Date: 2022-03-04T17:38:56+00:00

Actual source code: gamg.c

      1: /*
      2:  GAMG geometric-algebric multigrid PC - Mark Adams 2011
      3:  */
      4: #include <petsc/private/matimpl.h>
      5: #include <../src/ksp/pc/impls/gamg/gamg.h>
      6: #include <../src/ksp/ksp/impls/cheby/chebyshevimpl.h>

      8: #if defined(PETSC_HAVE_CUDA)
      9:   #include <cuda_runtime.h>
     10: #endif

     12: #if defined(PETSC_HAVE_HIP)
     13:   #include <hip/hip_runtime.h>
     14: #endif

     16: PetscLogEvent petsc_gamg_setup_events[NUM_SET];
     17: PetscLogEvent petsc_gamg_setup_matmat_events[PETSC_MG_MAXLEVELS][3];
     18: PetscLogEvent PC_GAMGGraph_AGG;
     19: PetscLogEvent PC_GAMGGraph_GEO;
     20: PetscLogEvent PC_GAMGCoarsen_AGG;
     21: PetscLogEvent PC_GAMGCoarsen_GEO;
     22: PetscLogEvent PC_GAMGProlongator_AGG;
     23: PetscLogEvent PC_GAMGProlongator_GEO;
     24: PetscLogEvent PC_GAMGOptProlongator_AGG;

     26: /* #define GAMG_STAGES */
     27: #if defined(GAMG_STAGES)
     28: static PetscLogStage gamg_stages[PETSC_MG_MAXLEVELS];
     29: #endif

     31: static PetscFunctionList GAMGList = NULL;
     32: static PetscBool PCGAMGPackageInitialized;

     34: /* ----------------------------------------------------------------------------- */
     35: PetscErrorCode PCReset_GAMG(PC pc)
     36: {
     37:   PetscErrorCode ierr, level;
     38:   PC_MG          *mg      = (PC_MG*)pc->data;
     39:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

     42:   PetscFree(pc_gamg->data);
     43:   pc_gamg->data_sz = 0;
     44:   PetscFree(pc_gamg->orig_data);
     45:   for (level = 0; level < PETSC_MG_MAXLEVELS ; level++) {
     46:     mg->min_eigen_DinvA[level] = 0;
     47:     mg->max_eigen_DinvA[level] = 0;
     48:   }
     49:   pc_gamg->emin = 0;
     50:   pc_gamg->emax = 0;
     51:   return(0);
     52: }

     54: /* -------------------------------------------------------------------------- */
     55: /*
     56:    PCGAMGCreateLevel_GAMG: create coarse op with RAP.  repartition and/or reduce number
     57:      of active processors.

     59:    Input Parameter:
     60:    . pc - parameters + side effect: coarse data in 'pc_gamg->data' and
     61:           'pc_gamg->data_sz' are changed via repartitioning/reduction.
     62:    . Amat_fine - matrix on this fine (k) level
     63:    . cr_bs - coarse block size
     64:    In/Output Parameter:
     65:    . a_P_inout - prolongation operator to the next level (k-->k-1)
     66:    . a_nactive_proc - number of active procs
     67:    Output Parameter:
     68:    . a_Amat_crs - coarse matrix that is created (k-1)
     69: */

     71: static PetscErrorCode PCGAMGCreateLevel_GAMG(PC pc,Mat Amat_fine,PetscInt cr_bs,Mat *a_P_inout,Mat *a_Amat_crs,PetscMPIInt *a_nactive_proc,IS * Pcolumnperm, PetscBool is_last)
     72: {
     73:   PetscErrorCode  ierr;
     74:   PC_MG           *mg         = (PC_MG*)pc->data;
     75:   PC_GAMG         *pc_gamg    = (PC_GAMG*)mg->innerctx;
     76:   Mat             Cmat,Pold=*a_P_inout;
     77:   MPI_Comm        comm;
     78:   PetscMPIInt     rank,size,new_size,nactive=*a_nactive_proc;
     79:   PetscInt        ncrs_eq,ncrs,f_bs;

     82:   PetscObjectGetComm((PetscObject)Amat_fine,&comm);
     83:   MPI_Comm_rank(comm, &rank);
     84:   MPI_Comm_size(comm, &size);
     85:   MatGetBlockSize(Amat_fine, &f_bs);
     86:   PetscLogEventBegin(petsc_gamg_setup_matmat_events[pc_gamg->current_level][1],0,0,0,0);
     87:   MatPtAP(Amat_fine, Pold, MAT_INITIAL_MATRIX, 2.0, &Cmat);
     88:   PetscLogEventEnd(petsc_gamg_setup_matmat_events[pc_gamg->current_level][1],0,0,0,0);

     90:   if (Pcolumnperm) *Pcolumnperm = NULL;

     92:   /* set 'ncrs' (nodes), 'ncrs_eq' (equations)*/
     93:   MatGetLocalSize(Cmat, &ncrs_eq, NULL);
     94:   if (pc_gamg->data_cell_rows>0) {
     95:     ncrs = pc_gamg->data_sz/pc_gamg->data_cell_cols/pc_gamg->data_cell_rows;
     96:   } else {
     97:     PetscInt  bs;
     98:     MatGetBlockSize(Cmat, &bs);
     99:     ncrs = ncrs_eq/bs;
    100:   }
    101:   /* get number of PEs to make active 'new_size', reduce, can be any integer 1-P */
    102:   if (pc_gamg->level_reduction_factors[pc_gamg->current_level] == 0 && PetscDefined(HAVE_CUDA) && pc_gamg->current_level==0) { /* 0 turns reducing to 1 process/device on; do for HIP, etc. */
    103: #if defined(PETSC_HAVE_CUDA)
    104:     PetscShmComm pshmcomm;
    105:     PetscMPIInt  locrank;
    106:     MPI_Comm     loccomm;
    107:     PetscInt     s_nnodes,r_nnodes, new_new_size;
    108:     cudaError_t  cerr;
    109:     int          devCount;
    110:     PetscShmCommGet(comm,&pshmcomm);
    111:     PetscShmCommGetMpiShmComm(pshmcomm,&loccomm);
    112:     MPI_Comm_rank(loccomm, &locrank);
    113:     s_nnodes = !locrank;
    114:     MPI_Allreduce(&s_nnodes,&r_nnodes,1,MPIU_INT,MPI_SUM,comm);
    115:     if (size%r_nnodes) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"odd number of nodes np=%D nnodes%D",size,r_nnodes);
    116:     devCount = 0;
    117:     cerr = cudaGetDeviceCount(&devCount);
    118:     cudaGetLastError(); /* Reset the last error */
    119:     if (cerr == cudaSuccess && devCount >= 1) { /* There are devices, else go to heuristic */
    120:       new_new_size = r_nnodes * devCount;
    121:       new_size = new_new_size;
    122:       PetscInfo5(pc,"Fine grid with Cuda. %D nodes. Change new active set size %d --> %d (devCount=%d #nodes=%D)\n",r_nnodes,nactive,new_size,devCount,r_nnodes);
    123:     } else {
    124:       PetscInfo(pc,"With Cuda but no device. Use heuristics.");
    125:       goto HEURISTIC;
    126:     }
    127: #else
    128:     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"should not be here");
    129: #endif
    130:   } else if (pc_gamg->level_reduction_factors[pc_gamg->current_level] > 0) {
    131:     if (nactive%pc_gamg->level_reduction_factors[pc_gamg->current_level]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"odd number of active process %D wrt reduction factor %D",nactive,pc_gamg->level_reduction_factors[pc_gamg->current_level]);
    132:     new_size = nactive/pc_gamg->level_reduction_factors[pc_gamg->current_level];
    133:     PetscInfo3(pc,"Manually setting reduction to %d active processes (%d/%D)\n",new_size,nactive,pc_gamg->level_reduction_factors[pc_gamg->current_level]);
    134:   } else if (is_last && !pc_gamg->use_parallel_coarse_grid_solver) {
    135:     new_size = 1;
    136:     PetscInfo1(pc,"Force coarsest grid reduction to %d active processes\n",new_size);
    137:   } else {
    138:     PetscInt ncrs_eq_glob;
    139: #if defined(PETSC_HAVE_CUDA)
    140:     HEURISTIC:
    141: #endif
    142:     MatGetSize(Cmat, &ncrs_eq_glob, NULL);
    143:     new_size = (PetscMPIInt)((float)ncrs_eq_glob/(float)pc_gamg->min_eq_proc + 0.5); /* hardwire min. number of eq/proc */
    144:     if (!new_size) new_size = 1; /* not likely, posible? */
    145:     else if (new_size >= nactive) new_size = nactive; /* no change, rare */
    146:     PetscInfo2(pc,"Coarse grid reduction from %d to %d active processes\n",nactive,new_size);
    147:   }
    148:   if (new_size==nactive) {
    149:     *a_Amat_crs = Cmat; /* output - no repartitioning or reduction - could bail here */
    150:     if (new_size < size) {
    151:       /* odd case where multiple coarse grids are on one processor or no coarsening ... */
    152:       PetscInfo1(pc,"reduced grid using same number of processors (%d) as last grid (use larger coarse grid)\n",nactive);
    153:       if (pc_gamg->cpu_pin_coarse_grids) {
    154:         MatBindToCPU(*a_Amat_crs,PETSC_TRUE);
    155:         MatBindToCPU(*a_P_inout,PETSC_TRUE);
    156:       }
    157:     }
    158:     /* we know that the grid structure can be reused in MatPtAP */
    159:   } else { /* reduce active processors - we know that the grid structure can NOT be reused in MatPtAP */
    160:     PetscInt       *counts,*newproc_idx,ii,jj,kk,strideNew,*tidx,ncrs_new,ncrs_eq_new,nloc_old,expand_factor=1,rfactor=1;
    161:     IS             is_eq_newproc,is_eq_num,is_eq_num_prim,new_eq_indices;
    162:     nloc_old = ncrs_eq/cr_bs;
    163:     if (ncrs_eq % cr_bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"ncrs_eq %D not divisible by cr_bs %D",ncrs_eq,cr_bs);
    164:     /* get new_size and rfactor */
    165:     if (pc_gamg->layout_type==PCGAMG_LAYOUT_SPREAD || !pc_gamg->repart) {
    166:       /* find factor */
    167:       if (new_size == 1) rfactor = size; /* don't modify */
    168:       else {
    169:         PetscReal best_fact = 0.;
    170:         jj = -1;
    171:         for (kk = 1 ; kk <= size ; kk++) {
    172:           if (!(size%kk)) { /* a candidate */
    173:             PetscReal nactpe = (PetscReal)size/(PetscReal)kk, fact = nactpe/(PetscReal)new_size;
    174:             if (fact > 1.0) fact = 1./fact; /* keep fact < 1 */
    175:             if (fact > best_fact) {
    176:               best_fact = fact; jj = kk;
    177:             }
    178:           }
    179:         }
    180:         if (jj != -1) rfactor = jj;
    181:         else rfactor = 1; /* a prime */
    182:         if (pc_gamg->layout_type == PCGAMG_LAYOUT_COMPACT) expand_factor = 1;
    183:         else expand_factor = rfactor;
    184:       }
    185:       new_size = size/rfactor; /* make new size one that is factor */
    186:       if (new_size==nactive) { /* no repartitioning or reduction, bail out because nested here (rare) */
    187:         *a_Amat_crs = Cmat;
    188:         PetscInfo2(pc,"Finding factorable processor set stopped reduction: new_size=%d, neq(loc)=%D\n",new_size,ncrs_eq);
    189:         return(0);
    190:       }
    191:     }
    192:     PetscLogEventBegin(petsc_gamg_setup_events[SET12],0,0,0,0);
    193:     /* make 'is_eq_newproc' */
    194:     PetscMalloc1(size, &counts);
    195:     if (pc_gamg->repart) {
    196:       /* Repartition Cmat_{k} and move columns of P^{k}_{k-1} and coordinates of primal part accordingly */
    197:       Mat      adj;
    198:       PetscInfo4(pc,"Repartition: size (active): %d --> %d, %D local equations, using %s process layout\n",*a_nactive_proc, new_size, ncrs_eq, (pc_gamg->layout_type==PCGAMG_LAYOUT_COMPACT) ? "compact" : "spread");
    199:       /* get 'adj' */
    200:       if (cr_bs == 1) {
    201:         MatConvert(Cmat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
    202:       } else {
    203:         /* make a scalar matrix to partition (no Stokes here) */
    204:         Mat               tMat;
    205:         PetscInt          Istart_crs,Iend_crs,ncols,jj,Ii;
    206:         const PetscScalar *vals;
    207:         const PetscInt    *idx;
    208:         PetscInt          *d_nnz, *o_nnz, M, N;
    209:         static PetscInt   llev = 0; /* ugly but just used for debugging */
    210:         MatType           mtype;

    212:         PetscMalloc2(ncrs, &d_nnz,ncrs, &o_nnz);
    213:         MatGetOwnershipRange(Cmat, &Istart_crs, &Iend_crs);
    214:         MatGetSize(Cmat, &M, &N);
    215:         for (Ii = Istart_crs, jj = 0; Ii < Iend_crs; Ii += cr_bs, jj++) {
    216:           MatGetRow(Cmat,Ii,&ncols,NULL,NULL);
    217:           d_nnz[jj] = ncols/cr_bs;
    218:           o_nnz[jj] = ncols/cr_bs;
    219:           MatRestoreRow(Cmat,Ii,&ncols,NULL,NULL);
    220:           if (d_nnz[jj] > ncrs) d_nnz[jj] = ncrs;
    221:           if (o_nnz[jj] > (M/cr_bs-ncrs)) o_nnz[jj] = M/cr_bs-ncrs;
    222:         }

    224:         MatGetType(Amat_fine,&mtype);
    225:         MatCreate(comm, &tMat);
    226:         MatSetSizes(tMat, ncrs, ncrs,PETSC_DETERMINE, PETSC_DETERMINE);
    227:         MatSetType(tMat,mtype);
    228:         MatSeqAIJSetPreallocation(tMat,0,d_nnz);
    229:         MatMPIAIJSetPreallocation(tMat,0,d_nnz,0,o_nnz);
    230:         PetscFree2(d_nnz,o_nnz);

    232:         for (ii = Istart_crs; ii < Iend_crs; ii++) {
    233:           PetscInt dest_row = ii/cr_bs;
    234:           MatGetRow(Cmat,ii,&ncols,&idx,&vals);
    235:           for (jj = 0; jj < ncols; jj++) {
    236:             PetscInt    dest_col = idx[jj]/cr_bs;
    237:             PetscScalar v        = 1.0;
    238:             MatSetValues(tMat,1,&dest_row,1,&dest_col,&v,ADD_VALUES);
    239:           }
    240:           MatRestoreRow(Cmat,ii,&ncols,&idx,&vals);
    241:         }
    242:         MatAssemblyBegin(tMat,MAT_FINAL_ASSEMBLY);
    243:         MatAssemblyEnd(tMat,MAT_FINAL_ASSEMBLY);

    245:         if (llev++ == -1) {
    246:           PetscViewer viewer; char fname[32];
    247:           PetscSNPrintf(fname,sizeof(fname),"part_mat_%D.mat",llev);
    248:           PetscViewerBinaryOpen(comm,fname,FILE_MODE_WRITE,&viewer);
    249:           MatView(tMat, viewer);
    250:           PetscViewerDestroy(&viewer);
    251:         }
    252:         MatConvert(tMat, MATMPIADJ, MAT_INITIAL_MATRIX, &adj);
    253:         MatDestroy(&tMat);
    254:       } /* create 'adj' */

    256:       { /* partition: get newproc_idx */
    257:         char            prefix[256];
    258:         const char      *pcpre;
    259:         const PetscInt  *is_idx;
    260:         MatPartitioning mpart;
    261:         IS              proc_is;

    263:         MatPartitioningCreate(comm, &mpart);
    264:         MatPartitioningSetAdjacency(mpart, adj);
    265:         PCGetOptionsPrefix(pc, &pcpre);
    266:         PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
    267:         PetscObjectSetOptionsPrefix((PetscObject)mpart,prefix);
    268:         MatPartitioningSetFromOptions(mpart);
    269:         MatPartitioningSetNParts(mpart, new_size);
    270:         MatPartitioningApply(mpart, &proc_is);
    271:         MatPartitioningDestroy(&mpart);

    273:         /* collect IS info */
    274:         PetscMalloc1(ncrs_eq, &newproc_idx);
    275:         ISGetIndices(proc_is, &is_idx);
    276:         for (kk = jj = 0 ; kk < nloc_old ; kk++) {
    277:           for (ii = 0 ; ii < cr_bs ; ii++, jj++) {
    278:             newproc_idx[jj] = is_idx[kk] * expand_factor; /* distribution */
    279:           }
    280:         }
    281:         ISRestoreIndices(proc_is, &is_idx);
    282:         ISDestroy(&proc_is);
    283:       }
    284:       MatDestroy(&adj);

    286:       ISCreateGeneral(comm, ncrs_eq, newproc_idx, PETSC_COPY_VALUES, &is_eq_newproc);
    287:       PetscFree(newproc_idx);
    288:     } else { /* simple aggregation of parts -- 'is_eq_newproc' */
    289:       PetscInt targetPE;
    290:       if (new_size==nactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"new_size==nactive. Should not happen");
    291:       PetscInfo1(pc,"Number of equations (loc) %D with simple aggregation\n",ncrs_eq);
    292:       targetPE = (rank/rfactor)*expand_factor;
    293:       ISCreateStride(comm, ncrs_eq, targetPE, 0, &is_eq_newproc);
    294:     } /* end simple 'is_eq_newproc' */

    296:     /*
    297:       Create an index set from the is_eq_newproc index set to indicate the mapping TO
    298:     */
    299:     ISPartitioningToNumbering(is_eq_newproc, &is_eq_num);
    300:     is_eq_num_prim = is_eq_num;
    301:     /*
    302:       Determine how many equations/vertices are assigned to each processor
    303:     */
    304:     ISPartitioningCount(is_eq_newproc, size, counts);
    305:     ncrs_eq_new = counts[rank];
    306:     ISDestroy(&is_eq_newproc);
    307:     ncrs_new = ncrs_eq_new/cr_bs;

    309:     PetscFree(counts);
    310:     /* data movement scope -- this could be moved to subclasses so that we don't try to cram all auxilary data into some complex abstracted thing */
    311:     {
    312:       Vec            src_crd, dest_crd;
    313:       const PetscInt *idx,ndata_rows=pc_gamg->data_cell_rows,ndata_cols=pc_gamg->data_cell_cols,node_data_sz=ndata_rows*ndata_cols;
    314:       VecScatter     vecscat;
    315:       PetscScalar    *array;
    316:       IS isscat;
    317:       /* move data (for primal equations only) */
    318:       /* Create a vector to contain the newly ordered element information */
    319:       VecCreate(comm, &dest_crd);
    320:       VecSetSizes(dest_crd, node_data_sz*ncrs_new, PETSC_DECIDE);
    321:       VecSetType(dest_crd,VECSTANDARD); /* this is needed! */
    322:       /*
    323:         There are 'ndata_rows*ndata_cols' data items per node, (one can think of the vectors of having
    324:         a block size of ...).  Note, ISs are expanded into equation space by 'cr_bs'.
    325:       */
    326:       PetscMalloc1(ncrs*node_data_sz, &tidx);
    327:       ISGetIndices(is_eq_num_prim, &idx);
    328:       for (ii=0,jj=0; ii<ncrs; ii++) {
    329:         PetscInt id = idx[ii*cr_bs]/cr_bs; /* get node back */
    330:         for (kk=0; kk<node_data_sz; kk++, jj++) tidx[jj] = id*node_data_sz + kk;
    331:       }
    332:       ISRestoreIndices(is_eq_num_prim, &idx);
    333:       ISCreateGeneral(comm, node_data_sz*ncrs, tidx, PETSC_COPY_VALUES, &isscat);
    334:       PetscFree(tidx);
    335:       /*
    336:         Create a vector to contain the original vertex information for each element
    337:       */
    338:       VecCreateSeq(PETSC_COMM_SELF, node_data_sz*ncrs, &src_crd);
    339:       for (jj=0; jj<ndata_cols; jj++) {
    340:         const PetscInt stride0=ncrs*pc_gamg->data_cell_rows;
    341:         for (ii=0; ii<ncrs; ii++) {
    342:           for (kk=0; kk<ndata_rows; kk++) {
    343:             PetscInt    ix = ii*ndata_rows + kk + jj*stride0, jx = ii*node_data_sz + kk*ndata_cols + jj;
    344:             PetscScalar tt = (PetscScalar)pc_gamg->data[ix];
    345:             VecSetValues(src_crd, 1, &jx, &tt, INSERT_VALUES);
    346:           }
    347:         }
    348:       }
    349:       VecAssemblyBegin(src_crd);
    350:       VecAssemblyEnd(src_crd);
    351:       /*
    352:         Scatter the element vertex information (still in the original vertex ordering)
    353:         to the correct processor
    354:       */
    355:       VecScatterCreate(src_crd, NULL, dest_crd, isscat, &vecscat);
    356:       ISDestroy(&isscat);
    357:       VecScatterBegin(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
    358:       VecScatterEnd(vecscat,src_crd,dest_crd,INSERT_VALUES,SCATTER_FORWARD);
    359:       VecScatterDestroy(&vecscat);
    360:       VecDestroy(&src_crd);
    361:       /*
    362:         Put the element vertex data into a new allocation of the gdata->ele
    363:       */
    364:       PetscFree(pc_gamg->data);
    365:       PetscMalloc1(node_data_sz*ncrs_new, &pc_gamg->data);

    367:       pc_gamg->data_sz = node_data_sz*ncrs_new;
    368:       strideNew        = ncrs_new*ndata_rows;

    370:       VecGetArray(dest_crd, &array);
    371:       for (jj=0; jj<ndata_cols; jj++) {
    372:         for (ii=0; ii<ncrs_new; ii++) {
    373:           for (kk=0; kk<ndata_rows; kk++) {
    374:             PetscInt ix = ii*ndata_rows + kk + jj*strideNew, jx = ii*node_data_sz + kk*ndata_cols + jj;
    375:             pc_gamg->data[ix] = PetscRealPart(array[jx]);
    376:           }
    377:         }
    378:       }
    379:       VecRestoreArray(dest_crd, &array);
    380:       VecDestroy(&dest_crd);
    381:     }
    382:     /* move A and P (columns) with new layout */
    383:     PetscLogEventBegin(petsc_gamg_setup_events[SET13],0,0,0,0);
    384:     /*
    385:       Invert for MatCreateSubMatrix
    386:     */
    387:     ISInvertPermutation(is_eq_num, ncrs_eq_new, &new_eq_indices);
    388:     ISSort(new_eq_indices); /* is this needed? */
    389:     ISSetBlockSize(new_eq_indices, cr_bs);
    390:     if (is_eq_num != is_eq_num_prim) {
    391:       ISDestroy(&is_eq_num_prim); /* could be same as 'is_eq_num' */
    392:     }
    393:     if (Pcolumnperm) {
    394:       PetscObjectReference((PetscObject)new_eq_indices);
    395:       *Pcolumnperm = new_eq_indices;
    396:     }
    397:     ISDestroy(&is_eq_num);
    398:     PetscLogEventEnd(petsc_gamg_setup_events[SET13],0,0,0,0);
    399:     PetscLogEventBegin(petsc_gamg_setup_events[SET14],0,0,0,0);
    400:     /* 'a_Amat_crs' output */
    401:     {
    402:       Mat mat;
    403:       MatCreateSubMatrix(Cmat, new_eq_indices, new_eq_indices, MAT_INITIAL_MATRIX, &mat);
    404:       *a_Amat_crs = mat;
    405:     }
    406:     MatDestroy(&Cmat);

    408:     PetscLogEventEnd(petsc_gamg_setup_events[SET14],0,0,0,0);
    409:     /* prolongator */
    410:     {
    411:       IS       findices;
    412:       PetscInt Istart,Iend;
    413:       Mat      Pnew;

    415:       MatGetOwnershipRange(Pold, &Istart, &Iend);
    416:       PetscLogEventBegin(petsc_gamg_setup_events[SET15],0,0,0,0);
    417:       ISCreateStride(comm,Iend-Istart,Istart,1,&findices);
    418:       ISSetBlockSize(findices,f_bs);
    419:       MatCreateSubMatrix(Pold, findices, new_eq_indices, MAT_INITIAL_MATRIX, &Pnew);
    420:       ISDestroy(&findices);
    421:       MatSetOption(Pnew,MAT_FORM_EXPLICIT_TRANSPOSE,PETSC_TRUE);

    423:       PetscLogEventEnd(petsc_gamg_setup_events[SET15],0,0,0,0);
    424:       MatDestroy(a_P_inout);

    426:       /* output - repartitioned */
    427:       *a_P_inout = Pnew;
    428:     }
    429:     ISDestroy(&new_eq_indices);

    431:     *a_nactive_proc = new_size; /* output */

    433:     /* pinning on reduced grids, not a bad heuristic and optimization gets folded into process reduction optimization */
    434:     if (pc_gamg->cpu_pin_coarse_grids) {
    435: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
    436:       static PetscInt llev = 2;
    437:       PetscInfo1(pc,"Pinning level %D to the CPU\n",llev++);
    438: #endif
    439:       MatBindToCPU(*a_Amat_crs,PETSC_TRUE);
    440:       MatBindToCPU(*a_P_inout,PETSC_TRUE);
    441:       if (1) { /* HACK: move this to MatBindCPU_MPIAIJXXX; lvec is created, need to pin it, this is done in MatSetUpMultiply_MPIAIJ. Hack */
    442:         Mat         A = *a_Amat_crs, P = *a_P_inout;
    443:         PetscMPIInt size;
    444:         MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
    445:         if (size > 1) {
    446:           Mat_MPIAIJ     *a = (Mat_MPIAIJ*)A->data, *p = (Mat_MPIAIJ*)P->data;
    447:           VecBindToCPU(a->lvec,PETSC_TRUE);
    448:           VecBindToCPU(p->lvec,PETSC_TRUE);
    449:         }
    450:       }
    451:     }
    452:     PetscLogEventEnd(petsc_gamg_setup_events[SET12],0,0,0,0);
    453:   }
    454:   return(0);
    455: }

    457: PetscErrorCode PCGAMGSquareGraph_GAMG(PC a_pc, Mat Gmat1, Mat* Gmat2)
    458: {
    460:   const char     *prefix;
    461:   char           addp[32];
    462:   PC_MG          *mg      = (PC_MG*)a_pc->data;
    463:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

    466:   PCGetOptionsPrefix(a_pc,&prefix);
    467:   PetscInfo1(a_pc,"Square Graph on level %D\n",pc_gamg->current_level+1);
    468:   MatProductCreate(Gmat1,Gmat1,NULL,Gmat2);
    469:   MatSetOptionsPrefix(*Gmat2,prefix);
    470:   PetscSNPrintf(addp,sizeof(addp),"pc_gamg_square_%d_",pc_gamg->current_level);
    471:   MatAppendOptionsPrefix(*Gmat2,addp);
    472:   if ((*Gmat2)->structurally_symmetric) {
    473:     MatProductSetType(*Gmat2,MATPRODUCT_AB);
    474:   } else {
    475:     MatSetOption(Gmat1,MAT_FORM_EXPLICIT_TRANSPOSE,PETSC_TRUE);
    476:     MatProductSetType(*Gmat2,MATPRODUCT_AtB);
    477:   }
    478:   MatProductSetFromOptions(*Gmat2);
    479:   PetscLogEventBegin(petsc_gamg_setup_matmat_events[pc_gamg->current_level][0],0,0,0,0);
    480:   MatProductSymbolic(*Gmat2);
    481:   PetscLogEventEnd(petsc_gamg_setup_matmat_events[pc_gamg->current_level][0],0,0,0,0);
    482:   MatProductClear(*Gmat2);
    483:   /* we only need the sparsity, cheat and tell PETSc the matrix has been assembled */
    484:   (*Gmat2)->assembled = PETSC_TRUE;
    485:   return(0);
    486: }

    488: /* -------------------------------------------------------------------------- */
    489: /*
    490:    PCSetUp_GAMG - Prepares for the use of the GAMG preconditioner
    491:                     by setting data structures and options.

    493:    Input Parameter:
    494: .  pc - the preconditioner context

    496: */
    497: PetscErrorCode PCSetUp_GAMG(PC pc)
    498: {
    500:   PC_MG          *mg      = (PC_MG*)pc->data;
    501:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
    502:   Mat            Pmat     = pc->pmat;
    503:   PetscInt       fine_level,level,level1,bs,M,N,qq,lidx,nASMBlocksArr[PETSC_MG_MAXLEVELS];
    504:   MPI_Comm       comm;
    505:   PetscMPIInt    rank,size,nactivepe;
    506:   Mat            Aarr[PETSC_MG_MAXLEVELS],Parr[PETSC_MG_MAXLEVELS];
    507:   IS             *ASMLocalIDsArr[PETSC_MG_MAXLEVELS];
    508:   PetscLogDouble nnz0=0.,nnztot=0.;
    509:   MatInfo        info;
    510:   PetscBool      is_last = PETSC_FALSE;

    513:   PetscObjectGetComm((PetscObject)pc,&comm);
    514:   MPI_Comm_rank(comm,&rank);
    515:   MPI_Comm_size(comm,&size);

    517:   if (pc->setupcalled) {
    518:     if (!pc_gamg->reuse_prol || pc->flag == DIFFERENT_NONZERO_PATTERN) {
    519:       /* reset everything */
    520:       PCReset_MG(pc);
    521:       pc->setupcalled = 0;
    522:     } else {
    523:       PC_MG_Levels **mglevels = mg->levels;
    524:       /* just do Galerkin grids */
    525:       Mat          B,dA,dB;

    527:       if (pc_gamg->Nlevels > 1) {
    528:         PetscInt gl;
    529:         /* currently only handle case where mat and pmat are the same on coarser levels */
    530:         KSPGetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,&dA,&dB);
    531:         /* (re)set to get dirty flag */
    532:         KSPSetOperators(mglevels[pc_gamg->Nlevels-1]->smoothd,dA,dB);

    534:         for (level=pc_gamg->Nlevels-2,gl=0; level>=0; level--,gl++) {
    535:           MatReuse reuse = MAT_INITIAL_MATRIX ;

    537:           /* matrix structure can change from repartitioning or process reduction but don't know if we have process reduction here. Should fix */
    538:           KSPGetOperators(mglevels[level]->smoothd,NULL,&B);
    539:           if (B->product) {
    540:             if (B->product->A == dB && B->product->B == mglevels[level+1]->interpolate) {
    541:               reuse = MAT_REUSE_MATRIX;
    542:             }
    543:           }
    544:           if (reuse == MAT_INITIAL_MATRIX) { MatDestroy(&mglevels[level]->A); }
    545:           if (reuse == MAT_REUSE_MATRIX) {
    546:             PetscInfo1(pc,"RAP after first solve, reuse matrix level %D\n",level);
    547:           } else {
    548:             PetscInfo1(pc,"RAP after first solve, new matrix level %D\n",level);
    549:           }
    550:           PetscLogEventBegin(petsc_gamg_setup_matmat_events[gl][1],0,0,0,0);
    551:           MatPtAP(dB,mglevels[level+1]->interpolate,reuse,PETSC_DEFAULT,&B);
    552:           PetscLogEventEnd(petsc_gamg_setup_matmat_events[gl][1],0,0,0,0);
    553:           if (reuse == MAT_INITIAL_MATRIX) mglevels[level]->A = B;
    554:           KSPSetOperators(mglevels[level]->smoothd,B,B);
    555:           dB   = B;
    556:         }
    557:       }

    559:       PCSetUp_MG(pc);
    560:       return(0);
    561:     }
    562:   }

    564:   if (!pc_gamg->data) {
    565:     if (pc_gamg->orig_data) {
    566:       MatGetBlockSize(Pmat, &bs);
    567:       MatGetLocalSize(Pmat, &qq, NULL);

    569:       pc_gamg->data_sz        = (qq/bs)*pc_gamg->orig_data_cell_rows*pc_gamg->orig_data_cell_cols;
    570:       pc_gamg->data_cell_rows = pc_gamg->orig_data_cell_rows;
    571:       pc_gamg->data_cell_cols = pc_gamg->orig_data_cell_cols;

    573:       PetscMalloc1(pc_gamg->data_sz, &pc_gamg->data);
    574:       for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->data[qq] = pc_gamg->orig_data[qq];
    575:     } else {
    576:       if (!pc_gamg->ops->createdefaultdata) SETERRQ(comm,PETSC_ERR_PLIB,"'createdefaultdata' not set(?) need to support NULL data");
    577:       pc_gamg->ops->createdefaultdata(pc,Pmat);
    578:     }
    579:   }

    581:   /* cache original data for reuse */
    582:   if (!pc_gamg->orig_data && (PetscBool)(!pc_gamg->reuse_prol)) {
    583:     PetscMalloc1(pc_gamg->data_sz, &pc_gamg->orig_data);
    584:     for (qq=0; qq<pc_gamg->data_sz; qq++) pc_gamg->orig_data[qq] = pc_gamg->data[qq];
    585:     pc_gamg->orig_data_cell_rows = pc_gamg->data_cell_rows;
    586:     pc_gamg->orig_data_cell_cols = pc_gamg->data_cell_cols;
    587:   }

    589:   /* get basic dims */
    590:   MatGetBlockSize(Pmat, &bs);
    591:   MatGetSize(Pmat, &M, &N);

    593:   MatGetInfo(Pmat,MAT_GLOBAL_SUM,&info); /* global reduction */
    594:   nnz0   = info.nz_used;
    595:   nnztot = info.nz_used;
    596:   PetscInfo6(pc,"level %D) N=%D, n data rows=%D, n data cols=%D, nnz/row (ave)=%d, np=%D\n",0,M,pc_gamg->data_cell_rows,pc_gamg->data_cell_cols,(int)(nnz0/(PetscReal)M+0.5),size);

    598:   /* Get A_i and R_i */
    599:   for (level=0, Aarr[0]=Pmat, nactivepe = size; level < (pc_gamg->Nlevels-1) && (!level || M>pc_gamg->coarse_eq_limit); level++) {
    600:     pc_gamg->current_level = level;
    601:     if (level >= PETSC_MG_MAXLEVELS) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Too many levels %D",level);
    602:     level1 = level + 1;
    603:     PetscLogEventBegin(petsc_gamg_setup_events[SET1],0,0,0,0);
    604: #if defined(GAMG_STAGES)
    605:     PetscLogStagePush(gamg_stages[level]);
    606: #endif
    607:     { /* construct prolongator */
    608:       Mat              Gmat;
    609:       PetscCoarsenData *agg_lists;
    610:       Mat              Prol11;

    612:       pc_gamg->ops->graph(pc,Aarr[level], &Gmat);
    613:       pc_gamg->ops->coarsen(pc, &Gmat, &agg_lists);
    614:       pc_gamg->ops->prolongator(pc,Aarr[level],Gmat,agg_lists,&Prol11);

    616:       /* could have failed to create new level */
    617:       if (Prol11) {
    618:         const char *prefix;
    619:         char       addp[32];

    621:         /* get new block size of coarse matrices */
    622:         MatGetBlockSizes(Prol11, NULL, &bs);

    624:         if (pc_gamg->ops->optprolongator) {
    625:           /* smooth */
    626:           pc_gamg->ops->optprolongator(pc, Aarr[level], &Prol11);
    627:         }

    629:         if (pc_gamg->use_aggs_in_asm) {
    630:           PetscInt bs;
    631:           MatGetBlockSizes(Prol11, &bs, NULL);
    632:           PetscCDGetASMBlocks(agg_lists, bs, Gmat, &nASMBlocksArr[level], &ASMLocalIDsArr[level]);
    633:         }

    635:         PCGetOptionsPrefix(pc,&prefix);
    636:         MatSetOptionsPrefix(Prol11,prefix);
    637:         PetscSNPrintf(addp,sizeof(addp),"pc_gamg_prolongator_%d_",(int)level);
    638:         MatAppendOptionsPrefix(Prol11,addp);
    639:         /* Always generate the transpose with CUDA
    640:            Such behaviour can be adapted with -pc_gamg_prolongator_ prefixed options */
    641:         MatSetOption(Prol11,MAT_FORM_EXPLICIT_TRANSPOSE,PETSC_TRUE);
    642:         MatSetFromOptions(Prol11);
    643:         Parr[level1] = Prol11;
    644:       } else Parr[level1] = NULL; /* failed to coarsen */

    646:       MatDestroy(&Gmat);
    647:       PetscCDDestroy(agg_lists);
    648:     } /* construct prolongator scope */
    649:     PetscLogEventEnd(petsc_gamg_setup_events[SET1],0,0,0,0);
    650:     if (!level) Aarr[0] = Pmat; /* use Pmat for finest level setup */
    651:     if (!Parr[level1]) { /* failed to coarsen */
    652:       PetscInfo1(pc,"Stop gridding, level %D\n",level);
    653: #if defined(GAMG_STAGES)
    654:       PetscLogStagePop();
    655: #endif
    656:       break;
    657:     }
    658:     PetscLogEventBegin(petsc_gamg_setup_events[SET2],0,0,0,0);
    659:     MatGetSize(Parr[level1], &M, &N); /* N is next M, a loop test variables */
    660:     if (is_last) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Is last ?");
    661:     if (N <= pc_gamg->coarse_eq_limit) is_last = PETSC_TRUE;
    662:     if (level1 == pc_gamg->Nlevels-1) is_last = PETSC_TRUE;
    663:     pc_gamg->ops->createlevel(pc, Aarr[level], bs, &Parr[level1], &Aarr[level1], &nactivepe, NULL, is_last);

    665:     PetscLogEventEnd(petsc_gamg_setup_events[SET2],0,0,0,0);
    666:     MatGetSize(Aarr[level1], &M, &N); /* M is loop test variables */
    667:     MatGetInfo(Aarr[level1], MAT_GLOBAL_SUM, &info);
    668:     nnztot += info.nz_used;
    669:     PetscInfo5(pc,"%D) N=%D, n data cols=%D, nnz/row (ave)=%d, %D active pes\n",level1,M,pc_gamg->data_cell_cols,(int)(info.nz_used/(PetscReal)M),nactivepe);

    671: #if defined(GAMG_STAGES)
    672:     PetscLogStagePop();
    673: #endif
    674:     /* stop if one node or one proc -- could pull back for singular problems */
    675:     if ((pc_gamg->data_cell_cols && M/pc_gamg->data_cell_cols < 2) || (!pc_gamg->data_cell_cols && M/bs < 2)) {
    676:        PetscInfo2(pc,"HARD stop of coarsening on level %D.  Grid too small: %D block nodes\n",level,M/bs);
    677:       level++;
    678:       break;
    679:     }
    680:   } /* levels */
    681:   PetscFree(pc_gamg->data);

    683:   PetscInfo2(pc,"%D levels, grid complexity = %g\n",level+1,nnztot/nnz0);
    684:   pc_gamg->Nlevels = level + 1;
    685:   fine_level       = level;
    686:   PCMGSetLevels(pc,pc_gamg->Nlevels,NULL);

    688:   if (pc_gamg->Nlevels > 1) { /* don't setup MG if one level */
    689:     PetscErrorCode (*savesetfromoptions[PETSC_MG_MAXLEVELS])(PetscOptionItems*,KSP);

    691:     /* set default smoothers & set operators */
    692:     for (lidx = 1, level = pc_gamg->Nlevels-2; lidx <= fine_level; lidx++, level--) {
    693:       KSP smoother;
    694:       PC  subpc;

    696:       PCMGGetSmoother(pc, lidx, &smoother);
    697:       KSPGetPC(smoother, &subpc);

    699:       KSPSetNormType(smoother, KSP_NORM_NONE);
    700:       /* set ops */
    701:       KSPSetOperators(smoother, Aarr[level], Aarr[level]);
    702:       PCMGSetInterpolation(pc, lidx, Parr[level+1]);

    704:       /* set defaults */
    705:       KSPSetType(smoother, KSPCHEBYSHEV);

    707:       /* set blocks for ASM smoother that uses the 'aggregates' */
    708:       if (pc_gamg->use_aggs_in_asm) {
    709:         PetscInt sz;
    710:         IS       *iss;

    712:         sz   = nASMBlocksArr[level];
    713:         iss  = ASMLocalIDsArr[level];
    714:         PCSetType(subpc, PCASM);
    715:         PCASMSetOverlap(subpc, 0);
    716:         PCASMSetType(subpc,PC_ASM_BASIC);
    717:         if (!sz) {
    718:           IS       is;
    719:           ISCreateGeneral(PETSC_COMM_SELF, 0, NULL, PETSC_COPY_VALUES, &is);
    720:           PCASMSetLocalSubdomains(subpc, 1, NULL, &is);
    721:           ISDestroy(&is);
    722:         } else {
    723:           PetscInt kk;
    724:           PCASMSetLocalSubdomains(subpc, sz, NULL, iss);
    725:           for (kk=0; kk<sz; kk++) {
    726:             ISDestroy(&iss[kk]);
    727:           }
    728:           PetscFree(iss);
    729:         }
    730:         ASMLocalIDsArr[level] = NULL;
    731:         nASMBlocksArr[level]  = 0;
    732:       } else {
    733:         PCSetType(subpc, PCSOR);
    734:       }
    735:     }
    736:     {
    737:       /* coarse grid */
    738:       KSP smoother,*k2; PC subpc,pc2; PetscInt ii,first;
    739:       Mat Lmat = Aarr[(level=pc_gamg->Nlevels-1)]; lidx = 0;

    741:       PCMGGetSmoother(pc, lidx, &smoother);
    742:       KSPSetOperators(smoother, Lmat, Lmat);
    743:       if (!pc_gamg->use_parallel_coarse_grid_solver) {
    744:         KSPSetNormType(smoother, KSP_NORM_NONE);
    745:         KSPGetPC(smoother, &subpc);
    746:         PCSetType(subpc, PCBJACOBI);
    747:         PCSetUp(subpc);
    748:         PCBJacobiGetSubKSP(subpc,&ii,&first,&k2);
    749:         if (ii != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_PLIB,"ii %D is not one",ii);
    750:         KSPGetPC(k2[0],&pc2);
    751:         PCSetType(pc2, PCLU);
    752:         PCFactorSetShiftType(pc2,MAT_SHIFT_INBLOCKS);
    753:         KSPSetTolerances(k2[0],PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,1);
    754:         KSPSetType(k2[0], KSPPREONLY);
    755:       }
    756:     }

    758:     /* should be called in PCSetFromOptions_GAMG(), but cannot be called prior to PCMGSetLevels() */
    759:     PetscObjectOptionsBegin((PetscObject)pc);
    760:     PCSetFromOptions_MG(PetscOptionsObject,pc);
    761:     PetscOptionsEnd();
    762:     PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);

    764:     /* setup cheby eigen estimates from SA */
    765:     if (pc_gamg->use_sa_esteig==1) {
    766:       for (lidx = 1, level = pc_gamg->Nlevels-2; level >= 0 ; lidx++, level--) {
    767:         KSP       smoother;
    768:         PetscBool ischeb;

    770:         savesetfromoptions[level] = NULL;
    771:         PCMGGetSmoother(pc, lidx, &smoother);
    772:         PetscObjectTypeCompare((PetscObject)smoother,KSPCHEBYSHEV,&ischeb);
    773:         if (ischeb) {
    774:           KSP_Chebyshev *cheb = (KSP_Chebyshev*)smoother->data;

    776:           KSPSetFromOptions(smoother); /* let command line emax override using SA's eigenvalues */
    777:           if (mg->max_eigen_DinvA[level] > 0 && cheb->emax == 0.) {
    778:             PC        subpc;
    779:             PetscBool isjac;
    780:             KSPGetPC(smoother, &subpc);
    781:             PetscObjectTypeCompare((PetscObject)subpc,PCJACOBI,&isjac);
    782:             if (isjac && pc_gamg->use_sa_esteig==1) {
    783:               PetscReal emax,emin;

    785:               emin = mg->min_eigen_DinvA[level];
    786:               emax = mg->max_eigen_DinvA[level];
    787:               PetscInfo4(pc,"PCSetUp_GAMG: call KSPChebyshevSetEigenvalues on level %D (N=%D) with emax = %g emin = %g\n",level,Aarr[level]->rmap->N,(double)emax,(double)emin);
    788:               cheb->emin_computed = emin;
    789:               cheb->emax_computed = emax;
    790:               KSPChebyshevSetEigenvalues(smoother, cheb->tform[2]*emin + cheb->tform[3]*emax, cheb->tform[0]*emin + cheb->tform[1]*emax);

    792:               /* We have set the eigenvalues and consumed the transformation values
    793:                  prevent from flagging the recomputation of the eigenvalues again in PCSetUp_MG
    794:                  below when setfromoptions will be called again */
    795:               savesetfromoptions[level] = smoother->ops->setfromoptions;
    796:               smoother->ops->setfromoptions = NULL;
    797:             }
    798:           }
    799:         }
    800:       }
    801:     }

    803:     PCSetUp_MG(pc);

    805:     /* restore Chebyshev smoother for next calls */
    806:     if (pc_gamg->use_sa_esteig==1) {
    807:       for (lidx = 1, level = pc_gamg->Nlevels-2; level >= 0 ; lidx++, level--) {
    808:         if (savesetfromoptions[level]) {
    809:           KSP smoother;
    810:           PCMGGetSmoother(pc, lidx, &smoother);
    811:           smoother->ops->setfromoptions = savesetfromoptions[level];
    812:         }
    813:       }
    814:     }

    816:     /* clean up */
    817:     for (level=1; level<pc_gamg->Nlevels; level++) {
    818:       MatDestroy(&Parr[level]);
    819:       MatDestroy(&Aarr[level]);
    820:     }
    821:   } else {
    822:     KSP smoother;

    824:     PetscInfo(pc,"One level solver used (system is seen as DD). Using default solver.\n");
    825:     PCMGGetSmoother(pc, 0, &smoother);
    826:     KSPSetOperators(smoother, Aarr[0], Aarr[0]);
    827:     KSPSetType(smoother, KSPPREONLY);
    828:     PCSetUp_MG(pc);
    829:   }
    830:   return(0);
    831: }

    833: /* ------------------------------------------------------------------------- */
    834: /*
    835:  PCDestroy_GAMG - Destroys the private context for the GAMG preconditioner
    836:    that was created with PCCreate_GAMG().

    838:    Input Parameter:
    839: .  pc - the preconditioner context

    841:    Application Interface Routine: PCDestroy()
    842: */
    843: PetscErrorCode PCDestroy_GAMG(PC pc)
    844: {
    846:   PC_MG          *mg     = (PC_MG*)pc->data;
    847:   PC_GAMG        *pc_gamg= (PC_GAMG*)mg->innerctx;

    850:   PCReset_GAMG(pc);
    851:   if (pc_gamg->ops->destroy) {
    852:     (*pc_gamg->ops->destroy)(pc);
    853:   }
    854:   PetscFree(pc_gamg->ops);
    855:   PetscFree(pc_gamg->gamg_type_name);
    856:   PetscFree(pc_gamg);
    857:   PCDestroy_MG(pc);
    858:   return(0);
    859: }

    861: /*@
    862:    PCGAMGSetProcEqLim - Set number of equations to aim for per process on the coarse grids via processor reduction.

    864:    Logically Collective on PC

    866:    Input Parameters:
    867: +  pc - the preconditioner context
    868: -  n - the number of equations

    870:    Options Database Key:
    871: .  -pc_gamg_process_eq_limit <limit>

    873:    Notes:
    874:     GAMG will reduce the number of MPI processes used directly on the coarse grids so that there are around <limit> equations on each process
    875:           that has degrees of freedom

    877:    Level: intermediate

    879: .seealso: PCGAMGSetCoarseEqLim(), PCGAMGSetRankReductionFactors()
    880: @*/
    881: PetscErrorCode  PCGAMGSetProcEqLim(PC pc, PetscInt n)
    882: {

    887:   PetscTryMethod(pc,"PCGAMGSetProcEqLim_C",(PC,PetscInt),(pc,n));
    888:   return(0);
    889: }

    891: static PetscErrorCode PCGAMGSetProcEqLim_GAMG(PC pc, PetscInt n)
    892: {
    893:   PC_MG   *mg      = (PC_MG*)pc->data;
    894:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    897:   if (n>0) pc_gamg->min_eq_proc = n;
    898:   return(0);
    899: }

    901: /*@
    902:    PCGAMGSetCoarseEqLim - Set maximum number of equations on coarsest grid.

    904:  Collective on PC

    906:    Input Parameters:
    907: +  pc - the preconditioner context
    908: -  n - maximum number of equations to aim for

    910:    Options Database Key:
    911: .  -pc_gamg_coarse_eq_limit <limit>

    913:    Notes: For example -pc_gamg_coarse_eq_limit 1000 will stop coarsening once the coarse grid
    914:      has less than 1000 unknowns.

    916:    Level: intermediate

    918: .seealso: PCGAMGSetProcEqLim(), PCGAMGSetRankReductionFactors()
    919: @*/
    920: PetscErrorCode PCGAMGSetCoarseEqLim(PC pc, PetscInt n)
    921: {

    926:   PetscTryMethod(pc,"PCGAMGSetCoarseEqLim_C",(PC,PetscInt),(pc,n));
    927:   return(0);
    928: }

    930: static PetscErrorCode PCGAMGSetCoarseEqLim_GAMG(PC pc, PetscInt n)
    931: {
    932:   PC_MG   *mg      = (PC_MG*)pc->data;
    933:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    936:   if (n>0) pc_gamg->coarse_eq_limit = n;
    937:   return(0);
    938: }

    940: /*@
    941:    PCGAMGSetRepartition - Repartition the degrees of freedom across the processors on the coarser grids

    943:    Collective on PC

    945:    Input Parameters:
    946: +  pc - the preconditioner context
    947: -  n - PETSC_TRUE or PETSC_FALSE

    949:    Options Database Key:
    950: .  -pc_gamg_repartition <true,false>

    952:    Notes:
    953:     this will generally improve the loading balancing of the work on each level

    955:    Level: intermediate

    957: .seealso: ()
    958: @*/
    959: PetscErrorCode PCGAMGSetRepartition(PC pc, PetscBool n)
    960: {

    965:   PetscTryMethod(pc,"PCGAMGSetRepartition_C",(PC,PetscBool),(pc,n));
    966:   return(0);
    967: }

    969: static PetscErrorCode PCGAMGSetRepartition_GAMG(PC pc, PetscBool n)
    970: {
    971:   PC_MG   *mg      = (PC_MG*)pc->data;
    972:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    975:   pc_gamg->repart = n;
    976:   return(0);
    977: }

    979: /*@
    980:    PCGAMGSetEstEigKSPMaxIt - Set number of KSP iterations in eigen estimator (for Cheby)

    982:    Collective on PC

    984:    Input Parameters:
    985: +  pc - the preconditioner context
    986: -  n - number of its

    988:    Options Database Key:
    989: .  -pc_gamg_esteig_ksp_max_it <its>

    991:    Notes:

    993:    Level: intermediate

    995: .seealso: ()
    996: @*/
    997: PetscErrorCode PCGAMGSetEstEigKSPMaxIt(PC pc, PetscInt n)
    998: {

    1003:   PetscTryMethod(pc,"PCGAMGSetEstEigKSPMaxIt_C",(PC,PetscInt),(pc,n));
    1004:   return(0);
    1005: }

    1007: static PetscErrorCode PCGAMGSetEstEigKSPMaxIt_GAMG(PC pc, PetscInt n)
    1008: {
    1009:   PC_MG   *mg      = (PC_MG*)pc->data;
    1010:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1013:   pc_gamg->esteig_max_it = n;
    1014:   return(0);
    1015: }

    1017: /*@
    1018:    PCGAMGSetUseSAEstEig - Use eigen estimate from smoothed aggregation for Cheby smoother

    1020:    Collective on PC

    1022:    Input Parameters:
    1023: +  pc - the preconditioner context
    1024: -  n - number of its

    1026:    Options Database Key:
    1027: .  -pc_gamg_use_sa_esteig <true,false>

    1029:    Notes:

    1031:    Level: intermediate

    1033: .seealso: ()
    1034: @*/
    1035: PetscErrorCode PCGAMGSetUseSAEstEig(PC pc, PetscBool n)
    1036: {

    1041:   PetscTryMethod(pc,"PCGAMGSetUseSAEstEig_C",(PC,PetscBool),(pc,n));
    1042:   return(0);
    1043: }

    1045: static PetscErrorCode PCGAMGSetUseSAEstEig_GAMG(PC pc, PetscBool n)
    1046: {
    1047:   PC_MG   *mg      = (PC_MG*)pc->data;
    1048:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1051:   pc_gamg->use_sa_esteig = n ? 1 : 0;
    1052:   return(0);
    1053: }

    1055: /*@C
    1056:    PCGAMGSetEstEigKSPType - Set type of KSP in eigen estimator (for Cheby)

    1058:    Collective on PC

    1060:    Input Parameters:
    1061: +  pc - the preconditioner context
    1062: -  t - ksp type

    1064:    Options Database Key:
    1065: .  -pc_gamg_esteig_ksp_type <type>

    1067:    Notes:

    1069:    Level: intermediate

    1071: .seealso: ()
    1072: @*/
    1073: PetscErrorCode PCGAMGSetEstEigKSPType(PC pc, char t[])
    1074: {

    1079:   PetscTryMethod(pc,"PCGAMGSetEstEigKSPType_C",(PC,char[]),(pc,t));
    1080:   return(0);
    1081: }

    1083: static PetscErrorCode PCGAMGSetEstEigKSPType_GAMG(PC pc, char t[])
    1084: {
    1086:   PC_MG   *mg      = (PC_MG*)pc->data;
    1087:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1090:   PetscStrcpy(pc_gamg->esteig_type,t);
    1091:   return(0);
    1092: }

    1094: /*@
    1095:    PCGAMGSetEigenvalues - Set eigenvalues

    1097:    Collective on PC

    1099:    Input Parameters:
    1100: +  pc - the preconditioner context
    1101: -  emax - max eigenvalue
    1102: .  emin - min eigenvalue

    1104:    Options Database Key:
    1105: .  -pc_gamg_eigenvalues

    1107:    Level: intermediate

    1109: .seealso: PCGAMGSetEstEigKSPMaxIt(), PCGAMGSetUseSAEstEig(), PCGAMGSetEstEigKSPType()
    1110: @*/
    1111: PetscErrorCode PCGAMGSetEigenvalues(PC pc, PetscReal emax,PetscReal emin)
    1112: {

    1117:   PetscTryMethod(pc,"PCGAMGSetEigenvalues_C",(PC,PetscReal,PetscReal),(pc,emax,emin));
    1118:   return(0);
    1119: }

    1121: static PetscErrorCode PCGAMGSetEigenvalues_GAMG(PC pc,PetscReal emax,PetscReal emin)
    1122: {
    1123:   PC_MG          *mg      = (PC_MG*)pc->data;
    1124:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

    1127:   if (emax <= emin) SETERRQ2(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_INCOMP,"Maximum eigenvalue must be larger than minimum: max %g min %g",(double)emax,(double)emin);
    1128:   if (emax*emin <= 0.0) SETERRQ2(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_INCOMP,"Both eigenvalues must be of the same sign: max %g min %g",(double)emax,(double)emin);
    1129:   pc_gamg->emax = emax;
    1130:   pc_gamg->emin = emin;

    1132:   return(0);
    1133: }

    1135: /*@
    1136:    PCGAMGSetReuseInterpolation - Reuse prolongation when rebuilding algebraic multigrid preconditioner

    1138:    Collective on PC

    1140:    Input Parameters:
    1141: +  pc - the preconditioner context
    1142: -  n - PETSC_TRUE or PETSC_FALSE

    1144:    Options Database Key:
    1145: .  -pc_gamg_reuse_interpolation <true,false>

    1147:    Level: intermediate

    1149:    Notes:
    1150:     this may negatively affect the convergence rate of the method on new matrices if the matrix entries change a great deal, but allows
    1151:           rebuilding the preconditioner quicker.

    1153: .seealso: ()
    1154: @*/
    1155: PetscErrorCode PCGAMGSetReuseInterpolation(PC pc, PetscBool n)
    1156: {

    1161:   PetscTryMethod(pc,"PCGAMGSetReuseInterpolation_C",(PC,PetscBool),(pc,n));
    1162:   return(0);
    1163: }

    1165: static PetscErrorCode PCGAMGSetReuseInterpolation_GAMG(PC pc, PetscBool n)
    1166: {
    1167:   PC_MG   *mg      = (PC_MG*)pc->data;
    1168:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1171:   pc_gamg->reuse_prol = n;
    1172:   return(0);
    1173: }

    1175: /*@
    1176:    PCGAMGASMSetUseAggs - Have the PCGAMG smoother on each level use the aggregates defined by the coarsening process as the subdomains for the additive Schwarz preconditioner.

    1178:    Collective on PC

    1180:    Input Parameters:
    1181: +  pc - the preconditioner context
    1182: -  flg - PETSC_TRUE to use aggregates, PETSC_FALSE to not

    1184:    Options Database Key:
    1185: .  -pc_gamg_asm_use_agg

    1187:    Level: intermediate

    1189: .seealso: ()
    1190: @*/
    1191: PetscErrorCode PCGAMGASMSetUseAggs(PC pc, PetscBool flg)
    1192: {

    1197:   PetscTryMethod(pc,"PCGAMGASMSetUseAggs_C",(PC,PetscBool),(pc,flg));
    1198:   return(0);
    1199: }

    1201: static PetscErrorCode PCGAMGASMSetUseAggs_GAMG(PC pc, PetscBool flg)
    1202: {
    1203:   PC_MG   *mg      = (PC_MG*)pc->data;
    1204:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1207:   pc_gamg->use_aggs_in_asm = flg;
    1208:   return(0);
    1209: }

    1211: /*@
    1212:    PCGAMGSetUseParallelCoarseGridSolve - allow a parallel coarse grid solver

    1214:    Collective on PC

    1216:    Input Parameters:
    1217: +  pc - the preconditioner context
    1218: -  flg - PETSC_TRUE to not force coarse grid onto one processor

    1220:    Options Database Key:
    1221: .  -pc_gamg_use_parallel_coarse_grid_solver

    1223:    Level: intermediate

    1225: .seealso: PCGAMGSetCoarseGridLayoutType(), PCGAMGSetCpuPinCoarseGrids()
    1226: @*/
    1227: PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve(PC pc, PetscBool flg)
    1228: {

    1233:   PetscTryMethod(pc,"PCGAMGSetUseParallelCoarseGridSolve_C",(PC,PetscBool),(pc,flg));
    1234:   return(0);
    1235: }

    1237: static PetscErrorCode PCGAMGSetUseParallelCoarseGridSolve_GAMG(PC pc, PetscBool flg)
    1238: {
    1239:   PC_MG   *mg      = (PC_MG*)pc->data;
    1240:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1243:   pc_gamg->use_parallel_coarse_grid_solver = flg;
    1244:   return(0);
    1245: }

    1247: /*@
    1248:    PCGAMGSetCpuPinCoarseGrids - pin reduced grids to CPU

    1250:    Collective on PC

    1252:    Input Parameters:
    1253: +  pc - the preconditioner context
    1254: -  flg - PETSC_TRUE to pin coarse grids to CPU

    1256:    Options Database Key:
    1257: .  -pc_gamg_cpu_pin_coarse_grids

    1259:    Level: intermediate

    1261: .seealso: PCGAMGSetCoarseGridLayoutType(), PCGAMGSetUseParallelCoarseGridSolve()
    1262: @*/
    1263: PetscErrorCode PCGAMGSetCpuPinCoarseGrids(PC pc, PetscBool flg)
    1264: {

    1269:   PetscTryMethod(pc,"PCGAMGSetCpuPinCoarseGrids_C",(PC,PetscBool),(pc,flg));
    1270:   return(0);
    1271: }

    1273: static PetscErrorCode PCGAMGSetCpuPinCoarseGrids_GAMG(PC pc, PetscBool flg)
    1274: {
    1275:   PC_MG   *mg      = (PC_MG*)pc->data;
    1276:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1279:   pc_gamg->cpu_pin_coarse_grids = flg;
    1280:   return(0);
    1281: }

    1283: /*@
    1284:    PCGAMGSetCoarseGridLayoutType - place reduce grids on processors with natural order (compact type)

    1286:    Collective on PC

    1288:    Input Parameters:
    1289: +  pc - the preconditioner context
    1290: -  flg - Layout type

    1292:    Options Database Key:
    1293: .  -pc_gamg_coarse_grid_layout_type

    1295:    Level: intermediate

    1297: .seealso: PCGAMGSetUseParallelCoarseGridSolve(), PCGAMGSetCpuPinCoarseGrids()
    1298: @*/
    1299: PetscErrorCode PCGAMGSetCoarseGridLayoutType(PC pc, PCGAMGLayoutType flg)
    1300: {

    1305:   PetscTryMethod(pc,"PCGAMGSetCoarseGridLayoutType_C",(PC,PCGAMGLayoutType),(pc,flg));
    1306:   return(0);
    1307: }

    1309: static PetscErrorCode PCGAMGSetCoarseGridLayoutType_GAMG(PC pc, PCGAMGLayoutType flg)
    1310: {
    1311:   PC_MG   *mg      = (PC_MG*)pc->data;
    1312:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1315:   pc_gamg->layout_type = flg;
    1316:   return(0);
    1317: }

    1319: /*@
    1320:    PCGAMGSetNlevels -  Sets the maximum number of levels PCGAMG will use

    1322:    Not collective on PC

    1324:    Input Parameters:
    1325: +  pc - the preconditioner
    1326: -  n - the maximum number of levels to use

    1328:    Options Database Key:
    1329: .  -pc_mg_levels

    1331:    Level: intermediate

    1333: .seealso: ()
    1334: @*/
    1335: PetscErrorCode PCGAMGSetNlevels(PC pc, PetscInt n)
    1336: {

    1341:   PetscTryMethod(pc,"PCGAMGSetNlevels_C",(PC,PetscInt),(pc,n));
    1342:   return(0);
    1343: }

    1345: static PetscErrorCode PCGAMGSetNlevels_GAMG(PC pc, PetscInt n)
    1346: {
    1347:   PC_MG   *mg      = (PC_MG*)pc->data;
    1348:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;

    1351:   pc_gamg->Nlevels = n;
    1352:   return(0);
    1353: }

    1355: /*@
    1356:    PCGAMGSetThreshold - Relative threshold to use for dropping edges in aggregation graph

    1358:    Not collective on PC

    1360:    Input Parameters:
    1361: +  pc - the preconditioner context
    1362: .  v - array of threshold values for finest n levels; 0.0 means keep all nonzero entries in the graph; negative means keep even zero entries in the graph
    1363: -  n - number of threshold values provided in array

    1365:    Options Database Key:
    1366: .  -pc_gamg_threshold <threshold>

    1368:    Notes:
    1369:     Increasing the threshold decreases the rate of coarsening. Conversely reducing the threshold increases the rate of coarsening (aggressive coarsening) and thereby reduces the complexity of the coarse grids, and generally results in slower solver converge rates. Reducing coarse grid complexity reduced the complexity of Galerkin coarse grid construction considerably.
    1370:     Before coarsening or aggregating the graph, GAMG removes small values from the graph with this threshold, and thus reducing the coupling in the graph and a different (perhaps better) coarser set of points.

    1372:     If n is less than the total number of coarsenings (see PCGAMGSetNlevels()), then threshold scaling (see PCGAMGSetThresholdScale()) is used for each successive coarsening.
    1373:     In this case, PCGAMGSetThresholdScale() must be called before PCGAMGSetThreshold().
    1374:     If n is greater than the total number of levels, the excess entries in threshold will not be used.

    1376:    Level: intermediate

    1378: .seealso: PCGAMGFilterGraph(), PCGAMGSetSquareGraph()
    1379: @*/
    1380: PetscErrorCode PCGAMGSetThreshold(PC pc, PetscReal v[], PetscInt n)
    1381: {

    1387:   PetscTryMethod(pc,"PCGAMGSetThreshold_C",(PC,PetscReal[],PetscInt),(pc,v,n));
    1388:   return(0);
    1389: }

    1391: static PetscErrorCode PCGAMGSetThreshold_GAMG(PC pc, PetscReal v[], PetscInt n)
    1392: {
    1393:   PC_MG   *mg      = (PC_MG*)pc->data;
    1394:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
    1395:   PetscInt i;
    1397:   for (i=0; i<PetscMin(n,PETSC_MG_MAXLEVELS); i++) pc_gamg->threshold[i] = v[i];
    1398:   for (; i<PETSC_MG_MAXLEVELS; i++) pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;
    1399:   return(0);
    1400: }

    1402: /*@
    1403:    PCGAMGSetRankReductionFactors - Set manual schedual for process reduction on coarse grids

    1405:    Collective on PC

    1407:    Input Parameters:
    1408: +  pc - the preconditioner context
    1409: .  v - array of reduction factors. 0 for fist value forces a reduction to one process/device on first level in Cuda
    1410: -  n - number of values provided in array

    1412:    Options Database Key:
    1413: .  -pc_gamg_rank_reduction_factors <factors>

    1415:    Level: intermediate

    1417: .seealso: PCGAMGSetProcEqLim(), PCGAMGSetCoarseEqLim()
    1418: @*/
    1419: PetscErrorCode PCGAMGSetRankReductionFactors(PC pc, PetscInt v[], PetscInt n)
    1420: {

    1426:   PetscTryMethod(pc,"PCGAMGSetRankReductionFactors_C",(PC,PetscInt[],PetscInt),(pc,v,n));
    1427:   return(0);
    1428: }

    1430: static PetscErrorCode PCGAMGSetRankReductionFactors_GAMG(PC pc, PetscInt v[], PetscInt n)
    1431: {
    1432:   PC_MG   *mg      = (PC_MG*)pc->data;
    1433:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
    1434:   PetscInt i;
    1436:   for (i=0; i<PetscMin(n,PETSC_MG_MAXLEVELS); i++) pc_gamg->level_reduction_factors[i] = v[i];
    1437:   for (; i<PETSC_MG_MAXLEVELS; i++) pc_gamg->level_reduction_factors[i] = -1; /* 0 stop putting one process/device on first level */
    1438:   return(0);
    1439: }

    1441: /*@
    1442:    PCGAMGSetThresholdScale - Relative threshold reduction at each level

    1444:    Not collective on PC

    1446:    Input Parameters:
    1447: +  pc - the preconditioner context
    1448: -  scale - the threshold value reduction, ussually < 1.0

    1450:    Options Database Key:
    1451: .  -pc_gamg_threshold_scale <v>

    1453:    Notes:
    1454:    The initial threshold (for an arbitrary number of levels starting from the finest) can be set with PCGAMGSetThreshold().
    1455:    This scaling is used for each subsequent coarsening, but must be called before PCGAMGSetThreshold().

    1457:    Level: advanced

    1459: .seealso: PCGAMGSetThreshold()
    1460: @*/
    1461: PetscErrorCode PCGAMGSetThresholdScale(PC pc, PetscReal v)
    1462: {

    1467:   PetscTryMethod(pc,"PCGAMGSetThresholdScale_C",(PC,PetscReal),(pc,v));
    1468:   return(0);
    1469: }

    1471: static PetscErrorCode PCGAMGSetThresholdScale_GAMG(PC pc, PetscReal v)
    1472: {
    1473:   PC_MG   *mg      = (PC_MG*)pc->data;
    1474:   PC_GAMG *pc_gamg = (PC_GAMG*)mg->innerctx;
    1476:   pc_gamg->threshold_scale = v;
    1477:   return(0);
    1478: }

    1480: /*@C
    1481:    PCGAMGSetType - Set solution method

    1483:    Collective on PC

    1485:    Input Parameters:
    1486: +  pc - the preconditioner context
    1487: -  type - PCGAMGAGG, PCGAMGGEO, or PCGAMGCLASSICAL

    1489:    Options Database Key:
    1490: .  -pc_gamg_type <agg,geo,classical> - type of algebraic multigrid to apply

    1492:    Level: intermediate

    1494: .seealso: PCGAMGGetType(), PCGAMG, PCGAMGType
    1495: @*/
    1496: PetscErrorCode PCGAMGSetType(PC pc, PCGAMGType type)
    1497: {

    1502:   PetscTryMethod(pc,"PCGAMGSetType_C",(PC,PCGAMGType),(pc,type));
    1503:   return(0);
    1504: }

    1506: /*@C
    1507:    PCGAMGGetType - Get solution method

    1509:    Collective on PC

    1511:    Input Parameter:
    1512: .  pc - the preconditioner context

    1514:    Output Parameter:
    1515: .  type - the type of algorithm used

    1517:    Level: intermediate

    1519: .seealso: PCGAMGSetType(), PCGAMGType
    1520: @*/
    1521: PetscErrorCode PCGAMGGetType(PC pc, PCGAMGType *type)
    1522: {

    1527:   PetscUseMethod(pc,"PCGAMGGetType_C",(PC,PCGAMGType*),(pc,type));
    1528:   return(0);
    1529: }

    1531: static PetscErrorCode PCGAMGGetType_GAMG(PC pc, PCGAMGType *type)
    1532: {
    1533:   PC_MG          *mg      = (PC_MG*)pc->data;
    1534:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

    1537:   *type = pc_gamg->type;
    1538:   return(0);
    1539: }

    1541: static PetscErrorCode PCGAMGSetType_GAMG(PC pc, PCGAMGType type)
    1542: {
    1543:   PetscErrorCode ierr,(*r)(PC);
    1544:   PC_MG          *mg      = (PC_MG*)pc->data;
    1545:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;

    1548:   pc_gamg->type = type;
    1549:   PetscFunctionListFind(GAMGList,type,&r);
    1550:   if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown GAMG type %s given",type);
    1551:   if (pc_gamg->ops->destroy) {
    1552:     (*pc_gamg->ops->destroy)(pc);
    1553:     PetscMemzero(pc_gamg->ops,sizeof(struct _PCGAMGOps));
    1554:     pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;
    1555:     /* cleaning up common data in pc_gamg - this should disapear someday */
    1556:     pc_gamg->data_cell_cols = 0;
    1557:     pc_gamg->data_cell_rows = 0;
    1558:     pc_gamg->orig_data_cell_cols = 0;
    1559:     pc_gamg->orig_data_cell_rows = 0;
    1560:     PetscFree(pc_gamg->data);
    1561:     pc_gamg->data_sz = 0;
    1562:   }
    1563:   PetscFree(pc_gamg->gamg_type_name);
    1564:   PetscStrallocpy(type,&pc_gamg->gamg_type_name);
    1565:   (*r)(pc);
    1566:   return(0);
    1567: }

    1569: /* -------------------------------------------------------------------------- */
    1570: /*
    1571:    PCMGGetGridComplexity - compute coarse grid complexity of MG hierarchy

    1573:    Input Parameter:
    1574: .  pc - the preconditioner context

    1576:    Output Parameter:
    1577: .  gc - grid complexity = sum_i(nnz_i) / nnz_0

    1579:    Level: advanced
    1580: */
    1581: static PetscErrorCode PCMGGetGridComplexity(PC pc, PetscReal *gc)
    1582: {
    1584:   PC_MG          *mg      = (PC_MG*)pc->data;
    1585:   PC_MG_Levels   **mglevels = mg->levels;
    1586:   PetscInt       lev;
    1587:   PetscLogDouble nnz0 = 0, sgc = 0;
    1588:   MatInfo        info;

    1591:   if (!pc->setupcalled) {
    1592:     *gc = 0;
    1593:     return(0);
    1594:   }
    1595:   if (!mg->nlevels) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MG has no levels");
    1596:   for (lev=0; lev<mg->nlevels; lev++) {
    1597:     Mat dB;
    1598:     KSPGetOperators(mglevels[lev]->smoothd,NULL,&dB);
    1599:     MatGetInfo(dB,MAT_GLOBAL_SUM,&info); /* global reduction */
    1600:     sgc += info.nz_used;
    1601:     if (lev==mg->nlevels-1) nnz0 = info.nz_used;
    1602:   }
    1603:   if (nnz0 > 0) *gc = (PetscReal)(sgc/nnz0);
    1604:   else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Number for grid points on finest level is not available");
    1605:   return(0);
    1606: }

    1608: static PetscErrorCode PCView_GAMG(PC pc,PetscViewer viewer)
    1609: {
    1610:   PetscErrorCode ierr,i;
    1611:   PC_MG          *mg      = (PC_MG*)pc->data;
    1612:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
    1613:   PetscReal       gc=0;
    1615:   PetscViewerASCIIPrintf(viewer,"    GAMG specific options\n");
    1616:   PetscViewerASCIIPrintf(viewer,"      Threshold for dropping small values in graph on each level =");
    1617:   for (i=0;i<mg->nlevels; i++) {
    1618:     PetscViewerASCIIPrintf(viewer," %g",(double)pc_gamg->threshold[i]);
    1619:   }
    1620:   PetscViewerASCIIPrintf(viewer,"\n");
    1621:   PetscViewerASCIIPrintf(viewer,"      Threshold scaling factor for each level not specified = %g\n",(double)pc_gamg->threshold_scale);
    1622:   if (pc_gamg->use_aggs_in_asm) {
    1623:     PetscViewerASCIIPrintf(viewer,"      Using aggregates from coarsening process to define subdomains for PCASM\n");
    1624:   }
    1625:   if (pc_gamg->use_parallel_coarse_grid_solver) {
    1626:     PetscViewerASCIIPrintf(viewer,"      Using parallel coarse grid solver (all coarse grid equations not put on one process)\n");
    1627:   }
    1628: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
    1629:   if (pc_gamg->cpu_pin_coarse_grids) {
    1630:     /* PetscViewerASCIIPrintf(viewer,"      Pinning coarse grids to the CPU)\n"); */
    1631:   }
    1632: #endif
    1633:   /* if (pc_gamg->layout_type==PCGAMG_LAYOUT_COMPACT) { */
    1634:   /*   PetscViewerASCIIPrintf(viewer,"      Put reduced grids on processes in natural order (ie, 0,1,2...)\n"); */
    1635:   /* } else { */
    1636:   /*   PetscViewerASCIIPrintf(viewer,"      Put reduced grids on whole machine (ie, 0,1*f,2*f...,np-f)\n"); */
    1637:   /* } */
    1638:   if (pc_gamg->ops->view) {
    1639:     (*pc_gamg->ops->view)(pc,viewer);
    1640:   }
    1641:   PCMGGetGridComplexity(pc,&gc);
    1642:   PetscViewerASCIIPrintf(viewer,"      Complexity:    grid = %g\n",gc);
    1643:   return(0);
    1644: }

    1646: PetscErrorCode PCSetFromOptions_GAMG(PetscOptionItems *PetscOptionsObject,PC pc)
    1647: {
    1649:   PC_MG          *mg      = (PC_MG*)pc->data;
    1650:   PC_GAMG        *pc_gamg = (PC_GAMG*)mg->innerctx;
    1651:   PetscBool      flag,f2;
    1652:   MPI_Comm       comm;
    1653:   char           prefix[256],tname[32];
    1654:   PetscInt       i,n;
    1655:   const char     *pcpre;
    1656:   static const char *LayoutTypes[] = {"compact","spread","PCGAMGLayoutType","PC_GAMG_LAYOUT",NULL};
    1658:   PetscObjectGetComm((PetscObject)pc,&comm);
    1659:   PetscOptionsHead(PetscOptionsObject,"GAMG options");
    1660:   PetscOptionsFList("-pc_gamg_type","Type of AMG method","PCGAMGSetType",GAMGList, pc_gamg->gamg_type_name, tname, sizeof(tname), &flag);
    1661:   if (flag) {
    1662:     PCGAMGSetType(pc,tname);
    1663:   }
    1664:   PetscOptionsFList("-pc_gamg_esteig_ksp_type","Krylov method for eigen estimator","PCGAMGSetEstEigKSPType",KSPList,pc_gamg->esteig_type,tname,sizeof(tname),&flag);
    1665:   if (flag) {
    1666:     PCGAMGSetEstEigKSPType(pc,tname);
    1667:   }
    1668:   PetscOptionsBool("-pc_gamg_repartition","Repartion coarse grids","PCGAMGSetRepartition",pc_gamg->repart,&pc_gamg->repart,NULL);
    1669:   f2 = PETSC_TRUE;
    1670:   PetscOptionsBool("-pc_gamg_use_sa_esteig","Use eigen estimate from Smoothed aggregation for smoother","PCGAMGSetUseSAEstEig",f2,&f2,&flag);
    1671:   if (flag) pc_gamg->use_sa_esteig = f2 ? 1 : 0;
    1672:   PetscOptionsBool("-pc_gamg_reuse_interpolation","Reuse prolongation operator","PCGAMGReuseInterpolation",pc_gamg->reuse_prol,&pc_gamg->reuse_prol,NULL);
    1673:   PetscOptionsBool("-pc_gamg_asm_use_agg","Use aggregation aggregates for ASM smoother","PCGAMGASMSetUseAggs",pc_gamg->use_aggs_in_asm,&pc_gamg->use_aggs_in_asm,NULL);
    1674:   PetscOptionsBool("-pc_gamg_use_parallel_coarse_grid_solver","Use parallel coarse grid solver (otherwise put last grid on one process)","PCGAMGSetUseParallelCoarseGridSolve",pc_gamg->use_parallel_coarse_grid_solver,&pc_gamg->use_parallel_coarse_grid_solver,NULL);
    1675:   PetscOptionsBool("-pc_gamg_cpu_pin_coarse_grids","Pin coarse grids to the CPU","PCGAMGSetCpuPinCoarseGrids",pc_gamg->cpu_pin_coarse_grids,&pc_gamg->cpu_pin_coarse_grids,NULL);
    1676:   PetscOptionsEnum("-pc_gamg_coarse_grid_layout_type","compact: place reduced grids on processes in natural order; spread: distribute to whole machine for more memory bandwidth","PCGAMGSetCoarseGridLayoutType",LayoutTypes,(PetscEnum)pc_gamg->layout_type,(PetscEnum*)&pc_gamg->layout_type,NULL);
    1677:   PetscOptionsInt("-pc_gamg_process_eq_limit","Limit (goal) on number of equations per process on coarse grids","PCGAMGSetProcEqLim",pc_gamg->min_eq_proc,&pc_gamg->min_eq_proc,NULL);
    1678:   PetscOptionsInt("-pc_gamg_esteig_ksp_max_it","Number of iterations of eigen estimator","PCGAMGSetEstEigKSPMaxIt",pc_gamg->esteig_max_it,&pc_gamg->esteig_max_it,NULL);
    1679:   PetscOptionsInt("-pc_gamg_coarse_eq_limit","Limit on number of equations for the coarse grid","PCGAMGSetCoarseEqLim",pc_gamg->coarse_eq_limit,&pc_gamg->coarse_eq_limit,NULL);
    1680:   PetscOptionsReal("-pc_gamg_threshold_scale","Scaling of threshold for each level not specified","PCGAMGSetThresholdScale",pc_gamg->threshold_scale,&pc_gamg->threshold_scale,NULL);
    1681:   n = PETSC_MG_MAXLEVELS;
    1682:   PetscOptionsRealArray("-pc_gamg_threshold","Relative threshold to use for dropping edges in aggregation graph","PCGAMGSetThreshold",pc_gamg->threshold,&n,&flag);
    1683:   if (!flag || n < PETSC_MG_MAXLEVELS) {
    1684:     if (!flag) n = 1;
    1685:     i = n;
    1686:     do {pc_gamg->threshold[i] = pc_gamg->threshold[i-1]*pc_gamg->threshold_scale;} while (++i<PETSC_MG_MAXLEVELS);
    1687:   }
    1688:   n = PETSC_MG_MAXLEVELS;
    1689:   PetscOptionsIntArray("-pc_gamg_rank_reduction_factors","Manual schedule of coarse grid reduction factors that overrides internal heuristics (0 for first reduction puts one process/device)","PCGAMGSetRankReductionFactors",pc_gamg->level_reduction_factors,&n,&flag);
    1690:   if (!flag) i = 0;
    1691:   else i = n;
    1692:   do {pc_gamg->level_reduction_factors[i] = -1;} while (++i<PETSC_MG_MAXLEVELS);
    1693:   PetscOptionsInt("-pc_mg_levels","Set number of MG levels","PCGAMGSetNlevels",pc_gamg->Nlevels,&pc_gamg->Nlevels,NULL);
    1694:   {
    1695:     PetscReal eminmax[2] = {0., 0.};
    1696:     n = 2;
    1697:     PetscOptionsRealArray("-pc_gamg_eigenvalues","extreme eigenvalues for smoothed aggregation","PCGAMGSetEigenvalues",eminmax,&n,&flag);
    1698:     if (flag) {
    1699:       if (n != 2) SETERRQ(PetscObjectComm((PetscObject)pc),PETSC_ERR_ARG_INCOMP,"-pc_gamg_eigenvalues: must specify 2 parameters, min and max eigenvalues");
    1700:       PCGAMGSetEigenvalues(pc, eminmax[1], eminmax[0]);
    1701:     }
    1702:   }
    1703:   /* set options for subtype */
    1704:   if (pc_gamg->ops->setfromoptions) {(*pc_gamg->ops->setfromoptions)(PetscOptionsObject,pc);}

    1706:   PCGetOptionsPrefix(pc, &pcpre);
    1707:   PetscSNPrintf(prefix,sizeof(prefix),"%spc_gamg_",pcpre ? pcpre : "");
    1708:   PetscOptionsTail();
    1709:   return(0);
    1710: }

    1712: /* -------------------------------------------------------------------------- */
    1713: /*MC
    1714:      PCGAMG - Geometric algebraic multigrid (AMG) preconditioner

    1716:    Options Database Keys:
    1717: +   -pc_gamg_type <type> - one of agg, geo, or classical
    1718: .   -pc_gamg_repartition  <true,default=false> - repartition the degrees of freedom accross the coarse grids as they are determined
    1719: .   -pc_gamg_reuse_interpolation <true,default=false> - when rebuilding the algebraic multigrid preconditioner reuse the previously computed interpolations
    1720: .   -pc_gamg_asm_use_agg <true,default=false> - use the aggregates from the coasening process to defined the subdomains on each level for the PCASM smoother
    1721: .   -pc_gamg_process_eq_limit <limit, default=50> - GAMG will reduce the number of MPI processes used directly on the coarse grids so that there are around <limit>
    1722:                                         equations on each process that has degrees of freedom
    1723: .   -pc_gamg_coarse_eq_limit <limit, default=50> - Set maximum number of equations on coarsest grid to aim for.
    1724: .   -pc_gamg_threshold[] <thresh,default=0> - Before aggregating the graph GAMG will remove small values from the graph on each level
    1725: -   -pc_gamg_threshold_scale <scale,default=1> - Scaling of threshold on each coarser grid if not specified

    1727:    Options Database Keys for default Aggregation:
    1728: +  -pc_gamg_agg_nsmooths <nsmooth, default=1> - number of smoothing steps to use with smooth aggregation
    1729: .  -pc_gamg_sym_graph <true,default=false> - symmetrize the graph before computing the aggregation
    1730: -  -pc_gamg_square_graph <n,default=1> - number of levels to square the graph before aggregating it

    1732:    Multigrid options:
    1733: +  -pc_mg_cycles <v> - v or w, see PCMGSetCycleType()
    1734: .  -pc_mg_distinct_smoothup - configure the up and down (pre and post) smoothers separately, see PCMGSetDistinctSmoothUp()
    1735: .  -pc_mg_type <multiplicative> - (one of) additive multiplicative full kascade
    1736: -  -pc_mg_levels <levels> - Number of levels of multigrid to use.

    1738:   Notes:
    1739:     In order to obtain good performance for PCGAMG for vector valued problems you must
    1740:        Call MatSetBlockSize() to indicate the number of degrees of freedom per grid point
    1741:        Call MatSetNearNullSpace() (or PCSetCoordinates() if solving the equations of elasticity) to indicate the near null space of the operator
    1742:        See the Users Manual Chapter 4 for more details

    1744:   Level: intermediate

    1746: .seealso:  PCCreate(), PCSetType(), MatSetBlockSize(), PCMGType, PCSetCoordinates(), MatSetNearNullSpace(), PCGAMGSetType(), PCGAMGAGG, PCGAMGGEO, PCGAMGCLASSICAL, PCGAMGSetProcEqLim(),
    1747:            PCGAMGSetCoarseEqLim(), PCGAMGSetRepartition(), PCGAMGRegister(), PCGAMGSetReuseInterpolation(), PCGAMGASMSetUseAggs(), PCGAMGSetUseParallelCoarseGridSolve(), PCGAMGSetNlevels(), PCGAMGSetThreshold(), PCGAMGGetType(), PCGAMGSetReuseInterpolation(), PCGAMGSetUseSAEstEig(), PCGAMGSetEstEigKSPMaxIt(), PCGAMGSetEstEigKSPType()
    1748: M*/

    1750: PETSC_EXTERN PetscErrorCode PCCreate_GAMG(PC pc)
    1751: {
    1752:   PetscErrorCode ierr,i;
    1753:   PC_GAMG        *pc_gamg;
    1754:   PC_MG          *mg;

    1757:    /* register AMG type */
    1758:   PCGAMGInitializePackage();

    1760:   /* PCGAMG is an inherited class of PCMG. Initialize pc as PCMG */
    1761:   PCSetType(pc, PCMG);
    1762:   PetscObjectChangeTypeName((PetscObject)pc, PCGAMG);

    1764:   /* create a supporting struct and attach it to pc */
    1765:   PetscNewLog(pc,&pc_gamg);
    1766:   PCMGSetGalerkin(pc,PC_MG_GALERKIN_EXTERNAL);
    1767:   mg           = (PC_MG*)pc->data;
    1768:   mg->innerctx = pc_gamg;

    1770:   PetscNewLog(pc,&pc_gamg->ops);

    1772:   /* these should be in subctx but repartitioning needs simple arrays */
    1773:   pc_gamg->data_sz = 0;
    1774:   pc_gamg->data    = NULL;

    1776:   /* overwrite the pointers of PCMG by the functions of base class PCGAMG */
    1777:   pc->ops->setfromoptions = PCSetFromOptions_GAMG;
    1778:   pc->ops->setup          = PCSetUp_GAMG;
    1779:   pc->ops->reset          = PCReset_GAMG;
    1780:   pc->ops->destroy        = PCDestroy_GAMG;
    1781:   mg->view                = PCView_GAMG;

    1783:   PetscObjectComposeFunction((PetscObject)pc,"PCMGGetLevels_C",PCMGGetLevels_MG);
    1784:   PetscObjectComposeFunction((PetscObject)pc,"PCMGSetLevels_C",PCMGSetLevels_MG);
    1785:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetProcEqLim_C",PCGAMGSetProcEqLim_GAMG);
    1786:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetCoarseEqLim_C",PCGAMGSetCoarseEqLim_GAMG);
    1787:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetRepartition_C",PCGAMGSetRepartition_GAMG);
    1788:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetEstEigKSPType_C",PCGAMGSetEstEigKSPType_GAMG);
    1789:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetEstEigKSPMaxIt_C",PCGAMGSetEstEigKSPMaxIt_GAMG);
    1790:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetEigenvalues_C",PCGAMGSetEigenvalues_GAMG);
    1791:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetUseSAEstEig_C",PCGAMGSetUseSAEstEig_GAMG);
    1792:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetReuseInterpolation_C",PCGAMGSetReuseInterpolation_GAMG);
    1793:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGASMSetUseAggs_C",PCGAMGASMSetUseAggs_GAMG);
    1794:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetUseParallelCoarseGridSolve_C",PCGAMGSetUseParallelCoarseGridSolve_GAMG);
    1795:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetCpuPinCoarseGrids_C",PCGAMGSetCpuPinCoarseGrids_GAMG);
    1796:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetCoarseGridLayoutType_C",PCGAMGSetCoarseGridLayoutType_GAMG);
    1797:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThreshold_C",PCGAMGSetThreshold_GAMG);
    1798:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetRankReductionFactors_C",PCGAMGSetRankReductionFactors_GAMG);
    1799:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetThresholdScale_C",PCGAMGSetThresholdScale_GAMG);
    1800:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetType_C",PCGAMGSetType_GAMG);
    1801:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGGetType_C",PCGAMGGetType_GAMG);
    1802:   PetscObjectComposeFunction((PetscObject)pc,"PCGAMGSetNlevels_C",PCGAMGSetNlevels_GAMG);
    1803:   pc_gamg->repart           = PETSC_FALSE;
    1804:   pc_gamg->reuse_prol       = PETSC_FALSE;
    1805:   pc_gamg->use_aggs_in_asm  = PETSC_FALSE;
    1806:   pc_gamg->use_parallel_coarse_grid_solver = PETSC_FALSE;
    1807:   pc_gamg->cpu_pin_coarse_grids = PETSC_FALSE;
    1808:   pc_gamg->layout_type      = PCGAMG_LAYOUT_SPREAD;
    1809:   pc_gamg->min_eq_proc      = 50;
    1810:   pc_gamg->coarse_eq_limit  = 50;
    1811:   for (i=0;i<PETSC_MG_MAXLEVELS;i++) pc_gamg->threshold[i] = 0.;
    1812:   pc_gamg->threshold_scale = 1.;
    1813:   pc_gamg->Nlevels          = PETSC_MG_MAXLEVELS;
    1814:   pc_gamg->current_level    = 0; /* don't need to init really */
    1815:   PetscStrcpy(pc_gamg->esteig_type,NULL);
    1816:   pc_gamg->esteig_max_it    = 10;
    1817:   pc_gamg->use_sa_esteig    = -1;
    1818:   pc_gamg->emin             = 0;
    1819:   pc_gamg->emax             = 0;

    1821:   pc_gamg->ops->createlevel = PCGAMGCreateLevel_GAMG;

    1823:   /* PCSetUp_GAMG assumes that the type has been set, so set it to the default now */
    1824:   PCGAMGSetType(pc,PCGAMGAGG);
    1825:   return(0);
    1826: }

    1828: /*@C
    1829:  PCGAMGInitializePackage - This function initializes everything in the PCGAMG package. It is called
    1830:     from PCInitializePackage().

    1832:  Level: developer

    1834:  .seealso: PetscInitialize()
    1835: @*/
    1836: PetscErrorCode PCGAMGInitializePackage(void)
    1837: {
    1839:   PetscInt       l;

    1842:   if (PCGAMGPackageInitialized) return(0);
    1843:   PCGAMGPackageInitialized = PETSC_TRUE;
    1844:   PetscFunctionListAdd(&GAMGList,PCGAMGGEO,PCCreateGAMG_GEO);
    1845:   PetscFunctionListAdd(&GAMGList,PCGAMGAGG,PCCreateGAMG_AGG);
    1846:   PetscFunctionListAdd(&GAMGList,PCGAMGCLASSICAL,PCCreateGAMG_Classical);
    1847:   PetscRegisterFinalize(PCGAMGFinalizePackage);

    1849:   /* general events */
    1850:   PetscLogEventRegister("PCGAMGGraph_AGG", 0, &PC_GAMGGraph_AGG);
    1851:   PetscLogEventRegister("PCGAMGGraph_GEO", PC_CLASSID, &PC_GAMGGraph_GEO);
    1852:   PetscLogEventRegister("PCGAMGCoarse_AGG", PC_CLASSID, &PC_GAMGCoarsen_AGG);
    1853:   PetscLogEventRegister("PCGAMGCoarse_GEO", PC_CLASSID, &PC_GAMGCoarsen_GEO);
    1854:   PetscLogEventRegister("PCGAMGProl_AGG", PC_CLASSID, &PC_GAMGProlongator_AGG);
    1855:   PetscLogEventRegister("PCGAMGProl_GEO", PC_CLASSID, &PC_GAMGProlongator_GEO);
    1856:   PetscLogEventRegister("PCGAMGPOpt_AGG", PC_CLASSID, &PC_GAMGOptProlongator_AGG);

    1858:   PetscLogEventRegister("GAMG: createProl", PC_CLASSID, &petsc_gamg_setup_events[SET1]);
    1859:   PetscLogEventRegister("  Graph", PC_CLASSID, &petsc_gamg_setup_events[GRAPH]);
    1860:   /* PetscLogEventRegister("    G.Mat", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_MAT]); */
    1861:   /* PetscLogEventRegister("    G.Filter", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_FILTER]); */
    1862:   /* PetscLogEventRegister("    G.Square", PC_CLASSID, &petsc_gamg_setup_events[GRAPH_SQR]); */
    1863:   PetscLogEventRegister("  MIS/Agg", PC_CLASSID, &petsc_gamg_setup_events[SET4]);
    1864:   PetscLogEventRegister("  geo: growSupp", PC_CLASSID, &petsc_gamg_setup_events[SET5]);
    1865:   PetscLogEventRegister("  geo: triangle", PC_CLASSID, &petsc_gamg_setup_events[SET6]);
    1866:   PetscLogEventRegister("    search-set", PC_CLASSID, &petsc_gamg_setup_events[FIND_V]);
    1867:   PetscLogEventRegister("  SA: col data", PC_CLASSID, &petsc_gamg_setup_events[SET7]);
    1868:   PetscLogEventRegister("  SA: frmProl0", PC_CLASSID, &petsc_gamg_setup_events[SET8]);
    1869:   PetscLogEventRegister("  SA: smooth", PC_CLASSID, &petsc_gamg_setup_events[SET9]);
    1870:   PetscLogEventRegister("GAMG: partLevel", PC_CLASSID, &petsc_gamg_setup_events[SET2]);
    1871:   PetscLogEventRegister("  repartition", PC_CLASSID, &petsc_gamg_setup_events[SET12]);
    1872:   PetscLogEventRegister("  Invert-Sort", PC_CLASSID, &petsc_gamg_setup_events[SET13]);
    1873:   PetscLogEventRegister("  Move A", PC_CLASSID, &petsc_gamg_setup_events[SET14]);
    1874:   PetscLogEventRegister("  Move P", PC_CLASSID, &petsc_gamg_setup_events[SET15]);
    1875:   for (l=0;l<PETSC_MG_MAXLEVELS;l++) {
    1876:     char ename[32];

    1878:     PetscSNPrintf(ename,sizeof(ename),"PCGAMG Squ l%02d",l);
    1879:     PetscLogEventRegister(ename, PC_CLASSID, &petsc_gamg_setup_matmat_events[l][0]);
    1880:     PetscSNPrintf(ename,sizeof(ename),"PCGAMG Gal l%02d",l);
    1881:     PetscLogEventRegister(ename, PC_CLASSID, &petsc_gamg_setup_matmat_events[l][1]);
    1882:     PetscSNPrintf(ename,sizeof(ename),"PCGAMG Opt l%02d",l);
    1883:     PetscLogEventRegister(ename, PC_CLASSID, &petsc_gamg_setup_matmat_events[l][2]);
    1884:   }
    1885:   /* PetscLogEventRegister(" PL move data", PC_CLASSID, &petsc_gamg_setup_events[SET13]); */
    1886:   /* PetscLogEventRegister("GAMG: fix", PC_CLASSID, &petsc_gamg_setup_events[SET10]); */
    1887:   /* PetscLogEventRegister("GAMG: set levels", PC_CLASSID, &petsc_gamg_setup_events[SET11]); */
    1888:   /* create timer stages */
    1889: #if defined(GAMG_STAGES)
    1890:   {
    1891:     char     str[32];
    1892:     PetscInt lidx;
    1893:     sprintf(str,"MG Level %d (finest)",0);
    1894:     PetscLogStageRegister(str, &gamg_stages[0]);
    1895:     for (lidx=1; lidx<9; lidx++) {
    1896:       sprintf(str,"MG Level %d",(int)lidx);
    1897:       PetscLogStageRegister(str, &gamg_stages[lidx]);
    1898:     }
    1899:   }
    1900: #endif
    1901:   return(0);
    1902: }

    1904: /*@C
    1905:  PCGAMGFinalizePackage - This function frees everything from the PCGAMG package. It is
    1906:     called from PetscFinalize() automatically.

    1908:  Level: developer

    1910:  .seealso: PetscFinalize()
    1911: @*/
    1912: PetscErrorCode PCGAMGFinalizePackage(void)
    1913: {

    1917:   PCGAMGPackageInitialized = PETSC_FALSE;
    1918:   PetscFunctionListDestroy(&GAMGList);
    1919:   return(0);
    1920: }

    1922: /*@C
    1923:  PCGAMGRegister - Register a PCGAMG implementation.

    1925:  Input Parameters:
    1926:  + type - string that will be used as the name of the GAMG type.
    1927:  - create - function for creating the gamg context.

    1929:   Level: advanced

    1931:  .seealso: PCGAMGType, PCGAMG, PCGAMGSetType()
    1932: @*/
    1933: PetscErrorCode PCGAMGRegister(PCGAMGType type, PetscErrorCode (*create)(PC))
    1934: {

    1938:   PCGAMGInitializePackage();
    1939:   PetscFunctionListAdd(&GAMGList,type,create);
    1940:   return(0);
    1941: }