xref: /petsc/src/mat/impls/baij/seq/baijfact.c (revision 753ebd1d069d7a4e86ed47ccb83df941bd1fb5db)
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_newdatastruct"
11 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_newdatastruct(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,n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
19   PetscInt       *ajtmp,*bjtmp,nz,nzL,row,*bdiag=b->diag,*pj;
20   MatScalar      *rtmp,*pc,*mwork,*v,*pv,*aa=a->a;
21   PetscInt       bs2 = a->bs2,flg;
22   PetscReal      shift = info->shiftinblocks;
23 
24   PetscFunctionBegin;
25   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
26   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
27 
28   /* generate work space needed by the factorization */
29   ierr = PetscMalloc((bs2*n+bs2+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
30   mwork = rtmp + bs2*n;
31   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
32   ics  = ic;
33 
34   for (i=0; i<n; i++){
35     /* zero rtmp */
36     /* L part */
37     nz    = bi[i+1] - bi[i];
38     bjtmp = bj + bi[i];
39     for  (j=0; j<nz; j++){
40       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
41     }
42 
43     /* U part */
44     nz = bdiag[i] - bdiag[i+1];
45     bjtmp = bj + bdiag[i+1]+1;
46     for  (j=0; j<nz; j++){
47       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
48     }
49 
50     /* load in initial (unfactored row) */
51     nz    = ai[r[i]+1] - ai[r[i]];
52     ajtmp = aj + ai[r[i]];
53     v     = aa + bs2*ai[r[i]];
54     for (j=0; j<nz; j++) {
55       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
56     }
57 
58     /* elimination */
59     bjtmp = bj + bi[i];
60     nzL   = bi[i+1] - bi[i];
61     for(k=0;k < nzL;k++) {
62       row = bjtmp[k];
63       pc = rtmp + bs2*row;
64       for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }}
65       if (flg) {
66         pv = b->a + bs2*bdiag[row];
67         /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
68         ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
69 
70         pj = b->j + bdiag[row+1]+1; /* begining of U(row,:) */
71         pv = b->a + bs2*(bdiag[row+1]+1);
72         nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */
73         for (j=0; j<nz; j++) {
74           /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
75           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
76           v    = rtmp + 4*pj[j];
77           ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
78           pv  += 4;
79         }
80         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
81       }
82     }
83 
84     /* finished row so stick it into b->a */
85     /* L part */
86     pv   = b->a + bs2*bi[i] ;
87     pj   = b->j + bi[i] ;
88     nz   = bi[i+1] - bi[i];
89     for (j=0; j<nz; j++) {
90       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
91     }
92 
93     /* Mark diagonal and invert diagonal for simplier triangular solves */
94     pv   = b->a + bs2*bdiag[i];
95     pj   = b->j + bdiag[i];
96     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
97     /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
98     ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
99 
100     /* U part */
101     pv = b->a + bs2*(bdiag[i+1]+1);
102     pj = b->j + bdiag[i+1]+1;
103     nz = bdiag[i] - bdiag[i+1] - 1;
104     for (j=0; j<nz; j++){
105       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
106     }
107   }
108 
109   ierr = PetscFree(rtmp);CHKERRQ(ierr);
110   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
111   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
112 
113   C->assembled = PETSC_TRUE;
114   ierr = PetscLogFlops(1.3333*bs2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
115   PetscFunctionReturn(0);
116 }
117 
118 #undef __FUNCT__
119 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_newdatastruct"
120 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering_newdatastruct(Mat B,Mat A,const MatFactorInfo *info)
121 {
122   Mat            C=B;
123   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ *)C->data;
124   PetscErrorCode ierr;
125   PetscInt       i,j,k,n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
126   PetscInt       *ajtmp,*bjtmp,nz,nzL,row,*bdiag=b->diag,*pj;
127   MatScalar      *rtmp,*pc,*mwork,*v,*pv,*aa=a->a;
128   PetscInt       bs2 = a->bs2,flg;
129   PetscReal      shift = info->shiftinblocks;
130 
131   PetscFunctionBegin;
132   /* generate work space needed by the factorization */
133   ierr = PetscMalloc((bs2*n+bs2+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
134   mwork = rtmp + bs2*n;
135   ierr = PetscMemzero(rtmp,bs2*n*sizeof(MatScalar));CHKERRQ(ierr);
136 
137   for (i=0; i<n; i++){
138     /* zero rtmp */
139     /* L part */
140     nz    = bi[i+1] - bi[i];
141     bjtmp = bj + bi[i];
142     for  (j=0; j<nz; j++){
143       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
144     }
145 
146     /* U part */
147     nz = bdiag[i] - bdiag[i+1];
148     bjtmp = bj + bdiag[i+1]+1;
149     for  (j=0; j<nz; j++){
150       ierr = PetscMemzero(rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
151     }
152 
153     /* load in initial (unfactored row) */
154     nz    = ai[i+1] - ai[i];
155     ajtmp = aj + ai[i];
156     v     = aa + bs2*ai[i];
157     for (j=0; j<nz; j++) {
158       ierr = PetscMemcpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
159     }
160 
161     /* elimination */
162     bjtmp = bj + bi[i];
163     nzL   = bi[i+1] - bi[i];
164     for(k=0;k < nzL;k++) {
165       row = bjtmp[k];
166       pc = rtmp + bs2*row;
167       for (flg=0,j=0; j<bs2; j++) { if (pc[j]!=0.0) { flg = 1; break; }}
168       if (flg) {
169         pv = b->a + bs2*bdiag[row];
170         /* Kernel_A_gets_A_times_B(bs,pc,pv,mwork); *pc = *pc * (*pv); */
171         ierr = Kernel_A_gets_A_times_B_2(pc,pv,mwork);CHKERRQ(ierr);
172 
173         pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */
174 	pv = b->a + bs2*(bdiag[row+1]+1);
175 	nz = bdiag[row]-bdiag[row+1] - 1; /* num of entries in U(row,:) excluding diag */
176         for (j=0; j<nz; j++) {
177           /* Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j); */
178           /* rtmp+bs2*pj[j] = rtmp+bs2*pj[j] - (*pc)*(pv+bs2*j) */
179           v    = rtmp + 4*pj[j];
180           ierr = Kernel_A_gets_A_minus_B_times_C_2(v,pc,pv);CHKERRQ(ierr);
181           pv  += 4;
182         }
183         ierr = PetscLogFlops(16*nz+12);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
184       }
185     }
186 
187     /* finished row so stick it into b->a */
188     /* L part */
189     pv   = b->a + bs2*bi[i] ;
190     pj   = b->j + bi[i] ;
191     nz   = bi[i+1] - bi[i];
192     for (j=0; j<nz; j++) {
193       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
194     }
195 
196     /* Mark diagonal and invert diagonal for simplier triangular solves */
197     pv   = b->a + bs2*bdiag[i];
198     pj   = b->j + bdiag[i];
199     ierr = PetscMemcpy(pv,rtmp+bs2*pj[0],bs2*sizeof(MatScalar));CHKERRQ(ierr);
200     /* ierr = Kernel_A_gets_inverse_A(bs,pv,v_pivots,v_work);CHKERRQ(ierr); */
201     ierr = Kernel_A_gets_inverse_A_2(pv,shift);CHKERRQ(ierr);
202 
203     /* U part */
204     /*
205     pv = b->a + bs2*bi[2*n-i];
206     pj = b->j + bi[2*n-i];
207     nz = bi[2*n-i+1] - bi[2*n-i] - 1;
208     */
209     pv = b->a + bs2*(bdiag[i+1]+1);
210     pj = b->j + bdiag[i+1]+1;
211     nz = bdiag[i] - bdiag[i+1] - 1;
212     for (j=0; j<nz; j++){
213       ierr = PetscMemcpy(pv+bs2*j,rtmp+bs2*pj[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
214     }
215   }
216 
217   ierr = PetscFree(rtmp);CHKERRQ(ierr);
218   C->assembled = PETSC_TRUE;
219   ierr = PetscLogFlops(1.3333*bs2*n);CHKERRQ(ierr); /* from inverting diagonal blocks */
220   PetscFunctionReturn(0);
221 }
222 
223 #undef __FUNCT__
224 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2"
225 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2(Mat B,Mat A,const MatFactorInfo *info)
226 {
227   Mat            C = B;
228   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
229   IS             isrow = b->row,isicol = b->icol;
230   PetscErrorCode ierr;
231   const PetscInt *r,*ic;
232   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
233   PetscInt       *ajtmpold,*ajtmp,nz,row;
234   PetscInt       *diag_offset=b->diag,idx,*ai=a->i,*aj=a->j,*pj;
235   MatScalar      *pv,*v,*rtmp,m1,m2,m3,m4,*pc,*w,*x,x1,x2,x3,x4;
236   MatScalar      p1,p2,p3,p4;
237   MatScalar      *ba = b->a,*aa = a->a;
238   PetscReal      shift = info->shiftinblocks;
239 
240   PetscFunctionBegin;
241   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
242   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
243   ierr  = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
244 
245   for (i=0; i<n; i++) {
246     nz    = bi[i+1] - bi[i];
247     ajtmp = bj + bi[i];
248     for  (j=0; j<nz; j++) {
249       x = rtmp+4*ajtmp[j]; x[0] = x[1] = x[2] = x[3] = 0.0;
250     }
251     /* load in initial (unfactored row) */
252     idx      = r[i];
253     nz       = ai[idx+1] - ai[idx];
254     ajtmpold = aj + ai[idx];
255     v        = aa + 4*ai[idx];
256     for (j=0; j<nz; j++) {
257       x    = rtmp+4*ic[ajtmpold[j]];
258       x[0] = v[0]; x[1] = v[1]; x[2] = v[2]; x[3] = v[3];
259       v    += 4;
260     }
261     row = *ajtmp++;
262     while (row < i) {
263       pc = rtmp + 4*row;
264       p1 = pc[0]; p2 = pc[1]; p3 = pc[2]; p4 = pc[3];
265       if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) {
266         pv = ba + 4*diag_offset[row];
267         pj = bj + diag_offset[row] + 1;
268         x1 = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
269         pc[0] = m1 = p1*x1 + p3*x2;
270         pc[1] = m2 = p2*x1 + p4*x2;
271         pc[2] = m3 = p1*x3 + p3*x4;
272         pc[3] = m4 = p2*x3 + p4*x4;
273         nz = bi[row+1] - diag_offset[row] - 1;
274         pv += 4;
275         for (j=0; j<nz; j++) {
276           x1   = pv[0]; x2 = pv[1]; x3 = pv[2]; x4 = pv[3];
277           x    = rtmp + 4*pj[j];
278           x[0] -= m1*x1 + m3*x2;
279           x[1] -= m2*x1 + m4*x2;
280           x[2] -= m1*x3 + m3*x4;
281           x[3] -= m2*x3 + m4*x4;
282           pv   += 4;
283         }
284         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
285       }
286       row = *ajtmp++;
287     }
288     /* finished row so stick it into b->a */
289     pv = ba + 4*bi[i];
290     pj = bj + bi[i];
291     nz = bi[i+1] - bi[i];
292     for (j=0; j<nz; j++) {
293       x     = rtmp+4*pj[j];
294       pv[0] = x[0]; pv[1] = x[1]; pv[2] = x[2]; pv[3] = x[3];
295       pv   += 4;
296     }
297     /* invert diagonal block */
298     w = ba + 4*diag_offset[i];
299     ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
300   }
301 
302   ierr = PetscFree(rtmp);CHKERRQ(ierr);
303   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
304   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
305   C->ops->solve          = MatSolve_SeqBAIJ_2;
306   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2;
307   C->assembled = PETSC_TRUE;
308   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
309   PetscFunctionReturn(0);
310 }
311 /*
312       Version for when blocks are 2 by 2 Using natural ordering
313 */
314 #undef __FUNCT__
315 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering"
316 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_2_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
317 {
318   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
319   PetscErrorCode ierr;
320   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
321   PetscInt       *ajtmpold,*ajtmp,nz,row;
322   PetscInt       *diag_offset = b->diag,*ai=a->i,*aj=a->j,*pj;
323   MatScalar      *pv,*v,*rtmp,*pc,*w,*x;
324   MatScalar      p1,p2,p3,p4,m1,m2,m3,m4,x1,x2,x3,x4;
325   MatScalar      *ba = b->a,*aa = a->a;
326   PetscReal      shift = info->shiftinblocks;
327 
328   PetscFunctionBegin;
329   ierr = PetscMalloc(4*(n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
330   for (i=0; i<n; i++) {
331     nz    = bi[i+1] - bi[i];
332     ajtmp = bj + bi[i];
333     for  (j=0; j<nz; j++) {
334       x = rtmp+4*ajtmp[j];
335       x[0]  = x[1]  = x[2]  = x[3]  = 0.0;
336     }
337     /* load in initial (unfactored row) */
338     nz       = ai[i+1] - ai[i];
339     ajtmpold = aj + ai[i];
340     v        = aa + 4*ai[i];
341     for (j=0; j<nz; j++) {
342       x    = rtmp+4*ajtmpold[j];
343       x[0]  = v[0];  x[1]  = v[1];  x[2]  = v[2];  x[3]  = v[3];
344       v    += 4;
345     }
346     row = *ajtmp++;
347     while (row < i) {
348       pc  = rtmp + 4*row;
349       p1  = pc[0];  p2  = pc[1];  p3  = pc[2];  p4  = pc[3];
350       if (p1 != 0.0 || p2 != 0.0 || p3 != 0.0 || p4 != 0.0) {
351         pv = ba + 4*diag_offset[row];
352         pj = bj + diag_offset[row] + 1;
353         x1  = pv[0];  x2  = pv[1];  x3  = pv[2];  x4  = pv[3];
354         pc[0] = m1 = p1*x1 + p3*x2;
355         pc[1] = m2 = p2*x1 + p4*x2;
356         pc[2] = m3 = p1*x3 + p3*x4;
357         pc[3] = m4 = p2*x3 + p4*x4;
358         nz = bi[row+1] - diag_offset[row] - 1;
359         pv += 4;
360         for (j=0; j<nz; j++) {
361           x1   = pv[0];  x2  = pv[1];   x3 = pv[2];  x4  = pv[3];
362           x    = rtmp + 4*pj[j];
363           x[0] -= m1*x1 + m3*x2;
364           x[1] -= m2*x1 + m4*x2;
365           x[2] -= m1*x3 + m3*x4;
366           x[3] -= m2*x3 + m4*x4;
367           pv   += 4;
368         }
369         ierr = PetscLogFlops(16.0*nz+12.0);CHKERRQ(ierr);
370       }
371       row = *ajtmp++;
372     }
373     /* finished row so stick it into b->a */
374     pv = ba + 4*bi[i];
375     pj = bj + bi[i];
376     nz = bi[i+1] - bi[i];
377     for (j=0; j<nz; j++) {
378       x      = rtmp+4*pj[j];
379       pv[0]  = x[0];  pv[1]  = x[1];  pv[2]  = x[2];  pv[3]  = x[3];
380       /*
381       printf(" col %d:",pj[j]);
382       PetscInt j1;
383       for (j1=0; j1<4; j1++) printf(" %g,",*(pv+j1));
384       printf("\n");
385       */
386       pv   += 4;
387     }
388     /* invert diagonal block */
389     w = ba + 4*diag_offset[i];
390     /*
391     printf(" \n%d -th: diag: ",i);
392     for (j=0; j<4; j++){
393       printf(" %g,",w[j]);
394     }
395     printf("\n----------------------------\n");
396     */
397     ierr = Kernel_A_gets_inverse_A_2(w,shift);CHKERRQ(ierr);
398   }
399 
400   ierr = PetscFree(rtmp);CHKERRQ(ierr);
401   C->ops->solve          = MatSolve_SeqBAIJ_2_NaturalOrdering;
402   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_2_NaturalOrdering;
403   C->assembled = PETSC_TRUE;
404   ierr = PetscLogFlops(1.3333*8*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
405   PetscFunctionReturn(0);
406 }
407 
408 /* ----------------------------------------------------------- */
409 /*
410      Version for when blocks are 1 by 1.
411 */
412 #undef __FUNCT__
413 #define __FUNCT__ "MatLUFactorNumeric_SeqBAIJ_1"
414 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_1(Mat C,Mat A,const MatFactorInfo *info)
415 {
416   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b = (Mat_SeqBAIJ *)C->data;
417   IS             isrow = b->row,isicol = b->icol;
418   PetscErrorCode ierr;
419   const PetscInt *r,*ic;
420   PetscInt       i,j,n = a->mbs,*bi = b->i,*bj = b->j;
421   PetscInt       *ajtmpold,*ajtmp,nz,row,*ai = a->i,*aj = a->j;
422   PetscInt       *diag_offset = b->diag,diag,*pj;
423   MatScalar      *pv,*v,*rtmp,multiplier,*pc;
424   MatScalar      *ba = b->a,*aa = a->a;
425   PetscTruth     row_identity, col_identity;
426 
427   PetscFunctionBegin;
428   ierr  = ISGetIndices(isrow,&r);CHKERRQ(ierr);
429   ierr  = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
430   ierr  = PetscMalloc((n+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
431 
432   for (i=0; i<n; i++) {
433     nz    = bi[i+1] - bi[i];
434     ajtmp = bj + bi[i];
435     for  (j=0; j<nz; j++) rtmp[ajtmp[j]] = 0.0;
436 
437     /* load in initial (unfactored row) */
438     nz       = ai[r[i]+1] - ai[r[i]];
439     ajtmpold = aj + ai[r[i]];
440     v        = aa + ai[r[i]];
441     for (j=0; j<nz; j++) rtmp[ic[ajtmpold[j]]] =  v[j];
442 
443     row = *ajtmp++;
444     while (row < i) {
445       pc = rtmp + row;
446       if (*pc != 0.0) {
447         pv         = ba + diag_offset[row];
448         pj         = bj + diag_offset[row] + 1;
449         multiplier = *pc * *pv++;
450         *pc        = multiplier;
451         nz         = bi[row+1] - diag_offset[row] - 1;
452         for (j=0; j<nz; j++) rtmp[pj[j]] -= multiplier * pv[j];
453         ierr = PetscLogFlops(1.0+2.0*nz);CHKERRQ(ierr);
454       }
455       row = *ajtmp++;
456     }
457     /* finished row so stick it into b->a */
458     pv = ba + bi[i];
459     pj = bj + bi[i];
460     nz = bi[i+1] - bi[i];
461     for (j=0; j<nz; j++) {pv[j] = rtmp[pj[j]];}
462     diag = diag_offset[i] - bi[i];
463     /* check pivot entry for current row */
464     if (pv[diag] == 0.0) {
465       SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot: row in original ordering %D in permuted ordering %D",r[i],i);
466     }
467     pv[diag] = 1.0/pv[diag];
468   }
469 
470   ierr = PetscFree(rtmp);CHKERRQ(ierr);
471   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
472   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
473   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
474   ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr);
475   if (row_identity && col_identity) {
476     C->ops->solve          = MatSolve_SeqBAIJ_1_NaturalOrdering;
477     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1_NaturalOrdering;
478   } else {
479     C->ops->solve          = MatSolve_SeqBAIJ_1;
480     C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_1;
481   }
482   C->assembled = PETSC_TRUE;
483   ierr = PetscLogFlops(C->cmap->n);CHKERRQ(ierr);
484   PetscFunctionReturn(0);
485 }
486 
487 EXTERN_C_BEGIN
488 #undef __FUNCT__
489 #define __FUNCT__ "MatGetFactor_seqbaij_petsc"
490 PetscErrorCode MatGetFactor_seqbaij_petsc(Mat A,MatFactorType ftype,Mat *B)
491 {
492   PetscInt           n = A->rmap->n;
493   PetscErrorCode     ierr;
494 
495   PetscFunctionBegin;
496   ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr);
497   ierr = MatSetSizes(*B,n,n,n,n);CHKERRQ(ierr);
498   if (ftype == MAT_FACTOR_LU || ftype == MAT_FACTOR_ILU || ftype == MAT_FACTOR_ILUDT) {
499     ierr = MatSetType(*B,MATSEQBAIJ);CHKERRQ(ierr);
500     (*B)->ops->lufactorsymbolic  = MatLUFactorSymbolic_SeqBAIJ;
501     (*B)->ops->ilufactorsymbolic = MatILUFactorSymbolic_SeqBAIJ;
502     (*B)->ops->iludtfactor       = MatILUDTFactor_SeqBAIJ;
503   } else if (ftype == MAT_FACTOR_CHOLESKY || ftype == MAT_FACTOR_ICC) {
504     ierr = MatSetType(*B,MATSEQSBAIJ);CHKERRQ(ierr);
505     ierr = MatSeqSBAIJSetPreallocation(*B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
506     (*B)->ops->iccfactorsymbolic      = MatICCFactorSymbolic_SeqBAIJ;
507     (*B)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqBAIJ;
508   } else SETERRQ(PETSC_ERR_SUP,"Factor type not supported");
509   (*B)->factor = ftype;
510   PetscFunctionReturn(0);
511 }
512 EXTERN_C_END
513 
514 EXTERN_C_BEGIN
515 #undef __FUNCT__
516 #define __FUNCT__ "MatGetFactorAvailable_seqaij_petsc"
517 PetscErrorCode MatGetFactorAvailable_seqbaij_petsc(Mat A,MatFactorType ftype,PetscTruth *flg)
518 {
519   PetscFunctionBegin;
520   *flg = PETSC_TRUE;
521   PetscFunctionReturn(0);
522 }
523 EXTERN_C_END
524 
525 /* ----------------------------------------------------------- */
526 #undef __FUNCT__
527 #define __FUNCT__ "MatLUFactor_SeqBAIJ"
528 PetscErrorCode MatLUFactor_SeqBAIJ(Mat A,IS row,IS col,const MatFactorInfo *info)
529 {
530   PetscErrorCode ierr;
531   Mat            C;
532 
533   PetscFunctionBegin;
534   ierr = MatGetFactor(A,MAT_SOLVER_PETSC,MAT_FACTOR_LU,&C);CHKERRQ(ierr);
535   ierr = MatLUFactorSymbolic(C,A,row,col,info);CHKERRQ(ierr);
536   ierr = MatLUFactorNumeric(C,A,info);CHKERRQ(ierr);
537   A->ops->solve            = C->ops->solve;
538   A->ops->solvetranspose   = C->ops->solvetranspose;
539   ierr = MatHeaderCopy(A,C);CHKERRQ(ierr);
540   ierr = PetscLogObjectParent(A,((Mat_SeqBAIJ*)(A->data))->icol);CHKERRQ(ierr);
541   PetscFunctionReturn(0);
542 }
543 
544 #include "../src/mat/impls/sbaij/seq/sbaij.h"
545 #undef __FUNCT__
546 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N"
547 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N(Mat C,Mat A,const MatFactorInfo *info)
548 {
549   PetscErrorCode ierr;
550   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
551   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
552   IS             ip=b->row;
553   const PetscInt *rip;
554   PetscInt       i,j,mbs=a->mbs,bs=A->rmap->bs,*bi=b->i,*bj=b->j,*bcol;
555   PetscInt       *ai=a->i,*aj=a->j;
556   PetscInt       k,jmin,jmax,*jl,*il,col,nexti,ili,nz;
557   MatScalar      *rtmp,*ba=b->a,*bval,*aa=a->a,dk,uikdi;
558   PetscReal      zeropivot,rs,shiftnz;
559   PetscReal      shiftpd;
560   ChShift_Ctx    sctx;
561   PetscInt       newshift;
562 
563   PetscFunctionBegin;
564   if (bs > 1) {
565     if (!a->sbaijMat){
566       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
567     }
568     ierr = (a->sbaijMat)->ops->choleskyfactornumeric(C,a->sbaijMat,info);CHKERRQ(ierr);
569     ierr = MatDestroy(a->sbaijMat);CHKERRQ(ierr);
570     a->sbaijMat = PETSC_NULL;
571     PetscFunctionReturn(0);
572   }
573 
574   /* initialization */
575   shiftnz   = info->shiftnz;
576   shiftpd   = info->shiftpd;
577   zeropivot = info->zeropivot;
578 
579   ierr  = ISGetIndices(ip,&rip);CHKERRQ(ierr);
580   nz   = (2*mbs+1)*sizeof(PetscInt)+mbs*sizeof(MatScalar);
581   ierr = PetscMalloc(nz,&il);CHKERRQ(ierr);
582   jl   = il + mbs;
583   rtmp = (MatScalar*)(jl + mbs);
584 
585   sctx.shift_amount = 0;
586   sctx.nshift       = 0;
587   do {
588     sctx.chshift = PETSC_FALSE;
589     for (i=0; i<mbs; i++) {
590       rtmp[i] = 0.0; jl[i] = mbs; il[0] = 0;
591     }
592 
593     for (k = 0; k<mbs; k++){
594       bval = ba + bi[k];
595       /* initialize k-th row by the perm[k]-th row of A */
596       jmin = ai[rip[k]]; jmax = ai[rip[k]+1];
597       for (j = jmin; j < jmax; j++){
598         col = rip[aj[j]];
599         if (col >= k){ /* only take upper triangular entry */
600           rtmp[col] = aa[j];
601           *bval++  = 0.0; /* for in-place factorization */
602         }
603       }
604 
605       /* shift the diagonal of the matrix */
606       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
607 
608       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
609       dk = rtmp[k];
610       i = jl[k]; /* first row to be added to k_th row  */
611 
612       while (i < k){
613         nexti = jl[i]; /* next row to be added to k_th row */
614 
615         /* compute multiplier, update diag(k) and U(i,k) */
616         ili = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
617         uikdi = - ba[ili]*ba[bi[i]];  /* diagonal(k) */
618         dk += uikdi*ba[ili];
619         ba[ili] = uikdi; /* -U(i,k) */
620 
621         /* add multiple of row i to k-th row */
622         jmin = ili + 1; jmax = bi[i+1];
623         if (jmin < jmax){
624           for (j=jmin; j<jmax; j++) rtmp[bj[j]] += uikdi*ba[j];
625           /* update il and jl for row i */
626           il[i] = jmin;
627           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
628         }
629         i = nexti;
630       }
631 
632       /* shift the diagonals when zero pivot is detected */
633       /* compute rs=sum of abs(off-diagonal) */
634       rs   = 0.0;
635       jmin = bi[k]+1;
636       nz   = bi[k+1] - jmin;
637       if (nz){
638         bcol = bj + jmin;
639         while (nz--){
640           rs += PetscAbsScalar(rtmp[*bcol]);
641           bcol++;
642         }
643       }
644 
645       sctx.rs = rs;
646       sctx.pv = dk;
647       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
648       if (newshift == 1) break;
649 
650       /* copy data into U(k,:) */
651       ba[bi[k]] = 1.0/dk; /* U(k,k) */
652       jmin = bi[k]+1; jmax = bi[k+1];
653       if (jmin < jmax) {
654         for (j=jmin; j<jmax; j++){
655           col = bj[j]; ba[j] = rtmp[col]; rtmp[col] = 0.0;
656         }
657         /* add the k-th row into il and jl */
658         il[k] = jmin;
659         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
660       }
661     }
662   } while (sctx.chshift);
663   ierr = PetscFree(il);CHKERRQ(ierr);
664 
665   ierr = ISRestoreIndices(ip,&rip);CHKERRQ(ierr);
666   C->assembled    = PETSC_TRUE;
667   C->preallocated = PETSC_TRUE;
668   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
669   if (sctx.nshift){
670     if (shiftpd) {
671       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
672     } else if (shiftnz) {
673       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
674     }
675   }
676   PetscFunctionReturn(0);
677 }
678 
679 #undef __FUNCT__
680 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering"
681 PetscErrorCode MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering(Mat C,Mat A,const MatFactorInfo *info)
682 {
683   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
684   Mat_SeqSBAIJ   *b=(Mat_SeqSBAIJ*)C->data;
685   PetscErrorCode ierr;
686   PetscInt       i,j,am=a->mbs;
687   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
688   PetscInt       k,jmin,*jl,*il,nexti,ili,*acol,*bcol,nz;
689   MatScalar      *rtmp,*ba=b->a,*aa=a->a,dk,uikdi,*aval,*bval;
690   PetscReal      zeropivot,rs,shiftnz;
691   PetscReal      shiftpd;
692   ChShift_Ctx    sctx;
693   PetscInt       newshift;
694 
695   PetscFunctionBegin;
696   /* initialization */
697   shiftnz   = info->shiftnz;
698   shiftpd   = info->shiftpd;
699   zeropivot = info->zeropivot;
700 
701   nz   = (2*am+1)*sizeof(PetscInt)+am*sizeof(MatScalar);
702   ierr = PetscMalloc(nz,&il);CHKERRQ(ierr);
703   jl   = il + am;
704   rtmp = (MatScalar*)(jl + am);
705 
706   sctx.shift_amount = 0;
707   sctx.nshift       = 0;
708   do {
709     sctx.chshift = PETSC_FALSE;
710     for (i=0; i<am; i++) {
711       rtmp[i] = 0.0; jl[i] = am; il[0] = 0;
712     }
713 
714     for (k = 0; k<am; k++){
715     /* initialize k-th row with elements nonzero in row perm(k) of A */
716       nz   = ai[k+1] - ai[k];
717       acol = aj + ai[k];
718       aval = aa + ai[k];
719       bval = ba + bi[k];
720       while (nz -- ){
721         if (*acol < k) { /* skip lower triangular entries */
722           acol++; aval++;
723         } else {
724           rtmp[*acol++] = *aval++;
725           *bval++       = 0.0; /* for in-place factorization */
726         }
727       }
728 
729       /* shift the diagonal of the matrix */
730       if (sctx.nshift) rtmp[k] += sctx.shift_amount;
731 
732       /* modify k-th row by adding in those rows i with U(i,k)!=0 */
733       dk = rtmp[k];
734       i  = jl[k]; /* first row to be added to k_th row  */
735 
736       while (i < k){
737         nexti = jl[i]; /* next row to be added to k_th row */
738         /* compute multiplier, update D(k) and U(i,k) */
739         ili   = il[i];  /* index of first nonzero element in U(i,k:bms-1) */
740         uikdi = - ba[ili]*ba[bi[i]];
741         dk   += uikdi*ba[ili];
742         ba[ili] = uikdi; /* -U(i,k) */
743 
744         /* add multiple of row i to k-th row ... */
745         jmin = ili + 1;
746         nz   = bi[i+1] - jmin;
747         if (nz > 0){
748           bcol = bj + jmin;
749           bval = ba + jmin;
750           while (nz --) rtmp[*bcol++] += uikdi*(*bval++);
751           /* update il and jl for i-th row */
752           il[i] = jmin;
753           j = bj[jmin]; jl[i] = jl[j]; jl[j] = i;
754         }
755         i = nexti;
756       }
757 
758       /* shift the diagonals when zero pivot is detected */
759       /* compute rs=sum of abs(off-diagonal) */
760       rs   = 0.0;
761       jmin = bi[k]+1;
762       nz   = bi[k+1] - jmin;
763       if (nz){
764         bcol = bj + jmin;
765         while (nz--){
766           rs += PetscAbsScalar(rtmp[*bcol]);
767           bcol++;
768         }
769       }
770 
771       sctx.rs = rs;
772       sctx.pv = dk;
773       ierr = MatCholeskyCheckShift_inline(info,sctx,k,newshift);CHKERRQ(ierr);
774       if (newshift == 1) break;    /* sctx.shift_amount is updated */
775 
776       /* copy data into U(k,:) */
777       ba[bi[k]] = 1.0/dk;
778       jmin      = bi[k]+1;
779       nz        = bi[k+1] - jmin;
780       if (nz){
781         bcol = bj + jmin;
782         bval = ba + jmin;
783         while (nz--){
784           *bval++       = rtmp[*bcol];
785           rtmp[*bcol++] = 0.0;
786         }
787         /* add k-th row into il and jl */
788         il[k] = jmin;
789         i = bj[jmin]; jl[k] = jl[i]; jl[i] = k;
790       }
791     }
792   } while (sctx.chshift);
793   ierr = PetscFree(il);CHKERRQ(ierr);
794 
795   C->ops->solve                 = MatSolve_SeqSBAIJ_1_NaturalOrdering;
796   C->ops->solvetranspose        = MatSolve_SeqSBAIJ_1_NaturalOrdering;
797   C->assembled    = PETSC_TRUE;
798   C->preallocated = PETSC_TRUE;
799   ierr = PetscLogFlops(C->rmap->N);CHKERRQ(ierr);
800     if (sctx.nshift){
801     if (shiftnz) {
802       ierr = PetscInfo2(A,"number of shiftnz tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
803     } else if (shiftpd) {
804       ierr = PetscInfo2(A,"number of shiftpd tries %D, shift_amount %G\n",sctx.nshift,sctx.shift_amount);CHKERRQ(ierr);
805     }
806   }
807   PetscFunctionReturn(0);
808 }
809 
810 #include "petscbt.h"
811 #include "../src/mat/utils/freespace.h"
812 #undef __FUNCT__
813 #define __FUNCT__ "MatICCFactorSymbolic_SeqBAIJ"
814 PetscErrorCode MatICCFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
815 {
816   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
817   Mat_SeqSBAIJ       *b;
818   Mat                B;
819   PetscErrorCode     ierr;
820   PetscTruth         perm_identity;
821   PetscInt           reallocs=0,i,*ai=a->i,*aj=a->j,am=a->mbs,bs=A->rmap->bs,*ui;
822   const PetscInt     *rip;
823   PetscInt           jmin,jmax,nzk,k,j,*jl,prow,*il,nextprow;
824   PetscInt           nlnk,*lnk,*lnk_lvl=PETSC_NULL,ncols,ncols_upper,*cols,*cols_lvl,*uj,**uj_ptr,**uj_lvl_ptr;
825   PetscReal          fill=info->fill,levels=info->levels;
826   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
827   PetscFreeSpaceList free_space_lvl=PETSC_NULL,current_space_lvl=PETSC_NULL;
828   PetscBT            lnkbt;
829 
830   PetscFunctionBegin;
831   if (bs > 1){
832     if (!a->sbaijMat){
833       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
834     }
835     (fact)->ops->iccfactorsymbolic = MatICCFactorSymbolic_SeqSBAIJ;  /* undue the change made in MatGetFactor_seqbaij_petsc */
836     ierr = MatICCFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
837     PetscFunctionReturn(0);
838   }
839 
840   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
841   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
842 
843   /* special case that simply copies fill pattern */
844   if (!levels && perm_identity) {
845     ierr = MatMarkDiagonal_SeqBAIJ(A);CHKERRQ(ierr);
846     ierr = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
847     for (i=0; i<am; i++) {
848       ui[i] = ai[i+1] - a->diag[i]; /* ui: rowlengths - changes when !perm_identity */
849     }
850     B = fact;
851     ierr = MatSeqSBAIJSetPreallocation(B,1,0,ui);CHKERRQ(ierr);
852 
853 
854     b  = (Mat_SeqSBAIJ*)B->data;
855     uj = b->j;
856     for (i=0; i<am; i++) {
857       aj = a->j + a->diag[i];
858       for (j=0; j<ui[i]; j++){
859         *uj++ = *aj++;
860       }
861       b->ilen[i] = ui[i];
862     }
863     ierr = PetscFree(ui);CHKERRQ(ierr);
864     B->factor = MAT_FACTOR_NONE;
865     ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
866     ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
867     B->factor = MAT_FACTOR_ICC;
868 
869     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
870     PetscFunctionReturn(0);
871   }
872 
873   /* initialization */
874   ierr  = PetscMalloc((am+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
875   ui[0] = 0;
876   ierr  = PetscMalloc((2*am+1)*sizeof(PetscInt),&cols_lvl);CHKERRQ(ierr);
877 
878   /* jl: linked list for storing indices of the pivot rows
879      il: il[i] points to the 1st nonzero entry of U(i,k:am-1) */
880   ierr = PetscMalloc((2*am+1)*sizeof(PetscInt)+2*am*sizeof(PetscInt*),&jl);CHKERRQ(ierr);
881   il         = jl + am;
882   uj_ptr     = (PetscInt**)(il + am);
883   uj_lvl_ptr = (PetscInt**)(uj_ptr + am);
884   for (i=0; i<am; i++){
885     jl[i] = am; il[i] = 0;
886   }
887 
888   /* create and initialize a linked list for storing column indices of the active row k */
889   nlnk = am + 1;
890   ierr = PetscIncompleteLLCreate(am,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
891 
892   /* initial FreeSpace size is fill*(ai[am]+1) */
893   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space);CHKERRQ(ierr);
894   current_space = free_space;
895   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+1)),&free_space_lvl);CHKERRQ(ierr);
896   current_space_lvl = free_space_lvl;
897 
898   for (k=0; k<am; k++){  /* for each active row k */
899     /* initialize lnk by the column indices of row rip[k] of A */
900     nzk   = 0;
901     ncols = ai[rip[k]+1] - ai[rip[k]];
902     ncols_upper = 0;
903     cols        = cols_lvl + am;
904     for (j=0; j<ncols; j++){
905       i = rip[*(aj + ai[rip[k]] + j)];
906       if (i >= k){ /* only take upper triangular entry */
907         cols[ncols_upper] = i;
908         cols_lvl[ncols_upper] = -1;  /* initialize level for nonzero entries */
909         ncols_upper++;
910       }
911     }
912     ierr = PetscIncompleteLLAdd(ncols_upper,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
913     nzk += nlnk;
914 
915     /* update lnk by computing fill-in for each pivot row to be merged in */
916     prow = jl[k]; /* 1st pivot row */
917 
918     while (prow < k){
919       nextprow = jl[prow];
920 
921       /* merge prow into k-th row */
922       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:am-1) */
923       jmax = ui[prow+1];
924       ncols = jmax-jmin;
925       i     = jmin - ui[prow];
926       cols = uj_ptr[prow] + i; /* points to the 2nd nzero entry in U(prow,k:am-1) */
927       for (j=0; j<ncols; j++) cols_lvl[j] = *(uj_lvl_ptr[prow] + i + j);
928       ierr = PetscIncompleteLLAddSorted(ncols,cols,levels,cols_lvl,am,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
929       nzk += nlnk;
930 
931       /* update il and jl for prow */
932       if (jmin < jmax){
933         il[prow] = jmin;
934         j = *cols; jl[prow] = jl[j]; jl[j] = prow;
935       }
936       prow = nextprow;
937     }
938 
939     /* if free space is not available, make more free space */
940     if (current_space->local_remaining<nzk) {
941       i = am - k + 1; /* num of unfactored rows */
942       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
943       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
944       ierr = PetscFreeSpaceGet(i,&current_space_lvl);CHKERRQ(ierr);
945       reallocs++;
946     }
947 
948     /* copy data into free_space and free_space_lvl, then initialize lnk */
949     ierr = PetscIncompleteLLClean(am,am,nzk,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr);
950 
951     /* add the k-th row into il and jl */
952     if (nzk-1 > 0){
953       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:am-1) */
954       jl[k] = jl[i]; jl[i] = k;
955       il[k] = ui[k] + 1;
956     }
957     uj_ptr[k]     = current_space->array;
958     uj_lvl_ptr[k] = current_space_lvl->array;
959 
960     current_space->array           += nzk;
961     current_space->local_used      += nzk;
962     current_space->local_remaining -= nzk;
963 
964     current_space_lvl->array           += nzk;
965     current_space_lvl->local_used      += nzk;
966     current_space_lvl->local_remaining -= nzk;
967 
968     ui[k+1] = ui[k] + nzk;
969   }
970 
971 #if defined(PETSC_USE_INFO)
972   if (ai[am] != 0) {
973     PetscReal af = ((PetscReal)(2*ui[am]-am))/((PetscReal)ai[am]);
974     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
975     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
976     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
977   } else {
978     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
979   }
980 #endif
981 
982   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
983   ierr = PetscFree(jl);CHKERRQ(ierr);
984   ierr = PetscFree(cols_lvl);CHKERRQ(ierr);
985 
986   /* destroy list of free space and other temporary array(s) */
987   ierr = PetscMalloc((ui[am]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
988   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
989   ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
990   ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr);
991 
992   /* put together the new matrix in MATSEQSBAIJ format */
993   B = fact;
994   ierr = MatSeqSBAIJSetPreallocation(B,1,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
995 
996   b = (Mat_SeqSBAIJ*)B->data;
997   b->singlemalloc = PETSC_FALSE;
998   b->free_a       = PETSC_TRUE;
999   b->free_ij       = PETSC_TRUE;
1000   ierr = PetscMalloc((ui[am]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
1001   b->j    = uj;
1002   b->i    = ui;
1003   b->diag = 0;
1004   b->ilen = 0;
1005   b->imax = 0;
1006   b->row  = perm;
1007   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
1008   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1009   b->icol = perm;
1010   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1011   ierr    = PetscMalloc((am+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1012   ierr    = PetscLogObjectMemory(B,(ui[am]-am)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1013   b->maxnz = b->nz = ui[am];
1014 
1015   B->info.factor_mallocs    = reallocs;
1016   B->info.fill_ratio_given  = fill;
1017   if (ai[am] != 0) {
1018     B->info.fill_ratio_needed = ((PetscReal)ui[am])/((PetscReal)ai[am]);
1019   } else {
1020     B->info.fill_ratio_needed = 0.0;
1021   }
1022   if (perm_identity){
1023     B->ops->solve           = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1024     B->ops->solvetranspose  = MatSolve_SeqSBAIJ_1_NaturalOrdering;
1025     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1026   } else {
1027     (fact)->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1028   }
1029   PetscFunctionReturn(0);
1030 }
1031 
1032 #undef __FUNCT__
1033 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqBAIJ"
1034 PetscErrorCode MatCholeskyFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS perm,const MatFactorInfo *info)
1035 {
1036   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data;
1037   Mat_SeqSBAIJ       *b;
1038   Mat                B;
1039   PetscErrorCode     ierr;
1040   PetscTruth         perm_identity;
1041   PetscReal          fill = info->fill;
1042   const PetscInt     *rip;
1043   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,*ai=a->i,*aj=a->j,reallocs=0,prow;
1044   PetscInt           *jl,jmin,jmax,nzk,*ui,k,j,*il,nextprow;
1045   PetscInt           nlnk,*lnk,ncols,ncols_upper,*cols,*uj,**ui_ptr,*uj_ptr;
1046   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
1047   PetscBT            lnkbt;
1048 
1049   PetscFunctionBegin;
1050   if (bs > 1) { /* convert to seqsbaij */
1051     if (!a->sbaijMat){
1052       ierr = MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&a->sbaijMat);CHKERRQ(ierr);
1053     }
1054     (fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqSBAIJ; /* undue the change made in MatGetFactor_seqbaij_petsc */
1055     ierr = MatCholeskyFactorSymbolic(fact,a->sbaijMat,perm,info);CHKERRQ(ierr);
1056     PetscFunctionReturn(0);
1057   }
1058 
1059   /* check whether perm is the identity mapping */
1060   ierr = ISIdentity(perm,&perm_identity);CHKERRQ(ierr);
1061   if (!perm_identity) SETERRQ(PETSC_ERR_SUP,"Matrix reordering is not supported");
1062   ierr = ISGetIndices(perm,&rip);CHKERRQ(ierr);
1063 
1064   /* initialization */
1065   ierr  = PetscMalloc((mbs+1)*sizeof(PetscInt),&ui);CHKERRQ(ierr);
1066   ui[0] = 0;
1067 
1068   /* jl: linked list for storing indices of the pivot rows
1069      il: il[i] points to the 1st nonzero entry of U(i,k:mbs-1) */
1070   ierr = PetscMalloc((3*mbs+1)*sizeof(PetscInt)+mbs*sizeof(PetscInt*),&jl);CHKERRQ(ierr);
1071   il     = jl + mbs;
1072   cols   = il + mbs;
1073   ui_ptr = (PetscInt**)(cols + mbs);
1074   for (i=0; i<mbs; i++){
1075     jl[i] = mbs; il[i] = 0;
1076   }
1077 
1078   /* create and initialize a linked list for storing column indices of the active row k */
1079   nlnk = mbs + 1;
1080   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1081 
1082   /* initial FreeSpace size is fill*(ai[mbs]+1) */
1083   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[mbs]+1)),&free_space);CHKERRQ(ierr);
1084   current_space = free_space;
1085 
1086   for (k=0; k<mbs; k++){  /* for each active row k */
1087     /* initialize lnk by the column indices of row rip[k] of A */
1088     nzk   = 0;
1089     ncols = ai[rip[k]+1] - ai[rip[k]];
1090     ncols_upper = 0;
1091     for (j=0; j<ncols; j++){
1092       i = rip[*(aj + ai[rip[k]] + j)];
1093       if (i >= k){ /* only take upper triangular entry */
1094         cols[ncols_upper] = i;
1095         ncols_upper++;
1096       }
1097     }
1098     ierr = PetscLLAdd(ncols_upper,cols,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1099     nzk += nlnk;
1100 
1101     /* update lnk by computing fill-in for each pivot row to be merged in */
1102     prow = jl[k]; /* 1st pivot row */
1103 
1104     while (prow < k){
1105       nextprow = jl[prow];
1106       /* merge prow into k-th row */
1107       jmin = il[prow] + 1;  /* index of the 2nd nzero entry in U(prow,k:mbs-1) */
1108       jmax = ui[prow+1];
1109       ncols = jmax-jmin;
1110       uj_ptr = ui_ptr[prow] + jmin - ui[prow]; /* points to the 2nd nzero entry in U(prow,k:mbs-1) */
1111       ierr = PetscLLAddSorted(ncols,uj_ptr,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1112       nzk += nlnk;
1113 
1114       /* update il and jl for prow */
1115       if (jmin < jmax){
1116         il[prow] = jmin;
1117         j = *uj_ptr; jl[prow] = jl[j]; jl[j] = prow;
1118       }
1119       prow = nextprow;
1120     }
1121 
1122     /* if free space is not available, make more free space */
1123     if (current_space->local_remaining<nzk) {
1124       i = mbs - k + 1; /* num of unfactored rows */
1125       i = PetscMin(i*nzk, i*(i-1)); /* i*nzk, i*(i-1): estimated and max additional space needed */
1126       ierr = PetscFreeSpaceGet(i,&current_space);CHKERRQ(ierr);
1127       reallocs++;
1128     }
1129 
1130     /* copy data into free space, then initialize lnk */
1131     ierr = PetscLLClean(mbs,mbs,nzk,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
1132 
1133     /* add the k-th row into il and jl */
1134     if (nzk-1 > 0){
1135       i = current_space->array[1]; /* col value of the first nonzero element in U(k, k+1:mbs-1) */
1136       jl[k] = jl[i]; jl[i] = k;
1137       il[k] = ui[k] + 1;
1138     }
1139     ui_ptr[k] = current_space->array;
1140     current_space->array           += nzk;
1141     current_space->local_used      += nzk;
1142     current_space->local_remaining -= nzk;
1143 
1144     ui[k+1] = ui[k] + nzk;
1145   }
1146 
1147 #if defined(PETSC_USE_INFO)
1148   if (ai[mbs] != 0) {
1149     PetscReal af = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
1150     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %G needed %G\n",reallocs,fill,af);CHKERRQ(ierr);
1151     ierr = PetscInfo1(A,"Run with -pc_factor_fill %G or use \n",af);CHKERRQ(ierr);
1152     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%G) for best performance.\n",af);CHKERRQ(ierr);
1153   } else {
1154     ierr = PetscInfo(A,"Empty matrix.\n");CHKERRQ(ierr);
1155   }
1156 #endif
1157 
1158   ierr = ISRestoreIndices(perm,&rip);CHKERRQ(ierr);
1159   ierr = PetscFree(jl);CHKERRQ(ierr);
1160 
1161   /* destroy list of free space and other temporary array(s) */
1162   ierr = PetscMalloc((ui[mbs]+1)*sizeof(PetscInt),&uj);CHKERRQ(ierr);
1163   ierr = PetscFreeSpaceContiguous(&free_space,uj);CHKERRQ(ierr);
1164   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1165 
1166   /* put together the new matrix in MATSEQSBAIJ format */
1167   B    = fact;
1168   ierr = MatSeqSBAIJSetPreallocation(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1169 
1170   b = (Mat_SeqSBAIJ*)B->data;
1171   b->singlemalloc = PETSC_FALSE;
1172   b->free_a       = PETSC_TRUE;
1173   b->free_ij      = PETSC_TRUE;
1174   ierr = PetscMalloc((ui[mbs]+1)*sizeof(MatScalar),&b->a);CHKERRQ(ierr);
1175   b->j    = uj;
1176   b->i    = ui;
1177   b->diag = 0;
1178   b->ilen = 0;
1179   b->imax = 0;
1180   b->row  = perm;
1181   b->pivotinblocks = PETSC_FALSE; /* need to get from MatFactorInfo */
1182   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1183   b->icol = perm;
1184   ierr    = PetscObjectReference((PetscObject)perm);CHKERRQ(ierr);
1185   ierr    = PetscMalloc((mbs+1)*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1186   ierr    = PetscLogObjectMemory(B,(ui[mbs]-mbs)*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1187   b->maxnz = b->nz = ui[mbs];
1188 
1189   B->info.factor_mallocs    = reallocs;
1190   B->info.fill_ratio_given  = fill;
1191   if (ai[mbs] != 0) {
1192     B->info.fill_ratio_needed = ((PetscReal)ui[mbs])/((PetscReal)ai[mbs]);
1193   } else {
1194     B->info.fill_ratio_needed = 0.0;
1195   }
1196   if (perm_identity){
1197     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N_NaturalOrdering;
1198   } else {
1199     B->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqBAIJ_N;
1200   }
1201   PetscFunctionReturn(0);
1202 }
1203 
1204 /* --------------------------------------------------------- */
1205 #undef __FUNCT__
1206 #define __FUNCT__ "MatSolve_SeqBAIJ_N_NaturalOrdering_newdatastruct"
1207 PetscErrorCode MatSolve_SeqBAIJ_N_NaturalOrdering_newdatastruct(Mat A,Vec bb,Vec xx)
1208 {
1209   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1210   PetscErrorCode ierr;
1211   const PetscInt *ai=a->i,*aj=a->j,*vi;
1212   PetscInt       i,k,n=a->mbs;
1213   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2,*adiag=a->diag;
1214   MatScalar      *aa=a->a,*v;
1215   PetscScalar    *x,*b,*s,*t,*ls;
1216 
1217   PetscFunctionBegin;
1218   /* printf("MatSolve_SeqBAIJ_NaturalOrdering_iludt..bs %d\n",bs); */
1219   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1220   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1221   t  = a->solve_work;
1222 
1223   /* forward solve the lower triangular */
1224   ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy 1st block of b to t */
1225 
1226   for (i=1; i<n; i++) {
1227     v   = aa + bs2*ai[i];
1228     vi  = aj + ai[i];
1229     nz = ai[i+1] - ai[i];
1230     s = t + bs*i;
1231     ierr = PetscMemcpy(s,b+bs*i,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy i_th block of b to t */
1232     for(k=0;k<nz;k++){
1233       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[k]);
1234       v += bs2;
1235     }
1236   }
1237 
1238   /* backward solve the upper triangular */
1239   ls = a->solve_work + A->cmap->n;
1240   for (i=n-1; i>=0; i--){
1241     v  = aa + bs2*ai[2*n-i];
1242     vi = aj + ai[2*n-i];
1243     nz = ai[2*n-i +1] - ai[2*n-i]-1;
1244     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1245     for(k=0;k<nz;k++){
1246       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[k]);
1247       v += bs2;
1248     }
1249     Kernel_w_gets_A_times_v(bs,ls,aa+bs2*adiag[i],t+i*bs); /* *inv(diagonal[i]) */
1250     ierr = PetscMemcpy(x+i*bs,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1251   }
1252 
1253   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1254   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1255   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1256   PetscFunctionReturn(0);
1257 }
1258 
1259 #undef __FUNCT__
1260 #define __FUNCT__ "MatSolve_SeqBAIJ_N_NaturalOrdering_newdatastruct_v2"
1261 PetscErrorCode MatSolve_SeqBAIJ_N_NaturalOrdering_newdatastruct_v2(Mat A,Vec bb,Vec xx)
1262 {
1263   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1264   PetscErrorCode ierr;
1265   const PetscInt *ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1266   PetscInt       i,k,n=a->mbs;
1267   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1268   MatScalar      *aa=a->a,*v;
1269   PetscScalar    *x,*b,*s,*t,*ls;
1270 
1271   PetscFunctionBegin;
1272   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1273   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1274   t  = a->solve_work;
1275 
1276   /* forward solve the lower triangular */
1277   ierr = PetscMemcpy(t,b,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy 1st block of b to t */
1278 
1279   for (i=1; i<n; i++) {
1280     v   = aa + bs2*ai[i];
1281     vi  = aj + ai[i];
1282     nz = ai[i+1] - ai[i];
1283     s = t + bs*i;
1284     ierr = PetscMemcpy(s,b+bs*i,bs*sizeof(PetscScalar));CHKERRQ(ierr); /* copy i_th block of b to t */
1285     for(k=0;k<nz;k++){
1286       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[k]);
1287       v += bs2;
1288     }
1289   }
1290 
1291   /* backward solve the upper triangular */
1292   ls = a->solve_work + A->cmap->n;
1293   for (i=n-1; i>=0; i--){
1294     v  = aa + bs2*(adiag[i+1]+1);
1295     vi = aj + adiag[i+1]+1;
1296     nz = adiag[i] - adiag[i+1]-1;
1297     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1298     for(k=0;k<nz;k++){
1299       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[k]);
1300       v += bs2;
1301     }
1302     Kernel_w_gets_A_times_v(bs,ls,aa+bs2*adiag[i],t+i*bs); /* *inv(diagonal[i]) */
1303     ierr = PetscMemcpy(x+i*bs,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1304   }
1305 
1306   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1307   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1308   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1309   PetscFunctionReturn(0);
1310 }
1311 
1312 #undef __FUNCT__
1313 #define __FUNCT__ "MatSolve_SeqBAIJ_N_newdatastruct"
1314 PetscErrorCode MatSolve_SeqBAIJ_N_newdatastruct(Mat A,Vec bb,Vec xx)
1315 {
1316   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1317   IS             iscol=a->col,isrow=a->row;
1318   PetscErrorCode ierr;
1319   const PetscInt *r,*c,*rout,*cout,*ai=a->i,*aj=a->j,*vi;
1320   PetscInt       i,m,n=a->mbs;
1321   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2,k;
1322   MatScalar      *aa=a->a,*v;
1323   PetscScalar    *x,*b,*s,*t,*ls;
1324 
1325   PetscFunctionBegin;
1326   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1327   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1328   t  = a->solve_work;
1329 
1330   ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout;
1331   ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout;
1332 
1333   /* forward solve the lower triangular */
1334   ierr = PetscMemcpy(t,b+bs*r[0],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1335   for (i=1; i<n; i++) {
1336     v   = aa + bs2*ai[i];
1337     vi  = aj + ai[i];
1338     nz = ai[i+1] - ai[i];
1339     s = t + bs*i;
1340     ierr = PetscMemcpy(s,b+bs*r[i],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1341     for(m=0;m<nz;m++){
1342       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[m]);
1343       v += bs2;
1344     }
1345   }
1346 
1347   /* backward solve the upper triangular */
1348   ls = a->solve_work + A->cmap->n;
1349   for (i=n-1; i>=0; i--){
1350     k  = 2*n-i;
1351     v  = aa + bs2*ai[k];
1352     vi = aj + ai[k];
1353     nz = ai[k+1] - ai[k] - 1;
1354     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1355     for(m=0;m<nz;m++){
1356       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[m]);
1357       v += bs2;
1358     }
1359     Kernel_w_gets_A_times_v(bs,ls,v,t+i*bs); /* *inv(diagonal[i]) */
1360     ierr = PetscMemcpy(x + bs*c[i],t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1361   }
1362   ierr = ISRestoreIndices(isrow,&rout);CHKERRQ(ierr);
1363   ierr = ISRestoreIndices(iscol,&cout);CHKERRQ(ierr);
1364   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1365   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1366   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1367   PetscFunctionReturn(0);
1368 }
1369 
1370 #undef __FUNCT__
1371 #define __FUNCT__ "MatSolve_SeqBAIJ_N_newdatastruct_v2"
1372 PetscErrorCode MatSolve_SeqBAIJ_N_newdatastruct_v2(Mat A,Vec bb,Vec xx)
1373 {
1374   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ *)A->data;
1375   IS             iscol=a->col,isrow=a->row;
1376   PetscErrorCode ierr;
1377   const PetscInt *r,*c,*rout,*cout,*ai=a->i,*aj=a->j,*adiag=a->diag,*vi;
1378   PetscInt       i,m,n=a->mbs;
1379   PetscInt       nz,bs=A->rmap->bs,bs2=a->bs2;
1380   MatScalar      *aa=a->a,*v;
1381   PetscScalar    *x,*b,*s,*t,*ls;
1382 
1383   PetscFunctionBegin;
1384   ierr = VecGetArray(bb,&b);CHKERRQ(ierr);
1385   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
1386   t  = a->solve_work;
1387 
1388   ierr = ISGetIndices(isrow,&rout);CHKERRQ(ierr); r = rout;
1389   ierr = ISGetIndices(iscol,&cout);CHKERRQ(ierr); c = cout;
1390 
1391   /* forward solve the lower triangular */
1392   ierr = PetscMemcpy(t,b+bs*r[0],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1393   for (i=1; i<n; i++) {
1394     v   = aa + bs2*ai[i];
1395     vi  = aj + ai[i];
1396     nz = ai[i+1] - ai[i];
1397     s = t + bs*i;
1398     ierr = PetscMemcpy(s,b+bs*r[i],bs*sizeof(PetscScalar));CHKERRQ(ierr);
1399     for(m=0;m<nz;m++){
1400       Kernel_v_gets_v_minus_A_times_w(bs,s,v,t+bs*vi[m]);
1401       v += bs2;
1402     }
1403   }
1404 
1405   /* backward solve the upper triangular */
1406   ls = a->solve_work + A->cmap->n;
1407   for (i=n-1; i>=0; i--){
1408     v  = aa + bs2*(adiag[i+1]+1);
1409     vi = aj + adiag[i+1]+1;
1410     nz = adiag[i] - adiag[i+1] - 1;
1411     ierr = PetscMemcpy(ls,t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1412     for(m=0;m<nz;m++){
1413       Kernel_v_gets_v_minus_A_times_w(bs,ls,v,t+bs*vi[m]);
1414       v += bs2;
1415     }
1416     Kernel_w_gets_A_times_v(bs,ls,v,t+i*bs); /* *inv(diagonal[i]) */
1417     ierr = PetscMemcpy(x + bs*c[i],t+i*bs,bs*sizeof(PetscScalar));CHKERRQ(ierr);
1418   }
1419   ierr = ISRestoreIndices(isrow,&rout);CHKERRQ(ierr);
1420   ierr = ISRestoreIndices(iscol,&cout);CHKERRQ(ierr);
1421   ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);
1422   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
1423   ierr = PetscLogFlops(2.0*(a->bs2)*(a->nz) - A->rmap->bs*A->cmap->n);CHKERRQ(ierr);
1424   PetscFunctionReturn(0);
1425 }
1426 
1427 #undef __FUNCT__
1428 #define __FUNCT__ "BlockAbs_privat"
1429 PetscErrorCode BlockAbs_private(PetscInt nbs,PetscInt bs2,PetscScalar *blockarray,PetscReal *absarray)
1430 {
1431   PetscErrorCode     ierr;
1432   PetscInt           i,j;
1433   PetscFunctionBegin;
1434   ierr = PetscMemzero(absarray,(nbs+1)*sizeof(PetscReal));CHKERRQ(ierr);
1435   for (i=0; i<nbs; i++){
1436     for (j=0; j<bs2; j++){
1437       if (absarray[i] < PetscAbsScalar(blockarray[i*nbs+j])) absarray[i] = PetscAbsScalar(blockarray[i*nbs+j]);
1438     }
1439   }
1440   PetscFunctionReturn(0);
1441 }
1442 
1443 #undef __FUNCT__
1444 #define __FUNCT__ "MatILUDTFactor_SeqBAIJ"
1445 PetscErrorCode MatILUDTFactor_SeqBAIJ(Mat A,IS isrow,IS iscol,const MatFactorInfo *info,Mat *fact)
1446 {
1447   Mat                B = *fact;
1448   Mat_SeqBAIJ        *a=(Mat_SeqBAIJ*)A->data,*b;
1449   IS                 isicol;
1450   PetscErrorCode     ierr;
1451   const PetscInt     *r,*ic;
1452   PetscInt           i,mbs=a->mbs,bs=A->rmap->bs,bs2=a->bs2,*ai=a->i,*aj=a->j,*ajtmp,*adiag;
1453   PetscInt           *bi,*bj,*bdiag;
1454 
1455   PetscInt           row,nzi,nzi_bl,nzi_bu,*im,dtcount,nzi_al,nzi_au;
1456   PetscInt           nlnk,*lnk;
1457   PetscBT            lnkbt;
1458   PetscTruth         row_identity,icol_identity,both_identity;
1459   MatScalar          *aatmp,*pv,*batmp,*ba,*rtmp,*pc,*multiplier,*vtmp;
1460   const PetscInt     *ics;
1461   PetscInt           j,nz,*pj,*bjtmp,k,ncut,*jtmp;
1462 
1463   PetscReal          dt=info->dt; /* shift=info->shiftinblocks; */
1464   PetscInt           nnz_max;
1465   PetscTruth         missing;
1466   PetscReal          *vtmp_abs;
1467   MatScalar          *v_work;
1468   PetscInt           *v_pivots;
1469 
1470   PetscFunctionBegin;
1471   /* ------- symbolic factorization, can be reused ---------*/
1472   ierr = MatMissingDiagonal(A,&missing,&i);CHKERRQ(ierr);
1473   if (missing) SETERRQ1(PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",i);
1474   adiag=a->diag;
1475 
1476   ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr);
1477 
1478   /* bdiag is location of diagonal in factor */
1479   ierr = PetscMalloc((mbs+1)*sizeof(PetscInt),&bdiag);CHKERRQ(ierr);
1480 
1481   /* allocate row pointers bi */
1482   ierr = PetscMalloc((2*mbs+2)*sizeof(PetscInt),&bi);CHKERRQ(ierr);
1483 
1484   /* allocate bj and ba; max num of nonzero entries is (ai[n]+2*n*dtcount+2) */
1485   dtcount = (PetscInt)info->dtcount;
1486   if (dtcount > mbs-1) dtcount = mbs-1;
1487   nnz_max  = ai[mbs]+2*mbs*dtcount +2;
1488   /* printf("MatILUDTFactor_SeqBAIJ, bs %d, ai[mbs] %d, nnz_max  %d, dtcount %d\n",bs,ai[mbs],nnz_max,dtcount); */
1489   ierr = PetscMalloc(nnz_max*sizeof(PetscInt),&bj);CHKERRQ(ierr);
1490   nnz_max = nnz_max*bs2;
1491   ierr = PetscMalloc(nnz_max*sizeof(MatScalar),&ba);CHKERRQ(ierr);
1492 
1493   /* put together the new matrix */
1494   ierr = MatSeqBAIJSetPreallocation_SeqBAIJ(B,bs,MAT_SKIP_ALLOCATION,PETSC_NULL);CHKERRQ(ierr);
1495   ierr = PetscLogObjectParent(B,isicol);CHKERRQ(ierr);
1496   b    = (Mat_SeqBAIJ*)(B)->data;
1497   b->free_a       = PETSC_TRUE;
1498   b->free_ij      = PETSC_TRUE;
1499   b->singlemalloc = PETSC_FALSE;
1500   b->a          = ba;
1501   b->j          = bj;
1502   b->i          = bi;
1503   b->diag       = bdiag;
1504   b->ilen       = 0;
1505   b->imax       = 0;
1506   b->row        = isrow;
1507   b->col        = iscol;
1508   ierr          = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
1509   ierr          = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
1510   b->icol       = isicol;
1511   ierr = PetscMalloc((bs*(mbs+1))*sizeof(PetscScalar),&b->solve_work);CHKERRQ(ierr);
1512 
1513   ierr = PetscLogObjectMemory(B,nnz_max*(sizeof(PetscInt)+sizeof(MatScalar)));CHKERRQ(ierr);
1514   b->maxnz = nnz_max/bs2;
1515 
1516   (B)->factor                = MAT_FACTOR_ILUDT;
1517   (B)->info.factor_mallocs   = 0;
1518   (B)->info.fill_ratio_given = ((PetscReal)nnz_max)/((PetscReal)(ai[mbs]*bs2));
1519   CHKMEMQ;
1520   /* ------- end of symbolic factorization ---------*/
1521   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
1522   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
1523   ics  = ic;
1524 
1525   /* linked list for storing column indices of the active row */
1526   nlnk = mbs + 1;
1527   ierr = PetscLLCreate(mbs,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1528 
1529   /* im: used by PetscLLAddSortedLU(); jtmp: working array for column indices of active row */
1530   ierr = PetscMalloc((2*mbs+1)*sizeof(PetscInt),&im);CHKERRQ(ierr);
1531   jtmp = im + mbs;
1532   /* rtmp, vtmp: working arrays for sparse and contiguous row entries of active row */
1533   ierr = PetscMalloc((2*mbs*bs2+1)*sizeof(MatScalar),&rtmp);CHKERRQ(ierr);
1534   vtmp = rtmp + bs2*mbs;
1535   ierr = PetscMalloc((mbs+1)*sizeof(PetscReal),&vtmp_abs);CHKERRQ(ierr);
1536 
1537   ierr       = PetscMalloc(bs*sizeof(PetscInt) + (bs+bs2)*sizeof(MatScalar),&v_work);CHKERRQ(ierr);
1538   multiplier = v_work + bs;
1539   v_pivots   = (PetscInt*)(multiplier + bs2);
1540 
1541   bi[0]    = 0;
1542   bdiag[0] = (nnz_max/bs2)-1; /* location of diagonal in factor B */
1543   bi[2*mbs+1] = bdiag[0]+1; /* endof bj and ba array */
1544   for (i=0; i<mbs; i++) {
1545     /* copy initial fill into linked list */
1546     nzi = 0; /* nonzeros for active row i */
1547     nzi = ai[r[i]+1] - ai[r[i]];
1548     if (!nzi) SETERRQ2(PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[i],i);
1549     nzi_al = adiag[r[i]] - ai[r[i]];
1550     nzi_au = ai[r[i]+1] - adiag[r[i]] -1;
1551     /* printf("row %d, nzi_al/au %d %d\n",i,nzi_al,nzi_au); */
1552 
1553     /* load in initial unfactored row */
1554     ajtmp = aj + ai[r[i]];
1555     ierr = PetscLLAddPerm(nzi,ajtmp,ic,mbs,nlnk,lnk,lnkbt);CHKERRQ(ierr);
1556     ierr = PetscMemzero(rtmp,(mbs*bs2+1)*sizeof(PetscScalar));CHKERRQ(ierr);
1557     aatmp = a->a + bs2*ai[r[i]];
1558     for (j=0; j<nzi; j++) {
1559       ierr = PetscMemcpy(rtmp+bs2*ic[ajtmp[j]],aatmp+bs2*j,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1560     }
1561 
1562     /* add pivot rows into linked list */
1563     row = lnk[mbs];
1564     while (row < i) {
1565       nzi_bl = bi[row+1] - bi[row] + 1;
1566       bjtmp = bj + bdiag[row+1]+1; /* points to 1st column next to the diagonal in U */
1567       ierr  = PetscLLAddSortedLU(bjtmp,row,nlnk,lnk,lnkbt,i,nzi_bl,im);CHKERRQ(ierr);
1568       nzi  += nlnk;
1569       row   = lnk[row];
1570     }
1571 
1572     /* copy data from lnk into jtmp, then initialize lnk */
1573     ierr = PetscLLClean(mbs,mbs,nzi,lnk,jtmp,lnkbt);CHKERRQ(ierr);
1574 
1575     /* numerical factorization */
1576     bjtmp = jtmp;
1577     row   = *bjtmp++; /* 1st pivot row */
1578 
1579     while  (row < i) {
1580       pc = rtmp + bs2*row;
1581       pv = ba + bs2*bdiag[row]; /* inv(diag) of the pivot row */
1582       Kernel_A_gets_A_times_B(bs,pc,pv,multiplier); /* pc= multiplier = pc*inv(diag[row]) */
1583       ierr = BlockAbs_private(1,bs2,pc,vtmp_abs);CHKERRQ(ierr);
1584       if (vtmp_abs[0] > dt){ /* apply tolerance dropping rule */
1585         pj         = bj + bdiag[row+1] + 1; /* point to 1st entry of U(row,:) */
1586         pv         = ba + bs2*(bdiag[row+1] + 1);
1587         nz         = bdiag[row] - bdiag[row+1] - 1; /* num of entries in U(row,:), excluding diagonal */
1588         for (j=0; j<nz; j++){
1589           Kernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j);
1590         }
1591         /* ierr = PetscLogFlops(bslog*(nz+1.0)-bs);CHKERRQ(ierr); */
1592       }
1593       row = *bjtmp++;
1594     }
1595 
1596     /* copy sparse rtmp into contiguous vtmp; separate L and U part */
1597     nzi_bl = 0; j = 0;
1598     while (jtmp[j] < i){ /* L-part. Note: jtmp is sorted */
1599       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1600       nzi_bl++; j++;
1601     }
1602     nzi_bu = nzi - nzi_bl -1;
1603     /* printf("nzi %d, nzi_bl %d, nzi_bu %d\n",nzi,nzi_bl,nzi_bu); */
1604 
1605     while (j < nzi){ /* U-part */
1606       ierr = PetscMemcpy(vtmp+bs2*j,rtmp+bs2*jtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1607       /*
1608       printf(" col %d: ",jtmp[j]);
1609       for (j1=0; j1<bs2; j1++) printf(" %g",*(vtmp+bs2*j+j1));
1610       printf(" \n");
1611       */
1612       j++;
1613     }
1614 
1615     ierr = BlockAbs_private(nzi,bs2,vtmp,vtmp_abs);CHKERRQ(ierr);
1616     /*
1617     printf(" row %d, nzi %d, vtmp_abs\n",i,nzi);
1618     for (j1=0; j1<nzi; j1++) printf(" (%d %g),",jtmp[j1],vtmp_abs[j1]);
1619     printf(" \n");
1620     */
1621     bjtmp = bj + bi[i];
1622     batmp = ba + bs2*bi[i];
1623     /* apply level dropping rule to L part */
1624     ncut = nzi_al + dtcount;
1625     if (ncut < nzi_bl){
1626       ierr = PetscSortSplitReal(ncut,nzi_bl,vtmp_abs,jtmp);CHKERRQ(ierr);
1627       ierr = PetscSortIntWithScalarArray(ncut,jtmp,vtmp);CHKERRQ(ierr);
1628     } else {
1629       ncut = nzi_bl;
1630     }
1631     for (j=0; j<ncut; j++){
1632       bjtmp[j] = jtmp[j];
1633       ierr = PetscMemcpy(batmp+bs2*j,rtmp+bs2*bjtmp[j],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1634       /*
1635       printf(" col %d: ",bjtmp[j]);
1636       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*j+j1));
1637       printf("\n");
1638       */
1639     }
1640     bi[i+1] = bi[i] + ncut;
1641     nzi = ncut + 1;
1642 
1643     /* apply level dropping rule to U part */
1644     ncut = nzi_au + dtcount;
1645     if (ncut < nzi_bu){
1646       ierr = PetscSortSplitReal(ncut,nzi_bu,vtmp_abs+nzi_bl+1,jtmp+nzi_bl+1);CHKERRQ(ierr);
1647       ierr = PetscSortIntWithScalarArray(ncut,jtmp+nzi_bl+1,vtmp+nzi_bl+1);CHKERRQ(ierr);
1648     } else {
1649       ncut = nzi_bu;
1650     }
1651     nzi += ncut;
1652 
1653     /* mark bdiagonal */
1654     bdiag[i+1]    = bdiag[i] - (ncut + 1);
1655     bi[2*mbs - i] = bi[2*mbs - i +1] - (ncut + 1);
1656 
1657     bjtmp = bj + bdiag[i];
1658     batmp = ba + bs2*bdiag[i];
1659     ierr = PetscMemcpy(batmp,rtmp+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr);
1660     *bjtmp = i;
1661     /*
1662     printf(" diag %d: ",*bjtmp);
1663     for (j=0; j<bs2; j++){
1664       printf(" %g,",batmp[j]);
1665     }
1666     printf("\n");
1667     */
1668     bjtmp = bj + bdiag[i+1]+1;
1669     batmp = ba + (bdiag[i+1]+1)*bs2;
1670 
1671     for (k=0; k<ncut; k++){
1672       bjtmp[k] = jtmp[nzi_bl+1+k];
1673       ierr = PetscMemcpy(batmp+bs2*k,rtmp+bs2*bjtmp[k],bs2*sizeof(MatScalar));CHKERRQ(ierr);
1674       /*
1675       printf(" col %d:",bjtmp[k]);
1676       for (j1=0; j1<bs2; j1++) printf(" %g,",*(batmp+bs2*k+j1));
1677       printf("\n");
1678       */
1679     }
1680 
1681     im[i] = nzi; /* used by PetscLLAddSortedLU() */
1682 
1683     /* invert diagonal block for simplier triangular solves - add shift??? */
1684     batmp = ba + bs2*bdiag[i];
1685     ierr = Kernel_A_gets_inverse_A(bs,batmp,v_pivots,v_work);CHKERRQ(ierr);
1686   } /* for (i=0; i<mbs; i++) */
1687 
1688   /* printf("end of L %d, beginning of U %d\n",bi[mbs],bdiag[mbs]); */
1689   if (bi[mbs] >= bdiag[mbs]) SETERRQ2(PETSC_ERR_ARG_SIZ,"end of L array %d cannot >= the beginning of U array %d",bi[mbs],bdiag[mbs]);
1690 
1691   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
1692   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
1693 
1694   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
1695 
1696   ierr = PetscFree(im);CHKERRQ(ierr);
1697   ierr = PetscFree(rtmp);CHKERRQ(ierr);
1698 
1699   ierr = PetscLogFlops(bs2*B->cmap->n);CHKERRQ(ierr);
1700   b->maxnz = b->nz = bi[mbs] + bdiag[0] - bdiag[mbs];
1701 
1702   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
1703   ierr = ISIdentity(isicol,&icol_identity);CHKERRQ(ierr);
1704   both_identity = (PetscTruth) (row_identity && icol_identity);
1705   if (row_identity && icol_identity) {
1706     B->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering_newdatastruct;
1707   } else {
1708     B->ops->solve = MatSolve_SeqBAIJ_N_newdatastruct;
1709   }
1710 
1711   B->ops->solveadd          = 0;
1712   B->ops->solvetranspose    = 0;
1713   B->ops->solvetransposeadd = 0;
1714   B->ops->matsolve          = 0;
1715   B->assembled              = PETSC_TRUE;
1716   B->preallocated           = PETSC_TRUE;
1717   PetscFunctionReturn(0);
1718 }
1719