xref: /petsc/src/ksp/pc/impls/is/nn/nn.c (revision 2205254efee3a00a594e5e2a3a70f74dcb40bc03)
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++) size_of_Z += n_shared[i];
250     ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_IN[0]);CHKERRQ(ierr);
251     ierr = PetscMalloc ((size_of_Z+1)*sizeof(PetscScalar),&DZ_OUT[0]);CHKERRQ(ierr);
252   }
253   for (i=1; i<n_neigh; i++) {
254     DZ_IN[i]  = DZ_IN [i-1] + n_shared[i-1];
255     DZ_OUT[i] = DZ_OUT[i-1] + n_shared[i-1];
256   }
257 
258   /* Set the values of DZ_OUT, in order to send this info to the neighbours */
259   /* First, set the auxiliary array pcis->work_N. */
260   ierr = PCISScatterArrayNToVecB(pcis->work_N,pcis->D,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr);
261   for (i=1; i<n_neigh; i++) {
262     for (j=0; j<n_shared[i]; j++) {
263       DZ_OUT[i][j] = pcis->work_N[shared[i][j]];
264     }
265   }
266 
267   /* Non-blocking send/receive the common-interface chunks of scaled nullspaces */
268   /* Notice that send_request[] and recv_request[] could have one less element. */
269   /* We make them longer to have request[i] corresponding to neigh[i].          */
270   {
271     PetscMPIInt tag;
272     ierr         = PetscObjectGetNewTag((PetscObject)pc,&tag);CHKERRQ(ierr);
273     ierr         = PetscMalloc((2*(n_neigh)+1)*sizeof(MPI_Request),&send_request);CHKERRQ(ierr);
274     recv_request = send_request + (n_neigh);
275     for (i=1; i<n_neigh; i++) {
276       ierr = MPI_Isend((void*)(DZ_OUT[i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,((PetscObject)pc)->comm,&(send_request[i]));CHKERRQ(ierr);
277       ierr = MPI_Irecv((void*)(DZ_IN [i]),n_shared[i],MPIU_SCALAR,neigh[i],tag,((PetscObject)pc)->comm,&(recv_request[i]));CHKERRQ(ierr);
278     }
279   }
280 
281   /* Set DZ_IN[0][] (recall that neigh[0]==rank, always) */
282   for (j=0; j<n_shared[0]; j++) DZ_IN[0][j] = pcis->work_N[shared[0][j]];
283 
284   /* Start computing with local D*Z while communication goes on.    */
285   /* Apply Schur complement. The result is "stored" in vec (more    */
286   /* precisely, vec points to the result, stored in pc_nn->vec1_B)  */
287   /* and also scattered to pcnn->work_N.                            */
288   ierr = PCNNApplySchurToChunk(pc,n_shared[0],shared[0],DZ_IN[0],pcis->work_N,pcis->vec1_B,
289                                pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr);
290 
291   /* Compute the first column, while completing the receiving. */
292   for (i=0; i<n_neigh; i++) {
293     MPI_Status  stat;
294     PetscMPIInt ind=0;
295     if (i>0) { ierr = MPI_Waitany(n_neigh-1,recv_request+1,&ind,&stat);CHKERRQ(ierr); ind++;}
296     mat[ind*n_neigh+0] = 0.0;
297     for (k=0; k<n_shared[ind]; k++) mat[ind*n_neigh+0] += DZ_IN[ind][k] * pcis->work_N[shared[ind][k]];
298   }
299 
300   /* Compute the remaining of the columns */
301   for (j=1; j<n_neigh; j++) {
302     ierr = PCNNApplySchurToChunk(pc,n_shared[j],shared[j],DZ_IN[j],pcis->work_N,pcis->vec1_B,
303                                  pcis->vec2_B,pcis->vec1_D,pcis->vec2_D);CHKERRQ(ierr);
304     for (i=0; i<n_neigh; i++) {
305       mat[i*n_neigh+j] = 0.0;
306       for (k=0; k<n_shared[i]; k++) mat[i*n_neigh+j] += DZ_IN[i][k] * pcis->work_N[shared[i][k]];
307     }
308   }
309 
310   /* Complete the sending. */
311   if (n_neigh>1) {
312     MPI_Status *stat;
313     ierr = PetscMalloc((n_neigh-1)*sizeof(MPI_Status),&stat);CHKERRQ(ierr);
314     if (n_neigh-1) {ierr = MPI_Waitall(n_neigh-1,&(send_request[1]),stat);CHKERRQ(ierr);}
315     ierr = PetscFree(stat);CHKERRQ(ierr);
316   }
317 
318   /* Free the memory for the MPI requests */
319   ierr = PetscFree(send_request);CHKERRQ(ierr);
320 
321   /* Free the memory for DZ_OUT */
322   if (DZ_OUT) {
323     ierr = PetscFree(DZ_OUT[0]);CHKERRQ(ierr);
324     ierr = PetscFree(DZ_OUT);CHKERRQ(ierr);
325   }
326 
327   {
328     PetscMPIInt size;
329     ierr = MPI_Comm_size(((PetscObject)pc)->comm,&size);CHKERRQ(ierr);
330     /* Create the global coarse vectors (rhs and solution). */
331     ierr = VecCreateMPI(((PetscObject)pc)->comm,1,size,&(pcnn->coarse_b));CHKERRQ(ierr);
332     ierr = VecDuplicate(pcnn->coarse_b,&(pcnn->coarse_x));CHKERRQ(ierr);
333     /* Create and set the global coarse AIJ matrix. */
334     ierr = MatCreate(((PetscObject)pc)->comm,&(pcnn->coarse_mat));CHKERRQ(ierr);
335     ierr = MatSetSizes(pcnn->coarse_mat,1,1,size,size);CHKERRQ(ierr);
336     ierr = MatSetType(pcnn->coarse_mat,MATAIJ);CHKERRQ(ierr);
337     ierr = MatSeqAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL);CHKERRQ(ierr);
338     ierr = MatMPIAIJSetPreallocation(pcnn->coarse_mat,1,PETSC_NULL,1,PETSC_NULL);CHKERRQ(ierr);
339     ierr = MatSetValues(pcnn->coarse_mat,n_neigh,neigh,n_neigh,neigh,mat,ADD_VALUES);CHKERRQ(ierr);
340     ierr = MatAssemblyBegin(pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
341     ierr = MatAssemblyEnd  (pcnn->coarse_mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
342   }
343 
344   {
345     PetscMPIInt rank;
346     PetscScalar one = 1.0;
347     ierr = MPI_Comm_rank(((PetscObject)pc)->comm,&rank);CHKERRQ(ierr);
348     /* "Zero out" rows of not-purely-Neumann subdomains */
349     if (pcis->pure_neumann) {  /* does NOT zero the row; create an empty index set. The reason is that MatZeroRows() is collective. */
350       ierr = MatZeroRows(pcnn->coarse_mat,0,PETSC_NULL,one,0,0);CHKERRQ(ierr);
351     } else { /* here it DOES zero the row, since it's not a floating subdomain. */
352       PetscInt row = (PetscInt) rank;
353       ierr = MatZeroRows(pcnn->coarse_mat,1,&row,one,0,0);CHKERRQ(ierr);
354     }
355   }
356 
357   /* Create the coarse linear solver context */
358   {
359     PC  pc_ctx, inner_pc;
360     KSP inner_ksp;
361 
362     ierr = KSPCreate(((PetscObject)pc)->comm,&pcnn->ksp_coarse);CHKERRQ(ierr);
363     ierr = PetscObjectIncrementTabLevel((PetscObject)pcnn->ksp_coarse,(PetscObject)pc,2);CHKERRQ(ierr);
364     ierr = KSPSetOperators(pcnn->ksp_coarse,pcnn->coarse_mat,pcnn->coarse_mat,SAME_PRECONDITIONER);CHKERRQ(ierr);
365     ierr = KSPGetPC(pcnn->ksp_coarse,&pc_ctx);CHKERRQ(ierr);
366     ierr = PCSetType(pc_ctx,PCREDUNDANT);CHKERRQ(ierr);
367     ierr = KSPSetType(pcnn->ksp_coarse,KSPPREONLY);CHKERRQ(ierr);
368     ierr = PCRedundantGetKSP(pc_ctx,&inner_ksp);CHKERRQ(ierr);
369     ierr = KSPGetPC(inner_ksp,&inner_pc);CHKERRQ(ierr);
370     ierr = PCSetType(inner_pc,PCLU);CHKERRQ(ierr);
371     ierr = KSPSetOptionsPrefix(pcnn->ksp_coarse,"nn_coarse_");CHKERRQ(ierr);
372     ierr = KSPSetFromOptions(pcnn->ksp_coarse);CHKERRQ(ierr);
373     /* the vectors in the following line are dummy arguments, just telling the KSP the vector size. Values are not used */
374     ierr = KSPSetUp(pcnn->ksp_coarse);CHKERRQ(ierr);
375   }
376 
377   /* Free the memory for mat */
378   ierr = PetscFree(mat);CHKERRQ(ierr);
379 
380   /* for DEBUGGING, save the coarse matrix to a file. */
381   {
382     PetscBool flg = PETSC_FALSE;
383     ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_nn_save_coarse_matrix",&flg,PETSC_NULL);CHKERRQ(ierr);
384     if (flg) {
385       PetscViewer viewer;
386       ierr = PetscViewerASCIIOpen(PETSC_COMM_WORLD,"coarse.m",&viewer);CHKERRQ(ierr);
387       ierr = PetscViewerSetFormat(viewer,PETSC_VIEWER_ASCII_MATLAB);CHKERRQ(ierr);
388       ierr = MatView(pcnn->coarse_mat,viewer);CHKERRQ(ierr);
389       ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
390     }
391   }
392 
393   /*  Set the variable pcnn->factor_coarse_rhs. */
394   pcnn->factor_coarse_rhs = (pcis->pure_neumann) ? 1.0 : 0.0;
395 
396   /* See historical note 02, at the bottom of this file. */
397   PetscFunctionReturn(0);
398 }
399 
400 /* -------------------------------------------------------------------------- */
401 /*
402    PCNNApplySchurToChunk -
403 
404    Input parameters:
405 .  pcnn
406 .  n - size of chunk
407 .  idx - indices of chunk
408 .  chunk - values
409 
410    Output parameters:
411 .  array_N - result of Schur complement applied to chunk, scattered to big array
412 .  vec1_B  - result of Schur complement applied to chunk
413 .  vec2_B  - garbage (used as work space)
414 .  vec1_D  - garbage (used as work space)
415 .  vec2_D  - garbage (used as work space)
416 
417 */
418 #undef __FUNCT__
419 #define __FUNCT__ "PCNNApplySchurToChunk"
420 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)
421 {
422   PetscErrorCode ierr;
423   PetscInt       i;
424   PC_IS          *pcis = (PC_IS*)(pc->data);
425 
426   PetscFunctionBegin;
427   ierr = PetscMemzero((void*)array_N, pcis->n*sizeof(PetscScalar));CHKERRQ(ierr);
428   for (i=0; i<n; i++) array_N[idx[i]] = chunk[i];
429   ierr = PCISScatterArrayNToVecB(array_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr);
430   ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr);
431   ierr = PCISScatterArrayNToVecB(array_N,vec1_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr);
432   PetscFunctionReturn(0);
433 }
434 
435 /* -------------------------------------------------------------------------- */
436 /*
437    PCNNApplyInterfacePreconditioner - Apply the interface preconditioner, i.e.,
438                                       the preconditioner for the Schur complement.
439 
440    Input parameter:
441 .  r - global vector of interior and interface nodes. The values on the interior nodes are NOT used.
442 
443    Output parameters:
444 .  z - global vector of interior and interface nodes. The values on the interface are the result of
445        the application of the interface preconditioner to the interface part of r. The values on the
446        interior nodes are garbage.
447 .  work_N - array of local nodes (interior and interface, including ghosts); returns garbage (used as work space)
448 .  vec1_B - vector of local interface nodes (including ghosts); returns garbage (used as work space)
449 .  vec2_B - vector of local interface nodes (including ghosts); returns garbage (used as work space)
450 .  vec3_B - vector of local interface nodes (including ghosts); returns garbage (used as work space)
451 .  vec1_D - vector of local interior nodes; returns garbage (used as work space)
452 .  vec2_D - vector of local interior nodes; returns garbage (used as work space)
453 .  vec1_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space)
454 .  vec2_N - vector of local nodes (interior and interface, including ghosts); returns garbage (used as work space)
455 
456 */
457 #undef __FUNCT__
458 #define __FUNCT__ "PCNNApplyInterfacePreconditioner"
459 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)
460 {
461   PetscErrorCode ierr;
462   PC_IS          *pcis = (PC_IS*)(pc->data);
463 
464   PetscFunctionBegin;
465   /*
466     First balancing step.
467   */
468   {
469     PetscBool flg = PETSC_FALSE;
470     ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_nn_turn_off_first_balancing",&flg,PETSC_NULL);CHKERRQ(ierr);
471     if (!flg) {
472       ierr = PCNNBalancing(pc,r,(Vec)0,z,vec1_B,vec2_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr);
473     } else {
474       ierr = VecCopy(r,z);CHKERRQ(ierr);
475     }
476   }
477 
478   /*
479     Extract the local interface part of z and scale it by D
480   */
481   ierr = VecScatterBegin(pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
482   ierr = VecScatterEnd  (pcis->global_to_B,z,vec1_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
483   ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr);
484 
485   /* Neumann Solver */
486   ierr = PCISApplyInvSchur(pc,vec2_B,vec1_B,vec1_N,vec2_N);CHKERRQ(ierr);
487 
488   /*
489     Second balancing step.
490   */
491   {
492     PetscBool flg = PETSC_FALSE;
493     ierr = PetscOptionsGetBool(PETSC_NULL,"-pc_turn_off_second_balancing",&flg,PETSC_NULL);CHKERRQ(ierr);
494     if (!flg) {
495       ierr = PCNNBalancing(pc,r,vec1_B,z,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D,work_N);CHKERRQ(ierr);
496     } else {
497       ierr = VecPointwiseMult(vec2_B,pcis->D,vec1_B);CHKERRQ(ierr);
498       ierr = VecSet(z,0.0);CHKERRQ(ierr);
499       ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
500       ierr = VecScatterEnd  (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
501     }
502   }
503   PetscFunctionReturn(0);
504 }
505 
506 /* -------------------------------------------------------------------------- */
507 /*
508    PCNNBalancing - Computes z, as given in equations (15) and (16) (if the
509                    input argument u is provided), or s, as given in equations
510                    (12) and (13), if the input argument u is a null vector.
511                    Notice that the input argument u plays the role of u_i in
512                    equation (14). The equation numbers refer to [Man93].
513 
514    Input Parameters:
515 .  pcnn - NN preconditioner context.
516 .  r - MPI vector of all nodes (interior and interface). It's preserved.
517 .  u - (Optional) sequential vector of local interface nodes. It's preserved UNLESS vec3_B is null.
518 
519    Output Parameters:
520 .  z - MPI vector of interior and interface nodes. Returns s or z (see description above).
521 .  vec1_B - Sequential vector of local interface nodes. Workspace.
522 .  vec2_B - Sequential vector of local interface nodes. Workspace.
523 .  vec3_B - (Optional) sequential vector of local interface nodes. Workspace.
524 .  vec1_D - Sequential vector of local interior nodes. Workspace.
525 .  vec2_D - Sequential vector of local interior nodes. Workspace.
526 .  work_N - Array of all local nodes (interior and interface). Workspace.
527 
528 */
529 #undef __FUNCT__
530 #define __FUNCT__ "PCNNBalancing"
531 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)
532 {
533   PetscErrorCode ierr;
534   PetscInt       k;
535   PetscScalar    value;
536   PetscScalar    *lambda;
537   PC_NN          *pcnn = (PC_NN*)(pc->data);
538   PC_IS          *pcis = (PC_IS*)(pc->data);
539 
540   PetscFunctionBegin;
541   ierr = PetscLogEventBegin(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr);
542   if (u) {
543     if (!vec3_B) vec3_B = u;
544     ierr = VecPointwiseMult(vec1_B,pcis->D,u);CHKERRQ(ierr);
545     ierr = VecSet(z,0.0);CHKERRQ(ierr);
546     ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
547     ierr = VecScatterEnd  (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
548     ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
549     ierr = VecScatterEnd  (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
550     ierr = PCISApplySchur(pc,vec2_B,vec3_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr);
551     ierr = VecScale(vec3_B,-1.0);CHKERRQ(ierr);
552     ierr = VecCopy(r,z);CHKERRQ(ierr);
553     ierr = VecScatterBegin(pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
554     ierr = VecScatterEnd  (pcis->global_to_B,vec3_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
555   } else {
556     ierr = VecCopy(r,z);CHKERRQ(ierr);
557   }
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 = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_REVERSE,pc);CHKERRQ(ierr);
561   for (k=0, value=0.0; k<pcis->n_shared[0]; k++) value += pcnn->DZ_IN[0][k] * work_N[pcis->shared[0][k]];
562   value *= pcnn->factor_coarse_rhs;  /* This factor is set in CreateCoarseMatrix(). */
563   {
564     PetscMPIInt rank;
565     ierr = MPI_Comm_rank(((PetscObject)pc)->comm,&rank);CHKERRQ(ierr);
566     ierr = VecSetValue(pcnn->coarse_b,rank,value,INSERT_VALUES);CHKERRQ(ierr);
567     /*
568        Since we are only inserting local values (one value actually) we don't need to do the
569        reduction that tells us there is no data that needs to be moved. Hence we comment out these
570        ierr = VecAssemblyBegin(pcnn->coarse_b);CHKERRQ(ierr);
571        ierr = VecAssemblyEnd  (pcnn->coarse_b);CHKERRQ(ierr);
572     */
573   }
574   ierr = KSPSolve(pcnn->ksp_coarse,pcnn->coarse_b,pcnn->coarse_x);CHKERRQ(ierr);
575   if (!u) { ierr = VecScale(pcnn->coarse_x,-1.0);CHKERRQ(ierr); }
576   ierr = VecGetArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr);
577   for (k=0; k<pcis->n_shared[0]; k++) work_N[pcis->shared[0][k]] = *lambda * pcnn->DZ_IN[0][k];
578   ierr = VecRestoreArray(pcnn->coarse_x,&lambda);CHKERRQ(ierr);
579   ierr = PCISScatterArrayNToVecB(work_N,vec2_B,INSERT_VALUES,SCATTER_FORWARD,pc);CHKERRQ(ierr);
580   ierr = VecSet(z,0.0);CHKERRQ(ierr);
581   ierr = VecScatterBegin(pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
582   ierr = VecScatterEnd  (pcis->global_to_B,vec2_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
583   if (!u) {
584     ierr = VecScatterBegin(pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
585     ierr = VecScatterEnd  (pcis->global_to_B,z,vec2_B,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
586     ierr = PCISApplySchur(pc,vec2_B,vec1_B,(Vec)0,vec1_D,vec2_D);CHKERRQ(ierr);
587     ierr = VecCopy(r,z);CHKERRQ(ierr);
588   }
589   ierr = VecScatterBegin(pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
590   ierr = VecScatterEnd  (pcis->global_to_B,vec1_B,z,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
591   ierr = PetscLogEventEnd(PC_ApplyCoarse,0,0,0,0);CHKERRQ(ierr);
592   PetscFunctionReturn(0);
593 }
594 
595 #undef __FUNCT__
596 
597 
598 
599 /*  -------   E N D   O F   T H E   C O D E   -------  */
600 /*                                                     */
601 /*  From now on, "footnotes" (or "historical notes").  */
602 /*                                                     */
603 /*  -------------------------------------------------  */
604 
605 
606 
607 /* --------------------------------------------------------------------------
608    Historical note 01
609    -------------------------------------------------------------------------- */
610 /*
611    We considered the possibility of an alternative D_i that would still
612    provide a partition of unity (i.e., $ \sum_i  N_i D_i N_i^T = I $).
613    The basic principle was still the pseudo-inverse of the counting
614    function; the difference was that we would not count subdomains
615    that do not contribute to the coarse space (i.e., not pure-Neumann
616    subdomains).
617 
618    This turned out to be a bad idea:  we would solve trivial Neumann
619    problems in the not pure-Neumann subdomains, since we would be scaling
620    the balanced residual by zero.
621 */
622 
623 
624 
625 
626 /* --------------------------------------------------------------------------
627    Historical note 02
628    -------------------------------------------------------------------------- */
629 /*
630    We tried an alternative coarse problem, that would eliminate exactly a
631    constant error. Turned out not to improve the overall convergence.
632 */
633 
634 
635