xref: /petsc/src/mat/impls/baij/seq/baijfact.c (revision d736bfeb4d37a01fcbdf00fe73fb60d6f0ba2142)
1 #define PETSCMAT_DLL
2 
3 /*
4     Factorization code for BAIJ format.
5 */
6 #include "../src/mat/impls/baij/seq/baij.h"
7 #include "../src/mat/blockinvert.h"
8 
9 #undef __FUNCT__
10 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2"
11 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2(Mat B,Mat A,const MatFactorInfo *info)
12 {
13   Mat             C=B;
14   Mat_SeqBAIJ     *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
15   IS              isrow = b->row,isicol = b->icol;
16   PetscErrorCode  ierr;
17   const PetscInt  *r,*ic,*ics;
18   PetscInt        i,j,k,nz,nzL,row,*pj;
19   const PetscInt  n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2;
20   const PetscInt  *ajtmp,*bjtmp,*bdiag=b->diag;
21   MatScalar       *rtmp,*pc,*mwork,*pv;
22   MatScalar       *aa=a->a,*v;
23   PetscInt        flg;
24   PetscReal       shift = info->shiftamount;
25 
26   PetscFunctionBegin;
27   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
28   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
29 
30   /* generate work space needed by the factorization */
31   ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr);
32   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
33   ics  = ic;
34 
35   for (i=0; i<n; i++){
36     /* zero rtmp */
37     /* L part */
38     nz    = bi[i+1] - bi[i];
39     bjtmp = bj + bi[i];
40     for  (j=0; j<nz; j++){
41       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
42     }
43 
44     /* U part */
45     nz = bdiag[i] - bdiag[i+1];
46     bjtmp = bj + bdiag[i+1]+1;
47     for  (j=0; j<nz; j++){
48       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
49     }
50 
51     /* load in initial (unfactored row) */
52     nz    = ai[r[i]+1] - ai[r[i]];
53     ajtmp = aj + ai[r[i]];
54     v     = aa + bs2*ai[r[i]];
55     for (j=0; j<nz; j++) {
56       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
57     }
58 
59     /* elimination */
60     bjtmp = bj + bi[i];
61     nzL   = bi[i+1] - bi[i];
62     for(k=0;k < nzL;k++) {
63       row = bjtmp[k];
64       pc = rtmp + bs2*row;
65       for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }}
66       if (flg) {
67         pv = b->a + bs2*bdiag[row];
68         /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
69         ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
70 
71         pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */
72         pv = b->a + bs2*(bdiag[row+1]+1);
73         nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */
74         for (j=0; j<nz; j++) {
75           /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
76           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
77           v    = rtmp + 4*pj[j];
78           ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
79           pv  += 4;
80         }
81         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
82       }
83     }
84 
85     /* finished row so stick it into b->a */
86     /* L part */
87     pv   = b->a + bs2*bi[i] ;
88     pj   = b->j + bi[i] ;
89     nz   = bi[i+1] - bi[i];
90     for (j=0; j<nz; j++) {
91       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
92     }
93 
94     /* Mark diagonal and invert diagonal for simplier triangular solves */
95     pv   = b->a + bs2*bdiag[i];
96     pj   = b->j + bdiag[i];
97     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
98     /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
99     ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
100 
101     /* U part */
102     pv = b->a + bs2*(bdiag[i+1]+1);
103     pj = b->j + bdiag[i+1]+1;
104     nz = bdiag[i] - bdiag[i+1] - 1;
105     for (j=0; j<nz; j++){
106       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
107     }
108   }
109 
110   ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr);
111   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
112   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
113   C->ops->solve          = MatSolve_SeqBAIJ_2;
114   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2;
115 
116   C->assembled = PETSC_TRUE;
117   ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
118   PetscFunctionReturn(0);
119 }
120 
121 #undef __FUNCT__
122 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering"
123 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info)
124 {
125   Mat             C=B;
126   Mat_SeqBAIJ     *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
127   PetscErrorCode  ierr;
128   PetscInt        i,j,k,nz,nzL,row,*pj;
129   const PetscInt  n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,bs2=a->bs2;
130   const PetscInt  *ajtmp,*bjtmp,*bdiag=b->diag;
131   MatScalar       *rtmp,*pc,*mwork,*pv;
132   MatScalar       *aa=a->a,*v;
133   PetscInt       flg;
134   PetscReal      shift = info->shiftamount;
135 
136   PetscFunctionBegin;
137   /* generate work space needed by the factorization */
138   ierr = PetscMalloc2(bs2*n,MatScalar,&rtmp,bs2,MatScalar,&mwork);CHKERRQ(ierr);
139   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
140 
141   for (i=0; i<n; i++){
142     /* zero rtmp */
143     /* L part */
144     nz    = bi[i+1] - bi[i];
145     bjtmp = bj + bi[i];
146     for  (j=0; j<nz; j++){
147       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
148     }
149 
150     /* U part */
151     nz = bdiag[i] - bdiag[i+1];
152     bjtmp = bj + bdiag[i+1]+1;
153     for  (j=0; j<nz; j++){
154       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
155     }
156 
157     /* load in initial (unfactored row) */
158     nz    = ai[i+1] - ai[i];
159     ajtmp = aj + ai[i];
160     v     = aa + bs2*ai[i];
161     for (j=0; j<nz; j++) {
162       ierr = PetscMemcpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
163     }
164 
165     /* elimination */
166     bjtmp = bj + bi[i];
167     nzL   = bi[i+1] - bi[i];
168     for(k=0;k < nzL;k++) {
169       row = bjtmp[k];
170       pc = rtmp + bs2*row;
171       for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }}
172       if (flg) {
173         pv = b->a + bs2*bdiag[row];
174         /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
175         ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
176 
177         pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */
178 	pv = b->a + bs2*(bdiag[row+1]+1);
179 	nz = bdiag[row]-bdiag[row+1] - 1; /* num of entries in U(row,:) excluding diag */
180         for (j=0; j<nz; j++) {
181           /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
182           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
183           v    = rtmp + 4*pj[j];
184           ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
185           pv  += 4;
186         }
187         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
188       }
189     }
190 
191     /* finished row so stick it into b->a */
192     /* L part */
193     pv   = b->a + bs2*bi[i] ;
194     pj   = b->j + bi[i] ;
195     nz   = bi[i+1] - bi[i];
196     for (j=0; j<nz; j++) {
197       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
198     }
199 
200     /* Mark diagonal and invert diagonal for simplier triangular solves */
201     pv   = b->a + bs2*bdiag[i];
202     pj   = b->j + bdiag[i];
203     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
204     /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
205     ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
206 
207     /* U part */
208     /*
209     pv = b->a + bs2*bi[2*n-i];
210     pj = b->j + bi[2*n-i];
211     nz = bi[2*n-i+1] - bi[2*n-i] - 1;
212     */
213     pv = b->a + bs2*(bdiag[i+1]+1);
214     pj = b->j + bdiag[i+1]+1;
215     nz = bdiag[i] - bdiag[i+1] - 1;
216     for (j=0; j<nz; j++){
217       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
218     }
219   }
220   ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr);
221 
222   C->ops->solve          = MatSolve_SeqBAIJ_2_NaturalOrdering;
223   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering;
224   C->assembled = PETSC_TRUE;
225   ierr = PetscLogFlops(1.333333333333*2*2*2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
226   PetscFunctionReturn(0);
227 }
228 
229 #undef __FUNCT__
230 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_inplace"
231 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_inplace(Mat B,Mat A,const MatFactorInfo *info)
232 {
233   Mat            C = B;
234   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
235   IS             isrow = b->row,isicol = b->icol;
236   PetscErrorCode ierr;
237   const PetscInt *r,*ic;
238   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
239   PetscInt       *ajtmpold,*ajtmp,nz,row;
240   PetscInt       *diag_offset=b->diag,idx,*ai=a->i,*aj=a->j,*pj;
241   MatScalar      *pv,*v,*rtmp,m1,m2,m3,m4,*pc,*w,*x,x1,x2,x3,x4;
242   MatScalar      p1,p2,p3,p4;
243   MatScalar      *ba = b->a,*aa = a->a;
244   PetscReal      shift = info->shiftamount;
245 
246   PetscFunctionBegin;
247   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
248   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
249   ierr  = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
250 
251   for (i=0; i<n; i++) {
252     nz    = bi[i+1] - bi[i];
253     ajtmp = bj + bi[i];
254     for  (j=0; j<nz; j++) {
255       x = rtmp+4*ajtmp[j]; x[0] = x[1] = x[2] = x[3] = 0.0;
256     }
257     /* load in initial (unfactored row) */
258     idx      = r[i];
259     nz       = ai[idx+1] - ai[idx];
260     ajtmpold = aj + ai[idx];
261     v        = aa + 4*ai[idx];
262     for (j=0; j<nz; j++) {
263       x    = rtmp+4*ic[ajtmpold[j]];
264       x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3];
265       v    += 4;
266     }
267     row = *ajtmp++;
268     while (row < i) {
269       pc = rtmp + 4*row;
270       p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3];
271       if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) {
272         pv = ba + 4*diag_offset[row];
273         pj = bj + diag_offset[row] + 1;
274         x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
275         pc[0] = m1 = p1*x1 + p3*x2;
276         pc[1] = m2 = p2*x1 + p4*x2;
277         pc[2] = m3 = p1*x3 + p3*x4;
278         pc[3] = m4 = p2*x3 + p4*x4;
279         nz = bi[row+1] - diag_offset[row] - 1;
280         pv += 4;
281         for (j=0; j<nz; j++) {
282           x1   = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
283           x    = rtmp + 4*pj[j];
284           x[0] -= m1*x1 + m3*x2;
285           x[1] -= m2*x1 + m4*x2;
286           x[2] -= m1*x3 + m3*x4;
287           x[3] -= m2*x3 + m4*x4;
288           pv   += 4;
289         }
290         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
291       }
292       row = *ajtmp++;
293     }
294     /* finished row so stick it into b->a */
295     pv = ba + 4*bi[i];
296     pj = bj + bi[i];
297     nz = bi[i+1] - bi[i];
298     for (j=0; j<nz; j++) {
299       x     = rtmp+4*pj[j];
300       pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3];
301       pv   += 4;
302     }
303     /* invert diagonal block */
304     w = ba + 4*diag_offset[i];
305     ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
306   }
307 
308   ierr = PetscFree(rtmp);CHKERRQ(ierr);
309   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
310   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
311   C->ops->solve          = MatSolve_SeqBAIJ_2_inplace;
312   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_inplace;
313   C->assembled = PETSC_TRUE;
314   ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
315   PetscFunctionReturn(0);
316 }
317 /*
318       Version for when blocks are 2 by 2 Using natural ordering
319 */
320 #undef __FUNCT__
321 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace"
322 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_inplace(Mat C,Mat A,const MatFactorInfo *info)
323 {
324   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
325   PetscErrorCode ierr;
326   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
327   PetscInt       *ajtmpold,*ajtmp,nz,row;
328   PetscInt       *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj;
329   MatScalar      *pv,*v,*rtmp,*pc,*w,*x;
330   MatScalar      p1,p2,p3,p4,m1,m2,m3,m4,x1,x2,x3,x4;
331   MatScalar      *ba = b->a,*aa = a->a;
332   PetscReal      shift = info->shiftamount;
333 
334   PetscFunctionBegin;
335   ierr = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
336   for (i=0; i<n; i++) {
337     nz    = bi[i+1] - bi[i];
338     ajtmp = bj + bi[i];
339     for  (j=0; j<nz; j++) {
340       x = rtmp+4*ajtmp[j];
341       x[0]  = x[1]  = x[2]  = x[3]  = 0.0;
342     }
343     /* load in initial (unfactored row) */
344     nz       = ai[i+1] - ai[i];
345     ajtmpold = aj + ai[i];
346     v        = aa + 4*ai[i];
347     for (j=0; j<nz; j++) {
348       x    = rtmp+4*ajtmpold[j];
349       x[0]  = v[0];  x[1]  = v[1];  x[2]  = v[2];  x[3]  = v[3];
350       v    += 4;
351     }
352     row = *ajtmp++;
353     while (row < i) {
354       pc  = rtmp + 4*row;
355       p1  = pc[0];  p2  = pc[1];  p3  = pc[2];  p4  = pc[3];
356       if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) {
357         pv = ba + 4*diag_offset[row];
358         pj = bj + diag_offset[row] + 1;
359         x1  = pv[0];  x2  = pv[1];  x3  = pv[2];  x4  = pv[3];
360         pc[0] = m1 = p1*x1 + p3*x2;
361         pc[1] = m2 = p2*x1 + p4*x2;
362         pc[2] = m3 = p1*x3 + p3*x4;
363         pc[3] = m4 = p2*x3 + p4*x4;
364         nz = bi[row+1] - diag_offset[row] - 1;
365         pv += 4;
366         for (j=0; j<nz; j++) {
367           x1   = pv[0];  x2  = pv[1];   x3 = pv[2];  x4  = pv[3];
368           x    = rtmp + 4*pj[j];
369           x[0] -= m1*x1 + m3*x2;
370           x[1] -= m2*x1 + m4*x2;
371           x[2] -= m1*x3 + m3*x4;
372           x[3] -= m2*x3 + m4*x4;
373           pv   += 4;
374         }
375         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
376       }
377       row = *ajtmp++;
378     }
379     /* finished row so stick it into b->a */
380     pv = ba + 4*bi[i];
381     pj = bj + bi[i];
382     nz = bi[i+1] - bi[i];
383     for (j=0; j<nz; j++) {
384       x      = rtmp+4*pj[j];
385       pv[0]  = x[0];  pv[1]  = x[1];  pv[2]  = x[2];  pv[3]  = x[3];
386       /*
387       printf(" col %d:",pj[j]);
388       PetscInt j1;
389       for (j1=0; j1<4; j1++) printf(" %g,",*(pv+j1));
390       printf("\n");
391       */
392       pv   += 4;
393     }
394     /* invert diagonal block */
395     w = ba + 4*diag_offset[i];
396     /*
397     printf(" \n%d -th: diag: ",i);
398     for (j=0; j<4; j++){
399       printf(" %g,",w[j]);
400     }
401     printf("\n----------------------------\n");
402     */
403     ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
404   }
405 
406   ierr = PetscFree(rtmp);CHKERRQ(ierr);
407   C->ops->solve          = MatSolve_SeqBAIJ_2_NaturalOrdering_inplace;
408   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering_inplace;
409   C->assembled = PETSC_TRUE;
410   ierr = PetscLogFlops(1.333333333333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
411   PetscFunctionReturn(0);
412 }
413 
414 /* ----------------------------------------------------------- */
415 /*
416      Version for when blocks are 1 by 1.
417 */
418 #undef __FUNCT__
419 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_1_inplace"
420 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_1_inplace(Mat C,Mat A,const MatFactorInfo *info)
421 {
422   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
423   IS             isrow = b->row,isicol = b->icol;
424   PetscErrorCode ierr;
425   const PetscInt *r,*ic;
426   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
427   PetscInt       *ajtmpold,*ajtmp,nz,row,*ai = a->i,*aj = a->j;
428   PetscInt       *diag_offset = b->diag,diag,*pj;
429   MatScalar      *pv,*v,*rtmp,multiplier,*pc;
430   MatScalar      *ba = b->a,*aa = a->a;
431   PetscTruth     row_identity, col_identity;
432 
433   PetscFunctionBegin;
434   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
435   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
436   ierr  = PetscMalloc((n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
437 
438   for (i=0; i<n; i++) {
439     nz    = bi[i+1] - bi[i];
440     ajtmp = bj + bi[i];
441     for  (j=0; j<nz; j++) rtmp[ajtmp[j]] = 0.0;
442 
443     /* load in initial (unfactored row) */
444     nz       = ai[r[i]+1] - ai[r[i]];
445     ajtmpold = aj + ai[r[i]];
446     v        = aa + ai[r[i]];
447     for (j=0; j<nz; j++) rtmp[ic[ajtmpold[j]]] =  v[j];
448 
449     row = *ajtmp++;
450     while (row < i) {
451       pc = rtmp + row;
452       if (*pc != 0.0) {
453         pv         = ba + diag_offset[row];
454         pj         = bj + diag_offset[row] + 1;
455         multiplier = *pc * *pv++;
456         *pc        = multiplier;
457         nz         = bi[row+1] - diag_offset[row] - 1;
458         for (j=0; j<nz; j++) rtmp[pj[j]] -= multiplier * pv[j];
459         ierr = PetscLogFlops(1.0+2.0*nz);CHKERRQ(ierr);
460       }
461       row = *ajtmp++;
462     }
463     /* finished row so stick it into b->a */
464     pv = ba + bi[i];
465     pj = bj + bi[i];
466     nz = bi[i+1] - bi[i];
467     for (j=0; j<nz; j++) {pv[j] = rtmp[pj[j]];}
468     diag = diag_offset[i] - bi[i];
469     /* check pivot entry for current row */
470     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);
471     pv[diag] = 1.0/pv[diag];
472   }
473 
474   ierr = PetscFree(rtmp);CHKERRQ(ierr);
475   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
476   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
477   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
478   ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr);
479   if (row_identity && col_identity) {
480     C->ops->solve          = MatSolve_SeqBAIJ_1_NaturalOrdering_inplace;
481     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_NaturalOrdering_inplace;
482   } else {
483     C->ops->solve          = MatSolve_SeqBAIJ_1_inplace;
484     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_inplace;
485   }
486   C->assembled = PETSC_TRUE;
487   ierr = PetscLogFlops(C->cmap->n);CHKERRQ(ierr);
488   PetscFunctionReturn(0);
489 }
490 
491 EXTERN_C_BEGIN
492 #undef __FUNCT__
493 #define __FUNCT__ "MatGetFactor_seqbaij_petsc"
494 PetscErrorCode MatGetFactor_seqbaij_petsc(Mat A,MatFactorType ftype,Mat *B)
495 {
496   PetscInt           n = A->rmap->n;
497   PetscErrorCode     ierr;
498 
499   PetscFunctionBegin;
500   ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr);
501   ierr = MatSetSizes(*B,n,n,n,n);CHKERRQ(ierr);
502   if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU || ftype == MAT_FACTOR_ILUDT) {
503     ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr);
504     (*B)->ops->lufactorsymbolic  = MatLUFactorSymbolic_SeqBAIJ;
505     (*B)->ops->ilufactorsymbolic = MatILUFactorSymbolic_SeqBAIJ;
506   } else if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
507     ierr = MatSetType(*B,MATSEQSBAIJ);CHKERRQ(ierr);
508     ierr = MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
509     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqBAIJ;
510     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqBAIJ;
511   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Factor type not supported");
512   (*B)->factortype = ftype;
513   PetscFunctionReturn(0);
514 }
515 EXTERN_C_END
516 
517 EXTERN_C_BEGIN
518 #undef __FUNCT__
519 #define __FUNCT__ "MatGetFactorAvailable_seqaij_petsc"
520 PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat A,MatFactorType ftype,PetscTruth *flg)
521 {
522   PetscFunctionBegin;
523   *flg = PETSC_TRUE;
524   PetscFunctionReturn(0);
525 }
526 EXTERN_C_END
527 
528 /* ----------------------------------------------------------- */
529 #undef __FUNCT__
530 #define __FUNCT__ "MatLUFactor_SeqBAIJ"
531 PetscErrorCode MatLUFactor_SeqBAIJ(Mat A,IS row,IS col,const MatFactorInfo *info)
532 {
533   PetscErrorCode ierr;
534   Mat            C;
535 
536   PetscFunctionBegin;
537   ierr = MatGetFactor(A,MAT_SOLVER_PETSC,MAT_FACTOR_LU,&C);CHKERRQ(ierr);
538   ierr = MatLUFactorSymbolic(C,A,row,col,info);CHKERRQ(ierr);
539   ierr = MatLUFactorNumeric(C,A,info);CHKERRQ(ierr);
540   A->ops->solve            = C->ops->solve;
541   A->ops->solvetranspose   = C->ops->solvetranspose;
542   ierr = MatHeaderCopy(A,C);CHKERRQ(ierr);
543   ierr = PetscLogObjectParent(A,((Mat_SeqBAIJ*)(A->data))->icol);CHKERRQ(ierr);
544   PetscFunctionReturn(0);
545 }
546 
547 #include "../src/mat/impls/sbaij/seq/sbaij.h"
548 #undef __FUNCT__
549 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N"
550 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N(Mat C,Mat A,const MatFactorInfo *info)
551 {
552   PetscErrorCode ierr;
553   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
554   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
555   IS             ip=b->row;
556   const PetscInt *rip;
557   PetscInt       i,j,mbs=a->mbs,bs=A->rmap->bs,*bi=b->i,*bj=b->j,*bcol;
558   PetscInt       *ai=a->i,*aj=a->j;
559   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
560   MatScalar      *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi;
561   PetscReal      zeropivot,rs;
562   ChShift_Ctx    sctx;
563   PetscInt       newshift;
564 
565   PetscFunctionBegin;
566   if (bs > 1) {
567     if (!a->sbaijMat){
568       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
569     }
570     ierr = (a->sbaijMat)->ops->choleskyfactornumeric(C,a->sbaijMat,info);CHKERRQ(ierr);
571     ierr = MatDestroy(a->sbaijMat);CHKERRQ(ierr);
572     a->sbaijMat = PETSC_NULL;
573     PetscFunctionReturn(0);
574   }
575 
576   /* initialization */
577   zeropivot = info->zeropivot;
578 
579   ierr  = ISGetIndices(ip,&rip);CHKERRQ(ierr);
580   ierr = PetscMalloc3(mbs,MatScalar,&rtmp,mbs,PetscInt,&il,mbs,PetscInt,&jl);CHKERRQ(ierr);
581 
582   sctx.shift_amount = 0.;
583   sctx.nshift       = 0;
584   do {
585     sctx.chshift = PETSC_FALSE;
586     for (i=0; i<mbs; i++) {
587       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
588     }
589 
590     for (k = 0; k<mbs; k++){
591       bval = ba + bi[k];
592       /* initialize k-th row by the perm[k]-th row of A */
593       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
594       for (j = jmin; j < jmax; j++){
595         col = rip[aj[j]];
596         if (col >= k){ /* only take upper triangular entry */
597           rtmp[col] = aa[j];
598           *bval++  = 0.0; /* for in-place factorization */
599         }
600       }
601 
602       /* shift the diagonal of the matrix */
603       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
604 
605       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
606       dk = rtmp[k];
607       i = jl[k]; /* first row to be added to k_th row  */
608 
609       while (i < k){
610         nexti = jl[i]; /* next row to be added to k_th row */
611 
612         /* compute multiplier, update diag(k) and U(i,k) */
613         ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
614         uikdi = - ba[ili]*ba[bi[i]];  /* diagonal(k) */
615         dk += uikdi*ba[ili];
616         ba[ili] = uikdi; /* -U(i,k) */
617 
618         /* add multiple of row i to k-th row */
619         jmin = ili + 1; jmax = bi[i+1];
620         if (jmin < jmax){
621           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
622           /* update il and jl for row i */
623           il[i] = jmin;
624           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
625         }
626         i = nexti;
627       }
628 
629       /* shift the diagonals when zero pivot is detected */
630       /* compute rs=sum of abs(off-diagonal) */
631       rs   = 0.0;
632       jmin = bi[k]+1;
633       nz   = bi[k+1] - jmin;
634       if (nz){
635         bcol = bj + jmin;
636         while (nz--){
637           rs += PetscAbsScalar(rtmp[*bcol]);
638           bcol++;
639         }
640       }
641 
642       sctx.rs = rs;
643       sctx.pv = dk;
644       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
645       if (newshift == 1) break;
646 
647       /* copy data into U(k,:) */
648       ba[bi[k]] = 1.0/dk; /* U(k,k) */
649       jmin = bi[k]+1; jmax = bi[k+1];
650       if (jmin < jmax) {
651         for (j=jmin; j<jmax; j++){
652           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
653         }
654         /* add the k-th row into il and jl */
655         il[k] = jmin;
656         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
657       }
658     }
659   } while (sctx.chshift);
660   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
661 
662   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
663   C->assembled    = PETSC_TRUE;
664   C->preallocated = PETSC_TRUE;
665   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
666   if (sctx.nshift){
667     if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
668       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
669     } else if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
670       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
671     }
672   }
673   PetscFunctionReturn(0);
674 }
675 
676 #undef __FUNCT__
677 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering"
678 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
679 {
680   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
681   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
682   PetscErrorCode ierr;
683   PetscInt       i,j,am=a->mbs;
684   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
685   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
686   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
687   PetscReal      zeropivot,rs;
688   ChShift_Ctx    sctx;
689   PetscInt       newshift;
690 
691   PetscFunctionBegin;
692   /* initialization */
693   zeropivot = info->zeropivot;
694 
695   ierr = PetscMalloc3(am,MatScalar,&rtmp,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr);
696 
697   sctx.shift_amount = 0.;
698   sctx.nshift       = 0;
699   do {
700     sctx.chshift = PETSC_FALSE;
701     for (i=0; i<am; i++) {
702       rtmp[i] = 0.0; jl[i] = am; il[0] = 0;
703     }
704 
705     for (k = 0; k<am; k++){
706     /* initialize k-th row with elements nonzero in row perm(k) of A */
707       nz   = ai[k+1] - ai[k];
708       acol = aj + ai[k];
709       aval = aa + ai[k];
710       bval = ba + bi[k];
711       while (nz -- ){
712         if (*acol < k) { /* skip lower triangular entries */
713           acol++; aval++;
714         } else {
715           rtmp[*acol++] = *aval++;
716           *bval++       = 0.0; /* for in-place factorization */
717         }
718       }
719 
720       /* shift the diagonal of the matrix */
721       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
722 
723       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
724       dk = rtmp[k];
725       i  = jl[k]; /* first row to be added to k_th row  */
726 
727       while (i < k){
728         nexti = jl[i]; /* next row to be added to k_th row */
729         /* compute multiplier, update D(k) and U(i,k) */
730         ili   = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
731         uikdi = - ba[ili]*ba[bi[i]];
732         dk   += uikdi*ba[ili];
733         ba[ili] = uikdi; /* -U(i,k) */
734 
735         /* add multiple of row i to k-th row ... */
736         jmin = ili + 1;
737         nz   = bi[i+1] - jmin;
738         if (nz > 0){
739           bcol = bj + jmin;
740           bval = ba + jmin;
741           while (nz --) rtmp[*bcol++] += uikdi*(*bval++);
742           /* update il and jl for i-th row */
743           il[i] = jmin;
744           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
745         }
746         i = nexti;
747       }
748 
749       /* shift the diagonals when zero pivot is detected */
750       /* compute rs=sum of abs(off-diagonal) */
751       rs   = 0.0;
752       jmin = bi[k]+1;
753       nz   = bi[k+1] - jmin;
754       if (nz){
755         bcol = bj + jmin;
756         while (nz--){
757           rs += PetscAbsScalar(rtmp[*bcol]);
758           bcol++;
759         }
760       }
761 
762       sctx.rs = rs;
763       sctx.pv = dk;
764       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
765       if (newshift == 1) break;    /* sctx.shift_amount is updated */
766 
767       /* copy data into U(k,:) */
768       ba[bi[k]] = 1.0/dk;
769       jmin      = bi[k]+1;
770       nz        = bi[k+1] - jmin;
771       if (nz){
772         bcol = bj + jmin;
773         bval = ba + jmin;
774         while (nz--){
775           *bval++       = rtmp[*bcol];
776           rtmp[*bcol++] = 0.0;
777         }
778         /* add k-th row into il and jl */
779         il[k] = jmin;
780         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
781       }
782     }
783   } while (sctx.chshift);
784   ierr = PetscFree3(rtmp,il,jl);CHKERRQ(ierr);
785 
786   C->ops->solve                 = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
787   C->ops->solvetranspose        = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
788   C->assembled    = PETSC_TRUE;
789   C->preallocated = PETSC_TRUE;
790   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
791     if (sctx.nshift){
792       if (info->shifttype == (PetscReal)MAT_SHIFT_NONZERO) {
793       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
794       } else if (info->shifttype == (PetscReal)MAT_SHIFT_POSITIVE_DEFINITE) {
795       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
796     }
797   }
798   PetscFunctionReturn(0);
799 }
800 
801 #include "petscbt.h"
802 #include "../src/mat/utils/freespace.h"
803 #undef __FUNCT__
804 #define __FUNCT__ "MatICCFactorSymbolic_SeqBAIJ"
805 PetscErrorCode MatICCFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
806 {
807   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
808   Mat_SeqSBAIJ       *b;
809   Mat                B;
810   PetscErrorCode     ierr;
811   PetscTruth         perm_identity;
812   PetscInt           reallocs=0,i,*ai=a->i,*aj=a->j,am=a->mbs,bs=A->rmap->bs,*ui;
813   const PetscInt     *rip;
814   PetscInt           jmin,jmax,nzk,k,j,*jl,prow,*il,nextprow;
815   PetscInt           nlnk,*lnk,*lnk_lvl=PETSC_NULL,ncols,ncols_upper,*cols,*cols_lvl,*uj,**uj_ptr,**uj_lvl_ptr;
816   PetscReal          fill=info->fill,levels=info->levels;
817   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
818   PetscFreeSpaceList free_space_lvl=PETSC_NULL,current_space_lvl=PETSC_NULL;
819   PetscBT            lnkbt;
820 
821   PetscFunctionBegin;
822   if (bs > 1){
823     if (!a->sbaijMat){
824       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
825     }
826     (fact)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;  /* undue the change made in MatGetFactor_seqbaij_petsc */
827     ierr = MatICCFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
828     PetscFunctionReturn(0);
829   }
830 
831   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
832   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
833 
834   /* special case that simply copies fill pattern */
835   if (!levels && perm_identity) {
836     ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr);
837     ierr = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
838     for (i=0; i<am; i++) {
839       ui[i] = ai[i+1] - a->diag[i]; /* ui: rowlengths - changes when !perm_identity */
840     }
841     B = fact;
842     ierr = MatSeqSBAIJSetPreallocation(B,1,0,ui);CHKERRQ(ierr);
843 
844 
845     b  = (Mat_SeqSBAIJ*)B->data;
846     uj = b->j;
847     for (i=0; i<am; i++) {
848       aj = a->j + a->diag[i];
849       for (j=0; j<ui[i]; j++){
850         *uj++ = *aj++;
851       }
852       b->ilen[i] = ui[i];
853     }
854     ierr = PetscFree(ui);CHKERRQ(ierr);
855     B->factortype = MAT_FACTOR_NONE;
856     ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
857     ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
858     B->factortype = MAT_FACTOR_ICC;
859 
860     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
861     PetscFunctionReturn(0);
862   }
863 
864   /* initialization */
865   ierr  = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
866   ui[0] = 0;
867   ierr  = PetscMalloc((2*am+1)*sizeof(PetscInt),&cols_lvl);CHKERRQ(ierr);
868 
869   /* jl: linked list for storing indices of the pivot rows
870      il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */
871   ierr = PetscMalloc4(am,PetscInt*,&uj_ptr,am,PetscInt*,&uj_lvl_ptr,am,PetscInt,&il,am,PetscInt,&jl);CHKERRQ(ierr);
872   for (i=0; i<am; i++){
873     jl[i] = am; il[i] = 0;
874   }
875 
876   /* create and initialize a linked list for storing column indices of the active row k */
877   nlnk = am + 1;
878   ierr = PetscIncompleteLLCreate(am,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
879 
880   /* initial FreeSpace size is fill*(ai[am]+1) */
881   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space);CHKERRQ(ierr);
882   current_space = free_space;
883   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space_lvl);CHKERRQ(ierr);
884   current_space_lvl = free_space_lvl;
885 
886   for (k=0; k<am; k++){  /* for each active row k */
887     /* initialize lnk by the column indices of row rip[k] of A */
888     nzk   = 0;
889     ncols = ai[rip[k]+1] - ai[rip[k]];
890     ncols_upper = 0;
891     cols        = cols_lvl + am;
892     for (j=0; j<ncols; j++){
893       i = rip[*(aj + ai[rip[k]] + j)];
894       if (i >= k){ /* only take upper triangular entry */
895         cols[ncols_upper] = i;
896         cols_lvl[ncols_upper] = -1;  /* initialize level for nonzero entries */
897         ncols_upper++;
898       }
899     }
900     ierr = PetscIncompleteLLAdd(ncols_upper,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
901     nzk += nlnk;
902 
903     /* update lnk by computing fill-in for each pivot row to be merged in */
904     prow = jl[k]; /* 1st pivot row */
905 
906     while (prow < k){
907       nextprow = jl[prow];
908 
909       /* merge prow into k-th row */
910       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:am-1) */
911       jmax = ui[prow+1];
912       ncols = jmax-jmin;
913       i     = jmin - ui[prow];
914       cols = uj_ptr[prow] + i; /* points to the 2nd nzero entry in U(prow,k:am-1) */
915       for (j=0; j<ncols; j++) cols_lvl[j] = *(uj_lvl_ptr[prow] + i + j);
916       ierr = PetscIncompleteLLAddSorted(ncols,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
917       nzk += nlnk;
918 
919       /* update il and jl for prow */
920       if (jmin < jmax){
921         il[prow] = jmin;
922         j = *cols; jl[prow] = jl[j]; jl[j] = prow;
923       }
924       prow = nextprow;
925     }
926 
927     /* if free space is not available, make more free space */
928     if (current_space->local_remaining<nzk) {
929       i = am - k + 1; /* num of unfactored rows */
930       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
931       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
932       ierr = PetscFreeSpaceGet(i,&current_space_lvl);CHKERRQ(ierr);
933       reallocs++;
934     }
935 
936     /* copy data into free_space and free_space_lvl, then initialize lnk */
937     ierr = PetscIncompleteLLClean(am,am,nzk,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr);
938 
939     /* add the k-th row into il and jl */
940     if (nzk-1 > 0){
941       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */
942       jl[k] = jl[i]; jl[i] = k;
943       il[k] = ui[k] + 1;
944     }
945     uj_ptr[k]     = current_space->array;
946     uj_lvl_ptr[k] = current_space_lvl->array;
947 
948     current_space->array           += nzk;
949     current_space->local_used      += nzk;
950     current_space->local_remaining -= nzk;
951 
952     current_space_lvl->array           += nzk;
953     current_space_lvl->local_used      += nzk;
954     current_space_lvl->local_remaining -= nzk;
955 
956     ui[k+1] = ui[k] + nzk;
957   }
958 
959 #if defined(PETSC_USE_INFO)
960   if (ai[am] != 0) {
961     PetscReal af = ((PetscReal)(2*ui[am]-am))/((PetscReal)ai[am]);
962     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
963     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
964     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
965   } else {
966     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
967   }
968 #endif
969 
970   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
971   ierr = PetscFree4(uj_ptr,uj_lvl_ptr,il,jl);CHKERRQ(ierr);
972   ierr = PetscFree(cols_lvl);CHKERRQ(ierr);
973 
974   /* destroy list of free space and other temporary array(s) */
975   ierr = PetscMalloc((ui[am]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
976   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
977   ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
978   ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr);
979 
980   /* put together the new matrix in MATSEQSBAIJ format */
981   B = fact;
982   ierr = MatSeqSBAIJSetPreallocation(B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
983 
984   b = (Mat_SeqSBAIJ*)B->data;
985   b->singlemalloc = PETSC_FALSE;
986   b->free_a       = PETSC_TRUE;
987   b->free_ij       = PETSC_TRUE;
988   ierr = PetscMalloc((ui[am]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
989   b->j    = uj;
990   b->i    = ui;
991   b->diag = 0;
992   b->ilen = 0;
993   b->imax = 0;
994   b->row  = perm;
995   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
996   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
997   b->icol = perm;
998   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
999   ierr    = PetscMalloc((am+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1000   ierr    = PetscLogObjectMemory(B,(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1001   b->maxnz = b->nz = ui[am];
1002 
1003   B->info.factor_mallocs    = reallocs;
1004   B->info.fill_ratio_given  = fill;
1005   if (ai[am] != 0.) {
1006     B->info.fill_ratio_needed = ((PetscReal)ui[am])/((PetscReal)ai[am]);
1007   } else {
1008     B->info.fill_ratio_needed = 0.0;
1009   }
1010   if (perm_identity){
1011     B->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1012     B->ops->solvetranspose  = MatSolve_SeqSBAIJ_1_NaturalOrdering_inplace;
1013     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1014   } else {
1015     (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1016   }
1017   PetscFunctionReturn(0);
1018 }
1019 
1020 #undef __FUNCT__
1021 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqBAIJ"
1022 PetscErrorCode MatCholeskyFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
1023 {
1024   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
1025   Mat_SeqSBAIJ       *b;
1026   Mat                B;
1027   PetscErrorCode     ierr;
1028   PetscTruth         perm_identity;
1029   PetscReal          fill = info->fill;
1030   const PetscInt     *rip;
1031   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,*ai=a->i,*aj=a->j,reallocs=0,prow;
1032   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
1033   PetscInt           nlnk,*lnk,ncols,ncols_upper,*cols,*uj,**ui_ptr,*uj_ptr;
1034   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
1035   PetscBT            lnkbt;
1036 
1037   PetscFunctionBegin;
1038   if (bs > 1) { /* convert to seqsbaij */
1039     if (!a->sbaijMat){
1040       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
1041     }
1042     (fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ; /* undue the change made in MatGetFactor_seqbaij_petsc */
1043     ierr = MatCholeskyFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
1044     PetscFunctionReturn(0);
1045   }
1046 
1047   /* check whether perm is the identity mapping */
1048   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
1049   if (!perm_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix reordering is not supported");
1050   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
1051 
1052   /* initialization */
1053   ierr  = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
1054   ui[0] = 0;
1055 
1056   /* jl: linked list for storing indices of the pivot rows
1057      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
1058   ierr = PetscMalloc4(mbs,PetscInt*,&ui_ptr,mbs,PetscInt,&il,mbs,PetscInt,&jl,mbs,PetscInt,&cols);CHKERRQ(ierr);
1059   for (i=0; i<mbs; i++){
1060     jl[i] = mbs; il[i] = 0;
1061   }
1062 
1063   /* create and initialize a linked list for storing column indices of the active row k */
1064   nlnk = mbs + 1;
1065   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1066 
1067   /* initial FreeSpace size is fill*(ai[mbs]+1) */
1068   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr);
1069   current_space = free_space;
1070 
1071   for (k=0; k<mbs; k++){  /* for each active row k */
1072     /* initialize lnk by the column indices of row rip[k] of A */
1073     nzk   = 0;
1074     ncols = ai[rip[k]+1] - ai[rip[k]];
1075     ncols_upper = 0;
1076     for (j=0; j<ncols; j++){
1077       i = rip[*(aj + ai[rip[k]] + j)];
1078       if (i >= k){ /* only take upper triangular entry */
1079         cols[ncols_upper] = i;
1080         ncols_upper++;
1081       }
1082     }
1083     ierr = PetscLLAdd(ncols_upper,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1084     nzk += nlnk;
1085 
1086     /* update lnk by computing fill-in for each pivot row to be merged in */
1087     prow = jl[k]; /* 1st pivot row */
1088 
1089     while (prow < k){
1090       nextprow = jl[prow];
1091       /* merge prow into k-th row */
1092       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
1093       jmax = ui[prow+1];
1094       ncols = jmax-jmin;
1095       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
1096       ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1097       nzk += nlnk;
1098 
1099       /* update il and jl for prow */
1100       if (jmin < jmax){
1101         il[prow] = jmin;
1102         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
1103       }
1104       prow = nextprow;
1105     }
1106 
1107     /* if free space is not available, make more free space */
1108     if (current_space->local_remaining<nzk) {
1109       i = mbs - k + 1; /* num of unfactored rows */
1110       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
1111       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
1112       reallocs++;
1113     }
1114 
1115     /* copy data into free space, then initialize lnk */
1116     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
1117 
1118     /* add the k-th row into il and jl */
1119     if (nzk-1 > 0){
1120       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
1121       jl[k] = jl[i]; jl[i] = k;
1122       il[k] = ui[k] + 1;
1123     }
1124     ui_ptr[k] = current_space->array;
1125     current_space->array           += nzk;
1126     current_space->local_used      += nzk;
1127     current_space->local_remaining -= nzk;
1128 
1129     ui[k+1] = ui[k] + nzk;
1130   }
1131 
1132 #if defined(PETSC_USE_INFO)
1133   if (ai[mbs] != 0.) {
1134     PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
1135     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
1136     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
1137     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
1138   } else {
1139     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
1140   }
1141 #endif
1142 
1143   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
1144   ierr = PetscFree4(ui_ptr,il,jl,cols);CHKERRQ(ierr);
1145 
1146   /* destroy list of free space and other temporary array(s) */
1147   ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
1148   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
1149   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1150 
1151   /* put together the new matrix in MATSEQSBAIJ format */
1152   B    = fact;
1153   ierr = MatSeqSBAIJSetPreallocation(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1154 
1155   b = (Mat_SeqSBAIJ*)B->data;
1156   b->singlemalloc = PETSC_FALSE;
1157   b->free_a       = PETSC_TRUE;
1158   b->free_ij      = PETSC_TRUE;
1159   ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
1160   b->j    = uj;
1161   b->i    = ui;
1162   b->diag = 0;
1163   b->ilen = 0;
1164   b->imax = 0;
1165   b->row  = perm;
1166   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
1167   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1168   b->icol = perm;
1169   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1170   ierr    = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1171   ierr    = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1172   b->maxnz = b->nz = ui[mbs];
1173 
1174   B->info.factor_mallocs    = reallocs;
1175   B->info.fill_ratio_given  = fill;
1176   if (ai[mbs] != 0.) {
1177     B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
1178   } else {
1179     B->info.fill_ratio_needed = 0.0;
1180   }
1181   if (perm_identity){
1182     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1183   } else {
1184     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1185   }
1186   PetscFunctionReturn(0);
1187 }
1188 
1189 #undef __FUNCT__
1190 #define __FUNCT__ "MatSolve_SeqBAIJ_N_NaturalOrdering"
1191 PetscErrorCode MatSolve_SeqBAIJ_N_NaturalOrdering(Mat A,Vec bb,Vec xx)
1192 {
1193   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1194   PetscErrorCode ierr;
1195   const PetscInt *ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1196   PetscInt       i,k,n=a->mbs;
1197   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1198   MatScalar      *aa=a->a,*v;
1199   PetscScalar    *x,*b,*s,*t,*ls;
1200 
1201   PetscFunctionBegin;
1202   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1203   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1204   t  = a->solve_work;
1205 
1206   /* forward solve the lower triangular */
1207   ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy 1st block of b to t */
1208 
1209   for (i=1; i<n; i++) {
1210     v   = aa + bs2*ai[i];
1211     vi  = aj + ai[i];
1212     nz = ai[i+1] - ai[i];
1213     s = t + bs*i;
1214     ierr = PetscMemcpy(s,b+bs*i,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy i_th block of b to t */
1215     for(k=0;k<nz;k++){
1216       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[k]);
1217       v += bs2;
1218     }
1219   }
1220 
1221   /* backward solve the upper triangular */
1222   ls = a->solve_work + A->cmap->n;
1223   for (i=n-1; i>=0; i--){
1224     v  = aa + bs2*(adiag[i+1]+1);
1225     vi = aj + adiag[i+1]+1;
1226     nz = adiag[i] - adiag[i+1]-1;
1227     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1228     for(k=0;k<nz;k++){
1229       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[k]);
1230       v += bs2;
1231     }
1232     Kernel_w_gets_A_times_v(bs,ls,aa+bs2*adiag[i],t+i*bs); /* *inv(diagonal[i]) */
1233     ierr = PetscMemcpy(x+i*bs,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1234   }
1235 
1236   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1237   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1238   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1239   PetscFunctionReturn(0);
1240 }
1241 
1242 #undef __FUNCT__
1243 #define __FUNCT__ "MatSolve_SeqBAIJ_N"
1244 PetscErrorCode MatSolve_SeqBAIJ_N(Mat A,Vec bb,Vec xx)
1245 {
1246   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1247   IS             iscol=a->col,isrow=a->row;
1248   PetscErrorCode ierr;
1249   const PetscInt *r,*c,*rout,*cout,*ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1250   PetscInt       i,m,n=a->mbs;
1251   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1252   MatScalar      *aa=a->a,*v;
1253   PetscScalar    *x,*b,*s,*t,*ls;
1254 
1255   PetscFunctionBegin;
1256   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1257   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1258   t  = a->solve_work;
1259 
1260   ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout;
1261   ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout;
1262 
1263   /* forward solve the lower triangular */
1264   ierr = PetscMemcpy(t,b+bs*r[0],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1265   for (i=1; i<n; i++) {
1266     v   = aa + bs2*ai[i];
1267     vi  = aj + ai[i];
1268     nz = ai[i+1] - ai[i];
1269     s = t + bs*i;
1270     ierr = PetscMemcpy(s,b+bs*r[i],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1271     for(m=0;m<nz;m++){
1272       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[m]);
1273       v += bs2;
1274     }
1275   }
1276 
1277   /* backward solve the upper triangular */
1278   ls = a->solve_work + A->cmap->n;
1279   for (i=n-1; i>=0; i--){
1280     v  = aa + bs2*(adiag[i+1]+1);
1281     vi = aj + adiag[i+1]+1;
1282     nz = adiag[i] - adiag[i+1] - 1;
1283     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1284     for(m=0;m<nz;m++){
1285       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[m]);
1286       v += bs2;
1287     }
1288     Kernel_w_gets_A_times_v(bs,ls,v,t+i*bs); /* *inv(diagonal[i]) */
1289     ierr = PetscMemcpy(x + bs*c[i],t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1290   }
1291   ierr = ISRestoreIndices(isrow,&rout);CHKERRQ(ierr);
1292   ierr = ISRestoreIndices(iscol,&cout);CHKERRQ(ierr);
1293   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1294   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1295   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1296   PetscFunctionReturn(0);
1297 }
1298 
1299 #undef __FUNCT__
1300 #define __FUNCT__ "BlockAbs_privat"
1301 PetscErrorCode BlockAbs_private(PetscInt nbs,PetscInt bs2,PetscScalar *blockarray,PetscReal *absarray)
1302 {
1303   PetscErrorCode     ierr;
1304   PetscInt           i,j;
1305   PetscFunctionBegin;
1306   ierr = PetscMemzero(absarray,(nbs+1)*sizeof(PetscReal));CHKERRQ(ierr);
1307   for (i=0; i<nbs; i++){
1308     for (j=0; j<bs2; j++){
1309       if (absarray[i] < PetscAbsScalar(blockarray[i*nbs+j])) absarray[i] = PetscAbsScalar(blockarray[i*nbs+j]);
1310     }
1311   }
1312   PetscFunctionReturn(0);
1313 }
1314 
1315 #undef __FUNCT__
1316 #define __FUNCT__ "MatILUDTFactor_SeqBAIJ"
1317 /*
1318      This needs to be renamed and called by the regular MatILUFactor_SeqBAIJ when drop tolerance is used
1319 */
1320 PetscErrorCode MatILUDTFactor_SeqBAIJ(Mat A,IS isrow,IS iscol,const MatFactorInfo *info,Mat *fact)
1321 {
1322   Mat                B = *fact;
1323   Mat_SeqBAIJ        *a=(Mat_SeqBAIJ*)A->data,*b;
1324   IS                 isicol;
1325   PetscErrorCode     ierr;
1326   const PetscInt     *r,*ic;
1327   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,bs2=a->bs2,*ai=a->i,*aj=a->j,*ajtmp,*adiag;
1328   PetscInt           *bi,*bj,*bdiag;
1329 
1330   PetscInt           row,nzi,nzi_bl,nzi_bu,*im,dtcount,nzi_al,nzi_au;
1331   PetscInt           nlnk,*lnk;
1332   PetscBT            lnkbt;
1333   PetscTruth         row_identity,icol_identity,both_identity;
1334   MatScalar          *aatmp,*pv,*batmp,*ba,*rtmp,*pc,*multiplier,*vtmp;
1335   const PetscInt     *ics;
1336   PetscInt           j,nz,*pj,*bjtmp,k,ncut,*jtmp;
1337 
1338   PetscReal          dt=info->dt; /* shift=info->shiftamount; */
1339   PetscInt           nnz_max;
1340   PetscTruth         missing;
1341   PetscReal          *vtmp_abs;
1342   MatScalar          *v_work;
1343   PetscInt           *v_pivots;
1344 
1345   PetscFunctionBegin;
1346   /* ------- symbolic factorization, can be reused ---------*/
1347   ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr);
1348   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i);
1349   adiag=a->diag;
1350 
1351   ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr);
1352 
1353   /* bdiag is location of diagonal in factor */
1354   ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr);
1355 
1356   /* allocate row pointers bi */
1357   ierr = PetscMalloc((2*mbs+2)*sizeof(PetscInt),&bi);CHKERRQ(ierr);
1358 
1359   /* allocate bj and ba; max num of nonzero entries is (ai[n]+2*n*dtcount+2) */
1360   dtcount = (PetscInt)info->dtcount;
1361   if (dtcount > mbs-1) dtcount = mbs-1;
1362   nnz_max  = ai[mbs]+2*mbs*dtcount +2;
1363   /* printf("MatILUDTFactor_SeqBAIJ, bs %d, ai[mbs] %d, nnz_max  %d, dtcount %d\n",bs,ai[mbs],nnz_max,dtcount); */
1364   ierr = PetscMalloc(nnz_max*sizeof(PetscInt),&bj);CHKERRQ(ierr);
1365   nnz_max = nnz_max*bs2;
1366   ierr = PetscMalloc(nnz_max*sizeof(MatScalar),&ba);CHKERRQ(ierr);
1367 
1368   /* put together the new matrix */
1369   ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1370   ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr);
1371   b    = (Mat_SeqBAIJ*)(B)->data;
1372   b->free_a       = PETSC_TRUE;
1373   b->free_ij      = PETSC_TRUE;
1374   b->singlemalloc = PETSC_FALSE;
1375   b->a          = ba;
1376   b->j          = bj;
1377   b->i          = bi;
1378   b->diag       = bdiag;
1379   b->ilen       = 0;
1380   b->imax       = 0;
1381   b->row        = isrow;
1382   b->col        = iscol;
1383   ierr          = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
1384   ierr          = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
1385   b->icol       = isicol;
1386   ierr = PetscMalloc((bs*(mbs+1))*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1387 
1388   ierr = PetscLogObjectMemory(B,nnz_max*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1389   b->maxnz = nnz_max/bs2;
1390 
1391   (B)->factortype            = MAT_FACTOR_ILUDT;
1392   (B)->info.factor_mallocs   = 0;
1393   (B)->info.fill_ratio_given = ((PetscReal)nnz_max)/((PetscReal)(ai[mbs]*bs2));
1394   CHKMEMQ;
1395   /* ------- end of symbolic factorization ---------*/
1396   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
1397   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
1398   ics  = ic;
1399 
1400   /* linked list for storing column indices of the active row */
1401   nlnk = mbs + 1;
1402   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1403 
1404   /* im: used by PetscLLAddSortedLU(); jtmp: working array for column indices of active row */
1405   ierr = PetscMalloc2(mbs,PetscInt,&im,mbs,PetscInt,&jtmp);CHKERRQ(ierr);
1406   /* rtmp, vtmp: working arrays for sparse and contiguous row entries of active row */
1407   ierr = PetscMalloc2(mbs*bs2,MatScalar,&rtmp,mbs*bs2,MatScalar,&vtmp);CHKERRQ(ierr);
1408   ierr = PetscMalloc((mbs+1)*sizeof(PetscReal),&vtmp_abs);CHKERRQ(ierr);
1409   ierr = PetscMalloc3(bs,MatScalar,&v_work,bs2,MatScalar,&multiplier,bs,PetscInt,&v_pivots);CHKERRQ(ierr);
1410 
1411   bi[0]    = 0;
1412   bdiag[0] = (nnz_max/bs2)-1; /* location of diagonal in factor B */
1413   bi[2*mbs+1] = bdiag[0]+1; /* endof bj and ba array */
1414   for (i=0; i<mbs; i++) {
1415     /* copy initial fill into linked list */
1416     nzi = 0; /* nonzeros for active row i */
1417     nzi = ai[r[i]+1] - ai[r[i]];
1418     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);
1419     nzi_al = adiag[r[i]] - ai[r[i]];
1420     nzi_au = ai[r[i]+1] - adiag[r[i]] -1;
1421     /* printf("row %d, nzi_al/au %d %d\n",i,nzi_al,nzi_au); */
1422 
1423     /* load in initial unfactored row */
1424     ajtmp = aj + ai[r[i]];
1425     ierr = PetscLLAddPerm(nzi,ajtmp,ic,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1426     ierr = PetscMemzero(rtmp,mbs*bs2*sizeof(PetscScalar));CHKERRQ(ierr);
1427     aatmp = a->a + bs2*ai[r[i]];
1428     for (j=0; j<nzi; j++) {
1429       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],aatmp+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1430     }
1431 
1432     /* add pivot rows into linked list */
1433     row = lnk[mbs];
1434     while (row < i) {
1435       nzi_bl = bi[row+1] - bi[row] + 1;
1436       bjtmp = bj + bdiag[row+1]+1; /* points to 1st column next to the diagonal in U */
1437       ierr  = PetscLLAddSortedLU(bjtmp,row,nlnk,lnk,lnkbt,i,nzi_bl,im);CHKERRQ(ierr);
1438       nzi  += nlnk;
1439       row   = lnk[row];
1440     }
1441 
1442     /* copy data from lnk into jtmp, then initialize lnk */
1443     ierr = PetscLLClean(mbs,mbs,nzi,lnk,jtmp,lnkbt);CHKERRQ(ierr);
1444 
1445     /* numerical factorization */
1446     bjtmp = jtmp;
1447     row   = *bjtmp++; /* 1st pivot row */
1448 
1449     while  (row < i) {
1450       pc = rtmp + bs2*row;
1451       pv = ba + bs2*bdiag[row]; /* inv(diag) of the pivot row */
1452       Kernel_A_gets_A_times_B(bs,pc,pv,multiplier); /* pc= multiplier = pc*inv(diag[row]) */
1453       ierr = BlockAbs_private(1,bs2,pc,vtmp_abs);CHKERRQ(ierr);
1454       if (vtmp_abs[0] > dt){ /* apply tolerance dropping rule */
1455         pj         = bj + bdiag[row+1] + 1; /* point to 1st entry of U(row,:) */
1456         pv         = ba + bs2*(bdiag[row+1] + 1);
1457         nz         = bdiag[row] - bdiag[row+1] - 1; /* num of entries in U(row,:), excluding diagonal */
1458         for (j=0; j<nz; j++){
1459           Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j);
1460         }
1461         /* ierr = PetscLogFlops(bslog*(nz+1.0)-bs);CHKERRQ(ierr); */
1462       }
1463       row = *bjtmp++;
1464     }
1465 
1466     /* copy sparse rtmp into contiguous vtmp; separate L and U part */
1467     nzi_bl = 0; j = 0;
1468     while (jtmp[j] < i){ /* L-part. Note: jtmp is sorted */
1469       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1470       nzi_bl++; j++;
1471     }
1472     nzi_bu = nzi - nzi_bl -1;
1473     /* printf("nzi %d, nzi_bl %d, nzi_bu %d\n",nzi,nzi_bl,nzi_bu); */
1474 
1475     while (j < nzi){ /* U-part */
1476       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1477       /*
1478       printf(" col %d: ",jtmp[j]);
1479       for (j1=0; j1<bs2; j1++) printf(" %g",*(vtmp+bs2*j+j1));
1480       printf(" \n");
1481       */
1482       j++;
1483     }
1484 
1485     ierr = BlockAbs_private(nzi,bs2,vtmp,vtmp_abs);CHKERRQ(ierr);
1486     /*
1487     printf(" row %d, nzi %d, vtmp_abs\n",i,nzi);
1488     for (j1=0; j1<nzi; j1++) printf(" (%d %g),",jtmp[j1],vtmp_abs[j1]);
1489     printf(" \n");
1490     */
1491     bjtmp = bj + bi[i];
1492     batmp = ba + bs2*bi[i];
1493     /* apply level dropping rule to L part */
1494     ncut = nzi_al + dtcount;
1495     if (ncut < nzi_bl){
1496       ierr = PetscSortSplitReal(ncut,nzi_bl,vtmp_abs,jtmp);CHKERRQ(ierr);
1497       ierr = PetscSortIntWithScalarArray(ncut,jtmp,vtmp);CHKERRQ(ierr);
1498     } else {
1499       ncut = nzi_bl;
1500     }
1501     for (j=0; j<ncut; j++){
1502       bjtmp[j] = jtmp[j];
1503       ierr = PetscMemcpy(batmp+bs2*j,rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1504       /*
1505       printf(" col %d: ",bjtmp[j]);
1506       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*j+j1));
1507       printf("\n");
1508       */
1509     }
1510     bi[i+1] = bi[i] + ncut;
1511     nzi = ncut + 1;
1512 
1513     /* apply level dropping rule to U part */
1514     ncut = nzi_au + dtcount;
1515     if (ncut < nzi_bu){
1516       ierr = PetscSortSplitReal(ncut,nzi_bu,vtmp_abs+nzi_bl+1,jtmp+nzi_bl+1);CHKERRQ(ierr);
1517       ierr = PetscSortIntWithScalarArray(ncut,jtmp+nzi_bl+1,vtmp+nzi_bl+1);CHKERRQ(ierr);
1518     } else {
1519       ncut = nzi_bu;
1520     }
1521     nzi += ncut;
1522 
1523     /* mark bdiagonal */
1524     bdiag[i+1]    = bdiag[i] - (ncut + 1);
1525     bi[2*mbs - i] = bi[2*mbs - i +1] - (ncut + 1);
1526 
1527     bjtmp = bj + bdiag[i];
1528     batmp = ba + bs2*bdiag[i];
1529     ierr = PetscMemcpy(batmp,rtmp+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1530     *bjtmp = i;
1531     /*
1532     printf(" diag %d: ",*bjtmp);
1533     for (j=0; j<bs2; j++){
1534       printf(" %g,",batmp[j]);
1535     }
1536     printf("\n");
1537     */
1538     bjtmp = bj + bdiag[i+1]+1;
1539     batmp = ba + (bdiag[i+1]+1)*bs2;
1540 
1541     for (k=0; k<ncut; k++){
1542       bjtmp[k] = jtmp[nzi_bl+1+k];
1543       ierr = PetscMemcpy(batmp+bs2*k,rtmp+bs2*bjtmp[k],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1544       /*
1545       printf(" col %d:",bjtmp[k]);
1546       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*k+j1));
1547       printf("\n");
1548       */
1549     }
1550 
1551     im[i] = nzi; /* used by PetscLLAddSortedLU() */
1552 
1553     /* invert diagonal block for simplier triangular solves - add shift??? */
1554     batmp = ba + bs2*bdiag[i];
1555     ierr = Kernel_A_gets_inverse_A(bs,batmp,v_pivots,v_work);CHKERRQ(ierr);
1556   } /* for (i=0; i<mbs; i++) */
1557   ierr = PetscFree3(v_work,multiplier,v_pivots);CHKERRQ(ierr);
1558 
1559   /* printf("end of L %d, beginning of U %d\n",bi[mbs],bdiag[mbs]); */
1560   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]);
1561 
1562   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
1563   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
1564 
1565   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1566 
1567   ierr = PetscFree2(im,jtmp);CHKERRQ(ierr);
1568   ierr = PetscFree2(rtmp,vtmp);CHKERRQ(ierr);
1569 
1570   ierr = PetscLogFlops(bs2*B->cmap->n);CHKERRQ(ierr);
1571   b->maxnz = b->nz = bi[mbs] + bdiag[0] - bdiag[mbs];
1572 
1573   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
1574   ierr = ISIdentity(isicol,&icol_identity);CHKERRQ(ierr);
1575   both_identity = (PetscTruth) (row_identity && icol_identity);
1576   if (row_identity && icol_identity) {
1577     B->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering;
1578   } else {
1579     B->ops->solve = MatSolve_SeqBAIJ_N;
1580   }
1581 
1582   B->ops->solveadd          = 0;
1583   B->ops->solvetranspose    = 0;
1584   B->ops->solvetransposeadd = 0;
1585   B->ops->matsolve          = 0;
1586   B->assembled              = PETSC_TRUE;
1587   B->preallocated           = PETSC_TRUE;
1588   PetscFunctionReturn(0);
1589 }
1590