xref: /petsc/src/mat/impls/aij/seq/matmatmult.c (revision c01495d35ab0aa12df72ec9df40ea6922abcdd00)
1 
2 /*
3   Defines matrix-matrix product routines for pairs of SeqAIJ matrices
4           C = A * B
5 */
6 
7 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/
8 #include <../src/mat/utils/freespace.h>
9 #include <petscbt.h>
10 #include <../src/mat/impls/dense/seq/dense.h> /*I "petscmat.h" I*/
11 
12 EXTERN_C_BEGIN
13 #undef __FUNCT__
14 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqAIJ"
15 PetscErrorCode MatMatMult_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
16 {
17   PetscErrorCode ierr;
18 
19   PetscFunctionBegin;
20   if (scall == MAT_INITIAL_MATRIX){
21     ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr);
22   }
23   ierr = MatMatMultNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
24   PetscFunctionReturn(0);
25 }
26 EXTERN_C_END
27 
28 #undef __FUNCT__
29 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqAIJ"
30 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
31 {
32   PetscErrorCode     ierr;
33   PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL;
34   Mat_SeqAIJ         *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c;
35   PetscInt           *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci,*cj;
36   PetscInt           am=A->rmap->N,bn=B->cmap->N,bm=B->rmap->N;
37   PetscInt           i,j,anzi,brow,bnzj,cnzi,nlnk,*lnk,nspacedouble=0;
38   MatScalar          *ca;
39   PetscBT            lnkbt;
40   PetscReal          afill;
41 
42   PetscFunctionBegin;
43   /* Set up */
44   /* Allocate ci array, arrays for fill computation and */
45   /* free space for accumulating nonzero column info */
46   ierr = PetscMalloc(((am+1)+1)*sizeof(PetscInt),&ci);CHKERRQ(ierr);
47   ci[0] = 0;
48 
49   /* create and initialize a linked list */
50   nlnk = bn+1;
51   ierr = PetscLLCreate(bn,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr);
52 
53   /* Initial FreeSpace size is fill*(nnz(A)+nnz(B)) */
54   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+bi[bm])),&free_space);CHKERRQ(ierr);
55   current_space = free_space;
56 
57   /* Determine symbolic info for each row of the product: */
58   for (i=0;i<am;i++) {
59     anzi = ai[i+1] - ai[i];
60     cnzi = 0;
61     j    = anzi;
62     aj   = a->j + ai[i];
63     while (j){/* assume cols are almost in increasing order, starting from its end saves computation */
64       j--;
65       brow = *(aj + j);
66       bnzj = bi[brow+1] - bi[brow];
67       bjj  = bj + bi[brow];
68       /* add non-zero cols of B into the sorted linked list lnk */
69       ierr = PetscLLAdd(bnzj,bjj,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr);
70       cnzi += nlnk;
71     }
72 
73     /* If free space is not available, make more free space */
74     /* Double the amount of total space in the list */
75     if (current_space->local_remaining<cnzi) {
76       ierr = PetscFreeSpaceGet(cnzi+current_space->total_array_size,&current_space);CHKERRQ(ierr);
77       nspacedouble++;
78     }
79 
80     /* Copy data into free space, then initialize lnk */
81     ierr = PetscLLClean(bn,bn,cnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
82     current_space->array           += cnzi;
83     current_space->local_used      += cnzi;
84     current_space->local_remaining -= cnzi;
85 
86     ci[i+1] = ci[i] + cnzi;
87   }
88 
89   /* Column indices are in the list of free space */
90   /* Allocate space for cj, initialize cj, and */
91   /* destroy list of free space and other temporary array(s) */
92   ierr = PetscMalloc((ci[am]+1)*sizeof(PetscInt),&cj);CHKERRQ(ierr);
93   ierr = PetscFreeSpaceContiguous(&free_space,cj);CHKERRQ(ierr);
94   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
95 
96   /* Allocate space for ca */
97   ierr = PetscMalloc((ci[am]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr);
98   ierr = PetscMemzero(ca,(ci[am]+1)*sizeof(MatScalar));CHKERRQ(ierr);
99 
100   /* put together the new symbolic matrix */
101   ierr = MatCreateSeqAIJWithArrays(((PetscObject)A)->comm,am,bn,ci,cj,ca,C);CHKERRQ(ierr);
102 
103   /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
104   /* These are PETSc arrays, so change flags so arrays can be deleted by PETSc */
105   c = (Mat_SeqAIJ *)((*C)->data);
106   c->free_a   = PETSC_TRUE;
107   c->free_ij  = PETSC_TRUE;
108   c->nonew    = 0;
109 
110   /* set MatInfo */
111   afill = (PetscReal)ci[am]/(ai[am]+bi[bm]) + 1.e-5;
112   if (afill < 1.0) afill = 1.0;
113   c->maxnz                     = ci[am];
114   c->nz                        = ci[am];
115   (*C)->info.mallocs           = nspacedouble;
116   (*C)->info.fill_ratio_given  = fill;
117   (*C)->info.fill_ratio_needed = afill;
118 
119 #if defined(PETSC_USE_INFO)
120   if (ci[am]) {
121     ierr = PetscInfo3((*C),"Reallocs %D; Fill ratio: given %G needed %G.\n",nspacedouble,fill,afill);CHKERRQ(ierr);
122     ierr = PetscInfo1((*C),"Use MatMatMult(A,B,MatReuse,%G,&C) for best performance.;\n",afill);CHKERRQ(ierr);
123   } else {
124     ierr = PetscInfo((*C),"Empty matrix product\n");CHKERRQ(ierr);
125   }
126 #endif
127   PetscFunctionReturn(0);
128 }
129 
130 
131 #undef __FUNCT__
132 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqAIJ"
133 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
134 {
135   PetscErrorCode ierr;
136   PetscLogDouble flops=0.0;
137   Mat_SeqAIJ     *a = (Mat_SeqAIJ *)A->data;
138   Mat_SeqAIJ     *b = (Mat_SeqAIJ *)B->data;
139   Mat_SeqAIJ     *c = (Mat_SeqAIJ *)C->data;
140   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci=c->i,*cj=c->j;
141   PetscInt       am=A->rmap->N,cm=C->rmap->N;
142   PetscInt       i,j,k,anzi,bnzi,cnzi,brow,nextb;
143   MatScalar      *aa=a->a,*ba=b->a,*baj,*ca=c->a;
144 
145   PetscFunctionBegin;
146   /* clean old values in C */
147   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
148   /* Traverse A row-wise. */
149   /* Build the ith row in C by summing over nonzero columns in A, */
150   /* the rows of B corresponding to nonzeros of A. */
151   for (i=0;i<am;i++) {
152     anzi = ai[i+1] - ai[i];
153     for (j=0;j<anzi;j++) {
154       brow = *aj++;
155       bnzi = bi[brow+1] - bi[brow];
156       bjj  = bj + bi[brow];
157       baj  = ba + bi[brow];
158       nextb = 0;
159       for (k=0; nextb<bnzi; k++) {
160         if (cj[k] == bjj[nextb]){ /* ccol == bcol */
161           ca[k] += (*aa)*baj[nextb++];
162         }
163       }
164       flops += 2*bnzi;
165       aa++;
166     }
167     cnzi = ci[i+1] - ci[i];
168     ca += cnzi;
169     cj += cnzi;
170   }
171   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
172   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
173 
174   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
175   PetscFunctionReturn(0);
176 }
177 
178 #undef __FUNCT__
179 #define __FUNCT__ "MatMatMultTranspose_SeqAIJ_SeqAIJ"
180 PetscErrorCode MatMatMultTranspose_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
181 {
182   PetscErrorCode ierr;
183 
184   PetscFunctionBegin;
185   SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Not done yet");
186   if (scall == MAT_INITIAL_MATRIX){
187     ierr = MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr);
188   }
189   ierr = MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
190   PetscFunctionReturn(0);
191 }
192 
193 #undef __FUNCT__
194 #define __FUNCT__ "MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ"
195 PetscErrorCode MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
196 {
197   /*
198   PetscErrorCode ierr;
199   Mat            At;
200   PetscInt       *ati,*atj;
201    */
202   PetscFunctionBegin;
203 
204   PetscFunctionReturn(0);
205 }
206 
207 #undef __FUNCT__
208 #define __FUNCT__ "MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ"
209 PetscErrorCode MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
210 {
211   /*
212   PetscErrorCode ierr;
213   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c=(Mat_SeqAIJ*)C->data;
214   PetscInt       am=A->rmap->n,anzi,*ai=a->i,*aj=a->j,*bi=b->i,*bj,bnzi,nextb;
215   PetscInt       cm=C->rmap->n,*ci=c->i,*cj=c->j,crow,*cjj,i,j,k;
216   PetscLogDouble flops=0.0;
217   MatScalar      *aa=a->a,*ba,*ca=c->a,*caj;
218    */
219 
220   PetscFunctionBegin;
221 
222   PetscFunctionReturn(0);
223 }
224 
225 #undef __FUNCT__
226 #define __FUNCT__ "MatMatTransposeMult_SeqAIJ_SeqAIJ"
227 PetscErrorCode MatMatTransposeMult_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) {
228   PetscErrorCode ierr;
229 
230   PetscFunctionBegin;
231   if (scall == MAT_INITIAL_MATRIX){
232     ierr = MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr);
233   }
234   ierr = MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
235   PetscFunctionReturn(0);
236 }
237 
238 #undef __FUNCT__
239 #define __FUNCT__ "MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ"
240 PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
241 {
242   PetscErrorCode ierr;
243   Mat            At;
244   PetscInt       *ati,*atj;
245 
246   PetscFunctionBegin;
247   /* create symbolic At */
248   ierr = MatGetSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
249   ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,A->cmap->n,A->rmap->n,ati,atj,PETSC_NULL,&At);CHKERRQ(ierr);
250 
251   /* get symbolic C=At*B */
252   ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(At,B,fill,C);CHKERRQ(ierr);
253 
254   /* clean up */
255   ierr = MatDestroy(&At);CHKERRQ(ierr);
256   ierr = MatRestoreSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
257   PetscFunctionReturn(0);
258 }
259 
260 #undef __FUNCT__
261 #define __FUNCT__ "MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ"
262 PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
263 {
264   PetscErrorCode ierr;
265   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c=(Mat_SeqAIJ*)C->data;
266   PetscInt       am=A->rmap->n,anzi,*ai=a->i,*aj=a->j,*bi=b->i,*bj,bnzi,nextb;
267   PetscInt       cm=C->rmap->n,*ci=c->i,*cj=c->j,crow,*cjj,i,j,k;
268   PetscLogDouble flops=0.0;
269   MatScalar      *aa=a->a,*ba,*ca=c->a,*caj;
270 
271   PetscFunctionBegin;
272   /* clear old values in C */
273   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
274 
275   /* compute A^T*B using outer product (A^T)[:,i]*B[i,:] */
276   for (i=0;i<am;i++) {
277     bj   = b->j + bi[i];
278     ba   = b->a + bi[i];
279     bnzi = bi[i+1] - bi[i];
280     anzi = ai[i+1] - ai[i];
281     for (j=0; j<anzi; j++) {
282       nextb = 0;
283       crow  = *aj++;
284       cjj   = cj + ci[crow];
285       caj   = ca + ci[crow];
286       /* perform sparse axpy operation.  Note cjj includes bj. */
287       for (k=0; nextb<bnzi; k++) {
288         if (cjj[k] == *(bj+nextb)) { /* ccol == bcol */
289           caj[k] += (*aa)*(*(ba+nextb));
290           nextb++;
291         }
292       }
293       flops += 2*bnzi;
294       aa++;
295     }
296   }
297 
298   /* Assemble the final matrix and clean up */
299   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
300   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
301   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
302   PetscFunctionReturn(0);
303 }
304 
305 EXTERN_C_BEGIN
306 #undef __FUNCT__
307 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqDense"
308 PetscErrorCode MatMatMult_SeqAIJ_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
309 {
310   PetscErrorCode ierr;
311 
312   PetscFunctionBegin;
313   if (scall == MAT_INITIAL_MATRIX){
314     ierr = MatMatMultSymbolic_SeqAIJ_SeqDense(A,B,fill,C);CHKERRQ(ierr);
315   }
316   ierr = MatMatMultNumeric_SeqAIJ_SeqDense(A,B,*C);CHKERRQ(ierr);
317   PetscFunctionReturn(0);
318 }
319 EXTERN_C_END
320 
321 #undef __FUNCT__
322 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqDense"
323 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
324 {
325   PetscErrorCode ierr;
326 
327   PetscFunctionBegin;
328   ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,0.0,C);CHKERRQ(ierr);
329   PetscFunctionReturn(0);
330 }
331 
332 #undef __FUNCT__
333 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqDense"
334 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
335 {
336   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
337   PetscErrorCode ierr;
338   PetscScalar    *b,*c,r1,r2,r3,r4,*b1,*b2,*b3,*b4;
339   MatScalar      *aa;
340   PetscInt       cm=C->rmap->n, cn=B->cmap->n, bm=B->rmap->n, col, i,j,n,*aj, am = A->rmap->n;
341   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam;
342 
343   PetscFunctionBegin;
344   if (!cm || !cn) PetscFunctionReturn(0);
345   if (bm != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number columns in A %D not equal rows in B %D\n",A->cmap->n,bm);
346   if (A->rmap->n != C->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows in C %D not equal rows in A %D\n",C->rmap->n,A->rmap->n);
347   if (B->cmap->n != C->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number columns in B %D not equal columns in C %D\n",B->cmap->n,C->cmap->n);
348   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
349   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
350   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
351   for (col=0; col<cn-4; col += 4){  /* over columns of C */
352     colam = col*am;
353     for (i=0; i<am; i++) {        /* over rows of C in those columns */
354       r1 = r2 = r3 = r4 = 0.0;
355       n   = a->i[i+1] - a->i[i];
356       aj  = a->j + a->i[i];
357       aa  = a->a + a->i[i];
358       for (j=0; j<n; j++) {
359         r1 += (*aa)*b1[*aj];
360         r2 += (*aa)*b2[*aj];
361         r3 += (*aa)*b3[*aj];
362         r4 += (*aa++)*b4[*aj++];
363       }
364       c[colam + i]       = r1;
365       c[colam + am + i]  = r2;
366       c[colam + am2 + i] = r3;
367       c[colam + am3 + i] = r4;
368     }
369     b1 += bm4;
370     b2 += bm4;
371     b3 += bm4;
372     b4 += bm4;
373   }
374   for (;col<cn; col++){     /* over extra columns of C */
375     for (i=0; i<am; i++) {  /* over rows of C in those columns */
376       r1 = 0.0;
377       n   = a->i[i+1] - a->i[i];
378       aj  = a->j + a->i[i];
379       aa  = a->a + a->i[i];
380 
381       for (j=0; j<n; j++) {
382         r1 += (*aa++)*b1[*aj++];
383       }
384       c[col*am + i]     = r1;
385     }
386     b1 += bm;
387   }
388   ierr = PetscLogFlops(cn*(2.0*a->nz));CHKERRQ(ierr);
389   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
390   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
391   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
392   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
393   PetscFunctionReturn(0);
394 }
395 
396 /*
397    Note very similar to MatMult_SeqAIJ(), should generate both codes from same base
398 */
399 #undef __FUNCT__
400 #define __FUNCT__ "MatMatMultNumericAdd_SeqAIJ_SeqDense"
401 PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
402 {
403   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
404   PetscErrorCode ierr;
405   PetscScalar    *b,*c,r1,r2,r3,r4,*b1,*b2,*b3,*b4;
406   MatScalar      *aa;
407   PetscInt       cm=C->rmap->n, cn=B->cmap->n, bm=B->rmap->n, col, i,j,n,*aj, am = A->rmap->n,*ii,arm;
408   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam,*ridx;
409 
410   PetscFunctionBegin;
411   if (!cm || !cn) PetscFunctionReturn(0);
412   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
413   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
414   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
415 
416   if (a->compressedrow.use){ /* use compressed row format */
417     for (col=0; col<cn-4; col += 4){  /* over columns of C */
418       colam = col*am;
419       arm   = a->compressedrow.nrows;
420       ii    = a->compressedrow.i;
421       ridx  = a->compressedrow.rindex;
422       for (i=0; i<arm; i++) {        /* over rows of C in those columns */
423 	r1 = r2 = r3 = r4 = 0.0;
424 	n   = ii[i+1] - ii[i];
425 	aj  = a->j + ii[i];
426 	aa  = a->a + ii[i];
427 	for (j=0; j<n; j++) {
428 	  r1 += (*aa)*b1[*aj];
429 	  r2 += (*aa)*b2[*aj];
430 	  r3 += (*aa)*b3[*aj];
431 	  r4 += (*aa++)*b4[*aj++];
432 	}
433 	c[colam       + ridx[i]] += r1;
434 	c[colam + am  + ridx[i]] += r2;
435 	c[colam + am2 + ridx[i]] += r3;
436 	c[colam + am3 + ridx[i]] += r4;
437       }
438       b1 += bm4;
439       b2 += bm4;
440       b3 += bm4;
441       b4 += bm4;
442     }
443     for (;col<cn; col++){     /* over extra columns of C */
444       colam = col*am;
445       arm   = a->compressedrow.nrows;
446       ii    = a->compressedrow.i;
447       ridx  = a->compressedrow.rindex;
448       for (i=0; i<arm; i++) {  /* over rows of C in those columns */
449 	r1 = 0.0;
450 	n   = ii[i+1] - ii[i];
451 	aj  = a->j + ii[i];
452 	aa  = a->a + ii[i];
453 
454 	for (j=0; j<n; j++) {
455 	  r1 += (*aa++)*b1[*aj++];
456 	}
457 	c[col*am + ridx[i]] += r1;
458       }
459       b1 += bm;
460     }
461   } else {
462     for (col=0; col<cn-4; col += 4){  /* over columns of C */
463       colam = col*am;
464       for (i=0; i<am; i++) {        /* over rows of C in those columns */
465 	r1 = r2 = r3 = r4 = 0.0;
466 	n   = a->i[i+1] - a->i[i];
467 	aj  = a->j + a->i[i];
468 	aa  = a->a + a->i[i];
469 	for (j=0; j<n; j++) {
470 	  r1 += (*aa)*b1[*aj];
471 	  r2 += (*aa)*b2[*aj];
472 	  r3 += (*aa)*b3[*aj];
473 	  r4 += (*aa++)*b4[*aj++];
474 	}
475 	c[colam + i]       += r1;
476 	c[colam + am + i]  += r2;
477 	c[colam + am2 + i] += r3;
478 	c[colam + am3 + i] += r4;
479       }
480       b1 += bm4;
481       b2 += bm4;
482       b3 += bm4;
483       b4 += bm4;
484     }
485     for (;col<cn; col++){     /* over extra columns of C */
486       for (i=0; i<am; i++) {  /* over rows of C in those columns */
487 	r1 = 0.0;
488 	n   = a->i[i+1] - a->i[i];
489 	aj  = a->j + a->i[i];
490 	aa  = a->a + a->i[i];
491 
492 	for (j=0; j<n; j++) {
493 	  r1 += (*aa++)*b1[*aj++];
494 	}
495 	c[col*am + i]     += r1;
496       }
497       b1 += bm;
498     }
499   }
500   ierr = PetscLogFlops(cn*2.0*a->nz);CHKERRQ(ierr);
501   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
502   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
503   PetscFunctionReturn(0);
504 }
505