xref: /petsc/src/mat/impls/sbaij/seq/sbaijfact.c (revision 2e92ee13a8395f820cc1e3fd74a7607ed52efa2a)
1 
2 #include <../src/mat/impls/baij/seq/baij.h>
3 #include <../src/mat/impls/sbaij/seq/sbaij.h>
4 #include <petsc/private/kernels/blockinvert.h>
5 #include <petscis.h>
6 
7 /*
8   input:
9    F -- numeric factor
10   output:
11    nneg, nzero, npos: matrix inertia
12 */
13 
14 #undef __FUNCT__
15 #define __FUNCT__ "MatGetInertia_SeqSBAIJ"
16 PetscErrorCode MatGetInertia_SeqSBAIJ(Mat F,PetscInt *nneig,PetscInt *nzero,PetscInt *npos)
17 {
18   Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data;
19   MatScalar    *dd       = fact_ptr->a;
20   PetscInt     mbs       =fact_ptr->mbs,bs=F->rmap->bs,i,nneig_tmp,npos_tmp,*fi = fact_ptr->diag;
21 
22   PetscFunctionBegin;
23   if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for bs: %D >1 yet",bs);
24   nneig_tmp = 0; npos_tmp = 0;
25   for (i=0; i<mbs; i++) {
26     if (PetscRealPart(dd[*fi]) > 0.0) npos_tmp++;
27     else if (PetscRealPart(dd[*fi]) < 0.0) nneig_tmp++;
28     fi++;
29   }
30   if (nneig) *nneig = nneig_tmp;
31   if (npos)  *npos  = npos_tmp;
32   if (nzero) *nzero = mbs - nneig_tmp - npos_tmp;
33   PetscFunctionReturn(0);
34 }
35 
36 /*
37   Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP.
38   Use Modified Sparse Row (MSR) storage for u and ju. See page 85, "Iterative Methods ..." by Saad.
39 */
40 #undef __FUNCT__
41 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_MSR"
42 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(Mat F,Mat A,IS perm,const MatFactorInfo *info)
43 {
44   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b;
45   PetscErrorCode ierr;
46   const PetscInt *rip,*ai,*aj;
47   PetscInt       i,mbs = a->mbs,*jutmp,bs = A->rmap->bs,bs2=a->bs2;
48   PetscInt       m,reallocs = 0,prow;
49   PetscInt       *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd;
50   PetscReal      f = info->fill;
51   PetscBool      perm_identity;
52 
53   PetscFunctionBegin;
54   /* check whether perm is the identity mapping */
55   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
56   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
57 
58   if (perm_identity) { /* without permutation */
59     a->permute = PETSC_FALSE;
60 
61     ai = a->i; aj = a->j;
62   } else {            /* non-trivial permutation */
63     a->permute = PETSC_TRUE;
64 
65     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
66 
67     ai = a->inew; aj = a->jnew;
68   }
69 
70   /* initialization */
71   ierr  = PetscMalloc1(mbs+1,&iu);CHKERRQ(ierr);
72   umax  = (PetscInt)(f*ai[mbs] + 1); umax += mbs + 1;
73   ierr  = PetscMalloc1(umax,&ju);CHKERRQ(ierr);
74   iu[0] = mbs+1;
75   juidx = mbs + 1; /* index for ju */
76   /* jl linked list for pivot row -- linked list for col index */
77   ierr = PetscMalloc2(mbs,&jl,mbs,&q);CHKERRQ(ierr);
78   for (i=0; i<mbs; i++) {
79     jl[i] = mbs;
80     q[i]  = 0;
81   }
82 
83   /* for each row k */
84   for (k=0; k<mbs; k++) {
85     for (i=0; i<mbs; i++) q[i] = 0;  /* to be removed! */
86     nzk  = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */
87     q[k] = mbs;
88     /* initialize nonzero structure of k-th row to row rip[k] of A */
89     jmin = ai[rip[k]] +1; /* exclude diag[k] */
90     jmax = ai[rip[k]+1];
91     for (j=jmin; j<jmax; j++) {
92       vj = rip[aj[j]]; /* col. value */
93       if (vj > k) {
94         qm = k;
95         do {
96           m = qm; qm = q[m];
97         } while (qm < vj);
98         if (qm == vj) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Duplicate entry in A\n");
99         nzk++;
100         q[m]  = vj;
101         q[vj] = qm;
102       } /* if (vj > k) */
103     } /* for (j=jmin; j<jmax; j++) */
104 
105     /* modify nonzero structure of k-th row by computing fill-in
106        for each row i to be merged in */
107     prow = k;
108     prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */
109 
110     while (prow < k) {
111       /* merge row prow into k-th row */
112       jmin = iu[prow] + 1; jmax = iu[prow+1];
113       qm   = k;
114       for (j=jmin; j<jmax; j++) {
115         vj = ju[j];
116         do {
117           m = qm; qm = q[m];
118         } while (qm < vj);
119         if (qm != vj) {
120           nzk++; q[m] = vj; q[vj] = qm; qm = vj;
121         }
122       }
123       prow = jl[prow]; /* next pivot row */
124     }
125 
126     /* add k to row list for first nonzero element in k-th row */
127     if (nzk > 0) {
128       i     = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */
129       jl[k] = jl[i]; jl[i] = k;
130     }
131     iu[k+1] = iu[k] + nzk;
132 
133     /* allocate more space to ju if needed */
134     if (iu[k+1] > umax) {
135       /* estimate how much additional space we will need */
136       /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
137       /* just double the memory each time */
138       maxadd = umax;
139       if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2;
140       umax += maxadd;
141 
142       /* allocate a longer ju */
143       ierr = PetscMalloc1(umax,&jutmp);CHKERRQ(ierr);
144       ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(PetscInt));CHKERRQ(ierr);
145       ierr = PetscFree(ju);CHKERRQ(ierr);
146       ju   = jutmp;
147       reallocs++; /* count how many times we realloc */
148     }
149 
150     /* save nonzero structure of k-th row in ju */
151     i=k;
152     while (nzk--) {
153       i           = q[i];
154       ju[juidx++] = i;
155     }
156   }
157 
158 #if defined(PETSC_USE_INFO)
159   if (ai[mbs] != 0) {
160     PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
161     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)f,(double)af);CHKERRQ(ierr);
162     ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
163     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g);\n",(double)af);CHKERRQ(ierr);
164     ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr);
165   } else {
166     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
167   }
168 #endif
169 
170   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
171   ierr = PetscFree2(jl,q);CHKERRQ(ierr);
172 
173   /* put together the new matrix */
174   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(F,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
175 
176   /* ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)iperm);CHKERRQ(ierr); */
177   b                = (Mat_SeqSBAIJ*)(F)->data;
178   b->singlemalloc  = PETSC_FALSE;
179   b->free_a        = PETSC_TRUE;
180   b->free_ij       = PETSC_TRUE;
181 
182   ierr    = PetscMalloc1((iu[mbs]+1)*bs2,&b->a);CHKERRQ(ierr);
183   b->j    = ju;
184   b->i    = iu;
185   b->diag = 0;
186   b->ilen = 0;
187   b->imax = 0;
188   b->row  = perm;
189 
190   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
191 
192   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
193 
194   b->icol = perm;
195   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
196   ierr    = PetscMalloc1(bs*mbs+bs,&b->solve_work);CHKERRQ(ierr);
197   /* In b structure:  Free imax, ilen, old a, old j.
198      Allocate idnew, solve_work, new a, new j */
199   ierr     = PetscLogObjectMemory((PetscObject)F,(iu[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
200   b->maxnz = b->nz = iu[mbs];
201 
202   (F)->info.factor_mallocs   = reallocs;
203   (F)->info.fill_ratio_given = f;
204   if (ai[mbs] != 0) {
205     (F)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
206   } else {
207     (F)->info.fill_ratio_needed = 0.0;
208   }
209   ierr = MatSeqSBAIJSetNumericFactorization_inplace(F,perm_identity);CHKERRQ(ierr);
210   PetscFunctionReturn(0);
211 }
212 /*
213     Symbolic U^T*D*U factorization for SBAIJ format.
214     See MatICCFactorSymbolic_SeqAIJ() for description of its data structure.
215 */
216 #include <petscbt.h>
217 #include <../src/mat/utils/freespace.h>
218 #undef __FUNCT__
219 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ"
220 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
221 {
222   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data;
223   Mat_SeqSBAIJ       *b;
224   PetscErrorCode     ierr;
225   PetscBool          perm_identity,missing;
226   PetscReal          fill = info->fill;
227   const PetscInt     *rip,*ai=a->i,*aj=a->j;
228   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,reallocs=0,prow;
229   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
230   PetscInt           nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr,*udiag;
231   PetscFreeSpaceList free_space=NULL,current_space=NULL;
232   PetscBT            lnkbt;
233 
234   PetscFunctionBegin;
235   if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must be square matrix, rows %D columns %D",A->rmap->n,A->cmap->n);
236   ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr);
237   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i);
238   if (bs > 1) {
239     ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(fact,A,perm,info);CHKERRQ(ierr);
240     PetscFunctionReturn(0);
241   }
242 
243   /* check whether perm is the identity mapping */
244   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
245   if (!perm_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format");
246   a->permute = PETSC_FALSE;
247   ierr       = ISGetIndices(perm,&rip);CHKERRQ(ierr);
248 
249   /* initialization */
250   ierr  = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr);
251   ierr  = PetscMalloc1(mbs+1,&udiag);CHKERRQ(ierr);
252   ui[0] = 0;
253 
254   /* jl: linked list for storing indices of the pivot rows
255      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
256   ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr);
257   for (i=0; i<mbs; i++) {
258     jl[i] = mbs; il[i] = 0;
259   }
260 
261   /* create and initialize a linked list for storing column indices of the active row k */
262   nlnk = mbs + 1;
263   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
264 
265   /* initial FreeSpace size is fill*(ai[mbs]+1) */
266   ierr          = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,ai[mbs]+1),&free_space);CHKERRQ(ierr);
267   current_space = free_space;
268 
269   for (k=0; k<mbs; k++) {  /* for each active row k */
270     /* initialize lnk by the column indices of row rip[k] of A */
271     nzk   = 0;
272     ncols = ai[k+1] - ai[k];
273     if (!ncols) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Empty row %D in matrix ",k);
274     for (j=0; j<ncols; j++) {
275       i       = *(aj + ai[k] + j);
276       cols[j] = i;
277     }
278     ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
279     nzk += nlnk;
280 
281     /* update lnk by computing fill-in for each pivot row to be merged in */
282     prow = jl[k]; /* 1st pivot row */
283 
284     while (prow < k) {
285       nextprow = jl[prow];
286       /* merge prow into k-th row */
287       jmin   = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
288       jmax   = ui[prow+1];
289       ncols  = jmax-jmin;
290       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
291       ierr   = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
292       nzk   += nlnk;
293 
294       /* update il and jl for prow */
295       if (jmin < jmax) {
296         il[prow] = jmin;
297         j        = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
298       }
299       prow = nextprow;
300     }
301 
302     /* if free space is not available, make more free space */
303     if (current_space->local_remaining<nzk) {
304       i    = mbs - k + 1; /* num of unfactored rows */
305       i    = PetscIntMultTruncate(i,PetscMin(nzk, i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
306       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
307       reallocs++;
308     }
309 
310     /* copy data into free space, then initialize lnk */
311     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
312 
313     /* add the k-th row into il and jl */
314     if (nzk > 1) {
315       i     = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
316       jl[k] = jl[i]; jl[i] = k;
317       il[k] = ui[k] + 1;
318     }
319     ui_ptr[k] = current_space->array;
320 
321     current_space->array           += nzk;
322     current_space->local_used      += nzk;
323     current_space->local_remaining -= nzk;
324 
325     ui[k+1] = ui[k] + nzk;
326   }
327 
328   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
329   ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr);
330 
331   /* destroy list of free space and other temporary array(s) */
332   ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr);
333   ierr = PetscFreeSpaceContiguous_Cholesky(&free_space,uj,mbs,ui,udiag);CHKERRQ(ierr); /* store matrix factor */
334   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
335 
336   /* put together the new matrix in MATSEQSBAIJ format */
337   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
338 
339   b               = (Mat_SeqSBAIJ*)fact->data;
340   b->singlemalloc = PETSC_FALSE;
341   b->free_a       = PETSC_TRUE;
342   b->free_ij      = PETSC_TRUE;
343 
344   ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr);
345 
346   b->j         = uj;
347   b->i         = ui;
348   b->diag      = udiag;
349   b->free_diag = PETSC_TRUE;
350   b->ilen      = 0;
351   b->imax      = 0;
352   b->row       = perm;
353   b->icol      = perm;
354 
355   ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
356   ierr = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
357 
358   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
359 
360   ierr = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr);
361   ierr = PetscLogObjectMemory((PetscObject)fact,ui[mbs]*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
362 
363   b->maxnz = b->nz = ui[mbs];
364 
365   fact->info.factor_mallocs   = reallocs;
366   fact->info.fill_ratio_given = fill;
367   if (ai[mbs] != 0) {
368     fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs];
369   } else {
370     fact->info.fill_ratio_needed = 0.0;
371   }
372 #if defined(PETSC_USE_INFO)
373   if (ai[mbs] != 0) {
374     PetscReal af = fact->info.fill_ratio_needed;
375     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr);
376     ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
377     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr);
378   } else {
379     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
380   }
381 #endif
382   fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
383   PetscFunctionReturn(0);
384 }
385 
386 #undef __FUNCT__
387 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ_inplace"
388 PetscErrorCode MatCholeskyFactorSymbolic_SeqSBAIJ_inplace(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
389 {
390   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data;
391   Mat_SeqSBAIJ       *b;
392   PetscErrorCode     ierr;
393   PetscBool          perm_identity,missing;
394   PetscReal          fill = info->fill;
395   const PetscInt     *rip,*ai,*aj;
396   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,reallocs=0,prow,d;
397   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
398   PetscInt           nlnk,*lnk,ncols,*cols,*uj,**ui_ptr,*uj_ptr;
399   PetscFreeSpaceList free_space=NULL,current_space=NULL;
400   PetscBT            lnkbt;
401 
402   PetscFunctionBegin;
403   ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr);
404   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d);
405 
406   /*
407    This code originally uses Modified Sparse Row (MSR) storage
408    (see page 85, "Iterative Methods ..." by Saad) for the output matrix B - bad choise!
409    Then it is rewritten so the factor B takes seqsbaij format. However the associated
410    MatCholeskyFactorNumeric_() have not been modified for the cases of bs>1 or !perm_identity,
411    thus the original code in MSR format is still used for these cases.
412    The code below should replace MatCholeskyFactorSymbolic_SeqSBAIJ_MSR() whenever
413    MatCholeskyFactorNumeric_() is modified for using sbaij symbolic factor.
414   */
415   if (bs > 1) {
416     ierr = MatCholeskyFactorSymbolic_SeqSBAIJ_MSR(fact,A,perm,info);CHKERRQ(ierr);
417     PetscFunctionReturn(0);
418   }
419 
420   /* check whether perm is the identity mapping */
421   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
422 
423   if (perm_identity) {
424     a->permute = PETSC_FALSE;
425 
426     ai = a->i; aj = a->j;
427   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format");
428   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
429 
430   /* initialization */
431   ierr  = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr);
432   ui[0] = 0;
433 
434   /* jl: linked list for storing indices of the pivot rows
435      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
436   ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr);
437   for (i=0; i<mbs; i++) {
438     jl[i] = mbs; il[i] = 0;
439   }
440 
441   /* create and initialize a linked list for storing column indices of the active row k */
442   nlnk = mbs + 1;
443   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
444 
445   /* initial FreeSpace size is fill*(ai[mbs]+1) */
446   ierr          = PetscFreeSpaceGet(PetscRealIntMultTruncate(fill,ai[mbs]+1),&free_space);CHKERRQ(ierr);
447   current_space = free_space;
448 
449   for (k=0; k<mbs; k++) {  /* for each active row k */
450     /* initialize lnk by the column indices of row rip[k] of A */
451     nzk   = 0;
452     ncols = ai[rip[k]+1] - ai[rip[k]];
453     for (j=0; j<ncols; j++) {
454       i       = *(aj + ai[rip[k]] + j);
455       cols[j] = rip[i];
456     }
457     ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
458     nzk += nlnk;
459 
460     /* update lnk by computing fill-in for each pivot row to be merged in */
461     prow = jl[k]; /* 1st pivot row */
462 
463     while (prow < k) {
464       nextprow = jl[prow];
465       /* merge prow into k-th row */
466       jmin   = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
467       jmax   = ui[prow+1];
468       ncols  = jmax-jmin;
469       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
470       ierr   = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
471       nzk   += nlnk;
472 
473       /* update il and jl for prow */
474       if (jmin < jmax) {
475         il[prow] = jmin;
476 
477         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
478       }
479       prow = nextprow;
480     }
481 
482     /* if free space is not available, make more free space */
483     if (current_space->local_remaining<nzk) {
484       i    = mbs - k + 1; /* num of unfactored rows */
485       i    = PetscMin(PetscIntMultTruncate(i,nzk), PetscIntMultTruncate(i,i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
486       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
487       reallocs++;
488     }
489 
490     /* copy data into free space, then initialize lnk */
491     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
492 
493     /* add the k-th row into il and jl */
494     if (nzk-1 > 0) {
495       i     = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
496       jl[k] = jl[i]; jl[i] = k;
497       il[k] = ui[k] + 1;
498     }
499     ui_ptr[k] = current_space->array;
500 
501     current_space->array           += nzk;
502     current_space->local_used      += nzk;
503     current_space->local_remaining -= nzk;
504 
505     ui[k+1] = ui[k] + nzk;
506   }
507 
508   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
509   ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr);
510 
511   /* destroy list of free space and other temporary array(s) */
512   ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr);
513   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
514   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
515 
516   /* put together the new matrix in MATSEQSBAIJ format */
517   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
518 
519   b               = (Mat_SeqSBAIJ*)fact->data;
520   b->singlemalloc = PETSC_FALSE;
521   b->free_a       = PETSC_TRUE;
522   b->free_ij      = PETSC_TRUE;
523 
524   ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr);
525 
526   b->j    = uj;
527   b->i    = ui;
528   b->diag = 0;
529   b->ilen = 0;
530   b->imax = 0;
531   b->row  = perm;
532 
533   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
534 
535   ierr     = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
536   b->icol  = perm;
537   ierr     = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
538   ierr     = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr);
539   ierr     = PetscLogObjectMemory((PetscObject)fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
540   b->maxnz = b->nz = ui[mbs];
541 
542   fact->info.factor_mallocs   = reallocs;
543   fact->info.fill_ratio_given = fill;
544   if (ai[mbs] != 0) {
545     fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs];
546   } else {
547     fact->info.fill_ratio_needed = 0.0;
548   }
549 #if defined(PETSC_USE_INFO)
550   if (ai[mbs] != 0) {
551     PetscReal af = fact->info.fill_ratio_needed;
552     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr);
553     ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
554     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr);
555   } else {
556     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
557   }
558 #endif
559   ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr);
560   PetscFunctionReturn(0);
561 }
562 
563 #undef __FUNCT__
564 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N"
565 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info)
566 {
567   Mat_SeqSBAIJ   *a   = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
568   IS             perm = b->row;
569   PetscErrorCode ierr;
570   const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j;
571   PetscInt       i,j;
572   PetscInt       *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
573   PetscInt       bs  =A->rmap->bs,bs2 = a->bs2;
574   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
575   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
576   MatScalar      *work;
577   PetscInt       *pivots;
578 
579   PetscFunctionBegin;
580   /* initialization */
581   ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr);
582   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
583   for (i=0; i<mbs; i++) {
584     jl[i] = mbs; il[0] = 0;
585   }
586   ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr);
587   ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr);
588 
589   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
590 
591   /* check permutation */
592   if (!a->permute) {
593     ai = a->i; aj = a->j; aa = a->a;
594   } else {
595     ai   = a->inew; aj = a->jnew;
596     ierr = PetscMalloc1(bs2*ai[mbs],&aa);CHKERRQ(ierr);
597     ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
598     ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr);
599     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
600 
601     for (i=0; i<mbs; i++) {
602       jmin = ai[i]; jmax = ai[i+1];
603       for (j=jmin; j<jmax; j++) {
604         while (a2anew[j] != j) {
605           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
606           for (k1=0; k1<bs2; k1++) {
607             dk[k1]       = aa[k*bs2+k1];
608             aa[k*bs2+k1] = aa[j*bs2+k1];
609             aa[j*bs2+k1] = dk[k1];
610           }
611         }
612         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
613         if (i > aj[j]) {
614           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
615           ap = aa + j*bs2;                     /* ptr to the beginning of j-th block of aa */
616           for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */
617           for (k=0; k<bs; k++) {               /* j-th block of aa <- dk^T */
618             for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1];
619           }
620         }
621       }
622     }
623     ierr = PetscFree(a2anew);CHKERRQ(ierr);
624   }
625 
626   /* for each row k */
627   for (k = 0; k<mbs; k++) {
628 
629     /*initialize k-th row with elements nonzero in row perm(k) of A */
630     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
631 
632     ap = aa + jmin*bs2;
633     for (j = jmin; j < jmax; j++) {
634       vj       = perm_ptr[aj[j]];   /* block col. index */
635       rtmp_ptr = rtmp + vj*bs2;
636       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
637     }
638 
639     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
640     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
641     i    = jl[k]; /* first row to be added to k_th row  */
642 
643     while (i < k) {
644       nexti = jl[i]; /* next row to be added to k_th row */
645 
646       /* compute multiplier */
647       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
648 
649       /* uik = -inv(Di)*U_bar(i,k) */
650       diag = ba + i*bs2;
651       u    = ba + ili*bs2;
652       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
653       PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
654 
655       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
656       PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
657       ierr = PetscLogFlops(4.0*bs*bs2);CHKERRQ(ierr);
658 
659       /* update -U(i,k) */
660       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
661 
662       /* add multiple of row i to k-th row ... */
663       jmin = ili + 1; jmax = bi[i+1];
664       if (jmin < jmax) {
665         for (j=jmin; j<jmax; j++) {
666           /* rtmp += -U(i,k)^T * U_bar(i,j) */
667           rtmp_ptr = rtmp + bj[j]*bs2;
668           u        = ba + j*bs2;
669           PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
670         }
671         ierr = PetscLogFlops(2.0*bs*bs2*(jmax-jmin));CHKERRQ(ierr);
672 
673         /* ... add i to row list for next nonzero entry */
674         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
675         j     = bj[jmin];
676         jl[i] = jl[j]; jl[j] = i; /* update jl */
677       }
678       i = nexti;
679     }
680 
681     /* save nonzero entries in k-th row of U ... */
682 
683     /* invert diagonal block */
684     diag = ba+k*bs2;
685     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
686     ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
687 
688     jmin = bi[k]; jmax = bi[k+1];
689     if (jmin < jmax) {
690       for (j=jmin; j<jmax; j++) {
691         vj       = bj[j];      /* block col. index of U */
692         u        = ba + j*bs2;
693         rtmp_ptr = rtmp + vj*bs2;
694         for (k1=0; k1<bs2; k1++) {
695           *u++        = *rtmp_ptr;
696           *rtmp_ptr++ = 0.0;
697         }
698       }
699 
700       /* ... add k to row list for first nonzero entry in k-th row */
701       il[k] = jmin;
702       i     = bj[jmin];
703       jl[k] = jl[i]; jl[i] = k;
704     }
705   }
706 
707   ierr = PetscFree(rtmp);CHKERRQ(ierr);
708   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
709   ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr);
710   ierr = PetscFree(pivots);CHKERRQ(ierr);
711   if (a->permute) {
712     ierr = PetscFree(aa);CHKERRQ(ierr);
713   }
714 
715   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
716 
717   C->ops->solve          = MatSolve_SeqSBAIJ_N_inplace;
718   C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace;
719   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_N_inplace;
720   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_N_inplace;
721 
722   C->assembled    = PETSC_TRUE;
723   C->preallocated = PETSC_TRUE;
724 
725   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
726   PetscFunctionReturn(0);
727 }
728 
729 #undef __FUNCT__
730 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering"
731 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
732 {
733   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
734   PetscErrorCode ierr;
735   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
736   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
737   PetscInt       bs  =A->rmap->bs,bs2 = a->bs2;
738   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
739   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
740   MatScalar      *work;
741   PetscInt       *pivots;
742 
743   PetscFunctionBegin;
744   ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr);
745   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
746   for (i=0; i<mbs; i++) {
747     jl[i] = mbs; il[0] = 0;
748   }
749   ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr);
750   ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr);
751 
752   ai = a->i; aj = a->j; aa = a->a;
753 
754   /* for each row k */
755   for (k = 0; k<mbs; k++) {
756 
757     /*initialize k-th row with elements nonzero in row k of A */
758     jmin = ai[k]; jmax = ai[k+1];
759     ap   = aa + jmin*bs2;
760     for (j = jmin; j < jmax; j++) {
761       vj       = aj[j];   /* block col. index */
762       rtmp_ptr = rtmp + vj*bs2;
763       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
764     }
765 
766     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
767     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
768     i    = jl[k]; /* first row to be added to k_th row  */
769 
770     while (i < k) {
771       nexti = jl[i]; /* next row to be added to k_th row */
772 
773       /* compute multiplier */
774       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
775 
776       /* uik = -inv(Di)*U_bar(i,k) */
777       diag = ba + i*bs2;
778       u    = ba + ili*bs2;
779       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
780       PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
781 
782       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
783       PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
784       ierr = PetscLogFlops(2.0*bs*bs2);CHKERRQ(ierr);
785 
786       /* update -U(i,k) */
787       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
788 
789       /* add multiple of row i to k-th row ... */
790       jmin = ili + 1; jmax = bi[i+1];
791       if (jmin < jmax) {
792         for (j=jmin; j<jmax; j++) {
793           /* rtmp += -U(i,k)^T * U_bar(i,j) */
794           rtmp_ptr = rtmp + bj[j]*bs2;
795           u        = ba + j*bs2;
796           PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
797         }
798         ierr = PetscLogFlops(2.0*bs*bs2*(jmax-jmin));CHKERRQ(ierr);
799 
800         /* ... add i to row list for next nonzero entry */
801         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
802         j     = bj[jmin];
803         jl[i] = jl[j]; jl[j] = i; /* update jl */
804       }
805       i = nexti;
806     }
807 
808     /* save nonzero entries in k-th row of U ... */
809 
810     /* invert diagonal block */
811     diag = ba+k*bs2;
812     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
813     ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
814 
815     jmin = bi[k]; jmax = bi[k+1];
816     if (jmin < jmax) {
817       for (j=jmin; j<jmax; j++) {
818         vj       = bj[j];      /* block col. index of U */
819         u        = ba + j*bs2;
820         rtmp_ptr = rtmp + vj*bs2;
821         for (k1=0; k1<bs2; k1++) {
822           *u++        = *rtmp_ptr;
823           *rtmp_ptr++ = 0.0;
824         }
825       }
826 
827       /* ... add k to row list for first nonzero entry in k-th row */
828       il[k] = jmin;
829       i     = bj[jmin];
830       jl[k] = jl[i]; jl[i] = k;
831     }
832   }
833 
834   ierr = PetscFree(rtmp);CHKERRQ(ierr);
835   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
836   ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr);
837   ierr = PetscFree(pivots);CHKERRQ(ierr);
838 
839   C->ops->solve          = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
840   C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
841   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
842   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
843   C->assembled           = PETSC_TRUE;
844   C->preallocated        = PETSC_TRUE;
845 
846   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
847   PetscFunctionReturn(0);
848 }
849 
850 /*
851     Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP.
852     Version for blocks 2 by 2.
853 */
854 #undef __FUNCT__
855 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2"
856 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info)
857 {
858   Mat_SeqSBAIJ   *a   = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
859   IS             perm = b->row;
860   PetscErrorCode ierr;
861   const PetscInt *ai,*aj,*perm_ptr;
862   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
863   PetscInt       *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
864   MatScalar      *ba = b->a,*aa,*ap;
865   MatScalar      *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4];
866   PetscReal      shift = info->shiftamount;
867   PetscBool      zeropivotdetected;
868 
869   PetscFunctionBegin;
870   /* initialization */
871   /* il and jl record the first nonzero element in each row of the accessing
872      window U(0:k, k:mbs-1).
873      jl:    list of rows to be added to uneliminated rows
874             i>= k: jl(i) is the first row to be added to row i
875             i<  k: jl(i) is the row following row i in some list of rows
876             jl(i) = mbs indicates the end of a list
877      il(i): points to the first nonzero element in columns k,...,mbs-1 of
878             row i of U */
879   ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr);
880   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
881   for (i=0; i<mbs; i++) {
882     jl[i] = mbs; il[0] = 0;
883   }
884   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
885 
886   /* check permutation */
887   if (!a->permute) {
888     ai = a->i; aj = a->j; aa = a->a;
889   } else {
890     ai   = a->inew; aj = a->jnew;
891     ierr = PetscMalloc1(4*ai[mbs],&aa);CHKERRQ(ierr);
892     ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
893     ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr);
894     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
895 
896     for (i=0; i<mbs; i++) {
897       jmin = ai[i]; jmax = ai[i+1];
898       for (j=jmin; j<jmax; j++) {
899         while (a2anew[j] != j) {
900           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
901           for (k1=0; k1<4; k1++) {
902             dk[k1]     = aa[k*4+k1];
903             aa[k*4+k1] = aa[j*4+k1];
904             aa[j*4+k1] = dk[k1];
905           }
906         }
907         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
908         if (i > aj[j]) {
909           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
910           ap    = aa + j*4;  /* ptr to the beginning of the block */
911           dk[1] = ap[1];     /* swap ap[1] and ap[2] */
912           ap[1] = ap[2];
913           ap[2] = dk[1];
914         }
915       }
916     }
917     ierr = PetscFree(a2anew);CHKERRQ(ierr);
918   }
919 
920   /* for each row k */
921   for (k = 0; k<mbs; k++) {
922 
923     /*initialize k-th row with elements nonzero in row perm(k) of A */
924     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
925     ap   = aa + jmin*4;
926     for (j = jmin; j < jmax; j++) {
927       vj       = perm_ptr[aj[j]];   /* block col. index */
928       rtmp_ptr = rtmp + vj*4;
929       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
930     }
931 
932     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
933     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
934     i    = jl[k]; /* first row to be added to k_th row  */
935 
936     while (i < k) {
937       nexti = jl[i]; /* next row to be added to k_th row */
938 
939       /* compute multiplier */
940       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
941 
942       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
943       diag   = ba + i*4;
944       u      = ba + ili*4;
945       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
946       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
947       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
948       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
949 
950       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
951       dk[0] += uik[0]*u[0] + uik[1]*u[1];
952       dk[1] += uik[2]*u[0] + uik[3]*u[1];
953       dk[2] += uik[0]*u[2] + uik[1]*u[3];
954       dk[3] += uik[2]*u[2] + uik[3]*u[3];
955 
956       ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr);
957 
958       /* update -U(i,k): ba[ili] = uik */
959       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
960 
961       /* add multiple of row i to k-th row ... */
962       jmin = ili + 1; jmax = bi[i+1];
963       if (jmin < jmax) {
964         for (j=jmin; j<jmax; j++) {
965           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
966           rtmp_ptr     = rtmp + bj[j]*4;
967           u            = ba + j*4;
968           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
969           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
970           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
971           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
972         }
973         ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr);
974 
975         /* ... add i to row list for next nonzero entry */
976         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
977         j     = bj[jmin];
978         jl[i] = jl[j]; jl[j] = i; /* update jl */
979       }
980       i = nexti;
981     }
982 
983     /* save nonzero entries in k-th row of U ... */
984 
985     /* invert diagonal block */
986     diag = ba+k*4;
987     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
988     ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,!A->erroriffailure,&zeropivotdetected);CHKERRQ(ierr);
989     if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
990 
991     jmin = bi[k]; jmax = bi[k+1];
992     if (jmin < jmax) {
993       for (j=jmin; j<jmax; j++) {
994         vj       = bj[j];      /* block col. index of U */
995         u        = ba + j*4;
996         rtmp_ptr = rtmp + vj*4;
997         for (k1=0; k1<4; k1++) {
998           *u++        = *rtmp_ptr;
999           *rtmp_ptr++ = 0.0;
1000         }
1001       }
1002 
1003       /* ... add k to row list for first nonzero entry in k-th row */
1004       il[k] = jmin;
1005       i     = bj[jmin];
1006       jl[k] = jl[i]; jl[i] = k;
1007     }
1008   }
1009 
1010   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1011   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1012   if (a->permute) {
1013     ierr = PetscFree(aa);CHKERRQ(ierr);
1014   }
1015   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
1016 
1017   C->ops->solve          = MatSolve_SeqSBAIJ_2_inplace;
1018   C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace;
1019   C->assembled           = PETSC_TRUE;
1020   C->preallocated        = PETSC_TRUE;
1021 
1022   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
1023   PetscFunctionReturn(0);
1024 }
1025 
1026 /*
1027       Version for when blocks are 2 by 2 Using natural ordering
1028 */
1029 #undef __FUNCT__
1030 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering"
1031 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
1032 {
1033   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
1034   PetscErrorCode ierr;
1035   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
1036   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
1037   MatScalar      *ba = b->a,*aa,*ap,dk[8],uik[8];
1038   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
1039   PetscReal      shift = info->shiftamount;
1040   PetscBool      zeropivotdetected;
1041 
1042   PetscFunctionBegin;
1043   /* initialization */
1044   /* il and jl record the first nonzero element in each row of the accessing
1045      window U(0:k, k:mbs-1).
1046      jl:    list of rows to be added to uneliminated rows
1047             i>= k: jl(i) is the first row to be added to row i
1048             i<  k: jl(i) is the row following row i in some list of rows
1049             jl(i) = mbs indicates the end of a list
1050      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1051             row i of U */
1052   ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr);
1053   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
1054   for (i=0; i<mbs; i++) {
1055     jl[i] = mbs; il[0] = 0;
1056   }
1057   ai = a->i; aj = a->j; aa = a->a;
1058 
1059   /* for each row k */
1060   for (k = 0; k<mbs; k++) {
1061 
1062     /*initialize k-th row with elements nonzero in row k of A */
1063     jmin = ai[k]; jmax = ai[k+1];
1064     ap   = aa + jmin*4;
1065     for (j = jmin; j < jmax; j++) {
1066       vj       = aj[j];   /* block col. index */
1067       rtmp_ptr = rtmp + vj*4;
1068       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
1069     }
1070 
1071     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
1072     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
1073     i    = jl[k]; /* first row to be added to k_th row  */
1074 
1075     while (i < k) {
1076       nexti = jl[i]; /* next row to be added to k_th row */
1077 
1078       /* compute multiplier */
1079       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1080 
1081       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
1082       diag   = ba + i*4;
1083       u      = ba + ili*4;
1084       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
1085       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
1086       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
1087       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
1088 
1089       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
1090       dk[0] += uik[0]*u[0] + uik[1]*u[1];
1091       dk[1] += uik[2]*u[0] + uik[3]*u[1];
1092       dk[2] += uik[0]*u[2] + uik[1]*u[3];
1093       dk[3] += uik[2]*u[2] + uik[3]*u[3];
1094 
1095       ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr);
1096 
1097       /* update -U(i,k): ba[ili] = uik */
1098       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
1099 
1100       /* add multiple of row i to k-th row ... */
1101       jmin = ili + 1; jmax = bi[i+1];
1102       if (jmin < jmax) {
1103         for (j=jmin; j<jmax; j++) {
1104           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
1105           rtmp_ptr     = rtmp + bj[j]*4;
1106           u            = ba + j*4;
1107           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
1108           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
1109           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
1110           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
1111         }
1112         ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr);
1113 
1114         /* ... add i to row list for next nonzero entry */
1115         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
1116         j     = bj[jmin];
1117         jl[i] = jl[j]; jl[j] = i; /* update jl */
1118       }
1119       i = nexti;
1120     }
1121 
1122     /* save nonzero entries in k-th row of U ... */
1123 
1124     /* invert diagonal block */
1125     diag = ba+k*4;
1126     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
1127     ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,!A->erroriffailure,&zeropivotdetected);CHKERRQ(ierr);
1128     if (zeropivotdetected) C->errortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
1129 
1130     jmin = bi[k]; jmax = bi[k+1];
1131     if (jmin < jmax) {
1132       for (j=jmin; j<jmax; j++) {
1133         vj       = bj[j];      /* block col. index of U */
1134         u        = ba + j*4;
1135         rtmp_ptr = rtmp + vj*4;
1136         for (k1=0; k1<4; k1++) {
1137           *u++        = *rtmp_ptr;
1138           *rtmp_ptr++ = 0.0;
1139         }
1140       }
1141 
1142       /* ... add k to row list for first nonzero entry in k-th row */
1143       il[k] = jmin;
1144       i     = bj[jmin];
1145       jl[k] = jl[i]; jl[i] = k;
1146     }
1147   }
1148 
1149   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1150   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1151 
1152   C->ops->solve          = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1153   C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1154   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1155   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1156   C->assembled           = PETSC_TRUE;
1157   C->preallocated        = PETSC_TRUE;
1158 
1159   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
1160   PetscFunctionReturn(0);
1161 }
1162 
1163 /*
1164     Numeric U^T*D*U factorization for SBAIJ format.
1165     Version for blocks are 1 by 1.
1166 */
1167 #undef __FUNCT__
1168 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace"
1169 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info)
1170 {
1171   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data;
1172   IS             ip=b->row;
1173   PetscErrorCode ierr;
1174   const PetscInt *ai,*aj,*rip;
1175   PetscInt       *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol;
1176   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
1177   MatScalar      *rtmp,*ba=b->a,*bval,*aa,dk,uikdi;
1178   PetscReal      rs;
1179   FactorShiftCtx sctx;
1180 
1181   PetscFunctionBegin;
1182   /* MatPivotSetUp(): initialize shift context sctx */
1183   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1184 
1185   ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr);
1186   if (!a->permute) {
1187     ai = a->i; aj = a->j; aa = a->a;
1188   } else {
1189     ai     = a->inew; aj = a->jnew;
1190     nz     = ai[mbs];
1191     ierr   = PetscMalloc1(nz,&aa);CHKERRQ(ierr);
1192     a2anew = a->a2anew;
1193     bval   = a->a;
1194     for (j=0; j<nz; j++) {
1195       aa[a2anew[j]] = *(bval++);
1196     }
1197   }
1198 
1199   /* initialization */
1200   /* il and jl record the first nonzero element in each row of the accessing
1201      window U(0:k, k:mbs-1).
1202      jl:    list of rows to be added to uneliminated rows
1203             i>= k: jl(i) is the first row to be added to row i
1204             i<  k: jl(i) is the row following row i in some list of rows
1205             jl(i) = mbs indicates the end of a list
1206      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1207             row i of U */
1208   ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&jl);CHKERRQ(ierr);
1209 
1210   do {
1211     sctx.newshift = PETSC_FALSE;
1212     for (i=0; i<mbs; i++) {
1213       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1214     }
1215 
1216     for (k = 0; k<mbs; k++) {
1217       /*initialize k-th row by the perm[k]-th row of A */
1218       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
1219       bval = ba + bi[k];
1220       for (j = jmin; j < jmax; j++) {
1221         col       = rip[aj[j]];
1222         rtmp[col] = aa[j];
1223         *bval++   = 0.0; /* for in-place factorization */
1224       }
1225 
1226       /* shift the diagonal of the matrix */
1227       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1228 
1229       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1230       dk = rtmp[k];
1231       i  = jl[k]; /* first row to be added to k_th row  */
1232 
1233       while (i < k) {
1234         nexti = jl[i]; /* next row to be added to k_th row */
1235 
1236         /* compute multiplier, update diag(k) and U(i,k) */
1237         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1238         uikdi   = -ba[ili]*ba[bi[i]]; /* diagonal(k) */
1239         dk     += uikdi*ba[ili];
1240         ba[ili] = uikdi; /* -U(i,k) */
1241 
1242         /* add multiple of row i to k-th row */
1243         jmin = ili + 1; jmax = bi[i+1];
1244         if (jmin < jmax) {
1245           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
1246           ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr);
1247 
1248           /* update il and jl for row i */
1249           il[i] = jmin;
1250           j     = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1251         }
1252         i = nexti;
1253       }
1254 
1255       /* shift the diagonals when zero pivot is detected */
1256       /* compute rs=sum of abs(off-diagonal) */
1257       rs   = 0.0;
1258       jmin = bi[k]+1;
1259       nz   = bi[k+1] - jmin;
1260       if (nz) {
1261         bcol = bj + jmin;
1262         while (nz--) {
1263           rs += PetscAbsScalar(rtmp[*bcol]);
1264           bcol++;
1265         }
1266       }
1267 
1268       sctx.rs = rs;
1269       sctx.pv = dk;
1270       ierr    = MatPivotCheck(C,A,info,&sctx,k);CHKERRQ(ierr);
1271       if (sctx.newshift) break;    /* sctx.shift_amount is updated */
1272       dk = sctx.pv;
1273 
1274       /* copy data into U(k,:) */
1275       ba[bi[k]] = 1.0/dk; /* U(k,k) */
1276       jmin      = bi[k]+1; jmax = bi[k+1];
1277       if (jmin < jmax) {
1278         for (j=jmin; j<jmax; j++) {
1279           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
1280         }
1281         /* add the k-th row into il and jl */
1282         il[k] = jmin;
1283         i     = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1284       }
1285     }
1286   } while (sctx.newshift);
1287   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
1288   if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);}
1289 
1290   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
1291 
1292   C->ops->solve          = MatSolve_SeqSBAIJ_1_inplace;
1293   C->ops->solves         = MatSolves_SeqSBAIJ_1_inplace;
1294   C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace;
1295   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_inplace;
1296   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_inplace;
1297   C->assembled           = PETSC_TRUE;
1298   C->preallocated        = PETSC_TRUE;
1299 
1300   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
1301   if (sctx.nshift) {
1302     if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1303       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1304     } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1305       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1306     }
1307   }
1308   PetscFunctionReturn(0);
1309 }
1310 
1311 /*
1312   Version for when blocks are 1 by 1 Using natural ordering under new datastructure
1313   Modified from MatCholeskyFactorNumeric_SeqAIJ()
1314 */
1315 #undef __FUNCT__
1316 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering"
1317 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info)
1318 {
1319   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data;
1320   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)B->data;
1321   PetscErrorCode ierr;
1322   PetscInt       i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp;
1323   PetscInt       *ai=a->i,*aj=a->j,*ajtmp;
1324   PetscInt       k,jmin,jmax,*c2r,*il,col,nexti,ili,nz;
1325   MatScalar      *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi;
1326   FactorShiftCtx sctx;
1327   PetscReal      rs;
1328   MatScalar      d,*v;
1329 
1330   PetscFunctionBegin;
1331   ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&c2r);CHKERRQ(ierr);
1332 
1333   /* MatPivotSetUp(): initialize shift context sctx */
1334   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1335 
1336   if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */
1337     sctx.shift_top = info->zeropivot;
1338 
1339     ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr);
1340 
1341     for (i=0; i<mbs; i++) {
1342       /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */
1343       d        = (aa)[a->diag[i]];
1344       rtmp[i] += -PetscRealPart(d);  /* diagonal entry */
1345       ajtmp    = aj + ai[i] + 1;     /* exclude diagonal */
1346       v        = aa + ai[i] + 1;
1347       nz       = ai[i+1] - ai[i] - 1;
1348       for (j=0; j<nz; j++) {
1349         rtmp[i]        += PetscAbsScalar(v[j]);
1350         rtmp[ajtmp[j]] += PetscAbsScalar(v[j]);
1351       }
1352       if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]);
1353     }
1354     sctx.shift_top *= 1.1;
1355     sctx.nshift_max = 5;
1356     sctx.shift_lo   = 0.;
1357     sctx.shift_hi   = 1.;
1358   }
1359 
1360   /* allocate working arrays
1361      c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col
1362      il:  for active k row, il[i] gives the index of the 1st nonzero entry in U[i,k:n-1] in bj and ba arrays
1363   */
1364   do {
1365     sctx.newshift = PETSC_FALSE;
1366 
1367     for (i=0; i<mbs; i++) c2r[i] = mbs;
1368     if (mbs) il[0] = 0;
1369 
1370     for (k = 0; k<mbs; k++) {
1371       /* zero rtmp */
1372       nz    = bi[k+1] - bi[k];
1373       bjtmp = bj + bi[k];
1374       for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0;
1375 
1376       /* load in initial unfactored row */
1377       bval = ba + bi[k];
1378       jmin = ai[k]; jmax = ai[k+1];
1379       for (j = jmin; j < jmax; j++) {
1380         col       = aj[j];
1381         rtmp[col] = aa[j];
1382         *bval++   = 0.0; /* for in-place factorization */
1383       }
1384       /* shift the diagonal of the matrix: ZeropivotApply() */
1385       rtmp[k] += sctx.shift_amount;  /* shift the diagonal of the matrix */
1386 
1387       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1388       dk = rtmp[k];
1389       i  = c2r[k]; /* first row to be added to k_th row  */
1390 
1391       while (i < k) {
1392         nexti = c2r[i]; /* next row to be added to k_th row */
1393 
1394         /* compute multiplier, update diag(k) and U(i,k) */
1395         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1396         uikdi   = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */
1397         dk     += uikdi*ba[ili]; /* update diag[k] */
1398         ba[ili] = uikdi; /* -U(i,k) */
1399 
1400         /* add multiple of row i to k-th row */
1401         jmin = ili + 1; jmax = bi[i+1];
1402         if (jmin < jmax) {
1403           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
1404           /* update il and c2r for row i */
1405           il[i] = jmin;
1406           j     = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i;
1407         }
1408         i = nexti;
1409       }
1410 
1411       /* copy data into U(k,:) */
1412       rs   = 0.0;
1413       jmin = bi[k]; jmax = bi[k+1]-1;
1414       if (jmin < jmax) {
1415         for (j=jmin; j<jmax; j++) {
1416           col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]);
1417         }
1418         /* add the k-th row into il and c2r */
1419         il[k] = jmin;
1420         i     = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k;
1421       }
1422 
1423       sctx.rs = rs;
1424       sctx.pv = dk;
1425       ierr    = MatPivotCheck(B,A,info,&sctx,k);CHKERRQ(ierr);
1426       if (sctx.newshift) break;
1427       dk = sctx.pv;
1428 
1429       ba[bdiag[k]] = 1.0/dk; /* U(k,k) */
1430     }
1431   } while (sctx.newshift);
1432 
1433   ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr);
1434 
1435   B->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1436   B->ops->solves         = MatSolves_SeqSBAIJ_1;
1437   B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1438   B->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering;
1439   B->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering;
1440 
1441   B->assembled    = PETSC_TRUE;
1442   B->preallocated = PETSC_TRUE;
1443 
1444   ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr);
1445 
1446   /* MatPivotView() */
1447   if (sctx.nshift) {
1448     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1449       ierr = PetscInfo4(A,"number of shift_pd tries %D, shift_amount %g, diagonal shifted up by %e fraction top_value %e\n",sctx.nshift,(double)sctx.shift_amount,(double)sctx.shift_fraction,(double)sctx.shift_top);CHKERRQ(ierr);
1450     } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1451       ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1452     } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) {
1453       ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %g\n",sctx.nshift,(double)info->shiftamount);CHKERRQ(ierr);
1454     }
1455   }
1456   PetscFunctionReturn(0);
1457 }
1458 
1459 #undef __FUNCT__
1460 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace"
1461 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info)
1462 {
1463   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data;
1464   PetscErrorCode ierr;
1465   PetscInt       i,j,mbs = a->mbs;
1466   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
1467   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
1468   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
1469   PetscReal      rs;
1470   FactorShiftCtx sctx;
1471 
1472   PetscFunctionBegin;
1473   /* MatPivotSetUp(): initialize shift context sctx */
1474   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1475 
1476   /* initialization */
1477   /* il and jl record the first nonzero element in each row of the accessing
1478      window U(0:k, k:mbs-1).
1479      jl:    list of rows to be added to uneliminated rows
1480             i>= k: jl(i) is the first row to be added to row i
1481             i<  k: jl(i) is the row following row i in some list of rows
1482             jl(i) = mbs indicates the end of a list
1483      il(i): points to the first nonzero element in U(i,k:mbs-1)
1484   */
1485   ierr = PetscMalloc1(mbs,&rtmp);CHKERRQ(ierr);
1486   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
1487 
1488   do {
1489     sctx.newshift = PETSC_FALSE;
1490     for (i=0; i<mbs; i++) {
1491       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1492     }
1493 
1494     for (k = 0; k<mbs; k++) {
1495       /*initialize k-th row with elements nonzero in row perm(k) of A */
1496       nz   = ai[k+1] - ai[k];
1497       acol = aj + ai[k];
1498       aval = aa + ai[k];
1499       bval = ba + bi[k];
1500       while (nz--) {
1501         rtmp[*acol++] = *aval++;
1502         *bval++       = 0.0; /* for in-place factorization */
1503       }
1504 
1505       /* shift the diagonal of the matrix */
1506       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1507 
1508       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1509       dk = rtmp[k];
1510       i  = jl[k]; /* first row to be added to k_th row  */
1511 
1512       while (i < k) {
1513         nexti = jl[i]; /* next row to be added to k_th row */
1514         /* compute multiplier, update D(k) and U(i,k) */
1515         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1516         uikdi   = -ba[ili]*ba[bi[i]];
1517         dk     += uikdi*ba[ili];
1518         ba[ili] = uikdi; /* -U(i,k) */
1519 
1520         /* add multiple of row i to k-th row ... */
1521         jmin = ili + 1;
1522         nz   = bi[i+1] - jmin;
1523         if (nz > 0) {
1524           bcol = bj + jmin;
1525           bval = ba + jmin;
1526           ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr);
1527           while (nz--) rtmp[*bcol++] += uikdi*(*bval++);
1528 
1529           /* update il and jl for i-th row */
1530           il[i] = jmin;
1531           j     = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1532         }
1533         i = nexti;
1534       }
1535 
1536       /* shift the diagonals when zero pivot is detected */
1537       /* compute rs=sum of abs(off-diagonal) */
1538       rs   = 0.0;
1539       jmin = bi[k]+1;
1540       nz   = bi[k+1] - jmin;
1541       if (nz) {
1542         bcol = bj + jmin;
1543         while (nz--) {
1544           rs += PetscAbsScalar(rtmp[*bcol]);
1545           bcol++;
1546         }
1547       }
1548 
1549       sctx.rs = rs;
1550       sctx.pv = dk;
1551       ierr    = MatPivotCheck(C,A,info,&sctx,k);CHKERRQ(ierr);
1552       if (sctx.newshift) break;    /* sctx.shift_amount is updated */
1553       dk = sctx.pv;
1554 
1555       /* copy data into U(k,:) */
1556       ba[bi[k]] = 1.0/dk;
1557       jmin      = bi[k]+1;
1558       nz        = bi[k+1] - jmin;
1559       if (nz) {
1560         bcol = bj + jmin;
1561         bval = ba + jmin;
1562         while (nz--) {
1563           *bval++       = rtmp[*bcol];
1564           rtmp[*bcol++] = 0.0;
1565         }
1566         /* add k-th row into il and jl */
1567         il[k] = jmin;
1568         i     = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1569       }
1570     } /* end of for (k = 0; k<mbs; k++) */
1571   } while (sctx.newshift);
1572   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1573   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1574 
1575   C->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1576   C->ops->solves         = MatSolves_SeqSBAIJ_1_inplace;
1577   C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1578   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1579   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1580 
1581   C->assembled    = PETSC_TRUE;
1582   C->preallocated = PETSC_TRUE;
1583 
1584   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
1585   if (sctx.nshift) {
1586     if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1587       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1588     } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1589       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1590     }
1591   }
1592   PetscFunctionReturn(0);
1593 }
1594 
1595 #undef __FUNCT__
1596 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ"
1597 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info)
1598 {
1599   PetscErrorCode ierr;
1600   Mat            C;
1601 
1602   PetscFunctionBegin;
1603   ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr);
1604   ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr);
1605   ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr);
1606 
1607   A->ops->solve          = C->ops->solve;
1608   A->ops->solvetranspose = C->ops->solvetranspose;
1609 
1610   ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr);
1611   PetscFunctionReturn(0);
1612 }
1613 
1614 
1615