1 /* 2 The basic KSP routines, Create, View etc. are here. 3 */ 4 #include <petsc/private/kspimpl.h> /*I "petscksp.h" I*/ 5 6 /* Logging support */ 7 PetscClassId KSP_CLASSID; 8 PetscClassId DMKSP_CLASSID; 9 PetscClassId KSPGUESS_CLASSID; 10 PetscLogEvent KSP_GMRESOrthogonalization, KSP_SetUp, KSP_Solve, KSP_SolveTranspose, KSP_MatSolve, KSP_MatSolveTranspose; 11 12 /* 13 Contains the list of registered KSP routines 14 */ 15 PetscFunctionList KSPList = NULL; 16 PetscBool KSPRegisterAllCalled = PETSC_FALSE; 17 18 /* 19 Contains the list of registered KSP monitors 20 */ 21 PetscFunctionList KSPMonitorList = NULL; 22 PetscFunctionList KSPMonitorCreateList = NULL; 23 PetscFunctionList KSPMonitorDestroyList = NULL; 24 PetscBool KSPMonitorRegisterAllCalled = PETSC_FALSE; 25 26 /*@ 27 KSPLoad - Loads a `KSP` that has been stored in a `PETSCVIEWERBINARY` with `KSPView()`. 28 29 Collective 30 31 Input Parameters: 32 + newdm - the newly loaded `KSP`, this needs to have been created with `KSPCreate()` or 33 some related function before a call to `KSPLoad()`. 34 - viewer - binary file viewer, obtained from `PetscViewerBinaryOpen()` 35 36 Level: intermediate 37 38 Note: 39 The type is determined by the data in the file, any type set into the `KSP` before this call is ignored. 40 41 .seealso: [](ch_ksp), `KSP`, `PetscViewerBinaryOpen()`, `KSPView()`, `MatLoad()`, `VecLoad()` 42 @*/ 43 PetscErrorCode KSPLoad(KSP newdm, PetscViewer viewer) 44 { 45 PetscBool isbinary; 46 PetscInt classid; 47 char type[256]; 48 PC pc; 49 50 PetscFunctionBegin; 51 PetscValidHeaderSpecific(newdm, KSP_CLASSID, 1); 52 PetscValidHeaderSpecific(viewer, PETSC_VIEWER_CLASSID, 2); 53 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 54 PetscCheck(isbinary, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Invalid viewer; open viewer with PetscViewerBinaryOpen()"); 55 56 PetscCall(PetscViewerBinaryRead(viewer, &classid, 1, NULL, PETSC_INT)); 57 PetscCheck(classid == KSP_FILE_CLASSID, PetscObjectComm((PetscObject)newdm), PETSC_ERR_ARG_WRONG, "Not KSP next in file"); 58 PetscCall(PetscViewerBinaryRead(viewer, type, 256, NULL, PETSC_CHAR)); 59 PetscCall(KSPSetType(newdm, type)); 60 PetscTryTypeMethod(newdm, load, viewer); 61 PetscCall(KSPGetPC(newdm, &pc)); 62 PetscCall(PCLoad(pc, viewer)); 63 PetscFunctionReturn(PETSC_SUCCESS); 64 } 65 66 #include <petscdraw.h> 67 #if defined(PETSC_HAVE_SAWS) 68 #include <petscviewersaws.h> 69 #endif 70 /*@ 71 KSPView - Prints the various parameters currently set in the `KSP` object. For example, the convergence tolerances and `KSPType`. 72 Also views the `PC` and `Mat` contained by the `KSP` with `PCView()` and `MatView()`. 73 74 Collective 75 76 Input Parameters: 77 + ksp - the Krylov space context 78 - viewer - visualization context 79 80 Options Database Key: 81 . -ksp_view - print the `KSP` data structure at the end of each `KSPSolve()` call 82 83 Level: beginner 84 85 Notes: 86 The available visualization contexts include 87 + `PETSC_VIEWER_STDOUT_SELF` - standard output (default) 88 - `PETSC_VIEWER_STDOUT_WORLD` - synchronized standard 89 output where only the first processor opens 90 the file. All other processors send their 91 data to the first processor to print. 92 93 The available formats include 94 + `PETSC_VIEWER_DEFAULT` - standard output (default) 95 - `PETSC_VIEWER_ASCII_INFO_DETAIL` - more verbose output for `PCBJACOBI` and `PCASM` 96 97 The user can open an alternative visualization context with 98 `PetscViewerASCIIOpen()` - output to a specified file. 99 100 Use `KSPViewFromOptions()` to allow the user to select many different `PetscViewerType` and formats from the options database. 101 102 In the debugger you can do call `KSPView(ksp,0)` to display the `KSP`. (The same holds for any PETSc object viewer). 103 104 .seealso: [](ch_ksp), `KSP`, `PetscViewer`, `PCView()`, `PetscViewerASCIIOpen()`, `KSPViewFromOptions()` 105 @*/ 106 PetscErrorCode KSPView(KSP ksp, PetscViewer viewer) 107 { 108 PetscBool isascii, isbinary, isdraw, isstring; 109 #if defined(PETSC_HAVE_SAWS) 110 PetscBool issaws; 111 #endif 112 113 PetscFunctionBegin; 114 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 115 if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ksp), &viewer)); 116 PetscValidHeaderSpecific(viewer, PETSC_VIEWER_CLASSID, 2); 117 PetscCheckSameComm(ksp, 1, viewer, 2); 118 119 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii)); 120 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary)); 121 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw)); 122 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSTRING, &isstring)); 123 #if defined(PETSC_HAVE_SAWS) 124 PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSAWS, &issaws)); 125 #endif 126 if (isascii) { 127 PetscCall(PetscObjectPrintClassNamePrefixType((PetscObject)ksp, viewer)); 128 PetscCall(PetscViewerASCIIPushTab(viewer)); 129 PetscTryTypeMethod(ksp, view, viewer); 130 PetscCall(PetscViewerASCIIPopTab(viewer)); 131 if (ksp->guess_zero) { 132 PetscCall(PetscViewerASCIIPrintf(viewer, " maximum iterations=%" PetscInt_FMT ", initial guess is zero\n", ksp->max_it)); 133 } else { 134 PetscCall(PetscViewerASCIIPrintf(viewer, " maximum iterations=%" PetscInt_FMT ", nonzero initial guess\n", ksp->max_it)); 135 } 136 if (ksp->min_it) PetscCall(PetscViewerASCIIPrintf(viewer, " minimum iterations=%" PetscInt_FMT "\n", ksp->min_it)); 137 if (ksp->guess_knoll) PetscCall(PetscViewerASCIIPrintf(viewer, " using preconditioner applied to right-hand side for initial guess\n")); 138 PetscCall(PetscViewerASCIIPrintf(viewer, " tolerances: relative=%g, absolute=%g, divergence=%g\n", (double)ksp->rtol, (double)ksp->abstol, (double)ksp->divtol)); 139 if (ksp->pc_side == PC_RIGHT) { 140 PetscCall(PetscViewerASCIIPrintf(viewer, " right preconditioning\n")); 141 } else if (ksp->pc_side == PC_SYMMETRIC) { 142 PetscCall(PetscViewerASCIIPrintf(viewer, " symmetric preconditioning\n")); 143 } else { 144 PetscCall(PetscViewerASCIIPrintf(viewer, " left preconditioning\n")); 145 } 146 if (ksp->guess) { 147 PetscCall(PetscViewerASCIIPushTab(viewer)); 148 PetscCall(KSPGuessView(ksp->guess, viewer)); 149 PetscCall(PetscViewerASCIIPopTab(viewer)); 150 } 151 if (ksp->dscale) PetscCall(PetscViewerASCIIPrintf(viewer, " diagonally scaled system\n")); 152 if (ksp->converged == KSPConvergedSkip || ksp->normtype == KSP_NORM_NONE) PetscCall(PetscViewerASCIIPrintf(viewer, " not checking for convergence\n")); 153 else PetscCall(PetscViewerASCIIPrintf(viewer, " using %s norm type for convergence test\n", KSPNormTypes[ksp->normtype])); 154 } else if (isbinary) { 155 PetscInt classid = KSP_FILE_CLASSID; 156 MPI_Comm comm; 157 PetscMPIInt rank; 158 char type[256]; 159 160 PetscCall(PetscObjectGetComm((PetscObject)ksp, &comm)); 161 PetscCallMPI(MPI_Comm_rank(comm, &rank)); 162 if (rank == 0) { 163 PetscCall(PetscViewerBinaryWrite(viewer, &classid, 1, PETSC_INT)); 164 PetscCall(PetscStrncpy(type, ((PetscObject)ksp)->type_name, 256)); 165 PetscCall(PetscViewerBinaryWrite(viewer, type, 256, PETSC_CHAR)); 166 } 167 PetscTryTypeMethod(ksp, view, viewer); 168 } else if (isstring) { 169 const char *type; 170 PetscCall(KSPGetType(ksp, &type)); 171 PetscCall(PetscViewerStringSPrintf(viewer, " KSPType: %-7.7s", type)); 172 PetscTryTypeMethod(ksp, view, viewer); 173 } else if (isdraw) { 174 PetscDraw draw; 175 char str[36]; 176 PetscReal x, y, bottom, h; 177 PetscBool flg; 178 179 PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); 180 PetscCall(PetscDrawGetCurrentPoint(draw, &x, &y)); 181 PetscCall(PetscObjectTypeCompare((PetscObject)ksp, KSPPREONLY, &flg)); 182 if (!flg) { 183 PetscCall(PetscStrncpy(str, "KSP: ", sizeof(str))); 184 PetscCall(PetscStrlcat(str, ((PetscObject)ksp)->type_name, sizeof(str))); 185 PetscCall(PetscDrawStringBoxed(draw, x, y, PETSC_DRAW_RED, PETSC_DRAW_BLACK, str, NULL, &h)); 186 bottom = y - h; 187 } else { 188 bottom = y; 189 } 190 PetscCall(PetscDrawPushCurrentPoint(draw, x, bottom)); 191 #if defined(PETSC_HAVE_SAWS) 192 } else if (issaws) { 193 PetscMPIInt rank; 194 const char *name; 195 196 PetscCall(PetscObjectGetName((PetscObject)ksp, &name)); 197 PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank)); 198 if (!((PetscObject)ksp)->amsmem && rank == 0) { 199 char dir[1024]; 200 201 PetscCall(PetscObjectViewSAWs((PetscObject)ksp, viewer)); 202 PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/its", name)); 203 PetscCallSAWs(SAWs_Register, (dir, &ksp->its, 1, SAWs_READ, SAWs_INT)); 204 if (!ksp->res_hist) PetscCall(KSPSetResidualHistory(ksp, NULL, PETSC_DECIDE, PETSC_TRUE)); 205 PetscCall(PetscSNPrintf(dir, 1024, "/PETSc/Objects/%s/res_hist", name)); 206 PetscCallSAWs(SAWs_Register, (dir, ksp->res_hist, 10, SAWs_READ, SAWs_DOUBLE)); 207 } 208 #endif 209 } else PetscTryTypeMethod(ksp, view, viewer); 210 if (ksp->pc) PetscCall(PCView(ksp->pc, viewer)); 211 if (isdraw) { 212 PetscDraw draw; 213 PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw)); 214 PetscCall(PetscDrawPopCurrentPoint(draw)); 215 } 216 PetscFunctionReturn(PETSC_SUCCESS); 217 } 218 219 /*@ 220 KSPViewFromOptions - View (print) a `KSP` object based on values in the options database. Also views the `PC` and `Mat` contained by the `KSP` 221 with `PCView()` and `MatView()`. 222 223 Collective 224 225 Input Parameters: 226 + A - Krylov solver context 227 . obj - Optional object that provides the options prefix used to query the options database 228 - name - command line option 229 230 Level: intermediate 231 232 .seealso: [](ch_ksp), `KSP`, `KSPView()`, `PetscObjectViewFromOptions()`, `KSPCreate()` 233 @*/ 234 PetscErrorCode KSPViewFromOptions(KSP A, PetscObject obj, const char name[]) 235 { 236 PetscFunctionBegin; 237 PetscValidHeaderSpecific(A, KSP_CLASSID, 1); 238 PetscCall(PetscObjectViewFromOptions((PetscObject)A, obj, name)); 239 PetscFunctionReturn(PETSC_SUCCESS); 240 } 241 242 /*@ 243 KSPSetNormType - Sets the type of residual norm that is used for convergence testing in `KSPSolve()` for the given `KSP` context 244 245 Logically Collective 246 247 Input Parameters: 248 + ksp - Krylov solver context 249 - normtype - one of 250 .vb 251 KSP_NORM_NONE - skips computing the norm, this should generally only be used if you are using 252 the Krylov method as a smoother with a fixed small number of iterations. 253 Implicitly sets `KSPConvergedSkip()` as the `KSP` convergence test. 254 Note that certain algorithms such as `KSPGMRES` ALWAYS require the norm calculation, 255 for these methods the norms are still computed, they are just not used in 256 the convergence test. 257 KSP_NORM_PRECONDITIONED - the default for left-preconditioned solves, uses the 2-norm 258 of the preconditioned residual $B^{-1}(b - A x)$. 259 KSP_NORM_UNPRECONDITIONED - uses the 2-norm of the true $b - Ax$ residual. 260 KSP_NORM_NATURAL - uses the $A$ norm of the true $b - Ax$ residual; supported by `KSPCG`, `KSPCR`, `KSPCGNE`, `KSPCGS` 261 .ve 262 263 Options Database Key: 264 . -ksp_norm_type <none,preconditioned,unpreconditioned,natural> - set `KSP` norm type 265 266 Level: advanced 267 268 Notes: 269 The norm is always of the equations residual $\| b - A x^n \|$ (or an approximation to that norm), they are never a norm of the error in the equation. 270 271 Not all combinations of preconditioner side (see `KSPSetPCSide()`) and norm types are supported by all Krylov methods. 272 If only one is set, PETSc tries to automatically change the other to find a compatible pair. If no such combination 273 is supported, PETSc will generate an error. 274 275 Developer Note: 276 Supported combinations of norm and preconditioner side are set using `KSPSetSupportedNorm()` for each `KSPType`. 277 278 .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetCheckNormIteration()`, `KSPSetPCSide()`, `KSPGetPCSide()`, `KSPNormType` 279 @*/ 280 PetscErrorCode KSPSetNormType(KSP ksp, KSPNormType normtype) 281 { 282 PetscFunctionBegin; 283 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 284 PetscValidLogicalCollectiveEnum(ksp, normtype, 2); 285 ksp->normtype = ksp->normtype_set = normtype; 286 PetscFunctionReturn(PETSC_SUCCESS); 287 } 288 289 /*@ 290 KSPSetCheckNormIteration - Sets the first iteration at which the norm of the residual will be 291 computed and used in the convergence test of `KSPSolve()` for the given `KSP` context 292 293 Logically Collective 294 295 Input Parameters: 296 + ksp - Krylov solver context 297 - it - use -1 to check at all iterations 298 299 Level: advanced 300 301 Notes: 302 Currently only works with `KSPCG`, `KSPBCGS` and `KSPIBCGS` 303 304 Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm 305 306 On steps where the norm is not computed, the previous norm is still in the variable, so if you run with, for example, 307 `-ksp_monitor` the residual norm will appear to be unchanged for several iterations (though it is not really unchanged). 308 309 Certain methods such as `KSPGMRES` always compute the residual norm, this routine will not change that computation, but it will 310 prevent the computed norm from being checked. 311 312 .seealso: [](ch_ksp), `KSP`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetLagNorm()` 313 @*/ 314 PetscErrorCode KSPSetCheckNormIteration(KSP ksp, PetscInt it) 315 { 316 PetscFunctionBegin; 317 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 318 PetscValidLogicalCollectiveInt(ksp, it, 2); 319 ksp->chknorm = it; 320 PetscFunctionReturn(PETSC_SUCCESS); 321 } 322 323 /*@ 324 KSPSetLagNorm - Lags the residual norm calculation so that it is computed as part of the `MPI_Allreduce()` used for 325 computing the inner products needed for the next iteration. 326 327 Logically Collective 328 329 Input Parameters: 330 + ksp - Krylov solver context 331 - flg - `PETSC_TRUE` or `PETSC_FALSE` 332 333 Options Database Key: 334 . -ksp_lag_norm - lag the calculated residual norm 335 336 Level: advanced 337 338 Notes: 339 Currently only works with `KSPIBCGS`. 340 341 This can reduce communication costs at the expense of doing 342 one additional iteration because the norm used in the convergence test of `KSPSolve()` is one iteration behind the actual 343 current residual norm (which has not yet been computed due to the lag). 344 345 Use `KSPSetNormType`(ksp,`KSP_NORM_NONE`) to never check the norm 346 347 If you lag the norm and run with, for example, `-ksp_monitor`, the residual norm reported will be the lagged one. 348 349 `KSPSetCheckNormIteration()` is an alternative way of avoiding the expense of computing the residual norm at each iteration. 350 351 .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSPConvergedSkip()`, `KSPSetNormType()`, `KSPSetCheckNormIteration()` 352 @*/ 353 PetscErrorCode KSPSetLagNorm(KSP ksp, PetscBool flg) 354 { 355 PetscFunctionBegin; 356 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 357 PetscValidLogicalCollectiveBool(ksp, flg, 2); 358 ksp->lagnorm = flg; 359 PetscFunctionReturn(PETSC_SUCCESS); 360 } 361 362 /*@ 363 KSPSetSupportedNorm - Sets a norm and preconditioner side supported by a `KSPType` 364 365 Logically Collective 366 367 Input Parameters: 368 + ksp - Krylov method 369 . normtype - supported norm type of the type `KSPNormType` 370 . pcside - preconditioner side, of the type `PCSide` that can be used with this `KSPNormType` 371 - priority - positive integer preference for this combination; larger values have higher priority 372 373 Level: developer 374 375 Notes: 376 This function should be called from the implementation files `KSPCreate_XXX()` to declare 377 which norms and preconditioner sides are supported. Users should not call this 378 function. 379 380 This function can be called multiple times for each combination of `KSPNormType` and `PCSide` 381 the `KSPType` supports 382 383 .seealso: [](ch_ksp), `KSP`, `KSPNormType`, `PCSide`, `KSPSetNormType()`, `KSPSetPCSide()` 384 @*/ 385 PetscErrorCode KSPSetSupportedNorm(KSP ksp, KSPNormType normtype, PCSide pcside, PetscInt priority) 386 { 387 PetscFunctionBegin; 388 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 389 ksp->normsupporttable[normtype][pcside] = priority; 390 PetscFunctionReturn(PETSC_SUCCESS); 391 } 392 393 static PetscErrorCode KSPNormSupportTableReset_Private(KSP ksp) 394 { 395 PetscFunctionBegin; 396 PetscCall(PetscMemzero(ksp->normsupporttable, sizeof(ksp->normsupporttable))); 397 ksp->pc_side = ksp->pc_side_set; 398 ksp->normtype = ksp->normtype_set; 399 PetscFunctionReturn(PETSC_SUCCESS); 400 } 401 402 PetscErrorCode KSPSetUpNorms_Private(KSP ksp, PetscBool errorifnotsupported, KSPNormType *normtype, PCSide *pcside) 403 { 404 PetscInt i, j, best, ibest = 0, jbest = 0; 405 406 PetscFunctionBegin; 407 best = 0; 408 for (i = 0; i < KSP_NORM_MAX; i++) { 409 for (j = 0; j < PC_SIDE_MAX; j++) { 410 if ((ksp->normtype == KSP_NORM_DEFAULT || ksp->normtype == i) && (ksp->pc_side == PC_SIDE_DEFAULT || ksp->pc_side == j) && ksp->normsupporttable[i][j] > best) { 411 best = ksp->normsupporttable[i][j]; 412 ibest = i; 413 jbest = j; 414 } 415 } 416 } 417 if (best < 1 && errorifnotsupported) { 418 PetscCheck(ksp->normtype != KSP_NORM_DEFAULT || ksp->pc_side != PC_SIDE_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_PLIB, "The %s KSP implementation did not call KSPSetSupportedNorm()", ((PetscObject)ksp)->type_name); 419 PetscCheck(ksp->normtype != KSP_NORM_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support preconditioner side %s", ((PetscObject)ksp)->type_name, PCSides[ksp->pc_side]); 420 PetscCheck(ksp->pc_side != PC_SIDE_DEFAULT, PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support norm type %s", ((PetscObject)ksp)->type_name, KSPNormTypes[ksp->normtype]); 421 SETERRQ(PetscObjectComm((PetscObject)ksp), PETSC_ERR_SUP, "KSP %s does not support norm type %s with preconditioner side %s", ((PetscObject)ksp)->type_name, KSPNormTypes[ksp->normtype], PCSides[ksp->pc_side]); 422 } 423 if (normtype) *normtype = (KSPNormType)ibest; 424 if (pcside) *pcside = (PCSide)jbest; 425 PetscFunctionReturn(PETSC_SUCCESS); 426 } 427 428 /*@ 429 KSPGetNormType - Gets the `KSPNormType` that is used for convergence testing during `KSPSolve()` for this `KSP` context 430 431 Not Collective 432 433 Input Parameter: 434 . ksp - Krylov solver context 435 436 Output Parameter: 437 . normtype - the `KSPNormType` that is used for convergence testing 438 439 Level: advanced 440 441 .seealso: [](ch_ksp), `KSPNormType`, `KSPSetNormType()`, `KSPConvergedSkip()` 442 @*/ 443 PetscErrorCode KSPGetNormType(KSP ksp, KSPNormType *normtype) 444 { 445 PetscFunctionBegin; 446 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 447 PetscAssertPointer(normtype, 2); 448 PetscCall(KSPSetUpNorms_Private(ksp, PETSC_TRUE, &ksp->normtype, &ksp->pc_side)); 449 *normtype = ksp->normtype; 450 PetscFunctionReturn(PETSC_SUCCESS); 451 } 452 453 #if defined(PETSC_HAVE_SAWS) 454 #include <petscviewersaws.h> 455 #endif 456 457 /*@ 458 KSPSetOperators - Sets the matrix associated with the linear system 459 and a (possibly) different one from which the preconditioner will be built into the `KSP` context. The matrix will then be used during `KSPSolve()` 460 461 Collective 462 463 Input Parameters: 464 + ksp - the `KSP` context 465 . Amat - the matrix that defines the linear system 466 - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`. 467 468 Level: beginner 469 470 Notes: 471 .vb 472 KSPSetOperators(ksp, Amat, Pmat); 473 .ve 474 is the same as 475 .vb 476 KSPGetPC(ksp, &pc); 477 PCSetOperators(pc, Amat, Pmat); 478 .ve 479 and is equivalent to 480 .vb 481 PCCreate(PetscObjectComm((PetscObject)ksp), &pc); 482 PCSetOperators(pc, Amat, Pmat); 483 KSPSetPC(ksp, pc); 484 .ve 485 486 If you know the operator `Amat` has a null space you can use `MatSetNullSpace()` and `MatSetTransposeNullSpace()` to supply the null 487 space to `Amat` and the `KSP` solvers will automatically use that null space as needed during the solution process. 488 489 All future calls to `KSPSetOperators()` must use the same size matrices, unless `KSPReset()` is called! 490 491 Passing a `NULL` for `Amat` or `Pmat` removes the matrix that is currently being used from the `KSP` context. 492 493 If you wish to replace either `Amat` or `Pmat` but leave the other one untouched then 494 first call `KSPGetOperators()` to get the one you wish to keep, call `PetscObjectReference()` 495 on it and then pass it back in your call to `KSPSetOperators()`. 496 497 Developer Notes: 498 If the operators have NOT been set with `KSPSetOperators()` then the operators 499 are created in the `PC` and returned to the user. In this case, if both operators 500 mat and pmat are requested, two DIFFERENT operators will be returned. If 501 only one is requested both operators in the `PC` will be the same (i.e. as 502 if one had called `KSPSetOperators()` with the same argument for both `Mat`s). 503 The user must set the sizes of the returned matrices and their type etc just 504 as if the user created them with `MatCreate()`. For example, 505 506 .vb 507 KSPGetOperators(ksp/pc,&mat,NULL); is equivalent to 508 set size, type, etc of mat 509 510 MatCreate(comm,&mat); 511 KSP/PCSetOperators(ksp/pc,mat,mat); 512 PetscObjectDereference((PetscObject)mat); 513 set size, type, etc of mat 514 515 and 516 517 KSP/PCGetOperators(ksp/pc,&mat,&pmat); is equivalent to 518 set size, type, etc of mat and pmat 519 520 MatCreate(comm,&mat); 521 MatCreate(comm,&pmat); 522 KSP/PCSetOperators(ksp/pc,mat,pmat); 523 PetscObjectDereference((PetscObject)mat); 524 PetscObjectDereference((PetscObject)pmat); 525 set size, type, etc of mat and pmat 526 .ve 527 528 The rationale for this support is so that when creating a `TS`, `SNES`, or `KSP` the hierarchy 529 of underlying objects (i.e. `SNES`, `KSP`, `PC`, `Mat`) and their lifespans can be completely 530 managed by the top most level object (i.e. the `TS`, `SNES`, or `KSP`). Another way to look 531 at this is when you create a `SNES` you do not NEED to create a `KSP` and attach it to 532 the `SNES` object (the `SNES` object manages it for you). Similarly when you create a `KSP` 533 you do not need to attach a `PC` to it (the `KSP` object manages the `PC` object for you). 534 Thus, why should YOU have to create the `Mat` and attach it to the `SNES`/`KSP`/`PC`, when 535 it can be created for you? 536 537 .seealso: [](ch_ksp), `KSP`, `Mat`, `KSPSolve()`, `KSPGetPC()`, `PCGetOperators()`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetComputeOperators()`, `KSPSetComputeInitialGuess()`, `KSPSetComputeRHS()` 538 @*/ 539 PetscErrorCode KSPSetOperators(KSP ksp, Mat Amat, Mat Pmat) 540 { 541 PetscFunctionBegin; 542 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 543 if (Amat) PetscValidHeaderSpecific(Amat, MAT_CLASSID, 2); 544 if (Pmat) PetscValidHeaderSpecific(Pmat, MAT_CLASSID, 3); 545 if (Amat) PetscCheckSameComm(ksp, 1, Amat, 2); 546 if (Pmat) PetscCheckSameComm(ksp, 1, Pmat, 3); 547 if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc)); 548 PetscCall(PCSetOperators(ksp->pc, Amat, Pmat)); 549 if (ksp->setupstage == KSP_SETUP_NEWRHS) ksp->setupstage = KSP_SETUP_NEWMATRIX; /* so that next solve call will call PCSetUp() on new matrix */ 550 PetscFunctionReturn(PETSC_SUCCESS); 551 } 552 553 /*@ 554 KSPGetOperators - Gets the matrix associated with the linear system 555 and a (possibly) different one used to construct the preconditioner from the `KSP` context 556 557 Collective 558 559 Input Parameter: 560 . ksp - the `KSP` context 561 562 Output Parameters: 563 + Amat - the matrix that defines the linear system 564 - Pmat - the matrix to be used in constructing the preconditioner, usually the same as `Amat`. 565 566 Level: intermediate 567 568 Notes: 569 If `KSPSetOperators()` has not been called then the `KSP` object will attempt to automatically create the matrix `Amat` and return it 570 571 Use `KSPGetOperatorsSet()` to determine if matrices have been provided. 572 573 DOES NOT increase the reference counts of the matrix, so you should NOT destroy them. 574 575 .seealso: [](ch_ksp), `KSP`, `KSPSolve()`, `KSPGetPC()`, `PCSetOperators()`, `KSPSetOperators()`, `KSPGetOperatorsSet()` 576 @*/ 577 PetscErrorCode KSPGetOperators(KSP ksp, Mat *Amat, Mat *Pmat) 578 { 579 PetscFunctionBegin; 580 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 581 if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc)); 582 PetscCall(PCGetOperators(ksp->pc, Amat, Pmat)); 583 PetscFunctionReturn(PETSC_SUCCESS); 584 } 585 586 /*@ 587 KSPGetOperatorsSet - Determines if the matrix associated with the linear system and 588 possibly a different one from which the preconditioner will be built have been set in the `KSP` with `KSPSetOperators()` 589 590 Not Collective, though the results on all processes will be the same 591 592 Input Parameter: 593 . ksp - the `KSP` context 594 595 Output Parameters: 596 + mat - the matrix associated with the linear system was set 597 - pmat - matrix from which the preconditioner will be built, usually the same as `mat` was set 598 599 Level: intermediate 600 601 Note: 602 This routine exists because if you call `KSPGetOperators()` on a `KSP` that does not yet have operators they are 603 automatically created in the call. 604 605 .seealso: [](ch_ksp), `KSP`, `PCSetOperators()`, `KSPGetOperators()`, `KSPSetOperators()`, `PCGetOperators()`, `PCGetOperatorsSet()` 606 @*/ 607 PetscErrorCode KSPGetOperatorsSet(KSP ksp, PetscBool *mat, PetscBool *pmat) 608 { 609 PetscFunctionBegin; 610 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 611 if (!ksp->pc) PetscCall(KSPGetPC(ksp, &ksp->pc)); 612 PetscCall(PCGetOperatorsSet(ksp->pc, mat, pmat)); 613 PetscFunctionReturn(PETSC_SUCCESS); 614 } 615 616 /*@C 617 KSPSetPreSolve - Sets a function that is called at the beginning of each `KSPSolve()`. Used in conjunction with `KSPSetPostSolve()`. 618 619 Logically Collective 620 621 Input Parameters: 622 + ksp - the solver object 623 . presolve - the function to call before the solve, see` KSPPSolveFn` 624 - ctx - an optional context needed by the function 625 626 Level: developer 627 628 Notes: 629 The function provided here `presolve` is used to modify the right hand side, and possibly the matrix, of the linear system to be solved. 630 The function provided with `KSPSetPostSolve()` then modifies the resulting solution of that linear system to obtain the correct solution 631 to the initial linear system. 632 633 The functions `PCPreSolve()` and `PCPostSolve()` provide a similar functionality and are used, for example with `PCEISENSTAT`. 634 635 .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPostSolve()`, `PCEISENSTAT`, `PCPreSolve()`, `PCPostSolve()` 636 @*/ 637 PetscErrorCode KSPSetPreSolve(KSP ksp, KSPPSolveFn *presolve, void *ctx) 638 { 639 PetscFunctionBegin; 640 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 641 ksp->presolve = presolve; 642 ksp->prectx = ctx; 643 PetscFunctionReturn(PETSC_SUCCESS); 644 } 645 646 /*@C 647 KSPSetPostSolve - Sets a function that is called at the end of each `KSPSolve()` (whether it converges or not). Used in conjunction with `KSPSetPreSolve()`. 648 649 Logically Collective 650 651 Input Parameters: 652 + ksp - the solver object 653 . postsolve - the function to call after the solve, see` KSPPSolveFn` 654 - ctx - an optional context needed by the function 655 656 Level: developer 657 658 .seealso: [](ch_ksp), `KSPPSolveFn`, `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPSetPreSolve()`, `PCEISENSTAT` 659 @*/ 660 PetscErrorCode KSPSetPostSolve(KSP ksp, KSPPSolveFn *postsolve, void *ctx) 661 { 662 PetscFunctionBegin; 663 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 664 ksp->postsolve = postsolve; 665 ksp->postctx = ctx; 666 PetscFunctionReturn(PETSC_SUCCESS); 667 } 668 669 /*@ 670 KSPSetNestLevel - sets the amount of nesting the `KSP` has. That is the number of levels of `KSP` above this `KSP` in a linear solve. 671 672 Collective 673 674 Input Parameters: 675 + ksp - the `KSP` 676 - level - the nest level 677 678 Level: developer 679 680 Note: 681 For example, the `KSP` in each block of a `KSPBJACOBI` has a level of 1, while the outer `KSP` has a level of 0. 682 683 .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPGetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()` 684 @*/ 685 PetscErrorCode KSPSetNestLevel(KSP ksp, PetscInt level) 686 { 687 PetscFunctionBegin; 688 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 689 PetscValidLogicalCollectiveInt(ksp, level, 2); 690 ksp->nestlevel = level; 691 PetscFunctionReturn(PETSC_SUCCESS); 692 } 693 694 /*@ 695 KSPGetNestLevel - gets the amount of nesting the `KSP` has 696 697 Not Collective 698 699 Input Parameter: 700 . ksp - the `KSP` 701 702 Output Parameter: 703 . level - the nest level 704 705 Level: developer 706 707 .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetNestLevel()`, `PCSetKSPNestLevel()`, `PCGetKSPNestLevel()` 708 @*/ 709 PetscErrorCode KSPGetNestLevel(KSP ksp, PetscInt *level) 710 { 711 PetscFunctionBegin; 712 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 713 PetscAssertPointer(level, 2); 714 *level = ksp->nestlevel; 715 PetscFunctionReturn(PETSC_SUCCESS); 716 } 717 718 /*@ 719 KSPCreate - Creates the `KSP` context. This `KSP` context is used in PETSc to solve linear systems with `KSPSolve()` 720 721 Collective 722 723 Input Parameter: 724 . comm - MPI communicator 725 726 Output Parameter: 727 . inksp - location to put the `KSP` context 728 729 Level: beginner 730 731 Note: 732 The default `KSPType` is `KSPGMRES` with a restart of 30, using modified Gram-Schmidt orthogonalization. The `KSPType` may be 733 changed with `KSPSetType()` 734 735 .seealso: [](ch_ksp), `KSPSetUp()`, `KSPSolve()`, `KSPDestroy()`, `KSP`, `KSPGMRES`, `KSPType`, `KSPSetType()` 736 @*/ 737 PetscErrorCode KSPCreate(MPI_Comm comm, KSP *inksp) 738 { 739 KSP ksp; 740 void *ctx; 741 742 PetscFunctionBegin; 743 PetscAssertPointer(inksp, 2); 744 PetscCall(KSPInitializePackage()); 745 746 PetscCall(PetscHeaderCreate(ksp, KSP_CLASSID, "KSP", "Krylov Method", "KSP", comm, KSPDestroy, KSPView)); 747 ksp->default_max_it = ksp->max_it = 10000; 748 ksp->pc_side = ksp->pc_side_set = PC_SIDE_DEFAULT; 749 750 ksp->default_rtol = ksp->rtol = 1.e-5; 751 ksp->default_abstol = ksp->abstol = PetscDefined(USE_REAL_SINGLE) ? 1.e-25 : 1.e-50; 752 ksp->default_divtol = ksp->divtol = 1.e4; 753 754 ksp->chknorm = -1; 755 ksp->normtype = ksp->normtype_set = KSP_NORM_DEFAULT; 756 ksp->rnorm = 0.0; 757 ksp->its = 0; 758 ksp->guess_zero = PETSC_TRUE; 759 ksp->calc_sings = PETSC_FALSE; 760 ksp->res_hist = NULL; 761 ksp->res_hist_alloc = NULL; 762 ksp->res_hist_len = 0; 763 ksp->res_hist_max = 0; 764 ksp->res_hist_reset = PETSC_TRUE; 765 ksp->err_hist = NULL; 766 ksp->err_hist_alloc = NULL; 767 ksp->err_hist_len = 0; 768 ksp->err_hist_max = 0; 769 ksp->err_hist_reset = PETSC_TRUE; 770 ksp->numbermonitors = 0; 771 ksp->numberreasonviews = 0; 772 ksp->setfromoptionscalled = 0; 773 ksp->nmax = PETSC_DECIDE; 774 775 PetscCall(KSPConvergedDefaultCreate(&ctx)); 776 PetscCall(KSPSetConvergenceTest(ksp, KSPConvergedDefault, ctx, KSPConvergedDefaultDestroy)); 777 ksp->ops->buildsolution = KSPBuildSolutionDefault; 778 ksp->ops->buildresidual = KSPBuildResidualDefault; 779 780 ksp->vec_sol = NULL; 781 ksp->vec_rhs = NULL; 782 ksp->pc = NULL; 783 ksp->data = NULL; 784 ksp->nwork = 0; 785 ksp->work = NULL; 786 ksp->reason = KSP_CONVERGED_ITERATING; 787 ksp->setupstage = KSP_SETUP_NEW; 788 789 PetscCall(KSPNormSupportTableReset_Private(ksp)); 790 791 *inksp = ksp; 792 PetscFunctionReturn(PETSC_SUCCESS); 793 } 794 795 /*@ 796 KSPSetType - Sets the algorithm/method to be used to solve the linear system with the given `KSP` 797 798 Logically Collective 799 800 Input Parameters: 801 + ksp - the Krylov space context 802 - type - a known method 803 804 Options Database Key: 805 . -ksp_type <method> - Sets the method; see `KSPType` or use `-help` for a list of available methods (for instance, cg or gmres) 806 807 Level: intermediate 808 809 Notes: 810 See `KSPType` for available methods (for instance, `KSPCG` or `KSPGMRES`). 811 812 Normally, it is best to use the `KSPSetFromOptions()` command and 813 then set the `KSP` type from the options database rather than by using 814 this routine. Using the options database provides the user with 815 maximum flexibility in evaluating the many different Krylov methods. 816 The `KSPSetType()` routine is provided for those situations where it 817 is necessary to set the iterative solver independently of the command 818 line or options database. This might be the case, for example, when 819 the choice of iterative solver changes during the execution of the 820 program, and the user's application is taking responsibility for 821 choosing the appropriate method. In other words, this routine is 822 not for beginners. 823 824 Developer Note: 825 `KSPRegister()` is used to add Krylov types to `KSPList` from which they are accessed by `KSPSetType()`. 826 827 .seealso: [](ch_ksp), `PCSetType()`, `KSPType`, `KSPRegister()`, `KSPCreate()`, `KSP` 828 @*/ 829 PetscErrorCode KSPSetType(KSP ksp, KSPType type) 830 { 831 PetscBool match; 832 PetscErrorCode (*r)(KSP); 833 834 PetscFunctionBegin; 835 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 836 PetscAssertPointer(type, 2); 837 838 PetscCall(PetscObjectTypeCompare((PetscObject)ksp, type, &match)); 839 if (match) PetscFunctionReturn(PETSC_SUCCESS); 840 841 PetscCall(PetscFunctionListFind(KSPList, type, &r)); 842 PetscCheck(r, PetscObjectComm((PetscObject)ksp), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unable to find requested KSP type %s", type); 843 /* Destroy the previous private KSP context */ 844 PetscTryTypeMethod(ksp, destroy); 845 846 /* Reinitialize function pointers in KSPOps structure */ 847 PetscCall(PetscMemzero(ksp->ops, sizeof(struct _KSPOps))); 848 ksp->ops->buildsolution = KSPBuildSolutionDefault; 849 ksp->ops->buildresidual = KSPBuildResidualDefault; 850 PetscCall(KSPNormSupportTableReset_Private(ksp)); 851 ksp->converged_neg_curve = PETSC_FALSE; // restore default 852 ksp->setupnewmatrix = PETSC_FALSE; // restore default (setup not called in case of new matrix) 853 /* Call the KSPCreate_XXX routine for this particular Krylov solver */ 854 ksp->setupstage = KSP_SETUP_NEW; 855 ksp->guess_not_read = PETSC_FALSE; // restore default 856 PetscCall((*r)(ksp)); 857 PetscCall(PetscObjectChangeTypeName((PetscObject)ksp, type)); 858 PetscFunctionReturn(PETSC_SUCCESS); 859 } 860 861 /*@ 862 KSPGetType - Gets the `KSP` type as a string from the `KSP` object. 863 864 Not Collective 865 866 Input Parameter: 867 . ksp - Krylov context 868 869 Output Parameter: 870 . type - name of the `KSP` method 871 872 Level: intermediate 873 874 .seealso: [](ch_ksp), `KSPType`, `KSP`, `KSPSetType()` 875 @*/ 876 PetscErrorCode KSPGetType(KSP ksp, KSPType *type) 877 { 878 PetscFunctionBegin; 879 PetscValidHeaderSpecific(ksp, KSP_CLASSID, 1); 880 PetscAssertPointer(type, 2); 881 *type = ((PetscObject)ksp)->type_name; 882 PetscFunctionReturn(PETSC_SUCCESS); 883 } 884 885 /*@C 886 KSPRegister - Adds a method, `KSPType`, to the Krylov subspace solver package. 887 888 Not Collective, No Fortran Support 889 890 Input Parameters: 891 + sname - name of a new user-defined solver 892 - function - routine to create method 893 894 Level: advanced 895 896 Note: 897 `KSPRegister()` may be called multiple times to add several user-defined solvers. 898 899 Example Usage: 900 .vb 901 KSPRegister("my_solver", MySolverCreate); 902 .ve 903 904 Then, your solver can be chosen with the procedural interface via 905 .vb 906 KSPSetType(ksp, "my_solver") 907 .ve 908 or at runtime via the option `-ksp_type my_solver` 909 910 .seealso: [](ch_ksp), `KSP`, `KSPType`, `KSPSetType`, `KSPRegisterAll()` 911 @*/ 912 PetscErrorCode KSPRegister(const char sname[], PetscErrorCode (*function)(KSP)) 913 { 914 PetscFunctionBegin; 915 PetscCall(KSPInitializePackage()); 916 PetscCall(PetscFunctionListAdd(&KSPList, sname, function)); 917 PetscFunctionReturn(PETSC_SUCCESS); 918 } 919 920 PetscErrorCode KSPMonitorMakeKey_Internal(const char name[], PetscViewerType vtype, PetscViewerFormat format, char key[]) 921 { 922 PetscFunctionBegin; 923 PetscCall(PetscStrncpy(key, name, PETSC_MAX_PATH_LEN)); 924 PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN)); 925 PetscCall(PetscStrlcat(key, vtype, PETSC_MAX_PATH_LEN)); 926 PetscCall(PetscStrlcat(key, ":", PETSC_MAX_PATH_LEN)); 927 PetscCall(PetscStrlcat(key, PetscViewerFormats[format], PETSC_MAX_PATH_LEN)); 928 PetscFunctionReturn(PETSC_SUCCESS); 929 } 930 931 /*@C 932 KSPMonitorRegister - Registers a Krylov subspace solver monitor routine that may be accessed with `KSPMonitorSetFromOptions()` 933 934 Not Collective 935 936 Input Parameters: 937 + name - name of a new monitor type 938 . vtype - A `PetscViewerType` for the output 939 . format - A `PetscViewerFormat` for the output 940 . monitor - Monitor routine, see `KSPMonitorRegisterFn` 941 . create - Creation routine, or `NULL` 942 - destroy - Destruction routine, or `NULL` 943 944 Level: advanced 945 946 Notes: 947 `KSPMonitorRegister()` may be called multiple times to add several user-defined monitors. 948 949 The calling sequence for the given function matches the calling sequence used by `KSPMonitorFn` functions passed to `KSPMonitorSet()` with the additional 950 requirement that its final argument be a `PetscViewerAndFormat`. 951 952 Example Usage: 953 .vb 954 KSPMonitorRegister("my_monitor", PETSCVIEWERASCII, PETSC_VIEWER_ASCII_INFO_DETAIL, MyMonitor, NULL, NULL); 955 .ve 956 957 Then, your monitor can be chosen with the procedural interface via 958 .vb 959 KSPMonitorSetFromOptions(ksp, "-ksp_monitor_my_monitor", "my_monitor", NULL) 960 .ve 961 or at runtime via the option `-ksp_monitor_my_monitor` 962 963 .seealso: [](ch_ksp), `KSP`, `KSPMonitorSet()`, `KSPMonitorRegisterAll()`, `KSPMonitorSetFromOptions()` 964 @*/ 965 PetscErrorCode KSPMonitorRegister(const char name[], PetscViewerType vtype, PetscViewerFormat format, KSPMonitorRegisterFn *monitor, KSPMonitorRegisterCreateFn *create, KSPMonitorRegisterDestroyFn *destroy) 966 { 967 char key[PETSC_MAX_PATH_LEN]; 968 969 PetscFunctionBegin; 970 PetscCall(KSPInitializePackage()); 971 PetscCall(KSPMonitorMakeKey_Internal(name, vtype, format, key)); 972 PetscCall(PetscFunctionListAdd(&KSPMonitorList, key, monitor)); 973 if (create) PetscCall(PetscFunctionListAdd(&KSPMonitorCreateList, key, create)); 974 if (destroy) PetscCall(PetscFunctionListAdd(&KSPMonitorDestroyList, key, destroy)); 975 PetscFunctionReturn(PETSC_SUCCESS); 976 } 977