Actual source code: iscoloring.c

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

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

      8: PetscErrorCode ISColoringReference(ISColoring coloring)
      9: {
     11:   coloring->refct++;
     12:   return(0);
     13: }

     15: /*@C

     17:     ISColoringSetType - indicates if the coloring is for the local representation (including ghost points) or the global representation

     19:    Collective on coloring

     21:    Input Parameters:
     22: +    coloring - the coloring object
     23: -    type - either IS_COLORING_LOCAL or IS_COLORING_GLOBAL

     25:    Notes:
     26:      With IS_COLORING_LOCAL the coloring is in the numbering of the local vector, for IS_COLORING_GLOBAL it is in the number of the global vector

     28:    Level: intermediate

     30: .seealso: MatFDColoringCreate(), ISColoring, ISColoringCreate(), IS_COLORING_LOCAL, IS_COLORING_GLOBAL, ISColoringGetType()

     32: @*/
     33: PetscErrorCode ISColoringSetType(ISColoring coloring,ISColoringType type)
     34: {
     36:   coloring->ctype = type;
     37:   return(0);
     38: }

     40: /*@C

     42:     ISColoringGetType - gets if the coloring is for the local representation (including ghost points) or the global representation

     44:    Collective on coloring

     46:    Input Parameter:
     47: .   coloring - the coloring object

     49:    Output Parameter:
     50: .    type - either IS_COLORING_LOCAL or IS_COLORING_GLOBAL

     52:    Level: intermediate

     54: .seealso: MatFDColoringCreate(), ISColoring, ISColoringCreate(), IS_COLORING_LOCAL, IS_COLORING_GLOBAL, ISColoringSetType()

     56: @*/
     57: PetscErrorCode ISColoringGetType(ISColoring coloring,ISColoringType *type)
     58: {
     60:   *type = coloring->ctype;
     61:   return(0);
     62: }

     64: /*@
     65:    ISColoringDestroy - Destroys a coloring context.

     67:    Collective on ISColoring

     69:    Input Parameter:
     70: .  iscoloring - the coloring context

     72:    Level: advanced

     74: .seealso: ISColoringView(), MatColoring
     75: @*/
     76: PetscErrorCode  ISColoringDestroy(ISColoring *iscoloring)
     77: {
     78:   PetscInt       i;

     82:   if (!*iscoloring) return(0);
     84:   if (--(*iscoloring)->refct > 0) {*iscoloring = NULL; return(0);}

     86:   if ((*iscoloring)->is) {
     87:     for (i=0; i<(*iscoloring)->n; i++) {
     88:       ISDestroy(&(*iscoloring)->is[i]);
     89:     }
     90:     PetscFree((*iscoloring)->is);
     91:   }
     92:   if ((*iscoloring)->allocated) {PetscFree((*iscoloring)->colors);}
     93:   PetscCommDestroy(&(*iscoloring)->comm);
     94:   PetscFree((*iscoloring));
     95:   return(0);
     96: }

     98: /*
     99:   ISColoringViewFromOptions - Processes command line options to determine if/how an ISColoring object is to be viewed.

    101:   Collective on ISColoring

    103:   Input Parameters:
    104: + obj   - the ISColoring object
    105: . prefix - prefix to use for viewing, or NULL to use prefix of 'mat'
    106: - optionname - option to activate viewing

    108:   Level: intermediate

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

    112: */
    113: PetscErrorCode ISColoringViewFromOptions(ISColoring obj,PetscObject bobj,const char optionname[])
    114: {
    115:   PetscErrorCode    ierr;
    116:   PetscViewer       viewer;
    117:   PetscBool         flg;
    118:   PetscViewerFormat format;
    119:   char              *prefix;

    122:   prefix = bobj ? bobj->prefix : NULL;
    123:   PetscOptionsGetViewer(obj->comm,NULL,prefix,optionname,&viewer,&format,&flg);
    124:   if (flg) {
    125:     PetscViewerPushFormat(viewer,format);
    126:     ISColoringView(obj,viewer);
    127:     PetscViewerPopFormat(viewer);
    128:     PetscViewerDestroy(&viewer);
    129:   }
    130:   return(0);
    131: }

    133: /*@C
    134:    ISColoringView - Views a coloring context.

    136:    Collective on ISColoring

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

    142:    Level: advanced

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

    155:   if (!viewer) {
    156:     PetscViewerASCIIGetStdout(iscoloring->comm,&viewer);
    157:   }

    160:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    161:   if (iascii) {
    162:     MPI_Comm    comm;
    163:     PetscMPIInt size,rank;

    165:     PetscObjectGetComm((PetscObject)viewer,&comm);
    166:     MPI_Comm_size(comm,&size);
    167:     MPI_Comm_rank(comm,&rank);
    168:     PetscViewerASCIIPrintf(viewer,"ISColoring Object: %d MPI processes\n",size);
    169:     PetscViewerASCIIPrintf(viewer,"ISColoringType: %s\n",ISColoringTypes[iscoloring->ctype]);
    170:     PetscViewerASCIIPushSynchronized(viewer);
    171:     PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Number of colors %d\n",rank,iscoloring->n);
    172:     PetscViewerFlush(viewer);
    173:     PetscViewerASCIIPopSynchronized(viewer);
    174:   }

    176:   ISColoringGetIS(iscoloring,PETSC_USE_POINTER,PETSC_IGNORE,&is);
    177:   for (i=0; i<iscoloring->n; i++) {
    178:     ISView(iscoloring->is[i],viewer);
    179:   }
    180:   ISColoringRestoreIS(iscoloring,PETSC_USE_POINTER,&is);
    181:   return(0);
    182: }

    184: /*@C
    185:    ISColoringGetColors - Returns an array with the color for each node

    187:    Not Collective

    189:    Input Parameter:
    190: .  iscoloring - the coloring context

    192:    Output Parameters:
    193: +  n - number of nodes
    194: .  nc - number of colors
    195: -  colors - color for each node

    197:    Level: advanced

    199: .seealso: ISColoringRestoreIS(), ISColoringView(), ISColoringGetIS()
    200: @*/
    201: PetscErrorCode  ISColoringGetColors(ISColoring iscoloring,PetscInt *n,PetscInt *nc,const ISColoringValue **colors)
    202: {

    206:   if (n) *n = iscoloring->N;
    207:   if (nc) *nc = iscoloring->n;
    208:   if (colors) *colors = iscoloring->colors;
    209:   return(0);
    210: }

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

    215:    Collective on ISColoring

    217:    Input Parameter:
    218: +  iscoloring - the coloring context
    219: -  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

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

    225:    Level: advanced

    227: .seealso: ISColoringRestoreIS(), ISColoringView(), ISColoringGetColoring()
    228: @*/
    229: PetscErrorCode  ISColoringGetIS(ISColoring iscoloring,PetscCopyMode mode, PetscInt *nn,IS *isis[])
    230: {

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

    243:       if (PetscDefined(USE_DEBUG)) {
    244:         for (i=0; i<n; i++) {
    245:           if (((PetscInt)colors[i]) >= nc) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Coloring is our of range index %d value %d number colors %d",(int)i,(int)colors[i],(int)nc);
    246:         }
    247:       }

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

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

    258:       if (iscoloring->ctype == IS_COLORING_GLOBAL) {
    259:         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:       PetscMalloc1(nc,&is);
    267:       for (i=0; i<nc; i++) {
    268:         ISCreateGeneral(iscoloring->comm,mcolors[i],ii[i],PETSC_COPY_VALUES,is+i);
    269:       }

    271:       if (mode != PETSC_OWN_POINTER) iscoloring->is = is;
    272:       *isis = is;
    273:       PetscFree(ii[0]);
    274:       PetscFree(ii);
    275:       PetscFree(mcolors);
    276:     } else {
    277:       *isis = iscoloring->is;
    278:     }
    279:   }
    280:   return(0);
    281: }

    283: /*@C
    284:    ISColoringRestoreIS - Restores the index sets extracted from the coloring context

    286:    Collective on ISColoring

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

    293:    Level: advanced

    295: .seealso: ISColoringGetIS(), ISColoringView()
    296: @*/
    297: PetscErrorCode  ISColoringRestoreIS(ISColoring iscoloring,PetscCopyMode mode,IS *is[])
    298: {

    302:   /* currently nothing is done here */
    303:   return(0);
    304: }

    307: /*@
    308:     ISColoringCreate - Generates an ISColoring context from lists (provided
    309:     by each processor) of colors for each node.

    311:     Collective

    313:     Input Parameters:
    314: +   comm - communicator for the processors creating the coloring
    315: .   ncolors - max color value
    316: .   n - number of nodes on this processor
    317: .   colors - array containing the colors for this processor, color numbers begin at 0.
    318: -   mode - see PetscCopyMode for meaning of this flag.

    320:     Output Parameter:
    321: .   iscoloring - the resulting coloring data structure

    323:     Options Database Key:
    324: .   -is_coloring_view - Activates ISColoringView()

    326:    Level: advanced

    328:     Notes:
    329:     By default sets coloring type to  IS_COLORING_GLOBAL

    331: .seealso: MatColoringCreate(), ISColoringView(), ISColoringDestroy(), ISColoringSetType()

    333: @*/
    334: PetscErrorCode  ISColoringCreate(MPI_Comm comm,PetscInt ncolors,PetscInt n,const ISColoringValue colors[],PetscCopyMode mode,ISColoring *iscoloring)
    335: {
    337:   PetscMPIInt    size,rank,tag;
    338:   PetscInt       base,top,i;
    339:   PetscInt       nc,ncwork;
    340:   MPI_Status     status;

    343:   if (ncolors != PETSC_DECIDE && ncolors > IS_COLORING_MAX) {
    344:     if (ncolors > PETSC_MAX_UINT16) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Max color value exceeds %d limit. This number is unrealistic. Perhaps a bug in code?\nCurrent max: %d user requested: %D",PETSC_MAX_UINT16,PETSC_IS_COLORING_MAX,ncolors);
    345:     else                 SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Max color value exceeds limit. Perhaps reconfigure PETSc with --with-is-color-value-type=short?\n Current max: %d user requested: %D",PETSC_IS_COLORING_MAX,ncolors);
    346:   }
    347:   PetscNew(iscoloring);
    348:   PetscCommDuplicate(comm,&(*iscoloring)->comm,&tag);
    349:   comm = (*iscoloring)->comm;

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

    354:   /* should use MPI_Scan() */
    355:   MPI_Comm_rank(comm,&rank);
    356:   if (!rank) {
    357:     base = 0;
    358:     top  = n;
    359:   } else {
    360:     MPI_Recv(&base,1,MPIU_INT,rank-1,tag,comm,&status);
    361:     top  = base+n;
    362:   }
    363:   if (rank < size-1) {
    364:     MPI_Send(&top,1,MPIU_INT,rank+1,tag,comm);
    365:   }

    367:   /* compute the total number of colors */
    368:   ncwork = 0;
    369:   for (i=0; i<n; i++) {
    370:     if (ncwork < colors[i]) ncwork = colors[i];
    371:   }
    372:   ncwork++;
    373:   MPIU_Allreduce(&ncwork,&nc,1,MPIU_INT,MPI_MAX,comm);
    374:   if (nc > ncolors) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of colors passed in %D is less then the actual number of colors in array %D",ncolors,nc);
    375:   (*iscoloring)->n      = nc;
    376:   (*iscoloring)->is     = NULL;
    377:   (*iscoloring)->N      = n;
    378:   (*iscoloring)->refct  = 1;
    379:   (*iscoloring)->ctype  = IS_COLORING_GLOBAL;
    380:   if (mode == PETSC_COPY_VALUES) {
    381:     PetscMalloc1(n,&(*iscoloring)->colors);
    382:     PetscLogObjectMemory((PetscObject)(*iscoloring),n*sizeof(ISColoringValue));
    383:     PetscArraycpy((*iscoloring)->colors,colors,n);
    384:     (*iscoloring)->allocated = PETSC_TRUE;
    385:   } else if (mode == PETSC_OWN_POINTER) {
    386:     (*iscoloring)->colors    = (ISColoringValue*)colors;
    387:     (*iscoloring)->allocated = PETSC_TRUE;
    388:   } else {
    389:     (*iscoloring)->colors    = (ISColoringValue*)colors;
    390:     (*iscoloring)->allocated = PETSC_FALSE;
    391:   }
    392:   ISColoringViewFromOptions(*iscoloring,NULL,"-is_coloring_view");
    393:   PetscInfo1(0,"Number of colors %D\n",nc);
    394:   return(0);
    395: }

    397: /*@
    398:     ISBuildTwoSided - Takes an IS that describes where we will go. Generates an IS that contains new numbers from remote or local
    399:     on the IS.

    401:     Collective on IS

    403:     Input Parameters:
    404: +   ito - an IS describes where we will go. Negative target rank will be ignored
    405: -   toindx - an IS describes what indices should send. NULL means sending natural numbering

    407:     Output Parameter:
    408: .   rows - contains new numbers from remote or local

    410:    Level: advanced

    412: .seealso: MatPartitioningCreate(), ISPartitioningToNumbering(), ISPartitioningCount()

    414: @*/
    415: PetscErrorCode  ISBuildTwoSided(IS ito,IS toindx, IS *rows)
    416: {
    417:    const PetscInt *ito_indices,*toindx_indices;
    418:    PetscInt       *send_indices,rstart,*recv_indices,nrecvs,nsends;
    419:    PetscInt       *tosizes,*fromsizes,i,j,*tosizes_tmp,*tooffsets_tmp,ito_ln;
    420:    PetscMPIInt    *toranks,*fromranks,size,target_rank,*fromperm_newtoold,nto,nfrom;
    421:    PetscLayout     isrmap;
    422:    MPI_Comm        comm;
    423:    PetscSF         sf;
    424:    PetscSFNode    *iremote;
    425:    PetscErrorCode  ierr;

    428:    PetscObjectGetComm((PetscObject)ito,&comm);
    429:    MPI_Comm_size(comm,&size);
    430:    ISGetLocalSize(ito,&ito_ln);
    431:    /* why we do not have ISGetLayout? */
    432:    isrmap = ito->map;
    433:    PetscLayoutGetRange(isrmap,&rstart,NULL);
    434:    ISGetIndices(ito,&ito_indices);
    435:    PetscCalloc2(size,&tosizes_tmp,size+1,&tooffsets_tmp);
    436:    for (i=0; i<ito_ln; i++) {
    437:      if (ito_indices[i]<0) continue;
    438:      if (ito_indices[i]>=size) SETERRQ2(comm,PETSC_ERR_ARG_OUTOFRANGE,"target rank %d is larger than communicator size %d ",ito_indices[i],size);
    439:      tosizes_tmp[ito_indices[i]]++;
    440:    }
    441:    nto = 0;
    442:    for (i=0; i<size; i++) {
    443:      tooffsets_tmp[i+1] = tooffsets_tmp[i]+tosizes_tmp[i];
    444:      if (tosizes_tmp[i]>0) nto++;
    445:    }
    446:    PetscCalloc2(nto,&toranks,2*nto,&tosizes);
    447:    nto  = 0;
    448:    for (i=0; i<size; i++) {
    449:      if (tosizes_tmp[i]>0) {
    450:        toranks[nto]     = i;
    451:        tosizes[2*nto]   = tosizes_tmp[i];/* size */
    452:        tosizes[2*nto+1] = tooffsets_tmp[i];/* offset */
    453:        nto++;
    454:      }
    455:    }
    456:    nsends = tooffsets_tmp[size];
    457:    PetscCalloc1(nsends,&send_indices);
    458:    if (toindx) {
    459:      ISGetIndices(toindx,&toindx_indices);
    460:    }
    461:    for (i=0; i<ito_ln; i++) {
    462:      if (ito_indices[i]<0) continue;
    463:      target_rank = ito_indices[i];
    464:      send_indices[tooffsets_tmp[target_rank]] = toindx? toindx_indices[i]:(i+rstart);
    465:      tooffsets_tmp[target_rank]++;
    466:    }
    467:    if (toindx) {
    468:      ISRestoreIndices(toindx,&toindx_indices);
    469:    }
    470:    ISRestoreIndices(ito,&ito_indices);
    471:    PetscFree2(tosizes_tmp,tooffsets_tmp);
    472:    PetscCommBuildTwoSided(comm,2,MPIU_INT,nto,toranks,tosizes,&nfrom,&fromranks,&fromsizes);
    473:    PetscFree2(toranks,tosizes);
    474:    PetscMalloc1(nfrom,&fromperm_newtoold);
    475:    for (i=0; i<nfrom; i++) fromperm_newtoold[i] = i;
    476:    PetscSortMPIIntWithArray(nfrom,fromranks,fromperm_newtoold);
    477:    nrecvs = 0;
    478:    for (i=0; i<nfrom; i++) nrecvs += fromsizes[i*2];
    479:    PetscCalloc1(nrecvs,&recv_indices);
    480:    PetscMalloc1(nrecvs,&iremote);
    481:    nrecvs = 0;
    482:    for (i=0; i<nfrom; i++) {
    483:      for (j=0; j<fromsizes[2*fromperm_newtoold[i]]; j++) {
    484:        iremote[nrecvs].rank    = fromranks[i];
    485:        iremote[nrecvs++].index = fromsizes[2*fromperm_newtoold[i]+1]+j;
    486:      }
    487:    }
    488:    PetscSFCreate(comm,&sf);
    489:    PetscSFSetGraph(sf,nsends,nrecvs,NULL,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
    490:    PetscSFSetType(sf,PETSCSFBASIC);
    491:    /* how to put a prefix ? */
    492:    PetscSFSetFromOptions(sf);
    493:    PetscSFBcastBegin(sf,MPIU_INT,send_indices,recv_indices,MPI_REPLACE);
    494:    PetscSFBcastEnd(sf,MPIU_INT,send_indices,recv_indices,MPI_REPLACE);
    495:    PetscSFDestroy(&sf);
    496:    PetscFree(fromranks);
    497:    PetscFree(fromsizes);
    498:    PetscFree(fromperm_newtoold);
    499:    PetscFree(send_indices);
    500:    if (rows) {
    501:      PetscSortInt(nrecvs,recv_indices);
    502:      ISCreateGeneral(comm,nrecvs,recv_indices,PETSC_OWN_POINTER,rows);
    503:    } else {
    504:      PetscFree(recv_indices);
    505:    }
    506:    return(0);
    507: }

    510: /*@
    511:     ISPartitioningToNumbering - Takes an ISPartitioning and on each processor
    512:     generates an IS that contains a new global node number for each index based
    513:     on the partitioing.

    515:     Collective on IS

    517:     Input Parameters:
    518: .   partitioning - a partitioning as generated by MatPartitioningApply()
    519:                    or MatPartitioningApplyND()

    521:     Output Parameter:
    522: .   is - on each processor the index set that defines the global numbers
    523:          (in the new numbering) for all the nodes currently (before the partitioning)
    524:          on that processor

    526:    Level: advanced

    528: .seealso: MatPartitioningCreate(), AOCreateBasic(), ISPartitioningCount()

    530: @*/
    531: PetscErrorCode  ISPartitioningToNumbering(IS part,IS *is)
    532: {
    533:   MPI_Comm       comm;
    534:   IS             ndorder;
    535:   PetscInt       i,np,npt,n,*starts = NULL,*sums = NULL,*lsizes = NULL,*newi = NULL;
    536:   const PetscInt *indices = NULL;

    542:   /* see if the partitioning comes from nested dissection */
    543:   PetscObjectQuery((PetscObject)part,"_petsc_matpartitioning_ndorder",(PetscObject*)&ndorder);
    544:   if (ndorder) {
    545:     PetscObjectReference((PetscObject)ndorder);
    546:     *is  = ndorder;
    547:     return(0);
    548:   }

    550:   PetscObjectGetComm((PetscObject)part,&comm);
    551:   /* count the number of partitions, i.e., virtual processors */
    552:   ISGetLocalSize(part,&n);
    553:   ISGetIndices(part,&indices);
    554:   np   = 0;
    555:   for (i=0; i<n; i++) np = PetscMax(np,indices[i]);
    556:   MPIU_Allreduce(&np,&npt,1,MPIU_INT,MPI_MAX,comm);
    557:   np   = npt+1; /* so that it looks like a MPI_Comm_size output */

    559:   /*
    560:         lsizes - number of elements of each partition on this particular processor
    561:         sums - total number of "previous" nodes for any particular partition
    562:         starts - global number of first element in each partition on this processor
    563:   */
    564:   PetscMalloc3(np,&lsizes,np,&starts,np,&sums);
    565:   PetscArrayzero(lsizes,np);
    566:   for (i=0; i<n; i++) lsizes[indices[i]]++;
    567:   MPIU_Allreduce(lsizes,sums,np,MPIU_INT,MPI_SUM,comm);
    568:   MPI_Scan(lsizes,starts,np,MPIU_INT,MPI_SUM,comm);
    569:   for (i=0; i<np; i++) starts[i] -= lsizes[i];
    570:   for (i=1; i<np; i++) {
    571:     sums[i]   += sums[i-1];
    572:     starts[i] += sums[i-1];
    573:   }

    575:   /*
    576:       For each local index give it the new global number
    577:   */
    578:   PetscMalloc1(n,&newi);
    579:   for (i=0; i<n; i++) newi[i] = starts[indices[i]]++;
    580:   PetscFree3(lsizes,starts,sums);

    582:   ISRestoreIndices(part,&indices);
    583:   ISCreateGeneral(comm,n,newi,PETSC_OWN_POINTER,is);
    584:   ISSetPermutation(*is);
    585:   return(0);
    586: }

    588: /*@
    589:     ISPartitioningCount - Takes a ISPartitioning and determines the number of
    590:     resulting elements on each (partition) process

    592:     Collective on IS

    594:     Input Parameters:
    595: +   partitioning - a partitioning as generated by MatPartitioningApply() or
    596:                    MatPartitioningApplyND()
    597: -   len - length of the array count, this is the total number of partitions

    599:     Output Parameter:
    600: .   count - array of length size, to contain the number of elements assigned
    601:         to each partition, where size is the number of partitions generated
    602:          (see notes below).

    604:    Level: advanced

    606:     Notes:
    607:         By default the number of partitions generated (and thus the length
    608:         of count) is the size of the communicator associated with IS,
    609:         but it can be set by MatPartitioningSetNParts. The resulting array
    610:         of lengths can for instance serve as input of PCBJacobiSetTotalBlocks.
    611:         If the partitioning has been obtained by MatPartitioningApplyND(),
    612:         the returned count does not include the separators.

    614: .seealso: MatPartitioningCreate(), AOCreateBasic(), ISPartitioningToNumbering(),
    615:         MatPartitioningSetNParts(), MatPartitioningApply(), MatPartitioningApplyND()

    617: @*/
    618: PetscErrorCode  ISPartitioningCount(IS part,PetscInt len,PetscInt count[])
    619: {
    620:   MPI_Comm       comm;
    621:   PetscInt       i,n,*lsizes;
    622:   const PetscInt *indices;
    624:   PetscMPIInt    npp;

    627:   PetscObjectGetComm((PetscObject)part,&comm);
    628:   if (len == PETSC_DEFAULT) {
    629:     PetscMPIInt size;
    630:     MPI_Comm_size(comm,&size);
    631:     len  = (PetscInt) size;
    632:   }

    634:   /* count the number of partitions */
    635:   ISGetLocalSize(part,&n);
    636:   ISGetIndices(part,&indices);
    637:   if (PetscDefined(USE_DEBUG)) {
    638:     PetscInt np = 0,npt;
    639:     for (i=0; i<n; i++) np = PetscMax(np,indices[i]);
    640:     MPIU_Allreduce(&np,&npt,1,MPIU_INT,MPI_MAX,comm);
    641:     np   = npt+1; /* so that it looks like a MPI_Comm_size output */
    642:     if (np > len) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Length of count array %D is less than number of partitions %D",len,np);
    643:   }

    645:   /*
    646:         lsizes - number of elements of each partition on this particular processor
    647:         sums - total number of "previous" nodes for any particular partition
    648:         starts - global number of first element in each partition on this processor
    649:   */
    650:   PetscCalloc1(len,&lsizes);
    651:   for (i=0; i<n; i++) {
    652:     if (indices[i] > -1) lsizes[indices[i]]++;
    653:   }
    654:   ISRestoreIndices(part,&indices);
    655:   PetscMPIIntCast(len,&npp);
    656:   MPIU_Allreduce(lsizes,count,npp,MPIU_INT,MPI_SUM,comm);
    657:   PetscFree(lsizes);
    658:   return(0);
    659: }

    661: /*@
    662:     ISAllGather - Given an index set (IS) on each processor, generates a large
    663:     index set (same on each processor) by concatenating together each
    664:     processors index set.

    666:     Collective on IS

    668:     Input Parameter:
    669: .   is - the distributed index set

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

    674:     Notes:
    675:     ISAllGather() is clearly not scalable for large index sets.

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

    683:     The communicator for this new IS is PETSC_COMM_SELF

    685:     Level: intermediate

    687: .seealso: ISCreateGeneral(), ISCreateStride(), ISCreateBlock()
    688: @*/
    689: PetscErrorCode  ISAllGather(IS is,IS *isout)
    690: {
    692:   PetscInt       *indices,n,i,N,step,first;
    693:   const PetscInt *lindices;
    694:   MPI_Comm       comm;
    695:   PetscMPIInt    size,*sizes = NULL,*offsets = NULL,nn;
    696:   PetscBool      stride;

    702:   PetscObjectGetComm((PetscObject)is,&comm);
    703:   MPI_Comm_size(comm,&size);
    704:   ISGetLocalSize(is,&n);
    705:   PetscObjectTypeCompare((PetscObject)is,ISSTRIDE,&stride);
    706:   if (size == 1 && stride) { /* should handle parallel ISStride also */
    707:     ISStrideGetInfo(is,&first,&step);
    708:     ISCreateStride(PETSC_COMM_SELF,n,first,step,isout);
    709:   } else {
    710:     PetscMalloc2(size,&sizes,size,&offsets);

    712:     PetscMPIIntCast(n,&nn);
    713:     MPI_Allgather(&nn,1,MPI_INT,sizes,1,MPI_INT,comm);
    714:     offsets[0] = 0;
    715:     for (i=1; i<size; i++) {
    716:       PetscInt s = offsets[i-1] + sizes[i-1];
    717:       PetscMPIIntCast(s,&offsets[i]);
    718:     }
    719:     N = offsets[size-1] + sizes[size-1];

    721:     PetscMalloc1(N,&indices);
    722:     ISGetIndices(is,&lindices);
    723:     MPI_Allgatherv((void*)lindices,nn,MPIU_INT,indices,sizes,offsets,MPIU_INT,comm);
    724:     ISRestoreIndices(is,&lindices);
    725:     PetscFree2(sizes,offsets);

    727:     ISCreateGeneral(PETSC_COMM_SELF,N,indices,PETSC_OWN_POINTER,isout);
    728:   }
    729:   return(0);
    730: }

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

    736:     Collective

    738:     Input Parameter:
    739: +   comm - communicator to share the indices
    740: .   n - local size of set
    741: -   lindices - local colors

    743:     Output Parameter:
    744: +   outN - total number of indices
    745: -   outindices - all of the colors

    747:     Notes:
    748:     ISAllGatherColors() is clearly not scalable for large index sets.

    751:     Level: intermediate

    753: .seealso: ISCreateGeneral(), ISCreateStride(), ISCreateBlock(), ISAllGather()
    754: @*/
    755: PetscErrorCode  ISAllGatherColors(MPI_Comm comm,PetscInt n,ISColoringValue *lindices,PetscInt *outN,ISColoringValue *outindices[])
    756: {
    757:   ISColoringValue *indices;
    758:   PetscErrorCode  ierr;
    759:   PetscInt        i,N;
    760:   PetscMPIInt     size,*offsets = NULL,*sizes = NULL, nn = n;

    763:   MPI_Comm_size(comm,&size);
    764:   PetscMalloc2(size,&sizes,size,&offsets);

    766:   MPI_Allgather(&nn,1,MPI_INT,sizes,1,MPI_INT,comm);
    767:   offsets[0] = 0;
    768:   for (i=1; i<size; i++) offsets[i] = offsets[i-1] + sizes[i-1];
    769:   N    = offsets[size-1] + sizes[size-1];
    770:   PetscFree2(sizes,offsets);

    772:   PetscMalloc1(N+1,&indices);
    773:   MPI_Allgatherv(lindices,(PetscMPIInt)n,MPIU_COLORING_VALUE,indices,sizes,offsets,MPIU_COLORING_VALUE,comm);

    775:   *outindices = indices;
    776:   if (outN) *outN = N;
    777:   return(0);
    778: }

    780: /*@
    781:     ISComplement - Given an index set (IS) generates the complement index set. That is all
    782:        all indices that are NOT in the given set.

    784:     Collective on IS

    786:     Input Parameter:
    787: +   is - the index set
    788: .   nmin - the first index desired in the local part of the complement
    789: -   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)

    791:     Output Parameter:
    792: .   isout - the complement

    794:     Notes:
    795:     The communicator for this new IS is the same as for the input IS

    797:       For a parallel IS, this will generate the local part of the complement on each process

    799:       To generate the entire complement (on each process) of a parallel IS, first call ISAllGather() and then
    800:     call this routine.

    802:     Level: intermediate

    804: .seealso: ISCreateGeneral(), ISCreateStride(), ISCreateBlock(), ISAllGather()
    805: @*/
    806: PetscErrorCode  ISComplement(IS is,PetscInt nmin,PetscInt nmax,IS *isout)
    807: {
    809:   const PetscInt *indices;
    810:   PetscInt       n,i,j,unique,cnt,*nindices;
    811:   PetscBool      sorted;

    816:   if (nmin < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nmin %D cannot be negative",nmin);
    817:   if (nmin > nmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nmin %D cannot be greater than nmax %D",nmin,nmax);
    818:   ISSorted(is,&sorted);
    819:   if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Index set must be sorted");

    821:   ISGetLocalSize(is,&n);
    822:   ISGetIndices(is,&indices);
    823:   if (PetscDefined(USE_DEBUG)) {
    824:     for (i=0; i<n; i++) {
    825:       if (indices[i] <  nmin) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index %D's value %D is smaller than minimum given %D",i,indices[i],nmin);
    826:       if (indices[i] >= nmax) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index %D's value %D is larger than maximum given %D",i,indices[i],nmax);
    827:     }
    828:   }
    829:   /* Count number of unique entries */
    830:   unique = (n>0);
    831:   for (i=0; i<n-1; i++) {
    832:     if (indices[i+1] != indices[i]) unique++;
    833:   }
    834:   PetscMalloc1(nmax-nmin-unique,&nindices);
    835:   cnt  = 0;
    836:   for (i=nmin,j=0; i<nmax; i++) {
    837:     if (j<n && i==indices[j]) do { j++; } while (j<n && i==indices[j]);
    838:     else nindices[cnt++] = i;
    839:   }
    840:   if (cnt != nmax-nmin-unique) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Number of entries found in complement %D does not match expected %D",cnt,nmax-nmin-unique);
    841:   ISCreateGeneral(PetscObjectComm((PetscObject)is),cnt,nindices,PETSC_OWN_POINTER,isout);
    842:   ISRestoreIndices(is,&indices);
    843:   return(0);
    844: }