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