1 2 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I "petscmat.h" I*/ 3 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 #undef __FUNCT__ 8 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ" 9 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[]) 10 { 11 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 12 PetscErrorCode ierr; 13 PetscInt i,*idxb = 0; 14 PetscScalar *va,*vb; 15 Vec vtmp; 16 17 PetscFunctionBegin; 18 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 19 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 20 if (idx) { 21 for (i=0; i<A->rmap->n; i++) { 22 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 23 } 24 } 25 26 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 27 if (idx) {ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr);} 28 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 29 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 30 31 for (i=0; i<A->rmap->n; i++) { 32 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 33 va[i] = vb[i]; 34 if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs); 35 } 36 } 37 38 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 39 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 40 ierr = PetscFree(idxb);CHKERRQ(ierr); 41 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 42 PetscFunctionReturn(0); 43 } 44 45 #undef __FUNCT__ 46 #define __FUNCT__ "MatStoreValues_MPIBAIJ" 47 PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat) 48 { 49 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 50 PetscErrorCode ierr; 51 52 PetscFunctionBegin; 53 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 54 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 55 PetscFunctionReturn(0); 56 } 57 58 #undef __FUNCT__ 59 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ" 60 PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat) 61 { 62 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)mat->data; 63 PetscErrorCode ierr; 64 65 PetscFunctionBegin; 66 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 67 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 68 PetscFunctionReturn(0); 69 } 70 71 /* 72 Local utility routine that creates a mapping from the global column 73 number to the local number in the off-diagonal part of the local 74 storage of the matrix. This is done in a non scalable way since the 75 length of colmap equals the global matrix length. 76 */ 77 #undef __FUNCT__ 78 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private" 79 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat) 80 { 81 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 82 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 83 PetscErrorCode ierr; 84 PetscInt nbs = B->nbs,i,bs=mat->rmap->bs; 85 86 PetscFunctionBegin; 87 #if defined(PETSC_USE_CTABLE) 88 ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 89 for (i=0; i<nbs; i++) { 90 ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr); 91 } 92 #else 93 ierr = PetscMalloc1(baij->Nbs+1,&baij->colmap);CHKERRQ(ierr); 94 ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 95 ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr); 96 for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1; 97 #endif 98 PetscFunctionReturn(0); 99 } 100 101 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol) \ 102 { \ 103 \ 104 brow = row/bs; \ 105 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 106 rmax = aimax[brow]; nrow = ailen[brow]; \ 107 bcol = col/bs; \ 108 ridx = row % bs; cidx = col % bs; \ 109 low = 0; high = nrow; \ 110 while (high-low > 3) { \ 111 t = (low+high)/2; \ 112 if (rp[t] > bcol) high = t; \ 113 else low = t; \ 114 } \ 115 for (_i=low; _i<high; _i++) { \ 116 if (rp[_i] > bcol) break; \ 117 if (rp[_i] == bcol) { \ 118 bap = ap + bs2*_i + bs*cidx + ridx; \ 119 if (addv == ADD_VALUES) *bap += value; \ 120 else *bap = value; \ 121 goto a_noinsert; \ 122 } \ 123 } \ 124 if (a->nonew == 1) goto a_noinsert; \ 125 if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 126 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \ 127 N = nrow++ - 1; \ 128 /* shift up all the later entries in this row */ \ 129 for (ii=N; ii>=_i; ii--) { \ 130 rp[ii+1] = rp[ii]; \ 131 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 132 } \ 133 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 134 rp[_i] = bcol; \ 135 ap[bs2*_i + bs*cidx + ridx] = value; \ 136 a_noinsert:; \ 137 ailen[brow] = nrow; \ 138 } 139 140 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol) \ 141 { \ 142 brow = row/bs; \ 143 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 144 rmax = bimax[brow]; nrow = bilen[brow]; \ 145 bcol = col/bs; \ 146 ridx = row % bs; cidx = col % bs; \ 147 low = 0; high = nrow; \ 148 while (high-low > 3) { \ 149 t = (low+high)/2; \ 150 if (rp[t] > bcol) high = t; \ 151 else low = t; \ 152 } \ 153 for (_i=low; _i<high; _i++) { \ 154 if (rp[_i] > bcol) break; \ 155 if (rp[_i] == bcol) { \ 156 bap = ap + bs2*_i + bs*cidx + ridx; \ 157 if (addv == ADD_VALUES) *bap += value; \ 158 else *bap = value; \ 159 goto b_noinsert; \ 160 } \ 161 } \ 162 if (b->nonew == 1) goto b_noinsert; \ 163 if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \ 164 MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \ 165 N = nrow++ - 1; \ 166 /* shift up all the later entries in this row */ \ 167 for (ii=N; ii>=_i; ii--) { \ 168 rp[ii+1] = rp[ii]; \ 169 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 170 } \ 171 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 172 rp[_i] = bcol; \ 173 ap[bs2*_i + bs*cidx + ridx] = value; \ 174 b_noinsert:; \ 175 bilen[brow] = nrow; \ 176 } 177 178 #undef __FUNCT__ 179 #define __FUNCT__ "MatSetValues_MPIBAIJ" 180 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 181 { 182 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 183 MatScalar value; 184 PetscBool roworiented = baij->roworiented; 185 PetscErrorCode ierr; 186 PetscInt i,j,row,col; 187 PetscInt rstart_orig=mat->rmap->rstart; 188 PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart; 189 PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs; 190 191 /* Some Variables required in the macro */ 192 Mat A = baij->A; 193 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)(A)->data; 194 PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 195 MatScalar *aa =a->a; 196 197 Mat B = baij->B; 198 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 199 PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 200 MatScalar *ba =b->a; 201 202 PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol; 203 PetscInt low,high,t,ridx,cidx,bs2=a->bs2; 204 MatScalar *ap,*bap; 205 206 PetscFunctionBegin; 207 for (i=0; i<m; i++) { 208 if (im[i] < 0) continue; 209 #if defined(PETSC_USE_DEBUG) 210 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 211 #endif 212 if (im[i] >= rstart_orig && im[i] < rend_orig) { 213 row = im[i] - rstart_orig; 214 for (j=0; j<n; j++) { 215 if (in[j] >= cstart_orig && in[j] < cend_orig) { 216 col = in[j] - cstart_orig; 217 if (roworiented) value = v[i*n+j]; 218 else value = v[i+j*m]; 219 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]); 220 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 221 } else if (in[j] < 0) continue; 222 #if defined(PETSC_USE_DEBUG) 223 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 224 #endif 225 else { 226 if (mat->was_assembled) { 227 if (!baij->colmap) { 228 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 229 } 230 #if defined(PETSC_USE_CTABLE) 231 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 232 col = col - 1; 233 #else 234 col = baij->colmap[in[j]/bs] - 1; 235 #endif 236 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 237 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 238 col = in[j]; 239 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 240 B = baij->B; 241 b = (Mat_SeqBAIJ*)(B)->data; 242 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 243 ba =b->a; 244 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 245 else col += in[j]%bs; 246 } else col = in[j]; 247 if (roworiented) value = v[i*n+j]; 248 else value = v[i+j*m]; 249 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]); 250 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 251 } 252 } 253 } else { 254 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 255 if (!baij->donotstash) { 256 mat->assembled = PETSC_FALSE; 257 if (roworiented) { 258 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 259 } else { 260 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 261 } 262 } 263 } 264 } 265 PetscFunctionReturn(0); 266 } 267 268 #undef __FUNCT__ 269 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ_Inlined" 270 PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol) 271 { 272 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data; 273 PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N; 274 PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen; 275 PetscErrorCode ierr; 276 PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs; 277 PetscBool roworiented=a->roworiented; 278 const PetscScalar *value = v; 279 MatScalar *ap,*aa = a->a,*bap; 280 281 PetscFunctionBegin; 282 rp = aj + ai[row]; 283 ap = aa + bs2*ai[row]; 284 rmax = imax[row]; 285 nrow = ailen[row]; 286 value = v; 287 low = 0; 288 high = nrow; 289 while (high-low > 7) { 290 t = (low+high)/2; 291 if (rp[t] > col) high = t; 292 else low = t; 293 } 294 for (i=low; i<high; i++) { 295 if (rp[i] > col) break; 296 if (rp[i] == col) { 297 bap = ap + bs2*i; 298 if (roworiented) { 299 if (is == ADD_VALUES) { 300 for (ii=0; ii<bs; ii++) { 301 for (jj=ii; jj<bs2; jj+=bs) { 302 bap[jj] += *value++; 303 } 304 } 305 } else { 306 for (ii=0; ii<bs; ii++) { 307 for (jj=ii; jj<bs2; jj+=bs) { 308 bap[jj] = *value++; 309 } 310 } 311 } 312 } else { 313 if (is == ADD_VALUES) { 314 for (ii=0; ii<bs; ii++,value+=bs) { 315 for (jj=0; jj<bs; jj++) { 316 bap[jj] += value[jj]; 317 } 318 bap += bs; 319 } 320 } else { 321 for (ii=0; ii<bs; ii++,value+=bs) { 322 for (jj=0; jj<bs; jj++) { 323 bap[jj] = value[jj]; 324 } 325 bap += bs; 326 } 327 } 328 } 329 goto noinsert2; 330 } 331 } 332 if (nonew == 1) goto noinsert2; 333 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol); 334 MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 335 N = nrow++ - 1; high++; 336 /* shift up all the later entries in this row */ 337 for (ii=N; ii>=i; ii--) { 338 rp[ii+1] = rp[ii]; 339 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); 340 } 341 if (N >= i) { 342 ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr); 343 } 344 rp[i] = col; 345 bap = ap + bs2*i; 346 if (roworiented) { 347 for (ii=0; ii<bs; ii++) { 348 for (jj=ii; jj<bs2; jj+=bs) { 349 bap[jj] = *value++; 350 } 351 } 352 } else { 353 for (ii=0; ii<bs; ii++) { 354 for (jj=0; jj<bs; jj++) { 355 *bap++ = *value++; 356 } 357 } 358 } 359 noinsert2:; 360 ailen[row] = nrow; 361 PetscFunctionReturn(0); 362 } 363 364 #undef __FUNCT__ 365 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ" 366 /* 367 This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed 368 by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine 369 */ 370 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 371 { 372 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 373 const PetscScalar *value; 374 MatScalar *barray = baij->barray; 375 PetscBool roworiented = baij->roworiented; 376 PetscErrorCode ierr; 377 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 378 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 379 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 380 381 PetscFunctionBegin; 382 if (!barray) { 383 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 384 baij->barray = barray; 385 } 386 387 if (roworiented) stepval = (n-1)*bs; 388 else stepval = (m-1)*bs; 389 390 for (i=0; i<m; i++) { 391 if (im[i] < 0) continue; 392 #if defined(PETSC_USE_DEBUG) 393 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1); 394 #endif 395 if (im[i] >= rstart && im[i] < rend) { 396 row = im[i] - rstart; 397 for (j=0; j<n; j++) { 398 /* If NumCol = 1 then a copy is not required */ 399 if ((roworiented) && (n == 1)) { 400 barray = (MatScalar*)v + i*bs2; 401 } else if ((!roworiented) && (m == 1)) { 402 barray = (MatScalar*)v + j*bs2; 403 } else { /* Here a copy is required */ 404 if (roworiented) { 405 value = v + (i*(stepval+bs) + j)*bs; 406 } else { 407 value = v + (j*(stepval+bs) + i)*bs; 408 } 409 for (ii=0; ii<bs; ii++,value+=bs+stepval) { 410 for (jj=0; jj<bs; jj++) barray[jj] = value[jj]; 411 barray += bs; 412 } 413 barray -= bs2; 414 } 415 416 if (in[j] >= cstart && in[j] < cend) { 417 col = in[j] - cstart; 418 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 419 } else if (in[j] < 0) continue; 420 #if defined(PETSC_USE_DEBUG) 421 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1); 422 #endif 423 else { 424 if (mat->was_assembled) { 425 if (!baij->colmap) { 426 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 427 } 428 429 #if defined(PETSC_USE_DEBUG) 430 #if defined(PETSC_USE_CTABLE) 431 { PetscInt data; 432 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 433 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 434 } 435 #else 436 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 437 #endif 438 #endif 439 #if defined(PETSC_USE_CTABLE) 440 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 441 col = (col - 1)/bs; 442 #else 443 col = (baij->colmap[in[j]] - 1)/bs; 444 #endif 445 if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) { 446 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 447 col = in[j]; 448 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked indexed nonzero block (%D, %D) into matrix",im[i],in[j]); 449 } else col = in[j]; 450 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 451 } 452 } 453 } else { 454 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 455 if (!baij->donotstash) { 456 if (roworiented) { 457 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 458 } else { 459 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 460 } 461 } 462 } 463 } 464 PetscFunctionReturn(0); 465 } 466 467 #define HASH_KEY 0.6180339887 468 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp))) 469 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 470 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */ 471 #undef __FUNCT__ 472 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT" 473 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 474 { 475 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 476 PetscBool roworiented = baij->roworiented; 477 PetscErrorCode ierr; 478 PetscInt i,j,row,col; 479 PetscInt rstart_orig=mat->rmap->rstart; 480 PetscInt rend_orig =mat->rmap->rend,Nbs=baij->Nbs; 481 PetscInt h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx; 482 PetscReal tmp; 483 MatScalar **HD = baij->hd,value; 484 #if defined(PETSC_USE_DEBUG) 485 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 486 #endif 487 488 PetscFunctionBegin; 489 for (i=0; i<m; i++) { 490 #if defined(PETSC_USE_DEBUG) 491 if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 492 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 493 #endif 494 row = im[i]; 495 if (row >= rstart_orig && row < rend_orig) { 496 for (j=0; j<n; j++) { 497 col = in[j]; 498 if (roworiented) value = v[i*n+j]; 499 else value = v[i+j*m]; 500 /* Look up PetscInto the Hash Table */ 501 key = (row/bs)*Nbs+(col/bs)+1; 502 h1 = HASH(size,key,tmp); 503 504 505 idx = h1; 506 #if defined(PETSC_USE_DEBUG) 507 insert_ct++; 508 total_ct++; 509 if (HT[idx] != key) { 510 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 511 if (idx == size) { 512 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 513 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 514 } 515 } 516 #else 517 if (HT[idx] != key) { 518 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 519 if (idx == size) { 520 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 521 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 522 } 523 } 524 #endif 525 /* A HASH table entry is found, so insert the values at the correct address */ 526 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 527 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 528 } 529 } else if (!baij->donotstash) { 530 if (roworiented) { 531 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 532 } else { 533 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 534 } 535 } 536 } 537 #if defined(PETSC_USE_DEBUG) 538 baij->ht_total_ct = total_ct; 539 baij->ht_insert_ct = insert_ct; 540 #endif 541 PetscFunctionReturn(0); 542 } 543 544 #undef __FUNCT__ 545 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT" 546 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 547 { 548 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 549 PetscBool roworiented = baij->roworiented; 550 PetscErrorCode ierr; 551 PetscInt i,j,ii,jj,row,col; 552 PetscInt rstart=baij->rstartbs; 553 PetscInt rend =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2; 554 PetscInt h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 555 PetscReal tmp; 556 MatScalar **HD = baij->hd,*baij_a; 557 const PetscScalar *v_t,*value; 558 #if defined(PETSC_USE_DEBUG) 559 PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 560 #endif 561 562 PetscFunctionBegin; 563 if (roworiented) stepval = (n-1)*bs; 564 else stepval = (m-1)*bs; 565 566 for (i=0; i<m; i++) { 567 #if defined(PETSC_USE_DEBUG) 568 if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]); 569 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1); 570 #endif 571 row = im[i]; 572 v_t = v + i*nbs2; 573 if (row >= rstart && row < rend) { 574 for (j=0; j<n; j++) { 575 col = in[j]; 576 577 /* Look up into the Hash Table */ 578 key = row*Nbs+col+1; 579 h1 = HASH(size,key,tmp); 580 581 idx = h1; 582 #if defined(PETSC_USE_DEBUG) 583 total_ct++; 584 insert_ct++; 585 if (HT[idx] != key) { 586 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ; 587 if (idx == size) { 588 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ; 589 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 590 } 591 } 592 #else 593 if (HT[idx] != key) { 594 for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ; 595 if (idx == size) { 596 for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ; 597 if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col); 598 } 599 } 600 #endif 601 baij_a = HD[idx]; 602 if (roworiented) { 603 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 604 /* value = v + (i*(stepval+bs)+j)*bs; */ 605 value = v_t; 606 v_t += bs; 607 if (addv == ADD_VALUES) { 608 for (ii=0; ii<bs; ii++,value+=stepval) { 609 for (jj=ii; jj<bs2; jj+=bs) { 610 baij_a[jj] += *value++; 611 } 612 } 613 } else { 614 for (ii=0; ii<bs; ii++,value+=stepval) { 615 for (jj=ii; jj<bs2; jj+=bs) { 616 baij_a[jj] = *value++; 617 } 618 } 619 } 620 } else { 621 value = v + j*(stepval+bs)*bs + i*bs; 622 if (addv == ADD_VALUES) { 623 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 624 for (jj=0; jj<bs; jj++) { 625 baij_a[jj] += *value++; 626 } 627 } 628 } else { 629 for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) { 630 for (jj=0; jj<bs; jj++) { 631 baij_a[jj] = *value++; 632 } 633 } 634 } 635 } 636 } 637 } else { 638 if (!baij->donotstash) { 639 if (roworiented) { 640 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 641 } else { 642 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 643 } 644 } 645 } 646 } 647 #if defined(PETSC_USE_DEBUG) 648 baij->ht_total_ct = total_ct; 649 baij->ht_insert_ct = insert_ct; 650 #endif 651 PetscFunctionReturn(0); 652 } 653 654 #undef __FUNCT__ 655 #define __FUNCT__ "MatGetValues_MPIBAIJ" 656 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 657 { 658 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 659 PetscErrorCode ierr; 660 PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend; 661 PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data; 662 663 PetscFunctionBegin; 664 for (i=0; i<m; i++) { 665 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 666 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 667 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 668 row = idxm[i] - bsrstart; 669 for (j=0; j<n; j++) { 670 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 671 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 672 if (idxn[j] >= bscstart && idxn[j] < bscend) { 673 col = idxn[j] - bscstart; 674 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 675 } else { 676 if (!baij->colmap) { 677 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 678 } 679 #if defined(PETSC_USE_CTABLE) 680 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 681 data--; 682 #else 683 data = baij->colmap[idxn[j]/bs]-1; 684 #endif 685 if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 686 else { 687 col = data + idxn[j]%bs; 688 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 689 } 690 } 691 } 692 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 693 } 694 PetscFunctionReturn(0); 695 } 696 697 #undef __FUNCT__ 698 #define __FUNCT__ "MatNorm_MPIBAIJ" 699 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm) 700 { 701 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 702 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data; 703 PetscErrorCode ierr; 704 PetscInt i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col; 705 PetscReal sum = 0.0; 706 MatScalar *v; 707 708 PetscFunctionBegin; 709 if (baij->size == 1) { 710 ierr = MatNorm(baij->A,type,nrm);CHKERRQ(ierr); 711 } else { 712 if (type == NORM_FROBENIUS) { 713 v = amat->a; 714 nz = amat->nz*bs2; 715 for (i=0; i<nz; i++) { 716 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 717 } 718 v = bmat->a; 719 nz = bmat->nz*bs2; 720 for (i=0; i<nz; i++) { 721 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 722 } 723 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 724 *nrm = PetscSqrtReal(*nrm); 725 } else if (type == NORM_1) { /* max column sum */ 726 PetscReal *tmp,*tmp2; 727 PetscInt *jj,*garray=baij->garray,cstart=baij->rstartbs; 728 ierr = PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);CHKERRQ(ierr); 729 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 730 v = amat->a; jj = amat->j; 731 for (i=0; i<amat->nz; i++) { 732 for (j=0; j<bs; j++) { 733 col = bs*(cstart + *jj) + j; /* column index */ 734 for (row=0; row<bs; row++) { 735 tmp[col] += PetscAbsScalar(*v); v++; 736 } 737 } 738 jj++; 739 } 740 v = bmat->a; jj = bmat->j; 741 for (i=0; i<bmat->nz; i++) { 742 for (j=0; j<bs; j++) { 743 col = bs*garray[*jj] + j; 744 for (row=0; row<bs; row++) { 745 tmp[col] += PetscAbsScalar(*v); v++; 746 } 747 } 748 jj++; 749 } 750 ierr = MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 751 *nrm = 0.0; 752 for (j=0; j<mat->cmap->N; j++) { 753 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 754 } 755 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 756 } else if (type == NORM_INFINITY) { /* max row sum */ 757 PetscReal *sums; 758 ierr = PetscMalloc1(bs,&sums);CHKERRQ(ierr); 759 sum = 0.0; 760 for (j=0; j<amat->mbs; j++) { 761 for (row=0; row<bs; row++) sums[row] = 0.0; 762 v = amat->a + bs2*amat->i[j]; 763 nz = amat->i[j+1]-amat->i[j]; 764 for (i=0; i<nz; i++) { 765 for (col=0; col<bs; col++) { 766 for (row=0; row<bs; row++) { 767 sums[row] += PetscAbsScalar(*v); v++; 768 } 769 } 770 } 771 v = bmat->a + bs2*bmat->i[j]; 772 nz = bmat->i[j+1]-bmat->i[j]; 773 for (i=0; i<nz; i++) { 774 for (col=0; col<bs; col++) { 775 for (row=0; row<bs; row++) { 776 sums[row] += PetscAbsScalar(*v); v++; 777 } 778 } 779 } 780 for (row=0; row<bs; row++) { 781 if (sums[row] > sum) sum = sums[row]; 782 } 783 } 784 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 785 ierr = PetscFree(sums);CHKERRQ(ierr); 786 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet"); 787 } 788 PetscFunctionReturn(0); 789 } 790 791 /* 792 Creates the hash table, and sets the table 793 This table is created only once. 794 If new entried need to be added to the matrix 795 then the hash table has to be destroyed and 796 recreated. 797 */ 798 #undef __FUNCT__ 799 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private" 800 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor) 801 { 802 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 803 Mat A = baij->A,B=baij->B; 804 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data; 805 PetscInt i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 806 PetscErrorCode ierr; 807 PetscInt ht_size,bs2=baij->bs2,rstart=baij->rstartbs; 808 PetscInt cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs; 809 PetscInt *HT,key; 810 MatScalar **HD; 811 PetscReal tmp; 812 #if defined(PETSC_USE_INFO) 813 PetscInt ct=0,max=0; 814 #endif 815 816 PetscFunctionBegin; 817 if (baij->ht) PetscFunctionReturn(0); 818 819 baij->ht_size = (PetscInt)(factor*nz); 820 ht_size = baij->ht_size; 821 822 /* Allocate Memory for Hash Table */ 823 ierr = PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);CHKERRQ(ierr); 824 HD = baij->hd; 825 HT = baij->ht; 826 827 /* Loop Over A */ 828 for (i=0; i<a->mbs; i++) { 829 for (j=ai[i]; j<ai[i+1]; j++) { 830 row = i+rstart; 831 col = aj[j]+cstart; 832 833 key = row*Nbs + col + 1; 834 h1 = HASH(ht_size,key,tmp); 835 for (k=0; k<ht_size; k++) { 836 if (!HT[(h1+k)%ht_size]) { 837 HT[(h1+k)%ht_size] = key; 838 HD[(h1+k)%ht_size] = a->a + j*bs2; 839 break; 840 #if defined(PETSC_USE_INFO) 841 } else { 842 ct++; 843 #endif 844 } 845 } 846 #if defined(PETSC_USE_INFO) 847 if (k> max) max = k; 848 #endif 849 } 850 } 851 /* Loop Over B */ 852 for (i=0; i<b->mbs; i++) { 853 for (j=bi[i]; j<bi[i+1]; j++) { 854 row = i+rstart; 855 col = garray[bj[j]]; 856 key = row*Nbs + col + 1; 857 h1 = HASH(ht_size,key,tmp); 858 for (k=0; k<ht_size; k++) { 859 if (!HT[(h1+k)%ht_size]) { 860 HT[(h1+k)%ht_size] = key; 861 HD[(h1+k)%ht_size] = b->a + j*bs2; 862 break; 863 #if defined(PETSC_USE_INFO) 864 } else { 865 ct++; 866 #endif 867 } 868 } 869 #if defined(PETSC_USE_INFO) 870 if (k> max) max = k; 871 #endif 872 } 873 } 874 875 /* Print Summary */ 876 #if defined(PETSC_USE_INFO) 877 for (i=0,j=0; i<ht_size; i++) { 878 if (HT[i]) j++; 879 } 880 ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr); 881 #endif 882 PetscFunctionReturn(0); 883 } 884 885 #undef __FUNCT__ 886 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ" 887 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 888 { 889 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 890 PetscErrorCode ierr; 891 PetscInt nstash,reallocs; 892 893 PetscFunctionBegin; 894 if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 895 896 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 897 ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr); 898 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 899 ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 900 ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr); 901 ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 902 PetscFunctionReturn(0); 903 } 904 905 #undef __FUNCT__ 906 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ" 907 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 908 { 909 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 910 Mat_SeqBAIJ *a =(Mat_SeqBAIJ*)baij->A->data; 911 PetscErrorCode ierr; 912 PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2; 913 PetscInt *row,*col; 914 PetscBool r1,r2,r3,other_disassembled; 915 MatScalar *val; 916 PetscMPIInt n; 917 918 PetscFunctionBegin; 919 /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */ 920 if (!baij->donotstash && !mat->nooffprocentries) { 921 while (1) { 922 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 923 if (!flg) break; 924 925 for (i=0; i<n;) { 926 /* Now identify the consecutive vals belonging to the same row */ 927 for (j=i,rstart=row[j]; j<n; j++) { 928 if (row[j] != rstart) break; 929 } 930 if (j < n) ncols = j-i; 931 else ncols = n-i; 932 /* Now assemble all these values with a single function call */ 933 ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 934 i = j; 935 } 936 } 937 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 938 /* Now process the block-stash. Since the values are stashed column-oriented, 939 set the roworiented flag to column oriented, and after MatSetValues() 940 restore the original flags */ 941 r1 = baij->roworiented; 942 r2 = a->roworiented; 943 r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented; 944 945 baij->roworiented = PETSC_FALSE; 946 a->roworiented = PETSC_FALSE; 947 948 (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */ 949 while (1) { 950 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 951 if (!flg) break; 952 953 for (i=0; i<n;) { 954 /* Now identify the consecutive vals belonging to the same row */ 955 for (j=i,rstart=row[j]; j<n; j++) { 956 if (row[j] != rstart) break; 957 } 958 if (j < n) ncols = j-i; 959 else ncols = n-i; 960 ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);CHKERRQ(ierr); 961 i = j; 962 } 963 } 964 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 965 966 baij->roworiented = r1; 967 a->roworiented = r2; 968 969 ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */ 970 } 971 972 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 973 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 974 975 /* determine if any processor has disassembled, if so we must 976 also disassemble ourselfs, in order that we may reassemble. */ 977 /* 978 if nonzero structure of submatrix B cannot change then we know that 979 no processor disassembled thus we can skip this stuff 980 */ 981 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 982 ierr = MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 983 if (mat->was_assembled && !other_disassembled) { 984 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 985 } 986 } 987 988 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 989 ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr); 990 } 991 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 992 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 993 994 #if defined(PETSC_USE_INFO) 995 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 996 ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr); 997 998 baij->ht_total_ct = 0; 999 baij->ht_insert_ct = 0; 1000 } 1001 #endif 1002 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 1003 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 1004 1005 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 1006 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 1007 } 1008 1009 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1010 1011 baij->rowvalues = 0; 1012 1013 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 1014 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 1015 PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate; 1016 ierr = MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1017 } 1018 PetscFunctionReturn(0); 1019 } 1020 1021 extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer); 1022 #include <petscdraw.h> 1023 #undef __FUNCT__ 1024 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket" 1025 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1026 { 1027 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1028 PetscErrorCode ierr; 1029 PetscMPIInt rank = baij->rank; 1030 PetscInt bs = mat->rmap->bs; 1031 PetscBool iascii,isdraw; 1032 PetscViewer sviewer; 1033 PetscViewerFormat format; 1034 1035 PetscFunctionBegin; 1036 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1037 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1038 if (iascii) { 1039 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1040 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1041 MatInfo info; 1042 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1043 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1044 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 1045 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n", 1046 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr); 1047 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1048 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1049 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1050 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1051 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1052 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 1053 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1054 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1057 ierr = PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);CHKERRQ(ierr); 1058 PetscFunctionReturn(0); 1059 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1060 PetscFunctionReturn(0); 1061 } 1062 } 1063 1064 if (isdraw) { 1065 PetscDraw draw; 1066 PetscBool isnull; 1067 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1068 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1069 if (isnull) PetscFunctionReturn(0); 1070 } 1071 1072 { 1073 /* assemble the entire matrix onto first processor. */ 1074 Mat A; 1075 Mat_SeqBAIJ *Aloc; 1076 PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 1077 MatScalar *a; 1078 const char *matname; 1079 1080 /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */ 1081 /* Perhaps this should be the type of mat? */ 1082 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1083 if (!rank) { 1084 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1085 } else { 1086 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1087 } 1088 ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr); 1089 ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); 1090 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1091 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1092 1093 /* copy over the A part */ 1094 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1095 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1096 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1097 1098 for (i=0; i<mbs; i++) { 1099 rvals[0] = bs*(baij->rstartbs + i); 1100 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1101 for (j=ai[i]; j<ai[i+1]; j++) { 1102 col = (baij->cstartbs+aj[j])*bs; 1103 for (k=0; k<bs; k++) { 1104 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1105 col++; a += bs; 1106 } 1107 } 1108 } 1109 /* copy over the B part */ 1110 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1111 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1112 for (i=0; i<mbs; i++) { 1113 rvals[0] = bs*(baij->rstartbs + i); 1114 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1115 for (j=ai[i]; j<ai[i+1]; j++) { 1116 col = baij->garray[aj[j]]*bs; 1117 for (k=0; k<bs; k++) { 1118 ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1119 col++; a += bs; 1120 } 1121 } 1122 } 1123 ierr = PetscFree(rvals);CHKERRQ(ierr); 1124 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1125 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1126 /* 1127 Everyone has to call to draw the matrix since the graphics waits are 1128 synchronized across all processors that share the PetscDraw object 1129 */ 1130 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1131 ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr); 1132 if (!rank) { 1133 ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr); 1134 ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1135 } 1136 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 1137 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1138 ierr = MatDestroy(&A);CHKERRQ(ierr); 1139 } 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatView_MPIBAIJ_Binary" 1145 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer) 1146 { 1147 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)mat->data; 1148 Mat_SeqBAIJ *A = (Mat_SeqBAIJ*)a->A->data; 1149 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data; 1150 PetscErrorCode ierr; 1151 PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen; 1152 PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll; 1153 int fd; 1154 PetscScalar *column_values; 1155 FILE *file; 1156 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1157 PetscInt message_count,flowcontrolcount; 1158 1159 PetscFunctionBegin; 1160 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1161 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1162 nz = bs2*(A->nz + B->nz); 1163 rlen = mat->rmap->n; 1164 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1165 if (!rank) { 1166 header[0] = MAT_FILE_CLASSID; 1167 header[1] = mat->rmap->N; 1168 header[2] = mat->cmap->N; 1169 1170 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1171 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1172 /* get largest number of rows any processor has */ 1173 range = mat->rmap->range; 1174 for (i=1; i<size; i++) { 1175 rlen = PetscMax(rlen,range[i+1] - range[i]); 1176 } 1177 } else { 1178 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1179 } 1180 1181 ierr = PetscMalloc1(rlen/bs,&crow_lens);CHKERRQ(ierr); 1182 /* compute lengths of each row */ 1183 for (i=0; i<a->mbs; i++) { 1184 crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1185 } 1186 /* store the row lengths to the file */ 1187 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1188 if (!rank) { 1189 MPI_Status status; 1190 ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr); 1191 rlen = (range[1] - range[0])/bs; 1192 for (i=0; i<rlen; i++) { 1193 for (j=0; j<bs; j++) { 1194 row_lens[i*bs+j] = bs*crow_lens[i]; 1195 } 1196 } 1197 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1198 for (i=1; i<size; i++) { 1199 rlen = (range[i+1] - range[i])/bs; 1200 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1201 ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1202 for (k=0; k<rlen; k++) { 1203 for (j=0; j<bs; j++) { 1204 row_lens[k*bs+j] = bs*crow_lens[k]; 1205 } 1206 } 1207 ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1208 } 1209 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1210 ierr = PetscFree(row_lens);CHKERRQ(ierr); 1211 } else { 1212 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1213 ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1214 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1215 } 1216 ierr = PetscFree(crow_lens);CHKERRQ(ierr); 1217 1218 /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the 1219 information needed to make it for each row from a block row. This does require more communication but still not more than 1220 the communication needed for the nonzero values */ 1221 nzmax = nz; /* space a largest processor needs */ 1222 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1223 ierr = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr); 1224 cnt = 0; 1225 for (i=0; i<a->mbs; i++) { 1226 pcnt = cnt; 1227 for (j=B->i[i]; j<B->i[i+1]; j++) { 1228 if ((col = garray[B->j[j]]) > cstart) break; 1229 for (l=0; l<bs; l++) { 1230 column_indices[cnt++] = bs*col+l; 1231 } 1232 } 1233 for (k=A->i[i]; k<A->i[i+1]; k++) { 1234 for (l=0; l<bs; l++) { 1235 column_indices[cnt++] = bs*(A->j[k] + cstart)+l; 1236 } 1237 } 1238 for (; j<B->i[i+1]; j++) { 1239 for (l=0; l<bs; l++) { 1240 column_indices[cnt++] = bs*garray[B->j[j]]+l; 1241 } 1242 } 1243 len = cnt - pcnt; 1244 for (k=1; k<bs; k++) { 1245 ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr); 1246 cnt += len; 1247 } 1248 } 1249 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1250 1251 /* store the columns to the file */ 1252 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1253 if (!rank) { 1254 MPI_Status status; 1255 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1256 for (i=1; i<size; i++) { 1257 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1258 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1259 ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1260 ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1261 } 1262 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1263 } else { 1264 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1265 ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1266 ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1267 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1268 } 1269 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1270 1271 /* load up the numerical values */ 1272 ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr); 1273 cnt = 0; 1274 for (i=0; i<a->mbs; i++) { 1275 rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]); 1276 for (j=B->i[i]; j<B->i[i+1]; j++) { 1277 if (garray[B->j[j]] > cstart) break; 1278 for (l=0; l<bs; l++) { 1279 for (ll=0; ll<bs; ll++) { 1280 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1281 } 1282 } 1283 cnt += bs; 1284 } 1285 for (k=A->i[i]; k<A->i[i+1]; k++) { 1286 for (l=0; l<bs; l++) { 1287 for (ll=0; ll<bs; ll++) { 1288 column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll]; 1289 } 1290 } 1291 cnt += bs; 1292 } 1293 for (; j<B->i[i+1]; j++) { 1294 for (l=0; l<bs; l++) { 1295 for (ll=0; ll<bs; ll++) { 1296 column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll]; 1297 } 1298 } 1299 cnt += bs; 1300 } 1301 cnt += (bs-1)*rlen; 1302 } 1303 if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz); 1304 1305 /* store the column values to the file */ 1306 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1307 if (!rank) { 1308 MPI_Status status; 1309 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1310 for (i=1; i<size; i++) { 1311 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1312 ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1313 ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1314 ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1315 } 1316 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1317 } else { 1318 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1319 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1320 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1321 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1322 } 1323 ierr = PetscFree(column_values);CHKERRQ(ierr); 1324 1325 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1326 if (file) { 1327 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1328 } 1329 PetscFunctionReturn(0); 1330 } 1331 1332 #undef __FUNCT__ 1333 #define __FUNCT__ "MatView_MPIBAIJ" 1334 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer) 1335 { 1336 PetscErrorCode ierr; 1337 PetscBool iascii,isdraw,issocket,isbinary; 1338 1339 PetscFunctionBegin; 1340 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1341 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1342 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1343 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1344 if (iascii || isdraw || issocket) { 1345 ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1346 } else if (isbinary) { 1347 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1348 } 1349 PetscFunctionReturn(0); 1350 } 1351 1352 #undef __FUNCT__ 1353 #define __FUNCT__ "MatDestroy_MPIBAIJ" 1354 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat) 1355 { 1356 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1357 PetscErrorCode ierr; 1358 1359 PetscFunctionBegin; 1360 #if defined(PETSC_USE_LOG) 1361 PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N); 1362 #endif 1363 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1364 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 1365 ierr = MatDestroy(&baij->A);CHKERRQ(ierr); 1366 ierr = MatDestroy(&baij->B);CHKERRQ(ierr); 1367 #if defined(PETSC_USE_CTABLE) 1368 ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr); 1369 #else 1370 ierr = PetscFree(baij->colmap);CHKERRQ(ierr); 1371 #endif 1372 ierr = PetscFree(baij->garray);CHKERRQ(ierr); 1373 ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr); 1374 ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr); 1375 ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr); 1376 ierr = PetscFree(baij->barray);CHKERRQ(ierr); 1377 ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr); 1378 ierr = PetscFree(baij->rangebs);CHKERRQ(ierr); 1379 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1380 1381 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1382 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1383 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1384 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1385 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1386 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1387 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1388 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1389 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1390 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1391 PetscFunctionReturn(0); 1392 } 1393 1394 #undef __FUNCT__ 1395 #define __FUNCT__ "MatMult_MPIBAIJ" 1396 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1397 { 1398 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1399 PetscErrorCode ierr; 1400 PetscInt nt; 1401 1402 PetscFunctionBegin; 1403 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1404 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1405 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1406 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1407 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1408 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1409 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1410 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1411 PetscFunctionReturn(0); 1412 } 1413 1414 #undef __FUNCT__ 1415 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1416 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1417 { 1418 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1419 PetscErrorCode ierr; 1420 1421 PetscFunctionBegin; 1422 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1423 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1424 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1425 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1426 PetscFunctionReturn(0); 1427 } 1428 1429 #undef __FUNCT__ 1430 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1431 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1432 { 1433 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1434 PetscErrorCode ierr; 1435 PetscBool merged; 1436 1437 PetscFunctionBegin; 1438 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1439 /* do nondiagonal part */ 1440 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1441 if (!merged) { 1442 /* send it on its way */ 1443 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1444 /* do local part */ 1445 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1446 /* receive remote parts: note this assumes the values are not actually */ 1447 /* inserted in yy until the next line */ 1448 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1449 } else { 1450 /* do local part */ 1451 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1452 /* send it on its way */ 1453 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1454 /* values actually were received in the Begin() but we need to call this nop */ 1455 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1456 } 1457 PetscFunctionReturn(0); 1458 } 1459 1460 #undef __FUNCT__ 1461 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1462 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1463 { 1464 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1465 PetscErrorCode ierr; 1466 1467 PetscFunctionBegin; 1468 /* do nondiagonal part */ 1469 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1470 /* send it on its way */ 1471 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1472 /* do local part */ 1473 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1474 /* receive remote parts: note this assumes the values are not actually */ 1475 /* inserted in yy until the next line, which is true for my implementation*/ 1476 /* but is not perhaps always true. */ 1477 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1478 PetscFunctionReturn(0); 1479 } 1480 1481 /* 1482 This only works correctly for square matrices where the subblock A->A is the 1483 diagonal block 1484 */ 1485 #undef __FUNCT__ 1486 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1487 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1488 { 1489 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1490 PetscErrorCode ierr; 1491 1492 PetscFunctionBegin; 1493 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1494 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1495 PetscFunctionReturn(0); 1496 } 1497 1498 #undef __FUNCT__ 1499 #define __FUNCT__ "MatScale_MPIBAIJ" 1500 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1501 { 1502 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1503 PetscErrorCode ierr; 1504 1505 PetscFunctionBegin; 1506 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1507 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1508 PetscFunctionReturn(0); 1509 } 1510 1511 #undef __FUNCT__ 1512 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1513 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1514 { 1515 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1516 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1517 PetscErrorCode ierr; 1518 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1519 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1520 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1521 1522 PetscFunctionBegin; 1523 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1524 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1525 mat->getrowactive = PETSC_TRUE; 1526 1527 if (!mat->rowvalues && (idx || v)) { 1528 /* 1529 allocate enough space to hold information from the longest row. 1530 */ 1531 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1532 PetscInt max = 1,mbs = mat->mbs,tmp; 1533 for (i=0; i<mbs; i++) { 1534 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1535 if (max < tmp) max = tmp; 1536 } 1537 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1538 } 1539 lrow = row - brstart; 1540 1541 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1542 if (!v) {pvA = 0; pvB = 0;} 1543 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1544 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1545 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1546 nztot = nzA + nzB; 1547 1548 cmap = mat->garray; 1549 if (v || idx) { 1550 if (nztot) { 1551 /* Sort by increasing column numbers, assuming A and B already sorted */ 1552 PetscInt imark = -1; 1553 if (v) { 1554 *v = v_p = mat->rowvalues; 1555 for (i=0; i<nzB; i++) { 1556 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1557 else break; 1558 } 1559 imark = i; 1560 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1561 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1562 } 1563 if (idx) { 1564 *idx = idx_p = mat->rowindices; 1565 if (imark > -1) { 1566 for (i=0; i<imark; i++) { 1567 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1568 } 1569 } else { 1570 for (i=0; i<nzB; i++) { 1571 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1572 else break; 1573 } 1574 imark = i; 1575 } 1576 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1577 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1578 } 1579 } else { 1580 if (idx) *idx = 0; 1581 if (v) *v = 0; 1582 } 1583 } 1584 *nz = nztot; 1585 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1586 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1587 PetscFunctionReturn(0); 1588 } 1589 1590 #undef __FUNCT__ 1591 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1592 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1593 { 1594 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1595 1596 PetscFunctionBegin; 1597 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1598 baij->getrowactive = PETSC_FALSE; 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1604 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1605 { 1606 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1607 PetscErrorCode ierr; 1608 1609 PetscFunctionBegin; 1610 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1611 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1612 PetscFunctionReturn(0); 1613 } 1614 1615 #undef __FUNCT__ 1616 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1617 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1618 { 1619 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1620 Mat A = a->A,B = a->B; 1621 PetscErrorCode ierr; 1622 PetscReal isend[5],irecv[5]; 1623 1624 PetscFunctionBegin; 1625 info->block_size = (PetscReal)matin->rmap->bs; 1626 1627 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1628 1629 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1630 isend[3] = info->memory; isend[4] = info->mallocs; 1631 1632 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1633 1634 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1635 isend[3] += info->memory; isend[4] += info->mallocs; 1636 1637 if (flag == MAT_LOCAL) { 1638 info->nz_used = isend[0]; 1639 info->nz_allocated = isend[1]; 1640 info->nz_unneeded = isend[2]; 1641 info->memory = isend[3]; 1642 info->mallocs = isend[4]; 1643 } else if (flag == MAT_GLOBAL_MAX) { 1644 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1645 1646 info->nz_used = irecv[0]; 1647 info->nz_allocated = irecv[1]; 1648 info->nz_unneeded = irecv[2]; 1649 info->memory = irecv[3]; 1650 info->mallocs = irecv[4]; 1651 } else if (flag == MAT_GLOBAL_SUM) { 1652 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1653 1654 info->nz_used = irecv[0]; 1655 info->nz_allocated = irecv[1]; 1656 info->nz_unneeded = irecv[2]; 1657 info->memory = irecv[3]; 1658 info->mallocs = irecv[4]; 1659 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1660 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1661 info->fill_ratio_needed = 0; 1662 info->factor_mallocs = 0; 1663 PetscFunctionReturn(0); 1664 } 1665 1666 #undef __FUNCT__ 1667 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1668 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1669 { 1670 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1671 PetscErrorCode ierr; 1672 1673 PetscFunctionBegin; 1674 switch (op) { 1675 case MAT_NEW_NONZERO_LOCATIONS: 1676 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1677 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1678 case MAT_KEEP_NONZERO_PATTERN: 1679 case MAT_NEW_NONZERO_LOCATION_ERR: 1680 MatCheckPreallocated(A,1); 1681 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1682 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1683 break; 1684 case MAT_ROW_ORIENTED: 1685 MatCheckPreallocated(A,1); 1686 a->roworiented = flg; 1687 1688 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1689 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1690 break; 1691 case MAT_NEW_DIAGONALS: 1692 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1693 break; 1694 case MAT_IGNORE_OFF_PROC_ENTRIES: 1695 a->donotstash = flg; 1696 break; 1697 case MAT_USE_HASH_TABLE: 1698 a->ht_flag = flg; 1699 break; 1700 case MAT_SYMMETRIC: 1701 case MAT_STRUCTURALLY_SYMMETRIC: 1702 case MAT_HERMITIAN: 1703 case MAT_SYMMETRY_ETERNAL: 1704 MatCheckPreallocated(A,1); 1705 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1706 break; 1707 default: 1708 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1709 } 1710 PetscFunctionReturn(0); 1711 } 1712 1713 #undef __FUNCT__ 1714 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1715 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1716 { 1717 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1718 Mat_SeqBAIJ *Aloc; 1719 Mat B; 1720 PetscErrorCode ierr; 1721 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1722 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1723 MatScalar *a; 1724 1725 PetscFunctionBegin; 1726 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1727 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1728 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1729 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1730 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1731 /* Do not know preallocation information, but must set block size */ 1732 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1733 } else { 1734 B = *matout; 1735 } 1736 1737 /* copy over the A part */ 1738 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1739 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1740 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1741 1742 for (i=0; i<mbs; i++) { 1743 rvals[0] = bs*(baij->rstartbs + i); 1744 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1745 for (j=ai[i]; j<ai[i+1]; j++) { 1746 col = (baij->cstartbs+aj[j])*bs; 1747 for (k=0; k<bs; k++) { 1748 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1749 1750 col++; a += bs; 1751 } 1752 } 1753 } 1754 /* copy over the B part */ 1755 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1756 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1757 for (i=0; i<mbs; i++) { 1758 rvals[0] = bs*(baij->rstartbs + i); 1759 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 col = baij->garray[aj[j]]*bs; 1762 for (k=0; k<bs; k++) { 1763 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1764 col++; 1765 a += bs; 1766 } 1767 } 1768 } 1769 ierr = PetscFree(rvals);CHKERRQ(ierr); 1770 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1771 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1772 1773 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1774 else { 1775 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1776 } 1777 PetscFunctionReturn(0); 1778 } 1779 1780 #undef __FUNCT__ 1781 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1782 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1783 { 1784 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1785 Mat a = baij->A,b = baij->B; 1786 PetscErrorCode ierr; 1787 PetscInt s1,s2,s3; 1788 1789 PetscFunctionBegin; 1790 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1791 if (rr) { 1792 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1793 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1794 /* Overlap communication with computation. */ 1795 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1796 } 1797 if (ll) { 1798 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1799 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1800 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1801 } 1802 /* scale the diagonal block */ 1803 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1804 1805 if (rr) { 1806 /* Do a scatter end and then right scale the off-diagonal block */ 1807 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1808 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1809 } 1810 PetscFunctionReturn(0); 1811 } 1812 1813 #undef __FUNCT__ 1814 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1815 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1816 { 1817 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1818 PetscInt *owners = A->rmap->range; 1819 PetscInt n = A->rmap->n; 1820 PetscSF sf; 1821 PetscInt *lrows; 1822 PetscSFNode *rrows; 1823 PetscInt r, p = 0, len = 0; 1824 PetscErrorCode ierr; 1825 1826 PetscFunctionBegin; 1827 /* Create SF where leaves are input rows and roots are owned rows */ 1828 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1829 for (r = 0; r < n; ++r) lrows[r] = -1; 1830 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 1831 for (r = 0; r < N; ++r) { 1832 const PetscInt idx = rows[r]; 1833 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1834 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1835 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1836 } 1837 if (A->nooffproczerorows) { 1838 if (p != l->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,l->rank); 1839 lrows[len++] = idx - owners[p]; 1840 } else { 1841 rrows[r].rank = p; 1842 rrows[r].index = rows[r] - owners[p]; 1843 } 1844 } 1845 if (!A->nooffproczerorows) { 1846 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1847 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1848 /* Collect flags for rows to be zeroed */ 1849 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1850 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1851 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1852 /* Compress and put in row numbers */ 1853 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1854 } 1855 /* fix right hand side if needed */ 1856 if (x && b) { 1857 const PetscScalar *xx; 1858 PetscScalar *bb; 1859 1860 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1861 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1862 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1863 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1864 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1865 } 1866 1867 /* actually zap the local rows */ 1868 /* 1869 Zero the required rows. If the "diagonal block" of the matrix 1870 is square and the user wishes to set the diagonal we use separate 1871 code so that MatSetValues() is not called for each diagonal allocating 1872 new memory, thus calling lots of mallocs and slowing things down. 1873 1874 */ 1875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1876 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 1878 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1879 } else if (diag != 0.0) { 1880 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1881 if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1882 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1883 for (r = 0; r < len; ++r) { 1884 const PetscInt row = lrows[r] + A->rmap->rstart; 1885 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1886 } 1887 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1888 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1889 } else { 1890 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1891 } 1892 ierr = PetscFree(lrows);CHKERRQ(ierr); 1893 1894 /* only change matrix nonzero state if pattern was allowed to be changed */ 1895 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1896 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1897 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1898 } 1899 PetscFunctionReturn(0); 1900 } 1901 1902 #undef __FUNCT__ 1903 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1904 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1905 { 1906 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1907 PetscErrorCode ierr; 1908 PetscMPIInt n = A->rmap->n; 1909 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1910 PetscInt *lrows,*owners = A->rmap->range; 1911 PetscSFNode *rrows; 1912 PetscSF sf; 1913 const PetscScalar *xx; 1914 PetscScalar *bb,*mask; 1915 Vec xmask,lmask; 1916 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1917 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1918 PetscScalar *aa; 1919 1920 PetscFunctionBegin; 1921 /* Create SF where leaves are input rows and roots are owned rows */ 1922 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1923 for (r = 0; r < n; ++r) lrows[r] = -1; 1924 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1925 for (r = 0; r < N; ++r) { 1926 const PetscInt idx = rows[r]; 1927 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 1928 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1929 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1930 } 1931 rrows[r].rank = p; 1932 rrows[r].index = rows[r] - owners[p]; 1933 } 1934 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1935 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1936 /* Collect flags for rows to be zeroed */ 1937 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1938 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1939 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1940 /* Compress and put in row numbers */ 1941 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1942 /* zero diagonal part of matrix */ 1943 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1944 /* handle off diagonal part of matrix */ 1945 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 1946 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1947 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1948 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1949 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1950 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1951 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1952 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1953 if (x) { 1954 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1955 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1956 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1957 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1958 } 1959 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1960 /* remove zeroed rows of off diagonal matrix */ 1961 for (i = 0; i < len; ++i) { 1962 row = lrows[i]; 1963 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1964 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1965 for (k = 0; k < count; ++k) { 1966 aa[0] = 0.0; 1967 aa += bs; 1968 } 1969 } 1970 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1971 for (i = 0; i < l->B->rmap->N; ++i) { 1972 row = i/bs; 1973 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1974 for (k = 0; k < bs; ++k) { 1975 col = bs*baij->j[j] + k; 1976 if (PetscAbsScalar(mask[col])) { 1977 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1978 if (x) bb[i] -= aa[0]*xx[col]; 1979 aa[0] = 0.0; 1980 } 1981 } 1982 } 1983 } 1984 if (x) { 1985 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1986 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1987 } 1988 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1989 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1990 ierr = PetscFree(lrows);CHKERRQ(ierr); 1991 1992 /* only change matrix nonzero state if pattern was allowed to be changed */ 1993 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1994 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1995 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1996 } 1997 PetscFunctionReturn(0); 1998 } 1999 2000 #undef __FUNCT__ 2001 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 2002 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 2003 { 2004 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2005 PetscErrorCode ierr; 2006 2007 PetscFunctionBegin; 2008 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2009 PetscFunctionReturn(0); 2010 } 2011 2012 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 2013 2014 #undef __FUNCT__ 2015 #define __FUNCT__ "MatEqual_MPIBAIJ" 2016 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 2017 { 2018 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 2019 Mat a,b,c,d; 2020 PetscBool flg; 2021 PetscErrorCode ierr; 2022 2023 PetscFunctionBegin; 2024 a = matA->A; b = matA->B; 2025 c = matB->A; d = matB->B; 2026 2027 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2028 if (flg) { 2029 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2030 } 2031 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2032 PetscFunctionReturn(0); 2033 } 2034 2035 #undef __FUNCT__ 2036 #define __FUNCT__ "MatCopy_MPIBAIJ" 2037 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 2038 { 2039 PetscErrorCode ierr; 2040 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2041 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2042 2043 PetscFunctionBegin; 2044 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2045 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2046 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2047 } else { 2048 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2049 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2050 } 2051 PetscFunctionReturn(0); 2052 } 2053 2054 #undef __FUNCT__ 2055 #define __FUNCT__ "MatSetUp_MPIBAIJ" 2056 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 2057 { 2058 PetscErrorCode ierr; 2059 2060 PetscFunctionBegin; 2061 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2062 PetscFunctionReturn(0); 2063 } 2064 2065 #undef __FUNCT__ 2066 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 2067 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2068 { 2069 PetscErrorCode ierr; 2070 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 2071 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 2072 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 2073 2074 PetscFunctionBegin; 2075 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2076 PetscFunctionReturn(0); 2077 } 2078 2079 #undef __FUNCT__ 2080 #define __FUNCT__ "MatAXPY_MPIBAIJ" 2081 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2082 { 2083 PetscErrorCode ierr; 2084 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 2085 PetscBLASInt bnz,one=1; 2086 Mat_SeqBAIJ *x,*y; 2087 2088 PetscFunctionBegin; 2089 if (str == SAME_NONZERO_PATTERN) { 2090 PetscScalar alpha = a; 2091 x = (Mat_SeqBAIJ*)xx->A->data; 2092 y = (Mat_SeqBAIJ*)yy->A->data; 2093 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2094 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2095 x = (Mat_SeqBAIJ*)xx->B->data; 2096 y = (Mat_SeqBAIJ*)yy->B->data; 2097 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2098 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2099 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2100 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2101 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2102 } else { 2103 Mat B; 2104 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2105 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2106 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2107 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2108 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2109 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2110 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2111 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2112 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2113 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2114 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2115 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2116 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2117 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2118 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2119 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2120 } 2121 PetscFunctionReturn(0); 2122 } 2123 2124 #undef __FUNCT__ 2125 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2126 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2127 { 2128 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2129 PetscErrorCode ierr; 2130 2131 PetscFunctionBegin; 2132 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2133 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2134 PetscFunctionReturn(0); 2135 } 2136 2137 #undef __FUNCT__ 2138 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2139 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2140 { 2141 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2142 PetscErrorCode ierr; 2143 2144 PetscFunctionBegin; 2145 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2146 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2147 PetscFunctionReturn(0); 2148 } 2149 2150 #undef __FUNCT__ 2151 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2152 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2153 { 2154 PetscErrorCode ierr; 2155 IS iscol_local; 2156 PetscInt csize; 2157 2158 PetscFunctionBegin; 2159 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2160 if (call == MAT_REUSE_MATRIX) { 2161 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2162 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2163 } else { 2164 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2165 } 2166 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2167 if (call == MAT_INITIAL_MATRIX) { 2168 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2169 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2170 } 2171 PetscFunctionReturn(0); 2172 } 2173 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2174 #undef __FUNCT__ 2175 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2176 /* 2177 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2178 in local and then by concatenating the local matrices the end result. 2179 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ(). 2180 This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency). 2181 */ 2182 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2183 { 2184 PetscErrorCode ierr; 2185 PetscMPIInt rank,size; 2186 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2187 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2188 Mat M,Mreuse; 2189 MatScalar *vwork,*aa; 2190 MPI_Comm comm; 2191 IS isrow_new, iscol_new; 2192 PetscBool idflag,allrows, allcols; 2193 Mat_SeqBAIJ *aij; 2194 2195 PetscFunctionBegin; 2196 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2199 /* The compression and expansion should be avoided. Doesn't point 2200 out errors, might change the indices, hence buggey */ 2201 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2202 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2203 2204 /* Check for special case: each processor gets entire matrix columns */ 2205 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2206 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2207 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2208 else allcols = PETSC_FALSE; 2209 2210 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2211 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2212 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2213 else allrows = PETSC_FALSE; 2214 2215 if (call == MAT_REUSE_MATRIX) { 2216 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2217 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2218 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2219 } else { 2220 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2221 } 2222 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2223 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2224 /* 2225 m - number of local rows 2226 n - number of columns (same on all processors) 2227 rstart - first row in new global matrix generated 2228 */ 2229 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2230 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2231 m = m/bs; 2232 n = n/bs; 2233 2234 if (call == MAT_INITIAL_MATRIX) { 2235 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2236 ii = aij->i; 2237 jj = aij->j; 2238 2239 /* 2240 Determine the number of non-zeros in the diagonal and off-diagonal 2241 portions of the matrix in order to do correct preallocation 2242 */ 2243 2244 /* first get start and end of "diagonal" columns */ 2245 if (csize == PETSC_DECIDE) { 2246 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2247 if (mglobal == n*bs) { /* square matrix */ 2248 nlocal = m; 2249 } else { 2250 nlocal = n/size + ((n % size) > rank); 2251 } 2252 } else { 2253 nlocal = csize/bs; 2254 } 2255 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2256 rstart = rend - nlocal; 2257 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2258 2259 /* next, compute all the lengths */ 2260 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2261 for (i=0; i<m; i++) { 2262 jend = ii[i+1] - ii[i]; 2263 olen = 0; 2264 dlen = 0; 2265 for (j=0; j<jend; j++) { 2266 if (*jj < rstart || *jj >= rend) olen++; 2267 else dlen++; 2268 jj++; 2269 } 2270 olens[i] = olen; 2271 dlens[i] = dlen; 2272 } 2273 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2274 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2275 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2276 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2277 ierr = MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2278 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2279 } else { 2280 PetscInt ml,nl; 2281 2282 M = *newmat; 2283 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2284 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2285 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2286 /* 2287 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2288 rather than the slower MatSetValues(). 2289 */ 2290 M->was_assembled = PETSC_TRUE; 2291 M->assembled = PETSC_FALSE; 2292 } 2293 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2294 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2295 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2296 ii = aij->i; 2297 jj = aij->j; 2298 aa = aij->a; 2299 for (i=0; i<m; i++) { 2300 row = rstart/bs + i; 2301 nz = ii[i+1] - ii[i]; 2302 cwork = jj; jj += nz; 2303 vwork = aa; aa += nz*bs*bs; 2304 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2305 } 2306 2307 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2308 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2309 *newmat = M; 2310 2311 /* save submatrix used in processor for next request */ 2312 if (call == MAT_INITIAL_MATRIX) { 2313 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2314 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2315 } 2316 PetscFunctionReturn(0); 2317 } 2318 2319 #undef __FUNCT__ 2320 #define __FUNCT__ "MatPermute_MPIBAIJ" 2321 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2322 { 2323 MPI_Comm comm,pcomm; 2324 PetscInt clocal_size,nrows; 2325 const PetscInt *rows; 2326 PetscMPIInt size; 2327 IS crowp,lcolp; 2328 PetscErrorCode ierr; 2329 2330 PetscFunctionBegin; 2331 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2332 /* make a collective version of 'rowp' */ 2333 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2334 if (pcomm==comm) { 2335 crowp = rowp; 2336 } else { 2337 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2338 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2339 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2340 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2341 } 2342 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2343 /* make a local version of 'colp' */ 2344 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2345 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2346 if (size==1) { 2347 lcolp = colp; 2348 } else { 2349 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2350 } 2351 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2352 /* now we just get the submatrix */ 2353 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2354 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2355 /* clean up */ 2356 if (pcomm!=comm) { 2357 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2358 } 2359 if (size>1) { 2360 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2361 } 2362 PetscFunctionReturn(0); 2363 } 2364 2365 #undef __FUNCT__ 2366 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2367 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2368 { 2369 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2370 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2371 2372 PetscFunctionBegin; 2373 if (nghosts) *nghosts = B->nbs; 2374 if (ghosts) *ghosts = baij->garray; 2375 PetscFunctionReturn(0); 2376 } 2377 2378 #undef __FUNCT__ 2379 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2380 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2381 { 2382 Mat B; 2383 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2384 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2385 Mat_SeqAIJ *b; 2386 PetscErrorCode ierr; 2387 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2388 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2389 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2390 2391 PetscFunctionBegin; 2392 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2393 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2394 2395 /* ---------------------------------------------------------------- 2396 Tell every processor the number of nonzeros per row 2397 */ 2398 ierr = PetscMalloc1(A->rmap->N/bs,&lens);CHKERRQ(ierr); 2399 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2400 lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs]; 2401 } 2402 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2403 displs = recvcounts + size; 2404 for (i=0; i<size; i++) { 2405 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2406 displs[i] = A->rmap->range[i]/bs; 2407 } 2408 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2409 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2410 #else 2411 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2412 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2413 #endif 2414 /* --------------------------------------------------------------- 2415 Create the sequential matrix of the same type as the local block diagonal 2416 */ 2417 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2418 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2419 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2420 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2421 b = (Mat_SeqAIJ*)B->data; 2422 2423 /*-------------------------------------------------------------------- 2424 Copy my part of matrix column indices over 2425 */ 2426 sendcount = ad->nz + bd->nz; 2427 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2428 a_jsendbuf = ad->j; 2429 b_jsendbuf = bd->j; 2430 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2431 cnt = 0; 2432 for (i=0; i<n; i++) { 2433 2434 /* put in lower diagonal portion */ 2435 m = bd->i[i+1] - bd->i[i]; 2436 while (m > 0) { 2437 /* is it above diagonal (in bd (compressed) numbering) */ 2438 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2439 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2440 m--; 2441 } 2442 2443 /* put in diagonal portion */ 2444 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2445 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2446 } 2447 2448 /* put in upper diagonal portion */ 2449 while (m-- > 0) { 2450 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2451 } 2452 } 2453 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2454 2455 /*-------------------------------------------------------------------- 2456 Gather all column indices to all processors 2457 */ 2458 for (i=0; i<size; i++) { 2459 recvcounts[i] = 0; 2460 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2461 recvcounts[i] += lens[j]; 2462 } 2463 } 2464 displs[0] = 0; 2465 for (i=1; i<size; i++) { 2466 displs[i] = displs[i-1] + recvcounts[i-1]; 2467 } 2468 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2469 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2470 #else 2471 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2472 #endif 2473 /*-------------------------------------------------------------------- 2474 Assemble the matrix into useable form (note numerical values not yet set) 2475 */ 2476 /* set the b->ilen (length of each row) values */ 2477 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2478 /* set the b->i indices */ 2479 b->i[0] = 0; 2480 for (i=1; i<=A->rmap->N/bs; i++) { 2481 b->i[i] = b->i[i-1] + lens[i-1]; 2482 } 2483 ierr = PetscFree(lens);CHKERRQ(ierr); 2484 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2485 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2486 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2487 2488 if (A->symmetric) { 2489 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2490 } else if (A->hermitian) { 2491 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2492 } else if (A->structurally_symmetric) { 2493 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2494 } 2495 *newmat = B; 2496 PetscFunctionReturn(0); 2497 } 2498 2499 #undef __FUNCT__ 2500 #define __FUNCT__ "MatSOR_MPIBAIJ" 2501 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2502 { 2503 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2504 PetscErrorCode ierr; 2505 Vec bb1 = 0; 2506 2507 PetscFunctionBegin; 2508 if (flag == SOR_APPLY_UPPER) { 2509 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2510 PetscFunctionReturn(0); 2511 } 2512 2513 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2514 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2515 } 2516 2517 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2518 if (flag & SOR_ZERO_INITIAL_GUESS) { 2519 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2520 its--; 2521 } 2522 2523 while (its--) { 2524 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2525 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2526 2527 /* update rhs: bb1 = bb - B*x */ 2528 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2529 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2530 2531 /* local sweep */ 2532 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2533 } 2534 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2535 if (flag & SOR_ZERO_INITIAL_GUESS) { 2536 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2537 its--; 2538 } 2539 while (its--) { 2540 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2541 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2542 2543 /* update rhs: bb1 = bb - B*x */ 2544 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2545 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2546 2547 /* local sweep */ 2548 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2549 } 2550 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2551 if (flag & SOR_ZERO_INITIAL_GUESS) { 2552 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2553 its--; 2554 } 2555 while (its--) { 2556 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2557 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2558 2559 /* update rhs: bb1 = bb - B*x */ 2560 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2561 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2562 2563 /* local sweep */ 2564 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2565 } 2566 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2567 2568 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2569 PetscFunctionReturn(0); 2570 } 2571 2572 #undef __FUNCT__ 2573 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2574 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2575 { 2576 PetscErrorCode ierr; 2577 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2578 PetscInt N,i,*garray = aij->garray; 2579 PetscInt ib,jb,bs = A->rmap->bs; 2580 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2581 MatScalar *a_val = a_aij->a; 2582 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2583 MatScalar *b_val = b_aij->a; 2584 PetscReal *work; 2585 2586 PetscFunctionBegin; 2587 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2588 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2589 if (type == NORM_2) { 2590 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2591 for (jb=0; jb<bs; jb++) { 2592 for (ib=0; ib<bs; ib++) { 2593 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2594 a_val++; 2595 } 2596 } 2597 } 2598 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2599 for (jb=0; jb<bs; jb++) { 2600 for (ib=0; ib<bs; ib++) { 2601 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2602 b_val++; 2603 } 2604 } 2605 } 2606 } else if (type == NORM_1) { 2607 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2608 for (jb=0; jb<bs; jb++) { 2609 for (ib=0; ib<bs; ib++) { 2610 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2611 a_val++; 2612 } 2613 } 2614 } 2615 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2616 for (jb=0; jb<bs; jb++) { 2617 for (ib=0; ib<bs; ib++) { 2618 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2619 b_val++; 2620 } 2621 } 2622 } 2623 } else if (type == NORM_INFINITY) { 2624 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2625 for (jb=0; jb<bs; jb++) { 2626 for (ib=0; ib<bs; ib++) { 2627 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2628 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2629 a_val++; 2630 } 2631 } 2632 } 2633 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2634 for (jb=0; jb<bs; jb++) { 2635 for (ib=0; ib<bs; ib++) { 2636 int col = garray[b_aij->j[i]] * bs + jb; 2637 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2638 b_val++; 2639 } 2640 } 2641 } 2642 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2643 if (type == NORM_INFINITY) { 2644 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2645 } else { 2646 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2647 } 2648 ierr = PetscFree(work);CHKERRQ(ierr); 2649 if (type == NORM_2) { 2650 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2651 } 2652 PetscFunctionReturn(0); 2653 } 2654 2655 #undef __FUNCT__ 2656 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2657 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2658 { 2659 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2660 PetscErrorCode ierr; 2661 2662 PetscFunctionBegin; 2663 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2664 A->errortype = a->A->errortype; 2665 PetscFunctionReturn(0); 2666 } 2667 2668 #undef __FUNCT__ 2669 #define __FUNCT__ "MatShift_MPIBAIJ" 2670 PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a) 2671 { 2672 PetscErrorCode ierr; 2673 Mat_MPIBAIJ *maij = (Mat_MPIBAIJ*)Y->data; 2674 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)maij->A->data; 2675 2676 PetscFunctionBegin; 2677 if (!Y->preallocated) { 2678 ierr = MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);CHKERRQ(ierr); 2679 } else if (!aij->nz) { 2680 PetscInt nonew = aij->nonew; 2681 ierr = MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);CHKERRQ(ierr); 2682 aij->nonew = nonew; 2683 } 2684 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2685 PetscFunctionReturn(0); 2686 } 2687 2688 #undef __FUNCT__ 2689 #define __FUNCT__ "MatMissingDiagonal_MPIBAIJ" 2690 PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool *missing,PetscInt *d) 2691 { 2692 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2693 PetscErrorCode ierr; 2694 2695 PetscFunctionBegin; 2696 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2697 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2698 if (d) { 2699 PetscInt rstart; 2700 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2701 *d += rstart/A->rmap->bs; 2702 2703 } 2704 PetscFunctionReturn(0); 2705 } 2706 2707 /* -------------------------------------------------------------------*/ 2708 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2709 MatGetRow_MPIBAIJ, 2710 MatRestoreRow_MPIBAIJ, 2711 MatMult_MPIBAIJ, 2712 /* 4*/ MatMultAdd_MPIBAIJ, 2713 MatMultTranspose_MPIBAIJ, 2714 MatMultTransposeAdd_MPIBAIJ, 2715 0, 2716 0, 2717 0, 2718 /*10*/ 0, 2719 0, 2720 0, 2721 MatSOR_MPIBAIJ, 2722 MatTranspose_MPIBAIJ, 2723 /*15*/ MatGetInfo_MPIBAIJ, 2724 MatEqual_MPIBAIJ, 2725 MatGetDiagonal_MPIBAIJ, 2726 MatDiagonalScale_MPIBAIJ, 2727 MatNorm_MPIBAIJ, 2728 /*20*/ MatAssemblyBegin_MPIBAIJ, 2729 MatAssemblyEnd_MPIBAIJ, 2730 MatSetOption_MPIBAIJ, 2731 MatZeroEntries_MPIBAIJ, 2732 /*24*/ MatZeroRows_MPIBAIJ, 2733 0, 2734 0, 2735 0, 2736 0, 2737 /*29*/ MatSetUp_MPIBAIJ, 2738 0, 2739 0, 2740 0, 2741 0, 2742 /*34*/ MatDuplicate_MPIBAIJ, 2743 0, 2744 0, 2745 0, 2746 0, 2747 /*39*/ MatAXPY_MPIBAIJ, 2748 MatGetSubMatrices_MPIBAIJ, 2749 MatIncreaseOverlap_MPIBAIJ, 2750 MatGetValues_MPIBAIJ, 2751 MatCopy_MPIBAIJ, 2752 /*44*/ 0, 2753 MatScale_MPIBAIJ, 2754 MatShift_MPIBAIJ, 2755 0, 2756 MatZeroRowsColumns_MPIBAIJ, 2757 /*49*/ 0, 2758 0, 2759 0, 2760 0, 2761 0, 2762 /*54*/ MatFDColoringCreate_MPIXAIJ, 2763 0, 2764 MatSetUnfactored_MPIBAIJ, 2765 MatPermute_MPIBAIJ, 2766 MatSetValuesBlocked_MPIBAIJ, 2767 /*59*/ MatGetSubMatrix_MPIBAIJ, 2768 MatDestroy_MPIBAIJ, 2769 MatView_MPIBAIJ, 2770 0, 2771 0, 2772 /*64*/ 0, 2773 0, 2774 0, 2775 0, 2776 0, 2777 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2778 0, 2779 0, 2780 0, 2781 0, 2782 /*74*/ 0, 2783 MatFDColoringApply_BAIJ, 2784 0, 2785 0, 2786 0, 2787 /*79*/ 0, 2788 0, 2789 0, 2790 0, 2791 MatLoad_MPIBAIJ, 2792 /*84*/ 0, 2793 0, 2794 0, 2795 0, 2796 0, 2797 /*89*/ 0, 2798 0, 2799 0, 2800 0, 2801 0, 2802 /*94*/ 0, 2803 0, 2804 0, 2805 0, 2806 0, 2807 /*99*/ 0, 2808 0, 2809 0, 2810 0, 2811 0, 2812 /*104*/0, 2813 MatRealPart_MPIBAIJ, 2814 MatImaginaryPart_MPIBAIJ, 2815 0, 2816 0, 2817 /*109*/0, 2818 0, 2819 0, 2820 0, 2821 MatMissingDiagonal_MPIBAIJ, 2822 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2823 0, 2824 MatGetGhosts_MPIBAIJ, 2825 0, 2826 0, 2827 /*119*/0, 2828 0, 2829 0, 2830 0, 2831 MatGetMultiProcBlock_MPIBAIJ, 2832 /*124*/0, 2833 MatGetColumnNorms_MPIBAIJ, 2834 MatInvertBlockDiagonal_MPIBAIJ, 2835 0, 2836 0, 2837 /*129*/ 0, 2838 0, 2839 0, 2840 0, 2841 0, 2842 /*134*/ 0, 2843 0, 2844 0, 2845 0, 2846 0, 2847 /*139*/ 0, 2848 0, 2849 0, 2850 MatFDColoringSetUp_MPIXAIJ, 2851 0, 2852 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ 2853 }; 2854 2855 #undef __FUNCT__ 2856 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2857 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2858 { 2859 PetscFunctionBegin; 2860 *a = ((Mat_MPIBAIJ*)A->data)->A; 2861 PetscFunctionReturn(0); 2862 } 2863 2864 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2865 2866 #undef __FUNCT__ 2867 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2868 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2869 { 2870 PetscInt m,rstart,cstart,cend; 2871 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2872 const PetscInt *JJ =0; 2873 PetscScalar *values=0; 2874 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2875 PetscErrorCode ierr; 2876 2877 PetscFunctionBegin; 2878 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2879 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2880 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2881 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2882 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2883 m = B->rmap->n/bs; 2884 rstart = B->rmap->rstart/bs; 2885 cstart = B->cmap->rstart/bs; 2886 cend = B->cmap->rend/bs; 2887 2888 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2889 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2890 for (i=0; i<m; i++) { 2891 nz = ii[i+1] - ii[i]; 2892 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2893 nz_max = PetscMax(nz_max,nz); 2894 JJ = jj + ii[i]; 2895 for (j=0; j<nz; j++) { 2896 if (*JJ >= cstart) break; 2897 JJ++; 2898 } 2899 d = 0; 2900 for (; j<nz; j++) { 2901 if (*JJ++ >= cend) break; 2902 d++; 2903 } 2904 d_nnz[i] = d; 2905 o_nnz[i] = nz - d; 2906 } 2907 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2908 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2909 2910 values = (PetscScalar*)V; 2911 if (!values) { 2912 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2913 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2914 } 2915 for (i=0; i<m; i++) { 2916 PetscInt row = i + rstart; 2917 PetscInt ncols = ii[i+1] - ii[i]; 2918 const PetscInt *icols = jj + ii[i]; 2919 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2920 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2921 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2922 } else { /* block ordering does not match so we can only insert one block at a time. */ 2923 PetscInt j; 2924 for (j=0; j<ncols; j++) { 2925 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2926 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2927 } 2928 } 2929 } 2930 2931 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2932 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2933 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2934 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2935 PetscFunctionReturn(0); 2936 } 2937 2938 #undef __FUNCT__ 2939 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2940 /*@C 2941 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2942 (the default parallel PETSc format). 2943 2944 Collective on MPI_Comm 2945 2946 Input Parameters: 2947 + B - the matrix 2948 . bs - the block size 2949 . i - the indices into j for the start of each local row (starts with zero) 2950 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2951 - v - optional values in the matrix 2952 2953 Level: developer 2954 2955 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2956 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2957 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2958 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2959 block column and the second index is over columns within a block. 2960 2961 .keywords: matrix, aij, compressed row, sparse, parallel 2962 2963 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2964 @*/ 2965 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2966 { 2967 PetscErrorCode ierr; 2968 2969 PetscFunctionBegin; 2970 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2971 PetscValidType(B,1); 2972 PetscValidLogicalCollectiveInt(B,bs,2); 2973 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2974 PetscFunctionReturn(0); 2975 } 2976 2977 #undef __FUNCT__ 2978 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2979 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2980 { 2981 Mat_MPIBAIJ *b; 2982 PetscErrorCode ierr; 2983 PetscInt i; 2984 2985 PetscFunctionBegin; 2986 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2987 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2988 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2989 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2990 2991 if (d_nnz) { 2992 for (i=0; i<B->rmap->n/bs; i++) { 2993 if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]); 2994 } 2995 } 2996 if (o_nnz) { 2997 for (i=0; i<B->rmap->n/bs; i++) { 2998 if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]); 2999 } 3000 } 3001 3002 b = (Mat_MPIBAIJ*)B->data; 3003 b->bs2 = bs*bs; 3004 b->mbs = B->rmap->n/bs; 3005 b->nbs = B->cmap->n/bs; 3006 b->Mbs = B->rmap->N/bs; 3007 b->Nbs = B->cmap->N/bs; 3008 3009 for (i=0; i<=b->size; i++) { 3010 b->rangebs[i] = B->rmap->range[i]/bs; 3011 } 3012 b->rstartbs = B->rmap->rstart/bs; 3013 b->rendbs = B->rmap->rend/bs; 3014 b->cstartbs = B->cmap->rstart/bs; 3015 b->cendbs = B->cmap->rend/bs; 3016 3017 if (!B->preallocated) { 3018 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3019 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3020 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 3021 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3022 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3023 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3024 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 3025 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3026 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 3027 } 3028 3029 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3030 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 3031 B->preallocated = PETSC_TRUE; 3032 PetscFunctionReturn(0); 3033 } 3034 3035 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 3036 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 3037 3038 #undef __FUNCT__ 3039 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 3040 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 3041 { 3042 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 3043 PetscErrorCode ierr; 3044 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 3045 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 3046 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 3047 3048 PetscFunctionBegin; 3049 ierr = PetscMalloc1(M+1,&ii);CHKERRQ(ierr); 3050 ii[0] = 0; 3051 for (i=0; i<M; i++) { 3052 if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]); 3053 if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]); 3054 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 3055 /* remove one from count of matrix has diagonal */ 3056 for (j=id[i]; j<id[i+1]; j++) { 3057 if (jd[j] == i) {ii[i+1]--;break;} 3058 } 3059 } 3060 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 3061 cnt = 0; 3062 for (i=0; i<M; i++) { 3063 for (j=io[i]; j<io[i+1]; j++) { 3064 if (garray[jo[j]] > rstart) break; 3065 jj[cnt++] = garray[jo[j]]; 3066 } 3067 for (k=id[i]; k<id[i+1]; k++) { 3068 if (jd[k] != i) { 3069 jj[cnt++] = rstart + jd[k]; 3070 } 3071 } 3072 for (; j<io[i+1]; j++) { 3073 jj[cnt++] = garray[jo[j]]; 3074 } 3075 } 3076 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 3077 PetscFunctionReturn(0); 3078 } 3079 3080 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3081 3082 PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 3083 3084 #undef __FUNCT__ 3085 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 3086 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 3087 { 3088 PetscErrorCode ierr; 3089 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3090 Mat B; 3091 Mat_MPIAIJ *b; 3092 3093 PetscFunctionBegin; 3094 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 3095 3096 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 3097 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 3098 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 3099 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 3100 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3101 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 3102 b = (Mat_MPIAIJ*) B->data; 3103 3104 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 3105 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3106 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 3107 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 3108 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 3109 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3110 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3111 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3112 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3113 if (reuse == MAT_INPLACE_MATRIX) { 3114 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 3115 } else { 3116 *newmat = B; 3117 } 3118 PetscFunctionReturn(0); 3119 } 3120 3121 /*MC 3122 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 3123 3124 Options Database Keys: 3125 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3126 . -mat_block_size <bs> - set the blocksize used to store the matrix 3127 - -mat_use_hash_table <fact> 3128 3129 Level: beginner 3130 3131 .seealso: MatCreateMPIBAIJ 3132 M*/ 3133 3134 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3135 3136 #undef __FUNCT__ 3137 #define __FUNCT__ "MatCreate_MPIBAIJ" 3138 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3139 { 3140 Mat_MPIBAIJ *b; 3141 PetscErrorCode ierr; 3142 PetscBool flg = PETSC_FALSE; 3143 3144 PetscFunctionBegin; 3145 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3146 B->data = (void*)b; 3147 3148 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3149 B->assembled = PETSC_FALSE; 3150 3151 B->insertmode = NOT_SET_VALUES; 3152 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3153 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3154 3155 /* build local table of row and column ownerships */ 3156 ierr = PetscMalloc1(b->size+1,&b->rangebs);CHKERRQ(ierr); 3157 3158 /* build cache for off array entries formed */ 3159 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3160 3161 b->donotstash = PETSC_FALSE; 3162 b->colmap = NULL; 3163 b->garray = NULL; 3164 b->roworiented = PETSC_TRUE; 3165 3166 /* stuff used in block assembly */ 3167 b->barray = 0; 3168 3169 /* stuff used for matrix vector multiply */ 3170 b->lvec = 0; 3171 b->Mvctx = 0; 3172 3173 /* stuff for MatGetRow() */ 3174 b->rowindices = 0; 3175 b->rowvalues = 0; 3176 b->getrowactive = PETSC_FALSE; 3177 3178 /* hash table stuff */ 3179 b->ht = 0; 3180 b->hd = 0; 3181 b->ht_size = 0; 3182 b->ht_flag = PETSC_FALSE; 3183 b->ht_fact = 0; 3184 b->ht_total_ct = 0; 3185 b->ht_insert_ct = 0; 3186 3187 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3188 b->ijonly = PETSC_FALSE; 3189 3190 3191 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3192 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3193 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3194 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3195 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3196 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr); 3197 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3198 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3199 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3200 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3201 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3202 3203 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3204 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);CHKERRQ(ierr); 3205 if (flg) { 3206 PetscReal fact = 1.39; 3207 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3208 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3209 if (fact <= 1.0) fact = 1.39; 3210 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3211 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3212 } 3213 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3214 PetscFunctionReturn(0); 3215 } 3216 3217 /*MC 3218 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3219 3220 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3221 and MATMPIBAIJ otherwise. 3222 3223 Options Database Keys: 3224 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3225 3226 Level: beginner 3227 3228 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3229 M*/ 3230 3231 #undef __FUNCT__ 3232 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3233 /*@C 3234 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3235 (block compressed row). For good matrix assembly performance 3236 the user should preallocate the matrix storage by setting the parameters 3237 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3238 performance can be increased by more than a factor of 50. 3239 3240 Collective on Mat 3241 3242 Input Parameters: 3243 + B - the matrix 3244 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3245 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3246 . d_nz - number of block nonzeros per block row in diagonal portion of local 3247 submatrix (same for all local rows) 3248 . d_nnz - array containing the number of block nonzeros in the various block rows 3249 of the in diagonal portion of the local (possibly different for each block 3250 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3251 set it even if it is zero. 3252 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3253 submatrix (same for all local rows). 3254 - o_nnz - array containing the number of nonzeros in the various block rows of the 3255 off-diagonal portion of the local submatrix (possibly different for 3256 each block row) or NULL. 3257 3258 If the *_nnz parameter is given then the *_nz parameter is ignored 3259 3260 Options Database Keys: 3261 + -mat_block_size - size of the blocks to use 3262 - -mat_use_hash_table <fact> 3263 3264 Notes: 3265 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3266 than it must be used on all processors that share the object for that argument. 3267 3268 Storage Information: 3269 For a square global matrix we define each processor's diagonal portion 3270 to be its local rows and the corresponding columns (a square submatrix); 3271 each processor's off-diagonal portion encompasses the remainder of the 3272 local matrix (a rectangular submatrix). 3273 3274 The user can specify preallocated storage for the diagonal part of 3275 the local submatrix with either d_nz or d_nnz (not both). Set 3276 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3277 memory allocation. Likewise, specify preallocated storage for the 3278 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3279 3280 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3281 the figure below we depict these three local rows and all columns (0-11). 3282 3283 .vb 3284 0 1 2 3 4 5 6 7 8 9 10 11 3285 -------------------------- 3286 row 3 |o o o d d d o o o o o o 3287 row 4 |o o o d d d o o o o o o 3288 row 5 |o o o d d d o o o o o o 3289 -------------------------- 3290 .ve 3291 3292 Thus, any entries in the d locations are stored in the d (diagonal) 3293 submatrix, and any entries in the o locations are stored in the 3294 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3295 stored simply in the MATSEQBAIJ format for compressed row storage. 3296 3297 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3298 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3299 In general, for PDE problems in which most nonzeros are near the diagonal, 3300 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3301 or you will get TERRIBLE performance; see the users' manual chapter on 3302 matrices. 3303 3304 You can call MatGetInfo() to get information on how effective the preallocation was; 3305 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3306 You can also run with the option -info and look for messages with the string 3307 malloc in them to see if additional memory allocation was needed. 3308 3309 Level: intermediate 3310 3311 .keywords: matrix, block, aij, compressed row, sparse, parallel 3312 3313 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3314 @*/ 3315 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3316 { 3317 PetscErrorCode ierr; 3318 3319 PetscFunctionBegin; 3320 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3321 PetscValidType(B,1); 3322 PetscValidLogicalCollectiveInt(B,bs,2); 3323 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3324 PetscFunctionReturn(0); 3325 } 3326 3327 #undef __FUNCT__ 3328 #define __FUNCT__ "MatCreateBAIJ" 3329 /*@C 3330 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3331 (block compressed row). For good matrix assembly performance 3332 the user should preallocate the matrix storage by setting the parameters 3333 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3334 performance can be increased by more than a factor of 50. 3335 3336 Collective on MPI_Comm 3337 3338 Input Parameters: 3339 + comm - MPI communicator 3340 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3341 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3342 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3343 This value should be the same as the local size used in creating the 3344 y vector for the matrix-vector product y = Ax. 3345 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3346 This value should be the same as the local size used in creating the 3347 x vector for the matrix-vector product y = Ax. 3348 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3349 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3350 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3351 submatrix (same for all local rows) 3352 . d_nnz - array containing the number of nonzero blocks in the various block rows 3353 of the in diagonal portion of the local (possibly different for each block 3354 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3355 and set it even if it is zero. 3356 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3357 submatrix (same for all local rows). 3358 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3359 off-diagonal portion of the local submatrix (possibly different for 3360 each block row) or NULL. 3361 3362 Output Parameter: 3363 . A - the matrix 3364 3365 Options Database Keys: 3366 + -mat_block_size - size of the blocks to use 3367 - -mat_use_hash_table <fact> 3368 3369 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3370 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3371 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3372 3373 Notes: 3374 If the *_nnz parameter is given then the *_nz parameter is ignored 3375 3376 A nonzero block is any block that as 1 or more nonzeros in it 3377 3378 The user MUST specify either the local or global matrix dimensions 3379 (possibly both). 3380 3381 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3382 than it must be used on all processors that share the object for that argument. 3383 3384 Storage Information: 3385 For a square global matrix we define each processor's diagonal portion 3386 to be its local rows and the corresponding columns (a square submatrix); 3387 each processor's off-diagonal portion encompasses the remainder of the 3388 local matrix (a rectangular submatrix). 3389 3390 The user can specify preallocated storage for the diagonal part of 3391 the local submatrix with either d_nz or d_nnz (not both). Set 3392 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3393 memory allocation. Likewise, specify preallocated storage for the 3394 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3395 3396 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3397 the figure below we depict these three local rows and all columns (0-11). 3398 3399 .vb 3400 0 1 2 3 4 5 6 7 8 9 10 11 3401 -------------------------- 3402 row 3 |o o o d d d o o o o o o 3403 row 4 |o o o d d d o o o o o o 3404 row 5 |o o o d d d o o o o o o 3405 -------------------------- 3406 .ve 3407 3408 Thus, any entries in the d locations are stored in the d (diagonal) 3409 submatrix, and any entries in the o locations are stored in the 3410 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3411 stored simply in the MATSEQBAIJ format for compressed row storage. 3412 3413 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3414 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3415 In general, for PDE problems in which most nonzeros are near the diagonal, 3416 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3417 or you will get TERRIBLE performance; see the users' manual chapter on 3418 matrices. 3419 3420 Level: intermediate 3421 3422 .keywords: matrix, block, aij, compressed row, sparse, parallel 3423 3424 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3425 @*/ 3426 PetscErrorCode MatCreateBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3427 { 3428 PetscErrorCode ierr; 3429 PetscMPIInt size; 3430 3431 PetscFunctionBegin; 3432 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3433 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3434 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3435 if (size > 1) { 3436 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3437 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3438 } else { 3439 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3440 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3441 } 3442 PetscFunctionReturn(0); 3443 } 3444 3445 #undef __FUNCT__ 3446 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3447 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3448 { 3449 Mat mat; 3450 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3451 PetscErrorCode ierr; 3452 PetscInt len=0; 3453 3454 PetscFunctionBegin; 3455 *newmat = 0; 3456 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3457 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3458 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3459 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3460 3461 mat->factortype = matin->factortype; 3462 mat->preallocated = PETSC_TRUE; 3463 mat->assembled = PETSC_TRUE; 3464 mat->insertmode = NOT_SET_VALUES; 3465 3466 a = (Mat_MPIBAIJ*)mat->data; 3467 mat->rmap->bs = matin->rmap->bs; 3468 a->bs2 = oldmat->bs2; 3469 a->mbs = oldmat->mbs; 3470 a->nbs = oldmat->nbs; 3471 a->Mbs = oldmat->Mbs; 3472 a->Nbs = oldmat->Nbs; 3473 3474 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3475 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3476 3477 a->size = oldmat->size; 3478 a->rank = oldmat->rank; 3479 a->donotstash = oldmat->donotstash; 3480 a->roworiented = oldmat->roworiented; 3481 a->rowindices = 0; 3482 a->rowvalues = 0; 3483 a->getrowactive = PETSC_FALSE; 3484 a->barray = 0; 3485 a->rstartbs = oldmat->rstartbs; 3486 a->rendbs = oldmat->rendbs; 3487 a->cstartbs = oldmat->cstartbs; 3488 a->cendbs = oldmat->cendbs; 3489 3490 /* hash table stuff */ 3491 a->ht = 0; 3492 a->hd = 0; 3493 a->ht_size = 0; 3494 a->ht_flag = oldmat->ht_flag; 3495 a->ht_fact = oldmat->ht_fact; 3496 a->ht_total_ct = 0; 3497 a->ht_insert_ct = 0; 3498 3499 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3500 if (oldmat->colmap) { 3501 #if defined(PETSC_USE_CTABLE) 3502 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3503 #else 3504 ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr); 3505 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3506 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3507 #endif 3508 } else a->colmap = 0; 3509 3510 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3511 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3512 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3513 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3514 } else a->garray = 0; 3515 3516 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3517 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3518 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3519 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3520 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3521 3522 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3523 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3524 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3525 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3526 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3527 *newmat = mat; 3528 PetscFunctionReturn(0); 3529 } 3530 3531 #undef __FUNCT__ 3532 #define __FUNCT__ "MatLoad_MPIBAIJ" 3533 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3534 { 3535 PetscErrorCode ierr; 3536 int fd; 3537 PetscInt i,nz,j,rstart,rend; 3538 PetscScalar *vals,*buf; 3539 MPI_Comm comm; 3540 MPI_Status status; 3541 PetscMPIInt rank,size,maxnz; 3542 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3543 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3544 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3545 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3546 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3547 PetscInt dcount,kmax,k,nzcount,tmp,mend; 3548 3549 PetscFunctionBegin; 3550 /* force binary viewer to load .info file if it has not yet done so */ 3551 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 3552 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3553 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3554 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3555 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3556 if (bs < 0) bs = 1; 3557 3558 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3559 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3560 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3561 if (!rank) { 3562 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3563 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3564 } 3565 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3566 M = header[1]; N = header[2]; 3567 3568 /* If global sizes are set, check if they are consistent with that given in the file */ 3569 if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M); 3570 if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N); 3571 3572 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3573 3574 /* 3575 This code adds extra rows to make sure the number of rows is 3576 divisible by the blocksize 3577 */ 3578 Mbs = M/bs; 3579 extra_rows = bs - M + bs*Mbs; 3580 if (extra_rows == bs) extra_rows = 0; 3581 else Mbs++; 3582 if (extra_rows && !rank) { 3583 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3584 } 3585 3586 /* determine ownership of all rows */ 3587 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3588 mbs = Mbs/size + ((Mbs % size) > rank); 3589 m = mbs*bs; 3590 } else { /* User set */ 3591 m = newmat->rmap->n; 3592 mbs = m/bs; 3593 } 3594 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3595 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3596 3597 /* process 0 needs enough room for process with most rows */ 3598 if (!rank) { 3599 mmax = rowners[1]; 3600 for (i=2; i<=size; i++) { 3601 mmax = PetscMax(mmax,rowners[i]); 3602 } 3603 mmax*=bs; 3604 } else mmax = -1; /* unused, but compiler warns anyway */ 3605 3606 rowners[0] = 0; 3607 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3608 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3609 rstart = rowners[rank]; 3610 rend = rowners[rank+1]; 3611 3612 /* distribute row lengths to all processors */ 3613 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3614 if (!rank) { 3615 mend = m; 3616 if (size == 1) mend = mend - extra_rows; 3617 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3618 for (j=mend; j<m; j++) locrowlens[j] = 1; 3619 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3620 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3621 for (j=0; j<m; j++) { 3622 procsnz[0] += locrowlens[j]; 3623 } 3624 for (i=1; i<size; i++) { 3625 mend = browners[i+1] - browners[i]; 3626 if (i == size-1) mend = mend - extra_rows; 3627 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3628 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3629 /* calculate the number of nonzeros on each processor */ 3630 for (j=0; j<browners[i+1]-browners[i]; j++) { 3631 procsnz[i] += rowlengths[j]; 3632 } 3633 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3634 } 3635 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3636 } else { 3637 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3638 } 3639 3640 if (!rank) { 3641 /* determine max buffer needed and allocate it */ 3642 maxnz = procsnz[0]; 3643 for (i=1; i<size; i++) { 3644 maxnz = PetscMax(maxnz,procsnz[i]); 3645 } 3646 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3647 3648 /* read in my part of the matrix column indices */ 3649 nz = procsnz[0]; 3650 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3651 mycols = ibuf; 3652 if (size == 1) nz -= extra_rows; 3653 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3654 if (size == 1) { 3655 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3656 } 3657 3658 /* read in every ones (except the last) and ship off */ 3659 for (i=1; i<size-1; i++) { 3660 nz = procsnz[i]; 3661 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3662 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3663 } 3664 /* read in the stuff for the last proc */ 3665 if (size != 1) { 3666 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3667 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3668 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3669 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3670 } 3671 ierr = PetscFree(cols);CHKERRQ(ierr); 3672 } else { 3673 /* determine buffer space needed for message */ 3674 nz = 0; 3675 for (i=0; i<m; i++) { 3676 nz += locrowlens[i]; 3677 } 3678 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3679 mycols = ibuf; 3680 /* receive message of column indices*/ 3681 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3682 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3683 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3684 } 3685 3686 /* loop over local rows, determining number of off diagonal entries */ 3687 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3688 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3689 rowcount = 0; nzcount = 0; 3690 for (i=0; i<mbs; i++) { 3691 dcount = 0; 3692 odcount = 0; 3693 for (j=0; j<bs; j++) { 3694 kmax = locrowlens[rowcount]; 3695 for (k=0; k<kmax; k++) { 3696 tmp = mycols[nzcount++]/bs; 3697 if (!mask[tmp]) { 3698 mask[tmp] = 1; 3699 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3700 else masked1[dcount++] = tmp; 3701 } 3702 } 3703 rowcount++; 3704 } 3705 3706 dlens[i] = dcount; 3707 odlens[i] = odcount; 3708 3709 /* zero out the mask elements we set */ 3710 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3711 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3712 } 3713 3714 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3715 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3716 3717 if (!rank) { 3718 ierr = PetscMalloc1(maxnz+1,&buf);CHKERRQ(ierr); 3719 /* read in my part of the matrix numerical values */ 3720 nz = procsnz[0]; 3721 vals = buf; 3722 mycols = ibuf; 3723 if (size == 1) nz -= extra_rows; 3724 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3725 if (size == 1) { 3726 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3727 } 3728 3729 /* insert into matrix */ 3730 jj = rstart*bs; 3731 for (i=0; i<m; i++) { 3732 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3733 mycols += locrowlens[i]; 3734 vals += locrowlens[i]; 3735 jj++; 3736 } 3737 /* read in other processors (except the last one) and ship out */ 3738 for (i=1; i<size-1; i++) { 3739 nz = procsnz[i]; 3740 vals = buf; 3741 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3742 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3743 } 3744 /* the last proc */ 3745 if (size != 1) { 3746 nz = procsnz[i] - extra_rows; 3747 vals = buf; 3748 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3749 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3750 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3751 } 3752 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3753 } else { 3754 /* receive numeric values */ 3755 ierr = PetscMalloc1(nz+1,&buf);CHKERRQ(ierr); 3756 3757 /* receive message of values*/ 3758 vals = buf; 3759 mycols = ibuf; 3760 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3761 3762 /* insert into matrix */ 3763 jj = rstart*bs; 3764 for (i=0; i<m; i++) { 3765 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3766 mycols += locrowlens[i]; 3767 vals += locrowlens[i]; 3768 jj++; 3769 } 3770 } 3771 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3772 ierr = PetscFree(buf);CHKERRQ(ierr); 3773 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3774 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3775 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3776 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3777 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3778 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3779 PetscFunctionReturn(0); 3780 } 3781 3782 #undef __FUNCT__ 3783 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3784 /*@ 3785 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3786 3787 Input Parameters: 3788 . mat - the matrix 3789 . fact - factor 3790 3791 Not Collective, each process can use a different factor 3792 3793 Level: advanced 3794 3795 Notes: 3796 This can also be set by the command line option: -mat_use_hash_table <fact> 3797 3798 .keywords: matrix, hashtable, factor, HT 3799 3800 .seealso: MatSetOption() 3801 @*/ 3802 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3803 { 3804 PetscErrorCode ierr; 3805 3806 PetscFunctionBegin; 3807 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3808 PetscFunctionReturn(0); 3809 } 3810 3811 #undef __FUNCT__ 3812 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3813 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3814 { 3815 Mat_MPIBAIJ *baij; 3816 3817 PetscFunctionBegin; 3818 baij = (Mat_MPIBAIJ*)mat->data; 3819 baij->ht_fact = fact; 3820 PetscFunctionReturn(0); 3821 } 3822 3823 #undef __FUNCT__ 3824 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3825 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3826 { 3827 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3828 3829 PetscFunctionBegin; 3830 if (Ad) *Ad = a->A; 3831 if (Ao) *Ao = a->B; 3832 if (colmap) *colmap = a->garray; 3833 PetscFunctionReturn(0); 3834 } 3835 3836 /* 3837 Special version for direct calls from Fortran (to eliminate two function call overheads 3838 */ 3839 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3840 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3841 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3842 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3843 #endif 3844 3845 #undef __FUNCT__ 3846 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3847 /*@C 3848 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3849 3850 Collective on Mat 3851 3852 Input Parameters: 3853 + mat - the matrix 3854 . min - number of input rows 3855 . im - input rows 3856 . nin - number of input columns 3857 . in - input columns 3858 . v - numerical values input 3859 - addvin - INSERT_VALUES or ADD_VALUES 3860 3861 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3862 3863 Level: advanced 3864 3865 .seealso: MatSetValuesBlocked() 3866 @*/ 3867 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3868 { 3869 /* convert input arguments to C version */ 3870 Mat mat = *matin; 3871 PetscInt m = *min, n = *nin; 3872 InsertMode addv = *addvin; 3873 3874 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3875 const MatScalar *value; 3876 MatScalar *barray = baij->barray; 3877 PetscBool roworiented = baij->roworiented; 3878 PetscErrorCode ierr; 3879 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3880 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3881 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3882 3883 PetscFunctionBegin; 3884 /* tasks normally handled by MatSetValuesBlocked() */ 3885 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3886 #if defined(PETSC_USE_DEBUG) 3887 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3888 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3889 #endif 3890 if (mat->assembled) { 3891 mat->was_assembled = PETSC_TRUE; 3892 mat->assembled = PETSC_FALSE; 3893 } 3894 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3895 3896 3897 if (!barray) { 3898 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3899 baij->barray = barray; 3900 } 3901 3902 if (roworiented) stepval = (n-1)*bs; 3903 else stepval = (m-1)*bs; 3904 3905 for (i=0; i<m; i++) { 3906 if (im[i] < 0) continue; 3907 #if defined(PETSC_USE_DEBUG) 3908 if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1); 3909 #endif 3910 if (im[i] >= rstart && im[i] < rend) { 3911 row = im[i] - rstart; 3912 for (j=0; j<n; j++) { 3913 /* If NumCol = 1 then a copy is not required */ 3914 if ((roworiented) && (n == 1)) { 3915 barray = (MatScalar*)v + i*bs2; 3916 } else if ((!roworiented) && (m == 1)) { 3917 barray = (MatScalar*)v + j*bs2; 3918 } else { /* Here a copy is required */ 3919 if (roworiented) { 3920 value = v + i*(stepval+bs)*bs + j*bs; 3921 } else { 3922 value = v + j*(stepval+bs)*bs + i*bs; 3923 } 3924 for (ii=0; ii<bs; ii++,value+=stepval) { 3925 for (jj=0; jj<bs; jj++) { 3926 *barray++ = *value++; 3927 } 3928 } 3929 barray -=bs2; 3930 } 3931 3932 if (in[j] >= cstart && in[j] < cend) { 3933 col = in[j] - cstart; 3934 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3935 } else if (in[j] < 0) continue; 3936 #if defined(PETSC_USE_DEBUG) 3937 else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1); 3938 #endif 3939 else { 3940 if (mat->was_assembled) { 3941 if (!baij->colmap) { 3942 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3943 } 3944 3945 #if defined(PETSC_USE_DEBUG) 3946 #if defined(PETSC_USE_CTABLE) 3947 { PetscInt data; 3948 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3949 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3950 } 3951 #else 3952 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3953 #endif 3954 #endif 3955 #if defined(PETSC_USE_CTABLE) 3956 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3957 col = (col - 1)/bs; 3958 #else 3959 col = (baij->colmap[in[j]] - 1)/bs; 3960 #endif 3961 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3962 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3963 col = in[j]; 3964 } 3965 } else col = in[j]; 3966 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3967 } 3968 } 3969 } else { 3970 if (!baij->donotstash) { 3971 if (roworiented) { 3972 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3973 } else { 3974 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3975 } 3976 } 3977 } 3978 } 3979 3980 /* task normally handled by MatSetValuesBlocked() */ 3981 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3982 PetscFunctionReturn(0); 3983 } 3984 3985 #undef __FUNCT__ 3986 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3987 /*@ 3988 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3989 CSR format the local rows. 3990 3991 Collective on MPI_Comm 3992 3993 Input Parameters: 3994 + comm - MPI communicator 3995 . bs - the block size, only a block size of 1 is supported 3996 . m - number of local rows (Cannot be PETSC_DECIDE) 3997 . n - This value should be the same as the local size used in creating the 3998 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3999 calculated if N is given) For square matrices n is almost always m. 4000 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4001 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4002 . i - row indices 4003 . j - column indices 4004 - a - matrix values 4005 4006 Output Parameter: 4007 . mat - the matrix 4008 4009 Level: intermediate 4010 4011 Notes: 4012 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4013 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4014 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4015 4016 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 4017 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 4018 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 4019 with column-major ordering within blocks. 4020 4021 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4022 4023 .keywords: matrix, aij, compressed row, sparse, parallel 4024 4025 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4026 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4027 @*/ 4028 PetscErrorCode MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4029 { 4030 PetscErrorCode ierr; 4031 4032 PetscFunctionBegin; 4033 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4034 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4035 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4036 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4037 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 4038 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 4039 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 4040 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 4041 PetscFunctionReturn(0); 4042 } 4043 4044 #undef __FUNCT__ 4045 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIBAIJ" 4046 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4047 { 4048 PetscErrorCode ierr; 4049 PetscInt m,N,i,rstart,nnz,Ii,bs,cbs; 4050 PetscInt *indx; 4051 PetscScalar *values; 4052 4053 PetscFunctionBegin; 4054 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4055 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4056 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inmat->data; 4057 PetscInt *dnz,*onz,sum,mbs,Nbs; 4058 PetscInt *bindx,rmax=a->rmax,j; 4059 4060 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4061 mbs = m/bs; Nbs = N/cbs; 4062 if (n == PETSC_DECIDE) { 4063 ierr = PetscSplitOwnership(comm,&n,&Nbs);CHKERRQ(ierr); 4064 } 4065 /* Check sum(n) = Nbs */ 4066 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4067 if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs); 4068 4069 ierr = MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4070 rstart -= mbs; 4071 4072 ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr); 4073 ierr = MatPreallocateInitialize(comm,mbs,n,dnz,onz);CHKERRQ(ierr); 4074 for (i=0; i<mbs; i++) { 4075 ierr = MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */ 4076 nnz = nnz/bs; 4077 for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs; 4078 ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr); 4079 ierr = MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); 4080 } 4081 ierr = PetscFree(bindx);CHKERRQ(ierr); 4082 4083 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4084 ierr = MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4085 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4086 ierr = MatSetType(*outmat,MATMPIBAIJ);CHKERRQ(ierr); 4087 ierr = MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr); 4088 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4089 } 4090 4091 /* numeric phase */ 4092 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4093 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4094 4095 for (i=0; i<m; i++) { 4096 ierr = MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4097 Ii = i + rstart; 4098 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4099 ierr = MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4100 } 4101 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4102 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4103 PetscFunctionReturn(0); 4104 } 4105