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,PC_NN,&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 = PetscMalloc((n_neigh*n_neigh+1)*sizeof(PetscScalar),&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 = PetscMalloc((2*(n_neigh)+1)*sizeof(MPI_Request),&send_request);CHKERRQ(ierr); 272 recv_request = send_request + (n_neigh); 273 for (i=1; i<n_neigh; i++) { 274 ierr = MPI_Isend((void*)(DZ_OUT[i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,PetscObjectComm((PetscObject)pc),&(send_request[i]));CHKERRQ(ierr); 275 ierr = MPI_Irecv((void*)(DZ_IN [i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,PetscObjectComm((PetscObject)pc),&(recv_request[i]));CHKERRQ(ierr); 276 } 277 } 278 279 /* Set DZ_IN[0][] (recall that neigh[0]==rank, always) */ 280 for (j=0; j<n_shared[0]; j++) DZ_IN[0][j] = pcis->work_N[shared[0][j]]; 281 282 /* Start computing with local D*Z while communication goes on. */ 283 /* Apply Schur complement. The result is "stored" in vec (more */ 284 /* precisely, vec points to the result, stored in pc_nn->vec1_B) */ 285 /* and also scattered to pcnn->work_N. */ 286 ierr = PCNNApplySchurToChunk(pc,n_shared[0],shared[0],DZ_IN[0],pcis->work_N,pcis->vec1_B, 287 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 288 289 /* Compute the first column, while completing the receiving. */ 290 for (i=0; i<n_neigh; i++) { 291 MPI_Status stat; 292 PetscMPIInt ind=0; 293 if (i>0) { ierr = MPI_Waitany(n_neigh-1,recv_request+1,&ind,&stat);CHKERRQ(ierr); ind++;} 294 mat[ind*n_neigh+0] = 0.0; 295 for (k=0; k<n_shared[ind]; k++) mat[ind*n_neigh+0] += DZ_IN[ind][k] * pcis->work_N[shared[ind][k]]; 296 } 297 298 /* Compute the remaining of the columns */ 299 for (j=1; j<n_neigh; j++) { 300 ierr = PCNNApplySchurToChunk(pc,n_shared[j],shared[j],DZ_IN[j],pcis->work_N,pcis->vec1_B, 301 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 302 for (i=0; i<n_neigh; i++) { 303 mat[i*n_neigh+j] = 0.0; 304 for (k=0; k<n_shared[i]; k++) mat[i*n_neigh+j] += DZ_IN[i][k] * pcis->work_N[shared[i][k]]; 305 } 306 } 307 308 /* Complete the sending. */ 309 if (n_neigh>1) { 310 MPI_Status *stat; 311 ierr = PetscMalloc((n_neigh-1)*sizeof(MPI_Status),&stat);CHKERRQ(ierr); 312 if (n_neigh-1) {ierr = MPI_Waitall(n_neigh-1,&(send_request[1]),stat);CHKERRQ(ierr);} 313 ierr = PetscFree(stat);CHKERRQ(ierr); 314 } 315 316 /* Free the memory for the MPI requests */ 317 ierr = PetscFree(send_request);CHKERRQ(ierr); 318 319 /* Free the memory for DZ_OUT */ 320 if (DZ_OUT) { 321 ierr = PetscFree(DZ_OUT[0]);CHKERRQ(ierr); 322 ierr = PetscFree(DZ_OUT);CHKERRQ(ierr); 323 } 324 325 { 326 PetscMPIInt size; 327 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)pc),&size);CHKERRQ(ierr); 328 /* Create the global coarse vectors (rhs and solution). */ 329 ierr = VecCreateMPI(PetscObjectComm((PetscObject)pc),1,size,&(pcnn->coarse_b));CHKERRQ(ierr); 330 ierr = VecDuplicate(pcnn->coarse_b,&(pcnn->coarse_x));CHKERRQ(ierr); 331 /* Create and set the global coarse AIJ matrix. */ 332 ierr = MatCreate(PetscObjectComm((PetscObject)pc),&(pcnn->coarse_mat));CHKERRQ(ierr); 333 ierr = MatSetSizes(pcnn->coarse_mat,1,1,size,size);CHKERRQ(ierr); 334 ierr = MatSetType(pcnn->coarse_mat,MATAIJ);CHKERRQ(ierr); 335 ierr = MatSeqAIJSetPreallocation(pcnn->coarse_mat,1,NULL);CHKERRQ(ierr); 336 ierr = MatMPIAIJSetPreallocation(pcnn->coarse_mat,1,NULL,1,NULL);CHKERRQ(ierr); 337 ierr = MatSetValues(pcnn->coarse_mat,n_neigh,neigh,n_neigh,neigh,mat,ADD_VALUES);CHKERRQ(ierr); 338 ierr = MatAssemblyBegin(pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 339 ierr = MatAssemblyEnd (pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 340 } 341 342 { 343 PetscMPIInt rank; 344 PetscScalar one = 1.0; 345 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)pc),&rank);CHKERRQ(ierr); 346 /* "Zero out" rows of not-purely-Neumann subdomains */ 347 if (pcis->pure_neumann) { /* does NOT zero the row; create an empty index set. The reason is that MatZeroRows() is collective. */ 348 ierr = MatZeroRows(pcnn->coarse_mat,0,NULL,one,0,0);CHKERRQ(ierr); 349 } else { /* here it DOES zero the row, since it's not a floating subdomain. */ 350 PetscInt row = (PetscInt) rank; 351 ierr = MatZeroRows(pcnn->coarse_mat,1,&row,one,0,0);CHKERRQ(ierr); 352 } 353 } 354 355 /* Create the coarse linear solver context */ 356 { 357 PC pc_ctx, inner_pc; 358 KSP inner_ksp; 359 360 ierr = KSPCreate(PetscObjectComm((PetscObject)pc),&pcnn->ksp_coarse);CHKERRQ(ierr); 361 ierr = PetscObjectIncrementTabLevel((PetscObject)pcnn->ksp_coarse,(PetscObject)pc,2);CHKERRQ(ierr); 362 ierr = KSPSetOperators(pcnn->ksp_coarse,pcnn->coarse_mat,pcnn->coarse_mat,SAME_PRECONDITIONER);CHKERRQ(ierr); 363 ierr = KSPGetPC(pcnn->ksp_coarse,&pc_ctx);CHKERRQ(ierr); 364 ierr = PCSetType(pc_ctx,PCREDUNDANT);CHKERRQ(ierr); 365 ierr = KSPSetType(pcnn->ksp_coarse,KSPPREONLY);CHKERRQ(ierr); 366 ierr = PCRedundantGetKSP(pc_ctx,&inner_ksp);CHKERRQ(ierr); 367 ierr = KSPGetPC(inner_ksp,&inner_pc);CHKERRQ(ierr); 368 ierr = PCSetType(inner_pc,PCLU);CHKERRQ(ierr); 369 ierr = KSPSetOptionsPrefix(pcnn->ksp_coarse,"nn_coarse_");CHKERRQ(ierr); 370 ierr = KSPSetFromOptions(pcnn->ksp_coarse);CHKERRQ(ierr); 371 /* the vectors in the following line are dummy arguments, just telling the KSP the vector size. Values are not used */ 372 ierr = KSPSetUp(pcnn->ksp_coarse);CHKERRQ(ierr); 373 } 374 375 /* Free the memory for mat */ 376 ierr = PetscFree(mat);CHKERRQ(ierr); 377 378 /* for DEBUGGING, save the coarse matrix to a file. */ 379 { 380 PetscBool flg = PETSC_FALSE; 381 ierr = PetscOptionsGetBool(NULL,"-pc_nn_save_coarse_matrix",&flg,NULL);CHKERRQ(ierr); 382 if (flg) { 383 PetscViewer viewer; 384 ierr = PetscViewerASCIIOpen(PETSC_COMM_WORLD,"coarse.m",&viewer);CHKERRQ(ierr); 385 ierr = PetscViewerSetFormat(viewer,PETSC_VIEWER_ASCII_MATLAB);CHKERRQ(ierr); 386 ierr = MatView(pcnn->coarse_mat,viewer);CHKERRQ(ierr); 387 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 388 } 389 } 390 391 /* Set the variable pcnn->factor_coarse_rhs. */ 392 pcnn->factor_coarse_rhs = (pcis->pure_neumann) ? 1.0 : 0.0; 393 394 /* See historical note 02, at the bottom of this file. */ 395 PetscFunctionReturn(0); 396 } 397 398 /* -------------------------------------------------------------------------- */ 399 /* 400 PCNNApplySchurToChunk - 401 402 Input parameters: 403 . pcnn 404 . n - size of chunk 405 . idx - indices of chunk 406 . chunk - values 407 408 Output parameters: 409 . array_N - result of Schur complement applied to chunk, scattered to big array 410 . vec1_B - result of Schur complement applied to chunk 411 . vec2_B - garbage (used as work space) 412 . vec1_D - garbage (used as work space) 413 . vec2_D - garbage (used as work space) 414 415 */ 416 #undef __FUNCT__ 417 #define __FUNCT__ "PCNNApplySchurToChunk" 418 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) 419 { 420 PetscErrorCode ierr; 421 PetscInt i; 422 PC_IS *pcis = (PC_IS*)(pc->data); 423 424 PetscFunctionBegin; 425 ierr = PetscMemzero((void*)array_N, pcis->n*sizeof(PetscScalar));CHKERRQ(ierr); 426 for (i=0; i<n; i++) array_N[idx[i]] = chunk[i]; 427 ierr = PCISScatterArrayNToVecB(array_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 428 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 429 ierr = PCISScatterArrayNToVecB(array_N,vec1_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 430 PetscFunctionReturn(0); 431 } 432 433 /* -------------------------------------------------------------------------- */ 434 /* 435 PCNNApplyInterfacePreconditioner - Apply the interface preconditioner, i.e., 436 the preconditioner for the Schur complement. 437 438 Input parameter: 439 . r - global vector of interior and interface nodes. The values on the interior nodes are NOT used. 440 441 Output parameters: 442 . z - global vector of interior and interface nodes. The values on the interface are the result of 443 the application of the interface preconditioner to the interface part of r. The values on the 444 interior nodes are garbage. 445 . work_N - array of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 446 . vec1_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 447 . vec2_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 448 . vec3_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 449 . vec1_D - vector of local interior nodes; returns garbage (used as work space) 450 . vec2_D - vector of local interior nodes; returns garbage (used as work space) 451 . vec1_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 452 . vec2_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 453 454 */ 455 #undef __FUNCT__ 456 #define __FUNCT__ "PCNNApplyInterfacePreconditioner" 457 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) 458 { 459 PetscErrorCode ierr; 460 PC_IS *pcis = (PC_IS*)(pc->data); 461 462 PetscFunctionBegin; 463 /* 464 First balancing step. 465 */ 466 { 467 PetscBool flg = PETSC_FALSE; 468 ierr = PetscOptionsGetBool(NULL,"-pc_nn_turn_off_first_balancing",&flg,NULL);CHKERRQ(ierr); 469 if (!flg) { 470 ierr = PCNNBalancing(pc,r,(Vec)0,z,vec1_B,vec2_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 471 } else { 472 ierr = VecCopy(r,z);CHKERRQ(ierr); 473 } 474 } 475 476 /* 477 Extract the local interface part of z and scale it by D 478 */ 479 ierr = VecScatterBegin(pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 480 ierr = VecScatterEnd (pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 481 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 482 483 /* Neumann Solver */ 484 ierr = PCISApplyInvSchur(pc,vec2_B,vec1_B,vec1_N,vec2_N);CHKERRQ(ierr); 485 486 /* 487 Second balancing step. 488 */ 489 { 490 PetscBool flg = PETSC_FALSE; 491 ierr = PetscOptionsGetBool(NULL,"-pc_turn_off_second_balancing",&flg,NULL);CHKERRQ(ierr); 492 if (!flg) { 493 ierr = PCNNBalancing(pc,r,vec1_B,z,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 494 } else { 495 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 496 ierr = VecSet(z,0.0);CHKERRQ(ierr); 497 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 498 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 499 } 500 } 501 PetscFunctionReturn(0); 502 } 503 504 /* -------------------------------------------------------------------------- */ 505 /* 506 PCNNBalancing - Computes z, as given in equations (15) and (16) (if the 507 input argument u is provided), or s, as given in equations 508 (12) and (13), if the input argument u is a null vector. 509 Notice that the input argument u plays the role of u_i in 510 equation (14). The equation numbers refer to [Man93]. 511 512 Input Parameters: 513 . pcnn - NN preconditioner context. 514 . r - MPI vector of all nodes (interior and interface). It's preserved. 515 . u - (Optional) sequential vector of local interface nodes. It's preserved UNLESS vec3_B is null. 516 517 Output Parameters: 518 . z - MPI vector of interior and interface nodes. Returns s or z (see description above). 519 . vec1_B - Sequential vector of local interface nodes. Workspace. 520 . vec2_B - Sequential vector of local interface nodes. Workspace. 521 . vec3_B - (Optional) sequential vector of local interface nodes. Workspace. 522 . vec1_D - Sequential vector of local interior nodes. Workspace. 523 . vec2_D - Sequential vector of local interior nodes. Workspace. 524 . work_N - Array of all local nodes (interior and interface). Workspace. 525 526 */ 527 #undef __FUNCT__ 528 #define __FUNCT__ "PCNNBalancing" 529 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) 530 { 531 PetscErrorCode ierr; 532 PetscInt k; 533 PetscScalar value; 534 PetscScalar *lambda; 535 PC_NN *pcnn = (PC_NN*)(pc->data); 536 PC_IS *pcis = (PC_IS*)(pc->data); 537 538 PetscFunctionBegin; 539 ierr = PetscLogEventBegin(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 540 if (u) { 541 if (!vec3_B) vec3_B = u; 542 ierr = VecPointwiseMult(vec1_B,pcis->D,u);CHKERRQ(ierr); 543 ierr = VecSet(z,0.0);CHKERRQ(ierr); 544 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 545 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 546 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 547 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 548 ierr = PCISApplySchur(pc,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 549 ierr = VecScale(vec3_B,-1.0);CHKERRQ(ierr); 550 ierr = VecCopy(r,z);CHKERRQ(ierr); 551 ierr = VecScatterBegin(pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 552 ierr = VecScatterEnd (pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 553 } else { 554 ierr = VecCopy(r,z);CHKERRQ(ierr); 555 } 556 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 557 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 558 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 559 for (k=0, value=0.0; k<pcis->n_shared[0]; k++) value += pcnn->DZ_IN[0][k] * work_N[pcis->shared[0][k]]; 560 value *= pcnn->factor_coarse_rhs; /* This factor is set in CreateCoarseMatrix(). */ 561 { 562 PetscMPIInt rank; 563 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)pc),&rank);CHKERRQ(ierr); 564 ierr = VecSetValue(pcnn->coarse_b,rank,value,INSERT_VALUES);CHKERRQ(ierr); 565 /* 566 Since we are only inserting local values (one value actually) we don't need to do the 567 reduction that tells us there is no data that needs to be moved. Hence we comment out these 568 ierr = VecAssemblyBegin(pcnn->coarse_b);CHKERRQ(ierr); 569 ierr = VecAssemblyEnd (pcnn->coarse_b);CHKERRQ(ierr); 570 */ 571 } 572 ierr = KSPSolve(pcnn->ksp_coarse,pcnn->coarse_b,pcnn->coarse_x);CHKERRQ(ierr); 573 if (!u) { ierr = VecScale(pcnn->coarse_x,-1.0);CHKERRQ(ierr); } 574 ierr = VecGetArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 575 for (k=0; k<pcis->n_shared[0]; k++) work_N[pcis->shared[0][k]] = *lambda * pcnn->DZ_IN[0][k]; 576 ierr = VecRestoreArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 577 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 578 ierr = VecSet(z,0.0);CHKERRQ(ierr); 579 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 580 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 581 if (!u) { 582 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 583 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 584 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 585 ierr = VecCopy(r,z);CHKERRQ(ierr); 586 } 587 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 588 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 589 ierr = PetscLogEventEnd(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 590 PetscFunctionReturn(0); 591 } 592 593 #undef __FUNCT__ 594 595 596 597 /* ------- E N D O F T H E C O D E ------- */ 598 /* */ 599 /* From now on, "footnotes" (or "historical notes"). */ 600 /* */ 601 /* ------------------------------------------------- */ 602 603 604 605 /* -------------------------------------------------------------------------- 606 Historical note 01 607 -------------------------------------------------------------------------- */ 608 /* 609 We considered the possibility of an alternative D_i that would still 610 provide a partition of unity (i.e., $ \sum_i N_i D_i N_i^T = I $). 611 The basic principle was still the pseudo-inverse of the counting 612 function; the difference was that we would not count subdomains 613 that do not contribute to the coarse space (i.e., not pure-Neumann 614 subdomains). 615 616 This turned out to be a bad idea: we would solve trivial Neumann 617 problems in the not pure-Neumann subdomains, since we would be scaling 618 the balanced residual by zero. 619 */ 620 621 622 623 624 /* -------------------------------------------------------------------------- 625 Historical note 02 626 -------------------------------------------------------------------------- */ 627 /* 628 We tried an alternative coarse problem, that would eliminate exactly a 629 constant error. Turned out not to improve the overall convergence. 630 */ 631 632 633