Actual source code: agg.c

  1: /*
  2:  GAMG geometric-algebric multigrid PC - Mark Adams 2011
  3:  */

  5: #include <../src/ksp/pc/impls/gamg/gamg.h>
  6: #include <petscblaslapack.h>
  7: #include <petscdm.h>
  8: #include <petsc/private/kspimpl.h>

 10: typedef struct {
 11:   PetscInt   nsmooths;
 12:   PetscInt   aggressive_coarsening_levels; // number of aggressive coarsening levels (square or MISk)
 13:   MatCoarsen crs;
 14: } PC_GAMG_AGG;

 16: /*@
 17:    PCGAMGSetNSmooths - Set number of smoothing steps (1 is typical) used for multigrid on all the levels

 19:    Logically Collective

 21:    Input Parameters:
 22: .  pc - the preconditioner context

 24:    Options Database Key:
 25: .  -pc_gamg_agg_nsmooths <nsmooth, default=1> - number of smoothing steps to use with smooth aggregation

 27:    Level: intermediate

 29: .seealso: `PCMG`, `PCGAMG`
 30: @*/
 31: PetscErrorCode PCGAMGSetNSmooths(PC pc, PetscInt n)
 32: {
 33:   PetscFunctionBegin;
 36:   PetscTryMethod(pc, "PCGAMGSetNSmooths_C", (PC, PetscInt), (pc, n));
 37:   PetscFunctionReturn(PETSC_SUCCESS);
 38: }

 40: static PetscErrorCode PCGAMGSetNSmooths_AGG(PC pc, PetscInt n)
 41: {
 42:   PC_MG       *mg          = (PC_MG *)pc->data;
 43:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
 44:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;

 46:   PetscFunctionBegin;
 47:   pc_gamg_agg->nsmooths = n;
 48:   PetscFunctionReturn(PETSC_SUCCESS);
 49: }

 51: /*@
 52:    PCGAMGSetAggressiveLevels -  Use aggressive coarsening on first n levels

 54:    Logically Collective

 56:    Input Parameters:
 57: +  pc - the preconditioner context
 58: -  n - 0, 1 or more

 60:    Options Database Key:
 61: .  -pc_gamg_aggressive_coarsening <n,default = 1> - Number of levels to square the graph on before aggregating it

 63:    Level: intermediate

 65: .seealso: `PCGAMG`, `PCGAMGSetThreshold()`
 66: @*/
 67: PetscErrorCode PCGAMGSetAggressiveLevels(PC pc, PetscInt n)
 68: {
 69:   PetscFunctionBegin;
 72:   PetscTryMethod(pc, "PCGAMGSetAggressiveLevels_C", (PC, PetscInt), (pc, n));
 73:   PetscFunctionReturn(PETSC_SUCCESS);
 74: }

 76: static PetscErrorCode PCGAMGSetAggressiveLevels_AGG(PC pc, PetscInt n)
 77: {
 78:   PC_MG       *mg          = (PC_MG *)pc->data;
 79:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
 80:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;

 82:   PetscFunctionBegin;
 83:   pc_gamg_agg->aggressive_coarsening_levels = n;
 84:   PetscFunctionReturn(PETSC_SUCCESS);
 85: }

 87: static PetscErrorCode PCSetFromOptions_GAMG_AGG(PC pc, PetscOptionItems *PetscOptionsObject)
 88: {
 89:   PC_MG       *mg          = (PC_MG *)pc->data;
 90:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
 91:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;

 93:   PetscFunctionBegin;
 94:   PetscOptionsHeadBegin(PetscOptionsObject, "GAMG-AGG options");
 95:   {
 96:     PetscBool flg;
 97:     PetscCall(PetscOptionsInt("-pc_gamg_agg_nsmooths", "smoothing steps for smoothed aggregation, usually 1", "PCGAMGSetNSmooths", pc_gamg_agg->nsmooths, &pc_gamg_agg->nsmooths, NULL));
 98:     PetscCall(
 99:       PetscOptionsInt("-pc_gamg_square_graph", "Number of aggressive coarsening (MIS-2) levels from finest (alias for -pc_gamg_aggressive_coarsening, deprecated)", "PCGAMGSetAggressiveLevels", pc_gamg_agg->aggressive_coarsening_levels, &pc_gamg_agg->aggressive_coarsening_levels, &flg));
100:     if (!flg) {
101:       PetscCall(PetscOptionsInt("-pc_gamg_aggressive_coarsening", "Number of aggressive coarsening (MIS-2) levels from finest", "PCGAMGSetAggressiveLevels", pc_gamg_agg->aggressive_coarsening_levels, &pc_gamg_agg->aggressive_coarsening_levels, NULL));
102:     } else {
103:       PetscCall(PetscOptionsInt("-pc_gamg_aggressive_coarsening", "Number of aggressive coarsening (MIS-2) levels from finest", "PCGAMGSetAggressiveLevels", pc_gamg_agg->aggressive_coarsening_levels, &pc_gamg_agg->aggressive_coarsening_levels, &flg));
104:       if (flg) PetscCall(PetscInfo(pc, "Warning: both -pc_gamg_square_graph and -pc_gamg_aggressive_coarsening are used. -pc_gamg_square_graph is deprecated, Number of aggressive levels is %d\n", (int)pc_gamg_agg->aggressive_coarsening_levels));
105:     }
106:   }
107:   PetscOptionsHeadEnd();
108:   PetscFunctionReturn(PETSC_SUCCESS);
109: }

111: static PetscErrorCode PCDestroy_GAMG_AGG(PC pc)
112: {
113:   PC_MG   *mg      = (PC_MG *)pc->data;
114:   PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx;

116:   PetscFunctionBegin;
117:   PetscCall(PetscFree(pc_gamg->subctx));
118:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGSetNSmooths_C", NULL));
119:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGSetAggressiveLevels_C", NULL));
120:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCSetCoordinates_C", NULL));
121:   PetscFunctionReturn(PETSC_SUCCESS);
122: }

124: /*
125:    PCSetCoordinates_AGG
126:      - collective

128:    Input Parameter:
129:    . pc - the preconditioner context
130:    . ndm - dimesion of data (used for dof/vertex for Stokes)
131:    . a_nloc - number of vertices local
132:    . coords - [a_nloc][ndm] - interleaved coordinate data: {x_0, y_0, z_0, x_1, y_1, ...}
133: */

135: static PetscErrorCode PCSetCoordinates_AGG(PC pc, PetscInt ndm, PetscInt a_nloc, PetscReal *coords)
136: {
137:   PC_MG   *mg      = (PC_MG *)pc->data;
138:   PC_GAMG *pc_gamg = (PC_GAMG *)mg->innerctx;
139:   PetscInt arrsz, kk, ii, jj, nloc, ndatarows, ndf;
140:   Mat      mat = pc->pmat;

142:   PetscFunctionBegin;
145:   nloc = a_nloc;

147:   /* SA: null space vectors */
148:   PetscCall(MatGetBlockSize(mat, &ndf));               /* this does not work for Stokes */
149:   if (coords && ndf == 1) pc_gamg->data_cell_cols = 1; /* scalar w/ coords and SA (not needed) */
150:   else if (coords) {
151:     PetscCheck(ndm <= ndf, PETSC_COMM_SELF, PETSC_ERR_PLIB, "degrees of motion %" PetscInt_FMT " > block size %" PetscInt_FMT, ndm, ndf);
152:     pc_gamg->data_cell_cols = (ndm == 2 ? 3 : 6); /* displacement elasticity */
153:     if (ndm != ndf) PetscCheck(pc_gamg->data_cell_cols == ndf, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Don't know how to create null space for ndm=%" PetscInt_FMT ", ndf=%" PetscInt_FMT ".  Use MatSetNearNullSpace().", ndm, ndf);
154:   } else pc_gamg->data_cell_cols = ndf; /* no data, force SA with constant null space vectors */
155:   pc_gamg->data_cell_rows = ndatarows = ndf;
156:   PetscCheck(pc_gamg->data_cell_cols > 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "pc_gamg->data_cell_cols %" PetscInt_FMT " <= 0", pc_gamg->data_cell_cols);
157:   arrsz = nloc * pc_gamg->data_cell_rows * pc_gamg->data_cell_cols;

159:   if (!pc_gamg->data || (pc_gamg->data_sz != arrsz)) {
160:     PetscCall(PetscFree(pc_gamg->data));
161:     PetscCall(PetscMalloc1(arrsz + 1, &pc_gamg->data));
162:   }
163:   /* copy data in - column oriented */
164:   for (kk = 0; kk < nloc; kk++) {
165:     const PetscInt M    = nloc * pc_gamg->data_cell_rows; /* stride into data */
166:     PetscReal     *data = &pc_gamg->data[kk * ndatarows]; /* start of cell */
167:     if (pc_gamg->data_cell_cols == 1) *data = 1.0;
168:     else {
169:       /* translational modes */
170:       for (ii = 0; ii < ndatarows; ii++) {
171:         for (jj = 0; jj < ndatarows; jj++) {
172:           if (ii == jj) data[ii * M + jj] = 1.0;
173:           else data[ii * M + jj] = 0.0;
174:         }
175:       }

177:       /* rotational modes */
178:       if (coords) {
179:         if (ndm == 2) {
180:           data += 2 * M;
181:           data[0] = -coords[2 * kk + 1];
182:           data[1] = coords[2 * kk];
183:         } else {
184:           data += 3 * M;
185:           data[0]         = 0.0;
186:           data[M + 0]     = coords[3 * kk + 2];
187:           data[2 * M + 0] = -coords[3 * kk + 1];
188:           data[1]         = -coords[3 * kk + 2];
189:           data[M + 1]     = 0.0;
190:           data[2 * M + 1] = coords[3 * kk];
191:           data[2]         = coords[3 * kk + 1];
192:           data[M + 2]     = -coords[3 * kk];
193:           data[2 * M + 2] = 0.0;
194:         }
195:       }
196:     }
197:   }
198:   pc_gamg->data_sz = arrsz;
199:   PetscFunctionReturn(PETSC_SUCCESS);
200: }

202: /*
203:    PCSetData_AGG - called if data is not set with PCSetCoordinates.
204:       Looks in Mat for near null space.
205:       Does not work for Stokes

207:   Input Parameter:
208:    . pc -
209:    . a_A - matrix to get (near) null space out of.
210: */
211: static PetscErrorCode PCSetData_AGG(PC pc, Mat a_A)
212: {
213:   PC_MG       *mg      = (PC_MG *)pc->data;
214:   PC_GAMG     *pc_gamg = (PC_GAMG *)mg->innerctx;
215:   MatNullSpace mnull;

217:   PetscFunctionBegin;
218:   PetscCall(MatGetNearNullSpace(a_A, &mnull));
219:   if (!mnull) {
220:     DM dm;
221:     PetscCall(PCGetDM(pc, &dm));
222:     if (!dm) PetscCall(MatGetDM(a_A, &dm));
223:     if (dm) {
224:       PetscObject deformation;
225:       PetscInt    Nf;

227:       PetscCall(DMGetNumFields(dm, &Nf));
228:       if (Nf) {
229:         PetscCall(DMGetField(dm, 0, NULL, &deformation));
230:         PetscCall(PetscObjectQuery((PetscObject)deformation, "nearnullspace", (PetscObject *)&mnull));
231:         if (!mnull) PetscCall(PetscObjectQuery((PetscObject)deformation, "nullspace", (PetscObject *)&mnull));
232:       }
233:     }
234:   }

236:   if (!mnull) {
237:     PetscInt bs, NN, MM;
238:     PetscCall(MatGetBlockSize(a_A, &bs));
239:     PetscCall(MatGetLocalSize(a_A, &MM, &NN));
240:     PetscCheck(MM % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "MM %" PetscInt_FMT " must be divisible by bs %" PetscInt_FMT, MM, bs);
241:     PetscCall(PCSetCoordinates_AGG(pc, bs, MM / bs, NULL));
242:   } else {
243:     PetscReal         *nullvec;
244:     PetscBool          has_const;
245:     PetscInt           i, j, mlocal, nvec, bs;
246:     const Vec         *vecs;
247:     const PetscScalar *v;

249:     PetscCall(MatGetLocalSize(a_A, &mlocal, NULL));
250:     PetscCall(MatNullSpaceGetVecs(mnull, &has_const, &nvec, &vecs));
251:     for (i = 0; i < nvec; i++) {
252:       PetscCall(VecGetLocalSize(vecs[i], &j));
253:       PetscCheck(j == mlocal, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Attached null space vector size %" PetscInt_FMT " != matrix size %" PetscInt_FMT, j, mlocal);
254:     }
255:     pc_gamg->data_sz = (nvec + !!has_const) * mlocal;
256:     PetscCall(PetscMalloc1((nvec + !!has_const) * mlocal, &nullvec));
257:     if (has_const)
258:       for (i = 0; i < mlocal; i++) nullvec[i] = 1.0;
259:     for (i = 0; i < nvec; i++) {
260:       PetscCall(VecGetArrayRead(vecs[i], &v));
261:       for (j = 0; j < mlocal; j++) nullvec[(i + !!has_const) * mlocal + j] = PetscRealPart(v[j]);
262:       PetscCall(VecRestoreArrayRead(vecs[i], &v));
263:     }
264:     pc_gamg->data           = nullvec;
265:     pc_gamg->data_cell_cols = (nvec + !!has_const);
266:     PetscCall(MatGetBlockSize(a_A, &bs));
267:     pc_gamg->data_cell_rows = bs;
268:   }
269:   PetscFunctionReturn(PETSC_SUCCESS);
270: }

272: /*
273:   formProl0 - collect null space data for each aggregate, do QR, put R in coarse grid data and Q in P_0

275:   Input Parameter:
276:    . agg_llists - list of arrays with aggregates -- list from selected vertices of aggregate unselected vertices
277:    . bs - row block size
278:    . nSAvec - column bs of new P
279:    . my0crs - global index of start of locals
280:    . data_stride - bs*(nloc nodes + ghost nodes) [data_stride][nSAvec]
281:    . data_in[data_stride*nSAvec] - local data on fine grid
282:    . flid_fgid[data_stride/bs] - make local to global IDs, includes ghosts in 'locals_llist'

284:   Output Parameter:
285:    . a_data_out - in with fine grid data (w/ghosts), out with coarse grid data
286:    . a_Prol - prolongation operator
287: */
288: static PetscErrorCode formProl0(PetscCoarsenData *agg_llists, PetscInt bs, PetscInt nSAvec, PetscInt my0crs, PetscInt data_stride, PetscReal data_in[], const PetscInt flid_fgid[], PetscReal **a_data_out, Mat a_Prol)
289: {
290:   PetscInt        Istart, my0, Iend, nloc, clid, flid = 0, aggID, kk, jj, ii, mm, nSelected, minsz, nghosts, out_data_stride;
291:   MPI_Comm        comm;
292:   PetscReal      *out_data;
293:   PetscCDIntNd   *pos;
294:   PCGAMGHashTable fgid_flid;

296:   PetscFunctionBegin;
297:   PetscCall(PetscObjectGetComm((PetscObject)a_Prol, &comm));
298:   PetscCall(MatGetOwnershipRange(a_Prol, &Istart, &Iend));
299:   nloc = (Iend - Istart) / bs;
300:   my0  = Istart / bs;
301:   PetscCheck((Iend - Istart) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Iend %" PetscInt_FMT " - Istart %" PetscInt_FMT " must be divisible by bs %" PetscInt_FMT, Iend, Istart, bs);
302:   Iend /= bs;
303:   nghosts = data_stride / bs - nloc;

305:   PetscCall(PCGAMGHashTableCreate(2 * nghosts + 1, &fgid_flid));
306:   for (kk = 0; kk < nghosts; kk++) PetscCall(PCGAMGHashTableAdd(&fgid_flid, flid_fgid[nloc + kk], nloc + kk));

308:   /* count selected -- same as number of cols of P */
309:   for (nSelected = mm = 0; mm < nloc; mm++) {
310:     PetscBool ise;
311:     PetscCall(PetscCDEmptyAt(agg_llists, mm, &ise));
312:     if (!ise) nSelected++;
313:   }
314:   PetscCall(MatGetOwnershipRangeColumn(a_Prol, &ii, &jj));
315:   PetscCheck((ii / nSAvec) == my0crs, PETSC_COMM_SELF, PETSC_ERR_PLIB, "ii %" PetscInt_FMT " /nSAvec %" PetscInt_FMT "  != my0crs %" PetscInt_FMT, ii, nSAvec, my0crs);
316:   PetscCheck(nSelected == (jj - ii) / nSAvec, PETSC_COMM_SELF, PETSC_ERR_PLIB, "nSelected %" PetscInt_FMT " != (jj %" PetscInt_FMT " - ii %" PetscInt_FMT ")/nSAvec %" PetscInt_FMT, nSelected, jj, ii, nSAvec);

318:   /* aloc space for coarse point data (output) */
319:   out_data_stride = nSelected * nSAvec;

321:   PetscCall(PetscMalloc1(out_data_stride * nSAvec, &out_data));
322:   for (ii = 0; ii < out_data_stride * nSAvec; ii++) out_data[ii] = PETSC_MAX_REAL;
323:   *a_data_out = out_data; /* output - stride nSelected*nSAvec */

325:   /* find points and set prolongation */
326:   minsz = 100;
327:   for (mm = clid = 0; mm < nloc; mm++) {
328:     PetscCall(PetscCDSizeAt(agg_llists, mm, &jj));
329:     if (jj > 0) {
330:       const PetscInt lid = mm, cgid = my0crs + clid;
331:       PetscInt       cids[100]; /* max bs */
332:       PetscBLASInt   asz = jj, M = asz * bs, N = nSAvec, INFO;
333:       PetscBLASInt   Mdata = M + ((N - M > 0) ? N - M : 0), LDA = Mdata, LWORK = N * bs;
334:       PetscScalar   *qqc, *qqr, *TAU, *WORK;
335:       PetscInt      *fids;
336:       PetscReal     *data;

338:       /* count agg */
339:       if (asz < minsz) minsz = asz;

341:       /* get block */
342:       PetscCall(PetscMalloc5(Mdata * N, &qqc, M * N, &qqr, N, &TAU, LWORK, &WORK, M, &fids));

344:       aggID = 0;
345:       PetscCall(PetscCDGetHeadPos(agg_llists, lid, &pos));
346:       while (pos) {
347:         PetscInt gid1;
348:         PetscCall(PetscCDIntNdGetID(pos, &gid1));
349:         PetscCall(PetscCDGetNextPos(agg_llists, lid, &pos));

351:         if (gid1 >= my0 && gid1 < Iend) flid = gid1 - my0;
352:         else {
353:           PetscCall(PCGAMGHashTableFind(&fgid_flid, gid1, &flid));
354:           PetscCheck(flid >= 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Cannot find gid1 in table");
355:         }
356:         /* copy in B_i matrix - column oriented */
357:         data = &data_in[flid * bs];
358:         for (ii = 0; ii < bs; ii++) {
359:           for (jj = 0; jj < N; jj++) {
360:             PetscReal d                       = data[jj * data_stride + ii];
361:             qqc[jj * Mdata + aggID * bs + ii] = d;
362:           }
363:         }
364:         /* set fine IDs */
365:         for (kk = 0; kk < bs; kk++) fids[aggID * bs + kk] = flid_fgid[flid] * bs + kk;
366:         aggID++;
367:       }

369:       /* pad with zeros */
370:       for (ii = asz * bs; ii < Mdata; ii++) {
371:         for (jj = 0; jj < N; jj++, kk++) qqc[jj * Mdata + ii] = .0;
372:       }

374:       /* QR */
375:       PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF));
376:       PetscCallBLAS("LAPACKgeqrf", LAPACKgeqrf_(&Mdata, &N, qqc, &LDA, TAU, WORK, &LWORK, &INFO));
377:       PetscCall(PetscFPTrapPop());
378:       PetscCheck(INFO == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "xGEQRF error");
379:       /* get R - column oriented - output B_{i+1} */
380:       {
381:         PetscReal *data = &out_data[clid * nSAvec];
382:         for (jj = 0; jj < nSAvec; jj++) {
383:           for (ii = 0; ii < nSAvec; ii++) {
384:             PetscCheck(data[jj * out_data_stride + ii] == PETSC_MAX_REAL, PETSC_COMM_SELF, PETSC_ERR_PLIB, "data[jj*out_data_stride + ii] != %e", (double)PETSC_MAX_REAL);
385:             if (ii <= jj) data[jj * out_data_stride + ii] = PetscRealPart(qqc[jj * Mdata + ii]);
386:             else data[jj * out_data_stride + ii] = 0.;
387:           }
388:         }
389:       }

391:       /* get Q - row oriented */
392:       PetscCallBLAS("LAPACKorgqr", LAPACKorgqr_(&Mdata, &N, &N, qqc, &LDA, TAU, WORK, &LWORK, &INFO));
393:       PetscCheck(INFO == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "xORGQR error arg %" PetscBLASInt_FMT, -INFO);

395:       for (ii = 0; ii < M; ii++) {
396:         for (jj = 0; jj < N; jj++) qqr[N * ii + jj] = qqc[jj * Mdata + ii];
397:       }

399:       /* add diagonal block of P0 */
400:       for (kk = 0; kk < N; kk++) { cids[kk] = N * cgid + kk; /* global col IDs in P0 */ }
401:       PetscCall(MatSetValues(a_Prol, M, fids, N, cids, qqr, INSERT_VALUES));
402:       PetscCall(PetscFree5(qqc, qqr, TAU, WORK, fids));
403:       clid++;
404:     } /* coarse agg */
405:   }   /* for all fine nodes */
406:   PetscCall(MatAssemblyBegin(a_Prol, MAT_FINAL_ASSEMBLY));
407:   PetscCall(MatAssemblyEnd(a_Prol, MAT_FINAL_ASSEMBLY));
408:   PetscCall(PCGAMGHashTableDestroy(&fgid_flid));
409:   PetscFunctionReturn(PETSC_SUCCESS);
410: }

412: static PetscErrorCode PCView_GAMG_AGG(PC pc, PetscViewer viewer)
413: {
414:   PC_MG       *mg          = (PC_MG *)pc->data;
415:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
416:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;

418:   PetscFunctionBegin;
419:   PetscCall(PetscViewerASCIIPrintf(viewer, "      AGG specific options\n"));
420:   PetscCall(PetscViewerASCIIPrintf(viewer, "        Number of levels to square graph %d\n", (int)pc_gamg_agg->aggressive_coarsening_levels));
421:   PetscCall(PetscViewerASCIIPrintf(viewer, "        Number smoothing steps %d\n", (int)pc_gamg_agg->nsmooths));
422:   PetscFunctionReturn(PETSC_SUCCESS);
423: }

425: static PetscErrorCode PCGAMGCreateGraph_AGG(PC pc, Mat Amat, Mat *a_Gmat)
426: {
427:   PC_MG          *mg          = (PC_MG *)pc->data;
428:   PC_GAMG        *pc_gamg     = (PC_GAMG *)mg->innerctx;
429:   PC_GAMG_AGG    *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;
430:   const PetscReal vfilter     = pc_gamg->threshold[pc_gamg->current_level];
431:   PetscBool       ishem;
432:   const char     *prefix;

434:   PetscFunctionBegin;
435:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_GRAPH], 0, 0, 0, 0));
436:   /* Note: depending on the algorithm that will be used for computing the coarse grid points this should pass PETSC_TRUE or PETSC_FALSE as the first argument */

438:   /* MATCOARSENHEM requires numerical weights for edges so ensure they are computed */
439:   PetscCall(MatCoarsenCreate(PetscObjectComm((PetscObject)pc), &pc_gamg_agg->crs));
440:   PetscCall(PetscObjectGetOptionsPrefix((PetscObject)pc, &prefix));
441:   PetscCall(PetscObjectSetOptionsPrefix((PetscObject)pc_gamg_agg->crs, prefix));
442:   PetscCall(MatCoarsenSetFromOptions(pc_gamg_agg->crs));
443:   PetscCall(PetscObjectTypeCompare((PetscObject)pc_gamg_agg->crs, MATCOARSENHEM, &ishem));

445:   PetscCall(MatCreateGraph(Amat, PETSC_TRUE, (vfilter >= 0 || ishem) ? PETSC_TRUE : PETSC_FALSE, vfilter, a_Gmat));
446:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_GRAPH], 0, 0, 0, 0));
447:   PetscFunctionReturn(PETSC_SUCCESS);
448: }

450: /*
451:    PCGAMGCoarsen_AGG - supports squaring the graph (deprecated) and new graph for
452:      communication of QR data used with HEM and MISk coarsening

454:   Input Parameter:
455:    . a_pc - this

457:   Input/Output Parameter:
458:    . a_Gmat1 - graph to coarsen (in), graph off processor edges for QR gather scatter (out)

460:   Output Parameter:
461:    . agg_lists - list of aggregates

463: */
464: static PetscErrorCode PCGAMGCoarsen_AGG(PC a_pc, Mat *a_Gmat1, PetscCoarsenData **agg_lists)
465: {
466:   PC_MG       *mg          = (PC_MG *)a_pc->data;
467:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
468:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;
469:   Mat          mat, Gmat1 = *a_Gmat1; /* aggressive graph */
470:   IS           perm;
471:   PetscInt     Istart, Iend, Ii, nloc, bs, nn;
472:   PetscInt    *permute, *degree;
473:   PetscBool   *bIndexSet;
474:   PetscReal    hashfact;
475:   PetscInt     iSwapIndex;
476:   PetscRandom  random;

478:   PetscFunctionBegin;
479:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_COARSEN], 0, 0, 0, 0));
480:   PetscCall(MatGetLocalSize(Gmat1, &nn, NULL));
481:   PetscCall(MatGetBlockSize(Gmat1, &bs));
482:   PetscCheck(bs == 1, PETSC_COMM_SELF, PETSC_ERR_PLIB, "bs %" PetscInt_FMT " must be 1", bs);
483:   nloc = nn / bs;

485:   /* get MIS aggs - randomize */
486:   PetscCall(PetscMalloc2(nloc, &permute, nloc, &degree));
487:   PetscCall(PetscCalloc1(nloc, &bIndexSet));
488:   for (Ii = 0; Ii < nloc; Ii++) permute[Ii] = Ii;
489:   PetscCall(PetscRandomCreate(PETSC_COMM_SELF, &random));
490:   PetscCall(MatGetOwnershipRange(Gmat1, &Istart, &Iend));
491:   for (Ii = 0; Ii < nloc; Ii++) {
492:     PetscInt nc;
493:     PetscCall(MatGetRow(Gmat1, Istart + Ii, &nc, NULL, NULL));
494:     degree[Ii] = nc;
495:     PetscCall(MatRestoreRow(Gmat1, Istart + Ii, &nc, NULL, NULL));
496:   }
497:   for (Ii = 0; Ii < nloc; Ii++) {
498:     PetscCall(PetscRandomGetValueReal(random, &hashfact));
499:     iSwapIndex = (PetscInt)(hashfact * nloc) % nloc;
500:     if (!bIndexSet[iSwapIndex] && iSwapIndex != Ii) {
501:       PetscInt iTemp        = permute[iSwapIndex];
502:       permute[iSwapIndex]   = permute[Ii];
503:       permute[Ii]           = iTemp;
504:       iTemp                 = degree[iSwapIndex];
505:       degree[iSwapIndex]    = degree[Ii];
506:       degree[Ii]            = iTemp;
507:       bIndexSet[iSwapIndex] = PETSC_TRUE;
508:     }
509:   }
510:   // create minimum degree ordering
511:   PetscCall(PetscSortIntWithArray(nloc, degree, permute));

513:   PetscCall(PetscFree(bIndexSet));
514:   PetscCall(PetscRandomDestroy(&random));
515:   PetscCall(ISCreateGeneral(PETSC_COMM_SELF, nloc, permute, PETSC_USE_POINTER, &perm));
516:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_MIS], 0, 0, 0, 0));
517:   PetscCall(MatCoarsenSetGreedyOrdering(pc_gamg_agg->crs, perm));
518:   PetscCall(MatCoarsenSetAdjacency(pc_gamg_agg->crs, Gmat1));
519:   PetscCall(MatCoarsenSetStrictAggs(pc_gamg_agg->crs, PETSC_TRUE));
520:   if (pc_gamg->current_level < pc_gamg_agg->aggressive_coarsening_levels) PetscCall(MatCoarsenMISKSetDistance(pc_gamg_agg->crs, 2)); // hardwire to MIS-2
521:   else PetscCall(MatCoarsenMISKSetDistance(pc_gamg_agg->crs, 1));                                                                    // MIS
522:   PetscCall(MatCoarsenApply(pc_gamg_agg->crs));
523:   PetscCall(MatCoarsenViewFromOptions(pc_gamg_agg->crs, NULL, "-mat_coarsen_view"));
524:   PetscCall(MatCoarsenGetData(pc_gamg_agg->crs, agg_lists)); /* output */
525:   PetscCall(MatCoarsenDestroy(&pc_gamg_agg->crs));

527:   PetscCall(ISDestroy(&perm));
528:   PetscCall(PetscFree2(permute, degree));
529:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_MIS], 0, 0, 0, 0));

531:   {
532:     PetscCoarsenData *llist = *agg_lists;
533:     /* see if we have a matrix that takes precedence (returned from MatCoarsenApply) */
534:     PetscCall(PetscCDGetMat(llist, &mat));
535:     if (mat) {
536:       PetscCall(MatDestroy(&Gmat1));
537:       *a_Gmat1 = mat; /* output */
538:     }
539:   }
540:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_COARSEN], 0, 0, 0, 0));
541:   PetscFunctionReturn(PETSC_SUCCESS);
542: }

544: /*
545:  PCGAMGProlongator_AGG

547:  Input Parameter:
548:  . pc - this
549:  . Amat - matrix on this fine level
550:  . Graph - used to get ghost data for nodes in
551:  . agg_lists - list of aggregates
552:  Output Parameter:
553:  . a_P_out - prolongation operator to the next level
554:  */
555: static PetscErrorCode PCGAMGProlongator_AGG(PC pc, Mat Amat, Mat Gmat, PetscCoarsenData *agg_lists, Mat *a_P_out)
556: {
557:   PC_MG         *mg      = (PC_MG *)pc->data;
558:   PC_GAMG       *pc_gamg = (PC_GAMG *)mg->innerctx;
559:   const PetscInt col_bs  = pc_gamg->data_cell_cols;
560:   PetscInt       Istart, Iend, nloc, ii, jj, kk, my0, nLocalSelected, bs;
561:   Mat            Prol;
562:   PetscMPIInt    size;
563:   MPI_Comm       comm;
564:   PetscReal     *data_w_ghost;
565:   PetscInt       myCrs0, nbnodes = 0, *flid_fgid;
566:   MatType        mtype;

568:   PetscFunctionBegin;
569:   PetscCall(PetscObjectGetComm((PetscObject)Amat, &comm));
570:   PetscCheck(col_bs >= 1, comm, PETSC_ERR_PLIB, "Column bs cannot be less than 1");
571:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_PROL], 0, 0, 0, 0));
572:   PetscCallMPI(MPI_Comm_size(comm, &size));
573:   PetscCall(MatGetOwnershipRange(Amat, &Istart, &Iend));
574:   PetscCall(MatGetBlockSize(Amat, &bs));
575:   nloc = (Iend - Istart) / bs;
576:   my0  = Istart / bs;
577:   PetscCheck((Iend - Istart) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "(Iend %" PetscInt_FMT " - Istart %" PetscInt_FMT ") not divisible by bs %" PetscInt_FMT, Iend, Istart, bs);

579:   /* get 'nLocalSelected' */
580:   for (ii = 0, nLocalSelected = 0; ii < nloc; ii++) {
581:     PetscBool ise;
582:     /* filter out singletons 0 or 1? */
583:     PetscCall(PetscCDEmptyAt(agg_lists, ii, &ise));
584:     if (!ise) nLocalSelected++;
585:   }

587:   /* create prolongator, create P matrix */
588:   PetscCall(MatGetType(Amat, &mtype));
589:   PetscCall(MatCreate(comm, &Prol));
590:   PetscCall(MatSetSizes(Prol, nloc * bs, nLocalSelected * col_bs, PETSC_DETERMINE, PETSC_DETERMINE));
591:   PetscCall(MatSetBlockSizes(Prol, bs, col_bs));
592:   PetscCall(MatSetType(Prol, mtype));
593:   PetscCall(MatSeqAIJSetPreallocation(Prol, col_bs, NULL));
594:   PetscCall(MatMPIAIJSetPreallocation(Prol, col_bs, NULL, col_bs, NULL));

596:   /* can get all points "removed" */
597:   PetscCall(MatGetSize(Prol, &kk, &ii));
598:   if (!ii) {
599:     PetscCall(PetscInfo(pc, "%s: No selected points on coarse grid\n", ((PetscObject)pc)->prefix));
600:     PetscCall(MatDestroy(&Prol));
601:     *a_P_out = NULL; /* out */
602:     PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_PROL], 0, 0, 0, 0));
603:     PetscFunctionReturn(PETSC_SUCCESS);
604:   }
605:   PetscCall(PetscInfo(pc, "%s: New grid %" PetscInt_FMT " nodes\n", ((PetscObject)pc)->prefix, ii / col_bs));
606:   PetscCall(MatGetOwnershipRangeColumn(Prol, &myCrs0, &kk));

608:   PetscCheck((kk - myCrs0) % col_bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "(kk %" PetscInt_FMT " -myCrs0 %" PetscInt_FMT ") not divisible by col_bs %" PetscInt_FMT, kk, myCrs0, col_bs);
609:   myCrs0 = myCrs0 / col_bs;
610:   PetscCheck((kk / col_bs - myCrs0) == nLocalSelected, PETSC_COMM_SELF, PETSC_ERR_PLIB, "(kk %" PetscInt_FMT "/col_bs %" PetscInt_FMT " - myCrs0 %" PetscInt_FMT ") != nLocalSelected %" PetscInt_FMT ")", kk, col_bs, myCrs0, nLocalSelected);

612:   /* create global vector of data in 'data_w_ghost' */
613:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_PROLA], 0, 0, 0, 0));
614:   if (size > 1) { /* get ghost null space data */
615:     PetscReal *tmp_gdata, *tmp_ldata, *tp2;
616:     PetscCall(PetscMalloc1(nloc, &tmp_ldata));
617:     for (jj = 0; jj < col_bs; jj++) {
618:       for (kk = 0; kk < bs; kk++) {
619:         PetscInt         ii, stride;
620:         const PetscReal *tp = pc_gamg->data + jj * bs * nloc + kk;
621:         for (ii = 0; ii < nloc; ii++, tp += bs) tmp_ldata[ii] = *tp;

623:         PetscCall(PCGAMGGetDataWithGhosts(Gmat, 1, tmp_ldata, &stride, &tmp_gdata));

625:         if (!jj && !kk) { /* now I know how many total nodes - allocate TODO: move below and do in one 'col_bs' call */
626:           PetscCall(PetscMalloc1(stride * bs * col_bs, &data_w_ghost));
627:           nbnodes = bs * stride;
628:         }
629:         tp2 = data_w_ghost + jj * bs * stride + kk;
630:         for (ii = 0; ii < stride; ii++, tp2 += bs) *tp2 = tmp_gdata[ii];
631:         PetscCall(PetscFree(tmp_gdata));
632:       }
633:     }
634:     PetscCall(PetscFree(tmp_ldata));
635:   } else {
636:     nbnodes      = bs * nloc;
637:     data_w_ghost = (PetscReal *)pc_gamg->data;
638:   }

640:   /* get 'flid_fgid' TODO - move up to get 'stride' and do get null space data above in one step (jj loop) */
641:   if (size > 1) {
642:     PetscReal *fid_glid_loc, *fiddata;
643:     PetscInt   stride;

645:     PetscCall(PetscMalloc1(nloc, &fid_glid_loc));
646:     for (kk = 0; kk < nloc; kk++) fid_glid_loc[kk] = (PetscReal)(my0 + kk);
647:     PetscCall(PCGAMGGetDataWithGhosts(Gmat, 1, fid_glid_loc, &stride, &fiddata));
648:     PetscCall(PetscMalloc1(stride, &flid_fgid)); /* copy real data to in */
649:     for (kk = 0; kk < stride; kk++) flid_fgid[kk] = (PetscInt)fiddata[kk];
650:     PetscCall(PetscFree(fiddata));

652:     PetscCheck(stride == nbnodes / bs, PETSC_COMM_SELF, PETSC_ERR_PLIB, "stride %" PetscInt_FMT " != nbnodes %" PetscInt_FMT "/bs %" PetscInt_FMT, stride, nbnodes, bs);
653:     PetscCall(PetscFree(fid_glid_loc));
654:   } else {
655:     PetscCall(PetscMalloc1(nloc, &flid_fgid));
656:     for (kk = 0; kk < nloc; kk++) flid_fgid[kk] = my0 + kk;
657:   }
658:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_PROLA], 0, 0, 0, 0));
659:   /* get P0 */
660:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_PROLB], 0, 0, 0, 0));
661:   {
662:     PetscReal *data_out = NULL;
663:     PetscCall(formProl0(agg_lists, bs, col_bs, myCrs0, nbnodes, data_w_ghost, flid_fgid, &data_out, Prol));
664:     PetscCall(PetscFree(pc_gamg->data));

666:     pc_gamg->data           = data_out;
667:     pc_gamg->data_cell_rows = col_bs;
668:     pc_gamg->data_sz        = col_bs * col_bs * nLocalSelected;
669:   }
670:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_PROLB], 0, 0, 0, 0));
671:   if (size > 1) PetscCall(PetscFree(data_w_ghost));
672:   PetscCall(PetscFree(flid_fgid));

674:   *a_P_out = Prol; /* out */

676:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_PROL], 0, 0, 0, 0));
677:   PetscFunctionReturn(PETSC_SUCCESS);
678: }

680: /*
681:    PCGAMGOptProlongator_AGG

683:   Input Parameter:
684:    . pc - this
685:    . Amat - matrix on this fine level
686:  In/Output Parameter:
687:    . a_P - prolongation operator to the next level
688: */
689: static PetscErrorCode PCGAMGOptProlongator_AGG(PC pc, Mat Amat, Mat *a_P)
690: {
691:   PC_MG       *mg          = (PC_MG *)pc->data;
692:   PC_GAMG     *pc_gamg     = (PC_GAMG *)mg->innerctx;
693:   PC_GAMG_AGG *pc_gamg_agg = (PC_GAMG_AGG *)pc_gamg->subctx;
694:   PetscInt     jj;
695:   Mat          Prol = *a_P;
696:   MPI_Comm     comm;
697:   KSP          eksp;
698:   Vec          bb, xx;
699:   PC           epc;
700:   PetscReal    alpha, emax, emin;

702:   PetscFunctionBegin;
703:   PetscCall(PetscObjectGetComm((PetscObject)Amat, &comm));
704:   PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_OPT], 0, 0, 0, 0));

706:   /* compute maximum singular value of operator to be used in smoother */
707:   if (0 < pc_gamg_agg->nsmooths) {
708:     /* get eigen estimates */
709:     if (pc_gamg->emax > 0) {
710:       emin = pc_gamg->emin;
711:       emax = pc_gamg->emax;
712:     } else {
713:       const char *prefix;

715:       PetscCall(MatCreateVecs(Amat, &bb, NULL));
716:       PetscCall(MatCreateVecs(Amat, &xx, NULL));
717:       PetscCall(KSPSetNoisy_Private(bb));

719:       PetscCall(KSPCreate(comm, &eksp));
720:       PetscCall(PCGetOptionsPrefix(pc, &prefix));
721:       PetscCall(KSPSetOptionsPrefix(eksp, prefix));
722:       PetscCall(KSPAppendOptionsPrefix(eksp, "pc_gamg_esteig_"));
723:       {
724:         PetscBool isset, sflg;
725:         PetscCall(MatIsSPDKnown(Amat, &isset, &sflg));
726:         if (isset && sflg) PetscCall(KSPSetType(eksp, KSPCG));
727:       }
728:       PetscCall(KSPSetErrorIfNotConverged(eksp, pc->erroriffailure));
729:       PetscCall(KSPSetNormType(eksp, KSP_NORM_NONE));

731:       PetscCall(KSPSetInitialGuessNonzero(eksp, PETSC_FALSE));
732:       PetscCall(KSPSetOperators(eksp, Amat, Amat));

734:       PetscCall(KSPGetPC(eksp, &epc));
735:       PetscCall(PCSetType(epc, PCJACOBI)); /* smoother in smoothed agg. */

737:       PetscCall(KSPSetTolerances(eksp, PETSC_DEFAULT, PETSC_DEFAULT, PETSC_DEFAULT, 10)); // 10 is safer, but 5 is often fine, can override with -pc_gamg_esteig_ksp_max_it -mg_levels_ksp_chebyshev_esteig 0,0.25,0,1.2

739:       PetscCall(KSPSetFromOptions(eksp));
740:       PetscCall(KSPSetComputeSingularValues(eksp, PETSC_TRUE));
741:       PetscCall(KSPSolve(eksp, bb, xx));
742:       PetscCall(KSPCheckSolve(eksp, pc, xx));

744:       PetscCall(KSPComputeExtremeSingularValues(eksp, &emax, &emin));
745:       PetscCall(PetscInfo(pc, "%s: Smooth P0: max eigen=%e min=%e PC=%s\n", ((PetscObject)pc)->prefix, (double)emax, (double)emin, PCJACOBI));
746:       PetscCall(VecDestroy(&xx));
747:       PetscCall(VecDestroy(&bb));
748:       PetscCall(KSPDestroy(&eksp));
749:     }
750:     if (pc_gamg->use_sa_esteig) {
751:       mg->min_eigen_DinvA[pc_gamg->current_level] = emin;
752:       mg->max_eigen_DinvA[pc_gamg->current_level] = emax;
753:       PetscCall(PetscInfo(pc, "%s: Smooth P0: level %" PetscInt_FMT ", cache spectra %g %g\n", ((PetscObject)pc)->prefix, pc_gamg->current_level, (double)emin, (double)emax));
754:     } else {
755:       mg->min_eigen_DinvA[pc_gamg->current_level] = 0;
756:       mg->max_eigen_DinvA[pc_gamg->current_level] = 0;
757:     }
758:   } else {
759:     mg->min_eigen_DinvA[pc_gamg->current_level] = 0;
760:     mg->max_eigen_DinvA[pc_gamg->current_level] = 0;
761:   }

763:   /* smooth P0 */
764:   for (jj = 0; jj < pc_gamg_agg->nsmooths; jj++) {
765:     Mat tMat;
766:     Vec diag;

768:     PetscCall(PetscLogEventBegin(petsc_gamg_setup_events[GAMG_OPTSM], 0, 0, 0, 0));

770:     /* smooth P1 := (I - omega/lam D^{-1}A)P0 */
771:     PetscCall(PetscLogEventBegin(petsc_gamg_setup_matmat_events[pc_gamg->current_level][2], 0, 0, 0, 0));
772:     PetscCall(MatMatMult(Amat, Prol, MAT_INITIAL_MATRIX, PETSC_DEFAULT, &tMat));
773:     PetscCall(PetscLogEventEnd(petsc_gamg_setup_matmat_events[pc_gamg->current_level][2], 0, 0, 0, 0));
774:     PetscCall(MatProductClear(tMat));
775:     PetscCall(MatCreateVecs(Amat, &diag, NULL));
776:     PetscCall(MatGetDiagonal(Amat, diag)); /* effectively PCJACOBI */
777:     PetscCall(VecReciprocal(diag));
778:     PetscCall(MatDiagonalScale(tMat, diag, NULL));
779:     PetscCall(VecDestroy(&diag));

781:     /* TODO: Set a PCFailedReason and exit the building of the AMG preconditioner */
782:     PetscCheck(emax != 0.0, PetscObjectComm((PetscObject)pc), PETSC_ERR_PLIB, "Computed maximum singular value as zero");
783:     /* TODO: Document the 1.4 and don't hardwire it in this routine */
784:     alpha = -1.4 / emax;

786:     PetscCall(MatAYPX(tMat, alpha, Prol, SUBSET_NONZERO_PATTERN));
787:     PetscCall(MatDestroy(&Prol));
788:     Prol = tMat;
789:     PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_OPTSM], 0, 0, 0, 0));
790:   }
791:   PetscCall(PetscLogEventEnd(petsc_gamg_setup_events[GAMG_OPT], 0, 0, 0, 0));
792:   *a_P = Prol;
793:   PetscFunctionReturn(PETSC_SUCCESS);
794: }

796: /*
797:    PCCreateGAMG_AGG

799:   Input Parameter:
800:    . pc -
801: */
802: PetscErrorCode PCCreateGAMG_AGG(PC pc)
803: {
804:   PC_MG       *mg      = (PC_MG *)pc->data;
805:   PC_GAMG     *pc_gamg = (PC_GAMG *)mg->innerctx;
806:   PC_GAMG_AGG *pc_gamg_agg;

808:   PetscFunctionBegin;
809:   /* create sub context for SA */
810:   PetscCall(PetscNew(&pc_gamg_agg));
811:   pc_gamg->subctx = pc_gamg_agg;

813:   pc_gamg->ops->setfromoptions = PCSetFromOptions_GAMG_AGG;
814:   pc_gamg->ops->destroy        = PCDestroy_GAMG_AGG;
815:   /* reset does not do anything; setup not virtual */

817:   /* set internal function pointers */
818:   pc_gamg->ops->creategraph       = PCGAMGCreateGraph_AGG;
819:   pc_gamg->ops->coarsen           = PCGAMGCoarsen_AGG;
820:   pc_gamg->ops->prolongator       = PCGAMGProlongator_AGG;
821:   pc_gamg->ops->optprolongator    = PCGAMGOptProlongator_AGG;
822:   pc_gamg->ops->createdefaultdata = PCSetData_AGG;
823:   pc_gamg->ops->view              = PCView_GAMG_AGG;

825:   pc_gamg_agg->aggressive_coarsening_levels = 1;
826:   pc_gamg_agg->nsmooths                     = 1;

828:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGSetNSmooths_C", PCGAMGSetNSmooths_AGG));
829:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCGAMGSetAggressiveLevels_C", PCGAMGSetAggressiveLevels_AGG));
830:   PetscCall(PetscObjectComposeFunction((PetscObject)pc, "PCSetCoordinates_C", PCSetCoordinates_AGG));
831:   PetscFunctionReturn(PETSC_SUCCESS);
832: }