xref: /petsc/src/ksp/pc/impls/is/nn/nn.c (revision bebe2cf65d55febe21a5af8db2bd2e168caaa2e7)
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