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 = PC_MG_ADDITIVE; 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 ierr = PetscOptionsEnum("-pc_mg_type","Multigrid type","PCMGSetType",PCMGTypes,(PetscEnum)mgtype,(PetscEnum*)&mgtype,&flg);CHKERRQ(ierr); 295 if (flg) { 296 ierr = PCMGSetType(pc,mgtype);CHKERRQ(ierr); 297 } 298 if (mg[0]->am == PC_MG_MULTIPLICATIVE) { 299 ierr = PetscOptionsInt("-pc_mg_multiplicative_cycles","Number of cycles for each preconditioner step","PCMGSetLevels",mg[0]->cyclesperpcapply,&cycles,&flg);CHKERRQ(ierr); 300 if (flg) { 301 ierr = PCMGMultiplicativeSetCycles(pc,cycles);CHKERRQ(ierr); 302 } 303 } 304 flg = PETSC_FALSE; 305 ierr = PetscOptionsTruth("-pc_mg_log","Log times for each multigrid level","None",flg,&flg,PETSC_NULL);CHKERRQ(ierr); 306 if (flg) { 307 PetscInt i; 308 char eventname[128]; 309 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 310 levels = mg[0]->levels; 311 for (i=0; i<levels; i++) { 312 sprintf(eventname,"MGSetup Level %d",(int)i); 313 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventsmoothsetup);CHKERRQ(ierr); 314 sprintf(eventname,"MGSmooth Level %d",(int)i); 315 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventsmoothsolve);CHKERRQ(ierr); 316 if (i) { 317 sprintf(eventname,"MGResid Level %d",(int)i); 318 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventresidual);CHKERRQ(ierr); 319 sprintf(eventname,"MGInterp Level %d",(int)i); 320 ierr = PetscLogEventRegister(eventname,((PetscObject)pc)->cookie,&mg[i]->eventinterprestrict);CHKERRQ(ierr); 321 } 322 } 323 } 324 ierr = PetscOptionsTail();CHKERRQ(ierr); 325 PetscFunctionReturn(0); 326 } 327 328 const char *PCMGTypes[] = {"MULTIPLICATIVE","ADDITIVE","FULL","KASKADE","PCMGType","PC_MG",0}; 329 const char *PCMGCycleTypes[] = {"invalid","v","w","PCMGCycleType","PC_MG_CYCLE",0}; 330 331 #undef __FUNCT__ 332 #define __FUNCT__ "PCView_MG" 333 PetscErrorCode PCView_MG(PC pc,PetscViewer viewer) 334 { 335 PC_MG **mg = (PC_MG**)pc->data; 336 PetscErrorCode ierr; 337 PetscInt levels = mg[0]->levels,i; 338 PetscTruth iascii; 339 340 PetscFunctionBegin; 341 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 342 if (iascii) { 343 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); 344 if (mg[0]->am == PC_MG_MULTIPLICATIVE) { 345 ierr = PetscViewerASCIIPrintf(viewer," Cycles per PCApply=%d\n",mg[0]->cyclesperpcapply);CHKERRQ(ierr); 346 } 347 if (mg[0]->galerkin) { 348 ierr = PetscViewerASCIIPrintf(viewer," Using Galerkin computed coarse grid matrices\n");CHKERRQ(ierr); 349 } 350 for (i=0; i<levels; i++) { 351 if (!i) { 352 ierr = PetscViewerASCIIPrintf(viewer,"Coarse grid solver -- level %D presmooths=%D postsmooths=%D -----\n",i,mg[0]->default_smoothd,mg[0]->default_smoothu);CHKERRQ(ierr); 353 } else { 354 ierr = PetscViewerASCIIPrintf(viewer,"Down solver (pre-smoother) on level %D smooths=%D --------------------\n",i,mg[i]->default_smoothd);CHKERRQ(ierr); 355 } 356 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 357 ierr = KSPView(mg[i]->smoothd,viewer);CHKERRQ(ierr); 358 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 359 if (i && mg[i]->smoothd == mg[i]->smoothu) { 360 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) same as down solver (pre-smoother)\n");CHKERRQ(ierr); 361 } else if (i){ 362 ierr = PetscViewerASCIIPrintf(viewer,"Up solver (post-smoother) on level %D smooths=%D --------------------\n",i,mg[i]->default_smoothu);CHKERRQ(ierr); 363 ierr = PetscViewerASCIIPushTab(viewer);CHKERRQ(ierr); 364 ierr = KSPView(mg[i]->smoothu,viewer);CHKERRQ(ierr); 365 ierr = PetscViewerASCIIPopTab(viewer);CHKERRQ(ierr); 366 } 367 } 368 } else { 369 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for PCMG",((PetscObject)viewer)->type_name); 370 } 371 PetscFunctionReturn(0); 372 } 373 374 /* 375 Calls setup for the KSP on each level 376 */ 377 #undef __FUNCT__ 378 #define __FUNCT__ "PCSetUp_MG" 379 PetscErrorCode PCSetUp_MG(PC pc) 380 { 381 PC_MG **mg = (PC_MG**)pc->data; 382 PetscErrorCode ierr; 383 PetscInt i,n = mg[0]->levels; 384 PC cpc,mpc; 385 PetscTruth preonly,lu,redundant,cholesky,monitor = PETSC_FALSE,dump = PETSC_FALSE,opsset; 386 PetscViewerASCIIMonitor ascii; 387 PetscViewer viewer = PETSC_NULL; 388 MPI_Comm comm; 389 Mat dA,dB; 390 MatStructure uflag; 391 Vec tvec; 392 393 PetscFunctionBegin; 394 395 /* If user did not provide fine grid operators OR operator was not updated since last global KSPSetOperators() */ 396 /* so use those from global PC */ 397 /* Is this what we always want? What if user wants to keep old one? */ 398 ierr = KSPGetOperatorsSet(mg[n-1]->smoothd,PETSC_NULL,&opsset);CHKERRQ(ierr); 399 ierr = KSPGetPC(mg[0]->smoothd,&cpc);CHKERRQ(ierr); 400 ierr = KSPGetPC(mg[n-1]->smoothd,&mpc);CHKERRQ(ierr); 401 if (!opsset || ((cpc->setupcalled == 1) && (mpc->setupcalled == 2))) { 402 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); 403 ierr = KSPSetOperators(mg[n-1]->smoothd,pc->mat,pc->pmat,pc->flag);CHKERRQ(ierr); 404 } 405 406 if (mg[0]->galerkin) { 407 Mat B; 408 mg[0]->galerkinused = PETSC_TRUE; 409 /* currently only handle case where mat and pmat are the same on coarser levels */ 410 ierr = KSPGetOperators(mg[n-1]->smoothd,&dA,&dB,&uflag);CHKERRQ(ierr); 411 if (!pc->setupcalled) { 412 for (i=n-2; i>-1; i--) { 413 ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_INITIAL_MATRIX,1.0,&B);CHKERRQ(ierr); 414 ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 415 if (i != n-2) {ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr);} 416 dB = B; 417 } 418 ierr = PetscObjectDereference((PetscObject)dB);CHKERRQ(ierr); 419 } else { 420 for (i=n-2; i>-1; i--) { 421 ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&B,PETSC_NULL);CHKERRQ(ierr); 422 ierr = MatPtAP(dB,mg[i+1]->interpolate,MAT_REUSE_MATRIX,1.0,&B);CHKERRQ(ierr); 423 ierr = KSPSetOperators(mg[i]->smoothd,B,B,uflag);CHKERRQ(ierr); 424 dB = B; 425 } 426 } 427 } 428 429 if (!pc->setupcalled) { 430 ierr = PetscOptionsGetTruth(0,"-pc_mg_monitor",&monitor,PETSC_NULL);CHKERRQ(ierr); 431 432 for (i=0; i<n; i++) { 433 if (monitor) { 434 ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothd,&comm);CHKERRQ(ierr); 435 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr); 436 ierr = KSPMonitorSet(mg[i]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 437 } 438 ierr = KSPSetFromOptions(mg[i]->smoothd);CHKERRQ(ierr); 439 } 440 for (i=1; i<n; i++) { 441 if (mg[i]->smoothu && (mg[i]->smoothu != mg[i]->smoothd)) { 442 if (monitor) { 443 ierr = PetscObjectGetComm((PetscObject)mg[i]->smoothu,&comm);CHKERRQ(ierr); 444 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n-i,&ascii);CHKERRQ(ierr); 445 ierr = KSPMonitorSet(mg[i]->smoothu,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 446 } 447 ierr = KSPSetFromOptions(mg[i]->smoothu);CHKERRQ(ierr); 448 } 449 } 450 for (i=1; i<n; i++) { 451 if (!mg[i]->residual) { 452 Mat mat; 453 ierr = KSPGetOperators(mg[i]->smoothd,PETSC_NULL,&mat,PETSC_NULL);CHKERRQ(ierr); 454 ierr = PCMGSetResidual(pc,i,PCMGDefaultResidual,mat);CHKERRQ(ierr); 455 } 456 if (mg[i]->restrct && !mg[i]->interpolate) { 457 ierr = PCMGSetInterpolation(pc,i,mg[i]->restrct);CHKERRQ(ierr); 458 } 459 if (!mg[i]->restrct && mg[i]->interpolate) { 460 ierr = PCMGSetRestriction(pc,i,mg[i]->interpolate);CHKERRQ(ierr); 461 } 462 #if defined(PETSC_USE_DEBUG) 463 if (!mg[i]->restrct || !mg[i]->interpolate) { 464 SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Need to set restriction or interpolation on level %d",(int)i); 465 } 466 #endif 467 } 468 for (i=0; i<n-1; i++) { 469 if (!mg[i]->b) { 470 Vec *vec; 471 ierr = KSPGetVecs(mg[i]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 472 ierr = PCMGSetRhs(pc,i,*vec);CHKERRQ(ierr); 473 ierr = VecDestroy(*vec);CHKERRQ(ierr); 474 ierr = PetscFree(vec);CHKERRQ(ierr); 475 } 476 if (!mg[i]->r && i) { 477 ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr); 478 ierr = PCMGSetR(pc,i,tvec);CHKERRQ(ierr); 479 ierr = VecDestroy(tvec);CHKERRQ(ierr); 480 } 481 if (!mg[i]->x) { 482 ierr = VecDuplicate(mg[i]->b,&tvec);CHKERRQ(ierr); 483 ierr = PCMGSetX(pc,i,tvec);CHKERRQ(ierr); 484 ierr = VecDestroy(tvec);CHKERRQ(ierr); 485 } 486 } 487 if (n != 1 && !mg[n-1]->r) { 488 /* PCMGSetR() on the finest level if user did not supply it */ 489 Vec *vec; 490 ierr = KSPGetVecs(mg[n-1]->smoothd,1,&vec,0,PETSC_NULL);CHKERRQ(ierr); 491 ierr = PCMGSetR(pc,n-1,*vec);CHKERRQ(ierr); 492 ierr = VecDestroy(*vec);CHKERRQ(ierr); 493 ierr = PetscFree(vec);CHKERRQ(ierr); 494 } 495 } 496 497 498 for (i=1; i<n; i++) { 499 if (mg[i]->smoothu == mg[i]->smoothd) { 500 /* if doing only down then initial guess is zero */ 501 ierr = KSPSetInitialGuessNonzero(mg[i]->smoothd,PETSC_TRUE);CHKERRQ(ierr); 502 } 503 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 504 ierr = KSPSetUp(mg[i]->smoothd);CHKERRQ(ierr); 505 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 506 } 507 for (i=1; i<n; i++) { 508 if (mg[i]->smoothu && mg[i]->smoothu != mg[i]->smoothd) { 509 Mat downmat,downpmat; 510 MatStructure matflag; 511 PetscTruth opsset; 512 513 /* check if operators have been set for up, if not use down operators to set them */ 514 ierr = KSPGetOperatorsSet(mg[i]->smoothu,&opsset,PETSC_NULL);CHKERRQ(ierr); 515 if (!opsset) { 516 ierr = KSPGetOperators(mg[i]->smoothd,&downmat,&downpmat,&matflag);CHKERRQ(ierr); 517 ierr = KSPSetOperators(mg[i]->smoothu,downmat,downpmat,matflag);CHKERRQ(ierr); 518 } 519 520 ierr = KSPSetInitialGuessNonzero(mg[i]->smoothu,PETSC_TRUE);CHKERRQ(ierr); 521 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 522 ierr = KSPSetUp(mg[i]->smoothu);CHKERRQ(ierr); 523 if (mg[i]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[i]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 524 } 525 } 526 527 /* 528 If coarse solver is not direct method then DO NOT USE preonly 529 */ 530 ierr = PetscTypeCompare((PetscObject)mg[0]->smoothd,KSPPREONLY,&preonly);CHKERRQ(ierr); 531 if (preonly) { 532 ierr = PetscTypeCompare((PetscObject)cpc,PCLU,&lu);CHKERRQ(ierr); 533 ierr = PetscTypeCompare((PetscObject)cpc,PCREDUNDANT,&redundant);CHKERRQ(ierr); 534 ierr = PetscTypeCompare((PetscObject)cpc,PCCHOLESKY,&cholesky);CHKERRQ(ierr); 535 if (!lu && !redundant && !cholesky) { 536 ierr = KSPSetType(mg[0]->smoothd,KSPGMRES);CHKERRQ(ierr); 537 } 538 } 539 540 if (!pc->setupcalled) { 541 if (monitor) { 542 ierr = PetscObjectGetComm((PetscObject)mg[0]->smoothd,&comm);CHKERRQ(ierr); 543 ierr = PetscViewerASCIIMonitorCreate(comm,"stdout",n,&ascii);CHKERRQ(ierr); 544 ierr = KSPMonitorSet(mg[0]->smoothd,KSPMonitorDefault,ascii,(PetscErrorCode(*)(void*))PetscViewerASCIIMonitorDestroy);CHKERRQ(ierr); 545 } 546 ierr = KSPSetFromOptions(mg[0]->smoothd);CHKERRQ(ierr); 547 } 548 549 if (mg[0]->eventsmoothsetup) {ierr = PetscLogEventBegin(mg[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 550 ierr = KSPSetUp(mg[0]->smoothd);CHKERRQ(ierr); 551 if (mg[0]->eventsmoothsetup) {ierr = PetscLogEventEnd(mg[0]->eventsmoothsetup,0,0,0,0);CHKERRQ(ierr);} 552 553 /* 554 Dump the interpolation/restriction matrices plus the 555 Jacobian/stiffness on each level. This allows Matlab users to 556 easily check if the Galerkin condition A_c = R A_f R^T is satisfied. 557 558 Only support one or the other at the same time. 559 */ 560 #if defined(PETSC_USE_SOCKET_VIEWER) 561 ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_matlab",&dump,PETSC_NULL);CHKERRQ(ierr); 562 if (dump) { 563 viewer = PETSC_VIEWER_SOCKET_(((PetscObject)pc)->comm); 564 } 565 dump = PETSC_FALSE; 566 #endif 567 ierr = PetscOptionsGetTruth(((PetscObject)pc)->prefix,"-pc_mg_dump_binary",&dump,PETSC_NULL);CHKERRQ(ierr); 568 if (dump) { 569 viewer = PETSC_VIEWER_BINARY_(((PetscObject)pc)->comm); 570 } 571 572 if (viewer) { 573 for (i=1; i<n; i++) { 574 ierr = MatView(mg[i]->restrct,viewer);CHKERRQ(ierr); 575 } 576 for (i=0; i<n; i++) { 577 ierr = KSPGetPC(mg[i]->smoothd,&pc);CHKERRQ(ierr); 578 ierr = MatView(pc->mat,viewer);CHKERRQ(ierr); 579 } 580 } 581 PetscFunctionReturn(0); 582 } 583 584 /* -------------------------------------------------------------------------------------*/ 585 586 #undef __FUNCT__ 587 #define __FUNCT__ "PCMGSetLevels" 588 /*@C 589 PCMGSetLevels - Sets the number of levels to use with MG. 590 Must be called before any other MG routine. 591 592 Collective on PC 593 594 Input Parameters: 595 + pc - the preconditioner context 596 . levels - the number of levels 597 - comms - optional communicators for each level; this is to allow solving the coarser problems 598 on smaller sets of processors. Use PETSC_NULL_OBJECT for default in Fortran 599 600 Level: intermediate 601 602 Notes: 603 If the number of levels is one then the multigrid uses the -mg_levels prefix 604 for setting the level options rather than the -mg_coarse prefix. 605 606 .keywords: MG, set, levels, multigrid 607 608 .seealso: PCMGSetType(), PCMGGetLevels() 609 @*/ 610 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetLevels(PC pc,PetscInt levels,MPI_Comm *comms) 611 { 612 PetscErrorCode ierr; 613 PC_MG **mg=0; 614 615 PetscFunctionBegin; 616 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 617 618 if (pc->data) { 619 SETERRQ(PETSC_ERR_ORDER,"Number levels already set for MG\n\ 620 make sure that you call PCMGSetLevels() before KSPSetFromOptions()"); 621 } 622 ierr = PCMGCreate_Private(((PetscObject)pc)->comm,levels,pc,comms,&mg);CHKERRQ(ierr); 623 mg[0]->am = PC_MG_MULTIPLICATIVE; 624 pc->data = (void*)mg; 625 pc->ops->applyrichardson = PCApplyRichardson_MG; 626 PetscFunctionReturn(0); 627 } 628 629 #undef __FUNCT__ 630 #define __FUNCT__ "PCMGGetLevels" 631 /*@ 632 PCMGGetLevels - Gets the number of levels to use with MG. 633 634 Not Collective 635 636 Input Parameter: 637 . pc - the preconditioner context 638 639 Output parameter: 640 . levels - the number of levels 641 642 Level: advanced 643 644 .keywords: MG, get, levels, multigrid 645 646 .seealso: PCMGSetLevels() 647 @*/ 648 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetLevels(PC pc,PetscInt *levels) 649 { 650 PC_MG **mg; 651 652 PetscFunctionBegin; 653 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 654 PetscValidIntPointer(levels,2); 655 656 mg = (PC_MG**)pc->data; 657 *levels = mg[0]->levels; 658 PetscFunctionReturn(0); 659 } 660 661 #undef __FUNCT__ 662 #define __FUNCT__ "PCMGSetType" 663 /*@ 664 PCMGSetType - Determines the form of multigrid to use: 665 multiplicative, additive, full, or the Kaskade algorithm. 666 667 Collective on PC 668 669 Input Parameters: 670 + pc - the preconditioner context 671 - form - multigrid form, one of PC_MG_MULTIPLICATIVE, PC_MG_ADDITIVE, 672 PC_MG_FULL, PC_MG_KASKADE 673 674 Options Database Key: 675 . -pc_mg_type <form> - Sets <form>, one of multiplicative, 676 additive, full, kaskade 677 678 Level: advanced 679 680 .keywords: MG, set, method, multiplicative, additive, full, Kaskade, multigrid 681 682 .seealso: PCMGSetLevels() 683 @*/ 684 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetType(PC pc,PCMGType form) 685 { 686 PC_MG **mg; 687 688 PetscFunctionBegin; 689 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 690 mg = (PC_MG**)pc->data; 691 692 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 693 mg[0]->am = form; 694 if (form == PC_MG_MULTIPLICATIVE) pc->ops->applyrichardson = PCApplyRichardson_MG; 695 else pc->ops->applyrichardson = 0; 696 PetscFunctionReturn(0); 697 } 698 699 #undef __FUNCT__ 700 #define __FUNCT__ "PCMGSetCycleType" 701 /*@ 702 PCMGSetCycleType - Sets the type cycles to use. Use PCMGSetCycleTypeOnLevel() for more 703 complicated cycling. 704 705 Collective on PC 706 707 Input Parameters: 708 + pc - the multigrid context 709 - PC_MG_CYCLE_V or PC_MG_CYCLE_W 710 711 Options Database Key: 712 $ -pc_mg_cycle_type v or w 713 714 Level: advanced 715 716 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 717 718 .seealso: PCMGSetCycleTypeOnLevel() 719 @*/ 720 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetCycleType(PC pc,PCMGCycleType n) 721 { 722 PC_MG **mg; 723 PetscInt i,levels; 724 725 PetscFunctionBegin; 726 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 727 mg = (PC_MG**)pc->data; 728 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 729 levels = mg[0]->levels; 730 731 for (i=0; i<levels; i++) { 732 mg[i]->cycles = n; 733 } 734 PetscFunctionReturn(0); 735 } 736 737 #undef __FUNCT__ 738 #define __FUNCT__ "PCMGMultiplicativeSetCycles" 739 /*@ 740 PCMGMultiplicativeSetCycles - Sets the number of cycles to use for each preconditioner step 741 of multigrid when PCMGType of PC_MG_MULTIPLICATIVE is used 742 743 Collective on PC 744 745 Input Parameters: 746 + pc - the multigrid context 747 - n - number of cycles (default is 1) 748 749 Options Database Key: 750 $ -pc_mg_multiplicative_cycles n 751 752 Level: advanced 753 754 Notes: This is not associated with setting a v or w cycle, that is set with PCMGSetCycleType() 755 756 .keywords: MG, set, cycles, V-cycle, W-cycle, multigrid 757 758 .seealso: PCMGSetCycleTypeOnLevel(), PCMGSetCycleType() 759 @*/ 760 PetscErrorCode PETSCKSP_DLLEXPORT PCMGMultiplicativeSetCycles(PC pc,PetscInt n) 761 { 762 PC_MG **mg; 763 PetscInt i,levels; 764 765 PetscFunctionBegin; 766 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 767 mg = (PC_MG**)pc->data; 768 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 769 levels = mg[0]->levels; 770 771 for (i=0; i<levels; i++) { 772 mg[i]->cyclesperpcapply = n; 773 } 774 PetscFunctionReturn(0); 775 } 776 777 #undef __FUNCT__ 778 #define __FUNCT__ "PCMGSetGalerkin" 779 /*@ 780 PCMGSetGalerkin - Causes the coarser grid matrices to be computed from the 781 finest grid via the Galerkin process: A_i-1 = r_i * A_i * r_i^t 782 783 Collective on PC 784 785 Input Parameters: 786 . pc - the multigrid context 787 788 Options Database Key: 789 $ -pc_mg_galerkin 790 791 Level: intermediate 792 793 .keywords: MG, set, Galerkin 794 795 .seealso: PCMGGetGalerkin() 796 797 @*/ 798 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetGalerkin(PC pc) 799 { 800 PC_MG **mg; 801 PetscInt i,levels; 802 803 PetscFunctionBegin; 804 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 805 mg = (PC_MG**)pc->data; 806 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 807 levels = mg[0]->levels; 808 809 for (i=0; i<levels; i++) { 810 mg[i]->galerkin = PETSC_TRUE; 811 } 812 PetscFunctionReturn(0); 813 } 814 815 #undef __FUNCT__ 816 #define __FUNCT__ "PCMGGetGalerkin" 817 /*@ 818 PCMGGetGalerkin - Checks if Galerkin multigrid is being used, i.e. 819 A_i-1 = r_i * A_i * r_i^t 820 821 Not Collective 822 823 Input Parameter: 824 . pc - the multigrid context 825 826 Output Parameter: 827 . gelerkin - PETSC_TRUE or PETSC_FALSE 828 829 Options Database Key: 830 $ -pc_mg_galerkin 831 832 Level: intermediate 833 834 .keywords: MG, set, Galerkin 835 836 .seealso: PCMGSetGalerkin() 837 838 @*/ 839 PetscErrorCode PETSCKSP_DLLEXPORT PCMGGetGalerkin(PC pc,PetscTruth *galerkin) 840 { 841 PC_MG **mg; 842 843 PetscFunctionBegin; 844 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 845 mg = (PC_MG**)pc->data; 846 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 847 *galerkin = mg[0]->galerkin; 848 PetscFunctionReturn(0); 849 } 850 851 #undef __FUNCT__ 852 #define __FUNCT__ "PCMGSetNumberSmoothDown" 853 /*@ 854 PCMGSetNumberSmoothDown - Sets the number of pre-smoothing steps to 855 use on all levels. Use PCMGGetSmootherDown() to set different 856 pre-smoothing steps on different levels. 857 858 Collective on PC 859 860 Input Parameters: 861 + mg - the multigrid context 862 - n - the number of smoothing steps 863 864 Options Database Key: 865 . -pc_mg_smoothdown <n> - Sets number of pre-smoothing steps 866 867 Level: advanced 868 869 .keywords: MG, smooth, down, pre-smoothing, steps, multigrid 870 871 .seealso: PCMGSetNumberSmoothUp() 872 @*/ 873 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothDown(PC pc,PetscInt n) 874 { 875 PC_MG **mg; 876 PetscErrorCode ierr; 877 PetscInt i,levels; 878 879 PetscFunctionBegin; 880 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 881 mg = (PC_MG**)pc->data; 882 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 883 levels = mg[0]->levels; 884 885 for (i=1; i<levels; i++) { 886 /* make sure smoother up and down are different */ 887 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 888 ierr = KSPSetTolerances(mg[i]->smoothd,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 889 mg[i]->default_smoothd = n; 890 } 891 PetscFunctionReturn(0); 892 } 893 894 #undef __FUNCT__ 895 #define __FUNCT__ "PCMGSetNumberSmoothUp" 896 /*@ 897 PCMGSetNumberSmoothUp - Sets the number of post-smoothing steps to use 898 on all levels. Use PCMGGetSmootherUp() to set different numbers of 899 post-smoothing steps on different levels. 900 901 Collective on PC 902 903 Input Parameters: 904 + mg - the multigrid context 905 - n - the number of smoothing steps 906 907 Options Database Key: 908 . -pc_mg_smoothup <n> - Sets number of post-smoothing steps 909 910 Level: advanced 911 912 Note: this does not set a value on the coarsest grid, since we assume that 913 there is no separate smooth up on the coarsest grid. 914 915 .keywords: MG, smooth, up, post-smoothing, steps, multigrid 916 917 .seealso: PCMGSetNumberSmoothDown() 918 @*/ 919 PetscErrorCode PETSCKSP_DLLEXPORT PCMGSetNumberSmoothUp(PC pc,PetscInt n) 920 { 921 PC_MG **mg; 922 PetscErrorCode ierr; 923 PetscInt i,levels; 924 925 PetscFunctionBegin; 926 PetscValidHeaderSpecific(pc,PC_COOKIE,1); 927 mg = (PC_MG**)pc->data; 928 if (!mg) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must set MG levels before calling"); 929 levels = mg[0]->levels; 930 931 for (i=1; i<levels; i++) { 932 /* make sure smoother up and down are different */ 933 ierr = PCMGGetSmootherUp(pc,i,PETSC_NULL);CHKERRQ(ierr); 934 ierr = KSPSetTolerances(mg[i]->smoothu,PETSC_DEFAULT,PETSC_DEFAULT,PETSC_DEFAULT,n);CHKERRQ(ierr); 935 mg[i]->default_smoothu = n; 936 } 937 PetscFunctionReturn(0); 938 } 939 940 /* ----------------------------------------------------------------------------------------*/ 941 942 /*MC 943 PCMG - Use multigrid preconditioning. This preconditioner requires you provide additional 944 information about the coarser grid matrices and restriction/interpolation operators. 945 946 Options Database Keys: 947 + -pc_mg_levels <nlevels> - number of levels including finest 948 . -pc_mg_cycles v or w 949 . -pc_mg_smoothup <n> - number of smoothing steps after interpolation 950 . -pc_mg_smoothdown <n> - number of smoothing steps before applying restriction operator 951 . -pc_mg_type <additive,multiplicative,full,cascade> - multiplicative is the default 952 . -pc_mg_log - log information about time spent on each level of the solver 953 . -pc_mg_monitor - print information on the multigrid convergence 954 . -pc_mg_galerkin - use Galerkin process to compute coarser operators 955 - -pc_mg_dump_matlab - dumps the matrices for each level and the restriction/interpolation matrices 956 to the Socket viewer for reading from Matlab. 957 958 Notes: 959 960 Level: intermediate 961 962 Concepts: multigrid/multilevel 963 964 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, PCMGType, 965 PCMGSetLevels(), PCMGGetLevels(), PCMGSetType(), PCMGSetCycleType(), PCMGSetNumberSmoothDown(), 966 PCMGSetNumberSmoothUp(), PCMGGetCoarseSolve(), PCMGSetResidual(), PCMGSetInterpolation(), 967 PCMGSetRestriction(), PCMGGetSmoother(), PCMGGetSmootherUp(), PCMGGetSmootherDown(), 968 PCMGSetCycleTypeOnLevel(), PCMGSetRhs(), PCMGSetX(), PCMGSetR() 969 M*/ 970 971 EXTERN_C_BEGIN 972 #undef __FUNCT__ 973 #define __FUNCT__ "PCCreate_MG" 974 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_MG(PC pc) 975 { 976 PetscFunctionBegin; 977 pc->ops->apply = PCApply_MG; 978 pc->ops->setup = PCSetUp_MG; 979 pc->ops->destroy = PCDestroy_MG; 980 pc->ops->setfromoptions = PCSetFromOptions_MG; 981 pc->ops->view = PCView_MG; 982 983 pc->data = (void*)0; 984 PetscFunctionReturn(0); 985 } 986 EXTERN_C_END 987