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