1 /*$Id: mpiaij.c,v 1.331 2001/03/23 20:13:45 bsmith 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 __FUNC__ 22 #define __FUNC__ "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 __FUNC__ 193 #define __FUNC__ "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 __FUNC__ 279 #define __FUNC__ "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 __FUNC__ 322 #define __FUNC__ "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 __FUNC__ 349 #define __FUNC__ "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 __FUNC__ 407 #define __FUNC__ "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 __FUNC__ 420 #define __FUNC__ "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 __FUNC__ 572 #define __FUNC__ "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 __FUNC__ 591 #define __FUNC__ "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 __FUNC__ 606 #define __FUNC__ "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 __FUNC__ 627 #define __FUNC__ "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 __FUNC__ 652 #define __FUNC__ "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 __FUNC__ 668 #define __FUNC__ "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 __FUNC__ 681 #define __FUNC__ "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 __FUNC__ 709 #define __FUNC__ "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 __FUNC__ 810 #define __FUNC__ "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 __FUNC__ 837 #define __FUNC__ "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 __FUNC__ 978 #define __FUNC__ "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 __FUNC__ 1027 #define __FUNC__ "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 __FUNC__ 1069 #define __FUNC__ "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 __FUNC__ 1081 #define __FUNC__ "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 __FUNC__ 1161 #define __FUNC__ "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 __FUNC__ 1175 #define __FUNC__ "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 __FUNC__ 1251 #define __FUNC__ "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 __FUNC__ 1303 #define __FUNC__ "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 __FUNC__ 1337 #define __FUNC__ "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 __FUNC__ 1351 #define __FUNC__ "MatGetBlockSize_MPIAIJ" 1352 int MatGetBlockSize_MPIAIJ(Mat A,int *bs) 1353 { 1354 PetscFunctionBegin; 1355 *bs = 1; 1356 PetscFunctionReturn(0); 1357 } 1358 #undef __FUNC__ 1359 #define __FUNC__ "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 __FUNC__ 1371 #define __FUNC__ "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 __FUNC__ 1394 #define __FUNC__ "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 __FUNC__ 1419 #define __FUNC__ "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 1435 /* -------------------------------------------------------------------*/ 1436 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 1437 MatGetRow_MPIAIJ, 1438 MatRestoreRow_MPIAIJ, 1439 MatMult_MPIAIJ, 1440 MatMultAdd_MPIAIJ, 1441 MatMultTranspose_MPIAIJ, 1442 MatMultTransposeAdd_MPIAIJ, 1443 0, 1444 0, 1445 0, 1446 0, 1447 0, 1448 0, 1449 MatRelax_MPIAIJ, 1450 MatTranspose_MPIAIJ, 1451 MatGetInfo_MPIAIJ, 1452 MatEqual_MPIAIJ, 1453 MatGetDiagonal_MPIAIJ, 1454 MatDiagonalScale_MPIAIJ, 1455 MatNorm_MPIAIJ, 1456 MatAssemblyBegin_MPIAIJ, 1457 MatAssemblyEnd_MPIAIJ, 1458 0, 1459 MatSetOption_MPIAIJ, 1460 MatZeroEntries_MPIAIJ, 1461 MatZeroRows_MPIAIJ, 1462 0, 1463 0, 1464 0, 1465 0, 1466 MatSetUpPreallocation_MPIAIJ, 1467 0, 1468 MatGetOwnershipRange_MPIAIJ, 1469 0, 1470 0, 1471 0, 1472 0, 1473 MatDuplicate_MPIAIJ, 1474 0, 1475 0, 1476 0, 1477 0, 1478 0, 1479 MatGetSubMatrices_MPIAIJ, 1480 MatIncreaseOverlap_MPIAIJ, 1481 MatGetValues_MPIAIJ, 1482 MatCopy_MPIAIJ, 1483 MatPrintHelp_MPIAIJ, 1484 MatScale_MPIAIJ, 1485 0, 1486 0, 1487 0, 1488 MatGetBlockSize_MPIAIJ, 1489 0, 1490 0, 1491 0, 1492 0, 1493 MatFDColoringCreate_MPIAIJ, 1494 0, 1495 MatSetUnfactored_MPIAIJ, 1496 0, 1497 0, 1498 MatGetSubMatrix_MPIAIJ, 1499 MatDestroy_MPIAIJ, 1500 MatView_MPIAIJ, 1501 MatGetMaps_Petsc}; 1502 1503 /* ----------------------------------------------------------------------------------------*/ 1504 1505 EXTERN_C_BEGIN 1506 #undef __FUNC__ 1507 #define __FUNC__ "MatStoreValues_MPIAIJ" 1508 int MatStoreValues_MPIAIJ(Mat mat) 1509 { 1510 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1511 int ierr; 1512 1513 PetscFunctionBegin; 1514 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 1515 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 1516 PetscFunctionReturn(0); 1517 } 1518 EXTERN_C_END 1519 1520 EXTERN_C_BEGIN 1521 #undef __FUNC__ 1522 #define __FUNC__ "MatRetrieveValues_MPIAIJ" 1523 int MatRetrieveValues_MPIAIJ(Mat mat) 1524 { 1525 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1526 int ierr; 1527 1528 PetscFunctionBegin; 1529 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 1530 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 1531 PetscFunctionReturn(0); 1532 } 1533 EXTERN_C_END 1534 1535 #include "petscpc.h" 1536 EXTERN_C_BEGIN 1537 EXTERN int MatGetDiagonalBlock_MPIAIJ(Mat,PetscTruth *,MatReuse,Mat *); 1538 EXTERN_C_END 1539 1540 EXTERN int MatUseTFS_MPIAIJ(Mat); 1541 1542 EXTERN_C_BEGIN 1543 #undef __FUNC__ 1544 #define __FUNC__ "MatCreate_MPIAIJ" 1545 int MatCreate_MPIAIJ(Mat B) 1546 { 1547 Mat_MPIAIJ *b; 1548 int ierr,i,size; 1549 PetscTruth flg; 1550 1551 PetscFunctionBegin; 1552 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 1553 1554 ierr = PetscNew(Mat_MPIAIJ,&b);CHKERRQ(ierr); 1555 B->data = (void*)b; 1556 ierr = PetscMemzero(b,sizeof(Mat_MPIAIJ));CHKERRQ(ierr); 1557 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1558 B->factor = 0; 1559 B->assembled = PETSC_FALSE; 1560 B->mapping = 0; 1561 1562 B->insertmode = NOT_SET_VALUES; 1563 b->size = size; 1564 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1565 1566 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1567 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1568 1569 /* the information in the maps duplicates the information computed below, eventually 1570 we should remove the duplicate information that is not contained in the maps */ 1571 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1572 ierr = MapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 1573 1574 /* build local table of row and column ownerships */ 1575 ierr = PetscMalloc(2*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1576 PetscLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIAIJ)); 1577 b->cowners = b->rowners + b->size + 2; 1578 ierr = MPI_Allgather(&B->m,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1579 b->rowners[0] = 0; 1580 for (i=2; i<=b->size; i++) { 1581 b->rowners[i] += b->rowners[i-1]; 1582 } 1583 b->rstart = b->rowners[b->rank]; 1584 b->rend = b->rowners[b->rank+1]; 1585 ierr = MPI_Allgather(&B->n,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1586 b->cowners[0] = 0; 1587 for (i=2; i<=b->size; i++) { 1588 b->cowners[i] += b->cowners[i-1]; 1589 } 1590 b->cstart = b->cowners[b->rank]; 1591 b->cend = b->cowners[b->rank+1]; 1592 1593 /* build cache for off array entries formed */ 1594 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1595 b->donotstash = PETSC_FALSE; 1596 b->colmap = 0; 1597 b->garray = 0; 1598 b->roworiented = PETSC_TRUE; 1599 1600 /* stuff used for matrix vector multiply */ 1601 b->lvec = PETSC_NULL; 1602 b->Mvctx = PETSC_NULL; 1603 1604 /* stuff for MatGetRow() */ 1605 b->rowindices = 0; 1606 b->rowvalues = 0; 1607 b->getrowactive = PETSC_FALSE; 1608 1609 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_mpiaij_tfs",&flg);CHKERRQ(ierr); 1610 if (flg) { ierr = MatUseTFS_MPIAIJ(B);CHKERRQ(ierr); } 1611 1612 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1613 "MatStoreValues_MPIAIJ", 1614 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 1615 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1616 "MatRetrieveValues_MPIAIJ", 1617 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 1618 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1619 "MatGetDiagonalBlock_MPIAIJ", 1620 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 1621 PetscFunctionReturn(0); 1622 } 1623 EXTERN_C_END 1624 1625 #undef __FUNC__ 1626 #define __FUNC__ "MatDuplicate_MPIAIJ" 1627 int MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1628 { 1629 Mat mat; 1630 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 1631 int ierr; 1632 1633 PetscFunctionBegin; 1634 *newmat = 0; 1635 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1636 ierr = MatSetType(mat,MATMPIAIJ);CHKERRQ(ierr); 1637 a = (Mat_MPIAIJ*)mat->data; 1638 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1639 mat->factor = matin->factor; 1640 mat->assembled = PETSC_TRUE; 1641 mat->insertmode = NOT_SET_VALUES; 1642 mat->preallocated = PETSC_TRUE; 1643 1644 a->rstart = oldmat->rstart; 1645 a->rend = oldmat->rend; 1646 a->cstart = oldmat->cstart; 1647 a->cend = oldmat->cend; 1648 a->size = oldmat->size; 1649 a->rank = oldmat->rank; 1650 a->donotstash = oldmat->donotstash; 1651 a->roworiented = oldmat->roworiented; 1652 a->rowindices = 0; 1653 a->rowvalues = 0; 1654 a->getrowactive = PETSC_FALSE; 1655 1656 ierr = PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1657 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1658 if (oldmat->colmap) { 1659 #if defined (PETSC_USE_CTABLE) 1660 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1661 #else 1662 ierr = PetscMalloc((mat->N)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1663 PetscLogObjectMemory(mat,(mat->N)*sizeof(int)); 1664 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->N)*sizeof(int));CHKERRQ(ierr); 1665 #endif 1666 } else a->colmap = 0; 1667 if (oldmat->garray) { 1668 int len; 1669 len = oldmat->B->n; 1670 ierr = PetscMalloc((len+1)*sizeof(int),&a->garray);CHKERRQ(ierr); 1671 PetscLogObjectMemory(mat,len*sizeof(int)); 1672 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); } 1673 } else a->garray = 0; 1674 1675 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1676 PetscLogObjectParent(mat,a->lvec); 1677 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1678 PetscLogObjectParent(mat,a->Mvctx); 1679 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1680 PetscLogObjectParent(mat,a->A); 1681 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1682 PetscLogObjectParent(mat,a->B); 1683 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 1684 *newmat = mat; 1685 PetscFunctionReturn(0); 1686 } 1687 1688 #include "petscsys.h" 1689 1690 EXTERN_C_BEGIN 1691 #undef __FUNC__ 1692 #define __FUNC__ "MatLoad_MPIAIJ" 1693 int MatLoad_MPIAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1694 { 1695 Mat A; 1696 Scalar *vals,*svals; 1697 MPI_Comm comm = ((PetscObject)viewer)->comm; 1698 MPI_Status status; 1699 int i,nz,ierr,j,rstart,rend,fd; 1700 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,maxnz,*cols; 1701 int *ourlens,*sndcounts = 0,*procsnz = 0,*offlens,jj,*mycols,*smycols; 1702 int tag = ((PetscObject)viewer)->tag,cend,cstart,n; 1703 1704 PetscFunctionBegin; 1705 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1706 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1707 if (!rank) { 1708 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1709 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1710 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1711 if (header[3] < 0) { 1712 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix in special format on disk, cannot load as MPIAIJ"); 1713 } 1714 } 1715 1716 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 1717 M = header[1]; N = header[2]; 1718 /* determine ownership of all rows */ 1719 m = M/size + ((M % size) > rank); 1720 ierr = PetscMalloc((size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 1721 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1722 rowners[0] = 0; 1723 for (i=2; i<=size; i++) { 1724 rowners[i] += rowners[i-1]; 1725 } 1726 rstart = rowners[rank]; 1727 rend = rowners[rank+1]; 1728 1729 /* distribute row lengths to all processors */ 1730 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&ourlens);CHKERRQ(ierr); 1731 offlens = ourlens + (rend-rstart); 1732 if (!rank) { 1733 ierr = PetscMalloc(M*sizeof(int),&rowlengths);CHKERRQ(ierr); 1734 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1735 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 1736 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1737 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1738 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1739 } else { 1740 ierr = MPI_Scatterv(0,0,0,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1741 } 1742 1743 if (!rank) { 1744 /* calculate the number of nonzeros on each processor */ 1745 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 1746 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 1747 for (i=0; i<size; i++) { 1748 for (j=rowners[i]; j< rowners[i+1]; j++) { 1749 procsnz[i] += rowlengths[j]; 1750 } 1751 } 1752 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1753 1754 /* determine max buffer needed and allocate it */ 1755 maxnz = 0; 1756 for (i=0; i<size; i++) { 1757 maxnz = PetscMax(maxnz,procsnz[i]); 1758 } 1759 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 1760 1761 /* read in my part of the matrix column indices */ 1762 nz = procsnz[0]; 1763 ierr = PetscMalloc(nz*sizeof(int),&mycols);CHKERRQ(ierr); 1764 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1765 1766 /* read in every one elses and ship off */ 1767 for (i=1; i<size; i++) { 1768 nz = procsnz[i]; 1769 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1770 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 1771 } 1772 ierr = PetscFree(cols);CHKERRQ(ierr); 1773 } else { 1774 /* determine buffer space needed for message */ 1775 nz = 0; 1776 for (i=0; i<m; i++) { 1777 nz += ourlens[i]; 1778 } 1779 ierr = PetscMalloc((nz+1)*sizeof(int),&mycols);CHKERRQ(ierr); 1780 1781 /* receive message of column indices*/ 1782 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 1783 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 1784 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1785 } 1786 1787 /* determine column ownership if matrix is not square */ 1788 if (N != M) { 1789 n = N/size + ((N % size) > rank); 1790 ierr = MPI_Scan(&n,&cend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1791 cstart = cend - n; 1792 } else { 1793 cstart = rstart; 1794 cend = rend; 1795 n = cend - cstart; 1796 } 1797 1798 /* loop over local rows, determining number of off diagonal entries */ 1799 ierr = PetscMemzero(offlens,m*sizeof(int));CHKERRQ(ierr); 1800 jj = 0; 1801 for (i=0; i<m; i++) { 1802 for (j=0; j<ourlens[i]; j++) { 1803 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 1804 jj++; 1805 } 1806 } 1807 1808 /* create our matrix */ 1809 for (i=0; i<m; i++) { 1810 ourlens[i] -= offlens[i]; 1811 } 1812 ierr = MatCreateMPIAIJ(comm,m,n,M,N,0,ourlens,0,offlens,newmat);CHKERRQ(ierr); 1813 A = *newmat; 1814 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 1815 for (i=0; i<m; i++) { 1816 ourlens[i] += offlens[i]; 1817 } 1818 1819 if (!rank) { 1820 ierr = PetscMalloc(maxnz*sizeof(Scalar),&vals);CHKERRQ(ierr); 1821 1822 /* read in my part of the matrix numerical values */ 1823 nz = procsnz[0]; 1824 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1825 1826 /* insert into matrix */ 1827 jj = rstart; 1828 smycols = mycols; 1829 svals = vals; 1830 for (i=0; i<m; i++) { 1831 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1832 smycols += ourlens[i]; 1833 svals += ourlens[i]; 1834 jj++; 1835 } 1836 1837 /* read in other processors and ship out */ 1838 for (i=1; i<size; i++) { 1839 nz = procsnz[i]; 1840 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1841 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 1842 } 1843 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1844 } else { 1845 /* receive numeric values */ 1846 ierr = PetscMalloc((nz+1)*sizeof(Scalar),&vals);CHKERRQ(ierr); 1847 1848 /* receive message of values*/ 1849 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 1850 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1851 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1852 1853 /* insert into matrix */ 1854 jj = rstart; 1855 smycols = mycols; 1856 svals = vals; 1857 for (i=0; i<m; i++) { 1858 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1859 smycols += ourlens[i]; 1860 svals += ourlens[i]; 1861 jj++; 1862 } 1863 } 1864 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1865 ierr = PetscFree(vals);CHKERRQ(ierr); 1866 ierr = PetscFree(mycols);CHKERRQ(ierr); 1867 ierr = PetscFree(rowners);CHKERRQ(ierr); 1868 1869 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1870 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1871 PetscFunctionReturn(0); 1872 } 1873 EXTERN_C_END 1874 1875 #undef __FUNC__ 1876 #define __FUNC__ "MatGetSubMatrix_MPIAIJ" 1877 /* 1878 Not great since it makes two copies of the submatrix, first an SeqAIJ 1879 in local and then by concatenating the local matrices the end result. 1880 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 1881 */ 1882 int MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,int csize,MatReuse call,Mat *newmat) 1883 { 1884 int ierr,i,m,n,rstart,row,rend,nz,*cwork,size,rank,j; 1885 int *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend; 1886 Mat *local,M,Mreuse; 1887 Scalar *vwork,*aa; 1888 MPI_Comm comm = mat->comm; 1889 Mat_SeqAIJ *aij; 1890 1891 1892 PetscFunctionBegin; 1893 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1894 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1895 1896 if (call == MAT_REUSE_MATRIX) { 1897 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 1898 if (!Mreuse) SETERRQ(1,"Submatrix passed in was not used before, cannot reuse"); 1899 local = &Mreuse; 1900 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 1901 } else { 1902 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 1903 Mreuse = *local; 1904 ierr = PetscFree(local);CHKERRQ(ierr); 1905 } 1906 1907 /* 1908 m - number of local rows 1909 n - number of columns (same on all processors) 1910 rstart - first row in new global matrix generated 1911 */ 1912 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 1913 if (call == MAT_INITIAL_MATRIX) { 1914 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1915 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1916 ii = aij->i; 1917 jj = aij->j; 1918 1919 /* 1920 Determine the number of non-zeros in the diagonal and off-diagonal 1921 portions of the matrix in order to do correct preallocation 1922 */ 1923 1924 /* first get start and end of "diagonal" columns */ 1925 if (csize == PETSC_DECIDE) { 1926 nlocal = n/size + ((n % size) > rank); 1927 } else { 1928 nlocal = csize; 1929 } 1930 ierr = MPI_Scan(&nlocal,&rend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1931 rstart = rend - nlocal; 1932 if (rank == size - 1 && rend != n) { 1933 SETERRQ(1,"Local column sizes do not add up to total number of columns"); 1934 } 1935 1936 /* next, compute all the lengths */ 1937 ierr = PetscMalloc((2*m+1)*sizeof(int),&dlens);CHKERRQ(ierr); 1938 olens = dlens + m; 1939 for (i=0; i<m; i++) { 1940 jend = ii[i+1] - ii[i]; 1941 olen = 0; 1942 dlen = 0; 1943 for (j=0; j<jend; j++) { 1944 if (*jj < rstart || *jj >= rend) olen++; 1945 else dlen++; 1946 jj++; 1947 } 1948 olens[i] = olen; 1949 dlens[i] = dlen; 1950 } 1951 ierr = MatCreateMPIAIJ(comm,m,nlocal,PETSC_DECIDE,n,0,dlens,0,olens,&M);CHKERRQ(ierr); 1952 ierr = PetscFree(dlens);CHKERRQ(ierr); 1953 } else { 1954 int ml,nl; 1955 1956 M = *newmat; 1957 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 1958 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 1959 ierr = MatZeroEntries(M);CHKERRQ(ierr); 1960 /* 1961 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 1962 rather than the slower MatSetValues(). 1963 */ 1964 M->was_assembled = PETSC_TRUE; 1965 M->assembled = PETSC_FALSE; 1966 } 1967 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 1968 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1969 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1970 ii = aij->i; 1971 jj = aij->j; 1972 aa = aij->a; 1973 for (i=0; i<m; i++) { 1974 row = rstart + i; 1975 nz = ii[i+1] - ii[i]; 1976 cwork = jj; jj += nz; 1977 vwork = aa; aa += nz; 1978 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 1979 } 1980 1981 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1982 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1983 *newmat = M; 1984 1985 /* save submatrix used in processor for next request */ 1986 if (call == MAT_INITIAL_MATRIX) { 1987 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 1988 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 1989 } 1990 1991 PetscFunctionReturn(0); 1992 } 1993 1994 #undef __FUNC__ 1995 #define __FUNC__ "MatMPIAIJSetPreallocation" 1996 /*@C 1997 MatMPIAIJSetPreallocation - Creates a sparse parallel matrix in AIJ format 1998 (the default parallel PETSc format). For good matrix assembly performance 1999 the user should preallocate the matrix storage by setting the parameters 2000 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2001 performance can be increased by more than a factor of 50. 2002 2003 Collective on MPI_Comm 2004 2005 Input Parameters: 2006 + A - the matrix 2007 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2008 (same value is used for all local rows) 2009 . d_nnz - array containing the number of nonzeros in the various rows of the 2010 DIAGONAL portion of the local submatrix (possibly different for each row) 2011 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2012 The size of this array is equal to the number of local rows, i.e 'm'. 2013 You must leave room for the diagonal entry even if it is zero. 2014 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2015 submatrix (same value is used for all local rows). 2016 - o_nnz - array containing the number of nonzeros in the various rows of the 2017 OFF-DIAGONAL portion of the local submatrix (possibly different for 2018 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2019 structure. The size of this array is equal to the number 2020 of local rows, i.e 'm'. 2021 2022 The AIJ format (also called the Yale sparse matrix format or 2023 compressed row storage), is fully compatible with standard Fortran 77 2024 storage. That is, the stored row and column indices can begin at 2025 either one (as in Fortran) or zero. See the users manual for details. 2026 2027 The user MUST specify either the local or global matrix dimensions 2028 (possibly both). 2029 2030 The parallel matrix is partitioned such that the first m0 rows belong to 2031 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2032 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2033 2034 The DIAGONAL portion of the local submatrix of a processor can be defined 2035 as the submatrix which is obtained by extraction the part corresponding 2036 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2037 first row that belongs to the processor, and r2 is the last row belonging 2038 to the this processor. This is a square mxm matrix. The remaining portion 2039 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2040 2041 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2042 2043 By default, this format uses inodes (identical nodes) when possible. 2044 We search for consecutive rows with the same nonzero structure, thereby 2045 reusing matrix information to achieve increased efficiency. 2046 2047 Options Database Keys: 2048 + -mat_aij_no_inode - Do not use inodes 2049 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2050 - -mat_aij_oneindex - Internally use indexing starting at 1 2051 rather than 0. Note that when calling MatSetValues(), 2052 the user still MUST index entries starting at 0! 2053 2054 Example usage: 2055 2056 Consider the following 8x8 matrix with 34 non-zero values, that is 2057 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2058 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2059 as follows: 2060 2061 .vb 2062 1 2 0 | 0 3 0 | 0 4 2063 Proc0 0 5 6 | 7 0 0 | 8 0 2064 9 0 10 | 11 0 0 | 12 0 2065 ------------------------------------- 2066 13 0 14 | 15 16 17 | 0 0 2067 Proc1 0 18 0 | 19 20 21 | 0 0 2068 0 0 0 | 22 23 0 | 24 0 2069 ------------------------------------- 2070 Proc2 25 26 27 | 0 0 28 | 29 0 2071 30 0 0 | 31 32 33 | 0 34 2072 .ve 2073 2074 This can be represented as a collection of submatrices as: 2075 2076 .vb 2077 A B C 2078 D E F 2079 G H I 2080 .ve 2081 2082 Where the submatrices A,B,C are owned by proc0, D,E,F are 2083 owned by proc1, G,H,I are owned by proc2. 2084 2085 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2086 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2087 The 'M','N' parameters are 8,8, and have the same values on all procs. 2088 2089 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2090 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2091 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2092 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2093 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2094 matrix, ans [DF] as another SeqAIJ matrix. 2095 2096 When d_nz, o_nz parameters are specified, d_nz storage elements are 2097 allocated for every row of the local diagonal submatrix, and o_nz 2098 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2099 One way to choose d_nz and o_nz is to use the max nonzerors per local 2100 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2101 In this case, the values of d_nz,o_nz are: 2102 .vb 2103 proc0 : dnz = 2, o_nz = 2 2104 proc1 : dnz = 3, o_nz = 2 2105 proc2 : dnz = 1, o_nz = 4 2106 .ve 2107 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2108 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2109 for proc3. i.e we are using 12+15+10=37 storage locations to store 2110 34 values. 2111 2112 When d_nnz, o_nnz parameters are specified, the storage is specified 2113 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2114 In the above case the values for d_nnz,o_nnz are: 2115 .vb 2116 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2117 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2118 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2119 .ve 2120 Here the space allocated is sum of all the above values i.e 34, and 2121 hence pre-allocation is perfect. 2122 2123 Level: intermediate 2124 2125 .keywords: matrix, aij, compressed row, sparse, parallel 2126 2127 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2128 @*/ 2129 int MatMPIAIJSetPreallocation(Mat B,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2130 { 2131 Mat_MPIAIJ *b; 2132 int ierr,i; 2133 PetscTruth flg2; 2134 2135 PetscFunctionBegin; 2136 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg2);CHKERRQ(ierr); 2137 if (!flg2) PetscFunctionReturn(0); 2138 B->preallocated = PETSC_TRUE; 2139 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2140 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2141 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2142 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2143 if (d_nnz) { 2144 for (i=0; i<B->m; i++) { 2145 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]); 2146 } 2147 } 2148 if (o_nnz) { 2149 for (i=0; i<B->m; i++) { 2150 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]); 2151 } 2152 } 2153 b = (Mat_MPIAIJ*)B->data; 2154 2155 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2156 PetscLogObjectParent(B,b->A); 2157 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2158 PetscLogObjectParent(B,b->B); 2159 2160 PetscFunctionReturn(0); 2161 } 2162 2163 #undef __FUNC__ 2164 #define __FUNC__ "MatCreateMPIAIJ" 2165 /*@C 2166 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 2167 (the default parallel PETSc format). For good matrix assembly performance 2168 the user should preallocate the matrix storage by setting the parameters 2169 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2170 performance can be increased by more than a factor of 50. 2171 2172 Collective on MPI_Comm 2173 2174 Input Parameters: 2175 + comm - MPI communicator 2176 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2177 This value should be the same as the local size used in creating the 2178 y vector for the matrix-vector product y = Ax. 2179 . n - This value should be the same as the local size used in creating the 2180 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2181 calculated if N is given) For square matrices n is almost always m. 2182 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2183 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2184 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2185 (same value is used for all local rows) 2186 . d_nnz - array containing the number of nonzeros in the various rows of the 2187 DIAGONAL portion of the local submatrix (possibly different for each row) 2188 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2189 The size of this array is equal to the number of local rows, i.e 'm'. 2190 You must leave room for the diagonal entry even if it is zero. 2191 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2192 submatrix (same value is used for all local rows). 2193 - o_nnz - array containing the number of nonzeros in the various rows of the 2194 OFF-DIAGONAL portion of the local submatrix (possibly different for 2195 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2196 structure. The size of this array is equal to the number 2197 of local rows, i.e 'm'. 2198 2199 Output Parameter: 2200 . A - the matrix 2201 2202 Notes: 2203 m,n,M,N parameters specify the size of the matrix, and its partitioning across 2204 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 2205 storage requirements for this matrix. 2206 2207 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 2208 processor than it must be used on all processors that share the object for 2209 that argument. 2210 2211 The AIJ format (also called the Yale sparse matrix format or 2212 compressed row storage), is fully compatible with standard Fortran 77 2213 storage. That is, the stored row and column indices can begin at 2214 either one (as in Fortran) or zero. See the users manual for details. 2215 2216 The user MUST specify either the local or global matrix dimensions 2217 (possibly both). 2218 2219 The parallel matrix is partitioned such that the first m0 rows belong to 2220 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2221 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2222 2223 The DIAGONAL portion of the local submatrix of a processor can be defined 2224 as the submatrix which is obtained by extraction the part corresponding 2225 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2226 first row that belongs to the processor, and r2 is the last row belonging 2227 to the this processor. This is a square mxm matrix. The remaining portion 2228 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2229 2230 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2231 2232 By default, this format uses inodes (identical nodes) when possible. 2233 We search for consecutive rows with the same nonzero structure, thereby 2234 reusing matrix information to achieve increased efficiency. 2235 2236 Options Database Keys: 2237 + -mat_aij_no_inode - Do not use inodes 2238 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2239 - -mat_aij_oneindex - Internally use indexing starting at 1 2240 rather than 0. Note that when calling MatSetValues(), 2241 the user still MUST index entries starting at 0! 2242 2243 2244 Example usage: 2245 2246 Consider the following 8x8 matrix with 34 non-zero values, that is 2247 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2248 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2249 as follows: 2250 2251 .vb 2252 1 2 0 | 0 3 0 | 0 4 2253 Proc0 0 5 6 | 7 0 0 | 8 0 2254 9 0 10 | 11 0 0 | 12 0 2255 ------------------------------------- 2256 13 0 14 | 15 16 17 | 0 0 2257 Proc1 0 18 0 | 19 20 21 | 0 0 2258 0 0 0 | 22 23 0 | 24 0 2259 ------------------------------------- 2260 Proc2 25 26 27 | 0 0 28 | 29 0 2261 30 0 0 | 31 32 33 | 0 34 2262 .ve 2263 2264 This can be represented as a collection of submatrices as: 2265 2266 .vb 2267 A B C 2268 D E F 2269 G H I 2270 .ve 2271 2272 Where the submatrices A,B,C are owned by proc0, D,E,F are 2273 owned by proc1, G,H,I are owned by proc2. 2274 2275 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2276 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2277 The 'M','N' parameters are 8,8, and have the same values on all procs. 2278 2279 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2280 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2281 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2282 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2283 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2284 matrix, ans [DF] as another SeqAIJ matrix. 2285 2286 When d_nz, o_nz parameters are specified, d_nz storage elements are 2287 allocated for every row of the local diagonal submatrix, and o_nz 2288 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2289 One way to choose d_nz and o_nz is to use the max nonzerors per local 2290 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2291 In this case, the values of d_nz,o_nz are: 2292 .vb 2293 proc0 : dnz = 2, o_nz = 2 2294 proc1 : dnz = 3, o_nz = 2 2295 proc2 : dnz = 1, o_nz = 4 2296 .ve 2297 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2298 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2299 for proc3. i.e we are using 12+15+10=37 storage locations to store 2300 34 values. 2301 2302 When d_nnz, o_nnz parameters are specified, the storage is specified 2303 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2304 In the above case the values for d_nnz,o_nnz are: 2305 .vb 2306 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2307 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2308 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2309 .ve 2310 Here the space allocated is sum of all the above values i.e 34, and 2311 hence pre-allocation is perfect. 2312 2313 Level: intermediate 2314 2315 .keywords: matrix, aij, compressed row, sparse, parallel 2316 2317 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2318 @*/ 2319 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) 2320 { 2321 int ierr,size; 2322 2323 PetscFunctionBegin; 2324 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2325 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2326 if (size > 1) { 2327 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 2328 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2329 } else { 2330 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2331 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 2332 } 2333 PetscFunctionReturn(0); 2334 } 2335 2336 #undef __FUNC__ 2337 #define __FUNC__ "MatMPIAIJGetSeqAIJ" 2338 int MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2339 { 2340 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 2341 PetscFunctionBegin; 2342 *Ad = a->A; 2343 *Ao = a->B; 2344 *colmap = a->garray; 2345 PetscFunctionReturn(0); 2346 } 2347