1 /*$Id: mpiaij.c,v 1.333 2001/03/23 23:21:56 balay Exp bsmith $*/ 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*,Scalar*,InsertMode); 10 EXTERN int MatGetRow_SeqAIJ(Mat,int,int*,int**,Scalar**); 11 EXTERN int MatRestoreRow_SeqAIJ(Mat,int,int*,int**,Scalar**); 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 Scalar *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(Scalar))+(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(Scalar));CHKERRQ(ierr); \ 88 ierr = PetscMemcpy(new_a+ai[row]+shift+nrow+CHUNKSIZE,aa+ai[row]+shift+nrow, \ 89 len*sizeof(Scalar));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(Scalar))); \ 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 Scalar *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(Scalar))+(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(Scalar));CHKERRQ(ierr); \ 162 ierr = PetscMemcpy(new_a+bi[row]+shift+nrow+CHUNKSIZE,ba+bi[row]+shift+nrow, \ 163 len*sizeof(Scalar));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(Scalar))); \ 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,Scalar *v,InsertMode addv) 195 { 196 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 197 Scalar 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 Scalar *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 Scalar *ba = b->a; 212 213 int *rp,ii,nrow,_i,rmax,N,col1,low,high,t; 214 int nonew = a->nonew,shift = a->indexshift; 215 Scalar *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,Scalar *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 int i,j,rstart,ncols,n,ierr,flg; 354 int *row,*col,other_disassembled; 355 Scalar *val; 356 InsertMode addv = mat->insertmode; 357 358 PetscFunctionBegin; 359 if (!aij->donotstash) { 360 while (1) { 361 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 362 if (!flg) break; 363 364 for (i=0; i<n;) { 365 /* Now identify the consecutive vals belonging to the same row */ 366 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 367 if (j < n) ncols = j-i; 368 else ncols = n-i; 369 /* Now assemble all these values with a single function call */ 370 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 371 i = j; 372 } 373 } 374 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 375 } 376 377 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 378 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 379 380 /* determine if any processor has disassembled, if so we must 381 also disassemble ourselfs, in order that we may reassemble. */ 382 /* 383 if nonzero structure of submatrix B cannot change then we know that 384 no processor disassembled thus we can skip this stuff 385 */ 386 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 387 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 388 if (mat->was_assembled && !other_disassembled) { 389 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 390 } 391 } 392 393 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 394 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 395 } 396 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 397 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 398 399 if (aij->rowvalues) { 400 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 401 aij->rowvalues = 0; 402 } 403 PetscFunctionReturn(0); 404 } 405 406 #undef __FUNCT__ 407 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 408 int MatZeroEntries_MPIAIJ(Mat A) 409 { 410 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 411 int ierr; 412 413 PetscFunctionBegin; 414 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 415 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 416 PetscFunctionReturn(0); 417 } 418 419 #undef __FUNCT__ 420 #define __FUNCT__ "MatZeroRows_MPIAIJ" 421 int MatZeroRows_MPIAIJ(Mat A,IS is,Scalar *diag) 422 { 423 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 424 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 425 int *procs,*nprocs,j,idx,nsends,*work,row; 426 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 427 int *rvalues,tag = A->tag,count,base,slen,n,*source; 428 int *lens,imdex,*lrows,*values,rstart=l->rstart; 429 MPI_Comm comm = A->comm; 430 MPI_Request *send_waits,*recv_waits; 431 MPI_Status recv_status,*send_status; 432 IS istmp; 433 PetscTruth found; 434 435 PetscFunctionBegin; 436 ierr = ISGetLocalSize(is,&N);CHKERRQ(ierr); 437 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 438 439 /* first count number of contributors to each processor */ 440 ierr = PetscMalloc(2*size*sizeof(int),&nprocs);CHKERRQ(ierr); 441 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 442 procs = nprocs + size; 443 ierr = PetscMalloc((N+1)*sizeof(int),&owner);CHKERRQ(ierr); /* see note*/ 444 for (i=0; i<N; i++) { 445 idx = rows[i]; 446 found = PETSC_FALSE; 447 for (j=0; j<size; j++) { 448 if (idx >= owners[j] && idx < owners[j+1]) { 449 nprocs[j]++; procs[j] = 1; owner[i] = j; found = PETSC_TRUE; break; 450 } 451 } 452 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 453 } 454 nsends = 0; for (i=0; i<size; i++) { nsends += procs[i];} 455 456 /* inform other processors of number of messages and max length*/ 457 ierr = PetscMalloc(2*size*sizeof(int),&work);CHKERRQ(ierr); 458 ierr = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr); 459 nrecvs = work[size+rank]; 460 nmax = work[rank]; 461 ierr = PetscFree(work);CHKERRQ(ierr); 462 463 /* post receives: */ 464 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),&rvalues);CHKERRQ(ierr); 465 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 466 for (i=0; i<nrecvs; i++) { 467 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 468 } 469 470 /* do sends: 471 1) starts[i] gives the starting index in svalues for stuff going to 472 the ith processor 473 */ 474 ierr = PetscMalloc((N+1)*sizeof(int),&svalues);CHKERRQ(ierr); 475 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 476 ierr = PetscMalloc((size+1)*sizeof(int),&starts);CHKERRQ(ierr); 477 starts[0] = 0; 478 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 479 for (i=0; i<N; i++) { 480 svalues[starts[owner[i]]++] = rows[i]; 481 } 482 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 483 484 starts[0] = 0; 485 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 486 count = 0; 487 for (i=0; i<size; i++) { 488 if (procs[i]) { 489 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 490 } 491 } 492 ierr = PetscFree(starts);CHKERRQ(ierr); 493 494 base = owners[rank]; 495 496 /* wait on receives */ 497 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),&lens);CHKERRQ(ierr); 498 source = lens + nrecvs; 499 count = nrecvs; slen = 0; 500 while (count) { 501 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 502 /* unpack receives into our local space */ 503 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 504 source[imdex] = recv_status.MPI_SOURCE; 505 lens[imdex] = n; 506 slen += n; 507 count--; 508 } 509 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 510 511 /* move the data into the send scatter */ 512 ierr = PetscMalloc((slen+1)*sizeof(int),&lrows);CHKERRQ(ierr); 513 count = 0; 514 for (i=0; i<nrecvs; i++) { 515 values = rvalues + i*nmax; 516 for (j=0; j<lens[i]; j++) { 517 lrows[count++] = values[j] - base; 518 } 519 } 520 ierr = PetscFree(rvalues);CHKERRQ(ierr); 521 ierr = PetscFree(lens);CHKERRQ(ierr); 522 ierr = PetscFree(owner);CHKERRQ(ierr); 523 ierr = PetscFree(nprocs);CHKERRQ(ierr); 524 525 /* actually zap the local rows */ 526 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 527 PetscLogObjectParent(A,istmp); 528 529 /* 530 Zero the required rows. If the "diagonal block" of the matrix 531 is square and the user wishes to set the diagonal we use seperate 532 code so that MatSetValues() is not called for each diagonal allocating 533 new memory, thus calling lots of mallocs and slowing things down. 534 535 Contributed by: Mathew Knepley 536 */ 537 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 538 ierr = MatZeroRows(l->B,istmp,0);CHKERRQ(ierr); 539 if (diag && (l->A->M == l->A->N)) { 540 ierr = MatZeroRows(l->A,istmp,diag);CHKERRQ(ierr); 541 } else if (diag) { 542 ierr = MatZeroRows(l->A,istmp,0);CHKERRQ(ierr); 543 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 544 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 545 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 546 } 547 for (i = 0; i < slen; i++) { 548 row = lrows[i] + rstart; 549 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 550 } 551 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 552 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 553 } else { 554 ierr = MatZeroRows(l->A,istmp,0);CHKERRQ(ierr); 555 } 556 ierr = ISDestroy(istmp);CHKERRQ(ierr); 557 ierr = PetscFree(lrows);CHKERRQ(ierr); 558 559 /* wait on sends */ 560 if (nsends) { 561 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 562 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 563 ierr = PetscFree(send_status);CHKERRQ(ierr); 564 } 565 ierr = PetscFree(send_waits);CHKERRQ(ierr); 566 ierr = PetscFree(svalues);CHKERRQ(ierr); 567 568 PetscFunctionReturn(0); 569 } 570 571 #undef __FUNCT__ 572 #define __FUNCT__ "MatMult_MPIAIJ" 573 int MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 574 { 575 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 576 int ierr,nt; 577 578 PetscFunctionBegin; 579 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 580 if (nt != A->n) { 581 SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%d) and xx (%d)",A->n,nt); 582 } 583 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 584 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 585 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 586 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatMultAdd_MPIAIJ" 592 int MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 593 { 594 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 595 int ierr; 596 597 PetscFunctionBegin; 598 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 599 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 600 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 601 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 602 PetscFunctionReturn(0); 603 } 604 605 #undef __FUNCT__ 606 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 607 int MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 608 { 609 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 610 int ierr; 611 612 PetscFunctionBegin; 613 /* do nondiagonal part */ 614 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 615 /* send it on its way */ 616 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 617 /* do local part */ 618 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 619 /* receive remote parts: note this assumes the values are not actually */ 620 /* inserted in yy until the next line, which is true for my implementation*/ 621 /* but is not perhaps always true. */ 622 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 623 PetscFunctionReturn(0); 624 } 625 626 #undef __FUNCT__ 627 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 628 int MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 629 { 630 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 631 int ierr; 632 633 PetscFunctionBegin; 634 /* do nondiagonal part */ 635 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 636 /* send it on its way */ 637 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 638 /* do local part */ 639 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 640 /* receive remote parts: note this assumes the values are not actually */ 641 /* inserted in yy until the next line, which is true for my implementation*/ 642 /* but is not perhaps always true. */ 643 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 644 PetscFunctionReturn(0); 645 } 646 647 /* 648 This only works correctly for square matrices where the subblock A->A is the 649 diagonal block 650 */ 651 #undef __FUNCT__ 652 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 653 int MatGetDiagonal_MPIAIJ(Mat A,Vec v) 654 { 655 int ierr; 656 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 657 658 PetscFunctionBegin; 659 if (A->M != A->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 660 if (a->rstart != a->cstart || a->rend != a->cend) { 661 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 662 } 663 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 664 PetscFunctionReturn(0); 665 } 666 667 #undef __FUNCT__ 668 #define __FUNCT__ "MatScale_MPIAIJ" 669 int MatScale_MPIAIJ(Scalar *aa,Mat A) 670 { 671 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 672 int ierr; 673 674 PetscFunctionBegin; 675 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 676 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 677 PetscFunctionReturn(0); 678 } 679 680 #undef __FUNCT__ 681 #define __FUNCT__ "MatDestroy_MPIAIJ" 682 int MatDestroy_MPIAIJ(Mat mat) 683 { 684 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 685 int ierr; 686 687 PetscFunctionBegin; 688 #if defined(PETSC_USE_LOG) 689 PetscLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",mat->M,mat->N); 690 #endif 691 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 692 ierr = PetscFree(aij->rowners);CHKERRQ(ierr); 693 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 694 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 695 #if defined (PETSC_USE_CTABLE) 696 if (aij->colmap) {ierr = PetscTableDelete(aij->colmap);CHKERRQ(ierr);} 697 #else 698 if (aij->colmap) {ierr = PetscFree(aij->colmap);CHKERRQ(ierr);} 699 #endif 700 if (aij->garray) {ierr = PetscFree(aij->garray);CHKERRQ(ierr);} 701 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 702 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 703 if (aij->rowvalues) {ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr);} 704 ierr = PetscFree(aij);CHKERRQ(ierr); 705 PetscFunctionReturn(0); 706 } 707 708 #undef __FUNCT__ 709 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 710 int MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 711 { 712 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 713 Mat_SeqAIJ* C = (Mat_SeqAIJ*)aij->A->data; 714 int ierr,shift = C->indexshift,rank = aij->rank,size = aij->size; 715 PetscTruth isdraw,isascii,flg; 716 PetscViewer sviewer; 717 PetscViewerFormat format; 718 719 PetscFunctionBegin; 720 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 721 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 722 if (isascii) { 723 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 724 if (format == PETSC_VIEWER_ASCII_INFO_LONG) { 725 MatInfo info; 726 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 727 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 728 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_aij_no_inode",&flg);CHKERRQ(ierr); 729 if (flg) { 730 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d mem %d, not using I-node routines\n", 731 rank,mat->m,(int)info.nz_used,(int)info.nz_allocated,(int)info.memory);CHKERRQ(ierr); 732 } else { 733 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d mem %d, using I-node routines\n", 734 rank,mat->m,(int)info.nz_used,(int)info.nz_allocated,(int)info.memory);CHKERRQ(ierr); 735 } 736 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 737 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used);CHKERRQ(ierr); 738 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 739 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used);CHKERRQ(ierr); 740 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 741 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 742 PetscFunctionReturn(0); 743 } else if (format == PETSC_VIEWER_ASCII_INFO) { 744 PetscFunctionReturn(0); 745 } 746 } else if (isdraw) { 747 PetscDraw draw; 748 PetscTruth isnull; 749 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 750 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 751 } 752 753 if (size == 1) { 754 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 755 } else { 756 /* assemble the entire matrix onto first processor. */ 757 Mat A; 758 Mat_SeqAIJ *Aloc; 759 int M = mat->M,N = mat->N,m,*ai,*aj,row,*cols,i,*ct; 760 Scalar *a; 761 762 if (!rank) { 763 ierr = MatCreateMPIAIJ(mat->comm,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 764 } else { 765 ierr = MatCreateMPIAIJ(mat->comm,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 766 } 767 PetscLogObjectParent(mat,A); 768 769 /* copy over the A part */ 770 Aloc = (Mat_SeqAIJ*)aij->A->data; 771 m = aij->A->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 772 row = aij->rstart; 773 for (i=0; i<ai[m]+shift; i++) {aj[i] += aij->cstart + shift;} 774 for (i=0; i<m; i++) { 775 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 776 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 777 } 778 aj = Aloc->j; 779 for (i=0; i<ai[m]+shift; i++) {aj[i] -= aij->cstart + shift;} 780 781 /* copy over the B part */ 782 Aloc = (Mat_SeqAIJ*)aij->B->data; 783 m = aij->B->m; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 784 row = aij->rstart; 785 ierr = PetscMalloc((ai[m]+1)*sizeof(int),&cols);CHKERRQ(ierr); 786 ct = cols; 787 for (i=0; i<ai[m]+shift; i++) {cols[i] = aij->garray[aj[i]+shift];} 788 for (i=0; i<m; i++) { 789 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 790 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 791 } 792 ierr = PetscFree(ct);CHKERRQ(ierr); 793 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 794 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 795 /* 796 Everyone has to call to draw the matrix since the graphics waits are 797 synchronized across all processors that share the PetscDraw object 798 */ 799 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 800 if (!rank) { 801 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 802 } 803 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 804 ierr = MatDestroy(A);CHKERRQ(ierr); 805 } 806 PetscFunctionReturn(0); 807 } 808 809 #undef __FUNCT__ 810 #define __FUNCT__ "MatView_MPIAIJ" 811 int MatView_MPIAIJ(Mat mat,PetscViewer viewer) 812 { 813 int ierr; 814 PetscTruth isascii,isdraw,issocket,isbinary; 815 816 PetscFunctionBegin; 817 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 818 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 819 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 820 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 821 if (isascii || isdraw || isbinary || issocket) { 822 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 823 } else { 824 SETERRQ1(1,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 825 } 826 PetscFunctionReturn(0); 827 } 828 829 /* 830 This has to provide several versions. 831 832 2) a) use only local smoothing updating outer values only once. 833 b) local smoothing updating outer values each inner iteration 834 3) color updating out values betwen colors. 835 */ 836 #undef __FUNCT__ 837 #define __FUNCT__ "MatRelax_MPIAIJ" 838 int MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,int its,Vec xx) 839 { 840 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 841 Mat AA = mat->A,BB = mat->B; 842 Mat_SeqAIJ *A = (Mat_SeqAIJ*)AA->data,*B = (Mat_SeqAIJ *)BB->data; 843 Scalar *b,*x,*xs,*ls,d,*v,sum; 844 int ierr,*idx,*diag; 845 int n = matin->n,m = matin->m,i,shift = A->indexshift; 846 847 PetscFunctionBegin; 848 if (!A->diag) {ierr = MatMarkDiagonal_SeqAIJ(AA);CHKERRQ(ierr);} 849 diag = A->diag; 850 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 851 if (flag & SOR_ZERO_INITIAL_GUESS) { 852 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,its,xx);CHKERRQ(ierr); 853 PetscFunctionReturn(0); 854 } 855 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 856 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 857 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 858 if (xx != bb) { 859 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 860 } else { 861 b = x; 862 } 863 ierr = VecGetArray(mat->lvec,&ls);CHKERRQ(ierr); 864 xs = x + shift; /* shift by one for index start of 1 */ 865 ls = ls + shift; 866 while (its--) { 867 /* go down through the rows */ 868 for (i=0; i<m; i++) { 869 n = A->i[i+1] - A->i[i]; 870 PetscLogFlops(4*n+3); 871 idx = A->j + A->i[i] + shift; 872 v = A->a + A->i[i] + shift; 873 sum = b[i]; 874 SPARSEDENSEMDOT(sum,xs,v,idx,n); 875 d = fshift + A->a[diag[i]+shift]; 876 n = B->i[i+1] - B->i[i]; 877 idx = B->j + B->i[i] + shift; 878 v = B->a + B->i[i] + shift; 879 SPARSEDENSEMDOT(sum,ls,v,idx,n); 880 x[i] = (1. - omega)*x[i] + omega*(sum + A->a[diag[i]+shift]*x[i])/d; 881 } 882 /* come up through the rows */ 883 for (i=m-1; i>-1; i--) { 884 n = A->i[i+1] - A->i[i]; 885 PetscLogFlops(4*n+3); 886 idx = A->j + A->i[i] + shift; 887 v = A->a + A->i[i] + shift; 888 sum = b[i]; 889 SPARSEDENSEMDOT(sum,xs,v,idx,n); 890 d = fshift + A->a[diag[i]+shift]; 891 n = B->i[i+1] - B->i[i]; 892 idx = B->j + B->i[i] + shift; 893 v = B->a + B->i[i] + shift; 894 SPARSEDENSEMDOT(sum,ls,v,idx,n); 895 x[i] = (1. - omega)*x[i] + omega*(sum + A->a[diag[i]+shift]*x[i])/d; 896 } 897 } 898 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 899 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); } 900 ierr = VecRestoreArray(mat->lvec,&ls);CHKERRQ(ierr); 901 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 902 if (flag & SOR_ZERO_INITIAL_GUESS) { 903 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,its,xx);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } 906 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 907 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 908 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 909 if (xx != bb) { 910 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 911 } else { 912 b = x; 913 } 914 ierr = VecGetArray(mat->lvec,&ls);CHKERRQ(ierr); 915 xs = x + shift; /* shift by one for index start of 1 */ 916 ls = ls + shift; 917 while (its--) { 918 for (i=0; i<m; i++) { 919 n = A->i[i+1] - A->i[i]; 920 PetscLogFlops(4*n+3); 921 idx = A->j + A->i[i] + shift; 922 v = A->a + A->i[i] + shift; 923 sum = b[i]; 924 SPARSEDENSEMDOT(sum,xs,v,idx,n); 925 d = fshift + A->a[diag[i]+shift]; 926 n = B->i[i+1] - B->i[i]; 927 idx = B->j + B->i[i] + shift; 928 v = B->a + B->i[i] + shift; 929 SPARSEDENSEMDOT(sum,ls,v,idx,n); 930 x[i] = (1. - omega)*x[i] + omega*(sum + A->a[diag[i]+shift]*x[i])/d; 931 } 932 } 933 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 934 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); } 935 ierr = VecRestoreArray(mat->lvec,&ls);CHKERRQ(ierr); 936 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 937 if (flag & SOR_ZERO_INITIAL_GUESS) { 938 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,its,xx);CHKERRQ(ierr); 939 PetscFunctionReturn(0); 940 } 941 ierr = VecScatterBegin(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 942 ierr = VecScatterEnd(xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD,mat->Mvctx);CHKERRQ(ierr); 943 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 944 if (xx != bb) { 945 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 946 } else { 947 b = x; 948 } 949 ierr = VecGetArray(mat->lvec,&ls);CHKERRQ(ierr); 950 xs = x + shift; /* shift by one for index start of 1 */ 951 ls = ls + shift; 952 while (its--) { 953 for (i=m-1; i>-1; i--) { 954 n = A->i[i+1] - A->i[i]; 955 PetscLogFlops(4*n+3); 956 idx = A->j + A->i[i] + shift; 957 v = A->a + A->i[i] + shift; 958 sum = b[i]; 959 SPARSEDENSEMDOT(sum,xs,v,idx,n); 960 d = fshift + A->a[diag[i]+shift]; 961 n = B->i[i+1] - B->i[i]; 962 idx = B->j + B->i[i] + shift; 963 v = B->a + B->i[i] + shift; 964 SPARSEDENSEMDOT(sum,ls,v,idx,n); 965 x[i] = (1. - omega)*x[i] + omega*(sum + A->a[diag[i]+shift]*x[i])/d; 966 } 967 } 968 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 969 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); } 970 ierr = VecRestoreArray(mat->lvec,&ls);CHKERRQ(ierr); 971 } else { 972 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 973 } 974 PetscFunctionReturn(0); 975 } 976 977 #undef __FUNCT__ 978 #define __FUNCT__ "MatGetInfo_MPIAIJ" 979 int MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 980 { 981 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 982 Mat A = mat->A,B = mat->B; 983 int ierr; 984 PetscReal isend[5],irecv[5]; 985 986 PetscFunctionBegin; 987 info->block_size = 1.0; 988 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 989 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 990 isend[3] = info->memory; isend[4] = info->mallocs; 991 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 992 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 993 isend[3] += info->memory; isend[4] += info->mallocs; 994 if (flag == MAT_LOCAL) { 995 info->nz_used = isend[0]; 996 info->nz_allocated = isend[1]; 997 info->nz_unneeded = isend[2]; 998 info->memory = isend[3]; 999 info->mallocs = isend[4]; 1000 } else if (flag == MAT_GLOBAL_MAX) { 1001 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1002 info->nz_used = irecv[0]; 1003 info->nz_allocated = irecv[1]; 1004 info->nz_unneeded = irecv[2]; 1005 info->memory = irecv[3]; 1006 info->mallocs = irecv[4]; 1007 } else if (flag == MAT_GLOBAL_SUM) { 1008 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1009 info->nz_used = irecv[0]; 1010 info->nz_allocated = irecv[1]; 1011 info->nz_unneeded = irecv[2]; 1012 info->memory = irecv[3]; 1013 info->mallocs = irecv[4]; 1014 } 1015 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1016 info->fill_ratio_needed = 0; 1017 info->factor_mallocs = 0; 1018 info->rows_global = (double)matin->M; 1019 info->columns_global = (double)matin->N; 1020 info->rows_local = (double)matin->m; 1021 info->columns_local = (double)matin->N; 1022 1023 PetscFunctionReturn(0); 1024 } 1025 1026 #undef __FUNCT__ 1027 #define __FUNCT__ "MatSetOption_MPIAIJ" 1028 int MatSetOption_MPIAIJ(Mat A,MatOption op) 1029 { 1030 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1031 int ierr; 1032 1033 PetscFunctionBegin; 1034 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1035 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1036 op == MAT_COLUMNS_UNSORTED || 1037 op == MAT_COLUMNS_SORTED || 1038 op == MAT_NEW_NONZERO_ALLOCATION_ERR || 1039 op == MAT_KEEP_ZEROED_ROWS || 1040 op == MAT_NEW_NONZERO_LOCATION_ERR || 1041 op == MAT_USE_INODES || 1042 op == MAT_DO_NOT_USE_INODES || 1043 op == MAT_IGNORE_ZERO_ENTRIES) { 1044 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1045 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1046 } else if (op == MAT_ROW_ORIENTED) { 1047 a->roworiented = PETSC_TRUE; 1048 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1049 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1050 } else if (op == MAT_ROWS_SORTED || 1051 op == MAT_ROWS_UNSORTED || 1052 op == MAT_YES_NEW_DIAGONALS) { 1053 PetscLogInfo(A,"MatSetOption_MPIAIJ:Option ignored\n"); 1054 } else if (op == MAT_COLUMN_ORIENTED) { 1055 a->roworiented = PETSC_FALSE; 1056 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1057 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1058 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1059 a->donotstash = PETSC_TRUE; 1060 } else if (op == MAT_NO_NEW_DIAGONALS){ 1061 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1062 } else { 1063 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1064 } 1065 PetscFunctionReturn(0); 1066 } 1067 1068 #undef __FUNCT__ 1069 #define __FUNCT__ "MatGetOwnershipRange_MPIAIJ" 1070 int MatGetOwnershipRange_MPIAIJ(Mat matin,int *m,int *n) 1071 { 1072 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1073 1074 PetscFunctionBegin; 1075 if (m) *m = mat->rstart; 1076 if (n) *n = mat->rend; 1077 PetscFunctionReturn(0); 1078 } 1079 1080 #undef __FUNCT__ 1081 #define __FUNCT__ "MatGetRow_MPIAIJ" 1082 int MatGetRow_MPIAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1083 { 1084 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1085 Scalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1086 int i,ierr,*cworkA,*cworkB,**pcA,**pcB,cstart = mat->cstart; 1087 int nztot,nzA,nzB,lrow,rstart = mat->rstart,rend = mat->rend; 1088 int *cmap,*idx_p; 1089 1090 PetscFunctionBegin; 1091 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1092 mat->getrowactive = PETSC_TRUE; 1093 1094 if (!mat->rowvalues && (idx || v)) { 1095 /* 1096 allocate enough space to hold information from the longest row. 1097 */ 1098 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1099 int max = 1,tmp; 1100 for (i=0; i<matin->m; i++) { 1101 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1102 if (max < tmp) { max = tmp; } 1103 } 1104 ierr = PetscMalloc(max*(sizeof(int)+sizeof(Scalar)),&mat->rowvalues);CHKERRQ(ierr); 1105 mat->rowindices = (int*)(mat->rowvalues + max); 1106 } 1107 1108 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1109 lrow = row - rstart; 1110 1111 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1112 if (!v) {pvA = 0; pvB = 0;} 1113 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1114 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1115 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1116 nztot = nzA + nzB; 1117 1118 cmap = mat->garray; 1119 if (v || idx) { 1120 if (nztot) { 1121 /* Sort by increasing column numbers, assuming A and B already sorted */ 1122 int imark = -1; 1123 if (v) { 1124 *v = v_p = mat->rowvalues; 1125 for (i=0; i<nzB; i++) { 1126 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1127 else break; 1128 } 1129 imark = i; 1130 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1131 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1132 } 1133 if (idx) { 1134 *idx = idx_p = mat->rowindices; 1135 if (imark > -1) { 1136 for (i=0; i<imark; i++) { 1137 idx_p[i] = cmap[cworkB[i]]; 1138 } 1139 } else { 1140 for (i=0; i<nzB; i++) { 1141 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1142 else break; 1143 } 1144 imark = i; 1145 } 1146 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1147 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1148 } 1149 } else { 1150 if (idx) *idx = 0; 1151 if (v) *v = 0; 1152 } 1153 } 1154 *nz = nztot; 1155 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1156 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1157 PetscFunctionReturn(0); 1158 } 1159 1160 #undef __FUNCT__ 1161 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1162 int MatRestoreRow_MPIAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1163 { 1164 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1165 1166 PetscFunctionBegin; 1167 if (aij->getrowactive == PETSC_FALSE) { 1168 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1169 } 1170 aij->getrowactive = PETSC_FALSE; 1171 PetscFunctionReturn(0); 1172 } 1173 1174 #undef __FUNCT__ 1175 #define __FUNCT__ "MatNorm_MPIAIJ" 1176 int MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1177 { 1178 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1179 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1180 int ierr,i,j,cstart = aij->cstart,shift = amat->indexshift; 1181 PetscReal sum = 0.0; 1182 Scalar *v; 1183 1184 PetscFunctionBegin; 1185 if (aij->size == 1) { 1186 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1187 } else { 1188 if (type == NORM_FROBENIUS) { 1189 v = amat->a; 1190 for (i=0; i<amat->nz; i++) { 1191 #if defined(PETSC_USE_COMPLEX) 1192 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1193 #else 1194 sum += (*v)*(*v); v++; 1195 #endif 1196 } 1197 v = bmat->a; 1198 for (i=0; i<bmat->nz; i++) { 1199 #if defined(PETSC_USE_COMPLEX) 1200 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1201 #else 1202 sum += (*v)*(*v); v++; 1203 #endif 1204 } 1205 ierr = MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 1206 *norm = sqrt(*norm); 1207 } else if (type == NORM_1) { /* max column norm */ 1208 PetscReal *tmp,*tmp2; 1209 int *jj,*garray = aij->garray; 1210 ierr = PetscMalloc((mat->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1211 ierr = PetscMalloc((mat->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1212 ierr = PetscMemzero(tmp,mat->N*sizeof(PetscReal));CHKERRQ(ierr); 1213 *norm = 0.0; 1214 v = amat->a; jj = amat->j; 1215 for (j=0; j<amat->nz; j++) { 1216 tmp[cstart + *jj++ + shift] += PetscAbsScalar(*v); v++; 1217 } 1218 v = bmat->a; jj = bmat->j; 1219 for (j=0; j<bmat->nz; j++) { 1220 tmp[garray[*jj++ + shift]] += PetscAbsScalar(*v); v++; 1221 } 1222 ierr = MPI_Allreduce(tmp,tmp2,mat->N,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 1223 for (j=0; j<mat->N; j++) { 1224 if (tmp2[j] > *norm) *norm = tmp2[j]; 1225 } 1226 ierr = PetscFree(tmp);CHKERRQ(ierr); 1227 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1228 } else if (type == NORM_INFINITY) { /* max row norm */ 1229 PetscReal ntemp = 0.0; 1230 for (j=0; j<aij->A->m; j++) { 1231 v = amat->a + amat->i[j] + shift; 1232 sum = 0.0; 1233 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1234 sum += PetscAbsScalar(*v); v++; 1235 } 1236 v = bmat->a + bmat->i[j] + shift; 1237 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1238 sum += PetscAbsScalar(*v); v++; 1239 } 1240 if (sum > ntemp) ntemp = sum; 1241 } 1242 ierr = MPI_Allreduce(&ntemp,norm,1,MPI_DOUBLE,MPI_MAX,mat->comm);CHKERRQ(ierr); 1243 } else { 1244 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1245 } 1246 } 1247 PetscFunctionReturn(0); 1248 } 1249 1250 #undef __FUNCT__ 1251 #define __FUNCT__ "MatTranspose_MPIAIJ" 1252 int MatTranspose_MPIAIJ(Mat A,Mat *matout) 1253 { 1254 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1255 Mat_SeqAIJ *Aloc = (Mat_SeqAIJ*)a->A->data; 1256 int ierr,shift = Aloc->indexshift; 1257 int M = A->M,N = A->N,m,*ai,*aj,row,*cols,i,*ct; 1258 Mat B; 1259 Scalar *array; 1260 1261 PetscFunctionBegin; 1262 if (!matout && M != N) { 1263 SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1264 } 1265 1266 ierr = MatCreateMPIAIJ(A->comm,A->n,A->m,N,M,0,PETSC_NULL,0,PETSC_NULL,&B);CHKERRQ(ierr); 1267 1268 /* copy over the A part */ 1269 Aloc = (Mat_SeqAIJ*)a->A->data; 1270 m = a->A->m; ai = Aloc->i; aj = Aloc->j; array = Aloc->a; 1271 row = a->rstart; 1272 for (i=0; i<ai[m]+shift; i++) {aj[i] += a->cstart + shift;} 1273 for (i=0; i<m; i++) { 1274 ierr = MatSetValues(B,ai[i+1]-ai[i],aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1275 row++; array += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1276 } 1277 aj = Aloc->j; 1278 for (i=0; i<ai[m]+shift; i++) {aj[i] -= a->cstart + shift;} 1279 1280 /* copy over the B part */ 1281 Aloc = (Mat_SeqAIJ*)a->B->data; 1282 m = a->B->m; ai = Aloc->i; aj = Aloc->j; array = Aloc->a; 1283 row = a->rstart; 1284 ierr = PetscMalloc((1+ai[m]-shift)*sizeof(int),&cols);CHKERRQ(ierr); 1285 ct = cols; 1286 for (i=0; i<ai[m]+shift; i++) {cols[i] = a->garray[aj[i]+shift];} 1287 for (i=0; i<m; i++) { 1288 ierr = MatSetValues(B,ai[i+1]-ai[i],cols,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1289 row++; array += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1290 } 1291 ierr = PetscFree(ct);CHKERRQ(ierr); 1292 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1293 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1294 if (matout) { 1295 *matout = B; 1296 } else { 1297 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1298 } 1299 PetscFunctionReturn(0); 1300 } 1301 1302 #undef __FUNCT__ 1303 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1304 int MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1305 { 1306 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1307 Mat a = aij->A,b = aij->B; 1308 int ierr,s1,s2,s3; 1309 1310 PetscFunctionBegin; 1311 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1312 if (rr) { 1313 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1314 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1315 /* Overlap communication with computation. */ 1316 ierr = VecScatterBegin(rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD,aij->Mvctx);CHKERRQ(ierr); 1317 } 1318 if (ll) { 1319 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1320 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1321 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1322 } 1323 /* scale the diagonal block */ 1324 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1325 1326 if (rr) { 1327 /* Do a scatter end and then right scale the off-diagonal block */ 1328 ierr = VecScatterEnd(rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD,aij->Mvctx);CHKERRQ(ierr); 1329 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1330 } 1331 1332 PetscFunctionReturn(0); 1333 } 1334 1335 1336 #undef __FUNCT__ 1337 #define __FUNCT__ "MatPrintHelp_MPIAIJ" 1338 int MatPrintHelp_MPIAIJ(Mat A) 1339 { 1340 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1341 int ierr; 1342 1343 PetscFunctionBegin; 1344 if (!a->rank) { 1345 ierr = MatPrintHelp_SeqAIJ(a->A);CHKERRQ(ierr); 1346 } 1347 PetscFunctionReturn(0); 1348 } 1349 1350 #undef __FUNCT__ 1351 #define __FUNCT__ "MatGetBlockSize_MPIAIJ" 1352 int MatGetBlockSize_MPIAIJ(Mat A,int *bs) 1353 { 1354 PetscFunctionBegin; 1355 *bs = 1; 1356 PetscFunctionReturn(0); 1357 } 1358 #undef __FUNCT__ 1359 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1360 int MatSetUnfactored_MPIAIJ(Mat A) 1361 { 1362 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1363 int ierr; 1364 1365 PetscFunctionBegin; 1366 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1367 PetscFunctionReturn(0); 1368 } 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatEqual_MPIAIJ" 1372 int MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1373 { 1374 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1375 Mat a,b,c,d; 1376 PetscTruth flg; 1377 int ierr; 1378 1379 PetscFunctionBegin; 1380 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg);CHKERRQ(ierr); 1381 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1382 a = matA->A; b = matA->B; 1383 c = matB->A; d = matB->B; 1384 1385 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1386 if (flg == PETSC_TRUE) { 1387 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1388 } 1389 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1390 PetscFunctionReturn(0); 1391 } 1392 1393 #undef __FUNCT__ 1394 #define __FUNCT__ "MatCopy_MPIAIJ" 1395 int MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1396 { 1397 int ierr; 1398 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1399 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1400 PetscTruth flg; 1401 1402 PetscFunctionBegin; 1403 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg);CHKERRQ(ierr); 1404 if (str != SAME_NONZERO_PATTERN || !flg) { 1405 /* because of the column compression in the off-processor part of the matrix a->B, 1406 the number of columns in a->B and b->B may be different, hence we cannot call 1407 the MatCopy() directly on the two parts. If need be, we can provide a more 1408 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1409 then copying the submatrices */ 1410 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1411 } else { 1412 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1413 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1414 } 1415 PetscFunctionReturn(0); 1416 } 1417 1418 #undef __FUNCT__ 1419 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1420 int MatSetUpPreallocation_MPIAIJ(Mat A) 1421 { 1422 int ierr; 1423 1424 PetscFunctionBegin; 1425 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1426 PetscFunctionReturn(0); 1427 } 1428 1429 EXTERN int MatDuplicate_MPIAIJ(Mat,MatDuplicateOption,Mat *); 1430 EXTERN int MatIncreaseOverlap_MPIAIJ(Mat,int,IS *,int); 1431 EXTERN int MatFDColoringCreate_MPIAIJ(Mat,ISColoring,MatFDColoring); 1432 EXTERN int MatGetSubMatrices_MPIAIJ (Mat,int,IS *,IS *,MatReuse,Mat **); 1433 EXTERN int MatGetSubMatrix_MPIAIJ (Mat,IS,IS,int,MatReuse,Mat *); 1434 #if !defined(PETSC_USE_COMPLEX) 1435 EXTERN int MatLUFactorSymbolic_MPIAIJ_TFS(Mat,IS,IS,MatLUInfo*,Mat*); 1436 #endif 1437 1438 /* -------------------------------------------------------------------*/ 1439 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 1440 MatGetRow_MPIAIJ, 1441 MatRestoreRow_MPIAIJ, 1442 MatMult_MPIAIJ, 1443 MatMultAdd_MPIAIJ, 1444 MatMultTranspose_MPIAIJ, 1445 MatMultTransposeAdd_MPIAIJ, 1446 0, 1447 0, 1448 0, 1449 0, 1450 0, 1451 0, 1452 MatRelax_MPIAIJ, 1453 MatTranspose_MPIAIJ, 1454 MatGetInfo_MPIAIJ, 1455 MatEqual_MPIAIJ, 1456 MatGetDiagonal_MPIAIJ, 1457 MatDiagonalScale_MPIAIJ, 1458 MatNorm_MPIAIJ, 1459 MatAssemblyBegin_MPIAIJ, 1460 MatAssemblyEnd_MPIAIJ, 1461 0, 1462 MatSetOption_MPIAIJ, 1463 MatZeroEntries_MPIAIJ, 1464 MatZeroRows_MPIAIJ, 1465 #if !defined(PETSC_USE_COMPLEX) 1466 MatLUFactorSymbolic_MPIAIJ_TFS, 1467 #else 1468 0, 1469 #endif 1470 0, 1471 0, 1472 0, 1473 MatSetUpPreallocation_MPIAIJ, 1474 0, 1475 MatGetOwnershipRange_MPIAIJ, 1476 0, 1477 0, 1478 0, 1479 0, 1480 MatDuplicate_MPIAIJ, 1481 0, 1482 0, 1483 0, 1484 0, 1485 0, 1486 MatGetSubMatrices_MPIAIJ, 1487 MatIncreaseOverlap_MPIAIJ, 1488 MatGetValues_MPIAIJ, 1489 MatCopy_MPIAIJ, 1490 MatPrintHelp_MPIAIJ, 1491 MatScale_MPIAIJ, 1492 0, 1493 0, 1494 0, 1495 MatGetBlockSize_MPIAIJ, 1496 0, 1497 0, 1498 0, 1499 0, 1500 MatFDColoringCreate_MPIAIJ, 1501 0, 1502 MatSetUnfactored_MPIAIJ, 1503 0, 1504 0, 1505 MatGetSubMatrix_MPIAIJ, 1506 MatDestroy_MPIAIJ, 1507 MatView_MPIAIJ, 1508 MatGetMaps_Petsc}; 1509 1510 /* ----------------------------------------------------------------------------------------*/ 1511 1512 EXTERN_C_BEGIN 1513 #undef __FUNCT__ 1514 #define __FUNCT__ "MatStoreValues_MPIAIJ" 1515 int MatStoreValues_MPIAIJ(Mat mat) 1516 { 1517 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1518 int ierr; 1519 1520 PetscFunctionBegin; 1521 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 1522 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 1523 PetscFunctionReturn(0); 1524 } 1525 EXTERN_C_END 1526 1527 EXTERN_C_BEGIN 1528 #undef __FUNCT__ 1529 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 1530 int MatRetrieveValues_MPIAIJ(Mat mat) 1531 { 1532 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1533 int ierr; 1534 1535 PetscFunctionBegin; 1536 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 1537 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 1538 PetscFunctionReturn(0); 1539 } 1540 EXTERN_C_END 1541 1542 #include "petscpc.h" 1543 EXTERN_C_BEGIN 1544 EXTERN int MatGetDiagonalBlock_MPIAIJ(Mat,PetscTruth *,MatReuse,Mat *); 1545 EXTERN_C_END 1546 1547 EXTERN_C_BEGIN 1548 #undef __FUNCT__ 1549 #define __FUNCT__ "MatCreate_MPIAIJ" 1550 int MatCreate_MPIAIJ(Mat B) 1551 { 1552 Mat_MPIAIJ *b; 1553 int ierr,i,size; 1554 1555 PetscFunctionBegin; 1556 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 1557 1558 ierr = PetscNew(Mat_MPIAIJ,&b);CHKERRQ(ierr); 1559 B->data = (void*)b; 1560 ierr = PetscMemzero(b,sizeof(Mat_MPIAIJ));CHKERRQ(ierr); 1561 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1562 B->factor = 0; 1563 B->assembled = PETSC_FALSE; 1564 B->mapping = 0; 1565 1566 B->insertmode = NOT_SET_VALUES; 1567 b->size = size; 1568 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1569 1570 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1571 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1572 1573 /* the information in the maps duplicates the information computed below, eventually 1574 we should remove the duplicate information that is not contained in the maps */ 1575 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1576 ierr = MapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 1577 1578 /* build local table of row and column ownerships */ 1579 ierr = PetscMalloc(2*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1580 PetscLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIAIJ)); 1581 b->cowners = b->rowners + b->size + 2; 1582 ierr = MPI_Allgather(&B->m,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1583 b->rowners[0] = 0; 1584 for (i=2; i<=b->size; i++) { 1585 b->rowners[i] += b->rowners[i-1]; 1586 } 1587 b->rstart = b->rowners[b->rank]; 1588 b->rend = b->rowners[b->rank+1]; 1589 ierr = MPI_Allgather(&B->n,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1590 b->cowners[0] = 0; 1591 for (i=2; i<=b->size; i++) { 1592 b->cowners[i] += b->cowners[i-1]; 1593 } 1594 b->cstart = b->cowners[b->rank]; 1595 b->cend = b->cowners[b->rank+1]; 1596 1597 /* build cache for off array entries formed */ 1598 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1599 b->donotstash = PETSC_FALSE; 1600 b->colmap = 0; 1601 b->garray = 0; 1602 b->roworiented = PETSC_TRUE; 1603 1604 /* stuff used for matrix vector multiply */ 1605 b->lvec = PETSC_NULL; 1606 b->Mvctx = PETSC_NULL; 1607 1608 /* stuff for MatGetRow() */ 1609 b->rowindices = 0; 1610 b->rowvalues = 0; 1611 b->getrowactive = PETSC_FALSE; 1612 1613 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1614 "MatStoreValues_MPIAIJ", 1615 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 1616 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1617 "MatRetrieveValues_MPIAIJ", 1618 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 1619 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1620 "MatGetDiagonalBlock_MPIAIJ", 1621 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 1622 PetscFunctionReturn(0); 1623 } 1624 EXTERN_C_END 1625 1626 #undef __FUNCT__ 1627 #define __FUNCT__ "MatDuplicate_MPIAIJ" 1628 int MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1629 { 1630 Mat mat; 1631 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 1632 int ierr; 1633 1634 PetscFunctionBegin; 1635 *newmat = 0; 1636 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1637 ierr = MatSetType(mat,MATMPIAIJ);CHKERRQ(ierr); 1638 a = (Mat_MPIAIJ*)mat->data; 1639 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1640 mat->factor = matin->factor; 1641 mat->assembled = PETSC_TRUE; 1642 mat->insertmode = NOT_SET_VALUES; 1643 mat->preallocated = PETSC_TRUE; 1644 1645 a->rstart = oldmat->rstart; 1646 a->rend = oldmat->rend; 1647 a->cstart = oldmat->cstart; 1648 a->cend = oldmat->cend; 1649 a->size = oldmat->size; 1650 a->rank = oldmat->rank; 1651 a->donotstash = oldmat->donotstash; 1652 a->roworiented = oldmat->roworiented; 1653 a->rowindices = 0; 1654 a->rowvalues = 0; 1655 a->getrowactive = PETSC_FALSE; 1656 1657 ierr = PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1658 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1659 if (oldmat->colmap) { 1660 #if defined (PETSC_USE_CTABLE) 1661 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1662 #else 1663 ierr = PetscMalloc((mat->N)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1664 PetscLogObjectMemory(mat,(mat->N)*sizeof(int)); 1665 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->N)*sizeof(int));CHKERRQ(ierr); 1666 #endif 1667 } else a->colmap = 0; 1668 if (oldmat->garray) { 1669 int len; 1670 len = oldmat->B->n; 1671 ierr = PetscMalloc((len+1)*sizeof(int),&a->garray);CHKERRQ(ierr); 1672 PetscLogObjectMemory(mat,len*sizeof(int)); 1673 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); } 1674 } else a->garray = 0; 1675 1676 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1677 PetscLogObjectParent(mat,a->lvec); 1678 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1679 PetscLogObjectParent(mat,a->Mvctx); 1680 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1681 PetscLogObjectParent(mat,a->A); 1682 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1683 PetscLogObjectParent(mat,a->B); 1684 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 1685 *newmat = mat; 1686 PetscFunctionReturn(0); 1687 } 1688 1689 #include "petscsys.h" 1690 1691 EXTERN_C_BEGIN 1692 #undef __FUNCT__ 1693 #define __FUNCT__ "MatLoad_MPIAIJ" 1694 int MatLoad_MPIAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1695 { 1696 Mat A; 1697 Scalar *vals,*svals; 1698 MPI_Comm comm = ((PetscObject)viewer)->comm; 1699 MPI_Status status; 1700 int i,nz,ierr,j,rstart,rend,fd; 1701 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,maxnz,*cols; 1702 int *ourlens,*sndcounts = 0,*procsnz = 0,*offlens,jj,*mycols,*smycols; 1703 int tag = ((PetscObject)viewer)->tag,cend,cstart,n; 1704 1705 PetscFunctionBegin; 1706 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1707 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1708 if (!rank) { 1709 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1710 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1711 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1712 if (header[3] < 0) { 1713 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix in special format on disk, cannot load as MPIAIJ"); 1714 } 1715 } 1716 1717 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 1718 M = header[1]; N = header[2]; 1719 /* determine ownership of all rows */ 1720 m = M/size + ((M % size) > rank); 1721 ierr = PetscMalloc((size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 1722 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1723 rowners[0] = 0; 1724 for (i=2; i<=size; i++) { 1725 rowners[i] += rowners[i-1]; 1726 } 1727 rstart = rowners[rank]; 1728 rend = rowners[rank+1]; 1729 1730 /* distribute row lengths to all processors */ 1731 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&ourlens);CHKERRQ(ierr); 1732 offlens = ourlens + (rend-rstart); 1733 if (!rank) { 1734 ierr = PetscMalloc(M*sizeof(int),&rowlengths);CHKERRQ(ierr); 1735 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1736 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 1737 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1738 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1739 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1740 } else { 1741 ierr = MPI_Scatterv(0,0,0,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1742 } 1743 1744 if (!rank) { 1745 /* calculate the number of nonzeros on each processor */ 1746 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 1747 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 1748 for (i=0; i<size; i++) { 1749 for (j=rowners[i]; j< rowners[i+1]; j++) { 1750 procsnz[i] += rowlengths[j]; 1751 } 1752 } 1753 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1754 1755 /* determine max buffer needed and allocate it */ 1756 maxnz = 0; 1757 for (i=0; i<size; i++) { 1758 maxnz = PetscMax(maxnz,procsnz[i]); 1759 } 1760 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 1761 1762 /* read in my part of the matrix column indices */ 1763 nz = procsnz[0]; 1764 ierr = PetscMalloc(nz*sizeof(int),&mycols);CHKERRQ(ierr); 1765 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1766 1767 /* read in every one elses and ship off */ 1768 for (i=1; i<size; i++) { 1769 nz = procsnz[i]; 1770 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1771 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 1772 } 1773 ierr = PetscFree(cols);CHKERRQ(ierr); 1774 } else { 1775 /* determine buffer space needed for message */ 1776 nz = 0; 1777 for (i=0; i<m; i++) { 1778 nz += ourlens[i]; 1779 } 1780 ierr = PetscMalloc((nz+1)*sizeof(int),&mycols);CHKERRQ(ierr); 1781 1782 /* receive message of column indices*/ 1783 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 1784 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 1785 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1786 } 1787 1788 /* determine column ownership if matrix is not square */ 1789 if (N != M) { 1790 n = N/size + ((N % size) > rank); 1791 ierr = MPI_Scan(&n,&cend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1792 cstart = cend - n; 1793 } else { 1794 cstart = rstart; 1795 cend = rend; 1796 n = cend - cstart; 1797 } 1798 1799 /* loop over local rows, determining number of off diagonal entries */ 1800 ierr = PetscMemzero(offlens,m*sizeof(int));CHKERRQ(ierr); 1801 jj = 0; 1802 for (i=0; i<m; i++) { 1803 for (j=0; j<ourlens[i]; j++) { 1804 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 1805 jj++; 1806 } 1807 } 1808 1809 /* create our matrix */ 1810 for (i=0; i<m; i++) { 1811 ourlens[i] -= offlens[i]; 1812 } 1813 ierr = MatCreateMPIAIJ(comm,m,n,M,N,0,ourlens,0,offlens,newmat);CHKERRQ(ierr); 1814 A = *newmat; 1815 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 1816 for (i=0; i<m; i++) { 1817 ourlens[i] += offlens[i]; 1818 } 1819 1820 if (!rank) { 1821 ierr = PetscMalloc(maxnz*sizeof(Scalar),&vals);CHKERRQ(ierr); 1822 1823 /* read in my part of the matrix numerical values */ 1824 nz = procsnz[0]; 1825 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1826 1827 /* insert into matrix */ 1828 jj = rstart; 1829 smycols = mycols; 1830 svals = vals; 1831 for (i=0; i<m; i++) { 1832 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1833 smycols += ourlens[i]; 1834 svals += ourlens[i]; 1835 jj++; 1836 } 1837 1838 /* read in other processors and ship out */ 1839 for (i=1; i<size; i++) { 1840 nz = procsnz[i]; 1841 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1842 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 1843 } 1844 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1845 } else { 1846 /* receive numeric values */ 1847 ierr = PetscMalloc((nz+1)*sizeof(Scalar),&vals);CHKERRQ(ierr); 1848 1849 /* receive message of values*/ 1850 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 1851 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1852 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1853 1854 /* insert into matrix */ 1855 jj = rstart; 1856 smycols = mycols; 1857 svals = vals; 1858 for (i=0; i<m; i++) { 1859 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1860 smycols += ourlens[i]; 1861 svals += ourlens[i]; 1862 jj++; 1863 } 1864 } 1865 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1866 ierr = PetscFree(vals);CHKERRQ(ierr); 1867 ierr = PetscFree(mycols);CHKERRQ(ierr); 1868 ierr = PetscFree(rowners);CHKERRQ(ierr); 1869 1870 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1871 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1872 PetscFunctionReturn(0); 1873 } 1874 EXTERN_C_END 1875 1876 #undef __FUNCT__ 1877 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 1878 /* 1879 Not great since it makes two copies of the submatrix, first an SeqAIJ 1880 in local and then by concatenating the local matrices the end result. 1881 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 1882 */ 1883 int MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,int csize,MatReuse call,Mat *newmat) 1884 { 1885 int ierr,i,m,n,rstart,row,rend,nz,*cwork,size,rank,j; 1886 int *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend; 1887 Mat *local,M,Mreuse; 1888 Scalar *vwork,*aa; 1889 MPI_Comm comm = mat->comm; 1890 Mat_SeqAIJ *aij; 1891 1892 1893 PetscFunctionBegin; 1894 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1895 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1896 1897 if (call == MAT_REUSE_MATRIX) { 1898 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 1899 if (!Mreuse) SETERRQ(1,"Submatrix passed in was not used before, cannot reuse"); 1900 local = &Mreuse; 1901 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 1902 } else { 1903 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 1904 Mreuse = *local; 1905 ierr = PetscFree(local);CHKERRQ(ierr); 1906 } 1907 1908 /* 1909 m - number of local rows 1910 n - number of columns (same on all processors) 1911 rstart - first row in new global matrix generated 1912 */ 1913 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 1914 if (call == MAT_INITIAL_MATRIX) { 1915 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1916 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1917 ii = aij->i; 1918 jj = aij->j; 1919 1920 /* 1921 Determine the number of non-zeros in the diagonal and off-diagonal 1922 portions of the matrix in order to do correct preallocation 1923 */ 1924 1925 /* first get start and end of "diagonal" columns */ 1926 if (csize == PETSC_DECIDE) { 1927 nlocal = n/size + ((n % size) > rank); 1928 } else { 1929 nlocal = csize; 1930 } 1931 ierr = MPI_Scan(&nlocal,&rend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1932 rstart = rend - nlocal; 1933 if (rank == size - 1 && rend != n) { 1934 SETERRQ(1,"Local column sizes do not add up to total number of columns"); 1935 } 1936 1937 /* next, compute all the lengths */ 1938 ierr = PetscMalloc((2*m+1)*sizeof(int),&dlens);CHKERRQ(ierr); 1939 olens = dlens + m; 1940 for (i=0; i<m; i++) { 1941 jend = ii[i+1] - ii[i]; 1942 olen = 0; 1943 dlen = 0; 1944 for (j=0; j<jend; j++) { 1945 if (*jj < rstart || *jj >= rend) olen++; 1946 else dlen++; 1947 jj++; 1948 } 1949 olens[i] = olen; 1950 dlens[i] = dlen; 1951 } 1952 ierr = MatCreateMPIAIJ(comm,m,nlocal,PETSC_DECIDE,n,0,dlens,0,olens,&M);CHKERRQ(ierr); 1953 ierr = PetscFree(dlens);CHKERRQ(ierr); 1954 } else { 1955 int ml,nl; 1956 1957 M = *newmat; 1958 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 1959 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 1960 ierr = MatZeroEntries(M);CHKERRQ(ierr); 1961 /* 1962 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 1963 rather than the slower MatSetValues(). 1964 */ 1965 M->was_assembled = PETSC_TRUE; 1966 M->assembled = PETSC_FALSE; 1967 } 1968 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 1969 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1970 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1971 ii = aij->i; 1972 jj = aij->j; 1973 aa = aij->a; 1974 for (i=0; i<m; i++) { 1975 row = rstart + i; 1976 nz = ii[i+1] - ii[i]; 1977 cwork = jj; jj += nz; 1978 vwork = aa; aa += nz; 1979 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 1980 } 1981 1982 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1983 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1984 *newmat = M; 1985 1986 /* save submatrix used in processor for next request */ 1987 if (call == MAT_INITIAL_MATRIX) { 1988 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 1989 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 1990 } 1991 1992 PetscFunctionReturn(0); 1993 } 1994 1995 #undef __FUNCT__ 1996 #define __FUNCT__ "MatMPIAIJSetPreallocation" 1997 /*@C 1998 MatMPIAIJSetPreallocation - Creates a sparse parallel matrix in AIJ format 1999 (the default parallel PETSc format). For good matrix assembly performance 2000 the user should preallocate the matrix storage by setting the parameters 2001 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2002 performance can be increased by more than a factor of 50. 2003 2004 Collective on MPI_Comm 2005 2006 Input Parameters: 2007 + A - the matrix 2008 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2009 (same value is used for all local rows) 2010 . d_nnz - array containing the number of nonzeros in the various rows of the 2011 DIAGONAL portion of the local submatrix (possibly different for each row) 2012 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2013 The size of this array is equal to the number of local rows, i.e 'm'. 2014 You must leave room for the diagonal entry even if it is zero. 2015 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2016 submatrix (same value is used for all local rows). 2017 - o_nnz - array containing the number of nonzeros in the various rows of the 2018 OFF-DIAGONAL portion of the local submatrix (possibly different for 2019 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2020 structure. The size of this array is equal to the number 2021 of local rows, i.e 'm'. 2022 2023 The AIJ format (also called the Yale sparse matrix format or 2024 compressed row storage), is fully compatible with standard Fortran 77 2025 storage. That is, the stored row and column indices can begin at 2026 either one (as in Fortran) or zero. See the users manual for details. 2027 2028 The user MUST specify either the local or global matrix dimensions 2029 (possibly both). 2030 2031 The parallel matrix is partitioned such that the first m0 rows belong to 2032 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2033 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2034 2035 The DIAGONAL portion of the local submatrix of a processor can be defined 2036 as the submatrix which is obtained by extraction the part corresponding 2037 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2038 first row that belongs to the processor, and r2 is the last row belonging 2039 to the this processor. This is a square mxm matrix. The remaining portion 2040 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2041 2042 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2043 2044 By default, this format uses inodes (identical nodes) when possible. 2045 We search for consecutive rows with the same nonzero structure, thereby 2046 reusing matrix information to achieve increased efficiency. 2047 2048 Options Database Keys: 2049 + -mat_aij_no_inode - Do not use inodes 2050 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2051 - -mat_aij_oneindex - Internally use indexing starting at 1 2052 rather than 0. Note that when calling MatSetValues(), 2053 the user still MUST index entries starting at 0! 2054 2055 Example usage: 2056 2057 Consider the following 8x8 matrix with 34 non-zero values, that is 2058 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2059 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2060 as follows: 2061 2062 .vb 2063 1 2 0 | 0 3 0 | 0 4 2064 Proc0 0 5 6 | 7 0 0 | 8 0 2065 9 0 10 | 11 0 0 | 12 0 2066 ------------------------------------- 2067 13 0 14 | 15 16 17 | 0 0 2068 Proc1 0 18 0 | 19 20 21 | 0 0 2069 0 0 0 | 22 23 0 | 24 0 2070 ------------------------------------- 2071 Proc2 25 26 27 | 0 0 28 | 29 0 2072 30 0 0 | 31 32 33 | 0 34 2073 .ve 2074 2075 This can be represented as a collection of submatrices as: 2076 2077 .vb 2078 A B C 2079 D E F 2080 G H I 2081 .ve 2082 2083 Where the submatrices A,B,C are owned by proc0, D,E,F are 2084 owned by proc1, G,H,I are owned by proc2. 2085 2086 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2087 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2088 The 'M','N' parameters are 8,8, and have the same values on all procs. 2089 2090 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2091 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2092 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2093 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2094 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2095 matrix, ans [DF] as another SeqAIJ matrix. 2096 2097 When d_nz, o_nz parameters are specified, d_nz storage elements are 2098 allocated for every row of the local diagonal submatrix, and o_nz 2099 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2100 One way to choose d_nz and o_nz is to use the max nonzerors per local 2101 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2102 In this case, the values of d_nz,o_nz are: 2103 .vb 2104 proc0 : dnz = 2, o_nz = 2 2105 proc1 : dnz = 3, o_nz = 2 2106 proc2 : dnz = 1, o_nz = 4 2107 .ve 2108 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2109 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2110 for proc3. i.e we are using 12+15+10=37 storage locations to store 2111 34 values. 2112 2113 When d_nnz, o_nnz parameters are specified, the storage is specified 2114 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2115 In the above case the values for d_nnz,o_nnz are: 2116 .vb 2117 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2118 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2119 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2120 .ve 2121 Here the space allocated is sum of all the above values i.e 34, and 2122 hence pre-allocation is perfect. 2123 2124 Level: intermediate 2125 2126 .keywords: matrix, aij, compressed row, sparse, parallel 2127 2128 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2129 @*/ 2130 int MatMPIAIJSetPreallocation(Mat B,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2131 { 2132 Mat_MPIAIJ *b; 2133 int ierr,i; 2134 PetscTruth flg2; 2135 2136 PetscFunctionBegin; 2137 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg2);CHKERRQ(ierr); 2138 if (!flg2) PetscFunctionReturn(0); 2139 B->preallocated = PETSC_TRUE; 2140 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2141 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2142 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2143 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2144 if (d_nnz) { 2145 for (i=0; i<B->m; i++) { 2146 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]); 2147 } 2148 } 2149 if (o_nnz) { 2150 for (i=0; i<B->m; i++) { 2151 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]); 2152 } 2153 } 2154 b = (Mat_MPIAIJ*)B->data; 2155 2156 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2157 PetscLogObjectParent(B,b->A); 2158 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2159 PetscLogObjectParent(B,b->B); 2160 2161 PetscFunctionReturn(0); 2162 } 2163 2164 #undef __FUNCT__ 2165 #define __FUNCT__ "MatCreateMPIAIJ" 2166 /*@C 2167 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 2168 (the default parallel PETSc format). For good matrix assembly performance 2169 the user should preallocate the matrix storage by setting the parameters 2170 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2171 performance can be increased by more than a factor of 50. 2172 2173 Collective on MPI_Comm 2174 2175 Input Parameters: 2176 + comm - MPI communicator 2177 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2178 This value should be the same as the local size used in creating the 2179 y vector for the matrix-vector product y = Ax. 2180 . n - This value should be the same as the local size used in creating the 2181 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2182 calculated if N is given) For square matrices n is almost always m. 2183 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2184 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2185 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2186 (same value is used for all local rows) 2187 . d_nnz - array containing the number of nonzeros in the various rows of the 2188 DIAGONAL portion of the local submatrix (possibly different for each row) 2189 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2190 The size of this array is equal to the number of local rows, i.e 'm'. 2191 You must leave room for the diagonal entry even if it is zero. 2192 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2193 submatrix (same value is used for all local rows). 2194 - o_nnz - array containing the number of nonzeros in the various rows of the 2195 OFF-DIAGONAL portion of the local submatrix (possibly different for 2196 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2197 structure. The size of this array is equal to the number 2198 of local rows, i.e 'm'. 2199 2200 Output Parameter: 2201 . A - the matrix 2202 2203 Notes: 2204 m,n,M,N parameters specify the size of the matrix, and its partitioning across 2205 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 2206 storage requirements for this matrix. 2207 2208 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 2209 processor than it must be used on all processors that share the object for 2210 that argument. 2211 2212 The AIJ format (also called the Yale sparse matrix format or 2213 compressed row storage), is fully compatible with standard Fortran 77 2214 storage. That is, the stored row and column indices can begin at 2215 either one (as in Fortran) or zero. See the users manual for details. 2216 2217 The user MUST specify either the local or global matrix dimensions 2218 (possibly both). 2219 2220 The parallel matrix is partitioned such that the first m0 rows belong to 2221 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2222 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2223 2224 The DIAGONAL portion of the local submatrix of a processor can be defined 2225 as the submatrix which is obtained by extraction the part corresponding 2226 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2227 first row that belongs to the processor, and r2 is the last row belonging 2228 to the this processor. This is a square mxm matrix. The remaining portion 2229 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2230 2231 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2232 2233 By default, this format uses inodes (identical nodes) when possible. 2234 We search for consecutive rows with the same nonzero structure, thereby 2235 reusing matrix information to achieve increased efficiency. 2236 2237 Options Database Keys: 2238 + -mat_aij_no_inode - Do not use inodes 2239 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2240 - -mat_aij_oneindex - Internally use indexing starting at 1 2241 rather than 0. Note that when calling MatSetValues(), 2242 the user still MUST index entries starting at 0! 2243 2244 2245 Example usage: 2246 2247 Consider the following 8x8 matrix with 34 non-zero values, that is 2248 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2249 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2250 as follows: 2251 2252 .vb 2253 1 2 0 | 0 3 0 | 0 4 2254 Proc0 0 5 6 | 7 0 0 | 8 0 2255 9 0 10 | 11 0 0 | 12 0 2256 ------------------------------------- 2257 13 0 14 | 15 16 17 | 0 0 2258 Proc1 0 18 0 | 19 20 21 | 0 0 2259 0 0 0 | 22 23 0 | 24 0 2260 ------------------------------------- 2261 Proc2 25 26 27 | 0 0 28 | 29 0 2262 30 0 0 | 31 32 33 | 0 34 2263 .ve 2264 2265 This can be represented as a collection of submatrices as: 2266 2267 .vb 2268 A B C 2269 D E F 2270 G H I 2271 .ve 2272 2273 Where the submatrices A,B,C are owned by proc0, D,E,F are 2274 owned by proc1, G,H,I are owned by proc2. 2275 2276 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2277 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2278 The 'M','N' parameters are 8,8, and have the same values on all procs. 2279 2280 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2281 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2282 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2283 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2284 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2285 matrix, ans [DF] as another SeqAIJ matrix. 2286 2287 When d_nz, o_nz parameters are specified, d_nz storage elements are 2288 allocated for every row of the local diagonal submatrix, and o_nz 2289 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2290 One way to choose d_nz and o_nz is to use the max nonzerors per local 2291 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2292 In this case, the values of d_nz,o_nz are: 2293 .vb 2294 proc0 : dnz = 2, o_nz = 2 2295 proc1 : dnz = 3, o_nz = 2 2296 proc2 : dnz = 1, o_nz = 4 2297 .ve 2298 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2299 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2300 for proc3. i.e we are using 12+15+10=37 storage locations to store 2301 34 values. 2302 2303 When d_nnz, o_nnz parameters are specified, the storage is specified 2304 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2305 In the above case the values for d_nnz,o_nnz are: 2306 .vb 2307 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2308 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2309 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2310 .ve 2311 Here the space allocated is sum of all the above values i.e 34, and 2312 hence pre-allocation is perfect. 2313 2314 Level: intermediate 2315 2316 .keywords: matrix, aij, compressed row, sparse, parallel 2317 2318 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2319 @*/ 2320 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) 2321 { 2322 int ierr,size; 2323 2324 PetscFunctionBegin; 2325 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2326 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2327 if (size > 1) { 2328 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 2329 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2330 } else { 2331 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2332 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 2333 } 2334 PetscFunctionReturn(0); 2335 } 2336 2337 #undef __FUNCT__ 2338 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 2339 int MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2340 { 2341 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 2342 PetscFunctionBegin; 2343 *Ad = a->A; 2344 *Ao = a->B; 2345 *colmap = a->garray; 2346 PetscFunctionReturn(0); 2347 } 2348