xref: /petsc/src/mat/impls/baij/seq/baijfact2.c (revision 7d5fd1e4d9337468ad3f05b65b7facdcd2dfd2a4)
1 
2 /*
3     Factorization code for BAIJ format.
4 */
5 
6 #include <../src/mat/impls/baij/seq/baij.h>
7 #include <petsc/private/kernels/blockinvert.h>
8 #include <petscbt.h>
9 #include <../src/mat/utils/freespace.h>
10 
11 /* ----------------------------------------------------------------*/
12 extern PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat,Mat,MatDuplicateOption,PetscBool);
13 
14 /*
15    This is not much faster than MatLUFactorNumeric_SeqBAIJ_N() but the solve is faster at least sometimes
16 */
17 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_15_NaturalOrdering(Mat B,Mat A,const MatFactorInfo *info)
18 {
19   Mat             C =B;
20   Mat_SeqBAIJ     *a=(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)C->data;
21   PetscErrorCode  ierr;
22   PetscInt        i,j,k,ipvt[15];
23   const PetscInt  n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*ajtmp,*bjtmp,*bdiag=b->diag,*pj;
24   PetscInt        nz,nzL,row;
25   MatScalar       *rtmp,*pc,*mwork,*pv,*vv,work[225];
26   const MatScalar *v,*aa=a->a;
27   PetscInt        bs2 = a->bs2,bs=A->rmap->bs,flg;
28   PetscInt        sol_ver;
29   PetscBool       allowzeropivot,zeropivotdetected;
30 
31   PetscFunctionBegin;
32   allowzeropivot = PetscNot(A->erroriffailure);
33   ierr = PetscOptionsGetInt(NULL,((PetscObject)A)->prefix,"-sol_ver",&sol_ver,NULL);CHKERRQ(ierr);
34 
35   /* generate work space needed by the factorization */
36   ierr = PetscMalloc2(bs2*n,&rtmp,bs2,&mwork);CHKERRQ(ierr);
37   ierr = PetscArrayzero(rtmp,bs2*n);CHKERRQ(ierr);
38 
39   for (i=0; i<n; i++) {
40     /* zero rtmp */
41     /* L part */
42     nz    = bi[i+1] - bi[i];
43     bjtmp = bj + bi[i];
44     for  (j=0; j<nz; j++) {
45       ierr = PetscArrayzero(rtmp+bs2*bjtmp[j],bs2);CHKERRQ(ierr);
46     }
47 
48     /* U part */
49     nz    = bdiag[i] - bdiag[i+1];
50     bjtmp = bj + bdiag[i+1]+1;
51     for  (j=0; j<nz; j++) {
52       ierr = PetscArrayzero(rtmp+bs2*bjtmp[j],bs2);CHKERRQ(ierr);
53     }
54 
55     /* load in initial (unfactored row) */
56     nz    = ai[i+1] - ai[i];
57     ajtmp = aj + ai[i];
58     v     = aa + bs2*ai[i];
59     for (j=0; j<nz; j++) {
60       ierr = PetscArraycpy(rtmp+bs2*ajtmp[j],v+bs2*j,bs2);CHKERRQ(ierr);
61     }
62 
63     /* elimination */
64     bjtmp = bj + bi[i];
65     nzL   = bi[i+1] - bi[i];
66     for (k=0; k < nzL; k++) {
67       row = bjtmp[k];
68       pc  = rtmp + bs2*row;
69       for (flg=0,j=0; j<bs2; j++) {
70         if (pc[j]!=0.0) {
71           flg = 1;
72           break;
73         }
74       }
75       if (flg) {
76         pv = b->a + bs2*bdiag[row];
77         PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork);
78         /*ierr = PetscKernel_A_gets_A_times_B_15(pc,pv,mwork);CHKERRQ(ierr);*/
79         pj = b->j + bdiag[row+1]+1; /* beginning of U(row,:) */
80         pv = b->a + bs2*(bdiag[row+1]+1);
81         nz = bdiag[row] - bdiag[row+1] - 1; /* num of entries inU(row,:), excluding diag */
82         for (j=0; j<nz; j++) {
83           vv = rtmp + bs2*pj[j];
84           PetscKernel_A_gets_A_minus_B_times_C(bs,vv,pc,pv);
85           /* ierr = PetscKernel_A_gets_A_minus_B_times_C_15(vv,pc,pv);CHKERRQ(ierr); */
86           pv += bs2;
87         }
88         ierr = PetscLogFlops(2.0*bs2*bs*(nz+1)-bs2);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
89       }
90     }
91 
92     /* finished row so stick it into b->a */
93     /* L part */
94     pv = b->a + bs2*bi[i];
95     pj = b->j + bi[i];
96     nz = bi[i+1] - bi[i];
97     for (j=0; j<nz; j++) {
98       ierr = PetscArraycpy(pv+bs2*j,rtmp+bs2*pj[j],bs2);CHKERRQ(ierr);
99     }
100 
101     /* Mark diagonal and invert diagonal for simpler triangular solves */
102     pv   = b->a + bs2*bdiag[i];
103     pj   = b->j + bdiag[i];
104     ierr = PetscArraycpy(pv,rtmp+bs2*pj[0],bs2);CHKERRQ(ierr);
105     ierr = PetscKernel_A_gets_inverse_A_15(pv,ipvt,work,info->shiftamount,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr);
106     if (zeropivotdetected) C->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
107 
108     /* U part */
109     pv = b->a + bs2*(bdiag[i+1]+1);
110     pj = b->j + bdiag[i+1]+1;
111     nz = bdiag[i] - bdiag[i+1] - 1;
112     for (j=0; j<nz; j++) {
113       ierr = PetscArraycpy(pv+bs2*j,rtmp+bs2*pj[j],bs2);CHKERRQ(ierr);
114     }
115   }
116 
117   ierr = PetscFree2(rtmp,mwork);CHKERRQ(ierr);
118 
119   C->ops->solve          = MatSolve_SeqBAIJ_15_NaturalOrdering_ver1;
120   C->ops->solvetranspose = MatSolve_SeqBAIJ_N_NaturalOrdering;
121   C->assembled           = PETSC_TRUE;
122 
123   ierr = PetscLogFlops(1.333333333333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
124   PetscFunctionReturn(0);
125 }
126 
127 PetscErrorCode MatLUFactorNumeric_SeqBAIJ_N(Mat B,Mat A,const MatFactorInfo *info)
128 {
129   Mat            C     =B;
130   Mat_SeqBAIJ    *a    =(Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)C->data;
131   IS             isrow = b->row,isicol = b->icol;
132   PetscErrorCode ierr;
133   const PetscInt *r,*ic;
134   PetscInt       i,j,k,n=a->mbs,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
135   PetscInt       *ajtmp,*bjtmp,nz,nzL,row,*bdiag=b->diag,*pj;
136   MatScalar      *rtmp,*pc,*mwork,*v,*pv,*aa=a->a;
137   PetscInt       bs=A->rmap->bs,bs2 = a->bs2,*v_pivots,flg;
138   MatScalar      *v_work;
139   PetscBool      col_identity,row_identity,both_identity;
140   PetscBool      allowzeropivot,zeropivotdetected;
141 
142   PetscFunctionBegin;
143   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
144   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
145   allowzeropivot = PetscNot(A->erroriffailure);
146 
147   ierr = PetscCalloc1(bs2*n,&rtmp);CHKERRQ(ierr);
148 
149   /* generate work space needed by dense LU factorization */
150   ierr = PetscMalloc3(bs,&v_work,bs2,&mwork,bs,&v_pivots);CHKERRQ(ierr);
151 
152   for (i=0; i<n; i++) {
153     /* zero rtmp */
154     /* L part */
155     nz    = bi[i+1] - bi[i];
156     bjtmp = bj + bi[i];
157     for  (j=0; j<nz; j++) {
158       ierr = PetscArrayzero(rtmp+bs2*bjtmp[j],bs2);CHKERRQ(ierr);
159     }
160 
161     /* U part */
162     nz    = bdiag[i] - bdiag[i+1];
163     bjtmp = bj + bdiag[i+1]+1;
164     for  (j=0; j<nz; j++) {
165       ierr = PetscArrayzero(rtmp+bs2*bjtmp[j],bs2);CHKERRQ(ierr);
166     }
167 
168     /* load in initial (unfactored row) */
169     nz    = ai[r[i]+1] - ai[r[i]];
170     ajtmp = aj + ai[r[i]];
171     v     = aa + bs2*ai[r[i]];
172     for (j=0; j<nz; j++) {
173       ierr = PetscArraycpy(rtmp+bs2*ic[ajtmp[j]],v+bs2*j,bs2);CHKERRQ(ierr);
174     }
175 
176     /* elimination */
177     bjtmp = bj + bi[i];
178     nzL   = bi[i+1] - bi[i];
179     for (k=0; k < nzL; k++) {
180       row = bjtmp[k];
181       pc  = rtmp + bs2*row;
182       for (flg=0,j=0; j<bs2; j++) {
183         if (pc[j]!=0.0) {
184           flg = 1;
185           break;
186         }
187       }
188       if (flg) {
189         pv = b->a + bs2*bdiag[row];
190         PetscKernel_A_gets_A_times_B(bs,pc,pv,mwork); /* *pc = *pc * (*pv); */
191         pj = b->j + bdiag[row+1]+1;         /* beginning of U(row,:) */
192         pv = b->a + bs2*(bdiag[row+1]+1);
193         nz = bdiag[row] - bdiag[row+1] - 1;         /* num of entries inU(row,:), excluding diag */
194         for (j=0; j<nz; j++) {
195           PetscKernel_A_gets_A_minus_B_times_C(bs,rtmp+bs2*pj[j],pc,pv+bs2*j);
196         }
197         ierr = PetscLogFlops(2.0*bs2*bs*(nz+1)-bs2);CHKERRQ(ierr); /* flops = 2*bs^3*nz + 2*bs^3 - bs2) */
198       }
199     }
200 
201     /* finished row so stick it into b->a */
202     /* L part */
203     pv = b->a + bs2*bi[i];
204     pj = b->j + bi[i];
205     nz = bi[i+1] - bi[i];
206     for (j=0; j<nz; j++) {
207       ierr = PetscArraycpy(pv+bs2*j,rtmp+bs2*pj[j],bs2);CHKERRQ(ierr);
208     }
209 
210     /* Mark diagonal and invert diagonal for simpler triangular solves */
211     pv = b->a + bs2*bdiag[i];
212     pj = b->j + bdiag[i];
213     ierr = PetscArraycpy(pv,rtmp+bs2*pj[0],bs2);CHKERRQ(ierr);
214 
215     ierr = PetscKernel_A_gets_inverse_A(bs,pv,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr);
216     if (zeropivotdetected) B->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
217 
218     /* U part */
219     pv = b->a + bs2*(bdiag[i+1]+1);
220     pj = b->j + bdiag[i+1]+1;
221     nz = bdiag[i] - bdiag[i+1] - 1;
222     for (j=0; j<nz; j++) {
223       ierr = PetscArraycpy(pv+bs2*j,rtmp+bs2*pj[j],bs2);CHKERRQ(ierr);
224     }
225   }
226 
227   ierr = PetscFree(rtmp);CHKERRQ(ierr);
228   ierr = PetscFree3(v_work,mwork,v_pivots);CHKERRQ(ierr);
229   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
230   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
231 
232   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
233   ierr = ISIdentity(isicol,&col_identity);CHKERRQ(ierr);
234 
235   both_identity = (PetscBool) (row_identity && col_identity);
236   if (both_identity) {
237     switch (bs) {
238     case  9:
239 #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
240       C->ops->solve = MatSolve_SeqBAIJ_9_NaturalOrdering;
241 #else
242       C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering;
243 #endif
244       break;
245     case 11:
246       C->ops->solve = MatSolve_SeqBAIJ_11_NaturalOrdering;
247       break;
248     case 12:
249       C->ops->solve = MatSolve_SeqBAIJ_12_NaturalOrdering;
250       break;
251     case 13:
252       C->ops->solve = MatSolve_SeqBAIJ_13_NaturalOrdering;
253       break;
254     case 14:
255       C->ops->solve = MatSolve_SeqBAIJ_14_NaturalOrdering;
256       break;
257     default:
258       C->ops->solve = MatSolve_SeqBAIJ_N_NaturalOrdering;
259       break;
260     }
261   } else {
262     C->ops->solve = MatSolve_SeqBAIJ_N;
263   }
264   C->ops->solvetranspose = MatSolveTranspose_SeqBAIJ_N;
265 
266   C->assembled = PETSC_TRUE;
267 
268   ierr = PetscLogFlops(1.333333333333*bs*bs2*b->mbs);CHKERRQ(ierr); /* from inverting diagonal blocks */
269   PetscFunctionReturn(0);
270 }
271 
272 /*
273    ilu(0) with natural ordering under new data structure.
274    See MatILUFactorSymbolic_SeqAIJ_ilu0() for detailed description
275    because this code is almost identical to MatILUFactorSymbolic_SeqAIJ_ilu0_inplace().
276 */
277 
278 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_ilu0(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info)
279 {
280 
281   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b;
282   PetscErrorCode ierr;
283   PetscInt       n=a->mbs,*ai=a->i,*aj,*adiag=a->diag,bs2 = a->bs2;
284   PetscInt       i,j,nz,*bi,*bj,*bdiag,bi_temp;
285 
286   PetscFunctionBegin;
287   ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_FALSE);CHKERRQ(ierr);
288   b    = (Mat_SeqBAIJ*)(fact)->data;
289 
290   /* allocate matrix arrays for new data structure */
291   ierr = PetscMalloc3(bs2*ai[n]+1,&b->a,ai[n]+1,&b->j,n+1,&b->i);CHKERRQ(ierr);
292   ierr = PetscLogObjectMemory((PetscObject)fact,ai[n]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(n+1)*sizeof(PetscInt));CHKERRQ(ierr);
293 
294   b->singlemalloc    = PETSC_TRUE;
295   b->free_a          = PETSC_TRUE;
296   b->free_ij         = PETSC_TRUE;
297   fact->preallocated = PETSC_TRUE;
298   fact->assembled    = PETSC_TRUE;
299   if (!b->diag) {
300     ierr = PetscMalloc1(n+1,&b->diag);CHKERRQ(ierr);
301     ierr = PetscLogObjectMemory((PetscObject)fact,(n+1)*sizeof(PetscInt));CHKERRQ(ierr);
302   }
303   bdiag = b->diag;
304 
305   if (n > 0) {
306     ierr = PetscArrayzero(b->a,bs2*ai[n]);CHKERRQ(ierr);
307   }
308 
309   /* set bi and bj with new data structure */
310   bi = b->i;
311   bj = b->j;
312 
313   /* L part */
314   bi[0] = 0;
315   for (i=0; i<n; i++) {
316     nz      = adiag[i] - ai[i];
317     bi[i+1] = bi[i] + nz;
318     aj      = a->j + ai[i];
319     for (j=0; j<nz; j++) {
320       *bj = aj[j]; bj++;
321     }
322   }
323 
324   /* U part */
325   bi_temp  = bi[n];
326   bdiag[n] = bi[n]-1;
327   for (i=n-1; i>=0; i--) {
328     nz      = ai[i+1] - adiag[i] - 1;
329     bi_temp = bi_temp + nz + 1;
330     aj      = a->j + adiag[i] + 1;
331     for (j=0; j<nz; j++) {
332       *bj = aj[j]; bj++;
333     }
334     /* diag[i] */
335     *bj      = i; bj++;
336     bdiag[i] = bi_temp - 1;
337   }
338   PetscFunctionReturn(0);
339 }
340 
341 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info)
342 {
343   Mat_SeqBAIJ        *a = (Mat_SeqBAIJ*)A->data,*b;
344   IS                 isicol;
345   PetscErrorCode     ierr;
346   const PetscInt     *r,*ic;
347   PetscInt           n=a->mbs,*ai=a->i,*aj=a->j,d;
348   PetscInt           *bi,*cols,nnz,*cols_lvl;
349   PetscInt           *bdiag,prow,fm,nzbd,reallocs=0,dcount=0;
350   PetscInt           i,levels,diagonal_fill;
351   PetscBool          col_identity,row_identity,both_identity;
352   PetscReal          f;
353   PetscInt           nlnk,*lnk,*lnk_lvl=NULL;
354   PetscBT            lnkbt;
355   PetscInt           nzi,*bj,**bj_ptr,**bjlvl_ptr;
356   PetscFreeSpaceList free_space    =NULL,current_space=NULL;
357   PetscFreeSpaceList free_space_lvl=NULL,current_space_lvl=NULL;
358   PetscBool          missing;
359   PetscInt           bs=A->rmap->bs,bs2=a->bs2;
360 
361   PetscFunctionBegin;
362   if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must be square matrix, rows %D columns %D",A->rmap->n,A->cmap->n);
363   if (bs>1) {  /* check shifttype */
364     if (info->shifttype == MAT_SHIFT_NONZERO || info->shifttype == MAT_SHIFT_POSITIVE_DEFINITE) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only MAT_SHIFT_NONE and MAT_SHIFT_INBLOCKS are supported for BAIJ matrix");
365   }
366 
367   ierr = MatMissingDiagonal(A,&missing,&d);CHKERRQ(ierr);
368   if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry %D",d);
369 
370   f             = info->fill;
371   levels        = (PetscInt)info->levels;
372   diagonal_fill = (PetscInt)info->diagonal_fill;
373 
374   ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr);
375 
376   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
377   ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr);
378 
379   both_identity = (PetscBool) (row_identity && col_identity);
380 
381   if (!levels && both_identity) {
382     /* special case: ilu(0) with natural ordering */
383     ierr = MatILUFactorSymbolic_SeqBAIJ_ilu0(fact,A,isrow,iscol,info);CHKERRQ(ierr);
384     ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr);
385 
386     fact->factortype               = MAT_FACTOR_ILU;
387     (fact)->info.factor_mallocs    = 0;
388     (fact)->info.fill_ratio_given  = info->fill;
389     (fact)->info.fill_ratio_needed = 1.0;
390 
391     b                = (Mat_SeqBAIJ*)(fact)->data;
392     b->row           = isrow;
393     b->col           = iscol;
394     b->icol          = isicol;
395     ierr             = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
396     ierr             = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
397     b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE;
398 
399     ierr = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr);
400     PetscFunctionReturn(0);
401   }
402 
403   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
404   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
405 
406   /* get new row pointers */
407   ierr  = PetscMalloc1(n+1,&bi);CHKERRQ(ierr);
408   bi[0] = 0;
409   /* bdiag is location of diagonal in factor */
410   ierr     = PetscMalloc1(n+1,&bdiag);CHKERRQ(ierr);
411   bdiag[0] = 0;
412 
413   ierr = PetscMalloc2(n,&bj_ptr,n,&bjlvl_ptr);CHKERRQ(ierr);
414 
415   /* create a linked list for storing column indices of the active row */
416   nlnk = n + 1;
417   ierr = PetscIncompleteLLCreate(n,n,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
418 
419   /* initial FreeSpace size is f*(ai[n]+1) */
420   ierr              = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space);CHKERRQ(ierr);
421   current_space     = free_space;
422   ierr              = PetscFreeSpaceGet(PetscRealIntMultTruncate(f,ai[n]+1),&free_space_lvl);CHKERRQ(ierr);
423   current_space_lvl = free_space_lvl;
424 
425   for (i=0; i<n; i++) {
426     nzi = 0;
427     /* copy current row into linked list */
428     nnz = ai[r[i]+1] - ai[r[i]];
429     if (!nnz) 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);
430     cols   = aj + ai[r[i]];
431     lnk[i] = -1; /* marker to indicate if diagonal exists */
432     ierr   = PetscIncompleteLLInit(nnz,cols,n,ic,nlnk,lnk,lnk_lvl,lnkbt);CHKERRQ(ierr);
433     nzi   += nlnk;
434 
435     /* make sure diagonal entry is included */
436     if (diagonal_fill && lnk[i] == -1) {
437       fm = n;
438       while (lnk[fm] < i) fm = lnk[fm];
439       lnk[i]     = lnk[fm]; /* insert diagonal into linked list */
440       lnk[fm]    = i;
441       lnk_lvl[i] = 0;
442       nzi++; dcount++;
443     }
444 
445     /* add pivot rows into the active row */
446     nzbd = 0;
447     prow = lnk[n];
448     while (prow < i) {
449       nnz      = bdiag[prow];
450       cols     = bj_ptr[prow] + nnz + 1;
451       cols_lvl = bjlvl_ptr[prow] + nnz + 1;
452       nnz      = bi[prow+1] - bi[prow] - nnz - 1;
453 
454       ierr = PetscILULLAddSorted(nnz,cols,levels,cols_lvl,prow,nlnk,lnk,lnk_lvl,lnkbt,prow);CHKERRQ(ierr);
455       nzi += nlnk;
456       prow = lnk[prow];
457       nzbd++;
458     }
459     bdiag[i] = nzbd;
460     bi[i+1]  = bi[i] + nzi;
461 
462     /* if free space is not available, make more free space */
463     if (current_space->local_remaining<nzi) {
464       nnz  = PetscIntMultTruncate(2,PetscIntMultTruncate(nzi,(n - i))); /* estimated and max additional space needed */
465       ierr = PetscFreeSpaceGet(nnz,&current_space);CHKERRQ(ierr);
466       ierr = PetscFreeSpaceGet(nnz,&current_space_lvl);CHKERRQ(ierr);
467       reallocs++;
468     }
469 
470     /* copy data into free_space and free_space_lvl, then initialize lnk */
471     ierr = PetscIncompleteLLClean(n,n,nzi,lnk,lnk_lvl,current_space->array,current_space_lvl->array,lnkbt);CHKERRQ(ierr);
472 
473     bj_ptr[i]    = current_space->array;
474     bjlvl_ptr[i] = current_space_lvl->array;
475 
476     /* make sure the active row i has diagonal entry */
477     if (*(bj_ptr[i]+bdiag[i]) != i) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Row %D has missing diagonal in factored matrix\ntry running with -pc_factor_nonzeros_along_diagonal or -pc_factor_diagonal_fill",i);
478 
479     current_space->array           += nzi;
480     current_space->local_used      += nzi;
481     current_space->local_remaining -= nzi;
482 
483     current_space_lvl->array           += nzi;
484     current_space_lvl->local_used      += nzi;
485     current_space_lvl->local_remaining -= nzi;
486   }
487 
488   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
489   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
490 
491   /* copy free_space into bj and free free_space; set bi, bj, bdiag in new datastructure; */
492   ierr = PetscMalloc1(bi[n]+1,&bj);CHKERRQ(ierr);
493   ierr = PetscFreeSpaceContiguous_LU(&free_space,bj,n,bi,bdiag);CHKERRQ(ierr);
494 
495   ierr = PetscIncompleteLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
496   ierr = PetscFreeSpaceDestroy(free_space_lvl);CHKERRQ(ierr);
497   ierr = PetscFree2(bj_ptr,bjlvl_ptr);CHKERRQ(ierr);
498 
499 #if defined(PETSC_USE_INFO)
500   {
501     PetscReal af = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]);
502     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocs,(double)f,(double)af);CHKERRQ(ierr);
503     ierr = PetscInfo1(A,"Run with -[sub_]pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
504     ierr = PetscInfo1(A,"PCFactorSetFill([sub]pc,%g);\n",(double)af);CHKERRQ(ierr);
505     ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr);
506     if (diagonal_fill) {
507       ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr);
508     }
509   }
510 #endif
511 
512   /* put together the new matrix */
513   ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
514   ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr);
515 
516   b               = (Mat_SeqBAIJ*)(fact)->data;
517   b->free_a       = PETSC_TRUE;
518   b->free_ij      = PETSC_TRUE;
519   b->singlemalloc = PETSC_FALSE;
520 
521   ierr = PetscMalloc1(bs2*(bdiag[0]+1),&b->a);CHKERRQ(ierr);
522 
523   b->j          = bj;
524   b->i          = bi;
525   b->diag       = bdiag;
526   b->free_diag  = PETSC_TRUE;
527   b->ilen       = NULL;
528   b->imax       = NULL;
529   b->row        = isrow;
530   b->col        = iscol;
531   ierr          = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
532   ierr          = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
533   b->icol       = isicol;
534 
535   ierr = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr);
536   /* In b structure:  Free imax, ilen, old a, old j.
537      Allocate bdiag, solve_work, new a, new j */
538   ierr     = PetscLogObjectMemory((PetscObject)fact,(bdiag[0]+1) * (sizeof(PetscInt)+bs2*sizeof(PetscScalar)));CHKERRQ(ierr);
539   b->maxnz = b->nz = bdiag[0]+1;
540 
541   fact->info.factor_mallocs    = reallocs;
542   fact->info.fill_ratio_given  = f;
543   fact->info.fill_ratio_needed = ((PetscReal)(bdiag[0]+1))/((PetscReal)ai[n]);
544 
545   ierr = MatSeqBAIJSetNumericFactorization(fact,both_identity);CHKERRQ(ierr);
546   PetscFunctionReturn(0);
547 }
548 
549 /*
550      This code is virtually identical to MatILUFactorSymbolic_SeqAIJ
551    except that the data structure of Mat_SeqAIJ is slightly different.
552    Not a good example of code reuse.
553 */
554 PetscErrorCode MatILUFactorSymbolic_SeqBAIJ_inplace(Mat fact,Mat A,IS isrow,IS iscol,const MatFactorInfo *info)
555 {
556   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data,*b;
557   IS             isicol;
558   PetscErrorCode ierr;
559   const PetscInt *r,*ic,*ai = a->i,*aj = a->j,*xi;
560   PetscInt       prow,n = a->mbs,*ainew,*ajnew,jmax,*fill,nz,*im,*ajfill,*flev,*xitmp;
561   PetscInt       *dloc,idx,row,m,fm,nzf,nzi,reallocate = 0,dcount = 0;
562   PetscInt       incrlev,nnz,i,bs = A->rmap->bs,bs2 = a->bs2,levels,diagonal_fill,dd;
563   PetscBool      col_identity,row_identity,both_identity,flg;
564   PetscReal      f;
565 
566   PetscFunctionBegin;
567   ierr = MatMissingDiagonal_SeqBAIJ(A,&flg,&dd);CHKERRQ(ierr);
568   if (flg) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix A is missing diagonal entry in row %D",dd);
569 
570   f             = info->fill;
571   levels        = (PetscInt)info->levels;
572   diagonal_fill = (PetscInt)info->diagonal_fill;
573 
574   ierr = ISInvertPermutation(iscol,PETSC_DECIDE,&isicol);CHKERRQ(ierr);
575 
576   ierr = ISIdentity(isrow,&row_identity);CHKERRQ(ierr);
577   ierr = ISIdentity(iscol,&col_identity);CHKERRQ(ierr);
578   both_identity = (PetscBool) (row_identity && col_identity);
579 
580   if (!levels && both_identity) {  /* special case copy the nonzero structure */
581     ierr = MatDuplicateNoCreate_SeqBAIJ(fact,A,MAT_DO_NOT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr);
582     ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr);
583 
584     fact->factortype = MAT_FACTOR_ILU;
585     b                = (Mat_SeqBAIJ*)fact->data;
586     b->row           = isrow;
587     b->col           = iscol;
588     ierr             = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
589     ierr             = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
590     b->icol          = isicol;
591     b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE;
592 
593     ierr         = PetscMalloc1((n+1)*bs,&b->solve_work);CHKERRQ(ierr);
594     PetscFunctionReturn(0);
595   }
596 
597   /* general case perform the symbolic factorization */
598   ierr = ISGetIndices(isrow,&r);CHKERRQ(ierr);
599   ierr = ISGetIndices(isicol,&ic);CHKERRQ(ierr);
600 
601   /* get new row pointers */
602   ierr     = PetscMalloc1(n+1,&ainew);CHKERRQ(ierr);
603   ainew[0] = 0;
604   /* don't know how many column pointers are needed so estimate */
605   jmax = (PetscInt)(f*ai[n] + 1);
606   ierr = PetscMalloc1(jmax,&ajnew);CHKERRQ(ierr);
607   /* ajfill is level of fill for each fill entry */
608   ierr = PetscMalloc1(jmax,&ajfill);CHKERRQ(ierr);
609   /* fill is a linked list of nonzeros in active row */
610   ierr = PetscMalloc1(n+1,&fill);CHKERRQ(ierr);
611   /* im is level for each filled value */
612   ierr = PetscMalloc1(n+1,&im);CHKERRQ(ierr);
613   /* dloc is location of diagonal in factor */
614   ierr    = PetscMalloc1(n+1,&dloc);CHKERRQ(ierr);
615   dloc[0] = 0;
616   for (prow=0; prow<n; prow++) {
617 
618     /* copy prow into linked list */
619     nzf = nz = ai[r[prow]+1] - ai[r[prow]];
620     if (!nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Empty row in matrix: row in original ordering %D in permuted ordering %D",r[prow],prow);
621     xi         = aj + ai[r[prow]];
622     fill[n]    = n;
623     fill[prow] = -1;   /* marker for diagonal entry */
624     while (nz--) {
625       fm  = n;
626       idx = ic[*xi++];
627       do {
628         m  = fm;
629         fm = fill[m];
630       } while (fm < idx);
631       fill[m]   = idx;
632       fill[idx] = fm;
633       im[idx]   = 0;
634     }
635 
636     /* make sure diagonal entry is included */
637     if (diagonal_fill && fill[prow] == -1) {
638       fm = n;
639       while (fill[fm] < prow) fm = fill[fm];
640       fill[prow] = fill[fm];    /* insert diagonal into linked list */
641       fill[fm]   = prow;
642       im[prow]   = 0;
643       nzf++;
644       dcount++;
645     }
646 
647     nzi = 0;
648     row = fill[n];
649     while (row < prow) {
650       incrlev = im[row] + 1;
651       nz      = dloc[row];
652       xi      = ajnew  + ainew[row] + nz + 1;
653       flev    = ajfill + ainew[row] + nz + 1;
654       nnz     = ainew[row+1] - ainew[row] - nz - 1;
655       fm      = row;
656       while (nnz-- > 0) {
657         idx = *xi++;
658         if (*flev + incrlev > levels) {
659           flev++;
660           continue;
661         }
662         do {
663           m  = fm;
664           fm = fill[m];
665         } while (fm < idx);
666         if (fm != idx) {
667           im[idx]   = *flev + incrlev;
668           fill[m]   = idx;
669           fill[idx] = fm;
670           fm        = idx;
671           nzf++;
672         } else if (im[idx] > *flev + incrlev) im[idx] = *flev+incrlev;
673         flev++;
674       }
675       row = fill[row];
676       nzi++;
677     }
678     /* copy new filled row into permanent storage */
679     ainew[prow+1] = ainew[prow] + nzf;
680     if (ainew[prow+1] > jmax) {
681 
682       /* estimate how much additional space we will need */
683       /* use the strategy suggested by David Hysom <hysom@perch-t.icase.edu> */
684       /* just double the memory each time */
685       PetscInt maxadd = jmax;
686       /* maxadd = (int)(((f*ai[n]+1)*(n-prow+5))/n); */
687       if (maxadd < nzf) maxadd = (n-prow)*(nzf+1);
688       jmax += maxadd;
689 
690       /* allocate a longer ajnew and ajfill */
691       ierr   = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr);
692       ierr   = PetscArraycpy(xitmp,ajnew,ainew[prow]);CHKERRQ(ierr);
693       ierr   = PetscFree(ajnew);CHKERRQ(ierr);
694       ajnew  = xitmp;
695       ierr   = PetscMalloc1(jmax,&xitmp);CHKERRQ(ierr);
696       ierr   = PetscArraycpy(xitmp,ajfill,ainew[prow]);CHKERRQ(ierr);
697       ierr   = PetscFree(ajfill);CHKERRQ(ierr);
698       ajfill = xitmp;
699       reallocate++;   /* count how many reallocations are needed */
700     }
701     xitmp      = ajnew + ainew[prow];
702     flev       = ajfill + ainew[prow];
703     dloc[prow] = nzi;
704     fm         = fill[n];
705     while (nzf--) {
706       *xitmp++ = fm;
707       *flev++  = im[fm];
708       fm       = fill[fm];
709     }
710     /* make sure row has diagonal entry */
711     if (ajnew[ainew[prow]+dloc[prow]] != prow) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Row %D has missing diagonal in factored matrix\n\
712                                                         try running with -pc_factor_nonzeros_along_diagonal or -pc_factor_diagonal_fill",prow);
713   }
714   ierr = PetscFree(ajfill);CHKERRQ(ierr);
715   ierr = ISRestoreIndices(isrow,&r);CHKERRQ(ierr);
716   ierr = ISRestoreIndices(isicol,&ic);CHKERRQ(ierr);
717   ierr = PetscFree(fill);CHKERRQ(ierr);
718   ierr = PetscFree(im);CHKERRQ(ierr);
719 
720 #if defined(PETSC_USE_INFO)
721   {
722     PetscReal af = ((PetscReal)ainew[n])/((PetscReal)ai[n]);
723     ierr = PetscInfo3(A,"Reallocs %D Fill ratio:given %g needed %g\n",reallocate,(double)f,(double)af);CHKERRQ(ierr);
724     ierr = PetscInfo1(A,"Run with -pc_factor_fill %g or use \n",(double)af);CHKERRQ(ierr);
725     ierr = PetscInfo1(A,"PCFactorSetFill(pc,%g);\n",(double)af);CHKERRQ(ierr);
726     ierr = PetscInfo(A,"for best performance.\n");CHKERRQ(ierr);
727     if (diagonal_fill) {
728       ierr = PetscInfo1(A,"Detected and replaced %D missing diagonals\n",dcount);CHKERRQ(ierr);
729     }
730   }
731 #endif
732 
733   /* put together the new matrix */
734   ierr = MatSeqBAIJSetPreallocation(fact,bs,MAT_SKIP_ALLOCATION,NULL);CHKERRQ(ierr);
735   ierr = PetscLogObjectParent((PetscObject)fact,(PetscObject)isicol);CHKERRQ(ierr);
736   b    = (Mat_SeqBAIJ*)fact->data;
737 
738   b->free_a       = PETSC_TRUE;
739   b->free_ij      = PETSC_TRUE;
740   b->singlemalloc = PETSC_FALSE;
741 
742   ierr = PetscMalloc1(bs2*ainew[n],&b->a);CHKERRQ(ierr);
743 
744   b->j          = ajnew;
745   b->i          = ainew;
746   for (i=0; i<n; i++) dloc[i] += ainew[i];
747   b->diag          = dloc;
748   b->free_diag     = PETSC_TRUE;
749   b->ilen          = NULL;
750   b->imax          = NULL;
751   b->row           = isrow;
752   b->col           = iscol;
753   b->pivotinblocks = (info->pivotinblocks) ? PETSC_TRUE : PETSC_FALSE;
754 
755   ierr    = PetscObjectReference((PetscObject)isrow);CHKERRQ(ierr);
756   ierr    = PetscObjectReference((PetscObject)iscol);CHKERRQ(ierr);
757   b->icol = isicol;
758   ierr    = PetscMalloc1(bs*n+bs,&b->solve_work);CHKERRQ(ierr);
759   /* In b structure:  Free imax, ilen, old a, old j.
760      Allocate dloc, solve_work, new a, new j */
761   ierr     = PetscLogObjectMemory((PetscObject)fact,(ainew[n]-n)*(sizeof(PetscInt))+bs2*ainew[n]*sizeof(PetscScalar));CHKERRQ(ierr);
762   b->maxnz = b->nz = ainew[n];
763 
764   fact->info.factor_mallocs    = reallocate;
765   fact->info.fill_ratio_given  = f;
766   fact->info.fill_ratio_needed = ((PetscReal)ainew[n])/((PetscReal)ai[prow]);
767 
768   ierr = MatSeqBAIJSetNumericFactorization_inplace(fact,both_identity);CHKERRQ(ierr);
769   PetscFunctionReturn(0);
770 }
771 
772 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE(Mat A)
773 {
774   /* Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; */
775   /* int i,*AJ=a->j,nz=a->nz; */
776 
777   PetscFunctionBegin;
778   /* Undo Column scaling */
779   /*    while (nz--) { */
780   /*      AJ[i] = AJ[i]/4; */
781   /*    } */
782   /* This should really invoke a push/pop logic, but we don't have that yet. */
783   A->ops->setunfactored = NULL;
784   PetscFunctionReturn(0);
785 }
786 
787 PetscErrorCode MatSetUnfactored_SeqBAIJ_4_NaturalOrdering_SSE_usj(Mat A)
788 {
789   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
790   PetscInt       *AJ=a->j,nz=a->nz;
791   unsigned short *aj=(unsigned short*)AJ;
792 
793   PetscFunctionBegin;
794   /* Is this really necessary? */
795   while (nz--) {
796     AJ[nz] = (int)((unsigned int)aj[nz]); /* First extend, then convert to signed. */
797   }
798   A->ops->setunfactored = NULL;
799   PetscFunctionReturn(0);
800 }
801 
802