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