1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/aij/mpi/mpiaij.h" /*I "petscmat.h" I*/ 4 #include "../src/inline/spops.h" 5 6 #undef __FUNCT__ 7 #define __FUNCT__ "MatDistribute_MPIAIJ" 8 /* 9 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 10 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 11 12 Only for square matrices 13 */ 14 PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 15 { 16 PetscMPIInt rank,size; 17 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld; 18 PetscErrorCode ierr; 19 Mat mat; 20 Mat_SeqAIJ *gmata; 21 PetscMPIInt tag; 22 MPI_Status status; 23 PetscTruth aij; 24 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 25 26 PetscFunctionBegin; 27 CHKMEMQ; 28 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 29 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 30 if (!rank) { 31 ierr = PetscTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 32 if (!aij) SETERRQ1(PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 33 } 34 if (reuse == MAT_INITIAL_MATRIX) { 35 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 36 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 37 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 38 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 39 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 40 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 41 rowners[0] = 0; 42 for (i=2; i<=size; i++) { 43 rowners[i] += rowners[i-1]; 44 } 45 rstart = rowners[rank]; 46 rend = rowners[rank+1]; 47 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 48 if (!rank) { 49 gmata = (Mat_SeqAIJ*) gmat->data; 50 /* send row lengths to all processors */ 51 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 52 for (i=1; i<size; i++) { 53 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 54 } 55 /* determine number diagonal and off-diagonal counts */ 56 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 57 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 58 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 59 jj = 0; 60 for (i=0; i<m; i++) { 61 for (j=0; j<dlens[i]; j++) { 62 if (gmata->j[jj] < rstart) ld[i]++; 63 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 64 jj++; 65 } 66 } 67 /* send column indices to other processes */ 68 for (i=1; i<size; i++) { 69 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 70 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 71 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 72 } 73 74 /* send numerical values to other processes */ 75 for (i=1; i<size; i++) { 76 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 77 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 78 } 79 gmataa = gmata->a; 80 gmataj = gmata->j; 81 82 } else { 83 /* receive row lengths */ 84 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 85 /* receive column indices */ 86 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 87 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 88 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 89 /* determine number diagonal and off-diagonal counts */ 90 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 91 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 92 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 93 jj = 0; 94 for (i=0; i<m; i++) { 95 for (j=0; j<dlens[i]; j++) { 96 if (gmataj[jj] < rstart) ld[i]++; 97 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 98 jj++; 99 } 100 } 101 /* receive numerical values */ 102 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 103 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 104 } 105 /* set preallocation */ 106 for (i=0; i<m; i++) { 107 dlens[i] -= olens[i]; 108 } 109 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 110 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 111 112 for (i=0; i<m; i++) { 113 dlens[i] += olens[i]; 114 } 115 cnt = 0; 116 for (i=0; i<m; i++) { 117 row = rstart + i; 118 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 119 cnt += dlens[i]; 120 } 121 if (rank) { 122 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 123 } 124 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 125 ierr = PetscFree(rowners);CHKERRQ(ierr); 126 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 127 *inmat = mat; 128 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 129 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 130 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 131 mat = *inmat; 132 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 133 if (!rank) { 134 /* send numerical values to other processes */ 135 gmata = (Mat_SeqAIJ*) gmat->data; 136 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 137 gmataa = gmata->a; 138 for (i=1; i<size; i++) { 139 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 140 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 141 } 142 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 143 } else { 144 /* receive numerical values from process 0*/ 145 nz = Ad->nz + Ao->nz; 146 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 147 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 148 } 149 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 150 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 151 ad = Ad->a; 152 ao = Ao->a; 153 if (mat->rmap->n) { 154 i = 0; 155 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 156 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 157 } 158 for (i=1; i<mat->rmap->n; i++) { 159 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 160 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 161 } 162 i--; 163 if (mat->rmap->n) { 164 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 165 } 166 if (rank) { 167 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 168 } 169 } 170 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 171 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 172 CHKMEMQ; 173 PetscFunctionReturn(0); 174 } 175 176 /* 177 Local utility routine that creates a mapping from the global column 178 number to the local number in the off-diagonal part of the local 179 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 180 a slightly higher hash table cost; without it it is not scalable (each processor 181 has an order N integer array but is fast to acess. 182 */ 183 #undef __FUNCT__ 184 #define __FUNCT__ "CreateColmap_MPIAIJ_Private" 185 PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat) 186 { 187 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 188 PetscErrorCode ierr; 189 PetscInt n = aij->B->cmap->n,i; 190 191 PetscFunctionBegin; 192 #if defined (PETSC_USE_CTABLE) 193 ierr = PetscTableCreate(n,&aij->colmap);CHKERRQ(ierr); 194 for (i=0; i<n; i++){ 195 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);CHKERRQ(ierr); 196 } 197 #else 198 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 199 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 200 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 201 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 202 #endif 203 PetscFunctionReturn(0); 204 } 205 206 207 #define CHUNKSIZE 15 208 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 209 { \ 210 if (col <= lastcol1) low1 = 0; else high1 = nrow1; \ 211 lastcol1 = col;\ 212 while (high1-low1 > 5) { \ 213 t = (low1+high1)/2; \ 214 if (rp1[t] > col) high1 = t; \ 215 else low1 = t; \ 216 } \ 217 for (_i=low1; _i<high1; _i++) { \ 218 if (rp1[_i] > col) break; \ 219 if (rp1[_i] == col) { \ 220 if (addv == ADD_VALUES) ap1[_i] += value; \ 221 else ap1[_i] = value; \ 222 goto a_noinsert; \ 223 } \ 224 } \ 225 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 226 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 227 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 228 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 229 N = nrow1++ - 1; a->nz++; high1++; \ 230 /* shift up all the later entries in this row */ \ 231 for (ii=N; ii>=_i; ii--) { \ 232 rp1[ii+1] = rp1[ii]; \ 233 ap1[ii+1] = ap1[ii]; \ 234 } \ 235 rp1[_i] = col; \ 236 ap1[_i] = value; \ 237 a_noinsert: ; \ 238 ailen[row] = nrow1; \ 239 } 240 241 242 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 243 { \ 244 if (col <= lastcol2) low2 = 0; else high2 = nrow2; \ 245 lastcol2 = col;\ 246 while (high2-low2 > 5) { \ 247 t = (low2+high2)/2; \ 248 if (rp2[t] > col) high2 = t; \ 249 else low2 = t; \ 250 } \ 251 for (_i=low2; _i<high2; _i++) { \ 252 if (rp2[_i] > col) break; \ 253 if (rp2[_i] == col) { \ 254 if (addv == ADD_VALUES) ap2[_i] += value; \ 255 else ap2[_i] = value; \ 256 goto b_noinsert; \ 257 } \ 258 } \ 259 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 260 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 261 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 262 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 263 N = nrow2++ - 1; b->nz++; high2++; \ 264 /* shift up all the later entries in this row */ \ 265 for (ii=N; ii>=_i; ii--) { \ 266 rp2[ii+1] = rp2[ii]; \ 267 ap2[ii+1] = ap2[ii]; \ 268 } \ 269 rp2[_i] = col; \ 270 ap2[_i] = value; \ 271 b_noinsert: ; \ 272 bilen[row] = nrow2; \ 273 } 274 275 #undef __FUNCT__ 276 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 277 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 278 { 279 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 280 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 281 PetscErrorCode ierr; 282 PetscInt l,*garray = mat->garray,diag; 283 284 PetscFunctionBegin; 285 /* code only works for square matrices A */ 286 287 /* find size of row to the left of the diagonal part */ 288 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 289 row = row - diag; 290 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 291 if (garray[b->j[b->i[row]+l]] > diag) break; 292 } 293 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 294 295 /* diagonal part */ 296 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 297 298 /* right of diagonal part */ 299 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 300 PetscFunctionReturn(0); 301 } 302 303 #undef __FUNCT__ 304 #define __FUNCT__ "MatSetValues_MPIAIJ" 305 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 306 { 307 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 308 PetscScalar value; 309 PetscErrorCode ierr; 310 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 311 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 312 PetscTruth roworiented = aij->roworiented; 313 314 /* Some Variables required in the macro */ 315 Mat A = aij->A; 316 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 317 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 318 MatScalar *aa = a->a; 319 PetscTruth ignorezeroentries = a->ignorezeroentries; 320 Mat B = aij->B; 321 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 322 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 323 MatScalar *ba = b->a; 324 325 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 326 PetscInt nonew = a->nonew; 327 MatScalar *ap1,*ap2; 328 329 PetscFunctionBegin; 330 for (i=0; i<m; i++) { 331 if (im[i] < 0) continue; 332 #if defined(PETSC_USE_DEBUG) 333 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 334 #endif 335 if (im[i] >= rstart && im[i] < rend) { 336 row = im[i] - rstart; 337 lastcol1 = -1; 338 rp1 = aj + ai[row]; 339 ap1 = aa + ai[row]; 340 rmax1 = aimax[row]; 341 nrow1 = ailen[row]; 342 low1 = 0; 343 high1 = nrow1; 344 lastcol2 = -1; 345 rp2 = bj + bi[row]; 346 ap2 = ba + bi[row]; 347 rmax2 = bimax[row]; 348 nrow2 = bilen[row]; 349 low2 = 0; 350 high2 = nrow2; 351 352 for (j=0; j<n; j++) { 353 if (v) {if (roworiented) value = v[i*n+j]; else value = v[i+j*m];} else value = 0.0; 354 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 355 if (in[j] >= cstart && in[j] < cend){ 356 col = in[j] - cstart; 357 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 358 } else if (in[j] < 0) continue; 359 #if defined(PETSC_USE_DEBUG) 360 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);} 361 #endif 362 else { 363 if (mat->was_assembled) { 364 if (!aij->colmap) { 365 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 366 } 367 #if defined (PETSC_USE_CTABLE) 368 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 369 col--; 370 #else 371 col = aij->colmap[in[j]] - 1; 372 #endif 373 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 374 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 375 col = in[j]; 376 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 377 B = aij->B; 378 b = (Mat_SeqAIJ*)B->data; 379 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 380 rp2 = bj + bi[row]; 381 ap2 = ba + bi[row]; 382 rmax2 = bimax[row]; 383 nrow2 = bilen[row]; 384 low2 = 0; 385 high2 = nrow2; 386 bm = aij->B->rmap->n; 387 ba = b->a; 388 } 389 } else col = in[j]; 390 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 391 } 392 } 393 } else { 394 if (!aij->donotstash) { 395 if (roworiented) { 396 if (ignorezeroentries && v[i*n] == 0.0) continue; 397 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 398 } else { 399 if (ignorezeroentries && v[i] == 0.0) continue; 400 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 401 } 402 } 403 } 404 } 405 PetscFunctionReturn(0); 406 } 407 408 #undef __FUNCT__ 409 #define __FUNCT__ "MatGetValues_MPIAIJ" 410 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 411 { 412 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 413 PetscErrorCode ierr; 414 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 415 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 416 417 PetscFunctionBegin; 418 for (i=0; i<m; i++) { 419 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 420 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 421 if (idxm[i] >= rstart && idxm[i] < rend) { 422 row = idxm[i] - rstart; 423 for (j=0; j<n; j++) { 424 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 425 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 426 if (idxn[j] >= cstart && idxn[j] < cend){ 427 col = idxn[j] - cstart; 428 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 429 } else { 430 if (!aij->colmap) { 431 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 432 } 433 #if defined (PETSC_USE_CTABLE) 434 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 435 col --; 436 #else 437 col = aij->colmap[idxn[j]] - 1; 438 #endif 439 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 440 else { 441 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 442 } 443 } 444 } 445 } else { 446 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 447 } 448 } 449 PetscFunctionReturn(0); 450 } 451 452 #undef __FUNCT__ 453 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 454 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 455 { 456 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 457 PetscErrorCode ierr; 458 PetscInt nstash,reallocs; 459 InsertMode addv; 460 461 PetscFunctionBegin; 462 if (aij->donotstash) { 463 PetscFunctionReturn(0); 464 } 465 466 /* make sure all processors are either in INSERTMODE or ADDMODE */ 467 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 468 if (addv == (ADD_VALUES|INSERT_VALUES)) { 469 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 470 } 471 mat->insertmode = addv; /* in case this processor had no cache */ 472 473 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 474 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 475 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 481 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data; 485 PetscErrorCode ierr; 486 PetscMPIInt n; 487 PetscInt i,j,rstart,ncols,flg; 488 PetscInt *row,*col; 489 PetscTruth other_disassembled; 490 PetscScalar *val; 491 InsertMode addv = mat->insertmode; 492 493 /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */ 494 PetscFunctionBegin; 495 if (!aij->donotstash) { 496 while (1) { 497 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 498 if (!flg) break; 499 500 for (i=0; i<n;) { 501 /* Now identify the consecutive vals belonging to the same row */ 502 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 503 if (j < n) ncols = j-i; 504 else ncols = n-i; 505 /* Now assemble all these values with a single function call */ 506 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 507 i = j; 508 } 509 } 510 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 511 } 512 a->compressedrow.use = PETSC_FALSE; 513 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 514 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 515 516 /* determine if any processor has disassembled, if so we must 517 also disassemble ourselfs, in order that we may reassemble. */ 518 /* 519 if nonzero structure of submatrix B cannot change then we know that 520 no processor disassembled thus we can skip this stuff 521 */ 522 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 523 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 524 if (mat->was_assembled && !other_disassembled) { 525 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 526 } 527 } 528 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 529 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 530 } 531 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 532 ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 533 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 534 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 535 536 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 537 aij->rowvalues = 0; 538 539 /* used by MatAXPY() */ 540 a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 541 a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 542 543 PetscFunctionReturn(0); 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 548 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 549 { 550 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 551 PetscErrorCode ierr; 552 553 PetscFunctionBegin; 554 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 555 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 556 PetscFunctionReturn(0); 557 } 558 559 #undef __FUNCT__ 560 #define __FUNCT__ "MatZeroRows_MPIAIJ" 561 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 562 { 563 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 564 PetscErrorCode ierr; 565 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 566 PetscInt i,*owners = A->rmap->range; 567 PetscInt *nprocs,j,idx,nsends,row; 568 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 569 PetscInt *rvalues,count,base,slen,*source; 570 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 571 MPI_Comm comm = ((PetscObject)A)->comm; 572 MPI_Request *send_waits,*recv_waits; 573 MPI_Status recv_status,*send_status; 574 #if defined(PETSC_DEBUG) 575 PetscTruth found = PETSC_FALSE; 576 #endif 577 578 PetscFunctionBegin; 579 /* first count number of contributors to each processor */ 580 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 581 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 582 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 583 j = 0; 584 for (i=0; i<N; i++) { 585 if (lastidx > (idx = rows[i])) j = 0; 586 lastidx = idx; 587 for (; j<size; j++) { 588 if (idx >= owners[j] && idx < owners[j+1]) { 589 nprocs[2*j]++; 590 nprocs[2*j+1] = 1; 591 owner[i] = j; 592 #if defined(PETSC_DEBUG) 593 found = PETSC_TRUE; 594 #endif 595 break; 596 } 597 } 598 #if defined(PETSC_DEBUG) 599 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 600 found = PETSC_FALSE; 601 #endif 602 } 603 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 604 605 /* inform other processors of number of messages and max length*/ 606 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 607 608 /* post receives: */ 609 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 610 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 611 for (i=0; i<nrecvs; i++) { 612 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 613 } 614 615 /* do sends: 616 1) starts[i] gives the starting index in svalues for stuff going to 617 the ith processor 618 */ 619 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 620 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 621 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 622 starts[0] = 0; 623 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 624 for (i=0; i<N; i++) { 625 svalues[starts[owner[i]]++] = rows[i]; 626 } 627 628 starts[0] = 0; 629 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 630 count = 0; 631 for (i=0; i<size; i++) { 632 if (nprocs[2*i+1]) { 633 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 634 } 635 } 636 ierr = PetscFree(starts);CHKERRQ(ierr); 637 638 base = owners[rank]; 639 640 /* wait on receives */ 641 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 642 source = lens + nrecvs; 643 count = nrecvs; slen = 0; 644 while (count) { 645 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 646 /* unpack receives into our local space */ 647 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 648 source[imdex] = recv_status.MPI_SOURCE; 649 lens[imdex] = n; 650 slen += n; 651 count--; 652 } 653 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 654 655 /* move the data into the send scatter */ 656 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 657 count = 0; 658 for (i=0; i<nrecvs; i++) { 659 values = rvalues + i*nmax; 660 for (j=0; j<lens[i]; j++) { 661 lrows[count++] = values[j] - base; 662 } 663 } 664 ierr = PetscFree(rvalues);CHKERRQ(ierr); 665 ierr = PetscFree(lens);CHKERRQ(ierr); 666 ierr = PetscFree(owner);CHKERRQ(ierr); 667 ierr = PetscFree(nprocs);CHKERRQ(ierr); 668 669 /* actually zap the local rows */ 670 /* 671 Zero the required rows. If the "diagonal block" of the matrix 672 is square and the user wishes to set the diagonal we use separate 673 code so that MatSetValues() is not called for each diagonal allocating 674 new memory, thus calling lots of mallocs and slowing things down. 675 676 Contributed by: Matthew Knepley 677 */ 678 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 679 ierr = MatZeroRows(l->B,slen,lrows,0.0);CHKERRQ(ierr); 680 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 681 ierr = MatZeroRows(l->A,slen,lrows,diag);CHKERRQ(ierr); 682 } else if (diag != 0.0) { 683 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 684 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 685 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 686 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 687 } 688 for (i = 0; i < slen; i++) { 689 row = lrows[i] + rstart; 690 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 691 } 692 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 693 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 694 } else { 695 ierr = MatZeroRows(l->A,slen,lrows,0.0);CHKERRQ(ierr); 696 } 697 ierr = PetscFree(lrows);CHKERRQ(ierr); 698 699 /* wait on sends */ 700 if (nsends) { 701 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 702 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 703 ierr = PetscFree(send_status);CHKERRQ(ierr); 704 } 705 ierr = PetscFree(send_waits);CHKERRQ(ierr); 706 ierr = PetscFree(svalues);CHKERRQ(ierr); 707 708 PetscFunctionReturn(0); 709 } 710 711 #undef __FUNCT__ 712 #define __FUNCT__ "MatMult_MPIAIJ" 713 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 714 { 715 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 716 PetscErrorCode ierr; 717 PetscInt nt; 718 719 PetscFunctionBegin; 720 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 721 if (nt != A->cmap->n) { 722 SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 723 } 724 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 725 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 726 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 727 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 728 PetscFunctionReturn(0); 729 } 730 731 #undef __FUNCT__ 732 #define __FUNCT__ "MatMultAdd_MPIAIJ" 733 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 734 { 735 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 736 PetscErrorCode ierr; 737 738 PetscFunctionBegin; 739 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 740 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 741 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 742 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 743 PetscFunctionReturn(0); 744 } 745 746 #undef __FUNCT__ 747 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 748 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 749 { 750 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 751 PetscErrorCode ierr; 752 PetscTruth merged; 753 754 PetscFunctionBegin; 755 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 756 /* do nondiagonal part */ 757 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 758 if (!merged) { 759 /* send it on its way */ 760 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 761 /* do local part */ 762 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 763 /* receive remote parts: note this assumes the values are not actually */ 764 /* added in yy until the next line, */ 765 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 766 } else { 767 /* do local part */ 768 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 769 /* send it on its way */ 770 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 771 /* values actually were received in the Begin() but we need to call this nop */ 772 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 773 } 774 PetscFunctionReturn(0); 775 } 776 777 EXTERN_C_BEGIN 778 #undef __FUNCT__ 779 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 780 PetscErrorCode PETSCMAT_DLLEXPORT MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f) 781 { 782 MPI_Comm comm; 783 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 784 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 785 IS Me,Notme; 786 PetscErrorCode ierr; 787 PetscInt M,N,first,last,*notme,i; 788 PetscMPIInt size; 789 790 PetscFunctionBegin; 791 792 /* Easy test: symmetric diagonal block */ 793 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 794 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 795 if (!*f) PetscFunctionReturn(0); 796 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 797 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 798 if (size == 1) PetscFunctionReturn(0); 799 800 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 801 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 802 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 803 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 804 for (i=0; i<first; i++) notme[i] = i; 805 for (i=last; i<M; i++) notme[i-last+first] = i; 806 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);CHKERRQ(ierr); 807 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 808 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 809 Aoff = Aoffs[0]; 810 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 811 Boff = Boffs[0]; 812 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 813 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 814 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 815 ierr = ISDestroy(Me);CHKERRQ(ierr); 816 ierr = ISDestroy(Notme);CHKERRQ(ierr); 817 818 PetscFunctionReturn(0); 819 } 820 EXTERN_C_END 821 822 #undef __FUNCT__ 823 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 824 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 825 { 826 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 827 PetscErrorCode ierr; 828 829 PetscFunctionBegin; 830 /* do nondiagonal part */ 831 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 832 /* send it on its way */ 833 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 834 /* do local part */ 835 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 836 /* receive remote parts */ 837 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 838 PetscFunctionReturn(0); 839 } 840 841 /* 842 This only works correctly for square matrices where the subblock A->A is the 843 diagonal block 844 */ 845 #undef __FUNCT__ 846 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 847 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 848 { 849 PetscErrorCode ierr; 850 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 851 852 PetscFunctionBegin; 853 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 854 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) { 855 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 856 } 857 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 858 PetscFunctionReturn(0); 859 } 860 861 #undef __FUNCT__ 862 #define __FUNCT__ "MatScale_MPIAIJ" 863 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 864 { 865 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 866 PetscErrorCode ierr; 867 868 PetscFunctionBegin; 869 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 870 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 871 PetscFunctionReturn(0); 872 } 873 874 #undef __FUNCT__ 875 #define __FUNCT__ "MatDestroy_MPIAIJ" 876 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 877 { 878 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 879 PetscErrorCode ierr; 880 881 PetscFunctionBegin; 882 #if defined(PETSC_USE_LOG) 883 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 884 #endif 885 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 886 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 887 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 888 #if defined (PETSC_USE_CTABLE) 889 if (aij->colmap) {ierr = PetscTableDestroy(aij->colmap);CHKERRQ(ierr);} 890 #else 891 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 892 #endif 893 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 894 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 895 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 896 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 897 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 898 ierr = PetscFree(aij);CHKERRQ(ierr); 899 900 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 901 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 902 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 903 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 904 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 905 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 906 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 907 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 908 PetscFunctionReturn(0); 909 } 910 911 #undef __FUNCT__ 912 #define __FUNCT__ "MatView_MPIAIJ_Binary" 913 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 914 { 915 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 916 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 917 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 918 PetscErrorCode ierr; 919 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 920 int fd; 921 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 922 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 923 PetscScalar *column_values; 924 925 PetscFunctionBegin; 926 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 927 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 928 nz = A->nz + B->nz; 929 if (!rank) { 930 header[0] = MAT_FILE_COOKIE; 931 header[1] = mat->rmap->N; 932 header[2] = mat->cmap->N; 933 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 934 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 935 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 936 /* get largest number of rows any processor has */ 937 rlen = mat->rmap->n; 938 range = mat->rmap->range; 939 for (i=1; i<size; i++) { 940 rlen = PetscMax(rlen,range[i+1] - range[i]); 941 } 942 } else { 943 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 944 rlen = mat->rmap->n; 945 } 946 947 /* load up the local row counts */ 948 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 949 for (i=0; i<mat->rmap->n; i++) { 950 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 951 } 952 953 /* store the row lengths to the file */ 954 if (!rank) { 955 MPI_Status status; 956 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 957 for (i=1; i<size; i++) { 958 rlen = range[i+1] - range[i]; 959 ierr = MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 960 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 961 } 962 } else { 963 ierr = MPI_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 964 } 965 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 966 967 /* load up the local column indices */ 968 nzmax = nz; /* )th processor needs space a largest processor needs */ 969 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 970 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 971 cnt = 0; 972 for (i=0; i<mat->rmap->n; i++) { 973 for (j=B->i[i]; j<B->i[i+1]; j++) { 974 if ( (col = garray[B->j[j]]) > cstart) break; 975 column_indices[cnt++] = col; 976 } 977 for (k=A->i[i]; k<A->i[i+1]; k++) { 978 column_indices[cnt++] = A->j[k] + cstart; 979 } 980 for (; j<B->i[i+1]; j++) { 981 column_indices[cnt++] = garray[B->j[j]]; 982 } 983 } 984 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 985 986 /* store the column indices to the file */ 987 if (!rank) { 988 MPI_Status status; 989 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 990 for (i=1; i<size; i++) { 991 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 992 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 993 ierr = MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 994 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 995 } 996 } else { 997 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 998 ierr = MPI_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 999 } 1000 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1001 1002 /* load up the local column values */ 1003 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1004 cnt = 0; 1005 for (i=0; i<mat->rmap->n; i++) { 1006 for (j=B->i[i]; j<B->i[i+1]; j++) { 1007 if ( garray[B->j[j]] > cstart) break; 1008 column_values[cnt++] = B->a[j]; 1009 } 1010 for (k=A->i[i]; k<A->i[i+1]; k++) { 1011 column_values[cnt++] = A->a[k]; 1012 } 1013 for (; j<B->i[i+1]; j++) { 1014 column_values[cnt++] = B->a[j]; 1015 } 1016 } 1017 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1018 1019 /* store the column values to the file */ 1020 if (!rank) { 1021 MPI_Status status; 1022 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1023 for (i=1; i<size; i++) { 1024 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1025 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1026 ierr = MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1027 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1028 } 1029 } else { 1030 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1031 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1032 } 1033 ierr = PetscFree(column_values);CHKERRQ(ierr); 1034 PetscFunctionReturn(0); 1035 } 1036 1037 #undef __FUNCT__ 1038 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1039 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1040 { 1041 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1042 PetscErrorCode ierr; 1043 PetscMPIInt rank = aij->rank,size = aij->size; 1044 PetscTruth isdraw,iascii,isbinary; 1045 PetscViewer sviewer; 1046 PetscViewerFormat format; 1047 1048 PetscFunctionBegin; 1049 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1050 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1051 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1052 if (iascii) { 1053 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1054 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1055 MatInfo info; 1056 PetscTruth inodes; 1057 1058 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1059 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1060 ierr = MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);CHKERRQ(ierr); 1061 if (!inodes) { 1062 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1063 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1064 } else { 1065 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1066 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1067 } 1068 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1069 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1070 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1071 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1072 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1073 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1074 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1075 PetscFunctionReturn(0); 1076 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1077 PetscInt inodecount,inodelimit,*inodes; 1078 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1079 if (inodes) { 1080 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1081 } else { 1082 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1083 } 1084 PetscFunctionReturn(0); 1085 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1086 PetscFunctionReturn(0); 1087 } 1088 } else if (isbinary) { 1089 if (size == 1) { 1090 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1091 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1092 } else { 1093 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1094 } 1095 PetscFunctionReturn(0); 1096 } else if (isdraw) { 1097 PetscDraw draw; 1098 PetscTruth isnull; 1099 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1100 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1101 } 1102 1103 if (size == 1) { 1104 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1105 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1106 } else { 1107 /* assemble the entire matrix onto first processor. */ 1108 Mat A; 1109 Mat_SeqAIJ *Aloc; 1110 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1111 MatScalar *a; 1112 1113 if (mat->rmap->N > 1024) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 512 rows, use binary format instead"); 1114 1115 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1116 if (!rank) { 1117 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1118 } else { 1119 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1120 } 1121 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1122 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1123 ierr = MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1124 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1125 1126 /* copy over the A part */ 1127 Aloc = (Mat_SeqAIJ*)aij->A->data; 1128 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1129 row = mat->rmap->rstart; 1130 for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap->rstart ;} 1131 for (i=0; i<m; i++) { 1132 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1133 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1134 } 1135 aj = Aloc->j; 1136 for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap->rstart;} 1137 1138 /* copy over the B part */ 1139 Aloc = (Mat_SeqAIJ*)aij->B->data; 1140 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1141 row = mat->rmap->rstart; 1142 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1143 ct = cols; 1144 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 1145 for (i=0; i<m; i++) { 1146 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1147 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1148 } 1149 ierr = PetscFree(ct);CHKERRQ(ierr); 1150 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1151 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1152 /* 1153 Everyone has to call to draw the matrix since the graphics waits are 1154 synchronized across all processors that share the PetscDraw object 1155 */ 1156 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1157 if (!rank) { 1158 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1159 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1160 } 1161 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1162 ierr = MatDestroy(A);CHKERRQ(ierr); 1163 } 1164 PetscFunctionReturn(0); 1165 } 1166 1167 #undef __FUNCT__ 1168 #define __FUNCT__ "MatView_MPIAIJ" 1169 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1170 { 1171 PetscErrorCode ierr; 1172 PetscTruth iascii,isdraw,issocket,isbinary; 1173 1174 PetscFunctionBegin; 1175 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1176 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1177 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1178 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1179 if (iascii || isdraw || isbinary || issocket) { 1180 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1181 } else { 1182 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1183 } 1184 PetscFunctionReturn(0); 1185 } 1186 1187 #undef __FUNCT__ 1188 #define __FUNCT__ "MatRelax_MPIAIJ" 1189 PetscErrorCode MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1190 { 1191 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1192 PetscErrorCode ierr; 1193 Vec bb1; 1194 1195 PetscFunctionBegin; 1196 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1197 1198 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1199 if (flag & SOR_ZERO_INITIAL_GUESS) { 1200 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr); 1201 its--; 1202 } 1203 1204 while (its--) { 1205 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1206 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1207 1208 /* update rhs: bb1 = bb - B*x */ 1209 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1210 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1211 1212 /* local sweep */ 1213 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr); 1214 } 1215 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1216 if (flag & SOR_ZERO_INITIAL_GUESS) { 1217 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1218 its--; 1219 } 1220 while (its--) { 1221 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1222 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1223 1224 /* update rhs: bb1 = bb - B*x */ 1225 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1226 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1227 1228 /* local sweep */ 1229 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1230 } 1231 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1232 if (flag & SOR_ZERO_INITIAL_GUESS) { 1233 ierr = (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1234 its--; 1235 } 1236 while (its--) { 1237 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1238 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1239 1240 /* update rhs: bb1 = bb - B*x */ 1241 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1242 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1243 1244 /* local sweep */ 1245 ierr = (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx);CHKERRQ(ierr); 1246 } 1247 } else { 1248 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1249 } 1250 1251 ierr = VecDestroy(bb1);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatPermute_MPIAIJ" 1257 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1258 { 1259 MPI_Comm comm,pcomm; 1260 PetscInt first,local_size,nrows; 1261 const PetscInt *rows; 1262 int ntids; 1263 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1264 PetscErrorCode ierr; 1265 1266 PetscFunctionBegin; 1267 ierr = PetscObjectGetComm((PetscObject)A,&comm); CHKERRQ(ierr); 1268 /* make a collective version of 'rowp' */ 1269 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm); CHKERRQ(ierr); 1270 if (pcomm==comm) { 1271 crowp = rowp; 1272 } else { 1273 ierr = ISGetSize(rowp,&nrows); CHKERRQ(ierr); 1274 ierr = ISGetIndices(rowp,&rows); CHKERRQ(ierr); 1275 ierr = ISCreateGeneral(comm,nrows,rows,&crowp); CHKERRQ(ierr); 1276 ierr = ISRestoreIndices(rowp,&rows); CHKERRQ(ierr); 1277 } 1278 /* collect the global row permutation and invert it */ 1279 ierr = ISAllGather(crowp,&growp); CHKERRQ(ierr); 1280 ierr = ISSetPermutation(growp); CHKERRQ(ierr); 1281 if (pcomm!=comm) { 1282 ierr = ISDestroy(crowp); CHKERRQ(ierr); 1283 } 1284 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1285 /* get the local target indices */ 1286 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL); CHKERRQ(ierr); 1287 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL); CHKERRQ(ierr); 1288 ierr = ISGetIndices(irowp,&rows); CHKERRQ(ierr); 1289 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp); CHKERRQ(ierr); 1290 ierr = ISRestoreIndices(irowp,&rows); CHKERRQ(ierr); 1291 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1292 /* the column permutation is so much easier; 1293 make a local version of 'colp' and invert it */ 1294 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm); CHKERRQ(ierr); 1295 ierr = MPI_Comm_size(pcomm,&ntids); CHKERRQ(ierr); 1296 if (ntids==1) { 1297 lcolp = colp; 1298 } else { 1299 ierr = ISGetSize(colp,&nrows); CHKERRQ(ierr); 1300 ierr = ISGetIndices(colp,&rows); CHKERRQ(ierr); 1301 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp); CHKERRQ(ierr); 1302 } 1303 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp); CHKERRQ(ierr); 1304 ierr = ISSetPermutation(lcolp); CHKERRQ(ierr); 1305 if (ntids>1) { 1306 ierr = ISRestoreIndices(colp,&rows); CHKERRQ(ierr); 1307 ierr = ISDestroy(lcolp); CHKERRQ(ierr); 1308 } 1309 /* now we just get the submatrix */ 1310 ierr = MatGetSubMatrix(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B); CHKERRQ(ierr); 1311 /* clean up */ 1312 ierr = ISDestroy(lrowp); CHKERRQ(ierr); 1313 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1314 PetscFunctionReturn(0); 1315 } 1316 1317 #undef __FUNCT__ 1318 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1319 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1320 { 1321 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1322 Mat A = mat->A,B = mat->B; 1323 PetscErrorCode ierr; 1324 PetscReal isend[5],irecv[5]; 1325 1326 PetscFunctionBegin; 1327 info->block_size = 1.0; 1328 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1329 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1330 isend[3] = info->memory; isend[4] = info->mallocs; 1331 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1332 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1333 isend[3] += info->memory; isend[4] += info->mallocs; 1334 if (flag == MAT_LOCAL) { 1335 info->nz_used = isend[0]; 1336 info->nz_allocated = isend[1]; 1337 info->nz_unneeded = isend[2]; 1338 info->memory = isend[3]; 1339 info->mallocs = isend[4]; 1340 } else if (flag == MAT_GLOBAL_MAX) { 1341 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1342 info->nz_used = irecv[0]; 1343 info->nz_allocated = irecv[1]; 1344 info->nz_unneeded = irecv[2]; 1345 info->memory = irecv[3]; 1346 info->mallocs = irecv[4]; 1347 } else if (flag == MAT_GLOBAL_SUM) { 1348 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1349 info->nz_used = irecv[0]; 1350 info->nz_allocated = irecv[1]; 1351 info->nz_unneeded = irecv[2]; 1352 info->memory = irecv[3]; 1353 info->mallocs = irecv[4]; 1354 } 1355 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1356 info->fill_ratio_needed = 0; 1357 info->factor_mallocs = 0; 1358 1359 PetscFunctionReturn(0); 1360 } 1361 1362 #undef __FUNCT__ 1363 #define __FUNCT__ "MatSetOption_MPIAIJ" 1364 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg) 1365 { 1366 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1367 PetscErrorCode ierr; 1368 1369 PetscFunctionBegin; 1370 switch (op) { 1371 case MAT_NEW_NONZERO_LOCATIONS: 1372 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1373 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1374 case MAT_KEEP_ZEROED_ROWS: 1375 case MAT_NEW_NONZERO_LOCATION_ERR: 1376 case MAT_USE_INODES: 1377 case MAT_IGNORE_ZERO_ENTRIES: 1378 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1379 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1380 break; 1381 case MAT_ROW_ORIENTED: 1382 a->roworiented = flg; 1383 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1384 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1385 break; 1386 case MAT_NEW_DIAGONALS: 1387 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1388 break; 1389 case MAT_IGNORE_OFF_PROC_ENTRIES: 1390 a->donotstash = PETSC_TRUE; 1391 break; 1392 case MAT_SYMMETRIC: 1393 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1394 break; 1395 case MAT_STRUCTURALLY_SYMMETRIC: 1396 case MAT_HERMITIAN: 1397 case MAT_SYMMETRY_ETERNAL: 1398 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1399 break; 1400 default: 1401 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1402 } 1403 PetscFunctionReturn(0); 1404 } 1405 1406 #undef __FUNCT__ 1407 #define __FUNCT__ "MatGetRow_MPIAIJ" 1408 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1409 { 1410 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1411 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1412 PetscErrorCode ierr; 1413 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1414 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1415 PetscInt *cmap,*idx_p; 1416 1417 PetscFunctionBegin; 1418 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1419 mat->getrowactive = PETSC_TRUE; 1420 1421 if (!mat->rowvalues && (idx || v)) { 1422 /* 1423 allocate enough space to hold information from the longest row. 1424 */ 1425 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1426 PetscInt max = 1,tmp; 1427 for (i=0; i<matin->rmap->n; i++) { 1428 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1429 if (max < tmp) { max = tmp; } 1430 } 1431 ierr = PetscMalloc(max*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1432 mat->rowindices = (PetscInt*)(mat->rowvalues + max); 1433 } 1434 1435 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1436 lrow = row - rstart; 1437 1438 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1439 if (!v) {pvA = 0; pvB = 0;} 1440 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1441 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1442 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1443 nztot = nzA + nzB; 1444 1445 cmap = mat->garray; 1446 if (v || idx) { 1447 if (nztot) { 1448 /* Sort by increasing column numbers, assuming A and B already sorted */ 1449 PetscInt imark = -1; 1450 if (v) { 1451 *v = v_p = mat->rowvalues; 1452 for (i=0; i<nzB; i++) { 1453 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1454 else break; 1455 } 1456 imark = i; 1457 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1458 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1459 } 1460 if (idx) { 1461 *idx = idx_p = mat->rowindices; 1462 if (imark > -1) { 1463 for (i=0; i<imark; i++) { 1464 idx_p[i] = cmap[cworkB[i]]; 1465 } 1466 } else { 1467 for (i=0; i<nzB; i++) { 1468 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1469 else break; 1470 } 1471 imark = i; 1472 } 1473 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1474 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1475 } 1476 } else { 1477 if (idx) *idx = 0; 1478 if (v) *v = 0; 1479 } 1480 } 1481 *nz = nztot; 1482 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1483 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1484 PetscFunctionReturn(0); 1485 } 1486 1487 #undef __FUNCT__ 1488 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1489 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1490 { 1491 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1492 1493 PetscFunctionBegin; 1494 if (!aij->getrowactive) { 1495 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1496 } 1497 aij->getrowactive = PETSC_FALSE; 1498 PetscFunctionReturn(0); 1499 } 1500 1501 #undef __FUNCT__ 1502 #define __FUNCT__ "MatNorm_MPIAIJ" 1503 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1504 { 1505 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1506 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1507 PetscErrorCode ierr; 1508 PetscInt i,j,cstart = mat->cmap->rstart; 1509 PetscReal sum = 0.0; 1510 MatScalar *v; 1511 1512 PetscFunctionBegin; 1513 if (aij->size == 1) { 1514 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1515 } else { 1516 if (type == NORM_FROBENIUS) { 1517 v = amat->a; 1518 for (i=0; i<amat->nz; i++) { 1519 #if defined(PETSC_USE_COMPLEX) 1520 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1521 #else 1522 sum += (*v)*(*v); v++; 1523 #endif 1524 } 1525 v = bmat->a; 1526 for (i=0; i<bmat->nz; i++) { 1527 #if defined(PETSC_USE_COMPLEX) 1528 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1529 #else 1530 sum += (*v)*(*v); v++; 1531 #endif 1532 } 1533 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1534 *norm = sqrt(*norm); 1535 } else if (type == NORM_1) { /* max column norm */ 1536 PetscReal *tmp,*tmp2; 1537 PetscInt *jj,*garray = aij->garray; 1538 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1539 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1540 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 1541 *norm = 0.0; 1542 v = amat->a; jj = amat->j; 1543 for (j=0; j<amat->nz; j++) { 1544 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1545 } 1546 v = bmat->a; jj = bmat->j; 1547 for (j=0; j<bmat->nz; j++) { 1548 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1549 } 1550 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1551 for (j=0; j<mat->cmap->N; j++) { 1552 if (tmp2[j] > *norm) *norm = tmp2[j]; 1553 } 1554 ierr = PetscFree(tmp);CHKERRQ(ierr); 1555 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1556 } else if (type == NORM_INFINITY) { /* max row norm */ 1557 PetscReal ntemp = 0.0; 1558 for (j=0; j<aij->A->rmap->n; j++) { 1559 v = amat->a + amat->i[j]; 1560 sum = 0.0; 1561 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1562 sum += PetscAbsScalar(*v); v++; 1563 } 1564 v = bmat->a + bmat->i[j]; 1565 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1566 sum += PetscAbsScalar(*v); v++; 1567 } 1568 if (sum > ntemp) ntemp = sum; 1569 } 1570 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 1571 } else { 1572 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1573 } 1574 } 1575 PetscFunctionReturn(0); 1576 } 1577 1578 #undef __FUNCT__ 1579 #define __FUNCT__ "MatTranspose_MPIAIJ" 1580 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1581 { 1582 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1583 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1584 PetscErrorCode ierr; 1585 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i,*d_nnz; 1586 PetscInt cstart=A->cmap->rstart,ncol; 1587 Mat B; 1588 MatScalar *array; 1589 1590 PetscFunctionBegin; 1591 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1592 1593 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; 1594 ai = Aloc->i; aj = Aloc->j; 1595 bi = Bloc->i; bj = Bloc->j; 1596 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1597 /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */ 1598 ierr = PetscMalloc((1+na)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1599 ierr = PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));CHKERRQ(ierr); 1600 for (i=0; i<ai[ma]; i++){ 1601 d_nnz[aj[i]] ++; 1602 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1603 } 1604 1605 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1606 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1607 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1608 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);CHKERRQ(ierr); 1609 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1610 } else { 1611 B = *matout; 1612 } 1613 1614 /* copy over the A part */ 1615 array = Aloc->a; 1616 row = A->rmap->rstart; 1617 for (i=0; i<ma; i++) { 1618 ncol = ai[i+1]-ai[i]; 1619 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1620 row++; array += ncol; aj += ncol; 1621 } 1622 aj = Aloc->j; 1623 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1624 1625 /* copy over the B part */ 1626 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1627 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 1628 array = Bloc->a; 1629 row = A->rmap->rstart; 1630 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 1631 cols_tmp = cols; 1632 for (i=0; i<mb; i++) { 1633 ncol = bi[i+1]-bi[i]; 1634 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1635 row++; array += ncol; cols_tmp += ncol; 1636 } 1637 ierr = PetscFree(cols);CHKERRQ(ierr); 1638 1639 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1640 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1641 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1642 *matout = B; 1643 } else { 1644 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1645 } 1646 PetscFunctionReturn(0); 1647 } 1648 1649 #undef __FUNCT__ 1650 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1651 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1652 { 1653 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1654 Mat a = aij->A,b = aij->B; 1655 PetscErrorCode ierr; 1656 PetscInt s1,s2,s3; 1657 1658 PetscFunctionBegin; 1659 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1660 if (rr) { 1661 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1662 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1663 /* Overlap communication with computation. */ 1664 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1665 } 1666 if (ll) { 1667 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1668 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1669 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1670 } 1671 /* scale the diagonal block */ 1672 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1673 1674 if (rr) { 1675 /* Do a scatter end and then right scale the off-diagonal block */ 1676 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1678 } 1679 1680 PetscFunctionReturn(0); 1681 } 1682 1683 #undef __FUNCT__ 1684 #define __FUNCT__ "MatSetBlockSize_MPIAIJ" 1685 PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs) 1686 { 1687 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1688 PetscErrorCode ierr; 1689 1690 PetscFunctionBegin; 1691 ierr = MatSetBlockSize(a->A,bs);CHKERRQ(ierr); 1692 ierr = MatSetBlockSize(a->B,bs);CHKERRQ(ierr); 1693 PetscFunctionReturn(0); 1694 } 1695 #undef __FUNCT__ 1696 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1697 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 1698 { 1699 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1700 PetscErrorCode ierr; 1701 1702 PetscFunctionBegin; 1703 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1704 PetscFunctionReturn(0); 1705 } 1706 1707 #undef __FUNCT__ 1708 #define __FUNCT__ "MatEqual_MPIAIJ" 1709 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1710 { 1711 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1712 Mat a,b,c,d; 1713 PetscTruth flg; 1714 PetscErrorCode ierr; 1715 1716 PetscFunctionBegin; 1717 a = matA->A; b = matA->B; 1718 c = matB->A; d = matB->B; 1719 1720 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1721 if (flg) { 1722 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1723 } 1724 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1725 PetscFunctionReturn(0); 1726 } 1727 1728 #undef __FUNCT__ 1729 #define __FUNCT__ "MatCopy_MPIAIJ" 1730 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1731 { 1732 PetscErrorCode ierr; 1733 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1734 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1735 1736 PetscFunctionBegin; 1737 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1738 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1739 /* because of the column compression in the off-processor part of the matrix a->B, 1740 the number of columns in a->B and b->B may be different, hence we cannot call 1741 the MatCopy() directly on the two parts. If need be, we can provide a more 1742 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1743 then copying the submatrices */ 1744 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1745 } else { 1746 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1747 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1748 } 1749 PetscFunctionReturn(0); 1750 } 1751 1752 #undef __FUNCT__ 1753 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1754 PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A) 1755 { 1756 PetscErrorCode ierr; 1757 1758 PetscFunctionBegin; 1759 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1760 PetscFunctionReturn(0); 1761 } 1762 1763 #include "petscblaslapack.h" 1764 #undef __FUNCT__ 1765 #define __FUNCT__ "MatAXPY_MPIAIJ" 1766 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1767 { 1768 PetscErrorCode ierr; 1769 PetscInt i; 1770 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1771 PetscBLASInt bnz,one=1; 1772 Mat_SeqAIJ *x,*y; 1773 1774 PetscFunctionBegin; 1775 if (str == SAME_NONZERO_PATTERN) { 1776 PetscScalar alpha = a; 1777 x = (Mat_SeqAIJ *)xx->A->data; 1778 y = (Mat_SeqAIJ *)yy->A->data; 1779 bnz = PetscBLASIntCast(x->nz); 1780 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1781 x = (Mat_SeqAIJ *)xx->B->data; 1782 y = (Mat_SeqAIJ *)yy->B->data; 1783 bnz = PetscBLASIntCast(x->nz); 1784 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1785 } else if (str == SUBSET_NONZERO_PATTERN) { 1786 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 1787 1788 x = (Mat_SeqAIJ *)xx->B->data; 1789 y = (Mat_SeqAIJ *)yy->B->data; 1790 if (y->xtoy && y->XtoY != xx->B) { 1791 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1792 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1793 } 1794 if (!y->xtoy) { /* get xtoy */ 1795 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1796 y->XtoY = xx->B; 1797 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 1798 } 1799 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 1800 } else { 1801 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1802 } 1803 PetscFunctionReturn(0); 1804 } 1805 1806 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat); 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatConjugate_MPIAIJ" 1810 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_MPIAIJ(Mat mat) 1811 { 1812 #if defined(PETSC_USE_COMPLEX) 1813 PetscErrorCode ierr; 1814 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1815 1816 PetscFunctionBegin; 1817 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 1818 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 1819 #else 1820 PetscFunctionBegin; 1821 #endif 1822 PetscFunctionReturn(0); 1823 } 1824 1825 #undef __FUNCT__ 1826 #define __FUNCT__ "MatRealPart_MPIAIJ" 1827 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 1828 { 1829 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1830 PetscErrorCode ierr; 1831 1832 PetscFunctionBegin; 1833 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1834 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1835 PetscFunctionReturn(0); 1836 } 1837 1838 #undef __FUNCT__ 1839 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 1840 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 1841 { 1842 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1843 PetscErrorCode ierr; 1844 1845 PetscFunctionBegin; 1846 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1847 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1848 PetscFunctionReturn(0); 1849 } 1850 1851 #ifdef PETSC_HAVE_PBGL 1852 1853 #include <boost/parallel/mpi/bsp_process_group.hpp> 1854 #include <boost/graph/distributed/ilu_default_graph.hpp> 1855 #include <boost/graph/distributed/ilu_0_block.hpp> 1856 #include <boost/graph/distributed/ilu_preconditioner.hpp> 1857 #include <boost/graph/distributed/petsc/interface.hpp> 1858 #include <boost/multi_array.hpp> 1859 #include <boost/parallel/distributed_property_map->hpp> 1860 1861 #undef __FUNCT__ 1862 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 1863 /* 1864 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1865 */ 1866 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 1867 { 1868 namespace petsc = boost::distributed::petsc; 1869 1870 namespace graph_dist = boost::graph::distributed; 1871 using boost::graph::distributed::ilu_default::process_group_type; 1872 using boost::graph::ilu_permuted; 1873 1874 PetscTruth row_identity, col_identity; 1875 PetscContainer c; 1876 PetscInt m, n, M, N; 1877 PetscErrorCode ierr; 1878 1879 PetscFunctionBegin; 1880 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 1881 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 1882 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 1883 if (!row_identity || !col_identity) { 1884 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 1885 } 1886 1887 process_group_type pg; 1888 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1889 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 1890 lgraph_type& level_graph = *lgraph_p; 1891 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1892 1893 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 1894 ilu_permuted(level_graph); 1895 1896 /* put together the new matrix */ 1897 ierr = MatCreate(((PetscObject)A)->comm, fact);CHKERRQ(ierr); 1898 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 1899 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 1900 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 1901 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 1902 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1903 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1904 1905 ierr = PetscContainerCreate(((PetscObject)A)->comm, &c); 1906 ierr = PetscContainerSetPointer(c, lgraph_p); 1907 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 1908 PetscFunctionReturn(0); 1909 } 1910 1911 #undef __FUNCT__ 1912 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 1913 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 1914 { 1915 PetscFunctionBegin; 1916 PetscFunctionReturn(0); 1917 } 1918 1919 #undef __FUNCT__ 1920 #define __FUNCT__ "MatSolve_MPIAIJ" 1921 /* 1922 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1923 */ 1924 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 1925 { 1926 namespace graph_dist = boost::graph::distributed; 1927 1928 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1929 lgraph_type* lgraph_p; 1930 PetscContainer c; 1931 PetscErrorCode ierr; 1932 1933 PetscFunctionBegin; 1934 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 1935 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 1936 ierr = VecCopy(b, x); CHKERRQ(ierr); 1937 1938 PetscScalar* array_x; 1939 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 1940 PetscInt sx; 1941 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 1942 1943 PetscScalar* array_b; 1944 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 1945 PetscInt sb; 1946 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 1947 1948 lgraph_type& level_graph = *lgraph_p; 1949 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1950 1951 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 1952 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 1953 ref_x(array_x, boost::extents[num_vertices(graph)]); 1954 1955 typedef boost::iterator_property_map<array_ref_type::iterator, 1956 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 1957 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 1958 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 1959 1960 ilu_set_solve(*lgraph_p, vector_b, vector_x); 1961 1962 PetscFunctionReturn(0); 1963 } 1964 #endif 1965 1966 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 1967 PetscInt nzlocal,nsends,nrecvs; 1968 PetscMPIInt *send_rank; 1969 PetscInt *sbuf_nz,*sbuf_j,**rbuf_j; 1970 PetscScalar *sbuf_a,**rbuf_a; 1971 PetscErrorCode (*MatDestroy)(Mat); 1972 } Mat_Redundant; 1973 1974 #undef __FUNCT__ 1975 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 1976 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 1977 { 1978 PetscErrorCode ierr; 1979 Mat_Redundant *redund=(Mat_Redundant*)ptr; 1980 PetscInt i; 1981 1982 PetscFunctionBegin; 1983 ierr = PetscFree(redund->send_rank);CHKERRQ(ierr); 1984 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1985 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1986 for (i=0; i<redund->nrecvs; i++){ 1987 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1988 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1989 } 1990 ierr = PetscFree3(redund->sbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1991 ierr = PetscFree(redund);CHKERRQ(ierr); 1992 PetscFunctionReturn(0); 1993 } 1994 1995 #undef __FUNCT__ 1996 #define __FUNCT__ "MatDestroy_MatRedundant" 1997 PetscErrorCode MatDestroy_MatRedundant(Mat A) 1998 { 1999 PetscErrorCode ierr; 2000 PetscContainer container; 2001 Mat_Redundant *redund=PETSC_NULL; 2002 2003 PetscFunctionBegin; 2004 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2005 if (container) { 2006 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2007 } else { 2008 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2009 } 2010 A->ops->destroy = redund->MatDestroy; 2011 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 2012 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 2013 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 2014 PetscFunctionReturn(0); 2015 } 2016 2017 #undef __FUNCT__ 2018 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2019 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 2020 { 2021 PetscMPIInt rank,size; 2022 MPI_Comm comm=((PetscObject)mat)->comm; 2023 PetscErrorCode ierr; 2024 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 2025 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 2026 PetscInt *rowrange=mat->rmap->range; 2027 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2028 Mat A=aij->A,B=aij->B,C=*matredundant; 2029 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2030 PetscScalar *sbuf_a; 2031 PetscInt nzlocal=a->nz+b->nz; 2032 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2033 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray,M,N; 2034 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2035 MatScalar *aworkA,*aworkB; 2036 PetscScalar *vals; 2037 PetscMPIInt tag1,tag2,tag3,imdex; 2038 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 2039 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 2040 MPI_Status recv_status,*send_status; 2041 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 2042 PetscInt **rbuf_j=PETSC_NULL; 2043 PetscScalar **rbuf_a=PETSC_NULL; 2044 Mat_Redundant *redund=PETSC_NULL; 2045 PetscContainer container; 2046 2047 PetscFunctionBegin; 2048 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2049 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2050 2051 if (reuse == MAT_REUSE_MATRIX) { 2052 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2053 if (M != N || M != mat->rmap->N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2054 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 2055 if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 2056 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2057 if (container) { 2058 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2059 } else { 2060 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2061 } 2062 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2063 2064 nsends = redund->nsends; 2065 nrecvs = redund->nrecvs; 2066 send_rank = redund->send_rank; recv_rank = send_rank + size; 2067 sbuf_nz = redund->sbuf_nz; rbuf_nz = sbuf_nz + nsends; 2068 sbuf_j = redund->sbuf_j; 2069 sbuf_a = redund->sbuf_a; 2070 rbuf_j = redund->rbuf_j; 2071 rbuf_a = redund->rbuf_a; 2072 } 2073 2074 if (reuse == MAT_INITIAL_MATRIX){ 2075 PetscMPIInt subrank,subsize; 2076 PetscInt nleftover,np_subcomm; 2077 /* get the destination processors' id send_rank, nsends and nrecvs */ 2078 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2079 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2080 ierr = PetscMalloc((2*size+1)*sizeof(PetscMPIInt),&send_rank); 2081 recv_rank = send_rank + size; 2082 np_subcomm = size/nsubcomm; 2083 nleftover = size - nsubcomm*np_subcomm; 2084 nsends = 0; nrecvs = 0; 2085 for (i=0; i<size; i++){ /* i=rank*/ 2086 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 2087 send_rank[nsends] = i; nsends++; 2088 recv_rank[nrecvs++] = i; 2089 } 2090 } 2091 if (rank >= size - nleftover){/* this proc is a leftover processor */ 2092 i = size-nleftover-1; 2093 j = 0; 2094 while (j < nsubcomm - nleftover){ 2095 send_rank[nsends++] = i; 2096 i--; j++; 2097 } 2098 } 2099 2100 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 2101 for (i=0; i<nleftover; i++){ 2102 recv_rank[nrecvs++] = size-nleftover+i; 2103 } 2104 } 2105 2106 /* allocate sbuf_j, sbuf_a */ 2107 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2108 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2109 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2110 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2111 2112 /* copy mat's local entries into the buffers */ 2113 if (reuse == MAT_INITIAL_MATRIX){ 2114 rownz_max = 0; 2115 rptr = sbuf_j; 2116 cols = sbuf_j + rend-rstart + 1; 2117 vals = sbuf_a; 2118 rptr[0] = 0; 2119 for (i=0; i<rend-rstart; i++){ 2120 row = i + rstart; 2121 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2122 ncols = nzA + nzB; 2123 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2124 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2125 /* load the column indices for this row into cols */ 2126 lwrite = 0; 2127 for (l=0; l<nzB; l++) { 2128 if ((ctmp = bmap[cworkB[l]]) < cstart){ 2129 vals[lwrite] = aworkB[l]; 2130 cols[lwrite++] = ctmp; 2131 } 2132 } 2133 for (l=0; l<nzA; l++){ 2134 vals[lwrite] = aworkA[l]; 2135 cols[lwrite++] = cstart + cworkA[l]; 2136 } 2137 for (l=0; l<nzB; l++) { 2138 if ((ctmp = bmap[cworkB[l]]) >= cend){ 2139 vals[lwrite] = aworkB[l]; 2140 cols[lwrite++] = ctmp; 2141 } 2142 } 2143 vals += ncols; 2144 cols += ncols; 2145 rptr[i+1] = rptr[i] + ncols; 2146 if (rownz_max < ncols) rownz_max = ncols; 2147 } 2148 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(1, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2149 } else { /* only copy matrix values into sbuf_a */ 2150 rptr = sbuf_j; 2151 vals = sbuf_a; 2152 rptr[0] = 0; 2153 for (i=0; i<rend-rstart; i++){ 2154 row = i + rstart; 2155 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2156 ncols = nzA + nzB; 2157 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2158 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2159 lwrite = 0; 2160 for (l=0; l<nzB; l++) { 2161 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2162 } 2163 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2164 for (l=0; l<nzB; l++) { 2165 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2166 } 2167 vals += ncols; 2168 rptr[i+1] = rptr[i] + ncols; 2169 } 2170 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2171 2172 /* send nzlocal to others, and recv other's nzlocal */ 2173 /*--------------------------------------------------*/ 2174 if (reuse == MAT_INITIAL_MATRIX){ 2175 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2176 s_waits2 = s_waits3 + nsends; 2177 s_waits1 = s_waits2 + nsends; 2178 r_waits1 = s_waits1 + nsends; 2179 r_waits2 = r_waits1 + nrecvs; 2180 r_waits3 = r_waits2 + nrecvs; 2181 } else { 2182 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2183 r_waits3 = s_waits3 + nsends; 2184 } 2185 2186 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2187 if (reuse == MAT_INITIAL_MATRIX){ 2188 /* get new tags to keep the communication clean */ 2189 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2190 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2191 ierr = PetscMalloc3(nsends+nrecvs+1,PetscInt,&sbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2192 rbuf_nz = sbuf_nz + nsends; 2193 2194 /* post receives of other's nzlocal */ 2195 for (i=0; i<nrecvs; i++){ 2196 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2197 } 2198 /* send nzlocal to others */ 2199 for (i=0; i<nsends; i++){ 2200 sbuf_nz[i] = nzlocal; 2201 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2202 } 2203 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2204 count = nrecvs; 2205 while (count) { 2206 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2207 recv_rank[imdex] = recv_status.MPI_SOURCE; 2208 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2209 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2210 2211 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2212 rbuf_nz[imdex] += i + 2; 2213 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2214 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2215 count--; 2216 } 2217 /* wait on sends of nzlocal */ 2218 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2219 /* send mat->i,j to others, and recv from other's */ 2220 /*------------------------------------------------*/ 2221 for (i=0; i<nsends; i++){ 2222 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2223 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2224 } 2225 /* wait on receives of mat->i,j */ 2226 /*------------------------------*/ 2227 count = nrecvs; 2228 while (count) { 2229 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2230 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2231 count--; 2232 } 2233 /* wait on sends of mat->i,j */ 2234 /*---------------------------*/ 2235 if (nsends) { 2236 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2237 } 2238 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2239 2240 /* post receives, send and receive mat->a */ 2241 /*----------------------------------------*/ 2242 for (imdex=0; imdex<nrecvs; imdex++) { 2243 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2244 } 2245 for (i=0; i<nsends; i++){ 2246 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2247 } 2248 count = nrecvs; 2249 while (count) { 2250 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2251 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2252 count--; 2253 } 2254 if (nsends) { 2255 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2256 } 2257 2258 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2259 2260 /* create redundant matrix */ 2261 /*-------------------------*/ 2262 if (reuse == MAT_INITIAL_MATRIX){ 2263 /* compute rownz_max for preallocation */ 2264 for (imdex=0; imdex<nrecvs; imdex++){ 2265 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2266 rptr = rbuf_j[imdex]; 2267 for (i=0; i<j; i++){ 2268 ncols = rptr[i+1] - rptr[i]; 2269 if (rownz_max < ncols) rownz_max = ncols; 2270 } 2271 } 2272 2273 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2274 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2275 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2276 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2277 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2278 } else { 2279 C = *matredundant; 2280 } 2281 2282 /* insert local matrix entries */ 2283 rptr = sbuf_j; 2284 cols = sbuf_j + rend-rstart + 1; 2285 vals = sbuf_a; 2286 for (i=0; i<rend-rstart; i++){ 2287 row = i + rstart; 2288 ncols = rptr[i+1] - rptr[i]; 2289 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2290 vals += ncols; 2291 cols += ncols; 2292 } 2293 /* insert received matrix entries */ 2294 for (imdex=0; imdex<nrecvs; imdex++){ 2295 rstart = rowrange[recv_rank[imdex]]; 2296 rend = rowrange[recv_rank[imdex]+1]; 2297 rptr = rbuf_j[imdex]; 2298 cols = rbuf_j[imdex] + rend-rstart + 1; 2299 vals = rbuf_a[imdex]; 2300 for (i=0; i<rend-rstart; i++){ 2301 row = i + rstart; 2302 ncols = rptr[i+1] - rptr[i]; 2303 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2304 vals += ncols; 2305 cols += ncols; 2306 } 2307 } 2308 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2309 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2310 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2311 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_INCOMP,"redundant mat size %d != input mat size %d",M,mat->rmap->N); 2312 if (reuse == MAT_INITIAL_MATRIX){ 2313 PetscContainer container; 2314 *matredundant = C; 2315 /* create a supporting struct and attach it to C for reuse */ 2316 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2317 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2318 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2319 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2320 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2321 2322 redund->nzlocal = nzlocal; 2323 redund->nsends = nsends; 2324 redund->nrecvs = nrecvs; 2325 redund->send_rank = send_rank; 2326 redund->sbuf_nz = sbuf_nz; 2327 redund->sbuf_j = sbuf_j; 2328 redund->sbuf_a = sbuf_a; 2329 redund->rbuf_j = rbuf_j; 2330 redund->rbuf_a = rbuf_a; 2331 2332 redund->MatDestroy = C->ops->destroy; 2333 C->ops->destroy = MatDestroy_MatRedundant; 2334 } 2335 PetscFunctionReturn(0); 2336 } 2337 2338 #undef __FUNCT__ 2339 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2340 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2341 { 2342 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2343 PetscErrorCode ierr; 2344 PetscInt i,*idxb = 0; 2345 PetscScalar *va,*vb; 2346 Vec vtmp; 2347 2348 PetscFunctionBegin; 2349 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2350 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2351 if (idx) { 2352 for (i=0; i<A->rmap->n; i++) { 2353 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2354 } 2355 } 2356 2357 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2358 if (idx) { 2359 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2360 } 2361 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2362 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2363 2364 for (i=0; i<A->rmap->n; i++){ 2365 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2366 va[i] = vb[i]; 2367 if (idx) idx[i] = a->garray[idxb[i]]; 2368 } 2369 } 2370 2371 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2372 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2373 if (idxb) { 2374 ierr = PetscFree(idxb);CHKERRQ(ierr); 2375 } 2376 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 2377 PetscFunctionReturn(0); 2378 } 2379 2380 #undef __FUNCT__ 2381 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2382 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2383 { 2384 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2385 PetscErrorCode ierr; 2386 PetscInt i,*idxb = 0; 2387 PetscScalar *va,*vb; 2388 Vec vtmp; 2389 2390 PetscFunctionBegin; 2391 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2392 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2393 if (idx) { 2394 for (i=0; i<A->cmap->n; i++) { 2395 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2396 } 2397 } 2398 2399 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2400 if (idx) { 2401 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2402 } 2403 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2404 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2405 2406 for (i=0; i<A->rmap->n; i++){ 2407 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2408 va[i] = vb[i]; 2409 if (idx) idx[i] = a->garray[idxb[i]]; 2410 } 2411 } 2412 2413 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2414 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2415 if (idxb) { 2416 ierr = PetscFree(idxb);CHKERRQ(ierr); 2417 } 2418 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 2419 PetscFunctionReturn(0); 2420 } 2421 2422 #undef __FUNCT__ 2423 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2424 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2425 { 2426 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2427 PetscInt n = A->rmap->n; 2428 PetscInt cstart = A->cmap->rstart; 2429 PetscInt *cmap = mat->garray; 2430 PetscInt *diagIdx, *offdiagIdx; 2431 Vec diagV, offdiagV; 2432 PetscScalar *a, *diagA, *offdiagA; 2433 PetscInt r; 2434 PetscErrorCode ierr; 2435 2436 PetscFunctionBegin; 2437 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2438 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2439 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2440 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2441 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2442 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2443 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2444 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2445 for(r = 0; r < n; ++r) { 2446 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2447 a[r] = diagA[r]; 2448 idx[r] = cstart + diagIdx[r]; 2449 } else { 2450 a[r] = offdiagA[r]; 2451 idx[r] = cmap[offdiagIdx[r]]; 2452 } 2453 } 2454 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2455 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2456 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2457 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2458 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2459 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2460 PetscFunctionReturn(0); 2461 } 2462 2463 #undef __FUNCT__ 2464 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2465 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2466 { 2467 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2468 PetscInt n = A->rmap->n; 2469 PetscInt cstart = A->cmap->rstart; 2470 PetscInt *cmap = mat->garray; 2471 PetscInt *diagIdx, *offdiagIdx; 2472 Vec diagV, offdiagV; 2473 PetscScalar *a, *diagA, *offdiagA; 2474 PetscInt r; 2475 PetscErrorCode ierr; 2476 2477 PetscFunctionBegin; 2478 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2479 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2480 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2481 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2482 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2483 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2484 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2485 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2486 for(r = 0; r < n; ++r) { 2487 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2488 a[r] = diagA[r]; 2489 idx[r] = cstart + diagIdx[r]; 2490 } else { 2491 a[r] = offdiagA[r]; 2492 idx[r] = cmap[offdiagIdx[r]]; 2493 } 2494 } 2495 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2496 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2497 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2498 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2499 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2500 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2501 PetscFunctionReturn(0); 2502 } 2503 2504 #undef __FUNCT__ 2505 #define __FUNCT__ "MatGetSeqNonzerostructure_MPIAIJ" 2506 PetscErrorCode MatGetSeqNonzerostructure_MPIAIJ(Mat mat,Mat *newmat[]) 2507 { 2508 PetscErrorCode ierr; 2509 2510 PetscFunctionBegin; 2511 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,newmat);CHKERRQ(ierr); 2512 PetscFunctionReturn(0); 2513 } 2514 2515 /* -------------------------------------------------------------------*/ 2516 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2517 MatGetRow_MPIAIJ, 2518 MatRestoreRow_MPIAIJ, 2519 MatMult_MPIAIJ, 2520 /* 4*/ MatMultAdd_MPIAIJ, 2521 MatMultTranspose_MPIAIJ, 2522 MatMultTransposeAdd_MPIAIJ, 2523 #ifdef PETSC_HAVE_PBGL 2524 MatSolve_MPIAIJ, 2525 #else 2526 0, 2527 #endif 2528 0, 2529 0, 2530 /*10*/ 0, 2531 0, 2532 0, 2533 MatRelax_MPIAIJ, 2534 MatTranspose_MPIAIJ, 2535 /*15*/ MatGetInfo_MPIAIJ, 2536 MatEqual_MPIAIJ, 2537 MatGetDiagonal_MPIAIJ, 2538 MatDiagonalScale_MPIAIJ, 2539 MatNorm_MPIAIJ, 2540 /*20*/ MatAssemblyBegin_MPIAIJ, 2541 MatAssemblyEnd_MPIAIJ, 2542 0, 2543 MatSetOption_MPIAIJ, 2544 MatZeroEntries_MPIAIJ, 2545 /*25*/ MatZeroRows_MPIAIJ, 2546 0, 2547 #ifdef PETSC_HAVE_PBGL 2548 0, 2549 #else 2550 0, 2551 #endif 2552 0, 2553 0, 2554 /*30*/ MatSetUpPreallocation_MPIAIJ, 2555 #ifdef PETSC_HAVE_PBGL 2556 0, 2557 #else 2558 0, 2559 #endif 2560 0, 2561 0, 2562 0, 2563 /*35*/ MatDuplicate_MPIAIJ, 2564 0, 2565 0, 2566 0, 2567 0, 2568 /*40*/ MatAXPY_MPIAIJ, 2569 MatGetSubMatrices_MPIAIJ, 2570 MatIncreaseOverlap_MPIAIJ, 2571 MatGetValues_MPIAIJ, 2572 MatCopy_MPIAIJ, 2573 /*45*/ MatGetRowMax_MPIAIJ, 2574 MatScale_MPIAIJ, 2575 0, 2576 0, 2577 0, 2578 /*50*/ MatSetBlockSize_MPIAIJ, 2579 0, 2580 0, 2581 0, 2582 0, 2583 /*55*/ MatFDColoringCreate_MPIAIJ, 2584 0, 2585 MatSetUnfactored_MPIAIJ, 2586 MatPermute_MPIAIJ, 2587 0, 2588 /*60*/ MatGetSubMatrix_MPIAIJ, 2589 MatDestroy_MPIAIJ, 2590 MatView_MPIAIJ, 2591 0, 2592 0, 2593 /*65*/ 0, 2594 0, 2595 0, 2596 0, 2597 0, 2598 /*70*/ MatGetRowMaxAbs_MPIAIJ, 2599 MatGetRowMinAbs_MPIAIJ, 2600 0, 2601 MatSetColoring_MPIAIJ, 2602 #if defined(PETSC_HAVE_ADIC) 2603 MatSetValuesAdic_MPIAIJ, 2604 #else 2605 0, 2606 #endif 2607 MatSetValuesAdifor_MPIAIJ, 2608 /*75*/ 0, 2609 0, 2610 0, 2611 0, 2612 0, 2613 /*80*/ 0, 2614 0, 2615 0, 2616 /*84*/ MatLoad_MPIAIJ, 2617 0, 2618 0, 2619 0, 2620 0, 2621 0, 2622 /*90*/ MatMatMult_MPIAIJ_MPIAIJ, 2623 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2624 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2625 MatPtAP_Basic, 2626 MatPtAPSymbolic_MPIAIJ, 2627 /*95*/ MatPtAPNumeric_MPIAIJ, 2628 0, 2629 0, 2630 0, 2631 0, 2632 /*100*/0, 2633 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2634 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2635 MatConjugate_MPIAIJ, 2636 0, 2637 /*105*/MatSetValuesRow_MPIAIJ, 2638 MatRealPart_MPIAIJ, 2639 MatImaginaryPart_MPIAIJ, 2640 0, 2641 0, 2642 /*110*/0, 2643 MatGetRedundantMatrix_MPIAIJ, 2644 MatGetRowMin_MPIAIJ, 2645 0, 2646 0, 2647 /*115*/MatGetSeqNonzerostructure_MPIAIJ}; 2648 2649 /* ----------------------------------------------------------------------------------------*/ 2650 2651 EXTERN_C_BEGIN 2652 #undef __FUNCT__ 2653 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2654 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2655 { 2656 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2657 PetscErrorCode ierr; 2658 2659 PetscFunctionBegin; 2660 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2661 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2662 PetscFunctionReturn(0); 2663 } 2664 EXTERN_C_END 2665 2666 EXTERN_C_BEGIN 2667 #undef __FUNCT__ 2668 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2669 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2670 { 2671 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2672 PetscErrorCode ierr; 2673 2674 PetscFunctionBegin; 2675 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2676 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2677 PetscFunctionReturn(0); 2678 } 2679 EXTERN_C_END 2680 2681 #include "petscpc.h" 2682 EXTERN_C_BEGIN 2683 #undef __FUNCT__ 2684 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2685 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2686 { 2687 Mat_MPIAIJ *b; 2688 PetscErrorCode ierr; 2689 PetscInt i; 2690 2691 PetscFunctionBegin; 2692 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2693 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2694 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2695 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2696 2697 ierr = PetscMapSetBlockSize(B->rmap,1);CHKERRQ(ierr); 2698 ierr = PetscMapSetBlockSize(B->cmap,1);CHKERRQ(ierr); 2699 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2700 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2701 if (d_nnz) { 2702 for (i=0; i<B->rmap->n; i++) { 2703 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]); 2704 } 2705 } 2706 if (o_nnz) { 2707 for (i=0; i<B->rmap->n; i++) { 2708 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]); 2709 } 2710 } 2711 b = (Mat_MPIAIJ*)B->data; 2712 2713 if (!B->preallocated) { 2714 /* Explicitly create 2 MATSEQAIJ matrices. */ 2715 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2716 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2717 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2718 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2719 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2720 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2721 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2722 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2723 } 2724 2725 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2726 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2727 B->preallocated = PETSC_TRUE; 2728 PetscFunctionReturn(0); 2729 } 2730 EXTERN_C_END 2731 2732 #undef __FUNCT__ 2733 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2734 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2735 { 2736 Mat mat; 2737 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2738 PetscErrorCode ierr; 2739 2740 PetscFunctionBegin; 2741 *newmat = 0; 2742 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2743 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2744 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2745 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2746 a = (Mat_MPIAIJ*)mat->data; 2747 2748 mat->factor = matin->factor; 2749 mat->rmap->bs = matin->rmap->bs; 2750 mat->assembled = PETSC_TRUE; 2751 mat->insertmode = NOT_SET_VALUES; 2752 mat->preallocated = PETSC_TRUE; 2753 2754 a->size = oldmat->size; 2755 a->rank = oldmat->rank; 2756 a->donotstash = oldmat->donotstash; 2757 a->roworiented = oldmat->roworiented; 2758 a->rowindices = 0; 2759 a->rowvalues = 0; 2760 a->getrowactive = PETSC_FALSE; 2761 2762 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2763 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2764 2765 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2766 if (oldmat->colmap) { 2767 #if defined (PETSC_USE_CTABLE) 2768 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2769 #else 2770 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2771 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2772 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2773 #endif 2774 } else a->colmap = 0; 2775 if (oldmat->garray) { 2776 PetscInt len; 2777 len = oldmat->B->cmap->n; 2778 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2779 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2780 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2781 } else a->garray = 0; 2782 2783 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2784 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2785 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2786 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2787 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2788 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2789 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2790 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2791 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2792 *newmat = mat; 2793 PetscFunctionReturn(0); 2794 } 2795 2796 #include "petscsys.h" 2797 2798 #undef __FUNCT__ 2799 #define __FUNCT__ "MatLoad_MPIAIJ" 2800 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2801 { 2802 Mat A; 2803 PetscScalar *vals,*svals; 2804 MPI_Comm comm = ((PetscObject)viewer)->comm; 2805 MPI_Status status; 2806 PetscErrorCode ierr; 2807 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,mpicnt,mpimaxnz; 2808 PetscInt i,nz,j,rstart,rend,mmax,maxnz; 2809 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2810 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2811 PetscInt cend,cstart,n,*rowners; 2812 int fd; 2813 2814 PetscFunctionBegin; 2815 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2816 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2817 if (!rank) { 2818 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2819 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2820 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2821 } 2822 2823 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2824 M = header[1]; N = header[2]; 2825 /* determine ownership of all rows */ 2826 m = M/size + ((M % size) > rank); 2827 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2828 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2829 2830 /* First process needs enough room for process with most rows */ 2831 if (!rank) { 2832 mmax = rowners[1]; 2833 for (i=2; i<size; i++) { 2834 mmax = PetscMax(mmax,rowners[i]); 2835 } 2836 } else mmax = m; 2837 2838 rowners[0] = 0; 2839 for (i=2; i<=size; i++) { 2840 rowners[i] += rowners[i-1]; 2841 } 2842 rstart = rowners[rank]; 2843 rend = rowners[rank+1]; 2844 2845 /* distribute row lengths to all processors */ 2846 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2847 if (!rank) { 2848 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2849 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2850 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2851 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2852 for (j=0; j<m; j++) { 2853 procsnz[0] += ourlens[j]; 2854 } 2855 for (i=1; i<size; i++) { 2856 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2857 /* calculate the number of nonzeros on each processor */ 2858 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2859 procsnz[i] += rowlengths[j]; 2860 } 2861 mpicnt = PetscMPIIntCast(rowners[i+1]-rowners[i]); 2862 ierr = MPI_Send(rowlengths,mpicnt,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2863 } 2864 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2865 } else { 2866 mpicnt = PetscMPIIntCast(m);CHKERRQ(ierr); 2867 ierr = MPI_Recv(ourlens,mpicnt,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2868 } 2869 2870 if (!rank) { 2871 /* determine max buffer needed and allocate it */ 2872 maxnz = 0; 2873 for (i=0; i<size; i++) { 2874 maxnz = PetscMax(maxnz,procsnz[i]); 2875 } 2876 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2877 2878 /* read in my part of the matrix column indices */ 2879 nz = procsnz[0]; 2880 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2881 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2882 2883 /* read in every one elses and ship off */ 2884 for (i=1; i<size; i++) { 2885 nz = procsnz[i]; 2886 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2887 mpicnt = PetscMPIIntCast(nz); 2888 ierr = MPI_Send(cols,mpicnt,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2889 } 2890 ierr = PetscFree(cols);CHKERRQ(ierr); 2891 } else { 2892 /* determine buffer space needed for message */ 2893 nz = 0; 2894 for (i=0; i<m; i++) { 2895 nz += ourlens[i]; 2896 } 2897 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2898 2899 /* receive message of column indices*/ 2900 mpicnt = PetscMPIIntCast(nz);CHKERRQ(ierr); 2901 ierr = MPI_Recv(mycols,mpicnt,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2902 ierr = MPI_Get_count(&status,MPIU_INT,&mpimaxnz);CHKERRQ(ierr); 2903 if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);} 2904 else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);} 2905 else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);} 2906 } 2907 2908 /* determine column ownership if matrix is not square */ 2909 if (N != M) { 2910 n = N/size + ((N % size) > rank); 2911 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2912 cstart = cend - n; 2913 } else { 2914 cstart = rstart; 2915 cend = rend; 2916 n = cend - cstart; 2917 } 2918 2919 /* loop over local rows, determining number of off diagonal entries */ 2920 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2921 jj = 0; 2922 for (i=0; i<m; i++) { 2923 for (j=0; j<ourlens[i]; j++) { 2924 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2925 jj++; 2926 } 2927 } 2928 2929 /* create our matrix */ 2930 for (i=0; i<m; i++) { 2931 ourlens[i] -= offlens[i]; 2932 } 2933 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2934 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2935 ierr = MatSetType(A,type);CHKERRQ(ierr); 2936 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2937 2938 for (i=0; i<m; i++) { 2939 ourlens[i] += offlens[i]; 2940 } 2941 2942 if (!rank) { 2943 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2944 2945 /* read in my part of the matrix numerical values */ 2946 nz = procsnz[0]; 2947 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2948 2949 /* insert into matrix */ 2950 jj = rstart; 2951 smycols = mycols; 2952 svals = vals; 2953 for (i=0; i<m; i++) { 2954 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2955 smycols += ourlens[i]; 2956 svals += ourlens[i]; 2957 jj++; 2958 } 2959 2960 /* read in other processors and ship out */ 2961 for (i=1; i<size; i++) { 2962 nz = procsnz[i]; 2963 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2964 mpicnt = PetscMPIIntCast(nz); 2965 ierr = MPI_Send(vals,mpicnt,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2966 } 2967 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2968 } else { 2969 /* receive numeric values */ 2970 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2971 2972 /* receive message of values*/ 2973 mpicnt = PetscMPIIntCast(nz); 2974 ierr = MPI_Recv(vals,mpicnt,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2975 ierr = MPI_Get_count(&status,MPIU_SCALAR,&mpimaxnz);CHKERRQ(ierr); 2976 if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);} 2977 else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);} 2978 else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);} 2979 2980 /* insert into matrix */ 2981 jj = rstart; 2982 smycols = mycols; 2983 svals = vals; 2984 for (i=0; i<m; i++) { 2985 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2986 smycols += ourlens[i]; 2987 svals += ourlens[i]; 2988 jj++; 2989 } 2990 } 2991 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2992 ierr = PetscFree(vals);CHKERRQ(ierr); 2993 ierr = PetscFree(mycols);CHKERRQ(ierr); 2994 ierr = PetscFree(rowners);CHKERRQ(ierr); 2995 2996 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2997 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2998 *newmat = A; 2999 PetscFunctionReturn(0); 3000 } 3001 3002 #undef __FUNCT__ 3003 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3004 /* 3005 Not great since it makes two copies of the submatrix, first an SeqAIJ 3006 in local and then by concatenating the local matrices the end result. 3007 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3008 */ 3009 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3010 { 3011 PetscErrorCode ierr; 3012 PetscMPIInt rank,size; 3013 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 3014 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3015 Mat *local,M,Mreuse; 3016 MatScalar *vwork,*aa; 3017 MPI_Comm comm = ((PetscObject)mat)->comm; 3018 Mat_SeqAIJ *aij; 3019 3020 3021 PetscFunctionBegin; 3022 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3023 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3024 3025 if (call == MAT_REUSE_MATRIX) { 3026 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 3027 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3028 local = &Mreuse; 3029 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 3030 } else { 3031 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 3032 Mreuse = *local; 3033 ierr = PetscFree(local);CHKERRQ(ierr); 3034 } 3035 3036 /* 3037 m - number of local rows 3038 n - number of columns (same on all processors) 3039 rstart - first row in new global matrix generated 3040 */ 3041 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3042 if (call == MAT_INITIAL_MATRIX) { 3043 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3044 ii = aij->i; 3045 jj = aij->j; 3046 3047 /* 3048 Determine the number of non-zeros in the diagonal and off-diagonal 3049 portions of the matrix in order to do correct preallocation 3050 */ 3051 3052 /* first get start and end of "diagonal" columns */ 3053 if (csize == PETSC_DECIDE) { 3054 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3055 if (mglobal == n) { /* square matrix */ 3056 nlocal = m; 3057 } else { 3058 nlocal = n/size + ((n % size) > rank); 3059 } 3060 } else { 3061 nlocal = csize; 3062 } 3063 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3064 rstart = rend - nlocal; 3065 if (rank == size - 1 && rend != n) { 3066 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3067 } 3068 3069 /* next, compute all the lengths */ 3070 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3071 olens = dlens + m; 3072 for (i=0; i<m; i++) { 3073 jend = ii[i+1] - ii[i]; 3074 olen = 0; 3075 dlen = 0; 3076 for (j=0; j<jend; j++) { 3077 if (*jj < rstart || *jj >= rend) olen++; 3078 else dlen++; 3079 jj++; 3080 } 3081 olens[i] = olen; 3082 dlens[i] = dlen; 3083 } 3084 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3085 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3086 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3087 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3088 ierr = PetscFree(dlens);CHKERRQ(ierr); 3089 } else { 3090 PetscInt ml,nl; 3091 3092 M = *newmat; 3093 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3094 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3095 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3096 /* 3097 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3098 rather than the slower MatSetValues(). 3099 */ 3100 M->was_assembled = PETSC_TRUE; 3101 M->assembled = PETSC_FALSE; 3102 } 3103 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3104 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3105 ii = aij->i; 3106 jj = aij->j; 3107 aa = aij->a; 3108 for (i=0; i<m; i++) { 3109 row = rstart + i; 3110 nz = ii[i+1] - ii[i]; 3111 cwork = jj; jj += nz; 3112 vwork = aa; aa += nz; 3113 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3114 } 3115 3116 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3117 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3118 *newmat = M; 3119 3120 /* save submatrix used in processor for next request */ 3121 if (call == MAT_INITIAL_MATRIX) { 3122 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3123 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 3124 } 3125 3126 PetscFunctionReturn(0); 3127 } 3128 3129 EXTERN_C_BEGIN 3130 #undef __FUNCT__ 3131 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3132 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3133 { 3134 PetscInt m,cstart, cend,j,nnz,i,d; 3135 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3136 const PetscInt *JJ; 3137 PetscScalar *values; 3138 PetscErrorCode ierr; 3139 3140 PetscFunctionBegin; 3141 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3142 3143 ierr = PetscMapSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3144 ierr = PetscMapSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3145 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 3146 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 3147 m = B->rmap->n; 3148 cstart = B->cmap->rstart; 3149 cend = B->cmap->rend; 3150 rstart = B->rmap->rstart; 3151 3152 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 3153 o_nnz = d_nnz + m; 3154 3155 #if defined(PETSC_USE_DEBUGGING) 3156 for (i=0; i<m; i++) { 3157 nnz = Ii[i+1]- Ii[i]; 3158 JJ = J + Ii[i]; 3159 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3160 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3161 if (nnz && (JJ[nnz-1] >= B->cmap->N) SETERRRQ3(PETSC_ERR_ARG_WRONGSTATE,"Row %D ends with too large a column index %D (max allowed %D)",i,JJ[nnz-1],B->cmap->N); 3162 for (j=1; j<nnz; j++) { 3163 if (JJ[i] <= JJ[i-1]) SETERRRQ(PETSC_ERR_ARG_WRONGSTATE,"Row %D has unsorted column index at %D location in column indices",i,j); 3164 } 3165 } 3166 #endif 3167 3168 for (i=0; i<m; i++) { 3169 nnz = Ii[i+1]- Ii[i]; 3170 JJ = J + Ii[i]; 3171 nnz_max = PetscMax(nnz_max,nnz); 3172 for (j=0; j<nnz; j++) { 3173 if (*JJ >= cstart) break; 3174 JJ++; 3175 } 3176 d = 0; 3177 for (; j<nnz; j++) { 3178 if (*JJ++ >= cend) break; 3179 d++; 3180 } 3181 d_nnz[i] = d; 3182 o_nnz[i] = nnz - d; 3183 } 3184 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3185 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 3186 3187 if (v) values = (PetscScalar*)v; 3188 else { 3189 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3190 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3191 } 3192 3193 for (i=0; i<m; i++) { 3194 ii = i + rstart; 3195 nnz = Ii[i+1]- Ii[i]; 3196 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3197 } 3198 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3199 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3200 3201 if (!v) { 3202 ierr = PetscFree(values);CHKERRQ(ierr); 3203 } 3204 PetscFunctionReturn(0); 3205 } 3206 EXTERN_C_END 3207 3208 #undef __FUNCT__ 3209 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3210 /*@ 3211 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3212 (the default parallel PETSc format). 3213 3214 Collective on MPI_Comm 3215 3216 Input Parameters: 3217 + B - the matrix 3218 . i - the indices into j for the start of each local row (starts with zero) 3219 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3220 - v - optional values in the matrix 3221 3222 Level: developer 3223 3224 Notes: 3225 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3226 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3227 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3228 3229 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3230 3231 The format which is used for the sparse matrix input, is equivalent to a 3232 row-major ordering.. i.e for the following matrix, the input data expected is 3233 as shown: 3234 3235 1 0 0 3236 2 0 3 P0 3237 ------- 3238 4 5 6 P1 3239 3240 Process0 [P0]: rows_owned=[0,1] 3241 i = {0,1,3} [size = nrow+1 = 2+1] 3242 j = {0,0,2} [size = nz = 6] 3243 v = {1,2,3} [size = nz = 6] 3244 3245 Process1 [P1]: rows_owned=[2] 3246 i = {0,3} [size = nrow+1 = 1+1] 3247 j = {0,1,2} [size = nz = 6] 3248 v = {4,5,6} [size = nz = 6] 3249 3250 The column indices for each row MUST be sorted. 3251 3252 .keywords: matrix, aij, compressed row, sparse, parallel 3253 3254 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 3255 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3256 @*/ 3257 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3258 { 3259 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3260 3261 PetscFunctionBegin; 3262 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3263 if (f) { 3264 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3265 } 3266 PetscFunctionReturn(0); 3267 } 3268 3269 #undef __FUNCT__ 3270 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3271 /*@C 3272 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3273 (the default parallel PETSc format). For good matrix assembly performance 3274 the user should preallocate the matrix storage by setting the parameters 3275 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3276 performance can be increased by more than a factor of 50. 3277 3278 Collective on MPI_Comm 3279 3280 Input Parameters: 3281 + A - the matrix 3282 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3283 (same value is used for all local rows) 3284 . d_nnz - array containing the number of nonzeros in the various rows of the 3285 DIAGONAL portion of the local submatrix (possibly different for each row) 3286 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3287 The size of this array is equal to the number of local rows, i.e 'm'. 3288 You must leave room for the diagonal entry even if it is zero. 3289 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3290 submatrix (same value is used for all local rows). 3291 - o_nnz - array containing the number of nonzeros in the various rows of the 3292 OFF-DIAGONAL portion of the local submatrix (possibly different for 3293 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3294 structure. The size of this array is equal to the number 3295 of local rows, i.e 'm'. 3296 3297 If the *_nnz parameter is given then the *_nz parameter is ignored 3298 3299 The AIJ format (also called the Yale sparse matrix format or 3300 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3301 storage. The stored row and column indices begin with zero. See the users manual for details. 3302 3303 The parallel matrix is partitioned such that the first m0 rows belong to 3304 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3305 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3306 3307 The DIAGONAL portion of the local submatrix of a processor can be defined 3308 as the submatrix which is obtained by extraction the part corresponding 3309 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 3310 first row that belongs to the processor, and r2 is the last row belonging 3311 to the this processor. This is a square mxm matrix. The remaining portion 3312 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 3313 3314 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3315 3316 You can call MatGetInfo() to get information on how effective the preallocation was; 3317 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3318 You can also run with the option -info and look for messages with the string 3319 malloc in them to see if additional memory allocation was needed. 3320 3321 Example usage: 3322 3323 Consider the following 8x8 matrix with 34 non-zero values, that is 3324 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3325 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3326 as follows: 3327 3328 .vb 3329 1 2 0 | 0 3 0 | 0 4 3330 Proc0 0 5 6 | 7 0 0 | 8 0 3331 9 0 10 | 11 0 0 | 12 0 3332 ------------------------------------- 3333 13 0 14 | 15 16 17 | 0 0 3334 Proc1 0 18 0 | 19 20 21 | 0 0 3335 0 0 0 | 22 23 0 | 24 0 3336 ------------------------------------- 3337 Proc2 25 26 27 | 0 0 28 | 29 0 3338 30 0 0 | 31 32 33 | 0 34 3339 .ve 3340 3341 This can be represented as a collection of submatrices as: 3342 3343 .vb 3344 A B C 3345 D E F 3346 G H I 3347 .ve 3348 3349 Where the submatrices A,B,C are owned by proc0, D,E,F are 3350 owned by proc1, G,H,I are owned by proc2. 3351 3352 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3353 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3354 The 'M','N' parameters are 8,8, and have the same values on all procs. 3355 3356 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3357 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3358 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3359 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3360 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3361 matrix, ans [DF] as another SeqAIJ matrix. 3362 3363 When d_nz, o_nz parameters are specified, d_nz storage elements are 3364 allocated for every row of the local diagonal submatrix, and o_nz 3365 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3366 One way to choose d_nz and o_nz is to use the max nonzerors per local 3367 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3368 In this case, the values of d_nz,o_nz are: 3369 .vb 3370 proc0 : dnz = 2, o_nz = 2 3371 proc1 : dnz = 3, o_nz = 2 3372 proc2 : dnz = 1, o_nz = 4 3373 .ve 3374 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3375 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3376 for proc3. i.e we are using 12+15+10=37 storage locations to store 3377 34 values. 3378 3379 When d_nnz, o_nnz parameters are specified, the storage is specified 3380 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3381 In the above case the values for d_nnz,o_nnz are: 3382 .vb 3383 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3384 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3385 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3386 .ve 3387 Here the space allocated is sum of all the above values i.e 34, and 3388 hence pre-allocation is perfect. 3389 3390 Level: intermediate 3391 3392 .keywords: matrix, aij, compressed row, sparse, parallel 3393 3394 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3395 MPIAIJ, MatGetInfo() 3396 @*/ 3397 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3398 { 3399 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3400 3401 PetscFunctionBegin; 3402 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3403 if (f) { 3404 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3405 } 3406 PetscFunctionReturn(0); 3407 } 3408 3409 #undef __FUNCT__ 3410 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3411 /*@ 3412 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3413 CSR format the local rows. 3414 3415 Collective on MPI_Comm 3416 3417 Input Parameters: 3418 + comm - MPI communicator 3419 . m - number of local rows (Cannot be PETSC_DECIDE) 3420 . n - This value should be the same as the local size used in creating the 3421 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3422 calculated if N is given) For square matrices n is almost always m. 3423 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3424 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3425 . i - row indices 3426 . j - column indices 3427 - a - matrix values 3428 3429 Output Parameter: 3430 . mat - the matrix 3431 3432 Level: intermediate 3433 3434 Notes: 3435 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3436 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3437 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3438 3439 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3440 3441 The format which is used for the sparse matrix input, is equivalent to a 3442 row-major ordering.. i.e for the following matrix, the input data expected is 3443 as shown: 3444 3445 1 0 0 3446 2 0 3 P0 3447 ------- 3448 4 5 6 P1 3449 3450 Process0 [P0]: rows_owned=[0,1] 3451 i = {0,1,3} [size = nrow+1 = 2+1] 3452 j = {0,0,2} [size = nz = 6] 3453 v = {1,2,3} [size = nz = 6] 3454 3455 Process1 [P1]: rows_owned=[2] 3456 i = {0,3} [size = nrow+1 = 1+1] 3457 j = {0,1,2} [size = nz = 6] 3458 v = {4,5,6} [size = nz = 6] 3459 3460 .keywords: matrix, aij, compressed row, sparse, parallel 3461 3462 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3463 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3464 @*/ 3465 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3466 { 3467 PetscErrorCode ierr; 3468 3469 PetscFunctionBegin; 3470 if (i[0]) { 3471 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3472 } 3473 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3474 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3475 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3476 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3477 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3478 PetscFunctionReturn(0); 3479 } 3480 3481 #undef __FUNCT__ 3482 #define __FUNCT__ "MatCreateMPIAIJ" 3483 /*@C 3484 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3485 (the default parallel PETSc format). For good matrix assembly performance 3486 the user should preallocate the matrix storage by setting the parameters 3487 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3488 performance can be increased by more than a factor of 50. 3489 3490 Collective on MPI_Comm 3491 3492 Input Parameters: 3493 + comm - MPI communicator 3494 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3495 This value should be the same as the local size used in creating the 3496 y vector for the matrix-vector product y = Ax. 3497 . n - This value should be the same as the local size used in creating the 3498 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3499 calculated if N is given) For square matrices n is almost always m. 3500 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3501 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3502 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3503 (same value is used for all local rows) 3504 . d_nnz - array containing the number of nonzeros in the various rows of the 3505 DIAGONAL portion of the local submatrix (possibly different for each row) 3506 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3507 The size of this array is equal to the number of local rows, i.e 'm'. 3508 You must leave room for the diagonal entry even if it is zero. 3509 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3510 submatrix (same value is used for all local rows). 3511 - o_nnz - array containing the number of nonzeros in the various rows of the 3512 OFF-DIAGONAL portion of the local submatrix (possibly different for 3513 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3514 structure. The size of this array is equal to the number 3515 of local rows, i.e 'm'. 3516 3517 Output Parameter: 3518 . A - the matrix 3519 3520 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3521 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3522 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3523 3524 Notes: 3525 If the *_nnz parameter is given then the *_nz parameter is ignored 3526 3527 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3528 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3529 storage requirements for this matrix. 3530 3531 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3532 processor than it must be used on all processors that share the object for 3533 that argument. 3534 3535 The user MUST specify either the local or global matrix dimensions 3536 (possibly both). 3537 3538 The parallel matrix is partitioned across processors such that the 3539 first m0 rows belong to process 0, the next m1 rows belong to 3540 process 1, the next m2 rows belong to process 2 etc.. where 3541 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3542 values corresponding to [m x N] submatrix. 3543 3544 The columns are logically partitioned with the n0 columns belonging 3545 to 0th partition, the next n1 columns belonging to the next 3546 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3547 3548 The DIAGONAL portion of the local submatrix on any given processor 3549 is the submatrix corresponding to the rows and columns m,n 3550 corresponding to the given processor. i.e diagonal matrix on 3551 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3552 etc. The remaining portion of the local submatrix [m x (N-n)] 3553 constitute the OFF-DIAGONAL portion. The example below better 3554 illustrates this concept. 3555 3556 For a square global matrix we define each processor's diagonal portion 3557 to be its local rows and the corresponding columns (a square submatrix); 3558 each processor's off-diagonal portion encompasses the remainder of the 3559 local matrix (a rectangular submatrix). 3560 3561 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3562 3563 When calling this routine with a single process communicator, a matrix of 3564 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3565 type of communicator, use the construction mechanism: 3566 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3567 3568 By default, this format uses inodes (identical nodes) when possible. 3569 We search for consecutive rows with the same nonzero structure, thereby 3570 reusing matrix information to achieve increased efficiency. 3571 3572 Options Database Keys: 3573 + -mat_no_inode - Do not use inodes 3574 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3575 - -mat_aij_oneindex - Internally use indexing starting at 1 3576 rather than 0. Note that when calling MatSetValues(), 3577 the user still MUST index entries starting at 0! 3578 3579 3580 Example usage: 3581 3582 Consider the following 8x8 matrix with 34 non-zero values, that is 3583 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3584 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3585 as follows: 3586 3587 .vb 3588 1 2 0 | 0 3 0 | 0 4 3589 Proc0 0 5 6 | 7 0 0 | 8 0 3590 9 0 10 | 11 0 0 | 12 0 3591 ------------------------------------- 3592 13 0 14 | 15 16 17 | 0 0 3593 Proc1 0 18 0 | 19 20 21 | 0 0 3594 0 0 0 | 22 23 0 | 24 0 3595 ------------------------------------- 3596 Proc2 25 26 27 | 0 0 28 | 29 0 3597 30 0 0 | 31 32 33 | 0 34 3598 .ve 3599 3600 This can be represented as a collection of submatrices as: 3601 3602 .vb 3603 A B C 3604 D E F 3605 G H I 3606 .ve 3607 3608 Where the submatrices A,B,C are owned by proc0, D,E,F are 3609 owned by proc1, G,H,I are owned by proc2. 3610 3611 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3612 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3613 The 'M','N' parameters are 8,8, and have the same values on all procs. 3614 3615 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3616 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3617 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3618 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3619 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3620 matrix, ans [DF] as another SeqAIJ matrix. 3621 3622 When d_nz, o_nz parameters are specified, d_nz storage elements are 3623 allocated for every row of the local diagonal submatrix, and o_nz 3624 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3625 One way to choose d_nz and o_nz is to use the max nonzerors per local 3626 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3627 In this case, the values of d_nz,o_nz are: 3628 .vb 3629 proc0 : dnz = 2, o_nz = 2 3630 proc1 : dnz = 3, o_nz = 2 3631 proc2 : dnz = 1, o_nz = 4 3632 .ve 3633 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3634 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3635 for proc3. i.e we are using 12+15+10=37 storage locations to store 3636 34 values. 3637 3638 When d_nnz, o_nnz parameters are specified, the storage is specified 3639 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3640 In the above case the values for d_nnz,o_nnz are: 3641 .vb 3642 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3643 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3644 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3645 .ve 3646 Here the space allocated is sum of all the above values i.e 34, and 3647 hence pre-allocation is perfect. 3648 3649 Level: intermediate 3650 3651 .keywords: matrix, aij, compressed row, sparse, parallel 3652 3653 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3654 MPIAIJ, MatCreateMPIAIJWithArrays() 3655 @*/ 3656 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 3657 { 3658 PetscErrorCode ierr; 3659 PetscMPIInt size; 3660 3661 PetscFunctionBegin; 3662 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3663 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3664 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3665 if (size > 1) { 3666 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3667 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3668 } else { 3669 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3670 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3671 } 3672 PetscFunctionReturn(0); 3673 } 3674 3675 #undef __FUNCT__ 3676 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3677 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3678 { 3679 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3680 3681 PetscFunctionBegin; 3682 *Ad = a->A; 3683 *Ao = a->B; 3684 *colmap = a->garray; 3685 PetscFunctionReturn(0); 3686 } 3687 3688 #undef __FUNCT__ 3689 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3690 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3691 { 3692 PetscErrorCode ierr; 3693 PetscInt i; 3694 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3695 3696 PetscFunctionBegin; 3697 if (coloring->ctype == IS_COLORING_GLOBAL) { 3698 ISColoringValue *allcolors,*colors; 3699 ISColoring ocoloring; 3700 3701 /* set coloring for diagonal portion */ 3702 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3703 3704 /* set coloring for off-diagonal portion */ 3705 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3706 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3707 for (i=0; i<a->B->cmap->n; i++) { 3708 colors[i] = allcolors[a->garray[i]]; 3709 } 3710 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3711 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3712 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3713 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3714 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3715 ISColoringValue *colors; 3716 PetscInt *larray; 3717 ISColoring ocoloring; 3718 3719 /* set coloring for diagonal portion */ 3720 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3721 for (i=0; i<a->A->cmap->n; i++) { 3722 larray[i] = i + A->cmap->rstart; 3723 } 3724 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3725 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3726 for (i=0; i<a->A->cmap->n; i++) { 3727 colors[i] = coloring->colors[larray[i]]; 3728 } 3729 ierr = PetscFree(larray);CHKERRQ(ierr); 3730 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3731 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3732 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3733 3734 /* set coloring for off-diagonal portion */ 3735 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3736 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3737 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3738 for (i=0; i<a->B->cmap->n; i++) { 3739 colors[i] = coloring->colors[larray[i]]; 3740 } 3741 ierr = PetscFree(larray);CHKERRQ(ierr); 3742 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3743 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3744 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3745 } else { 3746 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3747 } 3748 3749 PetscFunctionReturn(0); 3750 } 3751 3752 #if defined(PETSC_HAVE_ADIC) 3753 #undef __FUNCT__ 3754 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3755 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3756 { 3757 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3758 PetscErrorCode ierr; 3759 3760 PetscFunctionBegin; 3761 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3762 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3763 PetscFunctionReturn(0); 3764 } 3765 #endif 3766 3767 #undef __FUNCT__ 3768 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3769 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3770 { 3771 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3772 PetscErrorCode ierr; 3773 3774 PetscFunctionBegin; 3775 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3776 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3777 PetscFunctionReturn(0); 3778 } 3779 3780 #undef __FUNCT__ 3781 #define __FUNCT__ "MatMerge" 3782 /*@ 3783 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3784 matrices from each processor 3785 3786 Collective on MPI_Comm 3787 3788 Input Parameters: 3789 + comm - the communicators the parallel matrix will live on 3790 . inmat - the input sequential matrices 3791 . n - number of local columns (or PETSC_DECIDE) 3792 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3793 3794 Output Parameter: 3795 . outmat - the parallel matrix generated 3796 3797 Level: advanced 3798 3799 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3800 3801 @*/ 3802 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3803 { 3804 PetscErrorCode ierr; 3805 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3806 PetscInt *indx; 3807 PetscScalar *values; 3808 3809 PetscFunctionBegin; 3810 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3811 if (scall == MAT_INITIAL_MATRIX){ 3812 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3813 if (n == PETSC_DECIDE){ 3814 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3815 } 3816 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3817 rstart -= m; 3818 3819 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3820 for (i=0;i<m;i++) { 3821 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3822 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3823 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3824 } 3825 /* This routine will ONLY return MPIAIJ type matrix */ 3826 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3827 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3828 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3829 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3830 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3831 3832 } else if (scall == MAT_REUSE_MATRIX){ 3833 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3834 } else { 3835 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3836 } 3837 3838 for (i=0;i<m;i++) { 3839 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3840 Ii = i + rstart; 3841 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3842 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3843 } 3844 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3845 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3846 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3847 3848 PetscFunctionReturn(0); 3849 } 3850 3851 #undef __FUNCT__ 3852 #define __FUNCT__ "MatFileSplit" 3853 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3854 { 3855 PetscErrorCode ierr; 3856 PetscMPIInt rank; 3857 PetscInt m,N,i,rstart,nnz; 3858 size_t len; 3859 const PetscInt *indx; 3860 PetscViewer out; 3861 char *name; 3862 Mat B; 3863 const PetscScalar *values; 3864 3865 PetscFunctionBegin; 3866 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3867 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3868 /* Should this be the type of the diagonal block of A? */ 3869 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3870 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3871 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3872 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3873 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3874 for (i=0;i<m;i++) { 3875 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3876 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3877 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3878 } 3879 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3880 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3881 3882 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3883 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3884 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3885 sprintf(name,"%s.%d",outfile,rank); 3886 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3887 ierr = PetscFree(name); 3888 ierr = MatView(B,out);CHKERRQ(ierr); 3889 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3890 ierr = MatDestroy(B);CHKERRQ(ierr); 3891 PetscFunctionReturn(0); 3892 } 3893 3894 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3895 #undef __FUNCT__ 3896 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3897 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3898 { 3899 PetscErrorCode ierr; 3900 Mat_Merge_SeqsToMPI *merge; 3901 PetscContainer container; 3902 3903 PetscFunctionBegin; 3904 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3905 if (container) { 3906 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3907 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3908 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3909 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3910 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3911 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3912 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3913 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3914 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3915 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3916 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3917 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3918 3919 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3920 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3921 } 3922 ierr = PetscFree(merge);CHKERRQ(ierr); 3923 3924 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3925 PetscFunctionReturn(0); 3926 } 3927 3928 #include "../src/mat/utils/freespace.h" 3929 #include "petscbt.h" 3930 3931 #undef __FUNCT__ 3932 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3933 /*@C 3934 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3935 matrices from each processor 3936 3937 Collective on MPI_Comm 3938 3939 Input Parameters: 3940 + comm - the communicators the parallel matrix will live on 3941 . seqmat - the input sequential matrices 3942 . m - number of local rows (or PETSC_DECIDE) 3943 . n - number of local columns (or PETSC_DECIDE) 3944 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3945 3946 Output Parameter: 3947 . mpimat - the parallel matrix generated 3948 3949 Level: advanced 3950 3951 Notes: 3952 The dimensions of the sequential matrix in each processor MUST be the same. 3953 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3954 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3955 @*/ 3956 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3957 { 3958 PetscErrorCode ierr; 3959 MPI_Comm comm=((PetscObject)mpimat)->comm; 3960 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3961 PetscMPIInt size,rank,taga,*len_s; 3962 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j; 3963 PetscInt proc,m; 3964 PetscInt **buf_ri,**buf_rj; 3965 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3966 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3967 MPI_Request *s_waits,*r_waits; 3968 MPI_Status *status; 3969 MatScalar *aa=a->a; 3970 MatScalar **abuf_r,*ba_i; 3971 Mat_Merge_SeqsToMPI *merge; 3972 PetscContainer container; 3973 3974 PetscFunctionBegin; 3975 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3976 3977 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3978 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3979 3980 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3981 if (container) { 3982 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3983 } 3984 bi = merge->bi; 3985 bj = merge->bj; 3986 buf_ri = merge->buf_ri; 3987 buf_rj = merge->buf_rj; 3988 3989 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3990 owners = merge->rowmap.range; 3991 len_s = merge->len_s; 3992 3993 /* send and recv matrix values */ 3994 /*-----------------------------*/ 3995 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3996 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3997 3998 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3999 for (proc=0,k=0; proc<size; proc++){ 4000 if (!len_s[proc]) continue; 4001 i = owners[proc]; 4002 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4003 k++; 4004 } 4005 4006 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4007 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4008 ierr = PetscFree(status);CHKERRQ(ierr); 4009 4010 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4011 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4012 4013 /* insert mat values of mpimat */ 4014 /*----------------------------*/ 4015 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4016 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4017 nextrow = buf_ri_k + merge->nrecv; 4018 nextai = nextrow + merge->nrecv; 4019 4020 for (k=0; k<merge->nrecv; k++){ 4021 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4022 nrows = *(buf_ri_k[k]); 4023 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4024 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4025 } 4026 4027 /* set values of ba */ 4028 m = merge->rowmap.n; 4029 for (i=0; i<m; i++) { 4030 arow = owners[rank] + i; 4031 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4032 bnzi = bi[i+1] - bi[i]; 4033 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4034 4035 /* add local non-zero vals of this proc's seqmat into ba */ 4036 anzi = ai[arow+1] - ai[arow]; 4037 aj = a->j + ai[arow]; 4038 aa = a->a + ai[arow]; 4039 nextaj = 0; 4040 for (j=0; nextaj<anzi; j++){ 4041 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4042 ba_i[j] += aa[nextaj++]; 4043 } 4044 } 4045 4046 /* add received vals into ba */ 4047 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4048 /* i-th row */ 4049 if (i == *nextrow[k]) { 4050 anzi = *(nextai[k]+1) - *nextai[k]; 4051 aj = buf_rj[k] + *(nextai[k]); 4052 aa = abuf_r[k] + *(nextai[k]); 4053 nextaj = 0; 4054 for (j=0; nextaj<anzi; j++){ 4055 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4056 ba_i[j] += aa[nextaj++]; 4057 } 4058 } 4059 nextrow[k]++; nextai[k]++; 4060 } 4061 } 4062 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4063 } 4064 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4065 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4066 4067 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4068 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4069 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4070 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4071 PetscFunctionReturn(0); 4072 } 4073 4074 #undef __FUNCT__ 4075 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 4076 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4077 { 4078 PetscErrorCode ierr; 4079 Mat B_mpi; 4080 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4081 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4082 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4083 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4084 PetscInt len,proc,*dnz,*onz; 4085 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4086 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4087 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4088 MPI_Status *status; 4089 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 4090 PetscBT lnkbt; 4091 Mat_Merge_SeqsToMPI *merge; 4092 PetscContainer container; 4093 4094 PetscFunctionBegin; 4095 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4096 4097 /* make sure it is a PETSc comm */ 4098 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4099 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4100 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4101 4102 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4103 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4104 4105 /* determine row ownership */ 4106 /*---------------------------------------------------------*/ 4107 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 4108 merge->rowmap.n = m; 4109 merge->rowmap.N = M; 4110 merge->rowmap.bs = 1; 4111 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 4112 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4113 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4114 4115 m = merge->rowmap.n; 4116 M = merge->rowmap.N; 4117 owners = merge->rowmap.range; 4118 4119 /* determine the number of messages to send, their lengths */ 4120 /*---------------------------------------------------------*/ 4121 len_s = merge->len_s; 4122 4123 len = 0; /* length of buf_si[] */ 4124 merge->nsend = 0; 4125 for (proc=0; proc<size; proc++){ 4126 len_si[proc] = 0; 4127 if (proc == rank){ 4128 len_s[proc] = 0; 4129 } else { 4130 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4131 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4132 } 4133 if (len_s[proc]) { 4134 merge->nsend++; 4135 nrows = 0; 4136 for (i=owners[proc]; i<owners[proc+1]; i++){ 4137 if (ai[i+1] > ai[i]) nrows++; 4138 } 4139 len_si[proc] = 2*(nrows+1); 4140 len += len_si[proc]; 4141 } 4142 } 4143 4144 /* determine the number and length of messages to receive for ij-structure */ 4145 /*-------------------------------------------------------------------------*/ 4146 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4147 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4148 4149 /* post the Irecv of j-structure */ 4150 /*-------------------------------*/ 4151 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4152 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4153 4154 /* post the Isend of j-structure */ 4155 /*--------------------------------*/ 4156 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 4157 sj_waits = si_waits + merge->nsend; 4158 4159 for (proc=0, k=0; proc<size; proc++){ 4160 if (!len_s[proc]) continue; 4161 i = owners[proc]; 4162 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4163 k++; 4164 } 4165 4166 /* receives and sends of j-structure are complete */ 4167 /*------------------------------------------------*/ 4168 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4169 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4170 4171 /* send and recv i-structure */ 4172 /*---------------------------*/ 4173 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4174 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4175 4176 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4177 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4178 for (proc=0,k=0; proc<size; proc++){ 4179 if (!len_s[proc]) continue; 4180 /* form outgoing message for i-structure: 4181 buf_si[0]: nrows to be sent 4182 [1:nrows]: row index (global) 4183 [nrows+1:2*nrows+1]: i-structure index 4184 */ 4185 /*-------------------------------------------*/ 4186 nrows = len_si[proc]/2 - 1; 4187 buf_si_i = buf_si + nrows+1; 4188 buf_si[0] = nrows; 4189 buf_si_i[0] = 0; 4190 nrows = 0; 4191 for (i=owners[proc]; i<owners[proc+1]; i++){ 4192 anzi = ai[i+1] - ai[i]; 4193 if (anzi) { 4194 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4195 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4196 nrows++; 4197 } 4198 } 4199 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4200 k++; 4201 buf_si += len_si[proc]; 4202 } 4203 4204 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4205 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4206 4207 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4208 for (i=0; i<merge->nrecv; i++){ 4209 ierr = PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);CHKERRQ(ierr); 4210 } 4211 4212 ierr = PetscFree(len_si);CHKERRQ(ierr); 4213 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4214 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4215 ierr = PetscFree(si_waits);CHKERRQ(ierr); 4216 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4217 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4218 ierr = PetscFree(status);CHKERRQ(ierr); 4219 4220 /* compute a local seq matrix in each processor */ 4221 /*----------------------------------------------*/ 4222 /* allocate bi array and free space for accumulating nonzero column info */ 4223 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4224 bi[0] = 0; 4225 4226 /* create and initialize a linked list */ 4227 nlnk = N+1; 4228 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4229 4230 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4231 len = 0; 4232 len = ai[owners[rank+1]] - ai[owners[rank]]; 4233 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4234 current_space = free_space; 4235 4236 /* determine symbolic info for each local row */ 4237 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4238 nextrow = buf_ri_k + merge->nrecv; 4239 nextai = nextrow + merge->nrecv; 4240 for (k=0; k<merge->nrecv; k++){ 4241 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4242 nrows = *buf_ri_k[k]; 4243 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4244 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4245 } 4246 4247 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4248 len = 0; 4249 for (i=0;i<m;i++) { 4250 bnzi = 0; 4251 /* add local non-zero cols of this proc's seqmat into lnk */ 4252 arow = owners[rank] + i; 4253 anzi = ai[arow+1] - ai[arow]; 4254 aj = a->j + ai[arow]; 4255 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4256 bnzi += nlnk; 4257 /* add received col data into lnk */ 4258 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4259 if (i == *nextrow[k]) { /* i-th row */ 4260 anzi = *(nextai[k]+1) - *nextai[k]; 4261 aj = buf_rj[k] + *nextai[k]; 4262 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4263 bnzi += nlnk; 4264 nextrow[k]++; nextai[k]++; 4265 } 4266 } 4267 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4268 4269 /* if free space is not available, make more free space */ 4270 if (current_space->local_remaining<bnzi) { 4271 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4272 nspacedouble++; 4273 } 4274 /* copy data into free space, then initialize lnk */ 4275 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4276 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4277 4278 current_space->array += bnzi; 4279 current_space->local_used += bnzi; 4280 current_space->local_remaining -= bnzi; 4281 4282 bi[i+1] = bi[i] + bnzi; 4283 } 4284 4285 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4286 4287 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4288 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4289 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4290 4291 /* create symbolic parallel matrix B_mpi */ 4292 /*---------------------------------------*/ 4293 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4294 if (n==PETSC_DECIDE) { 4295 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4296 } else { 4297 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4298 } 4299 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4300 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4301 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4302 4303 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 4304 B_mpi->assembled = PETSC_FALSE; 4305 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4306 merge->bi = bi; 4307 merge->bj = bj; 4308 merge->buf_ri = buf_ri; 4309 merge->buf_rj = buf_rj; 4310 merge->coi = PETSC_NULL; 4311 merge->coj = PETSC_NULL; 4312 merge->owners_co = PETSC_NULL; 4313 4314 /* attach the supporting struct to B_mpi for reuse */ 4315 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4316 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4317 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4318 *mpimat = B_mpi; 4319 4320 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4321 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4322 PetscFunctionReturn(0); 4323 } 4324 4325 #undef __FUNCT__ 4326 #define __FUNCT__ "MatMerge_SeqsToMPI" 4327 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4328 { 4329 PetscErrorCode ierr; 4330 4331 PetscFunctionBegin; 4332 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4333 if (scall == MAT_INITIAL_MATRIX){ 4334 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4335 } 4336 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4337 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4338 PetscFunctionReturn(0); 4339 } 4340 4341 #undef __FUNCT__ 4342 #define __FUNCT__ "MatGetLocalMat" 4343 /*@ 4344 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4345 4346 Not Collective 4347 4348 Input Parameters: 4349 + A - the matrix 4350 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4351 4352 Output Parameter: 4353 . A_loc - the local sequential matrix generated 4354 4355 Level: developer 4356 4357 @*/ 4358 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4359 { 4360 PetscErrorCode ierr; 4361 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4362 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4363 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4364 MatScalar *aa=a->a,*ba=b->a,*cam; 4365 PetscScalar *ca; 4366 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4367 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4368 4369 PetscFunctionBegin; 4370 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4371 if (scall == MAT_INITIAL_MATRIX){ 4372 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4373 ci[0] = 0; 4374 for (i=0; i<am; i++){ 4375 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4376 } 4377 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4378 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4379 k = 0; 4380 for (i=0; i<am; i++) { 4381 ncols_o = bi[i+1] - bi[i]; 4382 ncols_d = ai[i+1] - ai[i]; 4383 /* off-diagonal portion of A */ 4384 for (jo=0; jo<ncols_o; jo++) { 4385 col = cmap[*bj]; 4386 if (col >= cstart) break; 4387 cj[k] = col; bj++; 4388 ca[k++] = *ba++; 4389 } 4390 /* diagonal portion of A */ 4391 for (j=0; j<ncols_d; j++) { 4392 cj[k] = cstart + *aj++; 4393 ca[k++] = *aa++; 4394 } 4395 /* off-diagonal portion of A */ 4396 for (j=jo; j<ncols_o; j++) { 4397 cj[k] = cmap[*bj++]; 4398 ca[k++] = *ba++; 4399 } 4400 } 4401 /* put together the new matrix */ 4402 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4403 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4404 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4405 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4406 mat->free_a = PETSC_TRUE; 4407 mat->free_ij = PETSC_TRUE; 4408 mat->nonew = 0; 4409 } else if (scall == MAT_REUSE_MATRIX){ 4410 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4411 ci = mat->i; cj = mat->j; cam = mat->a; 4412 for (i=0; i<am; i++) { 4413 /* off-diagonal portion of A */ 4414 ncols_o = bi[i+1] - bi[i]; 4415 for (jo=0; jo<ncols_o; jo++) { 4416 col = cmap[*bj]; 4417 if (col >= cstart) break; 4418 *cam++ = *ba++; bj++; 4419 } 4420 /* diagonal portion of A */ 4421 ncols_d = ai[i+1] - ai[i]; 4422 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4423 /* off-diagonal portion of A */ 4424 for (j=jo; j<ncols_o; j++) { 4425 *cam++ = *ba++; bj++; 4426 } 4427 } 4428 } else { 4429 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4430 } 4431 4432 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4433 PetscFunctionReturn(0); 4434 } 4435 4436 #undef __FUNCT__ 4437 #define __FUNCT__ "MatGetLocalMatCondensed" 4438 /*@C 4439 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4440 4441 Not Collective 4442 4443 Input Parameters: 4444 + A - the matrix 4445 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4446 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4447 4448 Output Parameter: 4449 . A_loc - the local sequential matrix generated 4450 4451 Level: developer 4452 4453 @*/ 4454 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4455 { 4456 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4457 PetscErrorCode ierr; 4458 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4459 IS isrowa,iscola; 4460 Mat *aloc; 4461 4462 PetscFunctionBegin; 4463 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4464 if (!row){ 4465 start = A->rmap->rstart; end = A->rmap->rend; 4466 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4467 } else { 4468 isrowa = *row; 4469 } 4470 if (!col){ 4471 start = A->cmap->rstart; 4472 cmap = a->garray; 4473 nzA = a->A->cmap->n; 4474 nzB = a->B->cmap->n; 4475 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4476 ncols = 0; 4477 for (i=0; i<nzB; i++) { 4478 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4479 else break; 4480 } 4481 imark = i; 4482 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4483 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4484 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4485 ierr = PetscFree(idx);CHKERRQ(ierr); 4486 } else { 4487 iscola = *col; 4488 } 4489 if (scall != MAT_INITIAL_MATRIX){ 4490 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4491 aloc[0] = *A_loc; 4492 } 4493 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4494 *A_loc = aloc[0]; 4495 ierr = PetscFree(aloc);CHKERRQ(ierr); 4496 if (!row){ 4497 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4498 } 4499 if (!col){ 4500 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4501 } 4502 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4503 PetscFunctionReturn(0); 4504 } 4505 4506 #undef __FUNCT__ 4507 #define __FUNCT__ "MatGetBrowsOfAcols" 4508 /*@C 4509 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4510 4511 Collective on Mat 4512 4513 Input Parameters: 4514 + A,B - the matrices in mpiaij format 4515 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4516 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4517 4518 Output Parameter: 4519 + rowb, colb - index sets of rows and columns of B to extract 4520 . brstart - row index of B_seq from which next B->rmap->n rows are taken from B's local rows 4521 - B_seq - the sequential matrix generated 4522 4523 Level: developer 4524 4525 @*/ 4526 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4527 { 4528 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4529 PetscErrorCode ierr; 4530 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4531 IS isrowb,iscolb; 4532 Mat *bseq; 4533 4534 PetscFunctionBegin; 4535 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4536 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%D, %D) != (%D,%D)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4537 } 4538 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4539 4540 if (scall == MAT_INITIAL_MATRIX){ 4541 start = A->cmap->rstart; 4542 cmap = a->garray; 4543 nzA = a->A->cmap->n; 4544 nzB = a->B->cmap->n; 4545 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4546 ncols = 0; 4547 for (i=0; i<nzB; i++) { /* row < local row index */ 4548 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4549 else break; 4550 } 4551 imark = i; 4552 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4553 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4554 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4555 ierr = PetscFree(idx);CHKERRQ(ierr); 4556 *brstart = imark; 4557 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4558 } else { 4559 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4560 isrowb = *rowb; iscolb = *colb; 4561 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4562 bseq[0] = *B_seq; 4563 } 4564 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4565 *B_seq = bseq[0]; 4566 ierr = PetscFree(bseq);CHKERRQ(ierr); 4567 if (!rowb){ 4568 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4569 } else { 4570 *rowb = isrowb; 4571 } 4572 if (!colb){ 4573 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4574 } else { 4575 *colb = iscolb; 4576 } 4577 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4578 PetscFunctionReturn(0); 4579 } 4580 4581 #undef __FUNCT__ 4582 #define __FUNCT__ "MatGetBrowsOfAoCols" 4583 /*@C 4584 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4585 of the OFF-DIAGONAL portion of local A 4586 4587 Collective on Mat 4588 4589 Input Parameters: 4590 + A,B - the matrices in mpiaij format 4591 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4592 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4593 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4594 4595 Output Parameter: 4596 + B_oth - the sequential matrix generated 4597 4598 Level: developer 4599 4600 @*/ 4601 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,MatScalar **bufa_ptr,Mat *B_oth) 4602 { 4603 VecScatter_MPI_General *gen_to,*gen_from; 4604 PetscErrorCode ierr; 4605 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4606 Mat_SeqAIJ *b_oth; 4607 VecScatter ctx=a->Mvctx; 4608 MPI_Comm comm=((PetscObject)ctx)->comm; 4609 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4610 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4611 PetscScalar *rvalues,*svalues; 4612 MatScalar *b_otha,*bufa,*bufA; 4613 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4614 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4615 MPI_Status *sstatus,rstatus; 4616 PetscMPIInt jj; 4617 PetscInt *cols,sbs,rbs; 4618 PetscScalar *vals; 4619 4620 PetscFunctionBegin; 4621 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4622 SETERRQ4(PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, (%d, %d) != (%d,%d)",A->cmap->rstart,A->cmap->rend,B->rmap->rstart,B->rmap->rend); 4623 } 4624 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4625 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4626 4627 gen_to = (VecScatter_MPI_General*)ctx->todata; 4628 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4629 rvalues = gen_from->values; /* holds the length of receiving row */ 4630 svalues = gen_to->values; /* holds the length of sending row */ 4631 nrecvs = gen_from->n; 4632 nsends = gen_to->n; 4633 4634 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4635 srow = gen_to->indices; /* local row index to be sent */ 4636 sstarts = gen_to->starts; 4637 sprocs = gen_to->procs; 4638 sstatus = gen_to->sstatus; 4639 sbs = gen_to->bs; 4640 rstarts = gen_from->starts; 4641 rprocs = gen_from->procs; 4642 rbs = gen_from->bs; 4643 4644 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4645 if (scall == MAT_INITIAL_MATRIX){ 4646 /* i-array */ 4647 /*---------*/ 4648 /* post receives */ 4649 for (i=0; i<nrecvs; i++){ 4650 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4651 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4652 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4653 } 4654 4655 /* pack the outgoing message */ 4656 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4657 rstartsj = sstartsj + nsends +1; 4658 sstartsj[0] = 0; rstartsj[0] = 0; 4659 len = 0; /* total length of j or a array to be sent */ 4660 k = 0; 4661 for (i=0; i<nsends; i++){ 4662 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4663 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4664 for (j=0; j<nrows; j++) { 4665 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4666 for (l=0; l<sbs; l++){ 4667 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4668 rowlen[j*sbs+l] = ncols; 4669 len += ncols; 4670 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4671 } 4672 k++; 4673 } 4674 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4675 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4676 } 4677 /* recvs and sends of i-array are completed */ 4678 i = nrecvs; 4679 while (i--) { 4680 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4681 } 4682 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4683 4684 /* allocate buffers for sending j and a arrays */ 4685 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4686 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4687 4688 /* create i-array of B_oth */ 4689 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4690 b_othi[0] = 0; 4691 len = 0; /* total length of j or a array to be received */ 4692 k = 0; 4693 for (i=0; i<nrecvs; i++){ 4694 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4695 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4696 for (j=0; j<nrows; j++) { 4697 b_othi[k+1] = b_othi[k] + rowlen[j]; 4698 len += rowlen[j]; k++; 4699 } 4700 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4701 } 4702 4703 /* allocate space for j and a arrrays of B_oth */ 4704 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4705 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 4706 4707 /* j-array */ 4708 /*---------*/ 4709 /* post receives of j-array */ 4710 for (i=0; i<nrecvs; i++){ 4711 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4712 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4713 } 4714 4715 /* pack the outgoing message j-array */ 4716 k = 0; 4717 for (i=0; i<nsends; i++){ 4718 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4719 bufJ = bufj+sstartsj[i]; 4720 for (j=0; j<nrows; j++) { 4721 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4722 for (ll=0; ll<sbs; ll++){ 4723 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4724 for (l=0; l<ncols; l++){ 4725 *bufJ++ = cols[l]; 4726 } 4727 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4728 } 4729 } 4730 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4731 } 4732 4733 /* recvs and sends of j-array are completed */ 4734 i = nrecvs; 4735 while (i--) { 4736 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4737 } 4738 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4739 } else if (scall == MAT_REUSE_MATRIX){ 4740 sstartsj = *startsj; 4741 rstartsj = sstartsj + nsends +1; 4742 bufa = *bufa_ptr; 4743 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4744 b_otha = b_oth->a; 4745 } else { 4746 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4747 } 4748 4749 /* a-array */ 4750 /*---------*/ 4751 /* post receives of a-array */ 4752 for (i=0; i<nrecvs; i++){ 4753 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4754 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4755 } 4756 4757 /* pack the outgoing message a-array */ 4758 k = 0; 4759 for (i=0; i<nsends; i++){ 4760 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4761 bufA = bufa+sstartsj[i]; 4762 for (j=0; j<nrows; j++) { 4763 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4764 for (ll=0; ll<sbs; ll++){ 4765 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4766 for (l=0; l<ncols; l++){ 4767 *bufA++ = vals[l]; 4768 } 4769 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4770 } 4771 } 4772 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4773 } 4774 /* recvs and sends of a-array are completed */ 4775 i = nrecvs; 4776 while (i--) { 4777 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4778 } 4779 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4780 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4781 4782 if (scall == MAT_INITIAL_MATRIX){ 4783 /* put together the new matrix */ 4784 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4785 4786 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4787 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4788 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4789 b_oth->free_a = PETSC_TRUE; 4790 b_oth->free_ij = PETSC_TRUE; 4791 b_oth->nonew = 0; 4792 4793 ierr = PetscFree(bufj);CHKERRQ(ierr); 4794 if (!startsj || !bufa_ptr){ 4795 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4796 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4797 } else { 4798 *startsj = sstartsj; 4799 *bufa_ptr = bufa; 4800 } 4801 } 4802 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4803 PetscFunctionReturn(0); 4804 } 4805 4806 #undef __FUNCT__ 4807 #define __FUNCT__ "MatGetCommunicationStructs" 4808 /*@C 4809 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4810 4811 Not Collective 4812 4813 Input Parameters: 4814 . A - The matrix in mpiaij format 4815 4816 Output Parameter: 4817 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4818 . colmap - A map from global column index to local index into lvec 4819 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4820 4821 Level: developer 4822 4823 @*/ 4824 #if defined (PETSC_USE_CTABLE) 4825 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4826 #else 4827 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4828 #endif 4829 { 4830 Mat_MPIAIJ *a; 4831 4832 PetscFunctionBegin; 4833 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4834 PetscValidPointer(lvec, 2) 4835 PetscValidPointer(colmap, 3) 4836 PetscValidPointer(multScatter, 4) 4837 a = (Mat_MPIAIJ *) A->data; 4838 if (lvec) *lvec = a->lvec; 4839 if (colmap) *colmap = a->colmap; 4840 if (multScatter) *multScatter = a->Mvctx; 4841 PetscFunctionReturn(0); 4842 } 4843 4844 EXTERN_C_BEGIN 4845 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,const MatType,MatReuse,Mat*); 4846 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,const MatType,MatReuse,Mat*); 4847 EXTERN_C_END 4848 4849 #include "../src/mat/impls/dense/mpi/mpidense.h" 4850 4851 #undef __FUNCT__ 4852 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4853 /* 4854 Computes (B'*A')' since computing B*A directly is untenable 4855 4856 n p p 4857 ( ) ( ) ( ) 4858 m ( A ) * n ( B ) = m ( C ) 4859 ( ) ( ) ( ) 4860 4861 */ 4862 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4863 { 4864 PetscErrorCode ierr; 4865 Mat At,Bt,Ct; 4866 4867 PetscFunctionBegin; 4868 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4869 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4870 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4871 ierr = MatDestroy(At);CHKERRQ(ierr); 4872 ierr = MatDestroy(Bt);CHKERRQ(ierr); 4873 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4874 ierr = MatDestroy(Ct);CHKERRQ(ierr); 4875 PetscFunctionReturn(0); 4876 } 4877 4878 #undef __FUNCT__ 4879 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4880 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4881 { 4882 PetscErrorCode ierr; 4883 PetscInt m=A->rmap->n,n=B->cmap->n; 4884 Mat Cmat; 4885 4886 PetscFunctionBegin; 4887 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 4888 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 4889 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4890 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4891 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 4892 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4893 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4894 *C = Cmat; 4895 PetscFunctionReturn(0); 4896 } 4897 4898 /* ----------------------------------------------------------------*/ 4899 #undef __FUNCT__ 4900 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4901 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4902 { 4903 PetscErrorCode ierr; 4904 4905 PetscFunctionBegin; 4906 if (scall == MAT_INITIAL_MATRIX){ 4907 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 4908 } 4909 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 4910 PetscFunctionReturn(0); 4911 } 4912 4913 EXTERN_C_BEGIN 4914 #if defined(PETSC_HAVE_MUMPS) 4915 extern PetscErrorCode MatGetFactor_mpiaij_mumps(Mat,MatFactorType,Mat*); 4916 #endif 4917 #if defined(PETSC_HAVE_PASTIX) 4918 extern PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 4919 #endif 4920 #if defined(PETSC_HAVE_SUPERLU_DIST) 4921 extern PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 4922 #endif 4923 #if defined(PETSC_HAVE_SPOOLES) 4924 extern PetscErrorCode MatGetFactor_mpiaij_spooles(Mat,MatFactorType,Mat*); 4925 #endif 4926 EXTERN_C_END 4927 4928 /*MC 4929 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4930 4931 Options Database Keys: 4932 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4933 4934 Level: beginner 4935 4936 .seealso: MatCreateMPIAIJ() 4937 M*/ 4938 4939 EXTERN_C_BEGIN 4940 #undef __FUNCT__ 4941 #define __FUNCT__ "MatCreate_MPIAIJ" 4942 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4943 { 4944 Mat_MPIAIJ *b; 4945 PetscErrorCode ierr; 4946 PetscMPIInt size; 4947 4948 PetscFunctionBegin; 4949 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4950 4951 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4952 B->data = (void*)b; 4953 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4954 B->rmap->bs = 1; 4955 B->assembled = PETSC_FALSE; 4956 B->mapping = 0; 4957 4958 B->insertmode = NOT_SET_VALUES; 4959 b->size = size; 4960 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4961 4962 /* build cache for off array entries formed */ 4963 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4964 b->donotstash = PETSC_FALSE; 4965 b->colmap = 0; 4966 b->garray = 0; 4967 b->roworiented = PETSC_TRUE; 4968 4969 /* stuff used for matrix vector multiply */ 4970 b->lvec = PETSC_NULL; 4971 b->Mvctx = PETSC_NULL; 4972 4973 /* stuff for MatGetRow() */ 4974 b->rowindices = 0; 4975 b->rowvalues = 0; 4976 b->getrowactive = PETSC_FALSE; 4977 4978 #if defined(PETSC_HAVE_SPOOLES) 4979 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_spooles_C", 4980 "MatGetFactor_mpiaij_spooles", 4981 MatGetFactor_mpiaij_spooles);CHKERRQ(ierr); 4982 #endif 4983 #if defined(PETSC_HAVE_MUMPS) 4984 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_mumps_C", 4985 "MatGetFactor_mpiaij_mumps", 4986 MatGetFactor_mpiaij_mumps);CHKERRQ(ierr); 4987 #endif 4988 #if defined(PETSC_HAVE_PASTIX) 4989 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_pastix_C", 4990 "MatGetFactor_mpiaij_pastix", 4991 MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 4992 #endif 4993 #if defined(PETSC_HAVE_SUPERLU_DIST) 4994 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_superlu_dist_C", 4995 "MatGetFactor_mpiaij_superlu_dist", 4996 MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 4997 #endif 4998 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4999 "MatStoreValues_MPIAIJ", 5000 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5001 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 5002 "MatRetrieveValues_MPIAIJ", 5003 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5004 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 5005 "MatGetDiagonalBlock_MPIAIJ", 5006 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5007 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 5008 "MatIsTranspose_MPIAIJ", 5009 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5010 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 5011 "MatMPIAIJSetPreallocation_MPIAIJ", 5012 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5013 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 5014 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 5015 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5016 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 5017 "MatDiagonalScaleLocal_MPIAIJ", 5018 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5019 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 5020 "MatConvert_MPIAIJ_MPICSRPERM", 5021 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 5022 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 5023 "MatConvert_MPIAIJ_MPICRL", 5024 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 5025 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 5026 "MatMatMult_MPIDense_MPIAIJ", 5027 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5028 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 5029 "MatMatMultSymbolic_MPIDense_MPIAIJ", 5030 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5031 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 5032 "MatMatMultNumeric_MPIDense_MPIAIJ", 5033 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5034 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5035 PetscFunctionReturn(0); 5036 } 5037 EXTERN_C_END 5038 5039 #undef __FUNCT__ 5040 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5041 /*@ 5042 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5043 and "off-diagonal" part of the matrix in CSR format. 5044 5045 Collective on MPI_Comm 5046 5047 Input Parameters: 5048 + comm - MPI communicator 5049 . m - number of local rows (Cannot be PETSC_DECIDE) 5050 . n - This value should be the same as the local size used in creating the 5051 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5052 calculated if N is given) For square matrices n is almost always m. 5053 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5054 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5055 . i - row indices for "diagonal" portion of matrix 5056 . j - column indices 5057 . a - matrix values 5058 . oi - row indices for "off-diagonal" portion of matrix 5059 . oj - column indices 5060 - oa - matrix values 5061 5062 Output Parameter: 5063 . mat - the matrix 5064 5065 Level: advanced 5066 5067 Notes: 5068 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 5069 5070 The i and j indices are 0 based 5071 5072 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5073 5074 5075 .keywords: matrix, aij, compressed row, sparse, parallel 5076 5077 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5078 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 5079 @*/ 5080 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 5081 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5082 { 5083 PetscErrorCode ierr; 5084 Mat_MPIAIJ *maij; 5085 5086 PetscFunctionBegin; 5087 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5088 if (i[0]) { 5089 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5090 } 5091 if (oi[0]) { 5092 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5093 } 5094 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5095 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5096 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5097 maij = (Mat_MPIAIJ*) (*mat)->data; 5098 maij->donotstash = PETSC_TRUE; 5099 (*mat)->preallocated = PETSC_TRUE; 5100 5101 ierr = PetscMapSetBlockSize((*mat)->rmap,1);CHKERRQ(ierr); 5102 ierr = PetscMapSetBlockSize((*mat)->cmap,1);CHKERRQ(ierr); 5103 ierr = PetscMapSetUp((*mat)->rmap);CHKERRQ(ierr); 5104 ierr = PetscMapSetUp((*mat)->cmap);CHKERRQ(ierr); 5105 5106 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5107 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5108 5109 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5110 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5111 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5112 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5113 5114 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5115 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5116 PetscFunctionReturn(0); 5117 } 5118 5119 /* 5120 Special version for direct calls from Fortran 5121 */ 5122 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5123 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5124 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5125 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5126 #endif 5127 5128 /* Change these macros so can be used in void function */ 5129 #undef CHKERRQ 5130 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5131 #undef SETERRQ2 5132 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5133 #undef SETERRQ 5134 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5135 5136 EXTERN_C_BEGIN 5137 #undef __FUNCT__ 5138 #define __FUNCT__ "matsetvaluesmpiaij_" 5139 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5140 { 5141 Mat mat = *mmat; 5142 PetscInt m = *mm, n = *mn; 5143 InsertMode addv = *maddv; 5144 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5145 PetscScalar value; 5146 PetscErrorCode ierr; 5147 5148 ierr = MatPreallocated(mat);CHKERRQ(ierr); 5149 if (mat->insertmode == NOT_SET_VALUES) { 5150 mat->insertmode = addv; 5151 } 5152 #if defined(PETSC_USE_DEBUG) 5153 else if (mat->insertmode != addv) { 5154 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5155 } 5156 #endif 5157 { 5158 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5159 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5160 PetscTruth roworiented = aij->roworiented; 5161 5162 /* Some Variables required in the macro */ 5163 Mat A = aij->A; 5164 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5165 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5166 MatScalar *aa = a->a; 5167 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5168 Mat B = aij->B; 5169 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5170 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5171 MatScalar *ba = b->a; 5172 5173 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5174 PetscInt nonew = a->nonew; 5175 MatScalar *ap1,*ap2; 5176 5177 PetscFunctionBegin; 5178 for (i=0; i<m; i++) { 5179 if (im[i] < 0) continue; 5180 #if defined(PETSC_USE_DEBUG) 5181 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5182 #endif 5183 if (im[i] >= rstart && im[i] < rend) { 5184 row = im[i] - rstart; 5185 lastcol1 = -1; 5186 rp1 = aj + ai[row]; 5187 ap1 = aa + ai[row]; 5188 rmax1 = aimax[row]; 5189 nrow1 = ailen[row]; 5190 low1 = 0; 5191 high1 = nrow1; 5192 lastcol2 = -1; 5193 rp2 = bj + bi[row]; 5194 ap2 = ba + bi[row]; 5195 rmax2 = bimax[row]; 5196 nrow2 = bilen[row]; 5197 low2 = 0; 5198 high2 = nrow2; 5199 5200 for (j=0; j<n; j++) { 5201 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5202 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5203 if (in[j] >= cstart && in[j] < cend){ 5204 col = in[j] - cstart; 5205 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5206 } else if (in[j] < 0) continue; 5207 #if defined(PETSC_USE_DEBUG) 5208 else if (in[j] >= mat->cmap->N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);} 5209 #endif 5210 else { 5211 if (mat->was_assembled) { 5212 if (!aij->colmap) { 5213 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5214 } 5215 #if defined (PETSC_USE_CTABLE) 5216 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5217 col--; 5218 #else 5219 col = aij->colmap[in[j]] - 1; 5220 #endif 5221 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5222 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5223 col = in[j]; 5224 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5225 B = aij->B; 5226 b = (Mat_SeqAIJ*)B->data; 5227 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5228 rp2 = bj + bi[row]; 5229 ap2 = ba + bi[row]; 5230 rmax2 = bimax[row]; 5231 nrow2 = bilen[row]; 5232 low2 = 0; 5233 high2 = nrow2; 5234 bm = aij->B->rmap->n; 5235 ba = b->a; 5236 } 5237 } else col = in[j]; 5238 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5239 } 5240 } 5241 } else { 5242 if (!aij->donotstash) { 5243 if (roworiented) { 5244 if (ignorezeroentries && v[i*n] == 0.0) continue; 5245 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 5246 } else { 5247 if (ignorezeroentries && v[i] == 0.0) continue; 5248 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 5249 } 5250 } 5251 } 5252 }} 5253 PetscFunctionReturnVoid(); 5254 } 5255 EXTERN_C_END 5256 5257