xref: /petsc/src/mat/impls/aij/seq/matmatmult.c (revision fd705b320d8d44969be9ca25a36dbdd35fbe8e12)
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(((PetscObject)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 defined(PETSC_USE_INFO)
110   if (ci[am] != 0) {
111     PetscReal afill = ((PetscReal)ci[am])/(ai[am]+bi[bm]);
112     if (afill < 1.0) afill = 1.0;
113     ierr = PetscInfo3((*C),"Reallocs %D; Fill ratio: given %G needed %G.\n",nspacedouble,fill,afill);CHKERRQ(ierr);
114     ierr = PetscInfo1((*C),"Use MatMatMult(A,B,MatReuse,%G,&C) for best performance.;\n",afill);CHKERRQ(ierr);
115   } else {
116     ierr = PetscInfo((*C),"Empty matrix product\n");CHKERRQ(ierr);
117   }
118 #endif
119   PetscFunctionReturn(0);
120 }
121 
122 
123 #undef __FUNCT__
124 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqAIJ"
125 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat A,Mat B,Mat C)
126 {
127   PetscErrorCode ierr;
128   PetscInt       flops=0;
129   Mat_SeqAIJ     *a = (Mat_SeqAIJ *)A->data;
130   Mat_SeqAIJ     *b = (Mat_SeqAIJ *)B->data;
131   Mat_SeqAIJ     *c = (Mat_SeqAIJ *)C->data;
132   PetscInt       *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*bjj,*ci=c->i,*cj=c->j;
133   PetscInt       am=A->rmap.N,cm=C->rmap.N;
134   PetscInt       i,j,k,anzi,bnzi,cnzi,brow,nextb;
135   MatScalar      *aa=a->a,*ba=b->a,*baj,*ca=c->a;
136 
137   PetscFunctionBegin;
138   /* clean old values in C */
139   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
140   /* Traverse A row-wise. */
141   /* Build the ith row in C by summing over nonzero columns in A, */
142   /* the rows of B corresponding to nonzeros of A. */
143   for (i=0;i<am;i++) {
144     anzi = ai[i+1] - ai[i];
145     for (j=0;j<anzi;j++) {
146       brow = *aj++;
147       bnzi = bi[brow+1] - bi[brow];
148       bjj  = bj + bi[brow];
149       baj  = ba + bi[brow];
150       nextb = 0;
151       for (k=0; nextb<bnzi; k++) {
152         if (cj[k] == bjj[nextb]){ /* ccol == bcol */
153           ca[k] += (*aa)*baj[nextb++];
154         }
155       }
156       flops += 2*bnzi;
157       aa++;
158     }
159     cnzi = ci[i+1] - ci[i];
160     ca += cnzi;
161     cj += cnzi;
162   }
163   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
164   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
165 
166   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
167   PetscFunctionReturn(0);
168 }
169 
170 
171 #undef __FUNCT__
172 #define __FUNCT__ "MatMatMultTranspose_SeqAIJ_SeqAIJ"
173 PetscErrorCode MatMatMultTranspose_SeqAIJ_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) {
174   PetscErrorCode ierr;
175 
176   PetscFunctionBegin;
177   if (scall == MAT_INITIAL_MATRIX){
178     ierr = MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(A,B,fill,C);CHKERRQ(ierr);
179   }
180   ierr = MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ(A,B,*C);CHKERRQ(ierr);
181   PetscFunctionReturn(0);
182 }
183 
184 #undef __FUNCT__
185 #define __FUNCT__ "MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ"
186 PetscErrorCode MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
187 {
188   PetscErrorCode ierr;
189   Mat            At;
190   PetscInt       *ati,*atj;
191 
192   PetscFunctionBegin;
193   /* create symbolic At */
194   ierr = MatGetSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
195   ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,A->cmap.n,A->rmap.n,ati,atj,PETSC_NULL,&At);CHKERRQ(ierr);
196 
197   /* get symbolic C=At*B */
198   ierr = MatMatMultSymbolic_SeqAIJ_SeqAIJ(At,B,fill,C);CHKERRQ(ierr);
199 
200   /* clean up */
201   ierr = MatDestroy(At);CHKERRQ(ierr);
202   ierr = MatRestoreSymbolicTranspose_SeqAIJ(A,&ati,&atj);CHKERRQ(ierr);
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   PetscErrorCode ierr;
212   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data,*c=(Mat_SeqAIJ*)C->data;
213   PetscInt       am=A->rmap.n,anzi,*ai=a->i,*aj=a->j,*bi=b->i,*bj,bnzi,nextb;
214   PetscInt       cm=C->rmap.n,*ci=c->i,*cj=c->j,crow,*cjj,i,j,k,flops=0;
215   MatScalar      *aa=a->a,*ba,*ca=c->a,*caj;
216 
217   PetscFunctionBegin;
218   /* clear old values in C */
219   ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr);
220 
221   /* compute A^T*B using outer product (A^T)[:,i]*B[i,:] */
222   for (i=0;i<am;i++) {
223     bj   = b->j + bi[i];
224     ba   = b->a + bi[i];
225     bnzi = bi[i+1] - bi[i];
226     anzi = ai[i+1] - ai[i];
227     for (j=0; j<anzi; j++) {
228       nextb = 0;
229       crow  = *aj++;
230       cjj   = cj + ci[crow];
231       caj   = ca + ci[crow];
232       /* perform sparse axpy operation.  Note cjj includes bj. */
233       for (k=0; nextb<bnzi; k++) {
234         if (cjj[k] == *(bj+nextb)) { /* ccol == bcol */
235           caj[k] += (*aa)*(*(ba+nextb));
236           nextb++;
237         }
238       }
239       flops += 2*bnzi;
240       aa++;
241     }
242   }
243 
244   /* Assemble the final matrix and clean up */
245   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
246   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
247   ierr = PetscLogFlops(flops);CHKERRQ(ierr);
248   PetscFunctionReturn(0);
249 }
250 
251 #undef __FUNCT__
252 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqDense"
253 PetscErrorCode MatMatMult_SeqAIJ_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
254 {
255   PetscErrorCode ierr;
256 
257   PetscFunctionBegin;
258   if (scall == MAT_INITIAL_MATRIX){
259     ierr = MatMatMultSymbolic_SeqAIJ_SeqDense(A,B,fill,C);CHKERRQ(ierr);
260   }
261   ierr = MatMatMultNumeric_SeqAIJ_SeqDense(A,B,*C);CHKERRQ(ierr);
262   PetscFunctionReturn(0);
263 }
264 
265 #undef __FUNCT__
266 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqDense"
267 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C)
268 {
269   PetscErrorCode ierr;
270 
271   PetscFunctionBegin;
272   ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,0.0,C);
273   PetscFunctionReturn(0);
274 }
275 
276 #undef __FUNCT__
277 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqDense"
278 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
279 {
280   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
281   PetscErrorCode ierr;
282   PetscScalar    *b,*c,r1,r2,r3,r4,*aa,*b1,*b2,*b3,*b4;
283   PetscInt       cm=C->rmap.n, cn=B->cmap.n, bm=B->rmap.n, col, i,j,n,*aj, am = A->rmap.n;
284   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam;
285 
286   PetscFunctionBegin;
287   if (!cm || !cn) PetscFunctionReturn(0);
288   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);
289   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);
290   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);
291   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
292   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
293   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
294   for (col=0; col<cn-4; col += 4){  /* over columns of C */
295     colam = col*am;
296     for (i=0; i<am; i++) {        /* over rows of C in those columns */
297       r1 = r2 = r3 = r4 = 0.0;
298       n   = a->i[i+1] - a->i[i];
299       aj  = a->j + a->i[i];
300       aa  = a->a + a->i[i];
301       for (j=0; j<n; j++) {
302         r1 += (*aa)*b1[*aj];
303         r2 += (*aa)*b2[*aj];
304         r3 += (*aa)*b3[*aj];
305         r4 += (*aa++)*b4[*aj++];
306       }
307       c[colam + i]       = r1;
308       c[colam + am + i]  = r2;
309       c[colam + am2 + i] = r3;
310       c[colam + am3 + i] = r4;
311     }
312     b1 += bm4;
313     b2 += bm4;
314     b3 += bm4;
315     b4 += bm4;
316   }
317   for (;col<cn; col++){     /* over extra columns of C */
318     for (i=0; i<am; i++) {  /* over rows of C in those columns */
319       r1 = 0.0;
320       n   = a->i[i+1] - a->i[i];
321       aj  = a->j + a->i[i];
322       aa  = a->a + a->i[i];
323 
324       for (j=0; j<n; j++) {
325         r1 += (*aa++)*b1[*aj++];
326       }
327       c[col*am + i]     = r1;
328     }
329     b1 += bm;
330   }
331   ierr = PetscLogFlops(cn*(2*a->nz - A->rmap.n));CHKERRQ(ierr);
332   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
333   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
334   ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
335   ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
336   PetscFunctionReturn(0);
337 }
338 
339 /*
340    Note very similar to MatMult_SeqAIJ(), should generate both codes from same base
341 */
342 #undef __FUNCT__
343 #define __FUNCT__ "MatMatMultNumericAdd_SeqAIJ_SeqDense"
344 PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat A,Mat B,Mat C)
345 {
346   Mat_SeqAIJ     *a=(Mat_SeqAIJ*)A->data;
347   PetscErrorCode ierr;
348   PetscScalar    *b,*c,r1,r2,r3,r4,*aa,*b1,*b2,*b3,*b4;
349   PetscInt       cm=C->rmap.n, cn=B->cmap.n, bm=B->rmap.n, col, i,j,n,*aj, am = A->rmap.n,*ii,arm;
350   PetscInt       am2 = 2*am, am3 = 3*am,  bm4 = 4*bm,colam,*ridx;
351 
352   PetscFunctionBegin;
353   if (!cm || !cn) PetscFunctionReturn(0);
354   ierr = MatGetArray(B,&b);CHKERRQ(ierr);
355   ierr = MatGetArray(C,&c);CHKERRQ(ierr);
356   b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm;
357 
358   if (a->compressedrow.use){ /* use compressed row format */
359     for (col=0; col<cn-4; col += 4){  /* over columns of C */
360       colam = col*am;
361       arm   = a->compressedrow.nrows;
362       ii    = a->compressedrow.i;
363       ridx  = a->compressedrow.rindex;
364       for (i=0; i<arm; i++) {        /* over rows of C in those columns */
365 	r1 = r2 = r3 = r4 = 0.0;
366 	n   = ii[i+1] - ii[i];
367 	aj  = a->j + ii[i];
368 	aa  = a->a + ii[i];
369 	for (j=0; j<n; j++) {
370 	  r1 += (*aa)*b1[*aj];
371 	  r2 += (*aa)*b2[*aj];
372 	  r3 += (*aa)*b3[*aj];
373 	  r4 += (*aa++)*b4[*aj++];
374 	}
375 	c[colam       + ridx[i]] += r1;
376 	c[colam + am  + ridx[i]] += r2;
377 	c[colam + am2 + ridx[i]] += r3;
378 	c[colam + am3 + ridx[i]] += r4;
379       }
380       b1 += bm4;
381       b2 += bm4;
382       b3 += bm4;
383       b4 += bm4;
384     }
385     for (;col<cn; col++){     /* over extra columns of C */
386       colam = col*am;
387       arm   = a->compressedrow.nrows;
388       ii    = a->compressedrow.i;
389       ridx  = a->compressedrow.rindex;
390       for (i=0; i<arm; i++) {  /* over rows of C in those columns */
391 	r1 = 0.0;
392 	n   = ii[i+1] - ii[i];
393 	aj  = a->j + ii[i];
394 	aa  = a->a + ii[i];
395 
396 	for (j=0; j<n; j++) {
397 	  r1 += (*aa++)*b1[*aj++];
398 	}
399 	c[col*am + ridx[i]] += r1;
400       }
401       b1 += bm;
402     }
403   } else {
404     for (col=0; col<cn-4; col += 4){  /* over columns of C */
405       colam = col*am;
406       for (i=0; i<am; i++) {        /* over rows of C in those columns */
407 	r1 = r2 = r3 = r4 = 0.0;
408 	n   = a->i[i+1] - a->i[i];
409 	aj  = a->j + a->i[i];
410 	aa  = a->a + a->i[i];
411 	for (j=0; j<n; j++) {
412 	  r1 += (*aa)*b1[*aj];
413 	  r2 += (*aa)*b2[*aj];
414 	  r3 += (*aa)*b3[*aj];
415 	  r4 += (*aa++)*b4[*aj++];
416 	}
417 	c[colam + i]       += r1;
418 	c[colam + am + i]  += r2;
419 	c[colam + am2 + i] += r3;
420 	c[colam + am3 + i] += r4;
421       }
422       b1 += bm4;
423       b2 += bm4;
424       b3 += bm4;
425       b4 += bm4;
426     }
427     for (;col<cn; col++){     /* over extra columns of C */
428       for (i=0; i<am; i++) {  /* over rows of C in those columns */
429 	r1 = 0.0;
430 	n   = a->i[i+1] - a->i[i];
431 	aj  = a->j + a->i[i];
432 	aa  = a->a + a->i[i];
433 
434 	for (j=0; j<n; j++) {
435 	  r1 += (*aa++)*b1[*aj++];
436 	}
437 	c[col*am + i]     += r1;
438       }
439       b1 += bm;
440     }
441   }
442   ierr = PetscLogFlops(cn*2*a->nz);CHKERRQ(ierr);
443   ierr = MatRestoreArray(B,&b);CHKERRQ(ierr);
444   ierr = MatRestoreArray(C,&c);CHKERRQ(ierr);
445   PetscFunctionReturn(0);
446 }
447