1 /*$Id: mpiaij.c,v 1.344 2001/08/10 03:30:48 bsmith Exp $*/ 2 3 #include "src/mat/impls/aij/mpi/mpiaij.h" 4 #include "src/vec/vecimpl.h" 5 #include "src/inline/spops.h" 6 7 EXTERN int MatSetUpMultiply_MPIAIJ(Mat); 8 EXTERN int DisAssemble_MPIAIJ(Mat); 9 EXTERN int MatSetValues_SeqAIJ(Mat,int,int*,int,int*,PetscScalar*,InsertMode); 10 EXTERN int MatGetRow_SeqAIJ(Mat,int,int*,int**,PetscScalar**); 11 EXTERN int MatRestoreRow_SeqAIJ(Mat,int,int*,int**,PetscScalar**); 12 EXTERN int MatPrintHelp_SeqAIJ(Mat); 13 14 /* 15 Local utility routine that creates a mapping from the global column 16 number to the local number in the off-diagonal part of the local 17 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 18 a slightly higher hash table cost; without it it is not scalable (each processor 19 has an order N integer array but is fast to acess. 20 */ 21 #undef __FUNCT__ 22 #define __FUNCT__ "CreateColmap_MPIAIJ_Private" 23 int CreateColmap_MPIAIJ_Private(Mat mat) 24 { 25 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 26 int n = aij->B->n,i,ierr; 27 28 PetscFunctionBegin; 29 #if defined (PETSC_USE_CTABLE) 30 ierr = PetscTableCreate(n,&aij->colmap);CHKERRQ(ierr); 31 for (i=0; i<n; i++){ 32 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);CHKERRQ(ierr); 33 } 34 #else 35 ierr = PetscMalloc((mat->N+1)*sizeof(int),&aij->colmap);CHKERRQ(ierr); 36 PetscLogObjectMemory(mat,mat->N*sizeof(int)); 37 ierr = PetscMemzero(aij->colmap,mat->N*sizeof(int));CHKERRQ(ierr); 38 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 39 #endif 40 PetscFunctionReturn(0); 41 } 42 43 #define CHUNKSIZE 15 44 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 45 { \ 46 \ 47 rp = aj + ai[row] + shift; ap = aa + ai[row] + shift; \ 48 rmax = aimax[row]; nrow = ailen[row]; \ 49 col1 = col - shift; \ 50 \ 51 low = 0; high = nrow; \ 52 while (high-low > 5) { \ 53 t = (low+high)/2; \ 54 if (rp[t] > col) high = t; \ 55 else low = t; \ 56 } \ 57 for (_i=low; _i<high; _i++) { \ 58 if (rp[_i] > col1) break; \ 59 if (rp[_i] == col1) { \ 60 if (addv == ADD_VALUES) ap[_i] += value; \ 61 else ap[_i] = value; \ 62 goto a_noinsert; \ 63 } \ 64 } \ 65 if (nonew == 1) goto a_noinsert; \ 66 else if (nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 67 if (nrow >= rmax) { \ 68 /* there is no extra room in row, therefore enlarge */ \ 69 int new_nz = ai[am] + CHUNKSIZE,len,*new_i,*new_j; \ 70 PetscScalar *new_a; \ 71 \ 72 if (nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 73 \ 74 /* malloc new storage space */ \ 75 len = new_nz*(sizeof(int)+sizeof(PetscScalar))+(am+1)*sizeof(int); \ 76 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 77 new_j = (int*)(new_a + new_nz); \ 78 new_i = new_j + new_nz; \ 79 \ 80 /* copy over old data into new slots */ \ 81 for (ii=0; ii<row+1; ii++) {new_i[ii] = ai[ii];} \ 82 for (ii=row+1; ii<am+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 83 ierr = PetscMemcpy(new_j,aj,(ai[row]+nrow+shift)*sizeof(int));CHKERRQ(ierr); \ 84 len = (new_nz - CHUNKSIZE - ai[row] - nrow - shift); \ 85 ierr = PetscMemcpy(new_j+ai[row]+shift+nrow+CHUNKSIZE,aj+ai[row]+shift+nrow, \ 86 len*sizeof(int));CHKERRQ(ierr); \ 87 ierr = PetscMemcpy(new_a,aa,(ai[row]+nrow+shift)*sizeof(PetscScalar));CHKERRQ(ierr); \ 88 ierr = PetscMemcpy(new_a+ai[row]+shift+nrow+CHUNKSIZE,aa+ai[row]+shift+nrow, \ 89 len*sizeof(PetscScalar));CHKERRQ(ierr); \ 90 /* free up old matrix storage */ \ 91 \ 92 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 93 if (!a->singlemalloc) { \ 94 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 95 ierr = PetscFree(a->j);CHKERRQ(ierr); \ 96 } \ 97 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 98 a->singlemalloc = PETSC_TRUE; \ 99 \ 100 rp = aj + ai[row] + shift; ap = aa + ai[row] + shift; \ 101 rmax = aimax[row] = aimax[row] + CHUNKSIZE; \ 102 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + sizeof(PetscScalar))); \ 103 a->maxnz += CHUNKSIZE; \ 104 a->reallocs++; \ 105 } \ 106 N = nrow++ - 1; a->nz++; \ 107 /* shift up all the later entries in this row */ \ 108 for (ii=N; ii>=_i; ii--) { \ 109 rp[ii+1] = rp[ii]; \ 110 ap[ii+1] = ap[ii]; \ 111 } \ 112 rp[_i] = col1; \ 113 ap[_i] = value; \ 114 a_noinsert: ; \ 115 ailen[row] = nrow; \ 116 } 117 118 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 119 { \ 120 \ 121 rp = bj + bi[row] + shift; ap = ba + bi[row] + shift; \ 122 rmax = bimax[row]; nrow = bilen[row]; \ 123 col1 = col - shift; \ 124 \ 125 low = 0; high = nrow; \ 126 while (high-low > 5) { \ 127 t = (low+high)/2; \ 128 if (rp[t] > col) high = t; \ 129 else low = t; \ 130 } \ 131 for (_i=low; _i<high; _i++) { \ 132 if (rp[_i] > col1) break; \ 133 if (rp[_i] == col1) { \ 134 if (addv == ADD_VALUES) ap[_i] += value; \ 135 else ap[_i] = value; \ 136 goto b_noinsert; \ 137 } \ 138 } \ 139 if (nonew == 1) goto b_noinsert; \ 140 else if (nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 141 if (nrow >= rmax) { \ 142 /* there is no extra room in row, therefore enlarge */ \ 143 int new_nz = bi[bm] + CHUNKSIZE,len,*new_i,*new_j; \ 144 PetscScalar *new_a; \ 145 \ 146 if (nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 147 \ 148 /* malloc new storage space */ \ 149 len = new_nz*(sizeof(int)+sizeof(PetscScalar))+(bm+1)*sizeof(int); \ 150 ierr = PetscMalloc(len,&new_a);CHKERRQ(ierr); \ 151 new_j = (int*)(new_a + new_nz); \ 152 new_i = new_j + new_nz; \ 153 \ 154 /* copy over old data into new slots */ \ 155 for (ii=0; ii<row+1; ii++) {new_i[ii] = bi[ii];} \ 156 for (ii=row+1; ii<bm+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 157 ierr = PetscMemcpy(new_j,bj,(bi[row]+nrow+shift)*sizeof(int));CHKERRQ(ierr); \ 158 len = (new_nz - CHUNKSIZE - bi[row] - nrow - shift); \ 159 ierr = PetscMemcpy(new_j+bi[row]+shift+nrow+CHUNKSIZE,bj+bi[row]+shift+nrow, \ 160 len*sizeof(int));CHKERRQ(ierr); \ 161 ierr = PetscMemcpy(new_a,ba,(bi[row]+nrow+shift)*sizeof(PetscScalar));CHKERRQ(ierr); \ 162 ierr = PetscMemcpy(new_a+bi[row]+shift+nrow+CHUNKSIZE,ba+bi[row]+shift+nrow, \ 163 len*sizeof(PetscScalar));CHKERRQ(ierr); \ 164 /* free up old matrix storage */ \ 165 \ 166 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 167 if (!b->singlemalloc) { \ 168 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 169 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 170 } \ 171 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 172 b->singlemalloc = PETSC_TRUE; \ 173 \ 174 rp = bj + bi[row] + shift; ap = ba + bi[row] + shift; \ 175 rmax = bimax[row] = bimax[row] + CHUNKSIZE; \ 176 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + sizeof(PetscScalar))); \ 177 b->maxnz += CHUNKSIZE; \ 178 b->reallocs++; \ 179 } \ 180 N = nrow++ - 1; b->nz++; \ 181 /* shift up all the later entries in this row */ \ 182 for (ii=N; ii>=_i; ii--) { \ 183 rp[ii+1] = rp[ii]; \ 184 ap[ii+1] = ap[ii]; \ 185 } \ 186 rp[_i] = col1; \ 187 ap[_i] = value; \ 188 b_noinsert: ; \ 189 bilen[row] = nrow; \ 190 } 191 192 #undef __FUNCT__ 193 #define __FUNCT__ "MatSetValues_MPIAIJ" 194 int MatSetValues_MPIAIJ(Mat mat,int m,int *im,int n,int *in,PetscScalar *v,InsertMode addv) 195 { 196 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 197 PetscScalar value; 198 int ierr,i,j,rstart = aij->rstart,rend = aij->rend; 199 int cstart = aij->cstart,cend = aij->cend,row,col; 200 PetscTruth roworiented = aij->roworiented; 201 202 /* Some Variables required in the macro */ 203 Mat A = aij->A; 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 int *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 206 PetscScalar *aa = a->a; 207 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 208 Mat B = aij->B; 209 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 210 int *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->m,am = aij->A->m; 211 PetscScalar *ba = b->a; 212 213 int *rp,ii,nrow,_i,rmax,N,col1,low,high,t; 214 int nonew = a->nonew,shift=0; 215 PetscScalar *ap; 216 217 PetscFunctionBegin; 218 for (i=0; i<m; i++) { 219 if (im[i] < 0) continue; 220 #if defined(PETSC_USE_BOPT_g) 221 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 222 #endif 223 if (im[i] >= rstart && im[i] < rend) { 224 row = im[i] - rstart; 225 for (j=0; j<n; j++) { 226 if (in[j] >= cstart && in[j] < cend){ 227 col = in[j] - cstart; 228 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 229 if (ignorezeroentries && value == 0.0) continue; 230 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 231 /* ierr = MatSetValues_SeqAIJ(aij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 232 } else if (in[j] < 0) continue; 233 #if defined(PETSC_USE_BOPT_g) 234 else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large");} 235 #endif 236 else { 237 if (mat->was_assembled) { 238 if (!aij->colmap) { 239 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 240 } 241 #if defined (PETSC_USE_CTABLE) 242 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 243 col--; 244 #else 245 col = aij->colmap[in[j]] - 1; 246 #endif 247 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 248 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 249 col = in[j]; 250 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 251 B = aij->B; 252 b = (Mat_SeqAIJ*)B->data; 253 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 254 ba = b->a; 255 } 256 } else col = in[j]; 257 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 258 if (ignorezeroentries && value == 0.0) continue; 259 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 260 /* ierr = MatSetValues_SeqAIJ(aij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 261 } 262 } 263 } else { 264 if (!aij->donotstash) { 265 if (roworiented) { 266 if (ignorezeroentries && v[i*n] == 0.0) continue; 267 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 268 } else { 269 if (ignorezeroentries && v[i] == 0.0) continue; 270 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 271 } 272 } 273 } 274 } 275 PetscFunctionReturn(0); 276 } 277 278 #undef __FUNCT__ 279 #define __FUNCT__ "MatGetValues_MPIAIJ" 280 int MatGetValues_MPIAIJ(Mat mat,int m,int *idxm,int n,int *idxn,PetscScalar *v) 281 { 282 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 283 int ierr,i,j,rstart = aij->rstart,rend = aij->rend; 284 int cstart = aij->cstart,cend = aij->cend,row,col; 285 286 PetscFunctionBegin; 287 for (i=0; i<m; i++) { 288 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 289 if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 290 if (idxm[i] >= rstart && idxm[i] < rend) { 291 row = idxm[i] - rstart; 292 for (j=0; j<n; j++) { 293 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 294 if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 295 if (idxn[j] >= cstart && idxn[j] < cend){ 296 col = idxn[j] - cstart; 297 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 298 } else { 299 if (!aij->colmap) { 300 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 301 } 302 #if defined (PETSC_USE_CTABLE) 303 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 304 col --; 305 #else 306 col = aij->colmap[idxn[j]] - 1; 307 #endif 308 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 309 else { 310 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 311 } 312 } 313 } 314 } else { 315 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 316 } 317 } 318 PetscFunctionReturn(0); 319 } 320 321 #undef __FUNCT__ 322 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 323 int MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 324 { 325 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 326 int ierr,nstash,reallocs; 327 InsertMode addv; 328 329 PetscFunctionBegin; 330 if (aij->donotstash) { 331 PetscFunctionReturn(0); 332 } 333 334 /* make sure all processors are either in INSERTMODE or ADDMODE */ 335 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 336 if (addv == (ADD_VALUES|INSERT_VALUES)) { 337 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 338 } 339 mat->insertmode = addv; /* in case this processor had no cache */ 340 341 ierr = MatStashScatterBegin_Private(&mat->stash,aij->rowners);CHKERRQ(ierr); 342 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 343 PetscLogInfo(aij->A,"MatAssemblyBegin_MPIAIJ:Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 344 PetscFunctionReturn(0); 345 } 346 347 348 #undef __FUNCT__ 349 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 350 int MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 351 { 352 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 353 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data,*b= (Mat_SeqAIJ *)aij->B->data; 354 int i,j,rstart,ncols,n,ierr,flg; 355 int *row,*col,other_disassembled; 356 PetscScalar *val; 357 InsertMode addv = mat->insertmode; 358 #if defined(PETSC_HAVE_SUPERLUDIST) || defined(PETSC_HAVE_SPOOLES) || defined(PETSC_HAVE_MUMPS) 359 PetscTruth flag; 360 #endif 361 362 PetscFunctionBegin; 363 if (!aij->donotstash) { 364 while (1) { 365 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 366 if (!flg) break; 367 368 for (i=0; i<n;) { 369 /* Now identify the consecutive vals belonging to the same row */ 370 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 371 if (j < n) ncols = j-i; 372 else ncols = n-i; 373 /* Now assemble all these values with a single function call */ 374 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 375 i = j; 376 } 377 } 378 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 379 } 380 381 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 382 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 383 384 /* determine if any processor has disassembled, if so we must 385 also disassemble ourselfs, in order that we may reassemble. */ 386 /* 387 if nonzero structure of submatrix B cannot change then we know that 388 no processor disassembled thus we can skip this stuff 389 */ 390 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 391 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 392 if (mat->was_assembled && !other_disassembled) { 393 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 394 } 395 } 396 397 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 398 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 399 } 400 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 401 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 402 403 if (aij->rowvalues) { 404 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 405 aij->rowvalues = 0; 406 } 407 408 /* used by MatAXPY() */ 409 a->xtoy = 0; b->xtoy = 0; 410 a->XtoY = 0; b->XtoY = 0; 411 412 #if defined(PETSC_HAVE_SUPERLUDIST) 413 ierr = PetscOptionsHasName(mat->prefix,"-mat_aij_superlu_dist",&flag);CHKERRQ(ierr); 414 if (flag) { ierr = MatUseSuperLU_DIST_MPIAIJ(mat);CHKERRQ(ierr); } 415 #endif 416 417 #if defined(PETSC_HAVE_SPOOLES) 418 ierr = PetscOptionsHasName(mat->prefix,"-mat_aij_spooles",&flag);CHKERRQ(ierr); 419 if (flag) { ierr = MatUseSpooles_MPIAIJ(mat);CHKERRQ(ierr); } 420 #endif 421 422 #if defined(PETSC_HAVE_MUMPS) 423 ierr = PetscOptionsHasName(mat->prefix,"-mat_aij_mumps",&flag);CHKERRQ(ierr); 424 if (flag) { ierr = MatUseMUMPS_MPIAIJ(mat);CHKERRQ(ierr); } 425 #endif 426 PetscFunctionReturn(0); 427 } 428 429 #undef __FUNCT__ 430 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 431 int MatZeroEntries_MPIAIJ(Mat A) 432 { 433 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 434 int ierr; 435 436 PetscFunctionBegin; 437 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 438 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 439 PetscFunctionReturn(0); 440 } 441 442 #undef __FUNCT__ 443 #define __FUNCT__ "MatZeroRows_MPIAIJ" 444 int MatZeroRows_MPIAIJ(Mat A,IS is,PetscScalar *diag) 445 { 446 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 447 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 448 int *nprocs,j,idx,nsends,row; 449 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 450 int *rvalues,tag = A->tag,count,base,slen,n,*source; 451 int *lens,imdex,*lrows,*values,rstart=l->rstart; 452 MPI_Comm comm = A->comm; 453 MPI_Request *send_waits,*recv_waits; 454 MPI_Status recv_status,*send_status; 455 IS istmp; 456 PetscTruth found; 457 458 PetscFunctionBegin; 459 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 460 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 461 462 /* first count number of contributors to each processor */ 463 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 464 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 465 ierr = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/ 466 for (i=0; i<N; i++) { 467 idx = rows[i]; 468 found = PETSC_FALSE; 469 for (j=0; j<size; j++) { 470 if (idx >= owners[j] && idx < owners[j+1]) { 471 nprocs[2*j]++; nprocs[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break; 472 } 473 } 474 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 475 } 476 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 477 478 /* inform other processors of number of messages and max length*/ 479 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 480 481 /* post receives: */ 482 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 483 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 484 for (i=0; i<nrecvs; i++) { 485 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 486 } 487 488 /* do sends: 489 1) starts[i] gives the starting index in svalues for stuff going to 490 the ith processor 491 */ 492 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 493 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 494 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 495 starts[0] = 0; 496 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 497 for (i=0; i<N; i++) { 498 svalues[starts[owner[i]]++] = rows[i]; 499 } 500 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 501 502 starts[0] = 0; 503 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 504 count = 0; 505 for (i=0; i<size; i++) { 506 if (nprocs[2*i+1]) { 507 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 508 } 509 } 510 ierr = PetscFree(starts);CHKERRQ(ierr); 511 512 base = owners[rank]; 513 514 /* wait on receives */ 515 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 516 source = lens + nrecvs; 517 count = nrecvs; slen = 0; 518 while (count) { 519 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 520 /* unpack receives into our local space */ 521 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 522 source[imdex] = recv_status.MPI_SOURCE; 523 lens[imdex] = n; 524 slen += n; 525 count--; 526 } 527 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 528 529 /* move the data into the send scatter */ 530 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 531 count = 0; 532 for (i=0; i<nrecvs; i++) { 533 values = rvalues + i*nmax; 534 for (j=0; j<lens[i]; j++) { 535 lrows[count++] = values[j] - base; 536 } 537 } 538 ierr = PetscFree(rvalues);CHKERRQ(ierr); 539 ierr = PetscFree(lens);CHKERRQ(ierr); 540 ierr = PetscFree(owner);CHKERRQ(ierr); 541 ierr = PetscFree(nprocs);CHKERRQ(ierr); 542 543 /* actually zap the local rows */ 544 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 545 PetscLogObjectParent(A,istmp); 546 547 /* 548 Zero the required rows. If the "diagonal block" of the matrix 549 is square and the user wishes to set the diagonal we use seperate 550 code so that MatSetValues() is not called for each diagonal allocating 551 new memory, thus calling lots of mallocs and slowing things down. 552 553 Contributed by: Mathew Knepley 554 */ 555 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 556 ierr = MatZeroRows(l->B,istmp,0);CHKERRQ(ierr); 557 if (diag && (l->A->M == l->A->N)) { 558 ierr = MatZeroRows(l->A,istmp,diag);CHKERRQ(ierr); 559 } else if (diag) { 560 ierr = MatZeroRows(l->A,istmp,0);CHKERRQ(ierr); 561 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 562 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 563 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 564 } 565 for (i = 0; i < slen; i++) { 566 row = lrows[i] + rstart; 567 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 568 } 569 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 570 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 571 } else { 572 ierr = MatZeroRows(l->A,istmp,0);CHKERRQ(ierr); 573 } 574 ierr = ISDestroy(istmp);CHKERRQ(ierr); 575 ierr = PetscFree(lrows);CHKERRQ(ierr); 576 577 /* wait on sends */ 578 if (nsends) { 579 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 580 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 581 ierr = PetscFree(send_status);CHKERRQ(ierr); 582 } 583 ierr = PetscFree(send_waits);CHKERRQ(ierr); 584 ierr = PetscFree(svalues);CHKERRQ(ierr); 585 586 PetscFunctionReturn(0); 587 } 588 589 #undef __FUNCT__ 590 #define __FUNCT__ "MatMult_MPIAIJ" 591 int MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 592 { 593 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 594 int ierr,nt; 595 596 PetscFunctionBegin; 597 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 598 if (nt != A->n) { 599 SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%d) and xx (%d)",A->n,nt); 600 } 601 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 602 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 603 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 604 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 605 PetscFunctionReturn(0); 606 } 607 608 #undef __FUNCT__ 609 #define __FUNCT__ "MatMultAdd_MPIAIJ" 610 int MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 611 { 612 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 613 int ierr; 614 615 PetscFunctionBegin; 616 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 617 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 618 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 619 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 620 PetscFunctionReturn(0); 621 } 622 623 #undef __FUNCT__ 624 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 625 int MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 626 { 627 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 628 int ierr; 629 630 PetscFunctionBegin; 631 /* do nondiagonal part */ 632 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 633 /* send it on its way */ 634 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 635 /* do local part */ 636 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 637 /* receive remote parts: note this assumes the values are not actually */ 638 /* inserted in yy until the next line, which is true for my implementation*/ 639 /* but is not perhaps always true. */ 640 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 641 PetscFunctionReturn(0); 642 } 643 644 EXTERN_C_BEGIN 645 #undef __FUNCT__ 646 #define __FUNCT__ "MatIsSymmetric_MPIAIJ" 647 int MatIsSymmetric_MPIAIJ(Mat Amat,Mat Bmat,PetscTruth *f) 648 { 649 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 650 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 651 MatType type; 652 IS Me,Notme; 653 int M,N,first,last,*notme,i, ierr; 654 655 PetscFunctionBegin; 656 657 /* Compatible types */ 658 ierr = MatGetType(Bmat,&type); CHKERRQ(ierr); 659 ierr = PetscStrcmp(type,MATMPIAIJ,f); CHKERRQ(ierr); 660 if (!*f) SETERRQ(1,"Second matrix needs to be MPIAIJ too"); 661 662 /* Easy test: symmetric diagonal block */ 663 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 664 ierr = MatIsSymmetric(Adia,Bdia,f); CHKERRQ(ierr); 665 if (!*f) PetscFunctionReturn(0); 666 667 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 668 ierr = MatGetSize(Amat,&M,&N); CHKERRQ(ierr); 669 ierr = MatGetOwnershipRange(Amat,&first,&last); CHKERRQ(ierr); 670 ierr = PetscMalloc((N-last+first)*sizeof(int),¬me); CHKERRQ(ierr); 671 for (i=0; i<first; i++) notme[i] = i; 672 for (i=last; i<M; i++) notme[i-last+first] = i; 673 ierr = ISCreateGeneral 674 (MPI_COMM_SELF,N-last+first,notme,&Notme); CHKERRQ(ierr); 675 ierr = ISCreateStride 676 (MPI_COMM_SELF,last-first,first,1,&Me); CHKERRQ(ierr); 677 ierr = MatGetSubMatrices 678 (Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs); CHKERRQ(ierr); 679 Aoff = Aoffs[0]; 680 ierr = MatGetSubMatrices 681 (Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs); CHKERRQ(ierr); 682 Boff = Boffs[0]; 683 ierr = MatIsSymmetric(Aoff,Boff,f); CHKERRQ(ierr); 684 ierr = MatDestroyMatrices(1,&Aoffs); CHKERRQ(ierr); 685 ierr = MatDestroyMatrices(1,&Boffs); CHKERRQ(ierr); 686 ierr = ISDestroy(Me); CHKERRQ(ierr); 687 ierr = ISDestroy(Notme); CHKERRQ(ierr); 688 689 PetscFunctionReturn(0); 690 } 691 EXTERN_C_END 692 693 #undef __FUNCT__ 694 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 695 int MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 696 { 697 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 698 int ierr; 699 700 PetscFunctionBegin; 701 /* do nondiagonal part */ 702 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 703 /* send it on its way */ 704 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 705 /* do local part */ 706 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 707 /* receive remote parts: note this assumes the values are not actually */ 708 /* inserted in yy until the next line, which is true for my implementation*/ 709 /* but is not perhaps always true. */ 710 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 711 PetscFunctionReturn(0); 712 } 713 714 /* 715 This only works correctly for square matrices where the subblock A->A is the 716 diagonal block 717 */ 718 #undef __FUNCT__ 719 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 720 int MatGetDiagonal_MPIAIJ(Mat A,Vec v) 721 { 722 int ierr; 723 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 724 725 PetscFunctionBegin; 726 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 727 if (a->rstart != a->cstart || a->rend != a->cend) { 728 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 729 } 730 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 731 PetscFunctionReturn(0); 732 } 733 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatScale_MPIAIJ" 736 int MatScale_MPIAIJ(PetscScalar *aa,Mat A) 737 { 738 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 739 int ierr; 740 741 PetscFunctionBegin; 742 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 743 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 744 PetscFunctionReturn(0); 745 } 746 747 #undef __FUNCT__ 748 #define __FUNCT__ "MatDestroy_MPIAIJ" 749 int MatDestroy_MPIAIJ(Mat mat) 750 { 751 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 752 int ierr; 753 754 PetscFunctionBegin; 755 #if defined(PETSC_USE_LOG) 756 PetscLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",mat->M,mat->N); 757 #endif 758 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 759 ierr = PetscFree(aij->rowners);CHKERRQ(ierr); 760 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 761 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 762 #if defined (PETSC_USE_CTABLE) 763 if (aij->colmap) {ierr = PetscTableDelete(aij->colmap);CHKERRQ(ierr);} 764 #else 765 if (aij->colmap) {ierr = PetscFree(aij->colmap);CHKERRQ(ierr);} 766 #endif 767 if (aij->garray) {ierr = PetscFree(aij->garray);CHKERRQ(ierr);} 768 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 769 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 770 if (aij->rowvalues) {ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr);} 771 ierr = PetscFree(aij);CHKERRQ(ierr); 772 PetscFunctionReturn(0); 773 } 774 775 extern int MatMPIAIJFactorInfo_SuperLu(Mat,PetscViewer); 776 extern int MatFactorInfo_Spooles(Mat,PetscViewer); 777 extern int MatFactorInfo_MUMPS(Mat,PetscViewer); 778 779 #undef __FUNCT__ 780 #define __FUNCT__ "MatView_MPIAIJ_Binary" 781 int MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 782 { 783 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 784 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 785 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 786 int nz,fd,ierr,header[4],rank,size,*row_lengths,*range,rlen,i,tag = ((PetscObject)viewer)->tag; 787 int nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = aij->cstart,rnz; 788 PetscScalar *column_values; 789 790 PetscFunctionBegin; 791 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 792 ierr = MPI_Comm_size(mat->comm,&size);CHKERRQ(ierr); 793 nz = A->nz + B->nz; 794 if (rank == 0) { 795 header[0] = MAT_FILE_COOKIE; 796 header[1] = mat->M; 797 header[2] = mat->N; 798 ierr = MPI_Reduce(&nz,&header[3],1,MPI_INT,MPI_SUM,0,mat->comm);CHKERRQ(ierr); 799 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 800 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,1);CHKERRQ(ierr); 801 /* get largest number of rows any processor has */ 802 rlen = mat->m; 803 ierr = PetscMapGetGlobalRange(mat->rmap,&range);CHKERRQ(ierr); 804 for (i=1; i<size; i++) { 805 rlen = PetscMax(rlen,range[i+1] - range[i]); 806 } 807 } else { 808 ierr = MPI_Reduce(&nz,0,1,MPI_INT,MPI_SUM,0,mat->comm);CHKERRQ(ierr); 809 rlen = mat->m; 810 } 811 812 /* load up the local row counts */ 813 ierr = PetscMalloc((rlen+1)*sizeof(int),&row_lengths);CHKERRQ(ierr); 814 for (i=0; i<mat->m; i++) { 815 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 816 } 817 818 /* store the row lengths to the file */ 819 if (rank == 0) { 820 MPI_Status status; 821 ierr = PetscBinaryWrite(fd,row_lengths,mat->m,PETSC_INT,1);CHKERRQ(ierr); 822 for (i=1; i<size; i++) { 823 rlen = range[i+1] - range[i]; 824 ierr = MPI_Recv(row_lengths,rlen,MPI_INT,i,tag,mat->comm,&status);CHKERRQ(ierr); 825 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,1);CHKERRQ(ierr); 826 } 827 } else { 828 ierr = MPI_Send(row_lengths,mat->m,MPI_INT,0,tag,mat->comm);CHKERRQ(ierr); 829 } 830 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 831 832 /* load up the local column indices */ 833 nzmax = nz; /* )th processor needs space a largest processor needs */ 834 ierr = MPI_Reduce(&nz,&nzmax,1,MPI_INT,MPI_MAX,0,mat->comm);CHKERRQ(ierr); 835 ierr = PetscMalloc((nzmax+1)*sizeof(int),&column_indices);CHKERRQ(ierr); 836 cnt = 0; 837 for (i=0; i<mat->m; i++) { 838 for (j=B->i[i]; j<B->i[i+1]; j++) { 839 if ( (col = garray[B->j[j]]) > cstart) break; 840 column_indices[cnt++] = col; 841 } 842 for (k=A->i[i]; k<A->i[i+1]; k++) { 843 column_indices[cnt++] = A->j[k] + cstart; 844 } 845 for (; j<B->i[i+1]; j++) { 846 column_indices[cnt++] = garray[B->j[j]]; 847 } 848 } 849 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %d nz = %d",cnt,A->nz+B->nz); 850 851 /* store the column indices to the file */ 852 if (rank == 0) { 853 MPI_Status status; 854 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,1);CHKERRQ(ierr); 855 for (i=1; i<size; i++) { 856 ierr = MPI_Recv(&rnz,1,MPI_INT,i,tag,mat->comm,&status);CHKERRQ(ierr); 857 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %d nzmax = %d",nz,nzmax); 858 ierr = MPI_Recv(column_indices,rnz,MPI_INT,i,tag,mat->comm,&status);CHKERRQ(ierr); 859 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,1);CHKERRQ(ierr); 860 } 861 } else { 862 ierr = MPI_Send(&nz,1,MPI_INT,0,tag,mat->comm);CHKERRQ(ierr); 863 ierr = MPI_Send(column_indices,nz,MPI_INT,0,tag,mat->comm);CHKERRQ(ierr); 864 } 865 ierr = PetscFree(column_indices);CHKERRQ(ierr); 866 867 /* load up the local column values */ 868 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 869 cnt = 0; 870 for (i=0; i<mat->m; i++) { 871 for (j=B->i[i]; j<B->i[i+1]; j++) { 872 if ( garray[B->j[j]] > cstart) break; 873 column_values[cnt++] = B->a[j]; 874 } 875 for (k=A->i[i]; k<A->i[i+1]; k++) { 876 column_values[cnt++] = A->a[k]; 877 } 878 for (; j<B->i[i+1]; j++) { 879 column_values[cnt++] = B->a[j]; 880 } 881 } 882 if (cnt != A->nz + B->nz) SETERRQ2(1,"Internal PETSc error: cnt = %d nz = %d",cnt,A->nz+B->nz); 883 884 /* store the column values to the file */ 885 if (rank == 0) { 886 MPI_Status status; 887 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,1);CHKERRQ(ierr); 888 for (i=1; i<size; i++) { 889 ierr = MPI_Recv(&rnz,1,MPI_INT,i,tag,mat->comm,&status);CHKERRQ(ierr); 890 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %d nzmax = %d",nz,nzmax); 891 ierr = MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,mat->comm,&status);CHKERRQ(ierr); 892 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,1);CHKERRQ(ierr); 893 } 894 } else { 895 ierr = MPI_Send(&nz,1,MPI_INT,0,tag,mat->comm);CHKERRQ(ierr); 896 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,mat->comm);CHKERRQ(ierr); 897 } 898 ierr = PetscFree(column_values);CHKERRQ(ierr); 899 PetscFunctionReturn(0); 900 } 901 902 #undef __FUNCT__ 903 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 904 int MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 905 { 906 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 907 int ierr,rank = aij->rank,size = aij->size; 908 PetscTruth isdraw,isascii,flg,isbinary; 909 PetscViewer sviewer; 910 PetscViewerFormat format; 911 912 PetscFunctionBegin; 913 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 914 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 915 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 916 if (isascii) { 917 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 918 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 919 MatInfo info; 920 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 921 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 922 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_aij_no_inode",&flg);CHKERRQ(ierr); 923 if (flg) { 924 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d mem %d, not using I-node routines\n", 925 rank,mat->m,(int)info.nz_used,(int)info.nz_allocated,(int)info.memory);CHKERRQ(ierr); 926 } else { 927 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d mem %d, using I-node routines\n", 928 rank,mat->m,(int)info.nz_used,(int)info.nz_allocated,(int)info.memory);CHKERRQ(ierr); 929 } 930 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 931 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used);CHKERRQ(ierr); 932 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 933 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used);CHKERRQ(ierr); 934 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 935 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 936 PetscFunctionReturn(0); 937 } else if (format == PETSC_VIEWER_ASCII_INFO) { 938 PetscFunctionReturn(0); 939 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 940 #if defined(PETSC_HAVE_SUPERLUDIST) && !defined(PETSC_USE_SINGLE) 941 ierr = MatMPIAIJFactorInfo_SuperLu(mat,viewer);CHKERRQ(ierr); 942 #endif 943 #if defined(PETSC_HAVE_SPOOLES) && !defined(PETSC_USE_SINGLE) 944 ierr = MatFactorInfo_Spooles(mat,viewer);CHKERRQ(ierr); 945 #endif 946 #if defined(PETSC_HAVE_MUMPS) && !defined(PETSC_USE_SINGLE) 947 ierr = MatFactorInfo_MUMPS(mat,viewer);CHKERRQ(ierr); 948 #endif 949 PetscFunctionReturn(0); 950 } 951 } else if (isbinary) { 952 if (size == 1) { 953 ierr = PetscObjectSetName((PetscObject)aij->A,mat->name);CHKERRQ(ierr); 954 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 955 } else { 956 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 957 } 958 PetscFunctionReturn(0); 959 } else if (isdraw) { 960 PetscDraw draw; 961 PetscTruth isnull; 962 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 963 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 964 } 965 966 if (size == 1) { 967 ierr = PetscObjectSetName((PetscObject)aij->A,mat->name);CHKERRQ(ierr); 968 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 969 } else { 970 /* assemble the entire matrix onto first processor. */ 971 Mat A; 972 Mat_SeqAIJ *Aloc; 973 int M = mat->M,N = mat->N,m,*ai,*aj,row,*cols,i,*ct; 974 PetscScalar *a; 975 976 if (!rank) { 977 ierr = MatCreateMPIAIJ(mat->comm,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 978 } else { 979 ierr = MatCreateMPIAIJ(mat->comm,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 980 } 981 PetscLogObjectParent(mat,A); 982 983 /* copy over the A part */ 984 Aloc = (Mat_SeqAIJ*)aij->A->data; 985 m = aij->A->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 986 row = aij->rstart; 987 for (i=0; i<ai[m]; i++) {aj[i] += aij->cstart ;} 988 for (i=0; i<m; i++) { 989 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 990 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 991 } 992 aj = Aloc->j; 993 for (i=0; i<ai[m]; i++) {aj[i] -= aij->cstart;} 994 995 /* copy over the B part */ 996 Aloc = (Mat_SeqAIJ*)aij->B->data; 997 m = aij->B->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 998 row = aij->rstart; 999 ierr = PetscMalloc((ai[m]+1)*sizeof(int),&cols);CHKERRQ(ierr); 1000 ct = cols; 1001 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 1002 for (i=0; i<m; i++) { 1003 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1004 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1005 } 1006 ierr = PetscFree(ct);CHKERRQ(ierr); 1007 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1008 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1009 /* 1010 Everyone has to call to draw the matrix since the graphics waits are 1011 synchronized across all processors that share the PetscDraw object 1012 */ 1013 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1014 if (!rank) { 1015 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,mat->name);CHKERRQ(ierr); 1016 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1017 } 1018 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1019 ierr = MatDestroy(A);CHKERRQ(ierr); 1020 } 1021 PetscFunctionReturn(0); 1022 } 1023 1024 #undef __FUNCT__ 1025 #define __FUNCT__ "MatView_MPIAIJ" 1026 int MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1027 { 1028 int ierr; 1029 PetscTruth isascii,isdraw,issocket,isbinary; 1030 1031 PetscFunctionBegin; 1032 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 1033 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1034 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1035 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1036 if (isascii || isdraw || isbinary || issocket) { 1037 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1038 } else { 1039 SETERRQ1(1,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1040 } 1041 PetscFunctionReturn(0); 1042 } 1043 1044 1045 1046 #undef __FUNCT__ 1047 #define __FUNCT__ "MatRelax_MPIAIJ" 1048 int MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,int lits,Vec xx) 1049 { 1050 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1051 int ierr; 1052 Vec bb1; 1053 PetscScalar mone=-1.0; 1054 1055 PetscFunctionBegin; 1056 if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %d and local its %d both positive",its,lits); 1057 1058 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1059 1060 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1061 if (flag & SOR_ZERO_INITIAL_GUESS) { 1062 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 1063 its--; 1064 } 1065 1066 while (its--) { 1067 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1068 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1069 1070 /* update rhs: bb1 = bb - B*x */ 1071 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 1072 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1073 1074 /* local sweep */ 1075 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx); 1076 CHKERRQ(ierr); 1077 } 1078 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1079 if (flag & SOR_ZERO_INITIAL_GUESS) { 1080 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1081 its--; 1082 } 1083 while (its--) { 1084 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1085 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1086 1087 /* update rhs: bb1 = bb - B*x */ 1088 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 1089 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1090 1091 /* local sweep */ 1092 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx); 1093 CHKERRQ(ierr); 1094 } 1095 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1096 if (flag & SOR_ZERO_INITIAL_GUESS) { 1097 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1098 its--; 1099 } 1100 while (its--) { 1101 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1102 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 1103 1104 /* update rhs: bb1 = bb - B*x */ 1105 ierr = VecScale(&mone,mat->lvec);CHKERRQ(ierr); 1106 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1107 1108 /* local sweep */ 1109 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx); 1110 CHKERRQ(ierr); 1111 } 1112 } else { 1113 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1114 } 1115 1116 ierr = VecDestroy(bb1);CHKERRQ(ierr); 1117 PetscFunctionReturn(0); 1118 } 1119 1120 #undef __FUNCT__ 1121 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1122 int MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1123 { 1124 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1125 Mat A = mat->A,B = mat->B; 1126 int ierr; 1127 PetscReal isend[5],irecv[5]; 1128 1129 PetscFunctionBegin; 1130 info->block_size = 1.0; 1131 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1132 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1133 isend[3] = info->memory; isend[4] = info->mallocs; 1134 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1135 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1136 isend[3] += info->memory; isend[4] += info->mallocs; 1137 if (flag == MAT_LOCAL) { 1138 info->nz_used = isend[0]; 1139 info->nz_allocated = isend[1]; 1140 info->nz_unneeded = isend[2]; 1141 info->memory = isend[3]; 1142 info->mallocs = isend[4]; 1143 } else if (flag == MAT_GLOBAL_MAX) { 1144 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);CHKERRQ(ierr); 1145 info->nz_used = irecv[0]; 1146 info->nz_allocated = irecv[1]; 1147 info->nz_unneeded = irecv[2]; 1148 info->memory = irecv[3]; 1149 info->mallocs = irecv[4]; 1150 } else if (flag == MAT_GLOBAL_SUM) { 1151 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);CHKERRQ(ierr); 1152 info->nz_used = irecv[0]; 1153 info->nz_allocated = irecv[1]; 1154 info->nz_unneeded = irecv[2]; 1155 info->memory = irecv[3]; 1156 info->mallocs = irecv[4]; 1157 } 1158 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1159 info->fill_ratio_needed = 0; 1160 info->factor_mallocs = 0; 1161 info->rows_global = (double)matin->M; 1162 info->columns_global = (double)matin->N; 1163 info->rows_local = (double)matin->m; 1164 info->columns_local = (double)matin->N; 1165 1166 PetscFunctionReturn(0); 1167 } 1168 1169 #undef __FUNCT__ 1170 #define __FUNCT__ "MatSetOption_MPIAIJ" 1171 int MatSetOption_MPIAIJ(Mat A,MatOption op) 1172 { 1173 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1174 int ierr; 1175 1176 PetscFunctionBegin; 1177 switch (op) { 1178 case MAT_NO_NEW_NONZERO_LOCATIONS: 1179 case MAT_YES_NEW_NONZERO_LOCATIONS: 1180 case MAT_COLUMNS_UNSORTED: 1181 case MAT_COLUMNS_SORTED: 1182 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1183 case MAT_KEEP_ZEROED_ROWS: 1184 case MAT_NEW_NONZERO_LOCATION_ERR: 1185 case MAT_USE_INODES: 1186 case MAT_DO_NOT_USE_INODES: 1187 case MAT_IGNORE_ZERO_ENTRIES: 1188 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1189 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1190 break; 1191 case MAT_ROW_ORIENTED: 1192 a->roworiented = PETSC_TRUE; 1193 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1194 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1195 break; 1196 case MAT_ROWS_SORTED: 1197 case MAT_ROWS_UNSORTED: 1198 case MAT_YES_NEW_DIAGONALS: 1199 PetscLogInfo(A,"MatSetOption_MPIAIJ:Option ignored\n"); 1200 break; 1201 case MAT_COLUMN_ORIENTED: 1202 a->roworiented = PETSC_FALSE; 1203 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1204 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1205 break; 1206 case MAT_IGNORE_OFF_PROC_ENTRIES: 1207 a->donotstash = PETSC_TRUE; 1208 break; 1209 case MAT_NO_NEW_DIAGONALS: 1210 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1211 default: 1212 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1213 } 1214 PetscFunctionReturn(0); 1215 } 1216 1217 #undef __FUNCT__ 1218 #define __FUNCT__ "MatGetRow_MPIAIJ" 1219 int MatGetRow_MPIAIJ(Mat matin,int row,int *nz,int **idx,PetscScalar **v) 1220 { 1221 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1222 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1223 int i,ierr,*cworkA,*cworkB,**pcA,**pcB,cstart = mat->cstart; 1224 int nztot,nzA,nzB,lrow,rstart = mat->rstart,rend = mat->rend; 1225 int *cmap,*idx_p; 1226 1227 PetscFunctionBegin; 1228 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1229 mat->getrowactive = PETSC_TRUE; 1230 1231 if (!mat->rowvalues && (idx || v)) { 1232 /* 1233 allocate enough space to hold information from the longest row. 1234 */ 1235 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1236 int max = 1,tmp; 1237 for (i=0; i<matin->m; i++) { 1238 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1239 if (max < tmp) { max = tmp; } 1240 } 1241 ierr = PetscMalloc(max*(sizeof(int)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1242 mat->rowindices = (int*)(mat->rowvalues + max); 1243 } 1244 1245 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1246 lrow = row - rstart; 1247 1248 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1249 if (!v) {pvA = 0; pvB = 0;} 1250 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1251 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1252 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1253 nztot = nzA + nzB; 1254 1255 cmap = mat->garray; 1256 if (v || idx) { 1257 if (nztot) { 1258 /* Sort by increasing column numbers, assuming A and B already sorted */ 1259 int imark = -1; 1260 if (v) { 1261 *v = v_p = mat->rowvalues; 1262 for (i=0; i<nzB; i++) { 1263 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1264 else break; 1265 } 1266 imark = i; 1267 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1268 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1269 } 1270 if (idx) { 1271 *idx = idx_p = mat->rowindices; 1272 if (imark > -1) { 1273 for (i=0; i<imark; i++) { 1274 idx_p[i] = cmap[cworkB[i]]; 1275 } 1276 } else { 1277 for (i=0; i<nzB; i++) { 1278 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1279 else break; 1280 } 1281 imark = i; 1282 } 1283 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1284 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1285 } 1286 } else { 1287 if (idx) *idx = 0; 1288 if (v) *v = 0; 1289 } 1290 } 1291 *nz = nztot; 1292 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1293 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1294 PetscFunctionReturn(0); 1295 } 1296 1297 #undef __FUNCT__ 1298 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1299 int MatRestoreRow_MPIAIJ(Mat mat,int row,int *nz,int **idx,PetscScalar **v) 1300 { 1301 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1302 1303 PetscFunctionBegin; 1304 if (aij->getrowactive == PETSC_FALSE) { 1305 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1306 } 1307 aij->getrowactive = PETSC_FALSE; 1308 PetscFunctionReturn(0); 1309 } 1310 1311 #undef __FUNCT__ 1312 #define __FUNCT__ "MatNorm_MPIAIJ" 1313 int MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1314 { 1315 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1316 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1317 int ierr,i,j,cstart = aij->cstart; 1318 PetscReal sum = 0.0; 1319 PetscScalar *v; 1320 1321 PetscFunctionBegin; 1322 if (aij->size == 1) { 1323 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1324 } else { 1325 if (type == NORM_FROBENIUS) { 1326 v = amat->a; 1327 for (i=0; i<amat->nz; i++) { 1328 #if defined(PETSC_USE_COMPLEX) 1329 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1330 #else 1331 sum += (*v)*(*v); v++; 1332 #endif 1333 } 1334 v = bmat->a; 1335 for (i=0; i<bmat->nz; i++) { 1336 #if defined(PETSC_USE_COMPLEX) 1337 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1338 #else 1339 sum += (*v)*(*v); v++; 1340 #endif 1341 } 1342 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 1343 *norm = sqrt(*norm); 1344 } else if (type == NORM_1) { /* max column norm */ 1345 PetscReal *tmp,*tmp2; 1346 int *jj,*garray = aij->garray; 1347 ierr = PetscMalloc((mat->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1348 ierr = PetscMalloc((mat->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1349 ierr = PetscMemzero(tmp,mat->N*sizeof(PetscReal));CHKERRQ(ierr); 1350 *norm = 0.0; 1351 v = amat->a; jj = amat->j; 1352 for (j=0; j<amat->nz; j++) { 1353 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1354 } 1355 v = bmat->a; jj = bmat->j; 1356 for (j=0; j<bmat->nz; j++) { 1357 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1358 } 1359 ierr = MPI_Allreduce(tmp,tmp2,mat->N,MPIU_REAL,MPI_SUM,mat->comm);CHKERRQ(ierr); 1360 for (j=0; j<mat->N; j++) { 1361 if (tmp2[j] > *norm) *norm = tmp2[j]; 1362 } 1363 ierr = PetscFree(tmp);CHKERRQ(ierr); 1364 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1365 } else if (type == NORM_INFINITY) { /* max row norm */ 1366 PetscReal ntemp = 0.0; 1367 for (j=0; j<aij->A->m; j++) { 1368 v = amat->a + amat->i[j]; 1369 sum = 0.0; 1370 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1371 sum += PetscAbsScalar(*v); v++; 1372 } 1373 v = bmat->a + bmat->i[j]; 1374 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1375 sum += PetscAbsScalar(*v); v++; 1376 } 1377 if (sum > ntemp) ntemp = sum; 1378 } 1379 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,mat->comm);CHKERRQ(ierr); 1380 } else { 1381 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1382 } 1383 } 1384 PetscFunctionReturn(0); 1385 } 1386 1387 #undef __FUNCT__ 1388 #define __FUNCT__ "MatTranspose_MPIAIJ" 1389 int MatTranspose_MPIAIJ(Mat A,Mat *matout) 1390 { 1391 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1392 Mat_SeqAIJ *Aloc = (Mat_SeqAIJ*)a->A->data; 1393 int ierr; 1394 int M = A->M,N = A->N,m,*ai,*aj,row,*cols,i,*ct; 1395 Mat B; 1396 PetscScalar *array; 1397 1398 PetscFunctionBegin; 1399 if (!matout && M != N) { 1400 SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1401 } 1402 1403 ierr = MatCreateMPIAIJ(A->comm,A->n,A->m,N,M,0,PETSC_NULL,0,PETSC_NULL,&B);CHKERRQ(ierr); 1404 1405 /* copy over the A part */ 1406 Aloc = (Mat_SeqAIJ*)a->A->data; 1407 m = a->A->m; ai = Aloc->i; aj = Aloc->j; array = Aloc->a; 1408 row = a->rstart; 1409 for (i=0; i<ai[m]; i++) {aj[i] += a->cstart ;} 1410 for (i=0; i<m; i++) { 1411 ierr = MatSetValues(B,ai[i+1]-ai[i],aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1412 row++; array += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1413 } 1414 aj = Aloc->j; 1415 for (i=0; i<ai[m]; i++) {aj[i] -= a->cstart ;} 1416 1417 /* copy over the B part */ 1418 Aloc = (Mat_SeqAIJ*)a->B->data; 1419 m = a->B->m; ai = Aloc->i; aj = Aloc->j; array = Aloc->a; 1420 row = a->rstart; 1421 ierr = PetscMalloc((1+ai[m])*sizeof(int),&cols);CHKERRQ(ierr); 1422 ct = cols; 1423 for (i=0; i<ai[m]; i++) {cols[i] = a->garray[aj[i]];} 1424 for (i=0; i<m; i++) { 1425 ierr = MatSetValues(B,ai[i+1]-ai[i],cols,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1426 row++; array += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1427 } 1428 ierr = PetscFree(ct);CHKERRQ(ierr); 1429 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1430 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1431 if (matout) { 1432 *matout = B; 1433 } else { 1434 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1435 } 1436 PetscFunctionReturn(0); 1437 } 1438 1439 #undef __FUNCT__ 1440 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1441 int MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1442 { 1443 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1444 Mat a = aij->A,b = aij->B; 1445 int ierr,s1,s2,s3; 1446 1447 PetscFunctionBegin; 1448 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1449 if (rr) { 1450 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1451 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1452 /* Overlap communication with computation. */ 1453 ierr = VecScatterBegin(rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD,aij->Mvctx);CHKERRQ(ierr); 1454 } 1455 if (ll) { 1456 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1457 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1458 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1459 } 1460 /* scale the diagonal block */ 1461 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1462 1463 if (rr) { 1464 /* Do a scatter end and then right scale the off-diagonal block */ 1465 ierr = VecScatterEnd(rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD,aij->Mvctx);CHKERRQ(ierr); 1466 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1467 } 1468 1469 PetscFunctionReturn(0); 1470 } 1471 1472 1473 #undef __FUNCT__ 1474 #define __FUNCT__ "MatPrintHelp_MPIAIJ" 1475 int MatPrintHelp_MPIAIJ(Mat A) 1476 { 1477 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1478 int ierr; 1479 1480 PetscFunctionBegin; 1481 if (!a->rank) { 1482 ierr = MatPrintHelp_SeqAIJ(a->A);CHKERRQ(ierr); 1483 } 1484 PetscFunctionReturn(0); 1485 } 1486 1487 #undef __FUNCT__ 1488 #define __FUNCT__ "MatGetBlockSize_MPIAIJ" 1489 int MatGetBlockSize_MPIAIJ(Mat A,int *bs) 1490 { 1491 PetscFunctionBegin; 1492 *bs = 1; 1493 PetscFunctionReturn(0); 1494 } 1495 #undef __FUNCT__ 1496 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1497 int MatSetUnfactored_MPIAIJ(Mat A) 1498 { 1499 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1500 int ierr; 1501 1502 PetscFunctionBegin; 1503 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1504 PetscFunctionReturn(0); 1505 } 1506 1507 #undef __FUNCT__ 1508 #define __FUNCT__ "MatEqual_MPIAIJ" 1509 int MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1510 { 1511 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1512 Mat a,b,c,d; 1513 PetscTruth flg; 1514 int ierr; 1515 1516 PetscFunctionBegin; 1517 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg);CHKERRQ(ierr); 1518 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1519 a = matA->A; b = matA->B; 1520 c = matB->A; d = matB->B; 1521 1522 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1523 if (flg == PETSC_TRUE) { 1524 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1525 } 1526 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1527 PetscFunctionReturn(0); 1528 } 1529 1530 #undef __FUNCT__ 1531 #define __FUNCT__ "MatCopy_MPIAIJ" 1532 int MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1533 { 1534 int ierr; 1535 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1536 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1537 PetscTruth flg; 1538 1539 PetscFunctionBegin; 1540 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg);CHKERRQ(ierr); 1541 if (str != SAME_NONZERO_PATTERN || !flg) { 1542 /* because of the column compression in the off-processor part of the matrix a->B, 1543 the number of columns in a->B and b->B may be different, hence we cannot call 1544 the MatCopy() directly on the two parts. If need be, we can provide a more 1545 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1546 then copying the submatrices */ 1547 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1548 } else { 1549 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1550 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1551 } 1552 PetscFunctionReturn(0); 1553 } 1554 1555 #undef __FUNCT__ 1556 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1557 int MatSetUpPreallocation_MPIAIJ(Mat A) 1558 { 1559 int ierr; 1560 1561 PetscFunctionBegin; 1562 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1563 PetscFunctionReturn(0); 1564 } 1565 1566 EXTERN int MatDuplicate_MPIAIJ(Mat,MatDuplicateOption,Mat *); 1567 EXTERN int MatIncreaseOverlap_MPIAIJ(Mat,int,IS *,int); 1568 EXTERN int MatFDColoringCreate_MPIAIJ(Mat,ISColoring,MatFDColoring); 1569 EXTERN int MatGetSubMatrices_MPIAIJ (Mat,int,IS *,IS *,MatReuse,Mat **); 1570 EXTERN int MatGetSubMatrix_MPIAIJ (Mat,IS,IS,int,MatReuse,Mat *); 1571 #if !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SINGLE) 1572 EXTERN int MatLUFactorSymbolic_MPIAIJ_TFS(Mat,IS,IS,MatFactorInfo*,Mat*); 1573 #endif 1574 1575 #include "petscblaslapack.h" 1576 extern int MatAXPY_SeqAIJ(PetscScalar *,Mat,Mat,MatStructure); 1577 #undef __FUNCT__ 1578 #define __FUNCT__ "MatAXPY_MPIAIJ" 1579 int MatAXPY_MPIAIJ(PetscScalar *a,Mat X,Mat Y,MatStructure str) 1580 { 1581 int ierr,one=1,i; 1582 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1583 Mat_SeqAIJ *x,*y; 1584 1585 PetscFunctionBegin; 1586 if (str == SAME_NONZERO_PATTERN) { 1587 x = (Mat_SeqAIJ *)xx->A->data; 1588 y = (Mat_SeqAIJ *)yy->A->data; 1589 BLaxpy_(&x->nz,a,x->a,&one,y->a,&one); 1590 x = (Mat_SeqAIJ *)xx->B->data; 1591 y = (Mat_SeqAIJ *)yy->B->data; 1592 BLaxpy_(&x->nz,a,x->a,&one,y->a,&one); 1593 } else if (str == SUBSET_NONZERO_PATTERN) { 1594 ierr = MatAXPY_SeqAIJ(a,xx->A,yy->A,str);CHKERRQ(ierr); 1595 1596 x = (Mat_SeqAIJ *)xx->B->data; 1597 y = (Mat_SeqAIJ *)yy->B->data; 1598 if (y->xtoy && y->XtoY != xx->B) { 1599 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1600 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1601 } 1602 if (!y->xtoy) { /* get xtoy */ 1603 ierr = MatAXPYGetxtoy_Private(xx->B->m,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1604 y->XtoY = xx->B; 1605 } 1606 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += (*a)*(x->a[i]); 1607 } else { 1608 ierr = MatAXPY_Basic(a,X,Y,str);CHKERRQ(ierr); 1609 } 1610 PetscFunctionReturn(0); 1611 } 1612 1613 /* -------------------------------------------------------------------*/ 1614 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 1615 MatGetRow_MPIAIJ, 1616 MatRestoreRow_MPIAIJ, 1617 MatMult_MPIAIJ, 1618 MatMultAdd_MPIAIJ, 1619 MatMultTranspose_MPIAIJ, 1620 MatMultTransposeAdd_MPIAIJ, 1621 0, 1622 0, 1623 0, 1624 0, 1625 0, 1626 0, 1627 MatRelax_MPIAIJ, 1628 MatTranspose_MPIAIJ, 1629 MatGetInfo_MPIAIJ, 1630 MatEqual_MPIAIJ, 1631 MatGetDiagonal_MPIAIJ, 1632 MatDiagonalScale_MPIAIJ, 1633 MatNorm_MPIAIJ, 1634 MatAssemblyBegin_MPIAIJ, 1635 MatAssemblyEnd_MPIAIJ, 1636 0, 1637 MatSetOption_MPIAIJ, 1638 MatZeroEntries_MPIAIJ, 1639 MatZeroRows_MPIAIJ, 1640 #if !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SINGLE) 1641 MatLUFactorSymbolic_MPIAIJ_TFS, 1642 #else 1643 0, 1644 #endif 1645 0, 1646 0, 1647 0, 1648 MatSetUpPreallocation_MPIAIJ, 1649 0, 1650 0, 1651 0, 1652 0, 1653 MatDuplicate_MPIAIJ, 1654 0, 1655 0, 1656 0, 1657 0, 1658 MatAXPY_MPIAIJ, 1659 MatGetSubMatrices_MPIAIJ, 1660 MatIncreaseOverlap_MPIAIJ, 1661 MatGetValues_MPIAIJ, 1662 MatCopy_MPIAIJ, 1663 MatPrintHelp_MPIAIJ, 1664 MatScale_MPIAIJ, 1665 0, 1666 0, 1667 0, 1668 MatGetBlockSize_MPIAIJ, 1669 0, 1670 0, 1671 0, 1672 0, 1673 MatFDColoringCreate_MPIAIJ, 1674 0, 1675 MatSetUnfactored_MPIAIJ, 1676 0, 1677 0, 1678 MatGetSubMatrix_MPIAIJ, 1679 MatDestroy_MPIAIJ, 1680 MatView_MPIAIJ, 1681 MatGetPetscMaps_Petsc, 1682 0, 1683 0, 1684 0, 1685 0, 1686 0, 1687 0, 1688 0, 1689 0, 1690 MatSetColoring_MPIAIJ, 1691 MatSetValuesAdic_MPIAIJ, 1692 MatSetValuesAdifor_MPIAIJ 1693 }; 1694 1695 /* ----------------------------------------------------------------------------------------*/ 1696 1697 EXTERN_C_BEGIN 1698 #undef __FUNCT__ 1699 #define __FUNCT__ "MatStoreValues_MPIAIJ" 1700 int MatStoreValues_MPIAIJ(Mat mat) 1701 { 1702 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1703 int ierr; 1704 1705 PetscFunctionBegin; 1706 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 1707 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 1708 PetscFunctionReturn(0); 1709 } 1710 EXTERN_C_END 1711 1712 EXTERN_C_BEGIN 1713 #undef __FUNCT__ 1714 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 1715 int MatRetrieveValues_MPIAIJ(Mat mat) 1716 { 1717 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1718 int ierr; 1719 1720 PetscFunctionBegin; 1721 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 1722 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 1723 PetscFunctionReturn(0); 1724 } 1725 EXTERN_C_END 1726 1727 #include "petscpc.h" 1728 EXTERN_C_BEGIN 1729 EXTERN int MatGetDiagonalBlock_MPIAIJ(Mat,PetscTruth *,MatReuse,Mat *); 1730 EXTERN_C_END 1731 1732 EXTERN_C_BEGIN 1733 #undef __FUNCT__ 1734 #define __FUNCT__ "MatCreate_MPIAIJ" 1735 int MatCreate_MPIAIJ(Mat B) 1736 { 1737 Mat_MPIAIJ *b; 1738 int ierr,i,size; 1739 1740 PetscFunctionBegin; 1741 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 1742 1743 ierr = PetscNew(Mat_MPIAIJ,&b);CHKERRQ(ierr); 1744 B->data = (void*)b; 1745 ierr = PetscMemzero(b,sizeof(Mat_MPIAIJ));CHKERRQ(ierr); 1746 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1747 B->factor = 0; 1748 B->assembled = PETSC_FALSE; 1749 B->mapping = 0; 1750 1751 B->insertmode = NOT_SET_VALUES; 1752 b->size = size; 1753 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1754 1755 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1756 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1757 1758 /* the information in the maps duplicates the information computed below, eventually 1759 we should remove the duplicate information that is not contained in the maps */ 1760 ierr = PetscMapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1761 ierr = PetscMapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 1762 1763 /* build local table of row and column ownerships */ 1764 ierr = PetscMalloc(2*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1765 PetscLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIAIJ)); 1766 b->cowners = b->rowners + b->size + 2; 1767 ierr = MPI_Allgather(&B->m,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1768 b->rowners[0] = 0; 1769 for (i=2; i<=b->size; i++) { 1770 b->rowners[i] += b->rowners[i-1]; 1771 } 1772 b->rstart = b->rowners[b->rank]; 1773 b->rend = b->rowners[b->rank+1]; 1774 ierr = MPI_Allgather(&B->n,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1775 b->cowners[0] = 0; 1776 for (i=2; i<=b->size; i++) { 1777 b->cowners[i] += b->cowners[i-1]; 1778 } 1779 b->cstart = b->cowners[b->rank]; 1780 b->cend = b->cowners[b->rank+1]; 1781 1782 /* build cache for off array entries formed */ 1783 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1784 b->donotstash = PETSC_FALSE; 1785 b->colmap = 0; 1786 b->garray = 0; 1787 b->roworiented = PETSC_TRUE; 1788 1789 /* stuff used for matrix vector multiply */ 1790 b->lvec = PETSC_NULL; 1791 b->Mvctx = PETSC_NULL; 1792 1793 /* stuff for MatGetRow() */ 1794 b->rowindices = 0; 1795 b->rowvalues = 0; 1796 b->getrowactive = PETSC_FALSE; 1797 1798 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1799 "MatStoreValues_MPIAIJ", 1800 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 1801 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1802 "MatRetrieveValues_MPIAIJ", 1803 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 1804 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1805 "MatGetDiagonalBlock_MPIAIJ", 1806 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 1807 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsSymmetric_C", 1808 "MatIsSymmetric_MPIAIJ", 1809 MatIsSymmetric_MPIAIJ); CHKERRQ(ierr); 1810 PetscFunctionReturn(0); 1811 } 1812 EXTERN_C_END 1813 1814 #undef __FUNCT__ 1815 #define __FUNCT__ "MatDuplicate_MPIAIJ" 1816 int MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1817 { 1818 Mat mat; 1819 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 1820 int ierr; 1821 1822 PetscFunctionBegin; 1823 *newmat = 0; 1824 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1825 ierr = MatSetType(mat,MATMPIAIJ);CHKERRQ(ierr); 1826 a = (Mat_MPIAIJ*)mat->data; 1827 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1828 mat->factor = matin->factor; 1829 mat->assembled = PETSC_TRUE; 1830 mat->insertmode = NOT_SET_VALUES; 1831 mat->preallocated = PETSC_TRUE; 1832 1833 a->rstart = oldmat->rstart; 1834 a->rend = oldmat->rend; 1835 a->cstart = oldmat->cstart; 1836 a->cend = oldmat->cend; 1837 a->size = oldmat->size; 1838 a->rank = oldmat->rank; 1839 a->donotstash = oldmat->donotstash; 1840 a->roworiented = oldmat->roworiented; 1841 a->rowindices = 0; 1842 a->rowvalues = 0; 1843 a->getrowactive = PETSC_FALSE; 1844 1845 ierr = PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1846 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1847 if (oldmat->colmap) { 1848 #if defined (PETSC_USE_CTABLE) 1849 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1850 #else 1851 ierr = PetscMalloc((mat->N)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1852 PetscLogObjectMemory(mat,(mat->N)*sizeof(int)); 1853 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->N)*sizeof(int));CHKERRQ(ierr); 1854 #endif 1855 } else a->colmap = 0; 1856 if (oldmat->garray) { 1857 int len; 1858 len = oldmat->B->n; 1859 ierr = PetscMalloc((len+1)*sizeof(int),&a->garray);CHKERRQ(ierr); 1860 PetscLogObjectMemory(mat,len*sizeof(int)); 1861 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); } 1862 } else a->garray = 0; 1863 1864 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1865 PetscLogObjectParent(mat,a->lvec); 1866 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1867 PetscLogObjectParent(mat,a->Mvctx); 1868 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1869 PetscLogObjectParent(mat,a->A); 1870 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1871 PetscLogObjectParent(mat,a->B); 1872 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 1873 *newmat = mat; 1874 PetscFunctionReturn(0); 1875 } 1876 1877 #include "petscsys.h" 1878 1879 EXTERN_C_BEGIN 1880 #undef __FUNCT__ 1881 #define __FUNCT__ "MatLoad_MPIAIJ" 1882 int MatLoad_MPIAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1883 { 1884 Mat A; 1885 PetscScalar *vals,*svals; 1886 MPI_Comm comm = ((PetscObject)viewer)->comm; 1887 MPI_Status status; 1888 int i,nz,ierr,j,rstart,rend,fd; 1889 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,maxnz,*cols; 1890 int *ourlens,*sndcounts = 0,*procsnz = 0,*offlens,jj,*mycols,*smycols; 1891 int tag = ((PetscObject)viewer)->tag,cend,cstart,n; 1892 #if defined(PETSC_HAVE_SPOOLES) || defined(PETSC_HAVE_SUPERLUDIST) || defined(PETSC_HAVE_MUMPS) 1893 PetscTruth flag; 1894 #endif 1895 1896 PetscFunctionBegin; 1897 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1898 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1899 if (!rank) { 1900 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1901 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1902 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1903 if (header[3] < 0) { 1904 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix in special format on disk, cannot load as MPIAIJ"); 1905 } 1906 } 1907 1908 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 1909 M = header[1]; N = header[2]; 1910 /* determine ownership of all rows */ 1911 m = M/size + ((M % size) > rank); 1912 ierr = PetscMalloc((size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 1913 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1914 rowners[0] = 0; 1915 for (i=2; i<=size; i++) { 1916 rowners[i] += rowners[i-1]; 1917 } 1918 rstart = rowners[rank]; 1919 rend = rowners[rank+1]; 1920 1921 /* distribute row lengths to all processors */ 1922 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&ourlens);CHKERRQ(ierr); 1923 offlens = ourlens + (rend-rstart); 1924 if (!rank) { 1925 ierr = PetscMalloc(M*sizeof(int),&rowlengths);CHKERRQ(ierr); 1926 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1927 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 1928 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1929 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1930 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1931 } else { 1932 ierr = MPI_Scatterv(0,0,0,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1933 } 1934 1935 if (!rank) { 1936 /* calculate the number of nonzeros on each processor */ 1937 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 1938 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 1939 for (i=0; i<size; i++) { 1940 for (j=rowners[i]; j< rowners[i+1]; j++) { 1941 procsnz[i] += rowlengths[j]; 1942 } 1943 } 1944 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1945 1946 /* determine max buffer needed and allocate it */ 1947 maxnz = 0; 1948 for (i=0; i<size; i++) { 1949 maxnz = PetscMax(maxnz,procsnz[i]); 1950 } 1951 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 1952 1953 /* read in my part of the matrix column indices */ 1954 nz = procsnz[0]; 1955 ierr = PetscMalloc(nz*sizeof(int),&mycols);CHKERRQ(ierr); 1956 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1957 1958 /* read in every one elses and ship off */ 1959 for (i=1; i<size; i++) { 1960 nz = procsnz[i]; 1961 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1962 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 1963 } 1964 ierr = PetscFree(cols);CHKERRQ(ierr); 1965 } else { 1966 /* determine buffer space needed for message */ 1967 nz = 0; 1968 for (i=0; i<m; i++) { 1969 nz += ourlens[i]; 1970 } 1971 ierr = PetscMalloc((nz+1)*sizeof(int),&mycols);CHKERRQ(ierr); 1972 1973 /* receive message of column indices*/ 1974 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 1975 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 1976 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1977 } 1978 1979 /* determine column ownership if matrix is not square */ 1980 if (N != M) { 1981 n = N/size + ((N % size) > rank); 1982 ierr = MPI_Scan(&n,&cend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1983 cstart = cend - n; 1984 } else { 1985 cstart = rstart; 1986 cend = rend; 1987 n = cend - cstart; 1988 } 1989 1990 /* loop over local rows, determining number of off diagonal entries */ 1991 ierr = PetscMemzero(offlens,m*sizeof(int));CHKERRQ(ierr); 1992 jj = 0; 1993 for (i=0; i<m; i++) { 1994 for (j=0; j<ourlens[i]; j++) { 1995 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 1996 jj++; 1997 } 1998 } 1999 2000 /* create our matrix */ 2001 for (i=0; i<m; i++) { 2002 ourlens[i] -= offlens[i]; 2003 } 2004 ierr = MatCreateMPIAIJ(comm,m,n,M,N,0,ourlens,0,offlens,newmat);CHKERRQ(ierr); 2005 A = *newmat; 2006 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2007 for (i=0; i<m; i++) { 2008 ourlens[i] += offlens[i]; 2009 } 2010 2011 if (!rank) { 2012 ierr = PetscMalloc(maxnz*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2013 2014 /* read in my part of the matrix numerical values */ 2015 nz = procsnz[0]; 2016 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2017 2018 /* insert into matrix */ 2019 jj = rstart; 2020 smycols = mycols; 2021 svals = vals; 2022 for (i=0; i<m; i++) { 2023 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2024 smycols += ourlens[i]; 2025 svals += ourlens[i]; 2026 jj++; 2027 } 2028 2029 /* read in other processors and ship out */ 2030 for (i=1; i<size; i++) { 2031 nz = procsnz[i]; 2032 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2033 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2034 } 2035 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2036 } else { 2037 /* receive numeric values */ 2038 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2039 2040 /* receive message of values*/ 2041 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2042 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2043 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2044 2045 /* insert into matrix */ 2046 jj = rstart; 2047 smycols = mycols; 2048 svals = vals; 2049 for (i=0; i<m; i++) { 2050 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2051 smycols += ourlens[i]; 2052 svals += ourlens[i]; 2053 jj++; 2054 } 2055 } 2056 ierr = PetscFree(ourlens);CHKERRQ(ierr); 2057 ierr = PetscFree(vals);CHKERRQ(ierr); 2058 ierr = PetscFree(mycols);CHKERRQ(ierr); 2059 ierr = PetscFree(rowners);CHKERRQ(ierr); 2060 2061 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2062 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2063 #if defined(PETSC_HAVE_SPOOLES) 2064 ierr = PetscOptionsHasName(A->prefix,"-mat_aij_spooles",&flag);CHKERRQ(ierr); 2065 if (flag) { 2066 if (size == 1) { 2067 ierr = MatUseSpooles_SeqAIJ(A);CHKERRQ(ierr); 2068 } else { 2069 ierr = MatUseSpooles_MPIAIJ(A);CHKERRQ(ierr); 2070 } 2071 } 2072 #endif 2073 #if defined(PETSC_HAVE_SUPERLUDIST) 2074 ierr = PetscOptionsHasName(A->prefix,"-mat_aij_superlu_dist",&flag);CHKERRQ(ierr); 2075 if (flag) { ierr = MatUseSuperLU_DIST_MPIAIJ(A);CHKERRQ(ierr); } 2076 #endif 2077 #if defined(PETSC_HAVE_MUMPS) 2078 ierr = PetscOptionsHasName(A->prefix,"-mat_aij_mumps",&flag);CHKERRQ(ierr); 2079 if (flag) { ierr = MatUseMUMPS_MPIAIJ(A);CHKERRQ(ierr); } 2080 #endif 2081 PetscFunctionReturn(0); 2082 } 2083 EXTERN_C_END 2084 2085 #undef __FUNCT__ 2086 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2087 /* 2088 Not great since it makes two copies of the submatrix, first an SeqAIJ 2089 in local and then by concatenating the local matrices the end result. 2090 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2091 */ 2092 int MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,int csize,MatReuse call,Mat *newmat) 2093 { 2094 int ierr,i,m,n,rstart,row,rend,nz,*cwork,size,rank,j; 2095 int *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 2096 Mat *local,M,Mreuse; 2097 PetscScalar *vwork,*aa; 2098 MPI_Comm comm = mat->comm; 2099 Mat_SeqAIJ *aij; 2100 2101 2102 PetscFunctionBegin; 2103 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2104 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2105 2106 if (call == MAT_REUSE_MATRIX) { 2107 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 2108 if (!Mreuse) SETERRQ(1,"Submatrix passed in was not used before, cannot reuse"); 2109 local = &Mreuse; 2110 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 2111 } else { 2112 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 2113 Mreuse = *local; 2114 ierr = PetscFree(local);CHKERRQ(ierr); 2115 } 2116 2117 /* 2118 m - number of local rows 2119 n - number of columns (same on all processors) 2120 rstart - first row in new global matrix generated 2121 */ 2122 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 2123 if (call == MAT_INITIAL_MATRIX) { 2124 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2125 ii = aij->i; 2126 jj = aij->j; 2127 2128 /* 2129 Determine the number of non-zeros in the diagonal and off-diagonal 2130 portions of the matrix in order to do correct preallocation 2131 */ 2132 2133 /* first get start and end of "diagonal" columns */ 2134 if (csize == PETSC_DECIDE) { 2135 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 2136 if (mglobal == n) { /* square matrix */ 2137 nlocal = m; 2138 } else { 2139 nlocal = n/size + ((n % size) > rank); 2140 } 2141 } else { 2142 nlocal = csize; 2143 } 2144 ierr = MPI_Scan(&nlocal,&rend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 2145 rstart = rend - nlocal; 2146 if (rank == size - 1 && rend != n) { 2147 SETERRQ2(1,"Local column sizes %d do not add up to total number of columns %d",rend,n); 2148 } 2149 2150 /* next, compute all the lengths */ 2151 ierr = PetscMalloc((2*m+1)*sizeof(int),&dlens);CHKERRQ(ierr); 2152 olens = dlens + m; 2153 for (i=0; i<m; i++) { 2154 jend = ii[i+1] - ii[i]; 2155 olen = 0; 2156 dlen = 0; 2157 for (j=0; j<jend; j++) { 2158 if (*jj < rstart || *jj >= rend) olen++; 2159 else dlen++; 2160 jj++; 2161 } 2162 olens[i] = olen; 2163 dlens[i] = dlen; 2164 } 2165 ierr = MatCreateMPIAIJ(comm,m,nlocal,PETSC_DECIDE,n,0,dlens,0,olens,&M);CHKERRQ(ierr); 2166 ierr = PetscFree(dlens);CHKERRQ(ierr); 2167 } else { 2168 int ml,nl; 2169 2170 M = *newmat; 2171 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 2172 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 2173 ierr = MatZeroEntries(M);CHKERRQ(ierr); 2174 /* 2175 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 2176 rather than the slower MatSetValues(). 2177 */ 2178 M->was_assembled = PETSC_TRUE; 2179 M->assembled = PETSC_FALSE; 2180 } 2181 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 2182 aij = (Mat_SeqAIJ*)(Mreuse)->data; 2183 ii = aij->i; 2184 jj = aij->j; 2185 aa = aij->a; 2186 for (i=0; i<m; i++) { 2187 row = rstart + i; 2188 nz = ii[i+1] - ii[i]; 2189 cwork = jj; jj += nz; 2190 vwork = aa; aa += nz; 2191 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 2192 } 2193 2194 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2195 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2196 *newmat = M; 2197 2198 /* save submatrix used in processor for next request */ 2199 if (call == MAT_INITIAL_MATRIX) { 2200 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 2201 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 2202 } 2203 2204 PetscFunctionReturn(0); 2205 } 2206 2207 #undef __FUNCT__ 2208 #define __FUNCT__ "MatMPIAIJSetPreallocation" 2209 /*@C 2210 MatMPIAIJSetPreallocation - Creates a sparse parallel matrix in AIJ format 2211 (the default parallel PETSc format). For good matrix assembly performance 2212 the user should preallocate the matrix storage by setting the parameters 2213 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2214 performance can be increased by more than a factor of 50. 2215 2216 Collective on MPI_Comm 2217 2218 Input Parameters: 2219 + A - the matrix 2220 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2221 (same value is used for all local rows) 2222 . d_nnz - array containing the number of nonzeros in the various rows of the 2223 DIAGONAL portion of the local submatrix (possibly different for each row) 2224 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2225 The size of this array is equal to the number of local rows, i.e 'm'. 2226 You must leave room for the diagonal entry even if it is zero. 2227 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2228 submatrix (same value is used for all local rows). 2229 - o_nnz - array containing the number of nonzeros in the various rows of the 2230 OFF-DIAGONAL portion of the local submatrix (possibly different for 2231 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2232 structure. The size of this array is equal to the number 2233 of local rows, i.e 'm'. 2234 2235 The AIJ format (also called the Yale sparse matrix format or 2236 compressed row storage), is fully compatible with standard Fortran 77 2237 storage. That is, the stored row and column indices can begin at 2238 either one (as in Fortran) or zero. See the users manual for details. 2239 2240 The user MUST specify either the local or global matrix dimensions 2241 (possibly both). 2242 2243 The parallel matrix is partitioned such that the first m0 rows belong to 2244 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2245 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2246 2247 The DIAGONAL portion of the local submatrix of a processor can be defined 2248 as the submatrix which is obtained by extraction the part corresponding 2249 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2250 first row that belongs to the processor, and r2 is the last row belonging 2251 to the this processor. This is a square mxm matrix. The remaining portion 2252 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2253 2254 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2255 2256 By default, this format uses inodes (identical nodes) when possible. 2257 We search for consecutive rows with the same nonzero structure, thereby 2258 reusing matrix information to achieve increased efficiency. 2259 2260 Options Database Keys: 2261 + -mat_aij_no_inode - Do not use inodes 2262 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2263 - -mat_aij_oneindex - Internally use indexing starting at 1 2264 rather than 0. Note that when calling MatSetValues(), 2265 the user still MUST index entries starting at 0! 2266 2267 Example usage: 2268 2269 Consider the following 8x8 matrix with 34 non-zero values, that is 2270 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2271 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2272 as follows: 2273 2274 .vb 2275 1 2 0 | 0 3 0 | 0 4 2276 Proc0 0 5 6 | 7 0 0 | 8 0 2277 9 0 10 | 11 0 0 | 12 0 2278 ------------------------------------- 2279 13 0 14 | 15 16 17 | 0 0 2280 Proc1 0 18 0 | 19 20 21 | 0 0 2281 0 0 0 | 22 23 0 | 24 0 2282 ------------------------------------- 2283 Proc2 25 26 27 | 0 0 28 | 29 0 2284 30 0 0 | 31 32 33 | 0 34 2285 .ve 2286 2287 This can be represented as a collection of submatrices as: 2288 2289 .vb 2290 A B C 2291 D E F 2292 G H I 2293 .ve 2294 2295 Where the submatrices A,B,C are owned by proc0, D,E,F are 2296 owned by proc1, G,H,I are owned by proc2. 2297 2298 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2299 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2300 The 'M','N' parameters are 8,8, and have the same values on all procs. 2301 2302 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2303 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2304 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2305 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2306 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2307 matrix, ans [DF] as another SeqAIJ matrix. 2308 2309 When d_nz, o_nz parameters are specified, d_nz storage elements are 2310 allocated for every row of the local diagonal submatrix, and o_nz 2311 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2312 One way to choose d_nz and o_nz is to use the max nonzerors per local 2313 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2314 In this case, the values of d_nz,o_nz are: 2315 .vb 2316 proc0 : dnz = 2, o_nz = 2 2317 proc1 : dnz = 3, o_nz = 2 2318 proc2 : dnz = 1, o_nz = 4 2319 .ve 2320 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2321 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2322 for proc3. i.e we are using 12+15+10=37 storage locations to store 2323 34 values. 2324 2325 When d_nnz, o_nnz parameters are specified, the storage is specified 2326 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2327 In the above case the values for d_nnz,o_nnz are: 2328 .vb 2329 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2330 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2331 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2332 .ve 2333 Here the space allocated is sum of all the above values i.e 34, and 2334 hence pre-allocation is perfect. 2335 2336 Level: intermediate 2337 2338 .keywords: matrix, aij, compressed row, sparse, parallel 2339 2340 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2341 @*/ 2342 int MatMPIAIJSetPreallocation(Mat B,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2343 { 2344 Mat_MPIAIJ *b; 2345 int ierr,i; 2346 PetscTruth flg2; 2347 2348 PetscFunctionBegin; 2349 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg2);CHKERRQ(ierr); 2350 if (!flg2) PetscFunctionReturn(0); 2351 B->preallocated = PETSC_TRUE; 2352 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2353 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2354 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2355 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2356 if (d_nnz) { 2357 for (i=0; i<B->m; i++) { 2358 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]); 2359 } 2360 } 2361 if (o_nnz) { 2362 for (i=0; i<B->m; i++) { 2363 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]); 2364 } 2365 } 2366 b = (Mat_MPIAIJ*)B->data; 2367 2368 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2369 PetscLogObjectParent(B,b->A); 2370 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2371 PetscLogObjectParent(B,b->B); 2372 2373 PetscFunctionReturn(0); 2374 } 2375 2376 #undef __FUNCT__ 2377 #define __FUNCT__ "MatCreateMPIAIJ" 2378 /*@C 2379 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 2380 (the default parallel PETSc format). For good matrix assembly performance 2381 the user should preallocate the matrix storage by setting the parameters 2382 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2383 performance can be increased by more than a factor of 50. 2384 2385 Collective on MPI_Comm 2386 2387 Input Parameters: 2388 + comm - MPI communicator 2389 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2390 This value should be the same as the local size used in creating the 2391 y vector for the matrix-vector product y = Ax. 2392 . n - This value should be the same as the local size used in creating the 2393 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2394 calculated if N is given) For square matrices n is almost always m. 2395 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2396 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2397 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2398 (same value is used for all local rows) 2399 . d_nnz - array containing the number of nonzeros in the various rows of the 2400 DIAGONAL portion of the local submatrix (possibly different for each row) 2401 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2402 The size of this array is equal to the number of local rows, i.e 'm'. 2403 You must leave room for the diagonal entry even if it is zero. 2404 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2405 submatrix (same value is used for all local rows). 2406 - o_nnz - array containing the number of nonzeros in the various rows of the 2407 OFF-DIAGONAL portion of the local submatrix (possibly different for 2408 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2409 structure. The size of this array is equal to the number 2410 of local rows, i.e 'm'. 2411 2412 Output Parameter: 2413 . A - the matrix 2414 2415 Notes: 2416 m,n,M,N parameters specify the size of the matrix, and its partitioning across 2417 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 2418 storage requirements for this matrix. 2419 2420 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 2421 processor than it must be used on all processors that share the object for 2422 that argument. 2423 2424 The AIJ format (also called the Yale sparse matrix format or 2425 compressed row storage), is fully compatible with standard Fortran 77 2426 storage. That is, the stored row and column indices can begin at 2427 either one (as in Fortran) or zero. See the users manual for details. 2428 2429 The user MUST specify either the local or global matrix dimensions 2430 (possibly both). 2431 2432 The parallel matrix is partitioned such that the first m0 rows belong to 2433 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2434 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2435 2436 The DIAGONAL portion of the local submatrix of a processor can be defined 2437 as the submatrix which is obtained by extraction the part corresponding 2438 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2439 first row that belongs to the processor, and r2 is the last row belonging 2440 to the this processor. This is a square mxm matrix. The remaining portion 2441 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2442 2443 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2444 2445 By default, this format uses inodes (identical nodes) when possible. 2446 We search for consecutive rows with the same nonzero structure, thereby 2447 reusing matrix information to achieve increased efficiency. 2448 2449 Options Database Keys: 2450 + -mat_aij_no_inode - Do not use inodes 2451 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2452 - -mat_aij_oneindex - Internally use indexing starting at 1 2453 rather than 0. Note that when calling MatSetValues(), 2454 the user still MUST index entries starting at 0! 2455 2456 2457 Example usage: 2458 2459 Consider the following 8x8 matrix with 34 non-zero values, that is 2460 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2461 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2462 as follows: 2463 2464 .vb 2465 1 2 0 | 0 3 0 | 0 4 2466 Proc0 0 5 6 | 7 0 0 | 8 0 2467 9 0 10 | 11 0 0 | 12 0 2468 ------------------------------------- 2469 13 0 14 | 15 16 17 | 0 0 2470 Proc1 0 18 0 | 19 20 21 | 0 0 2471 0 0 0 | 22 23 0 | 24 0 2472 ------------------------------------- 2473 Proc2 25 26 27 | 0 0 28 | 29 0 2474 30 0 0 | 31 32 33 | 0 34 2475 .ve 2476 2477 This can be represented as a collection of submatrices as: 2478 2479 .vb 2480 A B C 2481 D E F 2482 G H I 2483 .ve 2484 2485 Where the submatrices A,B,C are owned by proc0, D,E,F are 2486 owned by proc1, G,H,I are owned by proc2. 2487 2488 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2489 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2490 The 'M','N' parameters are 8,8, and have the same values on all procs. 2491 2492 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2493 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2494 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2495 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2496 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2497 matrix, ans [DF] as another SeqAIJ matrix. 2498 2499 When d_nz, o_nz parameters are specified, d_nz storage elements are 2500 allocated for every row of the local diagonal submatrix, and o_nz 2501 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2502 One way to choose d_nz and o_nz is to use the max nonzerors per local 2503 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2504 In this case, the values of d_nz,o_nz are: 2505 .vb 2506 proc0 : dnz = 2, o_nz = 2 2507 proc1 : dnz = 3, o_nz = 2 2508 proc2 : dnz = 1, o_nz = 4 2509 .ve 2510 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2511 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2512 for proc3. i.e we are using 12+15+10=37 storage locations to store 2513 34 values. 2514 2515 When d_nnz, o_nnz parameters are specified, the storage is specified 2516 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2517 In the above case the values for d_nnz,o_nnz are: 2518 .vb 2519 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2520 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2521 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2522 .ve 2523 Here the space allocated is sum of all the above values i.e 34, and 2524 hence pre-allocation is perfect. 2525 2526 Level: intermediate 2527 2528 .keywords: matrix, aij, compressed row, sparse, parallel 2529 2530 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2531 @*/ 2532 int MatCreateMPIAIJ(MPI_Comm comm,int m,int n,int M,int N,int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 2533 { 2534 int ierr,size; 2535 2536 PetscFunctionBegin; 2537 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2538 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2539 if (size > 1) { 2540 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 2541 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2542 } else { 2543 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2544 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 2545 } 2546 PetscFunctionReturn(0); 2547 } 2548 2549 #undef __FUNCT__ 2550 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 2551 int MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2552 { 2553 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 2554 PetscFunctionBegin; 2555 *Ad = a->A; 2556 *Ao = a->B; 2557 *colmap = a->garray; 2558 PetscFunctionReturn(0); 2559 } 2560 2561 #undef __FUNCT__ 2562 #define __FUNCT__ "MatSetColoring_MPIAIJ" 2563 int MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 2564 { 2565 int ierr,i; 2566 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2567 2568 PetscFunctionBegin; 2569 if (coloring->ctype == IS_COLORING_LOCAL) { 2570 ISColoringValue *allcolors,*colors; 2571 ISColoring ocoloring; 2572 2573 /* set coloring for diagonal portion */ 2574 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 2575 2576 /* set coloring for off-diagonal portion */ 2577 ierr = ISAllGatherColors(A->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 2578 ierr = PetscMalloc((a->B->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 2579 for (i=0; i<a->B->n; i++) { 2580 colors[i] = allcolors[a->garray[i]]; 2581 } 2582 ierr = PetscFree(allcolors);CHKERRQ(ierr); 2583 ierr = ISColoringCreate(MPI_COMM_SELF,a->B->n,colors,&ocoloring);CHKERRQ(ierr); 2584 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 2585 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 2586 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 2587 ISColoringValue *colors; 2588 int *larray; 2589 ISColoring ocoloring; 2590 2591 /* set coloring for diagonal portion */ 2592 ierr = PetscMalloc((a->A->n+1)*sizeof(int),&larray);CHKERRQ(ierr); 2593 for (i=0; i<a->A->n; i++) { 2594 larray[i] = i + a->cstart; 2595 } 2596 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 2597 ierr = PetscMalloc((a->A->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 2598 for (i=0; i<a->A->n; i++) { 2599 colors[i] = coloring->colors[larray[i]]; 2600 } 2601 ierr = PetscFree(larray);CHKERRQ(ierr); 2602 ierr = ISColoringCreate(PETSC_COMM_SELF,a->A->n,colors,&ocoloring);CHKERRQ(ierr); 2603 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 2604 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 2605 2606 /* set coloring for off-diagonal portion */ 2607 ierr = PetscMalloc((a->B->n+1)*sizeof(int),&larray);CHKERRQ(ierr); 2608 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 2609 ierr = PetscMalloc((a->B->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 2610 for (i=0; i<a->B->n; i++) { 2611 colors[i] = coloring->colors[larray[i]]; 2612 } 2613 ierr = PetscFree(larray);CHKERRQ(ierr); 2614 ierr = ISColoringCreate(MPI_COMM_SELF,a->B->n,colors,&ocoloring);CHKERRQ(ierr); 2615 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 2616 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 2617 } else { 2618 SETERRQ1(1,"No support ISColoringType %d",coloring->ctype); 2619 } 2620 2621 PetscFunctionReturn(0); 2622 } 2623 2624 #undef __FUNCT__ 2625 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 2626 int MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 2627 { 2628 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2629 int ierr; 2630 2631 PetscFunctionBegin; 2632 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 2633 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 2634 PetscFunctionReturn(0); 2635 } 2636 2637 #undef __FUNCT__ 2638 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 2639 int MatSetValuesAdifor_MPIAIJ(Mat A,int nl,void *advalues) 2640 { 2641 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2642 int ierr; 2643 2644 PetscFunctionBegin; 2645 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 2646 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 2647 PetscFunctionReturn(0); 2648 } 2649 2650 #undef __FUNCT__ 2651 #define __FUNCT__ "MatMerge" 2652 /*@C 2653 MatMerge - Creates a single large PETSc matrix by concatinating sequential 2654 matrices from each processor 2655 2656 Collective on MPI_Comm 2657 2658 Input Parameters: 2659 + comm - the communicators the parallel matrix will live on 2660 - inmat - the input sequential matrices 2661 2662 Output Parameter: 2663 . outmat - the parallel matrix generated 2664 2665 Level: advanced 2666 2667 Notes: The number of columns of the matrix in EACH of the seperate files 2668 MUST be the same. 2669 2670 @*/ 2671 int MatMerge(MPI_Comm comm,Mat inmat, Mat *outmat) 2672 { 2673 int ierr,m,n,i,rstart,*indx,nnz,I,*dnz,*onz; 2674 PetscScalar *values; 2675 PetscMap columnmap,rowmap; 2676 2677 PetscFunctionBegin; 2678 2679 ierr = MatGetSize(inmat,&m,&n);CHKERRQ(ierr); 2680 2681 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 2682 ierr = PetscMapCreate(comm,&columnmap);CHKERRQ(ierr); 2683 ierr = PetscMapSetSize(columnmap,n);CHKERRQ(ierr); 2684 ierr = PetscMapSetType(columnmap,MAP_MPI);CHKERRQ(ierr); 2685 ierr = PetscMapGetLocalSize(columnmap,&n);CHKERRQ(ierr); 2686 ierr = PetscMapDestroy(columnmap);CHKERRQ(ierr); 2687 2688 ierr = PetscMapCreate(comm,&rowmap);CHKERRQ(ierr); 2689 ierr = PetscMapSetLocalSize(rowmap,m);CHKERRQ(ierr); 2690 ierr = PetscMapSetType(rowmap,MAP_MPI);CHKERRQ(ierr); 2691 ierr = PetscMapGetLocalRange(rowmap,&rstart,0);CHKERRQ(ierr); 2692 ierr = PetscMapDestroy(rowmap);CHKERRQ(ierr); 2693 2694 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 2695 for (i=0;i<m;i++) { 2696 ierr = MatGetRow(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2697 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 2698 ierr = MatRestoreRow(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2699 } 2700 ierr = MatCreateMPIAIJ(comm,m,n,PETSC_DETERMINE,PETSC_DETERMINE,0,dnz,0,onz,outmat);CHKERRQ(ierr); 2701 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 2702 2703 for (i=0;i<m;i++) { 2704 ierr = MatGetRow(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2705 I = i + rstart; 2706 ierr = MatSetValues(*outmat,1,&I,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 2707 ierr = MatRestoreRow(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 2708 } 2709 ierr = MatDestroy(inmat);CHKERRQ(ierr); 2710 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2711 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2712 2713 PetscFunctionReturn(0); 2714 } 2715 2716 #undef __FUNCT__ 2717 #define __FUNCT__ "MatFileSplit" 2718 int MatFileSplit(Mat A,char *outfile) 2719 { 2720 int ierr,rank,len,m,N,i,rstart,*indx,nnz; 2721 PetscViewer out; 2722 char *name; 2723 Mat B; 2724 PetscScalar *values; 2725 2726 PetscFunctionBegin; 2727 2728 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 2729 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 2730 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,m,N,0,0,&B);CHKERRQ(ierr); 2731 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 2732 for (i=0;i<m;i++) { 2733 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 2734 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 2735 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 2736 } 2737 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2738 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2739 2740 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 2741 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 2742 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 2743 sprintf(name,"%s.%d",outfile,rank); 2744 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,PETSC_BINARY_CREATE,&out);CHKERRQ(ierr); 2745 ierr = PetscFree(name); 2746 ierr = MatView(B,out);CHKERRQ(ierr); 2747 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 2748 ierr = MatDestroy(B);CHKERRQ(ierr); 2749 PetscFunctionReturn(0); 2750 } 2751