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 (diagA[r] <= 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 for (i=0; i<m; i++) { 2825 nnz = Ii[i+1]- Ii[i]; 2826 JJ = J + Ii[i]; 2827 nnz_max = PetscMax(nnz_max,nnz); 2828 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 2829 for (j=0; j<nnz; j++) { 2830 if (*JJ >= cstart) break; 2831 JJ++; 2832 } 2833 d = 0; 2834 for (; j<nnz; j++) { 2835 if (*JJ++ >= cend) break; 2836 d++; 2837 } 2838 d_nnz[i] = d; 2839 o_nnz[i] = nnz - d; 2840 } 2841 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2842 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2843 2844 if (v) values = (PetscScalar*)v; 2845 else { 2846 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2847 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2848 } 2849 2850 for (i=0; i<m; i++) { 2851 ii = i + rstart; 2852 nnz = Ii[i+1]- Ii[i]; 2853 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 2854 } 2855 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2856 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2857 2858 if (!v) { 2859 ierr = PetscFree(values);CHKERRQ(ierr); 2860 } 2861 PetscFunctionReturn(0); 2862 } 2863 EXTERN_C_END 2864 2865 #undef __FUNCT__ 2866 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 2867 /*@ 2868 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2869 (the default parallel PETSc format). 2870 2871 Collective on MPI_Comm 2872 2873 Input Parameters: 2874 + B - the matrix 2875 . i - the indices into j for the start of each local row (starts with zero) 2876 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2877 - v - optional values in the matrix 2878 2879 Level: developer 2880 2881 Notes: this actually copies the values from i[], j[], and a[] to put them into PETSc's internal 2882 storage format. Thus changing the values in a[] after this call will not effect the matrix values. 2883 2884 .keywords: matrix, aij, compressed row, sparse, parallel 2885 2886 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 2887 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 2888 @*/ 2889 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2890 { 2891 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 2892 2893 PetscFunctionBegin; 2894 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2895 if (f) { 2896 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 2897 } 2898 PetscFunctionReturn(0); 2899 } 2900 2901 #undef __FUNCT__ 2902 #define __FUNCT__ "MatMPIAIJSetPreallocation" 2903 /*@C 2904 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 2905 (the default parallel PETSc format). For good matrix assembly performance 2906 the user should preallocate the matrix storage by setting the parameters 2907 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2908 performance can be increased by more than a factor of 50. 2909 2910 Collective on MPI_Comm 2911 2912 Input Parameters: 2913 + A - the matrix 2914 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2915 (same value is used for all local rows) 2916 . d_nnz - array containing the number of nonzeros in the various rows of the 2917 DIAGONAL portion of the local submatrix (possibly different for each row) 2918 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2919 The size of this array is equal to the number of local rows, i.e 'm'. 2920 You must leave room for the diagonal entry even if it is zero. 2921 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2922 submatrix (same value is used for all local rows). 2923 - o_nnz - array containing the number of nonzeros in the various rows of the 2924 OFF-DIAGONAL portion of the local submatrix (possibly different for 2925 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2926 structure. The size of this array is equal to the number 2927 of local rows, i.e 'm'. 2928 2929 If the *_nnz parameter is given then the *_nz parameter is ignored 2930 2931 The AIJ format (also called the Yale sparse matrix format or 2932 compressed row storage (CSR)), is fully compatible with standard Fortran 77 2933 storage. The stored row and column indices begin with zero. See the users manual for details. 2934 2935 The parallel matrix is partitioned such that the first m0 rows belong to 2936 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2937 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2938 2939 The DIAGONAL portion of the local submatrix of a processor can be defined 2940 as the submatrix which is obtained by extraction the part corresponding 2941 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2942 first row that belongs to the processor, and r2 is the last row belonging 2943 to the this processor. This is a square mxm matrix. The remaining portion 2944 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2945 2946 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2947 2948 Example usage: 2949 2950 Consider the following 8x8 matrix with 34 non-zero values, that is 2951 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2952 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2953 as follows: 2954 2955 .vb 2956 1 2 0 | 0 3 0 | 0 4 2957 Proc0 0 5 6 | 7 0 0 | 8 0 2958 9 0 10 | 11 0 0 | 12 0 2959 ------------------------------------- 2960 13 0 14 | 15 16 17 | 0 0 2961 Proc1 0 18 0 | 19 20 21 | 0 0 2962 0 0 0 | 22 23 0 | 24 0 2963 ------------------------------------- 2964 Proc2 25 26 27 | 0 0 28 | 29 0 2965 30 0 0 | 31 32 33 | 0 34 2966 .ve 2967 2968 This can be represented as a collection of submatrices as: 2969 2970 .vb 2971 A B C 2972 D E F 2973 G H I 2974 .ve 2975 2976 Where the submatrices A,B,C are owned by proc0, D,E,F are 2977 owned by proc1, G,H,I are owned by proc2. 2978 2979 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2980 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2981 The 'M','N' parameters are 8,8, and have the same values on all procs. 2982 2983 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2984 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2985 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2986 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2987 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2988 matrix, ans [DF] as another SeqAIJ matrix. 2989 2990 When d_nz, o_nz parameters are specified, d_nz storage elements are 2991 allocated for every row of the local diagonal submatrix, and o_nz 2992 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2993 One way to choose d_nz and o_nz is to use the max nonzerors per local 2994 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2995 In this case, the values of d_nz,o_nz are: 2996 .vb 2997 proc0 : dnz = 2, o_nz = 2 2998 proc1 : dnz = 3, o_nz = 2 2999 proc2 : dnz = 1, o_nz = 4 3000 .ve 3001 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3002 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3003 for proc3. i.e we are using 12+15+10=37 storage locations to store 3004 34 values. 3005 3006 When d_nnz, o_nnz parameters are specified, the storage is specified 3007 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3008 In the above case the values for d_nnz,o_nnz are: 3009 .vb 3010 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3011 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3012 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3013 .ve 3014 Here the space allocated is sum of all the above values i.e 34, and 3015 hence pre-allocation is perfect. 3016 3017 Level: intermediate 3018 3019 .keywords: matrix, aij, compressed row, sparse, parallel 3020 3021 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3022 MPIAIJ 3023 @*/ 3024 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3025 { 3026 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3027 3028 PetscFunctionBegin; 3029 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3030 if (f) { 3031 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3032 } 3033 PetscFunctionReturn(0); 3034 } 3035 3036 #undef __FUNCT__ 3037 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3038 /*@ 3039 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3040 CSR format the local rows. 3041 3042 Collective on MPI_Comm 3043 3044 Input Parameters: 3045 + comm - MPI communicator 3046 . m - number of local rows (Cannot be PETSC_DECIDE) 3047 . n - This value should be the same as the local size used in creating the 3048 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3049 calculated if N is given) For square matrices n is almost always m. 3050 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3051 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3052 . i - row indices 3053 . j - column indices 3054 - a - matrix values 3055 3056 Output Parameter: 3057 . mat - the matrix 3058 3059 Level: intermediate 3060 3061 Notes: 3062 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3063 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3064 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3065 3066 The i and j indices are 0 based 3067 3068 .keywords: matrix, aij, compressed row, sparse, parallel 3069 3070 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3071 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3072 @*/ 3073 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) 3074 { 3075 PetscErrorCode ierr; 3076 3077 PetscFunctionBegin; 3078 if (i[0]) { 3079 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3080 } 3081 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3082 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3083 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3084 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3085 PetscFunctionReturn(0); 3086 } 3087 3088 #undef __FUNCT__ 3089 #define __FUNCT__ "MatCreateMPIAIJ" 3090 /*@C 3091 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3092 (the default parallel PETSc format). For good matrix assembly performance 3093 the user should preallocate the matrix storage by setting the parameters 3094 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3095 performance can be increased by more than a factor of 50. 3096 3097 Collective on MPI_Comm 3098 3099 Input Parameters: 3100 + comm - MPI communicator 3101 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3102 This value should be the same as the local size used in creating the 3103 y vector for the matrix-vector product y = Ax. 3104 . n - This value should be the same as the local size used in creating the 3105 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3106 calculated if N is given) For square matrices n is almost always m. 3107 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3108 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3109 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3110 (same value is used for all local rows) 3111 . d_nnz - array containing the number of nonzeros in the various rows of the 3112 DIAGONAL portion of the local submatrix (possibly different for each row) 3113 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3114 The size of this array is equal to the number of local rows, i.e 'm'. 3115 You must leave room for the diagonal entry even if it is zero. 3116 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3117 submatrix (same value is used for all local rows). 3118 - o_nnz - array containing the number of nonzeros in the various rows of the 3119 OFF-DIAGONAL portion of the local submatrix (possibly different for 3120 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3121 structure. The size of this array is equal to the number 3122 of local rows, i.e 'm'. 3123 3124 Output Parameter: 3125 . A - the matrix 3126 3127 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3128 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3129 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3130 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3131 3132 Notes: 3133 If the *_nnz parameter is given then the *_nz parameter is ignored 3134 3135 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3136 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3137 storage requirements for this matrix. 3138 3139 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3140 processor than it must be used on all processors that share the object for 3141 that argument. 3142 3143 The user MUST specify either the local or global matrix dimensions 3144 (possibly both). 3145 3146 The parallel matrix is partitioned across processors such that the 3147 first m0 rows belong to process 0, the next m1 rows belong to 3148 process 1, the next m2 rows belong to process 2 etc.. where 3149 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3150 values corresponding to [m x N] submatrix. 3151 3152 The columns are logically partitioned with the n0 columns belonging 3153 to 0th partition, the next n1 columns belonging to the next 3154 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3155 3156 The DIAGONAL portion of the local submatrix on any given processor 3157 is the submatrix corresponding to the rows and columns m,n 3158 corresponding to the given processor. i.e diagonal matrix on 3159 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3160 etc. The remaining portion of the local submatrix [m x (N-n)] 3161 constitute the OFF-DIAGONAL portion. The example below better 3162 illustrates this concept. 3163 3164 For a square global matrix we define each processor's diagonal portion 3165 to be its local rows and the corresponding columns (a square submatrix); 3166 each processor's off-diagonal portion encompasses the remainder of the 3167 local matrix (a rectangular submatrix). 3168 3169 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3170 3171 When calling this routine with a single process communicator, a matrix of 3172 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3173 type of communicator, use the construction mechanism: 3174 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3175 3176 By default, this format uses inodes (identical nodes) when possible. 3177 We search for consecutive rows with the same nonzero structure, thereby 3178 reusing matrix information to achieve increased efficiency. 3179 3180 Options Database Keys: 3181 + -mat_no_inode - Do not use inodes 3182 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3183 - -mat_aij_oneindex - Internally use indexing starting at 1 3184 rather than 0. Note that when calling MatSetValues(), 3185 the user still MUST index entries starting at 0! 3186 3187 3188 Example usage: 3189 3190 Consider the following 8x8 matrix with 34 non-zero values, that is 3191 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3192 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3193 as follows: 3194 3195 .vb 3196 1 2 0 | 0 3 0 | 0 4 3197 Proc0 0 5 6 | 7 0 0 | 8 0 3198 9 0 10 | 11 0 0 | 12 0 3199 ------------------------------------- 3200 13 0 14 | 15 16 17 | 0 0 3201 Proc1 0 18 0 | 19 20 21 | 0 0 3202 0 0 0 | 22 23 0 | 24 0 3203 ------------------------------------- 3204 Proc2 25 26 27 | 0 0 28 | 29 0 3205 30 0 0 | 31 32 33 | 0 34 3206 .ve 3207 3208 This can be represented as a collection of submatrices as: 3209 3210 .vb 3211 A B C 3212 D E F 3213 G H I 3214 .ve 3215 3216 Where the submatrices A,B,C are owned by proc0, D,E,F are 3217 owned by proc1, G,H,I are owned by proc2. 3218 3219 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3220 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3221 The 'M','N' parameters are 8,8, and have the same values on all procs. 3222 3223 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3224 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3225 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3226 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3227 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3228 matrix, ans [DF] as another SeqAIJ matrix. 3229 3230 When d_nz, o_nz parameters are specified, d_nz storage elements are 3231 allocated for every row of the local diagonal submatrix, and o_nz 3232 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3233 One way to choose d_nz and o_nz is to use the max nonzerors per local 3234 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3235 In this case, the values of d_nz,o_nz are: 3236 .vb 3237 proc0 : dnz = 2, o_nz = 2 3238 proc1 : dnz = 3, o_nz = 2 3239 proc2 : dnz = 1, o_nz = 4 3240 .ve 3241 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3242 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3243 for proc3. i.e we are using 12+15+10=37 storage locations to store 3244 34 values. 3245 3246 When d_nnz, o_nnz parameters are specified, the storage is specified 3247 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3248 In the above case the values for d_nnz,o_nnz are: 3249 .vb 3250 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3251 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3252 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3253 .ve 3254 Here the space allocated is sum of all the above values i.e 34, and 3255 hence pre-allocation is perfect. 3256 3257 Level: intermediate 3258 3259 .keywords: matrix, aij, compressed row, sparse, parallel 3260 3261 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3262 MPIAIJ, MatCreateMPIAIJWithArrays() 3263 @*/ 3264 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) 3265 { 3266 PetscErrorCode ierr; 3267 PetscMPIInt size; 3268 3269 PetscFunctionBegin; 3270 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3271 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3272 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3273 if (size > 1) { 3274 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3275 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3276 } else { 3277 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3278 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3279 } 3280 PetscFunctionReturn(0); 3281 } 3282 3283 #undef __FUNCT__ 3284 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3285 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3286 { 3287 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3288 3289 PetscFunctionBegin; 3290 *Ad = a->A; 3291 *Ao = a->B; 3292 *colmap = a->garray; 3293 PetscFunctionReturn(0); 3294 } 3295 3296 #undef __FUNCT__ 3297 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3298 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3299 { 3300 PetscErrorCode ierr; 3301 PetscInt i; 3302 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3303 3304 PetscFunctionBegin; 3305 if (coloring->ctype == IS_COLORING_GLOBAL) { 3306 ISColoringValue *allcolors,*colors; 3307 ISColoring ocoloring; 3308 3309 /* set coloring for diagonal portion */ 3310 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3311 3312 /* set coloring for off-diagonal portion */ 3313 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3314 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3315 for (i=0; i<a->B->cmap.n; i++) { 3316 colors[i] = allcolors[a->garray[i]]; 3317 } 3318 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3319 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3320 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3321 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3322 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3323 ISColoringValue *colors; 3324 PetscInt *larray; 3325 ISColoring ocoloring; 3326 3327 /* set coloring for diagonal portion */ 3328 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3329 for (i=0; i<a->A->cmap.n; i++) { 3330 larray[i] = i + A->cmap.rstart; 3331 } 3332 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap.n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3333 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3334 for (i=0; i<a->A->cmap.n; i++) { 3335 colors[i] = coloring->colors[larray[i]]; 3336 } 3337 ierr = PetscFree(larray);CHKERRQ(ierr); 3338 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3339 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3340 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3341 3342 /* set coloring for off-diagonal portion */ 3343 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3344 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap.n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3345 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3346 for (i=0; i<a->B->cmap.n; i++) { 3347 colors[i] = coloring->colors[larray[i]]; 3348 } 3349 ierr = PetscFree(larray);CHKERRQ(ierr); 3350 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3351 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3352 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3353 } else { 3354 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3355 } 3356 3357 PetscFunctionReturn(0); 3358 } 3359 3360 #if defined(PETSC_HAVE_ADIC) 3361 #undef __FUNCT__ 3362 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3363 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3364 { 3365 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3366 PetscErrorCode ierr; 3367 3368 PetscFunctionBegin; 3369 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3370 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3371 PetscFunctionReturn(0); 3372 } 3373 #endif 3374 3375 #undef __FUNCT__ 3376 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3377 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3378 { 3379 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3380 PetscErrorCode ierr; 3381 3382 PetscFunctionBegin; 3383 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3384 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3385 PetscFunctionReturn(0); 3386 } 3387 3388 #undef __FUNCT__ 3389 #define __FUNCT__ "MatMerge" 3390 /*@ 3391 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3392 matrices from each processor 3393 3394 Collective on MPI_Comm 3395 3396 Input Parameters: 3397 + comm - the communicators the parallel matrix will live on 3398 . inmat - the input sequential matrices 3399 . n - number of local columns (or PETSC_DECIDE) 3400 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3401 3402 Output Parameter: 3403 . outmat - the parallel matrix generated 3404 3405 Level: advanced 3406 3407 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3408 3409 @*/ 3410 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3411 { 3412 PetscErrorCode ierr; 3413 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3414 PetscInt *indx; 3415 PetscScalar *values; 3416 3417 PetscFunctionBegin; 3418 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3419 if (scall == MAT_INITIAL_MATRIX){ 3420 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3421 if (n == PETSC_DECIDE){ 3422 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3423 } 3424 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3425 rstart -= m; 3426 3427 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3428 for (i=0;i<m;i++) { 3429 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3430 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3431 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3432 } 3433 /* This routine will ONLY return MPIAIJ type matrix */ 3434 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3435 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3436 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3437 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3438 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3439 3440 } else if (scall == MAT_REUSE_MATRIX){ 3441 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3442 } else { 3443 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3444 } 3445 3446 for (i=0;i<m;i++) { 3447 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3448 Ii = i + rstart; 3449 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3450 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3451 } 3452 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3453 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3454 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3455 3456 PetscFunctionReturn(0); 3457 } 3458 3459 #undef __FUNCT__ 3460 #define __FUNCT__ "MatFileSplit" 3461 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3462 { 3463 PetscErrorCode ierr; 3464 PetscMPIInt rank; 3465 PetscInt m,N,i,rstart,nnz; 3466 size_t len; 3467 const PetscInt *indx; 3468 PetscViewer out; 3469 char *name; 3470 Mat B; 3471 const PetscScalar *values; 3472 3473 PetscFunctionBegin; 3474 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3475 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3476 /* Should this be the type of the diagonal block of A? */ 3477 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3478 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3479 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3480 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3481 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3482 for (i=0;i<m;i++) { 3483 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3484 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3485 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3486 } 3487 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3488 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3489 3490 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3491 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3492 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3493 sprintf(name,"%s.%d",outfile,rank); 3494 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3495 ierr = PetscFree(name); 3496 ierr = MatView(B,out);CHKERRQ(ierr); 3497 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3498 ierr = MatDestroy(B);CHKERRQ(ierr); 3499 PetscFunctionReturn(0); 3500 } 3501 3502 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3503 #undef __FUNCT__ 3504 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3505 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3506 { 3507 PetscErrorCode ierr; 3508 Mat_Merge_SeqsToMPI *merge; 3509 PetscContainer container; 3510 3511 PetscFunctionBegin; 3512 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3513 if (container) { 3514 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3515 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3516 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3517 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3518 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3519 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3520 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3521 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3522 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3523 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3524 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3525 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3526 3527 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3528 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3529 } 3530 ierr = PetscFree(merge);CHKERRQ(ierr); 3531 3532 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3533 PetscFunctionReturn(0); 3534 } 3535 3536 #include "src/mat/utils/freespace.h" 3537 #include "petscbt.h" 3538 static PetscEvent logkey_seqstompinum = 0; 3539 #undef __FUNCT__ 3540 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3541 /*@C 3542 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3543 matrices from each processor 3544 3545 Collective on MPI_Comm 3546 3547 Input Parameters: 3548 + comm - the communicators the parallel matrix will live on 3549 . seqmat - the input sequential matrices 3550 . m - number of local rows (or PETSC_DECIDE) 3551 . n - number of local columns (or PETSC_DECIDE) 3552 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3553 3554 Output Parameter: 3555 . mpimat - the parallel matrix generated 3556 3557 Level: advanced 3558 3559 Notes: 3560 The dimensions of the sequential matrix in each processor MUST be the same. 3561 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3562 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3563 @*/ 3564 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3565 { 3566 PetscErrorCode ierr; 3567 MPI_Comm comm=((PetscObject)mpimat)->comm; 3568 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3569 PetscMPIInt size,rank,taga,*len_s; 3570 PetscInt N=mpimat->cmap.N,i,j,*owners,*ai=a->i,*aj=a->j; 3571 PetscInt proc,m; 3572 PetscInt **buf_ri,**buf_rj; 3573 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3574 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3575 MPI_Request *s_waits,*r_waits; 3576 MPI_Status *status; 3577 MatScalar *aa=a->a,**abuf_r,*ba_i; 3578 Mat_Merge_SeqsToMPI *merge; 3579 PetscContainer container; 3580 3581 PetscFunctionBegin; 3582 if (!logkey_seqstompinum) { 3583 ierr = PetscLogEventRegister(&logkey_seqstompinum,"MatMerge_SeqsToMPINumeric",MAT_COOKIE); 3584 } 3585 ierr = PetscLogEventBegin(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3586 3587 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3588 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3589 3590 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3591 if (container) { 3592 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3593 } 3594 bi = merge->bi; 3595 bj = merge->bj; 3596 buf_ri = merge->buf_ri; 3597 buf_rj = merge->buf_rj; 3598 3599 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3600 owners = merge->rowmap.range; 3601 len_s = merge->len_s; 3602 3603 /* send and recv matrix values */ 3604 /*-----------------------------*/ 3605 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3606 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3607 3608 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3609 for (proc=0,k=0; proc<size; proc++){ 3610 if (!len_s[proc]) continue; 3611 i = owners[proc]; 3612 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3613 k++; 3614 } 3615 3616 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3617 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3618 ierr = PetscFree(status);CHKERRQ(ierr); 3619 3620 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3621 ierr = PetscFree(r_waits);CHKERRQ(ierr); 3622 3623 /* insert mat values of mpimat */ 3624 /*----------------------------*/ 3625 ierr = PetscMalloc(N*sizeof(MatScalar),&ba_i);CHKERRQ(ierr); 3626 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3627 nextrow = buf_ri_k + merge->nrecv; 3628 nextai = nextrow + merge->nrecv; 3629 3630 for (k=0; k<merge->nrecv; k++){ 3631 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3632 nrows = *(buf_ri_k[k]); 3633 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 3634 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3635 } 3636 3637 /* set values of ba */ 3638 m = merge->rowmap.n; 3639 for (i=0; i<m; i++) { 3640 arow = owners[rank] + i; 3641 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 3642 bnzi = bi[i+1] - bi[i]; 3643 ierr = PetscMemzero(ba_i,bnzi*sizeof(MatScalar));CHKERRQ(ierr); 3644 3645 /* add local non-zero vals of this proc's seqmat into ba */ 3646 anzi = ai[arow+1] - ai[arow]; 3647 aj = a->j + ai[arow]; 3648 aa = a->a + ai[arow]; 3649 nextaj = 0; 3650 for (j=0; nextaj<anzi; j++){ 3651 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3652 ba_i[j] += aa[nextaj++]; 3653 } 3654 } 3655 3656 /* add received vals into ba */ 3657 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3658 /* i-th row */ 3659 if (i == *nextrow[k]) { 3660 anzi = *(nextai[k]+1) - *nextai[k]; 3661 aj = buf_rj[k] + *(nextai[k]); 3662 aa = abuf_r[k] + *(nextai[k]); 3663 nextaj = 0; 3664 for (j=0; nextaj<anzi; j++){ 3665 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3666 ba_i[j] += aa[nextaj++]; 3667 } 3668 } 3669 nextrow[k]++; nextai[k]++; 3670 } 3671 } 3672 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 3673 } 3674 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3675 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3676 3677 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 3678 ierr = PetscFree(ba_i);CHKERRQ(ierr); 3679 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3680 ierr = PetscLogEventEnd(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3681 PetscFunctionReturn(0); 3682 } 3683 3684 static PetscEvent logkey_seqstompisym = 0; 3685 #undef __FUNCT__ 3686 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 3687 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 3688 { 3689 PetscErrorCode ierr; 3690 Mat B_mpi; 3691 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3692 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 3693 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 3694 PetscInt M=seqmat->rmap.n,N=seqmat->cmap.n,i,*owners,*ai=a->i,*aj=a->j; 3695 PetscInt len,proc,*dnz,*onz; 3696 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 3697 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 3698 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 3699 MPI_Status *status; 3700 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 3701 PetscBT lnkbt; 3702 Mat_Merge_SeqsToMPI *merge; 3703 PetscContainer container; 3704 3705 PetscFunctionBegin; 3706 if (!logkey_seqstompisym) { 3707 ierr = PetscLogEventRegister(&logkey_seqstompisym,"MatMerge_SeqsToMPISymbolic",MAT_COOKIE); 3708 } 3709 ierr = PetscLogEventBegin(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3710 3711 /* make sure it is a PETSc comm */ 3712 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 3713 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3714 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3715 3716 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 3717 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3718 3719 /* determine row ownership */ 3720 /*---------------------------------------------------------*/ 3721 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 3722 merge->rowmap.n = m; 3723 merge->rowmap.N = M; 3724 merge->rowmap.bs = 1; 3725 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 3726 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 3727 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 3728 3729 m = merge->rowmap.n; 3730 M = merge->rowmap.N; 3731 owners = merge->rowmap.range; 3732 3733 /* determine the number of messages to send, their lengths */ 3734 /*---------------------------------------------------------*/ 3735 len_s = merge->len_s; 3736 3737 len = 0; /* length of buf_si[] */ 3738 merge->nsend = 0; 3739 for (proc=0; proc<size; proc++){ 3740 len_si[proc] = 0; 3741 if (proc == rank){ 3742 len_s[proc] = 0; 3743 } else { 3744 len_si[proc] = owners[proc+1] - owners[proc] + 1; 3745 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 3746 } 3747 if (len_s[proc]) { 3748 merge->nsend++; 3749 nrows = 0; 3750 for (i=owners[proc]; i<owners[proc+1]; i++){ 3751 if (ai[i+1] > ai[i]) nrows++; 3752 } 3753 len_si[proc] = 2*(nrows+1); 3754 len += len_si[proc]; 3755 } 3756 } 3757 3758 /* determine the number and length of messages to receive for ij-structure */ 3759 /*-------------------------------------------------------------------------*/ 3760 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 3761 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 3762 3763 /* post the Irecv of j-structure */ 3764 /*-------------------------------*/ 3765 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 3766 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 3767 3768 /* post the Isend of j-structure */ 3769 /*--------------------------------*/ 3770 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 3771 sj_waits = si_waits + merge->nsend; 3772 3773 for (proc=0, k=0; proc<size; proc++){ 3774 if (!len_s[proc]) continue; 3775 i = owners[proc]; 3776 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 3777 k++; 3778 } 3779 3780 /* receives and sends of j-structure are complete */ 3781 /*------------------------------------------------*/ 3782 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 3783 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 3784 3785 /* send and recv i-structure */ 3786 /*---------------------------*/ 3787 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 3788 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 3789 3790 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 3791 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 3792 for (proc=0,k=0; proc<size; proc++){ 3793 if (!len_s[proc]) continue; 3794 /* form outgoing message for i-structure: 3795 buf_si[0]: nrows to be sent 3796 [1:nrows]: row index (global) 3797 [nrows+1:2*nrows+1]: i-structure index 3798 */ 3799 /*-------------------------------------------*/ 3800 nrows = len_si[proc]/2 - 1; 3801 buf_si_i = buf_si + nrows+1; 3802 buf_si[0] = nrows; 3803 buf_si_i[0] = 0; 3804 nrows = 0; 3805 for (i=owners[proc]; i<owners[proc+1]; i++){ 3806 anzi = ai[i+1] - ai[i]; 3807 if (anzi) { 3808 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 3809 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 3810 nrows++; 3811 } 3812 } 3813 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 3814 k++; 3815 buf_si += len_si[proc]; 3816 } 3817 3818 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 3819 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 3820 3821 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 3822 for (i=0; i<merge->nrecv; i++){ 3823 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); 3824 } 3825 3826 ierr = PetscFree(len_si);CHKERRQ(ierr); 3827 ierr = PetscFree(len_ri);CHKERRQ(ierr); 3828 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 3829 ierr = PetscFree(si_waits);CHKERRQ(ierr); 3830 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 3831 ierr = PetscFree(buf_s);CHKERRQ(ierr); 3832 ierr = PetscFree(status);CHKERRQ(ierr); 3833 3834 /* compute a local seq matrix in each processor */ 3835 /*----------------------------------------------*/ 3836 /* allocate bi array and free space for accumulating nonzero column info */ 3837 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 3838 bi[0] = 0; 3839 3840 /* create and initialize a linked list */ 3841 nlnk = N+1; 3842 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3843 3844 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 3845 len = 0; 3846 len = ai[owners[rank+1]] - ai[owners[rank]]; 3847 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 3848 current_space = free_space; 3849 3850 /* determine symbolic info for each local row */ 3851 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3852 nextrow = buf_ri_k + merge->nrecv; 3853 nextai = nextrow + merge->nrecv; 3854 for (k=0; k<merge->nrecv; k++){ 3855 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3856 nrows = *buf_ri_k[k]; 3857 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 3858 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3859 } 3860 3861 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3862 len = 0; 3863 for (i=0;i<m;i++) { 3864 bnzi = 0; 3865 /* add local non-zero cols of this proc's seqmat into lnk */ 3866 arow = owners[rank] + i; 3867 anzi = ai[arow+1] - ai[arow]; 3868 aj = a->j + ai[arow]; 3869 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3870 bnzi += nlnk; 3871 /* add received col data into lnk */ 3872 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3873 if (i == *nextrow[k]) { /* i-th row */ 3874 anzi = *(nextai[k]+1) - *nextai[k]; 3875 aj = buf_rj[k] + *nextai[k]; 3876 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3877 bnzi += nlnk; 3878 nextrow[k]++; nextai[k]++; 3879 } 3880 } 3881 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 3882 3883 /* if free space is not available, make more free space */ 3884 if (current_space->local_remaining<bnzi) { 3885 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 3886 nspacedouble++; 3887 } 3888 /* copy data into free space, then initialize lnk */ 3889 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 3890 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 3891 3892 current_space->array += bnzi; 3893 current_space->local_used += bnzi; 3894 current_space->local_remaining -= bnzi; 3895 3896 bi[i+1] = bi[i] + bnzi; 3897 } 3898 3899 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3900 3901 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 3902 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 3903 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 3904 3905 /* create symbolic parallel matrix B_mpi */ 3906 /*---------------------------------------*/ 3907 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 3908 if (n==PETSC_DECIDE) { 3909 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 3910 } else { 3911 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3912 } 3913 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 3914 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 3915 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3916 3917 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 3918 B_mpi->assembled = PETSC_FALSE; 3919 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 3920 merge->bi = bi; 3921 merge->bj = bj; 3922 merge->buf_ri = buf_ri; 3923 merge->buf_rj = buf_rj; 3924 merge->coi = PETSC_NULL; 3925 merge->coj = PETSC_NULL; 3926 merge->owners_co = PETSC_NULL; 3927 3928 /* attach the supporting struct to B_mpi for reuse */ 3929 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 3930 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 3931 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 3932 *mpimat = B_mpi; 3933 3934 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 3935 ierr = PetscLogEventEnd(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3936 PetscFunctionReturn(0); 3937 } 3938 3939 static PetscEvent logkey_seqstompi = 0; 3940 #undef __FUNCT__ 3941 #define __FUNCT__ "MatMerge_SeqsToMPI" 3942 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 3943 { 3944 PetscErrorCode ierr; 3945 3946 PetscFunctionBegin; 3947 if (!logkey_seqstompi) { 3948 ierr = PetscLogEventRegister(&logkey_seqstompi,"MatMerge_SeqsToMPI",MAT_COOKIE); 3949 } 3950 ierr = PetscLogEventBegin(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 3951 if (scall == MAT_INITIAL_MATRIX){ 3952 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 3953 } 3954 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 3955 ierr = PetscLogEventEnd(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 3956 PetscFunctionReturn(0); 3957 } 3958 static PetscEvent logkey_getlocalmat = 0; 3959 #undef __FUNCT__ 3960 #define __FUNCT__ "MatGetLocalMat" 3961 /*@ 3962 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 3963 3964 Not Collective 3965 3966 Input Parameters: 3967 + A - the matrix 3968 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3969 3970 Output Parameter: 3971 . A_loc - the local sequential matrix generated 3972 3973 Level: developer 3974 3975 @*/ 3976 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 3977 { 3978 PetscErrorCode ierr; 3979 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 3980 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 3981 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 3982 PetscScalar *aa=a->a,*ba=b->a,*ca; 3983 PetscInt am=A->rmap.n,i,j,k,cstart=A->cmap.rstart; 3984 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 3985 3986 PetscFunctionBegin; 3987 if (!logkey_getlocalmat) { 3988 ierr = PetscLogEventRegister(&logkey_getlocalmat,"MatGetLocalMat",MAT_COOKIE); 3989 } 3990 ierr = PetscLogEventBegin(logkey_getlocalmat,A,0,0,0);CHKERRQ(ierr); 3991 if (scall == MAT_INITIAL_MATRIX){ 3992 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 3993 ci[0] = 0; 3994 for (i=0; i<am; i++){ 3995 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 3996 } 3997 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 3998 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 3999 k = 0; 4000 for (i=0; i<am; i++) { 4001 ncols_o = bi[i+1] - bi[i]; 4002 ncols_d = ai[i+1] - ai[i]; 4003 /* off-diagonal portion of A */ 4004 for (jo=0; jo<ncols_o; jo++) { 4005 col = cmap[*bj]; 4006 if (col >= cstart) break; 4007 cj[k] = col; bj++; 4008 ca[k++] = *ba++; 4009 } 4010 /* diagonal portion of A */ 4011 for (j=0; j<ncols_d; j++) { 4012 cj[k] = cstart + *aj++; 4013 ca[k++] = *aa++; 4014 } 4015 /* off-diagonal portion of A */ 4016 for (j=jo; j<ncols_o; j++) { 4017 cj[k] = cmap[*bj++]; 4018 ca[k++] = *ba++; 4019 } 4020 } 4021 /* put together the new matrix */ 4022 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap.N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4023 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4024 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4025 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4026 mat->free_a = PETSC_TRUE; 4027 mat->free_ij = PETSC_TRUE; 4028 mat->nonew = 0; 4029 } else if (scall == MAT_REUSE_MATRIX){ 4030 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4031 ci = mat->i; cj = mat->j; ca = mat->a; 4032 for (i=0; i<am; i++) { 4033 /* off-diagonal portion of A */ 4034 ncols_o = bi[i+1] - bi[i]; 4035 for (jo=0; jo<ncols_o; jo++) { 4036 col = cmap[*bj]; 4037 if (col >= cstart) break; 4038 *ca++ = *ba++; bj++; 4039 } 4040 /* diagonal portion of A */ 4041 ncols_d = ai[i+1] - ai[i]; 4042 for (j=0; j<ncols_d; j++) *ca++ = *aa++; 4043 /* off-diagonal portion of A */ 4044 for (j=jo; j<ncols_o; j++) { 4045 *ca++ = *ba++; bj++; 4046 } 4047 } 4048 } else { 4049 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4050 } 4051 4052 ierr = PetscLogEventEnd(logkey_getlocalmat,A,0,0,0);CHKERRQ(ierr); 4053 PetscFunctionReturn(0); 4054 } 4055 4056 static PetscEvent logkey_getlocalmatcondensed = 0; 4057 #undef __FUNCT__ 4058 #define __FUNCT__ "MatGetLocalMatCondensed" 4059 /*@C 4060 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4061 4062 Not Collective 4063 4064 Input Parameters: 4065 + A - the matrix 4066 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4067 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4068 4069 Output Parameter: 4070 . A_loc - the local sequential matrix generated 4071 4072 Level: developer 4073 4074 @*/ 4075 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4076 { 4077 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4078 PetscErrorCode ierr; 4079 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4080 IS isrowa,iscola; 4081 Mat *aloc; 4082 4083 PetscFunctionBegin; 4084 if (!logkey_getlocalmatcondensed) { 4085 ierr = PetscLogEventRegister(&logkey_getlocalmatcondensed,"MatGetLocalMatCondensed",MAT_COOKIE); 4086 } 4087 ierr = PetscLogEventBegin(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4088 if (!row){ 4089 start = A->rmap.rstart; end = A->rmap.rend; 4090 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4091 } else { 4092 isrowa = *row; 4093 } 4094 if (!col){ 4095 start = A->cmap.rstart; 4096 cmap = a->garray; 4097 nzA = a->A->cmap.n; 4098 nzB = a->B->cmap.n; 4099 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4100 ncols = 0; 4101 for (i=0; i<nzB; i++) { 4102 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4103 else break; 4104 } 4105 imark = i; 4106 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4107 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4108 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4109 ierr = PetscFree(idx);CHKERRQ(ierr); 4110 } else { 4111 iscola = *col; 4112 } 4113 if (scall != MAT_INITIAL_MATRIX){ 4114 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4115 aloc[0] = *A_loc; 4116 } 4117 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4118 *A_loc = aloc[0]; 4119 ierr = PetscFree(aloc);CHKERRQ(ierr); 4120 if (!row){ 4121 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4122 } 4123 if (!col){ 4124 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4125 } 4126 ierr = PetscLogEventEnd(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4127 PetscFunctionReturn(0); 4128 } 4129 4130 static PetscEvent logkey_GetBrowsOfAcols = 0; 4131 #undef __FUNCT__ 4132 #define __FUNCT__ "MatGetBrowsOfAcols" 4133 /*@C 4134 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4135 4136 Collective on Mat 4137 4138 Input Parameters: 4139 + A,B - the matrices in mpiaij format 4140 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4141 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4142 4143 Output Parameter: 4144 + rowb, colb - index sets of rows and columns of B to extract 4145 . brstart - row index of B_seq from which next B->rmap.n rows are taken from B's local rows 4146 - B_seq - the sequential matrix generated 4147 4148 Level: developer 4149 4150 @*/ 4151 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4152 { 4153 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4154 PetscErrorCode ierr; 4155 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4156 IS isrowb,iscolb; 4157 Mat *bseq; 4158 4159 PetscFunctionBegin; 4160 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4161 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); 4162 } 4163 if (!logkey_GetBrowsOfAcols) { 4164 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAcols,"MatGetBrowsOfAcols",MAT_COOKIE); 4165 } 4166 ierr = PetscLogEventBegin(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4167 4168 if (scall == MAT_INITIAL_MATRIX){ 4169 start = A->cmap.rstart; 4170 cmap = a->garray; 4171 nzA = a->A->cmap.n; 4172 nzB = a->B->cmap.n; 4173 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4174 ncols = 0; 4175 for (i=0; i<nzB; i++) { /* row < local row index */ 4176 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4177 else break; 4178 } 4179 imark = i; 4180 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4181 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4182 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4183 ierr = PetscFree(idx);CHKERRQ(ierr); 4184 *brstart = imark; 4185 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap.N,0,1,&iscolb);CHKERRQ(ierr); 4186 } else { 4187 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4188 isrowb = *rowb; iscolb = *colb; 4189 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4190 bseq[0] = *B_seq; 4191 } 4192 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4193 *B_seq = bseq[0]; 4194 ierr = PetscFree(bseq);CHKERRQ(ierr); 4195 if (!rowb){ 4196 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4197 } else { 4198 *rowb = isrowb; 4199 } 4200 if (!colb){ 4201 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4202 } else { 4203 *colb = iscolb; 4204 } 4205 ierr = PetscLogEventEnd(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4206 PetscFunctionReturn(0); 4207 } 4208 4209 static PetscEvent logkey_GetBrowsOfAocols = 0; 4210 #undef __FUNCT__ 4211 #define __FUNCT__ "MatGetBrowsOfAoCols" 4212 /*@C 4213 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4214 of the OFF-DIAGONAL portion of local A 4215 4216 Collective on Mat 4217 4218 Input Parameters: 4219 + A,B - the matrices in mpiaij format 4220 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4221 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4222 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4223 4224 Output Parameter: 4225 + B_oth - the sequential matrix generated 4226 4227 Level: developer 4228 4229 @*/ 4230 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,PetscScalar **bufa_ptr,Mat *B_oth) 4231 { 4232 VecScatter_MPI_General *gen_to,*gen_from; 4233 PetscErrorCode ierr; 4234 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4235 Mat_SeqAIJ *b_oth; 4236 VecScatter ctx=a->Mvctx; 4237 MPI_Comm comm=((PetscObject)ctx)->comm; 4238 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4239 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap.n,row,*b_othi,*b_othj; 4240 PetscScalar *rvalues,*svalues,*b_otha,*bufa,*bufA; 4241 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4242 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4243 MPI_Status *sstatus,rstatus; 4244 PetscMPIInt jj; 4245 PetscInt *cols,sbs,rbs; 4246 PetscScalar *vals; 4247 4248 PetscFunctionBegin; 4249 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4250 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); 4251 } 4252 if (!logkey_GetBrowsOfAocols) { 4253 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAocols,"MatGetBrAoCol",MAT_COOKIE); 4254 } 4255 ierr = PetscLogEventBegin(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4256 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4257 4258 gen_to = (VecScatter_MPI_General*)ctx->todata; 4259 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4260 rvalues = gen_from->values; /* holds the length of receiving row */ 4261 svalues = gen_to->values; /* holds the length of sending row */ 4262 nrecvs = gen_from->n; 4263 nsends = gen_to->n; 4264 4265 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4266 srow = gen_to->indices; /* local row index to be sent */ 4267 sstarts = gen_to->starts; 4268 sprocs = gen_to->procs; 4269 sstatus = gen_to->sstatus; 4270 sbs = gen_to->bs; 4271 rstarts = gen_from->starts; 4272 rprocs = gen_from->procs; 4273 rbs = gen_from->bs; 4274 4275 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4276 if (scall == MAT_INITIAL_MATRIX){ 4277 /* i-array */ 4278 /*---------*/ 4279 /* post receives */ 4280 for (i=0; i<nrecvs; i++){ 4281 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4282 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4283 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4284 } 4285 4286 /* pack the outgoing message */ 4287 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4288 rstartsj = sstartsj + nsends +1; 4289 sstartsj[0] = 0; rstartsj[0] = 0; 4290 len = 0; /* total length of j or a array to be sent */ 4291 k = 0; 4292 for (i=0; i<nsends; i++){ 4293 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4294 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4295 for (j=0; j<nrows; j++) { 4296 row = srow[k] + B->rmap.range[rank]; /* global row idx */ 4297 for (l=0; l<sbs; l++){ 4298 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4299 rowlen[j*sbs+l] = ncols; 4300 len += ncols; 4301 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4302 } 4303 k++; 4304 } 4305 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4306 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4307 } 4308 /* recvs and sends of i-array are completed */ 4309 i = nrecvs; 4310 while (i--) { 4311 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4312 } 4313 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4314 4315 /* allocate buffers for sending j and a arrays */ 4316 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4317 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4318 4319 /* create i-array of B_oth */ 4320 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4321 b_othi[0] = 0; 4322 len = 0; /* total length of j or a array to be received */ 4323 k = 0; 4324 for (i=0; i<nrecvs; i++){ 4325 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4326 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4327 for (j=0; j<nrows; j++) { 4328 b_othi[k+1] = b_othi[k] + rowlen[j]; 4329 len += rowlen[j]; k++; 4330 } 4331 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4332 } 4333 4334 /* allocate space for j and a arrrays of B_oth */ 4335 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4336 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscScalar),&b_otha);CHKERRQ(ierr); 4337 4338 /* j-array */ 4339 /*---------*/ 4340 /* post receives of j-array */ 4341 for (i=0; i<nrecvs; i++){ 4342 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4343 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4344 } 4345 4346 /* pack the outgoing message j-array */ 4347 k = 0; 4348 for (i=0; i<nsends; i++){ 4349 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4350 bufJ = bufj+sstartsj[i]; 4351 for (j=0; j<nrows; j++) { 4352 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4353 for (ll=0; ll<sbs; ll++){ 4354 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4355 for (l=0; l<ncols; l++){ 4356 *bufJ++ = cols[l]; 4357 } 4358 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4359 } 4360 } 4361 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4362 } 4363 4364 /* recvs and sends of j-array are completed */ 4365 i = nrecvs; 4366 while (i--) { 4367 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4368 } 4369 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4370 } else if (scall == MAT_REUSE_MATRIX){ 4371 sstartsj = *startsj; 4372 rstartsj = sstartsj + nsends +1; 4373 bufa = *bufa_ptr; 4374 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4375 b_otha = b_oth->a; 4376 } else { 4377 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4378 } 4379 4380 /* a-array */ 4381 /*---------*/ 4382 /* post receives of a-array */ 4383 for (i=0; i<nrecvs; i++){ 4384 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4385 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4386 } 4387 4388 /* pack the outgoing message a-array */ 4389 k = 0; 4390 for (i=0; i<nsends; i++){ 4391 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4392 bufA = bufa+sstartsj[i]; 4393 for (j=0; j<nrows; j++) { 4394 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4395 for (ll=0; ll<sbs; ll++){ 4396 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4397 for (l=0; l<ncols; l++){ 4398 *bufA++ = vals[l]; 4399 } 4400 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4401 } 4402 } 4403 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4404 } 4405 /* recvs and sends of a-array are completed */ 4406 i = nrecvs; 4407 while (i--) { 4408 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4409 } 4410 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4411 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4412 4413 if (scall == MAT_INITIAL_MATRIX){ 4414 /* put together the new matrix */ 4415 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap.N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4416 4417 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4418 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4419 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4420 b_oth->free_a = PETSC_TRUE; 4421 b_oth->free_ij = PETSC_TRUE; 4422 b_oth->nonew = 0; 4423 4424 ierr = PetscFree(bufj);CHKERRQ(ierr); 4425 if (!startsj || !bufa_ptr){ 4426 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4427 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4428 } else { 4429 *startsj = sstartsj; 4430 *bufa_ptr = bufa; 4431 } 4432 } 4433 ierr = PetscLogEventEnd(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4434 PetscFunctionReturn(0); 4435 } 4436 4437 #undef __FUNCT__ 4438 #define __FUNCT__ "MatGetCommunicationStructs" 4439 /*@C 4440 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4441 4442 Not Collective 4443 4444 Input Parameters: 4445 . A - The matrix in mpiaij format 4446 4447 Output Parameter: 4448 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4449 . colmap - A map from global column index to local index into lvec 4450 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4451 4452 Level: developer 4453 4454 @*/ 4455 #if defined (PETSC_USE_CTABLE) 4456 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4457 #else 4458 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4459 #endif 4460 { 4461 Mat_MPIAIJ *a; 4462 4463 PetscFunctionBegin; 4464 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4465 PetscValidPointer(lvec, 2) 4466 PetscValidPointer(colmap, 3) 4467 PetscValidPointer(multScatter, 4) 4468 a = (Mat_MPIAIJ *) A->data; 4469 if (lvec) *lvec = a->lvec; 4470 if (colmap) *colmap = a->colmap; 4471 if (multScatter) *multScatter = a->Mvctx; 4472 PetscFunctionReturn(0); 4473 } 4474 4475 EXTERN_C_BEGIN 4476 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,MatType,MatReuse,Mat*); 4477 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,MatType,MatReuse,Mat*); 4478 EXTERN_C_END 4479 4480 /*MC 4481 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4482 4483 Options Database Keys: 4484 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4485 4486 Level: beginner 4487 4488 .seealso: MatCreateMPIAIJ() 4489 M*/ 4490 4491 EXTERN_C_BEGIN 4492 #undef __FUNCT__ 4493 #define __FUNCT__ "MatCreate_MPIAIJ" 4494 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4495 { 4496 Mat_MPIAIJ *b; 4497 PetscErrorCode ierr; 4498 PetscMPIInt size; 4499 4500 PetscFunctionBegin; 4501 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4502 4503 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4504 B->data = (void*)b; 4505 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4506 B->factor = 0; 4507 B->rmap.bs = 1; 4508 B->assembled = PETSC_FALSE; 4509 B->mapping = 0; 4510 4511 B->insertmode = NOT_SET_VALUES; 4512 b->size = size; 4513 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4514 4515 /* build cache for off array entries formed */ 4516 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4517 b->donotstash = PETSC_FALSE; 4518 b->colmap = 0; 4519 b->garray = 0; 4520 b->roworiented = PETSC_TRUE; 4521 4522 /* stuff used for matrix vector multiply */ 4523 b->lvec = PETSC_NULL; 4524 b->Mvctx = PETSC_NULL; 4525 4526 /* stuff for MatGetRow() */ 4527 b->rowindices = 0; 4528 b->rowvalues = 0; 4529 b->getrowactive = PETSC_FALSE; 4530 4531 4532 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4533 "MatStoreValues_MPIAIJ", 4534 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4535 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4536 "MatRetrieveValues_MPIAIJ", 4537 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4538 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4539 "MatGetDiagonalBlock_MPIAIJ", 4540 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4541 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4542 "MatIsTranspose_MPIAIJ", 4543 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4544 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4545 "MatMPIAIJSetPreallocation_MPIAIJ", 4546 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4547 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4548 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4549 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4550 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4551 "MatDiagonalScaleLocal_MPIAIJ", 4552 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4553 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 4554 "MatConvert_MPIAIJ_MPICSRPERM", 4555 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 4556 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 4557 "MatConvert_MPIAIJ_MPICRL", 4558 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 4559 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 4560 PetscFunctionReturn(0); 4561 } 4562 EXTERN_C_END 4563 4564 #undef __FUNCT__ 4565 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 4566 /*@ 4567 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 4568 and "off-diagonal" part of the matrix in CSR format. 4569 4570 Collective on MPI_Comm 4571 4572 Input Parameters: 4573 + comm - MPI communicator 4574 . m - number of local rows (Cannot be PETSC_DECIDE) 4575 . n - This value should be the same as the local size used in creating the 4576 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4577 calculated if N is given) For square matrices n is almost always m. 4578 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4579 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4580 . i - row indices for "diagonal" portion of matrix 4581 . j - column indices 4582 . a - matrix values 4583 . oi - row indices for "off-diagonal" portion of matrix 4584 . oj - column indices 4585 - oa - matrix values 4586 4587 Output Parameter: 4588 . mat - the matrix 4589 4590 Level: advanced 4591 4592 Notes: 4593 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 4594 4595 The i and j indices are 0 based 4596 4597 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 4598 4599 4600 .keywords: matrix, aij, compressed row, sparse, parallel 4601 4602 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4603 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 4604 @*/ 4605 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 4606 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 4607 { 4608 PetscErrorCode ierr; 4609 Mat_MPIAIJ *maij; 4610 4611 PetscFunctionBegin; 4612 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4613 if (i[0]) { 4614 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4615 } 4616 if (oi[0]) { 4617 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 4618 } 4619 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4620 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4621 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4622 maij = (Mat_MPIAIJ*) (*mat)->data; 4623 maij->donotstash = PETSC_TRUE; 4624 (*mat)->preallocated = PETSC_TRUE; 4625 4626 (*mat)->rmap.bs = (*mat)->cmap.bs = 1; 4627 ierr = PetscMapSetUp(&(*mat)->rmap);CHKERRQ(ierr); 4628 ierr = PetscMapSetUp(&(*mat)->cmap);CHKERRQ(ierr); 4629 4630 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 4631 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap.N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 4632 4633 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4634 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4635 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4636 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4637 4638 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4639 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4640 PetscFunctionReturn(0); 4641 } 4642 4643 /* 4644 Special version for direct calls from Fortran 4645 */ 4646 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4647 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 4648 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4649 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 4650 #endif 4651 4652 /* Change these macros so can be used in void function */ 4653 #undef CHKERRQ 4654 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4655 #undef SETERRQ2 4656 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4657 #undef SETERRQ 4658 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 4659 4660 EXTERN_C_BEGIN 4661 #undef __FUNCT__ 4662 #define __FUNCT__ "matsetvaluesmpiaij_" 4663 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 4664 { 4665 Mat mat = *mmat; 4666 PetscInt m = *mm, n = *mn; 4667 InsertMode addv = *maddv; 4668 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 4669 PetscScalar value; 4670 PetscErrorCode ierr; 4671 4672 MatPreallocated(mat); 4673 if (mat->insertmode == NOT_SET_VALUES) { 4674 mat->insertmode = addv; 4675 } 4676 #if defined(PETSC_USE_DEBUG) 4677 else if (mat->insertmode != addv) { 4678 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 4679 } 4680 #endif 4681 { 4682 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 4683 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 4684 PetscTruth roworiented = aij->roworiented; 4685 4686 /* Some Variables required in the macro */ 4687 Mat A = aij->A; 4688 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4689 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 4690 PetscScalar *aa = a->a; 4691 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 4692 Mat B = aij->B; 4693 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 4694 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 4695 PetscScalar *ba = b->a; 4696 4697 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 4698 PetscInt nonew = a->nonew; 4699 PetscScalar *ap1,*ap2; 4700 4701 PetscFunctionBegin; 4702 for (i=0; i<m; i++) { 4703 if (im[i] < 0) continue; 4704 #if defined(PETSC_USE_DEBUG) 4705 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 4706 #endif 4707 if (im[i] >= rstart && im[i] < rend) { 4708 row = im[i] - rstart; 4709 lastcol1 = -1; 4710 rp1 = aj + ai[row]; 4711 ap1 = aa + ai[row]; 4712 rmax1 = aimax[row]; 4713 nrow1 = ailen[row]; 4714 low1 = 0; 4715 high1 = nrow1; 4716 lastcol2 = -1; 4717 rp2 = bj + bi[row]; 4718 ap2 = ba + bi[row]; 4719 rmax2 = bimax[row]; 4720 nrow2 = bilen[row]; 4721 low2 = 0; 4722 high2 = nrow2; 4723 4724 for (j=0; j<n; j++) { 4725 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 4726 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 4727 if (in[j] >= cstart && in[j] < cend){ 4728 col = in[j] - cstart; 4729 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 4730 } else if (in[j] < 0) continue; 4731 #if defined(PETSC_USE_DEBUG) 4732 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);} 4733 #endif 4734 else { 4735 if (mat->was_assembled) { 4736 if (!aij->colmap) { 4737 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 4738 } 4739 #if defined (PETSC_USE_CTABLE) 4740 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4741 col--; 4742 #else 4743 col = aij->colmap[in[j]] - 1; 4744 #endif 4745 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 4746 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 4747 col = in[j]; 4748 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 4749 B = aij->B; 4750 b = (Mat_SeqAIJ*)B->data; 4751 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 4752 rp2 = bj + bi[row]; 4753 ap2 = ba + bi[row]; 4754 rmax2 = bimax[row]; 4755 nrow2 = bilen[row]; 4756 low2 = 0; 4757 high2 = nrow2; 4758 bm = aij->B->rmap.n; 4759 ba = b->a; 4760 } 4761 } else col = in[j]; 4762 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 4763 } 4764 } 4765 } else { 4766 if (!aij->donotstash) { 4767 if (roworiented) { 4768 if (ignorezeroentries && v[i*n] == 0.0) continue; 4769 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 4770 } else { 4771 if (ignorezeroentries && v[i] == 0.0) continue; 4772 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 4773 } 4774 } 4775 } 4776 }} 4777 PetscFunctionReturnVoid(); 4778 } 4779 EXTERN_C_END 4780 4781