Actual source code: iscoloring.c

      1: #include <petsc/private/isimpl.h>
      2: #include <petscviewer.h>
      3: #include <petscsf.h>

      5: const char *const ISColoringTypes[] = {"global", "ghosted", "ISColoringType", "IS_COLORING_", NULL};

      7: PetscErrorCode ISColoringReference(ISColoring coloring)
      8: {
      9:   PetscFunctionBegin;
     10:   coloring->refct++;
     11:   PetscFunctionReturn(PETSC_SUCCESS);
     12: }

     14: /*@
     15:   ISColoringSetType - indicates if the coloring is for the local representation (including ghost points) or the global representation of a `Mat`

     17:   Collective

     19:   Input Parameters:
     20: + coloring - the coloring object
     21: - type     - either `IS_COLORING_LOCAL` or `IS_COLORING_GLOBAL`

     23:   Level: intermediate

     25:   Notes:
     26:   `IS_COLORING_LOCAL` can lead to faster computations since parallel ghost point updates are not needed for each color

     28:   With `IS_COLORING_LOCAL` the coloring is in the numbering of the local vector, for `IS_COLORING_GLOBAL` it is in the numbering of the global vector

     30: .seealso: `MatFDColoringCreate()`, `ISColoring`, `ISColoringType`, `ISColoringCreate()`, `IS_COLORING_LOCAL`, `IS_COLORING_GLOBAL`, `ISColoringGetType()`
     31: @*/
     32: PetscErrorCode ISColoringSetType(ISColoring coloring, ISColoringType type)
     33: {
     34:   PetscFunctionBegin;
     35:   coloring->ctype = type;
     36:   PetscFunctionReturn(PETSC_SUCCESS);
     37: }

     39: /*@
     40:   ISColoringGetType - gets if the coloring is for the local representation (including ghost points) or the global representation

     42:   Collective

     44:   Input Parameter:
     45: . coloring - the coloring object

     47:   Output Parameter:
     48: . type - either `IS_COLORING_LOCAL` or `IS_COLORING_GLOBAL`

     50:   Level: intermediate

     52: .seealso: `MatFDColoringCreate()`, `ISColoring`, `ISColoringType`, `ISColoringCreate()`, `IS_COLORING_LOCAL`, `IS_COLORING_GLOBAL`, `ISColoringSetType()`
     53: @*/
     54: PetscErrorCode ISColoringGetType(ISColoring coloring, ISColoringType *type)
     55: {
     56:   PetscFunctionBegin;
     57:   *type = coloring->ctype;
     58:   PetscFunctionReturn(PETSC_SUCCESS);
     59: }

     61: /*@
     62:   ISColoringDestroy - Destroys an `ISColoring` coloring context.

     64:   Collective

     66:   Input Parameter:
     67: . iscoloring - the coloring context

     69:   Level: advanced

     71: .seealso: `ISColoring`, `ISColoringView()`, `MatColoring`
     72: @*/
     73: PetscErrorCode ISColoringDestroy(ISColoring *iscoloring)
     74: {
     75:   PetscInt i;

     77:   PetscFunctionBegin;
     78:   if (!*iscoloring) PetscFunctionReturn(PETSC_SUCCESS);
     79:   PetscAssertPointer(*iscoloring, 1);
     80:   if (--(*iscoloring)->refct > 0) {
     81:     *iscoloring = NULL;
     82:     PetscFunctionReturn(PETSC_SUCCESS);
     83:   }

     85:   if ((*iscoloring)->is) {
     86:     for (i = 0; i < (*iscoloring)->n; i++) PetscCall(ISDestroy(&(*iscoloring)->is[i]));
     87:     PetscCall(PetscFree((*iscoloring)->is));
     88:   }
     89:   if ((*iscoloring)->allocated) PetscCall(PetscFree((*iscoloring)->colors));
     90:   PetscCall(PetscCommDestroy(&(*iscoloring)->comm));
     91:   PetscCall(PetscFree(*iscoloring));
     92:   PetscFunctionReturn(PETSC_SUCCESS);
     93: }

     95: /*@
     96:   ISColoringViewFromOptions - Processes command line options to determine if/how an `ISColoring` object is to be viewed.

     98:   Collective

    100:   Input Parameters:
    101: + obj  - the `ISColoring` object
    102: . bobj - prefix to use for viewing, or `NULL` to use prefix of `mat`
    103: - name - option to activate viewing

    105:   Options Database Key:
    106: . -name [viewertype][:...] - option name and values. See `PetscObjectViewFromOptions()` for the possible arguments

    108:   Level: intermediate

    110:   Developer Note:
    111:   This cannot use `PetscObjectViewFromOptions()` because `ISColoring` is not a `PetscObject`

    113: .seealso: `ISColoring`, `ISColoringView()`, `PetscObjectViewFromOptions()`
    114: @*/
    115: PetscErrorCode ISColoringViewFromOptions(ISColoring obj, PetscObject bobj, const char name[])
    116: {
    117:   PetscViewer       viewer;
    118:   PetscBool         flg;
    119:   PetscViewerFormat format;
    120:   char             *prefix;

    122:   PetscFunctionBegin;
    123:   prefix = bobj ? bobj->prefix : NULL;
    124:   PetscCall(PetscOptionsCreateViewer(obj->comm, NULL, prefix, name, &viewer, &format, &flg));
    125:   if (flg) {
    126:     PetscCall(PetscViewerPushFormat(viewer, format));
    127:     PetscCall(ISColoringView(obj, viewer));
    128:     PetscCall(PetscViewerPopFormat(viewer));
    129:     PetscCall(PetscViewerDestroy(&viewer));
    130:   }
    131:   PetscFunctionReturn(PETSC_SUCCESS);
    132: }

    134: /*@
    135:   ISColoringView - Views an `ISColoring` coloring context.

    137:   Collective

    139:   Input Parameters:
    140: + iscoloring - the coloring context
    141: - viewer     - the viewer

    143:   Level: advanced

    145: .seealso: `ISColoring()`, `ISColoringViewFromOptions()`, `ISColoringDestroy()`, `ISColoringGetIS()`, `MatColoring`
    146: @*/
    147: PetscErrorCode ISColoringView(ISColoring iscoloring, PetscViewer viewer)
    148: {
    149:   PetscInt  i;
    150:   PetscBool isascii;
    151:   IS       *is;

    153:   PetscFunctionBegin;
    154:   PetscAssertPointer(iscoloring, 1);
    155:   if (!viewer) PetscCall(PetscViewerASCIIGetStdout(iscoloring->comm, &viewer));

    158:   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii));
    159:   if (isascii) {
    160:     MPI_Comm    comm;
    161:     PetscMPIInt size, rank;

    163:     PetscCall(PetscObjectGetComm((PetscObject)viewer, &comm));
    164:     PetscCallMPI(MPI_Comm_size(comm, &size));
    165:     PetscCallMPI(MPI_Comm_rank(comm, &rank));
    166:     PetscCall(PetscViewerASCIIPrintf(viewer, "ISColoring Object: %d MPI processes\n", size));
    167:     PetscCall(PetscViewerASCIIPrintf(viewer, "ISColoringType: %s\n", ISColoringTypes[iscoloring->ctype]));
    168:     PetscCall(PetscViewerASCIIPushSynchronized(viewer));
    169:     PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Number of colors %" PetscInt_FMT "\n", rank, iscoloring->n));
    170:     PetscCall(PetscViewerFlush(viewer));
    171:     PetscCall(PetscViewerASCIIPopSynchronized(viewer));
    172:   }

    174:   PetscCall(ISColoringGetIS(iscoloring, PETSC_USE_POINTER, PETSC_IGNORE, &is));
    175:   for (i = 0; i < iscoloring->n; i++) PetscCall(ISView(iscoloring->is[i], viewer));
    176:   PetscCall(ISColoringRestoreIS(iscoloring, PETSC_USE_POINTER, &is));
    177:   PetscFunctionReturn(PETSC_SUCCESS);
    178: }

    180: /*@C
    181:   ISColoringGetColors - Returns an array with the color for each local node

    183:   Not Collective

    185:   Input Parameter:
    186: . iscoloring - the coloring context

    188:   Output Parameters:
    189: + n      - number of nodes
    190: . nc     - number of colors
    191: - colors - color for each node

    193:   Level: advanced

    195:   Notes:
    196:   Do not free the `colors` array.

    198:   The `colors` array will only be valid for the lifetime of the `ISColoring`

    200: .seealso: `ISColoring`, `ISColoringValue`, `ISColoringRestoreIS()`, `ISColoringView()`, `ISColoringGetIS()`
    201: @*/
    202: PetscErrorCode ISColoringGetColors(ISColoring iscoloring, PetscInt *n, PetscInt *nc, const ISColoringValue **colors)
    203: {
    204:   PetscFunctionBegin;
    205:   PetscAssertPointer(iscoloring, 1);

    207:   if (n) *n = iscoloring->N;
    208:   if (nc) *nc = iscoloring->n;
    209:   if (colors) *colors = iscoloring->colors;
    210:   PetscFunctionReturn(PETSC_SUCCESS);
    211: }

    213: /*@C
    214:   ISColoringGetIS - Extracts index sets from the coloring context. Each is contains the nodes of one color

    216:   Collective

    218:   Input Parameters:
    219: + iscoloring - the coloring context
    220: - mode       - if this value is `PETSC_OWN_POINTER` then the caller owns the pointer and must free the array of `IS` and each `IS` in the array

    222:   Output Parameters:
    223: + nn   - number of index sets in the coloring context
    224: - isis - array of index sets

    226:   Level: advanced

    228:   Note:
    229:   If mode is `PETSC_USE_POINTER` then `ISColoringRestoreIS()` must be called when the `IS` are no longer needed

    231: .seealso: `ISColoring`, `IS`, `ISColoringRestoreIS()`, `ISColoringView()`, `ISColoringGetColoring()`, `ISColoringGetColors()`
    232: @*/
    233: PetscErrorCode ISColoringGetIS(ISColoring iscoloring, PetscCopyMode mode, PetscInt *nn, IS *isis[])
    234: {
    235:   PetscFunctionBegin;
    236:   PetscAssertPointer(iscoloring, 1);

    238:   if (nn) *nn = iscoloring->n;
    239:   if (isis) {
    240:     if (!iscoloring->is) {
    241:       PetscInt        *mcolors, **ii, nc = iscoloring->n, i, base, n = iscoloring->N;
    242:       ISColoringValue *colors = iscoloring->colors;
    243:       IS              *is;

    245:       if (PetscDefined(USE_DEBUG)) {
    246:         for (i = 0; i < n; i++) PetscCheck(((PetscInt)colors[i]) < nc, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Coloring is our of range index %" PetscInt_FMT "value %d number colors %" PetscInt_FMT, i, (int)colors[i], nc);
    247:       }

    249:       /* generate the lists of nodes for each color */
    250:       PetscCall(PetscCalloc1(nc, &mcolors));
    251:       for (i = 0; i < n; i++) mcolors[colors[i]]++;

    253:       PetscCall(PetscMalloc1(nc, &ii));
    254:       PetscCall(PetscMalloc1(n, &ii[0]));
    255:       for (i = 1; i < nc; i++) ii[i] = ii[i - 1] + mcolors[i - 1];
    256:       PetscCall(PetscArrayzero(mcolors, nc));

    258:       if (iscoloring->ctype == IS_COLORING_GLOBAL) {
    259:         PetscCallMPI(MPI_Scan(&iscoloring->N, &base, 1, MPIU_INT, MPI_SUM, iscoloring->comm));
    260:         base -= iscoloring->N;
    261:         for (i = 0; i < n; i++) ii[colors[i]][mcolors[colors[i]]++] = i + base; /* global idx */
    262:       } else if (iscoloring->ctype == IS_COLORING_LOCAL) {
    263:         for (i = 0; i < n; i++) ii[colors[i]][mcolors[colors[i]]++] = i; /* local idx */
    264:       } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Not provided for this ISColoringType type");

    266:       PetscCall(PetscMalloc1(nc, &is));
    267:       for (i = 0; i < nc; i++) PetscCall(ISCreateGeneral(iscoloring->comm, mcolors[i], ii[i], PETSC_COPY_VALUES, is + i));

    269:       if (mode != PETSC_OWN_POINTER) iscoloring->is = is;
    270:       *isis = is;
    271:       PetscCall(PetscFree(ii[0]));
    272:       PetscCall(PetscFree(ii));
    273:       PetscCall(PetscFree(mcolors));
    274:     } else {
    275:       *isis = iscoloring->is;
    276:       if (mode == PETSC_OWN_POINTER) iscoloring->is = NULL;
    277:     }
    278:   }
    279:   PetscFunctionReturn(PETSC_SUCCESS);
    280: }

    282: /*@C
    283:   ISColoringRestoreIS - Restores the index sets extracted from the coloring context with `ISColoringGetIS()` using `PETSC_USE_POINTER`

    285:   Collective

    287:   Input Parameters:
    288: + iscoloring - the coloring context
    289: . mode       - who retains ownership of the is
    290: - is         - array of index sets

    292:   Level: advanced

    294: .seealso: `ISColoring()`, `IS`, `ISColoringGetIS()`, `ISColoringView()`, `PetscCopyMode`
    295: @*/
    296: PetscErrorCode ISColoringRestoreIS(ISColoring iscoloring, PetscCopyMode mode, IS *is[])
    297: {
    298:   PetscFunctionBegin;
    299:   PetscAssertPointer(iscoloring, 1);

    301:   /* currently nothing is done here */
    302:   PetscFunctionReturn(PETSC_SUCCESS);
    303: }

    305: /*@
    306:   ISColoringCreate - Generates an `ISColoring` context from lists (provided by each MPI process) of colors for each node.

    308:   Collective

    310:   Input Parameters:
    311: + comm    - communicator for the processors creating the coloring
    312: . ncolors - max color value
    313: . n       - number of nodes on this processor
    314: . colors  - array containing the colors for this MPI rank, color numbers begin at 0, for each local node
    315: - mode    - see `PetscCopyMode` for meaning of this flag.

    317:   Output Parameter:
    318: . iscoloring - the resulting coloring data structure

    320:   Options Database Key:
    321: . -is_coloring_view - Activates `ISColoringView()`

    323:   Level: advanced

    325:   Notes:
    326:   By default sets coloring type to  `IS_COLORING_GLOBAL`

    328: .seealso: `ISColoring`, `ISColoringValue`, `MatColoringCreate()`, `ISColoringView()`, `ISColoringDestroy()`, `ISColoringSetType()`
    329: @*/
    330: PetscErrorCode ISColoringCreate(MPI_Comm comm, PetscInt ncolors, PetscInt n, const ISColoringValue colors[], PetscCopyMode mode, ISColoring *iscoloring)
    331: {
    332:   PetscMPIInt size, rank, tag;
    333:   PetscInt    base, top, i;
    334:   PetscInt    nc, ncwork;
    335:   MPI_Status  status;

    337:   PetscFunctionBegin;
    338:   if (ncolors != PETSC_DECIDE && ncolors > IS_COLORING_MAX) {
    339:     PetscCheck(ncolors <= PETSC_UINT16_MAX, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Max color value exceeds %d limit. This number is unrealistic. Perhaps a bug in code? Current max: %d user requested: %" PetscInt_FMT, PETSC_UINT16_MAX, PETSC_IS_COLORING_MAX, ncolors);
    340:     SETERRQ(PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Max color value exceeds limit. Perhaps reconfigure PETSc with --with-is-color-value-type=short? Current max: %d user requested: %" PetscInt_FMT, PETSC_IS_COLORING_MAX, ncolors);
    341:   }
    342:   PetscCall(PetscNew(iscoloring));
    343:   PetscCall(PetscCommDuplicate(comm, &(*iscoloring)->comm, &tag));
    344:   comm = (*iscoloring)->comm;

    346:   /* compute the number of the first node on my processor */
    347:   PetscCallMPI(MPI_Comm_size(comm, &size));

    349:   /* should use MPI_Scan() */
    350:   PetscCallMPI(MPI_Comm_rank(comm, &rank));
    351:   if (rank == 0) {
    352:     base = 0;
    353:     top  = n;
    354:   } else {
    355:     PetscCallMPI(MPI_Recv(&base, 1, MPIU_INT, rank - 1, tag, comm, &status));
    356:     top = base + n;
    357:   }
    358:   if (rank < size - 1) PetscCallMPI(MPI_Send(&top, 1, MPIU_INT, rank + 1, tag, comm));

    360:   /* compute the total number of colors */
    361:   ncwork = 0;
    362:   for (i = 0; i < n; i++) {
    363:     if (ncwork < colors[i]) ncwork = colors[i];
    364:   }
    365:   ncwork++;
    366:   PetscCallMPI(MPIU_Allreduce(&ncwork, &nc, 1, MPIU_INT, MPI_MAX, comm));
    367:   PetscCheck(nc <= ncolors, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of colors passed in %" PetscInt_FMT " is less than the actual number of colors in array %" PetscInt_FMT, ncolors, nc);
    368:   (*iscoloring)->n     = nc;
    369:   (*iscoloring)->is    = NULL;
    370:   (*iscoloring)->N     = n;
    371:   (*iscoloring)->refct = 1;
    372:   (*iscoloring)->ctype = IS_COLORING_GLOBAL;
    373:   if (mode == PETSC_COPY_VALUES) {
    374:     PetscCall(PetscMalloc1(n, &(*iscoloring)->colors));
    375:     PetscCall(PetscArraycpy((*iscoloring)->colors, colors, n));
    376:     (*iscoloring)->allocated = PETSC_TRUE;
    377:   } else if (mode == PETSC_OWN_POINTER) {
    378:     (*iscoloring)->colors    = (ISColoringValue *)colors;
    379:     (*iscoloring)->allocated = PETSC_TRUE;
    380:   } else {
    381:     (*iscoloring)->colors    = (ISColoringValue *)colors;
    382:     (*iscoloring)->allocated = PETSC_FALSE;
    383:   }
    384:   PetscCall(ISColoringViewFromOptions(*iscoloring, NULL, "-is_coloring_view"));
    385:   PetscCall(PetscInfo(0, "Number of colors %" PetscInt_FMT "\n", nc));
    386:   PetscFunctionReturn(PETSC_SUCCESS);
    387: }

    389: /*@
    390:   ISBuildTwoSided - Takes an `IS` that describes where each element will be mapped globally over all ranks.
    391:   Generates an `IS` that contains new numbers from remote or local on the `IS`.

    393:   Collective

    395:   Input Parameters:
    396: + ito    - an `IS` describes to which rank each entry will be mapped. Negative target rank will be ignored
    397: - toindx - an `IS` describes what indices should send. `NULL` means sending natural numbering

    399:   Output Parameter:
    400: . rows - contains new numbers from remote or local

    402:   Level: advanced

    404:   Developer Note:
    405:   This manual page is incomprehensible and still needs to be fixed

    407: .seealso: [](sec_scatter), `IS`, `MatPartitioningCreate()`, `ISPartitioningToNumbering()`, `ISPartitioningCount()`
    408: @*/
    409: PetscErrorCode ISBuildTwoSided(IS ito, IS toindx, IS *rows)
    410: {
    411:   const PetscInt *ito_indices, *toindx_indices;
    412:   PetscInt       *send_indices, rstart, *recv_indices, nrecvs, nsends;
    413:   PetscInt       *tosizes, *fromsizes, j, *tosizes_tmp, *tooffsets_tmp, ito_ln;
    414:   PetscMPIInt    *toranks, *fromranks, size, target_rank, *fromperm_newtoold, nto, nfrom;
    415:   PetscLayout     isrmap;
    416:   MPI_Comm        comm;
    417:   PetscSF         sf;
    418:   PetscSFNode    *iremote;

    420:   PetscFunctionBegin;
    421:   PetscCall(PetscObjectGetComm((PetscObject)ito, &comm));
    422:   PetscCallMPI(MPI_Comm_size(comm, &size));
    423:   PetscCall(ISGetLocalSize(ito, &ito_ln));
    424:   PetscCall(ISGetLayout(ito, &isrmap));
    425:   PetscCall(PetscLayoutGetRange(isrmap, &rstart, NULL));
    426:   PetscCall(ISGetIndices(ito, &ito_indices));
    427:   PetscCall(PetscCalloc2(size, &tosizes_tmp, size + 1, &tooffsets_tmp));
    428:   for (PetscInt i = 0; i < ito_ln; i++) {
    429:     if (ito_indices[i] < 0) continue;
    430:     else PetscCheck(ito_indices[i] < size, comm, PETSC_ERR_ARG_OUTOFRANGE, "target rank %" PetscInt_FMT " is larger than communicator size %d ", ito_indices[i], size);
    431:     tosizes_tmp[ito_indices[i]]++;
    432:   }
    433:   nto = 0;
    434:   for (PetscMPIInt i = 0; i < size; i++) {
    435:     tooffsets_tmp[i + 1] = tooffsets_tmp[i] + tosizes_tmp[i];
    436:     if (tosizes_tmp[i] > 0) nto++;
    437:   }
    438:   PetscCall(PetscCalloc2(nto, &toranks, 2 * nto, &tosizes));
    439:   nto = 0;
    440:   for (PetscMPIInt i = 0; i < size; i++) {
    441:     if (tosizes_tmp[i] > 0) {
    442:       toranks[nto]         = i;
    443:       tosizes[2 * nto]     = tosizes_tmp[i];   /* size */
    444:       tosizes[2 * nto + 1] = tooffsets_tmp[i]; /* offset */
    445:       nto++;
    446:     }
    447:   }
    448:   nsends = tooffsets_tmp[size];
    449:   PetscCall(PetscCalloc1(nsends, &send_indices));
    450:   if (toindx) PetscCall(ISGetIndices(toindx, &toindx_indices));
    451:   for (PetscInt i = 0; i < ito_ln; i++) {
    452:     if (ito_indices[i] < 0) continue;
    453:     PetscCall(PetscMPIIntCast(ito_indices[i], &target_rank));
    454:     send_indices[tooffsets_tmp[target_rank]] = toindx ? toindx_indices[i] : (i + rstart);
    455:     tooffsets_tmp[target_rank]++;
    456:   }
    457:   if (toindx) PetscCall(ISRestoreIndices(toindx, &toindx_indices));
    458:   PetscCall(ISRestoreIndices(ito, &ito_indices));
    459:   PetscCall(PetscFree2(tosizes_tmp, tooffsets_tmp));
    460:   PetscCall(PetscCommBuildTwoSided(comm, 2, MPIU_INT, nto, toranks, tosizes, &nfrom, &fromranks, &fromsizes));
    461:   PetscCall(PetscFree2(toranks, tosizes));
    462:   PetscCall(PetscMalloc1(nfrom, &fromperm_newtoold));
    463:   for (PetscMPIInt i = 0; i < nfrom; i++) fromperm_newtoold[i] = i;
    464:   PetscCall(PetscSortMPIIntWithArray(nfrom, fromranks, fromperm_newtoold));
    465:   nrecvs = 0;
    466:   for (PetscMPIInt i = 0; i < nfrom; i++) nrecvs += fromsizes[i * 2];
    467:   PetscCall(PetscCalloc1(nrecvs, &recv_indices));
    468:   PetscCall(PetscMalloc1(nrecvs, &iremote));
    469:   nrecvs = 0;
    470:   for (PetscMPIInt i = 0; i < nfrom; i++) {
    471:     for (j = 0; j < fromsizes[2 * fromperm_newtoold[i]]; j++) {
    472:       iremote[nrecvs].rank    = fromranks[i];
    473:       iremote[nrecvs++].index = fromsizes[2 * fromperm_newtoold[i] + 1] + j;
    474:     }
    475:   }
    476:   PetscCall(PetscSFCreate(comm, &sf));
    477:   PetscCall(PetscSFSetGraph(sf, nsends, nrecvs, NULL, PETSC_OWN_POINTER, iremote, PETSC_OWN_POINTER));
    478:   PetscCall(PetscSFSetType(sf, PETSCSFBASIC));
    479:   /* how to put a prefix ? */
    480:   PetscCall(PetscSFSetFromOptions(sf));
    481:   PetscCall(PetscSFBcastBegin(sf, MPIU_INT, send_indices, recv_indices, MPI_REPLACE));
    482:   PetscCall(PetscSFBcastEnd(sf, MPIU_INT, send_indices, recv_indices, MPI_REPLACE));
    483:   PetscCall(PetscSFDestroy(&sf));
    484:   PetscCall(PetscFree(fromranks));
    485:   PetscCall(PetscFree(fromsizes));
    486:   PetscCall(PetscFree(fromperm_newtoold));
    487:   PetscCall(PetscFree(send_indices));
    488:   if (rows) {
    489:     PetscCall(PetscSortInt(nrecvs, recv_indices));
    490:     PetscCall(ISCreateGeneral(comm, nrecvs, recv_indices, PETSC_OWN_POINTER, rows));
    491:   } else {
    492:     PetscCall(PetscFree(recv_indices));
    493:   }
    494:   PetscFunctionReturn(PETSC_SUCCESS);
    495: }

    497: /*@
    498:   ISPartitioningToNumbering - Takes an `IS' that represents a partitioning (the MPI rank that each local entry belongs to) and on each MPI process
    499:   generates an `IS` that contains a new global node number in the new ordering for each entry

    501:   Collective

    503:   Input Parameter:
    504: . part - a partitioning as generated by `MatPartitioningApply()` or `MatPartitioningApplyND()`

    506:   Output Parameter:
    507: . is - on each processor the index set that defines the global numbers
    508:          (in the new numbering) for all the nodes currently (before the partitioning)
    509:          on that processor

    511:   Level: advanced

    513:   Note:
    514:   The resulting `IS` tells where each local entry is mapped to in a new global ordering

    516: .seealso: [](sec_scatter), `IS`, `MatPartitioningCreate()`, `AOCreateBasic()`, `ISPartitioningCount()`
    517: @*/
    518: PetscErrorCode ISPartitioningToNumbering(IS part, IS *is)
    519: {
    520:   MPI_Comm        comm;
    521:   IS              ndorder;
    522:   PetscInt        n, *starts = NULL, *sums = NULL, *lsizes = NULL, *newi = NULL;
    523:   const PetscInt *indices = NULL;
    524:   PetscMPIInt     np, npt;

    526:   PetscFunctionBegin;
    528:   PetscAssertPointer(is, 2);
    529:   /* see if the partitioning comes from nested dissection */
    530:   PetscCall(PetscObjectQuery((PetscObject)part, "_petsc_matpartitioning_ndorder", (PetscObject *)&ndorder));
    531:   if (ndorder) {
    532:     PetscCall(PetscObjectReference((PetscObject)ndorder));
    533:     *is = ndorder;
    534:     PetscFunctionReturn(PETSC_SUCCESS);
    535:   }

    537:   PetscCall(PetscObjectGetComm((PetscObject)part, &comm));
    538:   /* count the number of partitions, i.e., virtual processors */
    539:   PetscCall(ISGetLocalSize(part, &n));
    540:   PetscCall(ISGetIndices(part, &indices));
    541:   np = 0;
    542:   for (PetscInt i = 0; i < n; i++) PetscCall(PetscMPIIntCast(PetscMax(np, indices[i]), &np));
    543:   PetscCallMPI(MPIU_Allreduce(&np, &npt, 1, MPI_INT, MPI_MAX, comm));
    544:   np = npt + 1; /* so that it looks like a MPI_Comm_size output */

    546:   /*
    547:      lsizes - number of elements of each partition on this particular processor
    548:      sums - total number of "previous" nodes for any particular partition
    549:      starts - global number of first element in each partition on this processor
    550:   */
    551:   PetscCall(PetscMalloc3(np, &lsizes, np, &starts, np, &sums));
    552:   PetscCall(PetscArrayzero(lsizes, np));
    553:   for (PetscInt i = 0; i < n; i++) lsizes[indices[i]]++;
    554:   PetscCallMPI(MPIU_Allreduce(lsizes, sums, np, MPIU_INT, MPI_SUM, comm));
    555:   PetscCallMPI(MPI_Scan(lsizes, starts, np, MPIU_INT, MPI_SUM, comm));
    556:   for (PetscMPIInt i = 0; i < np; i++) starts[i] -= lsizes[i];
    557:   for (PetscMPIInt i = 1; i < np; i++) {
    558:     sums[i] += sums[i - 1];
    559:     starts[i] += sums[i - 1];
    560:   }

    562:   /*
    563:       For each local index give it the new global number
    564:   */
    565:   PetscCall(PetscMalloc1(n, &newi));
    566:   for (PetscInt i = 0; i < n; i++) newi[i] = starts[indices[i]]++;
    567:   PetscCall(PetscFree3(lsizes, starts, sums));

    569:   PetscCall(ISRestoreIndices(part, &indices));
    570:   PetscCall(ISCreateGeneral(comm, n, newi, PETSC_OWN_POINTER, is));
    571:   PetscCall(ISSetPermutation(*is));
    572:   PetscFunctionReturn(PETSC_SUCCESS);
    573: }

    575: /*@
    576:   ISPartitioningCount - Takes a `IS` that represents a partitioning (the MPI rank that each local entry belongs to) and determines the number of
    577:   resulting elements on each (partition) rank

    579:   Collective

    581:   Input Parameters:
    582: + part - a partitioning as generated by `MatPartitioningApply()` or `MatPartitioningApplyND()`
    583: - len  - length of the array count, this is the total number of partitions

    585:   Output Parameter:
    586: . count - array of length size, to contain the number of elements assigned
    587:         to each partition, where size is the number of partitions generated
    588:          (see notes below).

    590:   Level: advanced

    592:   Notes:
    593:   By default the number of partitions generated (and thus the length
    594:   of count) is the size of the communicator associated with `IS`,
    595:   but it can be set by `MatPartitioningSetNParts()`.

    597:   The resulting array of lengths can for instance serve as input of `PCBJacobiSetTotalBlocks()`.

    599:   If the partitioning has been obtained by `MatPartitioningApplyND()`, the returned count does not include the separators.

    601: .seealso: [](sec_scatter), `IS`, `MatPartitioningCreate()`, `AOCreateBasic()`, `ISPartitioningToNumbering()`,
    602:           `MatPartitioningSetNParts()`, `MatPartitioningApply()`, `MatPartitioningApplyND()`
    603: @*/
    604: PetscErrorCode ISPartitioningCount(IS part, PetscInt len, PetscInt count[])
    605: {
    606:   MPI_Comm        comm;
    607:   PetscInt        i, n, *lsizes;
    608:   const PetscInt *indices;

    610:   PetscFunctionBegin;
    611:   PetscCall(PetscObjectGetComm((PetscObject)part, &comm));
    612:   if (len == PETSC_DEFAULT) {
    613:     PetscMPIInt size;

    615:     PetscCallMPI(MPI_Comm_size(comm, &size));
    616:     len = size;
    617:   }

    619:   /* count the number of partitions */
    620:   PetscCall(ISGetLocalSize(part, &n));
    621:   PetscCall(ISGetIndices(part, &indices));
    622:   if (PetscDefined(USE_DEBUG)) {
    623:     PetscInt np = 0, npt;
    624:     for (i = 0; i < n; i++) np = PetscMax(np, indices[i]);
    625:     PetscCallMPI(MPIU_Allreduce(&np, &npt, 1, MPIU_INT, MPI_MAX, comm));
    626:     np = npt + 1; /* so that it looks like a MPI_Comm_size output */
    627:     PetscCheck(np <= len, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Length of count array %" PetscInt_FMT " is less than number of partitions %" PetscInt_FMT, len, np);
    628:   }

    630:   /*
    631:         lsizes - number of elements of each partition on this particular processor
    632:         sums - total number of "previous" nodes for any particular partition
    633:         starts - global number of first element in each partition on this processor
    634:   */
    635:   PetscCall(PetscCalloc1(len, &lsizes));
    636:   for (i = 0; i < n; i++) {
    637:     if (indices[i] > -1) lsizes[indices[i]]++;
    638:   }
    639:   PetscCall(ISRestoreIndices(part, &indices));
    640:   PetscCallMPI(MPIU_Allreduce(lsizes, count, len, MPIU_INT, MPI_SUM, comm));
    641:   PetscCall(PetscFree(lsizes));
    642:   PetscFunctionReturn(PETSC_SUCCESS);
    643: }

    645: /*@
    646:   ISAllGather - Given an index set `IS` on each processor, generates a large
    647:   index set (same on each processor) by concatenating together each
    648:   processors index set.

    650:   Collective

    652:   Input Parameter:
    653: . is - the distributed index set

    655:   Output Parameter:
    656: . isout - the concatenated index set (same on all processors)

    658:   Level: intermediate

    660:   Notes:
    661:   `ISAllGather()` is clearly not scalable for large index sets.

    663:   The `IS` created on each processor must be created with a common
    664:   communicator (e.g., `PETSC_COMM_WORLD`). If the index sets were created
    665:   with `PETSC_COMM_SELF`, this routine will not work as expected, since
    666:   each process will generate its own new `IS` that consists only of
    667:   itself.

    669:   The communicator for this new `IS` is `PETSC_COMM_SELF`

    671: .seealso: [](sec_scatter), `IS`, `ISCreateGeneral()`, `ISCreateStride()`, `ISCreateBlock()`
    672: @*/
    673: PetscErrorCode ISAllGather(IS is, IS *isout)
    674: {
    675:   PetscInt       *indices, n, i, N, step, first;
    676:   const PetscInt *lindices;
    677:   MPI_Comm        comm;
    678:   PetscMPIInt     size, *sizes = NULL, *offsets = NULL, nn;
    679:   PetscBool       stride;

    681:   PetscFunctionBegin;
    683:   PetscAssertPointer(isout, 2);

    685:   PetscCall(PetscObjectGetComm((PetscObject)is, &comm));
    686:   PetscCallMPI(MPI_Comm_size(comm, &size));
    687:   PetscCall(ISGetLocalSize(is, &n));
    688:   PetscCall(PetscObjectTypeCompare((PetscObject)is, ISSTRIDE, &stride));
    689:   if (size == 1 && stride) { /* should handle parallel ISStride also */
    690:     PetscCall(ISStrideGetInfo(is, &first, &step));
    691:     PetscCall(ISCreateStride(PETSC_COMM_SELF, n, first, step, isout));
    692:   } else {
    693:     PetscCall(PetscMalloc2(size, &sizes, size, &offsets));

    695:     PetscCall(PetscMPIIntCast(n, &nn));
    696:     PetscCallMPI(MPI_Allgather(&nn, 1, MPI_INT, sizes, 1, MPI_INT, comm));
    697:     offsets[0] = 0;
    698:     for (i = 1; i < size; i++) {
    699:       PetscInt s = offsets[i - 1] + sizes[i - 1];
    700:       PetscCall(PetscMPIIntCast(s, &offsets[i]));
    701:     }
    702:     N = offsets[size - 1] + sizes[size - 1];

    704:     PetscCall(PetscMalloc1(N, &indices));
    705:     PetscCall(ISGetIndices(is, &lindices));
    706:     PetscCallMPI(MPI_Allgatherv((void *)lindices, nn, MPIU_INT, indices, sizes, offsets, MPIU_INT, comm));
    707:     PetscCall(ISRestoreIndices(is, &lindices));
    708:     PetscCall(PetscFree2(sizes, offsets));

    710:     PetscCall(ISCreateGeneral(PETSC_COMM_SELF, N, indices, PETSC_OWN_POINTER, isout));
    711:   }
    712:   PetscFunctionReturn(PETSC_SUCCESS);
    713: }

    715: /*@C
    716:   ISAllGatherColors - Given a set of colors on each processor, generates a large
    717:   set (same on each processor) by concatenating together each processors colors

    719:   Collective

    721:   Input Parameters:
    722: + comm     - communicator to share the indices
    723: . n        - local size of set
    724: - lindices - local colors

    726:   Output Parameters:
    727: + outN       - total number of indices
    728: - outindices - all of the colors

    730:   Level: intermediate

    732:   Note:
    733:   `ISAllGatherColors()` is clearly not scalable for large index sets.

    735: .seealso: `ISColoringValue`, `ISColoring()`, `ISCreateGeneral()`, `ISCreateStride()`, `ISCreateBlock()`, `ISAllGather()`
    736: @*/
    737: PetscErrorCode ISAllGatherColors(MPI_Comm comm, PetscInt n, ISColoringValue lindices[], PetscInt *outN, ISColoringValue *outindices[])
    738: {
    739:   ISColoringValue *indices;
    740:   PetscInt         N;
    741:   PetscMPIInt      size, *offsets = NULL, *sizes = NULL, nn;

    743:   PetscFunctionBegin;
    744:   PetscCall(PetscMPIIntCast(n, &nn));
    745:   PetscCallMPI(MPI_Comm_size(comm, &size));
    746:   PetscCall(PetscMalloc2(size, &sizes, size, &offsets));

    748:   PetscCallMPI(MPI_Allgather(&nn, 1, MPI_INT, sizes, 1, MPI_INT, comm));
    749:   offsets[0] = 0;
    750:   for (PetscMPIInt i = 1; i < size; i++) offsets[i] = offsets[i - 1] + sizes[i - 1];
    751:   N = offsets[size - 1] + sizes[size - 1];
    752:   PetscCall(PetscFree2(sizes, offsets));

    754:   PetscCall(PetscMalloc1(N + 1, &indices));
    755:   PetscCallMPI(MPI_Allgatherv(lindices, nn, MPIU_COLORING_VALUE, indices, sizes, offsets, MPIU_COLORING_VALUE, comm));

    757:   *outindices = indices;
    758:   if (outN) *outN = N;
    759:   PetscFunctionReturn(PETSC_SUCCESS);
    760: }

    762: /*@
    763:   ISComplement - Given an index set `IS` generates the complement index set. That is
    764:   all indices that are NOT in the given set.

    766:   Collective

    768:   Input Parameters:
    769: + is   - the index set
    770: . nmin - the first index desired in the local part of the complement
    771: - nmax - the largest index desired in the local part of the complement (note that all indices in `is` must be greater or equal to `nmin` and less than `nmax`)

    773:   Output Parameter:
    774: . isout - the complement

    776:   Level: intermediate

    778:   Notes:
    779:   The communicator for `isout` is the same as for the input `is`

    781:   For a parallel `is`, this will generate the local part of the complement on each process

    783:   To generate the entire complement (on each process) of a parallel `is`, first call `ISAllGather()` and then
    784:   call this routine.

    786: .seealso: [](sec_scatter), `IS`, `ISCreateGeneral()`, `ISCreateStride()`, `ISCreateBlock()`, `ISAllGather()`
    787: @*/
    788: PetscErrorCode ISComplement(IS is, PetscInt nmin, PetscInt nmax, IS *isout)
    789: {
    790:   const PetscInt *indices;
    791:   PetscInt        n, i, j, unique, cnt, *nindices;
    792:   PetscBool       sorted;

    794:   PetscFunctionBegin;
    796:   PetscAssertPointer(isout, 4);
    797:   PetscCheck(nmin >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nmin %" PetscInt_FMT " cannot be negative", nmin);
    798:   PetscCheck(nmin <= nmax, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "nmin %" PetscInt_FMT " cannot be greater than nmax %" PetscInt_FMT, nmin, nmax);
    799:   PetscCall(ISSorted(is, &sorted));
    800:   PetscCheck(sorted, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Index set must be sorted");

    802:   PetscCall(ISGetLocalSize(is, &n));
    803:   PetscCall(ISGetIndices(is, &indices));
    804:   if (PetscDefined(USE_DEBUG)) {
    805:     for (i = 0; i < n; i++) {
    806:       PetscCheck(indices[i] >= nmin, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Index %" PetscInt_FMT "'s value %" PetscInt_FMT " is smaller than minimum given %" PetscInt_FMT, i, indices[i], nmin);
    807:       PetscCheck(indices[i] < nmax, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Index %" PetscInt_FMT "'s value %" PetscInt_FMT " is larger than maximum given %" PetscInt_FMT, i, indices[i], nmax);
    808:     }
    809:   }
    810:   /* Count number of unique entries */
    811:   unique = (n > 0);
    812:   for (i = 0; i < n - 1; i++) {
    813:     if (indices[i + 1] != indices[i]) unique++;
    814:   }
    815:   PetscCall(PetscMalloc1(nmax - nmin - unique, &nindices));
    816:   cnt = 0;
    817:   for (i = nmin, j = 0; i < nmax; i++) {
    818:     if (j < n && i == indices[j]) do {
    819:         j++;
    820:       } while (j < n && i == indices[j]);
    821:     else nindices[cnt++] = i;
    822:   }
    823:   PetscCheck(cnt == nmax - nmin - unique, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Number of entries found in complement %" PetscInt_FMT " does not match expected %" PetscInt_FMT, cnt, nmax - nmin - unique);
    824:   PetscCall(ISCreateGeneral(PetscObjectComm((PetscObject)is), cnt, nindices, PETSC_OWN_POINTER, isout));
    825:   PetscCall(ISSetInfo(*isout, IS_SORTED, IS_GLOBAL, PETSC_FALSE, PETSC_TRUE));
    826:   PetscCall(ISRestoreIndices(is, &indices));
    827:   PetscFunctionReturn(PETSC_SUCCESS);
    828: }