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