1 // Copyright (c) 2017, Lawrence Livermore National Security, LLC. Produced at 2 // the Lawrence Livermore National Laboratory. LLNL-CODE-734707. All Rights 3 // reserved. See files LICENSE and NOTICE for details. 4 // 5 // This file is part of CEED, a collection of benchmarks, miniapps, software 6 // libraries and APIs for efficient high-order finite element and spectral 7 // element discretizations for exascale applications. For more information and 8 // source code availability see http://github.com/ceed. 9 // 10 // The CEED research is supported by the Exascale Computing Project 17-SC-20-SC, 11 // a collaborative effort of two U.S. Department of Energy organizations (Office 12 // of Science and the National Nuclear Security Administration) responsible for 13 // the planning and preparation of a capable exascale ecosystem, including 14 // software, applications, hardware, advanced system engineering and early 15 // testbed platforms, in support of the nation's exascale computing imperative. 16 17 // libCEED + PETSc Example: CEED BPs 3-6 with Multigrid 18 // 19 // This example demonstrates a simple usage of libCEED with PETSc to solve the 20 // CEED BP benchmark problems, see http://ceed.exascaleproject.org/bps. 21 // 22 // The code uses higher level communication protocols in DMPlex. 23 // 24 // Build with: 25 // 26 // make multigrid [PETSC_DIR=</path/to/petsc>] [CEED_DIR=</path/to/libceed>] 27 // 28 // Sample runs: 29 // 30 // multigrid -problem bp3 31 // multigrid -problem bp4 -ceed /cpu/self 32 // multigrid -problem bp5 -ceed /cpu/occa 33 // multigrid -problem bp6 -ceed /gpu/cuda 34 // 35 //TESTARGS -ceed {ceed_resource} -test -problem bp3 -degree 3 36 37 /// @file 38 /// CEED BPs 1-6 multigrid example using PETSc 39 const char help[] = "Solve CEED BPs using p-multigrid with PETSc and DMPlex\n"; 40 41 #define multigrid 42 #include "setup.h" 43 44 int main(int argc, char **argv) { 45 PetscInt ierr; 46 MPI_Comm comm; 47 char filename[PETSC_MAX_PATH_LEN], 48 ceedresource[PETSC_MAX_PATH_LEN] = "/cpu/self"; 49 double my_rt_start, my_rt, rt_min, rt_max; 50 PetscInt degree = 3, qextra, *lsize, *xlsize, *gsize, dim = 3, 51 melem[3] = {3, 3, 3}, ncompu = 1, numlevels = degree, *leveldegrees; 52 PetscScalar *r; 53 PetscBool test_mode, benchmark_mode, read_mesh, write_solution; 54 DM *dm, dmOrig; 55 SNES snes_dummy; 56 KSP ksp; 57 PC pc; 58 Mat *matO, *matI, *matR, matCoarse; 59 Vec *X, *Xloc, *mult, rhs, rhsloc; 60 UserO *userO; 61 UserIR *userI, *userR; 62 Ceed ceed; 63 CeedData *ceeddata; 64 CeedVector rhsceed, target; 65 CeedQFunction qf_error, qf_restrict, qf_prolong; 66 CeedOperator op_error; 67 bpType bpChoice; 68 coarsenType coarsen; 69 70 ierr = PetscInitialize(&argc, &argv, NULL, help); 71 if (ierr) return ierr; 72 comm = PETSC_COMM_WORLD; 73 74 // Parse command line options 75 ierr = PetscOptionsBegin(comm, NULL, "CEED BPs in PETSc", NULL); CHKERRQ(ierr); 76 bpChoice = CEED_BP3; 77 ierr = PetscOptionsEnum("-problem", 78 "CEED benchmark problem to solve", NULL, 79 bpTypes, (PetscEnum)bpChoice, (PetscEnum *)&bpChoice, 80 NULL); CHKERRQ(ierr); 81 ncompu = bpOptions[bpChoice].ncompu; 82 test_mode = PETSC_FALSE; 83 ierr = PetscOptionsBool("-test", 84 "Testing mode (do not print unless error is large)", 85 NULL, test_mode, &test_mode, NULL); CHKERRQ(ierr); 86 benchmark_mode = PETSC_FALSE; 87 ierr = PetscOptionsBool("-benchmark", 88 "Benchmarking mode (prints benchmark statistics)", 89 NULL, benchmark_mode, &benchmark_mode, NULL); 90 CHKERRQ(ierr); 91 write_solution = PETSC_FALSE; 92 ierr = PetscOptionsBool("-write_solution", 93 "Write solution for visualization", 94 NULL, write_solution, &write_solution, NULL); 95 CHKERRQ(ierr); 96 degree = test_mode ? 3 : 2; 97 ierr = PetscOptionsInt("-degree", "Polynomial degree of tensor product basis", 98 NULL, degree, °ree, NULL); CHKERRQ(ierr); 99 if (degree < 1) SETERRQ1(PETSC_COMM_WORLD, PETSC_ERR_ARG_OUTOFRANGE, 100 "-degree %D must be at least 1", degree); 101 qextra = bpOptions[bpChoice].qextra; 102 ierr = PetscOptionsInt("-qextra", "Number of extra quadrature points", 103 NULL, qextra, &qextra, NULL); CHKERRQ(ierr); 104 ierr = PetscOptionsString("-ceed", "CEED resource specifier", 105 NULL, ceedresource, ceedresource, 106 sizeof(ceedresource), NULL); CHKERRQ(ierr); 107 coarsen = COARSEN_UNIFORM; 108 ierr = PetscOptionsEnum("-coarsen", 109 "Coarsening strategy to use", NULL, 110 coarsenTypes, (PetscEnum)coarsen, 111 (PetscEnum *)&coarsen, NULL); CHKERRQ(ierr); 112 read_mesh = PETSC_FALSE; 113 ierr = PetscOptionsString("-mesh", "Read mesh from file", NULL, 114 filename, filename, sizeof(filename), &read_mesh); 115 CHKERRQ(ierr); 116 if (!read_mesh) { 117 PetscInt tmp = dim; 118 ierr = PetscOptionsIntArray("-cells","Number of cells per dimension", NULL, 119 melem, &tmp, NULL); CHKERRQ(ierr); 120 } 121 ierr = PetscOptionsEnd(); CHKERRQ(ierr); 122 123 // Setup DM 124 if (read_mesh) { 125 ierr = DMPlexCreateFromFile(PETSC_COMM_WORLD, filename, PETSC_TRUE, &dmOrig); 126 CHKERRQ(ierr); 127 } else { 128 ierr = DMPlexCreateBoxMesh(PETSC_COMM_WORLD, dim, PETSC_FALSE, melem, NULL, 129 NULL, NULL, PETSC_TRUE,&dmOrig); CHKERRQ(ierr); 130 } 131 132 { 133 DM dmDist = NULL; 134 PetscPartitioner part; 135 136 ierr = DMPlexGetPartitioner(dmOrig, &part); CHKERRQ(ierr); 137 ierr = PetscPartitionerSetFromOptions(part); CHKERRQ(ierr); 138 ierr = DMPlexDistribute(dmOrig, 0, NULL, &dmDist); CHKERRQ(ierr); 139 if (dmDist) { 140 ierr = DMDestroy(&dmOrig); CHKERRQ(ierr); 141 dmOrig = dmDist; 142 } 143 } 144 145 // Allocate arrays for PETSc objects for each level 146 switch (coarsen) { 147 case COARSEN_UNIFORM: 148 numlevels = degree; 149 break; 150 case COARSEN_LOGARITHMIC: 151 numlevels = ceil(log(degree)/log(2)) + 1; 152 break; 153 } 154 ierr = PetscMalloc1(numlevels, &leveldegrees); CHKERRQ(ierr); 155 switch (coarsen) { 156 case COARSEN_UNIFORM: 157 for (int i=0; i<numlevels; i++) leveldegrees[i] = i + 1; 158 break; 159 case COARSEN_LOGARITHMIC: 160 for (int i=0; i<numlevels-1; i++) leveldegrees[i] = pow(2,i); 161 leveldegrees[numlevels-1] = degree; 162 break; 163 } 164 ierr = PetscMalloc1(numlevels, &dm); CHKERRQ(ierr); 165 ierr = PetscMalloc1(numlevels, &X); CHKERRQ(ierr); 166 ierr = PetscMalloc1(numlevels, &Xloc); CHKERRQ(ierr); 167 ierr = PetscMalloc1(numlevels, &mult); CHKERRQ(ierr); 168 ierr = PetscMalloc1(numlevels, &userO); CHKERRQ(ierr); 169 ierr = PetscMalloc1(numlevels, &userI); CHKERRQ(ierr); 170 ierr = PetscMalloc1(numlevels, &userR); CHKERRQ(ierr); 171 ierr = PetscMalloc1(numlevels, &matO); CHKERRQ(ierr); 172 ierr = PetscMalloc1(numlevels, &matI); CHKERRQ(ierr); 173 ierr = PetscMalloc1(numlevels, &matR); CHKERRQ(ierr); 174 ierr = PetscMalloc1(numlevels, &lsize); CHKERRQ(ierr); 175 ierr = PetscMalloc1(numlevels, &xlsize); CHKERRQ(ierr); 176 ierr = PetscMalloc1(numlevels, &gsize); CHKERRQ(ierr); 177 178 // Setup DM and Operator Mat Shells for each level 179 for (CeedInt i=0; i<numlevels; i++) { 180 // Create DM 181 ierr = DMClone(dmOrig, &dm[i]); CHKERRQ(ierr); 182 ierr = SetupDMByDegree(dm[i], leveldegrees[i], ncompu, bpChoice); 183 CHKERRQ(ierr); 184 185 // Create vectors 186 ierr = DMCreateGlobalVector(dm[i], &X[i]); CHKERRQ(ierr); 187 ierr = VecGetLocalSize(X[i], &lsize[i]); CHKERRQ(ierr); 188 ierr = VecGetSize(X[i], &gsize[i]); CHKERRQ(ierr); 189 ierr = DMCreateLocalVector(dm[i], &Xloc[i]); CHKERRQ(ierr); 190 ierr = VecGetSize(Xloc[i], &xlsize[i]); CHKERRQ(ierr); 191 192 // Operator 193 ierr = PetscMalloc1(1, &userO[i]); CHKERRQ(ierr); 194 ierr = MatCreateShell(comm, lsize[i], lsize[i], gsize[i], gsize[i], 195 userO[i], &matO[i]); CHKERRQ(ierr); 196 ierr = MatShellSetOperation(matO[i], MATOP_MULT, 197 (void(*)(void))MatMult_Ceed); 198 ierr = MatShellSetOperation(matO[i], MATOP_GET_DIAGONAL, 199 (void(*)(void))MatGetDiag); 200 CHKERRQ(ierr); 201 202 // Level transfers 203 if (i > 0) { 204 // Interp 205 ierr = PetscMalloc1(1, &userI[i]); CHKERRQ(ierr); 206 ierr = MatCreateShell(comm, lsize[i], lsize[i-1], gsize[i], gsize[i-1], 207 userI[i], &matI[i]); CHKERRQ(ierr); 208 ierr = MatShellSetOperation(matI[i], MATOP_MULT, 209 (void(*)(void))MatMult_Interp); 210 CHKERRQ(ierr); 211 212 // Restrict 213 ierr = PetscMalloc1(1, &userR[i]); CHKERRQ(ierr); 214 ierr = MatCreateShell(comm, lsize[i-1], lsize[i], gsize[i-1], gsize[i], 215 userR[i], &matR[i]); CHKERRQ(ierr); 216 ierr = MatShellSetOperation(matR[i], MATOP_MULT, 217 (void(*)(void))MatMult_Restrict); 218 CHKERRQ(ierr); 219 } 220 } 221 ierr = VecDuplicate(X[numlevels-1], &rhs); CHKERRQ(ierr); 222 223 // Set up libCEED 224 CeedInit(ceedresource, &ceed); 225 226 // Print global grid information 227 if (!test_mode) { 228 PetscInt P = degree + 1, Q = P + qextra; 229 const char *usedresource; 230 CeedGetResource(ceed, &usedresource); 231 ierr = PetscPrintf(comm, 232 "\n-- CEED Benchmark Problem %d -- libCEED + PETSc + PCMG --\n" 233 " libCEED:\n" 234 " libCEED Backend : %s\n" 235 " Mesh:\n" 236 " Number of 1D Basis Nodes (p) : %d\n" 237 " Number of 1D Quadrature Points (q) : %d\n" 238 " Global Nodes : %D\n" 239 " Owned Nodes : %D\n" 240 " DoF per node : %D\n" 241 " Multigrid:\n" 242 " Number of Levels : %d\n", 243 bpChoice+1, usedresource, P, Q, 244 gsize[numlevels-1]/ncompu, lsize[numlevels-1]/ncompu, 245 ncompu, numlevels); CHKERRQ(ierr); 246 } 247 248 // Create RHS vector 249 ierr = VecDuplicate(Xloc[numlevels-1], &rhsloc); CHKERRQ(ierr); 250 ierr = VecZeroEntries(rhsloc); CHKERRQ(ierr); 251 ierr = VecGetArray(rhsloc, &r); CHKERRQ(ierr); 252 CeedVectorCreate(ceed, xlsize[numlevels-1], &rhsceed); 253 CeedVectorSetArray(rhsceed, CEED_MEM_HOST, CEED_USE_POINTER, r); 254 255 // Set up libCEED operators on each level 256 ierr = PetscMalloc1(numlevels, &ceeddata); CHKERRQ(ierr); 257 for (int i=0; i<numlevels; i++) { 258 // Print level information 259 if (!test_mode && (i == 0 || i == numlevels-1)) { 260 ierr = PetscPrintf(comm," Level %D (%s):\n" 261 " Number of 1D Basis Nodes (p) : %d\n" 262 " Global Nodes : %D\n" 263 " Owned Nodes : %D\n", 264 i, (i? "fine" : "coarse"), leveldegrees[i] + 1, 265 gsize[i]/ncompu, lsize[i]/ncompu); CHKERRQ(ierr); 266 } 267 ierr = PetscMalloc1(1, &ceeddata[i]); CHKERRQ(ierr); 268 ierr = SetupLibceedByDegree(dm[i], ceed, leveldegrees[i], dim, qextra, 269 ncompu, gsize[i], xlsize[i], bpChoice, 270 ceeddata[i], i==(numlevels-1), rhsceed, 271 &target); CHKERRQ(ierr); 272 } 273 274 // Gather RHS 275 ierr = VecRestoreArray(rhsloc, &r); CHKERRQ(ierr); 276 ierr = VecZeroEntries(rhs); CHKERRQ(ierr); 277 ierr = DMLocalToGlobal(dm[numlevels-1], rhsloc, ADD_VALUES, rhs); 278 CHKERRQ(ierr); 279 CeedVectorDestroy(&rhsceed); 280 281 // Create the restriction/interpolation Q-function 282 CeedQFunctionCreateIdentity(ceed, ncompu, CEED_EVAL_NONE, CEED_EVAL_INTERP, 283 &qf_restrict); 284 CeedQFunctionCreateIdentity(ceed, ncompu, CEED_EVAL_INTERP, CEED_EVAL_NONE, 285 &qf_prolong); 286 287 // Set up libCEED level transfer operators 288 ierr = CeedLevelTransferSetup(ceed, numlevels, ncompu, bpChoice, ceeddata, 289 leveldegrees, qf_restrict, qf_prolong); 290 CHKERRQ(ierr); 291 292 // Create the error Q-function 293 CeedQFunctionCreateInterior(ceed, 1, bpOptions[bpChoice].error, 294 bpOptions[bpChoice].errorfname, &qf_error); 295 CeedQFunctionAddInput(qf_error, "u", ncompu, CEED_EVAL_INTERP); 296 CeedQFunctionAddInput(qf_error, "true_soln", ncompu, CEED_EVAL_NONE); 297 CeedQFunctionAddOutput(qf_error, "error", ncompu, CEED_EVAL_NONE); 298 299 // Create the error operator 300 CeedOperatorCreate(ceed, qf_error, CEED_QFUNCTION_NONE, CEED_QFUNCTION_NONE, 301 &op_error); 302 CeedOperatorSetField(op_error, "u", ceeddata[numlevels-1]->Erestrictu, 303 ceeddata[numlevels-1]->basisu, CEED_VECTOR_ACTIVE); 304 CeedOperatorSetField(op_error, "true_soln", ceeddata[numlevels-1]->Erestrictui, 305 CEED_BASIS_COLLOCATED, target); 306 CeedOperatorSetField(op_error, "error", ceeddata[numlevels-1]->Erestrictui, 307 CEED_BASIS_COLLOCATED, CEED_VECTOR_ACTIVE); 308 309 // Calculate multiplicity 310 for (int i=0; i<numlevels; i++) { 311 PetscScalar *x; 312 313 // CEED vector 314 ierr = VecGetArray(Xloc[i], &x); CHKERRQ(ierr); 315 CeedVectorSetArray(ceeddata[i]->xceed, CEED_MEM_HOST, CEED_USE_POINTER, x); 316 317 // Multiplicity 318 CeedElemRestrictionGetMultiplicity(ceeddata[i]->Erestrictu, 319 ceeddata[i]->xceed); 320 321 // Restore vector 322 ierr = VecRestoreArray(Xloc[i], &x); CHKERRQ(ierr); 323 324 // Creat mult vector 325 ierr = VecDuplicate(Xloc[i], &mult[i]); CHKERRQ(ierr); 326 327 // Local-to-global 328 ierr = VecZeroEntries(X[i]); CHKERRQ(ierr); 329 ierr = DMLocalToGlobal(dm[i], Xloc[i], ADD_VALUES, X[i]); 330 CHKERRQ(ierr); 331 ierr = VecZeroEntries(Xloc[i]); CHKERRQ(ierr); 332 333 // Global-to-local 334 ierr = DMGlobalToLocal(dm[i], X[i], INSERT_VALUES, mult[i]); 335 CHKERRQ(ierr); 336 ierr = VecZeroEntries(X[i]); CHKERRQ(ierr); 337 338 // Multiplicity scaling 339 ierr = VecReciprocal(mult[i]); 340 } 341 342 // Set up Mat 343 for (int i=0; i<numlevels; i++) { 344 // User Operator 345 userO[i]->comm = comm; 346 userO[i]->dm = dm[i]; 347 userO[i]->Xloc = Xloc[i]; 348 ierr = VecDuplicate(Xloc[i], &userO[i]->Yloc); CHKERRQ(ierr); 349 userO[i]->xceed = ceeddata[i]->xceed; 350 userO[i]->yceed = ceeddata[i]->yceed; 351 userO[i]->op = ceeddata[i]->op_apply; 352 userO[i]->ceed = ceed; 353 354 if (i > 0) { 355 // Interp Operator 356 userI[i]->comm = comm; 357 userI[i]->dmc = dm[i-1]; 358 userI[i]->dmf = dm[i]; 359 userI[i]->Xloc = Xloc[i-1]; 360 userI[i]->Yloc = userO[i]->Yloc; 361 userI[i]->mult = mult[i]; 362 userI[i]->ceedvecc = userO[i-1]->xceed; 363 userI[i]->ceedvecf = userO[i]->yceed; 364 userI[i]->op = ceeddata[i]->op_interp; 365 userI[i]->ceed = ceed; 366 367 // Restrict Operator 368 userR[i]->comm = comm; 369 userR[i]->dmc = dm[i-1]; 370 userR[i]->dmf = dm[i]; 371 userR[i]->Xloc = Xloc[i]; 372 userR[i]->Yloc = userO[i-1]->Yloc; 373 userR[i]->mult = mult[i]; 374 userR[i]->ceedvecf = userO[i]->xceed; 375 userR[i]->ceedvecc = userO[i-1]->yceed; 376 userR[i]->op = ceeddata[i]->op_restrict; 377 userR[i]->ceed = ceed; 378 } 379 } 380 381 // Setup dummy SNES for AMG coarse solve 382 ierr = SNESCreate(comm, &snes_dummy); CHKERRQ(ierr); 383 ierr = SNESSetDM(snes_dummy, dm[0]); CHKERRQ(ierr); 384 ierr = SNESSetSolution(snes_dummy, X[0]); CHKERRQ(ierr); 385 386 // -- Jacobian matrix 387 ierr = DMSetMatType(dm[0], MATAIJ); CHKERRQ(ierr); 388 ierr = DMCreateMatrix(dm[0], &matCoarse); CHKERRQ(ierr); 389 ierr = SNESSetJacobian(snes_dummy, matCoarse, matCoarse, NULL, 390 NULL); CHKERRQ(ierr); 391 392 // -- Residual evaluation function 393 ierr = SNESSetFunction(snes_dummy, X[0], FormResidual_Ceed, 394 userO[0]); CHKERRQ(ierr); 395 396 // -- Form Jacobian 397 ierr = SNESComputeJacobianDefaultColor(snes_dummy, X[0], matO[0], 398 matCoarse, NULL); CHKERRQ(ierr); 399 400 // Set up KSP 401 ierr = KSPCreate(comm, &ksp); CHKERRQ(ierr); 402 { 403 ierr = KSPSetType(ksp, KSPCG); CHKERRQ(ierr); 404 ierr = KSPSetNormType(ksp, KSP_NORM_NATURAL); CHKERRQ(ierr); 405 ierr = KSPSetTolerances(ksp, 1e-10, PETSC_DEFAULT, PETSC_DEFAULT, 406 PETSC_DEFAULT); CHKERRQ(ierr); 407 } 408 ierr = KSPSetFromOptions(ksp); CHKERRQ(ierr); 409 ierr = KSPSetOperators(ksp, matO[numlevels-1], matO[numlevels-1]); 410 CHKERRQ(ierr); 411 412 // Set up PCMG 413 ierr = KSPGetPC(ksp, &pc); CHKERRQ(ierr); 414 PCMGCycleType pcgmcycletype = PC_MG_CYCLE_V; 415 { 416 ierr = PCSetType(pc, PCMG); CHKERRQ(ierr); 417 418 // PCMG levels 419 ierr = PCMGSetLevels(pc, numlevels, NULL); CHKERRQ(ierr); 420 for (int i=0; i<numlevels; i++) { 421 // Smoother 422 KSP smoother; 423 PC smoother_pc; 424 ierr = PCMGGetSmoother(pc, i, &smoother); CHKERRQ(ierr); 425 ierr = KSPSetType(smoother, KSPCHEBYSHEV); CHKERRQ(ierr); 426 ierr = KSPChebyshevEstEigSet(smoother, 0, 0.1, 0, 1.1); CHKERRQ(ierr); 427 ierr = KSPChebyshevEstEigSetUseNoisy(smoother, PETSC_TRUE); CHKERRQ(ierr); 428 ierr = KSPSetOperators(smoother, matO[i], matO[i]); CHKERRQ(ierr); 429 ierr = KSPGetPC(smoother, &smoother_pc); CHKERRQ(ierr); 430 ierr = PCSetType(smoother_pc, PCJACOBI); CHKERRQ(ierr); 431 ierr = PCJacobiSetType(smoother_pc, PC_JACOBI_DIAGONAL); CHKERRQ(ierr); 432 433 // Work vector 434 if (i < numlevels-1) { 435 ierr = PCMGSetX(pc, i, X[i]); CHKERRQ(ierr); 436 } 437 438 // Level transfers 439 if (i > 0) { 440 // Interpolation 441 ierr = PCMGSetInterpolation(pc, i, matI[i]); CHKERRQ(ierr); 442 443 // Restriction 444 ierr = PCMGSetRestriction(pc, i, matR[i]); CHKERRQ(ierr); 445 } 446 447 // Coarse solve 448 KSP coarse; 449 PC coarse_pc; 450 ierr = PCMGGetCoarseSolve(pc, &coarse); CHKERRQ(ierr); 451 ierr = KSPSetType(coarse, KSPPREONLY); CHKERRQ(ierr); 452 ierr = KSPSetOperators(coarse, matCoarse, matCoarse); CHKERRQ(ierr); 453 454 ierr = KSPGetPC(coarse, &coarse_pc); CHKERRQ(ierr); 455 ierr = PCSetType(coarse_pc, PCGAMG); CHKERRQ(ierr); 456 457 ierr = KSPSetOptionsPrefix(coarse, "coarse_"); CHKERRQ(ierr); 458 ierr = PCSetOptionsPrefix(coarse_pc, "coarse_"); CHKERRQ(ierr); 459 ierr = KSPSetFromOptions(coarse); CHKERRQ(ierr); 460 ierr = PCSetFromOptions(coarse_pc); CHKERRQ(ierr); 461 } 462 463 // PCMG options 464 ierr = PCMGSetType(pc, PC_MG_MULTIPLICATIVE); CHKERRQ(ierr); 465 ierr = PCMGSetNumberSmooth(pc, 3); CHKERRQ(ierr); 466 ierr = PCMGSetCycleType(pc, pcgmcycletype); CHKERRQ(ierr); 467 } 468 469 // First run, if benchmarking 470 if (benchmark_mode) { 471 ierr = KSPSetTolerances(ksp, 1e-10, PETSC_DEFAULT, PETSC_DEFAULT, 1); 472 CHKERRQ(ierr); 473 ierr = VecZeroEntries(X[numlevels-1]); CHKERRQ(ierr); 474 my_rt_start = MPI_Wtime(); 475 ierr = KSPSolve(ksp, rhs, X[numlevels-1]); CHKERRQ(ierr); 476 my_rt = MPI_Wtime() - my_rt_start; 477 ierr = MPI_Allreduce(MPI_IN_PLACE, &my_rt, 1, MPI_DOUBLE, MPI_MIN, comm); 478 CHKERRQ(ierr); 479 // Set maxits based on first iteration timing 480 if (my_rt > 0.02) { 481 ierr = KSPSetTolerances(ksp, 1e-10, PETSC_DEFAULT, PETSC_DEFAULT, 5); 482 CHKERRQ(ierr); 483 } else { 484 ierr = KSPSetTolerances(ksp, 1e-10, PETSC_DEFAULT, PETSC_DEFAULT, 20); 485 CHKERRQ(ierr); 486 } 487 } 488 489 // Timed solve 490 ierr = VecZeroEntries(X[numlevels-1]); CHKERRQ(ierr); 491 ierr = PetscBarrier((PetscObject)ksp); CHKERRQ(ierr); 492 my_rt_start = MPI_Wtime(); 493 ierr = KSPSolve(ksp, rhs, X[numlevels-1]); CHKERRQ(ierr); 494 my_rt = MPI_Wtime() - my_rt_start; 495 496 // Output results 497 { 498 KSPType ksptype; 499 PCMGType pcmgtype; 500 KSPConvergedReason reason; 501 PetscReal rnorm; 502 PetscInt its; 503 ierr = KSPGetType(ksp, &ksptype); CHKERRQ(ierr); 504 ierr = KSPGetConvergedReason(ksp, &reason); CHKERRQ(ierr); 505 ierr = KSPGetIterationNumber(ksp, &its); CHKERRQ(ierr); 506 ierr = KSPGetResidualNorm(ksp, &rnorm); CHKERRQ(ierr); 507 ierr = PCMGGetType(pc, &pcmgtype); CHKERRQ(ierr); 508 if (!test_mode || reason < 0 || rnorm > 1e-8) { 509 ierr = PetscPrintf(comm, 510 " KSP:\n" 511 " KSP Type : %s\n" 512 " KSP Convergence : %s\n" 513 " Total KSP Iterations : %D\n" 514 " Final rnorm : %e\n", 515 ksptype, KSPConvergedReasons[reason], its, 516 (double)rnorm); CHKERRQ(ierr); 517 ierr = PetscPrintf(comm, 518 " PCMG:\n" 519 " PCMG Type : %s\n" 520 " PCMG Cycle Type : %s\n", 521 PCMGTypes[pcmgtype], 522 PCMGCycleTypes[pcgmcycletype]); CHKERRQ(ierr); 523 } 524 if (!test_mode) { 525 ierr = PetscPrintf(comm," Performance:\n"); CHKERRQ(ierr); 526 } 527 { 528 PetscReal maxerror; 529 ierr = ComputeErrorMax(userO[numlevels-1], op_error, X[numlevels-1], target, 530 &maxerror); CHKERRQ(ierr); 531 PetscReal tol = 5e-2; 532 if (!test_mode || maxerror > tol) { 533 ierr = MPI_Allreduce(&my_rt, &rt_min, 1, MPI_DOUBLE, MPI_MIN, comm); 534 CHKERRQ(ierr); 535 ierr = MPI_Allreduce(&my_rt, &rt_max, 1, MPI_DOUBLE, MPI_MAX, comm); 536 CHKERRQ(ierr); 537 ierr = PetscPrintf(comm, 538 " Pointwise Error (max) : %e\n" 539 " CG Solve Time : %g (%g) sec\n", 540 (double)maxerror, rt_max, rt_min); CHKERRQ(ierr); 541 } 542 } 543 if (benchmark_mode && (!test_mode)) { 544 ierr = PetscPrintf(comm, 545 " DoFs/Sec in CG : %g (%g) million\n", 546 1e-6*gsize[numlevels-1]*its/rt_max, 547 1e-6*gsize[numlevels-1]*its/rt_min); 548 CHKERRQ(ierr); 549 } 550 } 551 552 if (write_solution) { 553 PetscViewer vtkviewersoln; 554 555 ierr = PetscViewerCreate(comm, &vtkviewersoln); CHKERRQ(ierr); 556 ierr = PetscViewerSetType(vtkviewersoln, PETSCVIEWERVTK); CHKERRQ(ierr); 557 ierr = PetscViewerFileSetName(vtkviewersoln, "solution.vtk"); CHKERRQ(ierr); 558 ierr = VecView(X[numlevels-1], vtkviewersoln); CHKERRQ(ierr); 559 ierr = PetscViewerDestroy(&vtkviewersoln); CHKERRQ(ierr); 560 } 561 562 // Cleanup 563 for (int i=0; i<numlevels; i++) { 564 ierr = VecDestroy(&X[i]); CHKERRQ(ierr); 565 ierr = VecDestroy(&Xloc[i]); CHKERRQ(ierr); 566 ierr = VecDestroy(&mult[i]); CHKERRQ(ierr); 567 ierr = VecDestroy(&userO[i]->Yloc); CHKERRQ(ierr); 568 ierr = MatDestroy(&matO[i]); CHKERRQ(ierr); 569 ierr = PetscFree(userO[i]); CHKERRQ(ierr); 570 if (i > 0) { 571 ierr = MatDestroy(&matI[i]); CHKERRQ(ierr); 572 ierr = PetscFree(userI[i]); CHKERRQ(ierr); 573 ierr = MatDestroy(&matR[i]); CHKERRQ(ierr); 574 ierr = PetscFree(userR[i]); CHKERRQ(ierr); 575 } 576 ierr = CeedDataDestroy(i, ceeddata[i]); CHKERRQ(ierr); 577 ierr = DMDestroy(&dm[i]); CHKERRQ(ierr); 578 } 579 ierr = PetscFree(leveldegrees); CHKERRQ(ierr); 580 ierr = PetscFree(dm); CHKERRQ(ierr); 581 ierr = PetscFree(X); CHKERRQ(ierr); 582 ierr = PetscFree(Xloc); CHKERRQ(ierr); 583 ierr = PetscFree(mult); CHKERRQ(ierr); 584 ierr = PetscFree(matO); CHKERRQ(ierr); 585 ierr = PetscFree(matI); CHKERRQ(ierr); 586 ierr = PetscFree(matR); CHKERRQ(ierr); 587 ierr = PetscFree(ceeddata); CHKERRQ(ierr); 588 ierr = PetscFree(userO); CHKERRQ(ierr); 589 ierr = PetscFree(userI); CHKERRQ(ierr); 590 ierr = PetscFree(userR); CHKERRQ(ierr); 591 ierr = PetscFree(lsize); CHKERRQ(ierr); 592 ierr = PetscFree(xlsize); CHKERRQ(ierr); 593 ierr = PetscFree(gsize); CHKERRQ(ierr); 594 ierr = VecDestroy(&rhs); CHKERRQ(ierr); 595 ierr = VecDestroy(&rhsloc); CHKERRQ(ierr); 596 ierr = MatDestroy(&matCoarse); CHKERRQ(ierr); 597 ierr = KSPDestroy(&ksp); CHKERRQ(ierr); 598 ierr = SNESDestroy(&snes_dummy); CHKERRQ(ierr); 599 ierr = DMDestroy(&dmOrig); CHKERRQ(ierr); 600 CeedVectorDestroy(&target); 601 CeedQFunctionDestroy(&qf_error); 602 CeedQFunctionDestroy(&qf_restrict); 603 CeedQFunctionDestroy(&qf_prolong); 604 CeedOperatorDestroy(&op_error); 605 CeedDestroy(&ceed); 606 return PetscFinalize(); 607 } 608