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 EXTERN_C_BEGIN 172 #undef __FUNCT__ 173 #define __FUNCT__ "PCCreate_NN" 174 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 EXTERN_C_END 212 213 214 /* -------------------------------------------------------------------------- */ 215 /* 216 PCNNCreateCoarseMatrix - 217 */ 218 #undef __FUNCT__ 219 #define __FUNCT__ "PCNNCreateCoarseMatrix" 220 PetscErrorCode PCNNCreateCoarseMatrix (PC pc) 221 { 222 MPI_Request *send_request, *recv_request; 223 PetscErrorCode ierr; 224 PetscInt i, j, k; 225 PetscScalar* mat; /* Sub-matrix with this subdomain's contribution to the coarse matrix */ 226 PetscScalar** DZ_OUT; /* proc[k].DZ_OUT[i][] = bit of vector to be sent from processor k to processor i */ 227 228 /* aliasing some names */ 229 PC_IS* pcis = (PC_IS*)(pc->data); 230 PC_NN* pcnn = (PC_NN*)pc->data; 231 PetscInt n_neigh = pcis->n_neigh; 232 PetscInt* neigh = pcis->neigh; 233 PetscInt* n_shared = pcis->n_shared; 234 PetscInt** shared = pcis->shared; 235 PetscScalar** DZ_IN; /* Must be initialized after memory allocation. */ 236 237 PetscFunctionBegin; 238 /* Allocate memory for mat (the +1 is to handle the case n_neigh equal to zero) */ 239 ierr = PetscMalloc((n_neigh*n_neigh+1)*sizeof(PetscScalar),&mat);CHKERRQ(ierr); 240 241 /* Allocate memory for DZ */ 242 /* Notice that DZ_OUT[0] is allocated some space that is never used. */ 243 /* This is just in order to DZ_OUT and DZ_IN to have exactly the same form. */ 244 { 245 PetscInt size_of_Z = 0; 246 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&pcnn->DZ_IN);CHKERRQ(ierr); 247 DZ_IN = pcnn->DZ_IN; 248 ierr = PetscMalloc ((n_neigh+1)*sizeof(PetscScalar*),&DZ_OUT);CHKERRQ(ierr); 249 for (i=0; i<n_neigh; i++) { 250 size_of_Z += n_shared[i]; 251 } 252 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_IN[0]);CHKERRQ(ierr); 253 ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_OUT[0]);CHKERRQ(ierr); 254 } 255 for (i=1; i<n_neigh; i++) { 256 DZ_IN[i] = DZ_IN [i-1] + n_shared[i-1]; 257 DZ_OUT[i] = DZ_OUT[i-1] + n_shared[i-1]; 258 } 259 260 /* Set the values of DZ_OUT, in order to send this info to the neighbours */ 261 /* First, set the auxiliary array pcis->work_N. */ 262 ierr = PCISScatterArrayNToVecB(pcis->work_N,pcis->D,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 263 for (i=1; i<n_neigh; i++){ 264 for (j=0; j<n_shared[i]; j++) { 265 DZ_OUT[i][j] = pcis->work_N[shared[i][j]]; 266 } 267 } 268 269 /* Non-blocking send/receive the common-interface chunks of scaled nullspaces */ 270 /* Notice that send_request[] and recv_request[] could have one less element. */ 271 /* We make them longer to have request[i] corresponding to neigh[i]. */ 272 { 273 PetscMPIInt tag; 274 ierr = PetscObjectGetNewTag((PetscObject)pc,&tag);CHKERRQ(ierr); 275 ierr = PetscMalloc((2*(n_neigh)+1)*sizeof(MPI_Request),&send_request);CHKERRQ(ierr); 276 recv_request = send_request + (n_neigh); 277 for (i=1; i<n_neigh; i++) { 278 ierr = MPI_Isend((void*)(DZ_OUT[i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,((PetscObject)pc)->comm,&(send_request[i]));CHKERRQ(ierr); 279 ierr = MPI_Irecv((void*)(DZ_IN [i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,((PetscObject)pc)->comm,&(recv_request[i]));CHKERRQ(ierr); 280 } 281 } 282 283 /* Set DZ_IN[0][] (recall that neigh[0]==rank, always) */ 284 for(j=0; j<n_shared[0]; j++) { 285 DZ_IN[0][j] = pcis->work_N[shared[0][j]]; 286 } 287 288 /* Start computing with local D*Z while communication goes on. */ 289 /* Apply Schur complement. The result is "stored" in vec (more */ 290 /* precisely, vec points to the result, stored in pc_nn->vec1_B) */ 291 /* and also scattered to pcnn->work_N. */ 292 ierr = PCNNApplySchurToChunk(pc,n_shared[0],shared[0],DZ_IN[0],pcis->work_N,pcis->vec1_B, 293 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 294 295 /* Compute the first column, while completing the receiving. */ 296 for (i=0; i<n_neigh; i++) { 297 MPI_Status stat; 298 PetscMPIInt ind=0; 299 if (i>0) { ierr = MPI_Waitany(n_neigh-1,recv_request+1,&ind,&stat);CHKERRQ(ierr); ind++;} 300 mat[ind*n_neigh+0] = 0.0; 301 for (k=0; k<n_shared[ind]; k++) { 302 mat[ind*n_neigh+0] += DZ_IN[ind][k] * pcis->work_N[shared[ind][k]]; 303 } 304 } 305 306 /* Compute the remaining of the columns */ 307 for (j=1; j<n_neigh; j++) { 308 ierr = PCNNApplySchurToChunk(pc,n_shared[j],shared[j],DZ_IN[j],pcis->work_N,pcis->vec1_B, 309 pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr); 310 for (i=0; i<n_neigh; i++) { 311 mat[i*n_neigh+j] = 0.0; 312 for (k=0; k<n_shared[i]; k++) { 313 mat[i*n_neigh+j] += DZ_IN[i][k] * pcis->work_N[shared[i][k]]; 314 } 315 } 316 } 317 318 /* Complete the sending. */ 319 if (n_neigh>1) { 320 MPI_Status *stat; 321 ierr = PetscMalloc((n_neigh-1)*sizeof(MPI_Status),&stat);CHKERRQ(ierr); 322 if (n_neigh-1) {ierr = MPI_Waitall(n_neigh-1,&(send_request[1]),stat);CHKERRQ(ierr);} 323 ierr = PetscFree(stat);CHKERRQ(ierr); 324 } 325 326 /* Free the memory for the MPI requests */ 327 ierr = PetscFree(send_request);CHKERRQ(ierr); 328 329 /* Free the memory for DZ_OUT */ 330 if (DZ_OUT) { 331 ierr = PetscFree(DZ_OUT[0]);CHKERRQ(ierr); 332 ierr = PetscFree(DZ_OUT);CHKERRQ(ierr); 333 } 334 335 { 336 PetscMPIInt size; 337 ierr = MPI_Comm_size(((PetscObject)pc)->comm,&size);CHKERRQ(ierr); 338 /* Create the global coarse vectors (rhs and solution). */ 339 ierr = VecCreateMPI(((PetscObject)pc)->comm,1,size,&(pcnn->coarse_b));CHKERRQ(ierr); 340 ierr = VecDuplicate(pcnn->coarse_b,&(pcnn->coarse_x));CHKERRQ(ierr); 341 /* Create and set the global coarse AIJ matrix. */ 342 ierr = MatCreate(((PetscObject)pc)->comm,&(pcnn->coarse_mat));CHKERRQ(ierr); 343 ierr = MatSetSizes(pcnn->coarse_mat,1,1,size,size);CHKERRQ(ierr); 344 ierr = MatSetType(pcnn->coarse_mat,MATAIJ);CHKERRQ(ierr); 345 ierr = MatSeqAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL);CHKERRQ(ierr); 346 ierr = MatMPIAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL,1,PETSC_NULL);CHKERRQ(ierr); 347 ierr = MatSetValues(pcnn->coarse_mat,n_neigh,neigh,n_neigh,neigh,mat,ADD_VALUES);CHKERRQ(ierr); 348 ierr = MatAssemblyBegin(pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 349 ierr = MatAssemblyEnd (pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 350 } 351 352 { 353 PetscMPIInt rank; 354 PetscScalar one = 1.0; 355 ierr = MPI_Comm_rank(((PetscObject)pc)->comm,&rank);CHKERRQ(ierr); 356 /* "Zero out" rows of not-purely-Neumann subdomains */ 357 if (pcis->pure_neumann) { /* does NOT zero the row; create an empty index set. The reason is that MatZeroRows() is collective. */ 358 ierr = MatZeroRows(pcnn->coarse_mat,0,PETSC_NULL,one,0,0);CHKERRQ(ierr); 359 } else { /* here it DOES zero the row, since it's not a floating subdomain. */ 360 PetscInt row = (PetscInt) rank; 361 ierr = MatZeroRows(pcnn->coarse_mat,1,&row,one,0,0);CHKERRQ(ierr); 362 } 363 } 364 365 /* Create the coarse linear solver context */ 366 { 367 PC pc_ctx, inner_pc; 368 KSP inner_ksp; 369 370 ierr = KSPCreate(((PetscObject)pc)->comm,&pcnn->ksp_coarse);CHKERRQ(ierr); 371 ierr = PetscObjectIncrementTabLevel((PetscObject)pcnn->ksp_coarse,(PetscObject)pc,2);CHKERRQ(ierr); 372 ierr = KSPSetOperators(pcnn->ksp_coarse,pcnn->coarse_mat,pcnn->coarse_mat,SAME_PRECONDITIONER);CHKERRQ(ierr); 373 ierr = KSPGetPC(pcnn->ksp_coarse,&pc_ctx);CHKERRQ(ierr); 374 ierr = PCSetType(pc_ctx,PCREDUNDANT);CHKERRQ(ierr); 375 ierr = KSPSetType(pcnn->ksp_coarse,KSPPREONLY);CHKERRQ(ierr); 376 ierr = PCRedundantGetKSP(pc_ctx,&inner_ksp);CHKERRQ(ierr); 377 ierr = KSPGetPC(inner_ksp,&inner_pc);CHKERRQ(ierr); 378 ierr = PCSetType(inner_pc,PCLU);CHKERRQ(ierr); 379 ierr = KSPSetOptionsPrefix(pcnn->ksp_coarse,"nn_coarse_");CHKERRQ(ierr); 380 ierr = KSPSetFromOptions(pcnn->ksp_coarse);CHKERRQ(ierr); 381 /* the vectors in the following line are dummy arguments, just telling the KSP the vector size. Values are not used */ 382 ierr = KSPSetUp(pcnn->ksp_coarse);CHKERRQ(ierr); 383 } 384 385 /* Free the memory for mat */ 386 ierr = PetscFree(mat);CHKERRQ(ierr); 387 388 /* for DEBUGGING, save the coarse matrix to a file. */ 389 { 390 PetscBool flg = PETSC_FALSE; 391 ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_nn_save_coarse_matrix",&flg,PETSC_NULL);CHKERRQ(ierr); 392 if (flg) { 393 PetscViewer viewer; 394 ierr = PetscViewerASCIIOpen(PETSC_COMM_WORLD,"coarse.m",&viewer);CHKERRQ(ierr); 395 ierr = PetscViewerSetFormat(viewer,PETSC_VIEWER_ASCII_MATLAB);CHKERRQ(ierr); 396 ierr = MatView(pcnn->coarse_mat,viewer);CHKERRQ(ierr); 397 ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr); 398 } 399 } 400 401 /* Set the variable pcnn->factor_coarse_rhs. */ 402 pcnn->factor_coarse_rhs = (pcis->pure_neumann) ? 1.0 : 0.0; 403 404 /* See historical note 02, at the bottom of this file. */ 405 PetscFunctionReturn(0); 406 } 407 408 /* -------------------------------------------------------------------------- */ 409 /* 410 PCNNApplySchurToChunk - 411 412 Input parameters: 413 . pcnn 414 . n - size of chunk 415 . idx - indices of chunk 416 . chunk - values 417 418 Output parameters: 419 . array_N - result of Schur complement applied to chunk, scattered to big array 420 . vec1_B - result of Schur complement applied to chunk 421 . vec2_B - garbage (used as work space) 422 . vec1_D - garbage (used as work space) 423 . vec2_D - garbage (used as work space) 424 425 */ 426 #undef __FUNCT__ 427 #define __FUNCT__ "PCNNApplySchurToChunk" 428 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) 429 { 430 PetscErrorCode ierr; 431 PetscInt i; 432 PC_IS *pcis = (PC_IS*)(pc->data); 433 434 PetscFunctionBegin; 435 ierr = PetscMemzero((void*)array_N, pcis->n*sizeof(PetscScalar));CHKERRQ(ierr); 436 for (i=0; i<n; i++) { array_N[idx[i]] = chunk[i]; } 437 ierr = PCISScatterArrayNToVecB(array_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 438 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 439 ierr = PCISScatterArrayNToVecB(array_N,vec1_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 440 PetscFunctionReturn(0); 441 } 442 443 /* -------------------------------------------------------------------------- */ 444 /* 445 PCNNApplyInterfacePreconditioner - Apply the interface preconditioner, i.e., 446 the preconditioner for the Schur complement. 447 448 Input parameter: 449 . r - global vector of interior and interface nodes. The values on the interior nodes are NOT used. 450 451 Output parameters: 452 . z - global vector of interior and interface nodes. The values on the interface are the result of 453 the application of the interface preconditioner to the interface part of r. The values on the 454 interior nodes are garbage. 455 . work_N - array of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 456 . vec1_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 457 . vec2_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 458 . vec3_B - vector of local interface nodes (including ghosts); returns garbage (used as work space) 459 . vec1_D - vector of local interior nodes; returns garbage (used as work space) 460 . vec2_D - vector of local interior nodes; returns garbage (used as work space) 461 . vec1_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 462 . vec2_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space) 463 464 */ 465 #undef __FUNCT__ 466 #define __FUNCT__ "PCNNApplyInterfacePreconditioner" 467 PetscErrorCode PCNNApplyInterfacePreconditioner (PC pc, Vec r, Vec z, PetscScalar* work_N, Vec vec1_B, Vec vec2_B, Vec vec3_B, Vec vec1_D, 468 Vec vec2_D, Vec vec1_N, Vec vec2_N) 469 { 470 PetscErrorCode ierr; 471 PC_IS* pcis = (PC_IS*)(pc->data); 472 473 PetscFunctionBegin; 474 /* 475 First balancing step. 476 */ 477 { 478 PetscBool flg = PETSC_FALSE; 479 ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_nn_turn_off_first_balancing",&flg,PETSC_NULL);CHKERRQ(ierr); 480 if (!flg) { 481 ierr = PCNNBalancing(pc,r,(Vec)0,z,vec1_B,vec2_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 482 } else { 483 ierr = VecCopy(r,z);CHKERRQ(ierr); 484 } 485 } 486 487 /* 488 Extract the local interface part of z and scale it by D 489 */ 490 ierr = VecScatterBegin(pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 491 ierr = VecScatterEnd (pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 492 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 493 494 /* Neumann Solver */ 495 ierr = PCISApplyInvSchur(pc,vec2_B,vec1_B,vec1_N,vec2_N);CHKERRQ(ierr); 496 497 /* 498 Second balancing step. 499 */ 500 { 501 PetscBool flg = PETSC_FALSE; 502 ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_turn_off_second_balancing",&flg,PETSC_NULL);CHKERRQ(ierr); 503 if (!flg) { 504 ierr = PCNNBalancing(pc,r,vec1_B,z,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr); 505 } else { 506 ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr); 507 ierr = VecSet(z,0.0);CHKERRQ(ierr); 508 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 509 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 510 } 511 } 512 PetscFunctionReturn(0); 513 } 514 515 /* -------------------------------------------------------------------------- */ 516 /* 517 PCNNBalancing - Computes z, as given in equations (15) and (16) (if the 518 input argument u is provided), or s, as given in equations 519 (12) and (13), if the input argument u is a null vector. 520 Notice that the input argument u plays the role of u_i in 521 equation (14). The equation numbers refer to [Man93]. 522 523 Input Parameters: 524 . pcnn - NN preconditioner context. 525 . r - MPI vector of all nodes (interior and interface). It's preserved. 526 . u - (Optional) sequential vector of local interface nodes. It's preserved UNLESS vec3_B is null. 527 528 Output Parameters: 529 . z - MPI vector of interior and interface nodes. Returns s or z (see description above). 530 . vec1_B - Sequential vector of local interface nodes. Workspace. 531 . vec2_B - Sequential vector of local interface nodes. Workspace. 532 . vec3_B - (Optional) sequential vector of local interface nodes. Workspace. 533 . vec1_D - Sequential vector of local interior nodes. Workspace. 534 . vec2_D - Sequential vector of local interior nodes. Workspace. 535 . work_N - Array of all local nodes (interior and interface). Workspace. 536 537 */ 538 #undef __FUNCT__ 539 #define __FUNCT__ "PCNNBalancing" 540 PetscErrorCode PCNNBalancing (PC pc, Vec r, Vec u, Vec z, Vec vec1_B, Vec vec2_B, Vec vec3_B, 541 Vec vec1_D, Vec vec2_D, PetscScalar *work_N) 542 { 543 PetscErrorCode ierr; 544 PetscInt k; 545 PetscScalar value; 546 PetscScalar* lambda; 547 PC_NN* pcnn = (PC_NN*)(pc->data); 548 PC_IS* pcis = (PC_IS*)(pc->data); 549 550 PetscFunctionBegin; 551 ierr = PetscLogEventBegin(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 552 if (u) { 553 if (!vec3_B) { vec3_B = u; } 554 ierr = VecPointwiseMult(vec1_B,pcis->D,u);CHKERRQ(ierr); 555 ierr = VecSet(z,0.0);CHKERRQ(ierr); 556 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 557 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 558 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 559 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 560 ierr = PCISApplySchur(pc,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 561 ierr = VecScale(vec3_B,-1.0);CHKERRQ(ierr); 562 ierr = VecCopy(r,z);CHKERRQ(ierr); 563 ierr = VecScatterBegin(pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 564 ierr = VecScatterEnd (pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 565 } else { 566 ierr = VecCopy(r,z);CHKERRQ(ierr); 567 } 568 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 569 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 570 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr); 571 for (k=0, value=0.0; k<pcis->n_shared[0]; k++) { value += pcnn->DZ_IN[0][k] * work_N[pcis->shared[0][k]]; } 572 value *= pcnn->factor_coarse_rhs; /* This factor is set in CreateCoarseMatrix(). */ 573 { 574 PetscMPIInt rank; 575 ierr = MPI_Comm_rank(((PetscObject)pc)->comm,&rank);CHKERRQ(ierr); 576 ierr = VecSetValue(pcnn->coarse_b,rank,value,INSERT_VALUES);CHKERRQ(ierr); 577 /* 578 Since we are only inserting local values (one value actually) we don't need to do the 579 reduction that tells us there is no data that needs to be moved. Hence we comment out these 580 ierr = VecAssemblyBegin(pcnn->coarse_b);CHKERRQ(ierr); 581 ierr = VecAssemblyEnd (pcnn->coarse_b);CHKERRQ(ierr); 582 */ 583 } 584 ierr = KSPSolve(pcnn->ksp_coarse,pcnn->coarse_b,pcnn->coarse_x);CHKERRQ(ierr); 585 if (!u) { ierr = VecScale(pcnn->coarse_x,-1.0);CHKERRQ(ierr); } 586 ierr = VecGetArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 587 for (k=0; k<pcis->n_shared[0]; k++) { work_N[pcis->shared[0][k]] = *lambda * pcnn->DZ_IN[0][k]; } 588 ierr = VecRestoreArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr); 589 ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr); 590 ierr = VecSet(z,0.0);CHKERRQ(ierr); 591 ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 592 ierr = VecScatterEnd (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 593 if (!u) { 594 ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 595 ierr = VecScatterEnd (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 596 ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr); 597 ierr = VecCopy(r,z);CHKERRQ(ierr); 598 } 599 ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 600 ierr = VecScatterEnd (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 601 ierr = PetscLogEventEnd(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr); 602 PetscFunctionReturn(0); 603 } 604 605 #undef __FUNCT__ 606 607 608 609 /* ------- E N D O F T H E C O D E ------- */ 610 /* */ 611 /* From now on, "footnotes" (or "historical notes"). */ 612 /* */ 613 /* ------------------------------------------------- */ 614 615 616 617 /* -------------------------------------------------------------------------- 618 Historical note 01 619 -------------------------------------------------------------------------- */ 620 /* 621 We considered the possibility of an alternative D_i that would still 622 provide a partition of unity (i.e., $ \sum_i N_i D_i N_i^T = I $). 623 The basic principle was still the pseudo-inverse of the counting 624 function; the difference was that we would not count subdomains 625 that do not contribute to the coarse space (i.e., not pure-Neumann 626 subdomains). 627 628 This turned out to be a bad idea: we would solve trivial Neumann 629 problems in the not pure-Neumann subdomains, since we would be scaling 630 the balanced residual by zero. 631 */ 632 633 634 635 636 /* -------------------------------------------------------------------------- 637 Historical note 02 638 -------------------------------------------------------------------------- */ 639 /* 640 We tried an alternative coarse problem, that would eliminate exactly a 641 constant error. Turned out not to improve the overall convergence. 642 */ 643 644 645