1 #define PETSCMAT_DLL 2 3 #include "src/mat/impls/aij/mpi/mpiaij.h" /*I "petscmat.h" I*/ 4 #include "src/inline/spops.h" 5 6 /* 7 Local utility routine that creates a mapping from the global column 8 number to the local number in the off-diagonal part of the local 9 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 10 a slightly higher hash table cost; without it it is not scalable (each processor 11 has an order N integer array but is fast to acess. 12 */ 13 #undef __FUNCT__ 14 #define __FUNCT__ "CreateColmap_MPIAIJ_Private" 15 PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat) 16 { 17 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 18 PetscErrorCode ierr; 19 PetscInt n = aij->B->cmap.n,i; 20 21 PetscFunctionBegin; 22 #if defined (PETSC_USE_CTABLE) 23 ierr = PetscTableCreate(n,&aij->colmap);CHKERRQ(ierr); 24 for (i=0; i<n; i++){ 25 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);CHKERRQ(ierr); 26 } 27 #else 28 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 29 ierr = PetscLogObjectMemory(mat,mat->cmap.N*sizeof(PetscInt));CHKERRQ(ierr); 30 ierr = PetscMemzero(aij->colmap,mat->cmap.N*sizeof(PetscInt));CHKERRQ(ierr); 31 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 32 #endif 33 PetscFunctionReturn(0); 34 } 35 36 37 #define CHUNKSIZE 15 38 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 39 { \ 40 if (col <= lastcol1) low1 = 0; else high1 = nrow1; \ 41 lastcol1 = col;\ 42 while (high1-low1 > 5) { \ 43 t = (low1+high1)/2; \ 44 if (rp1[t] > col) high1 = t; \ 45 else low1 = t; \ 46 } \ 47 for (_i=low1; _i<high1; _i++) { \ 48 if (rp1[_i] > col) break; \ 49 if (rp1[_i] == col) { \ 50 if (addv == ADD_VALUES) ap1[_i] += value; \ 51 else ap1[_i] = value; \ 52 goto a_noinsert; \ 53 } \ 54 } \ 55 if (value == 0.0 && ignorezeroentries) goto a_noinsert; \ 56 if (nonew == 1) goto a_noinsert; \ 57 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 58 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 59 N = nrow1++ - 1; a->nz++; high1++; \ 60 /* shift up all the later entries in this row */ \ 61 for (ii=N; ii>=_i; ii--) { \ 62 rp1[ii+1] = rp1[ii]; \ 63 ap1[ii+1] = ap1[ii]; \ 64 } \ 65 rp1[_i] = col; \ 66 ap1[_i] = value; \ 67 a_noinsert: ; \ 68 ailen[row] = nrow1; \ 69 } 70 71 72 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 73 { \ 74 if (col <= lastcol2) low2 = 0; else high2 = nrow2; \ 75 lastcol2 = col;\ 76 while (high2-low2 > 5) { \ 77 t = (low2+high2)/2; \ 78 if (rp2[t] > col) high2 = t; \ 79 else low2 = t; \ 80 } \ 81 for (_i=low2; _i<high2; _i++) { \ 82 if (rp2[_i] > col) break; \ 83 if (rp2[_i] == col) { \ 84 if (addv == ADD_VALUES) ap2[_i] += value; \ 85 else ap2[_i] = value; \ 86 goto b_noinsert; \ 87 } \ 88 } \ 89 if (value == 0.0 && ignorezeroentries) goto b_noinsert; \ 90 if (nonew == 1) goto b_noinsert; \ 91 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 92 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 93 N = nrow2++ - 1; b->nz++; high2++;\ 94 /* shift up all the later entries in this row */ \ 95 for (ii=N; ii>=_i; ii--) { \ 96 rp2[ii+1] = rp2[ii]; \ 97 ap2[ii+1] = ap2[ii]; \ 98 } \ 99 rp2[_i] = col; \ 100 ap2[_i] = value; \ 101 b_noinsert: ; \ 102 bilen[row] = nrow2; \ 103 } 104 105 #undef __FUNCT__ 106 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 107 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 108 { 109 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 110 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 111 PetscErrorCode ierr; 112 PetscInt l,*garray = mat->garray,diag; 113 114 PetscFunctionBegin; 115 /* code only works for square matrices A */ 116 117 /* find size of row to the left of the diagonal part */ 118 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 119 row = row - diag; 120 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 121 if (garray[b->j[b->i[row]+l]] > diag) break; 122 } 123 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 124 125 /* diagonal part */ 126 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 127 128 /* right of diagonal part */ 129 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 130 PetscFunctionReturn(0); 131 } 132 133 #undef __FUNCT__ 134 #define __FUNCT__ "MatSetValues_MPIAIJ" 135 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 136 { 137 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 138 PetscScalar value; 139 PetscErrorCode ierr; 140 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 141 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 142 PetscTruth roworiented = aij->roworiented; 143 144 /* Some Variables required in the macro */ 145 Mat A = aij->A; 146 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 147 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 148 PetscScalar *aa = a->a; 149 PetscTruth ignorezeroentries = a->ignorezeroentries; 150 Mat B = aij->B; 151 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 152 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 153 PetscScalar *ba = b->a; 154 155 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 156 PetscInt nonew = a->nonew; 157 PetscScalar *ap1,*ap2; 158 159 PetscFunctionBegin; 160 for (i=0; i<m; i++) { 161 if (im[i] < 0) continue; 162 #if defined(PETSC_USE_DEBUG) 163 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 164 #endif 165 if (im[i] >= rstart && im[i] < rend) { 166 row = im[i] - rstart; 167 lastcol1 = -1; 168 rp1 = aj + ai[row]; 169 ap1 = aa + ai[row]; 170 rmax1 = aimax[row]; 171 nrow1 = ailen[row]; 172 low1 = 0; 173 high1 = nrow1; 174 lastcol2 = -1; 175 rp2 = bj + bi[row]; 176 ap2 = ba + bi[row]; 177 rmax2 = bimax[row]; 178 nrow2 = bilen[row]; 179 low2 = 0; 180 high2 = nrow2; 181 182 for (j=0; j<n; j++) { 183 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 184 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 185 if (in[j] >= cstart && in[j] < cend){ 186 col = in[j] - cstart; 187 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 188 } else if (in[j] < 0) continue; 189 #if defined(PETSC_USE_DEBUG) 190 else if (in[j] >= mat->cmap.N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap.N-1);} 191 #endif 192 else { 193 if (mat->was_assembled) { 194 if (!aij->colmap) { 195 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 196 } 197 #if defined (PETSC_USE_CTABLE) 198 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 199 col--; 200 #else 201 col = aij->colmap[in[j]] - 1; 202 #endif 203 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 204 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 205 col = in[j]; 206 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 207 B = aij->B; 208 b = (Mat_SeqAIJ*)B->data; 209 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 210 rp2 = bj + bi[row]; 211 ap2 = ba + bi[row]; 212 rmax2 = bimax[row]; 213 nrow2 = bilen[row]; 214 low2 = 0; 215 high2 = nrow2; 216 bm = aij->B->rmap.n; 217 ba = b->a; 218 } 219 } else col = in[j]; 220 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 221 } 222 } 223 } else { 224 if (!aij->donotstash) { 225 if (roworiented) { 226 if (ignorezeroentries && v[i*n] == 0.0) continue; 227 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 228 } else { 229 if (ignorezeroentries && v[i] == 0.0) continue; 230 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 231 } 232 } 233 } 234 } 235 PetscFunctionReturn(0); 236 } 237 238 #undef __FUNCT__ 239 #define __FUNCT__ "MatGetValues_MPIAIJ" 240 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 241 { 242 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 243 PetscErrorCode ierr; 244 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 245 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 246 247 PetscFunctionBegin; 248 for (i=0; i<m; i++) { 249 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 250 if (idxm[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap.N-1); 251 if (idxm[i] >= rstart && idxm[i] < rend) { 252 row = idxm[i] - rstart; 253 for (j=0; j<n; j++) { 254 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 255 if (idxn[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap.N-1); 256 if (idxn[j] >= cstart && idxn[j] < cend){ 257 col = idxn[j] - cstart; 258 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 259 } else { 260 if (!aij->colmap) { 261 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 262 } 263 #if defined (PETSC_USE_CTABLE) 264 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 265 col --; 266 #else 267 col = aij->colmap[idxn[j]] - 1; 268 #endif 269 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 270 else { 271 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 272 } 273 } 274 } 275 } else { 276 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 277 } 278 } 279 PetscFunctionReturn(0); 280 } 281 282 #undef __FUNCT__ 283 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 284 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 285 { 286 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 287 PetscErrorCode ierr; 288 PetscInt nstash,reallocs; 289 InsertMode addv; 290 291 PetscFunctionBegin; 292 if (aij->donotstash) { 293 PetscFunctionReturn(0); 294 } 295 296 /* make sure all processors are either in INSERTMODE or ADDMODE */ 297 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 298 if (addv == (ADD_VALUES|INSERT_VALUES)) { 299 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 300 } 301 mat->insertmode = addv; /* in case this processor had no cache */ 302 303 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap.range);CHKERRQ(ierr); 304 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 305 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 306 PetscFunctionReturn(0); 307 } 308 309 #undef __FUNCT__ 310 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 311 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 312 { 313 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 314 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data; 315 PetscErrorCode ierr; 316 PetscMPIInt n; 317 PetscInt i,j,rstart,ncols,flg; 318 PetscInt *row,*col,other_disassembled; 319 PetscScalar *val; 320 InsertMode addv = mat->insertmode; 321 322 /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */ 323 PetscFunctionBegin; 324 if (!aij->donotstash) { 325 while (1) { 326 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 327 if (!flg) break; 328 329 for (i=0; i<n;) { 330 /* Now identify the consecutive vals belonging to the same row */ 331 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 332 if (j < n) ncols = j-i; 333 else ncols = n-i; 334 /* Now assemble all these values with a single function call */ 335 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 336 i = j; 337 } 338 } 339 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 340 } 341 a->compressedrow.use = PETSC_FALSE; 342 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 343 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 344 345 /* determine if any processor has disassembled, if so we must 346 also disassemble ourselfs, in order that we may reassemble. */ 347 /* 348 if nonzero structure of submatrix B cannot change then we know that 349 no processor disassembled thus we can skip this stuff 350 */ 351 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 352 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 353 if (mat->was_assembled && !other_disassembled) { 354 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 355 } 356 } 357 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 358 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 359 } 360 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 361 ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 362 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 363 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 364 365 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 366 aij->rowvalues = 0; 367 368 /* used by MatAXPY() */ 369 a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 370 a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 371 372 PetscFunctionReturn(0); 373 } 374 375 #undef __FUNCT__ 376 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 377 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 378 { 379 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 380 PetscErrorCode ierr; 381 382 PetscFunctionBegin; 383 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 384 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 385 PetscFunctionReturn(0); 386 } 387 388 #undef __FUNCT__ 389 #define __FUNCT__ "MatZeroRows_MPIAIJ" 390 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 391 { 392 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 393 PetscErrorCode ierr; 394 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 395 PetscInt i,*owners = A->rmap.range; 396 PetscInt *nprocs,j,idx,nsends,row; 397 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 398 PetscInt *rvalues,count,base,slen,*source; 399 PetscInt *lens,*lrows,*values,rstart=A->rmap.rstart; 400 MPI_Comm comm = ((PetscObject)A)->comm; 401 MPI_Request *send_waits,*recv_waits; 402 MPI_Status recv_status,*send_status; 403 #if defined(PETSC_DEBUG) 404 PetscTruth found = PETSC_FALSE; 405 #endif 406 407 PetscFunctionBegin; 408 /* first count number of contributors to each processor */ 409 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 410 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 411 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 412 j = 0; 413 for (i=0; i<N; i++) { 414 if (lastidx > (idx = rows[i])) j = 0; 415 lastidx = idx; 416 for (; j<size; j++) { 417 if (idx >= owners[j] && idx < owners[j+1]) { 418 nprocs[2*j]++; 419 nprocs[2*j+1] = 1; 420 owner[i] = j; 421 #if defined(PETSC_DEBUG) 422 found = PETSC_TRUE; 423 #endif 424 break; 425 } 426 } 427 #if defined(PETSC_DEBUG) 428 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 429 found = PETSC_FALSE; 430 #endif 431 } 432 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 433 434 /* inform other processors of number of messages and max length*/ 435 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 436 437 /* post receives: */ 438 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 439 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 440 for (i=0; i<nrecvs; i++) { 441 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 442 } 443 444 /* do sends: 445 1) starts[i] gives the starting index in svalues for stuff going to 446 the ith processor 447 */ 448 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 449 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 450 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 451 starts[0] = 0; 452 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 453 for (i=0; i<N; i++) { 454 svalues[starts[owner[i]]++] = rows[i]; 455 } 456 457 starts[0] = 0; 458 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 459 count = 0; 460 for (i=0; i<size; i++) { 461 if (nprocs[2*i+1]) { 462 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 463 } 464 } 465 ierr = PetscFree(starts);CHKERRQ(ierr); 466 467 base = owners[rank]; 468 469 /* wait on receives */ 470 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 471 source = lens + nrecvs; 472 count = nrecvs; slen = 0; 473 while (count) { 474 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 475 /* unpack receives into our local space */ 476 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 477 source[imdex] = recv_status.MPI_SOURCE; 478 lens[imdex] = n; 479 slen += n; 480 count--; 481 } 482 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 483 484 /* move the data into the send scatter */ 485 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 486 count = 0; 487 for (i=0; i<nrecvs; i++) { 488 values = rvalues + i*nmax; 489 for (j=0; j<lens[i]; j++) { 490 lrows[count++] = values[j] - base; 491 } 492 } 493 ierr = PetscFree(rvalues);CHKERRQ(ierr); 494 ierr = PetscFree(lens);CHKERRQ(ierr); 495 ierr = PetscFree(owner);CHKERRQ(ierr); 496 ierr = PetscFree(nprocs);CHKERRQ(ierr); 497 498 /* actually zap the local rows */ 499 /* 500 Zero the required rows. If the "diagonal block" of the matrix 501 is square and the user wishes to set the diagonal we use separate 502 code so that MatSetValues() is not called for each diagonal allocating 503 new memory, thus calling lots of mallocs and slowing things down. 504 505 Contributed by: Matthew Knepley 506 */ 507 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 508 ierr = MatZeroRows(l->B,slen,lrows,0.0);CHKERRQ(ierr); 509 if ((diag != 0.0) && (l->A->rmap.N == l->A->cmap.N)) { 510 ierr = MatZeroRows(l->A,slen,lrows,diag);CHKERRQ(ierr); 511 } else if (diag != 0.0) { 512 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 513 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 514 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 515 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 516 } 517 for (i = 0; i < slen; i++) { 518 row = lrows[i] + rstart; 519 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 520 } 521 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 522 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 523 } else { 524 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 525 } 526 ierr = PetscFree(lrows);CHKERRQ(ierr); 527 528 /* wait on sends */ 529 if (nsends) { 530 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 531 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 532 ierr = PetscFree(send_status);CHKERRQ(ierr); 533 } 534 ierr = PetscFree(send_waits);CHKERRQ(ierr); 535 ierr = PetscFree(svalues);CHKERRQ(ierr); 536 537 PetscFunctionReturn(0); 538 } 539 540 #undef __FUNCT__ 541 #define __FUNCT__ "MatMult_MPIAIJ" 542 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 543 { 544 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 545 PetscErrorCode ierr; 546 PetscInt nt; 547 548 PetscFunctionBegin; 549 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 550 if (nt != A->cmap.n) { 551 SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap.n,nt); 552 } 553 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 554 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 555 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 556 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 557 PetscFunctionReturn(0); 558 } 559 560 #undef __FUNCT__ 561 #define __FUNCT__ "MatMultAdd_MPIAIJ" 562 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 563 { 564 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 565 PetscErrorCode ierr; 566 567 PetscFunctionBegin; 568 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 569 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 570 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 571 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 572 PetscFunctionReturn(0); 573 } 574 575 #undef __FUNCT__ 576 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 577 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 578 { 579 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 580 PetscErrorCode ierr; 581 PetscTruth merged; 582 583 PetscFunctionBegin; 584 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 585 /* do nondiagonal part */ 586 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 587 if (!merged) { 588 /* send it on its way */ 589 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 590 /* do local part */ 591 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 592 /* receive remote parts: note this assumes the values are not actually */ 593 /* added in yy until the next line, */ 594 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 595 } else { 596 /* do local part */ 597 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 598 /* send it on its way */ 599 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 600 /* values actually were received in the Begin() but we need to call this nop */ 601 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 602 } 603 PetscFunctionReturn(0); 604 } 605 606 EXTERN_C_BEGIN 607 #undef __FUNCT__ 608 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 609 PetscErrorCode PETSCMAT_DLLEXPORT MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f) 610 { 611 MPI_Comm comm; 612 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 613 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 614 IS Me,Notme; 615 PetscErrorCode ierr; 616 PetscInt M,N,first,last,*notme,i; 617 PetscMPIInt size; 618 619 PetscFunctionBegin; 620 621 /* Easy test: symmetric diagonal block */ 622 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 623 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 624 if (!*f) PetscFunctionReturn(0); 625 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 626 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 627 if (size == 1) PetscFunctionReturn(0); 628 629 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 630 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 631 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 632 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 633 for (i=0; i<first; i++) notme[i] = i; 634 for (i=last; i<M; i++) notme[i-last+first] = i; 635 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);CHKERRQ(ierr); 636 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 637 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 638 Aoff = Aoffs[0]; 639 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 640 Boff = Boffs[0]; 641 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 642 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 643 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 644 ierr = ISDestroy(Me);CHKERRQ(ierr); 645 ierr = ISDestroy(Notme);CHKERRQ(ierr); 646 647 PetscFunctionReturn(0); 648 } 649 EXTERN_C_END 650 651 #undef __FUNCT__ 652 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 653 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 654 { 655 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 656 PetscErrorCode ierr; 657 658 PetscFunctionBegin; 659 /* do nondiagonal part */ 660 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 661 /* send it on its way */ 662 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 663 /* do local part */ 664 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 665 /* receive remote parts */ 666 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 667 PetscFunctionReturn(0); 668 } 669 670 /* 671 This only works correctly for square matrices where the subblock A->A is the 672 diagonal block 673 */ 674 #undef __FUNCT__ 675 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 676 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 677 { 678 PetscErrorCode ierr; 679 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 680 681 PetscFunctionBegin; 682 if (A->rmap.N != A->cmap.N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 683 if (A->rmap.rstart != A->cmap.rstart || A->rmap.rend != A->cmap.rend) { 684 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 685 } 686 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 687 PetscFunctionReturn(0); 688 } 689 690 #undef __FUNCT__ 691 #define __FUNCT__ "MatScale_MPIAIJ" 692 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 693 { 694 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 695 PetscErrorCode ierr; 696 697 PetscFunctionBegin; 698 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 699 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 700 PetscFunctionReturn(0); 701 } 702 703 #undef __FUNCT__ 704 #define __FUNCT__ "MatDestroy_MPIAIJ" 705 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 706 { 707 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 708 PetscErrorCode ierr; 709 710 PetscFunctionBegin; 711 #if defined(PETSC_USE_LOG) 712 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap.N,mat->cmap.N); 713 #endif 714 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 715 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 716 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 717 #if defined (PETSC_USE_CTABLE) 718 if (aij->colmap) {ierr = PetscTableDestroy(aij->colmap);CHKERRQ(ierr);} 719 #else 720 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 721 #endif 722 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 723 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 724 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 725 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 726 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 727 ierr = PetscFree(aij);CHKERRQ(ierr); 728 729 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 730 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 731 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 732 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 733 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 734 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 735 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 736 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 737 PetscFunctionReturn(0); 738 } 739 740 #undef __FUNCT__ 741 #define __FUNCT__ "MatView_MPIAIJ_Binary" 742 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 743 { 744 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 745 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 746 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 747 PetscErrorCode ierr; 748 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 749 int fd; 750 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 751 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap.rstart,rnz; 752 PetscScalar *column_values; 753 754 PetscFunctionBegin; 755 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 756 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 757 nz = A->nz + B->nz; 758 if (!rank) { 759 header[0] = MAT_FILE_COOKIE; 760 header[1] = mat->rmap.N; 761 header[2] = mat->cmap.N; 762 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 763 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 764 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 765 /* get largest number of rows any processor has */ 766 rlen = mat->rmap.n; 767 range = mat->rmap.range; 768 for (i=1; i<size; i++) { 769 rlen = PetscMax(rlen,range[i+1] - range[i]); 770 } 771 } else { 772 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 773 rlen = mat->rmap.n; 774 } 775 776 /* load up the local row counts */ 777 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 778 for (i=0; i<mat->rmap.n; i++) { 779 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 780 } 781 782 /* store the row lengths to the file */ 783 if (!rank) { 784 MPI_Status status; 785 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap.n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 786 for (i=1; i<size; i++) { 787 rlen = range[i+1] - range[i]; 788 ierr = MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 789 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 790 } 791 } else { 792 ierr = MPI_Send(row_lengths,mat->rmap.n,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 793 } 794 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 795 796 /* load up the local column indices */ 797 nzmax = nz; /* )th processor needs space a largest processor needs */ 798 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 799 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 800 cnt = 0; 801 for (i=0; i<mat->rmap.n; i++) { 802 for (j=B->i[i]; j<B->i[i+1]; j++) { 803 if ( (col = garray[B->j[j]]) > cstart) break; 804 column_indices[cnt++] = col; 805 } 806 for (k=A->i[i]; k<A->i[i+1]; k++) { 807 column_indices[cnt++] = A->j[k] + cstart; 808 } 809 for (; j<B->i[i+1]; j++) { 810 column_indices[cnt++] = garray[B->j[j]]; 811 } 812 } 813 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 814 815 /* store the column indices to the file */ 816 if (!rank) { 817 MPI_Status status; 818 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 819 for (i=1; i<size; i++) { 820 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 821 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 822 ierr = MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 823 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 824 } 825 } else { 826 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 827 ierr = MPI_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 828 } 829 ierr = PetscFree(column_indices);CHKERRQ(ierr); 830 831 /* load up the local column values */ 832 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 833 cnt = 0; 834 for (i=0; i<mat->rmap.n; i++) { 835 for (j=B->i[i]; j<B->i[i+1]; j++) { 836 if ( garray[B->j[j]] > cstart) break; 837 column_values[cnt++] = B->a[j]; 838 } 839 for (k=A->i[i]; k<A->i[i+1]; k++) { 840 column_values[cnt++] = A->a[k]; 841 } 842 for (; j<B->i[i+1]; j++) { 843 column_values[cnt++] = B->a[j]; 844 } 845 } 846 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 847 848 /* store the column values to the file */ 849 if (!rank) { 850 MPI_Status status; 851 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 852 for (i=1; i<size; i++) { 853 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 854 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 855 ierr = MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 856 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 857 } 858 } else { 859 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 860 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 861 } 862 ierr = PetscFree(column_values);CHKERRQ(ierr); 863 PetscFunctionReturn(0); 864 } 865 866 #undef __FUNCT__ 867 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 868 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 869 { 870 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 871 PetscErrorCode ierr; 872 PetscMPIInt rank = aij->rank,size = aij->size; 873 PetscTruth isdraw,iascii,isbinary; 874 PetscViewer sviewer; 875 PetscViewerFormat format; 876 877 PetscFunctionBegin; 878 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 879 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 880 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 881 if (iascii) { 882 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 883 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 884 MatInfo info; 885 PetscTruth inodes; 886 887 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 888 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 889 ierr = MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);CHKERRQ(ierr); 890 if (!inodes) { 891 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 892 rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 893 } else { 894 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 895 rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 896 } 897 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 898 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 899 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 900 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 901 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 902 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 903 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } else if (format == PETSC_VIEWER_ASCII_INFO) { 906 PetscInt inodecount,inodelimit,*inodes; 907 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 908 if (inodes) { 909 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 910 } else { 911 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 912 } 913 PetscFunctionReturn(0); 914 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 915 PetscFunctionReturn(0); 916 } 917 } else if (isbinary) { 918 if (size == 1) { 919 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 920 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 921 } else { 922 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 923 } 924 PetscFunctionReturn(0); 925 } else if (isdraw) { 926 PetscDraw draw; 927 PetscTruth isnull; 928 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 929 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 930 } 931 932 if (size == 1) { 933 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 934 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 935 } else { 936 /* assemble the entire matrix onto first processor. */ 937 Mat A; 938 Mat_SeqAIJ *Aloc; 939 PetscInt M = mat->rmap.N,N = mat->cmap.N,m,*ai,*aj,row,*cols,i,*ct; 940 PetscScalar *a; 941 942 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 943 if (!rank) { 944 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 945 } else { 946 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 947 } 948 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 949 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 950 ierr = MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 951 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 952 953 /* copy over the A part */ 954 Aloc = (Mat_SeqAIJ*)aij->A->data; 955 m = aij->A->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 956 row = mat->rmap.rstart; 957 for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap.rstart ;} 958 for (i=0; i<m; i++) { 959 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 960 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 961 } 962 aj = Aloc->j; 963 for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap.rstart;} 964 965 /* copy over the B part */ 966 Aloc = (Mat_SeqAIJ*)aij->B->data; 967 m = aij->B->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 968 row = mat->rmap.rstart; 969 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 970 ct = cols; 971 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 972 for (i=0; i<m; i++) { 973 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 974 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 975 } 976 ierr = PetscFree(ct);CHKERRQ(ierr); 977 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 978 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 979 /* 980 Everyone has to call to draw the matrix since the graphics waits are 981 synchronized across all processors that share the PetscDraw object 982 */ 983 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 984 if (!rank) { 985 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 986 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 987 } 988 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 989 ierr = MatDestroy(A);CHKERRQ(ierr); 990 } 991 PetscFunctionReturn(0); 992 } 993 994 #undef __FUNCT__ 995 #define __FUNCT__ "MatView_MPIAIJ" 996 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 997 { 998 PetscErrorCode ierr; 999 PetscTruth iascii,isdraw,issocket,isbinary; 1000 1001 PetscFunctionBegin; 1002 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1003 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1004 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1005 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1006 if (iascii || isdraw || isbinary || issocket) { 1007 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1008 } else { 1009 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1010 } 1011 PetscFunctionReturn(0); 1012 } 1013 1014 #undef __FUNCT__ 1015 #define __FUNCT__ "MatRelax_MPIAIJ" 1016 PetscErrorCode MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1017 { 1018 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1019 PetscErrorCode ierr; 1020 Vec bb1; 1021 1022 PetscFunctionBegin; 1023 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1024 1025 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1026 if (flag & SOR_ZERO_INITIAL_GUESS) { 1027 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 1028 its--; 1029 } 1030 1031 while (its--) { 1032 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 1035 /* update rhs: bb1 = bb - B*x */ 1036 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1037 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1038 1039 /* local sweep */ 1040 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 1041 } 1042 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1043 if (flag & SOR_ZERO_INITIAL_GUESS) { 1044 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1045 its--; 1046 } 1047 while (its--) { 1048 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1049 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1050 1051 /* update rhs: bb1 = bb - B*x */ 1052 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1053 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1054 1055 /* local sweep */ 1056 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1057 } 1058 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1059 if (flag & SOR_ZERO_INITIAL_GUESS) { 1060 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1061 its--; 1062 } 1063 while (its--) { 1064 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1065 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1066 1067 /* update rhs: bb1 = bb - B*x */ 1068 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1069 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1070 1071 /* local sweep */ 1072 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1073 } 1074 } else { 1075 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1076 } 1077 1078 ierr = VecDestroy(bb1);CHKERRQ(ierr); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 #undef __FUNCT__ 1083 #define __FUNCT__ "MatPermute_MPIAIJ" 1084 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1085 { 1086 MPI_Comm comm,pcomm; 1087 PetscInt first,local_size,nrows,*rows; 1088 int ntids; 1089 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1090 PetscErrorCode ierr; 1091 1092 PetscFunctionBegin; 1093 ierr = PetscObjectGetComm((PetscObject)A,&comm); CHKERRQ(ierr); 1094 /* make a collective version of 'rowp' */ 1095 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm); CHKERRQ(ierr); 1096 if (pcomm==comm) { 1097 crowp = rowp; 1098 } else { 1099 ierr = ISGetSize(rowp,&nrows); CHKERRQ(ierr); 1100 ierr = ISGetIndices(rowp,&rows); CHKERRQ(ierr); 1101 ierr = ISCreateGeneral(comm,nrows,rows,&crowp); CHKERRQ(ierr); 1102 ierr = ISRestoreIndices(rowp,&rows); CHKERRQ(ierr); 1103 } 1104 /* collect the global row permutation and invert it */ 1105 ierr = ISAllGather(crowp,&growp); CHKERRQ(ierr); 1106 ierr = ISSetPermutation(growp); CHKERRQ(ierr); 1107 if (pcomm!=comm) { 1108 ierr = ISDestroy(crowp); CHKERRQ(ierr); 1109 } 1110 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1111 /* get the local target indices */ 1112 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL); CHKERRQ(ierr); 1113 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL); CHKERRQ(ierr); 1114 ierr = ISGetIndices(irowp,&rows); CHKERRQ(ierr); 1115 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp); CHKERRQ(ierr); 1116 ierr = ISRestoreIndices(irowp,&rows); CHKERRQ(ierr); 1117 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1118 /* the column permutation is so much easier; 1119 make a local version of 'colp' and invert it */ 1120 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm); CHKERRQ(ierr); 1121 ierr = MPI_Comm_size(pcomm,&ntids); CHKERRQ(ierr); 1122 if (ntids==1) { 1123 lcolp = colp; 1124 } else { 1125 ierr = ISGetSize(colp,&nrows); CHKERRQ(ierr); 1126 ierr = ISGetIndices(colp,&rows); CHKERRQ(ierr); 1127 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp); CHKERRQ(ierr); 1128 } 1129 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp); CHKERRQ(ierr); 1130 ierr = ISSetPermutation(lcolp); CHKERRQ(ierr); 1131 if (ntids>1) { 1132 ierr = ISRestoreIndices(colp,&rows); CHKERRQ(ierr); 1133 ierr = ISDestroy(lcolp); CHKERRQ(ierr); 1134 } 1135 /* now we just get the submatrix */ 1136 ierr = MatGetSubMatrix(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B); CHKERRQ(ierr); 1137 /* clean up */ 1138 ierr = ISDestroy(lrowp); CHKERRQ(ierr); 1139 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1140 PetscFunctionReturn(0); 1141 } 1142 1143 #undef __FUNCT__ 1144 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1145 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1146 { 1147 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1148 Mat A = mat->A,B = mat->B; 1149 PetscErrorCode ierr; 1150 PetscReal isend[5],irecv[5]; 1151 1152 PetscFunctionBegin; 1153 info->block_size = 1.0; 1154 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1155 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1156 isend[3] = info->memory; isend[4] = info->mallocs; 1157 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1158 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1159 isend[3] += info->memory; isend[4] += info->mallocs; 1160 if (flag == MAT_LOCAL) { 1161 info->nz_used = isend[0]; 1162 info->nz_allocated = isend[1]; 1163 info->nz_unneeded = isend[2]; 1164 info->memory = isend[3]; 1165 info->mallocs = isend[4]; 1166 } else if (flag == MAT_GLOBAL_MAX) { 1167 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1168 info->nz_used = irecv[0]; 1169 info->nz_allocated = irecv[1]; 1170 info->nz_unneeded = irecv[2]; 1171 info->memory = irecv[3]; 1172 info->mallocs = irecv[4]; 1173 } else if (flag == MAT_GLOBAL_SUM) { 1174 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1175 info->nz_used = irecv[0]; 1176 info->nz_allocated = irecv[1]; 1177 info->nz_unneeded = irecv[2]; 1178 info->memory = irecv[3]; 1179 info->mallocs = irecv[4]; 1180 } 1181 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1182 info->fill_ratio_needed = 0; 1183 info->factor_mallocs = 0; 1184 info->rows_global = (double)matin->rmap.N; 1185 info->columns_global = (double)matin->cmap.N; 1186 info->rows_local = (double)matin->rmap.n; 1187 info->columns_local = (double)matin->cmap.N; 1188 1189 PetscFunctionReturn(0); 1190 } 1191 1192 #undef __FUNCT__ 1193 #define __FUNCT__ "MatSetOption_MPIAIJ" 1194 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg) 1195 { 1196 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1197 PetscErrorCode ierr; 1198 1199 PetscFunctionBegin; 1200 switch (op) { 1201 case MAT_NEW_NONZERO_LOCATIONS: 1202 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1203 case MAT_KEEP_ZEROED_ROWS: 1204 case MAT_NEW_NONZERO_LOCATION_ERR: 1205 case MAT_USE_INODES: 1206 case MAT_IGNORE_ZERO_ENTRIES: 1207 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1208 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1209 break; 1210 case MAT_ROW_ORIENTED: 1211 a->roworiented = flg; 1212 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1213 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1214 break; 1215 case MAT_NEW_DIAGONALS: 1216 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1217 break; 1218 case MAT_IGNORE_OFF_PROC_ENTRIES: 1219 a->donotstash = PETSC_TRUE; 1220 break; 1221 case MAT_SYMMETRIC: 1222 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1223 break; 1224 case MAT_STRUCTURALLY_SYMMETRIC: 1225 case MAT_HERMITIAN: 1226 case MAT_SYMMETRY_ETERNAL: 1227 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1228 break; 1229 default: 1230 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1231 } 1232 PetscFunctionReturn(0); 1233 } 1234 1235 #undef __FUNCT__ 1236 #define __FUNCT__ "MatGetRow_MPIAIJ" 1237 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1238 { 1239 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1240 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1241 PetscErrorCode ierr; 1242 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap.rstart; 1243 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap.rstart,rend = matin->rmap.rend; 1244 PetscInt *cmap,*idx_p; 1245 1246 PetscFunctionBegin; 1247 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1248 mat->getrowactive = PETSC_TRUE; 1249 1250 if (!mat->rowvalues && (idx || v)) { 1251 /* 1252 allocate enough space to hold information from the longest row. 1253 */ 1254 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1255 PetscInt max = 1,tmp; 1256 for (i=0; i<matin->rmap.n; i++) { 1257 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1258 if (max < tmp) { max = tmp; } 1259 } 1260 ierr = PetscMalloc(max*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1261 mat->rowindices = (PetscInt*)(mat->rowvalues + max); 1262 } 1263 1264 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1265 lrow = row - rstart; 1266 1267 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1268 if (!v) {pvA = 0; pvB = 0;} 1269 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1270 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1271 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1272 nztot = nzA + nzB; 1273 1274 cmap = mat->garray; 1275 if (v || idx) { 1276 if (nztot) { 1277 /* Sort by increasing column numbers, assuming A and B already sorted */ 1278 PetscInt imark = -1; 1279 if (v) { 1280 *v = v_p = mat->rowvalues; 1281 for (i=0; i<nzB; i++) { 1282 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1283 else break; 1284 } 1285 imark = i; 1286 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1287 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1288 } 1289 if (idx) { 1290 *idx = idx_p = mat->rowindices; 1291 if (imark > -1) { 1292 for (i=0; i<imark; i++) { 1293 idx_p[i] = cmap[cworkB[i]]; 1294 } 1295 } else { 1296 for (i=0; i<nzB; i++) { 1297 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1298 else break; 1299 } 1300 imark = i; 1301 } 1302 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1303 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1304 } 1305 } else { 1306 if (idx) *idx = 0; 1307 if (v) *v = 0; 1308 } 1309 } 1310 *nz = nztot; 1311 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1312 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1313 PetscFunctionReturn(0); 1314 } 1315 1316 #undef __FUNCT__ 1317 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1318 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1319 { 1320 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1321 1322 PetscFunctionBegin; 1323 if (!aij->getrowactive) { 1324 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1325 } 1326 aij->getrowactive = PETSC_FALSE; 1327 PetscFunctionReturn(0); 1328 } 1329 1330 #undef __FUNCT__ 1331 #define __FUNCT__ "MatNorm_MPIAIJ" 1332 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1333 { 1334 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1335 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1336 PetscErrorCode ierr; 1337 PetscInt i,j,cstart = mat->cmap.rstart; 1338 PetscReal sum = 0.0; 1339 PetscScalar *v; 1340 1341 PetscFunctionBegin; 1342 if (aij->size == 1) { 1343 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1344 } else { 1345 if (type == NORM_FROBENIUS) { 1346 v = amat->a; 1347 for (i=0; i<amat->nz; i++) { 1348 #if defined(PETSC_USE_COMPLEX) 1349 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1350 #else 1351 sum += (*v)*(*v); v++; 1352 #endif 1353 } 1354 v = bmat->a; 1355 for (i=0; i<bmat->nz; i++) { 1356 #if defined(PETSC_USE_COMPLEX) 1357 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1358 #else 1359 sum += (*v)*(*v); v++; 1360 #endif 1361 } 1362 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1363 *norm = sqrt(*norm); 1364 } else if (type == NORM_1) { /* max column norm */ 1365 PetscReal *tmp,*tmp2; 1366 PetscInt *jj,*garray = aij->garray; 1367 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1368 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1369 ierr = PetscMemzero(tmp,mat->cmap.N*sizeof(PetscReal));CHKERRQ(ierr); 1370 *norm = 0.0; 1371 v = amat->a; jj = amat->j; 1372 for (j=0; j<amat->nz; j++) { 1373 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1374 } 1375 v = bmat->a; jj = bmat->j; 1376 for (j=0; j<bmat->nz; j++) { 1377 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1378 } 1379 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap.N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1380 for (j=0; j<mat->cmap.N; j++) { 1381 if (tmp2[j] > *norm) *norm = tmp2[j]; 1382 } 1383 ierr = PetscFree(tmp);CHKERRQ(ierr); 1384 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1385 } else if (type == NORM_INFINITY) { /* max row norm */ 1386 PetscReal ntemp = 0.0; 1387 for (j=0; j<aij->A->rmap.n; j++) { 1388 v = amat->a + amat->i[j]; 1389 sum = 0.0; 1390 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1391 sum += PetscAbsScalar(*v); v++; 1392 } 1393 v = bmat->a + bmat->i[j]; 1394 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1395 sum += PetscAbsScalar(*v); v++; 1396 } 1397 if (sum > ntemp) ntemp = sum; 1398 } 1399 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 1400 } else { 1401 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1402 } 1403 } 1404 PetscFunctionReturn(0); 1405 } 1406 1407 #undef __FUNCT__ 1408 #define __FUNCT__ "MatTranspose_MPIAIJ" 1409 PetscErrorCode MatTranspose_MPIAIJ(Mat A,Mat *matout) 1410 { 1411 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1412 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1413 PetscErrorCode ierr; 1414 PetscInt M = A->rmap.N,N = A->cmap.N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,i,*d_nnz; 1415 PetscInt cstart=A->cmap.rstart,ncol; 1416 Mat B; 1417 PetscScalar *array; 1418 1419 PetscFunctionBegin; 1420 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1421 1422 /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */ 1423 ma = A->rmap.n; na = A->cmap.n; mb = a->B->rmap.n; 1424 ai = Aloc->i; aj = Aloc->j; 1425 bi = Bloc->i; bj = Bloc->j; 1426 ierr = PetscMalloc((1+na+bi[mb])*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1427 cols = d_nnz + na + 1; /* work space to be used by B part */ 1428 ierr = PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));CHKERRQ(ierr); 1429 for (i=0; i<ai[ma]; i++){ 1430 d_nnz[aj[i]] ++; 1431 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1432 } 1433 1434 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1435 ierr = MatSetSizes(B,A->cmap.n,A->rmap.n,N,M);CHKERRQ(ierr); 1436 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1437 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);CHKERRQ(ierr); 1438 1439 /* copy over the A part */ 1440 array = Aloc->a; 1441 row = A->rmap.rstart; 1442 for (i=0; i<ma; i++) { 1443 ncol = ai[i+1]-ai[i]; 1444 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1445 row++; array += ncol; aj += ncol; 1446 } 1447 aj = Aloc->j; 1448 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1449 1450 /* copy over the B part */ 1451 array = Bloc->a; 1452 row = A->rmap.rstart; 1453 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 1454 for (i=0; i<mb; i++) { 1455 ncol = bi[i+1]-bi[i]; 1456 ierr = MatSetValues(B,ncol,cols,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1457 row++; array += ncol; cols += ncol; 1458 } 1459 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1460 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1461 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1462 if (matout) { 1463 *matout = B; 1464 } else { 1465 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1466 } 1467 PetscFunctionReturn(0); 1468 } 1469 1470 #undef __FUNCT__ 1471 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1472 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1473 { 1474 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1475 Mat a = aij->A,b = aij->B; 1476 PetscErrorCode ierr; 1477 PetscInt s1,s2,s3; 1478 1479 PetscFunctionBegin; 1480 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1481 if (rr) { 1482 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1483 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1484 /* Overlap communication with computation. */ 1485 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1486 } 1487 if (ll) { 1488 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1489 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1490 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1491 } 1492 /* scale the diagonal block */ 1493 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1494 1495 if (rr) { 1496 /* Do a scatter end and then right scale the off-diagonal block */ 1497 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1498 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1499 } 1500 1501 PetscFunctionReturn(0); 1502 } 1503 1504 #undef __FUNCT__ 1505 #define __FUNCT__ "MatSetBlockSize_MPIAIJ" 1506 PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs) 1507 { 1508 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1509 PetscErrorCode ierr; 1510 1511 PetscFunctionBegin; 1512 ierr = MatSetBlockSize(a->A,bs);CHKERRQ(ierr); 1513 ierr = MatSetBlockSize(a->B,bs);CHKERRQ(ierr); 1514 PetscFunctionReturn(0); 1515 } 1516 #undef __FUNCT__ 1517 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1518 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 1519 { 1520 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1521 PetscErrorCode ierr; 1522 1523 PetscFunctionBegin; 1524 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1525 PetscFunctionReturn(0); 1526 } 1527 1528 #undef __FUNCT__ 1529 #define __FUNCT__ "MatEqual_MPIAIJ" 1530 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1531 { 1532 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1533 Mat a,b,c,d; 1534 PetscTruth flg; 1535 PetscErrorCode ierr; 1536 1537 PetscFunctionBegin; 1538 a = matA->A; b = matA->B; 1539 c = matB->A; d = matB->B; 1540 1541 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1542 if (flg) { 1543 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1544 } 1545 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1546 PetscFunctionReturn(0); 1547 } 1548 1549 #undef __FUNCT__ 1550 #define __FUNCT__ "MatCopy_MPIAIJ" 1551 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1552 { 1553 PetscErrorCode ierr; 1554 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1555 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1556 1557 PetscFunctionBegin; 1558 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1559 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1560 /* because of the column compression in the off-processor part of the matrix a->B, 1561 the number of columns in a->B and b->B may be different, hence we cannot call 1562 the MatCopy() directly on the two parts. If need be, we can provide a more 1563 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1564 then copying the submatrices */ 1565 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1566 } else { 1567 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1568 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1569 } 1570 PetscFunctionReturn(0); 1571 } 1572 1573 #undef __FUNCT__ 1574 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1575 PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A) 1576 { 1577 PetscErrorCode ierr; 1578 1579 PetscFunctionBegin; 1580 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #include "petscblaslapack.h" 1585 #undef __FUNCT__ 1586 #define __FUNCT__ "MatAXPY_MPIAIJ" 1587 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1588 { 1589 PetscErrorCode ierr; 1590 PetscInt i; 1591 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1592 PetscBLASInt bnz,one=1; 1593 Mat_SeqAIJ *x,*y; 1594 1595 PetscFunctionBegin; 1596 if (str == SAME_NONZERO_PATTERN) { 1597 PetscScalar alpha = a; 1598 x = (Mat_SeqAIJ *)xx->A->data; 1599 y = (Mat_SeqAIJ *)yy->A->data; 1600 bnz = (PetscBLASInt)x->nz; 1601 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1602 x = (Mat_SeqAIJ *)xx->B->data; 1603 y = (Mat_SeqAIJ *)yy->B->data; 1604 bnz = (PetscBLASInt)x->nz; 1605 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1606 } else if (str == SUBSET_NONZERO_PATTERN) { 1607 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 1608 1609 x = (Mat_SeqAIJ *)xx->B->data; 1610 y = (Mat_SeqAIJ *)yy->B->data; 1611 if (y->xtoy && y->XtoY != xx->B) { 1612 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1613 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1614 } 1615 if (!y->xtoy) { /* get xtoy */ 1616 ierr = MatAXPYGetxtoy_Private(xx->B->rmap.n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1617 y->XtoY = xx->B; 1618 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 1619 } 1620 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 1621 } else { 1622 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1623 } 1624 PetscFunctionReturn(0); 1625 } 1626 1627 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat); 1628 1629 #undef __FUNCT__ 1630 #define __FUNCT__ "MatConjugate_MPIAIJ" 1631 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_MPIAIJ(Mat mat) 1632 { 1633 #if defined(PETSC_USE_COMPLEX) 1634 PetscErrorCode ierr; 1635 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1636 1637 PetscFunctionBegin; 1638 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 1639 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 1640 #else 1641 PetscFunctionBegin; 1642 #endif 1643 PetscFunctionReturn(0); 1644 } 1645 1646 #undef __FUNCT__ 1647 #define __FUNCT__ "MatRealPart_MPIAIJ" 1648 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 1649 { 1650 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1651 PetscErrorCode ierr; 1652 1653 PetscFunctionBegin; 1654 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1655 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1656 PetscFunctionReturn(0); 1657 } 1658 1659 #undef __FUNCT__ 1660 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 1661 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 1662 { 1663 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1664 PetscErrorCode ierr; 1665 1666 PetscFunctionBegin; 1667 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1668 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1669 PetscFunctionReturn(0); 1670 } 1671 1672 #ifdef PETSC_HAVE_PBGL 1673 1674 #include <boost/parallel/mpi/bsp_process_group.hpp> 1675 #include <boost/graph/distributed/ilu_default_graph.hpp> 1676 #include <boost/graph/distributed/ilu_0_block.hpp> 1677 #include <boost/graph/distributed/ilu_preconditioner.hpp> 1678 #include <boost/graph/distributed/petsc/interface.hpp> 1679 #include <boost/multi_array.hpp> 1680 #include <boost/parallel/distributed_property_map.hpp> 1681 1682 #undef __FUNCT__ 1683 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 1684 /* 1685 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1686 */ 1687 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat A, IS isrow, IS iscol, MatFactorInfo *info, Mat *fact) 1688 { 1689 namespace petsc = boost::distributed::petsc; 1690 1691 namespace graph_dist = boost::graph::distributed; 1692 using boost::graph::distributed::ilu_default::process_group_type; 1693 using boost::graph::ilu_permuted; 1694 1695 PetscTruth row_identity, col_identity; 1696 PetscContainer c; 1697 PetscInt m, n, M, N; 1698 PetscErrorCode ierr; 1699 1700 PetscFunctionBegin; 1701 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 1702 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 1703 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 1704 if (!row_identity || !col_identity) { 1705 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 1706 } 1707 1708 process_group_type pg; 1709 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1710 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 1711 lgraph_type& level_graph = *lgraph_p; 1712 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1713 1714 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 1715 ilu_permuted(level_graph); 1716 1717 /* put together the new matrix */ 1718 ierr = MatCreate(((PetscObject)A)->comm, fact);CHKERRQ(ierr); 1719 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 1720 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 1721 ierr = MatSetSizes(*fact, m, n, M, N);CHKERRQ(ierr); 1722 ierr = MatSetType(*fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 1723 ierr = MatAssemblyBegin(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1724 ierr = MatAssemblyEnd(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1725 (*fact)->factor = FACTOR_LU; 1726 1727 ierr = PetscContainerCreate(((PetscObject)A)->comm, &c); 1728 ierr = PetscContainerSetPointer(c, lgraph_p); 1729 ierr = PetscObjectCompose((PetscObject) (*fact), "graph", (PetscObject) c); 1730 PetscFunctionReturn(0); 1731 } 1732 1733 #undef __FUNCT__ 1734 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 1735 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat A, MatFactorInfo *info, Mat *B) 1736 { 1737 PetscFunctionBegin; 1738 PetscFunctionReturn(0); 1739 } 1740 1741 #undef __FUNCT__ 1742 #define __FUNCT__ "MatSolve_MPIAIJ" 1743 /* 1744 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1745 */ 1746 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 1747 { 1748 namespace graph_dist = boost::graph::distributed; 1749 1750 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1751 lgraph_type* lgraph_p; 1752 PetscContainer c; 1753 PetscErrorCode ierr; 1754 1755 PetscFunctionBegin; 1756 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 1757 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 1758 ierr = VecCopy(b, x); CHKERRQ(ierr); 1759 1760 PetscScalar* array_x; 1761 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 1762 PetscInt sx; 1763 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 1764 1765 PetscScalar* array_b; 1766 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 1767 PetscInt sb; 1768 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 1769 1770 lgraph_type& level_graph = *lgraph_p; 1771 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1772 1773 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 1774 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 1775 ref_x(array_x, boost::extents[num_vertices(graph)]); 1776 1777 typedef boost::iterator_property_map<array_ref_type::iterator, 1778 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 1779 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 1780 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 1781 1782 ilu_set_solve(*lgraph_p, vector_b, vector_x); 1783 1784 PetscFunctionReturn(0); 1785 } 1786 #endif 1787 1788 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 1789 PetscInt nzlocal,nsends,nrecvs; 1790 PetscMPIInt *send_rank; 1791 PetscInt *sbuf_nz,*sbuf_j,**rbuf_j; 1792 PetscScalar *sbuf_a,**rbuf_a; 1793 PetscErrorCode (*MatDestroy)(Mat); 1794 } Mat_Redundant; 1795 1796 #undef __FUNCT__ 1797 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 1798 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 1799 { 1800 PetscErrorCode ierr; 1801 Mat_Redundant *redund=(Mat_Redundant*)ptr; 1802 PetscInt i; 1803 1804 PetscFunctionBegin; 1805 ierr = PetscFree(redund->send_rank);CHKERRQ(ierr); 1806 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1807 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1808 for (i=0; i<redund->nrecvs; i++){ 1809 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1810 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1811 } 1812 ierr = PetscFree3(redund->sbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1813 ierr = PetscFree(redund);CHKERRQ(ierr); 1814 PetscFunctionReturn(0); 1815 } 1816 1817 #undef __FUNCT__ 1818 #define __FUNCT__ "MatDestroy_MatRedundant" 1819 PetscErrorCode MatDestroy_MatRedundant(Mat A) 1820 { 1821 PetscErrorCode ierr; 1822 PetscContainer container; 1823 Mat_Redundant *redund=PETSC_NULL; 1824 1825 PetscFunctionBegin; 1826 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 1827 if (container) { 1828 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 1829 } else { 1830 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 1831 } 1832 A->ops->destroy = redund->MatDestroy; 1833 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 1834 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 1835 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 1836 PetscFunctionReturn(0); 1837 } 1838 1839 #undef __FUNCT__ 1840 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 1841 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 1842 { 1843 PetscMPIInt rank,size; 1844 MPI_Comm comm=((PetscObject)mat)->comm; 1845 PetscErrorCode ierr; 1846 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 1847 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 1848 PetscInt *rowrange=mat->rmap.range; 1849 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1850 Mat A=aij->A,B=aij->B,C=*matredundant; 1851 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 1852 PetscScalar *sbuf_a; 1853 PetscInt nzlocal=a->nz+b->nz; 1854 PetscInt j,cstart=mat->cmap.rstart,cend=mat->cmap.rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 1855 PetscInt rstart=mat->rmap.rstart,rend=mat->rmap.rend,*bmap=aij->garray,M,N; 1856 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 1857 PetscScalar *vals,*aworkA,*aworkB; 1858 PetscMPIInt tag1,tag2,tag3,imdex; 1859 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 1860 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 1861 MPI_Status recv_status,*send_status; 1862 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 1863 PetscInt **rbuf_j=PETSC_NULL; 1864 PetscScalar **rbuf_a=PETSC_NULL; 1865 Mat_Redundant *redund=PETSC_NULL; 1866 PetscContainer container; 1867 1868 PetscFunctionBegin; 1869 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1870 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1871 1872 if (reuse == MAT_REUSE_MATRIX) { 1873 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 1874 if (M != N || M != mat->rmap.N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 1875 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 1876 if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 1877 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 1878 if (container) { 1879 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 1880 } else { 1881 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 1882 } 1883 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 1884 1885 nsends = redund->nsends; 1886 nrecvs = redund->nrecvs; 1887 send_rank = redund->send_rank; recv_rank = send_rank + size; 1888 sbuf_nz = redund->sbuf_nz; rbuf_nz = sbuf_nz + nsends; 1889 sbuf_j = redund->sbuf_j; 1890 sbuf_a = redund->sbuf_a; 1891 rbuf_j = redund->rbuf_j; 1892 rbuf_a = redund->rbuf_a; 1893 } 1894 1895 if (reuse == MAT_INITIAL_MATRIX){ 1896 PetscMPIInt subrank,subsize; 1897 PetscInt nleftover,np_subcomm; 1898 /* get the destination processors' id send_rank, nsends and nrecvs */ 1899 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 1900 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 1901 ierr = PetscMalloc((2*size+1)*sizeof(PetscMPIInt),&send_rank); 1902 recv_rank = send_rank + size; 1903 np_subcomm = size/nsubcomm; 1904 nleftover = size - nsubcomm*np_subcomm; 1905 nsends = 0; nrecvs = 0; 1906 for (i=0; i<size; i++){ /* i=rank*/ 1907 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 1908 send_rank[nsends] = i; nsends++; 1909 recv_rank[nrecvs++] = i; 1910 } 1911 } 1912 if (rank >= size - nleftover){/* this proc is a leftover processor */ 1913 i = size-nleftover-1; 1914 j = 0; 1915 while (j < nsubcomm - nleftover){ 1916 send_rank[nsends++] = i; 1917 i--; j++; 1918 } 1919 } 1920 1921 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 1922 for (i=0; i<nleftover; i++){ 1923 recv_rank[nrecvs++] = size-nleftover+i; 1924 } 1925 } 1926 1927 /* allocate sbuf_j, sbuf_a */ 1928 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 1929 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 1930 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 1931 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 1932 1933 /* copy mat's local entries into the buffers */ 1934 if (reuse == MAT_INITIAL_MATRIX){ 1935 rownz_max = 0; 1936 rptr = sbuf_j; 1937 cols = sbuf_j + rend-rstart + 1; 1938 vals = sbuf_a; 1939 rptr[0] = 0; 1940 for (i=0; i<rend-rstart; i++){ 1941 row = i + rstart; 1942 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 1943 ncols = nzA + nzB; 1944 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 1945 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 1946 /* load the column indices for this row into cols */ 1947 lwrite = 0; 1948 for (l=0; l<nzB; l++) { 1949 if ((ctmp = bmap[cworkB[l]]) < cstart){ 1950 vals[lwrite] = aworkB[l]; 1951 cols[lwrite++] = ctmp; 1952 } 1953 } 1954 for (l=0; l<nzA; l++){ 1955 vals[lwrite] = aworkA[l]; 1956 cols[lwrite++] = cstart + cworkA[l]; 1957 } 1958 for (l=0; l<nzB; l++) { 1959 if ((ctmp = bmap[cworkB[l]]) >= cend){ 1960 vals[lwrite] = aworkB[l]; 1961 cols[lwrite++] = ctmp; 1962 } 1963 } 1964 vals += ncols; 1965 cols += ncols; 1966 rptr[i+1] = rptr[i] + ncols; 1967 if (rownz_max < ncols) rownz_max = ncols; 1968 } 1969 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(1, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 1970 } else { /* only copy matrix values into sbuf_a */ 1971 rptr = sbuf_j; 1972 vals = sbuf_a; 1973 rptr[0] = 0; 1974 for (i=0; i<rend-rstart; i++){ 1975 row = i + rstart; 1976 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 1977 ncols = nzA + nzB; 1978 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 1979 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 1980 lwrite = 0; 1981 for (l=0; l<nzB; l++) { 1982 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 1983 } 1984 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 1985 for (l=0; l<nzB; l++) { 1986 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 1987 } 1988 vals += ncols; 1989 rptr[i+1] = rptr[i] + ncols; 1990 } 1991 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 1992 1993 /* send nzlocal to others, and recv other's nzlocal */ 1994 /*--------------------------------------------------*/ 1995 if (reuse == MAT_INITIAL_MATRIX){ 1996 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 1997 s_waits2 = s_waits3 + nsends; 1998 s_waits1 = s_waits2 + nsends; 1999 r_waits1 = s_waits1 + nsends; 2000 r_waits2 = r_waits1 + nrecvs; 2001 r_waits3 = r_waits2 + nrecvs; 2002 } else { 2003 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2004 r_waits3 = s_waits3 + nsends; 2005 } 2006 2007 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2008 if (reuse == MAT_INITIAL_MATRIX){ 2009 /* get new tags to keep the communication clean */ 2010 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2011 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2012 ierr = PetscMalloc3(nsends+nrecvs+1,PetscInt,&sbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2013 rbuf_nz = sbuf_nz + nsends; 2014 2015 /* post receives of other's nzlocal */ 2016 for (i=0; i<nrecvs; i++){ 2017 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2018 } 2019 /* send nzlocal to others */ 2020 for (i=0; i<nsends; i++){ 2021 sbuf_nz[i] = nzlocal; 2022 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2023 } 2024 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2025 count = nrecvs; 2026 while (count) { 2027 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2028 recv_rank[imdex] = recv_status.MPI_SOURCE; 2029 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2030 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2031 2032 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2033 rbuf_nz[imdex] += i + 2; 2034 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2035 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2036 count--; 2037 } 2038 /* wait on sends of nzlocal */ 2039 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2040 /* send mat->i,j to others, and recv from other's */ 2041 /*------------------------------------------------*/ 2042 for (i=0; i<nsends; i++){ 2043 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2044 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2045 } 2046 /* wait on receives of mat->i,j */ 2047 /*------------------------------*/ 2048 count = nrecvs; 2049 while (count) { 2050 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2051 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2052 count--; 2053 } 2054 /* wait on sends of mat->i,j */ 2055 /*---------------------------*/ 2056 if (nsends) { 2057 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2058 } 2059 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2060 2061 /* post receives, send and receive mat->a */ 2062 /*----------------------------------------*/ 2063 for (imdex=0; imdex<nrecvs; imdex++) { 2064 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2065 } 2066 for (i=0; i<nsends; i++){ 2067 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2068 } 2069 count = nrecvs; 2070 while (count) { 2071 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2072 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2073 count--; 2074 } 2075 if (nsends) { 2076 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2077 } 2078 2079 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2080 2081 /* create redundant matrix */ 2082 /*-------------------------*/ 2083 if (reuse == MAT_INITIAL_MATRIX){ 2084 /* compute rownz_max for preallocation */ 2085 for (imdex=0; imdex<nrecvs; imdex++){ 2086 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2087 rptr = rbuf_j[imdex]; 2088 for (i=0; i<j; i++){ 2089 ncols = rptr[i+1] - rptr[i]; 2090 if (rownz_max < ncols) rownz_max = ncols; 2091 } 2092 } 2093 2094 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2095 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2096 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2097 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2098 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2099 } else { 2100 C = *matredundant; 2101 } 2102 2103 /* insert local matrix entries */ 2104 rptr = sbuf_j; 2105 cols = sbuf_j + rend-rstart + 1; 2106 vals = sbuf_a; 2107 for (i=0; i<rend-rstart; i++){ 2108 row = i + rstart; 2109 ncols = rptr[i+1] - rptr[i]; 2110 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2111 vals += ncols; 2112 cols += ncols; 2113 } 2114 /* insert received matrix entries */ 2115 for (imdex=0; imdex<nrecvs; imdex++){ 2116 rstart = rowrange[recv_rank[imdex]]; 2117 rend = rowrange[recv_rank[imdex]+1]; 2118 rptr = rbuf_j[imdex]; 2119 cols = rbuf_j[imdex] + rend-rstart + 1; 2120 vals = rbuf_a[imdex]; 2121 for (i=0; i<rend-rstart; i++){ 2122 row = i + rstart; 2123 ncols = rptr[i+1] - rptr[i]; 2124 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2125 vals += ncols; 2126 cols += ncols; 2127 } 2128 } 2129 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2130 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2131 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2132 if (M != mat->rmap.N || N != mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_INCOMP,"redundant mat size %d != input mat size %d",M,mat->rmap.N); 2133 if (reuse == MAT_INITIAL_MATRIX){ 2134 PetscContainer container; 2135 *matredundant = C; 2136 /* create a supporting struct and attach it to C for reuse */ 2137 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2138 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2139 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2140 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2141 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2142 2143 redund->nzlocal = nzlocal; 2144 redund->nsends = nsends; 2145 redund->nrecvs = nrecvs; 2146 redund->send_rank = send_rank; 2147 redund->sbuf_nz = sbuf_nz; 2148 redund->sbuf_j = sbuf_j; 2149 redund->sbuf_a = sbuf_a; 2150 redund->rbuf_j = rbuf_j; 2151 redund->rbuf_a = rbuf_a; 2152 2153 redund->MatDestroy = C->ops->destroy; 2154 C->ops->destroy = MatDestroy_MatRedundant; 2155 } 2156 PetscFunctionReturn(0); 2157 } 2158 2159 #undef __FUNCT__ 2160 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2161 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2162 { 2163 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2164 PetscInt n = A->rmap.n; 2165 PetscInt cstart = A->cmap.rstart; 2166 PetscInt *cmap = mat->garray; 2167 PetscInt *diagIdx, *offdiagIdx; 2168 Vec diagV, offdiagV; 2169 PetscScalar *a, *diagA, *offdiagA; 2170 PetscInt r; 2171 PetscErrorCode ierr; 2172 2173 PetscFunctionBegin; 2174 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2175 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2176 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2177 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2178 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2179 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2180 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2181 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2182 for(r = 0; r < n; ++r) { 2183 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2184 a[r] = diagA[r]; 2185 idx[r] = cstart + diagIdx[r]; 2186 } else { 2187 a[r] = offdiagA[r]; 2188 idx[r] = cmap[offdiagIdx[r]]; 2189 } 2190 } 2191 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2192 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2193 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2194 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2195 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2196 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatGetSeqNonzerostructure_MPIAIJ" 2202 PetscErrorCode MatGetSeqNonzerostructure_MPIAIJ(Mat mat,Mat *newmat[]) 2203 { 2204 PetscErrorCode ierr; 2205 2206 PetscFunctionBegin; 2207 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,newmat);CHKERRQ(ierr); 2208 PetscFunctionReturn(0); 2209 } 2210 2211 /* -------------------------------------------------------------------*/ 2212 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2213 MatGetRow_MPIAIJ, 2214 MatRestoreRow_MPIAIJ, 2215 MatMult_MPIAIJ, 2216 /* 4*/ MatMultAdd_MPIAIJ, 2217 MatMultTranspose_MPIAIJ, 2218 MatMultTransposeAdd_MPIAIJ, 2219 #ifdef PETSC_HAVE_PBGL 2220 MatSolve_MPIAIJ, 2221 #else 2222 0, 2223 #endif 2224 0, 2225 0, 2226 /*10*/ 0, 2227 0, 2228 0, 2229 MatRelax_MPIAIJ, 2230 MatTranspose_MPIAIJ, 2231 /*15*/ MatGetInfo_MPIAIJ, 2232 MatEqual_MPIAIJ, 2233 MatGetDiagonal_MPIAIJ, 2234 MatDiagonalScale_MPIAIJ, 2235 MatNorm_MPIAIJ, 2236 /*20*/ MatAssemblyBegin_MPIAIJ, 2237 MatAssemblyEnd_MPIAIJ, 2238 0, 2239 MatSetOption_MPIAIJ, 2240 MatZeroEntries_MPIAIJ, 2241 /*25*/ MatZeroRows_MPIAIJ, 2242 0, 2243 #ifdef PETSC_HAVE_PBGL 2244 MatLUFactorNumeric_MPIAIJ, 2245 #else 2246 0, 2247 #endif 2248 0, 2249 0, 2250 /*30*/ MatSetUpPreallocation_MPIAIJ, 2251 #ifdef PETSC_HAVE_PBGL 2252 MatILUFactorSymbolic_MPIAIJ, 2253 #else 2254 0, 2255 #endif 2256 0, 2257 0, 2258 0, 2259 /*35*/ MatDuplicate_MPIAIJ, 2260 0, 2261 0, 2262 0, 2263 0, 2264 /*40*/ MatAXPY_MPIAIJ, 2265 MatGetSubMatrices_MPIAIJ, 2266 MatIncreaseOverlap_MPIAIJ, 2267 MatGetValues_MPIAIJ, 2268 MatCopy_MPIAIJ, 2269 /*45*/ 0, 2270 MatScale_MPIAIJ, 2271 0, 2272 0, 2273 0, 2274 /*50*/ MatSetBlockSize_MPIAIJ, 2275 0, 2276 0, 2277 0, 2278 0, 2279 /*55*/ MatFDColoringCreate_MPIAIJ, 2280 0, 2281 MatSetUnfactored_MPIAIJ, 2282 MatPermute_MPIAIJ, 2283 0, 2284 /*60*/ MatGetSubMatrix_MPIAIJ, 2285 MatDestroy_MPIAIJ, 2286 MatView_MPIAIJ, 2287 0, 2288 0, 2289 /*65*/ 0, 2290 0, 2291 0, 2292 0, 2293 0, 2294 /*70*/ 0, 2295 0, 2296 MatSetColoring_MPIAIJ, 2297 #if defined(PETSC_HAVE_ADIC) 2298 MatSetValuesAdic_MPIAIJ, 2299 #else 2300 0, 2301 #endif 2302 MatSetValuesAdifor_MPIAIJ, 2303 /*75*/ 0, 2304 0, 2305 0, 2306 0, 2307 0, 2308 /*80*/ 0, 2309 0, 2310 0, 2311 0, 2312 /*84*/ MatLoad_MPIAIJ, 2313 0, 2314 0, 2315 0, 2316 0, 2317 0, 2318 /*90*/ MatMatMult_MPIAIJ_MPIAIJ, 2319 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2320 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2321 MatPtAP_Basic, 2322 MatPtAPSymbolic_MPIAIJ, 2323 /*95*/ MatPtAPNumeric_MPIAIJ, 2324 0, 2325 0, 2326 0, 2327 0, 2328 /*100*/0, 2329 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2330 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2331 MatConjugate_MPIAIJ, 2332 0, 2333 /*105*/MatSetValuesRow_MPIAIJ, 2334 MatRealPart_MPIAIJ, 2335 MatImaginaryPart_MPIAIJ, 2336 0, 2337 0, 2338 /*110*/0, 2339 MatGetRedundantMatrix_MPIAIJ, 2340 MatGetRowMin_MPIAIJ, 2341 0, 2342 0, 2343 /*115*/MatGetSeqNonzerostructure_MPIAIJ}; 2344 2345 /* ----------------------------------------------------------------------------------------*/ 2346 2347 EXTERN_C_BEGIN 2348 #undef __FUNCT__ 2349 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2350 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2351 { 2352 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2353 PetscErrorCode ierr; 2354 2355 PetscFunctionBegin; 2356 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2357 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2358 PetscFunctionReturn(0); 2359 } 2360 EXTERN_C_END 2361 2362 EXTERN_C_BEGIN 2363 #undef __FUNCT__ 2364 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2365 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2366 { 2367 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2368 PetscErrorCode ierr; 2369 2370 PetscFunctionBegin; 2371 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2372 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2373 PetscFunctionReturn(0); 2374 } 2375 EXTERN_C_END 2376 2377 #include "petscpc.h" 2378 EXTERN_C_BEGIN 2379 #undef __FUNCT__ 2380 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2381 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2382 { 2383 Mat_MPIAIJ *b; 2384 PetscErrorCode ierr; 2385 PetscInt i; 2386 2387 PetscFunctionBegin; 2388 B->preallocated = PETSC_TRUE; 2389 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2390 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2391 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2392 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2393 2394 B->rmap.bs = B->cmap.bs = 1; 2395 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2396 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2397 if (d_nnz) { 2398 for (i=0; i<B->rmap.n; i++) { 2399 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than 0: local row %D value %D",i,d_nnz[i]); 2400 } 2401 } 2402 if (o_nnz) { 2403 for (i=0; i<B->rmap.n; i++) { 2404 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than 0: local row %D value %D",i,o_nnz[i]); 2405 } 2406 } 2407 b = (Mat_MPIAIJ*)B->data; 2408 2409 /* Explicitly create 2 MATSEQAIJ matrices. */ 2410 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2411 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2412 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2413 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2414 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2415 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2416 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2417 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2418 2419 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2420 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2421 2422 PetscFunctionReturn(0); 2423 } 2424 EXTERN_C_END 2425 2426 #undef __FUNCT__ 2427 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2428 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2429 { 2430 Mat mat; 2431 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2432 PetscErrorCode ierr; 2433 2434 PetscFunctionBegin; 2435 *newmat = 0; 2436 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2437 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2438 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2439 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2440 a = (Mat_MPIAIJ*)mat->data; 2441 2442 mat->factor = matin->factor; 2443 mat->rmap.bs = matin->rmap.bs; 2444 mat->assembled = PETSC_TRUE; 2445 mat->insertmode = NOT_SET_VALUES; 2446 mat->preallocated = PETSC_TRUE; 2447 2448 a->size = oldmat->size; 2449 a->rank = oldmat->rank; 2450 a->donotstash = oldmat->donotstash; 2451 a->roworiented = oldmat->roworiented; 2452 a->rowindices = 0; 2453 a->rowvalues = 0; 2454 a->getrowactive = PETSC_FALSE; 2455 2456 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2457 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2458 2459 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2460 if (oldmat->colmap) { 2461 #if defined (PETSC_USE_CTABLE) 2462 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2463 #else 2464 ierr = PetscMalloc((mat->cmap.N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2465 ierr = PetscLogObjectMemory(mat,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2466 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2467 #endif 2468 } else a->colmap = 0; 2469 if (oldmat->garray) { 2470 PetscInt len; 2471 len = oldmat->B->cmap.n; 2472 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2473 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2474 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2475 } else a->garray = 0; 2476 2477 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2478 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2479 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2480 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2481 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2482 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2483 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2484 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2485 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2486 *newmat = mat; 2487 PetscFunctionReturn(0); 2488 } 2489 2490 #include "petscsys.h" 2491 2492 #undef __FUNCT__ 2493 #define __FUNCT__ "MatLoad_MPIAIJ" 2494 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2495 { 2496 Mat A; 2497 PetscScalar *vals,*svals; 2498 MPI_Comm comm = ((PetscObject)viewer)->comm; 2499 MPI_Status status; 2500 PetscErrorCode ierr; 2501 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2502 PetscInt i,nz,j,rstart,rend,mmax; 2503 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2504 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2505 PetscInt cend,cstart,n,*rowners; 2506 int fd; 2507 2508 PetscFunctionBegin; 2509 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2510 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2511 if (!rank) { 2512 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2513 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2514 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2515 } 2516 2517 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2518 M = header[1]; N = header[2]; 2519 /* determine ownership of all rows */ 2520 m = M/size + ((M % size) > rank); 2521 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2522 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2523 2524 /* First process needs enough room for process with most rows */ 2525 if (!rank) { 2526 mmax = rowners[1]; 2527 for (i=2; i<size; i++) { 2528 mmax = PetscMax(mmax,rowners[i]); 2529 } 2530 } else mmax = m; 2531 2532 rowners[0] = 0; 2533 for (i=2; i<=size; i++) { 2534 rowners[i] += rowners[i-1]; 2535 } 2536 rstart = rowners[rank]; 2537 rend = rowners[rank+1]; 2538 2539 /* distribute row lengths to all processors */ 2540 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2541 if (!rank) { 2542 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2543 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2544 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2545 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2546 for (j=0; j<m; j++) { 2547 procsnz[0] += ourlens[j]; 2548 } 2549 for (i=1; i<size; i++) { 2550 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2551 /* calculate the number of nonzeros on each processor */ 2552 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2553 procsnz[i] += rowlengths[j]; 2554 } 2555 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2556 } 2557 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2558 } else { 2559 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2560 } 2561 2562 if (!rank) { 2563 /* determine max buffer needed and allocate it */ 2564 maxnz = 0; 2565 for (i=0; i<size; i++) { 2566 maxnz = PetscMax(maxnz,procsnz[i]); 2567 } 2568 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2569 2570 /* read in my part of the matrix column indices */ 2571 nz = procsnz[0]; 2572 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2573 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2574 2575 /* read in every one elses and ship off */ 2576 for (i=1; i<size; i++) { 2577 nz = procsnz[i]; 2578 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2579 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2580 } 2581 ierr = PetscFree(cols);CHKERRQ(ierr); 2582 } else { 2583 /* determine buffer space needed for message */ 2584 nz = 0; 2585 for (i=0; i<m; i++) { 2586 nz += ourlens[i]; 2587 } 2588 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2589 2590 /* receive message of column indices*/ 2591 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2592 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2593 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2594 } 2595 2596 /* determine column ownership if matrix is not square */ 2597 if (N != M) { 2598 n = N/size + ((N % size) > rank); 2599 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2600 cstart = cend - n; 2601 } else { 2602 cstart = rstart; 2603 cend = rend; 2604 n = cend - cstart; 2605 } 2606 2607 /* loop over local rows, determining number of off diagonal entries */ 2608 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2609 jj = 0; 2610 for (i=0; i<m; i++) { 2611 for (j=0; j<ourlens[i]; j++) { 2612 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2613 jj++; 2614 } 2615 } 2616 2617 /* create our matrix */ 2618 for (i=0; i<m; i++) { 2619 ourlens[i] -= offlens[i]; 2620 } 2621 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2622 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2623 ierr = MatSetType(A,type);CHKERRQ(ierr); 2624 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2625 2626 for (i=0; i<m; i++) { 2627 ourlens[i] += offlens[i]; 2628 } 2629 2630 if (!rank) { 2631 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2632 2633 /* read in my part of the matrix numerical values */ 2634 nz = procsnz[0]; 2635 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2636 2637 /* insert into matrix */ 2638 jj = rstart; 2639 smycols = mycols; 2640 svals = vals; 2641 for (i=0; i<m; i++) { 2642 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2643 smycols += ourlens[i]; 2644 svals += ourlens[i]; 2645 jj++; 2646 } 2647 2648 /* read in other processors and ship out */ 2649 for (i=1; i<size; i++) { 2650 nz = procsnz[i]; 2651 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2652 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2653 } 2654 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2655 } else { 2656 /* receive numeric values */ 2657 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2658 2659 /* receive message of values*/ 2660 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2661 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2662 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2663 2664 /* insert into matrix */ 2665 jj = rstart; 2666 smycols = mycols; 2667 svals = vals; 2668 for (i=0; i<m; i++) { 2669 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2670 smycols += ourlens[i]; 2671 svals += ourlens[i]; 2672 jj++; 2673 } 2674 } 2675 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2676 ierr = PetscFree(vals);CHKERRQ(ierr); 2677 ierr = PetscFree(mycols);CHKERRQ(ierr); 2678 ierr = PetscFree(rowners);CHKERRQ(ierr); 2679 2680 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2681 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2682 *newmat = A; 2683 PetscFunctionReturn(0); 2684 } 2685 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2688 /* 2689 Not great since it makes two copies of the submatrix, first an SeqAIJ 2690 in local and then by concatenating the local matrices the end result. 2691 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2692 */ 2693 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2694 { 2695 PetscErrorCode ierr; 2696 PetscMPIInt rank,size; 2697 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 2698 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2699 Mat *local,M,Mreuse; 2700 PetscScalar *vwork,*aa; 2701 MPI_Comm comm = ((PetscObject)mat)->comm; 2702 Mat_SeqAIJ *aij; 2703 2704 2705 PetscFunctionBegin; 2706 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2707 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2708 2709 if (call == MAT_REUSE_MATRIX) { 2710 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2711 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2712 local = &Mreuse; 2713 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2714 } else { 2715 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2716 Mreuse = *local; 2717 ierr = PetscFree(local);CHKERRQ(ierr); 2718 } 2719 2720 /* 2721 m - number of local rows 2722 n - number of columns (same on all processors) 2723 rstart - first row in new global matrix generated 2724 */ 2725 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2726 if (call == MAT_INITIAL_MATRIX) { 2727 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2728 ii = aij->i; 2729 jj = aij->j; 2730 2731 /* 2732 Determine the number of non-zeros in the diagonal and off-diagonal 2733 portions of the matrix in order to do correct preallocation 2734 */ 2735 2736 /* first get start and end of "diagonal" columns */ 2737 if (csize == PETSC_DECIDE) { 2738 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2739 if (mglobal == n) { /* square matrix */ 2740 nlocal = m; 2741 } else { 2742 nlocal = n/size + ((n % size) > rank); 2743 } 2744 } else { 2745 nlocal = csize; 2746 } 2747 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2748 rstart = rend - nlocal; 2749 if (rank == size - 1 && rend != n) { 2750 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2751 } 2752 2753 /* next, compute all the lengths */ 2754 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2755 olens = dlens + m; 2756 for (i=0; i<m; i++) { 2757 jend = ii[i+1] - ii[i]; 2758 olen = 0; 2759 dlen = 0; 2760 for (j=0; j<jend; j++) { 2761 if (*jj < rstart || *jj >= rend) olen++; 2762 else dlen++; 2763 jj++; 2764 } 2765 olens[i] = olen; 2766 dlens[i] = dlen; 2767 } 2768 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2769 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 2770 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2771 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 2772 ierr = PetscFree(dlens);CHKERRQ(ierr); 2773 } else { 2774 PetscInt ml,nl; 2775 2776 M = *newmat; 2777 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2778 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2779 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2780 /* 2781 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2782 rather than the slower MatSetValues(). 2783 */ 2784 M->was_assembled = PETSC_TRUE; 2785 M->assembled = PETSC_FALSE; 2786 } 2787 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2788 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2789 ii = aij->i; 2790 jj = aij->j; 2791 aa = aij->a; 2792 for (i=0; i<m; i++) { 2793 row = rstart + i; 2794 nz = ii[i+1] - ii[i]; 2795 cwork = jj; jj += nz; 2796 vwork = aa; aa += nz; 2797 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2798 } 2799 2800 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2801 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2802 *newmat = M; 2803 2804 /* save submatrix used in processor for next request */ 2805 if (call == MAT_INITIAL_MATRIX) { 2806 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2807 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2808 } 2809 2810 PetscFunctionReturn(0); 2811 } 2812 2813 EXTERN_C_BEGIN 2814 #undef __FUNCT__ 2815 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 2816 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 2817 { 2818 PetscInt m,cstart, cend,j,nnz,i,d; 2819 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 2820 const PetscInt *JJ; 2821 PetscScalar *values; 2822 PetscErrorCode ierr; 2823 2824 PetscFunctionBegin; 2825 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 2826 2827 B->rmap.bs = B->cmap.bs = 1; 2828 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2829 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2830 m = B->rmap.n; 2831 cstart = B->cmap.rstart; 2832 cend = B->cmap.rend; 2833 rstart = B->rmap.rstart; 2834 2835 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2836 o_nnz = d_nnz + m; 2837 2838 #if defined(PETSC_USE_DEBUGGING) 2839 for (i=0; i<m; i++) { 2840 nnz = Ii[i+1]- Ii[i]; 2841 JJ = J + Ii[i]; 2842 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 2843 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 2844 if (nnz && (JJ[nnz-1] >= B->cmap.N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap.N); 2845 for (j=1; j<nnz; j++) { 2846 if (JJ[i] <= JJ[i-1]) SETERRRQ(PETSC_ERR_ARG_WRONGSTATE,"Row %D has unsorted column index at %D location in column indices",i,j); 2847 } 2848 } 2849 #endif 2850 2851 for (i=0; i<m; i++) { 2852 nnz = Ii[i+1]- Ii[i]; 2853 JJ = J + Ii[i]; 2854 nnz_max = PetscMax(nnz_max,nnz); 2855 for (j=0; j<nnz; j++) { 2856 if (*JJ >= cstart) break; 2857 JJ++; 2858 } 2859 d = 0; 2860 for (; j<nnz; j++) { 2861 if (*JJ++ >= cend) break; 2862 d++; 2863 } 2864 d_nnz[i] = d; 2865 o_nnz[i] = nnz - d; 2866 } 2867 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2868 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2869 2870 if (v) values = (PetscScalar*)v; 2871 else { 2872 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2873 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2874 } 2875 2876 for (i=0; i<m; i++) { 2877 ii = i + rstart; 2878 nnz = Ii[i+1]- Ii[i]; 2879 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 2880 } 2881 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2882 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2883 2884 if (!v) { 2885 ierr = PetscFree(values);CHKERRQ(ierr); 2886 } 2887 PetscFunctionReturn(0); 2888 } 2889 EXTERN_C_END 2890 2891 #undef __FUNCT__ 2892 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 2893 /*@ 2894 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2895 (the default parallel PETSc format). 2896 2897 Collective on MPI_Comm 2898 2899 Input Parameters: 2900 + B - the matrix 2901 . i - the indices into j for the start of each local row (starts with zero) 2902 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2903 - v - optional values in the matrix 2904 2905 Level: developer 2906 2907 Notes: 2908 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2909 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2910 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2911 2912 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2913 2914 The format which is used for the sparse matrix input, is equivalent to a 2915 row-major ordering.. i.e for the following matrix, the input data expected is 2916 as shown: 2917 2918 1 0 0 2919 2 0 3 P0 2920 ------- 2921 4 5 6 P1 2922 2923 Process0 [P0]: rows_owned=[0,1] 2924 i = {0,1,3} [size = nrow+1 = 2+1] 2925 j = {0,0,2} [size = nz = 6] 2926 v = {1,2,3} [size = nz = 6] 2927 2928 Process1 [P1]: rows_owned=[2] 2929 i = {0,3} [size = nrow+1 = 1+1] 2930 j = {0,1,2} [size = nz = 6] 2931 v = {4,5,6} [size = nz = 6] 2932 2933 The column indices for each row MUST be sorted. 2934 2935 .keywords: matrix, aij, compressed row, sparse, parallel 2936 2937 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 2938 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 2939 @*/ 2940 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2941 { 2942 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 2943 2944 PetscFunctionBegin; 2945 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2946 if (f) { 2947 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 2948 } 2949 PetscFunctionReturn(0); 2950 } 2951 2952 #undef __FUNCT__ 2953 #define __FUNCT__ "MatMPIAIJSetPreallocation" 2954 /*@C 2955 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 2956 (the default parallel PETSc format). For good matrix assembly performance 2957 the user should preallocate the matrix storage by setting the parameters 2958 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2959 performance can be increased by more than a factor of 50. 2960 2961 Collective on MPI_Comm 2962 2963 Input Parameters: 2964 + A - the matrix 2965 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2966 (same value is used for all local rows) 2967 . d_nnz - array containing the number of nonzeros in the various rows of the 2968 DIAGONAL portion of the local submatrix (possibly different for each row) 2969 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2970 The size of this array is equal to the number of local rows, i.e 'm'. 2971 You must leave room for the diagonal entry even if it is zero. 2972 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2973 submatrix (same value is used for all local rows). 2974 - o_nnz - array containing the number of nonzeros in the various rows of the 2975 OFF-DIAGONAL portion of the local submatrix (possibly different for 2976 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2977 structure. The size of this array is equal to the number 2978 of local rows, i.e 'm'. 2979 2980 If the *_nnz parameter is given then the *_nz parameter is ignored 2981 2982 The AIJ format (also called the Yale sparse matrix format or 2983 compressed row storage (CSR)), is fully compatible with standard Fortran 77 2984 storage. The stored row and column indices begin with zero. See the users manual for details. 2985 2986 The parallel matrix is partitioned such that the first m0 rows belong to 2987 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2988 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2989 2990 The DIAGONAL portion of the local submatrix of a processor can be defined 2991 as the submatrix which is obtained by extraction the part corresponding 2992 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2993 first row that belongs to the processor, and r2 is the last row belonging 2994 to the this processor. This is a square mxm matrix. The remaining portion 2995 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2996 2997 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2998 2999 Example usage: 3000 3001 Consider the following 8x8 matrix with 34 non-zero values, that is 3002 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3003 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3004 as follows: 3005 3006 .vb 3007 1 2 0 | 0 3 0 | 0 4 3008 Proc0 0 5 6 | 7 0 0 | 8 0 3009 9 0 10 | 11 0 0 | 12 0 3010 ------------------------------------- 3011 13 0 14 | 15 16 17 | 0 0 3012 Proc1 0 18 0 | 19 20 21 | 0 0 3013 0 0 0 | 22 23 0 | 24 0 3014 ------------------------------------- 3015 Proc2 25 26 27 | 0 0 28 | 29 0 3016 30 0 0 | 31 32 33 | 0 34 3017 .ve 3018 3019 This can be represented as a collection of submatrices as: 3020 3021 .vb 3022 A B C 3023 D E F 3024 G H I 3025 .ve 3026 3027 Where the submatrices A,B,C are owned by proc0, D,E,F are 3028 owned by proc1, G,H,I are owned by proc2. 3029 3030 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3031 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3032 The 'M','N' parameters are 8,8, and have the same values on all procs. 3033 3034 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3035 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3036 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3037 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3038 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3039 matrix, ans [DF] as another SeqAIJ matrix. 3040 3041 When d_nz, o_nz parameters are specified, d_nz storage elements are 3042 allocated for every row of the local diagonal submatrix, and o_nz 3043 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3044 One way to choose d_nz and o_nz is to use the max nonzerors per local 3045 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3046 In this case, the values of d_nz,o_nz are: 3047 .vb 3048 proc0 : dnz = 2, o_nz = 2 3049 proc1 : dnz = 3, o_nz = 2 3050 proc2 : dnz = 1, o_nz = 4 3051 .ve 3052 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3053 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3054 for proc3. i.e we are using 12+15+10=37 storage locations to store 3055 34 values. 3056 3057 When d_nnz, o_nnz parameters are specified, the storage is specified 3058 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3059 In the above case the values for d_nnz,o_nnz are: 3060 .vb 3061 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3062 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3063 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3064 .ve 3065 Here the space allocated is sum of all the above values i.e 34, and 3066 hence pre-allocation is perfect. 3067 3068 Level: intermediate 3069 3070 .keywords: matrix, aij, compressed row, sparse, parallel 3071 3072 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3073 MPIAIJ 3074 @*/ 3075 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3076 { 3077 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3078 3079 PetscFunctionBegin; 3080 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3081 if (f) { 3082 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3083 } 3084 PetscFunctionReturn(0); 3085 } 3086 3087 #undef __FUNCT__ 3088 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3089 /*@ 3090 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3091 CSR format the local rows. 3092 3093 Collective on MPI_Comm 3094 3095 Input Parameters: 3096 + comm - MPI communicator 3097 . m - number of local rows (Cannot be PETSC_DECIDE) 3098 . n - This value should be the same as the local size used in creating the 3099 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3100 calculated if N is given) For square matrices n is almost always m. 3101 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3102 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3103 . i - row indices 3104 . j - column indices 3105 - a - matrix values 3106 3107 Output Parameter: 3108 . mat - the matrix 3109 3110 Level: intermediate 3111 3112 Notes: 3113 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3114 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3115 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3116 3117 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3118 3119 The format which is used for the sparse matrix input, is equivalent to a 3120 row-major ordering.. i.e for the following matrix, the input data expected is 3121 as shown: 3122 3123 1 0 0 3124 2 0 3 P0 3125 ------- 3126 4 5 6 P1 3127 3128 Process0 [P0]: rows_owned=[0,1] 3129 i = {0,1,3} [size = nrow+1 = 2+1] 3130 j = {0,0,2} [size = nz = 6] 3131 v = {1,2,3} [size = nz = 6] 3132 3133 Process1 [P1]: rows_owned=[2] 3134 i = {0,3} [size = nrow+1 = 1+1] 3135 j = {0,1,2} [size = nz = 6] 3136 v = {4,5,6} [size = nz = 6] 3137 3138 .keywords: matrix, aij, compressed row, sparse, parallel 3139 3140 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3141 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3142 @*/ 3143 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3144 { 3145 PetscErrorCode ierr; 3146 3147 PetscFunctionBegin; 3148 if (i[0]) { 3149 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3150 } 3151 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3152 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3153 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3154 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3155 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3156 PetscFunctionReturn(0); 3157 } 3158 3159 #undef __FUNCT__ 3160 #define __FUNCT__ "MatCreateMPIAIJ" 3161 /*@C 3162 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3163 (the default parallel PETSc format). For good matrix assembly performance 3164 the user should preallocate the matrix storage by setting the parameters 3165 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3166 performance can be increased by more than a factor of 50. 3167 3168 Collective on MPI_Comm 3169 3170 Input Parameters: 3171 + comm - MPI communicator 3172 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3173 This value should be the same as the local size used in creating the 3174 y vector for the matrix-vector product y = Ax. 3175 . n - This value should be the same as the local size used in creating the 3176 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3177 calculated if N is given) For square matrices n is almost always m. 3178 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3179 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3180 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3181 (same value is used for all local rows) 3182 . d_nnz - array containing the number of nonzeros in the various rows of the 3183 DIAGONAL portion of the local submatrix (possibly different for each row) 3184 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3185 The size of this array is equal to the number of local rows, i.e 'm'. 3186 You must leave room for the diagonal entry even if it is zero. 3187 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3188 submatrix (same value is used for all local rows). 3189 - o_nnz - array containing the number of nonzeros in the various rows of the 3190 OFF-DIAGONAL portion of the local submatrix (possibly different for 3191 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3192 structure. The size of this array is equal to the number 3193 of local rows, i.e 'm'. 3194 3195 Output Parameter: 3196 . A - the matrix 3197 3198 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3199 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3200 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3201 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3202 3203 Notes: 3204 If the *_nnz parameter is given then the *_nz parameter is ignored 3205 3206 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3207 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3208 storage requirements for this matrix. 3209 3210 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3211 processor than it must be used on all processors that share the object for 3212 that argument. 3213 3214 The user MUST specify either the local or global matrix dimensions 3215 (possibly both). 3216 3217 The parallel matrix is partitioned across processors such that the 3218 first m0 rows belong to process 0, the next m1 rows belong to 3219 process 1, the next m2 rows belong to process 2 etc.. where 3220 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3221 values corresponding to [m x N] submatrix. 3222 3223 The columns are logically partitioned with the n0 columns belonging 3224 to 0th partition, the next n1 columns belonging to the next 3225 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3226 3227 The DIAGONAL portion of the local submatrix on any given processor 3228 is the submatrix corresponding to the rows and columns m,n 3229 corresponding to the given processor. i.e diagonal matrix on 3230 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3231 etc. The remaining portion of the local submatrix [m x (N-n)] 3232 constitute the OFF-DIAGONAL portion. The example below better 3233 illustrates this concept. 3234 3235 For a square global matrix we define each processor's diagonal portion 3236 to be its local rows and the corresponding columns (a square submatrix); 3237 each processor's off-diagonal portion encompasses the remainder of the 3238 local matrix (a rectangular submatrix). 3239 3240 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3241 3242 When calling this routine with a single process communicator, a matrix of 3243 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3244 type of communicator, use the construction mechanism: 3245 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3246 3247 By default, this format uses inodes (identical nodes) when possible. 3248 We search for consecutive rows with the same nonzero structure, thereby 3249 reusing matrix information to achieve increased efficiency. 3250 3251 Options Database Keys: 3252 + -mat_no_inode - Do not use inodes 3253 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3254 - -mat_aij_oneindex - Internally use indexing starting at 1 3255 rather than 0. Note that when calling MatSetValues(), 3256 the user still MUST index entries starting at 0! 3257 3258 3259 Example usage: 3260 3261 Consider the following 8x8 matrix with 34 non-zero values, that is 3262 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3263 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3264 as follows: 3265 3266 .vb 3267 1 2 0 | 0 3 0 | 0 4 3268 Proc0 0 5 6 | 7 0 0 | 8 0 3269 9 0 10 | 11 0 0 | 12 0 3270 ------------------------------------- 3271 13 0 14 | 15 16 17 | 0 0 3272 Proc1 0 18 0 | 19 20 21 | 0 0 3273 0 0 0 | 22 23 0 | 24 0 3274 ------------------------------------- 3275 Proc2 25 26 27 | 0 0 28 | 29 0 3276 30 0 0 | 31 32 33 | 0 34 3277 .ve 3278 3279 This can be represented as a collection of submatrices as: 3280 3281 .vb 3282 A B C 3283 D E F 3284 G H I 3285 .ve 3286 3287 Where the submatrices A,B,C are owned by proc0, D,E,F are 3288 owned by proc1, G,H,I are owned by proc2. 3289 3290 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3291 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3292 The 'M','N' parameters are 8,8, and have the same values on all procs. 3293 3294 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3295 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3296 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3297 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3298 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3299 matrix, ans [DF] as another SeqAIJ matrix. 3300 3301 When d_nz, o_nz parameters are specified, d_nz storage elements are 3302 allocated for every row of the local diagonal submatrix, and o_nz 3303 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3304 One way to choose d_nz and o_nz is to use the max nonzerors per local 3305 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3306 In this case, the values of d_nz,o_nz are: 3307 .vb 3308 proc0 : dnz = 2, o_nz = 2 3309 proc1 : dnz = 3, o_nz = 2 3310 proc2 : dnz = 1, o_nz = 4 3311 .ve 3312 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3313 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3314 for proc3. i.e we are using 12+15+10=37 storage locations to store 3315 34 values. 3316 3317 When d_nnz, o_nnz parameters are specified, the storage is specified 3318 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3319 In the above case the values for d_nnz,o_nnz are: 3320 .vb 3321 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3322 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3323 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3324 .ve 3325 Here the space allocated is sum of all the above values i.e 34, and 3326 hence pre-allocation is perfect. 3327 3328 Level: intermediate 3329 3330 .keywords: matrix, aij, compressed row, sparse, parallel 3331 3332 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3333 MPIAIJ, MatCreateMPIAIJWithArrays() 3334 @*/ 3335 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3336 { 3337 PetscErrorCode ierr; 3338 PetscMPIInt size; 3339 3340 PetscFunctionBegin; 3341 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3342 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3343 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3344 if (size > 1) { 3345 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3346 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3347 } else { 3348 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3349 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3350 } 3351 PetscFunctionReturn(0); 3352 } 3353 3354 #undef __FUNCT__ 3355 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3356 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3357 { 3358 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3359 3360 PetscFunctionBegin; 3361 *Ad = a->A; 3362 *Ao = a->B; 3363 *colmap = a->garray; 3364 PetscFunctionReturn(0); 3365 } 3366 3367 #undef __FUNCT__ 3368 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3369 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3370 { 3371 PetscErrorCode ierr; 3372 PetscInt i; 3373 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3374 3375 PetscFunctionBegin; 3376 if (coloring->ctype == IS_COLORING_GLOBAL) { 3377 ISColoringValue *allcolors,*colors; 3378 ISColoring ocoloring; 3379 3380 /* set coloring for diagonal portion */ 3381 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3382 3383 /* set coloring for off-diagonal portion */ 3384 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3385 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3386 for (i=0; i<a->B->cmap.n; i++) { 3387 colors[i] = allcolors[a->garray[i]]; 3388 } 3389 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3390 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3391 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3392 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3393 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3394 ISColoringValue *colors; 3395 PetscInt *larray; 3396 ISColoring ocoloring; 3397 3398 /* set coloring for diagonal portion */ 3399 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3400 for (i=0; i<a->A->cmap.n; i++) { 3401 larray[i] = i + A->cmap.rstart; 3402 } 3403 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap.n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3404 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3405 for (i=0; i<a->A->cmap.n; i++) { 3406 colors[i] = coloring->colors[larray[i]]; 3407 } 3408 ierr = PetscFree(larray);CHKERRQ(ierr); 3409 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3410 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3411 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3412 3413 /* set coloring for off-diagonal portion */ 3414 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3415 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap.n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3416 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3417 for (i=0; i<a->B->cmap.n; i++) { 3418 colors[i] = coloring->colors[larray[i]]; 3419 } 3420 ierr = PetscFree(larray);CHKERRQ(ierr); 3421 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3422 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3423 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3424 } else { 3425 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3426 } 3427 3428 PetscFunctionReturn(0); 3429 } 3430 3431 #if defined(PETSC_HAVE_ADIC) 3432 #undef __FUNCT__ 3433 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3434 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3435 { 3436 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3437 PetscErrorCode ierr; 3438 3439 PetscFunctionBegin; 3440 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3441 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3442 PetscFunctionReturn(0); 3443 } 3444 #endif 3445 3446 #undef __FUNCT__ 3447 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3448 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3449 { 3450 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3451 PetscErrorCode ierr; 3452 3453 PetscFunctionBegin; 3454 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3455 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3456 PetscFunctionReturn(0); 3457 } 3458 3459 #undef __FUNCT__ 3460 #define __FUNCT__ "MatMerge" 3461 /*@ 3462 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3463 matrices from each processor 3464 3465 Collective on MPI_Comm 3466 3467 Input Parameters: 3468 + comm - the communicators the parallel matrix will live on 3469 . inmat - the input sequential matrices 3470 . n - number of local columns (or PETSC_DECIDE) 3471 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3472 3473 Output Parameter: 3474 . outmat - the parallel matrix generated 3475 3476 Level: advanced 3477 3478 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3479 3480 @*/ 3481 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3482 { 3483 PetscErrorCode ierr; 3484 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3485 PetscInt *indx; 3486 PetscScalar *values; 3487 3488 PetscFunctionBegin; 3489 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3490 if (scall == MAT_INITIAL_MATRIX){ 3491 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3492 if (n == PETSC_DECIDE){ 3493 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3494 } 3495 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3496 rstart -= m; 3497 3498 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3499 for (i=0;i<m;i++) { 3500 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3501 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3502 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3503 } 3504 /* This routine will ONLY return MPIAIJ type matrix */ 3505 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3506 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3507 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3508 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3509 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3510 3511 } else if (scall == MAT_REUSE_MATRIX){ 3512 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3513 } else { 3514 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3515 } 3516 3517 for (i=0;i<m;i++) { 3518 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3519 Ii = i + rstart; 3520 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3521 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3522 } 3523 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3524 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3525 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3526 3527 PetscFunctionReturn(0); 3528 } 3529 3530 #undef __FUNCT__ 3531 #define __FUNCT__ "MatFileSplit" 3532 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3533 { 3534 PetscErrorCode ierr; 3535 PetscMPIInt rank; 3536 PetscInt m,N,i,rstart,nnz; 3537 size_t len; 3538 const PetscInt *indx; 3539 PetscViewer out; 3540 char *name; 3541 Mat B; 3542 const PetscScalar *values; 3543 3544 PetscFunctionBegin; 3545 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3546 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3547 /* Should this be the type of the diagonal block of A? */ 3548 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3549 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3550 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3551 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3552 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3553 for (i=0;i<m;i++) { 3554 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3555 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3556 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3557 } 3558 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3559 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3560 3561 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3562 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3563 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3564 sprintf(name,"%s.%d",outfile,rank); 3565 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3566 ierr = PetscFree(name); 3567 ierr = MatView(B,out);CHKERRQ(ierr); 3568 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3569 ierr = MatDestroy(B);CHKERRQ(ierr); 3570 PetscFunctionReturn(0); 3571 } 3572 3573 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3574 #undef __FUNCT__ 3575 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3576 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3577 { 3578 PetscErrorCode ierr; 3579 Mat_Merge_SeqsToMPI *merge; 3580 PetscContainer container; 3581 3582 PetscFunctionBegin; 3583 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3584 if (container) { 3585 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3586 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3587 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3588 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3589 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3590 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3591 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3592 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3593 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3594 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3595 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3596 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3597 3598 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3599 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3600 } 3601 ierr = PetscFree(merge);CHKERRQ(ierr); 3602 3603 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3604 PetscFunctionReturn(0); 3605 } 3606 3607 #include "src/mat/utils/freespace.h" 3608 #include "petscbt.h" 3609 3610 #undef __FUNCT__ 3611 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3612 /*@C 3613 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3614 matrices from each processor 3615 3616 Collective on MPI_Comm 3617 3618 Input Parameters: 3619 + comm - the communicators the parallel matrix will live on 3620 . seqmat - the input sequential matrices 3621 . m - number of local rows (or PETSC_DECIDE) 3622 . n - number of local columns (or PETSC_DECIDE) 3623 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3624 3625 Output Parameter: 3626 . mpimat - the parallel matrix generated 3627 3628 Level: advanced 3629 3630 Notes: 3631 The dimensions of the sequential matrix in each processor MUST be the same. 3632 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3633 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3634 @*/ 3635 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3636 { 3637 PetscErrorCode ierr; 3638 MPI_Comm comm=((PetscObject)mpimat)->comm; 3639 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3640 PetscMPIInt size,rank,taga,*len_s; 3641 PetscInt N=mpimat->cmap.N,i,j,*owners,*ai=a->i,*aj=a->j; 3642 PetscInt proc,m; 3643 PetscInt **buf_ri,**buf_rj; 3644 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3645 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3646 MPI_Request *s_waits,*r_waits; 3647 MPI_Status *status; 3648 MatScalar *aa=a->a,**abuf_r,*ba_i; 3649 Mat_Merge_SeqsToMPI *merge; 3650 PetscContainer container; 3651 3652 PetscFunctionBegin; 3653 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3654 3655 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3656 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3657 3658 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3659 if (container) { 3660 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3661 } 3662 bi = merge->bi; 3663 bj = merge->bj; 3664 buf_ri = merge->buf_ri; 3665 buf_rj = merge->buf_rj; 3666 3667 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3668 owners = merge->rowmap.range; 3669 len_s = merge->len_s; 3670 3671 /* send and recv matrix values */ 3672 /*-----------------------------*/ 3673 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3674 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3675 3676 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3677 for (proc=0,k=0; proc<size; proc++){ 3678 if (!len_s[proc]) continue; 3679 i = owners[proc]; 3680 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3681 k++; 3682 } 3683 3684 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3685 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3686 ierr = PetscFree(status);CHKERRQ(ierr); 3687 3688 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3689 ierr = PetscFree(r_waits);CHKERRQ(ierr); 3690 3691 /* insert mat values of mpimat */ 3692 /*----------------------------*/ 3693 ierr = PetscMalloc(N*sizeof(MatScalar),&ba_i);CHKERRQ(ierr); 3694 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3695 nextrow = buf_ri_k + merge->nrecv; 3696 nextai = nextrow + merge->nrecv; 3697 3698 for (k=0; k<merge->nrecv; k++){ 3699 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3700 nrows = *(buf_ri_k[k]); 3701 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 3702 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3703 } 3704 3705 /* set values of ba */ 3706 m = merge->rowmap.n; 3707 for (i=0; i<m; i++) { 3708 arow = owners[rank] + i; 3709 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 3710 bnzi = bi[i+1] - bi[i]; 3711 ierr = PetscMemzero(ba_i,bnzi*sizeof(MatScalar));CHKERRQ(ierr); 3712 3713 /* add local non-zero vals of this proc's seqmat into ba */ 3714 anzi = ai[arow+1] - ai[arow]; 3715 aj = a->j + ai[arow]; 3716 aa = a->a + ai[arow]; 3717 nextaj = 0; 3718 for (j=0; nextaj<anzi; j++){ 3719 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3720 ba_i[j] += aa[nextaj++]; 3721 } 3722 } 3723 3724 /* add received vals into ba */ 3725 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3726 /* i-th row */ 3727 if (i == *nextrow[k]) { 3728 anzi = *(nextai[k]+1) - *nextai[k]; 3729 aj = buf_rj[k] + *(nextai[k]); 3730 aa = abuf_r[k] + *(nextai[k]); 3731 nextaj = 0; 3732 for (j=0; nextaj<anzi; j++){ 3733 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3734 ba_i[j] += aa[nextaj++]; 3735 } 3736 } 3737 nextrow[k]++; nextai[k]++; 3738 } 3739 } 3740 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 3741 } 3742 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3743 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3744 3745 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 3746 ierr = PetscFree(ba_i);CHKERRQ(ierr); 3747 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3748 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3749 PetscFunctionReturn(0); 3750 } 3751 3752 #undef __FUNCT__ 3753 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 3754 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 3755 { 3756 PetscErrorCode ierr; 3757 Mat B_mpi; 3758 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3759 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 3760 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 3761 PetscInt M=seqmat->rmap.n,N=seqmat->cmap.n,i,*owners,*ai=a->i,*aj=a->j; 3762 PetscInt len,proc,*dnz,*onz; 3763 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 3764 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 3765 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 3766 MPI_Status *status; 3767 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 3768 PetscBT lnkbt; 3769 Mat_Merge_SeqsToMPI *merge; 3770 PetscContainer container; 3771 3772 PetscFunctionBegin; 3773 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3774 3775 /* make sure it is a PETSc comm */ 3776 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 3777 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3778 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3779 3780 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 3781 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3782 3783 /* determine row ownership */ 3784 /*---------------------------------------------------------*/ 3785 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 3786 merge->rowmap.n = m; 3787 merge->rowmap.N = M; 3788 merge->rowmap.bs = 1; 3789 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 3790 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 3791 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 3792 3793 m = merge->rowmap.n; 3794 M = merge->rowmap.N; 3795 owners = merge->rowmap.range; 3796 3797 /* determine the number of messages to send, their lengths */ 3798 /*---------------------------------------------------------*/ 3799 len_s = merge->len_s; 3800 3801 len = 0; /* length of buf_si[] */ 3802 merge->nsend = 0; 3803 for (proc=0; proc<size; proc++){ 3804 len_si[proc] = 0; 3805 if (proc == rank){ 3806 len_s[proc] = 0; 3807 } else { 3808 len_si[proc] = owners[proc+1] - owners[proc] + 1; 3809 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 3810 } 3811 if (len_s[proc]) { 3812 merge->nsend++; 3813 nrows = 0; 3814 for (i=owners[proc]; i<owners[proc+1]; i++){ 3815 if (ai[i+1] > ai[i]) nrows++; 3816 } 3817 len_si[proc] = 2*(nrows+1); 3818 len += len_si[proc]; 3819 } 3820 } 3821 3822 /* determine the number and length of messages to receive for ij-structure */ 3823 /*-------------------------------------------------------------------------*/ 3824 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 3825 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 3826 3827 /* post the Irecv of j-structure */ 3828 /*-------------------------------*/ 3829 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 3830 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 3831 3832 /* post the Isend of j-structure */ 3833 /*--------------------------------*/ 3834 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 3835 sj_waits = si_waits + merge->nsend; 3836 3837 for (proc=0, k=0; proc<size; proc++){ 3838 if (!len_s[proc]) continue; 3839 i = owners[proc]; 3840 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 3841 k++; 3842 } 3843 3844 /* receives and sends of j-structure are complete */ 3845 /*------------------------------------------------*/ 3846 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 3847 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 3848 3849 /* send and recv i-structure */ 3850 /*---------------------------*/ 3851 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 3852 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 3853 3854 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 3855 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 3856 for (proc=0,k=0; proc<size; proc++){ 3857 if (!len_s[proc]) continue; 3858 /* form outgoing message for i-structure: 3859 buf_si[0]: nrows to be sent 3860 [1:nrows]: row index (global) 3861 [nrows+1:2*nrows+1]: i-structure index 3862 */ 3863 /*-------------------------------------------*/ 3864 nrows = len_si[proc]/2 - 1; 3865 buf_si_i = buf_si + nrows+1; 3866 buf_si[0] = nrows; 3867 buf_si_i[0] = 0; 3868 nrows = 0; 3869 for (i=owners[proc]; i<owners[proc+1]; i++){ 3870 anzi = ai[i+1] - ai[i]; 3871 if (anzi) { 3872 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 3873 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 3874 nrows++; 3875 } 3876 } 3877 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 3878 k++; 3879 buf_si += len_si[proc]; 3880 } 3881 3882 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 3883 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 3884 3885 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 3886 for (i=0; i<merge->nrecv; i++){ 3887 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 3888 } 3889 3890 ierr = PetscFree(len_si);CHKERRQ(ierr); 3891 ierr = PetscFree(len_ri);CHKERRQ(ierr); 3892 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 3893 ierr = PetscFree(si_waits);CHKERRQ(ierr); 3894 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 3895 ierr = PetscFree(buf_s);CHKERRQ(ierr); 3896 ierr = PetscFree(status);CHKERRQ(ierr); 3897 3898 /* compute a local seq matrix in each processor */ 3899 /*----------------------------------------------*/ 3900 /* allocate bi array and free space for accumulating nonzero column info */ 3901 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 3902 bi[0] = 0; 3903 3904 /* create and initialize a linked list */ 3905 nlnk = N+1; 3906 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3907 3908 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 3909 len = 0; 3910 len = ai[owners[rank+1]] - ai[owners[rank]]; 3911 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 3912 current_space = free_space; 3913 3914 /* determine symbolic info for each local row */ 3915 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3916 nextrow = buf_ri_k + merge->nrecv; 3917 nextai = nextrow + merge->nrecv; 3918 for (k=0; k<merge->nrecv; k++){ 3919 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3920 nrows = *buf_ri_k[k]; 3921 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 3922 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3923 } 3924 3925 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3926 len = 0; 3927 for (i=0;i<m;i++) { 3928 bnzi = 0; 3929 /* add local non-zero cols of this proc's seqmat into lnk */ 3930 arow = owners[rank] + i; 3931 anzi = ai[arow+1] - ai[arow]; 3932 aj = a->j + ai[arow]; 3933 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3934 bnzi += nlnk; 3935 /* add received col data into lnk */ 3936 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3937 if (i == *nextrow[k]) { /* i-th row */ 3938 anzi = *(nextai[k]+1) - *nextai[k]; 3939 aj = buf_rj[k] + *nextai[k]; 3940 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3941 bnzi += nlnk; 3942 nextrow[k]++; nextai[k]++; 3943 } 3944 } 3945 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 3946 3947 /* if free space is not available, make more free space */ 3948 if (current_space->local_remaining<bnzi) { 3949 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 3950 nspacedouble++; 3951 } 3952 /* copy data into free space, then initialize lnk */ 3953 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 3954 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 3955 3956 current_space->array += bnzi; 3957 current_space->local_used += bnzi; 3958 current_space->local_remaining -= bnzi; 3959 3960 bi[i+1] = bi[i] + bnzi; 3961 } 3962 3963 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3964 3965 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 3966 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 3967 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 3968 3969 /* create symbolic parallel matrix B_mpi */ 3970 /*---------------------------------------*/ 3971 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 3972 if (n==PETSC_DECIDE) { 3973 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 3974 } else { 3975 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3976 } 3977 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 3978 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 3979 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3980 3981 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 3982 B_mpi->assembled = PETSC_FALSE; 3983 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 3984 merge->bi = bi; 3985 merge->bj = bj; 3986 merge->buf_ri = buf_ri; 3987 merge->buf_rj = buf_rj; 3988 merge->coi = PETSC_NULL; 3989 merge->coj = PETSC_NULL; 3990 merge->owners_co = PETSC_NULL; 3991 3992 /* attach the supporting struct to B_mpi for reuse */ 3993 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 3994 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 3995 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 3996 *mpimat = B_mpi; 3997 3998 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 3999 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4000 PetscFunctionReturn(0); 4001 } 4002 4003 #undef __FUNCT__ 4004 #define __FUNCT__ "MatMerge_SeqsToMPI" 4005 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4006 { 4007 PetscErrorCode ierr; 4008 4009 PetscFunctionBegin; 4010 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4011 if (scall == MAT_INITIAL_MATRIX){ 4012 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4013 } 4014 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4015 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4016 PetscFunctionReturn(0); 4017 } 4018 4019 #undef __FUNCT__ 4020 #define __FUNCT__ "MatGetLocalMat" 4021 /*@ 4022 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4023 4024 Not Collective 4025 4026 Input Parameters: 4027 + A - the matrix 4028 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4029 4030 Output Parameter: 4031 . A_loc - the local sequential matrix generated 4032 4033 Level: developer 4034 4035 @*/ 4036 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4037 { 4038 PetscErrorCode ierr; 4039 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4040 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4041 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4042 PetscScalar *aa=a->a,*ba=b->a,*ca; 4043 PetscInt am=A->rmap.n,i,j,k,cstart=A->cmap.rstart; 4044 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4045 4046 PetscFunctionBegin; 4047 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4048 if (scall == MAT_INITIAL_MATRIX){ 4049 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4050 ci[0] = 0; 4051 for (i=0; i<am; i++){ 4052 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4053 } 4054 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4055 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4056 k = 0; 4057 for (i=0; i<am; i++) { 4058 ncols_o = bi[i+1] - bi[i]; 4059 ncols_d = ai[i+1] - ai[i]; 4060 /* off-diagonal portion of A */ 4061 for (jo=0; jo<ncols_o; jo++) { 4062 col = cmap[*bj]; 4063 if (col >= cstart) break; 4064 cj[k] = col; bj++; 4065 ca[k++] = *ba++; 4066 } 4067 /* diagonal portion of A */ 4068 for (j=0; j<ncols_d; j++) { 4069 cj[k] = cstart + *aj++; 4070 ca[k++] = *aa++; 4071 } 4072 /* off-diagonal portion of A */ 4073 for (j=jo; j<ncols_o; j++) { 4074 cj[k] = cmap[*bj++]; 4075 ca[k++] = *ba++; 4076 } 4077 } 4078 /* put together the new matrix */ 4079 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap.N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4080 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4081 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4082 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4083 mat->free_a = PETSC_TRUE; 4084 mat->free_ij = PETSC_TRUE; 4085 mat->nonew = 0; 4086 } else if (scall == MAT_REUSE_MATRIX){ 4087 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4088 ci = mat->i; cj = mat->j; ca = mat->a; 4089 for (i=0; i<am; i++) { 4090 /* off-diagonal portion of A */ 4091 ncols_o = bi[i+1] - bi[i]; 4092 for (jo=0; jo<ncols_o; jo++) { 4093 col = cmap[*bj]; 4094 if (col >= cstart) break; 4095 *ca++ = *ba++; bj++; 4096 } 4097 /* diagonal portion of A */ 4098 ncols_d = ai[i+1] - ai[i]; 4099 for (j=0; j<ncols_d; j++) *ca++ = *aa++; 4100 /* off-diagonal portion of A */ 4101 for (j=jo; j<ncols_o; j++) { 4102 *ca++ = *ba++; bj++; 4103 } 4104 } 4105 } else { 4106 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4107 } 4108 4109 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4110 PetscFunctionReturn(0); 4111 } 4112 4113 #undef __FUNCT__ 4114 #define __FUNCT__ "MatGetLocalMatCondensed" 4115 /*@C 4116 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4117 4118 Not Collective 4119 4120 Input Parameters: 4121 + A - the matrix 4122 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4123 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4124 4125 Output Parameter: 4126 . A_loc - the local sequential matrix generated 4127 4128 Level: developer 4129 4130 @*/ 4131 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4132 { 4133 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4134 PetscErrorCode ierr; 4135 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4136 IS isrowa,iscola; 4137 Mat *aloc; 4138 4139 PetscFunctionBegin; 4140 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4141 if (!row){ 4142 start = A->rmap.rstart; end = A->rmap.rend; 4143 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4144 } else { 4145 isrowa = *row; 4146 } 4147 if (!col){ 4148 start = A->cmap.rstart; 4149 cmap = a->garray; 4150 nzA = a->A->cmap.n; 4151 nzB = a->B->cmap.n; 4152 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4153 ncols = 0; 4154 for (i=0; i<nzB; i++) { 4155 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4156 else break; 4157 } 4158 imark = i; 4159 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4160 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4161 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4162 ierr = PetscFree(idx);CHKERRQ(ierr); 4163 } else { 4164 iscola = *col; 4165 } 4166 if (scall != MAT_INITIAL_MATRIX){ 4167 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4168 aloc[0] = *A_loc; 4169 } 4170 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4171 *A_loc = aloc[0]; 4172 ierr = PetscFree(aloc);CHKERRQ(ierr); 4173 if (!row){ 4174 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4175 } 4176 if (!col){ 4177 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4178 } 4179 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4180 PetscFunctionReturn(0); 4181 } 4182 4183 #undef __FUNCT__ 4184 #define __FUNCT__ "MatGetBrowsOfAcols" 4185 /*@C 4186 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4187 4188 Collective on Mat 4189 4190 Input Parameters: 4191 + A,B - the matrices in mpiaij format 4192 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4193 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4194 4195 Output Parameter: 4196 + rowb, colb - index sets of rows and columns of B to extract 4197 . brstart - row index of B_seq from which next B->rmap.n rows are taken from B's local rows 4198 - B_seq - the sequential matrix generated 4199 4200 Level: developer 4201 4202 @*/ 4203 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4204 { 4205 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4206 PetscErrorCode ierr; 4207 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4208 IS isrowb,iscolb; 4209 Mat *bseq; 4210 4211 PetscFunctionBegin; 4212 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4213 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap.rstart,A->cmap.rend,B->rmap.rstart,B->rmap.rend); 4214 } 4215 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4216 4217 if (scall == MAT_INITIAL_MATRIX){ 4218 start = A->cmap.rstart; 4219 cmap = a->garray; 4220 nzA = a->A->cmap.n; 4221 nzB = a->B->cmap.n; 4222 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4223 ncols = 0; 4224 for (i=0; i<nzB; i++) { /* row < local row index */ 4225 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4226 else break; 4227 } 4228 imark = i; 4229 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4230 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4231 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4232 ierr = PetscFree(idx);CHKERRQ(ierr); 4233 *brstart = imark; 4234 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap.N,0,1,&iscolb);CHKERRQ(ierr); 4235 } else { 4236 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4237 isrowb = *rowb; iscolb = *colb; 4238 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4239 bseq[0] = *B_seq; 4240 } 4241 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4242 *B_seq = bseq[0]; 4243 ierr = PetscFree(bseq);CHKERRQ(ierr); 4244 if (!rowb){ 4245 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4246 } else { 4247 *rowb = isrowb; 4248 } 4249 if (!colb){ 4250 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4251 } else { 4252 *colb = iscolb; 4253 } 4254 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4255 PetscFunctionReturn(0); 4256 } 4257 4258 #undef __FUNCT__ 4259 #define __FUNCT__ "MatGetBrowsOfAoCols" 4260 /*@C 4261 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4262 of the OFF-DIAGONAL portion of local A 4263 4264 Collective on Mat 4265 4266 Input Parameters: 4267 + A,B - the matrices in mpiaij format 4268 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4269 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4270 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4271 4272 Output Parameter: 4273 + B_oth - the sequential matrix generated 4274 4275 Level: developer 4276 4277 @*/ 4278 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,PetscScalar **bufa_ptr,Mat *B_oth) 4279 { 4280 VecScatter_MPI_General *gen_to,*gen_from; 4281 PetscErrorCode ierr; 4282 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4283 Mat_SeqAIJ *b_oth; 4284 VecScatter ctx=a->Mvctx; 4285 MPI_Comm comm=((PetscObject)ctx)->comm; 4286 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4287 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap.n,row,*b_othi,*b_othj; 4288 PetscScalar *rvalues,*svalues,*b_otha,*bufa,*bufA; 4289 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4290 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4291 MPI_Status *sstatus,rstatus; 4292 PetscMPIInt jj; 4293 PetscInt *cols,sbs,rbs; 4294 PetscScalar *vals; 4295 4296 PetscFunctionBegin; 4297 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4298 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap.rstart,A->cmap.rend,B->rmap.rstart,B->rmap.rend); 4299 } 4300 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4301 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4302 4303 gen_to = (VecScatter_MPI_General*)ctx->todata; 4304 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4305 rvalues = gen_from->values; /* holds the length of receiving row */ 4306 svalues = gen_to->values; /* holds the length of sending row */ 4307 nrecvs = gen_from->n; 4308 nsends = gen_to->n; 4309 4310 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4311 srow = gen_to->indices; /* local row index to be sent */ 4312 sstarts = gen_to->starts; 4313 sprocs = gen_to->procs; 4314 sstatus = gen_to->sstatus; 4315 sbs = gen_to->bs; 4316 rstarts = gen_from->starts; 4317 rprocs = gen_from->procs; 4318 rbs = gen_from->bs; 4319 4320 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4321 if (scall == MAT_INITIAL_MATRIX){ 4322 /* i-array */ 4323 /*---------*/ 4324 /* post receives */ 4325 for (i=0; i<nrecvs; i++){ 4326 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4327 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4328 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4329 } 4330 4331 /* pack the outgoing message */ 4332 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4333 rstartsj = sstartsj + nsends +1; 4334 sstartsj[0] = 0; rstartsj[0] = 0; 4335 len = 0; /* total length of j or a array to be sent */ 4336 k = 0; 4337 for (i=0; i<nsends; i++){ 4338 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4339 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4340 for (j=0; j<nrows; j++) { 4341 row = srow[k] + B->rmap.range[rank]; /* global row idx */ 4342 for (l=0; l<sbs; l++){ 4343 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4344 rowlen[j*sbs+l] = ncols; 4345 len += ncols; 4346 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4347 } 4348 k++; 4349 } 4350 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4351 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4352 } 4353 /* recvs and sends of i-array are completed */ 4354 i = nrecvs; 4355 while (i--) { 4356 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4357 } 4358 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4359 4360 /* allocate buffers for sending j and a arrays */ 4361 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4362 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4363 4364 /* create i-array of B_oth */ 4365 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4366 b_othi[0] = 0; 4367 len = 0; /* total length of j or a array to be received */ 4368 k = 0; 4369 for (i=0; i<nrecvs; i++){ 4370 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4371 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4372 for (j=0; j<nrows; j++) { 4373 b_othi[k+1] = b_othi[k] + rowlen[j]; 4374 len += rowlen[j]; k++; 4375 } 4376 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4377 } 4378 4379 /* allocate space for j and a arrrays of B_oth */ 4380 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4381 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscScalar),&b_otha);CHKERRQ(ierr); 4382 4383 /* j-array */ 4384 /*---------*/ 4385 /* post receives of j-array */ 4386 for (i=0; i<nrecvs; i++){ 4387 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4388 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4389 } 4390 4391 /* pack the outgoing message j-array */ 4392 k = 0; 4393 for (i=0; i<nsends; i++){ 4394 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4395 bufJ = bufj+sstartsj[i]; 4396 for (j=0; j<nrows; j++) { 4397 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4398 for (ll=0; ll<sbs; ll++){ 4399 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4400 for (l=0; l<ncols; l++){ 4401 *bufJ++ = cols[l]; 4402 } 4403 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4404 } 4405 } 4406 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4407 } 4408 4409 /* recvs and sends of j-array are completed */ 4410 i = nrecvs; 4411 while (i--) { 4412 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4413 } 4414 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4415 } else if (scall == MAT_REUSE_MATRIX){ 4416 sstartsj = *startsj; 4417 rstartsj = sstartsj + nsends +1; 4418 bufa = *bufa_ptr; 4419 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4420 b_otha = b_oth->a; 4421 } else { 4422 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4423 } 4424 4425 /* a-array */ 4426 /*---------*/ 4427 /* post receives of a-array */ 4428 for (i=0; i<nrecvs; i++){ 4429 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4430 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4431 } 4432 4433 /* pack the outgoing message a-array */ 4434 k = 0; 4435 for (i=0; i<nsends; i++){ 4436 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4437 bufA = bufa+sstartsj[i]; 4438 for (j=0; j<nrows; j++) { 4439 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4440 for (ll=0; ll<sbs; ll++){ 4441 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4442 for (l=0; l<ncols; l++){ 4443 *bufA++ = vals[l]; 4444 } 4445 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4446 } 4447 } 4448 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4449 } 4450 /* recvs and sends of a-array are completed */ 4451 i = nrecvs; 4452 while (i--) { 4453 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4454 } 4455 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4456 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4457 4458 if (scall == MAT_INITIAL_MATRIX){ 4459 /* put together the new matrix */ 4460 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap.N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4461 4462 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4463 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4464 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4465 b_oth->free_a = PETSC_TRUE; 4466 b_oth->free_ij = PETSC_TRUE; 4467 b_oth->nonew = 0; 4468 4469 ierr = PetscFree(bufj);CHKERRQ(ierr); 4470 if (!startsj || !bufa_ptr){ 4471 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4472 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4473 } else { 4474 *startsj = sstartsj; 4475 *bufa_ptr = bufa; 4476 } 4477 } 4478 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4479 PetscFunctionReturn(0); 4480 } 4481 4482 #undef __FUNCT__ 4483 #define __FUNCT__ "MatGetCommunicationStructs" 4484 /*@C 4485 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4486 4487 Not Collective 4488 4489 Input Parameters: 4490 . A - The matrix in mpiaij format 4491 4492 Output Parameter: 4493 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4494 . colmap - A map from global column index to local index into lvec 4495 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4496 4497 Level: developer 4498 4499 @*/ 4500 #if defined (PETSC_USE_CTABLE) 4501 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4502 #else 4503 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4504 #endif 4505 { 4506 Mat_MPIAIJ *a; 4507 4508 PetscFunctionBegin; 4509 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4510 PetscValidPointer(lvec, 2) 4511 PetscValidPointer(colmap, 3) 4512 PetscValidPointer(multScatter, 4) 4513 a = (Mat_MPIAIJ *) A->data; 4514 if (lvec) *lvec = a->lvec; 4515 if (colmap) *colmap = a->colmap; 4516 if (multScatter) *multScatter = a->Mvctx; 4517 PetscFunctionReturn(0); 4518 } 4519 4520 EXTERN_C_BEGIN 4521 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,MatType,MatReuse,Mat*); 4522 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,MatType,MatReuse,Mat*); 4523 EXTERN_C_END 4524 4525 /*MC 4526 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4527 4528 Options Database Keys: 4529 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4530 4531 Level: beginner 4532 4533 .seealso: MatCreateMPIAIJ() 4534 M*/ 4535 4536 EXTERN_C_BEGIN 4537 #undef __FUNCT__ 4538 #define __FUNCT__ "MatCreate_MPIAIJ" 4539 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4540 { 4541 Mat_MPIAIJ *b; 4542 PetscErrorCode ierr; 4543 PetscMPIInt size; 4544 4545 PetscFunctionBegin; 4546 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4547 4548 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4549 B->data = (void*)b; 4550 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4551 B->factor = 0; 4552 B->rmap.bs = 1; 4553 B->assembled = PETSC_FALSE; 4554 B->mapping = 0; 4555 4556 B->insertmode = NOT_SET_VALUES; 4557 b->size = size; 4558 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4559 4560 /* build cache for off array entries formed */ 4561 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4562 b->donotstash = PETSC_FALSE; 4563 b->colmap = 0; 4564 b->garray = 0; 4565 b->roworiented = PETSC_TRUE; 4566 4567 /* stuff used for matrix vector multiply */ 4568 b->lvec = PETSC_NULL; 4569 b->Mvctx = PETSC_NULL; 4570 4571 /* stuff for MatGetRow() */ 4572 b->rowindices = 0; 4573 b->rowvalues = 0; 4574 b->getrowactive = PETSC_FALSE; 4575 4576 4577 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4578 "MatStoreValues_MPIAIJ", 4579 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4580 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4581 "MatRetrieveValues_MPIAIJ", 4582 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4583 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4584 "MatGetDiagonalBlock_MPIAIJ", 4585 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4586 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4587 "MatIsTranspose_MPIAIJ", 4588 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4589 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4590 "MatMPIAIJSetPreallocation_MPIAIJ", 4591 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4592 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4593 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4594 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4595 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4596 "MatDiagonalScaleLocal_MPIAIJ", 4597 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4598 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 4599 "MatConvert_MPIAIJ_MPICSRPERM", 4600 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 4601 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 4602 "MatConvert_MPIAIJ_MPICRL", 4603 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 4604 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 4605 PetscFunctionReturn(0); 4606 } 4607 EXTERN_C_END 4608 4609 #undef __FUNCT__ 4610 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 4611 /*@ 4612 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 4613 and "off-diagonal" part of the matrix in CSR format. 4614 4615 Collective on MPI_Comm 4616 4617 Input Parameters: 4618 + comm - MPI communicator 4619 . m - number of local rows (Cannot be PETSC_DECIDE) 4620 . n - This value should be the same as the local size used in creating the 4621 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4622 calculated if N is given) For square matrices n is almost always m. 4623 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4624 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4625 . i - row indices for "diagonal" portion of matrix 4626 . j - column indices 4627 . a - matrix values 4628 . oi - row indices for "off-diagonal" portion of matrix 4629 . oj - column indices 4630 - oa - matrix values 4631 4632 Output Parameter: 4633 . mat - the matrix 4634 4635 Level: advanced 4636 4637 Notes: 4638 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 4639 4640 The i and j indices are 0 based 4641 4642 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 4643 4644 4645 .keywords: matrix, aij, compressed row, sparse, parallel 4646 4647 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4648 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 4649 @*/ 4650 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 4651 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 4652 { 4653 PetscErrorCode ierr; 4654 Mat_MPIAIJ *maij; 4655 4656 PetscFunctionBegin; 4657 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4658 if (i[0]) { 4659 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4660 } 4661 if (oi[0]) { 4662 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 4663 } 4664 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4665 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4666 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4667 maij = (Mat_MPIAIJ*) (*mat)->data; 4668 maij->donotstash = PETSC_TRUE; 4669 (*mat)->preallocated = PETSC_TRUE; 4670 4671 (*mat)->rmap.bs = (*mat)->cmap.bs = 1; 4672 ierr = PetscMapSetUp(&(*mat)->rmap);CHKERRQ(ierr); 4673 ierr = PetscMapSetUp(&(*mat)->cmap);CHKERRQ(ierr); 4674 4675 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 4676 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap.N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 4677 4678 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4679 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4680 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4681 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4682 4683 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4684 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4685 PetscFunctionReturn(0); 4686 } 4687 4688 /* 4689 Special version for direct calls from Fortran 4690 */ 4691 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4692 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 4693 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4694 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 4695 #endif 4696 4697 /* Change these macros so can be used in void function */ 4698 #undef CHKERRQ 4699 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4700 #undef SETERRQ2 4701 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4702 #undef SETERRQ 4703 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4704 4705 EXTERN_C_BEGIN 4706 #undef __FUNCT__ 4707 #define __FUNCT__ "matsetvaluesmpiaij_" 4708 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 4709 { 4710 Mat mat = *mmat; 4711 PetscInt m = *mm, n = *mn; 4712 InsertMode addv = *maddv; 4713 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 4714 PetscScalar value; 4715 PetscErrorCode ierr; 4716 4717 MatPreallocated(mat); 4718 if (mat->insertmode == NOT_SET_VALUES) { 4719 mat->insertmode = addv; 4720 } 4721 #if defined(PETSC_USE_DEBUG) 4722 else if (mat->insertmode != addv) { 4723 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 4724 } 4725 #endif 4726 { 4727 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 4728 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 4729 PetscTruth roworiented = aij->roworiented; 4730 4731 /* Some Variables required in the macro */ 4732 Mat A = aij->A; 4733 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4734 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 4735 PetscScalar *aa = a->a; 4736 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 4737 Mat B = aij->B; 4738 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 4739 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 4740 PetscScalar *ba = b->a; 4741 4742 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 4743 PetscInt nonew = a->nonew; 4744 PetscScalar *ap1,*ap2; 4745 4746 PetscFunctionBegin; 4747 for (i=0; i<m; i++) { 4748 if (im[i] < 0) continue; 4749 #if defined(PETSC_USE_DEBUG) 4750 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 4751 #endif 4752 if (im[i] >= rstart && im[i] < rend) { 4753 row = im[i] - rstart; 4754 lastcol1 = -1; 4755 rp1 = aj + ai[row]; 4756 ap1 = aa + ai[row]; 4757 rmax1 = aimax[row]; 4758 nrow1 = ailen[row]; 4759 low1 = 0; 4760 high1 = nrow1; 4761 lastcol2 = -1; 4762 rp2 = bj + bi[row]; 4763 ap2 = ba + bi[row]; 4764 rmax2 = bimax[row]; 4765 nrow2 = bilen[row]; 4766 low2 = 0; 4767 high2 = nrow2; 4768 4769 for (j=0; j<n; j++) { 4770 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 4771 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 4772 if (in[j] >= cstart && in[j] < cend){ 4773 col = in[j] - cstart; 4774 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 4775 } else if (in[j] < 0) continue; 4776 #if defined(PETSC_USE_DEBUG) 4777 else if (in[j] >= mat->cmap.N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap.N-1);} 4778 #endif 4779 else { 4780 if (mat->was_assembled) { 4781 if (!aij->colmap) { 4782 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 4783 } 4784 #if defined (PETSC_USE_CTABLE) 4785 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4786 col--; 4787 #else 4788 col = aij->colmap[in[j]] - 1; 4789 #endif 4790 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 4791 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 4792 col = in[j]; 4793 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 4794 B = aij->B; 4795 b = (Mat_SeqAIJ*)B->data; 4796 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 4797 rp2 = bj + bi[row]; 4798 ap2 = ba + bi[row]; 4799 rmax2 = bimax[row]; 4800 nrow2 = bilen[row]; 4801 low2 = 0; 4802 high2 = nrow2; 4803 bm = aij->B->rmap.n; 4804 ba = b->a; 4805 } 4806 } else col = in[j]; 4807 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 4808 } 4809 } 4810 } else { 4811 if (!aij->donotstash) { 4812 if (roworiented) { 4813 if (ignorezeroentries && v[i*n] == 0.0) continue; 4814 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 4815 } else { 4816 if (ignorezeroentries && v[i] == 0.0) continue; 4817 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 4818 } 4819 } 4820 } 4821 }} 4822 PetscFunctionReturnVoid(); 4823 } 4824 EXTERN_C_END 4825 4826