Date: 2026-03-31T05:46:18+00:00

Actual source code: mmaij.c

      1: /*
      2:    Support for the parallel AIJ matrix vector multiply
      3: */
      4: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      5: #include <petsc/private/vecimpl.h>
      6: #include <petsc/private/isimpl.h>

      8: PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat mat)
      9: {
     10:   Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data;
     11:   Mat_SeqAIJ *B   = (Mat_SeqAIJ *)aij->B->data;
     12:   PetscInt    i, j, *aj = B->j, *garray;
     13:   PetscInt    ec = 0; /* Number of nonzero external columns */
     14:   IS          from, to;
     15:   Vec         gvec;
     16: #if defined(PETSC_USE_CTABLE)
     17:   PetscHMapI    gid1_lid1 = NULL;
     18:   PetscHashIter tpos;
     19:   PetscInt      gid, lid;
     20: #else
     21:   PetscInt N = mat->cmap->N, *indices;
     22: #endif

     24:   PetscFunctionBegin;
     25:   if (!aij->garray) {
     26:     PetscCheck(aij->B, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing B mat");
     27: #if defined(PETSC_USE_CTABLE)
     28:     /* use a table */
     29:     PetscCall(PetscHMapICreateWithSize(aij->B->rmap->n, &gid1_lid1));
     30:     for (i = 0; i < aij->B->rmap->n; i++) {
     31:       for (j = 0; j < B->ilen[i]; j++) {
     32:         PetscInt data, gid1 = aj[B->i[i] + j] + 1;
     33:         PetscCall(PetscHMapIGetWithDefault(gid1_lid1, gid1, 0, &data));
     34:         if (!data) {
     35:           /* one based table */
     36:           PetscCall(PetscHMapISet(gid1_lid1, gid1, ++ec));
     37:         }
     38:       }
     39:     }
     40:     /* form array of columns we need */
     41:     PetscCall(PetscMalloc1(ec, &garray));
     42:     PetscHashIterBegin(gid1_lid1, tpos);
     43:     while (!PetscHashIterAtEnd(gid1_lid1, tpos)) {
     44:       PetscHashIterGetKey(gid1_lid1, tpos, gid);
     45:       PetscHashIterGetVal(gid1_lid1, tpos, lid);
     46:       PetscHashIterNext(gid1_lid1, tpos);
     47:       gid--;
     48:       lid--;
     49:       garray[lid] = gid;
     50:     }
     51:     PetscCall(PetscSortInt(ec, garray)); /* sort, and rebuild */
     52:     PetscCall(PetscHMapIClear(gid1_lid1));
     53:     for (i = 0; i < ec; i++) PetscCall(PetscHMapISet(gid1_lid1, garray[i] + 1, i + 1));
     54:     /* compact out the extra columns in B */
     55:     for (i = 0; i < aij->B->rmap->n; i++) {
     56:       for (j = 0; j < B->ilen[i]; j++) {
     57:         PetscInt gid1 = aj[B->i[i] + j] + 1;
     58:         PetscCall(PetscHMapIGetWithDefault(gid1_lid1, gid1, 0, &lid));
     59:         lid--;
     60:         aj[B->i[i] + j] = lid;
     61:       }
     62:     }
     63:     PetscCall(PetscLayoutDestroy(&aij->B->cmap));
     64:     PetscCall(PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)aij->B), ec, ec, 1, &aij->B->cmap));
     65:     PetscCall(PetscHMapIDestroy(&gid1_lid1));
     66: #else
     67:     /* Make an array as long as the number of columns */
     68:     /* mark those columns that are in aij->B */
     69:     PetscCall(PetscCalloc1(N, &indices));
     70:     for (i = 0; i < aij->B->rmap->n; i++) {
     71:       for (j = 0; j < B->ilen[i]; j++) {
     72:         if (!indices[aj[B->i[i] + j]]) ec++;
     73:         indices[aj[B->i[i] + j]] = 1;
     74:       }
     75:     }

     77:     /* form array of columns we need */
     78:     PetscCall(PetscMalloc1(ec, &garray));
     79:     ec = 0;
     80:     for (i = 0; i < N; i++) {
     81:       if (indices[i]) garray[ec++] = i;
     82:     }

     84:     /* make indices now point into garray */
     85:     for (i = 0; i < ec; i++) indices[garray[i]] = i;

     87:     /* compact out the extra columns in B */
     88:     for (i = 0; i < aij->B->rmap->n; i++) {
     89:       for (j = 0; j < B->ilen[i]; j++) aj[B->i[i] + j] = indices[aj[B->i[i] + j]];
     90:     }
     91:     PetscCall(PetscLayoutDestroy(&aij->B->cmap));
     92:     PetscCall(PetscLayoutCreateFromSizes(PetscObjectComm((PetscObject)aij->B), ec, ec, 1, &aij->B->cmap));
     93:     PetscCall(PetscFree(indices));
     94: #endif
     95:   } else {
     96:     garray = aij->garray;
     97:   }

     99:   if (!aij->lvec) {
    100:     PetscCheck(aij->B, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Missing B mat");
    101:     PetscCall(MatCreateVecs(aij->B, &aij->lvec, NULL));
    102:   }
    103:   PetscCall(VecGetSize(aij->lvec, &ec));

    105:   /* create two temporary Index sets for build scatter gather */
    106:   PetscCall(ISCreateGeneral(PETSC_COMM_SELF, ec, garray, PETSC_COPY_VALUES, &from));
    107:   PetscCall(ISCreateStride(PETSC_COMM_SELF, ec, 0, 1, &to));

    109:   /* create temporary global vector to generate scatter context */
    110:   /* This does not allocate the array's memory so is efficient */
    111:   PetscCall(VecCreateMPIWithArray(PetscObjectComm((PetscObject)mat), 1, mat->cmap->n, mat->cmap->N, NULL, &gvec));

    113:   /* generate the scatter context */
    114:   PetscCall(VecScatterDestroy(&aij->Mvctx));
    115:   PetscCall(VecScatterCreate(gvec, from, aij->lvec, to, &aij->Mvctx));
    116:   PetscCall(VecScatterViewFromOptions(aij->Mvctx, (PetscObject)mat, "-matmult_vecscatter_view"));
    117:   aij->garray = garray;

    119:   PetscCall(ISDestroy(&from));
    120:   PetscCall(ISDestroy(&to));
    121:   PetscCall(VecDestroy(&gvec));
    122:   PetscFunctionReturn(PETSC_SUCCESS);
    123: }

    125: /* Disassemble the off-diag portion of the MPIAIJXxx matrix.
    126:    In other words, change the B from reduced format using local col ids
    127:    to expanded format using global col ids, which will make it easier to
    128:    insert new nonzeros (with global col ids) into the matrix.
    129:    The off-diag B determines communication in the matrix vector multiply.
    130:    use_preallocation determines whether the use the preallocation or
    131:    existing non-zero structure when creating the global form of B
    132: */
    133: PetscErrorCode MatDisAssemble_MPIAIJ(Mat A, PetscBool use_preallocation)
    134: {
    135:   Mat_MPIAIJ *aij = (Mat_MPIAIJ *)A->data;
    136:   Mat         B = aij->B, Bnew = NULL;

    138:   PetscFunctionBegin;
    139:   /* free stuff related to matrix-vec multiply */
    140:   PetscCall(VecDestroy(&aij->lvec));
    141:   if (aij->colmap) {
    142: #if defined(PETSC_USE_CTABLE)
    143:     PetscCall(PetscHMapIDestroy(&aij->colmap));
    144: #else
    145:     PetscCall(PetscFree(aij->colmap));
    146: #endif
    147:   }

    149:   if (B) {
    150:     Mat_SeqAIJ        *Baij = (Mat_SeqAIJ *)B->data;
    151:     PetscInt           i, j, m = B->rmap->n, n = A->cmap->N, col, ct = 0, *garray = aij->garray, *nz;
    152:     PetscScalar        v;
    153:     const PetscScalar *ba;

    155:     /* make sure that B is assembled so we can access its values */
    156:     PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
    157:     PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));

    159:     /* invent new B and copy stuff over */
    160:     PetscCall(PetscMalloc1(m + 1, &nz));
    161:     if (use_preallocation)
    162:       for (i = 0; i < m; i++) nz[i] = Baij->ipre[i];
    163:     else
    164:       for (i = 0; i < m; i++) nz[i] = Baij->i[i + 1] - Baij->i[i];
    165:     PetscCall(MatCreate(PETSC_COMM_SELF, &Bnew));
    166:     PetscCall(MatSetSizes(Bnew, m, n, m, n)); /* Bnew now uses A->cmap->N as its col size */
    167:     PetscCall(MatSetBlockSizesFromMats(Bnew, A, A));
    168:     PetscCall(MatSetType(Bnew, ((PetscObject)B)->type_name));
    169:     PetscCall(MatSeqAIJSetPreallocation(Bnew, 0, nz));

    171:     if (Baij->nonew >= 0) { /* Inherit insertion error options (if positive). */
    172:       ((Mat_SeqAIJ *)Bnew->data)->nonew = Baij->nonew;
    173:     }

    175:     /*
    176:      Ensure that B's nonzerostate is monotonically increasing.
    177:      Or should this follow the MatSetValues() loop to preserve B's nonzerstate across a MatDisAssemble() call?
    178:      */
    179:     Bnew->nonzerostate = B->nonzerostate;

    181:     PetscCall(PetscFree(nz));
    182:     PetscCall(MatSeqAIJGetArrayRead(B, &ba));
    183:     for (i = 0; i < m; i++) {
    184:       for (j = Baij->i[i]; j < Baij->i[i + 1]; j++) {
    185:         col = garray[Baij->j[ct]];
    186:         v   = ba[ct++];
    187:         PetscCall(MatSetValues(Bnew, 1, &i, 1, &col, &v, B->insertmode));
    188:       }
    189:     }
    190:     PetscCall(MatSeqAIJRestoreArrayRead(B, &ba));
    191:     PetscCall(MatDestroy(&B));
    192:   }
    193:   PetscCall(PetscFree(aij->garray));

    195:   aij->B           = Bnew;
    196:   A->was_assembled = PETSC_FALSE;
    197:   A->assembled     = PETSC_FALSE;
    198:   PetscFunctionReturn(PETSC_SUCCESS);
    199: }

    201: /*      ugly stuff added for Glenn someday we should fix this up */

    203: static PetscInt *auglyrmapd = NULL, *auglyrmapo = NULL; /* mapping from the local ordering to the "diagonal" and "off-diagonal" parts of the local matrix */
    204: static Vec       auglydd = NULL, auglyoo = NULL;        /* work vectors used to scale the two parts of the local matrix */

    206: static PetscErrorCode MatMPIAIJDiagonalScaleLocalSetUp(Mat inA, Vec scale)
    207: {
    208:   Mat_MPIAIJ *ina = (Mat_MPIAIJ *)inA->data; /*access private part of matrix */
    209:   PetscInt    i, j, n, nt, cstart, cend, no, *garray = ina->garray, *lindices, bs = inA->rmap->bs;
    210:   PetscInt   *r_rmapd, *r_rmapo;

    212:   PetscFunctionBegin;
    213:   PetscCall(MatGetOwnershipRange(inA, &cstart, &cend));
    214:   PetscCall(MatGetSize(ina->A, NULL, &n));
    215:   PetscCall(PetscCalloc1(inA->rmap->mapping->n, &r_rmapd));
    216:   nt = 0;
    217:   for (i = 0; i < inA->rmap->mapping->n; i++) {
    218:     if (inA->rmap->mapping->indices[i] * bs >= cstart && inA->rmap->mapping->indices[i] * bs < cend) {
    219:       nt++;
    220:       r_rmapd[i] = inA->rmap->mapping->indices[i] + 1;
    221:     }
    222:   }
    223:   PetscCheck(nt * bs == n, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Hmm nt*bs %" PetscInt_FMT " n %" PetscInt_FMT, nt * bs, n);
    224:   PetscCall(PetscMalloc1(n, &auglyrmapd));
    225:   for (i = 0; i < inA->rmap->mapping->n; i++) {
    226:     if (r_rmapd[i]) {
    227:       for (j = 0; j < bs; j++) auglyrmapd[(r_rmapd[i] - 1) * bs + j - cstart] = i * bs + j;
    228:     }
    229:   }
    230:   PetscCall(PetscFree(r_rmapd));
    231:   PetscCall(VecCreateSeq(PETSC_COMM_SELF, n, &auglydd));

    233:   /* This loop handling the setup for the off-diagonal local portion of the matrix is extremely similar to
    234:      its counterpart in the MPIBAIJ version of this code.
    235:      The tricky difference is that lindices[] uses block-based indexing (just as in the BAIJ code),
    236:      but garray[] uses element-based indexing; hence the multiplications / divisions involving bs. */
    237:   PetscCall(PetscCalloc1(inA->cmap->N / bs, &lindices));
    238:   for (i = 0; i < ina->B->cmap->n / bs; i++) lindices[garray[i * bs] / bs] = i + 1;
    239:   no = inA->rmap->mapping->n - nt;
    240:   PetscCall(PetscCalloc1(inA->rmap->mapping->n, &r_rmapo));
    241:   nt = 0;
    242:   for (i = 0; i < inA->rmap->mapping->n; i++) {
    243:     if (lindices[inA->rmap->mapping->indices[i]]) {
    244:       nt++;
    245:       r_rmapo[i] = lindices[inA->rmap->mapping->indices[i]];
    246:     }
    247:   }
    248:   PetscCheck(nt <= no, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Hmm nt %" PetscInt_FMT " no %" PetscInt_FMT, nt, n);
    249:   PetscCall(PetscFree(lindices));
    250:   PetscCall(PetscMalloc1(nt * bs, &auglyrmapo));
    251:   for (i = 0; i < inA->rmap->mapping->n; i++) {
    252:     if (r_rmapo[i]) {
    253:       for (j = 0; j < bs; j++) auglyrmapo[(r_rmapo[i] - 1) * bs + j] = i * bs + j;
    254:     }
    255:   }
    256:   PetscCall(PetscFree(r_rmapo));
    257:   PetscCall(VecCreateSeq(PETSC_COMM_SELF, nt * bs, &auglyoo));
    258:   PetscFunctionReturn(PETSC_SUCCESS);
    259: }

    261: PetscErrorCode MatDiagonalScaleLocal_MPIAIJ(Mat A, Vec scale)
    262: {
    263:   Mat_MPIAIJ        *a = (Mat_MPIAIJ *)A->data; /*access private part of matrix */
    264:   PetscInt           n, i;
    265:   PetscScalar       *d, *o;
    266:   const PetscScalar *s;

    268:   PetscFunctionBegin;
    269:   if (!auglyrmapd) PetscCall(MatMPIAIJDiagonalScaleLocalSetUp(A, scale));

    271:   PetscCall(VecGetArrayRead(scale, &s));

    273:   PetscCall(VecGetLocalSize(auglydd, &n));
    274:   PetscCall(VecGetArray(auglydd, &d));
    275:   for (i = 0; i < n; i++) d[i] = s[auglyrmapd[i]]; /* copy "diagonal" (true local) portion of scale into dd vector */
    276:   PetscCall(VecRestoreArray(auglydd, &d));
    277:   /* column scale "diagonal" portion of local matrix */
    278:   PetscCall(MatDiagonalScale(a->A, NULL, auglydd));

    280:   PetscCall(VecGetLocalSize(auglyoo, &n));
    281:   PetscCall(VecGetArray(auglyoo, &o));
    282:   for (i = 0; i < n; i++) o[i] = s[auglyrmapo[i]]; /* copy "off-diagonal" portion of scale into oo vector */
    283:   PetscCall(VecRestoreArrayRead(scale, &s));
    284:   PetscCall(VecRestoreArray(auglyoo, &o));
    285:   /* column scale "off-diagonal" portion of local matrix */
    286:   PetscCall(MatDiagonalScale(a->B, NULL, auglyoo));
    287:   PetscCall(PetscFree(auglyrmapd));
    288:   PetscCall(PetscFree(auglyrmapo));
    289:   PetscCall(VecDestroy(&auglydd));
    290:   PetscCall(VecDestroy(&auglyoo));
    291:   PetscFunctionReturn(PETSC_SUCCESS);
    292: }