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,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1385 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1386 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1387 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr); 1388 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1389 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr); 1390 PetscFunctionReturn(0); 1391 } 1392 1393 #undef __FUNCT__ 1394 #define __FUNCT__ "MatMult_MPIBAIJ" 1395 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1396 { 1397 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1398 PetscErrorCode ierr; 1399 PetscInt nt; 1400 1401 PetscFunctionBegin; 1402 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1403 if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 1404 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1405 if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 1406 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1407 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1408 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1409 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1410 PetscFunctionReturn(0); 1411 } 1412 1413 #undef __FUNCT__ 1414 #define __FUNCT__ "MatMultAdd_MPIBAIJ" 1415 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1416 { 1417 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1418 PetscErrorCode ierr; 1419 1420 PetscFunctionBegin; 1421 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1422 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1423 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1424 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1425 PetscFunctionReturn(0); 1426 } 1427 1428 #undef __FUNCT__ 1429 #define __FUNCT__ "MatMultTranspose_MPIBAIJ" 1430 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy) 1431 { 1432 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1433 PetscErrorCode ierr; 1434 PetscBool merged; 1435 1436 PetscFunctionBegin; 1437 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1438 /* do nondiagonal part */ 1439 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1440 if (!merged) { 1441 /* send it on its way */ 1442 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1443 /* do local part */ 1444 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1445 /* receive remote parts: note this assumes the values are not actually */ 1446 /* inserted in yy until the next line */ 1447 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1448 } else { 1449 /* do local part */ 1450 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1451 /* send it on its way */ 1452 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1453 /* values actually were received in the Begin() but we need to call this nop */ 1454 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1455 } 1456 PetscFunctionReturn(0); 1457 } 1458 1459 #undef __FUNCT__ 1460 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ" 1461 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1462 { 1463 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1464 PetscErrorCode ierr; 1465 1466 PetscFunctionBegin; 1467 /* do nondiagonal part */ 1468 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1469 /* send it on its way */ 1470 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1471 /* do local part */ 1472 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1473 /* receive remote parts: note this assumes the values are not actually */ 1474 /* inserted in yy until the next line, which is true for my implementation*/ 1475 /* but is not perhaps always true. */ 1476 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1477 PetscFunctionReturn(0); 1478 } 1479 1480 /* 1481 This only works correctly for square matrices where the subblock A->A is the 1482 diagonal block 1483 */ 1484 #undef __FUNCT__ 1485 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ" 1486 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1487 { 1488 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1489 PetscErrorCode ierr; 1490 1491 PetscFunctionBegin; 1492 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1493 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1494 PetscFunctionReturn(0); 1495 } 1496 1497 #undef __FUNCT__ 1498 #define __FUNCT__ "MatScale_MPIBAIJ" 1499 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa) 1500 { 1501 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1502 PetscErrorCode ierr; 1503 1504 PetscFunctionBegin; 1505 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1506 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1507 PetscFunctionReturn(0); 1508 } 1509 1510 #undef __FUNCT__ 1511 #define __FUNCT__ "MatGetRow_MPIBAIJ" 1512 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1513 { 1514 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 1515 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1516 PetscErrorCode ierr; 1517 PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB; 1518 PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend; 1519 PetscInt *cmap,*idx_p,cstart = mat->cstartbs; 1520 1521 PetscFunctionBegin; 1522 if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows"); 1523 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1524 mat->getrowactive = PETSC_TRUE; 1525 1526 if (!mat->rowvalues && (idx || v)) { 1527 /* 1528 allocate enough space to hold information from the longest row. 1529 */ 1530 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data; 1531 PetscInt max = 1,mbs = mat->mbs,tmp; 1532 for (i=0; i<mbs; i++) { 1533 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1534 if (max < tmp) max = tmp; 1535 } 1536 ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr); 1537 } 1538 lrow = row - brstart; 1539 1540 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1541 if (!v) {pvA = 0; pvB = 0;} 1542 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1543 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1544 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1545 nztot = nzA + nzB; 1546 1547 cmap = mat->garray; 1548 if (v || idx) { 1549 if (nztot) { 1550 /* Sort by increasing column numbers, assuming A and B already sorted */ 1551 PetscInt imark = -1; 1552 if (v) { 1553 *v = v_p = mat->rowvalues; 1554 for (i=0; i<nzB; i++) { 1555 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1556 else break; 1557 } 1558 imark = i; 1559 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1560 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1561 } 1562 if (idx) { 1563 *idx = idx_p = mat->rowindices; 1564 if (imark > -1) { 1565 for (i=0; i<imark; i++) { 1566 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1567 } 1568 } else { 1569 for (i=0; i<nzB; i++) { 1570 if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1571 else break; 1572 } 1573 imark = i; 1574 } 1575 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1576 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1577 } 1578 } else { 1579 if (idx) *idx = 0; 1580 if (v) *v = 0; 1581 } 1582 } 1583 *nz = nztot; 1584 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1585 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1586 PetscFunctionReturn(0); 1587 } 1588 1589 #undef __FUNCT__ 1590 #define __FUNCT__ "MatRestoreRow_MPIBAIJ" 1591 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1592 { 1593 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1594 1595 PetscFunctionBegin; 1596 if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1597 baij->getrowactive = PETSC_FALSE; 1598 PetscFunctionReturn(0); 1599 } 1600 1601 #undef __FUNCT__ 1602 #define __FUNCT__ "MatZeroEntries_MPIBAIJ" 1603 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A) 1604 { 1605 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1606 PetscErrorCode ierr; 1607 1608 PetscFunctionBegin; 1609 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1610 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1611 PetscFunctionReturn(0); 1612 } 1613 1614 #undef __FUNCT__ 1615 #define __FUNCT__ "MatGetInfo_MPIBAIJ" 1616 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1617 { 1618 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)matin->data; 1619 Mat A = a->A,B = a->B; 1620 PetscErrorCode ierr; 1621 PetscReal isend[5],irecv[5]; 1622 1623 PetscFunctionBegin; 1624 info->block_size = (PetscReal)matin->rmap->bs; 1625 1626 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1627 1628 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1629 isend[3] = info->memory; isend[4] = info->mallocs; 1630 1631 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1632 1633 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1634 isend[3] += info->memory; isend[4] += info->mallocs; 1635 1636 if (flag == MAT_LOCAL) { 1637 info->nz_used = isend[0]; 1638 info->nz_allocated = isend[1]; 1639 info->nz_unneeded = isend[2]; 1640 info->memory = isend[3]; 1641 info->mallocs = isend[4]; 1642 } else if (flag == MAT_GLOBAL_MAX) { 1643 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1644 1645 info->nz_used = irecv[0]; 1646 info->nz_allocated = irecv[1]; 1647 info->nz_unneeded = irecv[2]; 1648 info->memory = irecv[3]; 1649 info->mallocs = irecv[4]; 1650 } else if (flag == MAT_GLOBAL_SUM) { 1651 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1652 1653 info->nz_used = irecv[0]; 1654 info->nz_allocated = irecv[1]; 1655 info->nz_unneeded = irecv[2]; 1656 info->memory = irecv[3]; 1657 info->mallocs = irecv[4]; 1658 } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag); 1659 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1660 info->fill_ratio_needed = 0; 1661 info->factor_mallocs = 0; 1662 PetscFunctionReturn(0); 1663 } 1664 1665 #undef __FUNCT__ 1666 #define __FUNCT__ "MatSetOption_MPIBAIJ" 1667 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg) 1668 { 1669 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1670 PetscErrorCode ierr; 1671 1672 PetscFunctionBegin; 1673 switch (op) { 1674 case MAT_NEW_NONZERO_LOCATIONS: 1675 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1676 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1677 case MAT_KEEP_NONZERO_PATTERN: 1678 case MAT_NEW_NONZERO_LOCATION_ERR: 1679 MatCheckPreallocated(A,1); 1680 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1681 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1682 break; 1683 case MAT_ROW_ORIENTED: 1684 MatCheckPreallocated(A,1); 1685 a->roworiented = flg; 1686 1687 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1688 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1689 break; 1690 case MAT_NEW_DIAGONALS: 1691 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1692 break; 1693 case MAT_IGNORE_OFF_PROC_ENTRIES: 1694 a->donotstash = flg; 1695 break; 1696 case MAT_USE_HASH_TABLE: 1697 a->ht_flag = flg; 1698 break; 1699 case MAT_SYMMETRIC: 1700 case MAT_STRUCTURALLY_SYMMETRIC: 1701 case MAT_HERMITIAN: 1702 case MAT_SYMMETRY_ETERNAL: 1703 MatCheckPreallocated(A,1); 1704 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1705 break; 1706 default: 1707 SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op); 1708 } 1709 PetscFunctionReturn(0); 1710 } 1711 1712 #undef __FUNCT__ 1713 #define __FUNCT__ "MatTranspose_MPIBAIJ" 1714 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout) 1715 { 1716 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)A->data; 1717 Mat_SeqBAIJ *Aloc; 1718 Mat B; 1719 PetscErrorCode ierr; 1720 PetscInt M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col; 1721 PetscInt bs=A->rmap->bs,mbs=baij->mbs; 1722 MatScalar *a; 1723 1724 PetscFunctionBegin; 1725 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1726 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1727 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1728 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1729 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1730 /* Do not know preallocation information, but must set block size */ 1731 ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr); 1732 } else { 1733 B = *matout; 1734 } 1735 1736 /* copy over the A part */ 1737 Aloc = (Mat_SeqBAIJ*)baij->A->data; 1738 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1739 ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr); 1740 1741 for (i=0; i<mbs; i++) { 1742 rvals[0] = bs*(baij->rstartbs + i); 1743 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1744 for (j=ai[i]; j<ai[i+1]; j++) { 1745 col = (baij->cstartbs+aj[j])*bs; 1746 for (k=0; k<bs; k++) { 1747 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1748 1749 col++; a += bs; 1750 } 1751 } 1752 } 1753 /* copy over the B part */ 1754 Aloc = (Mat_SeqBAIJ*)baij->B->data; 1755 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1756 for (i=0; i<mbs; i++) { 1757 rvals[0] = bs*(baij->rstartbs + i); 1758 for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1; 1759 for (j=ai[i]; j<ai[i+1]; j++) { 1760 col = baij->garray[aj[j]]*bs; 1761 for (k=0; k<bs; k++) { 1762 ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1763 col++; 1764 a += bs; 1765 } 1766 } 1767 } 1768 ierr = PetscFree(rvals);CHKERRQ(ierr); 1769 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1770 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1771 1772 if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B; 1773 else { 1774 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 1775 } 1776 PetscFunctionReturn(0); 1777 } 1778 1779 #undef __FUNCT__ 1780 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ" 1781 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr) 1782 { 1783 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 1784 Mat a = baij->A,b = baij->B; 1785 PetscErrorCode ierr; 1786 PetscInt s1,s2,s3; 1787 1788 PetscFunctionBegin; 1789 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1790 if (rr) { 1791 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1792 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1793 /* Overlap communication with computation. */ 1794 ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1795 } 1796 if (ll) { 1797 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1798 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1799 ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr); 1800 } 1801 /* scale the diagonal block */ 1802 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1803 1804 if (rr) { 1805 /* Do a scatter end and then right scale the off-diagonal block */ 1806 ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1807 ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr); 1808 } 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatZeroRows_MPIBAIJ" 1814 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1815 { 1816 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1817 PetscInt *lrows; 1818 PetscInt r, len; 1819 PetscErrorCode ierr; 1820 1821 PetscFunctionBegin; 1822 /* get locally owned rows */ 1823 ierr = MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);CHKERRQ(ierr); 1824 /* fix right hand side if needed */ 1825 if (x && b) { 1826 const PetscScalar *xx; 1827 PetscScalar *bb; 1828 1829 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1830 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1831 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 1832 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1833 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1834 } 1835 1836 /* actually zap the local rows */ 1837 /* 1838 Zero the required rows. If the "diagonal block" of the matrix 1839 is square and the user wishes to set the diagonal we use separate 1840 code so that MatSetValues() is not called for each diagonal allocating 1841 new memory, thus calling lots of mallocs and slowing things down. 1842 1843 */ 1844 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1845 ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1846 if (A->congruentlayouts == -1) { /* first time we compare rows and cols layouts */ 1847 PetscBool cong; 1848 ierr = PetscLayoutCompare(A->rmap,A->cmap,&cong);CHKERRQ(ierr); 1849 if (cong) A->congruentlayouts = 1; 1850 else A->congruentlayouts = 0; 1851 } 1852 if ((diag != 0.0) && A->congruentlayouts) { 1853 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr); 1854 } else if (diag != 0.0) { 1855 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr); 1856 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\ 1857 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1858 for (r = 0; r < len; ++r) { 1859 const PetscInt row = lrows[r] + A->rmap->rstart; 1860 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 1861 } 1862 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1863 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1864 } else { 1865 ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr); 1866 } 1867 ierr = PetscFree(lrows);CHKERRQ(ierr); 1868 1869 /* only change matrix nonzero state if pattern was allowed to be changed */ 1870 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1871 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1872 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1873 } 1874 PetscFunctionReturn(0); 1875 } 1876 1877 #undef __FUNCT__ 1878 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ" 1879 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1880 { 1881 Mat_MPIBAIJ *l = (Mat_MPIBAIJ*)A->data; 1882 PetscErrorCode ierr; 1883 PetscMPIInt n = A->rmap->n; 1884 PetscInt i,j,k,r,p = 0,len = 0,row,col,count; 1885 PetscInt *lrows,*owners = A->rmap->range; 1886 PetscSFNode *rrows; 1887 PetscSF sf; 1888 const PetscScalar *xx; 1889 PetscScalar *bb,*mask; 1890 Vec xmask,lmask; 1891 Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)l->B->data; 1892 PetscInt bs = A->rmap->bs, bs2 = baij->bs2; 1893 PetscScalar *aa; 1894 1895 PetscFunctionBegin; 1896 /* Create SF where leaves are input rows and roots are owned rows */ 1897 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 1898 for (r = 0; r < n; ++r) lrows[r] = -1; 1899 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 1900 for (r = 0; r < N; ++r) { 1901 const PetscInt idx = rows[r]; 1902 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); 1903 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 1904 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 1905 } 1906 rrows[r].rank = p; 1907 rrows[r].index = rows[r] - owners[p]; 1908 } 1909 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 1910 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 1911 /* Collect flags for rows to be zeroed */ 1912 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1913 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 1914 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1915 /* Compress and put in row numbers */ 1916 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 1917 /* zero diagonal part of matrix */ 1918 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 1919 /* handle off diagonal part of matrix */ 1920 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 1921 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1922 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1923 for (i=0; i<len; i++) bb[lrows[i]] = 1; 1924 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1925 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1926 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1927 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1928 if (x) { 1929 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1930 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1931 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1932 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1933 } 1934 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1935 /* remove zeroed rows of off diagonal matrix */ 1936 for (i = 0; i < len; ++i) { 1937 row = lrows[i]; 1938 count = (baij->i[row/bs +1] - baij->i[row/bs])*bs; 1939 aa = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs); 1940 for (k = 0; k < count; ++k) { 1941 aa[0] = 0.0; 1942 aa += bs; 1943 } 1944 } 1945 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1946 for (i = 0; i < l->B->rmap->N; ++i) { 1947 row = i/bs; 1948 for (j = baij->i[row]; j < baij->i[row+1]; ++j) { 1949 for (k = 0; k < bs; ++k) { 1950 col = bs*baij->j[j] + k; 1951 if (PetscAbsScalar(mask[col])) { 1952 aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k; 1953 if (x) bb[i] -= aa[0]*xx[col]; 1954 aa[0] = 0.0; 1955 } 1956 } 1957 } 1958 } 1959 if (x) { 1960 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1961 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1962 } 1963 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1964 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1965 ierr = PetscFree(lrows);CHKERRQ(ierr); 1966 1967 /* only change matrix nonzero state if pattern was allowed to be changed */ 1968 if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) { 1969 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 1970 ierr = MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1971 } 1972 PetscFunctionReturn(0); 1973 } 1974 1975 #undef __FUNCT__ 1976 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ" 1977 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A) 1978 { 1979 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 1980 PetscErrorCode ierr; 1981 1982 PetscFunctionBegin; 1983 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1984 PetscFunctionReturn(0); 1985 } 1986 1987 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*); 1988 1989 #undef __FUNCT__ 1990 #define __FUNCT__ "MatEqual_MPIBAIJ" 1991 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool *flag) 1992 { 1993 Mat_MPIBAIJ *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data; 1994 Mat a,b,c,d; 1995 PetscBool flg; 1996 PetscErrorCode ierr; 1997 1998 PetscFunctionBegin; 1999 a = matA->A; b = matA->B; 2000 c = matB->A; d = matB->B; 2001 2002 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2003 if (flg) { 2004 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2005 } 2006 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2007 PetscFunctionReturn(0); 2008 } 2009 2010 #undef __FUNCT__ 2011 #define __FUNCT__ "MatCopy_MPIBAIJ" 2012 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str) 2013 { 2014 PetscErrorCode ierr; 2015 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2016 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 2017 2018 PetscFunctionBegin; 2019 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2020 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2021 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2022 } else { 2023 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2024 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2025 } 2026 PetscFunctionReturn(0); 2027 } 2028 2029 #undef __FUNCT__ 2030 #define __FUNCT__ "MatSetUp_MPIBAIJ" 2031 PetscErrorCode MatSetUp_MPIBAIJ(Mat A) 2032 { 2033 PetscErrorCode ierr; 2034 2035 PetscFunctionBegin; 2036 ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2037 PetscFunctionReturn(0); 2038 } 2039 2040 #undef __FUNCT__ 2041 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ" 2042 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2043 { 2044 PetscErrorCode ierr; 2045 PetscInt bs = Y->rmap->bs,m = Y->rmap->N/bs; 2046 Mat_SeqBAIJ *x = (Mat_SeqBAIJ*)X->data; 2047 Mat_SeqBAIJ *y = (Mat_SeqBAIJ*)Y->data; 2048 2049 PetscFunctionBegin; 2050 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2051 PetscFunctionReturn(0); 2052 } 2053 2054 #undef __FUNCT__ 2055 #define __FUNCT__ "MatAXPY_MPIBAIJ" 2056 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2057 { 2058 PetscErrorCode ierr; 2059 Mat_MPIBAIJ *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data; 2060 PetscBLASInt bnz,one=1; 2061 Mat_SeqBAIJ *x,*y; 2062 2063 PetscFunctionBegin; 2064 if (str == SAME_NONZERO_PATTERN) { 2065 PetscScalar alpha = a; 2066 x = (Mat_SeqBAIJ*)xx->A->data; 2067 y = (Mat_SeqBAIJ*)yy->A->data; 2068 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2069 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2070 x = (Mat_SeqBAIJ*)xx->B->data; 2071 y = (Mat_SeqBAIJ*)yy->B->data; 2072 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2073 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2074 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2075 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2076 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2077 } else { 2078 Mat B; 2079 PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs; 2080 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2081 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2082 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2083 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2084 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2085 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2086 ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr); 2087 ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2088 ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2089 ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2090 /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */ 2091 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2092 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2093 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2094 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2095 } 2096 PetscFunctionReturn(0); 2097 } 2098 2099 #undef __FUNCT__ 2100 #define __FUNCT__ "MatRealPart_MPIBAIJ" 2101 PetscErrorCode MatRealPart_MPIBAIJ(Mat A) 2102 { 2103 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2104 PetscErrorCode ierr; 2105 2106 PetscFunctionBegin; 2107 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2108 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2109 PetscFunctionReturn(0); 2110 } 2111 2112 #undef __FUNCT__ 2113 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ" 2114 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A) 2115 { 2116 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2117 PetscErrorCode ierr; 2118 2119 PetscFunctionBegin; 2120 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2121 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2122 PetscFunctionReturn(0); 2123 } 2124 2125 #undef __FUNCT__ 2126 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ" 2127 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 2128 { 2129 PetscErrorCode ierr; 2130 IS iscol_local; 2131 PetscInt csize; 2132 2133 PetscFunctionBegin; 2134 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 2135 if (call == MAT_REUSE_MATRIX) { 2136 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 2137 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2138 } else { 2139 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 2140 } 2141 ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 2142 if (call == MAT_INITIAL_MATRIX) { 2143 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 2144 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 2145 } 2146 PetscFunctionReturn(0); 2147 } 2148 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*); 2149 #undef __FUNCT__ 2150 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private" 2151 /* 2152 Not great since it makes two copies of the submatrix, first an SeqBAIJ 2153 in local and then by concatenating the local matrices the end result. 2154 Writing it directly would be much like MatGetSubMatrices_MPIBAIJ(). 2155 This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency). 2156 */ 2157 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2158 { 2159 PetscErrorCode ierr; 2160 PetscMPIInt rank,size; 2161 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs; 2162 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow; 2163 Mat M,Mreuse; 2164 MatScalar *vwork,*aa; 2165 MPI_Comm comm; 2166 IS isrow_new, iscol_new; 2167 PetscBool idflag,allrows, allcols; 2168 Mat_SeqBAIJ *aij; 2169 2170 PetscFunctionBegin; 2171 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2172 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2173 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2174 /* The compression and expansion should be avoided. Doesn't point 2175 out errors, might change the indices, hence buggey */ 2176 ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr); 2177 ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr); 2178 2179 /* Check for special case: each processor gets entire matrix columns */ 2180 ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr); 2181 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 2182 if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE; 2183 else allcols = PETSC_FALSE; 2184 2185 ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr); 2186 ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr); 2187 if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE; 2188 else allrows = PETSC_FALSE; 2189 2190 if (call == MAT_REUSE_MATRIX) { 2191 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 2192 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2193 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2194 } else { 2195 ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr); 2196 } 2197 ierr = ISDestroy(&isrow_new);CHKERRQ(ierr); 2198 ierr = ISDestroy(&iscol_new);CHKERRQ(ierr); 2199 /* 2200 m - number of local rows 2201 n - number of columns (same on all processors) 2202 rstart - first row in new global matrix generated 2203 */ 2204 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 2205 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2206 m = m/bs; 2207 n = n/bs; 2208 2209 if (call == MAT_INITIAL_MATRIX) { 2210 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2211 ii = aij->i; 2212 jj = aij->j; 2213 2214 /* 2215 Determine the number of non-zeros in the diagonal and off-diagonal 2216 portions of the matrix in order to do correct preallocation 2217 */ 2218 2219 /* first get start and end of "diagonal" columns */ 2220 if (csize == PETSC_DECIDE) { 2221 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2222 if (mglobal == n*bs) { /* square matrix */ 2223 nlocal = m; 2224 } else { 2225 nlocal = n/size + ((n % size) > rank); 2226 } 2227 } else { 2228 nlocal = csize/bs; 2229 } 2230 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2231 rstart = rend - nlocal; 2232 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); 2233 2234 /* next, compute all the lengths */ 2235 ierr = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr); 2236 for (i=0; i<m; i++) { 2237 jend = ii[i+1] - ii[i]; 2238 olen = 0; 2239 dlen = 0; 2240 for (j=0; j<jend; j++) { 2241 if (*jj < rstart || *jj >= rend) olen++; 2242 else dlen++; 2243 jj++; 2244 } 2245 olens[i] = olen; 2246 dlens[i] = dlen; 2247 } 2248 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2249 ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr); 2250 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2251 ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2252 ierr = MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr); 2253 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 2254 } else { 2255 PetscInt ml,nl; 2256 2257 M = *newmat; 2258 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2259 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2260 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2261 /* 2262 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2263 rather than the slower MatSetValues(). 2264 */ 2265 M->was_assembled = PETSC_TRUE; 2266 M->assembled = PETSC_FALSE; 2267 } 2268 ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 2269 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2270 aij = (Mat_SeqBAIJ*)(Mreuse)->data; 2271 ii = aij->i; 2272 jj = aij->j; 2273 aa = aij->a; 2274 for (i=0; i<m; i++) { 2275 row = rstart/bs + i; 2276 nz = ii[i+1] - ii[i]; 2277 cwork = jj; jj += nz; 2278 vwork = aa; aa += nz*bs*bs; 2279 ierr = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2280 } 2281 2282 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2283 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2284 *newmat = M; 2285 2286 /* save submatrix used in processor for next request */ 2287 if (call == MAT_INITIAL_MATRIX) { 2288 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2289 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatPermute_MPIBAIJ" 2296 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B) 2297 { 2298 MPI_Comm comm,pcomm; 2299 PetscInt clocal_size,nrows; 2300 const PetscInt *rows; 2301 PetscMPIInt size; 2302 IS crowp,lcolp; 2303 PetscErrorCode ierr; 2304 2305 PetscFunctionBegin; 2306 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2307 /* make a collective version of 'rowp' */ 2308 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 2309 if (pcomm==comm) { 2310 crowp = rowp; 2311 } else { 2312 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 2313 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 2314 ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr); 2315 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 2316 } 2317 ierr = ISSetPermutation(crowp);CHKERRQ(ierr); 2318 /* make a local version of 'colp' */ 2319 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 2320 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 2321 if (size==1) { 2322 lcolp = colp; 2323 } else { 2324 ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr); 2325 } 2326 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 2327 /* now we just get the submatrix */ 2328 ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr); 2329 ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 2330 /* clean up */ 2331 if (pcomm!=comm) { 2332 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 2333 } 2334 if (size>1) { 2335 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 2336 } 2337 PetscFunctionReturn(0); 2338 } 2339 2340 #undef __FUNCT__ 2341 #define __FUNCT__ "MatGetGhosts_MPIBAIJ" 2342 PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[]) 2343 { 2344 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data; 2345 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)baij->B->data; 2346 2347 PetscFunctionBegin; 2348 if (nghosts) *nghosts = B->nbs; 2349 if (ghosts) *ghosts = baij->garray; 2350 PetscFunctionReturn(0); 2351 } 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ" 2355 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat) 2356 { 2357 Mat B; 2358 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2359 Mat_SeqBAIJ *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data; 2360 Mat_SeqAIJ *b; 2361 PetscErrorCode ierr; 2362 PetscMPIInt size,rank,*recvcounts = 0,*displs = 0; 2363 PetscInt sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs; 2364 PetscInt m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf; 2365 2366 PetscFunctionBegin; 2367 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); 2368 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 2369 2370 /* ---------------------------------------------------------------- 2371 Tell every processor the number of nonzeros per row 2372 */ 2373 ierr = PetscMalloc1(A->rmap->N/bs,&lens);CHKERRQ(ierr); 2374 for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) { 2375 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]; 2376 } 2377 ierr = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr); 2378 displs = recvcounts + size; 2379 for (i=0; i<size; i++) { 2380 recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs; 2381 displs[i] = A->rmap->range[i]/bs; 2382 } 2383 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2384 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2385 #else 2386 sendcount = A->rmap->rend/bs - A->rmap->rstart/bs; 2387 ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2388 #endif 2389 /* --------------------------------------------------------------- 2390 Create the sequential matrix of the same type as the local block diagonal 2391 */ 2392 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 2393 ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2394 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2395 ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr); 2396 b = (Mat_SeqAIJ*)B->data; 2397 2398 /*-------------------------------------------------------------------- 2399 Copy my part of matrix column indices over 2400 */ 2401 sendcount = ad->nz + bd->nz; 2402 jsendbuf = b->j + b->i[rstarts[rank]/bs]; 2403 a_jsendbuf = ad->j; 2404 b_jsendbuf = bd->j; 2405 n = A->rmap->rend/bs - A->rmap->rstart/bs; 2406 cnt = 0; 2407 for (i=0; i<n; i++) { 2408 2409 /* put in lower diagonal portion */ 2410 m = bd->i[i+1] - bd->i[i]; 2411 while (m > 0) { 2412 /* is it above diagonal (in bd (compressed) numbering) */ 2413 if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break; 2414 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2415 m--; 2416 } 2417 2418 /* put in diagonal portion */ 2419 for (j=ad->i[i]; j<ad->i[i+1]; j++) { 2420 jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++; 2421 } 2422 2423 /* put in upper diagonal portion */ 2424 while (m-- > 0) { 2425 jsendbuf[cnt++] = garray[*b_jsendbuf++]; 2426 } 2427 } 2428 if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt); 2429 2430 /*-------------------------------------------------------------------- 2431 Gather all column indices to all processors 2432 */ 2433 for (i=0; i<size; i++) { 2434 recvcounts[i] = 0; 2435 for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) { 2436 recvcounts[i] += lens[j]; 2437 } 2438 } 2439 displs[0] = 0; 2440 for (i=1; i<size; i++) { 2441 displs[i] = displs[i-1] + recvcounts[i-1]; 2442 } 2443 #if defined(PETSC_HAVE_MPI_IN_PLACE) 2444 ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2445 #else 2446 ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2447 #endif 2448 /*-------------------------------------------------------------------- 2449 Assemble the matrix into useable form (note numerical values not yet set) 2450 */ 2451 /* set the b->ilen (length of each row) values */ 2452 ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr); 2453 /* set the b->i indices */ 2454 b->i[0] = 0; 2455 for (i=1; i<=A->rmap->N/bs; i++) { 2456 b->i[i] = b->i[i-1] + lens[i-1]; 2457 } 2458 ierr = PetscFree(lens);CHKERRQ(ierr); 2459 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2460 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2461 ierr = PetscFree(recvcounts);CHKERRQ(ierr); 2462 2463 if (A->symmetric) { 2464 ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2465 } else if (A->hermitian) { 2466 ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr); 2467 } else if (A->structurally_symmetric) { 2468 ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr); 2469 } 2470 *newmat = B; 2471 PetscFunctionReturn(0); 2472 } 2473 2474 #undef __FUNCT__ 2475 #define __FUNCT__ "MatSOR_MPIBAIJ" 2476 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 2477 { 2478 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ*)matin->data; 2479 PetscErrorCode ierr; 2480 Vec bb1 = 0; 2481 2482 PetscFunctionBegin; 2483 if (flag == SOR_APPLY_UPPER) { 2484 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2485 PetscFunctionReturn(0); 2486 } 2487 2488 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) { 2489 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 2490 } 2491 2492 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 2493 if (flag & SOR_ZERO_INITIAL_GUESS) { 2494 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2495 its--; 2496 } 2497 2498 while (its--) { 2499 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2500 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2501 2502 /* update rhs: bb1 = bb - B*x */ 2503 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2504 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2505 2506 /* local sweep */ 2507 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2508 } 2509 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 2510 if (flag & SOR_ZERO_INITIAL_GUESS) { 2511 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2512 its--; 2513 } 2514 while (its--) { 2515 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2516 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2517 2518 /* update rhs: bb1 = bb - B*x */ 2519 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2520 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2521 2522 /* local sweep */ 2523 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2524 } 2525 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 2526 if (flag & SOR_ZERO_INITIAL_GUESS) { 2527 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 2528 its--; 2529 } 2530 while (its--) { 2531 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2532 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2533 2534 /* update rhs: bb1 = bb - B*x */ 2535 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 2536 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 2537 2538 /* local sweep */ 2539 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 2540 } 2541 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported"); 2542 2543 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 2544 PetscFunctionReturn(0); 2545 } 2546 2547 #undef __FUNCT__ 2548 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ" 2549 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms) 2550 { 2551 PetscErrorCode ierr; 2552 Mat_MPIBAIJ *aij = (Mat_MPIBAIJ*)A->data; 2553 PetscInt N,i,*garray = aij->garray; 2554 PetscInt ib,jb,bs = A->rmap->bs; 2555 Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ*) aij->A->data; 2556 MatScalar *a_val = a_aij->a; 2557 Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ*) aij->B->data; 2558 MatScalar *b_val = b_aij->a; 2559 PetscReal *work; 2560 2561 PetscFunctionBegin; 2562 ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr); 2563 ierr = PetscCalloc1(N,&work);CHKERRQ(ierr); 2564 if (type == NORM_2) { 2565 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2566 for (jb=0; jb<bs; jb++) { 2567 for (ib=0; ib<bs; ib++) { 2568 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val); 2569 a_val++; 2570 } 2571 } 2572 } 2573 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2574 for (jb=0; jb<bs; jb++) { 2575 for (ib=0; ib<bs; ib++) { 2576 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val); 2577 b_val++; 2578 } 2579 } 2580 } 2581 } else if (type == NORM_1) { 2582 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2583 for (jb=0; jb<bs; jb++) { 2584 for (ib=0; ib<bs; ib++) { 2585 work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val); 2586 a_val++; 2587 } 2588 } 2589 } 2590 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2591 for (jb=0; jb<bs; jb++) { 2592 for (ib=0; ib<bs; ib++) { 2593 work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val); 2594 b_val++; 2595 } 2596 } 2597 } 2598 } else if (type == NORM_INFINITY) { 2599 for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) { 2600 for (jb=0; jb<bs; jb++) { 2601 for (ib=0; ib<bs; ib++) { 2602 int col = A->cmap->rstart + a_aij->j[i] * bs + jb; 2603 work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]); 2604 a_val++; 2605 } 2606 } 2607 } 2608 for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) { 2609 for (jb=0; jb<bs; jb++) { 2610 for (ib=0; ib<bs; ib++) { 2611 int col = garray[b_aij->j[i]] * bs + jb; 2612 work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]); 2613 b_val++; 2614 } 2615 } 2616 } 2617 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2618 if (type == NORM_INFINITY) { 2619 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2620 } else { 2621 ierr = MPIU_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2622 } 2623 ierr = PetscFree(work);CHKERRQ(ierr); 2624 if (type == NORM_2) { 2625 for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]); 2626 } 2627 PetscFunctionReturn(0); 2628 } 2629 2630 #undef __FUNCT__ 2631 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ" 2632 PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values) 2633 { 2634 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 2635 PetscErrorCode ierr; 2636 2637 PetscFunctionBegin; 2638 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2639 A->factorerrortype = a->A->factorerrortype; 2640 A->factorerror_zeropivot_value = a->A->factorerror_zeropivot_value; 2641 A->factorerror_zeropivot_row = a->A->factorerror_zeropivot_row; 2642 PetscFunctionReturn(0); 2643 } 2644 2645 #undef __FUNCT__ 2646 #define __FUNCT__ "MatShift_MPIBAIJ" 2647 PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a) 2648 { 2649 PetscErrorCode ierr; 2650 Mat_MPIBAIJ *maij = (Mat_MPIBAIJ*)Y->data; 2651 Mat_SeqBAIJ *aij = (Mat_SeqBAIJ*)maij->A->data; 2652 2653 PetscFunctionBegin; 2654 if (!Y->preallocated) { 2655 ierr = MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);CHKERRQ(ierr); 2656 } else if (!aij->nz) { 2657 PetscInt nonew = aij->nonew; 2658 ierr = MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);CHKERRQ(ierr); 2659 aij->nonew = nonew; 2660 } 2661 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 2662 PetscFunctionReturn(0); 2663 } 2664 2665 #undef __FUNCT__ 2666 #define __FUNCT__ "MatMissingDiagonal_MPIBAIJ" 2667 PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A,PetscBool *missing,PetscInt *d) 2668 { 2669 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 2670 PetscErrorCode ierr; 2671 2672 PetscFunctionBegin; 2673 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices"); 2674 ierr = MatMissingDiagonal(a->A,missing,d);CHKERRQ(ierr); 2675 if (d) { 2676 PetscInt rstart; 2677 ierr = MatGetOwnershipRange(A,&rstart,NULL);CHKERRQ(ierr); 2678 *d += rstart/A->rmap->bs; 2679 2680 } 2681 PetscFunctionReturn(0); 2682 } 2683 2684 #undef __FUNCT__ 2685 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ" 2686 PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a) 2687 { 2688 PetscFunctionBegin; 2689 *a = ((Mat_MPIBAIJ*)A->data)->A; 2690 PetscFunctionReturn(0); 2691 } 2692 2693 /* -------------------------------------------------------------------*/ 2694 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ, 2695 MatGetRow_MPIBAIJ, 2696 MatRestoreRow_MPIBAIJ, 2697 MatMult_MPIBAIJ, 2698 /* 4*/ MatMultAdd_MPIBAIJ, 2699 MatMultTranspose_MPIBAIJ, 2700 MatMultTransposeAdd_MPIBAIJ, 2701 0, 2702 0, 2703 0, 2704 /*10*/ 0, 2705 0, 2706 0, 2707 MatSOR_MPIBAIJ, 2708 MatTranspose_MPIBAIJ, 2709 /*15*/ MatGetInfo_MPIBAIJ, 2710 MatEqual_MPIBAIJ, 2711 MatGetDiagonal_MPIBAIJ, 2712 MatDiagonalScale_MPIBAIJ, 2713 MatNorm_MPIBAIJ, 2714 /*20*/ MatAssemblyBegin_MPIBAIJ, 2715 MatAssemblyEnd_MPIBAIJ, 2716 MatSetOption_MPIBAIJ, 2717 MatZeroEntries_MPIBAIJ, 2718 /*24*/ MatZeroRows_MPIBAIJ, 2719 0, 2720 0, 2721 0, 2722 0, 2723 /*29*/ MatSetUp_MPIBAIJ, 2724 0, 2725 0, 2726 MatGetDiagonalBlock_MPIBAIJ, 2727 0, 2728 /*34*/ MatDuplicate_MPIBAIJ, 2729 0, 2730 0, 2731 0, 2732 0, 2733 /*39*/ MatAXPY_MPIBAIJ, 2734 MatGetSubMatrices_MPIBAIJ, 2735 MatIncreaseOverlap_MPIBAIJ, 2736 MatGetValues_MPIBAIJ, 2737 MatCopy_MPIBAIJ, 2738 /*44*/ 0, 2739 MatScale_MPIBAIJ, 2740 MatShift_MPIBAIJ, 2741 0, 2742 MatZeroRowsColumns_MPIBAIJ, 2743 /*49*/ 0, 2744 0, 2745 0, 2746 0, 2747 0, 2748 /*54*/ MatFDColoringCreate_MPIXAIJ, 2749 0, 2750 MatSetUnfactored_MPIBAIJ, 2751 MatPermute_MPIBAIJ, 2752 MatSetValuesBlocked_MPIBAIJ, 2753 /*59*/ MatGetSubMatrix_MPIBAIJ, 2754 MatDestroy_MPIBAIJ, 2755 MatView_MPIBAIJ, 2756 0, 2757 0, 2758 /*64*/ 0, 2759 0, 2760 0, 2761 0, 2762 0, 2763 /*69*/ MatGetRowMaxAbs_MPIBAIJ, 2764 0, 2765 0, 2766 0, 2767 0, 2768 /*74*/ 0, 2769 MatFDColoringApply_BAIJ, 2770 0, 2771 0, 2772 0, 2773 /*79*/ 0, 2774 0, 2775 0, 2776 0, 2777 MatLoad_MPIBAIJ, 2778 /*84*/ 0, 2779 0, 2780 0, 2781 0, 2782 0, 2783 /*89*/ 0, 2784 0, 2785 0, 2786 0, 2787 0, 2788 /*94*/ 0, 2789 0, 2790 0, 2791 0, 2792 0, 2793 /*99*/ 0, 2794 0, 2795 0, 2796 0, 2797 0, 2798 /*104*/0, 2799 MatRealPart_MPIBAIJ, 2800 MatImaginaryPart_MPIBAIJ, 2801 0, 2802 0, 2803 /*109*/0, 2804 0, 2805 0, 2806 0, 2807 MatMissingDiagonal_MPIBAIJ, 2808 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ, 2809 0, 2810 MatGetGhosts_MPIBAIJ, 2811 0, 2812 0, 2813 /*119*/0, 2814 0, 2815 0, 2816 0, 2817 MatGetMultiProcBlock_MPIBAIJ, 2818 /*124*/0, 2819 MatGetColumnNorms_MPIBAIJ, 2820 MatInvertBlockDiagonal_MPIBAIJ, 2821 0, 2822 0, 2823 /*129*/ 0, 2824 0, 2825 0, 2826 0, 2827 0, 2828 /*134*/ 0, 2829 0, 2830 0, 2831 0, 2832 0, 2833 /*139*/ 0, 2834 0, 2835 0, 2836 MatFDColoringSetUp_MPIXAIJ, 2837 0, 2838 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ 2839 }; 2840 2841 2842 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*); 2843 2844 #undef __FUNCT__ 2845 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ" 2846 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[]) 2847 { 2848 PetscInt m,rstart,cstart,cend; 2849 PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0; 2850 const PetscInt *JJ =0; 2851 PetscScalar *values=0; 2852 PetscBool roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented; 2853 PetscErrorCode ierr; 2854 2855 PetscFunctionBegin; 2856 ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr); 2857 ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr); 2858 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2859 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2860 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2861 m = B->rmap->n/bs; 2862 rstart = B->rmap->rstart/bs; 2863 cstart = B->cmap->rstart/bs; 2864 cend = B->cmap->rend/bs; 2865 2866 if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]); 2867 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 2868 for (i=0; i<m; i++) { 2869 nz = ii[i+1] - ii[i]; 2870 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz); 2871 nz_max = PetscMax(nz_max,nz); 2872 JJ = jj + ii[i]; 2873 for (j=0; j<nz; j++) { 2874 if (*JJ >= cstart) break; 2875 JJ++; 2876 } 2877 d = 0; 2878 for (; j<nz; j++) { 2879 if (*JJ++ >= cend) break; 2880 d++; 2881 } 2882 d_nnz[i] = d; 2883 o_nnz[i] = nz - d; 2884 } 2885 ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2886 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 2887 2888 values = (PetscScalar*)V; 2889 if (!values) { 2890 ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr); 2891 ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2892 } 2893 for (i=0; i<m; i++) { 2894 PetscInt row = i + rstart; 2895 PetscInt ncols = ii[i+1] - ii[i]; 2896 const PetscInt *icols = jj + ii[i]; 2897 if (!roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */ 2898 const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0); 2899 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr); 2900 } else { /* block ordering does not match so we can only insert one block at a time. */ 2901 PetscInt j; 2902 for (j=0; j<ncols; j++) { 2903 const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0); 2904 ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr); 2905 } 2906 } 2907 } 2908 2909 if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); } 2910 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2911 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2912 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2913 PetscFunctionReturn(0); 2914 } 2915 2916 #undef __FUNCT__ 2917 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR" 2918 /*@C 2919 MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format 2920 (the default parallel PETSc format). 2921 2922 Collective on MPI_Comm 2923 2924 Input Parameters: 2925 + B - the matrix 2926 . bs - the block size 2927 . i - the indices into j for the start of each local row (starts with zero) 2928 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2929 - v - optional values in the matrix 2930 2931 Level: developer 2932 2933 Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED. For example, C programs 2934 may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is 2935 over rows within a block and the last index is over columns within a block row. Fortran programs will likely set 2936 MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a 2937 block column and the second index is over columns within a block. 2938 2939 .keywords: matrix, aij, compressed row, sparse, parallel 2940 2941 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ 2942 @*/ 2943 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2944 { 2945 PetscErrorCode ierr; 2946 2947 PetscFunctionBegin; 2948 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 2949 PetscValidType(B,1); 2950 PetscValidLogicalCollectiveInt(B,bs,2); 2951 ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr); 2952 PetscFunctionReturn(0); 2953 } 2954 2955 #undef __FUNCT__ 2956 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ" 2957 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz) 2958 { 2959 Mat_MPIBAIJ *b; 2960 PetscErrorCode ierr; 2961 PetscInt i; 2962 2963 PetscFunctionBegin; 2964 ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr); 2965 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2966 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2967 ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr); 2968 2969 if (d_nnz) { 2970 for (i=0; i<B->rmap->n/bs; i++) { 2971 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]); 2972 } 2973 } 2974 if (o_nnz) { 2975 for (i=0; i<B->rmap->n/bs; i++) { 2976 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]); 2977 } 2978 } 2979 2980 b = (Mat_MPIBAIJ*)B->data; 2981 b->bs2 = bs*bs; 2982 b->mbs = B->rmap->n/bs; 2983 b->nbs = B->cmap->n/bs; 2984 b->Mbs = B->rmap->N/bs; 2985 b->Nbs = B->cmap->N/bs; 2986 2987 for (i=0; i<=b->size; i++) { 2988 b->rangebs[i] = B->rmap->range[i]/bs; 2989 } 2990 b->rstartbs = B->rmap->rstart/bs; 2991 b->rendbs = B->rmap->rend/bs; 2992 b->cstartbs = B->cmap->rstart/bs; 2993 b->cendbs = B->cmap->rend/bs; 2994 2995 #if defined(PETSC_USE_CTABLE) 2996 ierr = PetscTableDestroy(&b->colmap);CHKERRQ(ierr); 2997 #else 2998 ierr = PetscFree(b->colmap);CHKERRQ(ierr); 2999 #endif 3000 ierr = PetscFree(b->garray);CHKERRQ(ierr); 3001 ierr = VecDestroy(&b->lvec);CHKERRQ(ierr); 3002 ierr = VecScatterDestroy(&b->Mvctx);CHKERRQ(ierr); 3003 3004 /* Because the B will have been resized we simply destroy it and create a new one each time */ 3005 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3006 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3007 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3008 ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr); 3009 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3010 3011 if (!B->preallocated) { 3012 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3013 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3014 ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr); 3015 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3016 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr); 3017 } 3018 3019 ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3020 ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr); 3021 B->preallocated = PETSC_TRUE; 3022 B->was_assembled = PETSC_FALSE; 3023 B->assembled = PETSC_FALSE; 3024 PetscFunctionReturn(0); 3025 } 3026 3027 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec); 3028 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal); 3029 3030 #undef __FUNCT__ 3031 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj" 3032 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj) 3033 { 3034 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)B->data; 3035 PetscErrorCode ierr; 3036 Mat_SeqBAIJ *d = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data; 3037 PetscInt M = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs; 3038 const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray; 3039 3040 PetscFunctionBegin; 3041 ierr = PetscMalloc1(M+1,&ii);CHKERRQ(ierr); 3042 ii[0] = 0; 3043 for (i=0; i<M; i++) { 3044 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]); 3045 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]); 3046 ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i]; 3047 /* remove one from count of matrix has diagonal */ 3048 for (j=id[i]; j<id[i+1]; j++) { 3049 if (jd[j] == i) {ii[i+1]--;break;} 3050 } 3051 } 3052 ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr); 3053 cnt = 0; 3054 for (i=0; i<M; i++) { 3055 for (j=io[i]; j<io[i+1]; j++) { 3056 if (garray[jo[j]] > rstart) break; 3057 jj[cnt++] = garray[jo[j]]; 3058 } 3059 for (k=id[i]; k<id[i+1]; k++) { 3060 if (jd[k] != i) { 3061 jj[cnt++] = rstart + jd[k]; 3062 } 3063 } 3064 for (; j<io[i+1]; j++) { 3065 jj[cnt++] = garray[jo[j]]; 3066 } 3067 } 3068 ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr); 3069 PetscFunctionReturn(0); 3070 } 3071 3072 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3073 3074 PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*); 3075 3076 #undef __FUNCT__ 3077 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ" 3078 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 3079 { 3080 PetscErrorCode ierr; 3081 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3082 Mat B; 3083 Mat_MPIAIJ *b; 3084 3085 PetscFunctionBegin; 3086 if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled"); 3087 3088 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 3089 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 3090 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 3091 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 3092 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3093 ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); 3094 b = (Mat_MPIAIJ*) B->data; 3095 3096 ierr = MatDestroy(&b->A);CHKERRQ(ierr); 3097 ierr = MatDestroy(&b->B);CHKERRQ(ierr); 3098 ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr); 3099 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr); 3100 ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr); 3101 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3102 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3103 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3104 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3105 if (reuse == MAT_INPLACE_MATRIX) { 3106 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 3107 } else { 3108 *newmat = B; 3109 } 3110 PetscFunctionReturn(0); 3111 } 3112 3113 /*MC 3114 MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices. 3115 3116 Options Database Keys: 3117 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions() 3118 . -mat_block_size <bs> - set the blocksize used to store the matrix 3119 - -mat_use_hash_table <fact> 3120 3121 Level: beginner 3122 3123 .seealso: MatCreateMPIBAIJ 3124 M*/ 3125 3126 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*); 3127 3128 #undef __FUNCT__ 3129 #define __FUNCT__ "MatCreate_MPIBAIJ" 3130 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B) 3131 { 3132 Mat_MPIBAIJ *b; 3133 PetscErrorCode ierr; 3134 PetscBool flg = PETSC_FALSE; 3135 3136 PetscFunctionBegin; 3137 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3138 B->data = (void*)b; 3139 3140 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3141 B->assembled = PETSC_FALSE; 3142 3143 B->insertmode = NOT_SET_VALUES; 3144 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 3145 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr); 3146 3147 /* build local table of row and column ownerships */ 3148 ierr = PetscMalloc1(b->size+1,&b->rangebs);CHKERRQ(ierr); 3149 3150 /* build cache for off array entries formed */ 3151 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 3152 3153 b->donotstash = PETSC_FALSE; 3154 b->colmap = NULL; 3155 b->garray = NULL; 3156 b->roworiented = PETSC_TRUE; 3157 3158 /* stuff used in block assembly */ 3159 b->barray = 0; 3160 3161 /* stuff used for matrix vector multiply */ 3162 b->lvec = 0; 3163 b->Mvctx = 0; 3164 3165 /* stuff for MatGetRow() */ 3166 b->rowindices = 0; 3167 b->rowvalues = 0; 3168 b->getrowactive = PETSC_FALSE; 3169 3170 /* hash table stuff */ 3171 b->ht = 0; 3172 b->hd = 0; 3173 b->ht_size = 0; 3174 b->ht_flag = PETSC_FALSE; 3175 b->ht_fact = 0; 3176 b->ht_total_ct = 0; 3177 b->ht_insert_ct = 0; 3178 3179 /* stuff for MatGetSubMatrices_MPIBAIJ_local() */ 3180 b->ijonly = PETSC_FALSE; 3181 3182 3183 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr); 3184 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr); 3185 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr); 3186 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr); 3187 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr); 3188 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr); 3189 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr); 3190 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr); 3191 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr); 3192 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr); 3193 3194 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr); 3195 ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);CHKERRQ(ierr); 3196 if (flg) { 3197 PetscReal fact = 1.39; 3198 ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr); 3199 ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr); 3200 if (fact <= 1.0) fact = 1.39; 3201 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 3202 ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr); 3203 } 3204 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3205 PetscFunctionReturn(0); 3206 } 3207 3208 /*MC 3209 MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices. 3210 3211 This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator, 3212 and MATMPIBAIJ otherwise. 3213 3214 Options Database Keys: 3215 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions() 3216 3217 Level: beginner 3218 3219 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3220 M*/ 3221 3222 #undef __FUNCT__ 3223 #define __FUNCT__ "MatMPIBAIJSetPreallocation" 3224 /*@C 3225 MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format 3226 (block compressed row). For good matrix assembly performance 3227 the user should preallocate the matrix storage by setting the parameters 3228 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3229 performance can be increased by more than a factor of 50. 3230 3231 Collective on Mat 3232 3233 Input Parameters: 3234 + B - the matrix 3235 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3236 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3237 . d_nz - number of block nonzeros per block row in diagonal portion of local 3238 submatrix (same for all local rows) 3239 . d_nnz - array containing the number of block nonzeros in the various block rows 3240 of the in diagonal portion of the local (possibly different for each block 3241 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry and 3242 set it even if it is zero. 3243 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 3244 submatrix (same for all local rows). 3245 - o_nnz - array containing the number of nonzeros in the various block rows of the 3246 off-diagonal portion of the local submatrix (possibly different for 3247 each block row) or NULL. 3248 3249 If the *_nnz parameter is given then the *_nz parameter is ignored 3250 3251 Options Database Keys: 3252 + -mat_block_size - size of the blocks to use 3253 - -mat_use_hash_table <fact> 3254 3255 Notes: 3256 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3257 than it must be used on all processors that share the object for that argument. 3258 3259 Storage Information: 3260 For a square global matrix we define each processor's diagonal portion 3261 to be its local rows and the corresponding columns (a square submatrix); 3262 each processor's off-diagonal portion encompasses the remainder of the 3263 local matrix (a rectangular submatrix). 3264 3265 The user can specify preallocated storage for the diagonal part of 3266 the local submatrix with either d_nz or d_nnz (not both). Set 3267 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3268 memory allocation. Likewise, specify preallocated storage for the 3269 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3270 3271 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3272 the figure below we depict these three local rows and all columns (0-11). 3273 3274 .vb 3275 0 1 2 3 4 5 6 7 8 9 10 11 3276 -------------------------- 3277 row 3 |o o o d d d o o o o o o 3278 row 4 |o o o d d d o o o o o o 3279 row 5 |o o o d d d o o o o o o 3280 -------------------------- 3281 .ve 3282 3283 Thus, any entries in the d locations are stored in the d (diagonal) 3284 submatrix, and any entries in the o locations are stored in the 3285 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3286 stored simply in the MATSEQBAIJ format for compressed row storage. 3287 3288 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3289 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3290 In general, for PDE problems in which most nonzeros are near the diagonal, 3291 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3292 or you will get TERRIBLE performance; see the users' manual chapter on 3293 matrices. 3294 3295 You can call MatGetInfo() to get information on how effective the preallocation was; 3296 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3297 You can also run with the option -info and look for messages with the string 3298 malloc in them to see if additional memory allocation was needed. 3299 3300 Level: intermediate 3301 3302 .keywords: matrix, block, aij, compressed row, sparse, parallel 3303 3304 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership() 3305 @*/ 3306 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3307 { 3308 PetscErrorCode ierr; 3309 3310 PetscFunctionBegin; 3311 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3312 PetscValidType(B,1); 3313 PetscValidLogicalCollectiveInt(B,bs,2); 3314 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); 3315 PetscFunctionReturn(0); 3316 } 3317 3318 #undef __FUNCT__ 3319 #define __FUNCT__ "MatCreateBAIJ" 3320 /*@C 3321 MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format 3322 (block compressed row). For good matrix assembly performance 3323 the user should preallocate the matrix storage by setting the parameters 3324 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3325 performance can be increased by more than a factor of 50. 3326 3327 Collective on MPI_Comm 3328 3329 Input Parameters: 3330 + comm - MPI communicator 3331 . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row 3332 blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs() 3333 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3334 This value should be the same as the local size used in creating the 3335 y vector for the matrix-vector product y = Ax. 3336 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 3337 This value should be the same as the local size used in creating the 3338 x vector for the matrix-vector product y = Ax. 3339 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3340 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3341 . d_nz - number of nonzero blocks per block row in diagonal portion of local 3342 submatrix (same for all local rows) 3343 . d_nnz - array containing the number of nonzero blocks in the various block rows 3344 of the in diagonal portion of the local (possibly different for each block 3345 row) or NULL. If you plan to factor the matrix you must leave room for the diagonal entry 3346 and set it even if it is zero. 3347 . o_nz - number of nonzero blocks per block row in the off-diagonal portion of local 3348 submatrix (same for all local rows). 3349 - o_nnz - array containing the number of nonzero blocks in the various block rows of the 3350 off-diagonal portion of the local submatrix (possibly different for 3351 each block row) or NULL. 3352 3353 Output Parameter: 3354 . A - the matrix 3355 3356 Options Database Keys: 3357 + -mat_block_size - size of the blocks to use 3358 - -mat_use_hash_table <fact> 3359 3360 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3361 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3362 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3363 3364 Notes: 3365 If the *_nnz parameter is given then the *_nz parameter is ignored 3366 3367 A nonzero block is any block that as 1 or more nonzeros in it 3368 3369 The user MUST specify either the local or global matrix dimensions 3370 (possibly both). 3371 3372 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 3373 than it must be used on all processors that share the object for that argument. 3374 3375 Storage Information: 3376 For a square global matrix we define each processor's diagonal portion 3377 to be its local rows and the corresponding columns (a square submatrix); 3378 each processor's off-diagonal portion encompasses the remainder of the 3379 local matrix (a rectangular submatrix). 3380 3381 The user can specify preallocated storage for the diagonal part of 3382 the local submatrix with either d_nz or d_nnz (not both). Set 3383 d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic 3384 memory allocation. Likewise, specify preallocated storage for the 3385 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 3386 3387 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 3388 the figure below we depict these three local rows and all columns (0-11). 3389 3390 .vb 3391 0 1 2 3 4 5 6 7 8 9 10 11 3392 -------------------------- 3393 row 3 |o o o d d d o o o o o o 3394 row 4 |o o o d d d o o o o o o 3395 row 5 |o o o d d d o o o o o o 3396 -------------------------- 3397 .ve 3398 3399 Thus, any entries in the d locations are stored in the d (diagonal) 3400 submatrix, and any entries in the o locations are stored in the 3401 o (off-diagonal) submatrix. Note that the d and the o submatrices are 3402 stored simply in the MATSEQBAIJ format for compressed row storage. 3403 3404 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 3405 and o_nz should indicate the number of block nonzeros per row in the o matrix. 3406 In general, for PDE problems in which most nonzeros are near the diagonal, 3407 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 3408 or you will get TERRIBLE performance; see the users' manual chapter on 3409 matrices. 3410 3411 Level: intermediate 3412 3413 .keywords: matrix, block, aij, compressed row, sparse, parallel 3414 3415 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR() 3416 @*/ 3417 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) 3418 { 3419 PetscErrorCode ierr; 3420 PetscMPIInt size; 3421 3422 PetscFunctionBegin; 3423 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3424 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3425 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3426 if (size > 1) { 3427 ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr); 3428 ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3429 } else { 3430 ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr); 3431 ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 3432 } 3433 PetscFunctionReturn(0); 3434 } 3435 3436 #undef __FUNCT__ 3437 #define __FUNCT__ "MatDuplicate_MPIBAIJ" 3438 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3439 { 3440 Mat mat; 3441 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ*)matin->data; 3442 PetscErrorCode ierr; 3443 PetscInt len=0; 3444 3445 PetscFunctionBegin; 3446 *newmat = 0; 3447 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3448 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3449 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3450 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3451 3452 mat->factortype = matin->factortype; 3453 mat->preallocated = PETSC_TRUE; 3454 mat->assembled = PETSC_TRUE; 3455 mat->insertmode = NOT_SET_VALUES; 3456 3457 a = (Mat_MPIBAIJ*)mat->data; 3458 mat->rmap->bs = matin->rmap->bs; 3459 a->bs2 = oldmat->bs2; 3460 a->mbs = oldmat->mbs; 3461 a->nbs = oldmat->nbs; 3462 a->Mbs = oldmat->Mbs; 3463 a->Nbs = oldmat->Nbs; 3464 3465 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3466 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3467 3468 a->size = oldmat->size; 3469 a->rank = oldmat->rank; 3470 a->donotstash = oldmat->donotstash; 3471 a->roworiented = oldmat->roworiented; 3472 a->rowindices = 0; 3473 a->rowvalues = 0; 3474 a->getrowactive = PETSC_FALSE; 3475 a->barray = 0; 3476 a->rstartbs = oldmat->rstartbs; 3477 a->rendbs = oldmat->rendbs; 3478 a->cstartbs = oldmat->cstartbs; 3479 a->cendbs = oldmat->cendbs; 3480 3481 /* hash table stuff */ 3482 a->ht = 0; 3483 a->hd = 0; 3484 a->ht_size = 0; 3485 a->ht_flag = oldmat->ht_flag; 3486 a->ht_fact = oldmat->ht_fact; 3487 a->ht_total_ct = 0; 3488 a->ht_insert_ct = 0; 3489 3490 ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr); 3491 if (oldmat->colmap) { 3492 #if defined(PETSC_USE_CTABLE) 3493 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3494 #else 3495 ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr); 3496 ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3497 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr); 3498 #endif 3499 } else a->colmap = 0; 3500 3501 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 3502 ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr); 3503 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3504 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); 3505 } else a->garray = 0; 3506 3507 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr); 3508 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3509 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3510 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3511 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3512 3513 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3514 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3515 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3516 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3517 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3518 *newmat = mat; 3519 PetscFunctionReturn(0); 3520 } 3521 3522 #undef __FUNCT__ 3523 #define __FUNCT__ "MatLoad_MPIBAIJ" 3524 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer) 3525 { 3526 PetscErrorCode ierr; 3527 int fd; 3528 PetscInt i,nz,j,rstart,rend; 3529 PetscScalar *vals,*buf; 3530 MPI_Comm comm; 3531 MPI_Status status; 3532 PetscMPIInt rank,size,maxnz; 3533 PetscInt header[4],*rowlengths = 0,M,N,m,*rowners,*cols; 3534 PetscInt *locrowlens = NULL,*procsnz = NULL,*browners = NULL; 3535 PetscInt jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax; 3536 PetscMPIInt tag = ((PetscObject)viewer)->tag; 3537 PetscInt *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount; 3538 PetscInt dcount,kmax,k,nzcount,tmp,mend; 3539 3540 PetscFunctionBegin; 3541 /* force binary viewer to load .info file if it has not yet done so */ 3542 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 3543 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3544 ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr); 3545 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3546 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3547 if (bs < 0) bs = 1; 3548 3549 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3550 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3551 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3552 if (!rank) { 3553 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3554 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3555 if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk, cannot load as MPIAIJ"); 3556 } 3557 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3558 M = header[1]; N = header[2]; 3559 3560 /* If global sizes are set, check if they are consistent with that given in the file */ 3561 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); 3562 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); 3563 3564 if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices"); 3565 3566 /* 3567 This code adds extra rows to make sure the number of rows is 3568 divisible by the blocksize 3569 */ 3570 Mbs = M/bs; 3571 extra_rows = bs - M + bs*Mbs; 3572 if (extra_rows == bs) extra_rows = 0; 3573 else Mbs++; 3574 if (extra_rows && !rank) { 3575 ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr); 3576 } 3577 3578 /* determine ownership of all rows */ 3579 if (newmat->rmap->n < 0) { /* PETSC_DECIDE */ 3580 mbs = Mbs/size + ((Mbs % size) > rank); 3581 m = mbs*bs; 3582 } else { /* User set */ 3583 m = newmat->rmap->n; 3584 mbs = m/bs; 3585 } 3586 ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr); 3587 ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3588 3589 /* process 0 needs enough room for process with most rows */ 3590 if (!rank) { 3591 mmax = rowners[1]; 3592 for (i=2; i<=size; i++) { 3593 mmax = PetscMax(mmax,rowners[i]); 3594 } 3595 mmax*=bs; 3596 } else mmax = -1; /* unused, but compiler warns anyway */ 3597 3598 rowners[0] = 0; 3599 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 3600 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 3601 rstart = rowners[rank]; 3602 rend = rowners[rank+1]; 3603 3604 /* distribute row lengths to all processors */ 3605 ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr); 3606 if (!rank) { 3607 mend = m; 3608 if (size == 1) mend = mend - extra_rows; 3609 ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr); 3610 for (j=mend; j<m; j++) locrowlens[j] = 1; 3611 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3612 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3613 for (j=0; j<m; j++) { 3614 procsnz[0] += locrowlens[j]; 3615 } 3616 for (i=1; i<size; i++) { 3617 mend = browners[i+1] - browners[i]; 3618 if (i == size-1) mend = mend - extra_rows; 3619 ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr); 3620 for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1; 3621 /* calculate the number of nonzeros on each processor */ 3622 for (j=0; j<browners[i+1]-browners[i]; j++) { 3623 procsnz[i] += rowlengths[j]; 3624 } 3625 ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3626 } 3627 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3628 } else { 3629 ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3630 } 3631 3632 if (!rank) { 3633 /* determine max buffer needed and allocate it */ 3634 maxnz = procsnz[0]; 3635 for (i=1; i<size; i++) { 3636 maxnz = PetscMax(maxnz,procsnz[i]); 3637 } 3638 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3639 3640 /* read in my part of the matrix column indices */ 3641 nz = procsnz[0]; 3642 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3643 mycols = ibuf; 3644 if (size == 1) nz -= extra_rows; 3645 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3646 if (size == 1) { 3647 for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i; 3648 } 3649 3650 /* read in every ones (except the last) and ship off */ 3651 for (i=1; i<size-1; i++) { 3652 nz = procsnz[i]; 3653 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3654 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3655 } 3656 /* read in the stuff for the last proc */ 3657 if (size != 1) { 3658 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 3659 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3660 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 3661 ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr); 3662 } 3663 ierr = PetscFree(cols);CHKERRQ(ierr); 3664 } else { 3665 /* determine buffer space needed for message */ 3666 nz = 0; 3667 for (i=0; i<m; i++) { 3668 nz += locrowlens[i]; 3669 } 3670 ierr = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr); 3671 mycols = ibuf; 3672 /* receive message of column indices*/ 3673 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 3674 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 3675 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 3676 } 3677 3678 /* loop over local rows, determining number of off diagonal entries */ 3679 ierr = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr); 3680 ierr = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr); 3681 rowcount = 0; nzcount = 0; 3682 for (i=0; i<mbs; i++) { 3683 dcount = 0; 3684 odcount = 0; 3685 for (j=0; j<bs; j++) { 3686 kmax = locrowlens[rowcount]; 3687 for (k=0; k<kmax; k++) { 3688 tmp = mycols[nzcount++]/bs; 3689 if (!mask[tmp]) { 3690 mask[tmp] = 1; 3691 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; 3692 else masked1[dcount++] = tmp; 3693 } 3694 } 3695 rowcount++; 3696 } 3697 3698 dlens[i] = dcount; 3699 odlens[i] = odcount; 3700 3701 /* zero out the mask elements we set */ 3702 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 3703 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 3704 } 3705 3706 ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr); 3707 ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr); 3708 3709 if (!rank) { 3710 ierr = PetscMalloc1(maxnz+1,&buf);CHKERRQ(ierr); 3711 /* read in my part of the matrix numerical values */ 3712 nz = procsnz[0]; 3713 vals = buf; 3714 mycols = ibuf; 3715 if (size == 1) nz -= extra_rows; 3716 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3717 if (size == 1) { 3718 for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0; 3719 } 3720 3721 /* insert into matrix */ 3722 jj = rstart*bs; 3723 for (i=0; i<m; i++) { 3724 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3725 mycols += locrowlens[i]; 3726 vals += locrowlens[i]; 3727 jj++; 3728 } 3729 /* read in other processors (except the last one) and ship out */ 3730 for (i=1; i<size-1; i++) { 3731 nz = procsnz[i]; 3732 vals = buf; 3733 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3734 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3735 } 3736 /* the last proc */ 3737 if (size != 1) { 3738 nz = procsnz[i] - extra_rows; 3739 vals = buf; 3740 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3741 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 3742 ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3743 } 3744 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3745 } else { 3746 /* receive numeric values */ 3747 ierr = PetscMalloc1(nz+1,&buf);CHKERRQ(ierr); 3748 3749 /* receive message of values*/ 3750 vals = buf; 3751 mycols = ibuf; 3752 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 3753 3754 /* insert into matrix */ 3755 jj = rstart*bs; 3756 for (i=0; i<m; i++) { 3757 ierr = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 3758 mycols += locrowlens[i]; 3759 vals += locrowlens[i]; 3760 jj++; 3761 } 3762 } 3763 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 3764 ierr = PetscFree(buf);CHKERRQ(ierr); 3765 ierr = PetscFree(ibuf);CHKERRQ(ierr); 3766 ierr = PetscFree2(rowners,browners);CHKERRQ(ierr); 3767 ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr); 3768 ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr); 3769 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3770 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3771 PetscFunctionReturn(0); 3772 } 3773 3774 #undef __FUNCT__ 3775 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor" 3776 /*@ 3777 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 3778 3779 Input Parameters: 3780 . mat - the matrix 3781 . fact - factor 3782 3783 Not Collective, each process can use a different factor 3784 3785 Level: advanced 3786 3787 Notes: 3788 This can also be set by the command line option: -mat_use_hash_table <fact> 3789 3790 .keywords: matrix, hashtable, factor, HT 3791 3792 .seealso: MatSetOption() 3793 @*/ 3794 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact) 3795 { 3796 PetscErrorCode ierr; 3797 3798 PetscFunctionBegin; 3799 ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr); 3800 PetscFunctionReturn(0); 3801 } 3802 3803 #undef __FUNCT__ 3804 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ" 3805 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact) 3806 { 3807 Mat_MPIBAIJ *baij; 3808 3809 PetscFunctionBegin; 3810 baij = (Mat_MPIBAIJ*)mat->data; 3811 baij->ht_fact = fact; 3812 PetscFunctionReturn(0); 3813 } 3814 3815 #undef __FUNCT__ 3816 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ" 3817 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3818 { 3819 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data; 3820 3821 PetscFunctionBegin; 3822 if (Ad) *Ad = a->A; 3823 if (Ao) *Ao = a->B; 3824 if (colmap) *colmap = a->garray; 3825 PetscFunctionReturn(0); 3826 } 3827 3828 /* 3829 Special version for direct calls from Fortran (to eliminate two function call overheads 3830 */ 3831 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3832 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED 3833 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3834 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked 3835 #endif 3836 3837 #undef __FUNCT__ 3838 #define __FUNCT__ "matmpibiajsetvaluesblocked" 3839 /*@C 3840 MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked() 3841 3842 Collective on Mat 3843 3844 Input Parameters: 3845 + mat - the matrix 3846 . min - number of input rows 3847 . im - input rows 3848 . nin - number of input columns 3849 . in - input columns 3850 . v - numerical values input 3851 - addvin - INSERT_VALUES or ADD_VALUES 3852 3853 Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse. 3854 3855 Level: advanced 3856 3857 .seealso: MatSetValuesBlocked() 3858 @*/ 3859 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin) 3860 { 3861 /* convert input arguments to C version */ 3862 Mat mat = *matin; 3863 PetscInt m = *min, n = *nin; 3864 InsertMode addv = *addvin; 3865 3866 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data; 3867 const MatScalar *value; 3868 MatScalar *barray = baij->barray; 3869 PetscBool roworiented = baij->roworiented; 3870 PetscErrorCode ierr; 3871 PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs; 3872 PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval; 3873 PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2; 3874 3875 PetscFunctionBegin; 3876 /* tasks normally handled by MatSetValuesBlocked() */ 3877 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 3878 #if defined(PETSC_USE_DEBUG) 3879 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 3880 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3881 #endif 3882 if (mat->assembled) { 3883 mat->was_assembled = PETSC_TRUE; 3884 mat->assembled = PETSC_FALSE; 3885 } 3886 ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3887 3888 3889 if (!barray) { 3890 ierr = PetscMalloc1(bs2,&barray);CHKERRQ(ierr); 3891 baij->barray = barray; 3892 } 3893 3894 if (roworiented) stepval = (n-1)*bs; 3895 else stepval = (m-1)*bs; 3896 3897 for (i=0; i<m; i++) { 3898 if (im[i] < 0) continue; 3899 #if defined(PETSC_USE_DEBUG) 3900 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); 3901 #endif 3902 if (im[i] >= rstart && im[i] < rend) { 3903 row = im[i] - rstart; 3904 for (j=0; j<n; j++) { 3905 /* If NumCol = 1 then a copy is not required */ 3906 if ((roworiented) && (n == 1)) { 3907 barray = (MatScalar*)v + i*bs2; 3908 } else if ((!roworiented) && (m == 1)) { 3909 barray = (MatScalar*)v + j*bs2; 3910 } else { /* Here a copy is required */ 3911 if (roworiented) { 3912 value = v + i*(stepval+bs)*bs + j*bs; 3913 } else { 3914 value = v + j*(stepval+bs)*bs + i*bs; 3915 } 3916 for (ii=0; ii<bs; ii++,value+=stepval) { 3917 for (jj=0; jj<bs; jj++) { 3918 *barray++ = *value++; 3919 } 3920 } 3921 barray -=bs2; 3922 } 3923 3924 if (in[j] >= cstart && in[j] < cend) { 3925 col = in[j] - cstart; 3926 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3927 } else if (in[j] < 0) continue; 3928 #if defined(PETSC_USE_DEBUG) 3929 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); 3930 #endif 3931 else { 3932 if (mat->was_assembled) { 3933 if (!baij->colmap) { 3934 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 3935 } 3936 3937 #if defined(PETSC_USE_DEBUG) 3938 #if defined(PETSC_USE_CTABLE) 3939 { PetscInt data; 3940 ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr); 3941 if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3942 } 3943 #else 3944 if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap"); 3945 #endif 3946 #endif 3947 #if defined(PETSC_USE_CTABLE) 3948 ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr); 3949 col = (col - 1)/bs; 3950 #else 3951 col = (baij->colmap[in[j]] - 1)/bs; 3952 #endif 3953 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 3954 ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr); 3955 col = in[j]; 3956 } 3957 } else col = in[j]; 3958 ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr); 3959 } 3960 } 3961 } else { 3962 if (!baij->donotstash) { 3963 if (roworiented) { 3964 ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3965 } else { 3966 ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr); 3967 } 3968 } 3969 } 3970 } 3971 3972 /* task normally handled by MatSetValuesBlocked() */ 3973 ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr); 3974 PetscFunctionReturn(0); 3975 } 3976 3977 #undef __FUNCT__ 3978 #define __FUNCT__ "MatCreateMPIBAIJWithArrays" 3979 /*@ 3980 MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard 3981 CSR format the local rows. 3982 3983 Collective on MPI_Comm 3984 3985 Input Parameters: 3986 + comm - MPI communicator 3987 . bs - the block size, only a block size of 1 is supported 3988 . m - number of local rows (Cannot be PETSC_DECIDE) 3989 . n - This value should be the same as the local size used in creating the 3990 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3991 calculated if N is given) For square matrices n is almost always m. 3992 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3993 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3994 . i - row indices 3995 . j - column indices 3996 - a - matrix values 3997 3998 Output Parameter: 3999 . mat - the matrix 4000 4001 Level: intermediate 4002 4003 Notes: 4004 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4005 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4006 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4007 4008 The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is 4009 the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first 4010 block, followed by the second column of the first block etc etc. That is, the blocks are contiguous in memory 4011 with column-major ordering within blocks. 4012 4013 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4014 4015 .keywords: matrix, aij, compressed row, sparse, parallel 4016 4017 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4018 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4019 @*/ 4020 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) 4021 { 4022 PetscErrorCode ierr; 4023 4024 PetscFunctionBegin; 4025 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4026 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4027 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4028 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4029 ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr); 4030 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 4031 ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr); 4032 ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr); 4033 PetscFunctionReturn(0); 4034 } 4035 4036 #undef __FUNCT__ 4037 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIBAIJ" 4038 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4039 { 4040 PetscErrorCode ierr; 4041 PetscInt m,N,i,rstart,nnz,Ii,bs,cbs; 4042 PetscInt *indx; 4043 PetscScalar *values; 4044 4045 PetscFunctionBegin; 4046 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4047 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 4048 Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)inmat->data; 4049 PetscInt *dnz,*onz,sum,mbs,Nbs; 4050 PetscInt *bindx,rmax=a->rmax,j; 4051 4052 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4053 mbs = m/bs; Nbs = N/cbs; 4054 if (n == PETSC_DECIDE) { 4055 ierr = PetscSplitOwnership(comm,&n,&Nbs);CHKERRQ(ierr); 4056 } 4057 /* Check sum(n) = Nbs */ 4058 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4059 if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs); 4060 4061 ierr = MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4062 rstart -= mbs; 4063 4064 ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr); 4065 ierr = MatPreallocateInitialize(comm,mbs,n,dnz,onz);CHKERRQ(ierr); 4066 for (i=0; i<mbs; i++) { 4067 ierr = MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */ 4068 nnz = nnz/bs; 4069 for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs; 4070 ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr); 4071 ierr = MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); 4072 } 4073 ierr = PetscFree(bindx);CHKERRQ(ierr); 4074 4075 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4076 ierr = MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4077 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4078 ierr = MatSetType(*outmat,MATMPIBAIJ);CHKERRQ(ierr); 4079 ierr = MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr); 4080 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4081 } 4082 4083 /* numeric phase */ 4084 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4085 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 4086 4087 for (i=0; i<m; i++) { 4088 ierr = MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4089 Ii = i + rstart; 4090 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4091 ierr = MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4092 } 4093 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4094 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4095 PetscFunctionReturn(0); 4096 } 4097