xref: /petsc/src/mat/impls/sbaij/seq/sbaijfact.c (revision bebe2cf65d55febe21a5af8db2bd2e168caaa2e7)
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((PetscInt)(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   *= 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 {
428     SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported for sbaij matrix. Use aij format");
429 #if 0
430     /* There are bugs for reordeing. Needs further work.
431        MatReordering for sbaij cannot be efficient. User should use aij formt! */
432     a->permute = PETSC_TRUE;
433 
434     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
435     ai   = a->inew; aj = a->jnew;
436 #endif
437   }
438   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
439 
440   /* initialization */
441   ierr  = PetscMalloc1(mbs+1,&ui);CHKERRQ(ierr);
442   ui[0] = 0;
443 
444   /* jl: linked list for storing indices of the pivot rows
445      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
446   ierr = PetscMalloc4(mbs,&ui_ptr,mbs,&il,mbs,&jl,mbs,&cols);CHKERRQ(ierr);
447   for (i=0; i<mbs; i++) {
448     jl[i] = mbs; il[i] = 0;
449   }
450 
451   /* create and initialize a linked list for storing column indices of the active row k */
452   nlnk = mbs + 1;
453   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
454 
455   /* initial FreeSpace size is fill*(ai[mbs]+1) */
456   ierr          = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr);
457   current_space = free_space;
458 
459   for (k=0; k<mbs; k++) {  /* for each active row k */
460     /* initialize lnk by the column indices of row rip[k] of A */
461     nzk   = 0;
462     ncols = ai[rip[k]+1] - ai[rip[k]];
463     for (j=0; j<ncols; j++) {
464       i       = *(aj + ai[rip[k]] + j);
465       cols[j] = rip[i];
466     }
467     ierr = PetscLLAdd(ncols,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
468     nzk += nlnk;
469 
470     /* update lnk by computing fill-in for each pivot row to be merged in */
471     prow = jl[k]; /* 1st pivot row */
472 
473     while (prow < k) {
474       nextprow = jl[prow];
475       /* merge prow into k-th row */
476       jmin   = il[prow] + 1; /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
477       jmax   = ui[prow+1];
478       ncols  = jmax-jmin;
479       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
480       ierr   = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
481       nzk   += nlnk;
482 
483       /* update il and jl for prow */
484       if (jmin < jmax) {
485         il[prow] = jmin;
486 
487         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
488       }
489       prow = nextprow;
490     }
491 
492     /* if free space is not available, make more free space */
493     if (current_space->local_remaining<nzk) {
494       i    = mbs - k + 1; /* num of unfactored rows */
495       i    = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
496       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
497       reallocs++;
498     }
499 
500     /* copy data into free space, then initialize lnk */
501     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
502 
503     /* add the k-th row into il and jl */
504     if (nzk-1 > 0) {
505       i     = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
506       jl[k] = jl[i]; jl[i] = k;
507       il[k] = ui[k] + 1;
508     }
509     ui_ptr[k] = current_space->array;
510 
511     current_space->array           += nzk;
512     current_space->local_used      += nzk;
513     current_space->local_remaining -= nzk;
514 
515     ui[k+1] = ui[k] + nzk;
516   }
517 
518   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
519   ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr);
520 
521   /* destroy list of free space and other temporary array(s) */
522   ierr = PetscMalloc1(ui[mbs]+1,&uj);CHKERRQ(ierr);
523   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
524   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
525 
526   /* put together the new matrix in MATSEQSBAIJ format */
527   ierr = MatSeqSBAIJSetPreallocation_SeqSBAIJ(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
528 
529   b               = (Mat_SeqSBAIJ*)fact->data;
530   b->singlemalloc = PETSC_FALSE;
531   b->free_a       = PETSC_TRUE;
532   b->free_ij      = PETSC_TRUE;
533 
534   ierr = PetscMalloc1(ui[mbs]+1,&b->a);CHKERRQ(ierr);
535 
536   b->j    = uj;
537   b->i    = ui;
538   b->diag = 0;
539   b->ilen = 0;
540   b->imax = 0;
541   b->row  = perm;
542 
543   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
544 
545   ierr     = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
546   b->icol  = perm;
547   ierr     = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
548   ierr     = PetscMalloc1(mbs+1,&b->solve_work);CHKERRQ(ierr);
549   ierr     = PetscLogObjectMemory((PetscObject)fact,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
550   b->maxnz = b->nz = ui[mbs];
551 
552   fact->info.factor_mallocs   = reallocs;
553   fact->info.fill_ratio_given = fill;
554   if (ai[mbs] != 0) {
555     fact->info.fill_ratio_needed = ((PetscReal)ui[mbs])/ai[mbs];
556   } else {
557     fact->info.fill_ratio_needed = 0.0;
558   }
559 #if defined(PETSC_USE_INFO)
560   if (ai[mbs] != 0) {
561     PetscReal af = fact->info.fill_ratio_needed;
562     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)fill,(double)af);CHKERRQ(ierr);
563     ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
564     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g) for best performance.\n",(double)af);CHKERRQ(ierr);
565   } else {
566     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
567   }
568 #endif
569   ierr = MatSeqSBAIJSetNumericFactorization_inplace(fact,perm_identity);CHKERRQ(ierr);
570   PetscFunctionReturn(0);
571 }
572 
573 #undef __FUNCT__
574 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N"
575 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat C,Mat A,const MatFactorInfo *info)
576 {
577   Mat_SeqSBAIJ   *a   = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
578   IS             perm = b->row;
579   PetscErrorCode ierr;
580   const PetscInt *ai,*aj,*perm_ptr,mbs=a->mbs,*bi=b->i,*bj=b->j;
581   PetscInt       i,j;
582   PetscInt       *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
583   PetscInt       bs  =A->rmap->bs,bs2 = a->bs2,bslog = 0;
584   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
585   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
586   MatScalar      *work;
587   PetscInt       *pivots;
588 
589   PetscFunctionBegin;
590   /* initialization */
591   ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr);
592   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
593   for (i=0; i<mbs; i++) {
594     jl[i] = mbs; il[0] = 0;
595   }
596   ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr);
597   ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr);
598 
599   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
600 
601   /* check permutation */
602   if (!a->permute) {
603     ai = a->i; aj = a->j; aa = a->a;
604   } else {
605     ai   = a->inew; aj = a->jnew;
606     ierr = PetscMalloc1(bs2*ai[mbs],&aa);CHKERRQ(ierr);
607     ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
608     ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr);
609     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
610 
611     /* flops in while loop */
612     bslog = 2*bs*bs2;
613 
614     for (i=0; i<mbs; i++) {
615       jmin = ai[i]; jmax = ai[i+1];
616       for (j=jmin; j<jmax; j++) {
617         while (a2anew[j] != j) {
618           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
619           for (k1=0; k1<bs2; k1++) {
620             dk[k1]       = aa[k*bs2+k1];
621             aa[k*bs2+k1] = aa[j*bs2+k1];
622             aa[j*bs2+k1] = dk[k1];
623           }
624         }
625         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
626         if (i > aj[j]) {
627           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
628           ap = aa + j*bs2;                     /* ptr to the beginning of j-th block of aa */
629           for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */
630           for (k=0; k<bs; k++) {               /* j-th block of aa <- dk^T */
631             for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1];
632           }
633         }
634       }
635     }
636     ierr = PetscFree(a2anew);CHKERRQ(ierr);
637   }
638 
639   /* for each row k */
640   for (k = 0; k<mbs; k++) {
641 
642     /*initialize k-th row with elements nonzero in row perm(k) of A */
643     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
644 
645     ap = aa + jmin*bs2;
646     for (j = jmin; j < jmax; j++) {
647       vj       = perm_ptr[aj[j]];   /* block col. index */
648       rtmp_ptr = rtmp + vj*bs2;
649       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
650     }
651 
652     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
653     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
654     i    = jl[k]; /* first row to be added to k_th row  */
655 
656     while (i < k) {
657       nexti = jl[i]; /* next row to be added to k_th row */
658 
659       /* compute multiplier */
660       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
661 
662       /* uik = -inv(Di)*U_bar(i,k) */
663       diag = ba + i*bs2;
664       u    = ba + ili*bs2;
665       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
666       PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
667 
668       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
669       PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
670       ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr);
671 
672       /* update -U(i,k) */
673       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
674 
675       /* add multiple of row i to k-th row ... */
676       jmin = ili + 1; jmax = bi[i+1];
677       if (jmin < jmax) {
678         for (j=jmin; j<jmax; j++) {
679           /* rtmp += -U(i,k)^T * U_bar(i,j) */
680           rtmp_ptr = rtmp + bj[j]*bs2;
681           u        = ba + j*bs2;
682           PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
683         }
684         ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr);
685 
686         /* ... add i to row list for next nonzero entry */
687         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
688         j     = bj[jmin];
689         jl[i] = jl[j]; jl[j] = i; /* update jl */
690       }
691       i = nexti;
692     }
693 
694     /* save nonzero entries in k-th row of U ... */
695 
696     /* invert diagonal block */
697     diag = ba+k*bs2;
698     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
699     ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
700 
701     jmin = bi[k]; jmax = bi[k+1];
702     if (jmin < jmax) {
703       for (j=jmin; j<jmax; j++) {
704         vj       = bj[j];      /* block col. index of U */
705         u        = ba + j*bs2;
706         rtmp_ptr = rtmp + vj*bs2;
707         for (k1=0; k1<bs2; k1++) {
708           *u++        = *rtmp_ptr;
709           *rtmp_ptr++ = 0.0;
710         }
711       }
712 
713       /* ... add k to row list for first nonzero entry in k-th row */
714       il[k] = jmin;
715       i     = bj[jmin];
716       jl[k] = jl[i]; jl[i] = k;
717     }
718   }
719 
720   ierr = PetscFree(rtmp);CHKERRQ(ierr);
721   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
722   ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr);
723   ierr = PetscFree(pivots);CHKERRQ(ierr);
724   if (a->permute) {
725     ierr = PetscFree(aa);CHKERRQ(ierr);
726   }
727 
728   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
729 
730   C->ops->solve          = MatSolve_SeqSBAIJ_N_inplace;
731   C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_inplace;
732   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_N_inplace;
733   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_N_inplace;
734 
735   C->assembled    = PETSC_TRUE;
736   C->preallocated = PETSC_TRUE;
737 
738   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
739   PetscFunctionReturn(0);
740 }
741 
742 #undef __FUNCT__
743 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering"
744 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
745 {
746   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
747   PetscErrorCode ierr;
748   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
749   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
750   PetscInt       bs  =A->rmap->bs,bs2 = a->bs2,bslog;
751   MatScalar      *ba = b->a,*aa,*ap,*dk,*uik;
752   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
753   MatScalar      *work;
754   PetscInt       *pivots;
755 
756   PetscFunctionBegin;
757   ierr = PetscCalloc1(bs2*mbs,&rtmp);CHKERRQ(ierr);
758   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
759   for (i=0; i<mbs; i++) {
760     jl[i] = mbs; il[0] = 0;
761   }
762   ierr = PetscMalloc3(bs2,&dk,bs2,&uik,bs,&work);CHKERRQ(ierr);
763   ierr = PetscMalloc1(bs,&pivots);CHKERRQ(ierr);
764 
765   ai = a->i; aj = a->j; aa = a->a;
766 
767   /* flops in while loop */
768   bslog = 2*bs*bs2;
769 
770   /* for each row k */
771   for (k = 0; k<mbs; k++) {
772 
773     /*initialize k-th row with elements nonzero in row k of A */
774     jmin = ai[k]; jmax = ai[k+1];
775     ap   = aa + jmin*bs2;
776     for (j = jmin; j < jmax; j++) {
777       vj       = aj[j];   /* block col. index */
778       rtmp_ptr = rtmp + vj*bs2;
779       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
780     }
781 
782     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
783     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
784     i    = jl[k]; /* first row to be added to k_th row  */
785 
786     while (i < k) {
787       nexti = jl[i]; /* next row to be added to k_th row */
788 
789       /* compute multiplier */
790       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
791 
792       /* uik = -inv(Di)*U_bar(i,k) */
793       diag = ba + i*bs2;
794       u    = ba + ili*bs2;
795       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
796       PetscKernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
797 
798       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
799       PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
800       ierr = PetscLogFlops(bslog*2.0);CHKERRQ(ierr);
801 
802       /* update -U(i,k) */
803       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
804 
805       /* add multiple of row i to k-th row ... */
806       jmin = ili + 1; jmax = bi[i+1];
807       if (jmin < jmax) {
808         for (j=jmin; j<jmax; j++) {
809           /* rtmp += -U(i,k)^T * U_bar(i,j) */
810           rtmp_ptr = rtmp + bj[j]*bs2;
811           u        = ba + j*bs2;
812           PetscKernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
813         }
814         ierr = PetscLogFlops(bslog*(jmax-jmin));CHKERRQ(ierr);
815 
816         /* ... add i to row list for next nonzero entry */
817         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
818         j     = bj[jmin];
819         jl[i] = jl[j]; jl[j] = i; /* update jl */
820       }
821       i = nexti;
822     }
823 
824     /* save nonzero entries in k-th row of U ... */
825 
826     /* invert diagonal block */
827     diag = ba+k*bs2;
828     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
829     ierr = PetscKernel_A_gets_inverse_A(bs,diag,pivots,work);CHKERRQ(ierr);
830 
831     jmin = bi[k]; jmax = bi[k+1];
832     if (jmin < jmax) {
833       for (j=jmin; j<jmax; j++) {
834         vj       = bj[j];      /* block col. index of U */
835         u        = ba + j*bs2;
836         rtmp_ptr = rtmp + vj*bs2;
837         for (k1=0; k1<bs2; k1++) {
838           *u++        = *rtmp_ptr;
839           *rtmp_ptr++ = 0.0;
840         }
841       }
842 
843       /* ... add k to row list for first nonzero entry in k-th row */
844       il[k] = jmin;
845       i     = bj[jmin];
846       jl[k] = jl[i]; jl[i] = k;
847     }
848   }
849 
850   ierr = PetscFree(rtmp);CHKERRQ(ierr);
851   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
852   ierr = PetscFree3(dk,uik,work);CHKERRQ(ierr);
853   ierr = PetscFree(pivots);CHKERRQ(ierr);
854 
855   C->ops->solve          = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
856   C->ops->solvetranspose = MatSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
857   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
858   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_N_NaturalOrdering_inplace;
859   C->assembled           = PETSC_TRUE;
860   C->preallocated        = PETSC_TRUE;
861 
862   ierr = PetscLogFlops(1.3333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
863   PetscFunctionReturn(0);
864 }
865 
866 /*
867     Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP.
868     Version for blocks 2 by 2.
869 */
870 #undef __FUNCT__
871 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2"
872 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat C,Mat A,const MatFactorInfo *info)
873 {
874   Mat_SeqSBAIJ   *a   = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
875   IS             perm = b->row;
876   PetscErrorCode ierr;
877   const PetscInt *ai,*aj,*perm_ptr;
878   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
879   PetscInt       *a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
880   MatScalar      *ba = b->a,*aa,*ap;
881   MatScalar      *u,*diag,*rtmp,*rtmp_ptr,dk[4],uik[4];
882   PetscReal      shift = info->shiftamount;
883 
884   PetscFunctionBegin;
885   /* initialization */
886   /* il and jl record the first nonzero element in each row of the accessing
887      window U(0:k, k:mbs-1).
888      jl:    list of rows to be added to uneliminated rows
889             i>= k: jl(i) is the first row to be added to row i
890             i<  k: jl(i) is the row following row i in some list of rows
891             jl(i) = mbs indicates the end of a list
892      il(i): points to the first nonzero element in columns k,...,mbs-1 of
893             row i of U */
894   ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr);
895   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
896   for (i=0; i<mbs; i++) {
897     jl[i] = mbs; il[0] = 0;
898   }
899   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
900 
901   /* check permutation */
902   if (!a->permute) {
903     ai = a->i; aj = a->j; aa = a->a;
904   } else {
905     ai   = a->inew; aj = a->jnew;
906     ierr = PetscMalloc1(4*ai[mbs],&aa);CHKERRQ(ierr);
907     ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
908     ierr = PetscMalloc1(ai[mbs],&a2anew);CHKERRQ(ierr);
909     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(PetscInt));CHKERRQ(ierr);
910 
911     for (i=0; i<mbs; i++) {
912       jmin = ai[i]; jmax = ai[i+1];
913       for (j=jmin; j<jmax; j++) {
914         while (a2anew[j] != j) {
915           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
916           for (k1=0; k1<4; k1++) {
917             dk[k1]     = aa[k*4+k1];
918             aa[k*4+k1] = aa[j*4+k1];
919             aa[j*4+k1] = dk[k1];
920           }
921         }
922         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
923         if (i > aj[j]) {
924           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
925           ap    = aa + j*4;  /* ptr to the beginning of the block */
926           dk[1] = ap[1];     /* swap ap[1] and ap[2] */
927           ap[1] = ap[2];
928           ap[2] = dk[1];
929         }
930       }
931     }
932     ierr = PetscFree(a2anew);CHKERRQ(ierr);
933   }
934 
935   /* for each row k */
936   for (k = 0; k<mbs; k++) {
937 
938     /*initialize k-th row with elements nonzero in row perm(k) of A */
939     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
940     ap   = aa + jmin*4;
941     for (j = jmin; j < jmax; j++) {
942       vj       = perm_ptr[aj[j]];   /* block col. index */
943       rtmp_ptr = rtmp + vj*4;
944       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
945     }
946 
947     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
948     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
949     i    = jl[k]; /* first row to be added to k_th row  */
950 
951     while (i < k) {
952       nexti = jl[i]; /* next row to be added to k_th row */
953 
954       /* compute multiplier */
955       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
956 
957       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
958       diag   = ba + i*4;
959       u      = ba + ili*4;
960       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
961       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
962       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
963       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
964 
965       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
966       dk[0] += uik[0]*u[0] + uik[1]*u[1];
967       dk[1] += uik[2]*u[0] + uik[3]*u[1];
968       dk[2] += uik[0]*u[2] + uik[1]*u[3];
969       dk[3] += uik[2]*u[2] + uik[3]*u[3];
970 
971       ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr);
972 
973       /* update -U(i,k): ba[ili] = uik */
974       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
975 
976       /* add multiple of row i to k-th row ... */
977       jmin = ili + 1; jmax = bi[i+1];
978       if (jmin < jmax) {
979         for (j=jmin; j<jmax; j++) {
980           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
981           rtmp_ptr     = rtmp + bj[j]*4;
982           u            = ba + j*4;
983           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
984           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
985           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
986           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
987         }
988         ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr);
989 
990         /* ... add i to row list for next nonzero entry */
991         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
992         j     = bj[jmin];
993         jl[i] = jl[j]; jl[j] = i; /* update jl */
994       }
995       i = nexti;
996     }
997 
998     /* save nonzero entries in k-th row of U ... */
999 
1000     /* invert diagonal block */
1001     diag = ba+k*4;
1002     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
1003     ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr);
1004 
1005     jmin = bi[k]; jmax = bi[k+1];
1006     if (jmin < jmax) {
1007       for (j=jmin; j<jmax; j++) {
1008         vj       = bj[j];      /* block col. index of U */
1009         u        = ba + j*4;
1010         rtmp_ptr = rtmp + vj*4;
1011         for (k1=0; k1<4; k1++) {
1012           *u++        = *rtmp_ptr;
1013           *rtmp_ptr++ = 0.0;
1014         }
1015       }
1016 
1017       /* ... add k to row list for first nonzero entry in k-th row */
1018       il[k] = jmin;
1019       i     = bj[jmin];
1020       jl[k] = jl[i]; jl[i] = k;
1021     }
1022   }
1023 
1024   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1025   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1026   if (a->permute) {
1027     ierr = PetscFree(aa);CHKERRQ(ierr);
1028   }
1029   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
1030 
1031   C->ops->solve          = MatSolve_SeqSBAIJ_2_inplace;
1032   C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_inplace;
1033   C->assembled           = PETSC_TRUE;
1034   C->preallocated        = PETSC_TRUE;
1035 
1036   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
1037   PetscFunctionReturn(0);
1038 }
1039 
1040 /*
1041       Version for when blocks are 2 by 2 Using natural ordering
1042 */
1043 #undef __FUNCT__
1044 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering"
1045 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
1046 {
1047   Mat_SeqSBAIJ   *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ*)C->data;
1048   PetscErrorCode ierr;
1049   PetscInt       i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
1050   PetscInt       *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
1051   MatScalar      *ba = b->a,*aa,*ap,dk[8],uik[8];
1052   MatScalar      *u,*diag,*rtmp,*rtmp_ptr;
1053   PetscReal      shift = info->shiftamount;
1054 
1055   PetscFunctionBegin;
1056   /* initialization */
1057   /* il and jl record the first nonzero element in each row of the accessing
1058      window U(0:k, k:mbs-1).
1059      jl:    list of rows to be added to uneliminated rows
1060             i>= k: jl(i) is the first row to be added to row i
1061             i<  k: jl(i) is the row following row i in some list of rows
1062             jl(i) = mbs indicates the end of a list
1063      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1064             row i of U */
1065   ierr = PetscCalloc1(4*mbs,&rtmp);CHKERRQ(ierr);
1066   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
1067   for (i=0; i<mbs; i++) {
1068     jl[i] = mbs; il[0] = 0;
1069   }
1070   ai = a->i; aj = a->j; aa = a->a;
1071 
1072   /* for each row k */
1073   for (k = 0; k<mbs; k++) {
1074 
1075     /*initialize k-th row with elements nonzero in row k of A */
1076     jmin = ai[k]; jmax = ai[k+1];
1077     ap   = aa + jmin*4;
1078     for (j = jmin; j < jmax; j++) {
1079       vj       = aj[j];   /* block col. index */
1080       rtmp_ptr = rtmp + vj*4;
1081       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
1082     }
1083 
1084     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
1085     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
1086     i    = jl[k]; /* first row to be added to k_th row  */
1087 
1088     while (i < k) {
1089       nexti = jl[i]; /* next row to be added to k_th row */
1090 
1091       /* compute multiplier */
1092       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1093 
1094       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
1095       diag   = ba + i*4;
1096       u      = ba + ili*4;
1097       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
1098       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
1099       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
1100       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
1101 
1102       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
1103       dk[0] += uik[0]*u[0] + uik[1]*u[1];
1104       dk[1] += uik[2]*u[0] + uik[3]*u[1];
1105       dk[2] += uik[0]*u[2] + uik[1]*u[3];
1106       dk[3] += uik[2]*u[2] + uik[3]*u[3];
1107 
1108       ierr = PetscLogFlops(16.0*2.0);CHKERRQ(ierr);
1109 
1110       /* update -U(i,k): ba[ili] = uik */
1111       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
1112 
1113       /* add multiple of row i to k-th row ... */
1114       jmin = ili + 1; jmax = bi[i+1];
1115       if (jmin < jmax) {
1116         for (j=jmin; j<jmax; j++) {
1117           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
1118           rtmp_ptr     = rtmp + bj[j]*4;
1119           u            = ba + j*4;
1120           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
1121           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
1122           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
1123           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
1124         }
1125         ierr = PetscLogFlops(16.0*(jmax-jmin));CHKERRQ(ierr);
1126 
1127         /* ... add i to row list for next nonzero entry */
1128         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
1129         j     = bj[jmin];
1130         jl[i] = jl[j]; jl[j] = i; /* update jl */
1131       }
1132       i = nexti;
1133     }
1134 
1135     /* save nonzero entries in k-th row of U ... */
1136 
1137     /* invert diagonal block */
1138     diag = ba+k*4;
1139     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
1140     ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr);
1141 
1142     jmin = bi[k]; jmax = bi[k+1];
1143     if (jmin < jmax) {
1144       for (j=jmin; j<jmax; j++) {
1145         vj       = bj[j];      /* block col. index of U */
1146         u        = ba + j*4;
1147         rtmp_ptr = rtmp + vj*4;
1148         for (k1=0; k1<4; k1++) {
1149           *u++        = *rtmp_ptr;
1150           *rtmp_ptr++ = 0.0;
1151         }
1152       }
1153 
1154       /* ... add k to row list for first nonzero entry in k-th row */
1155       il[k] = jmin;
1156       i     = bj[jmin];
1157       jl[k] = jl[i]; jl[i] = k;
1158     }
1159   }
1160 
1161   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1162   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1163 
1164   C->ops->solve          = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1165   C->ops->solvetranspose = MatSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1166   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1167   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_2_NaturalOrdering_inplace;
1168   C->assembled           = PETSC_TRUE;
1169   C->preallocated        = PETSC_TRUE;
1170 
1171   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
1172   PetscFunctionReturn(0);
1173 }
1174 
1175 /*
1176     Numeric U^T*D*U factorization for SBAIJ format.
1177     Version for blocks are 1 by 1.
1178 */
1179 #undef __FUNCT__
1180 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace"
1181 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info)
1182 {
1183   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data;
1184   IS             ip=b->row;
1185   PetscErrorCode ierr;
1186   const PetscInt *ai,*aj,*rip;
1187   PetscInt       *a2anew,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j,*bcol;
1188   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
1189   MatScalar      *rtmp,*ba=b->a,*bval,*aa,dk,uikdi;
1190   PetscReal      rs;
1191   FactorShiftCtx sctx;
1192 
1193   PetscFunctionBegin;
1194   /* MatPivotSetUp(): initialize shift context sctx */
1195   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1196 
1197   ierr = ISGetIndices(ip,&rip);CHKERRQ(ierr);
1198   if (!a->permute) {
1199     ai = a->i; aj = a->j; aa = a->a;
1200   } else {
1201     ai     = a->inew; aj = a->jnew;
1202     nz     = ai[mbs];
1203     ierr   = PetscMalloc1(nz,&aa);CHKERRQ(ierr);
1204     a2anew = a->a2anew;
1205     bval   = a->a;
1206     for (j=0; j<nz; j++) {
1207       aa[a2anew[j]] = *(bval++);
1208     }
1209   }
1210 
1211   /* initialization */
1212   /* il and jl record the first nonzero element in each row of the accessing
1213      window U(0:k, k:mbs-1).
1214      jl:    list of rows to be added to uneliminated rows
1215             i>= k: jl(i) is the first row to be added to row i
1216             i<  k: jl(i) is the row following row i in some list of rows
1217             jl(i) = mbs indicates the end of a list
1218      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1219             row i of U */
1220   ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&jl);CHKERRQ(ierr);
1221 
1222   do {
1223     sctx.newshift = PETSC_FALSE;
1224     for (i=0; i<mbs; i++) {
1225       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1226     }
1227 
1228     for (k = 0; k<mbs; k++) {
1229       /*initialize k-th row by the perm[k]-th row of A */
1230       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
1231       bval = ba + bi[k];
1232       for (j = jmin; j < jmax; j++) {
1233         col       = rip[aj[j]];
1234         rtmp[col] = aa[j];
1235         *bval++   = 0.0; /* for in-place factorization */
1236       }
1237 
1238       /* shift the diagonal of the matrix */
1239       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1240 
1241       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1242       dk = rtmp[k];
1243       i  = jl[k]; /* first row to be added to k_th row  */
1244 
1245       while (i < k) {
1246         nexti = jl[i]; /* next row to be added to k_th row */
1247 
1248         /* compute multiplier, update diag(k) and U(i,k) */
1249         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1250         uikdi   = -ba[ili]*ba[bi[i]]; /* diagonal(k) */
1251         dk     += uikdi*ba[ili];
1252         ba[ili] = uikdi; /* -U(i,k) */
1253 
1254         /* add multiple of row i to k-th row */
1255         jmin = ili + 1; jmax = bi[i+1];
1256         if (jmin < jmax) {
1257           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
1258           ierr = PetscLogFlops(2.0*(jmax-jmin));CHKERRQ(ierr);
1259 
1260           /* update il and jl for row i */
1261           il[i] = jmin;
1262           j     = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1263         }
1264         i = nexti;
1265       }
1266 
1267       /* shift the diagonals when zero pivot is detected */
1268       /* compute rs=sum of abs(off-diagonal) */
1269       rs   = 0.0;
1270       jmin = bi[k]+1;
1271       nz   = bi[k+1] - jmin;
1272       if (nz) {
1273         bcol = bj + jmin;
1274         while (nz--) {
1275           rs += PetscAbsScalar(rtmp[*bcol]);
1276           bcol++;
1277         }
1278       }
1279 
1280       sctx.rs = rs;
1281       sctx.pv = dk;
1282       ierr    = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr);
1283       if (sctx.newshift) break;    /* sctx.shift_amount is updated */
1284       dk = sctx.pv;
1285 
1286       /* copy data into U(k,:) */
1287       ba[bi[k]] = 1.0/dk; /* U(k,k) */
1288       jmin      = bi[k]+1; jmax = bi[k+1];
1289       if (jmin < jmax) {
1290         for (j=jmin; j<jmax; j++) {
1291           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
1292         }
1293         /* add the k-th row into il and jl */
1294         il[k] = jmin;
1295         i     = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1296       }
1297     }
1298   } while (sctx.newshift);
1299   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
1300   if (a->permute) {ierr = PetscFree(aa);CHKERRQ(ierr);}
1301 
1302   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
1303 
1304   C->ops->solve          = MatSolve_SeqSBAIJ_1_inplace;
1305   C->ops->solves         = MatSolves_SeqSBAIJ_1_inplace;
1306   C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_inplace;
1307   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_inplace;
1308   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_inplace;
1309   C->assembled           = PETSC_TRUE;
1310   C->preallocated        = PETSC_TRUE;
1311 
1312   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
1313   if (sctx.nshift) {
1314     if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1315       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1316     } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1317       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1318     }
1319   }
1320   PetscFunctionReturn(0);
1321 }
1322 
1323 /*
1324   Version for when blocks are 1 by 1 Using natural ordering under new datastructure
1325   Modified from MatCholeskyFactorNumeric_SeqAIJ()
1326 */
1327 #undef __FUNCT__
1328 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering"
1329 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info)
1330 {
1331   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data;
1332   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)B->data;
1333   PetscErrorCode ierr;
1334   PetscInt       i,j,mbs=A->rmap->n,*bi=b->i,*bj=b->j,*bdiag=b->diag,*bjtmp;
1335   PetscInt       *ai=a->i,*aj=a->j,*ajtmp;
1336   PetscInt       k,jmin,jmax,*c2r,*il,col,nexti,ili,nz;
1337   MatScalar      *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi;
1338   FactorShiftCtx sctx;
1339   PetscReal      rs;
1340   MatScalar      d,*v;
1341 
1342   PetscFunctionBegin;
1343   ierr = PetscMalloc3(mbs,&rtmp,mbs,&il,mbs,&c2r);CHKERRQ(ierr);
1344 
1345   /* MatPivotSetUp(): initialize shift context sctx */
1346   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1347 
1348   if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */
1349     sctx.shift_top = info->zeropivot;
1350 
1351     ierr = PetscMemzero(rtmp,mbs*sizeof(MatScalar));CHKERRQ(ierr);
1352 
1353     for (i=0; i<mbs; i++) {
1354       /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */
1355       d        = (aa)[a->diag[i]];
1356       rtmp[i] += -PetscRealPart(d);  /* diagonal entry */
1357       ajtmp    = aj + ai[i] + 1;     /* exclude diagonal */
1358       v        = aa + ai[i] + 1;
1359       nz       = ai[i+1] - ai[i] - 1;
1360       for (j=0; j<nz; j++) {
1361         rtmp[i]        += PetscAbsScalar(v[j]);
1362         rtmp[ajtmp[j]] += PetscAbsScalar(v[j]);
1363       }
1364       if (PetscRealPart(rtmp[i]) > sctx.shift_top) sctx.shift_top = PetscRealPart(rtmp[i]);
1365     }
1366     sctx.shift_top *= 1.1;
1367     sctx.nshift_max = 5;
1368     sctx.shift_lo   = 0.;
1369     sctx.shift_hi   = 1.;
1370   }
1371 
1372   /* allocate working arrays
1373      c2r: linked list, keep track of pivot rows for a given column. c2r[col]: head of the list for a given col
1374      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
1375   */
1376   do {
1377     sctx.newshift = PETSC_FALSE;
1378 
1379     for (i=0; i<mbs; i++) c2r[i] = mbs;
1380     if (mbs) il[0] = 0;
1381 
1382     for (k = 0; k<mbs; k++) {
1383       /* zero rtmp */
1384       nz    = bi[k+1] - bi[k];
1385       bjtmp = bj + bi[k];
1386       for (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0;
1387 
1388       /* load in initial unfactored row */
1389       bval = ba + bi[k];
1390       jmin = ai[k]; jmax = ai[k+1];
1391       for (j = jmin; j < jmax; j++) {
1392         col       = aj[j];
1393         rtmp[col] = aa[j];
1394         *bval++   = 0.0; /* for in-place factorization */
1395       }
1396       /* shift the diagonal of the matrix: ZeropivotApply() */
1397       rtmp[k] += sctx.shift_amount;  /* shift the diagonal of the matrix */
1398 
1399       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1400       dk = rtmp[k];
1401       i  = c2r[k]; /* first row to be added to k_th row  */
1402 
1403       while (i < k) {
1404         nexti = c2r[i]; /* next row to be added to k_th row */
1405 
1406         /* compute multiplier, update diag(k) and U(i,k) */
1407         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1408         uikdi   = -ba[ili]*ba[bdiag[i]]; /* diagonal(k) */
1409         dk     += uikdi*ba[ili]; /* update diag[k] */
1410         ba[ili] = uikdi; /* -U(i,k) */
1411 
1412         /* add multiple of row i to k-th row */
1413         jmin = ili + 1; jmax = bi[i+1];
1414         if (jmin < jmax) {
1415           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
1416           /* update il and c2r for row i */
1417           il[i] = jmin;
1418           j     = bj[jmin]; c2r[i] = c2r[j]; c2r[j] = i;
1419         }
1420         i = nexti;
1421       }
1422 
1423       /* copy data into U(k,:) */
1424       rs   = 0.0;
1425       jmin = bi[k]; jmax = bi[k+1]-1;
1426       if (jmin < jmax) {
1427         for (j=jmin; j<jmax; j++) {
1428           col = bj[j]; ba[j] = rtmp[col]; rs += PetscAbsScalar(ba[j]);
1429         }
1430         /* add the k-th row into il and c2r */
1431         il[k] = jmin;
1432         i     = bj[jmin]; c2r[k] = c2r[i]; c2r[i] = k;
1433       }
1434 
1435       sctx.rs = rs;
1436       sctx.pv = dk;
1437       ierr    = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr);
1438       if (sctx.newshift) break;
1439       dk = sctx.pv;
1440 
1441       ba[bdiag[k]] = 1.0/dk; /* U(k,k) */
1442     }
1443   } while (sctx.newshift);
1444 
1445   ierr = PetscFree3(rtmp,il,c2r);CHKERRQ(ierr);
1446 
1447   B->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1448   B->ops->solves         = MatSolves_SeqSBAIJ_1;
1449   B->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1450   B->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering;
1451   B->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering;
1452 
1453   B->assembled    = PETSC_TRUE;
1454   B->preallocated = PETSC_TRUE;
1455 
1456   ierr = PetscLogFlops(B->rmap->n);CHKERRQ(ierr);
1457 
1458   /* MatPivotView() */
1459   if (sctx.nshift) {
1460     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1461       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);
1462     } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1463       ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1464     } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS) {
1465       ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %g\n",sctx.nshift,(double)info->shiftamount);CHKERRQ(ierr);
1466     }
1467   }
1468   PetscFunctionReturn(0);
1469 }
1470 
1471 #undef __FUNCT__
1472 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace"
1473 PetscErrorCode MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info)
1474 {
1475   Mat_SeqSBAIJ   *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ*)C->data;
1476   PetscErrorCode ierr;
1477   PetscInt       i,j,mbs = a->mbs;
1478   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
1479   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
1480   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
1481   PetscReal      rs;
1482   FactorShiftCtx sctx;
1483 
1484   PetscFunctionBegin;
1485   /* MatPivotSetUp(): initialize shift context sctx */
1486   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
1487 
1488   /* initialization */
1489   /* il and jl record the first nonzero element in each row of the accessing
1490      window U(0:k, k:mbs-1).
1491      jl:    list of rows to be added to uneliminated rows
1492             i>= k: jl(i) is the first row to be added to row i
1493             i<  k: jl(i) is the row following row i in some list of rows
1494             jl(i) = mbs indicates the end of a list
1495      il(i): points to the first nonzero element in U(i,k:mbs-1)
1496   */
1497   ierr = PetscMalloc1(mbs,&rtmp);CHKERRQ(ierr);
1498   ierr = PetscMalloc2(mbs,&il,mbs,&jl);CHKERRQ(ierr);
1499 
1500   do {
1501     sctx.newshift = PETSC_FALSE;
1502     for (i=0; i<mbs; i++) {
1503       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1504     }
1505 
1506     for (k = 0; k<mbs; k++) {
1507       /*initialize k-th row with elements nonzero in row perm(k) of A */
1508       nz   = ai[k+1] - ai[k];
1509       acol = aj + ai[k];
1510       aval = aa + ai[k];
1511       bval = ba + bi[k];
1512       while (nz--) {
1513         rtmp[*acol++] = *aval++;
1514         *bval++       = 0.0; /* for in-place factorization */
1515       }
1516 
1517       /* shift the diagonal of the matrix */
1518       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
1519 
1520       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
1521       dk = rtmp[k];
1522       i  = jl[k]; /* first row to be added to k_th row  */
1523 
1524       while (i < k) {
1525         nexti = jl[i]; /* next row to be added to k_th row */
1526         /* compute multiplier, update D(k) and U(i,k) */
1527         ili     = il[i]; /* index of first nonzero element in U(i,k:bms-1) */
1528         uikdi   = -ba[ili]*ba[bi[i]];
1529         dk     += uikdi*ba[ili];
1530         ba[ili] = uikdi; /* -U(i,k) */
1531 
1532         /* add multiple of row i to k-th row ... */
1533         jmin = ili + 1;
1534         nz   = bi[i+1] - jmin;
1535         if (nz > 0) {
1536           bcol = bj + jmin;
1537           bval = ba + jmin;
1538           ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr);
1539           while (nz--) rtmp[*bcol++] += uikdi*(*bval++);
1540 
1541           /* update il and jl for i-th row */
1542           il[i] = jmin;
1543           j     = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
1544         }
1545         i = nexti;
1546       }
1547 
1548       /* shift the diagonals when zero pivot is detected */
1549       /* compute rs=sum of abs(off-diagonal) */
1550       rs   = 0.0;
1551       jmin = bi[k]+1;
1552       nz   = bi[k+1] - jmin;
1553       if (nz) {
1554         bcol = bj + jmin;
1555         while (nz--) {
1556           rs += PetscAbsScalar(rtmp[*bcol]);
1557           bcol++;
1558         }
1559       }
1560 
1561       sctx.rs = rs;
1562       sctx.pv = dk;
1563       ierr    = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr);
1564       if (sctx.newshift) break;    /* sctx.shift_amount is updated */
1565       dk = sctx.pv;
1566 
1567       /* copy data into U(k,:) */
1568       ba[bi[k]] = 1.0/dk;
1569       jmin      = bi[k]+1;
1570       nz        = bi[k+1] - jmin;
1571       if (nz) {
1572         bcol = bj + jmin;
1573         bval = ba + jmin;
1574         while (nz--) {
1575           *bval++       = rtmp[*bcol];
1576           rtmp[*bcol++] = 0.0;
1577         }
1578         /* add k-th row into il and jl */
1579         il[k] = jmin;
1580         i     = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
1581       }
1582     } /* end of for (k = 0; k<mbs; k++) */
1583   } while (sctx.newshift);
1584   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1585   ierr = PetscFree2(il,jl);CHKERRQ(ierr);
1586 
1587   C->ops->solve          = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1588   C->ops->solves         = MatSolves_SeqSBAIJ_1_inplace;
1589   C->ops->solvetranspose = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1590   C->ops->forwardsolve   = MatForwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1591   C->ops->backwardsolve  = MatBackwardSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1592 
1593   C->assembled    = PETSC_TRUE;
1594   C->preallocated = PETSC_TRUE;
1595 
1596   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
1597   if (sctx.nshift) {
1598     if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
1599       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1600     } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
1601       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %g\n",sctx.nshift,(double)sctx.shift_amount);CHKERRQ(ierr);
1602     }
1603   }
1604   PetscFunctionReturn(0);
1605 }
1606 
1607 #undef __FUNCT__
1608 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ"
1609 PetscErrorCode MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,const MatFactorInfo *info)
1610 {
1611   PetscErrorCode ierr;
1612   Mat            C;
1613 
1614   PetscFunctionBegin;
1615   ierr = MatGetFactor(A,"petsc",MAT_FACTOR_CHOLESKY,&C);CHKERRQ(ierr);
1616   ierr = MatCholeskyFactorSymbolic(C,A,perm,info);CHKERRQ(ierr);
1617   ierr = MatCholeskyFactorNumeric(C,A,info);CHKERRQ(ierr);
1618 
1619   A->ops->solve          = C->ops->solve;
1620   A->ops->solvetranspose = C->ops->solvetranspose;
1621 
1622   ierr = MatHeaderMerge(A,C);CHKERRQ(ierr);
1623   PetscFunctionReturn(0);
1624 }
1625 
1626 
1627