   PetscMPIInt    size;


314:   PetscObjectGetComm((PetscObject)inmat,&comm);
315:   MPI_Comm_size(comm,&size);

317:   MatGetLocalSize(inmat,&m,&n);
318:   MatGetSize(inmat,&M,&N);
319:   MatCreateVecs(inmat,&in,&out);
320:   VecSetOption(in,VEC_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE);
321:   VecGetOwnershipRange(out,&start,&end);
322:   PetscMalloc1(m,&rows);
323:   for (i=0; i<m; i++) rows[i] = start + i;

325:   MatCreate(comm,mat);
326:   MatSetSizes(*mat,m,n,M,N);
327:   if (size == 1) {
328:     MatSetType(*mat,MATSEQDENSE);
329:     MatSeqDenseSetPreallocation(*mat,NULL);
330:   } else {
331:     MatSetType(*mat,MATMPIAIJ);
332:     MatMPIAIJSetPreallocation(*mat,n,NULL,N-n,NULL);
333:   }

335:   for (i=0; i<N; i++) {

337:     VecSet(in,zero);
338:     VecSetValues(in,1,&i,&one,INSERT_VALUES);
339:     VecAssemblyBegin(in);
340:     VecAssemblyEnd(in);

342:     MatMult(inmat,in,out);

344:     VecGetArray(out,&array);
345:     MatSetValues(*mat,m,rows,1,&i,array,INSERT_VALUES);
346:     VecRestoreArray(out,&array);

348:   }
349:   PetscFree(rows);
350:   VecDestroy(&out);
351:   VecDestroy(&in);
352:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
353:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
354:   return(0);
355: }

359: /*@
360:   MatChop - Set all values in the matrix less than the tolerance to zero

362:   Input Parameters:
363: + A   - The matrix
364: - tol - The zero tolerance

366:   Output Parameters:
367: . A - The chopped matrix

369:   Level: intermediate

371: .seealso: MatCreate(), MatZeroEntries()
372:  @*/
373: PetscErrorCode MatChop(Mat A, PetscReal tol)
374: {
375:   PetscScalar    *newVals;
376:   PetscInt       *newCols;
377:   PetscInt       rStart, rEnd, numRows, maxRows, r, colMax = 0;

381:   MatGetOwnershipRange(A, &rStart, &rEnd);
382:   for (r = rStart; r < rEnd; ++r) {
383:     PetscInt ncols;

385:     MatGetRow(A, r, &ncols, NULL, NULL);
386:     colMax = PetscMax(colMax, ncols);
387:     MatRestoreRow(A, r, &ncols, NULL, NULL);
388:   }
389:   numRows = rEnd - rStart;
390:   MPI_Allreduce(&numRows, &maxRows, 1, MPIU_INT, MPI_MAX, PetscObjectComm((PetscObject)A));
391:   PetscMalloc2(colMax,&newCols,colMax,&newVals);
392:   for (r = rStart; r < rStart+maxRows; ++r) {
393:     const PetscScalar *vals;
394:     const PetscInt    *cols;
395:     PetscInt           ncols, newcols, c;

397:     if (r < rEnd) {
398:       MatGetRow(A, r, &ncols, &cols, &vals);
399:       for (c = 0; c < ncols; ++c) {
400:         newCols[c] = cols[c];
401:         newVals[c] = PetscAbsScalar(vals[c]) < tol ? 0.0 : vals[c];
402:       }
403:       newcols = ncols;
404:       MatRestoreRow(A, r, &ncols, &cols, &vals);
405:       MatSetValues(A, 1, &r, newcols, newCols, newVals, INSERT_VALUES);
406:     }
407:     MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
408:     MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
409:   }
410:   PetscFree2(newCols,newVals);
411:   return(0);
412: }