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 B->rmap->bs = B->cmap->bs = 1; 2699 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 2700 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 2701 if (d_nnz) { 2702 for (i=0; i<B->rmap->n; i++) { 2703 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than 0: local row %D value %D",i,d_nnz[i]); 2704 } 2705 } 2706 if (o_nnz) { 2707 for (i=0; i<B->rmap->n; i++) { 2708 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than 0: local row %D value %D",i,o_nnz[i]); 2709 } 2710 } 2711 b = (Mat_MPIAIJ*)B->data; 2712 2713 /* Explicitly create 2 MATSEQAIJ matrices. */ 2714 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2715 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2716 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2717 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2718 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2719 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2720 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2721 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2722 2723 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2724 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2725 2726 PetscFunctionReturn(0); 2727 } 2728 EXTERN_C_END 2729 2730 #undef __FUNCT__ 2731 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2732 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2733 { 2734 Mat mat; 2735 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2736 PetscErrorCode ierr; 2737 2738 PetscFunctionBegin; 2739 *newmat = 0; 2740 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2741 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2742 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2743 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2744 a = (Mat_MPIAIJ*)mat->data; 2745 2746 mat->factor = matin->factor; 2747 mat->rmap->bs = matin->rmap->bs; 2748 mat->assembled = PETSC_TRUE; 2749 mat->insertmode = NOT_SET_VALUES; 2750 mat->preallocated = PETSC_TRUE; 2751 2752 a->size = oldmat->size; 2753 a->rank = oldmat->rank; 2754 a->donotstash = oldmat->donotstash; 2755 a->roworiented = oldmat->roworiented; 2756 a->rowindices = 0; 2757 a->rowvalues = 0; 2758 a->getrowactive = PETSC_FALSE; 2759 2760 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->rmap,mat->rmap);CHKERRQ(ierr); 2761 ierr = PetscMapCopy(((PetscObject)mat)->comm,matin->cmap,mat->cmap);CHKERRQ(ierr); 2762 2763 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2764 if (oldmat->colmap) { 2765 #if defined (PETSC_USE_CTABLE) 2766 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2767 #else 2768 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2769 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2770 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2771 #endif 2772 } else a->colmap = 0; 2773 if (oldmat->garray) { 2774 PetscInt len; 2775 len = oldmat->B->cmap->n; 2776 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2777 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2778 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2779 } else a->garray = 0; 2780 2781 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2782 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2783 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2784 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2785 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2786 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2787 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2788 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2789 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2790 *newmat = mat; 2791 PetscFunctionReturn(0); 2792 } 2793 2794 #include "petscsys.h" 2795 2796 #undef __FUNCT__ 2797 #define __FUNCT__ "MatLoad_MPIAIJ" 2798 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2799 { 2800 Mat A; 2801 PetscScalar *vals,*svals; 2802 MPI_Comm comm = ((PetscObject)viewer)->comm; 2803 MPI_Status status; 2804 PetscErrorCode ierr; 2805 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,maxnz; 2806 PetscInt i,nz,j,rstart,rend,mmax; 2807 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2808 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2809 PetscInt cend,cstart,n,*rowners; 2810 int fd; 2811 2812 PetscFunctionBegin; 2813 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2814 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2815 if (!rank) { 2816 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2817 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2818 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2819 } 2820 2821 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2822 M = header[1]; N = header[2]; 2823 /* determine ownership of all rows */ 2824 m = M/size + ((M % size) > rank); 2825 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2826 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2827 2828 /* First process needs enough room for process with most rows */ 2829 if (!rank) { 2830 mmax = rowners[1]; 2831 for (i=2; i<size; i++) { 2832 mmax = PetscMax(mmax,rowners[i]); 2833 } 2834 } else mmax = m; 2835 2836 rowners[0] = 0; 2837 for (i=2; i<=size; i++) { 2838 rowners[i] += rowners[i-1]; 2839 } 2840 rstart = rowners[rank]; 2841 rend = rowners[rank+1]; 2842 2843 /* distribute row lengths to all processors */ 2844 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2845 if (!rank) { 2846 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2847 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2848 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2849 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2850 for (j=0; j<m; j++) { 2851 procsnz[0] += ourlens[j]; 2852 } 2853 for (i=1; i<size; i++) { 2854 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2855 /* calculate the number of nonzeros on each processor */ 2856 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2857 procsnz[i] += rowlengths[j]; 2858 } 2859 ierr = MPI_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2860 } 2861 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2862 } else { 2863 ierr = MPI_Recv(ourlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2864 } 2865 2866 if (!rank) { 2867 /* determine max buffer needed and allocate it */ 2868 maxnz = 0; 2869 for (i=0; i<size; i++) { 2870 maxnz = PetscMax(maxnz,procsnz[i]); 2871 } 2872 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2873 2874 /* read in my part of the matrix column indices */ 2875 nz = procsnz[0]; 2876 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2877 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2878 2879 /* read in every one elses and ship off */ 2880 for (i=1; i<size; i++) { 2881 nz = procsnz[i]; 2882 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2883 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2884 } 2885 ierr = PetscFree(cols);CHKERRQ(ierr); 2886 } else { 2887 /* determine buffer space needed for message */ 2888 nz = 0; 2889 for (i=0; i<m; i++) { 2890 nz += ourlens[i]; 2891 } 2892 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2893 2894 /* receive message of column indices*/ 2895 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2896 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 2897 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2898 } 2899 2900 /* determine column ownership if matrix is not square */ 2901 if (N != M) { 2902 n = N/size + ((N % size) > rank); 2903 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2904 cstart = cend - n; 2905 } else { 2906 cstart = rstart; 2907 cend = rend; 2908 n = cend - cstart; 2909 } 2910 2911 /* loop over local rows, determining number of off diagonal entries */ 2912 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2913 jj = 0; 2914 for (i=0; i<m; i++) { 2915 for (j=0; j<ourlens[i]; j++) { 2916 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2917 jj++; 2918 } 2919 } 2920 2921 /* create our matrix */ 2922 for (i=0; i<m; i++) { 2923 ourlens[i] -= offlens[i]; 2924 } 2925 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 2926 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 2927 ierr = MatSetType(A,type);CHKERRQ(ierr); 2928 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 2929 2930 for (i=0; i<m; i++) { 2931 ourlens[i] += offlens[i]; 2932 } 2933 2934 if (!rank) { 2935 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2936 2937 /* read in my part of the matrix numerical values */ 2938 nz = procsnz[0]; 2939 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2940 2941 /* insert into matrix */ 2942 jj = rstart; 2943 smycols = mycols; 2944 svals = vals; 2945 for (i=0; i<m; i++) { 2946 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2947 smycols += ourlens[i]; 2948 svals += ourlens[i]; 2949 jj++; 2950 } 2951 2952 /* read in other processors and ship out */ 2953 for (i=1; i<size; i++) { 2954 nz = procsnz[i]; 2955 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2956 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 2957 } 2958 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2959 } else { 2960 /* receive numeric values */ 2961 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 2962 2963 /* receive message of values*/ 2964 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 2965 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2966 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2967 2968 /* insert into matrix */ 2969 jj = rstart; 2970 smycols = mycols; 2971 svals = vals; 2972 for (i=0; i<m; i++) { 2973 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 2974 smycols += ourlens[i]; 2975 svals += ourlens[i]; 2976 jj++; 2977 } 2978 } 2979 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 2980 ierr = PetscFree(vals);CHKERRQ(ierr); 2981 ierr = PetscFree(mycols);CHKERRQ(ierr); 2982 ierr = PetscFree(rowners);CHKERRQ(ierr); 2983 2984 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2985 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2986 *newmat = A; 2987 PetscFunctionReturn(0); 2988 } 2989 2990 #undef __FUNCT__ 2991 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 2992 /* 2993 Not great since it makes two copies of the submatrix, first an SeqAIJ 2994 in local and then by concatenating the local matrices the end result. 2995 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 2996 */ 2997 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 2998 { 2999 PetscErrorCode ierr; 3000 PetscMPIInt rank,size; 3001 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 3002 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3003 Mat *local,M,Mreuse; 3004 MatScalar *vwork,*aa; 3005 MPI_Comm comm = ((PetscObject)mat)->comm; 3006 Mat_SeqAIJ *aij; 3007 3008 3009 PetscFunctionBegin; 3010 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3011 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3012 3013 if (call == MAT_REUSE_MATRIX) { 3014 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 3015 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3016 local = &Mreuse; 3017 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 3018 } else { 3019 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 3020 Mreuse = *local; 3021 ierr = PetscFree(local);CHKERRQ(ierr); 3022 } 3023 3024 /* 3025 m - number of local rows 3026 n - number of columns (same on all processors) 3027 rstart - first row in new global matrix generated 3028 */ 3029 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3030 if (call == MAT_INITIAL_MATRIX) { 3031 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3032 ii = aij->i; 3033 jj = aij->j; 3034 3035 /* 3036 Determine the number of non-zeros in the diagonal and off-diagonal 3037 portions of the matrix in order to do correct preallocation 3038 */ 3039 3040 /* first get start and end of "diagonal" columns */ 3041 if (csize == PETSC_DECIDE) { 3042 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3043 if (mglobal == n) { /* square matrix */ 3044 nlocal = m; 3045 } else { 3046 nlocal = n/size + ((n % size) > rank); 3047 } 3048 } else { 3049 nlocal = csize; 3050 } 3051 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3052 rstart = rend - nlocal; 3053 if (rank == size - 1 && rend != n) { 3054 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3055 } 3056 3057 /* next, compute all the lengths */ 3058 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3059 olens = dlens + m; 3060 for (i=0; i<m; i++) { 3061 jend = ii[i+1] - ii[i]; 3062 olen = 0; 3063 dlen = 0; 3064 for (j=0; j<jend; j++) { 3065 if (*jj < rstart || *jj >= rend) olen++; 3066 else dlen++; 3067 jj++; 3068 } 3069 olens[i] = olen; 3070 dlens[i] = dlen; 3071 } 3072 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3073 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3074 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3075 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3076 ierr = PetscFree(dlens);CHKERRQ(ierr); 3077 } else { 3078 PetscInt ml,nl; 3079 3080 M = *newmat; 3081 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3082 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3083 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3084 /* 3085 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3086 rather than the slower MatSetValues(). 3087 */ 3088 M->was_assembled = PETSC_TRUE; 3089 M->assembled = PETSC_FALSE; 3090 } 3091 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3092 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3093 ii = aij->i; 3094 jj = aij->j; 3095 aa = aij->a; 3096 for (i=0; i<m; i++) { 3097 row = rstart + i; 3098 nz = ii[i+1] - ii[i]; 3099 cwork = jj; jj += nz; 3100 vwork = aa; aa += nz; 3101 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3102 } 3103 3104 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3105 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3106 *newmat = M; 3107 3108 /* save submatrix used in processor for next request */ 3109 if (call == MAT_INITIAL_MATRIX) { 3110 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3111 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 3112 } 3113 3114 PetscFunctionReturn(0); 3115 } 3116 3117 EXTERN_C_BEGIN 3118 #undef __FUNCT__ 3119 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3120 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3121 { 3122 PetscInt m,cstart, cend,j,nnz,i,d; 3123 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3124 const PetscInt *JJ; 3125 PetscScalar *values; 3126 PetscErrorCode ierr; 3127 3128 PetscFunctionBegin; 3129 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3130 3131 B->rmap->bs = B->cmap->bs = 1; 3132 ierr = PetscMapSetUp(B->rmap);CHKERRQ(ierr); 3133 ierr = PetscMapSetUp(B->cmap);CHKERRQ(ierr); 3134 m = B->rmap->n; 3135 cstart = B->cmap->rstart; 3136 cend = B->cmap->rend; 3137 rstart = B->rmap->rstart; 3138 3139 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 3140 o_nnz = d_nnz + m; 3141 3142 #if defined(PETSC_USE_DEBUGGING) 3143 for (i=0; i<m; i++) { 3144 nnz = Ii[i+1]- Ii[i]; 3145 JJ = J + Ii[i]; 3146 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3147 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3148 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); 3149 for (j=1; j<nnz; j++) { 3150 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); 3151 } 3152 } 3153 #endif 3154 3155 for (i=0; i<m; i++) { 3156 nnz = Ii[i+1]- Ii[i]; 3157 JJ = J + Ii[i]; 3158 nnz_max = PetscMax(nnz_max,nnz); 3159 for (j=0; j<nnz; j++) { 3160 if (*JJ >= cstart) break; 3161 JJ++; 3162 } 3163 d = 0; 3164 for (; j<nnz; j++) { 3165 if (*JJ++ >= cend) break; 3166 d++; 3167 } 3168 d_nnz[i] = d; 3169 o_nnz[i] = nnz - d; 3170 } 3171 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3172 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 3173 3174 if (v) values = (PetscScalar*)v; 3175 else { 3176 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3177 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3178 } 3179 3180 for (i=0; i<m; i++) { 3181 ii = i + rstart; 3182 nnz = Ii[i+1]- Ii[i]; 3183 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3184 } 3185 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3186 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3187 3188 if (!v) { 3189 ierr = PetscFree(values);CHKERRQ(ierr); 3190 } 3191 PetscFunctionReturn(0); 3192 } 3193 EXTERN_C_END 3194 3195 #undef __FUNCT__ 3196 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3197 /*@ 3198 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3199 (the default parallel PETSc format). 3200 3201 Collective on MPI_Comm 3202 3203 Input Parameters: 3204 + B - the matrix 3205 . i - the indices into j for the start of each local row (starts with zero) 3206 . j - the column indices for each local row (starts with zero) these must be sorted for each row 3207 - v - optional values in the matrix 3208 3209 Level: developer 3210 3211 Notes: 3212 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3213 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3214 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3215 3216 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3217 3218 The format which is used for the sparse matrix input, is equivalent to a 3219 row-major ordering.. i.e for the following matrix, the input data expected is 3220 as shown: 3221 3222 1 0 0 3223 2 0 3 P0 3224 ------- 3225 4 5 6 P1 3226 3227 Process0 [P0]: rows_owned=[0,1] 3228 i = {0,1,3} [size = nrow+1 = 2+1] 3229 j = {0,0,2} [size = nz = 6] 3230 v = {1,2,3} [size = nz = 6] 3231 3232 Process1 [P1]: rows_owned=[2] 3233 i = {0,3} [size = nrow+1 = 1+1] 3234 j = {0,1,2} [size = nz = 6] 3235 v = {4,5,6} [size = nz = 6] 3236 3237 The column indices for each row MUST be sorted. 3238 3239 .keywords: matrix, aij, compressed row, sparse, parallel 3240 3241 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 3242 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3243 @*/ 3244 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3245 { 3246 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3247 3248 PetscFunctionBegin; 3249 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3250 if (f) { 3251 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3252 } 3253 PetscFunctionReturn(0); 3254 } 3255 3256 #undef __FUNCT__ 3257 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3258 /*@C 3259 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3260 (the default parallel PETSc format). For good matrix assembly performance 3261 the user should preallocate the matrix storage by setting the parameters 3262 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3263 performance can be increased by more than a factor of 50. 3264 3265 Collective on MPI_Comm 3266 3267 Input Parameters: 3268 + A - the matrix 3269 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3270 (same value is used for all local rows) 3271 . d_nnz - array containing the number of nonzeros in the various rows of the 3272 DIAGONAL portion of the local submatrix (possibly different for each row) 3273 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3274 The size of this array is equal to the number of local rows, i.e 'm'. 3275 You must leave room for the diagonal entry even if it is zero. 3276 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3277 submatrix (same value is used for all local rows). 3278 - o_nnz - array containing the number of nonzeros in the various rows of the 3279 OFF-DIAGONAL portion of the local submatrix (possibly different for 3280 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3281 structure. The size of this array is equal to the number 3282 of local rows, i.e 'm'. 3283 3284 If the *_nnz parameter is given then the *_nz parameter is ignored 3285 3286 The AIJ format (also called the Yale sparse matrix format or 3287 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3288 storage. The stored row and column indices begin with zero. See the users manual for details. 3289 3290 The parallel matrix is partitioned such that the first m0 rows belong to 3291 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3292 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3293 3294 The DIAGONAL portion of the local submatrix of a processor can be defined 3295 as the submatrix which is obtained by extraction the part corresponding 3296 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 3297 first row that belongs to the processor, and r2 is the last row belonging 3298 to the this processor. This is a square mxm matrix. The remaining portion 3299 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 3300 3301 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3302 3303 You can call MatGetInfo() to get information on how effective the preallocation was; 3304 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3305 You can also run with the option -info and look for messages with the string 3306 malloc in them to see if additional memory allocation was needed. 3307 3308 Example usage: 3309 3310 Consider the following 8x8 matrix with 34 non-zero values, that is 3311 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3312 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3313 as follows: 3314 3315 .vb 3316 1 2 0 | 0 3 0 | 0 4 3317 Proc0 0 5 6 | 7 0 0 | 8 0 3318 9 0 10 | 11 0 0 | 12 0 3319 ------------------------------------- 3320 13 0 14 | 15 16 17 | 0 0 3321 Proc1 0 18 0 | 19 20 21 | 0 0 3322 0 0 0 | 22 23 0 | 24 0 3323 ------------------------------------- 3324 Proc2 25 26 27 | 0 0 28 | 29 0 3325 30 0 0 | 31 32 33 | 0 34 3326 .ve 3327 3328 This can be represented as a collection of submatrices as: 3329 3330 .vb 3331 A B C 3332 D E F 3333 G H I 3334 .ve 3335 3336 Where the submatrices A,B,C are owned by proc0, D,E,F are 3337 owned by proc1, G,H,I are owned by proc2. 3338 3339 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3340 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3341 The 'M','N' parameters are 8,8, and have the same values on all procs. 3342 3343 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3344 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3345 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3346 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3347 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3348 matrix, ans [DF] as another SeqAIJ matrix. 3349 3350 When d_nz, o_nz parameters are specified, d_nz storage elements are 3351 allocated for every row of the local diagonal submatrix, and o_nz 3352 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3353 One way to choose d_nz and o_nz is to use the max nonzerors per local 3354 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3355 In this case, the values of d_nz,o_nz are: 3356 .vb 3357 proc0 : dnz = 2, o_nz = 2 3358 proc1 : dnz = 3, o_nz = 2 3359 proc2 : dnz = 1, o_nz = 4 3360 .ve 3361 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3362 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3363 for proc3. i.e we are using 12+15+10=37 storage locations to store 3364 34 values. 3365 3366 When d_nnz, o_nnz parameters are specified, the storage is specified 3367 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3368 In the above case the values for d_nnz,o_nnz are: 3369 .vb 3370 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3371 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3372 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3373 .ve 3374 Here the space allocated is sum of all the above values i.e 34, and 3375 hence pre-allocation is perfect. 3376 3377 Level: intermediate 3378 3379 .keywords: matrix, aij, compressed row, sparse, parallel 3380 3381 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3382 MPIAIJ, MatGetInfo() 3383 @*/ 3384 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3385 { 3386 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3387 3388 PetscFunctionBegin; 3389 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3390 if (f) { 3391 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3392 } 3393 PetscFunctionReturn(0); 3394 } 3395 3396 #undef __FUNCT__ 3397 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3398 /*@ 3399 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3400 CSR format the local rows. 3401 3402 Collective on MPI_Comm 3403 3404 Input Parameters: 3405 + comm - MPI communicator 3406 . m - number of local rows (Cannot be PETSC_DECIDE) 3407 . n - This value should be the same as the local size used in creating the 3408 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3409 calculated if N is given) For square matrices n is almost always m. 3410 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3411 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3412 . i - row indices 3413 . j - column indices 3414 - a - matrix values 3415 3416 Output Parameter: 3417 . mat - the matrix 3418 3419 Level: intermediate 3420 3421 Notes: 3422 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3423 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3424 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3425 3426 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3427 3428 The format which is used for the sparse matrix input, is equivalent to a 3429 row-major ordering.. i.e for the following matrix, the input data expected is 3430 as shown: 3431 3432 1 0 0 3433 2 0 3 P0 3434 ------- 3435 4 5 6 P1 3436 3437 Process0 [P0]: rows_owned=[0,1] 3438 i = {0,1,3} [size = nrow+1 = 2+1] 3439 j = {0,0,2} [size = nz = 6] 3440 v = {1,2,3} [size = nz = 6] 3441 3442 Process1 [P1]: rows_owned=[2] 3443 i = {0,3} [size = nrow+1 = 1+1] 3444 j = {0,1,2} [size = nz = 6] 3445 v = {4,5,6} [size = nz = 6] 3446 3447 .keywords: matrix, aij, compressed row, sparse, parallel 3448 3449 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3450 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3451 @*/ 3452 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) 3453 { 3454 PetscErrorCode ierr; 3455 3456 PetscFunctionBegin; 3457 if (i[0]) { 3458 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3459 } 3460 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3461 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3462 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3463 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3464 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3465 PetscFunctionReturn(0); 3466 } 3467 3468 #undef __FUNCT__ 3469 #define __FUNCT__ "MatCreateMPIAIJ" 3470 /*@C 3471 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3472 (the default parallel PETSc format). For good matrix assembly performance 3473 the user should preallocate the matrix storage by setting the parameters 3474 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3475 performance can be increased by more than a factor of 50. 3476 3477 Collective on MPI_Comm 3478 3479 Input Parameters: 3480 + comm - MPI communicator 3481 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3482 This value should be the same as the local size used in creating the 3483 y vector for the matrix-vector product y = Ax. 3484 . n - This value should be the same as the local size used in creating the 3485 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3486 calculated if N is given) For square matrices n is almost always m. 3487 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3488 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3489 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3490 (same value is used for all local rows) 3491 . d_nnz - array containing the number of nonzeros in the various rows of the 3492 DIAGONAL portion of the local submatrix (possibly different for each row) 3493 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3494 The size of this array is equal to the number of local rows, i.e 'm'. 3495 You must leave room for the diagonal entry even if it is zero. 3496 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3497 submatrix (same value is used for all local rows). 3498 - o_nnz - array containing the number of nonzeros in the various rows of the 3499 OFF-DIAGONAL portion of the local submatrix (possibly different for 3500 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3501 structure. The size of this array is equal to the number 3502 of local rows, i.e 'm'. 3503 3504 Output Parameter: 3505 . A - the matrix 3506 3507 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3508 MatXXXXSetPreallocation() paradgm instead of this routine directly. This is definitely 3509 true if you plan to use the external direct solvers such as SuperLU, MUMPS or Spooles. 3510 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3511 3512 Notes: 3513 If the *_nnz parameter is given then the *_nz parameter is ignored 3514 3515 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3516 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3517 storage requirements for this matrix. 3518 3519 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3520 processor than it must be used on all processors that share the object for 3521 that argument. 3522 3523 The user MUST specify either the local or global matrix dimensions 3524 (possibly both). 3525 3526 The parallel matrix is partitioned across processors such that the 3527 first m0 rows belong to process 0, the next m1 rows belong to 3528 process 1, the next m2 rows belong to process 2 etc.. where 3529 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3530 values corresponding to [m x N] submatrix. 3531 3532 The columns are logically partitioned with the n0 columns belonging 3533 to 0th partition, the next n1 columns belonging to the next 3534 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3535 3536 The DIAGONAL portion of the local submatrix on any given processor 3537 is the submatrix corresponding to the rows and columns m,n 3538 corresponding to the given processor. i.e diagonal matrix on 3539 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3540 etc. The remaining portion of the local submatrix [m x (N-n)] 3541 constitute the OFF-DIAGONAL portion. The example below better 3542 illustrates this concept. 3543 3544 For a square global matrix we define each processor's diagonal portion 3545 to be its local rows and the corresponding columns (a square submatrix); 3546 each processor's off-diagonal portion encompasses the remainder of the 3547 local matrix (a rectangular submatrix). 3548 3549 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3550 3551 When calling this routine with a single process communicator, a matrix of 3552 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3553 type of communicator, use the construction mechanism: 3554 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 3555 3556 By default, this format uses inodes (identical nodes) when possible. 3557 We search for consecutive rows with the same nonzero structure, thereby 3558 reusing matrix information to achieve increased efficiency. 3559 3560 Options Database Keys: 3561 + -mat_no_inode - Do not use inodes 3562 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3563 - -mat_aij_oneindex - Internally use indexing starting at 1 3564 rather than 0. Note that when calling MatSetValues(), 3565 the user still MUST index entries starting at 0! 3566 3567 3568 Example usage: 3569 3570 Consider the following 8x8 matrix with 34 non-zero values, that is 3571 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3572 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3573 as follows: 3574 3575 .vb 3576 1 2 0 | 0 3 0 | 0 4 3577 Proc0 0 5 6 | 7 0 0 | 8 0 3578 9 0 10 | 11 0 0 | 12 0 3579 ------------------------------------- 3580 13 0 14 | 15 16 17 | 0 0 3581 Proc1 0 18 0 | 19 20 21 | 0 0 3582 0 0 0 | 22 23 0 | 24 0 3583 ------------------------------------- 3584 Proc2 25 26 27 | 0 0 28 | 29 0 3585 30 0 0 | 31 32 33 | 0 34 3586 .ve 3587 3588 This can be represented as a collection of submatrices as: 3589 3590 .vb 3591 A B C 3592 D E F 3593 G H I 3594 .ve 3595 3596 Where the submatrices A,B,C are owned by proc0, D,E,F are 3597 owned by proc1, G,H,I are owned by proc2. 3598 3599 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3600 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3601 The 'M','N' parameters are 8,8, and have the same values on all procs. 3602 3603 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3604 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3605 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3606 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3607 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3608 matrix, ans [DF] as another SeqAIJ matrix. 3609 3610 When d_nz, o_nz parameters are specified, d_nz storage elements are 3611 allocated for every row of the local diagonal submatrix, and o_nz 3612 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3613 One way to choose d_nz and o_nz is to use the max nonzerors per local 3614 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3615 In this case, the values of d_nz,o_nz are: 3616 .vb 3617 proc0 : dnz = 2, o_nz = 2 3618 proc1 : dnz = 3, o_nz = 2 3619 proc2 : dnz = 1, o_nz = 4 3620 .ve 3621 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3622 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3623 for proc3. i.e we are using 12+15+10=37 storage locations to store 3624 34 values. 3625 3626 When d_nnz, o_nnz parameters are specified, the storage is specified 3627 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3628 In the above case the values for d_nnz,o_nnz are: 3629 .vb 3630 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3631 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3632 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3633 .ve 3634 Here the space allocated is sum of all the above values i.e 34, and 3635 hence pre-allocation is perfect. 3636 3637 Level: intermediate 3638 3639 .keywords: matrix, aij, compressed row, sparse, parallel 3640 3641 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3642 MPIAIJ, MatCreateMPIAIJWithArrays() 3643 @*/ 3644 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) 3645 { 3646 PetscErrorCode ierr; 3647 PetscMPIInt size; 3648 3649 PetscFunctionBegin; 3650 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3651 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3652 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3653 if (size > 1) { 3654 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3655 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3656 } else { 3657 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3658 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3659 } 3660 PetscFunctionReturn(0); 3661 } 3662 3663 #undef __FUNCT__ 3664 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3665 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3666 { 3667 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3668 3669 PetscFunctionBegin; 3670 *Ad = a->A; 3671 *Ao = a->B; 3672 *colmap = a->garray; 3673 PetscFunctionReturn(0); 3674 } 3675 3676 #undef __FUNCT__ 3677 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3678 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3679 { 3680 PetscErrorCode ierr; 3681 PetscInt i; 3682 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3683 3684 PetscFunctionBegin; 3685 if (coloring->ctype == IS_COLORING_GLOBAL) { 3686 ISColoringValue *allcolors,*colors; 3687 ISColoring ocoloring; 3688 3689 /* set coloring for diagonal portion */ 3690 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3691 3692 /* set coloring for off-diagonal portion */ 3693 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3694 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3695 for (i=0; i<a->B->cmap->n; i++) { 3696 colors[i] = allcolors[a->garray[i]]; 3697 } 3698 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3699 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3700 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3701 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3702 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3703 ISColoringValue *colors; 3704 PetscInt *larray; 3705 ISColoring ocoloring; 3706 3707 /* set coloring for diagonal portion */ 3708 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3709 for (i=0; i<a->A->cmap->n; i++) { 3710 larray[i] = i + A->cmap->rstart; 3711 } 3712 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3713 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3714 for (i=0; i<a->A->cmap->n; i++) { 3715 colors[i] = coloring->colors[larray[i]]; 3716 } 3717 ierr = PetscFree(larray);CHKERRQ(ierr); 3718 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3719 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3720 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3721 3722 /* set coloring for off-diagonal portion */ 3723 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3724 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3725 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3726 for (i=0; i<a->B->cmap->n; i++) { 3727 colors[i] = coloring->colors[larray[i]]; 3728 } 3729 ierr = PetscFree(larray);CHKERRQ(ierr); 3730 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3731 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3732 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3733 } else { 3734 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3735 } 3736 3737 PetscFunctionReturn(0); 3738 } 3739 3740 #if defined(PETSC_HAVE_ADIC) 3741 #undef __FUNCT__ 3742 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3743 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3744 { 3745 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3746 PetscErrorCode ierr; 3747 3748 PetscFunctionBegin; 3749 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3750 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3751 PetscFunctionReturn(0); 3752 } 3753 #endif 3754 3755 #undef __FUNCT__ 3756 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3757 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3758 { 3759 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3760 PetscErrorCode ierr; 3761 3762 PetscFunctionBegin; 3763 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3764 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3765 PetscFunctionReturn(0); 3766 } 3767 3768 #undef __FUNCT__ 3769 #define __FUNCT__ "MatMerge" 3770 /*@ 3771 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3772 matrices from each processor 3773 3774 Collective on MPI_Comm 3775 3776 Input Parameters: 3777 + comm - the communicators the parallel matrix will live on 3778 . inmat - the input sequential matrices 3779 . n - number of local columns (or PETSC_DECIDE) 3780 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3781 3782 Output Parameter: 3783 . outmat - the parallel matrix generated 3784 3785 Level: advanced 3786 3787 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3788 3789 @*/ 3790 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3791 { 3792 PetscErrorCode ierr; 3793 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3794 PetscInt *indx; 3795 PetscScalar *values; 3796 3797 PetscFunctionBegin; 3798 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3799 if (scall == MAT_INITIAL_MATRIX){ 3800 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3801 if (n == PETSC_DECIDE){ 3802 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3803 } 3804 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3805 rstart -= m; 3806 3807 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3808 for (i=0;i<m;i++) { 3809 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3810 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3811 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3812 } 3813 /* This routine will ONLY return MPIAIJ type matrix */ 3814 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3815 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3816 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3817 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3818 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3819 3820 } else if (scall == MAT_REUSE_MATRIX){ 3821 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3822 } else { 3823 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3824 } 3825 3826 for (i=0;i<m;i++) { 3827 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3828 Ii = i + rstart; 3829 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3830 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3831 } 3832 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3833 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3834 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3835 3836 PetscFunctionReturn(0); 3837 } 3838 3839 #undef __FUNCT__ 3840 #define __FUNCT__ "MatFileSplit" 3841 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3842 { 3843 PetscErrorCode ierr; 3844 PetscMPIInt rank; 3845 PetscInt m,N,i,rstart,nnz; 3846 size_t len; 3847 const PetscInt *indx; 3848 PetscViewer out; 3849 char *name; 3850 Mat B; 3851 const PetscScalar *values; 3852 3853 PetscFunctionBegin; 3854 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3855 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3856 /* Should this be the type of the diagonal block of A? */ 3857 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3858 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3859 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3860 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3861 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3862 for (i=0;i<m;i++) { 3863 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3864 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3865 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3866 } 3867 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3868 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3869 3870 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3871 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3872 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3873 sprintf(name,"%s.%d",outfile,rank); 3874 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3875 ierr = PetscFree(name); 3876 ierr = MatView(B,out);CHKERRQ(ierr); 3877 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3878 ierr = MatDestroy(B);CHKERRQ(ierr); 3879 PetscFunctionReturn(0); 3880 } 3881 3882 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3883 #undef __FUNCT__ 3884 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3885 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3886 { 3887 PetscErrorCode ierr; 3888 Mat_Merge_SeqsToMPI *merge; 3889 PetscContainer container; 3890 3891 PetscFunctionBegin; 3892 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3893 if (container) { 3894 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3895 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3896 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3897 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3898 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3899 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3900 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3901 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3902 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3903 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 3904 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 3905 ierr = PetscFree(merge->rowmap.range);CHKERRQ(ierr); 3906 3907 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 3908 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 3909 } 3910 ierr = PetscFree(merge);CHKERRQ(ierr); 3911 3912 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 3913 PetscFunctionReturn(0); 3914 } 3915 3916 #include "../src/mat/utils/freespace.h" 3917 #include "petscbt.h" 3918 3919 #undef __FUNCT__ 3920 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 3921 /*@C 3922 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 3923 matrices from each processor 3924 3925 Collective on MPI_Comm 3926 3927 Input Parameters: 3928 + comm - the communicators the parallel matrix will live on 3929 . seqmat - the input sequential matrices 3930 . m - number of local rows (or PETSC_DECIDE) 3931 . n - number of local columns (or PETSC_DECIDE) 3932 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3933 3934 Output Parameter: 3935 . mpimat - the parallel matrix generated 3936 3937 Level: advanced 3938 3939 Notes: 3940 The dimensions of the sequential matrix in each processor MUST be the same. 3941 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 3942 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 3943 @*/ 3944 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 3945 { 3946 PetscErrorCode ierr; 3947 MPI_Comm comm=((PetscObject)mpimat)->comm; 3948 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 3949 PetscMPIInt size,rank,taga,*len_s; 3950 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j; 3951 PetscInt proc,m; 3952 PetscInt **buf_ri,**buf_rj; 3953 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 3954 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 3955 MPI_Request *s_waits,*r_waits; 3956 MPI_Status *status; 3957 MatScalar *aa=a->a; 3958 MatScalar **abuf_r,*ba_i; 3959 Mat_Merge_SeqsToMPI *merge; 3960 PetscContainer container; 3961 3962 PetscFunctionBegin; 3963 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 3964 3965 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3966 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3967 3968 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3969 if (container) { 3970 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3971 } 3972 bi = merge->bi; 3973 bj = merge->bj; 3974 buf_ri = merge->buf_ri; 3975 buf_rj = merge->buf_rj; 3976 3977 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 3978 owners = merge->rowmap.range; 3979 len_s = merge->len_s; 3980 3981 /* send and recv matrix values */ 3982 /*-----------------------------*/ 3983 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 3984 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 3985 3986 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 3987 for (proc=0,k=0; proc<size; proc++){ 3988 if (!len_s[proc]) continue; 3989 i = owners[proc]; 3990 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 3991 k++; 3992 } 3993 3994 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 3995 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 3996 ierr = PetscFree(status);CHKERRQ(ierr); 3997 3998 ierr = PetscFree(s_waits);CHKERRQ(ierr); 3999 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4000 4001 /* insert mat values of mpimat */ 4002 /*----------------------------*/ 4003 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4004 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4005 nextrow = buf_ri_k + merge->nrecv; 4006 nextai = nextrow + merge->nrecv; 4007 4008 for (k=0; k<merge->nrecv; k++){ 4009 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4010 nrows = *(buf_ri_k[k]); 4011 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4012 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4013 } 4014 4015 /* set values of ba */ 4016 m = merge->rowmap.n; 4017 for (i=0; i<m; i++) { 4018 arow = owners[rank] + i; 4019 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4020 bnzi = bi[i+1] - bi[i]; 4021 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4022 4023 /* add local non-zero vals of this proc's seqmat into ba */ 4024 anzi = ai[arow+1] - ai[arow]; 4025 aj = a->j + ai[arow]; 4026 aa = a->a + ai[arow]; 4027 nextaj = 0; 4028 for (j=0; nextaj<anzi; j++){ 4029 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4030 ba_i[j] += aa[nextaj++]; 4031 } 4032 } 4033 4034 /* add received vals into ba */ 4035 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4036 /* i-th row */ 4037 if (i == *nextrow[k]) { 4038 anzi = *(nextai[k]+1) - *nextai[k]; 4039 aj = buf_rj[k] + *(nextai[k]); 4040 aa = abuf_r[k] + *(nextai[k]); 4041 nextaj = 0; 4042 for (j=0; nextaj<anzi; j++){ 4043 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4044 ba_i[j] += aa[nextaj++]; 4045 } 4046 } 4047 nextrow[k]++; nextai[k]++; 4048 } 4049 } 4050 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4051 } 4052 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4053 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4054 4055 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4056 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4057 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4058 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4059 PetscFunctionReturn(0); 4060 } 4061 4062 #undef __FUNCT__ 4063 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 4064 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4065 { 4066 PetscErrorCode ierr; 4067 Mat B_mpi; 4068 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4069 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4070 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4071 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4072 PetscInt len,proc,*dnz,*onz; 4073 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4074 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4075 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4076 MPI_Status *status; 4077 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 4078 PetscBT lnkbt; 4079 Mat_Merge_SeqsToMPI *merge; 4080 PetscContainer container; 4081 4082 PetscFunctionBegin; 4083 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4084 4085 /* make sure it is a PETSc comm */ 4086 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4087 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4088 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4089 4090 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4091 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4092 4093 /* determine row ownership */ 4094 /*---------------------------------------------------------*/ 4095 ierr = PetscMapInitialize(comm,&merge->rowmap);CHKERRQ(ierr); 4096 merge->rowmap.n = m; 4097 merge->rowmap.N = M; 4098 merge->rowmap.bs = 1; 4099 ierr = PetscMapSetUp(&merge->rowmap);CHKERRQ(ierr); 4100 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4101 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4102 4103 m = merge->rowmap.n; 4104 M = merge->rowmap.N; 4105 owners = merge->rowmap.range; 4106 4107 /* determine the number of messages to send, their lengths */ 4108 /*---------------------------------------------------------*/ 4109 len_s = merge->len_s; 4110 4111 len = 0; /* length of buf_si[] */ 4112 merge->nsend = 0; 4113 for (proc=0; proc<size; proc++){ 4114 len_si[proc] = 0; 4115 if (proc == rank){ 4116 len_s[proc] = 0; 4117 } else { 4118 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4119 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4120 } 4121 if (len_s[proc]) { 4122 merge->nsend++; 4123 nrows = 0; 4124 for (i=owners[proc]; i<owners[proc+1]; i++){ 4125 if (ai[i+1] > ai[i]) nrows++; 4126 } 4127 len_si[proc] = 2*(nrows+1); 4128 len += len_si[proc]; 4129 } 4130 } 4131 4132 /* determine the number and length of messages to receive for ij-structure */ 4133 /*-------------------------------------------------------------------------*/ 4134 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4135 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4136 4137 /* post the Irecv of j-structure */ 4138 /*-------------------------------*/ 4139 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4140 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4141 4142 /* post the Isend of j-structure */ 4143 /*--------------------------------*/ 4144 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 4145 sj_waits = si_waits + merge->nsend; 4146 4147 for (proc=0, k=0; proc<size; proc++){ 4148 if (!len_s[proc]) continue; 4149 i = owners[proc]; 4150 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4151 k++; 4152 } 4153 4154 /* receives and sends of j-structure are complete */ 4155 /*------------------------------------------------*/ 4156 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4157 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4158 4159 /* send and recv i-structure */ 4160 /*---------------------------*/ 4161 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4162 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4163 4164 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4165 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4166 for (proc=0,k=0; proc<size; proc++){ 4167 if (!len_s[proc]) continue; 4168 /* form outgoing message for i-structure: 4169 buf_si[0]: nrows to be sent 4170 [1:nrows]: row index (global) 4171 [nrows+1:2*nrows+1]: i-structure index 4172 */ 4173 /*-------------------------------------------*/ 4174 nrows = len_si[proc]/2 - 1; 4175 buf_si_i = buf_si + nrows+1; 4176 buf_si[0] = nrows; 4177 buf_si_i[0] = 0; 4178 nrows = 0; 4179 for (i=owners[proc]; i<owners[proc+1]; i++){ 4180 anzi = ai[i+1] - ai[i]; 4181 if (anzi) { 4182 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4183 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4184 nrows++; 4185 } 4186 } 4187 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4188 k++; 4189 buf_si += len_si[proc]; 4190 } 4191 4192 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4193 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4194 4195 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4196 for (i=0; i<merge->nrecv; i++){ 4197 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); 4198 } 4199 4200 ierr = PetscFree(len_si);CHKERRQ(ierr); 4201 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4202 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4203 ierr = PetscFree(si_waits);CHKERRQ(ierr); 4204 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4205 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4206 ierr = PetscFree(status);CHKERRQ(ierr); 4207 4208 /* compute a local seq matrix in each processor */ 4209 /*----------------------------------------------*/ 4210 /* allocate bi array and free space for accumulating nonzero column info */ 4211 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4212 bi[0] = 0; 4213 4214 /* create and initialize a linked list */ 4215 nlnk = N+1; 4216 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4217 4218 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4219 len = 0; 4220 len = ai[owners[rank+1]] - ai[owners[rank]]; 4221 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4222 current_space = free_space; 4223 4224 /* determine symbolic info for each local row */ 4225 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4226 nextrow = buf_ri_k + merge->nrecv; 4227 nextai = nextrow + merge->nrecv; 4228 for (k=0; k<merge->nrecv; k++){ 4229 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4230 nrows = *buf_ri_k[k]; 4231 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4232 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4233 } 4234 4235 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4236 len = 0; 4237 for (i=0;i<m;i++) { 4238 bnzi = 0; 4239 /* add local non-zero cols of this proc's seqmat into lnk */ 4240 arow = owners[rank] + i; 4241 anzi = ai[arow+1] - ai[arow]; 4242 aj = a->j + ai[arow]; 4243 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4244 bnzi += nlnk; 4245 /* add received col data into lnk */ 4246 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4247 if (i == *nextrow[k]) { /* i-th row */ 4248 anzi = *(nextai[k]+1) - *nextai[k]; 4249 aj = buf_rj[k] + *nextai[k]; 4250 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4251 bnzi += nlnk; 4252 nextrow[k]++; nextai[k]++; 4253 } 4254 } 4255 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4256 4257 /* if free space is not available, make more free space */ 4258 if (current_space->local_remaining<bnzi) { 4259 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4260 nspacedouble++; 4261 } 4262 /* copy data into free space, then initialize lnk */ 4263 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4264 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4265 4266 current_space->array += bnzi; 4267 current_space->local_used += bnzi; 4268 current_space->local_remaining -= bnzi; 4269 4270 bi[i+1] = bi[i] + bnzi; 4271 } 4272 4273 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4274 4275 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4276 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4277 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4278 4279 /* create symbolic parallel matrix B_mpi */ 4280 /*---------------------------------------*/ 4281 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4282 if (n==PETSC_DECIDE) { 4283 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4284 } else { 4285 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4286 } 4287 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4288 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4289 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4290 4291 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 4292 B_mpi->assembled = PETSC_FALSE; 4293 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4294 merge->bi = bi; 4295 merge->bj = bj; 4296 merge->buf_ri = buf_ri; 4297 merge->buf_rj = buf_rj; 4298 merge->coi = PETSC_NULL; 4299 merge->coj = PETSC_NULL; 4300 merge->owners_co = PETSC_NULL; 4301 4302 /* attach the supporting struct to B_mpi for reuse */ 4303 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4304 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4305 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4306 *mpimat = B_mpi; 4307 4308 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4309 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4310 PetscFunctionReturn(0); 4311 } 4312 4313 #undef __FUNCT__ 4314 #define __FUNCT__ "MatMerge_SeqsToMPI" 4315 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4316 { 4317 PetscErrorCode ierr; 4318 4319 PetscFunctionBegin; 4320 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4321 if (scall == MAT_INITIAL_MATRIX){ 4322 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4323 } 4324 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4325 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4326 PetscFunctionReturn(0); 4327 } 4328 4329 #undef __FUNCT__ 4330 #define __FUNCT__ "MatGetLocalMat" 4331 /*@ 4332 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4333 4334 Not Collective 4335 4336 Input Parameters: 4337 + A - the matrix 4338 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4339 4340 Output Parameter: 4341 . A_loc - the local sequential matrix generated 4342 4343 Level: developer 4344 4345 @*/ 4346 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4347 { 4348 PetscErrorCode ierr; 4349 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4350 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4351 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4352 MatScalar *aa=a->a,*ba=b->a,*cam; 4353 PetscScalar *ca; 4354 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4355 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4356 4357 PetscFunctionBegin; 4358 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4359 if (scall == MAT_INITIAL_MATRIX){ 4360 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4361 ci[0] = 0; 4362 for (i=0; i<am; i++){ 4363 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4364 } 4365 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4366 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4367 k = 0; 4368 for (i=0; i<am; i++) { 4369 ncols_o = bi[i+1] - bi[i]; 4370 ncols_d = ai[i+1] - ai[i]; 4371 /* off-diagonal portion of A */ 4372 for (jo=0; jo<ncols_o; jo++) { 4373 col = cmap[*bj]; 4374 if (col >= cstart) break; 4375 cj[k] = col; bj++; 4376 ca[k++] = *ba++; 4377 } 4378 /* diagonal portion of A */ 4379 for (j=0; j<ncols_d; j++) { 4380 cj[k] = cstart + *aj++; 4381 ca[k++] = *aa++; 4382 } 4383 /* off-diagonal portion of A */ 4384 for (j=jo; j<ncols_o; j++) { 4385 cj[k] = cmap[*bj++]; 4386 ca[k++] = *ba++; 4387 } 4388 } 4389 /* put together the new matrix */ 4390 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4391 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4392 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4393 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4394 mat->free_a = PETSC_TRUE; 4395 mat->free_ij = PETSC_TRUE; 4396 mat->nonew = 0; 4397 } else if (scall == MAT_REUSE_MATRIX){ 4398 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4399 ci = mat->i; cj = mat->j; cam = mat->a; 4400 for (i=0; i<am; i++) { 4401 /* off-diagonal portion of A */ 4402 ncols_o = bi[i+1] - bi[i]; 4403 for (jo=0; jo<ncols_o; jo++) { 4404 col = cmap[*bj]; 4405 if (col >= cstart) break; 4406 *cam++ = *ba++; bj++; 4407 } 4408 /* diagonal portion of A */ 4409 ncols_d = ai[i+1] - ai[i]; 4410 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4411 /* off-diagonal portion of A */ 4412 for (j=jo; j<ncols_o; j++) { 4413 *cam++ = *ba++; bj++; 4414 } 4415 } 4416 } else { 4417 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4418 } 4419 4420 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4421 PetscFunctionReturn(0); 4422 } 4423 4424 #undef __FUNCT__ 4425 #define __FUNCT__ "MatGetLocalMatCondensed" 4426 /*@C 4427 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4428 4429 Not Collective 4430 4431 Input Parameters: 4432 + A - the matrix 4433 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4434 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4435 4436 Output Parameter: 4437 . A_loc - the local sequential matrix generated 4438 4439 Level: developer 4440 4441 @*/ 4442 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4443 { 4444 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4445 PetscErrorCode ierr; 4446 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4447 IS isrowa,iscola; 4448 Mat *aloc; 4449 4450 PetscFunctionBegin; 4451 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4452 if (!row){ 4453 start = A->rmap->rstart; end = A->rmap->rend; 4454 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4455 } else { 4456 isrowa = *row; 4457 } 4458 if (!col){ 4459 start = A->cmap->rstart; 4460 cmap = a->garray; 4461 nzA = a->A->cmap->n; 4462 nzB = a->B->cmap->n; 4463 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4464 ncols = 0; 4465 for (i=0; i<nzB; i++) { 4466 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4467 else break; 4468 } 4469 imark = i; 4470 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4471 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4472 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4473 ierr = PetscFree(idx);CHKERRQ(ierr); 4474 } else { 4475 iscola = *col; 4476 } 4477 if (scall != MAT_INITIAL_MATRIX){ 4478 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4479 aloc[0] = *A_loc; 4480 } 4481 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4482 *A_loc = aloc[0]; 4483 ierr = PetscFree(aloc);CHKERRQ(ierr); 4484 if (!row){ 4485 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4486 } 4487 if (!col){ 4488 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4489 } 4490 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4491 PetscFunctionReturn(0); 4492 } 4493 4494 #undef __FUNCT__ 4495 #define __FUNCT__ "MatGetBrowsOfAcols" 4496 /*@C 4497 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4498 4499 Collective on Mat 4500 4501 Input Parameters: 4502 + A,B - the matrices in mpiaij format 4503 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4504 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4505 4506 Output Parameter: 4507 + rowb, colb - index sets of rows and columns of B to extract 4508 . brstart - row index of B_seq from which next B->rmap->n rows are taken from B's local rows 4509 - B_seq - the sequential matrix generated 4510 4511 Level: developer 4512 4513 @*/ 4514 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4515 { 4516 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4517 PetscErrorCode ierr; 4518 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4519 IS isrowb,iscolb; 4520 Mat *bseq; 4521 4522 PetscFunctionBegin; 4523 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4524 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); 4525 } 4526 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4527 4528 if (scall == MAT_INITIAL_MATRIX){ 4529 start = A->cmap->rstart; 4530 cmap = a->garray; 4531 nzA = a->A->cmap->n; 4532 nzB = a->B->cmap->n; 4533 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4534 ncols = 0; 4535 for (i=0; i<nzB; i++) { /* row < local row index */ 4536 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4537 else break; 4538 } 4539 imark = i; 4540 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4541 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4542 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4543 ierr = PetscFree(idx);CHKERRQ(ierr); 4544 *brstart = imark; 4545 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4546 } else { 4547 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4548 isrowb = *rowb; iscolb = *colb; 4549 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4550 bseq[0] = *B_seq; 4551 } 4552 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4553 *B_seq = bseq[0]; 4554 ierr = PetscFree(bseq);CHKERRQ(ierr); 4555 if (!rowb){ 4556 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4557 } else { 4558 *rowb = isrowb; 4559 } 4560 if (!colb){ 4561 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4562 } else { 4563 *colb = iscolb; 4564 } 4565 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4566 PetscFunctionReturn(0); 4567 } 4568 4569 #undef __FUNCT__ 4570 #define __FUNCT__ "MatGetBrowsOfAoCols" 4571 /*@C 4572 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4573 of the OFF-DIAGONAL portion of local A 4574 4575 Collective on Mat 4576 4577 Input Parameters: 4578 + A,B - the matrices in mpiaij format 4579 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4580 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4581 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4582 4583 Output Parameter: 4584 + B_oth - the sequential matrix generated 4585 4586 Level: developer 4587 4588 @*/ 4589 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,MatScalar **bufa_ptr,Mat *B_oth) 4590 { 4591 VecScatter_MPI_General *gen_to,*gen_from; 4592 PetscErrorCode ierr; 4593 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4594 Mat_SeqAIJ *b_oth; 4595 VecScatter ctx=a->Mvctx; 4596 MPI_Comm comm=((PetscObject)ctx)->comm; 4597 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4598 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4599 PetscScalar *rvalues,*svalues; 4600 MatScalar *b_otha,*bufa,*bufA; 4601 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4602 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4603 MPI_Status *sstatus,rstatus; 4604 PetscMPIInt jj; 4605 PetscInt *cols,sbs,rbs; 4606 PetscScalar *vals; 4607 4608 PetscFunctionBegin; 4609 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4610 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); 4611 } 4612 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4613 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4614 4615 gen_to = (VecScatter_MPI_General*)ctx->todata; 4616 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4617 rvalues = gen_from->values; /* holds the length of receiving row */ 4618 svalues = gen_to->values; /* holds the length of sending row */ 4619 nrecvs = gen_from->n; 4620 nsends = gen_to->n; 4621 4622 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4623 srow = gen_to->indices; /* local row index to be sent */ 4624 sstarts = gen_to->starts; 4625 sprocs = gen_to->procs; 4626 sstatus = gen_to->sstatus; 4627 sbs = gen_to->bs; 4628 rstarts = gen_from->starts; 4629 rprocs = gen_from->procs; 4630 rbs = gen_from->bs; 4631 4632 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4633 if (scall == MAT_INITIAL_MATRIX){ 4634 /* i-array */ 4635 /*---------*/ 4636 /* post receives */ 4637 for (i=0; i<nrecvs; i++){ 4638 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4639 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4640 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4641 } 4642 4643 /* pack the outgoing message */ 4644 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4645 rstartsj = sstartsj + nsends +1; 4646 sstartsj[0] = 0; rstartsj[0] = 0; 4647 len = 0; /* total length of j or a array to be sent */ 4648 k = 0; 4649 for (i=0; i<nsends; i++){ 4650 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4651 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4652 for (j=0; j<nrows; j++) { 4653 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4654 for (l=0; l<sbs; l++){ 4655 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4656 rowlen[j*sbs+l] = ncols; 4657 len += ncols; 4658 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4659 } 4660 k++; 4661 } 4662 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4663 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4664 } 4665 /* recvs and sends of i-array are completed */ 4666 i = nrecvs; 4667 while (i--) { 4668 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4669 } 4670 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4671 4672 /* allocate buffers for sending j and a arrays */ 4673 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4674 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4675 4676 /* create i-array of B_oth */ 4677 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4678 b_othi[0] = 0; 4679 len = 0; /* total length of j or a array to be received */ 4680 k = 0; 4681 for (i=0; i<nrecvs; i++){ 4682 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4683 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4684 for (j=0; j<nrows; j++) { 4685 b_othi[k+1] = b_othi[k] + rowlen[j]; 4686 len += rowlen[j]; k++; 4687 } 4688 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4689 } 4690 4691 /* allocate space for j and a arrrays of B_oth */ 4692 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4693 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 4694 4695 /* j-array */ 4696 /*---------*/ 4697 /* post receives of j-array */ 4698 for (i=0; i<nrecvs; i++){ 4699 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4700 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4701 } 4702 4703 /* pack the outgoing message j-array */ 4704 k = 0; 4705 for (i=0; i<nsends; i++){ 4706 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4707 bufJ = bufj+sstartsj[i]; 4708 for (j=0; j<nrows; j++) { 4709 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4710 for (ll=0; ll<sbs; ll++){ 4711 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4712 for (l=0; l<ncols; l++){ 4713 *bufJ++ = cols[l]; 4714 } 4715 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4716 } 4717 } 4718 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4719 } 4720 4721 /* recvs and sends of j-array are completed */ 4722 i = nrecvs; 4723 while (i--) { 4724 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4725 } 4726 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4727 } else if (scall == MAT_REUSE_MATRIX){ 4728 sstartsj = *startsj; 4729 rstartsj = sstartsj + nsends +1; 4730 bufa = *bufa_ptr; 4731 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4732 b_otha = b_oth->a; 4733 } else { 4734 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4735 } 4736 4737 /* a-array */ 4738 /*---------*/ 4739 /* post receives of a-array */ 4740 for (i=0; i<nrecvs; i++){ 4741 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4742 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4743 } 4744 4745 /* pack the outgoing message a-array */ 4746 k = 0; 4747 for (i=0; i<nsends; i++){ 4748 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4749 bufA = bufa+sstartsj[i]; 4750 for (j=0; j<nrows; j++) { 4751 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4752 for (ll=0; ll<sbs; ll++){ 4753 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4754 for (l=0; l<ncols; l++){ 4755 *bufA++ = vals[l]; 4756 } 4757 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4758 } 4759 } 4760 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4761 } 4762 /* recvs and sends of a-array are completed */ 4763 i = nrecvs; 4764 while (i--) { 4765 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4766 } 4767 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4768 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4769 4770 if (scall == MAT_INITIAL_MATRIX){ 4771 /* put together the new matrix */ 4772 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4773 4774 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4775 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4776 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4777 b_oth->free_a = PETSC_TRUE; 4778 b_oth->free_ij = PETSC_TRUE; 4779 b_oth->nonew = 0; 4780 4781 ierr = PetscFree(bufj);CHKERRQ(ierr); 4782 if (!startsj || !bufa_ptr){ 4783 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4784 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4785 } else { 4786 *startsj = sstartsj; 4787 *bufa_ptr = bufa; 4788 } 4789 } 4790 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4791 PetscFunctionReturn(0); 4792 } 4793 4794 #undef __FUNCT__ 4795 #define __FUNCT__ "MatGetCommunicationStructs" 4796 /*@C 4797 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4798 4799 Not Collective 4800 4801 Input Parameters: 4802 . A - The matrix in mpiaij format 4803 4804 Output Parameter: 4805 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4806 . colmap - A map from global column index to local index into lvec 4807 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4808 4809 Level: developer 4810 4811 @*/ 4812 #if defined (PETSC_USE_CTABLE) 4813 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4814 #else 4815 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4816 #endif 4817 { 4818 Mat_MPIAIJ *a; 4819 4820 PetscFunctionBegin; 4821 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4822 PetscValidPointer(lvec, 2) 4823 PetscValidPointer(colmap, 3) 4824 PetscValidPointer(multScatter, 4) 4825 a = (Mat_MPIAIJ *) A->data; 4826 if (lvec) *lvec = a->lvec; 4827 if (colmap) *colmap = a->colmap; 4828 if (multScatter) *multScatter = a->Mvctx; 4829 PetscFunctionReturn(0); 4830 } 4831 4832 EXTERN_C_BEGIN 4833 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,const MatType,MatReuse,Mat*); 4834 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,const MatType,MatReuse,Mat*); 4835 EXTERN_C_END 4836 4837 #include "../src/mat/impls/dense/mpi/mpidense.h" 4838 4839 #undef __FUNCT__ 4840 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4841 /* 4842 Computes (B'*A')' since computing B*A directly is untenable 4843 4844 n p p 4845 ( ) ( ) ( ) 4846 m ( A ) * n ( B ) = m ( C ) 4847 ( ) ( ) ( ) 4848 4849 */ 4850 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4851 { 4852 PetscErrorCode ierr; 4853 Mat At,Bt,Ct; 4854 4855 PetscFunctionBegin; 4856 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4857 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4858 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4859 ierr = MatDestroy(At);CHKERRQ(ierr); 4860 ierr = MatDestroy(Bt);CHKERRQ(ierr); 4861 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4862 ierr = MatDestroy(Ct);CHKERRQ(ierr); 4863 PetscFunctionReturn(0); 4864 } 4865 4866 #undef __FUNCT__ 4867 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4868 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4869 { 4870 PetscErrorCode ierr; 4871 PetscInt m=A->rmap->n,n=B->cmap->n; 4872 Mat Cmat; 4873 4874 PetscFunctionBegin; 4875 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); 4876 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 4877 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4878 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4879 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 4880 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4881 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4882 *C = Cmat; 4883 PetscFunctionReturn(0); 4884 } 4885 4886 /* ----------------------------------------------------------------*/ 4887 #undef __FUNCT__ 4888 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4889 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4890 { 4891 PetscErrorCode ierr; 4892 4893 PetscFunctionBegin; 4894 if (scall == MAT_INITIAL_MATRIX){ 4895 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 4896 } 4897 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 4898 PetscFunctionReturn(0); 4899 } 4900 4901 EXTERN_C_BEGIN 4902 #if defined(PETSC_HAVE_MUMPS) 4903 extern PetscErrorCode MatGetFactor_mpiaij_mumps(Mat,MatFactorType,Mat*); 4904 #endif 4905 #if defined(PETSC_HAVE_SUPERLU_DIST) 4906 extern PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 4907 #endif 4908 #if defined(PETSC_HAVE_SPOOLES) 4909 extern PetscErrorCode MatGetFactor_mpiaij_spooles(Mat,MatFactorType,Mat*); 4910 #endif 4911 EXTERN_C_END 4912 4913 /*MC 4914 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 4915 4916 Options Database Keys: 4917 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 4918 4919 Level: beginner 4920 4921 .seealso: MatCreateMPIAIJ() 4922 M*/ 4923 4924 EXTERN_C_BEGIN 4925 #undef __FUNCT__ 4926 #define __FUNCT__ "MatCreate_MPIAIJ" 4927 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 4928 { 4929 Mat_MPIAIJ *b; 4930 PetscErrorCode ierr; 4931 PetscMPIInt size; 4932 4933 PetscFunctionBegin; 4934 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 4935 4936 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 4937 B->data = (void*)b; 4938 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4939 B->rmap->bs = 1; 4940 B->assembled = PETSC_FALSE; 4941 B->mapping = 0; 4942 4943 B->insertmode = NOT_SET_VALUES; 4944 b->size = size; 4945 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 4946 4947 /* build cache for off array entries formed */ 4948 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 4949 b->donotstash = PETSC_FALSE; 4950 b->colmap = 0; 4951 b->garray = 0; 4952 b->roworiented = PETSC_TRUE; 4953 4954 /* stuff used for matrix vector multiply */ 4955 b->lvec = PETSC_NULL; 4956 b->Mvctx = PETSC_NULL; 4957 4958 /* stuff for MatGetRow() */ 4959 b->rowindices = 0; 4960 b->rowvalues = 0; 4961 b->getrowactive = PETSC_FALSE; 4962 4963 #if defined(PETSC_HAVE_SPOOLES) 4964 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_spooles_C", 4965 "MatGetFactor_mpiaij_spooles", 4966 MatGetFactor_mpiaij_spooles);CHKERRQ(ierr); 4967 #endif 4968 #if defined(PETSC_HAVE_MUMPS) 4969 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_mumps_C", 4970 "MatGetFactor_mpiaij_mumps", 4971 MatGetFactor_mpiaij_mumps);CHKERRQ(ierr); 4972 #endif 4973 #if defined(PETSC_HAVE_SUPERLU_DIST) 4974 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mpiaij_superlu_dist_C", 4975 "MatGetFactor_mpiaij_superlu_dist", 4976 MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 4977 #endif 4978 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 4979 "MatStoreValues_MPIAIJ", 4980 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 4981 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 4982 "MatRetrieveValues_MPIAIJ", 4983 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 4984 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 4985 "MatGetDiagonalBlock_MPIAIJ", 4986 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 4987 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 4988 "MatIsTranspose_MPIAIJ", 4989 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 4990 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 4991 "MatMPIAIJSetPreallocation_MPIAIJ", 4992 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 4993 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 4994 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 4995 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 4996 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 4997 "MatDiagonalScaleLocal_MPIAIJ", 4998 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 4999 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 5000 "MatConvert_MPIAIJ_MPICSRPERM", 5001 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 5002 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 5003 "MatConvert_MPIAIJ_MPICRL", 5004 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 5005 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 5006 "MatMatMult_MPIDense_MPIAIJ", 5007 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5008 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 5009 "MatMatMultSymbolic_MPIDense_MPIAIJ", 5010 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5011 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 5012 "MatMatMultNumeric_MPIDense_MPIAIJ", 5013 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5014 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5015 PetscFunctionReturn(0); 5016 } 5017 EXTERN_C_END 5018 5019 #undef __FUNCT__ 5020 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5021 /*@ 5022 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5023 and "off-diagonal" part of the matrix in CSR format. 5024 5025 Collective on MPI_Comm 5026 5027 Input Parameters: 5028 + comm - MPI communicator 5029 . m - number of local rows (Cannot be PETSC_DECIDE) 5030 . n - This value should be the same as the local size used in creating the 5031 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5032 calculated if N is given) For square matrices n is almost always m. 5033 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5034 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5035 . i - row indices for "diagonal" portion of matrix 5036 . j - column indices 5037 . a - matrix values 5038 . oi - row indices for "off-diagonal" portion of matrix 5039 . oj - column indices 5040 - oa - matrix values 5041 5042 Output Parameter: 5043 . mat - the matrix 5044 5045 Level: advanced 5046 5047 Notes: 5048 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 5049 5050 The i and j indices are 0 based 5051 5052 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5053 5054 5055 .keywords: matrix, aij, compressed row, sparse, parallel 5056 5057 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5058 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 5059 @*/ 5060 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 5061 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5062 { 5063 PetscErrorCode ierr; 5064 Mat_MPIAIJ *maij; 5065 5066 PetscFunctionBegin; 5067 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5068 if (i[0]) { 5069 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5070 } 5071 if (oi[0]) { 5072 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5073 } 5074 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5075 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5076 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5077 maij = (Mat_MPIAIJ*) (*mat)->data; 5078 maij->donotstash = PETSC_TRUE; 5079 (*mat)->preallocated = PETSC_TRUE; 5080 5081 (*mat)->rmap->bs = (*mat)->cmap->bs = 1; 5082 ierr = PetscMapSetUp((*mat)->rmap);CHKERRQ(ierr); 5083 ierr = PetscMapSetUp((*mat)->cmap);CHKERRQ(ierr); 5084 5085 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5086 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5087 5088 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5089 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5090 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5091 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5092 5093 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5094 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5095 PetscFunctionReturn(0); 5096 } 5097 5098 /* 5099 Special version for direct calls from Fortran 5100 */ 5101 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5102 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5103 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5104 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5105 #endif 5106 5107 /* Change these macros so can be used in void function */ 5108 #undef CHKERRQ 5109 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5110 #undef SETERRQ2 5111 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5112 #undef SETERRQ 5113 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5114 5115 EXTERN_C_BEGIN 5116 #undef __FUNCT__ 5117 #define __FUNCT__ "matsetvaluesmpiaij_" 5118 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5119 { 5120 Mat mat = *mmat; 5121 PetscInt m = *mm, n = *mn; 5122 InsertMode addv = *maddv; 5123 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5124 PetscScalar value; 5125 PetscErrorCode ierr; 5126 5127 MatPreallocated(mat); 5128 if (mat->insertmode == NOT_SET_VALUES) { 5129 mat->insertmode = addv; 5130 } 5131 #if defined(PETSC_USE_DEBUG) 5132 else if (mat->insertmode != addv) { 5133 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5134 } 5135 #endif 5136 { 5137 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5138 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5139 PetscTruth roworiented = aij->roworiented; 5140 5141 /* Some Variables required in the macro */ 5142 Mat A = aij->A; 5143 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5144 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5145 MatScalar *aa = a->a; 5146 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5147 Mat B = aij->B; 5148 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5149 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5150 MatScalar *ba = b->a; 5151 5152 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5153 PetscInt nonew = a->nonew; 5154 MatScalar *ap1,*ap2; 5155 5156 PetscFunctionBegin; 5157 for (i=0; i<m; i++) { 5158 if (im[i] < 0) continue; 5159 #if defined(PETSC_USE_DEBUG) 5160 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5161 #endif 5162 if (im[i] >= rstart && im[i] < rend) { 5163 row = im[i] - rstart; 5164 lastcol1 = -1; 5165 rp1 = aj + ai[row]; 5166 ap1 = aa + ai[row]; 5167 rmax1 = aimax[row]; 5168 nrow1 = ailen[row]; 5169 low1 = 0; 5170 high1 = nrow1; 5171 lastcol2 = -1; 5172 rp2 = bj + bi[row]; 5173 ap2 = ba + bi[row]; 5174 rmax2 = bimax[row]; 5175 nrow2 = bilen[row]; 5176 low2 = 0; 5177 high2 = nrow2; 5178 5179 for (j=0; j<n; j++) { 5180 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5181 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5182 if (in[j] >= cstart && in[j] < cend){ 5183 col = in[j] - cstart; 5184 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5185 } else if (in[j] < 0) continue; 5186 #if defined(PETSC_USE_DEBUG) 5187 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);} 5188 #endif 5189 else { 5190 if (mat->was_assembled) { 5191 if (!aij->colmap) { 5192 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5193 } 5194 #if defined (PETSC_USE_CTABLE) 5195 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5196 col--; 5197 #else 5198 col = aij->colmap[in[j]] - 1; 5199 #endif 5200 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5201 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5202 col = in[j]; 5203 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5204 B = aij->B; 5205 b = (Mat_SeqAIJ*)B->data; 5206 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5207 rp2 = bj + bi[row]; 5208 ap2 = ba + bi[row]; 5209 rmax2 = bimax[row]; 5210 nrow2 = bilen[row]; 5211 low2 = 0; 5212 high2 = nrow2; 5213 bm = aij->B->rmap->n; 5214 ba = b->a; 5215 } 5216 } else col = in[j]; 5217 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5218 } 5219 } 5220 } else { 5221 if (!aij->donotstash) { 5222 if (roworiented) { 5223 if (ignorezeroentries && v[i*n] == 0.0) continue; 5224 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);CHKERRQ(ierr); 5225 } else { 5226 if (ignorezeroentries && v[i] == 0.0) continue; 5227 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);CHKERRQ(ierr); 5228 } 5229 } 5230 } 5231 }} 5232 PetscFunctionReturnVoid(); 5233 } 5234 EXTERN_C_END 5235 5236