xref: /petsc/src/mat/impls/baij/seq/baijfact.c (revision 0e9bae810fdaeb60e2713eaa8ddb89f42e079fd1)
1 
2 /*
3     Factorization code for BAIJ format.
4 */
5 #include <../src/mat/impls/baij/seq/baij.h>
6 #include <../src/mat/blockinvert.h>
7 
8 #undef __FUNCT__
9 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2"
10 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2(Mat B,Mat A,const MatFactorInfo *info)
11 {
12   Mat             C=B;
13   Mat_SeqBAIJ     *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
14   IS              isrow = b->row,isicol = b->icol;
15   PetscErrorCode  ierr;
16   const PetscInt  *r,*ic;
17   PetscInt        i,j,k,nz,nzL,row,*pj;
18   const PetscInt  n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2;
19   const PetscInt  *ajtmp,*bjtmp,*bdiag=b->diag;
20   MatScalar       *rtmp,*pc,*mwork,*pv;
21   MatScalar       *aa=a->a,*v;
22   PetscInt        flg;
23   PetscReal       shift = info->shiftamount;
24 
25   PetscFunctionBegin;
26   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
27   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
28 
29   /* generate work space needed by the factorization */
30   ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr);
31   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
32 
33   for (i=0; i<n; i++){
34     /* zero rtmp */
35     /* L part */
36     nz    = bi[i+1] - bi[i];
37     bjtmp = bj + bi[i];
38     for  (j=0; j<nz; j++){
39       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
40     }
41 
42     /* U part */
43     nz = bdiag[i] - bdiag[i+1];
44     bjtmp = bj + bdiag[i+1]+1;
45     for  (j=0; j<nz; j++){
46       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
47     }
48 
49     /* load in initial (unfactored row) */
50     nz    = ai[r[i]+1] - ai[r[i]];
51     ajtmp = aj + ai[r[i]];
52     v     = aa + bs2*ai[r[i]];
53     for (j=0; j<nz; j++) {
54       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
55     }
56 
57     /* elimination */
58     bjtmp = bj + bi[i];
59     nzL   = bi[i+1] - bi[i];
60     for(k=0;k < nzL;k++) {
61       row = bjtmp[k];
62       pc = rtmp + bs2*row;
63       for (flg=0,j=0; j<bs2; j++) { if (pc[j] != (PetscScalar)0.0) { flg = 1; break; }}
64       if (flg) {
65         pv = b->a + bs2*bdiag[row];
66         /* PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
67         ierr = PetscKernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
68 
69         pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */
70         pv = b->a + bs2*(bdiag[row+1]+1);
71         nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */
72         for (j=0; j<nz; j++) {
73           /* PetscKernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
74           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
75           v    = rtmp + 4*pj[j];
76           ierr = PetscKernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
77           pv  += 4;
78         }
79         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
80       }
81     }
82 
83     /* finished row so stick it into b->a */
84     /* L part */
85     pv   = b->a + bs2*bi[i] ;
86     pj   = b->j + bi[i] ;
87     nz   = bi[i+1] - bi[i];
88     for (j=0; j<nz; j++) {
89       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
90     }
91 
92     /* Mark diagonal and invert diagonal for simplier triangular solves */
93     pv   = b->a + bs2*bdiag[i];
94     pj   = b->j + bdiag[i];
95     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
96     /* ierr = PetscKernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
97     ierr = PetscKernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
98 
99     /* U part */
100     pv = b->a + bs2*(bdiag[i+1]+1);
101     pj = b->j + bdiag[i+1]+1;
102     nz = bdiag[i] - bdiag[i+1] - 1;
103     for (j=0; j<nz; j++){
104       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
105     }
106   }
107 
108   ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr);
109   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
110   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
111   C->ops->solve          = MatSolve_SeqBAIJ_2;
112   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2;
113 
114   C->assembled = PETSC_TRUE;
115   ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
116   PetscFunctionReturn(0);
117 }
118 
119 #undef __FUNCT__
120 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering"
121 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info)
122 {
123   Mat             C=B;
124   Mat_SeqBAIJ     *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
125   PetscErrorCode  ierr;
126   PetscInt        i,j,k,nz,nzL,row,*pj;
127   const PetscInt  n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2;
128   const PetscInt  *ajtmp,*bjtmp,*bdiag=b->diag;
129   MatScalar       *rtmp,*pc,*mwork,*pv;
130   MatScalar       *aa=a->a,*v;
131   PetscInt       flg;
132   PetscReal      shift = info->shiftamount;
133 
134   PetscFunctionBegin;
135   /* generate work space needed by the factorization */
136   ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr);
137   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
138 
139   for (i=0; i<n; i++){
140     /* zero rtmp */
141     /* L part */
142     nz    = bi[i+1] - bi[i];
143     bjtmp = bj + bi[i];
144     for  (j=0; j<nz; j++){
145       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
146     }
147 
148     /* U part */
149     nz = bdiag[i] - bdiag[i+1];
150     bjtmp = bj + bdiag[i+1]+1;
151     for  (j=0; j<nz; j++){
152       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
153     }
154 
155     /* load in initial (unfactored row) */
156     nz    = ai[i+1] - ai[i];
157     ajtmp = aj + ai[i];
158     v     = aa + bs2*ai[i];
159     for (j=0; j<nz; j++) {
160       ierr = PetscMemcpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
161     }
162 
163     /* elimination */
164     bjtmp = bj + bi[i];
165     nzL   = bi[i+1] - bi[i];
166     for(k=0;k < nzL;k++) {
167       row = bjtmp[k];
168       pc = rtmp + bs2*row;
169       for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=(PetscScalar)0.0) { flg = 1; break; }}
170       if (flg) {
171         pv = b->a + bs2*bdiag[row];
172         /* PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
173         ierr = PetscKernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
174 
175         pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */
176 	pv = b->a + bs2*(bdiag[row+1]+1);
177 	nz = bdiag[row]-bdiag[row+1] - 1; /* num of entries in U(row,:) excluding diag */
178         for (j=0; j<nz; j++) {
179           /* PetscKernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
180           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
181           v    = rtmp + 4*pj[j];
182           ierr = PetscKernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
183           pv  += 4;
184         }
185         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
186       }
187     }
188 
189     /* finished row so stick it into b->a */
190     /* L part */
191     pv   = b->a + bs2*bi[i] ;
192     pj   = b->j + bi[i] ;
193     nz   = bi[i+1] - bi[i];
194     for (j=0; j<nz; j++) {
195       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
196     }
197 
198     /* Mark diagonal and invert diagonal for simplier triangular solves */
199     pv   = b->a + bs2*bdiag[i];
200     pj   = b->j + bdiag[i];
201     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
202     /* ierr = PetscKernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
203     ierr = PetscKernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
204 
205     /* U part */
206     /*
207     pv = b->a + bs2*bi[2*n-i];
208     pj = b->j + bi[2*n-i];
209     nz = bi[2*n-i+1] - bi[2*n-i] - 1;
210     */
211     pv = b->a + bs2*(bdiag[i+1]+1);
212     pj = b->j + bdiag[i+1]+1;
213     nz = bdiag[i] - bdiag[i+1] - 1;
214     for (j=0; j<nz; j++){
215       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
216     }
217   }
218   ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr);
219 
220   C->ops->solve          = MatSolve_SeqBAIJ_2_NaturalOrdering;
221   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering;
222   C->assembled = PETSC_TRUE;
223   ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
224   PetscFunctionReturn(0);
225 }
226 
227 #undef __FUNCT__
228 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_inplace"
229 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_inplace(Mat B,Mat A,const MatFactorInfo *info)
230 {
231   Mat            C = B;
232   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
233   IS             isrow = b->row,isicol = b->icol;
234   PetscErrorCode ierr;
235   const PetscInt *r,*ic;
236   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
237   PetscInt       *ajtmpold,*ajtmp,nz,row;
238   PetscInt       *diag_offset=b->diag,idx,*ai=a->i,*aj=a->j,*pj;
239   MatScalar      *pv,*v,*rtmp,m1,m2,m3,m4,*pc,*w,*x,x1,x2,x3,x4;
240   MatScalar      p1,p2,p3,p4;
241   MatScalar      *ba = b->a,*aa = a->a;
242   PetscReal      shift = info->shiftamount;
243 
244   PetscFunctionBegin;
245   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
246   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
247   ierr  = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
248 
249   for (i=0; i<n; i++) {
250     nz    = bi[i+1] - bi[i];
251     ajtmp = bj + bi[i];
252     for  (j=0; j<nz; j++) {
253       x = rtmp+4*ajtmp[j]; x[0] = x[1] = x[2] = x[3] = 0.0;
254     }
255     /* load in initial (unfactored row) */
256     idx      = r[i];
257     nz       = ai[idx+1] - ai[idx];
258     ajtmpold = aj + ai[idx];
259     v        = aa + 4*ai[idx];
260     for (j=0; j<nz; j++) {
261       x    = rtmp+4*ic[ajtmpold[j]];
262       x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3];
263       v    += 4;
264     }
265     row = *ajtmp++;
266     while (row < i) {
267       pc = rtmp + 4*row;
268       p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3];
269       if (p1 != (PetscScalar)0.0 || p2 != (PetscScalar)0.0 || p3 != (PetscScalar)0.0 || p4 != (PetscScalar)0.0) {
270         pv = ba + 4*diag_offset[row];
271         pj = bj + diag_offset[row] + 1;
272         x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
273         pc[0] = m1 = p1*x1 + p3*x2;
274         pc[1] = m2 = p2*x1 + p4*x2;
275         pc[2] = m3 = p1*x3 + p3*x4;
276         pc[3] = m4 = p2*x3 + p4*x4;
277         nz = bi[row+1] - diag_offset[row] - 1;
278         pv += 4;
279         for (j=0; j<nz; j++) {
280           x1   = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
281           x    = rtmp + 4*pj[j];
282           x[0] -= m1*x1 + m3*x2;
283           x[1] -= m2*x1 + m4*x2;
284           x[2] -= m1*x3 + m3*x4;
285           x[3] -= m2*x3 + m4*x4;
286           pv   += 4;
287         }
288         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
289       }
290       row = *ajtmp++;
291     }
292     /* finished row so stick it into b->a */
293     pv = ba + 4*bi[i];
294     pj = bj + bi[i];
295     nz = bi[i+1] - bi[i];
296     for (j=0; j<nz; j++) {
297       x     = rtmp+4*pj[j];
298       pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3];
299       pv   += 4;
300     }
301     /* invert diagonal block */
302     w = ba + 4*diag_offset[i];
303     ierr = PetscKernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
304   }
305 
306   ierr = PetscFree(rtmp);CHKERRQ(ierr);
307   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
308   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
309   C->ops->solve          = MatSolve_SeqBAIJ_2_inplace;
310   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_inplace;
311   C->assembled = PETSC_TRUE;
312   ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
313   PetscFunctionReturn(0);
314 }
315 /*
316       Version for when blocks are 2 by 2 Using natural ordering
317 */
318 #undef __FUNCT__
319 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace"
320 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info)
321 {
322   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
323   PetscErrorCode ierr;
324   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
325   PetscInt       *ajtmpold,*ajtmp,nz,row;
326   PetscInt       *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj;
327   MatScalar      *pv,*v,*rtmp,*pc,*w,*x;
328   MatScalar      p1,p2,p3,p4,m1,m2,m3,m4,x1,x2,x3,x4;
329   MatScalar      *ba = b->a,*aa = a->a;
330   PetscReal      shift = info->shiftamount;
331 
332   PetscFunctionBegin;
333   ierr = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
334   for (i=0; i<n; i++) {
335     nz    = bi[i+1] - bi[i];
336     ajtmp = bj + bi[i];
337     for  (j=0; j<nz; j++) {
338       x = rtmp+4*ajtmp[j];
339       x[0]  = x[1]  = x[2]  = x[3]  = 0.0;
340     }
341     /* load in initial (unfactored row) */
342     nz       = ai[i+1] - ai[i];
343     ajtmpold = aj + ai[i];
344     v        = aa + 4*ai[i];
345     for (j=0; j<nz; j++) {
346       x    = rtmp+4*ajtmpold[j];
347       x[0]  = v[0];  x[1]  = v[1];  x[2]  = v[2];  x[3]  = v[3];
348       v    += 4;
349     }
350     row = *ajtmp++;
351     while (row < i) {
352       pc  = rtmp + 4*row;
353       p1  = pc[0];  p2  = pc[1];  p3  = pc[2];  p4  = pc[3];
354       if (p1 != (PetscScalar)0.0 || p2 != (PetscScalar)0.0 || p3 != (PetscScalar)0.0 || p4 != (PetscScalar)0.0) {
355         pv = ba + 4*diag_offset[row];
356         pj = bj + diag_offset[row] + 1;
357         x1  = pv[0];  x2  = pv[1];  x3  = pv[2];  x4  = pv[3];
358         pc[0] = m1 = p1*x1 + p3*x2;
359         pc[1] = m2 = p2*x1 + p4*x2;
360         pc[2] = m3 = p1*x3 + p3*x4;
361         pc[3] = m4 = p2*x3 + p4*x4;
362         nz = bi[row+1] - diag_offset[row] - 1;
363         pv += 4;
364         for (j=0; j<nz; j++) {
365           x1   = pv[0];  x2  = pv[1];   x3 = pv[2];  x4  = pv[3];
366           x    = rtmp + 4*pj[j];
367           x[0] -= m1*x1 + m3*x2;
368           x[1] -= m2*x1 + m4*x2;
369           x[2] -= m1*x3 + m3*x4;
370           x[3] -= m2*x3 + m4*x4;
371           pv   += 4;
372         }
373         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
374       }
375       row = *ajtmp++;
376     }
377     /* finished row so stick it into b->a */
378     pv = ba + 4*bi[i];
379     pj = bj + bi[i];
380     nz = bi[i+1] - bi[i];
381     for (j=0; j<nz; j++) {
382       x      = rtmp+4*pj[j];
383       pv[0]  = x[0];  pv[1]  = x[1];  pv[2]  = x[2];  pv[3]  = x[3];
384       /*
385       printf(" col %d:",pj[j]);
386       PetscInt j1;
387       for (j1=0; j1<4; j1++) printf(" %g,",*(pv+j1));
388       printf("\n");
389       */
390       pv   += 4;
391     }
392     /* invert diagonal block */
393     w = ba + 4*diag_offset[i];
394     /*
395     printf(" \n%d -th: diag: ",i);
396     for (j=0; j<4; j++){
397       printf(" %g,",w[j]);
398     }
399     printf("\n----------------------------\n");
400     */
401     ierr = PetscKernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
402   }
403 
404   ierr = PetscFree(rtmp);CHKERRQ(ierr);
405   C->ops->solve          = MatSolve_SeqBAIJ_2_NaturalOrdering_inplace;
406   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering_inplace;
407   C->assembled = PETSC_TRUE;
408   ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
409   PetscFunctionReturn(0);
410 }
411 
412 /* ----------------------------------------------------------- */
413 /*
414      Version for when blocks are 1 by 1.
415 */
416 #undef __FUNCT__
417 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_1"
418 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_1(Mat B,Mat A,const MatFactorInfo *info)
419 {
420   Mat              C=B;
421   Mat_SeqBAIJ      *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
422   IS               isrow = b->row,isicol = b->icol;
423   PetscErrorCode   ierr;
424   const PetscInt   *r,*ic,*ics;
425   const PetscInt   n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bdiag=b->diag;
426   PetscInt         i,j,k,nz,nzL,row,*pj;
427   const PetscInt   *ajtmp,*bjtmp;
428   MatScalar        *rtmp,*pc,multiplier,*pv;
429   const  MatScalar *aa=a->a,*v;
430   PetscBool        row_identity,col_identity;
431   FactorShiftCtx   sctx;
432   const PetscInt   *ddiag;
433   PetscReal        rs;
434   MatScalar        d;
435 
436   PetscFunctionBegin;
437   /* MatPivotSetUp(): initialize shift context sctx */
438   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
439 
440   if (info->shifttype == (PetscReal) MAT_SHIFT_POSITIVE_DEFINITE) { /* set sctx.shift_top=max{rs} */
441     ddiag          = a->diag;
442     sctx.shift_top = info->zeropivot;
443     for (i=0; i<n; i++) {
444       /* calculate sum(|aij|)-RealPart(aii), amt of shift needed for this row */
445       d  = (aa)[ddiag[i]];
446       rs = -PetscAbsScalar(d) - PetscRealPart(d);
447       v  = aa+ai[i];
448       nz = ai[i+1] - ai[i];
449       for (j=0; j<nz; j++)
450 	rs += PetscAbsScalar(v[j]);
451       if (rs>sctx.shift_top) sctx.shift_top = rs;
452     }
453     sctx.shift_top   *= 1.1;
454     sctx.nshift_max   = 5;
455     sctx.shift_lo     = 0.;
456     sctx.shift_hi     = 1.;
457   }
458 
459   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
460   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
461   ierr = PetscMalloc((n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
462   ics  = ic;
463 
464   do {
465     sctx.newshift = PETSC_FALSE;
466     for (i=0; i<n; i++){
467       /* zero rtmp */
468       /* L part */
469       nz    = bi[i+1] - bi[i];
470       bjtmp = bj + bi[i];
471       for  (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0;
472 
473       /* U part */
474       nz = bdiag[i]-bdiag[i+1];
475       bjtmp = bj + bdiag[i+1]+1;
476       for  (j=0; j<nz; j++) rtmp[bjtmp[j]] = 0.0;
477 
478       /* load in initial (unfactored row) */
479       nz    = ai[r[i]+1] - ai[r[i]];
480       ajtmp = aj + ai[r[i]];
481       v     = aa + ai[r[i]];
482       for (j=0; j<nz; j++) {
483         rtmp[ics[ajtmp[j]]] = v[j];
484       }
485       /* ZeropivotApply() */
486       rtmp[i] += sctx.shift_amount;  /* shift the diagonal of the matrix */
487 
488       /* elimination */
489       bjtmp = bj + bi[i];
490       row   = *bjtmp++;
491       nzL   = bi[i+1] - bi[i];
492       for(k=0; k < nzL;k++) {
493         pc = rtmp + row;
494         if (*pc != (PetscScalar)0.0) {
495           pv         = b->a + bdiag[row];
496           multiplier = *pc * (*pv);
497           *pc        = multiplier;
498           pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */
499 	  pv = b->a + bdiag[row+1]+1;
500 	  nz = bdiag[row]-bdiag[row+1]-1; /* num of entries in U(row,:) excluding diag */
501           for (j=0; j<nz; j++) rtmp[pj[j]] -= multiplier * pv[j];
502           ierr = PetscLogFlops(2.0*nz);CHKERRQ(ierr);
503         }
504         row = *bjtmp++;
505       }
506 
507       /* finished row so stick it into b->a */
508       rs = 0.0;
509       /* L part */
510       pv   = b->a + bi[i] ;
511       pj   = b->j + bi[i] ;
512       nz   = bi[i+1] - bi[i];
513       for (j=0; j<nz; j++) {
514         pv[j] = rtmp[pj[j]]; rs += PetscAbsScalar(pv[j]);
515       }
516 
517       /* U part */
518       pv = b->a + bdiag[i+1]+1;
519       pj = b->j + bdiag[i+1]+1;
520       nz = bdiag[i] - bdiag[i+1]-1;
521       for (j=0; j<nz; j++) {
522         pv[j] = rtmp[pj[j]]; rs += PetscAbsScalar(pv[j]);
523       }
524 
525       sctx.rs  = rs;
526       sctx.pv  = rtmp[i];
527       ierr = MatPivotCheck(A,info,&sctx,i);CHKERRQ(ierr);
528       if(sctx.newshift) break; /* break for-loop */
529       rtmp[i] = sctx.pv; /* sctx.pv might be updated in the case of MAT_SHIFT_INBLOCKS */
530 
531       /* Mark diagonal and invert diagonal for simplier triangular solves */
532       pv  = b->a + bdiag[i];
533       *pv = (PetscScalar)1.0/rtmp[i];
534 
535     } /* endof for (i=0; i<n; i++){ */
536 
537     /* MatPivotRefine() */
538     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE && !sctx.newshift && sctx.shift_fraction>0 && sctx.nshift<sctx.nshift_max){
539       /*
540        * if no shift in this attempt & shifting & started shifting & can refine,
541        * then try lower shift
542        */
543       sctx.shift_hi       = sctx.shift_fraction;
544       sctx.shift_fraction = (sctx.shift_hi+sctx.shift_lo)/2.;
545       sctx.shift_amount   = sctx.shift_fraction * sctx.shift_top;
546       sctx.newshift       = PETSC_TRUE;
547       sctx.nshift++;
548     }
549   } while (sctx.newshift);
550 
551   ierr = PetscFree(rtmp);CHKERRQ(ierr);
552   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
553   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
554 
555   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
556   ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr);
557   if (row_identity && col_identity) {
558     C->ops->solve = MatSolve_SeqBAIJ_1_NaturalOrdering;
559     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_NaturalOrdering;
560   } else {
561     C->ops->solve = MatSolve_SeqBAIJ_1;
562     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1;
563   }
564   C->assembled     = PETSC_TRUE;
565   ierr = PetscLogFlops(C->cmap->n);CHKERRQ(ierr);
566 
567   /* MatShiftView(A,info,&sctx) */
568   if (sctx.nshift){
569     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
570       ierr = PetscInfo4(A,"number of shift_pd tries %D, shift_amount %G, diagonal shifted up by %e fraction top_value %e\n",sctx.nshift,sctx.shift_amount,sctx.shift_fraction,sctx.shift_top);CHKERRQ(ierr);
571     } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
572       ierr = PetscInfo2(A,"number of shift_nz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
573     } else if (info->shifttype == (PetscReal)MAT_SHIFT_INBLOCKS){
574       ierr = PetscInfo2(A,"number of shift_inblocks applied %D, each shift_amount %G\n",sctx.nshift,info->shiftamount);CHKERRQ(ierr);
575     }
576   }
577   PetscFunctionReturn(0);
578 }
579 
580 #undef __FUNCT__
581 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_1_inplace"
582 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info)
583 {
584   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
585   IS             isrow = b->row,isicol = b->icol;
586   PetscErrorCode ierr;
587   const PetscInt *r,*ic;
588   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
589   PetscInt       *ajtmpold,*ajtmp,nz,row,*ai = a->i,*aj = a->j;
590   PetscInt       *diag_offset = b->diag,diag,*pj;
591   MatScalar      *pv,*v,*rtmp,multiplier,*pc;
592   MatScalar      *ba = b->a,*aa = a->a;
593   PetscBool      row_identity, col_identity;
594 
595   PetscFunctionBegin;
596   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
597   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
598   ierr  = PetscMalloc((n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
599 
600   for (i=0; i<n; i++) {
601     nz    = bi[i+1] - bi[i];
602     ajtmp = bj + bi[i];
603     for  (j=0; j<nz; j++) rtmp[ajtmp[j]] = 0.0;
604 
605     /* load in initial (unfactored row) */
606     nz       = ai[r[i]+1] - ai[r[i]];
607     ajtmpold = aj + ai[r[i]];
608     v        = aa + ai[r[i]];
609     for (j=0; j<nz; j++) rtmp[ic[ajtmpold[j]]] =  v[j];
610 
611     row = *ajtmp++;
612     while (row < i) {
613       pc = rtmp + row;
614       if (*pc != 0.0) {
615         pv         = ba + diag_offset[row];
616         pj         = bj + diag_offset[row] + 1;
617         multiplier = *pc * *pv++;
618         *pc        = multiplier;
619         nz         = bi[row+1] - diag_offset[row] - 1;
620         for (j=0; j<nz; j++) rtmp[pj[j]] -= multiplier * pv[j];
621         ierr = PetscLogFlops(1.0+2.0*nz);CHKERRQ(ierr);
622       }
623       row = *ajtmp++;
624     }
625     /* finished row so stick it into b->a */
626     pv = ba + bi[i];
627     pj = bj + bi[i];
628     nz = bi[i+1] - bi[i];
629     for (j=0; j<nz; j++) {pv[j] = rtmp[pj[j]];}
630     diag = diag_offset[i] - bi[i];
631     /* check pivot entry for current row */
632     if (pv[diag] == 0.0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot: row in original ordering %D in permuted ordering %D",r[i],i);
633     pv[diag] = 1.0/pv[diag];
634   }
635 
636   ierr = PetscFree(rtmp);CHKERRQ(ierr);
637   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
638   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
639   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
640   ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr);
641   if (row_identity && col_identity) {
642     C->ops->solve          = MatSolve_SeqBAIJ_1_NaturalOrdering_inplace;
643     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_NaturalOrdering_inplace;
644   } else {
645     C->ops->solve          = MatSolve_SeqBAIJ_1_inplace;
646     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_inplace;
647   }
648   C->assembled = PETSC_TRUE;
649   ierr = PetscLogFlops(C->cmap->n);CHKERRQ(ierr);
650   PetscFunctionReturn(0);
651 }
652 
653 EXTERN_C_BEGIN
654 #undef __FUNCT__
655 #define __FUNCT__ "MatGetFactor_seqbaij_petsc"
656 PetscErrorCode MatGetFactor_seqbaij_petsc(Mat A,MatFactorType ftype,Mat *B)
657 {
658   PetscInt           n = A->rmap->n;
659   PetscErrorCode     ierr;
660 
661   PetscFunctionBegin;
662 #if defined(PETSC_USE_COMPLEX)
663   if (A->hermitian && (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC))SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Hermitian Factor is not supported");
664 #endif
665   ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr);
666   ierr = MatSetSizes(*B,n,n,n,n);CHKERRQ(ierr);
667   if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU || ftype == MAT_FACTOR_ILUDT) {
668     ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr);
669     (*B)->ops->lufactorsymbolic  = MatLUFactorSymbolic_SeqBAIJ;
670     (*B)->ops->ilufactorsymbolic = MatILUFactorSymbolic_SeqBAIJ;
671   } else if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
672     ierr = MatSetType(*B,MATSEQSBAIJ);CHKERRQ(ierr);
673     ierr = MatSeqSBAIJSetPreallocation(*B,A->rmap->bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
674     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqBAIJ;
675     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqBAIJ;
676   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
677   (*B)->factortype = ftype;
678   PetscFunctionReturn(0);
679 }
680 EXTERN_C_END
681 
682 EXTERN_C_BEGIN
683 #undef __FUNCT__
684 #define __FUNCT__ "MatGetFactorAvailable_seqbaij_petsc"
685 PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat A,MatFactorType ftype,PetscBool  *flg)
686 {
687   PetscFunctionBegin;
688   *flg = PETSC_TRUE;
689   PetscFunctionReturn(0);
690 }
691 EXTERN_C_END
692 
693 /* ----------------------------------------------------------- */
694 #undef __FUNCT__
695 #define __FUNCT__ "MatLUFactor_SeqBAIJ"
696 PetscErrorCode MatLUFactor_SeqBAIJ(Mat A,IS row,IS col,const MatFactorInfo *info)
697 {
698   PetscErrorCode ierr;
699   Mat            C;
700 
701   PetscFunctionBegin;
702   ierr = MatGetFactor(A,MATSOLVERPETSC,MAT_FACTOR_LU,&C);CHKERRQ(ierr);
703   ierr = MatLUFactorSymbolic(C,A,row,col,info);CHKERRQ(ierr);
704   ierr = MatLUFactorNumeric(C,A,info);CHKERRQ(ierr);
705   A->ops->solve            = C->ops->solve;
706   A->ops->solvetranspose   = C->ops->solvetranspose;
707   ierr = MatHeaderMerge(A,C);CHKERRQ(ierr);
708   ierr = PetscLogObjectParent(A,((Mat_SeqBAIJ*)(A->data))->icol);CHKERRQ(ierr);
709   PetscFunctionReturn(0);
710 }
711 
712 #include <../src/mat/impls/sbaij/seq/sbaij.h>
713 #undef __FUNCT__
714 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N"
715 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N(Mat C,Mat A,const MatFactorInfo *info)
716 {
717   PetscErrorCode ierr;
718   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
719   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
720   IS             ip=b->row;
721   const PetscInt *rip;
722   PetscInt       i,j,mbs=a->mbs,bs=A->rmap->bs,*bi=b->i,*bj=b->j,*bcol;
723   PetscInt       *ai=a->i,*aj=a->j;
724   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
725   MatScalar      *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi;
726   PetscReal      rs;
727   FactorShiftCtx sctx;
728 
729   PetscFunctionBegin;
730   if (bs > 1) {/* convert A to a SBAIJ matrix and apply Cholesky factorization from it */
731     if (!a->sbaijMat){
732       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
733     }
734     ierr = (a->sbaijMat)->ops->choleskyfactornumeric(C,a->sbaijMat,info);CHKERRQ(ierr);
735     ierr = MatDestroy(&a->sbaijMat);CHKERRQ(ierr);
736     PetscFunctionReturn(0);
737   }
738 
739   /* MatPivotSetUp(): initialize shift context sctx */
740   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
741 
742   ierr  = ISGetIndices(ip,&rip);CHKERRQ(ierr);
743   ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr);
744 
745   sctx.shift_amount = 0.;
746   sctx.nshift       = 0;
747   do {
748     sctx.newshift = PETSC_FALSE;
749     for (i=0; i<mbs; i++) {
750       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
751     }
752 
753     for (k = 0; k<mbs; k++){
754       bval = ba + bi[k];
755       /* initialize k-th row by the perm[k]-th row of A */
756       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
757       for (j = jmin; j < jmax; j++){
758         col = rip[aj[j]];
759         if (col >= k){ /* only take upper triangular entry */
760           rtmp[col] = aa[j];
761           *bval++  = 0.0; /* for in-place factorization */
762         }
763       }
764 
765       /* shift the diagonal of the matrix */
766       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
767 
768       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
769       dk = rtmp[k];
770       i = jl[k]; /* first row to be added to k_th row  */
771 
772       while (i < k){
773         nexti = jl[i]; /* next row to be added to k_th row */
774 
775         /* compute multiplier, update diag(k) and U(i,k) */
776         ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
777         uikdi = - ba[ili]*ba[bi[i]];  /* diagonal(k) */
778         dk += uikdi*ba[ili];
779         ba[ili] = uikdi; /* -U(i,k) */
780 
781         /* add multiple of row i to k-th row */
782         jmin = ili + 1; jmax = bi[i+1];
783         if (jmin < jmax){
784           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
785           /* update il and jl for row i */
786           il[i] = jmin;
787           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
788         }
789         i = nexti;
790       }
791 
792       /* shift the diagonals when zero pivot is detected */
793       /* compute rs=sum of abs(off-diagonal) */
794       rs   = 0.0;
795       jmin = bi[k]+1;
796       nz   = bi[k+1] - jmin;
797       if (nz){
798         bcol = bj + jmin;
799         while (nz--){
800           rs += PetscAbsScalar(rtmp[*bcol]);
801           bcol++;
802         }
803       }
804 
805       sctx.rs = rs;
806       sctx.pv = dk;
807       ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr);
808       if (sctx.newshift) break;
809       dk = sctx.pv;
810 
811       /* copy data into U(k,:) */
812       ba[bi[k]] = 1.0/dk; /* U(k,k) */
813       jmin = bi[k]+1; jmax = bi[k+1];
814       if (jmin < jmax) {
815         for (j=jmin; j<jmax; j++){
816           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
817         }
818         /* add the k-th row into il and jl */
819         il[k] = jmin;
820         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
821       }
822     }
823   } while (sctx.newshift);
824   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
825 
826   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
827   C->assembled    = PETSC_TRUE;
828   C->preallocated = PETSC_TRUE;
829   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
830   if (sctx.nshift){
831     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
832       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
833     } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
834       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
835     }
836   }
837   PetscFunctionReturn(0);
838 }
839 
840 #undef __FUNCT__
841 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering"
842 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
843 {
844   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
845   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
846   PetscErrorCode ierr;
847   PetscInt       i,j,am=a->mbs;
848   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
849   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
850   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
851   PetscReal      rs;
852   FactorShiftCtx sctx;
853 
854   PetscFunctionBegin;
855   /* MatPivotSetUp(): initialize shift context sctx */
856   ierr = PetscMemzero(&sctx,sizeof(FactorShiftCtx));CHKERRQ(ierr);
857 
858   ierr = PetscMalloc3(am,MatScalar,&rtmp,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr);
859 
860   do {
861     sctx.newshift = PETSC_FALSE;
862     for (i=0; i<am; i++) {
863       rtmp[i] = 0.0; jl[i] = am; il[0] = 0;
864     }
865 
866     for (k = 0; k<am; k++){
867     /* initialize k-th row with elements nonzero in row perm(k) of A */
868       nz   = ai[k+1] - ai[k];
869       acol = aj + ai[k];
870       aval = aa + ai[k];
871       bval = ba + bi[k];
872       while (nz -- ){
873         if (*acol < k) { /* skip lower triangular entries */
874           acol++; aval++;
875         } else {
876           rtmp[*acol++] = *aval++;
877           *bval++       = 0.0; /* for in-place factorization */
878         }
879       }
880 
881       /* shift the diagonal of the matrix */
882       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
883 
884       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
885       dk = rtmp[k];
886       i  = jl[k]; /* first row to be added to k_th row  */
887 
888       while (i < k){
889         nexti = jl[i]; /* next row to be added to k_th row */
890         /* compute multiplier, update D(k) and U(i,k) */
891         ili   = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
892         uikdi = - ba[ili]*ba[bi[i]];
893         dk   += uikdi*ba[ili];
894         ba[ili] = uikdi; /* -U(i,k) */
895 
896         /* add multiple of row i to k-th row ... */
897         jmin = ili + 1;
898         nz   = bi[i+1] - jmin;
899         if (nz > 0){
900           bcol = bj + jmin;
901           bval = ba + jmin;
902           while (nz --) rtmp[*bcol++] += uikdi*(*bval++);
903           /* update il and jl for i-th row */
904           il[i] = jmin;
905           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
906         }
907         i = nexti;
908       }
909 
910       /* shift the diagonals when zero pivot is detected */
911       /* compute rs=sum of abs(off-diagonal) */
912       rs   = 0.0;
913       jmin = bi[k]+1;
914       nz   = bi[k+1] - jmin;
915       if (nz){
916         bcol = bj + jmin;
917         while (nz--){
918           rs += PetscAbsScalar(rtmp[*bcol]);
919           bcol++;
920         }
921       }
922 
923       sctx.rs = rs;
924       sctx.pv = dk;
925       ierr = MatPivotCheck(A,info,&sctx,k);CHKERRQ(ierr);
926       if (sctx.newshift) break;    /* sctx.shift_amount is updated */
927       dk = sctx.pv;
928 
929       /* copy data into U(k,:) */
930       ba[bi[k]] = 1.0/dk;
931       jmin      = bi[k]+1;
932       nz        = bi[k+1] - jmin;
933       if (nz){
934         bcol = bj + jmin;
935         bval = ba + jmin;
936         while (nz--){
937           *bval++       = rtmp[*bcol];
938           rtmp[*bcol++] = 0.0;
939         }
940         /* add k-th row into il and jl */
941         il[k] = jmin;
942         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
943       }
944     }
945   } while (sctx.newshift);
946   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
947 
948   C->ops->solve                 = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
949   C->ops->solvetranspose        = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
950   C->assembled    = PETSC_TRUE;
951   C->preallocated = PETSC_TRUE;
952   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
953     if (sctx.nshift){
954       if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
955       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
956       } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
957       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
958     }
959   }
960   PetscFunctionReturn(0);
961 }
962 
963 #include <petscbt.h>
964 #include <../src/mat/utils/freespace.h>
965 #undef __FUNCT__
966 #define __FUNCT__ "MatICCFactorSymbolic_SeqBAIJ"
967 PetscErrorCode MatICCFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
968 {
969   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
970   Mat_SeqSBAIJ       *b;
971   Mat                B;
972   PetscErrorCode     ierr;
973   PetscBool          perm_identity;
974   PetscInt           reallocs=0,i,*ai=a->i,*aj=a->j,am=a->mbs,bs=A->rmap->bs,*ui;
975   const PetscInt     *rip;
976   PetscInt           jmin,jmax,nzk,k,j,*jl,prow,*il,nextprow;
977   PetscInt           nlnk,*lnk,*lnk_lvl=PETSC_NULL,ncols,ncols_upper,*cols,*cols_lvl,*uj,**uj_ptr,**uj_lvl_ptr;
978   PetscReal          fill=info->fill,levels=info->levels;
979   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
980   PetscFreeSpaceList free_space_lvl=PETSC_NULL,current_space_lvl=PETSC_NULL;
981   PetscBT            lnkbt;
982 
983   PetscFunctionBegin;
984   if (bs > 1){
985     if (!a->sbaijMat){
986       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
987     }
988     (fact)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;  /* undue the change made in MatGetFactor_seqbaij_petsc */
989     ierr = MatICCFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
990     PetscFunctionReturn(0);
991   }
992 
993   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
994   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
995 
996   /* special case that simply copies fill pattern */
997   if (!levels && perm_identity) {
998     ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr);
999     ierr = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
1000     for (i=0; i<am; i++) {
1001       ui[i] = ai[i+1] - a->diag[i]; /* ui: rowlengths - changes when !perm_identity */
1002     }
1003     B = fact;
1004     ierr = MatSeqSBAIJSetPreallocation(B,1,0,ui);CHKERRQ(ierr);
1005 
1006 
1007     b  = (Mat_SeqSBAIJ*)B->data;
1008     uj = b->j;
1009     for (i=0; i<am; i++) {
1010       aj = a->j + a->diag[i];
1011       for (j=0; j<ui[i]; j++){
1012         *uj++ = *aj++;
1013       }
1014       b->ilen[i] = ui[i];
1015     }
1016     ierr = PetscFree(ui);CHKERRQ(ierr);
1017     B->factortype = MAT_FACTOR_NONE;
1018     ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1019     ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1020     B->factortype = MAT_FACTOR_ICC;
1021 
1022     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1023     PetscFunctionReturn(0);
1024   }
1025 
1026   /* initialization */
1027   ierr  = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
1028   ui[0] = 0;
1029   ierr  = PetscMalloc((2*am+1)*sizeof(PetscInt),&cols_lvl);CHKERRQ(ierr);
1030 
1031   /* jl: linked list for storing indices of the pivot rows
1032      il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */
1033   ierr = PetscMalloc4(am,PetscInt*,&uj_ptr,am,PetscInt*,&uj_lvl_ptr,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr);
1034   for (i=0; i<am; i++){
1035     jl[i] = am; il[i] = 0;
1036   }
1037 
1038   /* create and initialize a linked list for storing column indices of the active row k */
1039   nlnk = am + 1;
1040   ierr = PetscIncompleteLLCreate(am,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
1041 
1042   /* initial FreeSpace size is fill*(ai[am]+am)/2 */
1043   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+am)/2),&free_space);CHKERRQ(ierr);
1044   current_space = free_space;
1045   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+am)/2),&free_space_lvl);CHKERRQ(ierr);
1046   current_space_lvl = free_space_lvl;
1047 
1048   for (k=0; k<am; k++){  /* for each active row k */
1049     /* initialize lnk by the column indices of row rip[k] of A */
1050     nzk   = 0;
1051     ncols = ai[rip[k]+1] - ai[rip[k]];
1052     ncols_upper = 0;
1053     cols        = cols_lvl + am;
1054     for (j=0; j<ncols; j++){
1055       i = rip[*(aj + ai[rip[k]] + j)];
1056       if (i >= k){ /* only take upper triangular entry */
1057         cols[ncols_upper] = i;
1058         cols_lvl[ncols_upper] = -1;  /* initialize level for nonzero entries */
1059         ncols_upper++;
1060       }
1061     }
1062     ierr = PetscIncompleteLLAdd(ncols_upper,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
1063     nzk += nlnk;
1064 
1065     /* update lnk by computing fill-in for each pivot row to be merged in */
1066     prow = jl[k]; /* 1st pivot row */
1067 
1068     while (prow < k){
1069       nextprow = jl[prow];
1070 
1071       /* merge prow into k-th row */
1072       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:am-1) */
1073       jmax = ui[prow+1];
1074       ncols = jmax-jmin;
1075       i     = jmin - ui[prow];
1076       cols = uj_ptr[prow] + i; /* points to the 2nd nzero entry in U(prow,k:am-1) */
1077       for (j=0; j<ncols; j++) cols_lvl[j] = *(uj_lvl_ptr[prow] + i + j);
1078       ierr = PetscIncompleteLLAddSorted(ncols,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
1079       nzk += nlnk;
1080 
1081       /* update il and jl for prow */
1082       if (jmin < jmax){
1083         il[prow] = jmin;
1084         j = *cols; jl[prow] = jl[j]; jl[j] = prow;
1085       }
1086       prow = nextprow;
1087     }
1088 
1089     /* if free space is not available, make more free space */
1090     if (current_space->local_remaining<nzk) {
1091       i = am - k + 1; /* num of unfactored rows */
1092       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
1093       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
1094       ierr = PetscFreeSpaceGet(i,&current_space_lvl);CHKERRQ(ierr);
1095       reallocs++;
1096     }
1097 
1098     /* copy data into free_space and free_space_lvl, then initialize lnk */
1099     ierr = PetscIncompleteLLClean(am,am,nzk,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr);
1100 
1101     /* add the k-th row into il and jl */
1102     if (nzk-1 > 0){
1103       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */
1104       jl[k] = jl[i]; jl[i] = k;
1105       il[k] = ui[k] + 1;
1106     }
1107     uj_ptr[k]     = current_space->array;
1108     uj_lvl_ptr[k] = current_space_lvl->array;
1109 
1110     current_space->array           += nzk;
1111     current_space->local_used      += nzk;
1112     current_space->local_remaining -= nzk;
1113 
1114     current_space_lvl->array           += nzk;
1115     current_space_lvl->local_used      += nzk;
1116     current_space_lvl->local_remaining -= nzk;
1117 
1118     ui[k+1] = ui[k] + nzk;
1119   }
1120 
1121   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
1122   ierr = PetscFree4(uj_ptr,uj_lvl_ptr,il,jl);CHKERRQ(ierr);
1123   ierr = PetscFree(cols_lvl);CHKERRQ(ierr);
1124 
1125   /* copy free_space into uj and free free_space; set uj in new datastructure; */
1126   ierr = PetscMalloc((ui[am]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
1127   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
1128   ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1129   ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr);
1130 
1131   /* put together the new matrix in MATSEQSBAIJ format */
1132   B = fact;
1133   ierr = MatSeqSBAIJSetPreallocation(B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1134 
1135   b = (Mat_SeqSBAIJ*)B->data;
1136   b->singlemalloc = PETSC_FALSE;
1137   b->free_a       = PETSC_TRUE;
1138   b->free_ij       = PETSC_TRUE;
1139   ierr = PetscMalloc((ui[am]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
1140   b->j    = uj;
1141   b->i    = ui;
1142   b->diag = 0;
1143   b->ilen = 0;
1144   b->imax = 0;
1145   b->row  = perm;
1146   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
1147   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1148   b->icol = perm;
1149   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1150   ierr    = PetscMalloc((am+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1151   ierr    = PetscLogObjectMemory(B,(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1152   b->maxnz = b->nz = ui[am];
1153 
1154   B->info.factor_mallocs    = reallocs;
1155   B->info.fill_ratio_given  = fill;
1156   if (ai[am] != 0.) {
1157     /* nonzeros in lower triangular part of A (includign diagonals)= (ai[am]+am)/2 */
1158     B->info.fill_ratio_needed = ((PetscReal)2*ui[am])/(ai[am]+am);
1159   } else {
1160     B->info.fill_ratio_needed = 0.0;
1161   }
1162 #if defined(PETSC_USE_INFO)
1163   if (ai[am] != 0) {
1164     PetscReal af = B->info.fill_ratio_needed;
1165     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
1166     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
1167     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
1168   } else {
1169     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
1170   }
1171 #endif
1172   if (perm_identity){
1173     B->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1174     B->ops->solvetranspose  = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1175     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1176   } else {
1177     (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1178   }
1179   PetscFunctionReturn(0);
1180 }
1181 
1182 #undef __FUNCT__
1183 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqBAIJ"
1184 PetscErrorCode MatCholeskyFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
1185 {
1186   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
1187   Mat_SeqSBAIJ       *b;
1188   Mat                B;
1189   PetscErrorCode     ierr;
1190   PetscBool          perm_identity;
1191   PetscReal          fill = info->fill;
1192   const PetscInt     *rip;
1193   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,*ai=a->i,*aj=a->j,reallocs=0,prow;
1194   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
1195   PetscInt           nlnk,*lnk,ncols,ncols_upper,*cols,*uj,**ui_ptr,*uj_ptr;
1196   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
1197   PetscBT            lnkbt;
1198 
1199   PetscFunctionBegin;
1200   if (bs > 1) { /* convert to seqsbaij */
1201     if (!a->sbaijMat){
1202       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
1203     }
1204     (fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ; /* undue the change made in MatGetFactor_seqbaij_petsc */
1205     ierr = MatCholeskyFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
1206     PetscFunctionReturn(0);
1207   }
1208 
1209   /* check whether perm is the identity mapping */
1210   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
1211   if (!perm_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported");
1212   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
1213 
1214   /* initialization */
1215   ierr  = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
1216   ui[0] = 0;
1217 
1218   /* jl: linked list for storing indices of the pivot rows
1219      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
1220   ierr = PetscMalloc4(mbs,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&cols);CHKERRQ(ierr);
1221   for (i=0; i<mbs; i++){
1222     jl[i] = mbs; il[i] = 0;
1223   }
1224 
1225   /* create and initialize a linked list for storing column indices of the active row k */
1226   nlnk = mbs + 1;
1227   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1228 
1229   /* initial FreeSpace size is fill* (ai[mbs]+mbs)/2 */
1230   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+mbs)/2),&free_space);CHKERRQ(ierr);
1231   current_space = free_space;
1232 
1233   for (k=0; k<mbs; k++){  /* for each active row k */
1234     /* initialize lnk by the column indices of row rip[k] of A */
1235     nzk   = 0;
1236     ncols = ai[rip[k]+1] - ai[rip[k]];
1237     ncols_upper = 0;
1238     for (j=0; j<ncols; j++){
1239       i = rip[*(aj + ai[rip[k]] + j)];
1240       if (i >= k){ /* only take upper triangular entry */
1241         cols[ncols_upper] = i;
1242         ncols_upper++;
1243       }
1244     }
1245     ierr = PetscLLAdd(ncols_upper,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1246     nzk += nlnk;
1247 
1248     /* update lnk by computing fill-in for each pivot row to be merged in */
1249     prow = jl[k]; /* 1st pivot row */
1250 
1251     while (prow < k){
1252       nextprow = jl[prow];
1253       /* merge prow into k-th row */
1254       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
1255       jmax = ui[prow+1];
1256       ncols = jmax-jmin;
1257       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
1258       ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1259       nzk += nlnk;
1260 
1261       /* update il and jl for prow */
1262       if (jmin < jmax){
1263         il[prow] = jmin;
1264         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
1265       }
1266       prow = nextprow;
1267     }
1268 
1269     /* if free space is not available, make more free space */
1270     if (current_space->local_remaining<nzk) {
1271       i = mbs - k + 1; /* num of unfactored rows */
1272       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
1273       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
1274       reallocs++;
1275     }
1276 
1277     /* copy data into free space, then initialize lnk */
1278     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
1279 
1280     /* add the k-th row into il and jl */
1281     if (nzk-1 > 0){
1282       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
1283       jl[k] = jl[i]; jl[i] = k;
1284       il[k] = ui[k] + 1;
1285     }
1286     ui_ptr[k] = current_space->array;
1287     current_space->array           += nzk;
1288     current_space->local_used      += nzk;
1289     current_space->local_remaining -= nzk;
1290 
1291     ui[k+1] = ui[k] + nzk;
1292   }
1293 
1294   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
1295   ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr);
1296 
1297   /* copy free_space into uj and free free_space; set uj in new datastructure; */
1298   ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
1299   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
1300   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1301 
1302   /* put together the new matrix in MATSEQSBAIJ format */
1303   B    = fact;
1304   ierr = MatSeqSBAIJSetPreallocation(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1305 
1306   b = (Mat_SeqSBAIJ*)B->data;
1307   b->singlemalloc = PETSC_FALSE;
1308   b->free_a       = PETSC_TRUE;
1309   b->free_ij      = PETSC_TRUE;
1310   ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
1311   b->j    = uj;
1312   b->i    = ui;
1313   b->diag = 0;
1314   b->ilen = 0;
1315   b->imax = 0;
1316   b->row  = perm;
1317   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
1318   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1319   b->icol = perm;
1320   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1321   ierr    = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1322   ierr    = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1323   b->maxnz = b->nz = ui[mbs];
1324 
1325   B->info.factor_mallocs    = reallocs;
1326   B->info.fill_ratio_given  = fill;
1327   if (ai[mbs] != 0.) {
1328     /* nonzeros in lower triangular part of A = (ai[mbs]+mbs)/2 */
1329     B->info.fill_ratio_needed = ((PetscReal)2*ui[mbs])/(ai[mbs]+mbs);
1330   } else {
1331     B->info.fill_ratio_needed = 0.0;
1332   }
1333 #if defined(PETSC_USE_INFO)
1334   if (ai[mbs] != 0.) {
1335     PetscReal af = B->info.fill_ratio_needed;
1336     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
1337     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
1338     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
1339   } else {
1340     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
1341   }
1342 #endif
1343   if (perm_identity){
1344     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1345   } else {
1346     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1347   }
1348   PetscFunctionReturn(0);
1349 }
1350 
1351 #undef __FUNCT__
1352 #define __FUNCT__ "MatSolve_SeqBAIJ_N_NaturalOrdering"
1353 PetscErrorCode MatSolve_SeqBAIJ_N_NaturalOrdering(Mat A,Vec bb,Vec xx)
1354 {
1355   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1356   PetscErrorCode ierr;
1357   const PetscInt *ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1358   PetscInt       i,k,n=a->mbs;
1359   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1360   MatScalar      *aa=a->a,*v;
1361   PetscScalar    *x,*b,*s,*t,*ls;
1362 
1363   PetscFunctionBegin;
1364   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1365   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1366   t  = a->solve_work;
1367 
1368   /* forward solve the lower triangular */
1369   ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy 1st block of b to t */
1370 
1371   for (i=1; i<n; i++) {
1372     v   = aa + bs2*ai[i];
1373     vi  = aj + ai[i];
1374     nz = ai[i+1] - ai[i];
1375     s = t + bs*i;
1376     ierr = PetscMemcpy(s,b+bs*i,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy i_th block of b to t */
1377     for(k=0;k<nz;k++){
1378       PetscKernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[k]);
1379       v += bs2;
1380     }
1381   }
1382 
1383   /* backward solve the upper triangular */
1384   ls = a->solve_work + A->cmap->n;
1385   for (i=n-1; i>=0; i--){
1386     v  = aa + bs2*(adiag[i+1]+1);
1387     vi = aj + adiag[i+1]+1;
1388     nz = adiag[i] - adiag[i+1]-1;
1389     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1390     for(k=0;k<nz;k++){
1391       PetscKernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[k]);
1392       v += bs2;
1393     }
1394     PetscKernel_w_gets_A_times_v(bs,ls,aa+bs2*adiag[i],t+i*bs); /* *inv(diagonal[i]) */
1395     ierr = PetscMemcpy(x+i*bs,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1396   }
1397 
1398   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1399   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1400   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1401   PetscFunctionReturn(0);
1402 }
1403 
1404 #undef __FUNCT__
1405 #define __FUNCT__ "MatSolve_SeqBAIJ_N"
1406 PetscErrorCode MatSolve_SeqBAIJ_N(Mat A,Vec bb,Vec xx)
1407 {
1408   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1409   IS             iscol=a->col,isrow=a->row;
1410   PetscErrorCode ierr;
1411   const PetscInt *r,*c,*rout,*cout,*ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1412   PetscInt       i,m,n=a->mbs;
1413   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1414   MatScalar      *aa=a->a,*v;
1415   PetscScalar    *x,*b,*s,*t,*ls;
1416 
1417   PetscFunctionBegin;
1418   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1419   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1420   t  = a->solve_work;
1421 
1422   ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout;
1423   ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout;
1424 
1425   /* forward solve the lower triangular */
1426   ierr = PetscMemcpy(t,b+bs*r[0],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1427   for (i=1; i<n; i++) {
1428     v   = aa + bs2*ai[i];
1429     vi  = aj + ai[i];
1430     nz = ai[i+1] - ai[i];
1431     s = t + bs*i;
1432     ierr = PetscMemcpy(s,b+bs*r[i],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1433     for(m=0;m<nz;m++){
1434       PetscKernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[m]);
1435       v += bs2;
1436     }
1437   }
1438 
1439   /* backward solve the upper triangular */
1440   ls = a->solve_work + A->cmap->n;
1441   for (i=n-1; i>=0; i--){
1442     v  = aa + bs2*(adiag[i+1]+1);
1443     vi = aj + adiag[i+1]+1;
1444     nz = adiag[i] - adiag[i+1] - 1;
1445     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1446     for(m=0;m<nz;m++){
1447       PetscKernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[m]);
1448       v += bs2;
1449     }
1450     PetscKernel_w_gets_A_times_v(bs,ls,v,t+i*bs); /* *inv(diagonal[i]) */
1451     ierr = PetscMemcpy(x + bs*c[i],t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1452   }
1453   ierr = ISRestoreIndices(isrow,&rout);CHKERRQ(ierr);
1454   ierr = ISRestoreIndices(iscol,&cout);CHKERRQ(ierr);
1455   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1456   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1457   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1458   PetscFunctionReturn(0);
1459 }
1460 
1461 #undef __FUNCT__
1462 #define __FUNCT__ "MatBlockAbs_privat"
1463 /*
1464     For each block in an block array saves the largest absolute value in the block into another array
1465 */
1466 static PetscErrorCode MatBlockAbs_private(PetscInt nbs,PetscInt bs2,PetscScalar *blockarray,PetscReal *absarray)
1467 {
1468   PetscErrorCode     ierr;
1469   PetscInt           i,j;
1470   PetscFunctionBegin;
1471   ierr = PetscMemzero(absarray,(nbs+1)*sizeof(PetscReal));CHKERRQ(ierr);
1472   for (i=0; i<nbs; i++){
1473     for (j=0; j<bs2; j++){
1474       if (absarray[i] < PetscAbsScalar(blockarray[i*nbs+j])) absarray[i] = PetscAbsScalar(blockarray[i*nbs+j]);
1475     }
1476   }
1477   PetscFunctionReturn(0);
1478 }
1479 
1480 #undef __FUNCT__
1481 #define __FUNCT__ "MatILUDTFactor_SeqBAIJ"
1482 /*
1483      This needs to be renamed and called by the regular MatILUFactor_SeqBAIJ when drop tolerance is used
1484 */
1485 PetscErrorCode MatILUDTFactor_SeqBAIJ(Mat A,IS isrow,IS iscol,const MatFactorInfo *info,Mat *fact)
1486 {
1487   Mat                B = *fact;
1488   Mat_SeqBAIJ        *a=(Mat_SeqBAIJ*)A->data,*b;
1489   IS                 isicol;
1490   PetscErrorCode     ierr;
1491   const PetscInt     *r,*ic;
1492   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,bs2=a->bs2,*ai=a->i,*aj=a->j,*ajtmp,*adiag;
1493   PetscInt           *bi,*bj,*bdiag;
1494 
1495   PetscInt           row,nzi,nzi_bl,nzi_bu,*im,dtcount,nzi_al,nzi_au;
1496   PetscInt           nlnk,*lnk;
1497   PetscBT            lnkbt;
1498   PetscBool          row_identity,icol_identity;
1499   MatScalar          *aatmp,*pv,*batmp,*ba,*rtmp,*pc,*multiplier,*vtmp;
1500   PetscInt           j,nz,*pj,*bjtmp,k,ncut,*jtmp;
1501 
1502   PetscReal          dt=info->dt; /* shift=info->shiftamount; */
1503   PetscInt           nnz_max;
1504   PetscBool          missing;
1505   PetscReal          *vtmp_abs;
1506   MatScalar          *v_work;
1507   PetscInt           *v_pivots;
1508 
1509   PetscFunctionBegin;
1510   /* ------- symbolic factorization, can be reused ---------*/
1511   ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr);
1512   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i);
1513   adiag=a->diag;
1514 
1515   ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr);
1516 
1517   /* bdiag is location of diagonal in factor */
1518   ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr);
1519 
1520   /* allocate row pointers bi */
1521   ierr = PetscMalloc((2*mbs+2)*sizeof(PetscInt),&bi);CHKERRQ(ierr);
1522 
1523   /* allocate bj and ba; max num of nonzero entries is (ai[n]+2*n*dtcount+2) */
1524   dtcount = (PetscInt)info->dtcount;
1525   if (dtcount > mbs-1) dtcount = mbs-1;
1526   nnz_max  = ai[mbs]+2*mbs*dtcount +2;
1527   /* printf("MatILUDTFactor_SeqBAIJ, bs %d, ai[mbs] %d, nnz_max  %d, dtcount %d\n",bs,ai[mbs],nnz_max,dtcount); */
1528   ierr = PetscMalloc(nnz_max*sizeof(PetscInt),&bj);CHKERRQ(ierr);
1529   nnz_max = nnz_max*bs2;
1530   ierr = PetscMalloc(nnz_max*sizeof(MatScalar),&ba);CHKERRQ(ierr);
1531 
1532   /* put together the new matrix */
1533   ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1534   ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr);
1535   b    = (Mat_SeqBAIJ*)(B)->data;
1536   b->free_a       = PETSC_TRUE;
1537   b->free_ij      = PETSC_TRUE;
1538   b->singlemalloc = PETSC_FALSE;
1539   b->a          = ba;
1540   b->j          = bj;
1541   b->i          = bi;
1542   b->diag       = bdiag;
1543   b->ilen       = 0;
1544   b->imax       = 0;
1545   b->row        = isrow;
1546   b->col        = iscol;
1547   ierr          = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
1548   ierr          = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
1549   b->icol       = isicol;
1550   ierr = PetscMalloc((bs*(mbs+1))*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1551 
1552   ierr = PetscLogObjectMemory(B,nnz_max*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1553   b->maxnz = nnz_max/bs2;
1554 
1555   (B)->factortype            = MAT_FACTOR_ILUDT;
1556   (B)->info.factor_mallocs   = 0;
1557   (B)->info.fill_ratio_given = ((PetscReal)nnz_max)/((PetscReal)(ai[mbs]*bs2));
1558   CHKMEMQ;
1559   /* ------- end of symbolic factorization ---------*/
1560   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
1561   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
1562 
1563   /* linked list for storing column indices of the active row */
1564   nlnk = mbs + 1;
1565   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1566 
1567   /* im: used by PetscLLAddSortedLU(); jtmp: working array for column indices of active row */
1568   ierr = PetscMalloc2(mbs,PetscInt,&im,mbs,PetscInt,&jtmp);CHKERRQ(ierr);
1569   /* rtmp, vtmp: working arrays for sparse and contiguous row entries of active row */
1570   ierr = PetscMalloc2(mbs*bs2,MatScalar,&rtmp,mbs*bs2,MatScalar,&vtmp);CHKERRQ(ierr);
1571   ierr = PetscMalloc((mbs+1)*sizeof(PetscReal),&vtmp_abs);CHKERRQ(ierr);
1572   ierr = PetscMalloc3(bs,MatScalar,&v_work,bs2,MatScalar,&multiplier,bs,PetscInt,&v_pivots);CHKERRQ(ierr);
1573 
1574   bi[0]    = 0;
1575   bdiag[0] = (nnz_max/bs2)-1; /* location of diagonal in factor B */
1576   bi[2*mbs+1] = bdiag[0]+1; /* endof bj and ba array */
1577   for (i=0; i<mbs; i++) {
1578     /* copy initial fill into linked list */
1579     nzi = 0; /* nonzeros for active row i */
1580     nzi = ai[r[i]+1] - ai[r[i]];
1581     if (!nzi) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i);
1582     nzi_al = adiag[r[i]] - ai[r[i]];
1583     nzi_au = ai[r[i]+1] - adiag[r[i]] -1;
1584     /* printf("row %d, nzi_al/au %d %d\n",i,nzi_al,nzi_au); */
1585 
1586     /* load in initial unfactored row */
1587     ajtmp = aj + ai[r[i]];
1588     ierr = PetscLLAddPerm(nzi,ajtmp,ic,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1589     ierr = PetscMemzero(rtmp,mbs*bs2*sizeof(PetscScalar));CHKERRQ(ierr);
1590     aatmp = a->a + bs2*ai[r[i]];
1591     for (j=0; j<nzi; j++) {
1592       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],aatmp+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1593     }
1594 
1595     /* add pivot rows into linked list */
1596     row = lnk[mbs];
1597     while (row < i) {
1598       nzi_bl = bi[row+1] - bi[row] + 1;
1599       bjtmp = bj + bdiag[row+1]+1; /* points to 1st column next to the diagonal in U */
1600       ierr  = PetscLLAddSortedLU(bjtmp,row,nlnk,lnk,lnkbt,i,nzi_bl,im);CHKERRQ(ierr);
1601       nzi  += nlnk;
1602       row   = lnk[row];
1603     }
1604 
1605     /* copy data from lnk into jtmp, then initialize lnk */
1606     ierr = PetscLLClean(mbs,mbs,nzi,lnk,jtmp,lnkbt);CHKERRQ(ierr);
1607 
1608     /* numerical factorization */
1609     bjtmp = jtmp;
1610     row   = *bjtmp++; /* 1st pivot row */
1611 
1612     while  (row < i) {
1613       pc = rtmp + bs2*row;
1614       pv = ba + bs2*bdiag[row]; /* inv(diag) of the pivot row */
1615       PetscKernel_A_gets_A_times_B(bs,pc,pv,multiplier); /* pc= multiplier = pc*inv(diag[row]) */
1616       ierr = MatBlockAbs_private(1,bs2,pc,vtmp_abs);CHKERRQ(ierr);
1617       if (vtmp_abs[0] > dt){ /* apply tolerance dropping rule */
1618         pj         = bj + bdiag[row+1] + 1; /* point to 1st entry of U(row,:) */
1619         pv         = ba + bs2*(bdiag[row+1] + 1);
1620         nz         = bdiag[row] - bdiag[row+1] - 1; /* num of entries in U(row,:), excluding diagonal */
1621         for (j=0; j<nz; j++){
1622           PetscKernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j);
1623         }
1624         /* ierr = PetscLogFlops(bslog*(nz+1.0)-bs);CHKERRQ(ierr); */
1625       }
1626       row = *bjtmp++;
1627     }
1628 
1629     /* copy sparse rtmp into contiguous vtmp; separate L and U part */
1630     nzi_bl = 0; j = 0;
1631     while (jtmp[j] < i){ /* L-part. Note: jtmp is sorted */
1632       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1633       nzi_bl++; j++;
1634     }
1635     nzi_bu = nzi - nzi_bl -1;
1636     /* printf("nzi %d, nzi_bl %d, nzi_bu %d\n",nzi,nzi_bl,nzi_bu); */
1637 
1638     while (j < nzi){ /* U-part */
1639       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1640       /*
1641       printf(" col %d: ",jtmp[j]);
1642       for (j1=0; j1<bs2; j1++) printf(" %g",*(vtmp+bs2*j+j1));
1643       printf(" \n");
1644       */
1645       j++;
1646     }
1647 
1648     ierr = MatBlockAbs_private(nzi,bs2,vtmp,vtmp_abs);CHKERRQ(ierr);
1649     /*
1650     printf(" row %d, nzi %d, vtmp_abs\n",i,nzi);
1651     for (j1=0; j1<nzi; j1++) printf(" (%d %g),",jtmp[j1],vtmp_abs[j1]);
1652     printf(" \n");
1653     */
1654     bjtmp = bj + bi[i];
1655     batmp = ba + bs2*bi[i];
1656     /* apply level dropping rule to L part */
1657     ncut = nzi_al + dtcount;
1658     if (ncut < nzi_bl){
1659       ierr = PetscSortSplitReal(ncut,nzi_bl,vtmp_abs,jtmp);CHKERRQ(ierr);
1660       ierr = PetscSortIntWithScalarArray(ncut,jtmp,vtmp);CHKERRQ(ierr);
1661     } else {
1662       ncut = nzi_bl;
1663     }
1664     for (j=0; j<ncut; j++){
1665       bjtmp[j] = jtmp[j];
1666       ierr = PetscMemcpy(batmp+bs2*j,rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1667       /*
1668       printf(" col %d: ",bjtmp[j]);
1669       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*j+j1));
1670       printf("\n");
1671       */
1672     }
1673     bi[i+1] = bi[i] + ncut;
1674     nzi = ncut + 1;
1675 
1676     /* apply level dropping rule to U part */
1677     ncut = nzi_au + dtcount;
1678     if (ncut < nzi_bu){
1679       ierr = PetscSortSplitReal(ncut,nzi_bu,vtmp_abs+nzi_bl+1,jtmp+nzi_bl+1);CHKERRQ(ierr);
1680       ierr = PetscSortIntWithScalarArray(ncut,jtmp+nzi_bl+1,vtmp+nzi_bl+1);CHKERRQ(ierr);
1681     } else {
1682       ncut = nzi_bu;
1683     }
1684     nzi += ncut;
1685 
1686     /* mark bdiagonal */
1687     bdiag[i+1]    = bdiag[i] - (ncut + 1);
1688     bi[2*mbs - i] = bi[2*mbs - i +1] - (ncut + 1);
1689 
1690     bjtmp = bj + bdiag[i];
1691     batmp = ba + bs2*bdiag[i];
1692     ierr = PetscMemcpy(batmp,rtmp+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1693     *bjtmp = i;
1694     /*
1695     printf(" diag %d: ",*bjtmp);
1696     for (j=0; j<bs2; j++){
1697       printf(" %g,",batmp[j]);
1698     }
1699     printf("\n");
1700     */
1701     bjtmp = bj + bdiag[i+1]+1;
1702     batmp = ba + (bdiag[i+1]+1)*bs2;
1703 
1704     for (k=0; k<ncut; k++){
1705       bjtmp[k] = jtmp[nzi_bl+1+k];
1706       ierr = PetscMemcpy(batmp+bs2*k,rtmp+bs2*bjtmp[k],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1707       /*
1708       printf(" col %d:",bjtmp[k]);
1709       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*k+j1));
1710       printf("\n");
1711       */
1712     }
1713 
1714     im[i] = nzi; /* used by PetscLLAddSortedLU() */
1715 
1716     /* invert diagonal block for simplier triangular solves - add shift??? */
1717     batmp = ba + bs2*bdiag[i];
1718     ierr = PetscKernel_A_gets_inverse_A(bs,batmp,v_pivots,v_work);CHKERRQ(ierr);
1719   } /* for (i=0; i<mbs; i++) */
1720   ierr = PetscFree3(v_work,multiplier,v_pivots);CHKERRQ(ierr);
1721 
1722   /* printf("end of L %d, beginning of U %d\n",bi[mbs],bdiag[mbs]); */
1723   if (bi[mbs] >= bdiag[mbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"end of L array %d cannot >= the beginning of U array %d",bi[mbs],bdiag[mbs]);
1724 
1725   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
1726   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
1727 
1728   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1729 
1730   ierr = PetscFree2(im,jtmp);CHKERRQ(ierr);
1731   ierr = PetscFree2(rtmp,vtmp);CHKERRQ(ierr);
1732 
1733   ierr = PetscLogFlops(bs2*B->cmap->n);CHKERRQ(ierr);
1734   b->maxnz = b->nz = bi[mbs] + bdiag[0] - bdiag[mbs];
1735 
1736   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
1737   ierr = ISIdentity(isicol,&icol_identity);CHKERRQ(ierr);
1738   if (row_identity && icol_identity) {
1739     B->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering;
1740   } else {
1741     B->ops->solve = MatSolve_SeqBAIJ_N;
1742   }
1743 
1744   B->ops->solveadd          = 0;
1745   B->ops->solvetranspose    = 0;
1746   B->ops->solvetransposeadd = 0;
1747   B->ops->matsolve          = 0;
1748   B->assembled              = PETSC_TRUE;
1749   B->preallocated           = PETSC_TRUE;
1750   PetscFunctionReturn(0);
1751 }
1752