1 #define PETSCKSP_DLL 2 3 #include "src/ksp/pc/impls/is/nn/nn.h" 4 5 /* -------------------------------------------------------------------------- */ 6 /* 7 PCSetUp_NN - Prepares for the use of the NN preconditioner 8 by setting data structures and options. 9 10 Input Parameter: 11 . pc - the preconditioner context 12 13 Application Interface Routine: PCSetUp() 14 15 Notes: 16 The interface routine PCSetUp() is not usually called directly by 17 the user, but instead is called by PCApply() if necessary. 18 */ 19 #undef __FUNCT__ 20 #define __FUNCT__ "PCSetUp_NN" 21 static PetscErrorCode PCSetUp_NN(PC pc) 22 { 23 PetscErrorCode ierr; 24 25 PetscFunctionBegin; 26 if (!pc->setupcalled) { 27 /* Set up all the "iterative substructuring" common block */ 28 ierr = PCISSetUp(pc);CHKERRQ(ierr); 29 /* Create the coarse matrix. */ 30 ierr = PCNNCreateCoarseMatrix(pc);CHKERRQ(ierr); 31 } 32 PetscFunctionReturn(0); 33 } 34 35 /* -------------------------------------------------------------------------- */ 36 /* 37 PCApply_NN - Applies the NN preconditioner to a vector. 38 39 Input Parameters: 40 . pc - the preconditioner context 41 . r - input vector (global) 42 43 Output Parameter: 44 . z - output vector (global) 45 46 Application Interface Routine: PCApply() 47 */ 48 #undef __FUNCT__ 49 #define __FUNCT__ "PCApply_NN" 50 static PetscErrorCode PCApply_NN(PC pc,Vec r,Vec z) 51 { 52 PC_IS *pcis = (PC_IS*)(pc->data); 53 PetscErrorCode ierr; 54 PetscScalar m_one = -1.0; 55 Vec w = pcis->vec1_global; 56 57 PetscFunctionBegin; 58 /* 59 Dirichlet solvers. 60 Solving $ B_I^{(i)}r_I^{(i)} $ at each processor. 61 Storing the local results at vec2_D 62 */ 63 ierr = VecScatterBegin(r,pcis->vec1_D,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_D);CHKERRQ(ierr); 64 ierr = VecScatterEnd (r,pcis->vec1_D,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_D);CHKERRQ(ierr); 65 ierr = KSPSolve(pcis->ksp_D,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 66 67 /* 68 Computing $ r_B - \sum_j \tilde R_j^T A_{BI}^{(j)} (B_I^{(j)}r_I^{(j)}) $ . 69 Storing the result in the interface portion of the global vector w. 70 */ 71 ierr = MatMult(pcis->A_BI,pcis->vec2_D,pcis->vec1_B);CHKERRQ(ierr); 72 ierr = VecScale(&m_one,pcis->vec1_B);CHKERRQ(ierr); 73 ierr = VecCopy(r,w);CHKERRQ(ierr); 74 ierr = VecScatterBegin(pcis->vec1_B,w,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 75 ierr = VecScatterEnd (pcis->vec1_B,w,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 76 77 /* 78 Apply the interface preconditioner 79 */ 80 ierr = PCNNApplyInterfacePreconditioner(pc,w,z,pcis->work_N,pcis->vec1_B,pcis->vec2_B,pcis->vec3_B,pcis->vec1_D, 81 pcis->vec3_D,pcis->vec1_N,pcis->vec2_N);CHKERRQ(ierr); 82 83 /* 84 Computing $ t_I^{(i)} = A_{IB}^{(i)} \tilde R_i z_B $ 85 The result is stored in vec1_D. 86 */ 87 ierr = VecScatterBegin(z,pcis->vec1_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 88 ierr = VecScatterEnd (z,pcis->vec1_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 89 ierr = MatMult(pcis->A_IB,pcis->vec1_B,pcis->vec1_D);CHKERRQ(ierr); 90 91 /* 92 Dirichlet solvers. 93 Computing $ B_I^{(i)}t_I^{(i)} $ and sticking into the global vector the blocks 94 $ B_I^{(i)}r_I^{(i)} - B_I^{(i)}t_I^{(i)} $. 95 */ 96 ierr = VecScatterBegin(pcis->vec2_D,z,INSERT_VALUES,SCATTER_REVERSE,pcis->global_to_D);CHKERRQ(ierr); 97 ierr = VecScatterEnd (pcis->vec2_D,z,INSERT_VALUES,SCATTER_REVERSE,pcis->global_to_D);CHKERRQ(ierr); 98 ierr = KSPSolve(pcis->ksp_D,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 99 ierr = VecScale(&m_one,pcis->vec2_D);CHKERRQ(ierr); 100 ierr = VecScatterBegin(pcis->vec2_D,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_D);CHKERRQ(ierr); 101 ierr = VecScatterEnd (pcis->vec2_D,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_D);CHKERRQ(ierr); 102 PetscFunctionReturn(0); 103 } 104 105 /* -------------------------------------------------------------------------- */ 106 /* 107 PCDestroy_NN - Destroys the private context for the NN preconditioner 108 that was created with PCCreate_NN(). 109 110 Input Parameter: 111 . pc - the preconditioner context 112 113 Application Interface Routine: PCDestroy() 114 */ 115 #undef __FUNCT__ 116 #define __FUNCT__ "PCDestroy_NN" 117 static PetscErrorCode PCDestroy_NN(PC pc) 118 { 119 PC_NN *pcnn = (PC_NN*)pc->data; 120 PetscErrorCode ierr; 121 122 PetscFunctionBegin; 123 ierr = PCISDestroy(pc);CHKERRQ(ierr); 124 125 if (pcnn->coarse_mat) {ierr = MatDestroy(pcnn->coarse_mat);CHKERRQ(ierr);} 126 if (pcnn->coarse_x) {ierr = VecDestroy(pcnn->coarse_x);CHKERRQ(ierr);} 127 if (pcnn->coarse_b) {ierr = VecDestroy(pcnn->coarse_b);CHKERRQ(ierr);} 128 if (pcnn->ksp_coarse) {ierr = KSPDestroy(pcnn->ksp_coarse);CHKERRQ(ierr);} 129 if (pcnn->DZ_IN) { 130 if (pcnn->DZ_IN[0]) {ierr = PetscFree(pcnn->DZ_IN[0]);CHKERRQ(ierr);} 131 ierr = PetscFree(pcnn->DZ_IN);CHKERRQ(ierr); 132 } 133 134 /* 135 Free the private data structure that was hanging off the PC 136 */ 137 ierr = PetscFree(pcnn);CHKERRQ(ierr); 138 PetscFunctionReturn(0); 139 } 140 141 /* -------------------------------------------------------------------------- */ 142 /*MC 143 PCNN - Balancing Neumann-Neumann for scalar elliptic PDEs. 144 145 Options Database Keys: 146 + -pc_nn_turn_off_first_balancing - do not balance the residual before solving the local Neumann problems 147 (this skips the first coarse grid solve in the preconditioner) 148 . -pc_nn_turn_off_second_balancing - do not balance the solution solving the local Neumann problems 149 (this skips the second coarse grid solve in the preconditioner) 150 . -pc_is_damp_fixed <fact> - 151 . -pc_is_remove_nullspace_fixed - 152 . -pc_is_set_damping_factor_floating <fact> - 153 . -pc_is_not_damp_floating - 154 + -pc_is_not_remove_nullspace_floating - 155 156 Level: intermediate 157 158 Notes: The matrix used with this preconditioner must be of type MATIS 159 160 Unlike more 'conventional' Neumann-Neumann preconditioners this iterates over ALL the 161 degrees of freedom, NOT just those on the interface (this allows the use of approximate solvers 162 on the subdomains; though in our experience using approximate solvers is slower.). 163 164 Options for the coarse grid preconditioner can be set with -nn_coarse_pc_xxx 165 Options for the Dirichlet subproblem preconditioner can be set with -is_localD_pc_xxx 166 Options for the Neumann subproblem preconditioner can be set with -is_localN_pc_xxx 167 168 Contributed by Paulo Goldfeld 169 170 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, MatIS 171 M*/ 172 EXTERN_C_BEGIN 173 #undef __FUNCT__ 174 #define __FUNCT__ "PCCreate_NN" 175 PetscErrorCode PETSCKSP_DLLEXPORT PCCreate_NN(PC pc) 176 { 177 PetscErrorCode ierr; 178 PC_NN *pcnn; 179 180 PetscFunctionBegin; 181 /* 182 Creates the private data structure for this preconditioner and 183 attach it to the PC object. 184 */ 185 ierr = PetscNew(PC_NN,&pcnn);CHKERRQ(ierr); 186 pc->data = (void*)pcnn; 187 188 /* 189 Logs the memory usage; this is not needed but allows PETSc to 190 monitor how much memory is being used for various purposes. 191 */ 192 ierr = PetscLogObjectMemory(pc,sizeof(PC_NN)+sizeof(PC_IS));CHKERRQ(ierr); /* Is this the right thing to do? */ 193 194 ierr = PCISCreate(pc);CHKERRQ(ierr); 195 pcnn->coarse_mat = 0; 196 pcnn->coarse_x = 0; 197 pcnn->coarse_b = 0; 198 pcnn->ksp_coarse = 0; 199 pcnn->DZ_IN = 0; 200 201 /* 202 Set the pointers for the functions that are provided above. 203 Now when the user-level routines (such as PCApply(), PCDestroy(), etc.) 204 are called, they will automatically call these functions. Note we 205 choose not to provide a couple of these functions since they are 206 not needed. 207 */ 208 pc->ops->apply = PCApply_NN; 209 pc->ops->applytranspose = 0; 210 pc->ops->setup = PCSetUp_NN; 211 pc->ops->destroy = PCDestroy_NN; 212 pc->ops->view = 0; 213 pc->ops->applyrichardson = 0; 214 pc->ops->applysymmetricleft = 0; 215 pc->ops->applysymmetricright = 0; 216 PetscFunctionReturn(0); 217 } 218 EXTERN_C_END 219 220 221 /* -------------------------------------------------------------------------- */ 222 /* 223 PCNNCreateCoarseMatrix - 224 */ 225 #undef __FUNCT__ 226 #define __FUNCT__ "PCNNCreateCoarseMatrix" 227 PetscErrorCode PCNNCreateCoarseMatrix (PC pc) 228 { 229 MPI_Request *send_request, *recv_request; 230 PetscErrorCode ierr; 231 PetscInt i, j, k; 232 PetscScalar* mat; /* Sub-matrix with this subdomain's contribution to the coarse matrix */ 233 PetscScalar** DZ_OUT; /* proc[k].DZ_OUT[i][] = bit of vector to be sent from processor k to processor i */ 234 235 /* aliasing some names */ 236 PC_IS* pcis = (PC_IS*)(pc->data); 237 PC_NN* pcnn = (PC_NN*)pc->data; 238 PetscInt n_neigh = pcis->n_neigh; 239 PetscInt* neigh = pcis->neigh; 240 PetscInt* n_shared = pcis->n_shared; 241 PetscInt** shared = pcis->shared; 242 PetscScalar** DZ_IN; /* Must be initialized after memory allocation. */ 243 244 PetscFunctionBegin; 245 /* Allocate memory for mat (the +1 is to handle the case n_neigh equal to zero) */ 246 ierr = PetscMalloc((n_neigh*n_neigh+1)*sizeof(PetscScalar),&mat);CHKERRQ(ierr); 247 248 /* Allocate memory for DZ */ 249 /* Notice that DZ_OUT[0] is allocated some space that is never used. */ 250 /* This is just in order to DZ_OUT and DZ_IN to have exactly the same form. */ 251 { 252 PetscInt size_of_Z = 0; 253 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&pcnn->DZ_IN);CHKERRQ(ierr); 254 DZ_IN = pcnn->DZ_IN; 255 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&DZ_OUT);CHKERRQ(ierr); 256 for (i=0; i<n_neigh; i++) { 257 size_of_Z += n_shared[i]; 258 } 259 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_IN[0]);CHKERRQ(ierr); 260 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_OUT[0]);CHKERRQ(ierr); 261 } 262 for (i=1; i<n_neigh; i++) { 263 DZ_IN[i] = DZ_IN [i-1] + n_shared[i-1]; 264 DZ_OUT[i] = DZ_OUT[i-1] + n_shared[i-1]; 265 } 266 267 /* Set the values of DZ_OUT, in order to send this info to the neighbours */ 268 /* First, set the auxiliary array pcis->work_N. */ 269 ierr = PCISScatterArrayNToVecB(pcis->work_N,pcis->D,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 270 for (i=1; i<n_neigh; i++){ 271 for (j=0; j<n_shared[i]; j++) { 272 DZ_OUT[i][j] = pcis->work_N[shared[i][j]]; 273 } 274 } 275 276 /* Non-blocking send/receive the common-interface chunks of scaled nullspaces */ 277 /* Notice that send_request[] and recv_request[] could have one less element. */ 278 /* We make them longer to have request[i] corresponding to neigh[i]. */ 279 { 280 PetscMPIInt tag; 281 ierr = PetscObjectGetNewTag((PetscObject)pc,&tag);CHKERRQ(ierr); 282 ierr = PetscMalloc((2*(n_neigh)+1)*sizeof(MPI_Request),&send_request);CHKERRQ(ierr); 283 recv_request = send_request + (n_neigh); 284 for (i=1; i<n_neigh; i++) { 285 ierr = MPI_Isend((void*)(DZ_OUT[i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,pc->comm,&(send_request[i]));CHKERRQ(ierr); 286 ierr = MPI_Irecv((void*)(DZ_IN [i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,pc->comm,&(recv_request[i]));CHKERRQ(ierr); 287 } 288 } 289 290 /* Set DZ_IN[0][] (recall that neigh[0]==rank, always) */ 291 for(j=0; j<n_shared[0]; j++) { 292 DZ_IN[0][j] = pcis->work_N[shared[0][j]]; 293 } 294 295 /* Start computing with local D*Z while communication goes on. */ 296 /* Apply Schur complement. The result is "stored" in vec (more */ 297 /* precisely, vec points to the result, stored in pc_nn->vec1_B) */ 298 /* and also scattered to pcnn->work_N. */ 299 ierr = PCNNApplySchurToChunk(pc,n_shared[0],shared[0],DZ_IN[0],pcis->work_N,pcis->vec1_B, 300 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 301 302 /* Compute the first column, while completing the receiving. */ 303 for (i=0; i<n_neigh; i++) { 304 MPI_Status stat; 305 PetscMPIInt ind=0; 306 if (i>0) { ierr = MPI_Waitany(n_neigh-1,recv_request+1,&ind,&stat);CHKERRQ(ierr); ind++;} 307 mat[ind*n_neigh+0] = 0.0; 308 for (k=0; k<n_shared[ind]; k++) { 309 mat[ind*n_neigh+0] += DZ_IN[ind][k] * pcis->work_N[shared[ind][k]]; 310 } 311 } 312 313 /* Compute the remaining of the columns */ 314 for (j=1; j<n_neigh; j++) { 315 ierr = PCNNApplySchurToChunk(pc,n_shared[j],shared[j],DZ_IN[j],pcis->work_N,pcis->vec1_B, 316 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 317 for (i=0; i<n_neigh; i++) { 318 mat[i*n_neigh+j] = 0.0; 319 for (k=0; k<n_shared[i]; k++) { 320 mat[i*n_neigh+j] += DZ_IN[i][k] * pcis->work_N[shared[i][k]]; 321 } 322 } 323 } 324 325 /* Complete the sending. */ 326 if (n_neigh>1) { 327 MPI_Status *stat; 328 ierr = PetscMalloc((n_neigh-1)*sizeof(MPI_Status),&stat);CHKERRQ(ierr); 329 ierr = MPI_Waitall(n_neigh-1,&(send_request[1]),stat);CHKERRQ(ierr); 330 ierr = PetscFree(stat);CHKERRQ(ierr); 331 } 332 333 /* Free the memory for the MPI requests */ 334 ierr = PetscFree(send_request);CHKERRQ(ierr); 335 336 /* Free the memory for DZ_OUT */ 337 if (DZ_OUT) { 338 if (DZ_OUT[0]) { ierr = PetscFree(DZ_OUT[0]);CHKERRQ(ierr); } 339 ierr = PetscFree(DZ_OUT);CHKERRQ(ierr); 340 } 341 342 { 343 PetscMPIInt size; 344 ierr = MPI_Comm_size(pc->comm,&size);CHKERRQ(ierr); 345 /* Create the global coarse vectors (rhs and solution). */ 346 ierr = VecCreateMPI(pc->comm,1,size,&(pcnn->coarse_b));CHKERRQ(ierr); 347 ierr = VecDuplicate(pcnn->coarse_b,&(pcnn->coarse_x));CHKERRQ(ierr); 348 /* Create and set the global coarse AIJ matrix. */ 349 ierr = MatCreate(pc->comm,1,1,size,size,&(pcnn->coarse_mat));CHKERRQ(ierr); 350 ierr = MatSetType(pcnn->coarse_mat,MATAIJ);CHKERRQ(ierr); 351 ierr = MatSeqAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL);CHKERRQ(ierr); 352 ierr = MatMPIAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL,1,PETSC_NULL);CHKERRQ(ierr); 353 ierr = MatSetValues(pcnn->coarse_mat,n_neigh,neigh,n_neigh,neigh,mat,ADD_VALUES);CHKERRQ(ierr); 354 ierr = MatAssemblyBegin(pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 355 ierr = MatAssemblyEnd (pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 356 } 357 358 { 359 PetscMPIInt rank; 360 PetscScalar one = 1.0; 361 IS is; 362 ierr = MPI_Comm_rank(pc->comm,&rank);CHKERRQ(ierr); 363 /* "Zero out" rows of not-purely-Neumann subdomains */ 364 if (pcis->pure_neumann) { /* does NOT zero the row; create an empty index set. The reason is that MatZeroRows() is collective. */ 365 ierr = ISCreateStride(pc->comm,0,0,0,&is);CHKERRQ(ierr); 366 } else { /* here it DOES zero the row, since it's not a floating subdomain. */ 367 ierr = ISCreateStride(pc->comm,1,rank,0,&is);CHKERRQ(ierr); 368 } 369 ierr = MatZeroRows(pcnn->coarse_mat,is,&one);CHKERRQ(ierr); 370 ierr = ISDestroy(is);CHKERRQ(ierr); 371 } 372 373 /* Create the coarse linear solver context */ 374 { 375 PC pc_ctx, inner_pc; 376 ierr = KSPCreate(pc->comm,&pcnn->ksp_coarse);CHKERRQ(ierr); 377 ierr = KSPSetOperators(pcnn->ksp_coarse,pcnn->coarse_mat,pcnn->coarse_mat,SAME_PRECONDITIONER);CHKERRQ(ierr); 378 ierr = KSPGetPC(pcnn->ksp_coarse,&pc_ctx);CHKERRQ(ierr); 379 ierr = PCSetType(pc_ctx,PCREDUNDANT);CHKERRQ(ierr); 380 ierr = KSPSetType(pcnn->ksp_coarse,KSPPREONLY);CHKERRQ(ierr); 381 ierr = PCRedundantGetPC(pc_ctx,&inner_pc);CHKERRQ(ierr); 382 ierr = PCSetType(inner_pc,PCLU);CHKERRQ(ierr); 383 ierr = KSPSetOptionsPrefix(pcnn->ksp_coarse,"nn_coarse_");CHKERRQ(ierr); 384 ierr = KSPSetFromOptions(pcnn->ksp_coarse);CHKERRQ(ierr); 385 /* the vectors in the following line are dummy arguments, just telling the KSP the vector size. Values are not used */ 386 ierr = KSPSetUp(pcnn->ksp_coarse);CHKERRQ(ierr); 387 } 388 389 /* Free the memory for mat */ 390 ierr = PetscFree(mat);CHKERRQ(ierr); 391 392 /* for DEBUGGING, save the coarse matrix to a file. */ 393 { 394 PetscTruth flg; 395 ierr = PetscOptionsHasName(PETSC_NULL,"-pc_nn_save_coarse_matrix",&flg);CHKERRQ(ierr); 396 if (flg) { 397 PetscViewer viewer; 398 ierr = PetscViewerASCIIOpen(PETSC_COMM_WORLD,"coarse.m",&viewer);CHKERRQ(ierr); 399 ierr = PetscViewerSetFormat(viewer,PETSC_VIEWER_ASCII_MATLAB);CHKERRQ(ierr); 400 ierr = MatView(pcnn->coarse_mat,viewer);CHKERRQ(ierr); 401 ierr = PetscViewerDestroy(viewer);CHKERRQ(ierr); 402 } 403 } 404 405 /* Set the variable pcnn->factor_coarse_rhs. */ 406 pcnn->factor_coarse_rhs = (pcis->pure_neumann) ? 1.0 : 0.0; 407 408 /* See historical note 02, at the bottom of this file. */ 409 PetscFunctionReturn(0); 410 } 411 412 /* -------------------------------------------------------------------------- */ 413 /* 414 PCNNApplySchurToChunk - 415 416 Input parameters: 417 . pcnn 418 . n - size of chunk 419 . idx - indices of chunk 420 . chunk - values 421 422 Output parameters: 423 . array_N - result of Schur complement applied to chunk, scattered to big array 424 . vec1_B - result of Schur complement applied to chunk 425 . vec2_B - garbage (used as work space) 426 . vec1_D - garbage (used as work space) 427 . vec2_D - garbage (used as work space) 428 429 */ 430 #undef __FUNCT__ 431 #define __FUNCT__ "PCNNApplySchurToChunk" 432 PetscErrorCode PCNNApplySchurToChunk(PC pc, PetscInt n, PetscInt* idx, PetscScalar *chunk, PetscScalar* array_N, Vec vec1_B, Vec vec2_B, Vec vec1_D, Vec vec2_D) 433 { 434 PetscErrorCode ierr; 435 PetscInt i; 436 PC_IS *pcis = (PC_IS*)(pc->data); 437 438 PetscFunctionBegin; 439 ierr = PetscMemzero((void*)array_N, pcis->n*sizeof(PetscScalar));CHKERRQ(ierr); 440 for (i=0; i<n; i++) { array_N[idx[i]] = chunk[i]; } 441 ierr = PCISScatterArrayNToVecB(array_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 442 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 443 ierr = PCISScatterArrayNToVecB(array_N,vec1_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 444 PetscFunctionReturn(0); 445 } 446 447 /* -------------------------------------------------------------------------- */ 448 /* 449 PCNNApplyInterfacePreconditioner - Apply the interface preconditioner, i.e., 450 the preconditioner for the Schur complement. 451 452 Input parameter: 453 . r - global vector of interior and interface nodes. The values on the interior nodes are NOT used. 454 455 Output parameters: 456 . z - global vector of interior and interface nodes. The values on the interface are the result of 457 the application of the interface preconditioner to the interface part of r. The values on the 458 interior nodes are garbage. 459 . work_N - array of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 460 . vec1_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 461 . vec2_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 462 . vec3_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 463 . vec1_D - vector of local interior nodes; returns garbage (used as work space) 464 . vec2_D - vector of local interior nodes; returns garbage (used as work space) 465 . vec1_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 466 . vec2_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 467 468 */ 469 #undef __FUNCT__ 470 #define __FUNCT__ "PCNNApplyInterfacePreconditioner" 471 PetscErrorCode PCNNApplyInterfacePreconditioner (PC pc, Vec r, Vec z, PetscScalar* work_N, Vec vec1_B, Vec vec2_B, Vec vec3_B, Vec vec1_D, 472 Vec vec2_D, Vec vec1_N, Vec vec2_N) 473 { 474 PetscErrorCode ierr; 475 PC_IS* pcis = (PC_IS*)(pc->data); 476 477 PetscFunctionBegin; 478 /* 479 First balancing step. 480 */ 481 { 482 PetscTruth flg; 483 ierr = PetscOptionsHasName(PETSC_NULL,"-pc_nn_turn_off_first_balancing",&flg);CHKERRQ(ierr); 484 if (!flg) { 485 ierr = PCNNBalancing(pc,r,(Vec)0,z,vec1_B,vec2_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 486 } else { 487 ierr = VecCopy(r,z);CHKERRQ(ierr); 488 } 489 } 490 491 /* 492 Extract the local interface part of z and scale it by D 493 */ 494 ierr = VecScatterBegin(z,vec1_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 495 ierr = VecScatterEnd (z,vec1_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 496 ierr = VecPointwiseMult(pcis->D,vec1_B,vec2_B);CHKERRQ(ierr); 497 498 /* Neumann Solver */ 499 ierr = PCISApplyInvSchur(pc,vec2_B,vec1_B,vec1_N,vec2_N);CHKERRQ(ierr); 500 501 /* 502 Second balancing step. 503 */ 504 { 505 PetscTruth flg; 506 ierr = PetscOptionsHasName(PETSC_NULL,"-pc_turn_off_second_balancing",&flg);CHKERRQ(ierr); 507 if (!flg) { 508 ierr = PCNNBalancing(pc,r,vec1_B,z,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 509 } else { 510 PetscScalar zero = 0.0; 511 ierr = VecPointwiseMult(pcis->D,vec1_B,vec2_B);CHKERRQ(ierr); 512 ierr = VecSet(&zero,z);CHKERRQ(ierr); 513 ierr = VecScatterBegin(vec2_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 514 ierr = VecScatterEnd (vec2_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 515 } 516 } 517 PetscFunctionReturn(0); 518 } 519 520 /* -------------------------------------------------------------------------- */ 521 /* 522 PCNNBalancing - Computes z, as given in equations (15) and (16) (if the 523 input argument u is provided), or s, as given in equations 524 (12) and (13), if the input argument u is a null vector. 525 Notice that the input argument u plays the role of u_i in 526 equation (14). The equation numbers refer to [Man93]. 527 528 Input Parameters: 529 . pcnn - NN preconditioner context. 530 . r - MPI vector of all nodes (interior and interface). It's preserved. 531 . u - (Optional) sequential vector of local interface nodes. It's preserved UNLESS vec3_B is null. 532 533 Output Parameters: 534 . z - MPI vector of interior and interface nodes. Returns s or z (see description above). 535 . vec1_B - Sequential vector of local interface nodes. Workspace. 536 . vec2_B - Sequential vector of local interface nodes. Workspace. 537 . vec3_B - (Optional) sequential vector of local interface nodes. Workspace. 538 . vec1_D - Sequential vector of local interior nodes. Workspace. 539 . vec2_D - Sequential vector of local interior nodes. Workspace. 540 . work_N - Array of all local nodes (interior and interface). Workspace. 541 542 */ 543 #undef __FUNCT__ 544 #define __FUNCT__ "PCNNBalancing" 545 PetscErrorCode PCNNBalancing (PC pc, Vec r, Vec u, Vec z, Vec vec1_B, Vec vec2_B, Vec vec3_B, 546 Vec vec1_D, Vec vec2_D, PetscScalar *work_N) 547 { 548 PetscErrorCode ierr; 549 PetscInt k; 550 PetscScalar zero = 0.0; 551 PetscScalar m_one = -1.0; 552 PetscScalar value; 553 PetscScalar* lambda; 554 PC_NN* pcnn = (PC_NN*)(pc->data); 555 PC_IS* pcis = (PC_IS*)(pc->data); 556 557 PetscFunctionBegin; 558 ierr = PetscLogEventBegin(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 559 if (u) { 560 if (!vec3_B) { vec3_B = u; } 561 ierr = VecPointwiseMult(pcis->D,u,vec1_B);CHKERRQ(ierr); 562 ierr = VecSet(&zero,z);CHKERRQ(ierr); 563 ierr = VecScatterBegin(vec1_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 564 ierr = VecScatterEnd (vec1_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 565 ierr = VecScatterBegin(z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 566 ierr = VecScatterEnd (z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 567 ierr = PCISApplySchur(pc,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 568 ierr = VecScale(&m_one,vec3_B);CHKERRQ(ierr); 569 ierr = VecCopy(r,z);CHKERRQ(ierr); 570 ierr = VecScatterBegin(vec3_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 571 ierr = VecScatterEnd (vec3_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 572 } else { 573 ierr = VecCopy(r,z);CHKERRQ(ierr); 574 } 575 ierr = VecScatterBegin(z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 576 ierr = VecScatterEnd (z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 577 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 578 for (k=0, value=0.0; k<pcis->n_shared[0]; k++) { value += pcnn->DZ_IN[0][k] * work_N[pcis->shared[0][k]]; } 579 value *= pcnn->factor_coarse_rhs; /* This factor is set in CreateCoarseMatrix(). */ 580 { 581 PetscMPIInt rank; 582 ierr = MPI_Comm_rank(pc->comm,&rank);CHKERRQ(ierr); 583 ierr = VecSetValue(pcnn->coarse_b,rank,value,INSERT_VALUES);CHKERRQ(ierr); 584 /* 585 Since we are only inserting local values (one value actually) we don't need to do the 586 reduction that tells us there is no data that needs to be moved. Hence we comment out these 587 ierr = VecAssemblyBegin(pcnn->coarse_b);CHKERRQ(ierr); 588 ierr = VecAssemblyEnd (pcnn->coarse_b);CHKERRQ(ierr); 589 */ 590 } 591 ierr = KSPSolve(pcnn->ksp_coarse,pcnn->coarse_b,pcnn->coarse_x);CHKERRQ(ierr); 592 if (!u) { ierr = VecScale(&m_one,pcnn->coarse_x);CHKERRQ(ierr); } 593 ierr = VecGetArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 594 for (k=0; k<pcis->n_shared[0]; k++) { work_N[pcis->shared[0][k]] = *lambda * pcnn->DZ_IN[0][k]; } 595 ierr = VecRestoreArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 596 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 597 ierr = VecSet(&zero,z);CHKERRQ(ierr); 598 ierr = VecScatterBegin(vec2_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 599 ierr = VecScatterEnd (vec2_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 600 if (!u) { 601 ierr = VecScatterBegin(z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 602 ierr = VecScatterEnd (z,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pcis->global_to_B);CHKERRQ(ierr); 603 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 604 ierr = VecCopy(r,z);CHKERRQ(ierr); 605 } 606 ierr = VecScatterBegin(vec1_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 607 ierr = VecScatterEnd (vec1_B,z,ADD_VALUES,SCATTER_REVERSE,pcis->global_to_B);CHKERRQ(ierr); 608 ierr = PetscLogEventEnd(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 609 PetscFunctionReturn(0); 610 } 611 612 #undef __FUNCT__ 613 614 615 616 /* ------- E N D O F T H E C O D E ------- */ 617 /* */ 618 /* From now on, "footnotes" (or "historical notes"). */ 619 /* */ 620 /* ------------------------------------------------- */ 621 622 623 624 /* -------------------------------------------------------------------------- 625 Historical note 01 626 -------------------------------------------------------------------------- */ 627 /* 628 We considered the possibility of an alternative D_i that would still 629 provide a partition of unity (i.e., $ \sum_i N_i D_i N_i^T = I $). 630 The basic principle was still the pseudo-inverse of the counting 631 function; the difference was that we would not count subdomains 632 that do not contribute to the coarse space (i.e., not pure-Neumann 633 subdomains). 634 635 This turned out to be a bad idea: we would solve trivial Neumann 636 problems in the not pure-Neumann subdomains, since we would be scaling 637 the balanced residual by zero. 638 */ 639 640 641 642 643 /* -------------------------------------------------------------------------- 644 Historical note 02 645 -------------------------------------------------------------------------- */ 646 /* 647 We tried an alternative coarse problem, that would eliminate exactly a 648 constant error. Turned out not to improve the overall convergence. 649 */ 650 651 652