xref: /petsc/src/mat/impls/sbaij/seq/sbaijfact.c (revision 3ab47c1a6b8969b08cfdbd2a4b0fa9b1ca65d2f8)
1 #define PETSCMAT_DLL
2 
3 #include "src/mat/impls/baij/seq/baij.h"
4 #include "src/mat/impls/sbaij/seq/sbaij.h"
5 #include "src/inline/ilu.h"
6 #include "include/petscis.h"
7 
8 #if !defined(PETSC_USE_COMPLEX)
9 /*
10   input:
11    F -- numeric factor
12   output:
13    nneg, nzero, npos: matrix inertia
14 */
15 
16 #undef __FUNCT__
17 #define __FUNCT__ "MatGetInertia_SeqSBAIJ"
18 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos)
19 {
20   Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data;
21   PetscScalar  *dd = fact_ptr->a;
22   PetscInt     mbs=fact_ptr->mbs,bs=F->rmap.bs,i,nneig_tmp,npos_tmp,*fi = fact_ptr->i;
23 
24   PetscFunctionBegin;
25   if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"No support for bs: %D >1 yet",bs);
26   nneig_tmp = 0; npos_tmp = 0;
27   for (i=0; i<mbs; i++){
28     if (PetscRealPart(dd[*fi]) > 0.0){
29       npos_tmp++;
30     } else if (PetscRealPart(dd[*fi]) < 0.0){
31       nneig_tmp++;
32     }
33     fi++;
34   }
35   if (nneig) *nneig = nneig_tmp;
36   if (npos)  *npos  = npos_tmp;
37   if (nzero) *nzero = mbs - nneig_tmp - npos_tmp;
38 
39   PetscFunctionReturn(0);
40 }
41 #endif /* !defined(PETSC_USE_COMPLEX) */
42 
43 /*
44   Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP.
45   Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad.
46 */
47 #undef __FUNCT__
48 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR"
49 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat A,IS perm,MatFactorInfo *info,Mat *B)
50 {
51   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b;
52   PetscErrorCode ierr;
53   PetscInt       *rip,i,mbs = a->mbs,*ai,*aj;
54   PetscInt       *jutmp,bs = A->rmap.bs,bs2=a->bs2;
55   PetscInt       m,reallocs = 0,prow;
56   PetscInt       *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd;
57   PetscReal      f = info->fill;
58   PetscTruth     perm_identity;
59 
60   PetscFunctionBegin;
61   /* check whether perm is the identity mapping */
62   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
63   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
64 
65   if (perm_identity){ /* without permutation */
66     a->permute = PETSC_FALSE;
67     ai = a->i; aj = a->j;
68   } else {            /* non-trivial permutation */
69     a->permute = PETSC_TRUE;
70     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
71     ai = a->inew; aj = a->jnew;
72   }
73 
74   /* initialization */
75   ierr  = PetscMalloc((mbs+1)*sizeof(PetscInt),&iu);CHKERRQ(ierr);
76   umax  = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1;
77   ierr  = PetscMalloc(umax*sizeof(PetscInt),&ju);CHKERRQ(ierr);
78   iu[0] = mbs+1;
79   juidx = mbs + 1; /* index for ju */
80   ierr  = PetscMalloc(2*mbs*sizeof(PetscInt),&jl);CHKERRQ(ierr); /* linked list for pivot row */
81   q     = jl + mbs;   /* linked list for col index */
82   for (i=0; i<mbs; i++){
83     jl[i] = mbs;
84     q[i] = 0;
85   }
86 
87   /* for each row k */
88   for (k=0; k<mbs; k++){
89     for (i=0; i<mbs; i++) q[i] = 0;  /* to be removed! */
90     nzk  = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */
91     q[k] = mbs;
92     /* initialize nonzero structure of k-th row to row rip[k] of A */
93     jmin = ai[rip[k]] +1; /* exclude diag[k] */
94     jmax = ai[rip[k]+1];
95     for (j=jmin; j<jmax; j++){
96       vj = rip[aj[j]]; /* col. value */
97       if(vj > k){
98         qm = k;
99         do {
100           m  = qm; qm = q[m];
101         } while(qm < vj);
102         if (qm == vj) {
103           SETERRQ(PETSC_ERR_PLIB,"Duplicate entry in A\n");
104         }
105         nzk++;
106         q[m]  = vj;
107         q[vj] = qm;
108       } /* if(vj > k) */
109     } /* for (j=jmin; j<jmax; j++) */
110 
111     /* modify nonzero structure of k-th row by computing fill-in
112        for each row i to be merged in */
113     prow = k;
114     prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */
115 
116     while (prow < k){
117       /* merge row prow into k-th row */
118       jmin = iu[prow] + 1; jmax = iu[prow+1];
119       qm = k;
120       for (j=jmin; j<jmax; j++){
121         vj = ju[j];
122         do {
123           m = qm; qm = q[m];
124         } while (qm < vj);
125         if (qm != vj){
126          nzk++; q[m] = vj; q[vj] = qm; qm = vj;
127         }
128       }
129       prow = jl[prow]; /* next pivot row */
130     }
131 
132     /* add k to row list for first nonzero element in k-th row */
133     if (nzk > 0){
134       i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */
135       jl[k] = jl[i]; jl[i] = k;
136     }
137     iu[k+1] = iu[k] + nzk;
138 
139     /* allocate more space to ju if needed */
140     if (iu[k+1] > umax) {
141       /* estimate how much additional space we will need */
142       /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
143       /* just double the memory each time */
144       maxadd = umax;
145       if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2;
146       umax += maxadd;
147 
148       /* allocate a longer ju */
149       ierr = PetscMalloc(umax*sizeof(PetscInt),&jutmp);CHKERRQ(ierr);
150       ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr);
151       ierr = PetscFree(ju);CHKERRQ(ierr);
152       ju   = jutmp;
153       reallocs++; /* count how many times we realloc */
154     }
155 
156     /* save nonzero structure of k-th row in ju */
157     i=k;
158     while (nzk --) {
159       i           = q[i];
160       ju[juidx++] = i;
161     }
162   }
163 
164 #if defined(PETSC_USE_INFO)
165   if (ai[mbs] != 0) {
166     PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
167     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,f,af);CHKERRQ(ierr);
168     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
169     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G);\n",af);CHKERRQ(ierr);
170     ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr);
171   } else {
172     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
173   }
174 #endif
175 
176   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
177   ierr = PetscFree(jl);CHKERRQ(ierr);
178 
179   /* put together the new matrix */
180   ierr = MatCreate(A->comm,B);CHKERRQ(ierr);
181   ierr = MatSetSizes(*B,bs*mbs,bs*mbs,bs*mbs,bs*mbs);CHKERRQ(ierr);
182   ierr = MatSetType(*B,A->type_name);CHKERRQ(ierr);
183   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(*B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
184 
185   /* ierr = PetscLogObjectParent(*B,iperm);CHKERRQ(ierr); */
186   b = (Mat_SeqSBAIJ*)(*B)->data;
187   b->singlemalloc = PETSC_FALSE;
188   b->free_a       = PETSC_TRUE;
189   b->free_ij       = PETSC_TRUE;
190   ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr);
191   b->j    = ju;
192   b->i    = iu;
193   b->diag = 0;
194   b->ilen = 0;
195   b->imax = 0;
196   b->row  = perm;
197   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
198   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
199   b->icol = perm;
200   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
201   ierr    = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
202   /* In b structure:  Free imax, ilen, old a, old j.
203      Allocate idnew, solve_work, new a, new j */
204   ierr = PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
205   b->maxnz = b->nz = iu[mbs];
206 
207   (*B)->factor                 = FACTOR_CHOLESKY;
208   (*B)->info.factor_mallocs    = reallocs;
209   (*B)->info.fill_ratio_given  = f;
210   if (ai[mbs] != 0) {
211     (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
212   } else {
213     (*B)->info.fill_ratio_needed = 0.0;
214   }
215 
216   if (perm_identity){
217     switch (bs) {
218       case 1:
219         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
220         (*B)->ops->solve                 = MatSolve_SeqSBAIJ_1_NaturalOrdering;
221         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr);
222         break;
223       case 2:
224         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
225         (*B)->ops->solve           = MatSolve_SeqSBAIJ_2_NaturalOrdering;
226         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr);
227         break;
228       case 3:
229         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
230         (*B)->ops->solve           = MatSolve_SeqSBAIJ_3_NaturalOrdering;
231         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr);
232         break;
233       case 4:
234         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
235         (*B)->ops->solve           = MatSolve_SeqSBAIJ_4_NaturalOrdering;
236         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr);
237         break;
238       case 5:
239         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
240         (*B)->ops->solve           = MatSolve_SeqSBAIJ_5_NaturalOrdering;
241         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr);
242         break;
243       case 6:
244         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
245         (*B)->ops->solve           = MatSolve_SeqSBAIJ_6_NaturalOrdering;
246         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr);
247         break;
248       case 7:
249         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
250         (*B)->ops->solve           = MatSolve_SeqSBAIJ_7_NaturalOrdering;
251         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr);
252       break;
253       default:
254         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
255         (*B)->ops->solve           = MatSolve_SeqSBAIJ_N_NaturalOrdering;
256         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr);
257       break;
258     }
259   }
260   PetscFunctionReturn(0);
261 }
262 /*
263     Symbolic U^T*D*U factorization for SBAIJ format.
264 */
265 #include "petscbt.h"
266 #include "src/mat/utils/freespace.h"
267 #undef __FUNCT__
268 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ"
269 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *fact)
270 {
271   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data;
272   Mat_SeqSBAIJ       *b;
273   Mat                B;
274   PetscErrorCode     ierr;
275   PetscTruth         perm_identity;
276   PetscReal          fill = info->fill;
277   PetscInt           *rip,i,mbs=a->mbs,bs=A->rmap.bs,*ai,*aj,reallocs=0,prow;
278   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
279   PetscInt           nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr;
280   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
281   PetscBT            lnkbt;
282 
283   PetscFunctionBegin;
284   /*
285    This code originally uses Modified Sparse Row (MSR) storage
286    (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise!
287    Then it is rewritten so the factor B takes seqsbaij format. However the associated
288    MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity,
289    thus the original code in MSR format is still used for these cases.
290    The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever
291    MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor.
292   */
293   if (bs > 1){
294     ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(A,perm,info,fact);CHKERRQ(ierr);
295     PetscFunctionReturn(0);
296   }
297 
298   /* check whether perm is the identity mapping */
299   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
300 
301   if (perm_identity){
302     a->permute = PETSC_FALSE;
303     ai = a->i; aj = a->j;
304   } else {
305     SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format");
306     /* There are bugs for reordeing. Needs further work.
307        MatReordering for sbaij cannot be efficient. User should use aij formt! */
308     a->permute = PETSC_TRUE;
309     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
310     ai = a->inew; aj = a->jnew;
311   }
312   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
313 
314   /* initialization */
315   ierr  = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
316   ui[0] = 0;
317 
318   /* jl: linked list for storing indices of the pivot rows
319      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
320   ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr);
321   il     = jl + mbs;
322   cols   = il + mbs;
323   ui_ptr = (PetscInt**)(cols + mbs);
324 
325   for (i=0; i<mbs; i++){
326     jl[i] = mbs; il[i] = 0;
327   }
328 
329   /* create and initialize a linked list for storing column indices of the active row k */
330   nlnk = mbs + 1;
331   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
332 
333   /* initial FreeSpace size is fill*(ai[mbs]+1) */
334   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr);
335   current_space = free_space;
336 
337   for (k=0; k<mbs; k++){  /* for each active row k */
338     /* initialize lnk by the column indices of row rip[k] of A */
339     nzk   = 0;
340     ncols = ai[rip[k]+1] - ai[rip[k]];
341     for (j=0; j<ncols; j++){
342       i = *(aj + ai[rip[k]] + j);
343       cols[j] = rip[i];
344     }
345     ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
346     nzk += nlnk;
347 
348     /* update lnk by computing fill-in for each pivot row to be merged in */
349     prow = jl[k]; /* 1st pivot row */
350 
351     while (prow < k){
352       nextprow = jl[prow];
353       /* merge prow into k-th row */
354       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
355       jmax = ui[prow+1];
356       ncols = jmax-jmin;
357       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
358       ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
359       nzk += nlnk;
360 
361       /* update il and jl for prow */
362       if (jmin < jmax){
363         il[prow] = jmin;
364         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
365       }
366       prow = nextprow;
367     }
368 
369     /* if free space is not available, make more free space */
370     if (current_space->local_remaining<nzk) {
371       i = mbs - k + 1; /* num of unfactored rows */
372       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
373       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
374       reallocs++;
375     }
376 
377     /* copy data into free space, then initialize lnk */
378     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
379 
380     /* add the k-th row into il and jl */
381     if (nzk-1 > 0){
382       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
383       jl[k] = jl[i]; jl[i] = k;
384       il[k] = ui[k] + 1;
385     }
386     ui_ptr[k] = current_space->array;
387     current_space->array           += nzk;
388     current_space->local_used      += nzk;
389     current_space->local_remaining -= nzk;
390 
391     ui[k+1] = ui[k] + nzk;
392   }
393 
394 #if defined(PETSC_USE_INFO)
395   if (ai[mbs] != 0) {
396     PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
397     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
398     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
399     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
400   } else {
401     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
402   }
403 #endif
404 
405   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
406   ierr = PetscFree(jl);CHKERRQ(ierr);
407 
408   /* destroy list of free space and other temporary array(s) */
409   ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
410   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
411   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
412 
413   /* put together the new matrix in MATSEQSBAIJ format */
414   ierr = MatCreate(PETSC_COMM_SELF,fact);CHKERRQ(ierr);
415   ierr = MatSetSizes(*fact,mbs,mbs,mbs,mbs);CHKERRQ(ierr);
416   B    = *fact;
417   ierr = MatSetType(B,MATSEQSBAIJ);CHKERRQ(ierr);
418   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
419 
420   b = (Mat_SeqSBAIJ*)B->data;
421   b->singlemalloc = PETSC_FALSE;
422   b->free_a       = PETSC_TRUE;
423   b->free_ij      = PETSC_TRUE;
424   ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
425   b->j    = uj;
426   b->i    = ui;
427   b->diag = 0;
428   b->ilen = 0;
429   b->imax = 0;
430   b->row  = perm;
431   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
432   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
433   b->icol = perm;
434   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
435   ierr    = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
436   ierr    = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
437   b->maxnz = b->nz = ui[mbs];
438 
439   B->factor                 = FACTOR_CHOLESKY;
440   B->info.factor_mallocs    = reallocs;
441   B->info.fill_ratio_given  = fill;
442   if (ai[mbs] != 0) {
443     B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
444   } else {
445     B->info.fill_ratio_needed = 0.0;
446   }
447 
448   if (perm_identity){
449     switch (bs) {
450       case 1:
451         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
452         B->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering;
453         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=1\n");CHKERRQ(ierr);
454         break;
455       case 2:
456         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
457         B->ops->solve           = MatSolve_SeqSBAIJ_2_NaturalOrdering;
458         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=2\n");CHKERRQ(ierr);
459         break;
460       case 3:
461         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
462         B->ops->solve           = MatSolve_SeqSBAIJ_3_NaturalOrdering;
463         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=3\n");CHKERRQ(ierr);
464         break;
465       case 4:
466         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
467         B->ops->solve           = MatSolve_SeqSBAIJ_4_NaturalOrdering;
468         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=4\n");CHKERRQ(ierr);
469         break;
470       case 5:
471         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
472         B->ops->solve           = MatSolve_SeqSBAIJ_5_NaturalOrdering;
473         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=5\n");CHKERRQ(ierr);
474         break;
475       case 6:
476         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
477         B->ops->solve           = MatSolve_SeqSBAIJ_6_NaturalOrdering;
478         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=6\n");CHKERRQ(ierr);
479         break;
480       case 7:
481         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
482         B->ops->solve           = MatSolve_SeqSBAIJ_7_NaturalOrdering;
483         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS=7\n");CHKERRQ(ierr);
484       break;
485       default:
486         B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
487         B->ops->solve           = MatSolve_SeqSBAIJ_N_NaturalOrdering;
488         ierr = PetscInfo(A,"Using special in-place natural ordering factor and solve BS>7\n");CHKERRQ(ierr);
489       break;
490     }
491   }
492   PetscFunctionReturn(0);
493 }
494 #undef __FUNCT__
495 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N"
496 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,MatFactorInfo *info,Mat *B)
497 {
498   Mat            C = *B;
499   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
500   IS             perm = b->row;
501   PetscErrorCode ierr;
502   PetscInt       *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
503   PetscInt       *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
504   PetscInt       bs=A->rmap.bs,bs2 = a->bs2,bslog = 0;
505   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
506   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
507   MatScalar      *work;
508   PetscInt       *pivots;
509 
510   PetscFunctionBegin;
511   /* initialization */
512   ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
513   ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr);
514   ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr);
515   jl   = il + mbs;
516   for (i=0; i<mbs; i++) {
517     jl[i] = mbs; il[0] = 0;
518   }
519   ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr);
520   uik  = dk + bs2;
521   work = uik + bs2;
522   ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr);
523 
524   ierr  = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
525 
526   /* check permutation */
527   if (!a->permute){
528     ai = a->i; aj = a->j; aa = a->a;
529   } else {
530     ai   = a->inew; aj = a->jnew;
531     ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr);
532     ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
533     ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr);
534     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
535 
536     /* flops in while loop */
537     bslog = 2*bs*bs2;
538 
539     for (i=0; i<mbs; i++){
540       jmin = ai[i]; jmax = ai[i+1];
541       for (j=jmin; j<jmax; j++){
542         while (a2anew[j] != j){
543           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
544           for (k1=0; k1<bs2; k1++){
545             dk[k1]       = aa[k*bs2+k1];
546             aa[k*bs2+k1] = aa[j*bs2+k1];
547             aa[j*bs2+k1] = dk[k1];
548           }
549         }
550         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
551         if (i > aj[j]){
552           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
553           ap = aa + j*bs2;                     /* ptr to the beginning of j-th block of aa */
554           for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */
555           for (k=0; k<bs; k++){               /* j-th block of aa <- dk^T */
556             for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1];
557           }
558         }
559       }
560     }
561     ierr = PetscFree(a2anew);CHKERRQ(ierr);
562   }
563 
564   /* for each row k */
565   for (k = 0; k<mbs; k++){
566 
567     /*initialize k-th row with elements nonzero in row perm(k) of A */
568     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
569 
570     ap = aa + jmin*bs2;
571     for (j = jmin; j < jmax; j++){
572       vj = perm_ptr[aj[j]];         /* block col. index */
573       rtmp_ptr = rtmp + vj*bs2;
574       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
575     }
576 
577     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
578     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
579     i = jl[k]; /* first row to be added to k_th row  */
580 
581     while (i < k){
582       nexti = jl[i]; /* next row to be added to k_th row */
583 
584       /* compute multiplier */
585       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
586 
587       /* uik = -inv(Di)*U_bar(i,k) */
588       diag = ba + i*bs2;
589       u    = ba + ili*bs2;
590       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
591       Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
592 
593       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
594       Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
595       ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr);
596 
597       /* update -U(i,k) */
598       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
599 
600       /* add multiple of row i to k-th row ... */
601       jmin = ili + 1; jmax = bi[i+1];
602       if (jmin < jmax){
603         for (j=jmin; j<jmax; j++) {
604           /* rtmp += -U(i,k)^T * U_bar(i,j) */
605           rtmp_ptr = rtmp + bj[j]*bs2;
606           u = ba + j*bs2;
607           Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
608         }
609         ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr);
610 
611         /* ... add i to row list for next nonzero entry */
612         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
613         j     = bj[jmin];
614         jl[i] = jl[j]; jl[j] = i; /* update jl */
615       }
616       i = nexti;
617     }
618 
619     /* save nonzero entries in k-th row of U ... */
620 
621     /* invert diagonal block */
622     diag = ba+k*bs2;
623     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
624     ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
625 
626     jmin = bi[k]; jmax = bi[k+1];
627     if (jmin < jmax) {
628       for (j=jmin; j<jmax; j++){
629          vj = bj[j];           /* block col. index of U */
630          u   = ba + j*bs2;
631          rtmp_ptr = rtmp + vj*bs2;
632          for (k1=0; k1<bs2; k1++){
633            *u++        = *rtmp_ptr;
634            *rtmp_ptr++ = 0.0;
635          }
636       }
637 
638       /* ... add k to row list for first nonzero entry in k-th row */
639       il[k] = jmin;
640       i     = bj[jmin];
641       jl[k] = jl[i]; jl[i] = k;
642     }
643   }
644 
645   ierr = PetscFree(rtmp);CHKERRQ(ierr);
646   ierr = PetscFree(il);CHKERRQ(ierr);
647   ierr = PetscFree(dk);CHKERRQ(ierr);
648   ierr = PetscFree(pivots);CHKERRQ(ierr);
649   if (a->permute){
650     ierr = PetscFree(aa);CHKERRQ(ierr);
651   }
652 
653   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
654   C->factor       = FACTOR_CHOLESKY;
655   C->assembled    = PETSC_TRUE;
656   C->preallocated = PETSC_TRUE;
657   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
658   PetscFunctionReturn(0);
659 }
660 
661 #undef __FUNCT__
662 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering"
663 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B)
664 {
665   Mat            C = *B;
666   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
667   PetscErrorCode ierr;
668   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
669   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
670   PetscInt       bs=A->rmap.bs,bs2 = a->bs2,bslog;
671   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
672   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
673   MatScalar      *work;
674   PetscInt       *pivots;
675 
676   PetscFunctionBegin;
677   ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
678   ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr);
679   ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr);
680   jl   = il + mbs;
681   for (i=0; i<mbs; i++) {
682     jl[i] = mbs; il[0] = 0;
683   }
684   ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr);
685   uik  = dk + bs2;
686   work = uik + bs2;
687   ierr = PetscMalloc(bs*sizeof(PetscInt),&pivots);CHKERRQ(ierr);
688 
689   ai = a->i; aj = a->j; aa = a->a;
690 
691   /* flops in while loop */
692   bslog = 2*bs*bs2;
693 
694   /* for each row k */
695   for (k = 0; k<mbs; k++){
696 
697     /*initialize k-th row with elements nonzero in row k of A */
698     jmin = ai[k]; jmax = ai[k+1];
699     ap = aa + jmin*bs2;
700     for (j = jmin; j < jmax; j++){
701       vj = aj[j];         /* block col. index */
702       rtmp_ptr = rtmp + vj*bs2;
703       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
704     }
705 
706     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
707     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
708     i = jl[k]; /* first row to be added to k_th row  */
709 
710     while (i < k){
711       nexti = jl[i]; /* next row to be added to k_th row */
712 
713       /* compute multiplier */
714       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
715 
716       /* uik = -inv(Di)*U_bar(i,k) */
717       diag = ba + i*bs2;
718       u    = ba + ili*bs2;
719       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
720       Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
721 
722       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
723       Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
724       ierr = PetscLogFlops(bslog*2);CHKERRQ(ierr);
725 
726       /* update -U(i,k) */
727       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
728 
729       /* add multiple of row i to k-th row ... */
730       jmin = ili + 1; jmax = bi[i+1];
731       if (jmin < jmax){
732         for (j=jmin; j<jmax; j++) {
733           /* rtmp += -U(i,k)^T * U_bar(i,j) */
734           rtmp_ptr = rtmp + bj[j]*bs2;
735           u = ba + j*bs2;
736           Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
737         }
738         ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr);
739 
740         /* ... add i to row list for next nonzero entry */
741         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
742         j     = bj[jmin];
743         jl[i] = jl[j]; jl[j] = i; /* update jl */
744       }
745       i = nexti;
746     }
747 
748     /* save nonzero entries in k-th row of U ... */
749 
750     /* invert diagonal block */
751     diag = ba+k*bs2;
752     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
753     ierr = Kernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
754 
755     jmin = bi[k]; jmax = bi[k+1];
756     if (jmin < jmax) {
757       for (j=jmin; j<jmax; j++){
758          vj = bj[j];           /* block col. index of U */
759          u   = ba + j*bs2;
760          rtmp_ptr = rtmp + vj*bs2;
761          for (k1=0; k1<bs2; k1++){
762            *u++        = *rtmp_ptr;
763            *rtmp_ptr++ = 0.0;
764          }
765       }
766 
767       /* ... add k to row list for first nonzero entry in k-th row */
768       il[k] = jmin;
769       i     = bj[jmin];
770       jl[k] = jl[i]; jl[i] = k;
771     }
772   }
773 
774   ierr = PetscFree(rtmp);CHKERRQ(ierr);
775   ierr = PetscFree(il);CHKERRQ(ierr);
776   ierr = PetscFree(dk);CHKERRQ(ierr);
777   ierr = PetscFree(pivots);CHKERRQ(ierr);
778 
779   C->factor    = FACTOR_CHOLESKY;
780   C->assembled = PETSC_TRUE;
781   C->preallocated = PETSC_TRUE;
782   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
783   PetscFunctionReturn(0);
784 }
785 
786 /*
787     Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP.
788     Version for blocks 2 by 2.
789 */
790 #undef __FUNCT__
791 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2"
792 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,MatFactorInfo *info,Mat *B)
793 {
794   Mat            C = *B;
795   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
796   IS             perm = b->row;
797   PetscErrorCode ierr;
798   PetscInt       *perm_ptr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
799   PetscInt       *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
800   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
801   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
802 
803   PetscFunctionBegin;
804   /* initialization */
805   /* il and jl record the first nonzero element in each row of the accessing
806      window U(0:k, k:mbs-1).
807      jl:    list of rows to be added to uneliminated rows
808             i>= k: jl(i) is the first row to be added to row i
809             i<  k: jl(i) is the row following row i in some list of rows
810             jl(i) = mbs indicates the end of a list
811      il(i): points to the first nonzero element in columns k,...,mbs-1 of
812             row i of U */
813   ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
814   ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr);
815   ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr);
816   jl   = il + mbs;
817   for (i=0; i<mbs; i++) {
818     jl[i] = mbs; il[0] = 0;
819   }
820   ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr);
821   uik  = dk + 4;
822   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
823 
824   /* check permutation */
825   if (!a->permute){
826     ai = a->i; aj = a->j; aa = a->a;
827   } else {
828     ai   = a->inew; aj = a->jnew;
829     ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr);
830     ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
831     ierr = PetscMalloc(ai[mbs]*sizeof(PetscInt),&a2anew);CHKERRQ(ierr);
832     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
833 
834     for (i=0; i<mbs; i++){
835       jmin = ai[i]; jmax = ai[i+1];
836       for (j=jmin; j<jmax; j++){
837         while (a2anew[j] != j){
838           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
839           for (k1=0; k1<4; k1++){
840             dk[k1]       = aa[k*4+k1];
841             aa[k*4+k1] = aa[j*4+k1];
842             aa[j*4+k1] = dk[k1];
843           }
844         }
845         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
846         if (i > aj[j]){
847           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
848           ap = aa + j*4;     /* ptr to the beginning of the block */
849           dk[1] = ap[1];     /* swap ap[1] and ap[2] */
850           ap[1] = ap[2];
851           ap[2] = dk[1];
852         }
853       }
854     }
855     ierr = PetscFree(a2anew);CHKERRQ(ierr);
856   }
857 
858   /* for each row k */
859   for (k = 0; k<mbs; k++){
860 
861     /*initialize k-th row with elements nonzero in row perm(k) of A */
862     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
863     ap = aa + jmin*4;
864     for (j = jmin; j < jmax; j++){
865       vj = perm_ptr[aj[j]];         /* block col. index */
866       rtmp_ptr = rtmp + vj*4;
867       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
868     }
869 
870     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
871     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
872     i = jl[k]; /* first row to be added to k_th row  */
873 
874     while (i < k){
875       nexti = jl[i]; /* next row to be added to k_th row */
876 
877       /* compute multiplier */
878       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
879 
880       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
881       diag = ba + i*4;
882       u    = ba + ili*4;
883       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
884       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
885       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
886       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
887 
888       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
889       dk[0] += uik[0]*u[0] + uik[1]*u[1];
890       dk[1] += uik[2]*u[0] + uik[3]*u[1];
891       dk[2] += uik[0]*u[2] + uik[1]*u[3];
892       dk[3] += uik[2]*u[2] + uik[3]*u[3];
893 
894       ierr = PetscLogFlops(16*2);CHKERRQ(ierr);
895 
896       /* update -U(i,k): ba[ili] = uik */
897       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
898 
899       /* add multiple of row i to k-th row ... */
900       jmin = ili + 1; jmax = bi[i+1];
901       if (jmin < jmax){
902         for (j=jmin; j<jmax; j++) {
903           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
904           rtmp_ptr = rtmp + bj[j]*4;
905           u = ba + j*4;
906           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
907           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
908           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
909           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
910         }
911         ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr);
912 
913         /* ... add i to row list for next nonzero entry */
914         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
915         j     = bj[jmin];
916         jl[i] = jl[j]; jl[j] = i; /* update jl */
917       }
918       i = nexti;
919     }
920 
921     /* save nonzero entries in k-th row of U ... */
922 
923     /* invert diagonal block */
924     diag = ba+k*4;
925     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
926     ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr);
927 
928     jmin = bi[k]; jmax = bi[k+1];
929     if (jmin < jmax) {
930       for (j=jmin; j<jmax; j++){
931          vj = bj[j];           /* block col. index of U */
932          u   = ba + j*4;
933          rtmp_ptr = rtmp + vj*4;
934          for (k1=0; k1<4; k1++){
935            *u++        = *rtmp_ptr;
936            *rtmp_ptr++ = 0.0;
937          }
938       }
939 
940       /* ... add k to row list for first nonzero entry in k-th row */
941       il[k] = jmin;
942       i     = bj[jmin];
943       jl[k] = jl[i]; jl[i] = k;
944     }
945   }
946 
947   ierr = PetscFree(rtmp);CHKERRQ(ierr);
948   ierr = PetscFree(il);CHKERRQ(ierr);
949   ierr = PetscFree(dk);CHKERRQ(ierr);
950   if (a->permute) {
951     ierr = PetscFree(aa);CHKERRQ(ierr);
952   }
953   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
954   C->factor    = FACTOR_CHOLESKY;
955   C->assembled = PETSC_TRUE;
956   C->preallocated = PETSC_TRUE;
957   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
958   PetscFunctionReturn(0);
959 }
960 
961 /*
962       Version for when blocks are 2 by 2 Using natural ordering
963 */
964 #undef __FUNCT__
965 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering"
966 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B)
967 {
968   Mat            C = *B;
969   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
970   PetscErrorCode ierr;
971   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
972   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
973   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
974   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
975 
976   PetscFunctionBegin;
977   /* initialization */
978   /* il and jl record the first nonzero element in each row of the accessing
979      window U(0:k, k:mbs-1).
980      jl:    list of rows to be added to uneliminated rows
981             i>= k: jl(i) is the first row to be added to row i
982             i<  k: jl(i) is the row following row i in some list of rows
983             jl(i) = mbs indicates the end of a list
984      il(i): points to the first nonzero element in columns k,...,mbs-1 of
985             row i of U */
986   ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
987   ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr);
988   ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr);
989   jl   = il + mbs;
990   for (i=0; i<mbs; i++) {
991     jl[i] = mbs; il[0] = 0;
992   }
993   ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr);
994   uik  = dk + 4;
995 
996   ai = a->i; aj = a->j; aa = a->a;
997 
998   /* for each row k */
999   for (k = 0; k<mbs; k++){
1000 
1001     /*initialize k-th row with elements nonzero in row k of A */
1002     jmin = ai[k]; jmax = ai[k+1];
1003     ap = aa + jmin*4;
1004     for (j = jmin; j < jmax; j++){
1005       vj = aj[j];         /* block col. index */
1006       rtmp_ptr = rtmp + vj*4;
1007       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
1008     }
1009 
1010     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
1011     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
1012     i = jl[k]; /* first row to be added to k_th row  */
1013 
1014     while (i < k){
1015       nexti = jl[i]; /* next row to be added to k_th row */
1016 
1017       /* compute multiplier */
1018       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1019 
1020       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
1021       diag = ba + i*4;
1022       u    = ba + ili*4;
1023       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
1024       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
1025       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
1026       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
1027 
1028       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
1029       dk[0] += uik[0]*u[0] + uik[1]*u[1];
1030       dk[1] += uik[2]*u[0] + uik[3]*u[1];
1031       dk[2] += uik[0]*u[2] + uik[1]*u[3];
1032       dk[3] += uik[2]*u[2] + uik[3]*u[3];
1033 
1034       ierr = PetscLogFlops(16*2);CHKERRQ(ierr);
1035 
1036       /* update -U(i,k): ba[ili] = uik */
1037       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
1038 
1039       /* add multiple of row i to k-th row ... */
1040       jmin = ili + 1; jmax = bi[i+1];
1041       if (jmin < jmax){
1042         for (j=jmin; j<jmax; j++) {
1043           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
1044           rtmp_ptr = rtmp + bj[j]*4;
1045           u = ba + j*4;
1046           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
1047           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
1048           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
1049           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
1050         }
1051         ierr = PetscLogFlops(16*(jmax-jmin));CHKERRQ(ierr);
1052 
1053         /* ... add i to row list for next nonzero entry */
1054         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
1055         j     = bj[jmin];
1056         jl[i] = jl[j]; jl[j] = i; /* update jl */
1057       }
1058       i = nexti;
1059     }
1060 
1061     /* save nonzero entries in k-th row of U ... */
1062 
1063     /* invert diagonal block */
1064     diag = ba+k*4;
1065     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
1066     ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr);
1067 
1068     jmin = bi[k]; jmax = bi[k+1];
1069     if (jmin < jmax) {
1070       for (j=jmin; j<jmax; j++){
1071          vj = bj[j];           /* block col. index of U */
1072          u   = ba + j*4;
1073          rtmp_ptr = rtmp + vj*4;
1074          for (k1=0; k1<4; k1++){
1075            *u++        = *rtmp_ptr;
1076            *rtmp_ptr++ = 0.0;
1077          }
1078       }
1079 
1080       /* ... add k to row list for first nonzero entry in k-th row */
1081       il[k] = jmin;
1082       i     = bj[jmin];
1083       jl[k] = jl[i]; jl[i] = k;
1084     }
1085   }
1086 
1087   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1088   ierr = PetscFree(il);CHKERRQ(ierr);
1089   ierr = PetscFree(dk);CHKERRQ(ierr);
1090 
1091   C->factor    = FACTOR_CHOLESKY;
1092   C->assembled = PETSC_TRUE;
1093   C->preallocated = PETSC_TRUE;
1094   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
1095   PetscFunctionReturn(0);
1096 }
1097 
1098 /*
1099     Numeric U^T*D*U factorization for SBAIJ format.
1100     Version for blocks are 1 by 1.
1101 */
1102 #undef __FUNCT__
1103 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1"
1104 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,MatFactorInfo *info,Mat *B)
1105 {
1106   Mat            C = *B;
1107   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data;
1108   IS             ip=b->row;
1109   PetscErrorCode ierr;
1110   PetscInt       *rip,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol;
1111   PetscInt       *ai,*aj,*a2anew;
1112   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
1113   MatScalar      *rtmp,*ba=b->a,*bval,*aa,dk,uikdi;
1114   PetscReal      zeropivot,rs,shiftnz;
1115   PetscReal      shiftpd;
1116   ChShift_Ctx    sctx;
1117   PetscInt       newshift;
1118 
1119   PetscFunctionBegin;
1120   /* initialization */
1121   shiftnz   = info->shiftnz;
1122   shiftpd   = info->shiftpd;
1123   zeropivot = info->zeropivot;
1124 
1125   ierr  = ISGetIndices(ip,&rip);CHKERRQ(ierr);
1126   if (!a->permute){
1127     ai = a->i; aj = a->j; aa = a->a;
1128   } else {
1129     ai = a->inew; aj = a->jnew;
1130     nz = ai[mbs];
1131     ierr = PetscMalloc(nz*sizeof(MatScalar),&aa);CHKERRQ(ierr);
1132     a2anew = a->a2anew;
1133     bval   = a->a;
1134     for (j=0; j<nz; j++){
1135       aa[a2anew[j]] = *(bval++);
1136     }
1137   }
1138 
1139   /* initialization */
1140   /* il and jl record the first nonzero element in each row of the accessing
1141      window U(0:k, k:mbs-1).
1142      jl:    list of rows to be added to uneliminated rows
1143             i>= k: jl(i) is the first row to be added to row i
1144             i<  k: jl(i) is the row following row i in some list of rows
1145             jl(i) = mbs indicates the end of a list
1146      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1147             row i of U */
1148   nz   = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar);
1149   ierr = PetscMalloc(nz,&il);CHKERRQ(ierr);
1150   jl   = il + mbs;
1151   rtmp = (MatScalar*)(jl + mbs);
1152 
1153   sctx.shift_amount = 0;
1154   sctx.nshift       = 0;
1155   do {
1156     sctx.chshift = PETSC_FALSE;
1157     for (i=0; i<mbs; i++) {
1158       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1159     }
1160 
1161     for (k = 0; k<mbs; k++){
1162       /*initialize k-th row by the perm[k]-th row of A */
1163       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
1164       bval = ba + bi[k];
1165       for (j = jmin; j < jmax; j++){
1166         col = rip[aj[j]];
1167         rtmp[col] = aa[j];
1168         *bval++  = 0.0; /* for in-place factorization */
1169       }
1170 
1171       /* shift the diagonal of the matrix */
1172       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1173 
1174       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1175       dk = rtmp[k];
1176       i = jl[k]; /* first row to be added to k_th row  */
1177 
1178       while (i < k){
1179         nexti = jl[i]; /* next row to be added to k_th row */
1180 
1181         /* compute multiplier, update diag(k) and U(i,k) */
1182         ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1183         uikdi = - ba[ili]*ba[bi[i]];  /* diagonal(k) */
1184         dk += uikdi*ba[ili];
1185         ba[ili] = uikdi; /* -U(i,k) */
1186 
1187         /* add multiple of row i to k-th row */
1188         jmin = ili + 1; jmax = bi[i+1];
1189         if (jmin < jmax){
1190           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
1191           ierr = PetscLogFlops(2*(jmax-jmin));CHKERRQ(ierr);
1192 
1193           /* update il and jl for row i */
1194           il[i] = jmin;
1195           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1196         }
1197         i = nexti;
1198       }
1199 
1200       /* shift the diagonals when zero pivot is detected */
1201       /* compute rs=sum of abs(off-diagonal) */
1202       rs   = 0.0;
1203       jmin = bi[k]+1;
1204       nz   = bi[k+1] - jmin;
1205       if (nz){
1206         bcol = bj + jmin;
1207         while (nz--){
1208           rs += PetscAbsScalar(rtmp[*bcol]);
1209           bcol++;
1210         }
1211       }
1212 
1213       sctx.rs = rs;
1214       sctx.pv = dk;
1215       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
1216       if (newshift == 1) break;    /* sctx.shift_amount is updated */
1217 
1218       /* copy data into U(k,:) */
1219       ba[bi[k]] = 1.0/dk; /* U(k,k) */
1220       jmin = bi[k]+1; jmax = bi[k+1];
1221       if (jmin < jmax) {
1222         for (j=jmin; j<jmax; j++){
1223           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
1224         }
1225         /* add the k-th row into il and jl */
1226         il[k] = jmin;
1227         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1228       }
1229     }
1230   } while (sctx.chshift);
1231   ierr = PetscFree(il);CHKERRQ(ierr);
1232   if (a->permute){ierr = PetscFree(aa);CHKERRQ(ierr);}
1233 
1234   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
1235   C->factor       = FACTOR_CHOLESKY;
1236   C->assembled    = PETSC_TRUE;
1237   C->preallocated = PETSC_TRUE;
1238   ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr);
1239   if (sctx.nshift){
1240     if (shiftnz) {
1241       ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
1242     } else if (shiftpd) {
1243       ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
1244     }
1245   }
1246   PetscFunctionReturn(0);
1247 }
1248 
1249 /*
1250   Version for when blocks are 1 by 1 Using natural ordering
1251 */
1252 #undef __FUNCT__
1253 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering"
1254 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,MatFactorInfo *info,Mat *B)
1255 {
1256   Mat            C = *B;
1257   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data;
1258   PetscErrorCode ierr;
1259   PetscInt       i,j,mbs = a->mbs;
1260   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
1261   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
1262   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
1263   PetscReal      zeropivot,rs,shiftnz;
1264   PetscReal      shiftpd;
1265   ChShift_Ctx    sctx;
1266   PetscInt       newshift;
1267 
1268   PetscFunctionBegin;
1269   /* initialization */
1270   shiftnz   = info->shiftnz;
1271   shiftpd   = info->shiftpd;
1272   zeropivot = info->zeropivot;
1273 
1274   /* il and jl record the first nonzero element in each row of the accessing
1275      window U(0:k, k:mbs-1).
1276      jl:    list of rows to be added to uneliminated rows
1277             i>= k: jl(i) is the first row to be added to row i
1278             i<  k: jl(i) is the row following row i in some list of rows
1279             jl(i) = mbs indicates the end of a list
1280      il(i): points to the first nonzero element in U(i,k:mbs-1)
1281   */
1282   ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
1283   ierr = PetscMalloc(2*mbs*sizeof(PetscInt),&il);CHKERRQ(ierr);
1284   jl   = il + mbs;
1285 
1286   sctx.shift_amount = 0;
1287   sctx.nshift       = 0;
1288   do {
1289     sctx.chshift = PETSC_FALSE;
1290     for (i=0; i<mbs; i++) {
1291       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1292     }
1293 
1294     for (k = 0; k<mbs; k++){
1295       /*initialize k-th row with elements nonzero in row perm(k) of A */
1296       nz   = ai[k+1] - ai[k];
1297       acol = aj + ai[k];
1298       aval = aa + ai[k];
1299       bval = ba + bi[k];
1300       while (nz -- ){
1301         rtmp[*acol++] = *aval++;
1302         *bval++       = 0.0; /* for in-place factorization */
1303       }
1304 
1305       /* shift the diagonal of the matrix */
1306       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1307 
1308       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1309       dk = rtmp[k];
1310       i  = jl[k]; /* first row to be added to k_th row  */
1311 
1312       while (i < k){
1313         nexti = jl[i]; /* next row to be added to k_th row */
1314         /* compute multiplier, update D(k) and U(i,k) */
1315         ili   = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1316         uikdi = - ba[ili]*ba[bi[i]];
1317         dk   += uikdi*ba[ili];
1318         ba[ili] = uikdi; /* -U(i,k) */
1319 
1320         /* add multiple of row i to k-th row ... */
1321         jmin = ili + 1;
1322         nz   = bi[i+1] - jmin;
1323         if (nz > 0){
1324           bcol = bj + jmin;
1325           bval = ba + jmin;
1326           ierr = PetscLogFlops(2*nz);CHKERRQ(ierr);
1327           while (nz --) rtmp[*bcol++] += uikdi*(*bval++);
1328 
1329           /* update il and jl for i-th row */
1330           il[i] = jmin;
1331           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1332         }
1333         i = nexti;
1334       }
1335 
1336       /* shift the diagonals when zero pivot is detected */
1337       /* compute rs=sum of abs(off-diagonal) */
1338       rs   = 0.0;
1339       jmin = bi[k]+1;
1340       nz   = bi[k+1] - jmin;
1341       if (nz){
1342         bcol = bj + jmin;
1343         while (nz--){
1344           rs += PetscAbsScalar(rtmp[*bcol]);
1345           bcol++;
1346         }
1347       }
1348 
1349       sctx.rs = rs;
1350       sctx.pv = dk;
1351       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
1352       if (newshift == 1) break;    /* sctx.shift_amount is updated */
1353 
1354       /* copy data into U(k,:) */
1355       ba[bi[k]] = 1.0/dk;
1356       jmin      = bi[k]+1;
1357       nz        = bi[k+1] - jmin;
1358       if (nz){
1359         bcol = bj + jmin;
1360         bval = ba + jmin;
1361         while (nz--){
1362           *bval++       = rtmp[*bcol];
1363           rtmp[*bcol++] = 0.0;
1364         }
1365         /* add k-th row into il and jl */
1366         il[k] = jmin;
1367         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1368       }
1369     } /* end of for (k = 0; k<mbs; k++) */
1370   } while (sctx.chshift);
1371   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1372   ierr = PetscFree(il);CHKERRQ(ierr);
1373 
1374   C->factor       = FACTOR_CHOLESKY;
1375   C->assembled    = PETSC_TRUE;
1376   C->preallocated = PETSC_TRUE;
1377   ierr = PetscLogFlops(C->rmap.N);CHKERRQ(ierr);
1378   if (sctx.nshift){
1379     if (shiftnz) {
1380       ierr = PetscInfo2(0,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
1381     } else if (shiftpd) {
1382       ierr = PetscInfo2(0,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
1383     }
1384   }
1385   PetscFunctionReturn(0);
1386 }
1387 
1388 #undef __FUNCT__
1389 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ"
1390 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info)
1391 {
1392   PetscErrorCode ierr;
1393   Mat            C;
1394 
1395   PetscFunctionBegin;
1396   ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr);
1397   ierr = MatCholeskyFactorNumeric(A,info,&C);CHKERRQ(ierr);
1398   ierr = MatHeaderCopy(A,C);CHKERRQ(ierr);
1399   PetscFunctionReturn(0);
1400 }
1401 
1402 
1403