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(cnzi+current_space->total_array_size,¤t_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 PetscLogDouble flops=0.0; 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; 215 PetscLogDouble flops=0.0; 216 MatScalar *aa=a->a,*ba,*ca=c->a,*caj; 217 218 PetscFunctionBegin; 219 /* clear old values in C */ 220 ierr = PetscMemzero(ca,ci[cm]*sizeof(MatScalar));CHKERRQ(ierr); 221 222 /* compute A^T*B using outer product (A^T)[:,i]*B[i,:] */ 223 for (i=0;i<am;i++) { 224 bj = b->j + bi[i]; 225 ba = b->a + bi[i]; 226 bnzi = bi[i+1] - bi[i]; 227 anzi = ai[i+1] - ai[i]; 228 for (j=0; j<anzi; j++) { 229 nextb = 0; 230 crow = *aj++; 231 cjj = cj + ci[crow]; 232 caj = ca + ci[crow]; 233 /* perform sparse axpy operation. Note cjj includes bj. */ 234 for (k=0; nextb<bnzi; k++) { 235 if (cjj[k] == *(bj+nextb)) { /* ccol == bcol */ 236 caj[k] += (*aa)*(*(ba+nextb)); 237 nextb++; 238 } 239 } 240 flops += 2*bnzi; 241 aa++; 242 } 243 } 244 245 /* Assemble the final matrix and clean up */ 246 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 247 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 248 ierr = PetscLogFlops(flops);CHKERRQ(ierr); 249 PetscFunctionReturn(0); 250 } 251 252 #undef __FUNCT__ 253 #define __FUNCT__ "MatMatMult_SeqAIJ_SeqDense" 254 PetscErrorCode MatMatMult_SeqAIJ_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 255 { 256 PetscErrorCode ierr; 257 258 PetscFunctionBegin; 259 if (scall == MAT_INITIAL_MATRIX){ 260 ierr = MatMatMultSymbolic_SeqAIJ_SeqDense(A,B,fill,C);CHKERRQ(ierr); 261 } 262 ierr = MatMatMultNumeric_SeqAIJ_SeqDense(A,B,*C);CHKERRQ(ierr); 263 PetscFunctionReturn(0); 264 } 265 266 #undef __FUNCT__ 267 #define __FUNCT__ "MatMatMultSymbolic_SeqAIJ_SeqDense" 268 PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 269 { 270 PetscErrorCode ierr; 271 272 PetscFunctionBegin; 273 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,0.0,C); 274 PetscFunctionReturn(0); 275 } 276 277 #undef __FUNCT__ 278 #define __FUNCT__ "MatMatMultNumeric_SeqAIJ_SeqDense" 279 PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqDense(Mat A,Mat B,Mat C) 280 { 281 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 282 PetscErrorCode ierr; 283 PetscScalar *b,*c,r1,r2,r3,r4,*b1,*b2,*b3,*b4; 284 MatScalar *aa; 285 PetscInt cm=C->rmap->n, cn=B->cmap->n, bm=B->rmap->n, col, i,j,n,*aj, am = A->rmap->n; 286 PetscInt am2 = 2*am, am3 = 3*am, bm4 = 4*bm,colam; 287 288 PetscFunctionBegin; 289 if (!cm || !cn) PetscFunctionReturn(0); 290 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); 291 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); 292 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); 293 ierr = MatGetArray(B,&b);CHKERRQ(ierr); 294 ierr = MatGetArray(C,&c);CHKERRQ(ierr); 295 b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm; 296 for (col=0; col<cn-4; col += 4){ /* over columns of C */ 297 colam = col*am; 298 for (i=0; i<am; i++) { /* over rows of C in those columns */ 299 r1 = r2 = r3 = r4 = 0.0; 300 n = a->i[i+1] - a->i[i]; 301 aj = a->j + a->i[i]; 302 aa = a->a + a->i[i]; 303 for (j=0; j<n; j++) { 304 r1 += (*aa)*b1[*aj]; 305 r2 += (*aa)*b2[*aj]; 306 r3 += (*aa)*b3[*aj]; 307 r4 += (*aa++)*b4[*aj++]; 308 } 309 c[colam + i] = r1; 310 c[colam + am + i] = r2; 311 c[colam + am2 + i] = r3; 312 c[colam + am3 + i] = r4; 313 } 314 b1 += bm4; 315 b2 += bm4; 316 b3 += bm4; 317 b4 += bm4; 318 } 319 for (;col<cn; col++){ /* over extra columns of C */ 320 for (i=0; i<am; i++) { /* over rows of C in those columns */ 321 r1 = 0.0; 322 n = a->i[i+1] - a->i[i]; 323 aj = a->j + a->i[i]; 324 aa = a->a + a->i[i]; 325 326 for (j=0; j<n; j++) { 327 r1 += (*aa++)*b1[*aj++]; 328 } 329 c[col*am + i] = r1; 330 } 331 b1 += bm; 332 } 333 ierr = PetscLogFlops(cn*(2*a->nz));CHKERRQ(ierr); 334 ierr = MatRestoreArray(B,&b);CHKERRQ(ierr); 335 ierr = MatRestoreArray(C,&c);CHKERRQ(ierr); 336 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 337 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 338 PetscFunctionReturn(0); 339 } 340 341 /* 342 Note very similar to MatMult_SeqAIJ(), should generate both codes from same base 343 */ 344 #undef __FUNCT__ 345 #define __FUNCT__ "MatMatMultNumericAdd_SeqAIJ_SeqDense" 346 PetscErrorCode MatMatMultNumericAdd_SeqAIJ_SeqDense(Mat A,Mat B,Mat C) 347 { 348 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 349 PetscErrorCode ierr; 350 PetscScalar *b,*c,r1,r2,r3,r4,*b1,*b2,*b3,*b4; 351 MatScalar *aa; 352 PetscInt cm=C->rmap->n, cn=B->cmap->n, bm=B->rmap->n, col, i,j,n,*aj, am = A->rmap->n,*ii,arm; 353 PetscInt am2 = 2*am, am3 = 3*am, bm4 = 4*bm,colam,*ridx; 354 355 PetscFunctionBegin; 356 if (!cm || !cn) PetscFunctionReturn(0); 357 ierr = MatGetArray(B,&b);CHKERRQ(ierr); 358 ierr = MatGetArray(C,&c);CHKERRQ(ierr); 359 b1 = b; b2 = b1 + bm; b3 = b2 + bm; b4 = b3 + bm; 360 361 if (a->compressedrow.use){ /* use compressed row format */ 362 for (col=0; col<cn-4; col += 4){ /* over columns of C */ 363 colam = col*am; 364 arm = a->compressedrow.nrows; 365 ii = a->compressedrow.i; 366 ridx = a->compressedrow.rindex; 367 for (i=0; i<arm; i++) { /* over rows of C in those columns */ 368 r1 = r2 = r3 = r4 = 0.0; 369 n = ii[i+1] - ii[i]; 370 aj = a->j + ii[i]; 371 aa = a->a + ii[i]; 372 for (j=0; j<n; j++) { 373 r1 += (*aa)*b1[*aj]; 374 r2 += (*aa)*b2[*aj]; 375 r3 += (*aa)*b3[*aj]; 376 r4 += (*aa++)*b4[*aj++]; 377 } 378 c[colam + ridx[i]] += r1; 379 c[colam + am + ridx[i]] += r2; 380 c[colam + am2 + ridx[i]] += r3; 381 c[colam + am3 + ridx[i]] += r4; 382 } 383 b1 += bm4; 384 b2 += bm4; 385 b3 += bm4; 386 b4 += bm4; 387 } 388 for (;col<cn; col++){ /* over extra columns of C */ 389 colam = col*am; 390 arm = a->compressedrow.nrows; 391 ii = a->compressedrow.i; 392 ridx = a->compressedrow.rindex; 393 for (i=0; i<arm; i++) { /* over rows of C in those columns */ 394 r1 = 0.0; 395 n = ii[i+1] - ii[i]; 396 aj = a->j + ii[i]; 397 aa = a->a + ii[i]; 398 399 for (j=0; j<n; j++) { 400 r1 += (*aa++)*b1[*aj++]; 401 } 402 c[col*am + ridx[i]] += r1; 403 } 404 b1 += bm; 405 } 406 } else { 407 for (col=0; col<cn-4; col += 4){ /* over columns of C */ 408 colam = col*am; 409 for (i=0; i<am; i++) { /* over rows of C in those columns */ 410 r1 = r2 = r3 = r4 = 0.0; 411 n = a->i[i+1] - a->i[i]; 412 aj = a->j + a->i[i]; 413 aa = a->a + a->i[i]; 414 for (j=0; j<n; j++) { 415 r1 += (*aa)*b1[*aj]; 416 r2 += (*aa)*b2[*aj]; 417 r3 += (*aa)*b3[*aj]; 418 r4 += (*aa++)*b4[*aj++]; 419 } 420 c[colam + i] += r1; 421 c[colam + am + i] += r2; 422 c[colam + am2 + i] += r3; 423 c[colam + am3 + i] += r4; 424 } 425 b1 += bm4; 426 b2 += bm4; 427 b3 += bm4; 428 b4 += bm4; 429 } 430 for (;col<cn; col++){ /* over extra columns of C */ 431 for (i=0; i<am; i++) { /* over rows of C in those columns */ 432 r1 = 0.0; 433 n = a->i[i+1] - a->i[i]; 434 aj = a->j + a->i[i]; 435 aa = a->a + a->i[i]; 436 437 for (j=0; j<n; j++) { 438 r1 += (*aa++)*b1[*aj++]; 439 } 440 c[col*am + i] += r1; 441 } 442 b1 += bm; 443 } 444 } 445 ierr = PetscLogFlops(cn*2*a->nz);CHKERRQ(ierr); 446 ierr = MatRestoreArray(B,&b);CHKERRQ(ierr); 447 ierr = MatRestoreArray(C,&c);CHKERRQ(ierr); 448 PetscFunctionReturn(0); 449 } 450