1 /*$Id: mpiaij.c,v 1.330 2001/03/22 20:29:56 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 MatUseXT_MPIAIJ(Mat); 1541 EXTERN int MatUseXYT_MPIAIJ(Mat); 1542 1543 EXTERN_C_BEGIN 1544 #undef __FUNC__ 1545 #define __FUNC__ "MatCreate_MPIAIJ" 1546 int MatCreate_MPIAIJ(Mat B) 1547 { 1548 Mat_MPIAIJ *b; 1549 int ierr,i,size; 1550 PetscTruth flg; 1551 1552 PetscFunctionBegin; 1553 ierr = MPI_Comm_size(B->comm,&size);CHKERRQ(ierr); 1554 1555 ierr = PetscNew(Mat_MPIAIJ,&b);CHKERRQ(ierr); 1556 B->data = (void*)b; 1557 ierr = PetscMemzero(b,sizeof(Mat_MPIAIJ));CHKERRQ(ierr); 1558 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1559 B->factor = 0; 1560 B->assembled = PETSC_FALSE; 1561 B->mapping = 0; 1562 1563 B->insertmode = NOT_SET_VALUES; 1564 b->size = size; 1565 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1566 1567 ierr = PetscSplitOwnership(B->comm,&B->m,&B->M);CHKERRQ(ierr); 1568 ierr = PetscSplitOwnership(B->comm,&B->n,&B->N);CHKERRQ(ierr); 1569 1570 /* the information in the maps duplicates the information computed below, eventually 1571 we should remove the duplicate information that is not contained in the maps */ 1572 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1573 ierr = MapCreateMPI(B->comm,B->n,B->N,&B->cmap);CHKERRQ(ierr); 1574 1575 /* build local table of row and column ownerships */ 1576 ierr = PetscMalloc(2*(b->size+2)*sizeof(int),&b->rowners);CHKERRQ(ierr); 1577 PetscLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIAIJ)); 1578 b->cowners = b->rowners + b->size + 2; 1579 ierr = MPI_Allgather(&B->m,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1580 b->rowners[0] = 0; 1581 for (i=2; i<=b->size; i++) { 1582 b->rowners[i] += b->rowners[i-1]; 1583 } 1584 b->rstart = b->rowners[b->rank]; 1585 b->rend = b->rowners[b->rank+1]; 1586 ierr = MPI_Allgather(&B->n,1,MPI_INT,b->cowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1587 b->cowners[0] = 0; 1588 for (i=2; i<=b->size; i++) { 1589 b->cowners[i] += b->cowners[i-1]; 1590 } 1591 b->cstart = b->cowners[b->rank]; 1592 b->cend = b->cowners[b->rank+1]; 1593 1594 /* build cache for off array entries formed */ 1595 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1596 b->donotstash = PETSC_FALSE; 1597 b->colmap = 0; 1598 b->garray = 0; 1599 b->roworiented = PETSC_TRUE; 1600 1601 /* stuff used for matrix vector multiply */ 1602 b->lvec = PETSC_NULL; 1603 b->Mvctx = PETSC_NULL; 1604 1605 /* stuff for MatGetRow() */ 1606 b->rowindices = 0; 1607 b->rowvalues = 0; 1608 b->getrowactive = PETSC_FALSE; 1609 1610 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_mpiaij_xxt",&flg);CHKERRQ(ierr); 1611 if (flg) { ierr = MatUseXXT_MPIAIJ(B);CHKERRQ(ierr); } 1612 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_mpiaij_xyt",&flg);CHKERRQ(ierr); 1613 if (flg) { ierr = MatUseXYT_MPIAIJ(B);CHKERRQ(ierr); } 1614 1615 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1616 "MatStoreValues_MPIAIJ", 1617 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 1618 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1619 "MatRetrieveValues_MPIAIJ", 1620 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 1621 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1622 "MatGetDiagonalBlock_MPIAIJ", 1623 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 1624 PetscFunctionReturn(0); 1625 } 1626 EXTERN_C_END 1627 1628 #undef __FUNC__ 1629 #define __FUNC__ "MatDuplicate_MPIAIJ" 1630 int MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1631 { 1632 Mat mat; 1633 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 1634 int ierr; 1635 1636 PetscFunctionBegin; 1637 *newmat = 0; 1638 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1639 ierr = MatSetType(mat,MATMPIAIJ);CHKERRQ(ierr); 1640 a = (Mat_MPIAIJ*)mat->data; 1641 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1642 mat->factor = matin->factor; 1643 mat->assembled = PETSC_TRUE; 1644 mat->insertmode = NOT_SET_VALUES; 1645 mat->preallocated = PETSC_TRUE; 1646 1647 a->rstart = oldmat->rstart; 1648 a->rend = oldmat->rend; 1649 a->cstart = oldmat->cstart; 1650 a->cend = oldmat->cend; 1651 a->size = oldmat->size; 1652 a->rank = oldmat->rank; 1653 a->donotstash = oldmat->donotstash; 1654 a->roworiented = oldmat->roworiented; 1655 a->rowindices = 0; 1656 a->rowvalues = 0; 1657 a->getrowactive = PETSC_FALSE; 1658 1659 ierr = PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1660 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1661 if (oldmat->colmap) { 1662 #if defined (PETSC_USE_CTABLE) 1663 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1664 #else 1665 ierr = PetscMalloc((mat->N)*sizeof(int),&a->colmap);CHKERRQ(ierr); 1666 PetscLogObjectMemory(mat,(mat->N)*sizeof(int)); 1667 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->N)*sizeof(int));CHKERRQ(ierr); 1668 #endif 1669 } else a->colmap = 0; 1670 if (oldmat->garray) { 1671 int len; 1672 len = oldmat->B->n; 1673 ierr = PetscMalloc((len+1)*sizeof(int),&a->garray);CHKERRQ(ierr); 1674 PetscLogObjectMemory(mat,len*sizeof(int)); 1675 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); } 1676 } else a->garray = 0; 1677 1678 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1679 PetscLogObjectParent(mat,a->lvec); 1680 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1681 PetscLogObjectParent(mat,a->Mvctx); 1682 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1683 PetscLogObjectParent(mat,a->A); 1684 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1685 PetscLogObjectParent(mat,a->B); 1686 ierr = PetscFListDuplicate(matin->qlist,&mat->qlist);CHKERRQ(ierr); 1687 *newmat = mat; 1688 PetscFunctionReturn(0); 1689 } 1690 1691 #include "petscsys.h" 1692 1693 EXTERN_C_BEGIN 1694 #undef __FUNC__ 1695 #define __FUNC__ "MatLoad_MPIAIJ" 1696 int MatLoad_MPIAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1697 { 1698 Mat A; 1699 Scalar *vals,*svals; 1700 MPI_Comm comm = ((PetscObject)viewer)->comm; 1701 MPI_Status status; 1702 int i,nz,ierr,j,rstart,rend,fd; 1703 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,maxnz,*cols; 1704 int *ourlens,*sndcounts = 0,*procsnz = 0,*offlens,jj,*mycols,*smycols; 1705 int tag = ((PetscObject)viewer)->tag,cend,cstart,n; 1706 1707 PetscFunctionBegin; 1708 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1709 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1710 if (!rank) { 1711 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1712 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1713 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1714 if (header[3] < 0) { 1715 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix in special format on disk, cannot load as MPIAIJ"); 1716 } 1717 } 1718 1719 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 1720 M = header[1]; N = header[2]; 1721 /* determine ownership of all rows */ 1722 m = M/size + ((M % size) > rank); 1723 ierr = PetscMalloc((size+2)*sizeof(int),&rowners);CHKERRQ(ierr); 1724 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1725 rowners[0] = 0; 1726 for (i=2; i<=size; i++) { 1727 rowners[i] += rowners[i-1]; 1728 } 1729 rstart = rowners[rank]; 1730 rend = rowners[rank+1]; 1731 1732 /* distribute row lengths to all processors */ 1733 ierr = PetscMalloc(2*(rend-rstart+1)*sizeof(int),&ourlens);CHKERRQ(ierr); 1734 offlens = ourlens + (rend-rstart); 1735 if (!rank) { 1736 ierr = PetscMalloc(M*sizeof(int),&rowlengths);CHKERRQ(ierr); 1737 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1738 ierr = PetscMalloc(size*sizeof(int),&sndcounts);CHKERRQ(ierr); 1739 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1740 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1741 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1742 } else { 1743 ierr = MPI_Scatterv(0,0,0,MPI_INT,ourlens,rend-rstart,MPI_INT,0,comm);CHKERRQ(ierr); 1744 } 1745 1746 if (!rank) { 1747 /* calculate the number of nonzeros on each processor */ 1748 ierr = PetscMalloc(size*sizeof(int),&procsnz);CHKERRQ(ierr); 1749 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 1750 for (i=0; i<size; i++) { 1751 for (j=rowners[i]; j< rowners[i+1]; j++) { 1752 procsnz[i] += rowlengths[j]; 1753 } 1754 } 1755 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1756 1757 /* determine max buffer needed and allocate it */ 1758 maxnz = 0; 1759 for (i=0; i<size; i++) { 1760 maxnz = PetscMax(maxnz,procsnz[i]); 1761 } 1762 ierr = PetscMalloc(maxnz*sizeof(int),&cols);CHKERRQ(ierr); 1763 1764 /* read in my part of the matrix column indices */ 1765 nz = procsnz[0]; 1766 ierr = PetscMalloc(nz*sizeof(int),&mycols);CHKERRQ(ierr); 1767 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1768 1769 /* read in every one elses and ship off */ 1770 for (i=1; i<size; i++) { 1771 nz = procsnz[i]; 1772 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1773 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 1774 } 1775 ierr = PetscFree(cols);CHKERRQ(ierr); 1776 } else { 1777 /* determine buffer space needed for message */ 1778 nz = 0; 1779 for (i=0; i<m; i++) { 1780 nz += ourlens[i]; 1781 } 1782 ierr = PetscMalloc((nz+1)*sizeof(int),&mycols);CHKERRQ(ierr); 1783 1784 /* receive message of column indices*/ 1785 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 1786 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 1787 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1788 } 1789 1790 /* determine column ownership if matrix is not square */ 1791 if (N != M) { 1792 n = N/size + ((N % size) > rank); 1793 ierr = MPI_Scan(&n,&cend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1794 cstart = cend - n; 1795 } else { 1796 cstart = rstart; 1797 cend = rend; 1798 n = cend - cstart; 1799 } 1800 1801 /* loop over local rows, determining number of off diagonal entries */ 1802 ierr = PetscMemzero(offlens,m*sizeof(int));CHKERRQ(ierr); 1803 jj = 0; 1804 for (i=0; i<m; i++) { 1805 for (j=0; j<ourlens[i]; j++) { 1806 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 1807 jj++; 1808 } 1809 } 1810 1811 /* create our matrix */ 1812 for (i=0; i<m; i++) { 1813 ourlens[i] -= offlens[i]; 1814 } 1815 ierr = MatCreateMPIAIJ(comm,m,n,M,N,0,ourlens,0,offlens,newmat);CHKERRQ(ierr); 1816 A = *newmat; 1817 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 1818 for (i=0; i<m; i++) { 1819 ourlens[i] += offlens[i]; 1820 } 1821 1822 if (!rank) { 1823 ierr = PetscMalloc(maxnz*sizeof(Scalar),&vals);CHKERRQ(ierr); 1824 1825 /* read in my part of the matrix numerical values */ 1826 nz = procsnz[0]; 1827 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1828 1829 /* insert into matrix */ 1830 jj = rstart; 1831 smycols = mycols; 1832 svals = vals; 1833 for (i=0; i<m; i++) { 1834 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1835 smycols += ourlens[i]; 1836 svals += ourlens[i]; 1837 jj++; 1838 } 1839 1840 /* read in other processors and ship out */ 1841 for (i=1; i<size; i++) { 1842 nz = procsnz[i]; 1843 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1844 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 1845 } 1846 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1847 } else { 1848 /* receive numeric values */ 1849 ierr = PetscMalloc((nz+1)*sizeof(Scalar),&vals);CHKERRQ(ierr); 1850 1851 /* receive message of values*/ 1852 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 1853 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1854 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1855 1856 /* insert into matrix */ 1857 jj = rstart; 1858 smycols = mycols; 1859 svals = vals; 1860 for (i=0; i<m; i++) { 1861 ierr = MatSetValues(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1862 smycols += ourlens[i]; 1863 svals += ourlens[i]; 1864 jj++; 1865 } 1866 } 1867 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1868 ierr = PetscFree(vals);CHKERRQ(ierr); 1869 ierr = PetscFree(mycols);CHKERRQ(ierr); 1870 ierr = PetscFree(rowners);CHKERRQ(ierr); 1871 1872 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1873 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1874 PetscFunctionReturn(0); 1875 } 1876 EXTERN_C_END 1877 1878 #undef __FUNC__ 1879 #define __FUNC__ "MatGetSubMatrix_MPIAIJ" 1880 /* 1881 Not great since it makes two copies of the submatrix, first an SeqAIJ 1882 in local and then by concatenating the local matrices the end result. 1883 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 1884 */ 1885 int MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,int csize,MatReuse call,Mat *newmat) 1886 { 1887 int ierr,i,m,n,rstart,row,rend,nz,*cwork,size,rank,j; 1888 int *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend; 1889 Mat *local,M,Mreuse; 1890 Scalar *vwork,*aa; 1891 MPI_Comm comm = mat->comm; 1892 Mat_SeqAIJ *aij; 1893 1894 1895 PetscFunctionBegin; 1896 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1897 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1898 1899 if (call == MAT_REUSE_MATRIX) { 1900 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 1901 if (!Mreuse) SETERRQ(1,"Submatrix passed in was not used before, cannot reuse"); 1902 local = &Mreuse; 1903 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 1904 } else { 1905 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 1906 Mreuse = *local; 1907 ierr = PetscFree(local);CHKERRQ(ierr); 1908 } 1909 1910 /* 1911 m - number of local rows 1912 n - number of columns (same on all processors) 1913 rstart - first row in new global matrix generated 1914 */ 1915 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 1916 if (call == MAT_INITIAL_MATRIX) { 1917 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1918 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1919 ii = aij->i; 1920 jj = aij->j; 1921 1922 /* 1923 Determine the number of non-zeros in the diagonal and off-diagonal 1924 portions of the matrix in order to do correct preallocation 1925 */ 1926 1927 /* first get start and end of "diagonal" columns */ 1928 if (csize == PETSC_DECIDE) { 1929 nlocal = n/size + ((n % size) > rank); 1930 } else { 1931 nlocal = csize; 1932 } 1933 ierr = MPI_Scan(&nlocal,&rend,1,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1934 rstart = rend - nlocal; 1935 if (rank == size - 1 && rend != n) { 1936 SETERRQ(1,"Local column sizes do not add up to total number of columns"); 1937 } 1938 1939 /* next, compute all the lengths */ 1940 ierr = PetscMalloc((2*m+1)*sizeof(int),&dlens);CHKERRQ(ierr); 1941 olens = dlens + m; 1942 for (i=0; i<m; i++) { 1943 jend = ii[i+1] - ii[i]; 1944 olen = 0; 1945 dlen = 0; 1946 for (j=0; j<jend; j++) { 1947 if (*jj < rstart || *jj >= rend) olen++; 1948 else dlen++; 1949 jj++; 1950 } 1951 olens[i] = olen; 1952 dlens[i] = dlen; 1953 } 1954 ierr = MatCreateMPIAIJ(comm,m,nlocal,PETSC_DECIDE,n,0,dlens,0,olens,&M);CHKERRQ(ierr); 1955 ierr = PetscFree(dlens);CHKERRQ(ierr); 1956 } else { 1957 int ml,nl; 1958 1959 M = *newmat; 1960 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 1961 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 1962 ierr = MatZeroEntries(M);CHKERRQ(ierr); 1963 /* 1964 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 1965 rather than the slower MatSetValues(). 1966 */ 1967 M->was_assembled = PETSC_TRUE; 1968 M->assembled = PETSC_FALSE; 1969 } 1970 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 1971 aij = (Mat_SeqAIJ*)(Mreuse)->data; 1972 if (aij->indexshift) SETERRQ(PETSC_ERR_SUP,"No support for index shifted matrix"); 1973 ii = aij->i; 1974 jj = aij->j; 1975 aa = aij->a; 1976 for (i=0; i<m; i++) { 1977 row = rstart + i; 1978 nz = ii[i+1] - ii[i]; 1979 cwork = jj; jj += nz; 1980 vwork = aa; aa += nz; 1981 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 1982 } 1983 1984 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1985 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1986 *newmat = M; 1987 1988 /* save submatrix used in processor for next request */ 1989 if (call == MAT_INITIAL_MATRIX) { 1990 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 1991 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 1992 } 1993 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNC__ 1998 #define __FUNC__ "MatMPIAIJSetPreallocation" 1999 /*@C 2000 MatMPIAIJSetPreallocation - Creates a sparse parallel matrix in AIJ format 2001 (the default parallel PETSc format). For good matrix assembly performance 2002 the user should preallocate the matrix storage by setting the parameters 2003 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2004 performance can be increased by more than a factor of 50. 2005 2006 Collective on MPI_Comm 2007 2008 Input Parameters: 2009 + A - the matrix 2010 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2011 (same value is used for all local rows) 2012 . d_nnz - array containing the number of nonzeros in the various rows of the 2013 DIAGONAL portion of the local submatrix (possibly different for each row) 2014 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2015 The size of this array is equal to the number of local rows, i.e 'm'. 2016 You must leave room for the diagonal entry even if it is zero. 2017 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2018 submatrix (same value is used for all local rows). 2019 - o_nnz - array containing the number of nonzeros in the various rows of the 2020 OFF-DIAGONAL portion of the local submatrix (possibly different for 2021 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2022 structure. The size of this array is equal to the number 2023 of local rows, i.e 'm'. 2024 2025 The AIJ format (also called the Yale sparse matrix format or 2026 compressed row storage), is fully compatible with standard Fortran 77 2027 storage. That is, the stored row and column indices can begin at 2028 either one (as in Fortran) or zero. See the users manual for details. 2029 2030 The user MUST specify either the local or global matrix dimensions 2031 (possibly both). 2032 2033 The parallel matrix is partitioned such that the first m0 rows belong to 2034 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2035 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2036 2037 The DIAGONAL portion of the local submatrix of a processor can be defined 2038 as the submatrix which is obtained by extraction the part corresponding 2039 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2040 first row that belongs to the processor, and r2 is the last row belonging 2041 to the this processor. This is a square mxm matrix. The remaining portion 2042 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2043 2044 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2045 2046 By default, this format uses inodes (identical nodes) when possible. 2047 We search for consecutive rows with the same nonzero structure, thereby 2048 reusing matrix information to achieve increased efficiency. 2049 2050 Options Database Keys: 2051 + -mat_aij_no_inode - Do not use inodes 2052 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2053 - -mat_aij_oneindex - Internally use indexing starting at 1 2054 rather than 0. Note that when calling MatSetValues(), 2055 the user still MUST index entries starting at 0! 2056 2057 Example usage: 2058 2059 Consider the following 8x8 matrix with 34 non-zero values, that is 2060 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2061 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2062 as follows: 2063 2064 .vb 2065 1 2 0 | 0 3 0 | 0 4 2066 Proc0 0 5 6 | 7 0 0 | 8 0 2067 9 0 10 | 11 0 0 | 12 0 2068 ------------------------------------- 2069 13 0 14 | 15 16 17 | 0 0 2070 Proc1 0 18 0 | 19 20 21 | 0 0 2071 0 0 0 | 22 23 0 | 24 0 2072 ------------------------------------- 2073 Proc2 25 26 27 | 0 0 28 | 29 0 2074 30 0 0 | 31 32 33 | 0 34 2075 .ve 2076 2077 This can be represented as a collection of submatrices as: 2078 2079 .vb 2080 A B C 2081 D E F 2082 G H I 2083 .ve 2084 2085 Where the submatrices A,B,C are owned by proc0, D,E,F are 2086 owned by proc1, G,H,I are owned by proc2. 2087 2088 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2089 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2090 The 'M','N' parameters are 8,8, and have the same values on all procs. 2091 2092 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2093 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2094 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2095 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2096 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2097 matrix, ans [DF] as another SeqAIJ matrix. 2098 2099 When d_nz, o_nz parameters are specified, d_nz storage elements are 2100 allocated for every row of the local diagonal submatrix, and o_nz 2101 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2102 One way to choose d_nz and o_nz is to use the max nonzerors per local 2103 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2104 In this case, the values of d_nz,o_nz are: 2105 .vb 2106 proc0 : dnz = 2, o_nz = 2 2107 proc1 : dnz = 3, o_nz = 2 2108 proc2 : dnz = 1, o_nz = 4 2109 .ve 2110 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2111 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2112 for proc3. i.e we are using 12+15+10=37 storage locations to store 2113 34 values. 2114 2115 When d_nnz, o_nnz parameters are specified, the storage is specified 2116 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2117 In the above case the values for d_nnz,o_nnz are: 2118 .vb 2119 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2120 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2121 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2122 .ve 2123 Here the space allocated is sum of all the above values i.e 34, and 2124 hence pre-allocation is perfect. 2125 2126 Level: intermediate 2127 2128 .keywords: matrix, aij, compressed row, sparse, parallel 2129 2130 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2131 @*/ 2132 int MatMPIAIJSetPreallocation(Mat B,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 2133 { 2134 Mat_MPIAIJ *b; 2135 int ierr,i; 2136 PetscTruth flg2; 2137 2138 PetscFunctionBegin; 2139 ierr = PetscTypeCompare((PetscObject)B,MATMPIAIJ,&flg2);CHKERRQ(ierr); 2140 if (!flg2) PetscFunctionReturn(0); 2141 B->preallocated = PETSC_TRUE; 2142 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2143 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2144 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %d",d_nz); 2145 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %d",o_nz); 2146 if (d_nnz) { 2147 for (i=0; i<B->m; i++) { 2148 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]); 2149 } 2150 } 2151 if (o_nnz) { 2152 for (i=0; i<B->m; i++) { 2153 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]); 2154 } 2155 } 2156 b = (Mat_MPIAIJ*)B->data; 2157 2158 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->n,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 2159 PetscLogObjectParent(B,b->A); 2160 ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,B->m,B->N,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 2161 PetscLogObjectParent(B,b->B); 2162 2163 PetscFunctionReturn(0); 2164 } 2165 2166 #undef __FUNC__ 2167 #define __FUNC__ "MatCreateMPIAIJ" 2168 /*@C 2169 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 2170 (the default parallel PETSc format). For good matrix assembly performance 2171 the user should preallocate the matrix storage by setting the parameters 2172 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 2173 performance can be increased by more than a factor of 50. 2174 2175 Collective on MPI_Comm 2176 2177 Input Parameters: 2178 + comm - MPI communicator 2179 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 2180 This value should be the same as the local size used in creating the 2181 y vector for the matrix-vector product y = Ax. 2182 . n - This value should be the same as the local size used in creating the 2183 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 2184 calculated if N is given) For square matrices n is almost always m. 2185 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 2186 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 2187 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 2188 (same value is used for all local rows) 2189 . d_nnz - array containing the number of nonzeros in the various rows of the 2190 DIAGONAL portion of the local submatrix (possibly different for each row) 2191 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 2192 The size of this array is equal to the number of local rows, i.e 'm'. 2193 You must leave room for the diagonal entry even if it is zero. 2194 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 2195 submatrix (same value is used for all local rows). 2196 - o_nnz - array containing the number of nonzeros in the various rows of the 2197 OFF-DIAGONAL portion of the local submatrix (possibly different for 2198 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 2199 structure. The size of this array is equal to the number 2200 of local rows, i.e 'm'. 2201 2202 Output Parameter: 2203 . A - the matrix 2204 2205 Notes: 2206 m,n,M,N parameters specify the size of the matrix, and its partitioning across 2207 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 2208 storage requirements for this matrix. 2209 2210 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 2211 processor than it must be used on all processors that share the object for 2212 that argument. 2213 2214 The AIJ format (also called the Yale sparse matrix format or 2215 compressed row storage), is fully compatible with standard Fortran 77 2216 storage. That is, the stored row and column indices can begin at 2217 either one (as in Fortran) or zero. See the users manual for details. 2218 2219 The user MUST specify either the local or global matrix dimensions 2220 (possibly both). 2221 2222 The parallel matrix is partitioned such that the first m0 rows belong to 2223 process 0, the next m1 rows belong to process 1, the next m2 rows belong 2224 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 2225 2226 The DIAGONAL portion of the local submatrix of a processor can be defined 2227 as the submatrix which is obtained by extraction the part corresponding 2228 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 2229 first row that belongs to the processor, and r2 is the last row belonging 2230 to the this processor. This is a square mxm matrix. The remaining portion 2231 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 2232 2233 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 2234 2235 By default, this format uses inodes (identical nodes) when possible. 2236 We search for consecutive rows with the same nonzero structure, thereby 2237 reusing matrix information to achieve increased efficiency. 2238 2239 Options Database Keys: 2240 + -mat_aij_no_inode - Do not use inodes 2241 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2242 - -mat_aij_oneindex - Internally use indexing starting at 1 2243 rather than 0. Note that when calling MatSetValues(), 2244 the user still MUST index entries starting at 0! 2245 2246 2247 Example usage: 2248 2249 Consider the following 8x8 matrix with 34 non-zero values, that is 2250 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 2251 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 2252 as follows: 2253 2254 .vb 2255 1 2 0 | 0 3 0 | 0 4 2256 Proc0 0 5 6 | 7 0 0 | 8 0 2257 9 0 10 | 11 0 0 | 12 0 2258 ------------------------------------- 2259 13 0 14 | 15 16 17 | 0 0 2260 Proc1 0 18 0 | 19 20 21 | 0 0 2261 0 0 0 | 22 23 0 | 24 0 2262 ------------------------------------- 2263 Proc2 25 26 27 | 0 0 28 | 29 0 2264 30 0 0 | 31 32 33 | 0 34 2265 .ve 2266 2267 This can be represented as a collection of submatrices as: 2268 2269 .vb 2270 A B C 2271 D E F 2272 G H I 2273 .ve 2274 2275 Where the submatrices A,B,C are owned by proc0, D,E,F are 2276 owned by proc1, G,H,I are owned by proc2. 2277 2278 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2279 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 2280 The 'M','N' parameters are 8,8, and have the same values on all procs. 2281 2282 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 2283 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 2284 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 2285 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 2286 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 2287 matrix, ans [DF] as another SeqAIJ matrix. 2288 2289 When d_nz, o_nz parameters are specified, d_nz storage elements are 2290 allocated for every row of the local diagonal submatrix, and o_nz 2291 storage locations are allocated for every row of the OFF-DIAGONAL submat. 2292 One way to choose d_nz and o_nz is to use the max nonzerors per local 2293 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 2294 In this case, the values of d_nz,o_nz are: 2295 .vb 2296 proc0 : dnz = 2, o_nz = 2 2297 proc1 : dnz = 3, o_nz = 2 2298 proc2 : dnz = 1, o_nz = 4 2299 .ve 2300 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 2301 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 2302 for proc3. i.e we are using 12+15+10=37 storage locations to store 2303 34 values. 2304 2305 When d_nnz, o_nnz parameters are specified, the storage is specified 2306 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 2307 In the above case the values for d_nnz,o_nnz are: 2308 .vb 2309 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 2310 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 2311 proc2: d_nnz = [1,1] and o_nnz = [4,4] 2312 .ve 2313 Here the space allocated is sum of all the above values i.e 34, and 2314 hence pre-allocation is perfect. 2315 2316 Level: intermediate 2317 2318 .keywords: matrix, aij, compressed row, sparse, parallel 2319 2320 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues() 2321 @*/ 2322 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) 2323 { 2324 int ierr,size; 2325 2326 PetscFunctionBegin; 2327 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 2328 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2329 if (size > 1) { 2330 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 2331 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 2332 } else { 2333 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2334 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 2335 } 2336 PetscFunctionReturn(0); 2337 } 2338 2339 #undef __FUNC__ 2340 #define __FUNC__ "MatMPIAIJGetSeqAIJ" 2341 int MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,int **colmap) 2342 { 2343 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 2344 PetscFunctionBegin; 2345 *Ad = a->A; 2346 *Ao = a->B; 2347 *colmap = a->garray; 2348 PetscFunctionReturn(0); 2349 } 2350