1 #define PETSCKSP_DLL 2 3 /* 4 Defines the multigrid preconditioner interface. 5 */ 6 #include "../src/ksp/pc/impls/mg/mgimpl.h" /*I "petscmg.h" I*/ 7 8 9 #undef __FUNCT__ 10 #define __FUNCT__ "PCMGMCycle_Private" 11 PetscErrorCode PCMGMCycle_Private(PC pc,PC_MG **mglevels,PCRichardsonConvergedReason *reason) 12 { 13 PC_MG *mg = *mglevels,*mgc; 14 PetscErrorCode ierr; 15 PetscInt cycles = (mg->level == 1) ? 1 : (PetscInt) mg->cycles; 16 17 PetscFunctionBegin; 18 19 if (mg->eventsmoothsolve) {ierr = PetscLogEventBegin(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 20 ierr = KSPSolve(mg->smoothd,mg->b,mg->x);CHKERRQ(ierr); /* pre-smooth */ 21 if (mg->eventsmoothsolve) {ierr = PetscLogEventEnd(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 22 if (mg->level) { /* not the coarsest grid */ 23 if (mg->eventresidual) {ierr = PetscLogEventBegin(mg->eventresidual,0,0,0,0);CHKERRQ(ierr);} 24 ierr = (*mg->residual)(mg->A,mg->b,mg->x,mg->r);CHKERRQ(ierr); 25 if (mg->eventresidual) {ierr = PetscLogEventEnd(mg->eventresidual,0,0,0,0);CHKERRQ(ierr);} 26 27 /* if on finest level and have convergence criteria set */ 28 if (mg->level == mg->levels-1 && mg->ttol && reason) { 29 PetscReal rnorm; 30 ierr = VecNorm(mg->r,NORM_2,&rnorm);CHKERRQ(ierr); 31 if (rnorm <= mg->ttol) { 32 if (rnorm < mg->abstol) { 33 *reason = PCRICHARDSON_CONVERGED_ATOL; 34 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than absolute tolerance %G\n",rnorm,mg->abstol);CHKERRQ(ierr); 35 } else { 36 *reason = PCRICHARDSON_CONVERGED_RTOL; 37 ierr = PetscInfo2(pc,"Linear solver has converged. Residual norm %G is less than relative tolerance times initial residual norm %G\n",rnorm,mg->ttol);CHKERRQ(ierr); 38 } 39 PetscFunctionReturn(0); 40 } 41 } 42 43 mgc = *(mglevels - 1); 44 if (mg->eventinterprestrict) {ierr = PetscLogEventBegin(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 45 ierr = MatRestrict(mg->restrct,mg->r,mgc->b);CHKERRQ(ierr); 46 if (mg->eventinterprestrict) {ierr = PetscLogEventEnd(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 47 ierr = VecSet(mgc->x,0.0);CHKERRQ(ierr); 48 while (cycles--) { 49 ierr = PCMGMCycle_Private(pc,mglevels-1,reason);CHKERRQ(ierr); 50 } 51 if (mg->eventinterprestrict) {ierr = PetscLogEventBegin(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 52 ierr = MatInterpolateAdd(mg->interpolate,mgc->x,mg->x,mg->x);CHKERRQ(ierr); 53 if (mg->eventinterprestrict) {ierr = PetscLogEventEnd(mg->eventinterprestrict,0,0,0,0);CHKERRQ(ierr);} 54 if (mg->eventsmoothsolve) {ierr = PetscLogEventBegin(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 55 ierr = KSPSolve(mg->smoothu,mg->b,mg->x);CHKERRQ(ierr); /* post smooth */ 56 if (mg->eventsmoothsolve) {ierr = PetscLogEventEnd(mg->eventsmoothsolve,0,0,0,0);CHKERRQ(ierr);} 57 } 58 PetscFunctionReturn(0); 59 } 60 61 /* 62 PCMGCreate_Private - Creates a PC_MG structure for use with the 63 multigrid code. Level 0 is the coarsest. (But the 64 finest level is stored first in the array). 65 66 */ 67 #undef __FUNCT__ 68 #define __FUNCT__ "PCMGCreate_Private" 69 static PetscErrorCode PCMGCreate_Private(MPI_Comm comm,PetscInt levels,PC pc,MPI_Comm *comms,PC_MG ***result) 70 { 71 PC_MG **mg; 72 PetscErrorCode ierr; 73 PetscInt i; 74 PetscMPIInt size; 75 const char *prefix; 76 PC ipc; 77 78 PetscFunctionBegin; 79 ierr = PetscMalloc(levels*sizeof(PC_MG*),&mg);CHKERRQ(ierr); 80 ierr = PetscLogObjectMemory(pc,levels*(sizeof(PC_MG*)));CHKERRQ(ierr); 81 82 ierr = PCGetOptionsPrefix(pc,&prefix);CHKERRQ(ierr); 83 84 for (i=0; i<levels; i++) { 85 ierr = PetscNewLog(pc,PC_MG,&mg[i]);CHKERRQ(ierr); 86 mg[i]->level = i; 87 mg[i]->levels = levels; 88 mg[i]->cycles = PC_MG_CYCLE_V; 89 mg[i]->galerkin = PETSC_FALSE; 90 mg[i]->galerkinused = PETSC_FALSE; 91 mg[i]->default_smoothu = 1; 92 mg[i]->default_smoothd = 1; 93 94 if (comms) comm = comms[i]; 95 ierr = KSPCreate(comm,&mg[i]->smoothd);CHKERRQ(ierr); 96 ierr = PetscObjectIncrementTabLevel((PetscObject)mg[i]->smoothd,(PetscObject)pc,levels-i);CHKERRQ(ierr); 97 ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT, mg[i]->default_smoothd);CHKERRQ(ierr); 98 ierr = KSPSetOptionsPrefix(mg[i]->smoothd,prefix);CHKERRQ(ierr); 99 100 /* do special stuff for coarse grid */ 101 if (!i && levels > 1) { 102 ierr = KSPAppendOptionsPrefix(mg[0]->smoothd,"mg_coarse_");CHKERRQ(ierr); 103 104 /* coarse solve is (redundant) LU by default */ 105 ierr = KSPSetType(mg[0]->smoothd,KSPPREONLY);CHKERRQ(ierr); 106 ierr = KSPGetPC(mg[0]->smoothd,&ipc);CHKERRQ(ierr); 107 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 108 if (size > 1) { 109 ierr = PCSetType(ipc,PCREDUNDANT);CHKERRQ(ierr); 110 } else { 111 ierr = PCSetType(ipc,PCLU);CHKERRQ(ierr); 112 } 113 114 } else { 115 char tprefix[128]; 116 sprintf(tprefix,"mg_levels_%d_",(int)i); 117 ierr = KSPAppendOptionsPrefix(mg[i]->smoothd,tprefix);CHKERRQ(ierr); 118 } 119 ierr = PetscLogObjectParent(pc,mg[i]->smoothd);CHKERRQ(ierr); 120 mg[i]->smoothu = mg[i]->smoothd; 121 mg[i]->rtol = 0.0; 122 mg[i]->abstol = 0.0; 123 mg[i]->dtol = 0.0; 124 mg[i]->ttol = 0.0; 125 mg[i]->eventsmoothsetup = 0; 126 mg[i]->eventsmoothsolve = 0; 127 mg[i]->eventresidual = 0; 128 mg[i]->eventinterprestrict = 0; 129 mg[i]->cyclesperpcapply = 1; 130 } 131 *result = mg; 132 PetscFunctionReturn(0); 133 } 134 135 #undef __FUNCT__ 136 #define __FUNCT__ "PCDestroy_MG" 137 PetscErrorCode PCDestroy_MG(PC pc) 138 { 139 PC_MG **mg = (PC_MG**)pc->data; 140 PetscErrorCode ierr; 141 PetscInt i,n; 142 143 PetscFunctionBegin; 144 if (!mg) PetscFunctionReturn(0); 145 146 n = mg[0]->levels; 147 for (i=0; i<n-1; i++) { 148 if (mg[i+1]->r) {ierr = VecDestroy(mg[i+1]->r);CHKERRQ(ierr);} 149 if (mg[i]->b) {ierr = VecDestroy(mg[i]->b);CHKERRQ(ierr);} 150 if (mg[i]->x) {ierr = VecDestroy(mg[i]->x);CHKERRQ(ierr);} 151 if (mg[i+1]->restrct) {ierr = MatDestroy(mg[i+1]->restrct);CHKERRQ(ierr);} 152 if (mg[i+1]->interpolate) {ierr = MatDestroy(mg[i+1]->interpolate);CHKERRQ(ierr);} 153 } 154 155 for (i=0; i<n; i++) { 156 if (mg[i]->smoothd != mg[i]->smoothu) { 157 ierr = KSPDestroy(mg[i]->smoothd);CHKERRQ(ierr); 158 } 159 ierr = KSPDestroy(mg[i]->smoothu);CHKERRQ(ierr); 160 ierr = PetscFree(mg[i]);CHKERRQ(ierr); 161 } 162 ierr = PetscFree(mg);CHKERRQ(ierr); 163 PetscFunctionReturn(0); 164 } 165 166 167 168 EXTERN PetscErrorCode PCMGACycle_Private(PC_MG**); 169 EXTERN PetscErrorCode PCMGFCycle_Private(PC,PC_MG**); 170 EXTERN PetscErrorCode PCMGKCycle_Private(PC_MG**); 171 172 /* 173 PCApply_MG - Runs either an additive, multiplicative, Kaskadic 174 or full cycle of multigrid. 175 176 Note: 177 A simple wrapper which calls PCMGMCycle(),PCMGACycle(), or PCMGFCycle(). 178 */ 179 #undef __FUNCT__ 180 #define __FUNCT__ "PCApply_MG" 181 static PetscErrorCode PCApply_MG(PC pc,Vec b,Vec x) 182 { 183 PC_MG **mg = (PC_MG**)pc->data; 184 PetscErrorCode ierr; 185 PetscInt levels = mg[0]->levels,i; 186 187 PetscFunctionBegin; 188 mg[levels-1]->b = b; 189 mg[levels-1]->x = x; 190 if (mg[0]->am == PC_MG_MULTIPLICATIVE) { 191 ierr = VecSet(x,0.0);CHKERRQ(ierr); 192 for (i=0; i<mg[0]->cyclesperpcapply; i++) { 193 ierr = PCMGMCycle_Private(pc,mg+levels-1,PETSC_NULL);CHKERRQ(ierr); 194 } 195 } 196 else if (mg[0]->am == PC_MG_ADDITIVE) { 197 ierr = PCMGACycle_Private(mg);CHKERRQ(ierr); 198 } 199 else if (mg[0]->am == PC_MG_KASKADE) { 200 ierr = PCMGKCycle_Private(mg);CHKERRQ(ierr); 201 } 202 else { 203 ierr = PCMGFCycle_Private(pc,mg);CHKERRQ(ierr); 204 } 205 PetscFunctionReturn(0); 206 } 207 208 #undef __FUNCT__ 209 #define __FUNCT__ "PCApplyRichardson_MG" 210 static PetscErrorCode PCApplyRichardson_MG(PC pc,Vec b,Vec x,Vec w,PetscReal rtol,PetscReal abstol, PetscReal dtol,PetscInt its,PetscTruth zeroguess,PetscInt *outits,PCRichardsonConvergedReason *reason) 211 { 212 PC_MG **mg = (PC_MG**)pc->data; 213 PetscErrorCode ierr; 214 PetscInt levels = mg[0]->levels,i; 215 216 PetscFunctionBegin; 217 mg[levels-1]->b = b; 218 mg[levels-1]->x = x; 219 220 mg[levels-1]->rtol = rtol; 221 mg[levels-1]->abstol = abstol; 222 mg[levels-1]->dtol = dtol; 223 if (rtol) { 224 /* compute initial residual norm for relative convergence test */ 225 PetscReal rnorm; 226 if (zeroguess) { 227 ierr = VecNorm(b,NORM_2,&rnorm);CHKERRQ(ierr); 228 } else { 229 ierr = (*mg[levels-1]->residual)(mg[levels-1]->A,b,x,w);CHKERRQ(ierr); 230 ierr = VecNorm(w,NORM_2,&rnorm);CHKERRQ(ierr); 231 } 232 mg[levels-1]->ttol = PetscMax(rtol*rnorm,abstol); 233 } else if (abstol) { 234 mg[levels-1]->ttol = abstol; 235 } else { 236 mg[levels-1]->ttol = 0.0; 237 } 238 239 /* since smoother is applied to full system, not just residual we need to make sure that smoothers don't 240 stop prematurely do to small residual */ 241 for (i=1; i<levels; i++) { 242 ierr = KSPSetTolerances(mg[i]->smoothu,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 243 if (mg[i]->smoothu != mg[i]->smoothd) { 244 ierr = KSPSetTolerances(mg[i]->smoothd,0,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT);CHKERRQ(ierr); 245 } 246 } 247 248 *reason = (PCRichardsonConvergedReason)0; 249 for (i=0; i<its; i++) { 250 ierr = PCMGMCycle_Private(pc,mg+levels-1,reason);CHKERRQ(ierr); 251 if (*reason) break; 252 } 253 if (!*reason) *reason = PCRICHARDSON_CONVERGED_ITS; 254 *outits = i; 255 PetscFunctionReturn(0); 256 } 257 258 #undef __FUNCT__ 259 #define __FUNCT__ "PCSetFromOptions_MG" 260 PetscErrorCode PCSetFromOptions_MG(PC pc) 261 { 262 PetscErrorCode ierr; 263 PetscInt m,levels = 1,cycles; 264 PetscTruth flg; 265 PC_MG **mg = (PC_MG**)pc->data; 266 PCMGType mgtype; 267 PCMGCycleType mgctype; 268 269 PetscFunctionBegin; 270 ierr = PetscOptionsHead("Multigrid options");CHKERRQ(ierr); 271 if (!pc->data) { 272 ierr = PetscOptionsInt("-pc_mg_levels","Number of Levels","PCMGSetLevels",levels,&levels,&flg);CHKERRQ(ierr); 273 ierr = PCMGSetLevels(pc,levels,PETSC_NULL);CHKERRQ(ierr); 274 mg = (PC_MG**)pc->data; 275 } 276 mgctype = (PCMGCycleType) mg[0]->cycles; 277 ierr = PetscOptionsEnum("-pc_mg_cycle_type","V cycle or for W-cycle","PCMGSetCycleType",PCMGCycleTypes,(PetscEnum)mgctype,(PetscEnum*)&mgctype,&flg);CHKERRQ(ierr); 278 if (flg) { 279 ierr = PCMGSetCycleType(pc,mgctype);CHKERRQ(ierr); 280 }; 281 flg = PETSC_FALSE; 282 ierr = PetscOptionsTruth("-pc_mg_galerkin","Use Galerkin process to compute coarser operators","PCMGSetGalerkin",flg,&flg,PETSC_NULL);CHKERRQ(ierr); 283 if (flg) { 284 ierr = PCMGSetGalerkin(pc);CHKERRQ(ierr); 285 } 286 ierr = PetscOptionsInt("-pc_mg_smoothup","Number of post-smoothing steps","PCMGSetNumberSmoothUp",1,&m,&flg);CHKERRQ(ierr); 287 if (flg) { 288 ierr = PCMGSetNumberSmoothUp(pc,m);CHKERRQ(ierr); 289 } 290 ierr = PetscOptionsInt("-pc_mg_smoothdown","Number of pre-smoothing steps","PCMGSetNumberSmoothDown",1,&m,&flg);CHKERRQ(ierr); 291 if (flg) { 292 ierr = PCMGSetNumberSmoothDown(pc,m);CHKERRQ(ierr); 293 } 294 mgtype = mg[0]->am; 295 ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr); 296 if (flg) { 297 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 298 } 299 if (mg[0]->am == PC_MG_MULTIPLICATIVE) { 300 ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg[0]->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr); 301 if (flg) { 302 ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr); 303 } 304 } 305 flg = PETSC_FALSE; 306 ierr = PetscOptionsTruth("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,PETSC_NULL);CHKERRQ(ierr); 307 if (flg) { 308 PetscInt i; 309 char eventname[128]; 310 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 311 levels = mg[0]->levels; 312 for (i=0; i<levels; i++) { 313 sprintf(eventname,"MGSetup Level %d",(int)i); 314 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventsmoothsetup);CHKERRQ(ierr); 315 sprintf(eventname,"MGSmooth Level %d",(int)i); 316 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventsmoothsolve);CHKERRQ(ierr); 317 if (i) { 318 sprintf(eventname,"MGResid Level %d",(int)i); 319 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventresidual);CHKERRQ(ierr); 320 sprintf(eventname,"MGInterp Level %d",(int)i); 321 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventinterprestrict);CHKERRQ(ierr); 322 } 323 } 324 } 325 ierr = PetscOptionsTail();CHKERRQ(ierr); 326 PetscFunctionReturn(0); 327 } 328 329 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0}; 330 const char *PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0}; 331 332 #undef __FUNCT__ 333 #define __FUNCT__ "PCView_MG" 334 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer) 335 { 336 PC_MG **mg = (PC_MG**)pc->data; 337 PetscErrorCode ierr; 338 PetscInt levels = mg[0]->levels,i; 339 PetscTruth iascii; 340 341 PetscFunctionBegin; 342 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 343 if (iascii) { 344 ierr = PetscViewerASCIIPrintf(viewer," MG: type is %s, levels=%D cycles=%s\n", PCMGTypes[mg[0]->am],levels,(mg[0]->cycles == PC_MG_CYCLE_V) ? "v" : "w");CHKERRQ(ierr); 345 if (mg[0]->am == PC_MG_MULTIPLICATIVE) { 346 ierr = PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg[0]->cyclesperpcapply);CHKERRQ(ierr); 347 } 348 if (mg[0]->galerkin) { 349 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 350 } 351 for (i=0; i<levels; i++) { 352 if (!i) { 353 ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level %D presmooths=%D postsmooths=%D -----\n",i,mg[0]->default_smoothd,mg[0]->default_smoothu);CHKERRQ(ierr); 354 } else { 355 ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D smooths=%D --------------------\n",i,mg[i]->default_smoothd);CHKERRQ(ierr); 356 } 357 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 358 ierr = KSPView(mg[i]->smoothd,viewer);CHKERRQ(ierr); 359 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 360 if (i && mg[i]->smoothd == mg[i]->smoothu) { 361 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr); 362 } else if (i){ 363 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D smooths=%D --------------------\n",i,mg[i]->default_smoothu);CHKERRQ(ierr); 364 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 365 ierr = KSPView(mg[i]->smoothu,viewer);CHKERRQ(ierr); 366 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 367 } 368 } 369 } else { 370 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name); 371 } 372 PetscFunctionReturn(0); 373 } 374 375 /* 376 Calls setup for the KSP on each level 377 */ 378 #undef __FUNCT__ 379 #define __FUNCT__ "PCSetUp_MG" 380 PetscErrorCode PCSetUp_MG(PC pc) 381 { 382 PC_MG **mg = (PC_MG**)pc->data; 383 PetscErrorCode ierr; 384 PetscInt i,n = mg[0]->levels; 385 PC cpc,mpc; 386 PetscTruth preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump = PETSC_FALSE,opsset; 387 PetscViewerASCIIMonitor ascii; 388 PetscViewer viewer = PETSC_NULL; 389 MPI_Comm comm; 390 Mat dA,dB; 391 MatStructure uflag; 392 Vec tvec; 393 394 PetscFunctionBegin; 395 396 /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */ 397 /* so use those from global PC */ 398 /* Is this what we always want? What if user wants to keep old one? */ 399 ierr = KSPGetOperatorsSet(mg[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr); 400 ierr = KSPGetPC(mg[0]->smoothd,&cpc);CHKERRQ(ierr); 401 ierr = KSPGetPC(mg[n-1]->smoothd,&mpc);CHKERRQ(ierr); 402 if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2))) { 403 ierr = PetscInfo(pc,"Using outer operators to define finest grid operator \n because PCMGGetSmoother(pc,nlevels-1,&ksp);KSPSetOperators(ksp,...); was not called.\n");CHKERRQ(ierr); 404 ierr = KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr); 405 } 406 407 if (mg[0]->galerkin) { 408 Mat B; 409 mg[0]->galerkinused = PETSC_TRUE; 410 /* currently only handle case where mat and pmat are the same on coarser levels */ 411 ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr); 412 if (!pc->setupcalled) { 413 for (i=n-2; i>-1; i--) { 414 ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 415 ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 416 if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 417 dB = B; 418 } 419 ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr); 420 } else { 421 for (i=n-2; i>-1; i--) { 422 ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr); 423 ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 424 ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 425 dB = B; 426 } 427 } 428 } 429 430 if (!pc->setupcalled) { 431 ierr = PetscOptionsGetTruth(0,"-pc_mg_monitor",&monitor,PETSC_NULL);CHKERRQ(ierr); 432 433 for (i=0; i<n; i++) { 434 if (monitor) { 435 ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothd,&comm);CHKERRQ(ierr); 436 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr); 437 ierr = KSPMonitorSet(mg[i]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 438 } 439 ierr = KSPSetFromOptions(mg[i]->smoothd);CHKERRQ(ierr); 440 } 441 for (i=1; i<n; i++) { 442 if (mg[i]->smoothu && (mg[i]->smoothu != mg[i]->smoothd)) { 443 if (monitor) { 444 ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothu,&comm);CHKERRQ(ierr); 445 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr); 446 ierr = KSPMonitorSet(mg[i]->smoothu,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 447 } 448 ierr = KSPSetFromOptions(mg[i]->smoothu);CHKERRQ(ierr); 449 } 450 } 451 for (i=1; i<n; i++) { 452 if (!mg[i]->residual) { 453 Mat mat; 454 ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr); 455 ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr); 456 } 457 if (mg[i]->restrct && !mg[i]->interpolate) { 458 ierr = PCMGSetInterpolation(pc,i,mg[i]->restrct);CHKERRQ(ierr); 459 } 460 if (!mg[i]->restrct && mg[i]->interpolate) { 461 ierr = PCMGSetRestriction(pc,i,mg[i]->interpolate);CHKERRQ(ierr); 462 } 463 #if defined(PETSC_USE_DEBUG) 464 if (!mg[i]->restrct || !mg[i]->interpolate) { 465 SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i); 466 } 467 #endif 468 } 469 for (i=0; i<n-1; i++) { 470 if (!mg[i]->b) { 471 Vec *vec; 472 ierr = KSPGetVecs(mg[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 473 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 474 ierr = VecDestroy(*vec);CHKERRQ(ierr); 475 ierr = PetscFree(vec);CHKERRQ(ierr); 476 } 477 if (!mg[i]->r && i) { 478 ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr); 479 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 480 ierr = VecDestroy(tvec);CHKERRQ(ierr); 481 } 482 if (!mg[i]->x) { 483 ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr); 484 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 485 ierr = VecDestroy(tvec);CHKERRQ(ierr); 486 } 487 } 488 if (n != 1 && !mg[n-1]->r) { 489 /* PCMGSetR() on the finest level if user did not supply it */ 490 Vec *vec; 491 ierr = KSPGetVecs(mg[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 492 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 493 ierr = VecDestroy(*vec);CHKERRQ(ierr); 494 ierr = PetscFree(vec);CHKERRQ(ierr); 495 } 496 } 497 498 499 for (i=1; i<n; i++) { 500 if (mg[i]->smoothu == mg[i]->smoothd) { 501 /* if doing only down then initial guess is zero */ 502 ierr = KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 503 } 504 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 505 ierr = KSPSetUp(mg[i]->smoothd);CHKERRQ(ierr); 506 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 507 } 508 for (i=1; i<n; i++) { 509 if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) { 510 Mat downmat,downpmat; 511 MatStructure matflag; 512 PetscTruth opsset; 513 514 /* check if operators have been set for up, if not use down operators to set them */ 515 ierr = KSPGetOperatorsSet(mg[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr); 516 if (!opsset) { 517 ierr = KSPGetOperators(mg[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr); 518 ierr = KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr); 519 } 520 521 ierr = KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 522 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 523 ierr = KSPSetUp(mg[i]->smoothu);CHKERRQ(ierr); 524 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 525 } 526 } 527 528 /* 529 If coarse solver is not direct method then DO NOT USE preonly 530 */ 531 ierr = PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr); 532 if (preonly) { 533 ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr); 534 ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr); 535 ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr); 536 if (!lu && !redundant && !cholesky) { 537 ierr = KSPSetType(mg[0]->smoothd,KSPGMRES);CHKERRQ(ierr); 538 } 539 } 540 541 if (!pc->setupcalled) { 542 if (monitor) { 543 ierr = PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);CHKERRQ(ierr); 544 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n,&ascii);CHKERRQ(ierr); 545 ierr = KSPMonitorSet(mg[0]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 546 } 547 ierr = KSPSetFromOptions(mg[0]->smoothd);CHKERRQ(ierr); 548 } 549 550 if (mg[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 551 ierr = KSPSetUp(mg[0]->smoothd);CHKERRQ(ierr); 552 if (mg[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 553 554 /* 555 Dump the interpolation/restriction matrices plus the 556 Jacobian/stiffness on each level. This allows Matlab users to 557 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 558 559 Only support one or the other at the same time. 560 */ 561 #if defined(PETSC_USE_SOCKET_VIEWER) 562 ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr); 563 if (dump) { 564 viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm); 565 } 566 dump = PETSC_FALSE; 567 #endif 568 ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr); 569 if (dump) { 570 viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm); 571 } 572 573 if (viewer) { 574 for (i=1; i<n; i++) { 575 ierr = MatView(mg[i]->restrct,viewer);CHKERRQ(ierr); 576 } 577 for (i=0; i<n; i++) { 578 ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr); 579 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 580 } 581 } 582 PetscFunctionReturn(0); 583 } 584 585 /* -------------------------------------------------------------------------------------*/ 586 587 #undef __FUNCT__ 588 #define __FUNCT__ "PCMGSetLevels" 589 /*@C 590 PCMGSetLevels - Sets the number of levels to use with MG. 591 Must be called before any other MG routine. 592 593 Collective on PC 594 595 Input Parameters: 596 + pc - the preconditioner context 597 . levels - the number of levels 598 - comms - optional communicators for each level; this is to allow solving the coarser problems 599 on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran 600 601 Level: intermediate 602 603 Notes: 604 If the number of levels is one then the multigrid uses the -mg_levels prefix 605 for setting the level options rather than the -mg_coarse prefix. 606 607 .keywords: MG, set, levels, multigrid 608 609 .seealso: PCMGSetType(), PCMGGetLevels() 610 @*/ 611 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms) 612 { 613 PetscErrorCode ierr; 614 PC_MG **mg=0; 615 616 PetscFunctionBegin; 617 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 618 619 if (pc->data) { 620 SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\ 621 make sure that you call PCMGSetLevels() before KSPSetFromOptions()"); 622 } 623 ierr = PCMGCreate_Private(((PetscObject)pc)->comm,levels,pc,comms,&mg);CHKERRQ(ierr); 624 mg[0]->am = PC_MG_MULTIPLICATIVE; 625 pc->data = (void*)mg; 626 pc->ops->applyrichardson = PCApplyRichardson_MG; 627 PetscFunctionReturn(0); 628 } 629 630 #undef __FUNCT__ 631 #define __FUNCT__ "PCMGGetLevels" 632 /*@ 633 PCMGGetLevels - Gets the number of levels to use with MG. 634 635 Not Collective 636 637 Input Parameter: 638 . pc - the preconditioner context 639 640 Output parameter: 641 . levels - the number of levels 642 643 Level: advanced 644 645 .keywords: MG, get, levels, multigrid 646 647 .seealso: PCMGSetLevels() 648 @*/ 649 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels) 650 { 651 PC_MG **mg; 652 653 PetscFunctionBegin; 654 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 655 PetscValidIntPointer(levels,2); 656 657 mg = (PC_MG**)pc->data; 658 *levels = mg[0]->levels; 659 PetscFunctionReturn(0); 660 } 661 662 #undef __FUNCT__ 663 #define __FUNCT__ "PCMGSetType" 664 /*@ 665 PCMGSetType - Determines the form of multigrid to use: 666 multiplicative, additive, full, or the Kaskade algorithm. 667 668 Collective on PC 669 670 Input Parameters: 671 + pc - the preconditioner context 672 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 673 PC_MG_FULL, PC_MG_KASKADE 674 675 Options Database Key: 676 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 677 additive, full, kaskade 678 679 Level: advanced 680 681 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 682 683 .seealso: PCMGSetLevels() 684 @*/ 685 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form) 686 { 687 PC_MG **mg; 688 689 PetscFunctionBegin; 690 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 691 mg = (PC_MG**)pc->data; 692 693 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 694 mg[0]->am = form; 695 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 696 else pc->ops->applyrichardson = 0; 697 PetscFunctionReturn(0); 698 } 699 700 #undef __FUNCT__ 701 #define __FUNCT__ "PCMGSetCycleType" 702 /*@ 703 PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more 704 complicated cycling. 705 706 Collective on PC 707 708 Input Parameters: 709 + pc - the multigrid context 710 - PC_MG_CYCLE_V or PC_MG_CYCLE_W 711 712 Options Database Key: 713 $ -pc_mg_cycle_type v or w 714 715 Level: advanced 716 717 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 718 719 .seealso: PCMGSetCycleTypeOnLevel() 720 @*/ 721 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycleType(PC pc,PCMGCycleType n) 722 { 723 PC_MG **mg; 724 PetscInt i,levels; 725 726 PetscFunctionBegin; 727 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 728 mg = (PC_MG**)pc->data; 729 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 730 levels = mg[0]->levels; 731 732 for (i=0; i<levels; i++) { 733 mg[i]->cycles = n; 734 } 735 PetscFunctionReturn(0); 736 } 737 738 #undef __FUNCT__ 739 #define __FUNCT__ "PCMGMultiplicativeSetCycles" 740 /*@ 741 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 742 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 743 744 Collective on PC 745 746 Input Parameters: 747 + pc - the multigrid context 748 - n - number of cycles (default is 1) 749 750 Options Database Key: 751 $ -pc_mg_multiplicative_cycles n 752 753 Level: advanced 754 755 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 756 757 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 758 759 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 760 @*/ 761 PetscErrorCode PETSCKSP_DLLEXPORT PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 762 { 763 PC_MG **mg; 764 PetscInt i,levels; 765 766 PetscFunctionBegin; 767 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 768 mg = (PC_MG**)pc->data; 769 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 770 levels = mg[0]->levels; 771 772 for (i=0; i<levels; i++) { 773 mg[i]->cyclesperpcapply = n; 774 } 775 PetscFunctionReturn(0); 776 } 777 778 #undef __FUNCT__ 779 #define __FUNCT__ "PCMGSetGalerkin" 780 /*@ 781 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 782 finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t 783 784 Collective on PC 785 786 Input Parameters: 787 . pc - the multigrid context 788 789 Options Database Key: 790 $ -pc_mg_galerkin 791 792 Level: intermediate 793 794 .keywords: MG, set, Galerkin 795 796 .seealso: PCMGGetGalerkin() 797 798 @*/ 799 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc) 800 { 801 PC_MG **mg; 802 PetscInt i,levels; 803 804 PetscFunctionBegin; 805 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 806 mg = (PC_MG**)pc->data; 807 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 808 levels = mg[0]->levels; 809 810 for (i=0; i<levels; i++) { 811 mg[i]->galerkin = PETSC_TRUE; 812 } 813 PetscFunctionReturn(0); 814 } 815 816 #undef __FUNCT__ 817 #define __FUNCT__ "PCMGGetGalerkin" 818 /*@ 819 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 820 A_i-1 = r_i * A_i * r_i^t 821 822 Not Collective 823 824 Input Parameter: 825 . pc - the multigrid context 826 827 Output Parameter: 828 . gelerkin - PETSC_TRUE or PETSC_FALSE 829 830 Options Database Key: 831 $ -pc_mg_galerkin 832 833 Level: intermediate 834 835 .keywords: MG, set, Galerkin 836 837 .seealso: PCMGSetGalerkin() 838 839 @*/ 840 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetGalerkin(PC pc,PetscTruth *galerkin) 841 { 842 PC_MG **mg; 843 844 PetscFunctionBegin; 845 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 846 mg = (PC_MG**)pc->data; 847 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 848 *galerkin = mg[0]->galerkin; 849 PetscFunctionReturn(0); 850 } 851 852 #undef __FUNCT__ 853 #define __FUNCT__ "PCMGSetNumberSmoothDown" 854 /*@ 855 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 856 use on all levels. Use PCMGGetSmootherDown() to set different 857 pre-smoothing steps on different levels. 858 859 Collective on PC 860 861 Input Parameters: 862 + mg - the multigrid context 863 - n - the number of smoothing steps 864 865 Options Database Key: 866 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 867 868 Level: advanced 869 870 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 871 872 .seealso: PCMGSetNumberSmoothUp() 873 @*/ 874 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n) 875 { 876 PC_MG **mg; 877 PetscErrorCode ierr; 878 PetscInt i,levels; 879 880 PetscFunctionBegin; 881 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 882 mg = (PC_MG**)pc->data; 883 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 884 levels = mg[0]->levels; 885 886 for (i=1; i<levels; i++) { 887 /* make sure smoother up and down are different */ 888 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 889 ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 890 mg[i]->default_smoothd = n; 891 } 892 PetscFunctionReturn(0); 893 } 894 895 #undef __FUNCT__ 896 #define __FUNCT__ "PCMGSetNumberSmoothUp" 897 /*@ 898 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 899 on all levels. Use PCMGGetSmootherUp() to set different numbers of 900 post-smoothing steps on different levels. 901 902 Collective on PC 903 904 Input Parameters: 905 + mg - the multigrid context 906 - n - the number of smoothing steps 907 908 Options Database Key: 909 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 910 911 Level: advanced 912 913 Note: this does not set a value on the coarsest grid, since we assume that 914 there is no separate smooth up on the coarsest grid. 915 916 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 917 918 .seealso: PCMGSetNumberSmoothDown() 919 @*/ 920 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n) 921 { 922 PC_MG **mg; 923 PetscErrorCode ierr; 924 PetscInt i,levels; 925 926 PetscFunctionBegin; 927 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 928 mg = (PC_MG**)pc->data; 929 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 930 levels = mg[0]->levels; 931 932 for (i=1; i<levels; i++) { 933 /* make sure smoother up and down are different */ 934 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 935 ierr = KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 936 mg[i]->default_smoothu = n; 937 } 938 PetscFunctionReturn(0); 939 } 940 941 /* ----------------------------------------------------------------------------------------*/ 942 943 /*MC 944 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 945 information about the coarser grid matrices and restriction/interpolation operators. 946 947 Options Database Keys: 948 + -pc_mg_levels <nlevels> - number of levels including finest 949 . -pc_mg_cycles v or w 950 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 951 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 952 . -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default 953 . -pc_mg_log - log information about time spent on each level of the solver 954 . -pc_mg_monitor - print information on the multigrid convergence 955 . -pc_mg_galerkin - use Galerkin process to compute coarser operators 956 - -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 957 to the Socket viewer for reading from Matlab. 958 959 Notes: 960 961 Level: intermediate 962 963 Concepts: multigrid/multilevel 964 965 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, 966 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 967 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 968 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 969 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 970 M*/ 971 972 EXTERN_C_BEGIN 973 #undef __FUNCT__ 974 #define __FUNCT__ "PCCreate_MG" 975 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc) 976 { 977 PetscFunctionBegin; 978 pc->ops->apply = PCApply_MG; 979 pc->ops->setup = PCSetUp_MG; 980 pc->ops->destroy = PCDestroy_MG; 981 pc->ops->setfromoptions = PCSetFromOptions_MG; 982 pc->ops->view = PCView_MG; 983 984 pc->data = (void*)0; 985 PetscFunctionReturn(0); 986 } 987 EXTERN_C_END 988