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,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->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,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 = 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 = 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(mat->comm,&rank);CHKERRQ(ierr); 756 ierr = MPI_Comm_size(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,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,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,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,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,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,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,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,mat->comm);CHKERRQ(ierr); 827 ierr = MPI_Send(column_indices,nz,MPIU_INT,0,tag,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,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,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,mat->comm);CHKERRQ(ierr); 860 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,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(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,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,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(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,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 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 1024 1025 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1026 1027 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1028 if (flag & SOR_ZERO_INITIAL_GUESS) { 1029 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 1030 its--; 1031 } 1032 1033 while (its--) { 1034 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1035 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1036 1037 /* update rhs: bb1 = bb - B*x */ 1038 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1039 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1040 1041 /* local sweep */ 1042 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx); 1043 CHKERRQ(ierr); 1044 } 1045 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1046 if (flag & SOR_ZERO_INITIAL_GUESS) { 1047 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1048 its--; 1049 } 1050 while (its--) { 1051 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1052 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1053 1054 /* update rhs: bb1 = bb - B*x */ 1055 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1056 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1057 1058 /* local sweep */ 1059 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx); 1060 CHKERRQ(ierr); 1061 } 1062 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1063 if (flag & SOR_ZERO_INITIAL_GUESS) { 1064 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1065 its--; 1066 } 1067 while (its--) { 1068 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1069 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1070 1071 /* update rhs: bb1 = bb - B*x */ 1072 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1073 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1074 1075 /* local sweep */ 1076 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx); 1077 CHKERRQ(ierr); 1078 } 1079 } else { 1080 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1081 } 1082 1083 ierr = VecDestroy(bb1);CHKERRQ(ierr); 1084 PetscFunctionReturn(0); 1085 } 1086 1087 #undef __FUNCT__ 1088 #define __FUNCT__ "MatPermute_MPIAIJ" 1089 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1090 { 1091 MPI_Comm comm,pcomm; 1092 PetscInt first,local_size,nrows,*rows; 1093 int ntids; 1094 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1095 PetscErrorCode ierr; 1096 1097 PetscFunctionBegin; 1098 ierr = PetscObjectGetComm((PetscObject)A,&comm); CHKERRQ(ierr); 1099 /* make a collective version of 'rowp' */ 1100 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm); CHKERRQ(ierr); 1101 if (pcomm==comm) { 1102 crowp = rowp; 1103 } else { 1104 ierr = ISGetSize(rowp,&nrows); CHKERRQ(ierr); 1105 ierr = ISGetIndices(rowp,&rows); CHKERRQ(ierr); 1106 ierr = ISCreateGeneral(comm,nrows,rows,&crowp); CHKERRQ(ierr); 1107 ierr = ISRestoreIndices(rowp,&rows); CHKERRQ(ierr); 1108 } 1109 /* collect the global row permutation and invert it */ 1110 ierr = ISAllGather(crowp,&growp); CHKERRQ(ierr); 1111 ierr = ISSetPermutation(growp); CHKERRQ(ierr); 1112 if (pcomm!=comm) { 1113 ierr = ISDestroy(crowp); CHKERRQ(ierr); 1114 } 1115 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1116 /* get the local target indices */ 1117 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL); CHKERRQ(ierr); 1118 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL); CHKERRQ(ierr); 1119 ierr = ISGetIndices(irowp,&rows); CHKERRQ(ierr); 1120 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp); CHKERRQ(ierr); 1121 ierr = ISRestoreIndices(irowp,&rows); CHKERRQ(ierr); 1122 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1123 /* the column permutation is so much easier; 1124 make a local version of 'colp' and invert it */ 1125 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm); CHKERRQ(ierr); 1126 ierr = MPI_Comm_size(pcomm,&ntids); CHKERRQ(ierr); 1127 if (ntids==1) { 1128 lcolp = colp; 1129 } else { 1130 ierr = ISGetSize(colp,&nrows); CHKERRQ(ierr); 1131 ierr = ISGetIndices(colp,&rows); CHKERRQ(ierr); 1132 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp); CHKERRQ(ierr); 1133 } 1134 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp); CHKERRQ(ierr); 1135 ierr = ISSetPermutation(lcolp); CHKERRQ(ierr); 1136 if (ntids>1) { 1137 ierr = ISRestoreIndices(colp,&rows); CHKERRQ(ierr); 1138 ierr = ISDestroy(lcolp); CHKERRQ(ierr); 1139 } 1140 /* now we just get the submatrix */ 1141 ierr = MatGetSubMatrix(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B); CHKERRQ(ierr); 1142 /* clean up */ 1143 ierr = ISDestroy(lrowp); CHKERRQ(ierr); 1144 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1145 PetscFunctionReturn(0); 1146 } 1147 1148 #undef __FUNCT__ 1149 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1150 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1151 { 1152 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1153 Mat A = mat->A,B = mat->B; 1154 PetscErrorCode ierr; 1155 PetscReal isend[5],irecv[5]; 1156 1157 PetscFunctionBegin; 1158 info->block_size = 1.0; 1159 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1160 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1161 isend[3] = info->memory; isend[4] = info->mallocs; 1162 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1163 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1164 isend[3] += info->memory; isend[4] += info->mallocs; 1165 if (flag == MAT_LOCAL) { 1166 info->nz_used = isend[0]; 1167 info->nz_allocated = isend[1]; 1168 info->nz_unneeded = isend[2]; 1169 info->memory = isend[3]; 1170 info->mallocs = isend[4]; 1171 } else if (flag == MAT_GLOBAL_MAX) { 1172 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1173 info->nz_used = irecv[0]; 1174 info->nz_allocated = irecv[1]; 1175 info->nz_unneeded = irecv[2]; 1176 info->memory = irecv[3]; 1177 info->mallocs = irecv[4]; 1178 } else if (flag == MAT_GLOBAL_SUM) { 1179 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1180 info->nz_used = irecv[0]; 1181 info->nz_allocated = irecv[1]; 1182 info->nz_unneeded = irecv[2]; 1183 info->memory = irecv[3]; 1184 info->mallocs = irecv[4]; 1185 } 1186 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1187 info->fill_ratio_needed = 0; 1188 info->factor_mallocs = 0; 1189 info->rows_global = (double)matin->rmap.N; 1190 info->columns_global = (double)matin->cmap.N; 1191 info->rows_local = (double)matin->rmap.n; 1192 info->columns_local = (double)matin->cmap.N; 1193 1194 PetscFunctionReturn(0); 1195 } 1196 1197 #undef __FUNCT__ 1198 #define __FUNCT__ "MatSetOption_MPIAIJ" 1199 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg) 1200 { 1201 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1202 PetscErrorCode ierr; 1203 1204 PetscFunctionBegin; 1205 switch (op) { 1206 case MAT_NEW_NONZERO_LOCATIONS: 1207 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1208 case MAT_KEEP_ZEROED_ROWS: 1209 case MAT_NEW_NONZERO_LOCATION_ERR: 1210 case MAT_USE_INODES: 1211 case MAT_IGNORE_ZERO_ENTRIES: 1212 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1213 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1214 break; 1215 case MAT_ROW_ORIENTED: 1216 a->roworiented = flg; 1217 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1218 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1219 break; 1220 case MAT_NEW_DIAGONALS: 1221 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1222 break; 1223 case MAT_IGNORE_OFF_PROC_ENTRIES: 1224 a->donotstash = PETSC_TRUE; 1225 break; 1226 case MAT_SYMMETRIC: 1227 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1228 break; 1229 case MAT_STRUCTURALLY_SYMMETRIC: 1230 case MAT_HERMITIAN: 1231 case MAT_SYMMETRY_ETERNAL: 1232 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1233 break; 1234 default: 1235 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1236 } 1237 PetscFunctionReturn(0); 1238 } 1239 1240 #undef __FUNCT__ 1241 #define __FUNCT__ "MatGetRow_MPIAIJ" 1242 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1243 { 1244 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1245 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1246 PetscErrorCode ierr; 1247 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap.rstart; 1248 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap.rstart,rend = matin->rmap.rend; 1249 PetscInt *cmap,*idx_p; 1250 1251 PetscFunctionBegin; 1252 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1253 mat->getrowactive = PETSC_TRUE; 1254 1255 if (!mat->rowvalues && (idx || v)) { 1256 /* 1257 allocate enough space to hold information from the longest row. 1258 */ 1259 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1260 PetscInt max = 1,tmp; 1261 for (i=0; i<matin->rmap.n; i++) { 1262 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1263 if (max < tmp) { max = tmp; } 1264 } 1265 ierr = PetscMalloc(max*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1266 mat->rowindices = (PetscInt*)(mat->rowvalues + max); 1267 } 1268 1269 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1270 lrow = row - rstart; 1271 1272 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1273 if (!v) {pvA = 0; pvB = 0;} 1274 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1275 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1276 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1277 nztot = nzA + nzB; 1278 1279 cmap = mat->garray; 1280 if (v || idx) { 1281 if (nztot) { 1282 /* Sort by increasing column numbers, assuming A and B already sorted */ 1283 PetscInt imark = -1; 1284 if (v) { 1285 *v = v_p = mat->rowvalues; 1286 for (i=0; i<nzB; i++) { 1287 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1288 else break; 1289 } 1290 imark = i; 1291 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1292 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1293 } 1294 if (idx) { 1295 *idx = idx_p = mat->rowindices; 1296 if (imark > -1) { 1297 for (i=0; i<imark; i++) { 1298 idx_p[i] = cmap[cworkB[i]]; 1299 } 1300 } else { 1301 for (i=0; i<nzB; i++) { 1302 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1303 else break; 1304 } 1305 imark = i; 1306 } 1307 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1308 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1309 } 1310 } else { 1311 if (idx) *idx = 0; 1312 if (v) *v = 0; 1313 } 1314 } 1315 *nz = nztot; 1316 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1317 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1318 PetscFunctionReturn(0); 1319 } 1320 1321 #undef __FUNCT__ 1322 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1323 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1324 { 1325 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1326 1327 PetscFunctionBegin; 1328 if (!aij->getrowactive) { 1329 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1330 } 1331 aij->getrowactive = PETSC_FALSE; 1332 PetscFunctionReturn(0); 1333 } 1334 1335 #undef __FUNCT__ 1336 #define __FUNCT__ "MatNorm_MPIAIJ" 1337 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1338 { 1339 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1340 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1341 PetscErrorCode ierr; 1342 PetscInt i,j,cstart = mat->cmap.rstart; 1343 PetscReal sum = 0.0; 1344 PetscScalar *v; 1345 1346 PetscFunctionBegin; 1347 if (aij->size == 1) { 1348 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1349 } else { 1350 if (type == NORM_FROBENIUS) { 1351 v = amat->a; 1352 for (i=0; i<amat->nz; i++) { 1353 #if defined(PETSC_USE_COMPLEX) 1354 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1355 #else 1356 sum += (*v)*(*v); v++; 1357 #endif 1358 } 1359 v = bmat->a; 1360 for (i=0; i<bmat->nz; i++) { 1361 #if defined(PETSC_USE_COMPLEX) 1362 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1363 #else 1364 sum += (*v)*(*v); v++; 1365 #endif 1366 } 1367 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 1368 *norm = sqrt(*norm); 1369 } else if (type == NORM_1) { /* max column norm */ 1370 PetscReal *tmp,*tmp2; 1371 PetscInt *jj,*garray = aij->garray; 1372 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1373 ierr = PetscMalloc((mat->cmap.N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1374 ierr = PetscMemzero(tmp,mat->cmap.N*sizeof(PetscReal));CHKERRQ(ierr); 1375 *norm = 0.0; 1376 v = amat->a; jj = amat->j; 1377 for (j=0; j<amat->nz; j++) { 1378 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1379 } 1380 v = bmat->a; jj = bmat->j; 1381 for (j=0; j<bmat->nz; j++) { 1382 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1383 } 1384 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap.N,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 1385 for (j=0; j<mat->cmap.N; j++) { 1386 if (tmp2[j] > *norm) *norm = tmp2[j]; 1387 } 1388 ierr = PetscFree(tmp);CHKERRQ(ierr); 1389 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1390 } else if (type == NORM_INFINITY) { /* max row norm */ 1391 PetscReal ntemp = 0.0; 1392 for (j=0; j<aij->A->rmap.n; j++) { 1393 v = amat->a + amat->i[j]; 1394 sum = 0.0; 1395 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1396 sum += PetscAbsScalar(*v); v++; 1397 } 1398 v = bmat->a + bmat->i[j]; 1399 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1400 sum += PetscAbsScalar(*v); v++; 1401 } 1402 if (sum > ntemp) ntemp = sum; 1403 } 1404 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,mat->comm);CHKERRQ(ierr); 1405 } else { 1406 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1407 } 1408 } 1409 PetscFunctionReturn(0); 1410 } 1411 1412 #undef __FUNCT__ 1413 #define __FUNCT__ "MatTranspose_MPIAIJ" 1414 PetscErrorCode MatTranspose_MPIAIJ(Mat A,Mat *matout) 1415 { 1416 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1417 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1418 PetscErrorCode ierr; 1419 PetscInt M = A->rmap.N,N = A->cmap.N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,i,*d_nnz; 1420 PetscInt cstart=A->cmap.rstart,ncol; 1421 Mat B; 1422 PetscScalar *array; 1423 1424 PetscFunctionBegin; 1425 if (!matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1426 1427 /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */ 1428 ma = A->rmap.n; na = A->cmap.n; mb = a->B->rmap.n; 1429 ai = Aloc->i; aj = Aloc->j; 1430 bi = Bloc->i; bj = Bloc->j; 1431 ierr = PetscMalloc((1+na+bi[mb])*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1432 cols = d_nnz + na + 1; /* work space to be used by B part */ 1433 ierr = PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));CHKERRQ(ierr); 1434 for (i=0; i<ai[ma]; i++){ 1435 d_nnz[aj[i]] ++; 1436 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1437 } 1438 1439 ierr = MatCreate(A->comm,&B);CHKERRQ(ierr); 1440 ierr = MatSetSizes(B,A->cmap.n,A->rmap.n,N,M);CHKERRQ(ierr); 1441 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 1442 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);CHKERRQ(ierr); 1443 1444 /* copy over the A part */ 1445 array = Aloc->a; 1446 row = A->rmap.rstart; 1447 for (i=0; i<ma; i++) { 1448 ncol = ai[i+1]-ai[i]; 1449 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1450 row++; array += ncol; aj += ncol; 1451 } 1452 aj = Aloc->j; 1453 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1454 1455 /* copy over the B part */ 1456 array = Bloc->a; 1457 row = A->rmap.rstart; 1458 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 1459 for (i=0; i<mb; i++) { 1460 ncol = bi[i+1]-bi[i]; 1461 ierr = MatSetValues(B,ncol,cols,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1462 row++; array += ncol; cols += ncol; 1463 } 1464 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1465 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1466 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1467 if (matout) { 1468 *matout = B; 1469 } else { 1470 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1471 } 1472 PetscFunctionReturn(0); 1473 } 1474 1475 #undef __FUNCT__ 1476 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1477 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1478 { 1479 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1480 Mat a = aij->A,b = aij->B; 1481 PetscErrorCode ierr; 1482 PetscInt s1,s2,s3; 1483 1484 PetscFunctionBegin; 1485 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1486 if (rr) { 1487 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1488 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1489 /* Overlap communication with computation. */ 1490 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1491 } 1492 if (ll) { 1493 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1494 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1495 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1496 } 1497 /* scale the diagonal block */ 1498 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1499 1500 if (rr) { 1501 /* Do a scatter end and then right scale the off-diagonal block */ 1502 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1503 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1504 } 1505 1506 PetscFunctionReturn(0); 1507 } 1508 1509 #undef __FUNCT__ 1510 #define __FUNCT__ "MatSetBlockSize_MPIAIJ" 1511 PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs) 1512 { 1513 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1514 PetscErrorCode ierr; 1515 1516 PetscFunctionBegin; 1517 ierr = MatSetBlockSize(a->A,bs);CHKERRQ(ierr); 1518 ierr = MatSetBlockSize(a->B,bs);CHKERRQ(ierr); 1519 PetscFunctionReturn(0); 1520 } 1521 #undef __FUNCT__ 1522 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1523 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 1524 { 1525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1526 PetscErrorCode ierr; 1527 1528 PetscFunctionBegin; 1529 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1530 PetscFunctionReturn(0); 1531 } 1532 1533 #undef __FUNCT__ 1534 #define __FUNCT__ "MatEqual_MPIAIJ" 1535 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1536 { 1537 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1538 Mat a,b,c,d; 1539 PetscTruth flg; 1540 PetscErrorCode ierr; 1541 1542 PetscFunctionBegin; 1543 a = matA->A; b = matA->B; 1544 c = matB->A; d = matB->B; 1545 1546 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1547 if (flg) { 1548 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1549 } 1550 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1551 PetscFunctionReturn(0); 1552 } 1553 1554 #undef __FUNCT__ 1555 #define __FUNCT__ "MatCopy_MPIAIJ" 1556 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1557 { 1558 PetscErrorCode ierr; 1559 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1560 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1561 1562 PetscFunctionBegin; 1563 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1564 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1565 /* because of the column compression in the off-processor part of the matrix a->B, 1566 the number of columns in a->B and b->B may be different, hence we cannot call 1567 the MatCopy() directly on the two parts. If need be, we can provide a more 1568 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1569 then copying the submatrices */ 1570 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1571 } else { 1572 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1573 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1574 } 1575 PetscFunctionReturn(0); 1576 } 1577 1578 #undef __FUNCT__ 1579 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1580 PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A) 1581 { 1582 PetscErrorCode ierr; 1583 1584 PetscFunctionBegin; 1585 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1586 PetscFunctionReturn(0); 1587 } 1588 1589 #include "petscblaslapack.h" 1590 #undef __FUNCT__ 1591 #define __FUNCT__ "MatAXPY_MPIAIJ" 1592 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1593 { 1594 PetscErrorCode ierr; 1595 PetscInt i; 1596 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1597 PetscBLASInt bnz,one=1; 1598 Mat_SeqAIJ *x,*y; 1599 1600 PetscFunctionBegin; 1601 if (str == SAME_NONZERO_PATTERN) { 1602 PetscScalar alpha = a; 1603 x = (Mat_SeqAIJ *)xx->A->data; 1604 y = (Mat_SeqAIJ *)yy->A->data; 1605 bnz = (PetscBLASInt)x->nz; 1606 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1607 x = (Mat_SeqAIJ *)xx->B->data; 1608 y = (Mat_SeqAIJ *)yy->B->data; 1609 bnz = (PetscBLASInt)x->nz; 1610 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1611 } else if (str == SUBSET_NONZERO_PATTERN) { 1612 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 1613 1614 x = (Mat_SeqAIJ *)xx->B->data; 1615 y = (Mat_SeqAIJ *)yy->B->data; 1616 if (y->xtoy && y->XtoY != xx->B) { 1617 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1618 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1619 } 1620 if (!y->xtoy) { /* get xtoy */ 1621 ierr = MatAXPYGetxtoy_Private(xx->B->rmap.n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1622 y->XtoY = xx->B; 1623 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 1624 } 1625 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 1626 } else { 1627 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1628 } 1629 PetscFunctionReturn(0); 1630 } 1631 1632 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat); 1633 1634 #undef __FUNCT__ 1635 #define __FUNCT__ "MatConjugate_MPIAIJ" 1636 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_MPIAIJ(Mat mat) 1637 { 1638 #if defined(PETSC_USE_COMPLEX) 1639 PetscErrorCode ierr; 1640 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1641 1642 PetscFunctionBegin; 1643 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 1644 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 1645 #else 1646 PetscFunctionBegin; 1647 #endif 1648 PetscFunctionReturn(0); 1649 } 1650 1651 #undef __FUNCT__ 1652 #define __FUNCT__ "MatRealPart_MPIAIJ" 1653 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 1654 { 1655 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1656 PetscErrorCode ierr; 1657 1658 PetscFunctionBegin; 1659 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1660 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1661 PetscFunctionReturn(0); 1662 } 1663 1664 #undef __FUNCT__ 1665 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 1666 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 1667 { 1668 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1669 PetscErrorCode ierr; 1670 1671 PetscFunctionBegin; 1672 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1673 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1674 PetscFunctionReturn(0); 1675 } 1676 1677 #ifdef PETSC_HAVE_PBGL 1678 1679 #include <boost/parallel/mpi/bsp_process_group.hpp> 1680 #include <boost/graph/distributed/ilu_default_graph.hpp> 1681 #include <boost/graph/distributed/ilu_0_block.hpp> 1682 #include <boost/graph/distributed/ilu_preconditioner.hpp> 1683 #include <boost/graph/distributed/petsc/interface.hpp> 1684 #include <boost/multi_array.hpp> 1685 #include <boost/parallel/distributed_property_map.hpp> 1686 1687 #undef __FUNCT__ 1688 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 1689 /* 1690 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1691 */ 1692 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat A, IS isrow, IS iscol, MatFactorInfo *info, Mat *fact) 1693 { 1694 namespace petsc = boost::distributed::petsc; 1695 1696 namespace graph_dist = boost::graph::distributed; 1697 using boost::graph::distributed::ilu_default::process_group_type; 1698 using boost::graph::ilu_permuted; 1699 1700 PetscTruth row_identity, col_identity; 1701 PetscContainer c; 1702 PetscInt m, n, M, N; 1703 PetscErrorCode ierr; 1704 1705 PetscFunctionBegin; 1706 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 1707 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 1708 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 1709 if (!row_identity || !col_identity) { 1710 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 1711 } 1712 1713 process_group_type pg; 1714 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1715 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 1716 lgraph_type& level_graph = *lgraph_p; 1717 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1718 1719 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 1720 ilu_permuted(level_graph); 1721 1722 /* put together the new matrix */ 1723 ierr = MatCreate(A->comm, fact);CHKERRQ(ierr); 1724 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 1725 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 1726 ierr = MatSetSizes(*fact, m, n, M, N);CHKERRQ(ierr); 1727 ierr = MatSetType(*fact, A->type_name);CHKERRQ(ierr); 1728 ierr = MatAssemblyBegin(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1729 ierr = MatAssemblyEnd(*fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1730 (*fact)->factor = FACTOR_LU; 1731 1732 ierr = PetscContainerCreate(A->comm, &c); 1733 ierr = PetscContainerSetPointer(c, lgraph_p); 1734 ierr = PetscObjectCompose((PetscObject) (*fact), "graph", (PetscObject) c); 1735 PetscFunctionReturn(0); 1736 } 1737 1738 #undef __FUNCT__ 1739 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 1740 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat A, MatFactorInfo *info, Mat *B) 1741 { 1742 PetscFunctionBegin; 1743 PetscFunctionReturn(0); 1744 } 1745 1746 #undef __FUNCT__ 1747 #define __FUNCT__ "MatSolve_MPIAIJ" 1748 /* 1749 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1750 */ 1751 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 1752 { 1753 namespace graph_dist = boost::graph::distributed; 1754 1755 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1756 lgraph_type* lgraph_p; 1757 PetscContainer c; 1758 PetscErrorCode ierr; 1759 1760 PetscFunctionBegin; 1761 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 1762 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 1763 ierr = VecCopy(b, x); CHKERRQ(ierr); 1764 1765 PetscScalar* array_x; 1766 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 1767 PetscInt sx; 1768 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 1769 1770 PetscScalar* array_b; 1771 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 1772 PetscInt sb; 1773 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 1774 1775 lgraph_type& level_graph = *lgraph_p; 1776 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1777 1778 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 1779 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 1780 ref_x(array_x, boost::extents[num_vertices(graph)]); 1781 1782 typedef boost::iterator_property_map<array_ref_type::iterator, 1783 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 1784 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 1785 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 1786 1787 ilu_set_solve(*lgraph_p, vector_b, vector_x); 1788 1789 PetscFunctionReturn(0); 1790 } 1791 #endif 1792 1793 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 1794 PetscInt nzlocal,nsends,nrecvs; 1795 PetscMPIInt *send_rank; 1796 PetscInt *sbuf_nz,*sbuf_j,**rbuf_j; 1797 PetscScalar *sbuf_a,**rbuf_a; 1798 PetscErrorCode (*MatDestroy)(Mat); 1799 } Mat_Redundant; 1800 1801 #undef __FUNCT__ 1802 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 1803 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 1804 { 1805 PetscErrorCode ierr; 1806 Mat_Redundant *redund=(Mat_Redundant*)ptr; 1807 PetscInt i; 1808 1809 PetscFunctionBegin; 1810 ierr = PetscFree(redund->send_rank);CHKERRQ(ierr); 1811 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1812 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1813 for (i=0; i<redund->nrecvs; i++){ 1814 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1815 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1816 } 1817 ierr = PetscFree3(redund->sbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1818 ierr = PetscFree(redund);CHKERRQ(ierr); 1819 PetscFunctionReturn(0); 1820 } 1821 1822 #undef __FUNCT__ 1823 #define __FUNCT__ "MatDestroy_MatRedundant" 1824 PetscErrorCode MatDestroy_MatRedundant(Mat A) 1825 { 1826 PetscErrorCode ierr; 1827 PetscContainer container; 1828 Mat_Redundant *redund=PETSC_NULL; 1829 1830 PetscFunctionBegin; 1831 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 1832 if (container) { 1833 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 1834 } else { 1835 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 1836 } 1837 A->ops->destroy = redund->MatDestroy; 1838 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 1839 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 1840 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 1841 PetscFunctionReturn(0); 1842 } 1843 1844 #undef __FUNCT__ 1845 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 1846 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 1847 { 1848 PetscMPIInt rank,size; 1849 MPI_Comm comm=mat->comm; 1850 PetscErrorCode ierr; 1851 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 1852 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 1853 PetscInt *rowrange=mat->rmap.range; 1854 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1855 Mat A=aij->A,B=aij->B,C=*matredundant; 1856 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 1857 PetscScalar *sbuf_a; 1858 PetscInt nzlocal=a->nz+b->nz; 1859 PetscInt j,cstart=mat->cmap.rstart,cend=mat->cmap.rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 1860 PetscInt rstart=mat->rmap.rstart,rend=mat->rmap.rend,*bmap=aij->garray,M,N; 1861 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 1862 PetscScalar *vals,*aworkA,*aworkB; 1863 PetscMPIInt tag1,tag2,tag3,imdex; 1864 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 1865 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 1866 MPI_Status recv_status,*send_status; 1867 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 1868 PetscInt **rbuf_j=PETSC_NULL; 1869 PetscScalar **rbuf_a=PETSC_NULL; 1870 Mat_Redundant *redund=PETSC_NULL; 1871 PetscContainer container; 1872 1873 PetscFunctionBegin; 1874 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1875 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1876 1877 if (reuse == MAT_REUSE_MATRIX) { 1878 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 1879 if (M != N || M != mat->rmap.N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 1880 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 1881 if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 1882 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 1883 if (container) { 1884 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 1885 } else { 1886 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 1887 } 1888 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 1889 1890 nsends = redund->nsends; 1891 nrecvs = redund->nrecvs; 1892 send_rank = redund->send_rank; recv_rank = send_rank + size; 1893 sbuf_nz = redund->sbuf_nz; rbuf_nz = sbuf_nz + nsends; 1894 sbuf_j = redund->sbuf_j; 1895 sbuf_a = redund->sbuf_a; 1896 rbuf_j = redund->rbuf_j; 1897 rbuf_a = redund->rbuf_a; 1898 } 1899 1900 if (reuse == MAT_INITIAL_MATRIX){ 1901 PetscMPIInt subrank,subsize; 1902 PetscInt nleftover,np_subcomm; 1903 /* get the destination processors' id send_rank, nsends and nrecvs */ 1904 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 1905 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 1906 ierr = PetscMalloc((2*size+1)*sizeof(PetscMPIInt),&send_rank); 1907 recv_rank = send_rank + size; 1908 np_subcomm = size/nsubcomm; 1909 nleftover = size - nsubcomm*np_subcomm; 1910 nsends = 0; nrecvs = 0; 1911 for (i=0; i<size; i++){ /* i=rank*/ 1912 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 1913 send_rank[nsends] = i; nsends++; 1914 recv_rank[nrecvs++] = i; 1915 } 1916 } 1917 if (rank >= size - nleftover){/* this proc is a leftover processor */ 1918 i = size-nleftover-1; 1919 j = 0; 1920 while (j < nsubcomm - nleftover){ 1921 send_rank[nsends++] = i; 1922 i--; j++; 1923 } 1924 } 1925 1926 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 1927 for (i=0; i<nleftover; i++){ 1928 recv_rank[nrecvs++] = size-nleftover+i; 1929 } 1930 } 1931 1932 /* allocate sbuf_j, sbuf_a */ 1933 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 1934 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 1935 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 1936 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 1937 1938 /* copy mat's local entries into the buffers */ 1939 if (reuse == MAT_INITIAL_MATRIX){ 1940 rownz_max = 0; 1941 rptr = sbuf_j; 1942 cols = sbuf_j + rend-rstart + 1; 1943 vals = sbuf_a; 1944 rptr[0] = 0; 1945 for (i=0; i<rend-rstart; i++){ 1946 row = i + rstart; 1947 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 1948 ncols = nzA + nzB; 1949 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 1950 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 1951 /* load the column indices for this row into cols */ 1952 lwrite = 0; 1953 for (l=0; l<nzB; l++) { 1954 if ((ctmp = bmap[cworkB[l]]) < cstart){ 1955 vals[lwrite] = aworkB[l]; 1956 cols[lwrite++] = ctmp; 1957 } 1958 } 1959 for (l=0; l<nzA; l++){ 1960 vals[lwrite] = aworkA[l]; 1961 cols[lwrite++] = cstart + cworkA[l]; 1962 } 1963 for (l=0; l<nzB; l++) { 1964 if ((ctmp = bmap[cworkB[l]]) >= cend){ 1965 vals[lwrite] = aworkB[l]; 1966 cols[lwrite++] = ctmp; 1967 } 1968 } 1969 vals += ncols; 1970 cols += ncols; 1971 rptr[i+1] = rptr[i] + ncols; 1972 if (rownz_max < ncols) rownz_max = ncols; 1973 } 1974 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); 1975 } else { /* only copy matrix values into sbuf_a */ 1976 rptr = sbuf_j; 1977 vals = sbuf_a; 1978 rptr[0] = 0; 1979 for (i=0; i<rend-rstart; i++){ 1980 row = i + rstart; 1981 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 1982 ncols = nzA + nzB; 1983 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 1984 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 1985 lwrite = 0; 1986 for (l=0; l<nzB; l++) { 1987 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 1988 } 1989 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 1990 for (l=0; l<nzB; l++) { 1991 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 1992 } 1993 vals += ncols; 1994 rptr[i+1] = rptr[i] + ncols; 1995 } 1996 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 1997 1998 /* send nzlocal to others, and recv other's nzlocal */ 1999 /*--------------------------------------------------*/ 2000 if (reuse == MAT_INITIAL_MATRIX){ 2001 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2002 s_waits2 = s_waits3 + nsends; 2003 s_waits1 = s_waits2 + nsends; 2004 r_waits1 = s_waits1 + nsends; 2005 r_waits2 = r_waits1 + nrecvs; 2006 r_waits3 = r_waits2 + nrecvs; 2007 } else { 2008 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2009 r_waits3 = s_waits3 + nsends; 2010 } 2011 2012 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2013 if (reuse == MAT_INITIAL_MATRIX){ 2014 /* get new tags to keep the communication clean */ 2015 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2016 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2017 ierr = PetscMalloc3(nsends+nrecvs+1,PetscInt,&sbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2018 rbuf_nz = sbuf_nz + nsends; 2019 2020 /* post receives of other's nzlocal */ 2021 for (i=0; i<nrecvs; i++){ 2022 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2023 } 2024 /* send nzlocal to others */ 2025 for (i=0; i<nsends; i++){ 2026 sbuf_nz[i] = nzlocal; 2027 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2028 } 2029 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2030 count = nrecvs; 2031 while (count) { 2032 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2033 recv_rank[imdex] = recv_status.MPI_SOURCE; 2034 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2035 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2036 2037 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2038 rbuf_nz[imdex] += i + 2; 2039 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2040 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2041 count--; 2042 } 2043 /* wait on sends of nzlocal */ 2044 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2045 /* send mat->i,j to others, and recv from other's */ 2046 /*------------------------------------------------*/ 2047 for (i=0; i<nsends; i++){ 2048 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2049 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2050 } 2051 /* wait on receives of mat->i,j */ 2052 /*------------------------------*/ 2053 count = nrecvs; 2054 while (count) { 2055 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2056 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2057 count--; 2058 } 2059 /* wait on sends of mat->i,j */ 2060 /*---------------------------*/ 2061 if (nsends) { 2062 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2063 } 2064 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2065 2066 /* post receives, send and receive mat->a */ 2067 /*----------------------------------------*/ 2068 for (imdex=0; imdex<nrecvs; imdex++) { 2069 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2070 } 2071 for (i=0; i<nsends; i++){ 2072 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2073 } 2074 count = nrecvs; 2075 while (count) { 2076 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2077 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2078 count--; 2079 } 2080 if (nsends) { 2081 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2082 } 2083 2084 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2085 2086 /* create redundant matrix */ 2087 /*-------------------------*/ 2088 if (reuse == MAT_INITIAL_MATRIX){ 2089 /* compute rownz_max for preallocation */ 2090 for (imdex=0; imdex<nrecvs; imdex++){ 2091 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2092 rptr = rbuf_j[imdex]; 2093 for (i=0; i<j; i++){ 2094 ncols = rptr[i+1] - rptr[i]; 2095 if (rownz_max < ncols) rownz_max = ncols; 2096 } 2097 } 2098 2099 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2100 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2101 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2102 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2103 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2104 } else { 2105 C = *matredundant; 2106 } 2107 2108 /* insert local matrix entries */ 2109 rptr = sbuf_j; 2110 cols = sbuf_j + rend-rstart + 1; 2111 vals = sbuf_a; 2112 for (i=0; i<rend-rstart; i++){ 2113 row = i + rstart; 2114 ncols = rptr[i+1] - rptr[i]; 2115 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2116 vals += ncols; 2117 cols += ncols; 2118 } 2119 /* insert received matrix entries */ 2120 for (imdex=0; imdex<nrecvs; imdex++){ 2121 rstart = rowrange[recv_rank[imdex]]; 2122 rend = rowrange[recv_rank[imdex]+1]; 2123 rptr = rbuf_j[imdex]; 2124 cols = rbuf_j[imdex] + rend-rstart + 1; 2125 vals = rbuf_a[imdex]; 2126 for (i=0; i<rend-rstart; i++){ 2127 row = i + rstart; 2128 ncols = rptr[i+1] - rptr[i]; 2129 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2130 vals += ncols; 2131 cols += ncols; 2132 } 2133 } 2134 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2135 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2136 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2137 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); 2138 if (reuse == MAT_INITIAL_MATRIX){ 2139 PetscContainer container; 2140 *matredundant = C; 2141 /* create a supporting struct and attach it to C for reuse */ 2142 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2143 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2144 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2145 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2146 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2147 2148 redund->nzlocal = nzlocal; 2149 redund->nsends = nsends; 2150 redund->nrecvs = nrecvs; 2151 redund->send_rank = send_rank; 2152 redund->sbuf_nz = sbuf_nz; 2153 redund->sbuf_j = sbuf_j; 2154 redund->sbuf_a = sbuf_a; 2155 redund->rbuf_j = rbuf_j; 2156 redund->rbuf_a = rbuf_a; 2157 2158 redund->MatDestroy = C->ops->destroy; 2159 C->ops->destroy = MatDestroy_MatRedundant; 2160 } 2161 PetscFunctionReturn(0); 2162 } 2163 2164 /* -------------------------------------------------------------------*/ 2165 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2166 MatGetRow_MPIAIJ, 2167 MatRestoreRow_MPIAIJ, 2168 MatMult_MPIAIJ, 2169 /* 4*/ MatMultAdd_MPIAIJ, 2170 MatMultTranspose_MPIAIJ, 2171 MatMultTransposeAdd_MPIAIJ, 2172 #ifdef PETSC_HAVE_PBGL 2173 MatSolve_MPIAIJ, 2174 #else 2175 0, 2176 #endif 2177 0, 2178 0, 2179 /*10*/ 0, 2180 0, 2181 0, 2182 MatRelax_MPIAIJ, 2183 MatTranspose_MPIAIJ, 2184 /*15*/ MatGetInfo_MPIAIJ, 2185 MatEqual_MPIAIJ, 2186 MatGetDiagonal_MPIAIJ, 2187 MatDiagonalScale_MPIAIJ, 2188 MatNorm_MPIAIJ, 2189 /*20*/ MatAssemblyBegin_MPIAIJ, 2190 MatAssemblyEnd_MPIAIJ, 2191 0, 2192 MatSetOption_MPIAIJ, 2193 MatZeroEntries_MPIAIJ, 2194 /*25*/ MatZeroRows_MPIAIJ, 2195 0, 2196 #ifdef PETSC_HAVE_PBGL 2197 MatLUFactorNumeric_MPIAIJ, 2198 #else 2199 0, 2200 #endif 2201 0, 2202 0, 2203 /*30*/ MatSetUpPreallocation_MPIAIJ, 2204 #ifdef PETSC_HAVE_PBGL 2205 MatILUFactorSymbolic_MPIAIJ, 2206 #else 2207 0, 2208 #endif 2209 0, 2210 0, 2211 0, 2212 /*35*/ MatDuplicate_MPIAIJ, 2213 0, 2214 0, 2215 0, 2216 0, 2217 /*40*/ MatAXPY_MPIAIJ, 2218 MatGetSubMatrices_MPIAIJ, 2219 MatIncreaseOverlap_MPIAIJ, 2220 MatGetValues_MPIAIJ, 2221 MatCopy_MPIAIJ, 2222 /*45*/ 0, 2223 MatScale_MPIAIJ, 2224 0, 2225 0, 2226 0, 2227 /*50*/ MatSetBlockSize_MPIAIJ, 2228 0, 2229 0, 2230 0, 2231 0, 2232 /*55*/ MatFDColoringCreate_MPIAIJ, 2233 0, 2234 MatSetUnfactored_MPIAIJ, 2235 MatPermute_MPIAIJ, 2236 0, 2237 /*60*/ MatGetSubMatrix_MPIAIJ, 2238 MatDestroy_MPIAIJ, 2239 MatView_MPIAIJ, 2240 0, 2241 0, 2242 /*65*/ 0, 2243 0, 2244 0, 2245 0, 2246 0, 2247 /*70*/ 0, 2248 0, 2249 MatSetColoring_MPIAIJ, 2250 #if defined(PETSC_HAVE_ADIC) 2251 MatSetValuesAdic_MPIAIJ, 2252 #else 2253 0, 2254 #endif 2255 MatSetValuesAdifor_MPIAIJ, 2256 /*75*/ 0, 2257 0, 2258 0, 2259 0, 2260 0, 2261 /*80*/ 0, 2262 0, 2263 0, 2264 0, 2265 /*84*/ MatLoad_MPIAIJ, 2266 0, 2267 0, 2268 0, 2269 0, 2270 0, 2271 /*90*/ MatMatMult_MPIAIJ_MPIAIJ, 2272 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2273 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2274 MatPtAP_Basic, 2275 MatPtAPSymbolic_MPIAIJ, 2276 /*95*/ MatPtAPNumeric_MPIAIJ, 2277 0, 2278 0, 2279 0, 2280 0, 2281 /*100*/0, 2282 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2283 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2284 MatConjugate_MPIAIJ, 2285 0, 2286 /*105*/MatSetValuesRow_MPIAIJ, 2287 MatRealPart_MPIAIJ, 2288 MatImaginaryPart_MPIAIJ, 2289 0, 2290 0, 2291 /*110*/0, 2292 MatGetRedundantMatrix_MPIAIJ}; 2293 2294 /* ----------------------------------------------------------------------------------------*/ 2295 2296 EXTERN_C_BEGIN 2297 #undef __FUNCT__ 2298 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2299 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2300 { 2301 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2302 PetscErrorCode ierr; 2303 2304 PetscFunctionBegin; 2305 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2306 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2307 PetscFunctionReturn(0); 2308 } 2309 EXTERN_C_END 2310 2311 EXTERN_C_BEGIN 2312 #undef __FUNCT__ 2313 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2314 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2315 { 2316 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2317 PetscErrorCode ierr; 2318 2319 PetscFunctionBegin; 2320 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2321 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2322 PetscFunctionReturn(0); 2323 } 2324 EXTERN_C_END 2325 2326 #include "petscpc.h" 2327 EXTERN_C_BEGIN 2328 #undef __FUNCT__ 2329 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2330 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2331 { 2332 Mat_MPIAIJ *b; 2333 PetscErrorCode ierr; 2334 PetscInt i; 2335 2336 PetscFunctionBegin; 2337 B->preallocated = PETSC_TRUE; 2338 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2339 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2340 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2341 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2342 2343 B->rmap.bs = B->cmap.bs = 1; 2344 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2345 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2346 if (d_nnz) { 2347 for (i=0; i<B->rmap.n; i++) { 2348 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]); 2349 } 2350 } 2351 if (o_nnz) { 2352 for (i=0; i<B->rmap.n; i++) { 2353 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]); 2354 } 2355 } 2356 b = (Mat_MPIAIJ*)B->data; 2357 2358 /* Explicitly create 2 MATSEQAIJ matrices. */ 2359 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2360 ierr = MatSetSizes(b->A,B->rmap.n,B->cmap.n,B->rmap.n,B->cmap.n);CHKERRQ(ierr); 2361 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2362 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2363 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2364 ierr = MatSetSizes(b->B,B->rmap.n,B->cmap.N,B->rmap.n,B->cmap.N);CHKERRQ(ierr); 2365 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2366 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2367 2368 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2369 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2370 2371 PetscFunctionReturn(0); 2372 } 2373 EXTERN_C_END 2374 2375 #undef __FUNCT__ 2376 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2377 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2378 { 2379 Mat mat; 2380 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2381 PetscErrorCode ierr; 2382 2383 PetscFunctionBegin; 2384 *newmat = 0; 2385 ierr = MatCreate(matin->comm,&mat);CHKERRQ(ierr); 2386 ierr = MatSetSizes(mat,matin->rmap.n,matin->cmap.n,matin->rmap.N,matin->cmap.N);CHKERRQ(ierr); 2387 ierr = MatSetType(mat,matin->type_name);CHKERRQ(ierr); 2388 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2389 a = (Mat_MPIAIJ*)mat->data; 2390 2391 mat->factor = matin->factor; 2392 mat->rmap.bs = matin->rmap.bs; 2393 mat->assembled = PETSC_TRUE; 2394 mat->insertmode = NOT_SET_VALUES; 2395 mat->preallocated = PETSC_TRUE; 2396 2397 a->size = oldmat->size; 2398 a->rank = oldmat->rank; 2399 a->donotstash = oldmat->donotstash; 2400 a->roworiented = oldmat->roworiented; 2401 a->rowindices = 0; 2402 a->rowvalues = 0; 2403 a->getrowactive = PETSC_FALSE; 2404 2405 ierr = PetscMapCopy(mat->comm,&matin->rmap,&mat->rmap);CHKERRQ(ierr); 2406 ierr = PetscMapCopy(mat->comm,&matin->cmap,&mat->cmap);CHKERRQ(ierr); 2407 2408 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 2409 if (oldmat->colmap) { 2410 #if defined (PETSC_USE_CTABLE) 2411 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2412 #else 2413 ierr = PetscMalloc((mat->cmap.N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2414 ierr = PetscLogObjectMemory(mat,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2415 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap.N)*sizeof(PetscInt));CHKERRQ(ierr); 2416 #endif 2417 } else a->colmap = 0; 2418 if (oldmat->garray) { 2419 PetscInt len; 2420 len = oldmat->B->cmap.n; 2421 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2422 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2423 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2424 } else a->garray = 0; 2425 2426 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2427 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2428 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2429 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2430 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2431 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2432 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2433 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2434 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 2435 *newmat = mat; 2436 PetscFunctionReturn(0); 2437 } 2438 2439 #include "petscsys.h" 2440 2441 #undef __FUNCT__ 2442 #define __FUNCT__ "MatLoad_MPIAIJ" 2443 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, MatType type,Mat *newmat) 2444 { 2445 Mat A; 2446 PetscScalar *vals,*svals; 2447 MPI_Comm comm = ((PetscObject)viewer)->comm; 2448 MPI_Status status; 2449 PetscErrorCode ierr; 2450 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2451 PetscInt i,nz,j,rstart,rend,mmax; 2452 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2453 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2454 PetscInt cend,cstart,n,*rowners; 2455 int fd; 2456 2457 PetscFunctionBegin; 2458 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2459 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2460 if (!rank) { 2461 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2462 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2463 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2464 } 2465 2466 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2467 M = header[1]; N = header[2]; 2468 /* determine ownership of all rows */ 2469 m = M/size + ((M % size) > rank); 2470 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2471 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2472 2473 /* First process needs enough room for process with most rows */ 2474 if (!rank) { 2475 mmax = rowners[1]; 2476 for (i=2; i<size; i++) { 2477 mmax = PetscMax(mmax,rowners[i]); 2478 } 2479 } else mmax = m; 2480 2481 rowners[0] = 0; 2482 for (i=2; i<=size; i++) { 2483 rowners[i] += rowners[i-1]; 2484 } 2485 rstart = rowners[rank]; 2486 rend = rowners[rank+1]; 2487 2488 /* distribute row lengths to all processors */ 2489 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2490 if (!rank) { 2491 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2492 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2493 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2494 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2495 for (j=0; j<m; j++) { 2496 procsnz[0] += ourlens[j]; 2497 } 2498 for (i=1; i<size; i++) { 2499 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2500 /* calculate the number of nonzeros on each processor */ 2501 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2502 procsnz[i] += rowlengths[j]; 2503 } 2504 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2505 } 2506 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2507 } else { 2508 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2509 } 2510 2511 if (!rank) { 2512 /* determine max buffer needed and allocate it */ 2513 maxnz = 0; 2514 for (i=0; i<size; i++) { 2515 maxnz = PetscMax(maxnz,procsnz[i]); 2516 } 2517 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2518 2519 /* read in my part of the matrix column indices */ 2520 nz = procsnz[0]; 2521 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2522 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2523 2524 /* read in every one elses and ship off */ 2525 for (i=1; i<size; i++) { 2526 nz = procsnz[i]; 2527 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2528 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2529 } 2530 ierr = PetscFree(cols);CHKERRQ(ierr); 2531 } else { 2532 /* determine buffer space needed for message */ 2533 nz = 0; 2534 for (i=0; i<m; i++) { 2535 nz += ourlens[i]; 2536 } 2537 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2538 2539 /* receive message of column indices*/ 2540 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2541 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2542 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2543 } 2544 2545 /* determine column ownership if matrix is not square */ 2546 if (N != M) { 2547 n = N/size + ((N % size) > rank); 2548 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2549 cstart = cend - n; 2550 } else { 2551 cstart = rstart; 2552 cend = rend; 2553 n = cend - cstart; 2554 } 2555 2556 /* loop over local rows, determining number of off diagonal entries */ 2557 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2558 jj = 0; 2559 for (i=0; i<m; i++) { 2560 for (j=0; j<ourlens[i]; j++) { 2561 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2562 jj++; 2563 } 2564 } 2565 2566 /* create our matrix */ 2567 for (i=0; i<m; i++) { 2568 ourlens[i] -= offlens[i]; 2569 } 2570 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2571 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2572 ierr = MatSetType(A,type);CHKERRQ(ierr); 2573 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2574 2575 for (i=0; i<m; i++) { 2576 ourlens[i] += offlens[i]; 2577 } 2578 2579 if (!rank) { 2580 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2581 2582 /* read in my part of the matrix numerical values */ 2583 nz = procsnz[0]; 2584 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2585 2586 /* insert into matrix */ 2587 jj = rstart; 2588 smycols = mycols; 2589 svals = vals; 2590 for (i=0; i<m; i++) { 2591 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2592 smycols += ourlens[i]; 2593 svals += ourlens[i]; 2594 jj++; 2595 } 2596 2597 /* read in other processors and ship out */ 2598 for (i=1; i<size; i++) { 2599 nz = procsnz[i]; 2600 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2601 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2602 } 2603 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2604 } else { 2605 /* receive numeric values */ 2606 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2607 2608 /* receive message of values*/ 2609 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2610 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2611 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2612 2613 /* insert into matrix */ 2614 jj = rstart; 2615 smycols = mycols; 2616 svals = vals; 2617 for (i=0; i<m; i++) { 2618 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2619 smycols += ourlens[i]; 2620 svals += ourlens[i]; 2621 jj++; 2622 } 2623 } 2624 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2625 ierr = PetscFree(vals);CHKERRQ(ierr); 2626 ierr = PetscFree(mycols);CHKERRQ(ierr); 2627 ierr = PetscFree(rowners);CHKERRQ(ierr); 2628 2629 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2630 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2631 *newmat = A; 2632 PetscFunctionReturn(0); 2633 } 2634 2635 #undef __FUNCT__ 2636 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2637 /* 2638 Not great since it makes two copies of the submatrix, first an SeqAIJ 2639 in local and then by concatenating the local matrices the end result. 2640 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2641 */ 2642 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2643 { 2644 PetscErrorCode ierr; 2645 PetscMPIInt rank,size; 2646 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 2647 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2648 Mat *local,M,Mreuse; 2649 PetscScalar *vwork,*aa; 2650 MPI_Comm comm = mat->comm; 2651 Mat_SeqAIJ *aij; 2652 2653 2654 PetscFunctionBegin; 2655 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2656 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2657 2658 if (call == MAT_REUSE_MATRIX) { 2659 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2660 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 2661 local = &Mreuse; 2662 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2663 } else { 2664 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2665 Mreuse = *local; 2666 ierr = PetscFree(local);CHKERRQ(ierr); 2667 } 2668 2669 /* 2670 m - number of local rows 2671 n - number of columns (same on all processors) 2672 rstart - first row in new global matrix generated 2673 */ 2674 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2675 if (call == MAT_INITIAL_MATRIX) { 2676 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2677 ii = aij->i; 2678 jj = aij->j; 2679 2680 /* 2681 Determine the number of non-zeros in the diagonal and off-diagonal 2682 portions of the matrix in order to do correct preallocation 2683 */ 2684 2685 /* first get start and end of "diagonal" columns */ 2686 if (csize == PETSC_DECIDE) { 2687 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2688 if (mglobal == n) { /* square matrix */ 2689 nlocal = m; 2690 } else { 2691 nlocal = n/size + ((n % size) > rank); 2692 } 2693 } else { 2694 nlocal = csize; 2695 } 2696 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2697 rstart = rend - nlocal; 2698 if (rank == size - 1 && rend != n) { 2699 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 2700 } 2701 2702 /* next, compute all the lengths */ 2703 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 2704 olens = dlens + m; 2705 for (i=0; i<m; i++) { 2706 jend = ii[i+1] - ii[i]; 2707 olen = 0; 2708 dlen = 0; 2709 for (j=0; j<jend; j++) { 2710 if (*jj < rstart || *jj >= rend) olen++; 2711 else dlen++; 2712 jj++; 2713 } 2714 olens[i] = olen; 2715 dlens[i] = dlen; 2716 } 2717 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 2718 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 2719 ierr = MatSetType(M,mat->type_name);CHKERRQ(ierr); 2720 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 2721 ierr = PetscFree(dlens);CHKERRQ(ierr); 2722 } else { 2723 PetscInt ml,nl; 2724 2725 M = *newmat; 2726 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2727 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2728 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2729 /* 2730 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2731 rather than the slower MatSetValues(). 2732 */ 2733 M->was_assembled = PETSC_TRUE; 2734 M->assembled = PETSC_FALSE; 2735 } 2736 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2737 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2738 ii = aij->i; 2739 jj = aij->j; 2740 aa = aij->a; 2741 for (i=0; i<m; i++) { 2742 row = rstart + i; 2743 nz = ii[i+1] - ii[i]; 2744 cwork = jj; jj += nz; 2745 vwork = aa; aa += nz; 2746 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2747 } 2748 2749 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2750 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2751 *newmat = M; 2752 2753 /* save submatrix used in processor for next request */ 2754 if (call == MAT_INITIAL_MATRIX) { 2755 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2756 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2757 } 2758 2759 PetscFunctionReturn(0); 2760 } 2761 2762 EXTERN_C_BEGIN 2763 #undef __FUNCT__ 2764 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 2765 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 2766 { 2767 PetscInt m,cstart, cend,j,nnz,i,d; 2768 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 2769 const PetscInt *JJ; 2770 PetscScalar *values; 2771 PetscErrorCode ierr; 2772 2773 PetscFunctionBegin; 2774 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 2775 2776 B->rmap.bs = B->cmap.bs = 1; 2777 ierr = PetscMapSetUp(&B->rmap);CHKERRQ(ierr); 2778 ierr = PetscMapSetUp(&B->cmap);CHKERRQ(ierr); 2779 m = B->rmap.n; 2780 cstart = B->cmap.rstart; 2781 cend = B->cmap.rend; 2782 rstart = B->rmap.rstart; 2783 2784 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 2785 o_nnz = d_nnz + m; 2786 2787 for (i=0; i<m; i++) { 2788 nnz = Ii[i+1]- Ii[i]; 2789 JJ = J + Ii[i]; 2790 nnz_max = PetscMax(nnz_max,nnz); 2791 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 2792 for (j=0; j<nnz; j++) { 2793 if (*JJ >= cstart) break; 2794 JJ++; 2795 } 2796 d = 0; 2797 for (; j<nnz; j++) { 2798 if (*JJ++ >= cend) break; 2799 d++; 2800 } 2801 d_nnz[i] = d; 2802 o_nnz[i] = nnz - d; 2803 } 2804 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2805 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 2806 2807 if (v) values = (PetscScalar*)v; 2808 else { 2809 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 2810 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 2811 } 2812 2813 for (i=0; i<m; i++) { 2814 ii = i + rstart; 2815 nnz = Ii[i+1]- Ii[i]; 2816 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 2817 } 2818 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2819 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2820 2821 if (!v) { 2822 ierr = PetscFree(values);CHKERRQ(ierr); 2823 } 2824 PetscFunctionReturn(0); 2825 } 2826 EXTERN_C_END 2827 2828 #undef __FUNCT__ 2829 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 2830 /*@ 2831 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 2832 (the default parallel PETSc format). 2833 2834 Collective on MPI_Comm 2835 2836 Input Parameters: 2837 + B - the matrix 2838 . i - the indices into j for the start of each local row (starts with zero) 2839 . j - the column indices for each local row (starts with zero) these must be sorted for each row 2840 - v - optional values in the matrix 2841 2842 Level: developer 2843 2844 Notes: this actually copies the values from i[], j[], and a[] to put them into PETSc's internal 2845 storage format. Thus changing the values in a[] after this call will not effect the matrix values. 2846 2847 .keywords: matrix, aij, compressed row, sparse, parallel 2848 2849 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 2850 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 2851 @*/ 2852 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 2853 { 2854 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 2855 2856 PetscFunctionBegin; 2857 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 2858 if (f) { 2859 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 2860 } 2861 PetscFunctionReturn(0); 2862 } 2863 2864 #undef __FUNCT__ 2865 #define __FUNCT__ "MatMPIAIJSetPreallocation" 2866 /*@C 2867 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 2868 (the default parallel PETSc format). For good matrix assembly performance 2869 the user should preallocate the matrix storage by setting the parameters 2870 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2871 performance can be increased by more than a factor of 50. 2872 2873 Collective on MPI_Comm 2874 2875 Input Parameters: 2876 + A - the matrix 2877 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2878 (same value is used for all local rows) 2879 . d_nnz - array containing the number of nonzeros in the various rows of the 2880 DIAGONAL portion of the local submatrix (possibly different for each row) 2881 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2882 The size of this array is equal to the number of local rows, i.e 'm'. 2883 You must leave room for the diagonal entry even if it is zero. 2884 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2885 submatrix (same value is used for all local rows). 2886 - o_nnz - array containing the number of nonzeros in the various rows of the 2887 OFF-DIAGONAL portion of the local submatrix (possibly different for 2888 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2889 structure. The size of this array is equal to the number 2890 of local rows, i.e 'm'. 2891 2892 If the *_nnz parameter is given then the *_nz parameter is ignored 2893 2894 The AIJ format (also called the Yale sparse matrix format or 2895 compressed row storage (CSR)), is fully compatible with standard Fortran 77 2896 storage. The stored row and column indices begin with zero. See the users manual for details. 2897 2898 The parallel matrix is partitioned such that the first m0 rows belong to 2899 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2900 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2901 2902 The DIAGONAL portion of the local submatrix of a processor can be defined 2903 as the submatrix which is obtained by extraction the part corresponding 2904 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2905 first row that belongs to the processor, and r2 is the last row belonging 2906 to the this processor. This is a square mxm matrix. The remaining portion 2907 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2908 2909 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2910 2911 Example usage: 2912 2913 Consider the following 8x8 matrix with 34 non-zero values, that is 2914 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2915 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2916 as follows: 2917 2918 .vb 2919 1 2 0 | 0 3 0 | 0 4 2920 Proc0 0 5 6 | 7 0 0 | 8 0 2921 9 0 10 | 11 0 0 | 12 0 2922 ------------------------------------- 2923 13 0 14 | 15 16 17 | 0 0 2924 Proc1 0 18 0 | 19 20 21 | 0 0 2925 0 0 0 | 22 23 0 | 24 0 2926 ------------------------------------- 2927 Proc2 25 26 27 | 0 0 28 | 29 0 2928 30 0 0 | 31 32 33 | 0 34 2929 .ve 2930 2931 This can be represented as a collection of submatrices as: 2932 2933 .vb 2934 A B C 2935 D E F 2936 G H I 2937 .ve 2938 2939 Where the submatrices A,B,C are owned by proc0, D,E,F are 2940 owned by proc1, G,H,I are owned by proc2. 2941 2942 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2943 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2944 The 'M','N' parameters are 8,8, and have the same values on all procs. 2945 2946 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2947 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2948 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2949 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2950 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2951 matrix, ans [DF] as another SeqAIJ matrix. 2952 2953 When d_nz, o_nz parameters are specified, d_nz storage elements are 2954 allocated for every row of the local diagonal submatrix, and o_nz 2955 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2956 One way to choose d_nz and o_nz is to use the max nonzerors per local 2957 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2958 In this case, the values of d_nz,o_nz are: 2959 .vb 2960 proc0 : dnz = 2, o_nz = 2 2961 proc1 : dnz = 3, o_nz = 2 2962 proc2 : dnz = 1, o_nz = 4 2963 .ve 2964 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2965 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2966 for proc3. i.e we are using 12+15+10=37 storage locations to store 2967 34 values. 2968 2969 When d_nnz, o_nnz parameters are specified, the storage is specified 2970 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2971 In the above case the values for d_nnz,o_nnz are: 2972 .vb 2973 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2974 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2975 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2976 .ve 2977 Here the space allocated is sum of all the above values i.e 34, and 2978 hence pre-allocation is perfect. 2979 2980 Level: intermediate 2981 2982 .keywords: matrix, aij, compressed row, sparse, parallel 2983 2984 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 2985 MPIAIJ 2986 @*/ 2987 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2988 { 2989 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 2990 2991 PetscFunctionBegin; 2992 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2993 if (f) { 2994 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2995 } 2996 PetscFunctionReturn(0); 2997 } 2998 2999 #undef __FUNCT__ 3000 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3001 /*@C 3002 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3003 CSR format the local rows. 3004 3005 Collective on MPI_Comm 3006 3007 Input Parameters: 3008 + comm - MPI communicator 3009 . m - number of local rows (Cannot be PETSC_DECIDE) 3010 . n - This value should be the same as the local size used in creating the 3011 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3012 calculated if N is given) For square matrices n is almost always m. 3013 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3014 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3015 . i - row indices 3016 . j - column indices 3017 - a - matrix values 3018 3019 Output Parameter: 3020 . mat - the matrix 3021 3022 Level: intermediate 3023 3024 Notes: 3025 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3026 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3027 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3028 3029 The i and j indices are 0 based 3030 3031 .keywords: matrix, aij, compressed row, sparse, parallel 3032 3033 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3034 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3035 @*/ 3036 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) 3037 { 3038 PetscErrorCode ierr; 3039 3040 PetscFunctionBegin; 3041 if (i[0]) { 3042 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3043 } 3044 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3045 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3046 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3047 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3048 PetscFunctionReturn(0); 3049 } 3050 3051 #undef __FUNCT__ 3052 #define __FUNCT__ "MatCreateMPIAIJ" 3053 /*@C 3054 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3055 (the default parallel PETSc format). For good matrix assembly performance 3056 the user should preallocate the matrix storage by setting the parameters 3057 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3058 performance can be increased by more than a factor of 50. 3059 3060 Collective on MPI_Comm 3061 3062 Input Parameters: 3063 + comm - MPI communicator 3064 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3065 This value should be the same as the local size used in creating the 3066 y vector for the matrix-vector product y = Ax. 3067 . n - This value should be the same as the local size used in creating the 3068 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3069 calculated if N is given) For square matrices n is almost always m. 3070 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3071 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3072 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3073 (same value is used for all local rows) 3074 . d_nnz - array containing the number of nonzeros in the various rows of the 3075 DIAGONAL portion of the local submatrix (possibly different for each row) 3076 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3077 The size of this array is equal to the number of local rows, i.e 'm'. 3078 You must leave room for the diagonal entry even if it is zero. 3079 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3080 submatrix (same value is used for all local rows). 3081 - o_nnz - array containing the number of nonzeros in the various rows of the 3082 OFF-DIAGONAL portion of the local submatrix (possibly different for 3083 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3084 structure. The size of this array is equal to the number 3085 of local rows, i.e 'm'. 3086 3087 Output Parameter: 3088 . A - the matrix 3089 3090 Notes: 3091 If the *_nnz parameter is given then the *_nz parameter is ignored 3092 3093 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3094 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3095 storage requirements for this matrix. 3096 3097 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3098 processor than it must be used on all processors that share the object for 3099 that argument. 3100 3101 The user MUST specify either the local or global matrix dimensions 3102 (possibly both). 3103 3104 The parallel matrix is partitioned across processors such that the 3105 first m0 rows belong to process 0, the next m1 rows belong to 3106 process 1, the next m2 rows belong to process 2 etc.. where 3107 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3108 values corresponding to [m x N] submatrix. 3109 3110 The columns are logically partitioned with the n0 columns belonging 3111 to 0th partition, the next n1 columns belonging to the next 3112 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3113 3114 The DIAGONAL portion of the local submatrix on any given processor 3115 is the submatrix corresponding to the rows and columns m,n 3116 corresponding to the given processor. i.e diagonal matrix on 3117 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3118 etc. The remaining portion of the local submatrix [m x (N-n)] 3119 constitute the OFF-DIAGONAL portion. The example below better 3120 illustrates this concept. 3121 3122 For a square global matrix we define each processor's diagonal portion 3123 to be its local rows and the corresponding columns (a square submatrix); 3124 each processor's off-diagonal portion encompasses the remainder of the 3125 local matrix (a rectangular submatrix). 3126 3127 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3128 3129 When calling this routine with a single process communicator, a matrix of 3130 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3131 type of communicator, use the construction mechanism: 3132 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3133 3134 By default, this format uses inodes (identical nodes) when possible. 3135 We search for consecutive rows with the same nonzero structure, thereby 3136 reusing matrix information to achieve increased efficiency. 3137 3138 Options Database Keys: 3139 + -mat_no_inode - Do not use inodes 3140 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3141 - -mat_aij_oneindex - Internally use indexing starting at 1 3142 rather than 0. Note that when calling MatSetValues(), 3143 the user still MUST index entries starting at 0! 3144 3145 3146 Example usage: 3147 3148 Consider the following 8x8 matrix with 34 non-zero values, that is 3149 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3150 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3151 as follows: 3152 3153 .vb 3154 1 2 0 | 0 3 0 | 0 4 3155 Proc0 0 5 6 | 7 0 0 | 8 0 3156 9 0 10 | 11 0 0 | 12 0 3157 ------------------------------------- 3158 13 0 14 | 15 16 17 | 0 0 3159 Proc1 0 18 0 | 19 20 21 | 0 0 3160 0 0 0 | 22 23 0 | 24 0 3161 ------------------------------------- 3162 Proc2 25 26 27 | 0 0 28 | 29 0 3163 30 0 0 | 31 32 33 | 0 34 3164 .ve 3165 3166 This can be represented as a collection of submatrices as: 3167 3168 .vb 3169 A B C 3170 D E F 3171 G H I 3172 .ve 3173 3174 Where the submatrices A,B,C are owned by proc0, D,E,F are 3175 owned by proc1, G,H,I are owned by proc2. 3176 3177 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3178 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3179 The 'M','N' parameters are 8,8, and have the same values on all procs. 3180 3181 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3182 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3183 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3184 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3185 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3186 matrix, ans [DF] as another SeqAIJ matrix. 3187 3188 When d_nz, o_nz parameters are specified, d_nz storage elements are 3189 allocated for every row of the local diagonal submatrix, and o_nz 3190 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3191 One way to choose d_nz and o_nz is to use the max nonzerors per local 3192 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3193 In this case, the values of d_nz,o_nz are: 3194 .vb 3195 proc0 : dnz = 2, o_nz = 2 3196 proc1 : dnz = 3, o_nz = 2 3197 proc2 : dnz = 1, o_nz = 4 3198 .ve 3199 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3200 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3201 for proc3. i.e we are using 12+15+10=37 storage locations to store 3202 34 values. 3203 3204 When d_nnz, o_nnz parameters are specified, the storage is specified 3205 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3206 In the above case the values for d_nnz,o_nnz are: 3207 .vb 3208 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3209 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3210 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3211 .ve 3212 Here the space allocated is sum of all the above values i.e 34, and 3213 hence pre-allocation is perfect. 3214 3215 Level: intermediate 3216 3217 .keywords: matrix, aij, compressed row, sparse, parallel 3218 3219 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3220 MPIAIJ, MatCreateMPIAIJWithArrays() 3221 @*/ 3222 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) 3223 { 3224 PetscErrorCode ierr; 3225 PetscMPIInt size; 3226 3227 PetscFunctionBegin; 3228 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3229 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3230 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3231 if (size > 1) { 3232 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3233 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3234 } else { 3235 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3236 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3237 } 3238 PetscFunctionReturn(0); 3239 } 3240 3241 #undef __FUNCT__ 3242 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3243 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3244 { 3245 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3246 3247 PetscFunctionBegin; 3248 *Ad = a->A; 3249 *Ao = a->B; 3250 *colmap = a->garray; 3251 PetscFunctionReturn(0); 3252 } 3253 3254 #undef __FUNCT__ 3255 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3256 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3257 { 3258 PetscErrorCode ierr; 3259 PetscInt i; 3260 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3261 3262 PetscFunctionBegin; 3263 if (coloring->ctype == IS_COLORING_GLOBAL) { 3264 ISColoringValue *allcolors,*colors; 3265 ISColoring ocoloring; 3266 3267 /* set coloring for diagonal portion */ 3268 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3269 3270 /* set coloring for off-diagonal portion */ 3271 ierr = ISAllGatherColors(A->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3272 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3273 for (i=0; i<a->B->cmap.n; i++) { 3274 colors[i] = allcolors[a->garray[i]]; 3275 } 3276 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3277 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3278 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3279 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3280 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3281 ISColoringValue *colors; 3282 PetscInt *larray; 3283 ISColoring ocoloring; 3284 3285 /* set coloring for diagonal portion */ 3286 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3287 for (i=0; i<a->A->cmap.n; i++) { 3288 larray[i] = i + A->cmap.rstart; 3289 } 3290 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap.n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3291 ierr = PetscMalloc((a->A->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3292 for (i=0; i<a->A->cmap.n; i++) { 3293 colors[i] = coloring->colors[larray[i]]; 3294 } 3295 ierr = PetscFree(larray);CHKERRQ(ierr); 3296 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3297 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3298 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3299 3300 /* set coloring for off-diagonal portion */ 3301 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3302 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap.n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3303 ierr = PetscMalloc((a->B->cmap.n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3304 for (i=0; i<a->B->cmap.n; i++) { 3305 colors[i] = coloring->colors[larray[i]]; 3306 } 3307 ierr = PetscFree(larray);CHKERRQ(ierr); 3308 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap.n,colors,&ocoloring);CHKERRQ(ierr); 3309 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3310 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3311 } else { 3312 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3313 } 3314 3315 PetscFunctionReturn(0); 3316 } 3317 3318 #if defined(PETSC_HAVE_ADIC) 3319 #undef __FUNCT__ 3320 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3321 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3322 { 3323 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3324 PetscErrorCode ierr; 3325 3326 PetscFunctionBegin; 3327 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3328 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3329 PetscFunctionReturn(0); 3330 } 3331 #endif 3332 3333 #undef __FUNCT__ 3334 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3335 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3336 { 3337 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3338 PetscErrorCode ierr; 3339 3340 PetscFunctionBegin; 3341 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3342 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3343 PetscFunctionReturn(0); 3344 } 3345 3346 #undef __FUNCT__ 3347 #define __FUNCT__ "MatMerge" 3348 /*@C 3349 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3350 matrices from each processor 3351 3352 Collective on MPI_Comm 3353 3354 Input Parameters: 3355 + comm - the communicators the parallel matrix will live on 3356 . inmat - the input sequential matrices 3357 . n - number of local columns (or PETSC_DECIDE) 3358 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3359 3360 Output Parameter: 3361 . outmat - the parallel matrix generated 3362 3363 Level: advanced 3364 3365 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3366 3367 @*/ 3368 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3369 { 3370 PetscErrorCode ierr; 3371 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3372 PetscInt *indx; 3373 PetscScalar *values; 3374 3375 PetscFunctionBegin; 3376 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3377 if (scall == MAT_INITIAL_MATRIX){ 3378 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3379 if (n == PETSC_DECIDE){ 3380 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3381 } 3382 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3383 rstart -= m; 3384 3385 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3386 for (i=0;i<m;i++) { 3387 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3388 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3389 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3390 } 3391 /* This routine will ONLY return MPIAIJ type matrix */ 3392 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3393 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3394 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3395 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3396 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3397 3398 } else if (scall == MAT_REUSE_MATRIX){ 3399 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3400 } else { 3401 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3402 } 3403 3404 for (i=0;i<m;i++) { 3405 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3406 Ii = i + rstart; 3407 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3408 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3409 } 3410 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3411 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3412 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3413 3414 PetscFunctionReturn(0); 3415 } 3416 3417 #undef __FUNCT__ 3418 #define __FUNCT__ "MatFileSplit" 3419 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3420 { 3421 PetscErrorCode ierr; 3422 PetscMPIInt rank; 3423 PetscInt m,N,i,rstart,nnz; 3424 size_t len; 3425 const PetscInt *indx; 3426 PetscViewer out; 3427 char *name; 3428 Mat B; 3429 const PetscScalar *values; 3430 3431 PetscFunctionBegin; 3432 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3433 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3434 /* Should this be the type of the diagonal block of A? */ 3435 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3436 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3437 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3438 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3439 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3440 for (i=0;i<m;i++) { 3441 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3442 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3443 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3444 } 3445 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3446 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3447 3448 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 3449 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3450 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3451 sprintf(name,"%s.%d",outfile,rank); 3452 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3453 ierr = PetscFree(name); 3454 ierr = MatView(B,out);CHKERRQ(ierr); 3455 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3456 ierr = MatDestroy(B);CHKERRQ(ierr); 3457 PetscFunctionReturn(0); 3458 } 3459 3460 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3461 #undef __FUNCT__ 3462 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3463 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3464 { 3465 PetscErrorCode ierr; 3466 Mat_Merge_SeqsToMPI *merge; 3467 PetscContainer container; 3468 3469 PetscFunctionBegin; 3470 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3471 if (container) { 3472 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3473 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3474 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3475 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3476 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3477 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3478 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3479 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3480 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3481 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3482 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3483 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3484 3485 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3486 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3487 } 3488 ierr = PetscFree(merge);CHKERRQ(ierr); 3489 3490 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3491 PetscFunctionReturn(0); 3492 } 3493 3494 #include "src/mat/utils/freespace.h" 3495 #include "petscbt.h" 3496 static PetscEvent logkey_seqstompinum = 0; 3497 #undef __FUNCT__ 3498 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3499 /*@C 3500 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3501 matrices from each processor 3502 3503 Collective on MPI_Comm 3504 3505 Input Parameters: 3506 + comm - the communicators the parallel matrix will live on 3507 . seqmat - the input sequential matrices 3508 . m - number of local rows (or PETSC_DECIDE) 3509 . n - number of local columns (or PETSC_DECIDE) 3510 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3511 3512 Output Parameter: 3513 . mpimat - the parallel matrix generated 3514 3515 Level: advanced 3516 3517 Notes: 3518 The dimensions of the sequential matrix in each processor MUST be the same. 3519 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3520 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3521 @*/ 3522 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3523 { 3524 PetscErrorCode ierr; 3525 MPI_Comm comm=mpimat->comm; 3526 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3527 PetscMPIInt size,rank,taga,*len_s; 3528 PetscInt N=mpimat->cmap.N,i,j,*owners,*ai=a->i,*aj=a->j; 3529 PetscInt proc,m; 3530 PetscInt **buf_ri,**buf_rj; 3531 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3532 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3533 MPI_Request *s_waits,*r_waits; 3534 MPI_Status *status; 3535 MatScalar *aa=a->a,**abuf_r,*ba_i; 3536 Mat_Merge_SeqsToMPI *merge; 3537 PetscContainer container; 3538 3539 PetscFunctionBegin; 3540 if (!logkey_seqstompinum) { 3541 ierr = PetscLogEventRegister(&logkey_seqstompinum,"MatMerge_SeqsToMPINumeric",MAT_COOKIE); 3542 } 3543 ierr = PetscLogEventBegin(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3544 3545 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3546 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3547 3548 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3549 if (container) { 3550 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3551 } 3552 bi = merge->bi; 3553 bj = merge->bj; 3554 buf_ri = merge->buf_ri; 3555 buf_rj = merge->buf_rj; 3556 3557 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3558 owners = merge->rowmap.range; 3559 len_s = merge->len_s; 3560 3561 /* send and recv matrix values */ 3562 /*-----------------------------*/ 3563 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3564 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3565 3566 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3567 for (proc=0,k=0; proc<size; proc++){ 3568 if (!len_s[proc]) continue; 3569 i = owners[proc]; 3570 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3571 k++; 3572 } 3573 3574 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3575 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3576 ierr = PetscFree(status);CHKERRQ(ierr); 3577 3578 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3579 ierr = PetscFree(r_waits);CHKERRQ(ierr); 3580 3581 /* insert mat values of mpimat */ 3582 /*----------------------------*/ 3583 ierr = PetscMalloc(N*sizeof(MatScalar),&ba_i);CHKERRQ(ierr); 3584 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3585 nextrow = buf_ri_k + merge->nrecv; 3586 nextai = nextrow + merge->nrecv; 3587 3588 for (k=0; k<merge->nrecv; k++){ 3589 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3590 nrows = *(buf_ri_k[k]); 3591 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 3592 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3593 } 3594 3595 /* set values of ba */ 3596 m = merge->rowmap.n; 3597 for (i=0; i<m; i++) { 3598 arow = owners[rank] + i; 3599 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 3600 bnzi = bi[i+1] - bi[i]; 3601 ierr = PetscMemzero(ba_i,bnzi*sizeof(MatScalar));CHKERRQ(ierr); 3602 3603 /* add local non-zero vals of this proc's seqmat into ba */ 3604 anzi = ai[arow+1] - ai[arow]; 3605 aj = a->j + ai[arow]; 3606 aa = a->a + ai[arow]; 3607 nextaj = 0; 3608 for (j=0; nextaj<anzi; j++){ 3609 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3610 ba_i[j] += aa[nextaj++]; 3611 } 3612 } 3613 3614 /* add received vals into ba */ 3615 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3616 /* i-th row */ 3617 if (i == *nextrow[k]) { 3618 anzi = *(nextai[k]+1) - *nextai[k]; 3619 aj = buf_rj[k] + *(nextai[k]); 3620 aa = abuf_r[k] + *(nextai[k]); 3621 nextaj = 0; 3622 for (j=0; nextaj<anzi; j++){ 3623 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 3624 ba_i[j] += aa[nextaj++]; 3625 } 3626 } 3627 nextrow[k]++; nextai[k]++; 3628 } 3629 } 3630 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 3631 } 3632 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3633 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3634 3635 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 3636 ierr = PetscFree(ba_i);CHKERRQ(ierr); 3637 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3638 ierr = PetscLogEventEnd(logkey_seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3639 PetscFunctionReturn(0); 3640 } 3641 3642 static PetscEvent logkey_seqstompisym = 0; 3643 #undef __FUNCT__ 3644 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 3645 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 3646 { 3647 PetscErrorCode ierr; 3648 Mat B_mpi; 3649 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3650 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 3651 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 3652 PetscInt M=seqmat->rmap.n,N=seqmat->cmap.n,i,*owners,*ai=a->i,*aj=a->j; 3653 PetscInt len,proc,*dnz,*onz; 3654 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 3655 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 3656 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 3657 MPI_Status *status; 3658 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 3659 PetscBT lnkbt; 3660 Mat_Merge_SeqsToMPI *merge; 3661 PetscContainer container; 3662 3663 PetscFunctionBegin; 3664 if (!logkey_seqstompisym) { 3665 ierr = PetscLogEventRegister(&logkey_seqstompisym,"MatMerge_SeqsToMPISymbolic",MAT_COOKIE); 3666 } 3667 ierr = PetscLogEventBegin(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3668 3669 /* make sure it is a PETSc comm */ 3670 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 3671 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3672 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3673 3674 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 3675 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3676 3677 /* determine row ownership */ 3678 /*---------------------------------------------------------*/ 3679 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 3680 merge->rowmap.n = m; 3681 merge->rowmap.N = M; 3682 merge->rowmap.bs = 1; 3683 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 3684 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 3685 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 3686 3687 m = merge->rowmap.n; 3688 M = merge->rowmap.N; 3689 owners = merge->rowmap.range; 3690 3691 /* determine the number of messages to send, their lengths */ 3692 /*---------------------------------------------------------*/ 3693 len_s = merge->len_s; 3694 3695 len = 0; /* length of buf_si[] */ 3696 merge->nsend = 0; 3697 for (proc=0; proc<size; proc++){ 3698 len_si[proc] = 0; 3699 if (proc == rank){ 3700 len_s[proc] = 0; 3701 } else { 3702 len_si[proc] = owners[proc+1] - owners[proc] + 1; 3703 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 3704 } 3705 if (len_s[proc]) { 3706 merge->nsend++; 3707 nrows = 0; 3708 for (i=owners[proc]; i<owners[proc+1]; i++){ 3709 if (ai[i+1] > ai[i]) nrows++; 3710 } 3711 len_si[proc] = 2*(nrows+1); 3712 len += len_si[proc]; 3713 } 3714 } 3715 3716 /* determine the number and length of messages to receive for ij-structure */ 3717 /*-------------------------------------------------------------------------*/ 3718 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 3719 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 3720 3721 /* post the Irecv of j-structure */ 3722 /*-------------------------------*/ 3723 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 3724 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 3725 3726 /* post the Isend of j-structure */ 3727 /*--------------------------------*/ 3728 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 3729 sj_waits = si_waits + merge->nsend; 3730 3731 for (proc=0, k=0; proc<size; proc++){ 3732 if (!len_s[proc]) continue; 3733 i = owners[proc]; 3734 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 3735 k++; 3736 } 3737 3738 /* receives and sends of j-structure are complete */ 3739 /*------------------------------------------------*/ 3740 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 3741 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 3742 3743 /* send and recv i-structure */ 3744 /*---------------------------*/ 3745 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 3746 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 3747 3748 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 3749 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 3750 for (proc=0,k=0; proc<size; proc++){ 3751 if (!len_s[proc]) continue; 3752 /* form outgoing message for i-structure: 3753 buf_si[0]: nrows to be sent 3754 [1:nrows]: row index (global) 3755 [nrows+1:2*nrows+1]: i-structure index 3756 */ 3757 /*-------------------------------------------*/ 3758 nrows = len_si[proc]/2 - 1; 3759 buf_si_i = buf_si + nrows+1; 3760 buf_si[0] = nrows; 3761 buf_si_i[0] = 0; 3762 nrows = 0; 3763 for (i=owners[proc]; i<owners[proc+1]; i++){ 3764 anzi = ai[i+1] - ai[i]; 3765 if (anzi) { 3766 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 3767 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 3768 nrows++; 3769 } 3770 } 3771 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 3772 k++; 3773 buf_si += len_si[proc]; 3774 } 3775 3776 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 3777 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 3778 3779 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 3780 for (i=0; i<merge->nrecv; i++){ 3781 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); 3782 } 3783 3784 ierr = PetscFree(len_si);CHKERRQ(ierr); 3785 ierr = PetscFree(len_ri);CHKERRQ(ierr); 3786 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 3787 ierr = PetscFree(si_waits);CHKERRQ(ierr); 3788 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 3789 ierr = PetscFree(buf_s);CHKERRQ(ierr); 3790 ierr = PetscFree(status);CHKERRQ(ierr); 3791 3792 /* compute a local seq matrix in each processor */ 3793 /*----------------------------------------------*/ 3794 /* allocate bi array and free space for accumulating nonzero column info */ 3795 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 3796 bi[0] = 0; 3797 3798 /* create and initialize a linked list */ 3799 nlnk = N+1; 3800 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3801 3802 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 3803 len = 0; 3804 len = ai[owners[rank+1]] - ai[owners[rank]]; 3805 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 3806 current_space = free_space; 3807 3808 /* determine symbolic info for each local row */ 3809 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 3810 nextrow = buf_ri_k + merge->nrecv; 3811 nextai = nextrow + merge->nrecv; 3812 for (k=0; k<merge->nrecv; k++){ 3813 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 3814 nrows = *buf_ri_k[k]; 3815 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 3816 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 3817 } 3818 3819 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3820 len = 0; 3821 for (i=0;i<m;i++) { 3822 bnzi = 0; 3823 /* add local non-zero cols of this proc's seqmat into lnk */ 3824 arow = owners[rank] + i; 3825 anzi = ai[arow+1] - ai[arow]; 3826 aj = a->j + ai[arow]; 3827 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3828 bnzi += nlnk; 3829 /* add received col data into lnk */ 3830 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 3831 if (i == *nextrow[k]) { /* i-th row */ 3832 anzi = *(nextai[k]+1) - *nextai[k]; 3833 aj = buf_rj[k] + *nextai[k]; 3834 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 3835 bnzi += nlnk; 3836 nextrow[k]++; nextai[k]++; 3837 } 3838 } 3839 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 3840 3841 /* if free space is not available, make more free space */ 3842 if (current_space->local_remaining<bnzi) { 3843 ierr = PetscFreeSpaceGet(current_space->total_array_size,¤t_space);CHKERRQ(ierr); 3844 nspacedouble++; 3845 } 3846 /* copy data into free space, then initialize lnk */ 3847 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 3848 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 3849 3850 current_space->array += bnzi; 3851 current_space->local_used += bnzi; 3852 current_space->local_remaining -= bnzi; 3853 3854 bi[i+1] = bi[i] + bnzi; 3855 } 3856 3857 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 3858 3859 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 3860 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 3861 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 3862 3863 /* create symbolic parallel matrix B_mpi */ 3864 /*---------------------------------------*/ 3865 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 3866 if (n==PETSC_DECIDE) { 3867 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 3868 } else { 3869 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3870 } 3871 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 3872 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 3873 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3874 3875 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 3876 B_mpi->assembled = PETSC_FALSE; 3877 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 3878 merge->bi = bi; 3879 merge->bj = bj; 3880 merge->buf_ri = buf_ri; 3881 merge->buf_rj = buf_rj; 3882 merge->coi = PETSC_NULL; 3883 merge->coj = PETSC_NULL; 3884 merge->owners_co = PETSC_NULL; 3885 3886 /* attach the supporting struct to B_mpi for reuse */ 3887 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 3888 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 3889 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 3890 *mpimat = B_mpi; 3891 3892 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 3893 ierr = PetscLogEventEnd(logkey_seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 3894 PetscFunctionReturn(0); 3895 } 3896 3897 static PetscEvent logkey_seqstompi = 0; 3898 #undef __FUNCT__ 3899 #define __FUNCT__ "MatMerge_SeqsToMPI" 3900 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 3901 { 3902 PetscErrorCode ierr; 3903 3904 PetscFunctionBegin; 3905 if (!logkey_seqstompi) { 3906 ierr = PetscLogEventRegister(&logkey_seqstompi,"MatMerge_SeqsToMPI",MAT_COOKIE); 3907 } 3908 ierr = PetscLogEventBegin(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 3909 if (scall == MAT_INITIAL_MATRIX){ 3910 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 3911 } 3912 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 3913 ierr = PetscLogEventEnd(logkey_seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 3914 PetscFunctionReturn(0); 3915 } 3916 static PetscEvent logkey_getlocalmat = 0; 3917 #undef __FUNCT__ 3918 #define __FUNCT__ "MatGetLocalMat" 3919 /*@C 3920 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 3921 3922 Not Collective 3923 3924 Input Parameters: 3925 + A - the matrix 3926 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3927 3928 Output Parameter: 3929 . A_loc - the local sequential matrix generated 3930 3931 Level: developer 3932 3933 @*/ 3934 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 3935 { 3936 PetscErrorCode ierr; 3937 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 3938 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 3939 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 3940 PetscScalar *aa=a->a,*ba=b->a,*ca; 3941 PetscInt am=A->rmap.n,i,j,k,cstart=A->cmap.rstart; 3942 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 3943 3944 PetscFunctionBegin; 3945 if (!logkey_getlocalmat) { 3946 ierr = PetscLogEventRegister(&logkey_getlocalmat,"MatGetLocalMat",MAT_COOKIE); 3947 } 3948 ierr = PetscLogEventBegin(logkey_getlocalmat,A,0,0,0);CHKERRQ(ierr); 3949 if (scall == MAT_INITIAL_MATRIX){ 3950 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 3951 ci[0] = 0; 3952 for (i=0; i<am; i++){ 3953 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 3954 } 3955 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 3956 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 3957 k = 0; 3958 for (i=0; i<am; i++) { 3959 ncols_o = bi[i+1] - bi[i]; 3960 ncols_d = ai[i+1] - ai[i]; 3961 /* off-diagonal portion of A */ 3962 for (jo=0; jo<ncols_o; jo++) { 3963 col = cmap[*bj]; 3964 if (col >= cstart) break; 3965 cj[k] = col; bj++; 3966 ca[k++] = *ba++; 3967 } 3968 /* diagonal portion of A */ 3969 for (j=0; j<ncols_d; j++) { 3970 cj[k] = cstart + *aj++; 3971 ca[k++] = *aa++; 3972 } 3973 /* off-diagonal portion of A */ 3974 for (j=jo; j<ncols_o; j++) { 3975 cj[k] = cmap[*bj++]; 3976 ca[k++] = *ba++; 3977 } 3978 } 3979 /* put together the new matrix */ 3980 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap.N,ci,cj,ca,A_loc);CHKERRQ(ierr); 3981 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 3982 /* Since these are PETSc arrays, change flags to free them as necessary. */ 3983 mat = (Mat_SeqAIJ*)(*A_loc)->data; 3984 mat->free_a = PETSC_TRUE; 3985 mat->free_ij = PETSC_TRUE; 3986 mat->nonew = 0; 3987 } else if (scall == MAT_REUSE_MATRIX){ 3988 mat=(Mat_SeqAIJ*)(*A_loc)->data; 3989 ci = mat->i; cj = mat->j; ca = mat->a; 3990 for (i=0; i<am; i++) { 3991 /* off-diagonal portion of A */ 3992 ncols_o = bi[i+1] - bi[i]; 3993 for (jo=0; jo<ncols_o; jo++) { 3994 col = cmap[*bj]; 3995 if (col >= cstart) break; 3996 *ca++ = *ba++; bj++; 3997 } 3998 /* diagonal portion of A */ 3999 ncols_d = ai[i+1] - ai[i]; 4000 for (j=0; j<ncols_d; j++) *ca++ = *aa++; 4001 /* off-diagonal portion of A */ 4002 for (j=jo; j<ncols_o; j++) { 4003 *ca++ = *ba++; bj++; 4004 } 4005 } 4006 } else { 4007 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4008 } 4009 4010 ierr = PetscLogEventEnd(logkey_getlocalmat,A,0,0,0);CHKERRQ(ierr); 4011 PetscFunctionReturn(0); 4012 } 4013 4014 static PetscEvent logkey_getlocalmatcondensed = 0; 4015 #undef __FUNCT__ 4016 #define __FUNCT__ "MatGetLocalMatCondensed" 4017 /*@C 4018 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4019 4020 Not Collective 4021 4022 Input Parameters: 4023 + A - the matrix 4024 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4025 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4026 4027 Output Parameter: 4028 . A_loc - the local sequential matrix generated 4029 4030 Level: developer 4031 4032 @*/ 4033 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4034 { 4035 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4036 PetscErrorCode ierr; 4037 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4038 IS isrowa,iscola; 4039 Mat *aloc; 4040 4041 PetscFunctionBegin; 4042 if (!logkey_getlocalmatcondensed) { 4043 ierr = PetscLogEventRegister(&logkey_getlocalmatcondensed,"MatGetLocalMatCondensed",MAT_COOKIE); 4044 } 4045 ierr = PetscLogEventBegin(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4046 if (!row){ 4047 start = A->rmap.rstart; end = A->rmap.rend; 4048 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4049 } else { 4050 isrowa = *row; 4051 } 4052 if (!col){ 4053 start = A->cmap.rstart; 4054 cmap = a->garray; 4055 nzA = a->A->cmap.n; 4056 nzB = a->B->cmap.n; 4057 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4058 ncols = 0; 4059 for (i=0; i<nzB; i++) { 4060 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4061 else break; 4062 } 4063 imark = i; 4064 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4065 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4066 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4067 ierr = PetscFree(idx);CHKERRQ(ierr); 4068 } else { 4069 iscola = *col; 4070 } 4071 if (scall != MAT_INITIAL_MATRIX){ 4072 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4073 aloc[0] = *A_loc; 4074 } 4075 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4076 *A_loc = aloc[0]; 4077 ierr = PetscFree(aloc);CHKERRQ(ierr); 4078 if (!row){ 4079 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4080 } 4081 if (!col){ 4082 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4083 } 4084 ierr = PetscLogEventEnd(logkey_getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4085 PetscFunctionReturn(0); 4086 } 4087 4088 static PetscEvent logkey_GetBrowsOfAcols = 0; 4089 #undef __FUNCT__ 4090 #define __FUNCT__ "MatGetBrowsOfAcols" 4091 /*@C 4092 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4093 4094 Collective on Mat 4095 4096 Input Parameters: 4097 + A,B - the matrices in mpiaij format 4098 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4099 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4100 4101 Output Parameter: 4102 + rowb, colb - index sets of rows and columns of B to extract 4103 . brstart - row index of B_seq from which next B->rmap.n rows are taken from B's local rows 4104 - B_seq - the sequential matrix generated 4105 4106 Level: developer 4107 4108 @*/ 4109 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4110 { 4111 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4112 PetscErrorCode ierr; 4113 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4114 IS isrowb,iscolb; 4115 Mat *bseq; 4116 4117 PetscFunctionBegin; 4118 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4119 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); 4120 } 4121 if (!logkey_GetBrowsOfAcols) { 4122 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAcols,"MatGetBrowsOfAcols",MAT_COOKIE); 4123 } 4124 ierr = PetscLogEventBegin(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4125 4126 if (scall == MAT_INITIAL_MATRIX){ 4127 start = A->cmap.rstart; 4128 cmap = a->garray; 4129 nzA = a->A->cmap.n; 4130 nzB = a->B->cmap.n; 4131 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4132 ncols = 0; 4133 for (i=0; i<nzB; i++) { /* row < local row index */ 4134 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4135 else break; 4136 } 4137 imark = i; 4138 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4139 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4140 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4141 ierr = PetscFree(idx);CHKERRQ(ierr); 4142 *brstart = imark; 4143 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap.N,0,1,&iscolb);CHKERRQ(ierr); 4144 } else { 4145 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4146 isrowb = *rowb; iscolb = *colb; 4147 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4148 bseq[0] = *B_seq; 4149 } 4150 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4151 *B_seq = bseq[0]; 4152 ierr = PetscFree(bseq);CHKERRQ(ierr); 4153 if (!rowb){ 4154 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4155 } else { 4156 *rowb = isrowb; 4157 } 4158 if (!colb){ 4159 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4160 } else { 4161 *colb = iscolb; 4162 } 4163 ierr = PetscLogEventEnd(logkey_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4164 PetscFunctionReturn(0); 4165 } 4166 4167 static PetscEvent logkey_GetBrowsOfAocols = 0; 4168 #undef __FUNCT__ 4169 #define __FUNCT__ "MatGetBrowsOfAoCols" 4170 /*@C 4171 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4172 of the OFF-DIAGONAL portion of local A 4173 4174 Collective on Mat 4175 4176 Input Parameters: 4177 + A,B - the matrices in mpiaij format 4178 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4179 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4180 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4181 4182 Output Parameter: 4183 + B_oth - the sequential matrix generated 4184 4185 Level: developer 4186 4187 @*/ 4188 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,PetscScalar **bufa_ptr,Mat *B_oth) 4189 { 4190 VecScatter_MPI_General *gen_to,*gen_from; 4191 PetscErrorCode ierr; 4192 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4193 Mat_SeqAIJ *b_oth; 4194 VecScatter ctx=a->Mvctx; 4195 MPI_Comm comm=ctx->comm; 4196 PetscMPIInt *rprocs,*sprocs,tag=ctx->tag,rank; 4197 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap.n,row,*b_othi,*b_othj; 4198 PetscScalar *rvalues,*svalues,*b_otha,*bufa,*bufA; 4199 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4200 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4201 MPI_Status *sstatus,rstatus; 4202 PetscMPIInt jj; 4203 PetscInt *cols,sbs,rbs; 4204 PetscScalar *vals; 4205 4206 PetscFunctionBegin; 4207 if (A->cmap.rstart != B->rmap.rstart || A->cmap.rend != B->rmap.rend){ 4208 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); 4209 } 4210 if (!logkey_GetBrowsOfAocols) { 4211 ierr = PetscLogEventRegister(&logkey_GetBrowsOfAocols,"MatGetBrAoCol",MAT_COOKIE); 4212 } 4213 ierr = PetscLogEventBegin(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4214 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4215 4216 gen_to = (VecScatter_MPI_General*)ctx->todata; 4217 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4218 rvalues = gen_from->values; /* holds the length of receiving row */ 4219 svalues = gen_to->values; /* holds the length of sending row */ 4220 nrecvs = gen_from->n; 4221 nsends = gen_to->n; 4222 4223 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4224 srow = gen_to->indices; /* local row index to be sent */ 4225 sstarts = gen_to->starts; 4226 sprocs = gen_to->procs; 4227 sstatus = gen_to->sstatus; 4228 sbs = gen_to->bs; 4229 rstarts = gen_from->starts; 4230 rprocs = gen_from->procs; 4231 rbs = gen_from->bs; 4232 4233 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4234 if (scall == MAT_INITIAL_MATRIX){ 4235 /* i-array */ 4236 /*---------*/ 4237 /* post receives */ 4238 for (i=0; i<nrecvs; i++){ 4239 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4240 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4241 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4242 } 4243 4244 /* pack the outgoing message */ 4245 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4246 rstartsj = sstartsj + nsends +1; 4247 sstartsj[0] = 0; rstartsj[0] = 0; 4248 len = 0; /* total length of j or a array to be sent */ 4249 k = 0; 4250 for (i=0; i<nsends; i++){ 4251 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4252 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4253 for (j=0; j<nrows; j++) { 4254 row = srow[k] + B->rmap.range[rank]; /* global row idx */ 4255 for (l=0; l<sbs; l++){ 4256 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4257 rowlen[j*sbs+l] = ncols; 4258 len += ncols; 4259 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4260 } 4261 k++; 4262 } 4263 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4264 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4265 } 4266 /* recvs and sends of i-array are completed */ 4267 i = nrecvs; 4268 while (i--) { 4269 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4270 } 4271 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4272 4273 /* allocate buffers for sending j and a arrays */ 4274 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4275 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4276 4277 /* create i-array of B_oth */ 4278 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4279 b_othi[0] = 0; 4280 len = 0; /* total length of j or a array to be received */ 4281 k = 0; 4282 for (i=0; i<nrecvs; i++){ 4283 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4284 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4285 for (j=0; j<nrows; j++) { 4286 b_othi[k+1] = b_othi[k] + rowlen[j]; 4287 len += rowlen[j]; k++; 4288 } 4289 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4290 } 4291 4292 /* allocate space for j and a arrrays of B_oth */ 4293 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4294 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscScalar),&b_otha);CHKERRQ(ierr); 4295 4296 /* j-array */ 4297 /*---------*/ 4298 /* post receives of j-array */ 4299 for (i=0; i<nrecvs; i++){ 4300 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4301 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4302 } 4303 4304 /* pack the outgoing message j-array */ 4305 k = 0; 4306 for (i=0; i<nsends; i++){ 4307 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4308 bufJ = bufj+sstartsj[i]; 4309 for (j=0; j<nrows; j++) { 4310 row = srow[k++] + B->rmap.range[rank]; /* global row idx */ 4311 for (ll=0; ll<sbs; ll++){ 4312 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4313 for (l=0; l<ncols; l++){ 4314 *bufJ++ = cols[l]; 4315 } 4316 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4317 } 4318 } 4319 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4320 } 4321 4322 /* recvs and sends of j-array are completed */ 4323 i = nrecvs; 4324 while (i--) { 4325 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4326 } 4327 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4328 } else if (scall == MAT_REUSE_MATRIX){ 4329 sstartsj = *startsj; 4330 rstartsj = sstartsj + nsends +1; 4331 bufa = *bufa_ptr; 4332 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4333 b_otha = b_oth->a; 4334 } else { 4335 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4336 } 4337 4338 /* a-array */ 4339 /*---------*/ 4340 /* post receives of a-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_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4344 } 4345 4346 /* pack the outgoing message a-array */ 4347 k = 0; 4348 for (i=0; i<nsends; i++){ 4349 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4350 bufA = bufa+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,PETSC_NULL,&vals);CHKERRQ(ierr); 4355 for (l=0; l<ncols; l++){ 4356 *bufA++ = vals[l]; 4357 } 4358 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4359 } 4360 } 4361 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4362 } 4363 /* recvs and sends of a-array are completed */ 4364 i = nrecvs; 4365 while (i--) { 4366 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4367 } 4368 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4369 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4370 4371 if (scall == MAT_INITIAL_MATRIX){ 4372 /* put together the new matrix */ 4373 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap.N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4374 4375 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4376 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4377 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4378 b_oth->free_a = PETSC_TRUE; 4379 b_oth->free_ij = PETSC_TRUE; 4380 b_oth->nonew = 0; 4381 4382 ierr = PetscFree(bufj);CHKERRQ(ierr); 4383 if (!startsj || !bufa_ptr){ 4384 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4385 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4386 } else { 4387 *startsj = sstartsj; 4388 *bufa_ptr = bufa; 4389 } 4390 } 4391 ierr = PetscLogEventEnd(logkey_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4392 PetscFunctionReturn(0); 4393 } 4394 4395 #undef __FUNCT__ 4396 #define __FUNCT__ "MatGetCommunicationStructs" 4397 /*@C 4398 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4399 4400 Not Collective 4401 4402 Input Parameters: 4403 . A - The matrix in mpiaij format 4404 4405 Output Parameter: 4406 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4407 . colmap - A map from global column index to local index into lvec 4408 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4409 4410 Level: developer 4411 4412 @*/ 4413 #if defined (PETSC_USE_CTABLE) 4414 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4415 #else 4416 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4417 #endif 4418 { 4419 Mat_MPIAIJ *a; 4420 4421 PetscFunctionBegin; 4422 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4423 PetscValidPointer(lvec, 2) 4424 PetscValidPointer(colmap, 3) 4425 PetscValidPointer(multScatter, 4) 4426 a = (Mat_MPIAIJ *) A->data; 4427 if (lvec) *lvec = a->lvec; 4428 if (colmap) *colmap = a->colmap; 4429 if (multScatter) *multScatter = a->Mvctx; 4430 PetscFunctionReturn(0); 4431 } 4432 4433 EXTERN_C_BEGIN 4434 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,MatType,MatReuse,Mat*); 4435 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,MatType,MatReuse,Mat*); 4436 EXTERN_C_END 4437 4438 /*MC 4439 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4440 4441 Options Database Keys: 4442 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4443 4444 Level: beginner 4445 4446 .seealso: MatCreateMPIAIJ 4447 M*/ 4448 4449 EXTERN_C_BEGIN 4450 #undef __FUNCT__ 4451 #define __FUNCT__ "MatCreate_MPIAIJ" 4452 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4453 { 4454 Mat_MPIAIJ *b; 4455 PetscErrorCode ierr; 4456 PetscMPIInt size; 4457 4458 PetscFunctionBegin; 4459 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 4460 4461 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4462 B->data = (void*)b; 4463 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4464 B->factor = 0; 4465 B->rmap.bs = 1; 4466 B->assembled = PETSC_FALSE; 4467 B->mapping = 0; 4468 4469 B->insertmode = NOT_SET_VALUES; 4470 b->size = size; 4471 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 4472 4473 /* build cache for off array entries formed */ 4474 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 4475 b->donotstash = PETSC_FALSE; 4476 b->colmap = 0; 4477 b->garray = 0; 4478 b->roworiented = PETSC_TRUE; 4479 4480 /* stuff used for matrix vector multiply */ 4481 b->lvec = PETSC_NULL; 4482 b->Mvctx = PETSC_NULL; 4483 4484 /* stuff for MatGetRow() */ 4485 b->rowindices = 0; 4486 b->rowvalues = 0; 4487 b->getrowactive = PETSC_FALSE; 4488 4489 4490 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4491 "MatStoreValues_MPIAIJ", 4492 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4493 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4494 "MatRetrieveValues_MPIAIJ", 4495 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4496 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4497 "MatGetDiagonalBlock_MPIAIJ", 4498 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4499 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4500 "MatIsTranspose_MPIAIJ", 4501 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4502 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4503 "MatMPIAIJSetPreallocation_MPIAIJ", 4504 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4505 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4506 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4507 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4508 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4509 "MatDiagonalScaleLocal_MPIAIJ", 4510 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4511 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 4512 "MatConvert_MPIAIJ_MPICSRPERM", 4513 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 4514 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 4515 "MatConvert_MPIAIJ_MPICRL", 4516 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 4517 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 4518 PetscFunctionReturn(0); 4519 } 4520 EXTERN_C_END 4521 4522 #undef __FUNCT__ 4523 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 4524 /*@C 4525 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 4526 and "off-diagonal" part of the matrix in CSR format. 4527 4528 Collective on MPI_Comm 4529 4530 Input Parameters: 4531 + comm - MPI communicator 4532 . m - number of local rows (Cannot be PETSC_DECIDE) 4533 . n - This value should be the same as the local size used in creating the 4534 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4535 calculated if N is given) For square matrices n is almost always m. 4536 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4537 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4538 . i - row indices for "diagonal" portion of matrix 4539 . j - column indices 4540 . a - matrix values 4541 . oi - row indices for "off-diagonal" portion of matrix 4542 . oj - column indices 4543 - oa - matrix values 4544 4545 Output Parameter: 4546 . mat - the matrix 4547 4548 Level: advanced 4549 4550 Notes: 4551 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 4552 4553 The i and j indices are 0 based 4554 4555 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 4556 4557 4558 .keywords: matrix, aij, compressed row, sparse, parallel 4559 4560 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4561 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 4562 @*/ 4563 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 4564 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 4565 { 4566 PetscErrorCode ierr; 4567 Mat_MPIAIJ *maij; 4568 4569 PetscFunctionBegin; 4570 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4571 if (i[0]) { 4572 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4573 } 4574 if (oi[0]) { 4575 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 4576 } 4577 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4578 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4579 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4580 maij = (Mat_MPIAIJ*) (*mat)->data; 4581 maij->donotstash = PETSC_TRUE; 4582 (*mat)->preallocated = PETSC_TRUE; 4583 4584 (*mat)->rmap.bs = (*mat)->cmap.bs = 1; 4585 ierr = PetscMapSetUp(&(*mat)->rmap);CHKERRQ(ierr); 4586 ierr = PetscMapSetUp(&(*mat)->cmap);CHKERRQ(ierr); 4587 4588 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 4589 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap.N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 4590 4591 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4592 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4593 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4594 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4595 4596 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4597 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4598 PetscFunctionReturn(0); 4599 } 4600 4601 /* 4602 Special version for direct calls from Fortran 4603 */ 4604 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4605 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 4606 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4607 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 4608 #endif 4609 4610 /* Change these macros so can be used in void function */ 4611 #undef CHKERRQ 4612 #define CHKERRQ(ierr) CHKERRABORT(mat->comm,ierr) 4613 #undef SETERRQ2 4614 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(mat->comm,ierr) 4615 #undef SETERRQ 4616 #define SETERRQ(ierr,b) CHKERRABORT(mat->comm,ierr) 4617 4618 EXTERN_C_BEGIN 4619 #undef __FUNCT__ 4620 #define __FUNCT__ "matsetvaluesmpiaij_" 4621 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 4622 { 4623 Mat mat = *mmat; 4624 PetscInt m = *mm, n = *mn; 4625 InsertMode addv = *maddv; 4626 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 4627 PetscScalar value; 4628 PetscErrorCode ierr; 4629 4630 MatPreallocated(mat); 4631 if (mat->insertmode == NOT_SET_VALUES) { 4632 mat->insertmode = addv; 4633 } 4634 #if defined(PETSC_USE_DEBUG) 4635 else if (mat->insertmode != addv) { 4636 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 4637 } 4638 #endif 4639 { 4640 PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend; 4641 PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col; 4642 PetscTruth roworiented = aij->roworiented; 4643 4644 /* Some Variables required in the macro */ 4645 Mat A = aij->A; 4646 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4647 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 4648 PetscScalar *aa = a->a; 4649 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 4650 Mat B = aij->B; 4651 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 4652 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n; 4653 PetscScalar *ba = b->a; 4654 4655 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 4656 PetscInt nonew = a->nonew; 4657 PetscScalar *ap1,*ap2; 4658 4659 PetscFunctionBegin; 4660 for (i=0; i<m; i++) { 4661 if (im[i] < 0) continue; 4662 #if defined(PETSC_USE_DEBUG) 4663 if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1); 4664 #endif 4665 if (im[i] >= rstart && im[i] < rend) { 4666 row = im[i] - rstart; 4667 lastcol1 = -1; 4668 rp1 = aj + ai[row]; 4669 ap1 = aa + ai[row]; 4670 rmax1 = aimax[row]; 4671 nrow1 = ailen[row]; 4672 low1 = 0; 4673 high1 = nrow1; 4674 lastcol2 = -1; 4675 rp2 = bj + bi[row]; 4676 ap2 = ba + bi[row]; 4677 rmax2 = bimax[row]; 4678 nrow2 = bilen[row]; 4679 low2 = 0; 4680 high2 = nrow2; 4681 4682 for (j=0; j<n; j++) { 4683 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 4684 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 4685 if (in[j] >= cstart && in[j] < cend){ 4686 col = in[j] - cstart; 4687 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 4688 } else if (in[j] < 0) continue; 4689 #if defined(PETSC_USE_DEBUG) 4690 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);} 4691 #endif 4692 else { 4693 if (mat->was_assembled) { 4694 if (!aij->colmap) { 4695 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 4696 } 4697 #if defined (PETSC_USE_CTABLE) 4698 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 4699 col--; 4700 #else 4701 col = aij->colmap[in[j]] - 1; 4702 #endif 4703 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 4704 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 4705 col = in[j]; 4706 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 4707 B = aij->B; 4708 b = (Mat_SeqAIJ*)B->data; 4709 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 4710 rp2 = bj + bi[row]; 4711 ap2 = ba + bi[row]; 4712 rmax2 = bimax[row]; 4713 nrow2 = bilen[row]; 4714 low2 = 0; 4715 high2 = nrow2; 4716 bm = aij->B->rmap.n; 4717 ba = b->a; 4718 } 4719 } else col = in[j]; 4720 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 4721 } 4722 } 4723 } else { 4724 if (!aij->donotstash) { 4725 if (roworiented) { 4726 if (ignorezeroentries && v[i*n] == 0.0) continue; 4727 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 4728 } else { 4729 if (ignorezeroentries && v[i] == 0.0) continue; 4730 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 4731 } 4732 } 4733 } 4734 }} 4735 PetscFunctionReturnVoid(); 4736 } 4737 EXTERN_C_END 4738 4739