Date: 2022-03-31T04:47:21+00:00

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: }