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