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