1 2 #include <../src/ksp/pc/impls/is/nn/nn.h> 3 4 /* -------------------------------------------------------------------------- */ 5 /* 6 PCSetUp_NN - Prepares for the use of the NN preconditioner 7 by setting data structures and options. 8 9 Input Parameter: 10 . pc - the preconditioner context 11 12 Application Interface Routine: PCSetUp() 13 14 Notes: 15 The interface routine PCSetUp() is not usually called directly by 16 the user, but instead is called by PCApply() if necessary. 17 */ 18 #undef __FUNCT__ 19 #define __FUNCT__ "PCSetUp_NN" 20 static PetscErrorCode PCSetUp_NN(PC pc) 21 { 22 PetscErrorCode ierr; 23 24 PetscFunctionBegin; 25 if (!pc->setupcalled) { 26 /* Set up all the "iterative substructuring" common block */ 27 ierr = PCISSetUp(pc);CHKERRQ(ierr); 28 /* Create the coarse matrix. */ 29 ierr = PCNNCreateCoarseMatrix(pc);CHKERRQ(ierr); 30 } 31 PetscFunctionReturn(0); 32 } 33 34 /* -------------------------------------------------------------------------- */ 35 /* 36 PCApply_NN - Applies the NN preconditioner to a vector. 37 38 Input Parameters: 39 . pc - the preconditioner context 40 . r - input vector (global) 41 42 Output Parameter: 43 . z - output vector (global) 44 45 Application Interface Routine: PCApply() 46 */ 47 #undef __FUNCT__ 48 #define __FUNCT__ "PCApply_NN" 49 static PetscErrorCode PCApply_NN(PC pc,Vec r,Vec z) 50 { 51 PC_IS *pcis = (PC_IS*)(pc->data); 52 PetscErrorCode ierr; 53 PetscScalar m_one = -1.0; 54 Vec w = pcis->vec1_global; 55 56 PetscFunctionBegin; 57 /* 58 Dirichlet solvers. 59 Solving $ B_I^{(i)}r_I^{(i)} $ at each processor. 60 Storing the local results at vec2_D 61 */ 62 ierr = VecScatterBegin(pcis->global_to_D,r,pcis->vec1_D,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 63 ierr = VecScatterEnd (pcis->global_to_D,r,pcis->vec1_D,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 64 ierr = KSPSolve(pcis->ksp_D,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 65 66 /* 67 Computing $ r_B - \sum_j \tilde R_j^T A_{BI}^{(j)} (B_I^{(j)}r_I^{(j)}) $ . 68 Storing the result in the interface portion of the global vector w. 69 */ 70 ierr = MatMult(pcis->A_BI,pcis->vec2_D,pcis->vec1_B);CHKERRQ(ierr); 71 ierr = VecScale(pcis->vec1_B,m_one);CHKERRQ(ierr); 72 ierr = VecCopy(r,w);CHKERRQ(ierr); 73 ierr = VecScatterBegin(pcis->global_to_B,pcis->vec1_B,w,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 74 ierr = VecScatterEnd (pcis->global_to_B,pcis->vec1_B,w,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 75 76 /* 77 Apply the interface preconditioner 78 */ 79 ierr = PCNNApplyInterfacePreconditioner(pc,w,z,pcis->work_N,pcis->vec1_B,pcis->vec2_B,pcis->vec3_B,pcis->vec1_D, 80 pcis->vec3_D,pcis->vec1_N,pcis->vec2_N);CHKERRQ(ierr); 81 82 /* 83 Computing $ t_I^{(i)} = A_{IB}^{(i)} \tilde R_i z_B $ 84 The result is stored in vec1_D. 85 */ 86 ierr = VecScatterBegin(pcis->global_to_B,z,pcis->vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 87 ierr = VecScatterEnd (pcis->global_to_B,z,pcis->vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 88 ierr = MatMult(pcis->A_IB,pcis->vec1_B,pcis->vec1_D);CHKERRQ(ierr); 89 90 /* 91 Dirichlet solvers. 92 Computing $ B_I^{(i)}t_I^{(i)} $ and sticking into the global vector the blocks 93 $ B_I^{(i)}r_I^{(i)} - B_I^{(i)}t_I^{(i)} $. 94 */ 95 ierr = VecScatterBegin(pcis->global_to_D,pcis->vec2_D,z,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 96 ierr = VecScatterEnd (pcis->global_to_D,pcis->vec2_D,z,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 97 ierr = KSPSolve(pcis->ksp_D,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 98 ierr = VecScale(pcis->vec2_D,m_one);CHKERRQ(ierr); 99 ierr = VecScatterBegin(pcis->global_to_D,pcis->vec2_D,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 100 ierr = VecScatterEnd (pcis->global_to_D,pcis->vec2_D,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 101 PetscFunctionReturn(0); 102 } 103 104 /* -------------------------------------------------------------------------- */ 105 /* 106 PCDestroy_NN - Destroys the private context for the NN preconditioner 107 that was created with PCCreate_NN(). 108 109 Input Parameter: 110 . pc - the preconditioner context 111 112 Application Interface Routine: PCDestroy() 113 */ 114 #undef __FUNCT__ 115 #define __FUNCT__ "PCDestroy_NN" 116 static PetscErrorCode PCDestroy_NN(PC pc) 117 { 118 PC_NN *pcnn = (PC_NN*)pc->data; 119 PetscErrorCode ierr; 120 121 PetscFunctionBegin; 122 ierr = PCISDestroy(pc);CHKERRQ(ierr); 123 124 ierr = MatDestroy(&pcnn->coarse_mat);CHKERRQ(ierr); 125 ierr = VecDestroy(&pcnn->coarse_x);CHKERRQ(ierr); 126 ierr = VecDestroy(&pcnn->coarse_b);CHKERRQ(ierr); 127 ierr = KSPDestroy(&pcnn->ksp_coarse);CHKERRQ(ierr); 128 if (pcnn->DZ_IN) { 129 ierr = PetscFree(pcnn->DZ_IN[0]);CHKERRQ(ierr); 130 ierr = PetscFree(pcnn->DZ_IN);CHKERRQ(ierr); 131 } 132 133 /* 134 Free the private data structure that was hanging off the PC 135 */ 136 ierr = PetscFree(pc->data);CHKERRQ(ierr); 137 PetscFunctionReturn(0); 138 } 139 140 /* -------------------------------------------------------------------------- */ 141 /*MC 142 PCNN - Balancing Neumann-Neumann for scalar elliptic PDEs. 143 144 Options Database Keys: 145 + -pc_nn_turn_off_first_balancing - do not balance the residual before solving the local Neumann problems 146 (this skips the first coarse grid solve in the preconditioner) 147 . -pc_nn_turn_off_second_balancing - do not balance the solution solving the local Neumann problems 148 (this skips the second coarse grid solve in the preconditioner) 149 . -pc_is_damp_fixed <fact> - 150 . -pc_is_remove_nullspace_fixed - 151 . -pc_is_set_damping_factor_floating <fact> - 152 . -pc_is_not_damp_floating - 153 + -pc_is_not_remove_nullspace_floating - 154 155 Level: intermediate 156 157 Notes: The matrix used with this preconditioner must be of type MATIS 158 159 Unlike more 'conventional' Neumann-Neumann preconditioners this iterates over ALL the 160 degrees of freedom, NOT just those on the interface (this allows the use of approximate solvers 161 on the subdomains; though in our experience using approximate solvers is slower.). 162 163 Options for the coarse grid preconditioner can be set with -nn_coarse_pc_xxx 164 Options for the Dirichlet subproblem preconditioner can be set with -is_localD_pc_xxx 165 Options for the Neumann subproblem preconditioner can be set with -is_localN_pc_xxx 166 167 Contributed by Paulo Goldfeld 168 169 .seealso: PCCreate(), PCSetType(), PCType (for list of available types), PC, MATIS 170 M*/ 171 172 #undef __FUNCT__ 173 #define __FUNCT__ "PCCreate_NN" 174 PETSC_EXTERN PetscErrorCode PCCreate_NN(PC pc) 175 { 176 PetscErrorCode ierr; 177 PC_NN *pcnn; 178 179 PetscFunctionBegin; 180 /* 181 Creates the private data structure for this preconditioner and 182 attach it to the PC object. 183 */ 184 ierr = PetscNewLog(pc,&pcnn);CHKERRQ(ierr); 185 pc->data = (void*)pcnn; 186 187 ierr = PCISCreate(pc);CHKERRQ(ierr); 188 pcnn->coarse_mat = 0; 189 pcnn->coarse_x = 0; 190 pcnn->coarse_b = 0; 191 pcnn->ksp_coarse = 0; 192 pcnn->DZ_IN = 0; 193 194 /* 195 Set the pointers for the functions that are provided above. 196 Now when the user-level routines (such as PCApply(), PCDestroy(), etc.) 197 are called, they will automatically call these functions. Note we 198 choose not to provide a couple of these functions since they are 199 not needed. 200 */ 201 pc->ops->apply = PCApply_NN; 202 pc->ops->applytranspose = 0; 203 pc->ops->setup = PCSetUp_NN; 204 pc->ops->destroy = PCDestroy_NN; 205 pc->ops->view = 0; 206 pc->ops->applyrichardson = 0; 207 pc->ops->applysymmetricleft = 0; 208 pc->ops->applysymmetricright = 0; 209 PetscFunctionReturn(0); 210 } 211 212 /* -------------------------------------------------------------------------- */ 213 /* 214 PCNNCreateCoarseMatrix - 215 */ 216 #undef __FUNCT__ 217 #define __FUNCT__ "PCNNCreateCoarseMatrix" 218 PetscErrorCode PCNNCreateCoarseMatrix(PC pc) 219 { 220 MPI_Request *send_request, *recv_request; 221 PetscErrorCode ierr; 222 PetscInt i, j, k; 223 PetscScalar *mat; /* Sub-matrix with this subdomain's contribution to the coarse matrix */ 224 PetscScalar **DZ_OUT; /* proc[k].DZ_OUT[i][] = bit of vector to be sent from processor k to processor i */ 225 226 /* aliasing some names */ 227 PC_IS *pcis = (PC_IS*)(pc->data); 228 PC_NN *pcnn = (PC_NN*)pc->data; 229 PetscInt n_neigh = pcis->n_neigh; 230 PetscInt *neigh = pcis->neigh; 231 PetscInt *n_shared = pcis->n_shared; 232 PetscInt **shared = pcis->shared; 233 PetscScalar **DZ_IN; /* Must be initialized after memory allocation. */ 234 235 PetscFunctionBegin; 236 /* Allocate memory for mat (the +1 is to handle the case n_neigh equal to zero) */ 237 ierr = PetscMalloc1(n_neigh*n_neigh+1,&mat);CHKERRQ(ierr); 238 239 /* Allocate memory for DZ */ 240 /* Notice that DZ_OUT[0] is allocated some space that is never used. */ 241 /* This is just in order to DZ_OUT and DZ_IN to have exactly the same form. */ 242 { 243 PetscInt size_of_Z = 0; 244 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&pcnn->DZ_IN);CHKERRQ(ierr); 245 DZ_IN = pcnn->DZ_IN; 246 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&DZ_OUT);CHKERRQ(ierr); 247 for (i=0; i<n_neigh; i++) size_of_Z += n_shared[i]; 248 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_IN[0]);CHKERRQ(ierr); 249 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_OUT[0]);CHKERRQ(ierr); 250 } 251 for (i=1; i<n_neigh; i++) { 252 DZ_IN[i] = DZ_IN [i-1] + n_shared[i-1]; 253 DZ_OUT[i] = DZ_OUT[i-1] + n_shared[i-1]; 254 } 255 256 /* Set the values of DZ_OUT, in order to send this info to the neighbours */ 257 /* First, set the auxiliary array pcis->work_N. */ 258 ierr = PCISScatterArrayNToVecB(pcis->work_N,pcis->D,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 259 for (i=1; i<n_neigh; i++) { 260 for (j=0; j<n_shared[i]; j++) { 261 DZ_OUT[i][j] = pcis->work_N[shared[i][j]]; 262 } 263 } 264 265 /* Non-blocking send/receive the common-interface chunks of scaled nullspaces */ 266 /* Notice that send_request[] and recv_request[] could have one less element. */ 267 /* We make them longer to have request[i] corresponding to neigh[i]. */ 268 { 269 PetscMPIInt tag; 270 ierr = PetscObjectGetNewTag((PetscObject)pc,&tag);CHKERRQ(ierr); 271 ierr = PetscMalloc2(n_neigh+1,&send_request,n_neigh+1,&recv_request);CHKERRQ(ierr); 272 for (i=1; i<n_neigh; i++) { 273 ierr = MPI_Isend((void*)(DZ_OUT[i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,PetscObjectComm((PetscObject)pc),&(send_request[i]));CHKERRQ(ierr); 274 ierr = MPI_Irecv((void*)(DZ_IN [i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,PetscObjectComm((PetscObject)pc),&(recv_request[i]));CHKERRQ(ierr); 275 } 276 } 277 278 /* Set DZ_IN[0][] (recall that neigh[0]==rank, always) */ 279 for (j=0; j<n_shared[0]; j++) DZ_IN[0][j] = pcis->work_N[shared[0][j]]; 280 281 /* Start computing with local D*Z while communication goes on. */ 282 /* Apply Schur complement. The result is "stored" in vec (more */ 283 /* precisely, vec points to the result, stored in pc_nn->vec1_B) */ 284 /* and also scattered to pcnn->work_N. */ 285 ierr = PCNNApplySchurToChunk(pc,n_shared[0],shared[0],DZ_IN[0],pcis->work_N,pcis->vec1_B, 286 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 287 288 /* Compute the first column, while completing the receiving. */ 289 for (i=0; i<n_neigh; i++) { 290 MPI_Status stat; 291 PetscMPIInt ind=0; 292 if (i>0) { ierr = MPI_Waitany(n_neigh-1,recv_request+1,&ind,&stat);CHKERRQ(ierr); ind++;} 293 mat[ind*n_neigh+0] = 0.0; 294 for (k=0; k<n_shared[ind]; k++) mat[ind*n_neigh+0] += DZ_IN[ind][k] * pcis->work_N[shared[ind][k]]; 295 } 296 297 /* Compute the remaining of the columns */ 298 for (j=1; j<n_neigh; j++) { 299 ierr = PCNNApplySchurToChunk(pc,n_shared[j],shared[j],DZ_IN[j],pcis->work_N,pcis->vec1_B, 300 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 301 for (i=0; i<n_neigh; i++) { 302 mat[i*n_neigh+j] = 0.0; 303 for (k=0; k<n_shared[i]; k++) mat[i*n_neigh+j] += DZ_IN[i][k] * pcis->work_N[shared[i][k]]; 304 } 305 } 306 307 /* Complete the sending. */ 308 if (n_neigh>1) { 309 MPI_Status *stat; 310 ierr = PetscMalloc1(n_neigh-1,&stat);CHKERRQ(ierr); 311 if (n_neigh-1) {ierr = MPI_Waitall(n_neigh-1,&(send_request[1]),stat);CHKERRQ(ierr);} 312 ierr = PetscFree(stat);CHKERRQ(ierr); 313 } 314 315 /* Free the memory for the MPI requests */ 316 ierr = PetscFree2(send_request,recv_request);CHKERRQ(ierr); 317 318 /* Free the memory for DZ_OUT */ 319 if (DZ_OUT) { 320 ierr = PetscFree(DZ_OUT[0]);CHKERRQ(ierr); 321 ierr = PetscFree(DZ_OUT);CHKERRQ(ierr); 322 } 323 324 { 325 PetscMPIInt size; 326 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)pc),&size);CHKERRQ(ierr); 327 /* Create the global coarse vectors (rhs and solution). */ 328 ierr = VecCreateMPI(PetscObjectComm((PetscObject)pc),1,size,&(pcnn->coarse_b));CHKERRQ(ierr); 329 ierr = VecDuplicate(pcnn->coarse_b,&(pcnn->coarse_x));CHKERRQ(ierr); 330 /* Create and set the global coarse AIJ matrix. */ 331 ierr = MatCreate(PetscObjectComm((PetscObject)pc),&(pcnn->coarse_mat));CHKERRQ(ierr); 332 ierr = MatSetSizes(pcnn->coarse_mat,1,1,size,size);CHKERRQ(ierr); 333 ierr = MatSetType(pcnn->coarse_mat,MATAIJ);CHKERRQ(ierr); 334 ierr = MatSeqAIJSetPreallocation(pcnn->coarse_mat,1,NULL);CHKERRQ(ierr); 335 ierr = MatMPIAIJSetPreallocation(pcnn->coarse_mat,1,NULL,n_neigh,NULL);CHKERRQ(ierr); 336 ierr = MatSetOption(pcnn->coarse_mat,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 337 ierr = MatSetOption(pcnn->coarse_mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 338 ierr = MatSetValues(pcnn->coarse_mat,n_neigh,neigh,n_neigh,neigh,mat,ADD_VALUES);CHKERRQ(ierr); 339 ierr = MatAssemblyBegin(pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 340 ierr = MatAssemblyEnd (pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 341 } 342 343 { 344 PetscMPIInt rank; 345 PetscScalar one = 1.0; 346 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)pc),&rank);CHKERRQ(ierr); 347 /* "Zero out" rows of not-purely-Neumann subdomains */ 348 if (pcis->pure_neumann) { /* does NOT zero the row; create an empty index set. The reason is that MatZeroRows() is collective. */ 349 ierr = MatZeroRows(pcnn->coarse_mat,0,NULL,one,0,0);CHKERRQ(ierr); 350 } else { /* here it DOES zero the row, since it's not a floating subdomain. */ 351 PetscInt row = (PetscInt) rank; 352 ierr = MatZeroRows(pcnn->coarse_mat,1,&row,one,0,0);CHKERRQ(ierr); 353 } 354 } 355 356 /* Create the coarse linear solver context */ 357 { 358 PC pc_ctx, inner_pc; 359 KSP inner_ksp; 360 361 ierr = KSPCreate(PetscObjectComm((PetscObject)pc),&pcnn->ksp_coarse);CHKERRQ(ierr); 362 ierr = PetscObjectIncrementTabLevel((PetscObject)pcnn->ksp_coarse,(PetscObject)pc,2);CHKERRQ(ierr); 363 ierr = KSPSetOperators(pcnn->ksp_coarse,pcnn->coarse_mat,pcnn->coarse_mat);CHKERRQ(ierr); 364 ierr = KSPGetPC(pcnn->ksp_coarse,&pc_ctx);CHKERRQ(ierr); 365 ierr = PCSetType(pc_ctx,PCREDUNDANT);CHKERRQ(ierr); 366 ierr = KSPSetType(pcnn->ksp_coarse,KSPPREONLY);CHKERRQ(ierr); 367 ierr = PCRedundantGetKSP(pc_ctx,&inner_ksp);CHKERRQ(ierr); 368 ierr = KSPGetPC(inner_ksp,&inner_pc);CHKERRQ(ierr); 369 ierr = PCSetType(inner_pc,PCLU);CHKERRQ(ierr); 370 ierr = KSPSetOptionsPrefix(pcnn->ksp_coarse,"nn_coarse_");CHKERRQ(ierr); 371 ierr = KSPSetFromOptions(pcnn->ksp_coarse);CHKERRQ(ierr); 372 /* the vectors in the following line are dummy arguments, just telling the KSP the vector size. Values are not used */ 373 ierr = KSPSetUp(pcnn->ksp_coarse);CHKERRQ(ierr); 374 } 375 376 /* Free the memory for mat */ 377 ierr = PetscFree(mat);CHKERRQ(ierr); 378 379 /* for DEBUGGING, save the coarse matrix to a file. */ 380 { 381 PetscBool flg = PETSC_FALSE; 382 ierr = PetscOptionsGetBool(NULL,"-pc_nn_save_coarse_matrix",&flg,NULL);CHKERRQ(ierr); 383 if (flg) { 384 PetscViewer viewer; 385 ierr = PetscViewerASCIIOpen(PETSC_COMM_WORLD,"coarse.m",&viewer);CHKERRQ(ierr); 386 ierr = PetscViewerSetFormat(viewer,PETSC_VIEWER_ASCII_MATLAB);CHKERRQ(ierr); 387 ierr = MatView(pcnn->coarse_mat,viewer);CHKERRQ(ierr); 388 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 389 } 390 } 391 392 /* Set the variable pcnn->factor_coarse_rhs. */ 393 pcnn->factor_coarse_rhs = (pcis->pure_neumann) ? 1.0 : 0.0; 394 395 /* See historical note 02, at the bottom of this file. */ 396 PetscFunctionReturn(0); 397 } 398 399 /* -------------------------------------------------------------------------- */ 400 /* 401 PCNNApplySchurToChunk - 402 403 Input parameters: 404 . pcnn 405 . n - size of chunk 406 . idx - indices of chunk 407 . chunk - values 408 409 Output parameters: 410 . array_N - result of Schur complement applied to chunk, scattered to big array 411 . vec1_B - result of Schur complement applied to chunk 412 . vec2_B - garbage (used as work space) 413 . vec1_D - garbage (used as work space) 414 . vec2_D - garbage (used as work space) 415 416 */ 417 #undef __FUNCT__ 418 #define __FUNCT__ "PCNNApplySchurToChunk" 419 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) 420 { 421 PetscErrorCode ierr; 422 PetscInt i; 423 PC_IS *pcis = (PC_IS*)(pc->data); 424 425 PetscFunctionBegin; 426 ierr = PetscMemzero((void*)array_N, pcis->n*sizeof(PetscScalar));CHKERRQ(ierr); 427 for (i=0; i<n; i++) array_N[idx[i]] = chunk[i]; 428 ierr = PCISScatterArrayNToVecB(array_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 429 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 430 ierr = PCISScatterArrayNToVecB(array_N,vec1_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 431 PetscFunctionReturn(0); 432 } 433 434 /* -------------------------------------------------------------------------- */ 435 /* 436 PCNNApplyInterfacePreconditioner - Apply the interface preconditioner, i.e., 437 the preconditioner for the Schur complement. 438 439 Input parameter: 440 . r - global vector of interior and interface nodes. The values on the interior nodes are NOT used. 441 442 Output parameters: 443 . z - global vector of interior and interface nodes. The values on the interface are the result of 444 the application of the interface preconditioner to the interface part of r. The values on the 445 interior nodes are garbage. 446 . work_N - array of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 447 . vec1_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 448 . vec2_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 449 . vec3_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 450 . vec1_D - vector of local interior nodes; returns garbage (used as work space) 451 . vec2_D - vector of local interior nodes; returns garbage (used as work space) 452 . vec1_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 453 . vec2_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 454 455 */ 456 #undef __FUNCT__ 457 #define __FUNCT__ "PCNNApplyInterfacePreconditioner" 458 PetscErrorCode PCNNApplyInterfacePreconditioner(PC pc, Vec r, Vec z, PetscScalar *work_N, Vec vec1_B, Vec vec2_B, Vec vec3_B, Vec vec1_D,Vec vec2_D, Vec vec1_N, Vec vec2_N) 459 { 460 PetscErrorCode ierr; 461 PC_IS *pcis = (PC_IS*)(pc->data); 462 463 PetscFunctionBegin; 464 /* 465 First balancing step. 466 */ 467 { 468 PetscBool flg = PETSC_FALSE; 469 ierr = PetscOptionsGetBool(NULL,"-pc_nn_turn_off_first_balancing",&flg,NULL);CHKERRQ(ierr); 470 if (!flg) { 471 ierr = PCNNBalancing(pc,r,(Vec)0,z,vec1_B,vec2_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 472 } else { 473 ierr = VecCopy(r,z);CHKERRQ(ierr); 474 } 475 } 476 477 /* 478 Extract the local interface part of z and scale it by D 479 */ 480 ierr = VecScatterBegin(pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 481 ierr = VecScatterEnd (pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 482 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 483 484 /* Neumann Solver */ 485 ierr = PCISApplyInvSchur(pc,vec2_B,vec1_B,vec1_N,vec2_N);CHKERRQ(ierr); 486 487 /* 488 Second balancing step. 489 */ 490 { 491 PetscBool flg = PETSC_FALSE; 492 ierr = PetscOptionsGetBool(NULL,"-pc_turn_off_second_balancing",&flg,NULL);CHKERRQ(ierr); 493 if (!flg) { 494 ierr = PCNNBalancing(pc,r,vec1_B,z,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 495 } else { 496 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 497 ierr = VecSet(z,0.0);CHKERRQ(ierr); 498 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 499 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 500 } 501 } 502 PetscFunctionReturn(0); 503 } 504 505 /* -------------------------------------------------------------------------- */ 506 /* 507 PCNNBalancing - Computes z, as given in equations (15) and (16) (if the 508 input argument u is provided), or s, as given in equations 509 (12) and (13), if the input argument u is a null vector. 510 Notice that the input argument u plays the role of u_i in 511 equation (14). The equation numbers refer to [Man93]. 512 513 Input Parameters: 514 . pcnn - NN preconditioner context. 515 . r - MPI vector of all nodes (interior and interface). It's preserved. 516 . u - (Optional) sequential vector of local interface nodes. It's preserved UNLESS vec3_B is null. 517 518 Output Parameters: 519 . z - MPI vector of interior and interface nodes. Returns s or z (see description above). 520 . vec1_B - Sequential vector of local interface nodes. Workspace. 521 . vec2_B - Sequential vector of local interface nodes. Workspace. 522 . vec3_B - (Optional) sequential vector of local interface nodes. Workspace. 523 . vec1_D - Sequential vector of local interior nodes. Workspace. 524 . vec2_D - Sequential vector of local interior nodes. Workspace. 525 . work_N - Array of all local nodes (interior and interface). Workspace. 526 527 */ 528 #undef __FUNCT__ 529 #define __FUNCT__ "PCNNBalancing" 530 PetscErrorCode PCNNBalancing(PC pc, Vec r, Vec u, Vec z, Vec vec1_B, Vec vec2_B, Vec vec3_B,Vec vec1_D, Vec vec2_D, PetscScalar *work_N) 531 { 532 PetscErrorCode ierr; 533 PetscInt k; 534 PetscScalar value; 535 PetscScalar *lambda; 536 PC_NN *pcnn = (PC_NN*)(pc->data); 537 PC_IS *pcis = (PC_IS*)(pc->data); 538 539 PetscFunctionBegin; 540 ierr = PetscLogEventBegin(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 541 if (u) { 542 if (!vec3_B) vec3_B = u; 543 ierr = VecPointwiseMult(vec1_B,pcis->D,u);CHKERRQ(ierr); 544 ierr = VecSet(z,0.0);CHKERRQ(ierr); 545 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 546 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 547 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 548 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 549 ierr = PCISApplySchur(pc,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 550 ierr = VecScale(vec3_B,-1.0);CHKERRQ(ierr); 551 ierr = VecCopy(r,z);CHKERRQ(ierr); 552 ierr = VecScatterBegin(pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 553 ierr = VecScatterEnd (pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 554 } else { 555 ierr = VecCopy(r,z);CHKERRQ(ierr); 556 } 557 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 558 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 559 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 560 for (k=0, value=0.0; k<pcis->n_shared[0]; k++) value += pcnn->DZ_IN[0][k] * work_N[pcis->shared[0][k]]; 561 value *= pcnn->factor_coarse_rhs; /* This factor is set in CreateCoarseMatrix(). */ 562 { 563 PetscMPIInt rank; 564 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)pc),&rank);CHKERRQ(ierr); 565 ierr = VecSetValue(pcnn->coarse_b,rank,value,INSERT_VALUES);CHKERRQ(ierr); 566 /* 567 Since we are only inserting local values (one value actually) we don't need to do the 568 reduction that tells us there is no data that needs to be moved. Hence we comment out these 569 ierr = VecAssemblyBegin(pcnn->coarse_b);CHKERRQ(ierr); 570 ierr = VecAssemblyEnd (pcnn->coarse_b);CHKERRQ(ierr); 571 */ 572 } 573 ierr = KSPSolve(pcnn->ksp_coarse,pcnn->coarse_b,pcnn->coarse_x);CHKERRQ(ierr); 574 if (!u) { ierr = VecScale(pcnn->coarse_x,-1.0);CHKERRQ(ierr); } 575 ierr = VecGetArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 576 for (k=0; k<pcis->n_shared[0]; k++) work_N[pcis->shared[0][k]] = *lambda * pcnn->DZ_IN[0][k]; 577 ierr = VecRestoreArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 578 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 579 ierr = VecSet(z,0.0);CHKERRQ(ierr); 580 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 581 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 582 if (!u) { 583 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 584 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 585 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 586 ierr = VecCopy(r,z);CHKERRQ(ierr); 587 } 588 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 589 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 590 ierr = PetscLogEventEnd(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 591 PetscFunctionReturn(0); 592 } 593 594 #undef __FUNCT__ 595 596 597 598 /* ------- E N D O F T H E C O D E ------- */ 599 /* */ 600 /* From now on, "footnotes" (or "historical notes"). */ 601 /* */ 602 /* ------------------------------------------------- */ 603 604 605 606 /* -------------------------------------------------------------------------- 607 Historical note 01 608 -------------------------------------------------------------------------- */ 609 /* 610 We considered the possibility of an alternative D_i that would still 611 provide a partition of unity (i.e., $ \sum_i N_i D_i N_i^T = I $). 612 The basic principle was still the pseudo-inverse of the counting 613 function; the difference was that we would not count subdomains 614 that do not contribute to the coarse space (i.e., not pure-Neumann 615 subdomains). 616 617 This turned out to be a bad idea: we would solve trivial Neumann 618 problems in the not pure-Neumann subdomains, since we would be scaling 619 the balanced residual by zero. 620 */ 621 622 623 624 625 /* -------------------------------------------------------------------------- 626 Historical note 02 627 -------------------------------------------------------------------------- */ 628 /* 629 We tried an alternative coarse problem, that would eliminate exactly a 630 constant error. Turned out not to improve the overall convergence. 631 */ 632 633 634