xref: /petsc/src/mat/impls/aij/seq/matmatmult.c (revision 2a6744eb01855f5aa328eb8fdf4b0d01e72ad151)
1 #define PETSCMAT_DLL
2 
3 /*
4   Defines matrix-matrix product routines for pairs of SeqAIJ matrices
5           C = A * B
6 */
7 
8 #include "src/mat/impls/aij/seq/aij.h" /*I "petscmat.h" I*/
9 #include "src/mat/utils/freespace.h"
10 #include "petscbt.h"
11 #include "src/mat/impls/dense/seq/dense.h" /*I "petscmat.h" I*/
12 
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 
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 
41   PetscFunctionBegin;
42   /* Set up */
43   /* Allocate ci array, arrays for fill computation and */
44   /* free space for accumulating nonzero column info */
45   ierr = PetscMalloc(((am+1)+1)*sizeof(PetscInt),&ci);CHKERRQ(ierr);
46   ci[0] = 0;
47 
48   /* create and initialize a linked list */
49   nlnk = bn+1;
50   ierr = PetscLLCreate(bn,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr);
51 
52   /* Initial FreeSpace size is fill*(nnz(A)+nnz(B)) */
53   ierr = PetscFreeSpaceGet((PetscInt)(fill*(ai[am]+bi[bm])),&free_space);CHKERRQ(ierr);
54   current_space = free_space;
55 
56   /* Determine symbolic info for each row of the product: */
57   for (i=0;i<am;i++) {
58     anzi = ai[i+1] - ai[i];
59     cnzi = 0;
60     j    = anzi;
61     aj   = a->j + ai[i];
62     while (j){/* assume cols are almost in increasing order, starting from its end saves computation */
63       j--;
64       brow = *(aj + j);
65       bnzj = bi[brow+1] - bi[brow];
66       bjj  = bj + bi[brow];
67       /* add non-zero cols of B into the sorted linked list lnk */
68       ierr = PetscLLAdd(bnzj,bjj,bn,nlnk,lnk,lnkbt);CHKERRQ(ierr);
69       cnzi += nlnk;
70     }
71 
72     /* If free space is not available, make more free space */
73     /* Double the amount of total space in the list */
74     if (current_space->local_remaining<cnzi) {
75       ierr = PetscFreeSpaceGet(current_space->total_array_size,&current_space);CHKERRQ(ierr);
76       nspacedouble++;
77     }
78 
79     /* Copy data into free space, then initialize lnk */
80     ierr = PetscLLClean(bn,bn,cnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr);
81     current_space->array           += cnzi;
82     current_space->local_used      += cnzi;
83     current_space->local_remaining -= cnzi;
84 
85     ci[i+1] = ci[i] + cnzi;
86   }
87 
88   /* Column indices are in the list of free space */
89   /* Allocate space for cj, initialize cj, and */
90   /* destroy list of free space and other temporary array(s) */
91   ierr = PetscMalloc((ci[am]+1)*sizeof(PetscInt),&cj);CHKERRQ(ierr);
92   ierr = PetscFreeSpaceContiguous(&free_space,cj);CHKERRQ(ierr);
93   ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr);
94 
95   /* Allocate space for ca */
96   ierr = PetscMalloc((ci[am]+1)*sizeof(MatScalar),&ca);CHKERRQ(ierr);
97   ierr = PetscMemzero(ca,(ci[am]+1)*sizeof(MatScalar));CHKERRQ(ierr);
98 
99   /* put together the new symbolic matrix */
100   ierr = MatCreateSeqAIJWithArrays(A->comm,am,bn,ci,cj,ca,C);CHKERRQ(ierr);
101 
102   /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
103   /* These are PETSc arrays, so change flags so arrays can be deleted by PETSc */
104   c = (Mat_SeqAIJ *)((*C)->data);
105   c->free_a   = PETSC_TRUE;
106   c->free_ij  = PETSC_TRUE;
107   c->nonew    = 0;
108 
109   if (nspacedouble){
110     ierr = PetscInfo5((*C),"nspacedouble:%D, nnz(A):%D, nnz(B):%D, fill:%G, nnz(C):%D\n",nspacedouble,ai[am],bi[bm],fill,ci[am]);CHKERRQ(ierr);
111   }
112   PetscFunctionReturn(0);
113 }
114 
115 
116 #undef __FUNCT__
117 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqAIJ"
118 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
119 {
120   PetscErrorCode ierr;
121   PetscInt       flops=0;
122   Mat_SeqAIJ     *a = (Mat_SeqAIJ *)A->data;
123   Mat_SeqAIJ     *b = (Mat_SeqAIJ *)B->data;
124   Mat_SeqAIJ     *c = (Mat_SeqAIJ *)C->data;
125   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci=c->i,*cj=c->j;
126   PetscInt       am=A->rmap.N,cm=C->rmap.N;
127   PetscInt       i,j,k,anzi,bnzi,cnzi,brow,nextb;
128   MatScalar      *aa=a->a,*ba=b->a,*baj,*ca=c->a;
129 
130   PetscFunctionBegin;
131   /* clean old values in C */
132   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
133   /* Traverse A row-wise. */
134   /* Build the ith row in C by summing over nonzero columns in A, */
135   /* the rows of B corresponding to nonzeros of A. */
136   for (i=0;i<am;i++) {
137     anzi = ai[i+1] - ai[i];
138     for (j=0;j<anzi;j++) {
139       brow = *aj++;
140       bnzi = bi[brow+1] - bi[brow];
141       bjj  = bj + bi[brow];
142       baj  = ba + bi[brow];
143       nextb = 0;
144       for (k=0; nextb<bnzi; k++) {
145         if (cj[k] == bjj[nextb]){ /* ccol == bcol */
146           ca[k] += (*aa)*baj[nextb++];
147         }
148       }
149       flops += 2*bnzi;
150       aa++;
151     }
152     cnzi = ci[i+1] - ci[i];
153     ca += cnzi;
154     cj += cnzi;
155   }
156   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
157   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
158 
159   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
160   PetscFunctionReturn(0);
161 }
162 
163 
164 #undef __FUNCT__
165 #define __FUNCT__ "MatMatMultTranspose_SeqAIJ_SeqAIJ"
166 PetscErrorCode MatMatMultTranspose_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) {
167   PetscErrorCode ierr;
168 
169   PetscFunctionBegin;
170   if (scall == MAT_INITIAL_MATRIX){
171     ierr = MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr);
172   }
173   ierr = MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
174   PetscFunctionReturn(0);
175 }
176 
177 #undef __FUNCT__
178 #define __FUNCT__ "MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ"
179 PetscErrorCode MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
180 {
181   PetscErrorCode ierr;
182   Mat            At;
183   PetscInt       *ati,*atj;
184 
185   PetscFunctionBegin;
186   /* create symbolic At */
187   ierr = MatGetSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
188   ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,A->cmap.n,A->rmap.n,ati,atj,PETSC_NULL,&At);CHKERRQ(ierr);
189 
190   /* get symbolic C=At*B */
191   ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(At,B,fill,C);CHKERRQ(ierr);
192 
193   /* clean up */
194   ierr = MatDestroy(At);CHKERRQ(ierr);
195   ierr = MatRestoreSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
196 
197   PetscFunctionReturn(0);
198 }
199 
200 #undef __FUNCT__
201 #define __FUNCT__ "MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ"
202 PetscErrorCode MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
203 {
204   PetscErrorCode ierr;
205   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c=(Mat_SeqAIJ*)C->data;
206   PetscInt       am=A->rmap.n,anzi,*ai=a->i,*aj=a->j,*bi=b->i,*bj,bnzi,nextb;
207   PetscInt       cm=C->rmap.n,*ci=c->i,*cj=c->j,crow,*cjj,i,j,k,flops=0;
208   MatScalar      *aa=a->a,*ba,*ca=c->a,*caj;
209 
210   PetscFunctionBegin;
211   /* clear old values in C */
212   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
213 
214   /* compute A^T*B using outer product (A^T)[:,i]*B[i,:] */
215   for (i=0;i<am;i++) {
216     bj   = b->j + bi[i];
217     ba   = b->a + bi[i];
218     bnzi = bi[i+1] - bi[i];
219     anzi = ai[i+1] - ai[i];
220     for (j=0; j<anzi; j++) {
221       nextb = 0;
222       crow  = *aj++;
223       cjj   = cj + ci[crow];
224       caj   = ca + ci[crow];
225       /* perform sparse axpy operation.  Note cjj includes bj. */
226       for (k=0; nextb<bnzi; k++) {
227         if (cjj[k] == *(bj+nextb)) { /* ccol == bcol */
228           caj[k] += (*aa)*(*(ba+nextb));
229           nextb++;
230         }
231       }
232       flops += 2*bnzi;
233       aa++;
234     }
235   }
236 
237   /* Assemble the final matrix and clean up */
238   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
239   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
240   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
241   PetscFunctionReturn(0);
242 }
243 
244 #undef __FUNCT__
245 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqDense"
246 PetscErrorCode MatMatMult_SeqAIJ_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
247 {
248   PetscErrorCode ierr;
249 
250   PetscFunctionBegin;
251   if (scall == MAT_INITIAL_MATRIX){
252     ierr = MatMatMultSymbolic_SeqAIJ_SeqDense(A,B,fill,C);CHKERRQ(ierr);
253   }
254   ierr = MatMatMultNumeric_SeqAIJ_SeqDense(A,B,*C);CHKERRQ(ierr);
255   PetscFunctionReturn(0);
256 }
257 
258 #undef __FUNCT__
259 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqDense"
260 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
261 {
262   PetscErrorCode ierr;
263 
264   PetscFunctionBegin;
265   ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,0.0,C);
266   PetscFunctionReturn(0);
267 }
268 
269 #undef __FUNCT__
270 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqDense"
271 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
272 {
273   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
274   PetscErrorCode ierr;
275   PetscScalar    *b,*c,r1,r2,r3,r4,*aa,*b1,*b2,*b3,*b4;
276   PetscInt       cm=C->rmap.n, cn=B->cmap.n, bm=B->rmap.n, col, i,j,n,*aj, am = A->rmap.n;
277   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam;
278 
279   PetscFunctionBegin;
280   if (!cm || !cn) PetscFunctionReturn(0);
281   if (bm != A->cmap.n) SETERRQ2(PETSC_ERR_ARG_SIZ,"Number columns in A %D not equal rows in B %D\n",A->cmap.n,bm);
282   if (A->rmap.n != C->rmap.n) SETERRQ2(PETSC_ERR_ARG_SIZ,"Number rows in C %D not equal rows in A %D\n",C->rmap.n,A->rmap.n);
283   if (B->cmap.n != C->cmap.n) SETERRQ2(PETSC_ERR_ARG_SIZ,"Number columns in B %D not equal columns in C %D\n",B->cmap.n,C->cmap.n);
284   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
285   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
286   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
287   for (col=0; col<cn-4; col += 4){  /* over columns of C */
288     colam = col*am;
289     for (i=0; i<am; i++) {        /* over rows of C in those columns */
290       r1 = r2 = r3 = r4 = 0.0;
291       n   = a->i[i+1] - a->i[i];
292       aj  = a->j + a->i[i];
293       aa  = a->a + a->i[i];
294       for (j=0; j<n; j++) {
295         r1 += (*aa)*b1[*aj];
296         r2 += (*aa)*b2[*aj];
297         r3 += (*aa)*b3[*aj];
298         r4 += (*aa++)*b4[*aj++];
299       }
300       c[colam + i]       = r1;
301       c[colam + am + i]  = r2;
302       c[colam + am2 + i] = r3;
303       c[colam + am3 + i] = r4;
304     }
305     b1 += bm4;
306     b2 += bm4;
307     b3 += bm4;
308     b4 += bm4;
309   }
310   for (;col<cn; col++){     /* over extra columns of C */
311     for (i=0; i<am; i++) {  /* over rows of C in those columns */
312       r1 = 0.0;
313       n   = a->i[i+1] - a->i[i];
314       aj  = a->j + a->i[i];
315       aa  = a->a + a->i[i];
316 
317       for (j=0; j<n; j++) {
318         r1 += (*aa++)*b1[*aj++];
319       }
320       c[col*am + i]     = r1;
321     }
322     b1 += bm;
323   }
324   ierr = PetscLogFlops(cn*(2*a->nz - A->rmap.n));CHKERRQ(ierr);
325   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
326   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
327   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
328   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
329   PetscFunctionReturn(0);
330 }
331 
332 /*
333    Note very similar to MatMult_SeqAIJ(), should generate both codes from same base
334 */
335 #undef __FUNCT__
336 #define __FUNCT__ "MatMatMultNumericAdd_SeqAIJ_SeqDense"
337 PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
338 {
339   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
340   PetscErrorCode ierr;
341   PetscScalar    *b,*c,r1,r2,r3,r4,*aa,*b1,*b2,*b3,*b4;
342   PetscInt       cm=C->rmap.n, cn=B->cmap.n, bm=B->rmap.n, col, i,j,n,*aj, am = A->rmap.n,*ii,arm;
343   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam,*ridx;
344 
345   PetscFunctionBegin;
346   if (!cm || !cn) PetscFunctionReturn(0);
347   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
348   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
349   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
350 
351   if (a->compressedrow.use){ /* use compressed row format */
352     for (col=0; col<cn-4; col += 4){  /* over columns of C */
353       colam = col*am;
354       arm   = a->compressedrow.nrows;
355       ii    = a->compressedrow.i;
356       ridx  = a->compressedrow.rindex;
357       for (i=0; i<arm; i++) {        /* over rows of C in those columns */
358 	r1 = r2 = r3 = r4 = 0.0;
359 	n   = ii[i+1] - ii[i];
360 	aj  = a->j + ii[i];
361 	aa  = a->a + ii[i];
362 	for (j=0; j<n; j++) {
363 	  r1 += (*aa)*b1[*aj];
364 	  r2 += (*aa)*b2[*aj];
365 	  r3 += (*aa)*b3[*aj];
366 	  r4 += (*aa++)*b4[*aj++];
367 	}
368 	c[colam       + ridx[i]] += r1;
369 	c[colam + am  + ridx[i]] += r2;
370 	c[colam + am2 + ridx[i]] += r3;
371 	c[colam + am3 + ridx[i]] += r4;
372       }
373       b1 += bm4;
374       b2 += bm4;
375       b3 += bm4;
376       b4 += bm4;
377     }
378     for (;col<cn; col++){     /* over extra columns of C */
379       colam = col*am;
380       arm   = a->compressedrow.nrows;
381       ii    = a->compressedrow.i;
382       ridx  = a->compressedrow.rindex;
383       for (i=0; i<arm; i++) {  /* over rows of C in those columns */
384 	r1 = 0.0;
385 	n   = ii[i+1] - ii[i];
386 	aj  = a->j + ii[i];
387 	aa  = a->a + ii[i];
388 
389 	for (j=0; j<n; j++) {
390 	  r1 += (*aa++)*b1[*aj++];
391 	}
392 	c[col*am + ridx[i]] += r1;
393       }
394       b1 += bm;
395     }
396   } else {
397     for (col=0; col<cn-4; col += 4){  /* over columns of C */
398       colam = col*am;
399       for (i=0; i<am; i++) {        /* over rows of C in those columns */
400 	r1 = r2 = r3 = r4 = 0.0;
401 	n   = a->i[i+1] - a->i[i];
402 	aj  = a->j + a->i[i];
403 	aa  = a->a + a->i[i];
404 	for (j=0; j<n; j++) {
405 	  r1 += (*aa)*b1[*aj];
406 	  r2 += (*aa)*b2[*aj];
407 	  r3 += (*aa)*b3[*aj];
408 	  r4 += (*aa++)*b4[*aj++];
409 	}
410 	c[colam + i]       += r1;
411 	c[colam + am + i]  += r2;
412 	c[colam + am2 + i] += r3;
413 	c[colam + am3 + i] += r4;
414       }
415       b1 += bm4;
416       b2 += bm4;
417       b3 += bm4;
418       b4 += bm4;
419     }
420     for (;col<cn; col++){     /* over extra columns of C */
421       for (i=0; i<am; i++) {  /* over rows of C in those columns */
422 	r1 = 0.0;
423 	n   = a->i[i+1] - a->i[i];
424 	aj  = a->j + a->i[i];
425 	aa  = a->a + a->i[i];
426 
427 	for (j=0; j<n; j++) {
428 	  r1 += (*aa++)*b1[*aj++];
429 	}
430 	c[col*am + i]     += r1;
431       }
432       b1 += bm;
433     }
434   }
435   ierr = PetscLogFlops(cn*2*a->nz);CHKERRQ(ierr);
436   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
437   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
438   PetscFunctionReturn(0);
439 }
440