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 /* -------------------------------------------------------------------*/ 2201 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2202 MatGetRow_MPIAIJ, 2203 MatRestoreRow_MPIAIJ, 2204 MatMult_MPIAIJ, 2205 /* 4*/ MatMultAdd_MPIAIJ, 2206 MatMultTranspose_MPIAIJ, 2207 MatMultTransposeAdd_MPIAIJ, 2208 #ifdef PETSC_HAVE_PBGL 2209 MatSolve_MPIAIJ, 2210 #else 2211 0, 2212 #endif 2213 0, 2214 0, 2215 /*10*/ 0, 2216 0, 2217 0, 2218 MatRelax_MPIAIJ, 2219 MatTranspose_MPIAIJ, 2220 /*15*/ MatGetInfo_MPIAIJ, 2221 MatEqual_MPIAIJ, 2222 MatGetDiagonal_MPIAIJ, 2223 MatDiagonalScale_MPIAIJ, 2224 MatNorm_MPIAIJ, 2225 /*20*/ MatAssemblyBegin_MPIAIJ, 2226 MatAssemblyEnd_MPIAIJ, 2227 0, 2228 MatSetOption_MPIAIJ, 2229 MatZeroEntries_MPIAIJ, 2230 /*25*/ MatZeroRows_MPIAIJ, 2231 0, 2232 #ifdef PETSC_HAVE_PBGL 2233 MatLUFactorNumeric_MPIAIJ, 2234 #else 2235 0, 2236 #endif 2237 0, 2238 0, 2239 /*30*/ MatSetUpPreallocation_MPIAIJ, 2240 #ifdef PETSC_HAVE_PBGL 2241 MatILUFactorSymbolic_MPIAIJ, 2242 #else 2243 0, 2244 #endif 2245 0, 2246 0, 2247 0, 2248 /*35*/ MatDuplicate_MPIAIJ, 2249 0, 2250 0, 2251 0, 2252 0, 2253 /*40*/ MatAXPY_MPIAIJ, 2254 MatGetSubMatrices_MPIAIJ, 2255 MatIncreaseOverlap_MPIAIJ, 2256 MatGetValues_MPIAIJ, 2257 MatCopy_MPIAIJ, 2258 /*45*/ 0, 2259 MatScale_MPIAIJ, 2260 0, 2261 0, 2262 0, 2263 /*50*/ MatSetBlockSize_MPIAIJ, 2264 0, 2265 0, 2266 0, 2267 0, 2268 /*55*/ MatFDColoringCreate_MPIAIJ, 2269 0, 2270 MatSetUnfactored_MPIAIJ, 2271 MatPermute_MPIAIJ, 2272 0, 2273 /*60*/ MatGetSubMatrix_MPIAIJ, 2274 MatDestroy_MPIAIJ, 2275 MatView_MPIAIJ, 2276 0, 2277 0, 2278 /*65*/ 0, 2279 0, 2280 0, 2281 0, 2282 0, 2283 /*70*/ 0, 2284 0, 2285 MatSetColoring_MPIAIJ, 2286 #if defined(PETSC_HAVE_ADIC) 2287 MatSetValuesAdic_MPIAIJ, 2288 #else 2289 0, 2290 #endif 2291 MatSetValuesAdifor_MPIAIJ, 2292 /*75*/ 0, 2293 0, 2294 0, 2295 0, 2296 0, 2297 /*80*/ 0, 2298 0, 2299 0, 2300 0, 2301 /*84*/ MatLoad_MPIAIJ, 2302 0, 2303 0, 2304 0, 2305 0, 2306 0, 2307 /*90*/ MatMatMult_MPIAIJ_MPIAIJ, 2308 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2309 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2310 MatPtAP_Basic, 2311 MatPtAPSymbolic_MPIAIJ, 2312 /*95*/ MatPtAPNumeric_MPIAIJ, 2313 0, 2314 0, 2315 0, 2316 0, 2317 /*100*/0, 2318 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2319 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2320 MatConjugate_MPIAIJ, 2321 0, 2322 /*105*/MatSetValuesRow_MPIAIJ, 2323 MatRealPart_MPIAIJ, 2324 MatImaginaryPart_MPIAIJ, 2325 0, 2326 0, 2327 /*110*/0, 2328 MatGetRedundantMatrix_MPIAIJ, 2329 MatGetRowMin_MPIAIJ}; 2330 2331 /* ----------------------------------------------------------------------------------------*/ 2332 2333 EXTERN_C_BEGIN 2334 #undef __FUNCT__ 2335 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2336 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2337 { 2338 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2339 PetscErrorCode ierr; 2340 2341 PetscFunctionBegin; 2342 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2343 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2344 PetscFunctionReturn(0); 2345 } 2346 EXTERN_C_END 2347 2348 EXTERN_C_BEGIN 2349 #undef __FUNCT__ 2350 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2351 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2352 { 2353 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2354 PetscErrorCode ierr; 2355 2356 PetscFunctionBegin; 2357 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2358 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2359 PetscFunctionReturn(0); 2360 } 2361 EXTERN_C_END 2362 2363 #include "petscpc.h" 2364 EXTERN_C_BEGIN 2365 #undef __FUNCT__ 2366 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2367 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2368 { 2369 Mat_MPIAIJ *b; 2370 PetscErrorCode ierr; 2371 PetscInt i; 2372 2373 PetscFunctionBegin; 2374 B->preallocated = PETSC_TRUE; 2375 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2376 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2377 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2378 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2379 2380 B->rmap.bs = B->cmap.bs = 1; 2381 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2382 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2383 if (d_nnz) { 2384 for (i=0; i<B->rmap.n; i++) { 2385 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]); 2386 } 2387 } 2388 if (o_nnz) { 2389 for (i=0; i<B->rmap.n; i++) { 2390 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]); 2391 } 2392 } 2393 b = (Mat_MPIAIJ*)B->data; 2394 2395 /* Explicitly create 2 MATSEQAIJ matrices. */ 2396 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2397 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2398 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2399 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2400 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2401 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2402 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2403 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2404 2405 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2406 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2407 2408 PetscFunctionReturn(0); 2409 } 2410 EXTERN_C_END 2411 2412 #undef __FUNCT__ 2413 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2414 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2415 { 2416 Mat mat; 2417 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2418 PetscErrorCode ierr; 2419 2420 PetscFunctionBegin; 2421 *newmat = 0; 2422 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2423 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2424 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2425 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2426 a = (Mat_MPIAIJ*)mat->data; 2427 2428 mat->factor = matin->factor; 2429 mat->rmap.bs = matin->rmap.bs; 2430 mat->assembled = PETSC_TRUE; 2431 mat->insertmode = NOT_SET_VALUES; 2432 mat->preallocated = PETSC_TRUE; 2433 2434 a->size = oldmat->size; 2435 a->rank = oldmat->rank; 2436 a->donotstash = oldmat->donotstash; 2437 a->roworiented = oldmat->roworiented; 2438 a->rowindices = 0; 2439 a->rowvalues = 0; 2440 a->getrowactive = PETSC_FALSE; 2441 2442 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2443 ierr = PetscMapCopy(((PetscObject)mat)->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2444 2445 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2446 if (oldmat->colmap) { 2447 #if defined (PETSC_USE_CTABLE) 2448 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2449 #else 2450 ierr = PetscMalloc((mat->cmap.N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2451 ierr = PetscLogObjectMemory(mat,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2452 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2453 #endif 2454 } else a->colmap = 0; 2455 if (oldmat->garray) { 2456 PetscInt len; 2457 len = oldmat->B->cmap.n; 2458 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2459 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2460 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2461 } else a->garray = 0; 2462 2463 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2464 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2465 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2466 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2467 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2468 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2469 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2470 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2471 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2472 *newmat = mat; 2473 PetscFunctionReturn(0); 2474 } 2475 2476 #include "petscsys.h" 2477 2478 #undef __FUNCT__ 2479 #define __FUNCT__ "MatLoad_MPIAIJ" 2480 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2481 { 2482 Mat A; 2483 PetscScalar *vals,*svals; 2484 MPI_Comm comm = ((PetscObject)viewer)->comm; 2485 MPI_Status status; 2486 PetscErrorCode ierr; 2487 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2488 PetscInt i,nz,j,rstart,rend,mmax; 2489 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2490 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2491 PetscInt cend,cstart,n,*rowners; 2492 int fd; 2493 2494 PetscFunctionBegin; 2495 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2496 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2497 if (!rank) { 2498 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2499 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2500 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2501 } 2502 2503 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2504 M = header[1]; N = header[2]; 2505 /* determine ownership of all rows */ 2506 m = M/size + ((M % size) > rank); 2507 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2508 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2509 2510 /* First process needs enough room for process with most rows */ 2511 if (!rank) { 2512 mmax = rowners[1]; 2513 for (i=2; i<size; i++) { 2514 mmax = PetscMax(mmax,rowners[i]); 2515 } 2516 } else mmax = m; 2517 2518 rowners[0] = 0; 2519 for (i=2; i<=size; i++) { 2520 rowners[i] += rowners[i-1]; 2521 } 2522 rstart = rowners[rank]; 2523 rend = rowners[rank+1]; 2524 2525 /* distribute row lengths to all processors */ 2526 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2527 if (!rank) { 2528 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2529 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2530 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2531 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2532 for (j=0; j<m; j++) { 2533 procsnz[0] += ourlens[j]; 2534 } 2535 for (i=1; i<size; i++) { 2536 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2537 /* calculate the number of nonzeros on each processor */ 2538 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2539 procsnz[i] += rowlengths[j]; 2540 } 2541 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2542 } 2543 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2544 } else { 2545 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2546 } 2547 2548 if (!rank) { 2549 /* determine max buffer needed and allocate it */ 2550 maxnz = 0; 2551 for (i=0; i<size; i++) { 2552 maxnz = PetscMax(maxnz,procsnz[i]); 2553 } 2554 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2555 2556 /* read in my part of the matrix column indices */ 2557 nz = procsnz[0]; 2558 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2559 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2560 2561 /* read in every one elses and ship off */ 2562 for (i=1; i<size; i++) { 2563 nz = procsnz[i]; 2564 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2565 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2566 } 2567 ierr = PetscFree(cols);CHKERRQ(ierr); 2568 } else { 2569 /* determine buffer space needed for message */ 2570 nz = 0; 2571 for (i=0; i<m; i++) { 2572 nz += ourlens[i]; 2573 } 2574 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2575 2576 /* receive message of column indices*/ 2577 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2578 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2579 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2580 } 2581 2582 /* determine column ownership if matrix is not square */ 2583 if (N != M) { 2584 n = N/size + ((N % size) > rank); 2585 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2586 cstart = cend - n; 2587 } else { 2588 cstart = rstart; 2589 cend = rend; 2590 n = cend - cstart; 2591 } 2592 2593 /* loop over local rows, determining number of off diagonal entries */ 2594 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2595 jj = 0; 2596 for (i=0; i<m; i++) { 2597 for (j=0; j<ourlens[i]; j++) { 2598 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2599 jj++; 2600 } 2601 } 2602 2603 /* create our matrix */ 2604 for (i=0; i<m; i++) { 2605 ourlens[i] -= offlens[i]; 2606 } 2607 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2608 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2609 ierr = MatSetType(A,type);CHKERRQ(ierr); 2610 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2611 2612 for (i=0; i<m; i++) { 2613 ourlens[i] += offlens[i]; 2614 } 2615 2616 if (!rank) { 2617 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2618 2619 /* read in my part of the matrix numerical values */ 2620 nz = procsnz[0]; 2621 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2622 2623 /* insert into matrix */ 2624 jj = rstart; 2625 smycols = mycols; 2626 svals = vals; 2627 for (i=0; i<m; i++) { 2628 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2629 smycols += ourlens[i]; 2630 svals += ourlens[i]; 2631 jj++; 2632 } 2633 2634 /* read in other processors and ship out */ 2635 for (i=1; i<size; i++) { 2636 nz = procsnz[i]; 2637 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2638 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2639 } 2640 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2641 } else { 2642 /* receive numeric values */ 2643 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2644 2645 /* receive message of values*/ 2646 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2647 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2648 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2649 2650 /* insert into matrix */ 2651 jj = rstart; 2652 smycols = mycols; 2653 svals = vals; 2654 for (i=0; i<m; i++) { 2655 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2656 smycols += ourlens[i]; 2657 svals += ourlens[i]; 2658 jj++; 2659 } 2660 } 2661 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2662 ierr = PetscFree(vals);CHKERRQ(ierr); 2663 ierr = PetscFree(mycols);CHKERRQ(ierr); 2664 ierr = PetscFree(rowners);CHKERRQ(ierr); 2665 2666 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2667 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2668 *newmat = A; 2669 PetscFunctionReturn(0); 2670 } 2671 2672 #undef __FUNCT__ 2673 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2674 /* 2675 Not great since it makes two copies of the submatrix, first an SeqAIJ 2676 in local and then by concatenating the local matrices the end result. 2677 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2678 */ 2679 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2680 { 2681 PetscErrorCode ierr; 2682 PetscMPIInt rank,size; 2683 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 2684 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2685 Mat *local,M,Mreuse; 2686 PetscScalar *vwork,*aa; 2687 MPI_Comm comm = ((PetscObject)mat)->comm; 2688 Mat_SeqAIJ *aij; 2689 2690 2691 PetscFunctionBegin; 2692 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2693 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2694 2695 if (call == MAT_REUSE_MATRIX) { 2696 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2697 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2698 local = &Mreuse; 2699 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2700 } else { 2701 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2702 Mreuse = *local; 2703 ierr = PetscFree(local);CHKERRQ(ierr); 2704 } 2705 2706 /* 2707 m - number of local rows 2708 n - number of columns (same on all processors) 2709 rstart - first row in new global matrix generated 2710 */ 2711 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2712 if (call == MAT_INITIAL_MATRIX) { 2713 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2714 ii = aij->i; 2715 jj = aij->j; 2716 2717 /* 2718 Determine the number of non-zeros in the diagonal and off-diagonal 2719 portions of the matrix in order to do correct preallocation 2720 */ 2721 2722 /* first get start and end of "diagonal" columns */ 2723 if (csize == PETSC_DECIDE) { 2724 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2725 if (mglobal == n) { /* square matrix */ 2726 nlocal = m; 2727 } else { 2728 nlocal = n/size + ((n % size) > rank); 2729 } 2730 } else { 2731 nlocal = csize; 2732 } 2733 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2734 rstart = rend - nlocal; 2735 if (rank == size - 1 && rend != n) { 2736 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2737 } 2738 2739 /* next, compute all the lengths */ 2740 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2741 olens = dlens + m; 2742 for (i=0; i<m; i++) { 2743 jend = ii[i+1] - ii[i]; 2744 olen = 0; 2745 dlen = 0; 2746 for (j=0; j<jend; j++) { 2747 if (*jj < rstart || *jj >= rend) olen++; 2748 else dlen++; 2749 jj++; 2750 } 2751 olens[i] = olen; 2752 dlens[i] = dlen; 2753 } 2754 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2755 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 2756 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 2757 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 2758 ierr = PetscFree(dlens);CHKERRQ(ierr); 2759 } else { 2760 PetscInt ml,nl; 2761 2762 M = *newmat; 2763 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2764 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2765 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2766 /* 2767 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2768 rather than the slower MatSetValues(). 2769 */ 2770 M->was_assembled = PETSC_TRUE; 2771 M->assembled = PETSC_FALSE; 2772 } 2773 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2774 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2775 ii = aij->i; 2776 jj = aij->j; 2777 aa = aij->a; 2778 for (i=0; i<m; i++) { 2779 row = rstart + i; 2780 nz = ii[i+1] - ii[i]; 2781 cwork = jj; jj += nz; 2782 vwork = aa; aa += nz; 2783 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2784 } 2785 2786 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2787 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2788 *newmat = M; 2789 2790 /* save submatrix used in processor for next request */ 2791 if (call == MAT_INITIAL_MATRIX) { 2792 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2793 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2794 } 2795 2796 PetscFunctionReturn(0); 2797 } 2798 2799 EXTERN_C_BEGIN 2800 #undef __FUNCT__ 2801 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 2802 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 2803 { 2804 PetscInt m,cstart, cend,j,nnz,i,d; 2805 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 2806 const PetscInt *JJ; 2807 PetscScalar *values; 2808 PetscErrorCode ierr; 2809 2810 PetscFunctionBegin; 2811 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 2812 2813 B->rmap.bs = B->cmap.bs = 1; 2814 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2815 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2816 m = B->rmap.n; 2817 cstart = B->cmap.rstart; 2818 cend = B->cmap.rend; 2819 rstart = B->rmap.rstart; 2820 2821 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2822 o_nnz = d_nnz + m; 2823 2824 #if defined(PETSC_USE_DEBUGGING) 2825 for (i=0; i<m; i++) { 2826 nnz = Ii[i+1]- Ii[i]; 2827 JJ = J + Ii[i]; 2828 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 2829 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 2830 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); 2831 for (j=1; j<nnz; j++) { 2832 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); 2833 } 2834 } 2835 #endif 2836 2837 for (i=0; i<m; i++) { 2838 nnz = Ii[i+1]- Ii[i]; 2839 JJ = J + Ii[i]; 2840 nnz_max = PetscMax(nnz_max,nnz); 2841 for (j=0; j<nnz; j++) { 2842 if (*JJ >= cstart) break; 2843 JJ++; 2844 } 2845 d = 0; 2846 for (; j<nnz; j++) { 2847 if (*JJ++ >= cend) break; 2848 d++; 2849 } 2850 d_nnz[i] = d; 2851 o_nnz[i] = nnz - d; 2852 } 2853 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2854 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2855 2856 if (v) values = (PetscScalar*)v; 2857 else { 2858 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2859 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2860 } 2861 2862 for (i=0; i<m; i++) { 2863 ii = i + rstart; 2864 nnz = Ii[i+1]- Ii[i]; 2865 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 2866 } 2867 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2868 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2869 2870 if (!v) { 2871 ierr = PetscFree(values);CHKERRQ(ierr); 2872 } 2873 PetscFunctionReturn(0); 2874 } 2875 EXTERN_C_END 2876 2877 #undef __FUNCT__ 2878 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 2879 /*@ 2880 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2881 (the default parallel PETSc format). 2882 2883 Collective on MPI_Comm 2884 2885 Input Parameters: 2886 + B - the matrix 2887 . i - the indices into j for the start of each local row (starts with zero) 2888 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2889 - v - optional values in the matrix 2890 2891 Level: developer 2892 2893 Notes: 2894 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 2895 thus you CANNOT change the matrix entries by changing the values of a[] after you have 2896 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 2897 2898 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 2899 2900 The format which is used for the sparse matrix input, is equivalent to a 2901 row-major ordering.. i.e for the following matrix, the input data expected is 2902 as shown: 2903 2904 1 0 0 2905 2 0 3 P0 2906 ------- 2907 4 5 6 P1 2908 2909 Process0 [P0]: rows_owned=[0,1] 2910 i = {0,1,3} [size = nrow+1 = 2+1] 2911 j = {0,0,2} [size = nz = 6] 2912 v = {1,2,3} [size = nz = 6] 2913 2914 Process1 [P1]: rows_owned=[2] 2915 i = {0,3} [size = nrow+1 = 1+1] 2916 j = {0,1,2} [size = nz = 6] 2917 v = {4,5,6} [size = nz = 6] 2918 2919 The column indices for each row MUST be sorted. 2920 2921 .keywords: matrix, aij, compressed row, sparse, parallel 2922 2923 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 2924 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 2925 @*/ 2926 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2927 { 2928 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 2929 2930 PetscFunctionBegin; 2931 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2932 if (f) { 2933 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 2934 } 2935 PetscFunctionReturn(0); 2936 } 2937 2938 #undef __FUNCT__ 2939 #define __FUNCT__ "MatMPIAIJSetPreallocation" 2940 /*@C 2941 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 2942 (the default parallel PETSc format). For good matrix assembly performance 2943 the user should preallocate the matrix storage by setting the parameters 2944 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2945 performance can be increased by more than a factor of 50. 2946 2947 Collective on MPI_Comm 2948 2949 Input Parameters: 2950 + A - the matrix 2951 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2952 (same value is used for all local rows) 2953 . d_nnz - array containing the number of nonzeros in the various rows of the 2954 DIAGONAL portion of the local submatrix (possibly different for each row) 2955 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2956 The size of this array is equal to the number of local rows, i.e 'm'. 2957 You must leave room for the diagonal entry even if it is zero. 2958 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2959 submatrix (same value is used for all local rows). 2960 - o_nnz - array containing the number of nonzeros in the various rows of the 2961 OFF-DIAGONAL portion of the local submatrix (possibly different for 2962 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2963 structure. The size of this array is equal to the number 2964 of local rows, i.e 'm'. 2965 2966 If the *_nnz parameter is given then the *_nz parameter is ignored 2967 2968 The AIJ format (also called the Yale sparse matrix format or 2969 compressed row storage (CSR)), is fully compatible with standard Fortran 77 2970 storage. The stored row and column indices begin with zero. See the users manual for details. 2971 2972 The parallel matrix is partitioned such that the first m0 rows belong to 2973 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2974 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2975 2976 The DIAGONAL portion of the local submatrix of a processor can be defined 2977 as the submatrix which is obtained by extraction the part corresponding 2978 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2979 first row that belongs to the processor, and r2 is the last row belonging 2980 to the this processor. This is a square mxm matrix. The remaining portion 2981 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2982 2983 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2984 2985 Example usage: 2986 2987 Consider the following 8x8 matrix with 34 non-zero values, that is 2988 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2989 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2990 as follows: 2991 2992 .vb 2993 1 2 0 | 0 3 0 | 0 4 2994 Proc0 0 5 6 | 7 0 0 | 8 0 2995 9 0 10 | 11 0 0 | 12 0 2996 ------------------------------------- 2997 13 0 14 | 15 16 17 | 0 0 2998 Proc1 0 18 0 | 19 20 21 | 0 0 2999 0 0 0 | 22 23 0 | 24 0 3000 ------------------------------------- 3001 Proc2 25 26 27 | 0 0 28 | 29 0 3002 30 0 0 | 31 32 33 | 0 34 3003 .ve 3004 3005 This can be represented as a collection of submatrices as: 3006 3007 .vb 3008 A B C 3009 D E F 3010 G H I 3011 .ve 3012 3013 Where the submatrices A,B,C are owned by proc0, D,E,F are 3014 owned by proc1, G,H,I are owned by proc2. 3015 3016 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3017 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3018 The 'M','N' parameters are 8,8, and have the same values on all procs. 3019 3020 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3021 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3022 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3023 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3024 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3025 matrix, ans [DF] as another SeqAIJ matrix. 3026 3027 When d_nz, o_nz parameters are specified, d_nz storage elements are 3028 allocated for every row of the local diagonal submatrix, and o_nz 3029 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3030 One way to choose d_nz and o_nz is to use the max nonzerors per local 3031 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3032 In this case, the values of d_nz,o_nz are: 3033 .vb 3034 proc0 : dnz = 2, o_nz = 2 3035 proc1 : dnz = 3, o_nz = 2 3036 proc2 : dnz = 1, o_nz = 4 3037 .ve 3038 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3039 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3040 for proc3. i.e we are using 12+15+10=37 storage locations to store 3041 34 values. 3042 3043 When d_nnz, o_nnz parameters are specified, the storage is specified 3044 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3045 In the above case the values for d_nnz,o_nnz are: 3046 .vb 3047 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3048 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3049 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3050 .ve 3051 Here the space allocated is sum of all the above values i.e 34, and 3052 hence pre-allocation is perfect. 3053 3054 Level: intermediate 3055 3056 .keywords: matrix, aij, compressed row, sparse, parallel 3057 3058 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3059 MPIAIJ 3060 @*/ 3061 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3062 { 3063 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3064 3065 PetscFunctionBegin; 3066 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3067 if (f) { 3068 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3069 } 3070 PetscFunctionReturn(0); 3071 } 3072 3073 #undef __FUNCT__ 3074 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3075 /*@ 3076 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3077 CSR format the local rows. 3078 3079 Collective on MPI_Comm 3080 3081 Input Parameters: 3082 + comm - MPI communicator 3083 . m - number of local rows (Cannot be PETSC_DECIDE) 3084 . n - This value should be the same as the local size used in creating the 3085 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3086 calculated if N is given) For square matrices n is almost always m. 3087 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3088 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3089 . i - row indices 3090 . j - column indices 3091 - a - matrix values 3092 3093 Output Parameter: 3094 . mat - the matrix 3095 3096 Level: intermediate 3097 3098 Notes: 3099 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3100 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3101 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3102 3103 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3104 3105 The format which is used for the sparse matrix input, is equivalent to a 3106 row-major ordering.. i.e for the following matrix, the input data expected is 3107 as shown: 3108 3109 1 0 0 3110 2 0 3 P0 3111 ------- 3112 4 5 6 P1 3113 3114 Process0 [P0]: rows_owned=[0,1] 3115 i = {0,1,3} [size = nrow+1 = 2+1] 3116 j = {0,0,2} [size = nz = 6] 3117 v = {1,2,3} [size = nz = 6] 3118 3119 Process1 [P1]: rows_owned=[2] 3120 i = {0,3} [size = nrow+1 = 1+1] 3121 j = {0,1,2} [size = nz = 6] 3122 v = {4,5,6} [size = nz = 6] 3123 3124 .keywords: matrix, aij, compressed row, sparse, parallel 3125 3126 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3127 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3128 @*/ 3129 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) 3130 { 3131 PetscErrorCode ierr; 3132 3133 PetscFunctionBegin; 3134 if (i[0]) { 3135 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3136 } 3137 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3138 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3139 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3140 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3141 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3142 PetscFunctionReturn(0); 3143 } 3144 3145 #undef __FUNCT__ 3146 #define __FUNCT__ "MatCreateMPIAIJ" 3147 /*@C 3148 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3149 (the default parallel PETSc format). For good matrix assembly performance 3150 the user should preallocate the matrix storage by setting the parameters 3151 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3152 performance can be increased by more than a factor of 50. 3153 3154 Collective on MPI_Comm 3155 3156 Input Parameters: 3157 + comm - MPI communicator 3158 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3159 This value should be the same as the local size used in creating the 3160 y vector for the matrix-vector product y = Ax. 3161 . n - This value should be the same as the local size used in creating the 3162 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3163 calculated if N is given) For square matrices n is almost always m. 3164 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3165 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3166 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3167 (same value is used for all local rows) 3168 . d_nnz - array containing the number of nonzeros in the various rows of the 3169 DIAGONAL portion of the local submatrix (possibly different for each row) 3170 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3171 The size of this array is equal to the number of local rows, i.e 'm'. 3172 You must leave room for the diagonal entry even if it is zero. 3173 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3174 submatrix (same value is used for all local rows). 3175 - o_nnz - array containing the number of nonzeros in the various rows of the 3176 OFF-DIAGONAL portion of the local submatrix (possibly different for 3177 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3178 structure. The size of this array is equal to the number 3179 of local rows, i.e 'm'. 3180 3181 Output Parameter: 3182 . A - the matrix 3183 3184 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3185 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3186 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3187 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3188 3189 Notes: 3190 If the *_nnz parameter is given then the *_nz parameter is ignored 3191 3192 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3193 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3194 storage requirements for this matrix. 3195 3196 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3197 processor than it must be used on all processors that share the object for 3198 that argument. 3199 3200 The user MUST specify either the local or global matrix dimensions 3201 (possibly both). 3202 3203 The parallel matrix is partitioned across processors such that the 3204 first m0 rows belong to process 0, the next m1 rows belong to 3205 process 1, the next m2 rows belong to process 2 etc.. where 3206 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3207 values corresponding to [m x N] submatrix. 3208 3209 The columns are logically partitioned with the n0 columns belonging 3210 to 0th partition, the next n1 columns belonging to the next 3211 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3212 3213 The DIAGONAL portion of the local submatrix on any given processor 3214 is the submatrix corresponding to the rows and columns m,n 3215 corresponding to the given processor. i.e diagonal matrix on 3216 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3217 etc. The remaining portion of the local submatrix [m x (N-n)] 3218 constitute the OFF-DIAGONAL portion. The example below better 3219 illustrates this concept. 3220 3221 For a square global matrix we define each processor's diagonal portion 3222 to be its local rows and the corresponding columns (a square submatrix); 3223 each processor's off-diagonal portion encompasses the remainder of the 3224 local matrix (a rectangular submatrix). 3225 3226 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3227 3228 When calling this routine with a single process communicator, a matrix of 3229 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3230 type of communicator, use the construction mechanism: 3231 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3232 3233 By default, this format uses inodes (identical nodes) when possible. 3234 We search for consecutive rows with the same nonzero structure, thereby 3235 reusing matrix information to achieve increased efficiency. 3236 3237 Options Database Keys: 3238 + -mat_no_inode - Do not use inodes 3239 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3240 - -mat_aij_oneindex - Internally use indexing starting at 1 3241 rather than 0. Note that when calling MatSetValues(), 3242 the user still MUST index entries starting at 0! 3243 3244 3245 Example usage: 3246 3247 Consider the following 8x8 matrix with 34 non-zero values, that is 3248 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3249 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3250 as follows: 3251 3252 .vb 3253 1 2 0 | 0 3 0 | 0 4 3254 Proc0 0 5 6 | 7 0 0 | 8 0 3255 9 0 10 | 11 0 0 | 12 0 3256 ------------------------------------- 3257 13 0 14 | 15 16 17 | 0 0 3258 Proc1 0 18 0 | 19 20 21 | 0 0 3259 0 0 0 | 22 23 0 | 24 0 3260 ------------------------------------- 3261 Proc2 25 26 27 | 0 0 28 | 29 0 3262 30 0 0 | 31 32 33 | 0 34 3263 .ve 3264 3265 This can be represented as a collection of submatrices as: 3266 3267 .vb 3268 A B C 3269 D E F 3270 G H I 3271 .ve 3272 3273 Where the submatrices A,B,C are owned by proc0, D,E,F are 3274 owned by proc1, G,H,I are owned by proc2. 3275 3276 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3277 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3278 The 'M','N' parameters are 8,8, and have the same values on all procs. 3279 3280 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3281 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3282 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3283 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3284 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3285 matrix, ans [DF] as another SeqAIJ matrix. 3286 3287 When d_nz, o_nz parameters are specified, d_nz storage elements are 3288 allocated for every row of the local diagonal submatrix, and o_nz 3289 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3290 One way to choose d_nz and o_nz is to use the max nonzerors per local 3291 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3292 In this case, the values of d_nz,o_nz are: 3293 .vb 3294 proc0 : dnz = 2, o_nz = 2 3295 proc1 : dnz = 3, o_nz = 2 3296 proc2 : dnz = 1, o_nz = 4 3297 .ve 3298 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3299 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3300 for proc3. i.e we are using 12+15+10=37 storage locations to store 3301 34 values. 3302 3303 When d_nnz, o_nnz parameters are specified, the storage is specified 3304 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3305 In the above case the values for d_nnz,o_nnz are: 3306 .vb 3307 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3308 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3309 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3310 .ve 3311 Here the space allocated is sum of all the above values i.e 34, and 3312 hence pre-allocation is perfect. 3313 3314 Level: intermediate 3315 3316 .keywords: matrix, aij, compressed row, sparse, parallel 3317 3318 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3319 MPIAIJ, MatCreateMPIAIJWithArrays() 3320 @*/ 3321 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) 3322 { 3323 PetscErrorCode ierr; 3324 PetscMPIInt size; 3325 3326 PetscFunctionBegin; 3327 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3328 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3329 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3330 if (size > 1) { 3331 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3332 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3333 } else { 3334 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3335 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3336 } 3337 PetscFunctionReturn(0); 3338 } 3339 3340 #undef __FUNCT__ 3341 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3342 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3343 { 3344 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3345 3346 PetscFunctionBegin; 3347 *Ad = a->A; 3348 *Ao = a->B; 3349 *colmap = a->garray; 3350 PetscFunctionReturn(0); 3351 } 3352 3353 #undef __FUNCT__ 3354 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3355 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3356 { 3357 PetscErrorCode ierr; 3358 PetscInt i; 3359 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3360 3361 PetscFunctionBegin; 3362 if (coloring->ctype == IS_COLORING_GLOBAL) { 3363 ISColoringValue *allcolors,*colors; 3364 ISColoring ocoloring; 3365 3366 /* set coloring for diagonal portion */ 3367 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3368 3369 /* set coloring for off-diagonal portion */ 3370 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3371 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3372 for (i=0; i<a->B->cmap.n; i++) { 3373 colors[i] = allcolors[a->garray[i]]; 3374 } 3375 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3376 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3377 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3378 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3379 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3380 ISColoringValue *colors; 3381 PetscInt *larray; 3382 ISColoring ocoloring; 3383 3384 /* set coloring for diagonal portion */ 3385 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3386 for (i=0; i<a->A->cmap.n; i++) { 3387 larray[i] = i + A->cmap.rstart; 3388 } 3389 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap.n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3390 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3391 for (i=0; i<a->A->cmap.n; i++) { 3392 colors[i] = coloring->colors[larray[i]]; 3393 } 3394 ierr = PetscFree(larray);CHKERRQ(ierr); 3395 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3396 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3397 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3398 3399 /* set coloring for off-diagonal portion */ 3400 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3401 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap.n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3402 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3403 for (i=0; i<a->B->cmap.n; i++) { 3404 colors[i] = coloring->colors[larray[i]]; 3405 } 3406 ierr = PetscFree(larray);CHKERRQ(ierr); 3407 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3408 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3409 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3410 } else { 3411 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3412 } 3413 3414 PetscFunctionReturn(0); 3415 } 3416 3417 #if defined(PETSC_HAVE_ADIC) 3418 #undef __FUNCT__ 3419 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3420 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3421 { 3422 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3423 PetscErrorCode ierr; 3424 3425 PetscFunctionBegin; 3426 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3427 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3428 PetscFunctionReturn(0); 3429 } 3430 #endif 3431 3432 #undef __FUNCT__ 3433 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3434 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3435 { 3436 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3437 PetscErrorCode ierr; 3438 3439 PetscFunctionBegin; 3440 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3441 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3442 PetscFunctionReturn(0); 3443 } 3444 3445 #undef __FUNCT__ 3446 #define __FUNCT__ "MatMerge" 3447 /*@ 3448 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3449 matrices from each processor 3450 3451 Collective on MPI_Comm 3452 3453 Input Parameters: 3454 + comm - the communicators the parallel matrix will live on 3455 . inmat - the input sequential matrices 3456 . n - number of local columns (or PETSC_DECIDE) 3457 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3458 3459 Output Parameter: 3460 . outmat - the parallel matrix generated 3461 3462 Level: advanced 3463 3464 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3465 3466 @*/ 3467 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3468 { 3469 PetscErrorCode ierr; 3470 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3471 PetscInt *indx; 3472 PetscScalar *values; 3473 3474 PetscFunctionBegin; 3475 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3476 if (scall == MAT_INITIAL_MATRIX){ 3477 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3478 if (n == PETSC_DECIDE){ 3479 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3480 } 3481 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3482 rstart -= m; 3483 3484 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3485 for (i=0;i<m;i++) { 3486 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3487 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3488 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3489 } 3490 /* This routine will ONLY return MPIAIJ type matrix */ 3491 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3492 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3493 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3494 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3495 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3496 3497 } else if (scall == MAT_REUSE_MATRIX){ 3498 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3499 } else { 3500 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3501 } 3502 3503 for (i=0;i<m;i++) { 3504 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3505 Ii = i + rstart; 3506 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3507 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3508 } 3509 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3510 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3511 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3512 3513 PetscFunctionReturn(0); 3514 } 3515 3516 #undef __FUNCT__ 3517 #define __FUNCT__ "MatFileSplit" 3518 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3519 { 3520 PetscErrorCode ierr; 3521 PetscMPIInt rank; 3522 PetscInt m,N,i,rstart,nnz; 3523 size_t len; 3524 const PetscInt *indx; 3525 PetscViewer out; 3526 char *name; 3527 Mat B; 3528 const PetscScalar *values; 3529 3530 PetscFunctionBegin; 3531 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3532 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3533 /* Should this be the type of the diagonal block of A? */ 3534 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3535 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3536 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3537 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3538 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3539 for (i=0;i<m;i++) { 3540 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3541 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3542 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3543 } 3544 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3545 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3546 3547 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3548 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3549 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3550 sprintf(name,"%s.%d",outfile,rank); 3551 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3552 ierr = PetscFree(name); 3553 ierr = MatView(B,out);CHKERRQ(ierr); 3554 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3555 ierr = MatDestroy(B);CHKERRQ(ierr); 3556 PetscFunctionReturn(0); 3557 } 3558 3559 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3560 #undef __FUNCT__ 3561 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3562 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3563 { 3564 PetscErrorCode ierr; 3565 Mat_Merge_SeqsToMPI *merge; 3566 PetscContainer container; 3567 3568 PetscFunctionBegin; 3569 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3570 if (container) { 3571 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3572 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3573 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3574 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3575 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3576 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3577 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3578 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3579 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3580 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3581 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3582 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3583 3584 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3585 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3586 } 3587 ierr = PetscFree(merge);CHKERRQ(ierr); 3588 3589 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3590 PetscFunctionReturn(0); 3591 } 3592 3593 #include "src/mat/utils/freespace.h" 3594 #include "petscbt.h" 3595 static PetscEvent logkey_seqstompinum = 0; 3596 #undef __FUNCT__ 3597 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3598 /*@C 3599 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3600 matrices from each processor 3601 3602 Collective on MPI_Comm 3603 3604 Input Parameters: 3605 + comm - the communicators the parallel matrix will live on 3606 . seqmat - the input sequential matrices 3607 . m - number of local rows (or PETSC_DECIDE) 3608 . n - number of local columns (or PETSC_DECIDE) 3609 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3610 3611 Output Parameter: 3612 . mpimat - the parallel matrix generated 3613 3614 Level: advanced 3615 3616 Notes: 3617 The dimensions of the sequential matrix in each processor MUST be the same. 3618 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3619 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3620 @*/ 3621 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3622 { 3623 PetscErrorCode ierr; 3624 MPI_Comm comm=((PetscObject)mpimat)->comm; 3625 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3626 PetscMPIInt size,rank,taga,*len_s; 3627 PetscInt N=mpimat->cmap.N,i,j,*owners,*ai=a->i,*aj=a->j; 3628 PetscInt proc,m; 3629 PetscInt **buf_ri,**buf_rj; 3630 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3631 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3632 MPI_Request *s_waits,*r_waits; 3633 MPI_Status *status; 3634 MatScalar *aa=a->a,**abuf_r,*ba_i; 3635 Mat_Merge_SeqsToMPI *merge; 3636 PetscContainer container; 3637 3638 PetscFunctionBegin; 3639 if (!logkey_seqstompinum) { 3640 ierr = PetscLogEventRegister(&logkey_seqstompinum,"MatMerge_SeqsToMPINumeric",MAT_COOKIE); 3641 } 3642 ierr = PetscLogEventBegin(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3643 3644 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3645 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3646 3647 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3648 if (container) { 3649 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3650 } 3651 bi = merge->bi; 3652 bj = merge->bj; 3653 buf_ri = merge->buf_ri; 3654 buf_rj = merge->buf_rj; 3655 3656 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3657 owners = merge->rowmap.range; 3658 len_s = merge->len_s; 3659 3660 /* send and recv matrix values */ 3661 /*-----------------------------*/ 3662 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3663 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3664 3665 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3666 for (proc=0,k=0; proc<size; proc++){ 3667 if (!len_s[proc]) continue; 3668 i = owners[proc]; 3669 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3670 k++; 3671 } 3672 3673 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3674 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3675 ierr = PetscFree(status);CHKERRQ(ierr); 3676 3677 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3678 ierr = PetscFree(r_waits);CHKERRQ(ierr); 3679 3680 /* insert mat values of mpimat */ 3681 /*----------------------------*/ 3682 ierr = PetscMalloc(N*sizeof(MatScalar),&ba_i);CHKERRQ(ierr); 3683 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3684 nextrow = buf_ri_k + merge->nrecv; 3685 nextai = nextrow + merge->nrecv; 3686 3687 for (k=0; k<merge->nrecv; k++){ 3688 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3689 nrows = *(buf_ri_k[k]); 3690 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 3691 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3692 } 3693 3694 /* set values of ba */ 3695 m = merge->rowmap.n; 3696 for (i=0; i<m; i++) { 3697 arow = owners[rank] + i; 3698 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 3699 bnzi = bi[i+1] - bi[i]; 3700 ierr = PetscMemzero(ba_i,bnzi*sizeof(MatScalar));CHKERRQ(ierr); 3701 3702 /* add local non-zero vals of this proc's seqmat into ba */ 3703 anzi = ai[arow+1] - ai[arow]; 3704 aj = a->j + ai[arow]; 3705 aa = a->a + ai[arow]; 3706 nextaj = 0; 3707 for (j=0; nextaj<anzi; j++){ 3708 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3709 ba_i[j] += aa[nextaj++]; 3710 } 3711 } 3712 3713 /* add received vals into ba */ 3714 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3715 /* i-th row */ 3716 if (i == *nextrow[k]) { 3717 anzi = *(nextai[k]+1) - *nextai[k]; 3718 aj = buf_rj[k] + *(nextai[k]); 3719 aa = abuf_r[k] + *(nextai[k]); 3720 nextaj = 0; 3721 for (j=0; nextaj<anzi; j++){ 3722 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3723 ba_i[j] += aa[nextaj++]; 3724 } 3725 } 3726 nextrow[k]++; nextai[k]++; 3727 } 3728 } 3729 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 3730 } 3731 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3732 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3733 3734 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 3735 ierr = PetscFree(ba_i);CHKERRQ(ierr); 3736 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3737 ierr = PetscLogEventEnd(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3738 PetscFunctionReturn(0); 3739 } 3740 3741 static PetscEvent logkey_seqstompisym = 0; 3742 #undef __FUNCT__ 3743 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 3744 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 3745 { 3746 PetscErrorCode ierr; 3747 Mat B_mpi; 3748 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3749 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 3750 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 3751 PetscInt M=seqmat->rmap.n,N=seqmat->cmap.n,i,*owners,*ai=a->i,*aj=a->j; 3752 PetscInt len,proc,*dnz,*onz; 3753 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 3754 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 3755 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 3756 MPI_Status *status; 3757 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 3758 PetscBT lnkbt; 3759 Mat_Merge_SeqsToMPI *merge; 3760 PetscContainer container; 3761 3762 PetscFunctionBegin; 3763 if (!logkey_seqstompisym) { 3764 ierr = PetscLogEventRegister(&logkey_seqstompisym,"MatMerge_SeqsToMPISymbolic",MAT_COOKIE); 3765 } 3766 ierr = PetscLogEventBegin(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3767 3768 /* make sure it is a PETSc comm */ 3769 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 3770 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3771 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3772 3773 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 3774 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3775 3776 /* determine row ownership */ 3777 /*---------------------------------------------------------*/ 3778 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 3779 merge->rowmap.n = m; 3780 merge->rowmap.N = M; 3781 merge->rowmap.bs = 1; 3782 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 3783 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 3784 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 3785 3786 m = merge->rowmap.n; 3787 M = merge->rowmap.N; 3788 owners = merge->rowmap.range; 3789 3790 /* determine the number of messages to send, their lengths */ 3791 /*---------------------------------------------------------*/ 3792 len_s = merge->len_s; 3793 3794 len = 0; /* length of buf_si[] */ 3795 merge->nsend = 0; 3796 for (proc=0; proc<size; proc++){ 3797 len_si[proc] = 0; 3798 if (proc == rank){ 3799 len_s[proc] = 0; 3800 } else { 3801 len_si[proc] = owners[proc+1] - owners[proc] + 1; 3802 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 3803 } 3804 if (len_s[proc]) { 3805 merge->nsend++; 3806 nrows = 0; 3807 for (i=owners[proc]; i<owners[proc+1]; i++){ 3808 if (ai[i+1] > ai[i]) nrows++; 3809 } 3810 len_si[proc] = 2*(nrows+1); 3811 len += len_si[proc]; 3812 } 3813 } 3814 3815 /* determine the number and length of messages to receive for ij-structure */ 3816 /*-------------------------------------------------------------------------*/ 3817 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 3818 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 3819 3820 /* post the Irecv of j-structure */ 3821 /*-------------------------------*/ 3822 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 3823 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 3824 3825 /* post the Isend of j-structure */ 3826 /*--------------------------------*/ 3827 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 3828 sj_waits = si_waits + merge->nsend; 3829 3830 for (proc=0, k=0; proc<size; proc++){ 3831 if (!len_s[proc]) continue; 3832 i = owners[proc]; 3833 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 3834 k++; 3835 } 3836 3837 /* receives and sends of j-structure are complete */ 3838 /*------------------------------------------------*/ 3839 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 3840 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 3841 3842 /* send and recv i-structure */ 3843 /*---------------------------*/ 3844 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 3845 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 3846 3847 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 3848 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 3849 for (proc=0,k=0; proc<size; proc++){ 3850 if (!len_s[proc]) continue; 3851 /* form outgoing message for i-structure: 3852 buf_si[0]: nrows to be sent 3853 [1:nrows]: row index (global) 3854 [nrows+1:2*nrows+1]: i-structure index 3855 */ 3856 /*-------------------------------------------*/ 3857 nrows = len_si[proc]/2 - 1; 3858 buf_si_i = buf_si + nrows+1; 3859 buf_si[0] = nrows; 3860 buf_si_i[0] = 0; 3861 nrows = 0; 3862 for (i=owners[proc]; i<owners[proc+1]; i++){ 3863 anzi = ai[i+1] - ai[i]; 3864 if (anzi) { 3865 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 3866 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 3867 nrows++; 3868 } 3869 } 3870 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 3871 k++; 3872 buf_si += len_si[proc]; 3873 } 3874 3875 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 3876 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 3877 3878 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 3879 for (i=0; i<merge->nrecv; i++){ 3880 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); 3881 } 3882 3883 ierr = PetscFree(len_si);CHKERRQ(ierr); 3884 ierr = PetscFree(len_ri);CHKERRQ(ierr); 3885 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 3886 ierr = PetscFree(si_waits);CHKERRQ(ierr); 3887 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 3888 ierr = PetscFree(buf_s);CHKERRQ(ierr); 3889 ierr = PetscFree(status);CHKERRQ(ierr); 3890 3891 /* compute a local seq matrix in each processor */ 3892 /*----------------------------------------------*/ 3893 /* allocate bi array and free space for accumulating nonzero column info */ 3894 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 3895 bi[0] = 0; 3896 3897 /* create and initialize a linked list */ 3898 nlnk = N+1; 3899 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3900 3901 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 3902 len = 0; 3903 len = ai[owners[rank+1]] - ai[owners[rank]]; 3904 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 3905 current_space = free_space; 3906 3907 /* determine symbolic info for each local row */ 3908 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3909 nextrow = buf_ri_k + merge->nrecv; 3910 nextai = nextrow + merge->nrecv; 3911 for (k=0; k<merge->nrecv; k++){ 3912 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3913 nrows = *buf_ri_k[k]; 3914 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 3915 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3916 } 3917 3918 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3919 len = 0; 3920 for (i=0;i<m;i++) { 3921 bnzi = 0; 3922 /* add local non-zero cols of this proc's seqmat into lnk */ 3923 arow = owners[rank] + i; 3924 anzi = ai[arow+1] - ai[arow]; 3925 aj = a->j + ai[arow]; 3926 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3927 bnzi += nlnk; 3928 /* add received col data into lnk */ 3929 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3930 if (i == *nextrow[k]) { /* i-th row */ 3931 anzi = *(nextai[k]+1) - *nextai[k]; 3932 aj = buf_rj[k] + *nextai[k]; 3933 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3934 bnzi += nlnk; 3935 nextrow[k]++; nextai[k]++; 3936 } 3937 } 3938 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 3939 3940 /* if free space is not available, make more free space */ 3941 if (current_space->local_remaining<bnzi) { 3942 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 3943 nspacedouble++; 3944 } 3945 /* copy data into free space, then initialize lnk */ 3946 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 3947 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 3948 3949 current_space->array += bnzi; 3950 current_space->local_used += bnzi; 3951 current_space->local_remaining -= bnzi; 3952 3953 bi[i+1] = bi[i] + bnzi; 3954 } 3955 3956 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3957 3958 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 3959 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 3960 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 3961 3962 /* create symbolic parallel matrix B_mpi */ 3963 /*---------------------------------------*/ 3964 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 3965 if (n==PETSC_DECIDE) { 3966 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 3967 } else { 3968 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3969 } 3970 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 3971 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 3972 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3973 3974 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 3975 B_mpi->assembled = PETSC_FALSE; 3976 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 3977 merge->bi = bi; 3978 merge->bj = bj; 3979 merge->buf_ri = buf_ri; 3980 merge->buf_rj = buf_rj; 3981 merge->coi = PETSC_NULL; 3982 merge->coj = PETSC_NULL; 3983 merge->owners_co = PETSC_NULL; 3984 3985 /* attach the supporting struct to B_mpi for reuse */ 3986 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 3987 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 3988 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 3989 *mpimat = B_mpi; 3990 3991 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 3992 ierr = PetscLogEventEnd(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3993 PetscFunctionReturn(0); 3994 } 3995 3996 static PetscEvent logkey_seqstompi = 0; 3997 #undef __FUNCT__ 3998 #define __FUNCT__ "MatMerge_SeqsToMPI" 3999 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4000 { 4001 PetscErrorCode ierr; 4002 4003 PetscFunctionBegin; 4004 if (!logkey_seqstompi) { 4005 ierr = PetscLogEventRegister(&logkey_seqstompi,"MatMerge_SeqsToMPI",MAT_COOKIE); 4006 } 4007 ierr = PetscLogEventBegin(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4008 if (scall == MAT_INITIAL_MATRIX){ 4009 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4010 } 4011 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4012 ierr = PetscLogEventEnd(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4013 PetscFunctionReturn(0); 4014 } 4015 static PetscEvent logkey_getlocalmat = 0; 4016 #undef __FUNCT__ 4017 #define __FUNCT__ "MatGetLocalMat" 4018 /*@ 4019 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4020 4021 Not Collective 4022 4023 Input Parameters: 4024 + A - the matrix 4025 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4026 4027 Output Parameter: 4028 . A_loc - the local sequential matrix generated 4029 4030 Level: developer 4031 4032 @*/ 4033 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4034 { 4035 PetscErrorCode ierr; 4036 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4037 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4038 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4039 PetscScalar *aa=a->a,*ba=b->a,*ca; 4040 PetscInt am=A->rmap.n,i,j,k,cstart=A->cmap.rstart; 4041 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4042 4043 PetscFunctionBegin; 4044 if (!logkey_getlocalmat) { 4045 ierr = PetscLogEventRegister(&logkey_getlocalmat,"MatGetLocalMat",MAT_COOKIE); 4046 } 4047 ierr = PetscLogEventBegin(logkey_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(logkey_getlocalmat,A,0,0,0);CHKERRQ(ierr); 4110 PetscFunctionReturn(0); 4111 } 4112 4113 static PetscEvent logkey_getlocalmatcondensed = 0; 4114 #undef __FUNCT__ 4115 #define __FUNCT__ "MatGetLocalMatCondensed" 4116 /*@C 4117 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4118 4119 Not Collective 4120 4121 Input Parameters: 4122 + A - the matrix 4123 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4124 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4125 4126 Output Parameter: 4127 . A_loc - the local sequential matrix generated 4128 4129 Level: developer 4130 4131 @*/ 4132 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4133 { 4134 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4135 PetscErrorCode ierr; 4136 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4137 IS isrowa,iscola; 4138 Mat *aloc; 4139 4140 PetscFunctionBegin; 4141 if (!logkey_getlocalmatcondensed) { 4142 ierr = PetscLogEventRegister(&logkey_getlocalmatcondensed,"MatGetLocalMatCondensed",MAT_COOKIE); 4143 } 4144 ierr = PetscLogEventBegin(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4145 if (!row){ 4146 start = A->rmap.rstart; end = A->rmap.rend; 4147 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4148 } else { 4149 isrowa = *row; 4150 } 4151 if (!col){ 4152 start = A->cmap.rstart; 4153 cmap = a->garray; 4154 nzA = a->A->cmap.n; 4155 nzB = a->B->cmap.n; 4156 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4157 ncols = 0; 4158 for (i=0; i<nzB; i++) { 4159 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4160 else break; 4161 } 4162 imark = i; 4163 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4164 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4165 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4166 ierr = PetscFree(idx);CHKERRQ(ierr); 4167 } else { 4168 iscola = *col; 4169 } 4170 if (scall != MAT_INITIAL_MATRIX){ 4171 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4172 aloc[0] = *A_loc; 4173 } 4174 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4175 *A_loc = aloc[0]; 4176 ierr = PetscFree(aloc);CHKERRQ(ierr); 4177 if (!row){ 4178 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4179 } 4180 if (!col){ 4181 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4182 } 4183 ierr = PetscLogEventEnd(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4184 PetscFunctionReturn(0); 4185 } 4186 4187 static PetscEvent logkey_GetBrowsOfAcols = 0; 4188 #undef __FUNCT__ 4189 #define __FUNCT__ "MatGetBrowsOfAcols" 4190 /*@C 4191 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4192 4193 Collective on Mat 4194 4195 Input Parameters: 4196 + A,B - the matrices in mpiaij format 4197 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4198 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4199 4200 Output Parameter: 4201 + rowb, colb - index sets of rows and columns of B to extract 4202 . brstart - row index of B_seq from which next B->rmap.n rows are taken from B's local rows 4203 - B_seq - the sequential matrix generated 4204 4205 Level: developer 4206 4207 @*/ 4208 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4209 { 4210 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4211 PetscErrorCode ierr; 4212 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4213 IS isrowb,iscolb; 4214 Mat *bseq; 4215 4216 PetscFunctionBegin; 4217 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4218 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); 4219 } 4220 if (!logkey_GetBrowsOfAcols) { 4221 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAcols,"MatGetBrowsOfAcols",MAT_COOKIE); 4222 } 4223 ierr = PetscLogEventBegin(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4224 4225 if (scall == MAT_INITIAL_MATRIX){ 4226 start = A->cmap.rstart; 4227 cmap = a->garray; 4228 nzA = a->A->cmap.n; 4229 nzB = a->B->cmap.n; 4230 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4231 ncols = 0; 4232 for (i=0; i<nzB; i++) { /* row < local row index */ 4233 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4234 else break; 4235 } 4236 imark = i; 4237 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4238 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4239 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4240 ierr = PetscFree(idx);CHKERRQ(ierr); 4241 *brstart = imark; 4242 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap.N,0,1,&iscolb);CHKERRQ(ierr); 4243 } else { 4244 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4245 isrowb = *rowb; iscolb = *colb; 4246 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4247 bseq[0] = *B_seq; 4248 } 4249 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4250 *B_seq = bseq[0]; 4251 ierr = PetscFree(bseq);CHKERRQ(ierr); 4252 if (!rowb){ 4253 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4254 } else { 4255 *rowb = isrowb; 4256 } 4257 if (!colb){ 4258 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4259 } else { 4260 *colb = iscolb; 4261 } 4262 ierr = PetscLogEventEnd(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4263 PetscFunctionReturn(0); 4264 } 4265 4266 static PetscEvent logkey_GetBrowsOfAocols = 0; 4267 #undef __FUNCT__ 4268 #define __FUNCT__ "MatGetBrowsOfAoCols" 4269 /*@C 4270 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4271 of the OFF-DIAGONAL portion of local A 4272 4273 Collective on Mat 4274 4275 Input Parameters: 4276 + A,B - the matrices in mpiaij format 4277 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4278 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4279 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4280 4281 Output Parameter: 4282 + B_oth - the sequential matrix generated 4283 4284 Level: developer 4285 4286 @*/ 4287 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,PetscScalar **bufa_ptr,Mat *B_oth) 4288 { 4289 VecScatter_MPI_General *gen_to,*gen_from; 4290 PetscErrorCode ierr; 4291 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4292 Mat_SeqAIJ *b_oth; 4293 VecScatter ctx=a->Mvctx; 4294 MPI_Comm comm=((PetscObject)ctx)->comm; 4295 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4296 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap.n,row,*b_othi,*b_othj; 4297 PetscScalar *rvalues,*svalues,*b_otha,*bufa,*bufA; 4298 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4299 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4300 MPI_Status *sstatus,rstatus; 4301 PetscMPIInt jj; 4302 PetscInt *cols,sbs,rbs; 4303 PetscScalar *vals; 4304 4305 PetscFunctionBegin; 4306 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4307 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); 4308 } 4309 if (!logkey_GetBrowsOfAocols) { 4310 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAocols,"MatGetBrAoCol",MAT_COOKIE); 4311 } 4312 ierr = PetscLogEventBegin(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4313 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4314 4315 gen_to = (VecScatter_MPI_General*)ctx->todata; 4316 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4317 rvalues = gen_from->values; /* holds the length of receiving row */ 4318 svalues = gen_to->values; /* holds the length of sending row */ 4319 nrecvs = gen_from->n; 4320 nsends = gen_to->n; 4321 4322 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4323 srow = gen_to->indices; /* local row index to be sent */ 4324 sstarts = gen_to->starts; 4325 sprocs = gen_to->procs; 4326 sstatus = gen_to->sstatus; 4327 sbs = gen_to->bs; 4328 rstarts = gen_from->starts; 4329 rprocs = gen_from->procs; 4330 rbs = gen_from->bs; 4331 4332 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4333 if (scall == MAT_INITIAL_MATRIX){ 4334 /* i-array */ 4335 /*---------*/ 4336 /* post receives */ 4337 for (i=0; i<nrecvs; i++){ 4338 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4339 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4340 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4341 } 4342 4343 /* pack the outgoing message */ 4344 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4345 rstartsj = sstartsj + nsends +1; 4346 sstartsj[0] = 0; rstartsj[0] = 0; 4347 len = 0; /* total length of j or a array to be sent */ 4348 k = 0; 4349 for (i=0; i<nsends; i++){ 4350 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4351 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4352 for (j=0; j<nrows; j++) { 4353 row = srow[k] + B->rmap.range[rank]; /* global row idx */ 4354 for (l=0; l<sbs; l++){ 4355 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4356 rowlen[j*sbs+l] = ncols; 4357 len += ncols; 4358 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4359 } 4360 k++; 4361 } 4362 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4363 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4364 } 4365 /* recvs and sends of i-array are completed */ 4366 i = nrecvs; 4367 while (i--) { 4368 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4369 } 4370 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4371 4372 /* allocate buffers for sending j and a arrays */ 4373 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4374 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4375 4376 /* create i-array of B_oth */ 4377 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4378 b_othi[0] = 0; 4379 len = 0; /* total length of j or a array to be received */ 4380 k = 0; 4381 for (i=0; i<nrecvs; i++){ 4382 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4383 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4384 for (j=0; j<nrows; j++) { 4385 b_othi[k+1] = b_othi[k] + rowlen[j]; 4386 len += rowlen[j]; k++; 4387 } 4388 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4389 } 4390 4391 /* allocate space for j and a arrrays of B_oth */ 4392 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4393 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscScalar),&b_otha);CHKERRQ(ierr); 4394 4395 /* j-array */ 4396 /*---------*/ 4397 /* post receives of j-array */ 4398 for (i=0; i<nrecvs; i++){ 4399 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4400 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4401 } 4402 4403 /* pack the outgoing message j-array */ 4404 k = 0; 4405 for (i=0; i<nsends; i++){ 4406 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4407 bufJ = bufj+sstartsj[i]; 4408 for (j=0; j<nrows; j++) { 4409 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4410 for (ll=0; ll<sbs; ll++){ 4411 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4412 for (l=0; l<ncols; l++){ 4413 *bufJ++ = cols[l]; 4414 } 4415 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4416 } 4417 } 4418 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4419 } 4420 4421 /* recvs and sends of j-array are completed */ 4422 i = nrecvs; 4423 while (i--) { 4424 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4425 } 4426 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4427 } else if (scall == MAT_REUSE_MATRIX){ 4428 sstartsj = *startsj; 4429 rstartsj = sstartsj + nsends +1; 4430 bufa = *bufa_ptr; 4431 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4432 b_otha = b_oth->a; 4433 } else { 4434 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4435 } 4436 4437 /* a-array */ 4438 /*---------*/ 4439 /* post receives of a-array */ 4440 for (i=0; i<nrecvs; i++){ 4441 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4442 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4443 } 4444 4445 /* pack the outgoing message a-array */ 4446 k = 0; 4447 for (i=0; i<nsends; i++){ 4448 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4449 bufA = bufa+sstartsj[i]; 4450 for (j=0; j<nrows; j++) { 4451 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4452 for (ll=0; ll<sbs; ll++){ 4453 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4454 for (l=0; l<ncols; l++){ 4455 *bufA++ = vals[l]; 4456 } 4457 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4458 } 4459 } 4460 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4461 } 4462 /* recvs and sends of a-array are completed */ 4463 i = nrecvs; 4464 while (i--) { 4465 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4466 } 4467 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4468 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4469 4470 if (scall == MAT_INITIAL_MATRIX){ 4471 /* put together the new matrix */ 4472 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap.N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4473 4474 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4475 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4476 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4477 b_oth->free_a = PETSC_TRUE; 4478 b_oth->free_ij = PETSC_TRUE; 4479 b_oth->nonew = 0; 4480 4481 ierr = PetscFree(bufj);CHKERRQ(ierr); 4482 if (!startsj || !bufa_ptr){ 4483 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4484 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4485 } else { 4486 *startsj = sstartsj; 4487 *bufa_ptr = bufa; 4488 } 4489 } 4490 ierr = PetscLogEventEnd(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4491 PetscFunctionReturn(0); 4492 } 4493 4494 #undef __FUNCT__ 4495 #define __FUNCT__ "MatGetCommunicationStructs" 4496 /*@C 4497 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4498 4499 Not Collective 4500 4501 Input Parameters: 4502 . A - The matrix in mpiaij format 4503 4504 Output Parameter: 4505 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4506 . colmap - A map from global column index to local index into lvec 4507 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4508 4509 Level: developer 4510 4511 @*/ 4512 #if defined (PETSC_USE_CTABLE) 4513 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4514 #else 4515 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4516 #endif 4517 { 4518 Mat_MPIAIJ *a; 4519 4520 PetscFunctionBegin; 4521 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4522 PetscValidPointer(lvec, 2) 4523 PetscValidPointer(colmap, 3) 4524 PetscValidPointer(multScatter, 4) 4525 a = (Mat_MPIAIJ *) A->data; 4526 if (lvec) *lvec = a->lvec; 4527 if (colmap) *colmap = a->colmap; 4528 if (multScatter) *multScatter = a->Mvctx; 4529 PetscFunctionReturn(0); 4530 } 4531 4532 EXTERN_C_BEGIN 4533 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,MatType,MatReuse,Mat*); 4534 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,MatType,MatReuse,Mat*); 4535 EXTERN_C_END 4536 4537 /*MC 4538 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4539 4540 Options Database Keys: 4541 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4542 4543 Level: beginner 4544 4545 .seealso: MatCreateMPIAIJ() 4546 M*/ 4547 4548 EXTERN_C_BEGIN 4549 #undef __FUNCT__ 4550 #define __FUNCT__ "MatCreate_MPIAIJ" 4551 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4552 { 4553 Mat_MPIAIJ *b; 4554 PetscErrorCode ierr; 4555 PetscMPIInt size; 4556 4557 PetscFunctionBegin; 4558 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4559 4560 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4561 B->data = (void*)b; 4562 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4563 B->factor = 0; 4564 B->rmap.bs = 1; 4565 B->assembled = PETSC_FALSE; 4566 B->mapping = 0; 4567 4568 B->insertmode = NOT_SET_VALUES; 4569 b->size = size; 4570 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4571 4572 /* build cache for off array entries formed */ 4573 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4574 b->donotstash = PETSC_FALSE; 4575 b->colmap = 0; 4576 b->garray = 0; 4577 b->roworiented = PETSC_TRUE; 4578 4579 /* stuff used for matrix vector multiply */ 4580 b->lvec = PETSC_NULL; 4581 b->Mvctx = PETSC_NULL; 4582 4583 /* stuff for MatGetRow() */ 4584 b->rowindices = 0; 4585 b->rowvalues = 0; 4586 b->getrowactive = PETSC_FALSE; 4587 4588 4589 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4590 "MatStoreValues_MPIAIJ", 4591 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4592 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4593 "MatRetrieveValues_MPIAIJ", 4594 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4595 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4596 "MatGetDiagonalBlock_MPIAIJ", 4597 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4598 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4599 "MatIsTranspose_MPIAIJ", 4600 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4601 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4602 "MatMPIAIJSetPreallocation_MPIAIJ", 4603 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4604 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4605 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4606 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4607 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4608 "MatDiagonalScaleLocal_MPIAIJ", 4609 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4610 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 4611 "MatConvert_MPIAIJ_MPICSRPERM", 4612 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 4613 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 4614 "MatConvert_MPIAIJ_MPICRL", 4615 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 4616 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 4617 PetscFunctionReturn(0); 4618 } 4619 EXTERN_C_END 4620 4621 #undef __FUNCT__ 4622 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 4623 /*@ 4624 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 4625 and "off-diagonal" part of the matrix in CSR format. 4626 4627 Collective on MPI_Comm 4628 4629 Input Parameters: 4630 + comm - MPI communicator 4631 . m - number of local rows (Cannot be PETSC_DECIDE) 4632 . n - This value should be the same as the local size used in creating the 4633 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4634 calculated if N is given) For square matrices n is almost always m. 4635 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4636 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4637 . i - row indices for "diagonal" portion of matrix 4638 . j - column indices 4639 . a - matrix values 4640 . oi - row indices for "off-diagonal" portion of matrix 4641 . oj - column indices 4642 - oa - matrix values 4643 4644 Output Parameter: 4645 . mat - the matrix 4646 4647 Level: advanced 4648 4649 Notes: 4650 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 4651 4652 The i and j indices are 0 based 4653 4654 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 4655 4656 4657 .keywords: matrix, aij, compressed row, sparse, parallel 4658 4659 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4660 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 4661 @*/ 4662 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 4663 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 4664 { 4665 PetscErrorCode ierr; 4666 Mat_MPIAIJ *maij; 4667 4668 PetscFunctionBegin; 4669 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4670 if (i[0]) { 4671 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4672 } 4673 if (oi[0]) { 4674 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 4675 } 4676 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4677 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4678 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4679 maij = (Mat_MPIAIJ*) (*mat)->data; 4680 maij->donotstash = PETSC_TRUE; 4681 (*mat)->preallocated = PETSC_TRUE; 4682 4683 (*mat)->rmap.bs = (*mat)->cmap.bs = 1; 4684 ierr = PetscMapSetUp(&(*mat)->rmap);CHKERRQ(ierr); 4685 ierr = PetscMapSetUp(&(*mat)->cmap);CHKERRQ(ierr); 4686 4687 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 4688 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap.N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 4689 4690 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4691 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4692 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4693 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4694 4695 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4696 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4697 PetscFunctionReturn(0); 4698 } 4699 4700 /* 4701 Special version for direct calls from Fortran 4702 */ 4703 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4704 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 4705 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4706 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 4707 #endif 4708 4709 /* Change these macros so can be used in void function */ 4710 #undef CHKERRQ 4711 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4712 #undef SETERRQ2 4713 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4714 #undef SETERRQ 4715 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4716 4717 EXTERN_C_BEGIN 4718 #undef __FUNCT__ 4719 #define __FUNCT__ "matsetvaluesmpiaij_" 4720 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 4721 { 4722 Mat mat = *mmat; 4723 PetscInt m = *mm, n = *mn; 4724 InsertMode addv = *maddv; 4725 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 4726 PetscScalar value; 4727 PetscErrorCode ierr; 4728 4729 MatPreallocated(mat); 4730 if (mat->insertmode == NOT_SET_VALUES) { 4731 mat->insertmode = addv; 4732 } 4733 #if defined(PETSC_USE_DEBUG) 4734 else if (mat->insertmode != addv) { 4735 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 4736 } 4737 #endif 4738 { 4739 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 4740 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 4741 PetscTruth roworiented = aij->roworiented; 4742 4743 /* Some Variables required in the macro */ 4744 Mat A = aij->A; 4745 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4746 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 4747 PetscScalar *aa = a->a; 4748 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 4749 Mat B = aij->B; 4750 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 4751 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 4752 PetscScalar *ba = b->a; 4753 4754 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 4755 PetscInt nonew = a->nonew; 4756 PetscScalar *ap1,*ap2; 4757 4758 PetscFunctionBegin; 4759 for (i=0; i<m; i++) { 4760 if (im[i] < 0) continue; 4761 #if defined(PETSC_USE_DEBUG) 4762 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 4763 #endif 4764 if (im[i] >= rstart && im[i] < rend) { 4765 row = im[i] - rstart; 4766 lastcol1 = -1; 4767 rp1 = aj + ai[row]; 4768 ap1 = aa + ai[row]; 4769 rmax1 = aimax[row]; 4770 nrow1 = ailen[row]; 4771 low1 = 0; 4772 high1 = nrow1; 4773 lastcol2 = -1; 4774 rp2 = bj + bi[row]; 4775 ap2 = ba + bi[row]; 4776 rmax2 = bimax[row]; 4777 nrow2 = bilen[row]; 4778 low2 = 0; 4779 high2 = nrow2; 4780 4781 for (j=0; j<n; j++) { 4782 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 4783 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 4784 if (in[j] >= cstart && in[j] < cend){ 4785 col = in[j] - cstart; 4786 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 4787 } else if (in[j] < 0) continue; 4788 #if defined(PETSC_USE_DEBUG) 4789 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);} 4790 #endif 4791 else { 4792 if (mat->was_assembled) { 4793 if (!aij->colmap) { 4794 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 4795 } 4796 #if defined (PETSC_USE_CTABLE) 4797 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4798 col--; 4799 #else 4800 col = aij->colmap[in[j]] - 1; 4801 #endif 4802 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 4803 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 4804 col = in[j]; 4805 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 4806 B = aij->B; 4807 b = (Mat_SeqAIJ*)B->data; 4808 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 4809 rp2 = bj + bi[row]; 4810 ap2 = ba + bi[row]; 4811 rmax2 = bimax[row]; 4812 nrow2 = bilen[row]; 4813 low2 = 0; 4814 high2 = nrow2; 4815 bm = aij->B->rmap.n; 4816 ba = b->a; 4817 } 4818 } else col = in[j]; 4819 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 4820 } 4821 } 4822 } else { 4823 if (!aij->donotstash) { 4824 if (roworiented) { 4825 if (ignorezeroentries && v[i*n] == 0.0) continue; 4826 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 4827 } else { 4828 if (ignorezeroentries && v[i] == 0.0) continue; 4829 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 4830 } 4831 } 4832 } 4833 }} 4834 PetscFunctionReturnVoid(); 4835 } 4836 EXTERN_C_END 4837 4838