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->cmap->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 B->preallocated = PETSC_TRUE; 2693 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2694 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2695 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2696 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2697 2698 ierr = PetscMapSetBlockSize(B->rmap,1);CHKERRQ(ierr); 2699 ierr = PetscMapSetBlockSize(B->cmap,1);CHKERRQ(ierr); 2700 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2701 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2702 if (d_nnz) { 2703 for (i=0; i<B->rmap->n; i++) { 2704 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]); 2705 } 2706 } 2707 if (o_nnz) { 2708 for (i=0; i<B->rmap->n; i++) { 2709 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]); 2710 } 2711 } 2712 b = (Mat_MPIAIJ*)B->data; 2713 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 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2725 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2726 2727 PetscFunctionReturn(0); 2728 } 2729 EXTERN_C_END 2730 2731 #undef __FUNCT__ 2732 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2733 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2734 { 2735 Mat mat; 2736 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2737 PetscErrorCode ierr; 2738 2739 PetscFunctionBegin; 2740 *newmat = 0; 2741 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2742 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2743 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2744 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2745 a = (Mat_MPIAIJ*)mat->data; 2746 2747 mat->factor = matin->factor; 2748 mat->rmap->bs = matin->rmap->bs; 2749 mat->assembled = PETSC_TRUE; 2750 mat->insertmode = NOT_SET_VALUES; 2751 mat->preallocated = PETSC_TRUE; 2752 2753 a->size = oldmat->size; 2754 a->rank = oldmat->rank; 2755 a->donotstash = oldmat->donotstash; 2756 a->roworiented = oldmat->roworiented; 2757 a->rowindices = 0; 2758 a->rowvalues = 0; 2759 a->getrowactive = PETSC_FALSE; 2760 2761 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2762 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2763 2764 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2765 if (oldmat->colmap) { 2766 #if defined (PETSC_USE_CTABLE) 2767 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2768 #else 2769 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2770 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2771 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2772 #endif 2773 } else a->colmap = 0; 2774 if (oldmat->garray) { 2775 PetscInt len; 2776 len = oldmat->B->cmap->n; 2777 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2778 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2779 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2780 } else a->garray = 0; 2781 2782 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2783 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2784 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2785 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2786 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2787 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2788 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2789 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2790 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2791 *newmat = mat; 2792 PetscFunctionReturn(0); 2793 } 2794 2795 #include "petscsys.h" 2796 2797 #undef __FUNCT__ 2798 #define __FUNCT__ "MatLoad_MPIAIJ" 2799 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2800 { 2801 Mat A; 2802 PetscScalar *vals,*svals; 2803 MPI_Comm comm = ((PetscObject)viewer)->comm; 2804 MPI_Status status; 2805 PetscErrorCode ierr; 2806 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2807 PetscInt i,nz,j,rstart,rend,mmax; 2808 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2809 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2810 PetscInt cend,cstart,n,*rowners; 2811 int fd; 2812 2813 PetscFunctionBegin; 2814 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2815 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2816 if (!rank) { 2817 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2818 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2819 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2820 } 2821 2822 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2823 M = header[1]; N = header[2]; 2824 /* determine ownership of all rows */ 2825 m = M/size + ((M % size) > rank); 2826 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2827 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2828 2829 /* First process needs enough room for process with most rows */ 2830 if (!rank) { 2831 mmax = rowners[1]; 2832 for (i=2; i<size; i++) { 2833 mmax = PetscMax(mmax,rowners[i]); 2834 } 2835 } else mmax = m; 2836 2837 rowners[0] = 0; 2838 for (i=2; i<=size; i++) { 2839 rowners[i] += rowners[i-1]; 2840 } 2841 rstart = rowners[rank]; 2842 rend = rowners[rank+1]; 2843 2844 /* distribute row lengths to all processors */ 2845 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2846 if (!rank) { 2847 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2848 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2849 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2850 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2851 for (j=0; j<m; j++) { 2852 procsnz[0] += ourlens[j]; 2853 } 2854 for (i=1; i<size; i++) { 2855 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2856 /* calculate the number of nonzeros on each processor */ 2857 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2858 procsnz[i] += rowlengths[j]; 2859 } 2860 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2861 } 2862 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2863 } else { 2864 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2865 } 2866 2867 if (!rank) { 2868 /* determine max buffer needed and allocate it */ 2869 maxnz = 0; 2870 for (i=0; i<size; i++) { 2871 maxnz = PetscMax(maxnz,procsnz[i]); 2872 } 2873 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2874 2875 /* read in my part of the matrix column indices */ 2876 nz = procsnz[0]; 2877 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2878 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2879 2880 /* read in every one elses and ship off */ 2881 for (i=1; i<size; i++) { 2882 nz = procsnz[i]; 2883 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2884 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2885 } 2886 ierr = PetscFree(cols);CHKERRQ(ierr); 2887 } else { 2888 /* determine buffer space needed for message */ 2889 nz = 0; 2890 for (i=0; i<m; i++) { 2891 nz += ourlens[i]; 2892 } 2893 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2894 2895 /* receive message of column indices*/ 2896 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2897 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2898 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2899 } 2900 2901 /* determine column ownership if matrix is not square */ 2902 if (N != M) { 2903 n = N/size + ((N % size) > rank); 2904 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2905 cstart = cend - n; 2906 } else { 2907 cstart = rstart; 2908 cend = rend; 2909 n = cend - cstart; 2910 } 2911 2912 /* loop over local rows, determining number of off diagonal entries */ 2913 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2914 jj = 0; 2915 for (i=0; i<m; i++) { 2916 for (j=0; j<ourlens[i]; j++) { 2917 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2918 jj++; 2919 } 2920 } 2921 2922 /* create our matrix */ 2923 for (i=0; i<m; i++) { 2924 ourlens[i] -= offlens[i]; 2925 } 2926 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2927 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2928 ierr = MatSetType(A,type);CHKERRQ(ierr); 2929 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2930 2931 for (i=0; i<m; i++) { 2932 ourlens[i] += offlens[i]; 2933 } 2934 2935 if (!rank) { 2936 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2937 2938 /* read in my part of the matrix numerical values */ 2939 nz = procsnz[0]; 2940 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2941 2942 /* insert into matrix */ 2943 jj = rstart; 2944 smycols = mycols; 2945 svals = vals; 2946 for (i=0; i<m; i++) { 2947 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2948 smycols += ourlens[i]; 2949 svals += ourlens[i]; 2950 jj++; 2951 } 2952 2953 /* read in other processors and ship out */ 2954 for (i=1; i<size; i++) { 2955 nz = procsnz[i]; 2956 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2957 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2958 } 2959 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2960 } else { 2961 /* receive numeric values */ 2962 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2963 2964 /* receive message of values*/ 2965 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2966 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2967 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2968 2969 /* insert into matrix */ 2970 jj = rstart; 2971 smycols = mycols; 2972 svals = vals; 2973 for (i=0; i<m; i++) { 2974 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2975 smycols += ourlens[i]; 2976 svals += ourlens[i]; 2977 jj++; 2978 } 2979 } 2980 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2981 ierr = PetscFree(vals);CHKERRQ(ierr); 2982 ierr = PetscFree(mycols);CHKERRQ(ierr); 2983 ierr = PetscFree(rowners);CHKERRQ(ierr); 2984 2985 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2986 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2987 *newmat = A; 2988 PetscFunctionReturn(0); 2989 } 2990 2991 #undef __FUNCT__ 2992 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2993 /* 2994 Not great since it makes two copies of the submatrix, first an SeqAIJ 2995 in local and then by concatenating the local matrices the end result. 2996 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2997 */ 2998 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2999 { 3000 PetscErrorCode ierr; 3001 PetscMPIInt rank,size; 3002 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 3003 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3004 Mat *local,M,Mreuse; 3005 MatScalar *vwork,*aa; 3006 MPI_Comm comm = ((PetscObject)mat)->comm; 3007 Mat_SeqAIJ *aij; 3008 3009 3010 PetscFunctionBegin; 3011 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3012 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3013 3014 if (call == MAT_REUSE_MATRIX) { 3015 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 3016 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3017 local = &Mreuse; 3018 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 3019 } else { 3020 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 3021 Mreuse = *local; 3022 ierr = PetscFree(local);CHKERRQ(ierr); 3023 } 3024 3025 /* 3026 m - number of local rows 3027 n - number of columns (same on all processors) 3028 rstart - first row in new global matrix generated 3029 */ 3030 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3031 if (call == MAT_INITIAL_MATRIX) { 3032 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3033 ii = aij->i; 3034 jj = aij->j; 3035 3036 /* 3037 Determine the number of non-zeros in the diagonal and off-diagonal 3038 portions of the matrix in order to do correct preallocation 3039 */ 3040 3041 /* first get start and end of "diagonal" columns */ 3042 if (csize == PETSC_DECIDE) { 3043 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3044 if (mglobal == n) { /* square matrix */ 3045 nlocal = m; 3046 } else { 3047 nlocal = n/size + ((n % size) > rank); 3048 } 3049 } else { 3050 nlocal = csize; 3051 } 3052 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3053 rstart = rend - nlocal; 3054 if (rank == size - 1 && rend != n) { 3055 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3056 } 3057 3058 /* next, compute all the lengths */ 3059 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3060 olens = dlens + m; 3061 for (i=0; i<m; i++) { 3062 jend = ii[i+1] - ii[i]; 3063 olen = 0; 3064 dlen = 0; 3065 for (j=0; j<jend; j++) { 3066 if (*jj < rstart || *jj >= rend) olen++; 3067 else dlen++; 3068 jj++; 3069 } 3070 olens[i] = olen; 3071 dlens[i] = dlen; 3072 } 3073 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3074 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3075 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3076 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3077 ierr = PetscFree(dlens);CHKERRQ(ierr); 3078 } else { 3079 PetscInt ml,nl; 3080 3081 M = *newmat; 3082 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3083 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3084 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3085 /* 3086 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3087 rather than the slower MatSetValues(). 3088 */ 3089 M->was_assembled = PETSC_TRUE; 3090 M->assembled = PETSC_FALSE; 3091 } 3092 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3093 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3094 ii = aij->i; 3095 jj = aij->j; 3096 aa = aij->a; 3097 for (i=0; i<m; i++) { 3098 row = rstart + i; 3099 nz = ii[i+1] - ii[i]; 3100 cwork = jj; jj += nz; 3101 vwork = aa; aa += nz; 3102 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3103 } 3104 3105 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3106 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3107 *newmat = M; 3108 3109 /* save submatrix used in processor for next request */ 3110 if (call == MAT_INITIAL_MATRIX) { 3111 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3112 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 3113 } 3114 3115 PetscFunctionReturn(0); 3116 } 3117 3118 EXTERN_C_BEGIN 3119 #undef __FUNCT__ 3120 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3121 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3122 { 3123 PetscInt m,cstart, cend,j,nnz,i,d; 3124 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3125 const PetscInt *JJ; 3126 PetscScalar *values; 3127 PetscErrorCode ierr; 3128 3129 PetscFunctionBegin; 3130 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3131 3132 ierr = PetscMapSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3133 ierr = PetscMapSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3134 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 3135 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 3136 m = B->rmap->n; 3137 cstart = B->cmap->rstart; 3138 cend = B->cmap->rend; 3139 rstart = B->rmap->rstart; 3140 3141 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 3142 o_nnz = d_nnz + m; 3143 3144 #if defined(PETSC_USE_DEBUGGING) 3145 for (i=0; i<m; i++) { 3146 nnz = Ii[i+1]- Ii[i]; 3147 JJ = J + Ii[i]; 3148 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3149 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3150 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); 3151 for (j=1; j<nnz; j++) { 3152 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); 3153 } 3154 } 3155 #endif 3156 3157 for (i=0; i<m; i++) { 3158 nnz = Ii[i+1]- Ii[i]; 3159 JJ = J + Ii[i]; 3160 nnz_max = PetscMax(nnz_max,nnz); 3161 for (j=0; j<nnz; j++) { 3162 if (*JJ >= cstart) break; 3163 JJ++; 3164 } 3165 d = 0; 3166 for (; j<nnz; j++) { 3167 if (*JJ++ >= cend) break; 3168 d++; 3169 } 3170 d_nnz[i] = d; 3171 o_nnz[i] = nnz - d; 3172 } 3173 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3174 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 3175 3176 if (v) values = (PetscScalar*)v; 3177 else { 3178 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3179 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3180 } 3181 3182 for (i=0; i<m; i++) { 3183 ii = i + rstart; 3184 nnz = Ii[i+1]- Ii[i]; 3185 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3186 } 3187 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3188 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3189 3190 if (!v) { 3191 ierr = PetscFree(values);CHKERRQ(ierr); 3192 } 3193 PetscFunctionReturn(0); 3194 } 3195 EXTERN_C_END 3196 3197 #undef __FUNCT__ 3198 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3199 /*@ 3200 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3201 (the default parallel PETSc format). 3202 3203 Collective on MPI_Comm 3204 3205 Input Parameters: 3206 + B - the matrix 3207 . i - the indices into j for the start of each local row (starts with zero) 3208 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3209 - v - optional values in the matrix 3210 3211 Level: developer 3212 3213 Notes: 3214 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3215 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3216 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3217 3218 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3219 3220 The format which is used for the sparse matrix input, is equivalent to a 3221 row-major ordering.. i.e for the following matrix, the input data expected is 3222 as shown: 3223 3224 1 0 0 3225 2 0 3 P0 3226 ------- 3227 4 5 6 P1 3228 3229 Process0 [P0]: rows_owned=[0,1] 3230 i = {0,1,3} [size = nrow+1 = 2+1] 3231 j = {0,0,2} [size = nz = 6] 3232 v = {1,2,3} [size = nz = 6] 3233 3234 Process1 [P1]: rows_owned=[2] 3235 i = {0,3} [size = nrow+1 = 1+1] 3236 j = {0,1,2} [size = nz = 6] 3237 v = {4,5,6} [size = nz = 6] 3238 3239 The column indices for each row MUST be sorted. 3240 3241 .keywords: matrix, aij, compressed row, sparse, parallel 3242 3243 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 3244 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3245 @*/ 3246 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3247 { 3248 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3249 3250 PetscFunctionBegin; 3251 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3252 if (f) { 3253 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3254 } 3255 PetscFunctionReturn(0); 3256 } 3257 3258 #undef __FUNCT__ 3259 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3260 /*@C 3261 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3262 (the default parallel PETSc format). For good matrix assembly performance 3263 the user should preallocate the matrix storage by setting the parameters 3264 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3265 performance can be increased by more than a factor of 50. 3266 3267 Collective on MPI_Comm 3268 3269 Input Parameters: 3270 + A - the matrix 3271 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3272 (same value is used for all local rows) 3273 . d_nnz - array containing the number of nonzeros in the various rows of the 3274 DIAGONAL portion of the local submatrix (possibly different for each row) 3275 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3276 The size of this array is equal to the number of local rows, i.e 'm'. 3277 You must leave room for the diagonal entry even if it is zero. 3278 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3279 submatrix (same value is used for all local rows). 3280 - o_nnz - array containing the number of nonzeros in the various rows of the 3281 OFF-DIAGONAL portion of the local submatrix (possibly different for 3282 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3283 structure. The size of this array is equal to the number 3284 of local rows, i.e 'm'. 3285 3286 If the *_nnz parameter is given then the *_nz parameter is ignored 3287 3288 The AIJ format (also called the Yale sparse matrix format or 3289 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3290 storage. The stored row and column indices begin with zero. See the users manual for details. 3291 3292 The parallel matrix is partitioned such that the first m0 rows belong to 3293 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3294 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3295 3296 The DIAGONAL portion of the local submatrix of a processor can be defined 3297 as the submatrix which is obtained by extraction the part corresponding 3298 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 3299 first row that belongs to the processor, and r2 is the last row belonging 3300 to the this processor. This is a square mxm matrix. The remaining portion 3301 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 3302 3303 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3304 3305 You can call MatGetInfo() to get information on how effective the preallocation was; 3306 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3307 You can also run with the option -info and look for messages with the string 3308 malloc in them to see if additional memory allocation was needed. 3309 3310 Example usage: 3311 3312 Consider the following 8x8 matrix with 34 non-zero values, that is 3313 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3314 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3315 as follows: 3316 3317 .vb 3318 1 2 0 | 0 3 0 | 0 4 3319 Proc0 0 5 6 | 7 0 0 | 8 0 3320 9 0 10 | 11 0 0 | 12 0 3321 ------------------------------------- 3322 13 0 14 | 15 16 17 | 0 0 3323 Proc1 0 18 0 | 19 20 21 | 0 0 3324 0 0 0 | 22 23 0 | 24 0 3325 ------------------------------------- 3326 Proc2 25 26 27 | 0 0 28 | 29 0 3327 30 0 0 | 31 32 33 | 0 34 3328 .ve 3329 3330 This can be represented as a collection of submatrices as: 3331 3332 .vb 3333 A B C 3334 D E F 3335 G H I 3336 .ve 3337 3338 Where the submatrices A,B,C are owned by proc0, D,E,F are 3339 owned by proc1, G,H,I are owned by proc2. 3340 3341 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3342 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3343 The 'M','N' parameters are 8,8, and have the same values on all procs. 3344 3345 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3346 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3347 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3348 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3349 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3350 matrix, ans [DF] as another SeqAIJ matrix. 3351 3352 When d_nz, o_nz parameters are specified, d_nz storage elements are 3353 allocated for every row of the local diagonal submatrix, and o_nz 3354 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3355 One way to choose d_nz and o_nz is to use the max nonzerors per local 3356 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3357 In this case, the values of d_nz,o_nz are: 3358 .vb 3359 proc0 : dnz = 2, o_nz = 2 3360 proc1 : dnz = 3, o_nz = 2 3361 proc2 : dnz = 1, o_nz = 4 3362 .ve 3363 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3364 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3365 for proc3. i.e we are using 12+15+10=37 storage locations to store 3366 34 values. 3367 3368 When d_nnz, o_nnz parameters are specified, the storage is specified 3369 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3370 In the above case the values for d_nnz,o_nnz are: 3371 .vb 3372 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3373 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3374 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3375 .ve 3376 Here the space allocated is sum of all the above values i.e 34, and 3377 hence pre-allocation is perfect. 3378 3379 Level: intermediate 3380 3381 .keywords: matrix, aij, compressed row, sparse, parallel 3382 3383 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3384 MPIAIJ, MatGetInfo() 3385 @*/ 3386 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3387 { 3388 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3389 3390 PetscFunctionBegin; 3391 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3392 if (f) { 3393 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3394 } 3395 PetscFunctionReturn(0); 3396 } 3397 3398 #undef __FUNCT__ 3399 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3400 /*@ 3401 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3402 CSR format the local rows. 3403 3404 Collective on MPI_Comm 3405 3406 Input Parameters: 3407 + comm - MPI communicator 3408 . m - number of local rows (Cannot be PETSC_DECIDE) 3409 . n - This value should be the same as the local size used in creating the 3410 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3411 calculated if N is given) For square matrices n is almost always m. 3412 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3413 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3414 . i - row indices 3415 . j - column indices 3416 - a - matrix values 3417 3418 Output Parameter: 3419 . mat - the matrix 3420 3421 Level: intermediate 3422 3423 Notes: 3424 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3425 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3426 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3427 3428 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3429 3430 The format which is used for the sparse matrix input, is equivalent to a 3431 row-major ordering.. i.e for the following matrix, the input data expected is 3432 as shown: 3433 3434 1 0 0 3435 2 0 3 P0 3436 ------- 3437 4 5 6 P1 3438 3439 Process0 [P0]: rows_owned=[0,1] 3440 i = {0,1,3} [size = nrow+1 = 2+1] 3441 j = {0,0,2} [size = nz = 6] 3442 v = {1,2,3} [size = nz = 6] 3443 3444 Process1 [P1]: rows_owned=[2] 3445 i = {0,3} [size = nrow+1 = 1+1] 3446 j = {0,1,2} [size = nz = 6] 3447 v = {4,5,6} [size = nz = 6] 3448 3449 .keywords: matrix, aij, compressed row, sparse, parallel 3450 3451 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3452 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3453 @*/ 3454 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) 3455 { 3456 PetscErrorCode ierr; 3457 3458 PetscFunctionBegin; 3459 if (i[0]) { 3460 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3461 } 3462 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3463 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3464 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3465 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3466 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3467 PetscFunctionReturn(0); 3468 } 3469 3470 #undef __FUNCT__ 3471 #define __FUNCT__ "MatCreateMPIAIJ" 3472 /*@C 3473 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3474 (the default parallel PETSc format). For good matrix assembly performance 3475 the user should preallocate the matrix storage by setting the parameters 3476 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3477 performance can be increased by more than a factor of 50. 3478 3479 Collective on MPI_Comm 3480 3481 Input Parameters: 3482 + comm - MPI communicator 3483 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3484 This value should be the same as the local size used in creating the 3485 y vector for the matrix-vector product y = Ax. 3486 . n - This value should be the same as the local size used in creating the 3487 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3488 calculated if N is given) For square matrices n is almost always m. 3489 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3490 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3491 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3492 (same value is used for all local rows) 3493 . d_nnz - array containing the number of nonzeros in the various rows of the 3494 DIAGONAL portion of the local submatrix (possibly different for each row) 3495 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3496 The size of this array is equal to the number of local rows, i.e 'm'. 3497 You must leave room for the diagonal entry even if it is zero. 3498 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3499 submatrix (same value is used for all local rows). 3500 - o_nnz - array containing the number of nonzeros in the various rows of the 3501 OFF-DIAGONAL portion of the local submatrix (possibly different for 3502 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3503 structure. The size of this array is equal to the number 3504 of local rows, i.e 'm'. 3505 3506 Output Parameter: 3507 . A - the matrix 3508 3509 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3510 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3511 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3512 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3513 3514 Notes: 3515 If the *_nnz parameter is given then the *_nz parameter is ignored 3516 3517 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3518 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3519 storage requirements for this matrix. 3520 3521 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3522 processor than it must be used on all processors that share the object for 3523 that argument. 3524 3525 The user MUST specify either the local or global matrix dimensions 3526 (possibly both). 3527 3528 The parallel matrix is partitioned across processors such that the 3529 first m0 rows belong to process 0, the next m1 rows belong to 3530 process 1, the next m2 rows belong to process 2 etc.. where 3531 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3532 values corresponding to [m x N] submatrix. 3533 3534 The columns are logically partitioned with the n0 columns belonging 3535 to 0th partition, the next n1 columns belonging to the next 3536 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3537 3538 The DIAGONAL portion of the local submatrix on any given processor 3539 is the submatrix corresponding to the rows and columns m,n 3540 corresponding to the given processor. i.e diagonal matrix on 3541 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3542 etc. The remaining portion of the local submatrix [m x (N-n)] 3543 constitute the OFF-DIAGONAL portion. The example below better 3544 illustrates this concept. 3545 3546 For a square global matrix we define each processor's diagonal portion 3547 to be its local rows and the corresponding columns (a square submatrix); 3548 each processor's off-diagonal portion encompasses the remainder of the 3549 local matrix (a rectangular submatrix). 3550 3551 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3552 3553 When calling this routine with a single process communicator, a matrix of 3554 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3555 type of communicator, use the construction mechanism: 3556 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3557 3558 By default, this format uses inodes (identical nodes) when possible. 3559 We search for consecutive rows with the same nonzero structure, thereby 3560 reusing matrix information to achieve increased efficiency. 3561 3562 Options Database Keys: 3563 + -mat_no_inode - Do not use inodes 3564 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3565 - -mat_aij_oneindex - Internally use indexing starting at 1 3566 rather than 0. Note that when calling MatSetValues(), 3567 the user still MUST index entries starting at 0! 3568 3569 3570 Example usage: 3571 3572 Consider the following 8x8 matrix with 34 non-zero values, that is 3573 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3574 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3575 as follows: 3576 3577 .vb 3578 1 2 0 | 0 3 0 | 0 4 3579 Proc0 0 5 6 | 7 0 0 | 8 0 3580 9 0 10 | 11 0 0 | 12 0 3581 ------------------------------------- 3582 13 0 14 | 15 16 17 | 0 0 3583 Proc1 0 18 0 | 19 20 21 | 0 0 3584 0 0 0 | 22 23 0 | 24 0 3585 ------------------------------------- 3586 Proc2 25 26 27 | 0 0 28 | 29 0 3587 30 0 0 | 31 32 33 | 0 34 3588 .ve 3589 3590 This can be represented as a collection of submatrices as: 3591 3592 .vb 3593 A B C 3594 D E F 3595 G H I 3596 .ve 3597 3598 Where the submatrices A,B,C are owned by proc0, D,E,F are 3599 owned by proc1, G,H,I are owned by proc2. 3600 3601 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3602 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3603 The 'M','N' parameters are 8,8, and have the same values on all procs. 3604 3605 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3606 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3607 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3608 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3609 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3610 matrix, ans [DF] as another SeqAIJ matrix. 3611 3612 When d_nz, o_nz parameters are specified, d_nz storage elements are 3613 allocated for every row of the local diagonal submatrix, and o_nz 3614 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3615 One way to choose d_nz and o_nz is to use the max nonzerors per local 3616 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3617 In this case, the values of d_nz,o_nz are: 3618 .vb 3619 proc0 : dnz = 2, o_nz = 2 3620 proc1 : dnz = 3, o_nz = 2 3621 proc2 : dnz = 1, o_nz = 4 3622 .ve 3623 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3624 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3625 for proc3. i.e we are using 12+15+10=37 storage locations to store 3626 34 values. 3627 3628 When d_nnz, o_nnz parameters are specified, the storage is specified 3629 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3630 In the above case the values for d_nnz,o_nnz are: 3631 .vb 3632 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3633 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3634 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3635 .ve 3636 Here the space allocated is sum of all the above values i.e 34, and 3637 hence pre-allocation is perfect. 3638 3639 Level: intermediate 3640 3641 .keywords: matrix, aij, compressed row, sparse, parallel 3642 3643 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3644 MPIAIJ, MatCreateMPIAIJWithArrays() 3645 @*/ 3646 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) 3647 { 3648 PetscErrorCode ierr; 3649 PetscMPIInt size; 3650 3651 PetscFunctionBegin; 3652 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3653 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3654 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3655 if (size > 1) { 3656 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3657 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3658 } else { 3659 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3660 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3661 } 3662 PetscFunctionReturn(0); 3663 } 3664 3665 #undef __FUNCT__ 3666 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3667 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3668 { 3669 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3670 3671 PetscFunctionBegin; 3672 *Ad = a->A; 3673 *Ao = a->B; 3674 *colmap = a->garray; 3675 PetscFunctionReturn(0); 3676 } 3677 3678 #undef __FUNCT__ 3679 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3680 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3681 { 3682 PetscErrorCode ierr; 3683 PetscInt i; 3684 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3685 3686 PetscFunctionBegin; 3687 if (coloring->ctype == IS_COLORING_GLOBAL) { 3688 ISColoringValue *allcolors,*colors; 3689 ISColoring ocoloring; 3690 3691 /* set coloring for diagonal portion */ 3692 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3693 3694 /* set coloring for off-diagonal portion */ 3695 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3696 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3697 for (i=0; i<a->B->cmap->n; i++) { 3698 colors[i] = allcolors[a->garray[i]]; 3699 } 3700 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3701 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3702 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3703 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3704 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3705 ISColoringValue *colors; 3706 PetscInt *larray; 3707 ISColoring ocoloring; 3708 3709 /* set coloring for diagonal portion */ 3710 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3711 for (i=0; i<a->A->cmap->n; i++) { 3712 larray[i] = i + A->cmap->rstart; 3713 } 3714 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3715 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3716 for (i=0; i<a->A->cmap->n; i++) { 3717 colors[i] = coloring->colors[larray[i]]; 3718 } 3719 ierr = PetscFree(larray);CHKERRQ(ierr); 3720 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3721 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3722 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3723 3724 /* set coloring for off-diagonal portion */ 3725 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3726 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3727 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3728 for (i=0; i<a->B->cmap->n; i++) { 3729 colors[i] = coloring->colors[larray[i]]; 3730 } 3731 ierr = PetscFree(larray);CHKERRQ(ierr); 3732 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3733 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3734 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3735 } else { 3736 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3737 } 3738 3739 PetscFunctionReturn(0); 3740 } 3741 3742 #if defined(PETSC_HAVE_ADIC) 3743 #undef __FUNCT__ 3744 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3745 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3746 { 3747 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3748 PetscErrorCode ierr; 3749 3750 PetscFunctionBegin; 3751 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3752 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3753 PetscFunctionReturn(0); 3754 } 3755 #endif 3756 3757 #undef __FUNCT__ 3758 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3759 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3760 { 3761 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3762 PetscErrorCode ierr; 3763 3764 PetscFunctionBegin; 3765 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3766 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3767 PetscFunctionReturn(0); 3768 } 3769 3770 #undef __FUNCT__ 3771 #define __FUNCT__ "MatMerge" 3772 /*@ 3773 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3774 matrices from each processor 3775 3776 Collective on MPI_Comm 3777 3778 Input Parameters: 3779 + comm - the communicators the parallel matrix will live on 3780 . inmat - the input sequential matrices 3781 . n - number of local columns (or PETSC_DECIDE) 3782 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3783 3784 Output Parameter: 3785 . outmat - the parallel matrix generated 3786 3787 Level: advanced 3788 3789 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3790 3791 @*/ 3792 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3793 { 3794 PetscErrorCode ierr; 3795 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3796 PetscInt *indx; 3797 PetscScalar *values; 3798 3799 PetscFunctionBegin; 3800 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3801 if (scall == MAT_INITIAL_MATRIX){ 3802 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3803 if (n == PETSC_DECIDE){ 3804 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3805 } 3806 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3807 rstart -= m; 3808 3809 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3810 for (i=0;i<m;i++) { 3811 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3812 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3813 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3814 } 3815 /* This routine will ONLY return MPIAIJ type matrix */ 3816 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3817 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3818 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3819 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3820 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3821 3822 } else if (scall == MAT_REUSE_MATRIX){ 3823 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3824 } else { 3825 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3826 } 3827 3828 for (i=0;i<m;i++) { 3829 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3830 Ii = i + rstart; 3831 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3832 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3833 } 3834 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3835 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3836 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3837 3838 PetscFunctionReturn(0); 3839 } 3840 3841 #undef __FUNCT__ 3842 #define __FUNCT__ "MatFileSplit" 3843 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3844 { 3845 PetscErrorCode ierr; 3846 PetscMPIInt rank; 3847 PetscInt m,N,i,rstart,nnz; 3848 size_t len; 3849 const PetscInt *indx; 3850 PetscViewer out; 3851 char *name; 3852 Mat B; 3853 const PetscScalar *values; 3854 3855 PetscFunctionBegin; 3856 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3857 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3858 /* Should this be the type of the diagonal block of A? */ 3859 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3860 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3861 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3862 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3863 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3864 for (i=0;i<m;i++) { 3865 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3866 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3867 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3868 } 3869 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3870 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3871 3872 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3873 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3874 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3875 sprintf(name,"%s.%d",outfile,rank); 3876 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3877 ierr = PetscFree(name); 3878 ierr = MatView(B,out);CHKERRQ(ierr); 3879 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3880 ierr = MatDestroy(B);CHKERRQ(ierr); 3881 PetscFunctionReturn(0); 3882 } 3883 3884 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3885 #undef __FUNCT__ 3886 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3887 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3888 { 3889 PetscErrorCode ierr; 3890 Mat_Merge_SeqsToMPI *merge; 3891 PetscContainer container; 3892 3893 PetscFunctionBegin; 3894 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3895 if (container) { 3896 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3897 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3898 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3899 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3900 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3901 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3902 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3903 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3904 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3905 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3906 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3907 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3908 3909 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3910 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3911 } 3912 ierr = PetscFree(merge);CHKERRQ(ierr); 3913 3914 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3915 PetscFunctionReturn(0); 3916 } 3917 3918 #include "../src/mat/utils/freespace.h" 3919 #include "petscbt.h" 3920 3921 #undef __FUNCT__ 3922 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3923 /*@C 3924 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3925 matrices from each processor 3926 3927 Collective on MPI_Comm 3928 3929 Input Parameters: 3930 + comm - the communicators the parallel matrix will live on 3931 . seqmat - the input sequential matrices 3932 . m - number of local rows (or PETSC_DECIDE) 3933 . n - number of local columns (or PETSC_DECIDE) 3934 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3935 3936 Output Parameter: 3937 . mpimat - the parallel matrix generated 3938 3939 Level: advanced 3940 3941 Notes: 3942 The dimensions of the sequential matrix in each processor MUST be the same. 3943 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3944 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3945 @*/ 3946 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3947 { 3948 PetscErrorCode ierr; 3949 MPI_Comm comm=((PetscObject)mpimat)->comm; 3950 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3951 PetscMPIInt size,rank,taga,*len_s; 3952 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j; 3953 PetscInt proc,m; 3954 PetscInt **buf_ri,**buf_rj; 3955 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3956 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3957 MPI_Request *s_waits,*r_waits; 3958 MPI_Status *status; 3959 MatScalar *aa=a->a; 3960 MatScalar **abuf_r,*ba_i; 3961 Mat_Merge_SeqsToMPI *merge; 3962 PetscContainer container; 3963 3964 PetscFunctionBegin; 3965 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3966 3967 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3968 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3969 3970 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3971 if (container) { 3972 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3973 } 3974 bi = merge->bi; 3975 bj = merge->bj; 3976 buf_ri = merge->buf_ri; 3977 buf_rj = merge->buf_rj; 3978 3979 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3980 owners = merge->rowmap.range; 3981 len_s = merge->len_s; 3982 3983 /* send and recv matrix values */ 3984 /*-----------------------------*/ 3985 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3986 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3987 3988 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3989 for (proc=0,k=0; proc<size; proc++){ 3990 if (!len_s[proc]) continue; 3991 i = owners[proc]; 3992 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3993 k++; 3994 } 3995 3996 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3997 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3998 ierr = PetscFree(status);CHKERRQ(ierr); 3999 4000 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4001 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4002 4003 /* insert mat values of mpimat */ 4004 /*----------------------------*/ 4005 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4006 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4007 nextrow = buf_ri_k + merge->nrecv; 4008 nextai = nextrow + merge->nrecv; 4009 4010 for (k=0; k<merge->nrecv; k++){ 4011 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4012 nrows = *(buf_ri_k[k]); 4013 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4014 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4015 } 4016 4017 /* set values of ba */ 4018 m = merge->rowmap.n; 4019 for (i=0; i<m; i++) { 4020 arow = owners[rank] + i; 4021 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4022 bnzi = bi[i+1] - bi[i]; 4023 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4024 4025 /* add local non-zero vals of this proc's seqmat into ba */ 4026 anzi = ai[arow+1] - ai[arow]; 4027 aj = a->j + ai[arow]; 4028 aa = a->a + ai[arow]; 4029 nextaj = 0; 4030 for (j=0; nextaj<anzi; j++){ 4031 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4032 ba_i[j] += aa[nextaj++]; 4033 } 4034 } 4035 4036 /* add received vals into ba */ 4037 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4038 /* i-th row */ 4039 if (i == *nextrow[k]) { 4040 anzi = *(nextai[k]+1) - *nextai[k]; 4041 aj = buf_rj[k] + *(nextai[k]); 4042 aa = abuf_r[k] + *(nextai[k]); 4043 nextaj = 0; 4044 for (j=0; nextaj<anzi; j++){ 4045 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4046 ba_i[j] += aa[nextaj++]; 4047 } 4048 } 4049 nextrow[k]++; nextai[k]++; 4050 } 4051 } 4052 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4053 } 4054 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4055 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4056 4057 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4058 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4059 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4060 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4061 PetscFunctionReturn(0); 4062 } 4063 4064 #undef __FUNCT__ 4065 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 4066 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4067 { 4068 PetscErrorCode ierr; 4069 Mat B_mpi; 4070 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4071 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4072 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4073 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4074 PetscInt len,proc,*dnz,*onz; 4075 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4076 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4077 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4078 MPI_Status *status; 4079 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 4080 PetscBT lnkbt; 4081 Mat_Merge_SeqsToMPI *merge; 4082 PetscContainer container; 4083 4084 PetscFunctionBegin; 4085 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4086 4087 /* make sure it is a PETSc comm */ 4088 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4089 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4090 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4091 4092 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4093 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4094 4095 /* determine row ownership */ 4096 /*---------------------------------------------------------*/ 4097 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 4098 merge->rowmap.n = m; 4099 merge->rowmap.N = M; 4100 merge->rowmap.bs = 1; 4101 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 4102 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4103 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4104 4105 m = merge->rowmap.n; 4106 M = merge->rowmap.N; 4107 owners = merge->rowmap.range; 4108 4109 /* determine the number of messages to send, their lengths */ 4110 /*---------------------------------------------------------*/ 4111 len_s = merge->len_s; 4112 4113 len = 0; /* length of buf_si[] */ 4114 merge->nsend = 0; 4115 for (proc=0; proc<size; proc++){ 4116 len_si[proc] = 0; 4117 if (proc == rank){ 4118 len_s[proc] = 0; 4119 } else { 4120 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4121 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4122 } 4123 if (len_s[proc]) { 4124 merge->nsend++; 4125 nrows = 0; 4126 for (i=owners[proc]; i<owners[proc+1]; i++){ 4127 if (ai[i+1] > ai[i]) nrows++; 4128 } 4129 len_si[proc] = 2*(nrows+1); 4130 len += len_si[proc]; 4131 } 4132 } 4133 4134 /* determine the number and length of messages to receive for ij-structure */ 4135 /*-------------------------------------------------------------------------*/ 4136 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4137 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4138 4139 /* post the Irecv of j-structure */ 4140 /*-------------------------------*/ 4141 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4142 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4143 4144 /* post the Isend of j-structure */ 4145 /*--------------------------------*/ 4146 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 4147 sj_waits = si_waits + merge->nsend; 4148 4149 for (proc=0, k=0; proc<size; proc++){ 4150 if (!len_s[proc]) continue; 4151 i = owners[proc]; 4152 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4153 k++; 4154 } 4155 4156 /* receives and sends of j-structure are complete */ 4157 /*------------------------------------------------*/ 4158 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4159 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4160 4161 /* send and recv i-structure */ 4162 /*---------------------------*/ 4163 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4164 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4165 4166 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4167 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4168 for (proc=0,k=0; proc<size; proc++){ 4169 if (!len_s[proc]) continue; 4170 /* form outgoing message for i-structure: 4171 buf_si[0]: nrows to be sent 4172 [1:nrows]: row index (global) 4173 [nrows+1:2*nrows+1]: i-structure index 4174 */ 4175 /*-------------------------------------------*/ 4176 nrows = len_si[proc]/2 - 1; 4177 buf_si_i = buf_si + nrows+1; 4178 buf_si[0] = nrows; 4179 buf_si_i[0] = 0; 4180 nrows = 0; 4181 for (i=owners[proc]; i<owners[proc+1]; i++){ 4182 anzi = ai[i+1] - ai[i]; 4183 if (anzi) { 4184 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4185 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4186 nrows++; 4187 } 4188 } 4189 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4190 k++; 4191 buf_si += len_si[proc]; 4192 } 4193 4194 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4195 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4196 4197 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4198 for (i=0; i<merge->nrecv; i++){ 4199 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); 4200 } 4201 4202 ierr = PetscFree(len_si);CHKERRQ(ierr); 4203 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4204 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4205 ierr = PetscFree(si_waits);CHKERRQ(ierr); 4206 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4207 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4208 ierr = PetscFree(status);CHKERRQ(ierr); 4209 4210 /* compute a local seq matrix in each processor */ 4211 /*----------------------------------------------*/ 4212 /* allocate bi array and free space for accumulating nonzero column info */ 4213 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4214 bi[0] = 0; 4215 4216 /* create and initialize a linked list */ 4217 nlnk = N+1; 4218 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4219 4220 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4221 len = 0; 4222 len = ai[owners[rank+1]] - ai[owners[rank]]; 4223 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4224 current_space = free_space; 4225 4226 /* determine symbolic info for each local row */ 4227 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4228 nextrow = buf_ri_k + merge->nrecv; 4229 nextai = nextrow + merge->nrecv; 4230 for (k=0; k<merge->nrecv; k++){ 4231 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4232 nrows = *buf_ri_k[k]; 4233 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4234 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4235 } 4236 4237 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4238 len = 0; 4239 for (i=0;i<m;i++) { 4240 bnzi = 0; 4241 /* add local non-zero cols of this proc's seqmat into lnk */ 4242 arow = owners[rank] + i; 4243 anzi = ai[arow+1] - ai[arow]; 4244 aj = a->j + ai[arow]; 4245 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4246 bnzi += nlnk; 4247 /* add received col data into lnk */ 4248 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4249 if (i == *nextrow[k]) { /* i-th row */ 4250 anzi = *(nextai[k]+1) - *nextai[k]; 4251 aj = buf_rj[k] + *nextai[k]; 4252 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4253 bnzi += nlnk; 4254 nextrow[k]++; nextai[k]++; 4255 } 4256 } 4257 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4258 4259 /* if free space is not available, make more free space */ 4260 if (current_space->local_remaining<bnzi) { 4261 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4262 nspacedouble++; 4263 } 4264 /* copy data into free space, then initialize lnk */ 4265 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4266 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4267 4268 current_space->array += bnzi; 4269 current_space->local_used += bnzi; 4270 current_space->local_remaining -= bnzi; 4271 4272 bi[i+1] = bi[i] + bnzi; 4273 } 4274 4275 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4276 4277 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4278 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4279 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4280 4281 /* create symbolic parallel matrix B_mpi */ 4282 /*---------------------------------------*/ 4283 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4284 if (n==PETSC_DECIDE) { 4285 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4286 } else { 4287 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4288 } 4289 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4290 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4291 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4292 4293 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 4294 B_mpi->assembled = PETSC_FALSE; 4295 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4296 merge->bi = bi; 4297 merge->bj = bj; 4298 merge->buf_ri = buf_ri; 4299 merge->buf_rj = buf_rj; 4300 merge->coi = PETSC_NULL; 4301 merge->coj = PETSC_NULL; 4302 merge->owners_co = PETSC_NULL; 4303 4304 /* attach the supporting struct to B_mpi for reuse */ 4305 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4306 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4307 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4308 *mpimat = B_mpi; 4309 4310 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4311 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4312 PetscFunctionReturn(0); 4313 } 4314 4315 #undef __FUNCT__ 4316 #define __FUNCT__ "MatMerge_SeqsToMPI" 4317 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4318 { 4319 PetscErrorCode ierr; 4320 4321 PetscFunctionBegin; 4322 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4323 if (scall == MAT_INITIAL_MATRIX){ 4324 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4325 } 4326 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4327 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4328 PetscFunctionReturn(0); 4329 } 4330 4331 #undef __FUNCT__ 4332 #define __FUNCT__ "MatGetLocalMat" 4333 /*@ 4334 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4335 4336 Not Collective 4337 4338 Input Parameters: 4339 + A - the matrix 4340 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4341 4342 Output Parameter: 4343 . A_loc - the local sequential matrix generated 4344 4345 Level: developer 4346 4347 @*/ 4348 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4349 { 4350 PetscErrorCode ierr; 4351 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4352 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4353 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4354 MatScalar *aa=a->a,*ba=b->a,*cam; 4355 PetscScalar *ca; 4356 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4357 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4358 4359 PetscFunctionBegin; 4360 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4361 if (scall == MAT_INITIAL_MATRIX){ 4362 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4363 ci[0] = 0; 4364 for (i=0; i<am; i++){ 4365 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4366 } 4367 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4368 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4369 k = 0; 4370 for (i=0; i<am; i++) { 4371 ncols_o = bi[i+1] - bi[i]; 4372 ncols_d = ai[i+1] - ai[i]; 4373 /* off-diagonal portion of A */ 4374 for (jo=0; jo<ncols_o; jo++) { 4375 col = cmap[*bj]; 4376 if (col >= cstart) break; 4377 cj[k] = col; bj++; 4378 ca[k++] = *ba++; 4379 } 4380 /* diagonal portion of A */ 4381 for (j=0; j<ncols_d; j++) { 4382 cj[k] = cstart + *aj++; 4383 ca[k++] = *aa++; 4384 } 4385 /* off-diagonal portion of A */ 4386 for (j=jo; j<ncols_o; j++) { 4387 cj[k] = cmap[*bj++]; 4388 ca[k++] = *ba++; 4389 } 4390 } 4391 /* put together the new matrix */ 4392 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4393 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4394 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4395 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4396 mat->free_a = PETSC_TRUE; 4397 mat->free_ij = PETSC_TRUE; 4398 mat->nonew = 0; 4399 } else if (scall == MAT_REUSE_MATRIX){ 4400 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4401 ci = mat->i; cj = mat->j; cam = mat->a; 4402 for (i=0; i<am; i++) { 4403 /* off-diagonal portion of A */ 4404 ncols_o = bi[i+1] - bi[i]; 4405 for (jo=0; jo<ncols_o; jo++) { 4406 col = cmap[*bj]; 4407 if (col >= cstart) break; 4408 *cam++ = *ba++; bj++; 4409 } 4410 /* diagonal portion of A */ 4411 ncols_d = ai[i+1] - ai[i]; 4412 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4413 /* off-diagonal portion of A */ 4414 for (j=jo; j<ncols_o; j++) { 4415 *cam++ = *ba++; bj++; 4416 } 4417 } 4418 } else { 4419 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4420 } 4421 4422 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4423 PetscFunctionReturn(0); 4424 } 4425 4426 #undef __FUNCT__ 4427 #define __FUNCT__ "MatGetLocalMatCondensed" 4428 /*@C 4429 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4430 4431 Not Collective 4432 4433 Input Parameters: 4434 + A - the matrix 4435 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4436 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4437 4438 Output Parameter: 4439 . A_loc - the local sequential matrix generated 4440 4441 Level: developer 4442 4443 @*/ 4444 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4445 { 4446 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4447 PetscErrorCode ierr; 4448 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4449 IS isrowa,iscola; 4450 Mat *aloc; 4451 4452 PetscFunctionBegin; 4453 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4454 if (!row){ 4455 start = A->rmap->rstart; end = A->rmap->rend; 4456 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4457 } else { 4458 isrowa = *row; 4459 } 4460 if (!col){ 4461 start = A->cmap->rstart; 4462 cmap = a->garray; 4463 nzA = a->A->cmap->n; 4464 nzB = a->B->cmap->n; 4465 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4466 ncols = 0; 4467 for (i=0; i<nzB; i++) { 4468 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4469 else break; 4470 } 4471 imark = i; 4472 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4473 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4474 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4475 ierr = PetscFree(idx);CHKERRQ(ierr); 4476 } else { 4477 iscola = *col; 4478 } 4479 if (scall != MAT_INITIAL_MATRIX){ 4480 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4481 aloc[0] = *A_loc; 4482 } 4483 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4484 *A_loc = aloc[0]; 4485 ierr = PetscFree(aloc);CHKERRQ(ierr); 4486 if (!row){ 4487 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4488 } 4489 if (!col){ 4490 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4491 } 4492 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4493 PetscFunctionReturn(0); 4494 } 4495 4496 #undef __FUNCT__ 4497 #define __FUNCT__ "MatGetBrowsOfAcols" 4498 /*@C 4499 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4500 4501 Collective on Mat 4502 4503 Input Parameters: 4504 + A,B - the matrices in mpiaij format 4505 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4506 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4507 4508 Output Parameter: 4509 + rowb, colb - index sets of rows and columns of B to extract 4510 . brstart - row index of B_seq from which next B->rmap->n rows are taken from B's local rows 4511 - B_seq - the sequential matrix generated 4512 4513 Level: developer 4514 4515 @*/ 4516 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4517 { 4518 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4519 PetscErrorCode ierr; 4520 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4521 IS isrowb,iscolb; 4522 Mat *bseq; 4523 4524 PetscFunctionBegin; 4525 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4526 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); 4527 } 4528 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4529 4530 if (scall == MAT_INITIAL_MATRIX){ 4531 start = A->cmap->rstart; 4532 cmap = a->garray; 4533 nzA = a->A->cmap->n; 4534 nzB = a->B->cmap->n; 4535 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4536 ncols = 0; 4537 for (i=0; i<nzB; i++) { /* row < local row index */ 4538 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4539 else break; 4540 } 4541 imark = i; 4542 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4543 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4544 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4545 ierr = PetscFree(idx);CHKERRQ(ierr); 4546 *brstart = imark; 4547 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4548 } else { 4549 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4550 isrowb = *rowb; iscolb = *colb; 4551 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4552 bseq[0] = *B_seq; 4553 } 4554 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4555 *B_seq = bseq[0]; 4556 ierr = PetscFree(bseq);CHKERRQ(ierr); 4557 if (!rowb){ 4558 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4559 } else { 4560 *rowb = isrowb; 4561 } 4562 if (!colb){ 4563 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4564 } else { 4565 *colb = iscolb; 4566 } 4567 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4568 PetscFunctionReturn(0); 4569 } 4570 4571 #undef __FUNCT__ 4572 #define __FUNCT__ "MatGetBrowsOfAoCols" 4573 /*@C 4574 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4575 of the OFF-DIAGONAL portion of local A 4576 4577 Collective on Mat 4578 4579 Input Parameters: 4580 + A,B - the matrices in mpiaij format 4581 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4582 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4583 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4584 4585 Output Parameter: 4586 + B_oth - the sequential matrix generated 4587 4588 Level: developer 4589 4590 @*/ 4591 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,MatScalar **bufa_ptr,Mat *B_oth) 4592 { 4593 VecScatter_MPI_General *gen_to,*gen_from; 4594 PetscErrorCode ierr; 4595 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4596 Mat_SeqAIJ *b_oth; 4597 VecScatter ctx=a->Mvctx; 4598 MPI_Comm comm=((PetscObject)ctx)->comm; 4599 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4600 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4601 PetscScalar *rvalues,*svalues; 4602 MatScalar *b_otha,*bufa,*bufA; 4603 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4604 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4605 MPI_Status *sstatus,rstatus; 4606 PetscMPIInt jj; 4607 PetscInt *cols,sbs,rbs; 4608 PetscScalar *vals; 4609 4610 PetscFunctionBegin; 4611 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4612 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); 4613 } 4614 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4615 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4616 4617 gen_to = (VecScatter_MPI_General*)ctx->todata; 4618 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4619 rvalues = gen_from->values; /* holds the length of receiving row */ 4620 svalues = gen_to->values; /* holds the length of sending row */ 4621 nrecvs = gen_from->n; 4622 nsends = gen_to->n; 4623 4624 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4625 srow = gen_to->indices; /* local row index to be sent */ 4626 sstarts = gen_to->starts; 4627 sprocs = gen_to->procs; 4628 sstatus = gen_to->sstatus; 4629 sbs = gen_to->bs; 4630 rstarts = gen_from->starts; 4631 rprocs = gen_from->procs; 4632 rbs = gen_from->bs; 4633 4634 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4635 if (scall == MAT_INITIAL_MATRIX){ 4636 /* i-array */ 4637 /*---------*/ 4638 /* post receives */ 4639 for (i=0; i<nrecvs; i++){ 4640 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4641 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4642 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4643 } 4644 4645 /* pack the outgoing message */ 4646 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4647 rstartsj = sstartsj + nsends +1; 4648 sstartsj[0] = 0; rstartsj[0] = 0; 4649 len = 0; /* total length of j or a array to be sent */ 4650 k = 0; 4651 for (i=0; i<nsends; i++){ 4652 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4653 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4654 for (j=0; j<nrows; j++) { 4655 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4656 for (l=0; l<sbs; l++){ 4657 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4658 rowlen[j*sbs+l] = ncols; 4659 len += ncols; 4660 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4661 } 4662 k++; 4663 } 4664 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4665 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4666 } 4667 /* recvs and sends of i-array are completed */ 4668 i = nrecvs; 4669 while (i--) { 4670 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4671 } 4672 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4673 4674 /* allocate buffers for sending j and a arrays */ 4675 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4676 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4677 4678 /* create i-array of B_oth */ 4679 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4680 b_othi[0] = 0; 4681 len = 0; /* total length of j or a array to be received */ 4682 k = 0; 4683 for (i=0; i<nrecvs; i++){ 4684 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4685 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4686 for (j=0; j<nrows; j++) { 4687 b_othi[k+1] = b_othi[k] + rowlen[j]; 4688 len += rowlen[j]; k++; 4689 } 4690 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4691 } 4692 4693 /* allocate space for j and a arrrays of B_oth */ 4694 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4695 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 4696 4697 /* j-array */ 4698 /*---------*/ 4699 /* post receives of j-array */ 4700 for (i=0; i<nrecvs; i++){ 4701 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4702 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4703 } 4704 4705 /* pack the outgoing message j-array */ 4706 k = 0; 4707 for (i=0; i<nsends; i++){ 4708 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4709 bufJ = bufj+sstartsj[i]; 4710 for (j=0; j<nrows; j++) { 4711 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4712 for (ll=0; ll<sbs; ll++){ 4713 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4714 for (l=0; l<ncols; l++){ 4715 *bufJ++ = cols[l]; 4716 } 4717 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4718 } 4719 } 4720 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4721 } 4722 4723 /* recvs and sends of j-array are completed */ 4724 i = nrecvs; 4725 while (i--) { 4726 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4727 } 4728 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4729 } else if (scall == MAT_REUSE_MATRIX){ 4730 sstartsj = *startsj; 4731 rstartsj = sstartsj + nsends +1; 4732 bufa = *bufa_ptr; 4733 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4734 b_otha = b_oth->a; 4735 } else { 4736 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4737 } 4738 4739 /* a-array */ 4740 /*---------*/ 4741 /* post receives of a-array */ 4742 for (i=0; i<nrecvs; i++){ 4743 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4744 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4745 } 4746 4747 /* pack the outgoing message a-array */ 4748 k = 0; 4749 for (i=0; i<nsends; i++){ 4750 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4751 bufA = bufa+sstartsj[i]; 4752 for (j=0; j<nrows; j++) { 4753 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4754 for (ll=0; ll<sbs; ll++){ 4755 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4756 for (l=0; l<ncols; l++){ 4757 *bufA++ = vals[l]; 4758 } 4759 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4760 } 4761 } 4762 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4763 } 4764 /* recvs and sends of a-array are completed */ 4765 i = nrecvs; 4766 while (i--) { 4767 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4768 } 4769 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4770 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4771 4772 if (scall == MAT_INITIAL_MATRIX){ 4773 /* put together the new matrix */ 4774 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4775 4776 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4777 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4778 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4779 b_oth->free_a = PETSC_TRUE; 4780 b_oth->free_ij = PETSC_TRUE; 4781 b_oth->nonew = 0; 4782 4783 ierr = PetscFree(bufj);CHKERRQ(ierr); 4784 if (!startsj || !bufa_ptr){ 4785 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4786 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4787 } else { 4788 *startsj = sstartsj; 4789 *bufa_ptr = bufa; 4790 } 4791 } 4792 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4793 PetscFunctionReturn(0); 4794 } 4795 4796 #undef __FUNCT__ 4797 #define __FUNCT__ "MatGetCommunicationStructs" 4798 /*@C 4799 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4800 4801 Not Collective 4802 4803 Input Parameters: 4804 . A - The matrix in mpiaij format 4805 4806 Output Parameter: 4807 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4808 . colmap - A map from global column index to local index into lvec 4809 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4810 4811 Level: developer 4812 4813 @*/ 4814 #if defined (PETSC_USE_CTABLE) 4815 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4816 #else 4817 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4818 #endif 4819 { 4820 Mat_MPIAIJ *a; 4821 4822 PetscFunctionBegin; 4823 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4824 PetscValidPointer(lvec, 2) 4825 PetscValidPointer(colmap, 3) 4826 PetscValidPointer(multScatter, 4) 4827 a = (Mat_MPIAIJ *) A->data; 4828 if (lvec) *lvec = a->lvec; 4829 if (colmap) *colmap = a->colmap; 4830 if (multScatter) *multScatter = a->Mvctx; 4831 PetscFunctionReturn(0); 4832 } 4833 4834 EXTERN_C_BEGIN 4835 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,const MatType,MatReuse,Mat*); 4836 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,const MatType,MatReuse,Mat*); 4837 EXTERN_C_END 4838 4839 #include "../src/mat/impls/dense/mpi/mpidense.h" 4840 4841 #undef __FUNCT__ 4842 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4843 /* 4844 Computes (B'*A')' since computing B*A directly is untenable 4845 4846 n p p 4847 ( ) ( ) ( ) 4848 m ( A ) * n ( B ) = m ( C ) 4849 ( ) ( ) ( ) 4850 4851 */ 4852 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4853 { 4854 PetscErrorCode ierr; 4855 Mat At,Bt,Ct; 4856 4857 PetscFunctionBegin; 4858 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4859 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4860 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4861 ierr = MatDestroy(At);CHKERRQ(ierr); 4862 ierr = MatDestroy(Bt);CHKERRQ(ierr); 4863 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4864 ierr = MatDestroy(Ct);CHKERRQ(ierr); 4865 PetscFunctionReturn(0); 4866 } 4867 4868 #undef __FUNCT__ 4869 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4870 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4871 { 4872 PetscErrorCode ierr; 4873 PetscInt m=A->rmap->n,n=B->cmap->n; 4874 Mat Cmat; 4875 4876 PetscFunctionBegin; 4877 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); 4878 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 4879 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4880 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4881 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 4882 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4883 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4884 *C = Cmat; 4885 PetscFunctionReturn(0); 4886 } 4887 4888 /* ----------------------------------------------------------------*/ 4889 #undef __FUNCT__ 4890 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4891 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4892 { 4893 PetscErrorCode ierr; 4894 4895 PetscFunctionBegin; 4896 if (scall == MAT_INITIAL_MATRIX){ 4897 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 4898 } 4899 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 4900 PetscFunctionReturn(0); 4901 } 4902 4903 EXTERN_C_BEGIN 4904 #if defined(PETSC_HAVE_MUMPS) 4905 extern PetscErrorCode MatGetFactor_mpiaij_mumps(Mat,MatFactorType,Mat*); 4906 #endif 4907 #if defined(PETSC_HAVE_PASTIX) 4908 extern PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 4909 #endif 4910 #if defined(PETSC_HAVE_SUPERLU_DIST) 4911 extern PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 4912 #endif 4913 #if defined(PETSC_HAVE_SPOOLES) 4914 extern PetscErrorCode MatGetFactor_mpiaij_spooles(Mat,MatFactorType,Mat*); 4915 #endif 4916 EXTERN_C_END 4917 4918 /*MC 4919 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4920 4921 Options Database Keys: 4922 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4923 4924 Level: beginner 4925 4926 .seealso: MatCreateMPIAIJ() 4927 M*/ 4928 4929 EXTERN_C_BEGIN 4930 #undef __FUNCT__ 4931 #define __FUNCT__ "MatCreate_MPIAIJ" 4932 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4933 { 4934 Mat_MPIAIJ *b; 4935 PetscErrorCode ierr; 4936 PetscMPIInt size; 4937 4938 PetscFunctionBegin; 4939 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4940 4941 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4942 B->data = (void*)b; 4943 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4944 B->rmap->bs = 1; 4945 B->assembled = PETSC_FALSE; 4946 B->mapping = 0; 4947 4948 B->insertmode = NOT_SET_VALUES; 4949 b->size = size; 4950 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4951 4952 /* build cache for off array entries formed */ 4953 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4954 b->donotstash = PETSC_FALSE; 4955 b->colmap = 0; 4956 b->garray = 0; 4957 b->roworiented = PETSC_TRUE; 4958 4959 /* stuff used for matrix vector multiply */ 4960 b->lvec = PETSC_NULL; 4961 b->Mvctx = PETSC_NULL; 4962 4963 /* stuff for MatGetRow() */ 4964 b->rowindices = 0; 4965 b->rowvalues = 0; 4966 b->getrowactive = PETSC_FALSE; 4967 4968 #if defined(PETSC_HAVE_SPOOLES) 4969 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_spooles_C", 4970 "MatGetFactor_mpiaij_spooles", 4971 MatGetFactor_mpiaij_spooles);CHKERRQ(ierr); 4972 #endif 4973 #if defined(PETSC_HAVE_MUMPS) 4974 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_mumps_C", 4975 "MatGetFactor_mpiaij_mumps", 4976 MatGetFactor_mpiaij_mumps);CHKERRQ(ierr); 4977 #endif 4978 #if defined(PETSC_HAVE_PASTIX) 4979 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_pastix_C", 4980 "MatGetFactor_mpiaij_pastix", 4981 MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 4982 #endif 4983 #if defined(PETSC_HAVE_SUPERLU_DIST) 4984 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_superlu_dist_C", 4985 "MatGetFactor_mpiaij_superlu_dist", 4986 MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 4987 #endif 4988 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4989 "MatStoreValues_MPIAIJ", 4990 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4991 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4992 "MatRetrieveValues_MPIAIJ", 4993 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4994 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4995 "MatGetDiagonalBlock_MPIAIJ", 4996 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4997 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4998 "MatIsTranspose_MPIAIJ", 4999 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5000 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 5001 "MatMPIAIJSetPreallocation_MPIAIJ", 5002 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5003 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 5004 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 5005 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5006 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 5007 "MatDiagonalScaleLocal_MPIAIJ", 5008 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5009 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 5010 "MatConvert_MPIAIJ_MPICSRPERM", 5011 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 5012 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 5013 "MatConvert_MPIAIJ_MPICRL", 5014 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 5015 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 5016 "MatMatMult_MPIDense_MPIAIJ", 5017 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5018 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 5019 "MatMatMultSymbolic_MPIDense_MPIAIJ", 5020 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5021 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 5022 "MatMatMultNumeric_MPIDense_MPIAIJ", 5023 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5024 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5025 PetscFunctionReturn(0); 5026 } 5027 EXTERN_C_END 5028 5029 #undef __FUNCT__ 5030 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5031 /*@ 5032 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5033 and "off-diagonal" part of the matrix in CSR format. 5034 5035 Collective on MPI_Comm 5036 5037 Input Parameters: 5038 + comm - MPI communicator 5039 . m - number of local rows (Cannot be PETSC_DECIDE) 5040 . n - This value should be the same as the local size used in creating the 5041 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5042 calculated if N is given) For square matrices n is almost always m. 5043 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5044 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5045 . i - row indices for "diagonal" portion of matrix 5046 . j - column indices 5047 . a - matrix values 5048 . oi - row indices for "off-diagonal" portion of matrix 5049 . oj - column indices 5050 - oa - matrix values 5051 5052 Output Parameter: 5053 . mat - the matrix 5054 5055 Level: advanced 5056 5057 Notes: 5058 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 5059 5060 The i and j indices are 0 based 5061 5062 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5063 5064 5065 .keywords: matrix, aij, compressed row, sparse, parallel 5066 5067 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5068 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 5069 @*/ 5070 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 5071 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5072 { 5073 PetscErrorCode ierr; 5074 Mat_MPIAIJ *maij; 5075 5076 PetscFunctionBegin; 5077 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5078 if (i[0]) { 5079 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5080 } 5081 if (oi[0]) { 5082 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5083 } 5084 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5085 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5086 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5087 maij = (Mat_MPIAIJ*) (*mat)->data; 5088 maij->donotstash = PETSC_TRUE; 5089 (*mat)->preallocated = PETSC_TRUE; 5090 5091 ierr = PetscMapSetBlockSize((*mat)->rmap,1);CHKERRQ(ierr); 5092 ierr = PetscMapSetBlockSize((*mat)->cmap,1);CHKERRQ(ierr); 5093 ierr = PetscMapSetUp((*mat)->rmap);CHKERRQ(ierr); 5094 ierr = PetscMapSetUp((*mat)->cmap);CHKERRQ(ierr); 5095 5096 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5097 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5098 5099 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5100 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5101 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5102 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5103 5104 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5105 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5106 PetscFunctionReturn(0); 5107 } 5108 5109 /* 5110 Special version for direct calls from Fortran 5111 */ 5112 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5113 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5114 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5115 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5116 #endif 5117 5118 /* Change these macros so can be used in void function */ 5119 #undef CHKERRQ 5120 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5121 #undef SETERRQ2 5122 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5123 #undef SETERRQ 5124 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5125 5126 EXTERN_C_BEGIN 5127 #undef __FUNCT__ 5128 #define __FUNCT__ "matsetvaluesmpiaij_" 5129 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5130 { 5131 Mat mat = *mmat; 5132 PetscInt m = *mm, n = *mn; 5133 InsertMode addv = *maddv; 5134 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5135 PetscScalar value; 5136 PetscErrorCode ierr; 5137 5138 MatPreallocated(mat); 5139 if (mat->insertmode == NOT_SET_VALUES) { 5140 mat->insertmode = addv; 5141 } 5142 #if defined(PETSC_USE_DEBUG) 5143 else if (mat->insertmode != addv) { 5144 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5145 } 5146 #endif 5147 { 5148 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5149 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5150 PetscTruth roworiented = aij->roworiented; 5151 5152 /* Some Variables required in the macro */ 5153 Mat A = aij->A; 5154 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5155 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5156 MatScalar *aa = a->a; 5157 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5158 Mat B = aij->B; 5159 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5160 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5161 MatScalar *ba = b->a; 5162 5163 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5164 PetscInt nonew = a->nonew; 5165 MatScalar *ap1,*ap2; 5166 5167 PetscFunctionBegin; 5168 for (i=0; i<m; i++) { 5169 if (im[i] < 0) continue; 5170 #if defined(PETSC_USE_DEBUG) 5171 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5172 #endif 5173 if (im[i] >= rstart && im[i] < rend) { 5174 row = im[i] - rstart; 5175 lastcol1 = -1; 5176 rp1 = aj + ai[row]; 5177 ap1 = aa + ai[row]; 5178 rmax1 = aimax[row]; 5179 nrow1 = ailen[row]; 5180 low1 = 0; 5181 high1 = nrow1; 5182 lastcol2 = -1; 5183 rp2 = bj + bi[row]; 5184 ap2 = ba + bi[row]; 5185 rmax2 = bimax[row]; 5186 nrow2 = bilen[row]; 5187 low2 = 0; 5188 high2 = nrow2; 5189 5190 for (j=0; j<n; j++) { 5191 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5192 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5193 if (in[j] >= cstart && in[j] < cend){ 5194 col = in[j] - cstart; 5195 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5196 } else if (in[j] < 0) continue; 5197 #if defined(PETSC_USE_DEBUG) 5198 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);} 5199 #endif 5200 else { 5201 if (mat->was_assembled) { 5202 if (!aij->colmap) { 5203 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5204 } 5205 #if defined (PETSC_USE_CTABLE) 5206 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5207 col--; 5208 #else 5209 col = aij->colmap[in[j]] - 1; 5210 #endif 5211 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5212 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5213 col = in[j]; 5214 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5215 B = aij->B; 5216 b = (Mat_SeqAIJ*)B->data; 5217 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5218 rp2 = bj + bi[row]; 5219 ap2 = ba + bi[row]; 5220 rmax2 = bimax[row]; 5221 nrow2 = bilen[row]; 5222 low2 = 0; 5223 high2 = nrow2; 5224 bm = aij->B->rmap->n; 5225 ba = b->a; 5226 } 5227 } else col = in[j]; 5228 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5229 } 5230 } 5231 } else { 5232 if (!aij->donotstash) { 5233 if (roworiented) { 5234 if (ignorezeroentries && v[i*n] == 0.0) continue; 5235 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 5236 } else { 5237 if (ignorezeroentries && v[i] == 0.0) continue; 5238 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 5239 } 5240 } 5241 } 5242 }} 5243 PetscFunctionReturnVoid(); 5244 } 5245 EXTERN_C_END 5246 5247