xref: /petsc/src/mat/impls/sbaij/seq/sbaijfact.c (revision da05ed6dfa52d65e23e82fd45fa3cbbbc23c8277)
1 /*$Id: sbaijfact.c,v 1.61 2001/08/06 21:15:47 bsmith Exp $*/
2 
3 #include "src/mat/impls/baij/seq/baij.h"
4 #include "src/mat/impls/sbaij/seq/sbaij.h"
5 #include "src/vec/vecimpl.h"
6 #include "src/inline/ilu.h"
7 #include "include/petscis.h"
8 
9 #if !defined(PETSC_USE_COMPLEX)
10 /*
11   input:
12    F -- numeric factor
13   output:
14    nneg, nzero, npos: matrix inertia
15 */
16 
17 #undef __FUNCT__
18 #define __FUNCT__ "MatGetInertia_SeqSBAIJ"
19 int MatGetInertia_SeqSBAIJ(Mat F,int *nneig,int *nzero,int *npos)
20 {
21   Mat_SeqSBAIJ *fact_ptr = (Mat_SeqSBAIJ*)F->data;
22   PetscScalar  *dd = fact_ptr->a;
23   int          mbs=fact_ptr->mbs,bs=fact_ptr->bs,i,nneig_tmp,npos_tmp,
24                *fi = fact_ptr->i;
25 
26   PetscFunctionBegin;
27   if (bs != 1) SETERRQ1(PETSC_ERR_SUP,"No support for bs: %d >1 yet",bs);
28   nneig_tmp = 0; npos_tmp = 0;
29   for (i=0; i<mbs; i++){
30     if (PetscRealPart(dd[*fi]) > 0.0){
31       npos_tmp++;
32     } else if (PetscRealPart(dd[*fi]) < 0.0){
33       nneig_tmp++;
34     }
35     fi++;
36   }
37   if (nneig) *nneig = nneig_tmp;
38   if (npos)  *npos  = npos_tmp;
39   if (nzero) *nzero = mbs - nneig_tmp - npos_tmp;
40 
41   PetscFunctionReturn(0);
42 }
43 #endif /* !defined(PETSC_USE_COMPLEX) */
44 
45 /* Using Modified Sparse Row (MSR) storage.
46 See page 85, "Iterative Methods ..." by Saad. */
47 /*
48     Symbolic U^T*D*U factorization for SBAIJ format. Modified from SSF of YSMP.
49 */
50 /* Use Modified Sparse Row storage for u and ju, see Saad pp.85 */
51 #undef __FUNCT__
52 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqSBAIJ"
53 int MatCholeskyFactorSymbolic_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info,Mat *B)
54 {
55   Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data,*b;
56   int          *rip,ierr,i,mbs = a->mbs,*ai,*aj;
57   int          *jutmp,bs = a->bs,bs2=a->bs2;
58   int          m,realloc = 0,prow;
59   int          *jl,*q,jmin,jmax,juidx,nzk,qm,*iu,*ju,k,j,vj,umax,maxadd;
60   int          *il,ili,nextprow;
61   PetscReal    f = info->fill;
62   PetscTruth   perm_identity;
63 
64   PetscFunctionBegin;
65   /* check whether perm is the identity mapping */
66   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
67 
68   /* -- inplace factorization, i.e., use sbaij for *B -- */
69   if (perm_identity && bs==1 ){
70     if (!perm_identity) a->permute = PETSC_TRUE;
71 
72   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
73 
74   if (perm_identity){ /* without permutation */
75     ai = a->i; aj = a->j;
76   } else {            /* non-trivial permutation */
77     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
78     ai = a->inew; aj = a->jnew;
79   }
80 
81   /* initialization */
82   ierr  = PetscMalloc((mbs+1)*sizeof(int),&iu);CHKERRQ(ierr);
83   umax  = (int)(f*ai[mbs] + 1);
84   ierr  = PetscMalloc(umax*sizeof(int),&ju);CHKERRQ(ierr);
85   iu[0] = 0;
86   juidx = 0; /* index for ju */
87   ierr  = PetscMalloc((3*mbs+1)*sizeof(int),&jl);CHKERRQ(ierr); /* linked list for getting pivot row */
88   q     = jl + mbs;   /* linked list for col index of active row */
89   il    = q  + mbs;
90   for (i=0; i<mbs; i++){
91     jl[i] = mbs;
92     q[i]  = 0;
93     il[i] = 0;
94   }
95 
96   /* for each row k */
97   for (k=0; k<mbs; k++){
98     nzk  = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */
99     q[k] = mbs;
100     /* initialize nonzero structure of k-th row to row rip[k] of A */
101     jmin = ai[rip[k]] +1; /* exclude diag[k] */
102     jmax = ai[rip[k]+1];
103     for (j=jmin; j<jmax; j++){
104       vj = rip[aj[j]]; /* col. value */
105       if(vj > k){
106         qm = k;
107         do {
108           m  = qm; qm = q[m];
109         } while(qm < vj);
110         if (qm == vj) {
111           SETERRQ(1," error: duplicate entry in A\n");
112         }
113         nzk++;
114         q[m]  = vj;
115         q[vj] = qm;
116       } /* if(vj > k) */
117     } /* for (j=jmin; j<jmax; j++) */
118 
119     /* modify nonzero structure of k-th row by computing fill-in
120        for each row i to be merged in */
121     prow = k;
122     prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */
123 
124     while (prow < k){
125       nextprow = jl[prow];
126 
127       /* merge row prow into k-th row */
128       ili = il[prow];
129       jmin = ili + 1;  /* points to 2nd nzero entry in U(prow,k:mbs-1) */
130       jmax = iu[prow+1];
131       qm = k;
132       for (j=jmin; j<jmax; j++){
133         vj = ju[j];
134         do {
135           m = qm; qm = q[m];
136         } while (qm < vj);
137         if (qm != vj){  /* a fill */
138           nzk++; q[m] = vj; q[vj] = qm; qm = vj;
139         }
140       } /* end of for (j=jmin; j<jmax; j++) */
141       if (jmin < jmax){
142         il[prow] = jmin;
143         j = ju[jmin];
144         jl[prow] = jl[j]; jl[j] = prow;  /* update jl */
145       }
146       prow = nextprow;
147     }
148 
149     /* update il and jl */
150     if (nzk > 0){
151       i = q[k]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
152       jl[k] = jl[i]; jl[i] = k;
153       il[k] = iu[k] + 1;
154     }
155     iu[k+1] = iu[k] + nzk + 1;  /* include diag[k] */
156 
157     /* allocate more space to ju if needed */
158     if (iu[k+1] > umax) {
159       /* estimate how much additional space we will need */
160       /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
161       /* just double the memory each time */
162       maxadd = umax;
163       if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2;
164       umax += maxadd;
165 
166       /* allocate a longer ju */
167       ierr = PetscMalloc(umax*sizeof(int),&jutmp);CHKERRQ(ierr);
168       ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(int));CHKERRQ(ierr);
169       ierr = PetscFree(ju);CHKERRQ(ierr);
170       ju   = jutmp;
171       realloc++; /* count how many times we realloc */
172     }
173 
174     /* save nonzero structure of k-th row in ju */
175     ju[juidx++] = k; /* diag[k] */
176     i = k;
177     while (nzk --) {
178       i           = q[i];
179       ju[juidx++] = i;
180     }
181   }
182 
183   if (ai[mbs] != 0) {
184     PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
185     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Reallocs %d Fill ratio:given %g needed %g\n",realloc,f,af);
186     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Run with -pc_cholesky_fill %g or use \n",af);
187     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:PCCholeskySetFill(pc,%g);\n",af);
188     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:for best performance.\n");
189   } else {
190      PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Empty matrix.\n");
191   }
192 
193   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
194   /* ierr = PetscFree(q);CHKERRQ(ierr); */
195   ierr = PetscFree(jl);CHKERRQ(ierr);
196 
197   /* put together the new matrix */
198   ierr = MatCreateSeqSBAIJ(A->comm,bs,bs*mbs,bs*mbs,0,PETSC_NULL,B);CHKERRQ(ierr);
199   /* PetscLogObjectParent(*B,iperm); */
200   b = (Mat_SeqSBAIJ*)(*B)->data;
201   ierr = PetscFree(b->imax);CHKERRQ(ierr);
202   b->singlemalloc = PETSC_FALSE;
203   /* the next line frees the default space generated by the Create() */
204   ierr = PetscFree(b->a);CHKERRQ(ierr);
205   ierr = PetscFree(b->ilen);CHKERRQ(ierr);
206   ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr);
207   b->j    = ju;
208   b->i    = iu;
209   b->diag = 0;
210   b->ilen = 0;
211   b->imax = 0;
212   b->row  = perm;
213   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
214   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
215   b->icol = perm;
216   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
217   ierr    = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
218   /* In b structure:  Free imax, ilen, old a, old j.
219      Allocate idnew, solve_work, new a, new j */
220   PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(int)+sizeof(MatScalar)));
221   b->s_maxnz = b->s_nz = iu[mbs];
222 
223   (*B)->factor                 = FACTOR_CHOLESKY;
224   (*B)->info.factor_mallocs    = realloc;
225   (*B)->info.fill_ratio_given  = f;
226   if (ai[mbs] != 0) {
227     (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
228   } else {
229     (*B)->info.fill_ratio_needed = 0.0;
230   }
231 
232 
233   (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
234   (*B)->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering;
235   PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=1\n");
236 
237   PetscFunctionReturn(0);
238   }
239   /* -----------  end of new code --------------------*/
240 
241 
242   if (!perm_identity) a->permute = PETSC_TRUE;
243 
244   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
245 
246   if (perm_identity){ /* without permutation */
247     ai = a->i; aj = a->j;
248   } else {            /* non-trivial permutation */
249     ierr = MatReorderingSeqSBAIJ(A,perm);CHKERRQ(ierr);
250     ai = a->inew; aj = a->jnew;
251   }
252 
253   /* initialization */
254   ierr  = PetscMalloc((mbs+1)*sizeof(int),&iu);CHKERRQ(ierr);
255   umax  = (int)(f*ai[mbs] + 1); umax += mbs + 1;
256   ierr  = PetscMalloc(umax*sizeof(int),&ju);CHKERRQ(ierr);
257   iu[0] = mbs+1;
258   juidx = mbs + 1; /* index for ju */
259   ierr  = PetscMalloc(2*mbs*sizeof(int),&jl);CHKERRQ(ierr); /* linked list for pivot row */
260   q     = jl + mbs;   /* linked list for col index */
261   for (i=0; i<mbs; i++){
262     jl[i] = mbs;
263     q[i] = 0;
264   }
265 
266   /* for each row k */
267   for (k=0; k<mbs; k++){
268     for (i=0; i<mbs; i++) q[i] = 0;  /* to be removed! */
269     nzk  = 0; /* num. of nz blocks in k-th block row with diagonal block excluded */
270     q[k] = mbs;
271     /* initialize nonzero structure of k-th row to row rip[k] of A */
272     jmin = ai[rip[k]] +1; /* exclude diag[k] */
273     jmax = ai[rip[k]+1];
274     for (j=jmin; j<jmax; j++){
275       vj = rip[aj[j]]; /* col. value */
276       if(vj > k){
277         qm = k;
278         do {
279           m  = qm; qm = q[m];
280         } while(qm < vj);
281         if (qm == vj) {
282           SETERRQ(1," error: duplicate entry in A\n");
283         }
284         nzk++;
285         q[m]  = vj;
286         q[vj] = qm;
287       } /* if(vj > k) */
288     } /* for (j=jmin; j<jmax; j++) */
289 
290     /* modify nonzero structure of k-th row by computing fill-in
291        for each row i to be merged in */
292     prow = k;
293     prow = jl[prow]; /* next pivot row (== mbs for symbolic factorization) */
294 
295     while (prow < k){
296       /* merge row prow into k-th row */
297       jmin = iu[prow] + 1; jmax = iu[prow+1];
298       qm = k;
299       for (j=jmin; j<jmax; j++){
300         vj = ju[j];
301         do {
302           m = qm; qm = q[m];
303         } while (qm < vj);
304         if (qm != vj){
305          nzk++; q[m] = vj; q[vj] = qm; qm = vj;
306         }
307       }
308       prow = jl[prow]; /* next pivot row */
309     }
310 
311     /* add k to row list for first nonzero element in k-th row */
312     if (nzk > 0){
313       i = q[k]; /* col value of first nonzero element in U(k, k+1:mbs-1) */
314       jl[k] = jl[i]; jl[i] = k;
315     }
316     iu[k+1] = iu[k] + nzk;
317 
318     /* allocate more space to ju if needed */
319     if (iu[k+1] > umax) {
320       /* estimate how much additional space we will need */
321       /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
322       /* just double the memory each time */
323       maxadd = umax;
324       if (maxadd < nzk) maxadd = (mbs-k)*(nzk+1)/2;
325       umax += maxadd;
326 
327       /* allocate a longer ju */
328       ierr = PetscMalloc(umax*sizeof(int),&jutmp);CHKERRQ(ierr);
329       ierr = PetscMemcpy(jutmp,ju,iu[k]*sizeof(int));CHKERRQ(ierr);
330       ierr = PetscFree(ju);CHKERRQ(ierr);
331       ju   = jutmp;
332       realloc++; /* count how many times we realloc */
333     }
334 
335     /* save nonzero structure of k-th row in ju */
336     i=k;
337     while (nzk --) {
338       i           = q[i];
339       ju[juidx++] = i;
340     }
341   }
342 
343   if (ai[mbs] != 0) {
344     PetscReal af = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
345     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Reallocs %d Fill ratio:given %g needed %g\n",realloc,f,af);
346     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Run with -pc_cholesky_fill %g or use \n",af);
347     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:PCCholeskySetFill(pc,%g);\n",af);
348     PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:for best performance.\n");
349   } else {
350      PetscLogInfo(A,"MatCholeskyFactorSymbolic_SeqSBAIJ:Empty matrix.\n");
351   }
352 
353   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
354   /* ierr = PetscFree(q);CHKERRQ(ierr); */
355   ierr = PetscFree(jl);CHKERRQ(ierr);
356 
357   /* put together the new matrix */
358   ierr = MatCreateSeqSBAIJ(A->comm,bs,bs*mbs,bs*mbs,0,PETSC_NULL,B);CHKERRQ(ierr);
359   /* PetscLogObjectParent(*B,iperm); */
360   b = (Mat_SeqSBAIJ*)(*B)->data;
361   ierr = PetscFree(b->imax);CHKERRQ(ierr);
362   b->singlemalloc = PETSC_FALSE;
363   /* the next line frees the default space generated by the Create() */
364   ierr = PetscFree(b->a);CHKERRQ(ierr);
365   ierr = PetscFree(b->ilen);CHKERRQ(ierr);
366   ierr = PetscMalloc((iu[mbs]+1)*sizeof(MatScalar)*bs2,&b->a);CHKERRQ(ierr);
367   b->j    = ju;
368   b->i    = iu;
369   b->diag = 0;
370   b->ilen = 0;
371   b->imax = 0;
372   b->row  = perm;
373   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
374   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
375   b->icol = perm;
376   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
377   ierr    = PetscMalloc((bs*mbs+bs)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
378   /* In b structure:  Free imax, ilen, old a, old j.
379      Allocate idnew, solve_work, new a, new j */
380   PetscLogObjectMemory(*B,(iu[mbs]-mbs)*(sizeof(int)+sizeof(MatScalar)));
381   b->s_maxnz = b->s_nz = iu[mbs];
382 
383   (*B)->factor                 = FACTOR_CHOLESKY;
384   (*B)->info.factor_mallocs    = realloc;
385   (*B)->info.fill_ratio_given  = f;
386   if (ai[mbs] != 0) {
387     (*B)->info.fill_ratio_needed = ((PetscReal)iu[mbs])/((PetscReal)ai[mbs]);
388   } else {
389     (*B)->info.fill_ratio_needed = 0.0;
390   }
391 
392   if (perm_identity){
393     switch (bs) {
394       case 1:
395         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering;
396         (*B)->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering;
397         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=1\n");
398         break;
399       case 2:
400         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering;
401         (*B)->ops->solve           = MatSolve_SeqSBAIJ_2_NaturalOrdering;
402         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=2\n");
403         break;
404       case 3:
405         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_3_NaturalOrdering;
406         (*B)->ops->solve           = MatSolve_SeqSBAIJ_3_NaturalOrdering;
407         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:sing special in-place natural ordering factor and solve BS=3\n");
408         break;
409       case 4:
410         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_4_NaturalOrdering;
411         (*B)->ops->solve           = MatSolve_SeqSBAIJ_4_NaturalOrdering;
412         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=4\n");
413         break;
414       case 5:
415         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_5_NaturalOrdering;
416         (*B)->ops->solve           = MatSolve_SeqSBAIJ_5_NaturalOrdering;
417         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=5\n");
418         break;
419       case 6:
420         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_6_NaturalOrdering;
421         (*B)->ops->solve           = MatSolve_SeqSBAIJ_6_NaturalOrdering;
422         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=6\n");
423         break;
424       case 7:
425         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_7_NaturalOrdering;
426         (*B)->ops->solve           = MatSolve_SeqSBAIJ_7_NaturalOrdering;
427         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS=7\n");
428       break;
429       default:
430         (*B)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering;
431         (*B)->ops->solve           = MatSolve_SeqSBAIJ_N_NaturalOrdering;
432         PetscLogInfo(A,"MatICCFactorSymbolic_SeqSBAIJ:Using special in-place natural ordering factor and solve BS>7\n");
433       break;
434     }
435   }
436 
437   PetscFunctionReturn(0);
438 }
439 
440 
441 #undef __FUNCT__
442 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N"
443 int MatCholeskyFactorNumeric_SeqSBAIJ_N(Mat A,Mat *B)
444 {
445   Mat                C = *B;
446   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
447   IS                 perm = b->row;
448   int                *perm_ptr,ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
449   int                *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
450   int                bs=a->bs,bs2 = a->bs2;
451   MatScalar          *ba = b->a,*aa,*ap,*dk,*uik;
452   MatScalar          *u,*diag,*rtmp,*rtmp_ptr;
453   MatScalar          *work;
454   int                *pivots;
455 
456   PetscFunctionBegin;
457 
458   /* initialization */
459   ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
460   ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr);
461   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
462   jl   = il + mbs;
463   for (i=0; i<mbs; i++) {
464     jl[i] = mbs; il[0] = 0;
465   }
466   ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr);
467   uik  = dk + bs2;
468   work = uik + bs2;
469   ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr);
470 
471   ierr  = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
472 
473   /* check permutation */
474   if (!a->permute){
475     ai = a->i; aj = a->j; aa = a->a;
476   } else {
477     ai   = a->inew; aj = a->jnew;
478     ierr = PetscMalloc(bs2*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr);
479     ierr = PetscMemcpy(aa,a->a,bs2*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
480     ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr);
481     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr);
482 
483     for (i=0; i<mbs; i++){
484       jmin = ai[i]; jmax = ai[i+1];
485       for (j=jmin; j<jmax; j++){
486         while (a2anew[j] != j){
487           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
488           for (k1=0; k1<bs2; k1++){
489             dk[k1]       = aa[k*bs2+k1];
490             aa[k*bs2+k1] = aa[j*bs2+k1];
491             aa[j*bs2+k1] = dk[k1];
492           }
493         }
494         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
495         if (i > aj[j]){
496           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
497           ap = aa + j*bs2;                     /* ptr to the beginning of j-th block of aa */
498           for (k=0; k<bs2; k++) dk[k] = ap[k]; /* dk <- j-th block of aa */
499           for (k=0; k<bs; k++){               /* j-th block of aa <- dk^T */
500             for (k1=0; k1<bs; k1++) *ap++ = dk[k + bs*k1];
501           }
502         }
503       }
504     }
505     ierr = PetscFree(a2anew);CHKERRQ(ierr);
506   }
507 
508   /* for each row k */
509   for (k = 0; k<mbs; k++){
510 
511     /*initialize k-th row with elements nonzero in row perm(k) of A */
512     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
513 
514     ap = aa + jmin*bs2;
515     for (j = jmin; j < jmax; j++){
516       vj = perm_ptr[aj[j]];         /* block col. index */
517       rtmp_ptr = rtmp + vj*bs2;
518       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
519     }
520 
521     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
522     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
523     i = jl[k]; /* first row to be added to k_th row  */
524 
525     while (i < k){
526       nexti = jl[i]; /* next row to be added to k_th row */
527 
528       /* compute multiplier */
529       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
530 
531       /* uik = -inv(Di)*U_bar(i,k) */
532       diag = ba + i*bs2;
533       u    = ba + ili*bs2;
534       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
535       Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
536 
537       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
538       Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
539 
540       /* update -U(i,k) */
541       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
542 
543       /* add multiple of row i to k-th row ... */
544       jmin = ili + 1; jmax = bi[i+1];
545       if (jmin < jmax){
546         for (j=jmin; j<jmax; j++) {
547           /* rtmp += -U(i,k)^T * U_bar(i,j) */
548           rtmp_ptr = rtmp + bj[j]*bs2;
549           u = ba + j*bs2;
550           Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
551         }
552 
553         /* ... add i to row list for next nonzero entry */
554         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
555         j     = bj[jmin];
556         jl[i] = jl[j]; jl[j] = i; /* update jl */
557       }
558       i = nexti;
559     }
560 
561     /* save nonzero entries in k-th row of U ... */
562 
563     /* invert diagonal block */
564     diag = ba+k*bs2;
565     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
566     Kernel_A_gets_inverse_A(bs,diag,pivots,work);
567 
568     jmin = bi[k]; jmax = bi[k+1];
569     if (jmin < jmax) {
570       for (j=jmin; j<jmax; j++){
571          vj = bj[j];           /* block col. index of U */
572          u   = ba + j*bs2;
573          rtmp_ptr = rtmp + vj*bs2;
574          for (k1=0; k1<bs2; k1++){
575            *u++        = *rtmp_ptr;
576            *rtmp_ptr++ = 0.0;
577          }
578       }
579 
580       /* ... add k to row list for first nonzero entry in k-th row */
581       il[k] = jmin;
582       i     = bj[jmin];
583       jl[k] = jl[i]; jl[i] = k;
584     }
585   }
586 
587   ierr = PetscFree(rtmp);CHKERRQ(ierr);
588   ierr = PetscFree(il);CHKERRQ(ierr);
589   ierr = PetscFree(dk);CHKERRQ(ierr);
590   ierr = PetscFree(pivots);CHKERRQ(ierr);
591   if (a->permute){
592     ierr = PetscFree(aa);CHKERRQ(ierr);
593   }
594 
595   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
596   C->factor       = FACTOR_CHOLESKY;
597   C->assembled    = PETSC_TRUE;
598   C->preallocated = PETSC_TRUE;
599   PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */
600   PetscFunctionReturn(0);
601 }
602 
603 #undef __FUNCT__
604 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering"
605 int MatCholeskyFactorNumeric_SeqSBAIJ_N_NaturalOrdering(Mat A,Mat *B)
606 {
607   Mat                C = *B;
608   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
609   int                ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
610   int                *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
611   int                bs=a->bs,bs2 = a->bs2;
612   MatScalar          *ba = b->a,*aa,*ap,*dk,*uik;
613   MatScalar          *u,*diag,*rtmp,*rtmp_ptr;
614   MatScalar          *work;
615   int                *pivots;
616 
617   PetscFunctionBegin;
618 
619   /* initialization */
620 
621   ierr = PetscMalloc(bs2*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
622   ierr = PetscMemzero(rtmp,bs2*mbs*sizeof(MatScalar));CHKERRQ(ierr);
623   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
624   jl   = il + mbs;
625   for (i=0; i<mbs; i++) {
626     jl[i] = mbs; il[0] = 0;
627   }
628   ierr = PetscMalloc((2*bs2+bs)*sizeof(MatScalar),&dk);CHKERRQ(ierr);
629   uik  = dk + bs2;
630   work = uik + bs2;
631   ierr = PetscMalloc(bs*sizeof(int),&pivots);CHKERRQ(ierr);
632 
633   ai = a->i; aj = a->j; aa = a->a;
634 
635   /* for each row k */
636   for (k = 0; k<mbs; k++){
637 
638     /*initialize k-th row with elements nonzero in row k of A */
639     jmin = ai[k]; jmax = ai[k+1];
640     ap = aa + jmin*bs2;
641     for (j = jmin; j < jmax; j++){
642       vj = aj[j];         /* block col. index */
643       rtmp_ptr = rtmp + vj*bs2;
644       for (i=0; i<bs2; i++) *rtmp_ptr++ = *ap++;
645     }
646 
647     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
648     ierr = PetscMemcpy(dk,rtmp+k*bs2,bs2*sizeof(MatScalar));CHKERRQ(ierr);
649     i = jl[k]; /* first row to be added to k_th row  */
650 
651     while (i < k){
652       nexti = jl[i]; /* next row to be added to k_th row */
653 
654       /* compute multiplier */
655       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
656 
657       /* uik = -inv(Di)*U_bar(i,k) */
658       diag = ba + i*bs2;
659       u    = ba + ili*bs2;
660       ierr = PetscMemzero(uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
661       Kernel_A_gets_A_minus_B_times_C(bs,uik,diag,u);
662 
663       /* update D(k) += -U(i,k)^T * U_bar(i,k) */
664       Kernel_A_gets_A_plus_Btranspose_times_C(bs,dk,uik,u);
665 
666       /* update -U(i,k) */
667       ierr = PetscMemcpy(ba+ili*bs2,uik,bs2*sizeof(MatScalar));CHKERRQ(ierr);
668 
669       /* add multiple of row i to k-th row ... */
670       jmin = ili + 1; jmax = bi[i+1];
671       if (jmin < jmax){
672         for (j=jmin; j<jmax; j++) {
673           /* rtmp += -U(i,k)^T * U_bar(i,j) */
674           rtmp_ptr = rtmp + bj[j]*bs2;
675           u = ba + j*bs2;
676           Kernel_A_gets_A_plus_Btranspose_times_C(bs,rtmp_ptr,uik,u);
677         }
678 
679         /* ... add i to row list for next nonzero entry */
680         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
681         j     = bj[jmin];
682         jl[i] = jl[j]; jl[j] = i; /* update jl */
683       }
684       i = nexti;
685     }
686 
687     /* save nonzero entries in k-th row of U ... */
688 
689     /* invert diagonal block */
690     diag = ba+k*bs2;
691     ierr = PetscMemcpy(diag,dk,bs2*sizeof(MatScalar));CHKERRQ(ierr);
692     Kernel_A_gets_inverse_A(bs,diag,pivots,work);
693 
694     jmin = bi[k]; jmax = bi[k+1];
695     if (jmin < jmax) {
696       for (j=jmin; j<jmax; j++){
697          vj = bj[j];           /* block col. index of U */
698          u   = ba + j*bs2;
699          rtmp_ptr = rtmp + vj*bs2;
700          for (k1=0; k1<bs2; k1++){
701            *u++        = *rtmp_ptr;
702            *rtmp_ptr++ = 0.0;
703          }
704       }
705 
706       /* ... add k to row list for first nonzero entry in k-th row */
707       il[k] = jmin;
708       i     = bj[jmin];
709       jl[k] = jl[i]; jl[i] = k;
710     }
711   }
712 
713   ierr = PetscFree(rtmp);CHKERRQ(ierr);
714   ierr = PetscFree(il);CHKERRQ(ierr);
715   ierr = PetscFree(dk);CHKERRQ(ierr);
716   ierr = PetscFree(pivots);CHKERRQ(ierr);
717 
718   C->factor    = FACTOR_CHOLESKY;
719   C->assembled = PETSC_TRUE;
720   C->preallocated = PETSC_TRUE;
721   PetscLogFlops(1.3333*bs*bs2*b->mbs); /* from inverting diagonal blocks */
722   PetscFunctionReturn(0);
723 }
724 
725 /*
726     Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP.
727     Version for blocks 2 by 2.
728 */
729 #undef __FUNCT__
730 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2"
731 int MatCholeskyFactorNumeric_SeqSBAIJ_2(Mat A,Mat *B)
732 {
733   Mat                C = *B;
734   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
735   IS                 perm = b->row;
736   int                *perm_ptr,ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
737   int                *ai,*aj,*a2anew,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
738   MatScalar          *ba = b->a,*aa,*ap,*dk,*uik;
739   MatScalar          *u,*diag,*rtmp,*rtmp_ptr;
740 
741   PetscFunctionBegin;
742 
743   /* initialization */
744   /* il and jl record the first nonzero element in each row of the accessing
745      window U(0:k, k:mbs-1).
746      jl:    list of rows to be added to uneliminated rows
747             i>= k: jl(i) is the first row to be added to row i
748             i<  k: jl(i) is the row following row i in some list of rows
749             jl(i) = mbs indicates the end of a list
750      il(i): points to the first nonzero element in columns k,...,mbs-1 of
751             row i of U */
752   ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
753   ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr);
754   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
755   jl   = il + mbs;
756   for (i=0; i<mbs; i++) {
757     jl[i] = mbs; il[0] = 0;
758   }
759   ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr);
760   uik  = dk + 4;
761   ierr = ISGetIndices(perm,&perm_ptr);CHKERRQ(ierr);
762 
763   /* check permutation */
764   if (!a->permute){
765     ai = a->i; aj = a->j; aa = a->a;
766   } else {
767     ai   = a->inew; aj = a->jnew;
768     ierr = PetscMalloc(4*ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr);
769     ierr = PetscMemcpy(aa,a->a,4*ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
770     ierr = PetscMalloc(ai[mbs]*sizeof(int),&a2anew);CHKERRQ(ierr);
771     ierr = PetscMemcpy(a2anew,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr);
772 
773     for (i=0; i<mbs; i++){
774       jmin = ai[i]; jmax = ai[i+1];
775       for (j=jmin; j<jmax; j++){
776         while (a2anew[j] != j){
777           k = a2anew[j]; a2anew[j] = a2anew[k]; a2anew[k] = k;
778           for (k1=0; k1<4; k1++){
779             dk[k1]       = aa[k*4+k1];
780             aa[k*4+k1] = aa[j*4+k1];
781             aa[j*4+k1] = dk[k1];
782           }
783         }
784         /* transform columnoriented blocks that lie in the lower triangle to roworiented blocks */
785         if (i > aj[j]){
786           /* printf("change orientation, row: %d, col: %d\n",i,aj[j]); */
787           ap = aa + j*4;     /* ptr to the beginning of the block */
788           dk[1] = ap[1];     /* swap ap[1] and ap[2] */
789           ap[1] = ap[2];
790           ap[2] = dk[1];
791         }
792       }
793     }
794     ierr = PetscFree(a2anew);CHKERRQ(ierr);
795   }
796 
797   /* for each row k */
798   for (k = 0; k<mbs; k++){
799 
800     /*initialize k-th row with elements nonzero in row perm(k) of A */
801     jmin = ai[perm_ptr[k]]; jmax = ai[perm_ptr[k]+1];
802     ap = aa + jmin*4;
803     for (j = jmin; j < jmax; j++){
804       vj = perm_ptr[aj[j]];         /* block col. index */
805       rtmp_ptr = rtmp + vj*4;
806       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
807     }
808 
809     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
810     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
811     i = jl[k]; /* first row to be added to k_th row  */
812 
813     while (i < k){
814       nexti = jl[i]; /* next row to be added to k_th row */
815 
816       /* compute multiplier */
817       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
818 
819       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
820       diag = ba + i*4;
821       u    = ba + ili*4;
822       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
823       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
824       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
825       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
826 
827       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
828       dk[0] += uik[0]*u[0] + uik[1]*u[1];
829       dk[1] += uik[2]*u[0] + uik[3]*u[1];
830       dk[2] += uik[0]*u[2] + uik[1]*u[3];
831       dk[3] += uik[2]*u[2] + uik[3]*u[3];
832 
833       /* update -U(i,k): ba[ili] = uik */
834       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
835 
836       /* add multiple of row i to k-th row ... */
837       jmin = ili + 1; jmax = bi[i+1];
838       if (jmin < jmax){
839         for (j=jmin; j<jmax; j++) {
840           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
841           rtmp_ptr = rtmp + bj[j]*4;
842           u = ba + j*4;
843           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
844           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
845           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
846           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
847         }
848 
849         /* ... add i to row list for next nonzero entry */
850         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
851         j     = bj[jmin];
852         jl[i] = jl[j]; jl[j] = i; /* update jl */
853       }
854       i = nexti;
855     }
856 
857     /* save nonzero entries in k-th row of U ... */
858 
859     /* invert diagonal block */
860     diag = ba+k*4;
861     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
862     ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr);
863 
864     jmin = bi[k]; jmax = bi[k+1];
865     if (jmin < jmax) {
866       for (j=jmin; j<jmax; j++){
867          vj = bj[j];           /* block col. index of U */
868          u   = ba + j*4;
869          rtmp_ptr = rtmp + vj*4;
870          for (k1=0; k1<4; k1++){
871            *u++        = *rtmp_ptr;
872            *rtmp_ptr++ = 0.0;
873          }
874       }
875 
876       /* ... add k to row list for first nonzero entry in k-th row */
877       il[k] = jmin;
878       i     = bj[jmin];
879       jl[k] = jl[i]; jl[i] = k;
880     }
881   }
882 
883   ierr = PetscFree(rtmp);CHKERRQ(ierr);
884   ierr = PetscFree(il);CHKERRQ(ierr);
885   ierr = PetscFree(dk);CHKERRQ(ierr);
886   if (a->permute) {
887     ierr = PetscFree(aa);CHKERRQ(ierr);
888   }
889   ierr = ISRestoreIndices(perm,&perm_ptr);CHKERRQ(ierr);
890   C->factor    = FACTOR_CHOLESKY;
891   C->assembled = PETSC_TRUE;
892   C->preallocated = PETSC_TRUE;
893   PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */
894   PetscFunctionReturn(0);
895 }
896 
897 /*
898       Version for when blocks are 2 by 2 Using natural ordering
899 */
900 #undef __FUNCT__
901 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering"
902 int MatCholeskyFactorNumeric_SeqSBAIJ_2_NaturalOrdering(Mat A,Mat *B)
903 {
904   Mat                C = *B;
905   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
906   int                ierr,i,j,mbs=a->mbs,*bi=b->i,*bj=b->j;
907   int                *ai,*aj,k,k1,jmin,jmax,*jl,*il,vj,nexti,ili;
908   MatScalar          *ba = b->a,*aa,*ap,*dk,*uik;
909   MatScalar          *u,*diag,*rtmp,*rtmp_ptr;
910 
911   PetscFunctionBegin;
912 
913   /* initialization */
914   /* il and jl record the first nonzero element in each row of the accessing
915      window U(0:k, k:mbs-1).
916      jl:    list of rows to be added to uneliminated rows
917             i>= k: jl(i) is the first row to be added to row i
918             i<  k: jl(i) is the row following row i in some list of rows
919             jl(i) = mbs indicates the end of a list
920      il(i): points to the first nonzero element in columns k,...,mbs-1 of
921             row i of U */
922   ierr = PetscMalloc(4*mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
923   ierr = PetscMemzero(rtmp,4*mbs*sizeof(MatScalar));CHKERRQ(ierr);
924   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
925   jl   = il + mbs;
926   for (i=0; i<mbs; i++) {
927     jl[i] = mbs; il[0] = 0;
928   }
929   ierr = PetscMalloc(8*sizeof(MatScalar),&dk);CHKERRQ(ierr);
930   uik  = dk + 4;
931 
932   ai = a->i; aj = a->j; aa = a->a;
933 
934   /* for each row k */
935   for (k = 0; k<mbs; k++){
936 
937     /*initialize k-th row with elements nonzero in row k of A */
938     jmin = ai[k]; jmax = ai[k+1];
939     ap = aa + jmin*4;
940     for (j = jmin; j < jmax; j++){
941       vj = aj[j];         /* block col. index */
942       rtmp_ptr = rtmp + vj*4;
943       for (i=0; i<4; i++) *rtmp_ptr++ = *ap++;
944     }
945 
946     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
947     ierr = PetscMemcpy(dk,rtmp+k*4,4*sizeof(MatScalar));CHKERRQ(ierr);
948     i = jl[k]; /* first row to be added to k_th row  */
949 
950     while (i < k){
951       nexti = jl[i]; /* next row to be added to k_th row */
952 
953       /* compute multiplier */
954       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
955 
956       /* uik = -inv(Di)*U_bar(i,k): - ba[ili]*ba[i] */
957       diag = ba + i*4;
958       u    = ba + ili*4;
959       uik[0] = -(diag[0]*u[0] + diag[2]*u[1]);
960       uik[1] = -(diag[1]*u[0] + diag[3]*u[1]);
961       uik[2] = -(diag[0]*u[2] + diag[2]*u[3]);
962       uik[3] = -(diag[1]*u[2] + diag[3]*u[3]);
963 
964       /* update D(k) += -U(i,k)^T * U_bar(i,k): dk += uik*ba[ili] */
965       dk[0] += uik[0]*u[0] + uik[1]*u[1];
966       dk[1] += uik[2]*u[0] + uik[3]*u[1];
967       dk[2] += uik[0]*u[2] + uik[1]*u[3];
968       dk[3] += uik[2]*u[2] + uik[3]*u[3];
969 
970       /* update -U(i,k): ba[ili] = uik */
971       ierr = PetscMemcpy(ba+ili*4,uik,4*sizeof(MatScalar));CHKERRQ(ierr);
972 
973       /* add multiple of row i to k-th row ... */
974       jmin = ili + 1; jmax = bi[i+1];
975       if (jmin < jmax){
976         for (j=jmin; j<jmax; j++) {
977           /* rtmp += -U(i,k)^T * U_bar(i,j): rtmp[bj[j]] += uik*ba[j]; */
978           rtmp_ptr = rtmp + bj[j]*4;
979           u = ba + j*4;
980           rtmp_ptr[0] += uik[0]*u[0] + uik[1]*u[1];
981           rtmp_ptr[1] += uik[2]*u[0] + uik[3]*u[1];
982           rtmp_ptr[2] += uik[0]*u[2] + uik[1]*u[3];
983           rtmp_ptr[3] += uik[2]*u[2] + uik[3]*u[3];
984         }
985 
986         /* ... add i to row list for next nonzero entry */
987         il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
988         j     = bj[jmin];
989         jl[i] = jl[j]; jl[j] = i; /* update jl */
990       }
991       i = nexti;
992     }
993 
994     /* save nonzero entries in k-th row of U ... */
995 
996     /* invert diagonal block */
997     diag = ba+k*4;
998     ierr = PetscMemcpy(diag,dk,4*sizeof(MatScalar));CHKERRQ(ierr);
999     ierr = Kernel_A_gets_inverse_A_2(diag);CHKERRQ(ierr);
1000 
1001     jmin = bi[k]; jmax = bi[k+1];
1002     if (jmin < jmax) {
1003       for (j=jmin; j<jmax; j++){
1004          vj = bj[j];           /* block col. index of U */
1005          u   = ba + j*4;
1006          rtmp_ptr = rtmp + vj*4;
1007          for (k1=0; k1<4; k1++){
1008            *u++        = *rtmp_ptr;
1009            *rtmp_ptr++ = 0.0;
1010          }
1011       }
1012 
1013       /* ... add k to row list for first nonzero entry in k-th row */
1014       il[k] = jmin;
1015       i     = bj[jmin];
1016       jl[k] = jl[i]; jl[i] = k;
1017     }
1018   }
1019 
1020   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1021   ierr = PetscFree(il);CHKERRQ(ierr);
1022   ierr = PetscFree(dk);CHKERRQ(ierr);
1023 
1024   C->factor    = FACTOR_CHOLESKY;
1025   C->assembled = PETSC_TRUE;
1026   C->preallocated = PETSC_TRUE;
1027   PetscLogFlops(1.3333*8*b->mbs); /* from inverting diagonal blocks */
1028   PetscFunctionReturn(0);
1029 }
1030 
1031 /*
1032     Numeric U^T*D*U factorization for SBAIJ format. Modified from SNF of YSMP.
1033     Version for blocks are 1 by 1.
1034 */
1035 #undef __FUNCT__
1036 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1"
1037 int MatCholeskyFactorNumeric_SeqSBAIJ_1(Mat A,Mat *B)
1038 {
1039   Mat                C = *B;
1040   Mat_SeqSBAIJ       *a = (Mat_SeqSBAIJ*)A->data,*b = (Mat_SeqSBAIJ *)C->data;
1041   IS                 ip = b->row;
1042   int                *rip,ierr,i,j,mbs = a->mbs,*bi = b->i,*bj = b->j;
1043   int                *ai,*aj,*r;
1044   int                k,jmin,jmax,*jl,*il,vj,nexti,ili;
1045   MatScalar          *rtmp;
1046   MatScalar          *ba = b->a,*aa,ak;
1047   MatScalar          dk,uikdi;
1048 
1049   PetscFunctionBegin;
1050   ierr  = ISGetIndices(ip,&rip);CHKERRQ(ierr);
1051   if (!a->permute){
1052     ai = a->i; aj = a->j; aa = a->a;
1053   } else {
1054     ai = a->inew; aj = a->jnew;
1055     ierr = PetscMalloc(ai[mbs]*sizeof(MatScalar),&aa);CHKERRQ(ierr);
1056     ierr = PetscMemcpy(aa,a->a,ai[mbs]*sizeof(MatScalar));CHKERRQ(ierr);
1057     ierr = PetscMalloc(ai[mbs]*sizeof(int),&r);CHKERRQ(ierr);
1058     ierr= PetscMemcpy(r,a->a2anew,(ai[mbs])*sizeof(int));CHKERRQ(ierr);
1059 
1060     jmin = ai[0]; jmax = ai[mbs];
1061     for (j=jmin; j<jmax; j++){
1062       while (r[j] != j){
1063         k = r[j]; r[j] = r[k]; r[k] = k;
1064         ak = aa[k]; aa[k] = aa[j]; aa[j] = ak;
1065       }
1066     }
1067     ierr = PetscFree(r);CHKERRQ(ierr);
1068   }
1069 
1070   /* initialization */
1071   /* il and jl record the first nonzero element in each row of the accessing
1072      window U(0:k, k:mbs-1).
1073      jl:    list of rows to be added to uneliminated rows
1074             i>= k: jl(i) is the first row to be added to row i
1075             i<  k: jl(i) is the row following row i in some list of rows
1076             jl(i) = mbs indicates the end of a list
1077      il(i): points to the first nonzero element in columns k,...,mbs-1 of
1078             row i of U */
1079   ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
1080   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
1081   jl   = il + mbs;
1082   for (i=0; i<mbs; i++) {
1083     rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1084   }
1085 
1086   /* for each row k */
1087   for (k = 0; k<mbs; k++){
1088 
1089     /*initialize k-th row with elements nonzero in row perm(k) of A */
1090     jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
1091 
1092     for (j = jmin; j < jmax; j++){
1093       vj = rip[aj[j]];
1094       rtmp[vj] = aa[j];
1095     }
1096 
1097     /* modify k-th row by adding in those rows i with U(i,k) != 0 */
1098     dk = rtmp[k];
1099     i = jl[k]; /* first row to be added to k_th row  */
1100 
1101     while (i < k){
1102       nexti = jl[i]; /* next row to be added to k_th row */
1103 
1104       /* compute multiplier, update D(k) and U(i,k) */
1105       ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1106       uikdi = - ba[ili]*ba[i];
1107       dk += uikdi*ba[ili];
1108       ba[ili] = uikdi; /* -U(i,k) */
1109 
1110       /* add multiple of row i to k-th row ... */
1111       jmin = ili + 1; jmax = bi[i+1];
1112       if (jmin < jmax){
1113         for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
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     /* check for zero pivot and save diagoanl element */
1123     if (dk == 0.0){
1124       SETERRQ(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot");
1125       /*
1126     } else if (PetscRealPart(dk) < 0.0){
1127       SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Negative pivot: d[%d] = %g\n",k,dk);
1128       */
1129     }
1130 
1131     /* save nonzero entries in k-th row of U ... */
1132     ba[k] = 1.0/dk;
1133     jmin = bi[k]; jmax = bi[k+1];
1134     if (jmin < jmax) {
1135       for (j=jmin; j<jmax; j++){
1136          vj = bj[j]; ba[j] = rtmp[vj]; rtmp[vj] = 0.0;
1137       }
1138       /* ... add k to row list for first nonzero entry in k-th row */
1139       il[k] = jmin;
1140       i     = bj[jmin];
1141       jl[k] = jl[i]; jl[i] = k;
1142     }
1143   }
1144 
1145   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1146   ierr = PetscFree(il);CHKERRQ(ierr);
1147   if (a->permute){
1148     ierr = PetscFree(aa);CHKERRQ(ierr);
1149   }
1150 
1151   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
1152   C->factor    = FACTOR_CHOLESKY;
1153   C->assembled = PETSC_TRUE;
1154   C->preallocated = PETSC_TRUE;
1155   PetscLogFlops(b->mbs);
1156   PetscFunctionReturn(0);
1157 }
1158 
1159 /*
1160   Version for when blocks are 1 by 1 Using natural ordering
1161 */
1162 #undef __FUNCT__
1163 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering"
1164 int MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering(Mat A,Mat *B)
1165 {
1166   Mat                C = *B;
1167   Mat_SeqSBAIJ       *a=(Mat_SeqSBAIJ*)A->data,*b=(Mat_SeqSBAIJ *)C->data;
1168   int                ierr,i,j,mbs = a->mbs;
1169   int                *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
1170   int                k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz,ndamp = 0;
1171   MatScalar          *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
1172   PetscReal          damping=b->factor_damping, zeropivot=b->factor_zeropivot,shift_amount;
1173   PetscTruth         damp,chshift;
1174   int                nshift=0;
1175 
1176   PetscFunctionBegin;
1177   /* initialization */
1178   /* il and jl record the first nonzero element in each row of the accessing
1179      window U(0:k, k:mbs-1).
1180      jl:    list of rows to be added to uneliminated rows
1181             i>= k: jl(i) is the first row to be added to row i
1182             i<  k: jl(i) is the row following row i in some list of rows
1183             jl(i) = mbs indicates the end of a list
1184      il(i): points to the first nonzero element in U(i,k:mbs-1)
1185   */
1186   ierr = PetscMalloc(mbs*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
1187   ierr = PetscMalloc(2*mbs*sizeof(int),&il);CHKERRQ(ierr);
1188   jl   = il + mbs;
1189 
1190   shift_amount = 0;
1191   do {
1192     damp = PETSC_FALSE;
1193     chshift = PETSC_FALSE;
1194     for (i=0; i<mbs; i++) {
1195       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
1196     }
1197 
1198     for (k = 0; k<mbs; k++){ /* row k */
1199     /*initialize k-th row with elements nonzero in row perm(k) of A */
1200       nz   = ai[k+1] - ai[k];
1201       acol = aj + ai[k];
1202       aval = aa + ai[k];
1203       bval = ba + bi[k];
1204       while (nz -- ){
1205         rtmp[*acol++] = *aval++;
1206         *bval++       = 0.0; /* for in-place factorization */
1207       }
1208       /* damp the diagonal of the matrix */
1209       if (ndamp||nshift) rtmp[k] += damping+shift_amount;
1210 
1211       /* modify k-th row by adding in those rows i with U(i,k) != 0 */
1212       dk = rtmp[k];
1213       i  = jl[k]; /* first row to be added to k_th row  */
1214 
1215       while (i < k){
1216         nexti = jl[i]; /* next row to be added to k_th row */
1217 
1218         /* compute multiplier, update D(k) and U(i,k) */
1219         ili   = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
1220         uikdi = - ba[ili]*ba[bi[i]];
1221         dk   += uikdi*ba[ili];
1222         ba[ili] = uikdi; /* -U(i,k) */
1223 
1224         /* add multiple of row i to k-th row ... */
1225         jmin = ili + 1;
1226         nz   = bi[i+1] - jmin;
1227         if (nz > 0){
1228           bcol = bj + jmin;
1229           bval = ba + jmin;
1230           while (nz --) rtmp[*bcol++] += uikdi*(*bval++);
1231           /* ... add i to row list for next nonzero entry */
1232           il[i] = jmin;             /* update il(i) in column k+1, ... mbs-1 */
1233           j     = bj[jmin];
1234           jl[i] = jl[j]; jl[j] = i; /* update jl */
1235         }
1236         i = nexti;
1237       }
1238 
1239       if (PetscRealPart(dk) < zeropivot && b->factor_shift){
1240 	/* calculate a shift that would make this row diagonally dominant */
1241 	PetscReal rs = PetscAbs(PetscRealPart(dk));
1242 	jmin      = bi[k]+1;
1243 	nz        = bi[k+1] - jmin;
1244 	if (nz){
1245 	  bcol = bj + jmin;
1246 	  bval = ba + jmin;
1247 	  while (nz--){
1248 	    rs += PetscAbsScalar(rtmp[*bcol++]);
1249 	  }
1250 	}
1251 	/* if this shift is less than the previous, just up the previous
1252 	   one by a bit */
1253 	shift_amount = PetscMax(rs,1.1*shift_amount);
1254 	chshift  = PETSC_TRUE;
1255 	/* Unlike in the ILU case there is no exit condition on nshift:
1256 	   we increase the shift until it converges. There is no guarantee that
1257 	   this algorithm converges faster or slower, or is better or worse
1258 	   than the ILU algorithm. */
1259 	nshift++;
1260 	break;
1261       }
1262       if (PetscRealPart(dk) < zeropivot){
1263         if (damping == (PetscReal) PETSC_DECIDE) damping = -PetscRealPart(dk)/(k+1);
1264         if (damping > 0.0) {
1265           if (ndamp) damping *= 2.0;
1266           damp = PETSC_TRUE;
1267           ndamp++;
1268           break;
1269         } else if (PetscAbsScalar(dk) < zeropivot){
1270           SETERRQ3(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot row %d value %g tolerance %g",k,PetscRealPart(dk),zeropivot);
1271         } else {
1272           PetscLogInfo((PetscObject)A,"Negative pivot %g in row %d of Cholesky factorization\n",PetscRealPart(dk),k);
1273         }
1274       }
1275 
1276       /* save nonzero entries in k-th row of U ... */
1277       /* printf("%d, dk: %g, 1/dk: %g\n",k,dk,1/dk); */
1278       ba[bi[k]] = 1.0/dk;
1279       jmin      = bi[k]+1;
1280       nz        = bi[k+1] - jmin;
1281       if (nz){
1282         bcol = bj + jmin;
1283         bval = ba + jmin;
1284         while (nz--){
1285           *bval++       = rtmp[*bcol];
1286           rtmp[*bcol++] = 0.0;
1287         }
1288         /* ... add k to row list for first nonzero entry in k-th row */
1289         il[k] = jmin;
1290         i     = bj[jmin];
1291         jl[k] = jl[i]; jl[i] = k;
1292       }
1293     } /* end of for (k = 0; k<mbs; k++) */
1294   } while (damp||chshift);
1295   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1296   ierr = PetscFree(il);CHKERRQ(ierr);
1297 
1298   C->factor       = FACTOR_CHOLESKY;
1299   C->assembled    = PETSC_TRUE;
1300   C->preallocated = PETSC_TRUE;
1301   PetscLogFlops(b->mbs);
1302   if (ndamp) {
1303     PetscLogInfo(0,"MatCholeskyFactorNumerical_SeqSBAIJ_1_NaturalOrdering: number of damping tries %d damping value %g\n",ndamp,damping);
1304   }
1305  if (nshift) {
1306     PetscLogInfo(0,"MatCholeskyFactorNumeric_SeqSBAIJ_1_NaturalOrdering diagonal shifted %d shifts\n",nshift);
1307   }
1308 
1309   PetscFunctionReturn(0);
1310 }
1311 
1312 #undef __FUNCT__
1313 #define __FUNCT__ "MatCholeskyFactor_SeqSBAIJ"
1314 int MatCholeskyFactor_SeqSBAIJ(Mat A,IS perm,MatFactorInfo *info)
1315 {
1316   int ierr;
1317   Mat C;
1318 
1319   PetscFunctionBegin;
1320   ierr = MatCholeskyFactorSymbolic(A,perm,info,&C);CHKERRQ(ierr);
1321   ierr = MatCholeskyFactorNumeric(A,&C);CHKERRQ(ierr);
1322   ierr = MatHeaderCopy(A,C);CHKERRQ(ierr);
1323   PetscFunctionReturn(0);
1324 }
1325 
1326 
1327