1 #define PETSCMAT_DLL 2 3 #include "../src/mat/impls/aij/mpi/mpiaij.h" /*I "petscmat.h" I*/ 4 5 #undef __FUNCT__ 6 #define __FUNCT__ "MatDistribute_MPIAIJ" 7 /* 8 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 9 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 10 11 Only for square matrices 12 */ 13 PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 14 { 15 PetscMPIInt rank,size; 16 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld; 17 PetscErrorCode ierr; 18 Mat mat; 19 Mat_SeqAIJ *gmata; 20 PetscMPIInt tag; 21 MPI_Status status; 22 PetscTruth aij; 23 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 24 25 PetscFunctionBegin; 26 CHKMEMQ; 27 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 28 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 29 if (!rank) { 30 ierr = PetscTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 31 if (!aij) SETERRQ1(PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 32 } 33 if (reuse == MAT_INITIAL_MATRIX) { 34 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 35 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 36 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 37 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 38 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 39 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 40 rowners[0] = 0; 41 for (i=2; i<=size; i++) { 42 rowners[i] += rowners[i-1]; 43 } 44 rstart = rowners[rank]; 45 rend = rowners[rank+1]; 46 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 47 if (!rank) { 48 gmata = (Mat_SeqAIJ*) gmat->data; 49 /* send row lengths to all processors */ 50 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 51 for (i=1; i<size; i++) { 52 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 53 } 54 /* determine number diagonal and off-diagonal counts */ 55 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 56 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 57 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 58 jj = 0; 59 for (i=0; i<m; i++) { 60 for (j=0; j<dlens[i]; j++) { 61 if (gmata->j[jj] < rstart) ld[i]++; 62 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 63 jj++; 64 } 65 } 66 /* send column indices to other processes */ 67 for (i=1; i<size; i++) { 68 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 69 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 70 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 71 } 72 73 /* send numerical values to other processes */ 74 for (i=1; i<size; i++) { 75 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 76 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 77 } 78 gmataa = gmata->a; 79 gmataj = gmata->j; 80 81 } else { 82 /* receive row lengths */ 83 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 84 /* receive column indices */ 85 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 86 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 87 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 88 /* determine number diagonal and off-diagonal counts */ 89 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 90 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 91 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 92 jj = 0; 93 for (i=0; i<m; i++) { 94 for (j=0; j<dlens[i]; j++) { 95 if (gmataj[jj] < rstart) ld[i]++; 96 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 97 jj++; 98 } 99 } 100 /* receive numerical values */ 101 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 102 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 103 } 104 /* set preallocation */ 105 for (i=0; i<m; i++) { 106 dlens[i] -= olens[i]; 107 } 108 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 109 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 110 111 for (i=0; i<m; i++) { 112 dlens[i] += olens[i]; 113 } 114 cnt = 0; 115 for (i=0; i<m; i++) { 116 row = rstart + i; 117 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 118 cnt += dlens[i]; 119 } 120 if (rank) { 121 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 122 } 123 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 124 ierr = PetscFree(rowners);CHKERRQ(ierr); 125 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 126 *inmat = mat; 127 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 128 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 129 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 130 mat = *inmat; 131 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 132 if (!rank) { 133 /* send numerical values to other processes */ 134 gmata = (Mat_SeqAIJ*) gmat->data; 135 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 136 gmataa = gmata->a; 137 for (i=1; i<size; i++) { 138 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 139 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 140 } 141 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 142 } else { 143 /* receive numerical values from process 0*/ 144 nz = Ad->nz + Ao->nz; 145 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 146 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 147 } 148 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 149 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 150 ad = Ad->a; 151 ao = Ao->a; 152 if (mat->rmap->n) { 153 i = 0; 154 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 155 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 156 } 157 for (i=1; i<mat->rmap->n; i++) { 158 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; 159 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 160 } 161 i--; 162 if (mat->rmap->n) { 163 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 164 } 165 if (rank) { 166 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 167 } 168 } 169 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 170 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 171 CHKMEMQ; 172 PetscFunctionReturn(0); 173 } 174 175 /* 176 Local utility routine that creates a mapping from the global column 177 number to the local number in the off-diagonal part of the local 178 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 179 a slightly higher hash table cost; without it it is not scalable (each processor 180 has an order N integer array but is fast to acess. 181 */ 182 #undef __FUNCT__ 183 #define __FUNCT__ "CreateColmap_MPIAIJ_Private" 184 PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat) 185 { 186 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 187 PetscErrorCode ierr; 188 PetscInt n = aij->B->cmap->n,i; 189 190 PetscFunctionBegin; 191 #if defined (PETSC_USE_CTABLE) 192 ierr = PetscTableCreate(n,&aij->colmap);CHKERRQ(ierr); 193 for (i=0; i<n; i++){ 194 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);CHKERRQ(ierr); 195 } 196 #else 197 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 198 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 199 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 200 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 201 #endif 202 PetscFunctionReturn(0); 203 } 204 205 206 #define CHUNKSIZE 15 207 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 208 { \ 209 if (col <= lastcol1) low1 = 0; else high1 = nrow1; \ 210 lastcol1 = col;\ 211 while (high1-low1 > 5) { \ 212 t = (low1+high1)/2; \ 213 if (rp1[t] > col) high1 = t; \ 214 else low1 = t; \ 215 } \ 216 for (_i=low1; _i<high1; _i++) { \ 217 if (rp1[_i] > col) break; \ 218 if (rp1[_i] == col) { \ 219 if (addv == ADD_VALUES) ap1[_i] += value; \ 220 else ap1[_i] = value; \ 221 goto a_noinsert; \ 222 } \ 223 } \ 224 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 225 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 226 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 227 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 228 N = nrow1++ - 1; a->nz++; high1++; \ 229 /* shift up all the later entries in this row */ \ 230 for (ii=N; ii>=_i; ii--) { \ 231 rp1[ii+1] = rp1[ii]; \ 232 ap1[ii+1] = ap1[ii]; \ 233 } \ 234 rp1[_i] = col; \ 235 ap1[_i] = value; \ 236 a_noinsert: ; \ 237 ailen[row] = nrow1; \ 238 } 239 240 241 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 242 { \ 243 if (col <= lastcol2) low2 = 0; else high2 = nrow2; \ 244 lastcol2 = col;\ 245 while (high2-low2 > 5) { \ 246 t = (low2+high2)/2; \ 247 if (rp2[t] > col) high2 = t; \ 248 else low2 = t; \ 249 } \ 250 for (_i=low2; _i<high2; _i++) { \ 251 if (rp2[_i] > col) break; \ 252 if (rp2[_i] == col) { \ 253 if (addv == ADD_VALUES) ap2[_i] += value; \ 254 else ap2[_i] = value; \ 255 goto b_noinsert; \ 256 } \ 257 } \ 258 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 259 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 260 if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 261 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 262 N = nrow2++ - 1; b->nz++; high2++; \ 263 /* shift up all the later entries in this row */ \ 264 for (ii=N; ii>=_i; ii--) { \ 265 rp2[ii+1] = rp2[ii]; \ 266 ap2[ii+1] = ap2[ii]; \ 267 } \ 268 rp2[_i] = col; \ 269 ap2[_i] = value; \ 270 b_noinsert: ; \ 271 bilen[row] = nrow2; \ 272 } 273 274 #undef __FUNCT__ 275 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 276 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 277 { 278 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 279 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 280 PetscErrorCode ierr; 281 PetscInt l,*garray = mat->garray,diag; 282 283 PetscFunctionBegin; 284 /* code only works for square matrices A */ 285 286 /* find size of row to the left of the diagonal part */ 287 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 288 row = row - diag; 289 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 290 if (garray[b->j[b->i[row]+l]] > diag) break; 291 } 292 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 293 294 /* diagonal part */ 295 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 296 297 /* right of diagonal part */ 298 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); 299 PetscFunctionReturn(0); 300 } 301 302 #undef __FUNCT__ 303 #define __FUNCT__ "MatSetValues_MPIAIJ" 304 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 305 { 306 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 307 PetscScalar value; 308 PetscErrorCode ierr; 309 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 310 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 311 PetscTruth roworiented = aij->roworiented; 312 313 /* Some Variables required in the macro */ 314 Mat A = aij->A; 315 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 316 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 317 MatScalar *aa = a->a; 318 PetscTruth ignorezeroentries = a->ignorezeroentries; 319 Mat B = aij->B; 320 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 321 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 322 MatScalar *ba = b->a; 323 324 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 325 PetscInt nonew = a->nonew; 326 MatScalar *ap1,*ap2; 327 328 PetscFunctionBegin; 329 for (i=0; i<m; i++) { 330 if (im[i] < 0) continue; 331 #if defined(PETSC_USE_DEBUG) 332 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 333 #endif 334 if (im[i] >= rstart && im[i] < rend) { 335 row = im[i] - rstart; 336 lastcol1 = -1; 337 rp1 = aj + ai[row]; 338 ap1 = aa + ai[row]; 339 rmax1 = aimax[row]; 340 nrow1 = ailen[row]; 341 low1 = 0; 342 high1 = nrow1; 343 lastcol2 = -1; 344 rp2 = bj + bi[row]; 345 ap2 = ba + bi[row]; 346 rmax2 = bimax[row]; 347 nrow2 = bilen[row]; 348 low2 = 0; 349 high2 = nrow2; 350 351 for (j=0; j<n; j++) { 352 if (v) {if (roworiented) value = v[i*n+j]; else value = v[i+j*m];} else value = 0.0; 353 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 354 if (in[j] >= cstart && in[j] < cend){ 355 col = in[j] - cstart; 356 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 357 } else if (in[j] < 0) continue; 358 #if defined(PETSC_USE_DEBUG) 359 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);} 360 #endif 361 else { 362 if (mat->was_assembled) { 363 if (!aij->colmap) { 364 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 365 } 366 #if defined (PETSC_USE_CTABLE) 367 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 368 col--; 369 #else 370 col = aij->colmap[in[j]] - 1; 371 #endif 372 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 373 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 374 col = in[j]; 375 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 376 B = aij->B; 377 b = (Mat_SeqAIJ*)B->data; 378 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 379 rp2 = bj + bi[row]; 380 ap2 = ba + bi[row]; 381 rmax2 = bimax[row]; 382 nrow2 = bilen[row]; 383 low2 = 0; 384 high2 = nrow2; 385 bm = aij->B->rmap->n; 386 ba = b->a; 387 } 388 } else col = in[j]; 389 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 390 } 391 } 392 } else { 393 if (!aij->donotstash) { 394 if (roworiented) { 395 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 396 } else { 397 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 398 } 399 } 400 } 401 } 402 PetscFunctionReturn(0); 403 } 404 405 #undef __FUNCT__ 406 #define __FUNCT__ "MatGetValues_MPIAIJ" 407 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 408 { 409 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 410 PetscErrorCode ierr; 411 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 412 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 413 414 PetscFunctionBegin; 415 for (i=0; i<m; i++) { 416 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 417 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 418 if (idxm[i] >= rstart && idxm[i] < rend) { 419 row = idxm[i] - rstart; 420 for (j=0; j<n; j++) { 421 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 422 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 423 if (idxn[j] >= cstart && idxn[j] < cend){ 424 col = idxn[j] - cstart; 425 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 426 } else { 427 if (!aij->colmap) { 428 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 429 } 430 #if defined (PETSC_USE_CTABLE) 431 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 432 col --; 433 #else 434 col = aij->colmap[idxn[j]] - 1; 435 #endif 436 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 437 else { 438 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 439 } 440 } 441 } 442 } else { 443 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 444 } 445 } 446 PetscFunctionReturn(0); 447 } 448 449 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 453 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 454 { 455 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 456 PetscErrorCode ierr; 457 PetscInt nstash,reallocs; 458 InsertMode addv; 459 460 PetscFunctionBegin; 461 if (aij->donotstash) { 462 PetscFunctionReturn(0); 463 } 464 465 /* make sure all processors are either in INSERTMODE or ADDMODE */ 466 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 467 if (addv == (ADD_VALUES|INSERT_VALUES)) { 468 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 469 } 470 mat->insertmode = addv; /* in case this processor had no cache */ 471 472 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 473 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 474 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 475 PetscFunctionReturn(0); 476 } 477 478 #undef __FUNCT__ 479 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 480 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 481 { 482 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 483 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data; 484 PetscErrorCode ierr; 485 PetscMPIInt n; 486 PetscInt i,j,rstart,ncols,flg; 487 PetscInt *row,*col; 488 PetscTruth other_disassembled; 489 PetscScalar *val; 490 InsertMode addv = mat->insertmode; 491 492 /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */ 493 PetscFunctionBegin; 494 if (!aij->donotstash) { 495 while (1) { 496 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 497 if (!flg) break; 498 499 for (i=0; i<n;) { 500 /* Now identify the consecutive vals belonging to the same row */ 501 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 502 if (j < n) ncols = j-i; 503 else ncols = n-i; 504 /* Now assemble all these values with a single function call */ 505 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 506 i = j; 507 } 508 } 509 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 510 } 511 a->compressedrow.use = PETSC_FALSE; 512 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 513 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 514 515 /* determine if any processor has disassembled, if so we must 516 also disassemble ourselfs, in order that we may reassemble. */ 517 /* 518 if nonzero structure of submatrix B cannot change then we know that 519 no processor disassembled thus we can skip this stuff 520 */ 521 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 522 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 523 if (mat->was_assembled && !other_disassembled) { 524 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 525 } 526 } 527 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 528 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 529 } 530 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 531 ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */ 532 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 533 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 534 535 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 536 aij->rowvalues = 0; 537 538 /* used by MatAXPY() */ 539 a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 540 a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 541 542 if (aij->diag) {ierr = VecDestroy(aij->diag);CHKERRQ(ierr);aij->diag = 0;} 543 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 544 PetscFunctionReturn(0); 545 } 546 547 #undef __FUNCT__ 548 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 549 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 550 { 551 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 552 PetscErrorCode ierr; 553 554 PetscFunctionBegin; 555 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 556 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 557 PetscFunctionReturn(0); 558 } 559 560 #undef __FUNCT__ 561 #define __FUNCT__ "MatZeroRows_MPIAIJ" 562 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 563 { 564 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 565 PetscErrorCode ierr; 566 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 567 PetscInt i,*owners = A->rmap->range; 568 PetscInt *nprocs,j,idx,nsends,row; 569 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 570 PetscInt *rvalues,count,base,slen,*source; 571 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 572 MPI_Comm comm = ((PetscObject)A)->comm; 573 MPI_Request *send_waits,*recv_waits; 574 MPI_Status recv_status,*send_status; 575 #if defined(PETSC_DEBUG) 576 PetscTruth found = PETSC_FALSE; 577 #endif 578 579 PetscFunctionBegin; 580 /* first count number of contributors to each processor */ 581 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 582 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 583 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 584 j = 0; 585 for (i=0; i<N; i++) { 586 if (lastidx > (idx = rows[i])) j = 0; 587 lastidx = idx; 588 for (; j<size; j++) { 589 if (idx >= owners[j] && idx < owners[j+1]) { 590 nprocs[2*j]++; 591 nprocs[2*j+1] = 1; 592 owner[i] = j; 593 #if defined(PETSC_DEBUG) 594 found = PETSC_TRUE; 595 #endif 596 break; 597 } 598 } 599 #if defined(PETSC_DEBUG) 600 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 601 found = PETSC_FALSE; 602 #endif 603 } 604 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 605 606 /* inform other processors of number of messages and max length*/ 607 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 608 609 /* post receives: */ 610 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 611 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 612 for (i=0; i<nrecvs; i++) { 613 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 614 } 615 616 /* do sends: 617 1) starts[i] gives the starting index in svalues for stuff going to 618 the ith processor 619 */ 620 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 621 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 622 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 623 starts[0] = 0; 624 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 625 for (i=0; i<N; i++) { 626 svalues[starts[owner[i]]++] = rows[i]; 627 } 628 629 starts[0] = 0; 630 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 631 count = 0; 632 for (i=0; i<size; i++) { 633 if (nprocs[2*i+1]) { 634 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 635 } 636 } 637 ierr = PetscFree(starts);CHKERRQ(ierr); 638 639 base = owners[rank]; 640 641 /* wait on receives */ 642 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 643 source = lens + nrecvs; 644 count = nrecvs; slen = 0; 645 while (count) { 646 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 647 /* unpack receives into our local space */ 648 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 649 source[imdex] = recv_status.MPI_SOURCE; 650 lens[imdex] = n; 651 slen += n; 652 count--; 653 } 654 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 655 656 /* move the data into the send scatter */ 657 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 658 count = 0; 659 for (i=0; i<nrecvs; i++) { 660 values = rvalues + i*nmax; 661 for (j=0; j<lens[i]; j++) { 662 lrows[count++] = values[j] - base; 663 } 664 } 665 ierr = PetscFree(rvalues);CHKERRQ(ierr); 666 ierr = PetscFree(lens);CHKERRQ(ierr); 667 ierr = PetscFree(owner);CHKERRQ(ierr); 668 ierr = PetscFree(nprocs);CHKERRQ(ierr); 669 670 /* actually zap the local rows */ 671 /* 672 Zero the required rows. If the "diagonal block" of the matrix 673 is square and the user wishes to set the diagonal we use separate 674 code so that MatSetValues() is not called for each diagonal allocating 675 new memory, thus calling lots of mallocs and slowing things down. 676 677 */ 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__ "MatMultDiagonalBlock_MPIAIJ" 733 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 734 { 735 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 736 PetscErrorCode ierr; 737 738 PetscFunctionBegin; 739 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatMultAdd_MPIAIJ" 745 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 746 { 747 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 750 PetscFunctionBegin; 751 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 752 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 753 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 754 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 755 PetscFunctionReturn(0); 756 } 757 758 #undef __FUNCT__ 759 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 760 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 761 { 762 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 763 PetscErrorCode ierr; 764 PetscTruth merged; 765 766 PetscFunctionBegin; 767 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 768 /* do nondiagonal part */ 769 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 770 if (!merged) { 771 /* send it on its way */ 772 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 773 /* do local part */ 774 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 775 /* receive remote parts: note this assumes the values are not actually */ 776 /* added in yy until the next line, */ 777 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 778 } else { 779 /* do local part */ 780 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 781 /* send it on its way */ 782 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 783 /* values actually were received in the Begin() but we need to call this nop */ 784 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 785 } 786 PetscFunctionReturn(0); 787 } 788 789 EXTERN_C_BEGIN 790 #undef __FUNCT__ 791 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 792 PetscErrorCode PETSCMAT_DLLEXPORT MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f) 793 { 794 MPI_Comm comm; 795 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 796 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 797 IS Me,Notme; 798 PetscErrorCode ierr; 799 PetscInt M,N,first,last,*notme,i; 800 PetscMPIInt size; 801 802 PetscFunctionBegin; 803 804 /* Easy test: symmetric diagonal block */ 805 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 806 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 807 if (!*f) PetscFunctionReturn(0); 808 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 809 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 810 if (size == 1) PetscFunctionReturn(0); 811 812 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 813 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 814 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 815 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 816 for (i=0; i<first; i++) notme[i] = i; 817 for (i=last; i<M; i++) notme[i-last+first] = i; 818 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);CHKERRQ(ierr); 819 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 820 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 821 Aoff = Aoffs[0]; 822 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 823 Boff = Boffs[0]; 824 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 825 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 826 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 827 ierr = ISDestroy(Me);CHKERRQ(ierr); 828 ierr = ISDestroy(Notme);CHKERRQ(ierr); 829 830 PetscFunctionReturn(0); 831 } 832 EXTERN_C_END 833 834 #undef __FUNCT__ 835 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 836 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 837 { 838 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 839 PetscErrorCode ierr; 840 841 PetscFunctionBegin; 842 /* do nondiagonal part */ 843 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 844 /* send it on its way */ 845 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 846 /* do local part */ 847 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 848 /* receive remote parts */ 849 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 850 PetscFunctionReturn(0); 851 } 852 853 /* 854 This only works correctly for square matrices where the subblock A->A is the 855 diagonal block 856 */ 857 #undef __FUNCT__ 858 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 859 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 860 { 861 PetscErrorCode ierr; 862 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 863 864 PetscFunctionBegin; 865 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 866 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) { 867 SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 868 } 869 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 870 PetscFunctionReturn(0); 871 } 872 873 #undef __FUNCT__ 874 #define __FUNCT__ "MatScale_MPIAIJ" 875 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 876 { 877 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 878 PetscErrorCode ierr; 879 880 PetscFunctionBegin; 881 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 882 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 883 PetscFunctionReturn(0); 884 } 885 886 #undef __FUNCT__ 887 #define __FUNCT__ "MatDestroy_MPIAIJ" 888 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 889 { 890 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 891 PetscErrorCode ierr; 892 893 PetscFunctionBegin; 894 #if defined(PETSC_USE_LOG) 895 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 896 #endif 897 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 898 if (aij->diag) {ierr = VecDestroy(aij->diag);CHKERRQ(ierr);} 899 ierr = MatDestroy(aij->A);CHKERRQ(ierr); 900 ierr = MatDestroy(aij->B);CHKERRQ(ierr); 901 #if defined (PETSC_USE_CTABLE) 902 if (aij->colmap) {ierr = PetscTableDestroy(aij->colmap);CHKERRQ(ierr);} 903 #else 904 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 905 #endif 906 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 907 if (aij->lvec) {ierr = VecDestroy(aij->lvec);CHKERRQ(ierr);} 908 if (aij->Mvctx) {ierr = VecScatterDestroy(aij->Mvctx);CHKERRQ(ierr);} 909 ierr = PetscFree(aij->rowvalues);CHKERRQ(ierr); 910 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 911 ierr = PetscFree(aij);CHKERRQ(ierr); 912 913 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 914 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 915 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 916 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 917 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 918 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 919 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 920 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 921 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C","",PETSC_NULL);CHKERRQ(ierr); 922 PetscFunctionReturn(0); 923 } 924 925 #undef __FUNCT__ 926 #define __FUNCT__ "MatView_MPIAIJ_Binary" 927 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 928 { 929 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 930 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 931 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 932 PetscErrorCode ierr; 933 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 934 int fd; 935 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 936 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 937 PetscScalar *column_values; 938 939 PetscFunctionBegin; 940 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 941 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 942 nz = A->nz + B->nz; 943 if (!rank) { 944 header[0] = MAT_FILE_COOKIE; 945 header[1] = mat->rmap->N; 946 header[2] = mat->cmap->N; 947 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 948 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 949 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 950 /* get largest number of rows any processor has */ 951 rlen = mat->rmap->n; 952 range = mat->rmap->range; 953 for (i=1; i<size; i++) { 954 rlen = PetscMax(rlen,range[i+1] - range[i]); 955 } 956 } else { 957 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 958 rlen = mat->rmap->n; 959 } 960 961 /* load up the local row counts */ 962 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 963 for (i=0; i<mat->rmap->n; i++) { 964 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 965 } 966 967 /* store the row lengths to the file */ 968 if (!rank) { 969 MPI_Status status; 970 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 971 for (i=1; i<size; i++) { 972 rlen = range[i+1] - range[i]; 973 ierr = MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 974 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 975 } 976 } else { 977 ierr = MPI_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 978 } 979 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 980 981 /* load up the local column indices */ 982 nzmax = nz; /* )th processor needs space a largest processor needs */ 983 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 984 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 985 cnt = 0; 986 for (i=0; i<mat->rmap->n; i++) { 987 for (j=B->i[i]; j<B->i[i+1]; j++) { 988 if ( (col = garray[B->j[j]]) > cstart) break; 989 column_indices[cnt++] = col; 990 } 991 for (k=A->i[i]; k<A->i[i+1]; k++) { 992 column_indices[cnt++] = A->j[k] + cstart; 993 } 994 for (; j<B->i[i+1]; j++) { 995 column_indices[cnt++] = garray[B->j[j]]; 996 } 997 } 998 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 999 1000 /* store the column indices to the file */ 1001 if (!rank) { 1002 MPI_Status status; 1003 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1004 for (i=1; i<size; i++) { 1005 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1006 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1007 ierr = MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1008 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1009 } 1010 } else { 1011 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1012 ierr = MPI_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1013 } 1014 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1015 1016 /* load up the local column values */ 1017 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1018 cnt = 0; 1019 for (i=0; i<mat->rmap->n; i++) { 1020 for (j=B->i[i]; j<B->i[i+1]; j++) { 1021 if ( garray[B->j[j]] > cstart) break; 1022 column_values[cnt++] = B->a[j]; 1023 } 1024 for (k=A->i[i]; k<A->i[i+1]; k++) { 1025 column_values[cnt++] = A->a[k]; 1026 } 1027 for (; j<B->i[i+1]; j++) { 1028 column_values[cnt++] = B->a[j]; 1029 } 1030 } 1031 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1032 1033 /* store the column values to the file */ 1034 if (!rank) { 1035 MPI_Status status; 1036 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1037 for (i=1; i<size; i++) { 1038 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1039 if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1040 ierr = MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1041 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1042 } 1043 } else { 1044 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1045 ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1046 } 1047 ierr = PetscFree(column_values);CHKERRQ(ierr); 1048 PetscFunctionReturn(0); 1049 } 1050 1051 #undef __FUNCT__ 1052 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1053 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1054 { 1055 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1056 PetscErrorCode ierr; 1057 PetscMPIInt rank = aij->rank,size = aij->size; 1058 PetscTruth isdraw,iascii,isbinary; 1059 PetscViewer sviewer; 1060 PetscViewerFormat format; 1061 1062 PetscFunctionBegin; 1063 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1064 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1065 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1066 if (iascii) { 1067 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1068 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1069 MatInfo info; 1070 PetscTruth inodes; 1071 1072 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1073 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1074 ierr = MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);CHKERRQ(ierr); 1075 if (!inodes) { 1076 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1077 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1078 } else { 1079 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1080 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1081 } 1082 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1083 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1084 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1085 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1086 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1087 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1088 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1089 PetscFunctionReturn(0); 1090 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1091 PetscInt inodecount,inodelimit,*inodes; 1092 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1093 if (inodes) { 1094 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1095 } else { 1096 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1097 } 1098 PetscFunctionReturn(0); 1099 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1100 PetscFunctionReturn(0); 1101 } 1102 } else if (isbinary) { 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 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1108 } 1109 PetscFunctionReturn(0); 1110 } else if (isdraw) { 1111 PetscDraw draw; 1112 PetscTruth isnull; 1113 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1114 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1115 } 1116 1117 if (size == 1) { 1118 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1119 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1120 } else { 1121 /* assemble the entire matrix onto first processor. */ 1122 Mat A; 1123 Mat_SeqAIJ *Aloc; 1124 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1125 MatScalar *a; 1126 1127 if (mat->rmap->N > 1024) { 1128 PetscTruth flg = PETSC_FALSE; 1129 1130 ierr = PetscOptionsGetTruth(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,PETSC_NULL);CHKERRQ(ierr); 1131 if (!flg) { 1132 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1133 } 1134 } 1135 1136 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1137 if (!rank) { 1138 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1139 } else { 1140 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1141 } 1142 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1143 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1144 ierr = MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1145 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1146 1147 /* copy over the A part */ 1148 Aloc = (Mat_SeqAIJ*)aij->A->data; 1149 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1150 row = mat->rmap->rstart; 1151 for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap->rstart ;} 1152 for (i=0; i<m; i++) { 1153 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1154 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1155 } 1156 aj = Aloc->j; 1157 for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap->rstart;} 1158 1159 /* copy over the B part */ 1160 Aloc = (Mat_SeqAIJ*)aij->B->data; 1161 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1162 row = mat->rmap->rstart; 1163 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1164 ct = cols; 1165 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 1166 for (i=0; i<m; i++) { 1167 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1168 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1169 } 1170 ierr = PetscFree(ct);CHKERRQ(ierr); 1171 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1172 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1173 /* 1174 Everyone has to call to draw the matrix since the graphics waits are 1175 synchronized across all processors that share the PetscDraw object 1176 */ 1177 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1178 if (!rank) { 1179 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1180 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1181 } 1182 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1183 ierr = MatDestroy(A);CHKERRQ(ierr); 1184 } 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #undef __FUNCT__ 1189 #define __FUNCT__ "MatView_MPIAIJ" 1190 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1191 { 1192 PetscErrorCode ierr; 1193 PetscTruth iascii,isdraw,issocket,isbinary; 1194 1195 PetscFunctionBegin; 1196 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 1197 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr); 1198 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);CHKERRQ(ierr); 1199 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 1200 if (iascii || isdraw || isbinary || issocket) { 1201 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1202 } else { 1203 SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1204 } 1205 PetscFunctionReturn(0); 1206 } 1207 1208 #undef __FUNCT__ 1209 #define __FUNCT__ "MatSOR_MPIAIJ" 1210 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1211 { 1212 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1213 PetscErrorCode ierr; 1214 Vec bb1 = 0; 1215 PetscTruth hasop; 1216 1217 PetscFunctionBegin; 1218 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1219 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1220 } 1221 1222 if (flag == SOR_APPLY_UPPER) { 1223 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1224 PetscFunctionReturn(0); 1225 } 1226 1227 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1228 if (flag & SOR_ZERO_INITIAL_GUESS) { 1229 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1230 its--; 1231 } 1232 1233 while (its--) { 1234 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1235 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1236 1237 /* update rhs: bb1 = bb - B*x */ 1238 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1239 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1240 1241 /* local sweep */ 1242 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1243 } 1244 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1245 if (flag & SOR_ZERO_INITIAL_GUESS) { 1246 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1247 its--; 1248 } 1249 while (its--) { 1250 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1251 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1252 1253 /* update rhs: bb1 = bb - B*x */ 1254 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1255 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1256 1257 /* local sweep */ 1258 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1259 } 1260 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1261 if (flag & SOR_ZERO_INITIAL_GUESS) { 1262 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1263 its--; 1264 } 1265 while (its--) { 1266 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1267 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1268 1269 /* update rhs: bb1 = bb - B*x */ 1270 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1271 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1272 1273 /* local sweep */ 1274 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1275 } 1276 } else if (flag & SOR_EISENSTAT) { 1277 Vec xx1; 1278 1279 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1280 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1281 1282 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1283 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1284 if (!mat->diag) { 1285 ierr = MatGetVecs(matin,&mat->diag,PETSC_NULL);CHKERRQ(ierr); 1286 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1287 } 1288 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1289 if (hasop) { 1290 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1291 } else { 1292 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1293 } 1294 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1295 1296 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1297 1298 /* local sweep */ 1299 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1300 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1301 ierr = VecDestroy(xx1);CHKERRQ(ierr); 1302 } else { 1303 SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported"); 1304 } 1305 1306 if (bb1) {ierr = VecDestroy(bb1);CHKERRQ(ierr);} 1307 PetscFunctionReturn(0); 1308 } 1309 1310 #undef __FUNCT__ 1311 #define __FUNCT__ "MatPermute_MPIAIJ" 1312 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1313 { 1314 MPI_Comm comm,pcomm; 1315 PetscInt first,local_size,nrows; 1316 const PetscInt *rows; 1317 PetscMPIInt size; 1318 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1319 PetscErrorCode ierr; 1320 1321 PetscFunctionBegin; 1322 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1323 /* make a collective version of 'rowp' */ 1324 ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr); 1325 if (pcomm==comm) { 1326 crowp = rowp; 1327 } else { 1328 ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr); 1329 ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr); 1330 ierr = ISCreateGeneral(comm,nrows,rows,&crowp);CHKERRQ(ierr); 1331 ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr); 1332 } 1333 /* collect the global row permutation and invert it */ 1334 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 1335 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 1336 if (pcomm!=comm) { 1337 ierr = ISDestroy(crowp);CHKERRQ(ierr); 1338 } 1339 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1340 /* get the local target indices */ 1341 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 1342 ierr = MatGetLocalSize(A,&local_size,PETSC_NULL);CHKERRQ(ierr); 1343 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 1344 ierr = ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp);CHKERRQ(ierr); 1345 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 1346 ierr = ISDestroy(irowp);CHKERRQ(ierr); 1347 /* the column permutation is so much easier; 1348 make a local version of 'colp' and invert it */ 1349 ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr); 1350 ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr); 1351 if (size==1) { 1352 lcolp = colp; 1353 } else { 1354 ierr = ISGetSize(colp,&nrows);CHKERRQ(ierr); 1355 ierr = ISGetIndices(colp,&rows);CHKERRQ(ierr); 1356 ierr = ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp);CHKERRQ(ierr); 1357 } 1358 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 1359 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 1360 ierr = ISSetPermutation(icolp);CHKERRQ(ierr); 1361 if (size>1) { 1362 ierr = ISRestoreIndices(colp,&rows);CHKERRQ(ierr); 1363 ierr = ISDestroy(lcolp);CHKERRQ(ierr); 1364 } 1365 /* now we just get the submatrix */ 1366 ierr = MatGetSubMatrix_MPIAIJ_Private(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 1367 /* clean up */ 1368 ierr = ISDestroy(lrowp);CHKERRQ(ierr); 1369 ierr = ISDestroy(icolp);CHKERRQ(ierr); 1370 PetscFunctionReturn(0); 1371 } 1372 1373 #undef __FUNCT__ 1374 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1375 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1376 { 1377 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1378 Mat A = mat->A,B = mat->B; 1379 PetscErrorCode ierr; 1380 PetscReal isend[5],irecv[5]; 1381 1382 PetscFunctionBegin; 1383 info->block_size = 1.0; 1384 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1385 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1386 isend[3] = info->memory; isend[4] = info->mallocs; 1387 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1388 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1389 isend[3] += info->memory; isend[4] += info->mallocs; 1390 if (flag == MAT_LOCAL) { 1391 info->nz_used = isend[0]; 1392 info->nz_allocated = isend[1]; 1393 info->nz_unneeded = isend[2]; 1394 info->memory = isend[3]; 1395 info->mallocs = isend[4]; 1396 } else if (flag == MAT_GLOBAL_MAX) { 1397 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1398 info->nz_used = irecv[0]; 1399 info->nz_allocated = irecv[1]; 1400 info->nz_unneeded = irecv[2]; 1401 info->memory = irecv[3]; 1402 info->mallocs = irecv[4]; 1403 } else if (flag == MAT_GLOBAL_SUM) { 1404 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1405 info->nz_used = irecv[0]; 1406 info->nz_allocated = irecv[1]; 1407 info->nz_unneeded = irecv[2]; 1408 info->memory = irecv[3]; 1409 info->mallocs = irecv[4]; 1410 } 1411 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1412 info->fill_ratio_needed = 0; 1413 info->factor_mallocs = 0; 1414 1415 PetscFunctionReturn(0); 1416 } 1417 1418 #undef __FUNCT__ 1419 #define __FUNCT__ "MatSetOption_MPIAIJ" 1420 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscTruth flg) 1421 { 1422 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1423 PetscErrorCode ierr; 1424 1425 PetscFunctionBegin; 1426 switch (op) { 1427 case MAT_NEW_NONZERO_LOCATIONS: 1428 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1429 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1430 case MAT_KEEP_NONZERO_PATTERN: 1431 case MAT_NEW_NONZERO_LOCATION_ERR: 1432 case MAT_USE_INODES: 1433 case MAT_IGNORE_ZERO_ENTRIES: 1434 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1435 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1436 break; 1437 case MAT_ROW_ORIENTED: 1438 a->roworiented = flg; 1439 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1440 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1441 break; 1442 case MAT_NEW_DIAGONALS: 1443 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1444 break; 1445 case MAT_IGNORE_OFF_PROC_ENTRIES: 1446 a->donotstash = PETSC_TRUE; 1447 break; 1448 case MAT_SYMMETRIC: 1449 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1450 break; 1451 case MAT_STRUCTURALLY_SYMMETRIC: 1452 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1453 break; 1454 case MAT_HERMITIAN: 1455 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1456 break; 1457 case MAT_SYMMETRY_ETERNAL: 1458 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1459 break; 1460 default: 1461 SETERRQ1(PETSC_ERR_SUP,"unknown option %d",op); 1462 } 1463 PetscFunctionReturn(0); 1464 } 1465 1466 #undef __FUNCT__ 1467 #define __FUNCT__ "MatGetRow_MPIAIJ" 1468 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1469 { 1470 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1471 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1472 PetscErrorCode ierr; 1473 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1474 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1475 PetscInt *cmap,*idx_p; 1476 1477 PetscFunctionBegin; 1478 if (mat->getrowactive) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1479 mat->getrowactive = PETSC_TRUE; 1480 1481 if (!mat->rowvalues && (idx || v)) { 1482 /* 1483 allocate enough space to hold information from the longest row. 1484 */ 1485 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1486 PetscInt max = 1,tmp; 1487 for (i=0; i<matin->rmap->n; i++) { 1488 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1489 if (max < tmp) { max = tmp; } 1490 } 1491 ierr = PetscMalloc(max*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);CHKERRQ(ierr); 1492 mat->rowindices = (PetscInt*)(mat->rowvalues + max); 1493 } 1494 1495 if (row < rstart || row >= rend) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Only local rows") 1496 lrow = row - rstart; 1497 1498 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1499 if (!v) {pvA = 0; pvB = 0;} 1500 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1501 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1502 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1503 nztot = nzA + nzB; 1504 1505 cmap = mat->garray; 1506 if (v || idx) { 1507 if (nztot) { 1508 /* Sort by increasing column numbers, assuming A and B already sorted */ 1509 PetscInt imark = -1; 1510 if (v) { 1511 *v = v_p = mat->rowvalues; 1512 for (i=0; i<nzB; i++) { 1513 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1514 else break; 1515 } 1516 imark = i; 1517 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1518 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1519 } 1520 if (idx) { 1521 *idx = idx_p = mat->rowindices; 1522 if (imark > -1) { 1523 for (i=0; i<imark; i++) { 1524 idx_p[i] = cmap[cworkB[i]]; 1525 } 1526 } else { 1527 for (i=0; i<nzB; i++) { 1528 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1529 else break; 1530 } 1531 imark = i; 1532 } 1533 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1534 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1535 } 1536 } else { 1537 if (idx) *idx = 0; 1538 if (v) *v = 0; 1539 } 1540 } 1541 *nz = nztot; 1542 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1543 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1544 PetscFunctionReturn(0); 1545 } 1546 1547 #undef __FUNCT__ 1548 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1549 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1550 { 1551 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1552 1553 PetscFunctionBegin; 1554 if (!aij->getrowactive) { 1555 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1556 } 1557 aij->getrowactive = PETSC_FALSE; 1558 PetscFunctionReturn(0); 1559 } 1560 1561 #undef __FUNCT__ 1562 #define __FUNCT__ "MatNorm_MPIAIJ" 1563 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1564 { 1565 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1566 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1567 PetscErrorCode ierr; 1568 PetscInt i,j,cstart = mat->cmap->rstart; 1569 PetscReal sum = 0.0; 1570 MatScalar *v; 1571 1572 PetscFunctionBegin; 1573 if (aij->size == 1) { 1574 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1575 } else { 1576 if (type == NORM_FROBENIUS) { 1577 v = amat->a; 1578 for (i=0; i<amat->nz; i++) { 1579 #if defined(PETSC_USE_COMPLEX) 1580 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1581 #else 1582 sum += (*v)*(*v); v++; 1583 #endif 1584 } 1585 v = bmat->a; 1586 for (i=0; i<bmat->nz; i++) { 1587 #if defined(PETSC_USE_COMPLEX) 1588 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1589 #else 1590 sum += (*v)*(*v); v++; 1591 #endif 1592 } 1593 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1594 *norm = sqrt(*norm); 1595 } else if (type == NORM_1) { /* max column norm */ 1596 PetscReal *tmp,*tmp2; 1597 PetscInt *jj,*garray = aij->garray; 1598 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1599 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1600 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 1601 *norm = 0.0; 1602 v = amat->a; jj = amat->j; 1603 for (j=0; j<amat->nz; j++) { 1604 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 1605 } 1606 v = bmat->a; jj = bmat->j; 1607 for (j=0; j<bmat->nz; j++) { 1608 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1609 } 1610 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPI_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1611 for (j=0; j<mat->cmap->N; j++) { 1612 if (tmp2[j] > *norm) *norm = tmp2[j]; 1613 } 1614 ierr = PetscFree(tmp);CHKERRQ(ierr); 1615 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1616 } else if (type == NORM_INFINITY) { /* max row norm */ 1617 PetscReal ntemp = 0.0; 1618 for (j=0; j<aij->A->rmap->n; j++) { 1619 v = amat->a + amat->i[j]; 1620 sum = 0.0; 1621 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1622 sum += PetscAbsScalar(*v); v++; 1623 } 1624 v = bmat->a + bmat->i[j]; 1625 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1626 sum += PetscAbsScalar(*v); v++; 1627 } 1628 if (sum > ntemp) ntemp = sum; 1629 } 1630 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPI_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 1631 } else { 1632 SETERRQ(PETSC_ERR_SUP,"No support for two norm"); 1633 } 1634 } 1635 PetscFunctionReturn(0); 1636 } 1637 1638 #undef __FUNCT__ 1639 #define __FUNCT__ "MatTranspose_MPIAIJ" 1640 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1641 { 1642 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1643 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1644 PetscErrorCode ierr; 1645 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i,*d_nnz; 1646 PetscInt cstart=A->cmap->rstart,ncol; 1647 Mat B; 1648 MatScalar *array; 1649 1650 PetscFunctionBegin; 1651 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1652 1653 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; 1654 ai = Aloc->i; aj = Aloc->j; 1655 bi = Bloc->i; bj = Bloc->j; 1656 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1657 /* compute d_nnz for preallocation; o_nnz is approximated by d_nnz to avoid communication */ 1658 ierr = PetscMalloc((1+na)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 1659 ierr = PetscMemzero(d_nnz,(1+na)*sizeof(PetscInt));CHKERRQ(ierr); 1660 for (i=0; i<ai[ma]; i++){ 1661 d_nnz[aj[i]] ++; 1662 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1663 } 1664 1665 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 1666 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1667 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1668 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,d_nnz);CHKERRQ(ierr); 1669 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 1670 } else { 1671 B = *matout; 1672 } 1673 1674 /* copy over the A part */ 1675 array = Aloc->a; 1676 row = A->rmap->rstart; 1677 for (i=0; i<ma; i++) { 1678 ncol = ai[i+1]-ai[i]; 1679 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1680 row++; array += ncol; aj += ncol; 1681 } 1682 aj = Aloc->j; 1683 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 1684 1685 /* copy over the B part */ 1686 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1687 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 1688 array = Bloc->a; 1689 row = A->rmap->rstart; 1690 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 1691 cols_tmp = cols; 1692 for (i=0; i<mb; i++) { 1693 ncol = bi[i+1]-bi[i]; 1694 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 1695 row++; array += ncol; cols_tmp += ncol; 1696 } 1697 ierr = PetscFree(cols);CHKERRQ(ierr); 1698 1699 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1700 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1701 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 1702 *matout = B; 1703 } else { 1704 ierr = MatHeaderCopy(A,B);CHKERRQ(ierr); 1705 } 1706 PetscFunctionReturn(0); 1707 } 1708 1709 #undef __FUNCT__ 1710 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 1711 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 1712 { 1713 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1714 Mat a = aij->A,b = aij->B; 1715 PetscErrorCode ierr; 1716 PetscInt s1,s2,s3; 1717 1718 PetscFunctionBegin; 1719 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1720 if (rr) { 1721 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1722 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1723 /* Overlap communication with computation. */ 1724 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1725 } 1726 if (ll) { 1727 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1728 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1729 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 1730 } 1731 /* scale the diagonal block */ 1732 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1733 1734 if (rr) { 1735 /* Do a scatter end and then right scale the off-diagonal block */ 1736 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1737 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 1738 } 1739 1740 PetscFunctionReturn(0); 1741 } 1742 1743 #undef __FUNCT__ 1744 #define __FUNCT__ "MatSetBlockSize_MPIAIJ" 1745 PetscErrorCode MatSetBlockSize_MPIAIJ(Mat A,PetscInt bs) 1746 { 1747 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1748 PetscErrorCode ierr; 1749 1750 PetscFunctionBegin; 1751 ierr = MatSetBlockSize(a->A,bs);CHKERRQ(ierr); 1752 ierr = MatSetBlockSize(a->B,bs);CHKERRQ(ierr); 1753 PetscFunctionReturn(0); 1754 } 1755 #undef __FUNCT__ 1756 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 1757 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 1758 { 1759 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1760 PetscErrorCode ierr; 1761 1762 PetscFunctionBegin; 1763 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1764 PetscFunctionReturn(0); 1765 } 1766 1767 #undef __FUNCT__ 1768 #define __FUNCT__ "MatEqual_MPIAIJ" 1769 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscTruth *flag) 1770 { 1771 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 1772 Mat a,b,c,d; 1773 PetscTruth flg; 1774 PetscErrorCode ierr; 1775 1776 PetscFunctionBegin; 1777 a = matA->A; b = matA->B; 1778 c = matB->A; d = matB->B; 1779 1780 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1781 if (flg) { 1782 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1783 } 1784 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 1785 PetscFunctionReturn(0); 1786 } 1787 1788 #undef __FUNCT__ 1789 #define __FUNCT__ "MatCopy_MPIAIJ" 1790 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 1791 { 1792 PetscErrorCode ierr; 1793 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 1794 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 1795 1796 PetscFunctionBegin; 1797 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1798 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 1799 /* because of the column compression in the off-processor part of the matrix a->B, 1800 the number of columns in a->B and b->B may be different, hence we cannot call 1801 the MatCopy() directly on the two parts. If need be, we can provide a more 1802 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 1803 then copying the submatrices */ 1804 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1805 } else { 1806 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 1807 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 1808 } 1809 PetscFunctionReturn(0); 1810 } 1811 1812 #undef __FUNCT__ 1813 #define __FUNCT__ "MatSetUpPreallocation_MPIAIJ" 1814 PetscErrorCode MatSetUpPreallocation_MPIAIJ(Mat A) 1815 { 1816 PetscErrorCode ierr; 1817 1818 PetscFunctionBegin; 1819 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1820 PetscFunctionReturn(0); 1821 } 1822 1823 #include "petscblaslapack.h" 1824 #undef __FUNCT__ 1825 #define __FUNCT__ "MatAXPY_MPIAIJ" 1826 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 1827 { 1828 PetscErrorCode ierr; 1829 PetscInt i; 1830 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 1831 PetscBLASInt bnz,one=1; 1832 Mat_SeqAIJ *x,*y; 1833 1834 PetscFunctionBegin; 1835 if (str == SAME_NONZERO_PATTERN) { 1836 PetscScalar alpha = a; 1837 x = (Mat_SeqAIJ *)xx->A->data; 1838 y = (Mat_SeqAIJ *)yy->A->data; 1839 bnz = PetscBLASIntCast(x->nz); 1840 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1841 x = (Mat_SeqAIJ *)xx->B->data; 1842 y = (Mat_SeqAIJ *)yy->B->data; 1843 bnz = PetscBLASIntCast(x->nz); 1844 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 1845 } else if (str == SUBSET_NONZERO_PATTERN) { 1846 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 1847 1848 x = (Mat_SeqAIJ *)xx->B->data; 1849 y = (Mat_SeqAIJ *)yy->B->data; 1850 if (y->xtoy && y->XtoY != xx->B) { 1851 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 1852 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 1853 } 1854 if (!y->xtoy) { /* get xtoy */ 1855 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 1856 y->XtoY = xx->B; 1857 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 1858 } 1859 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 1860 } else { 1861 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 1862 } 1863 PetscFunctionReturn(0); 1864 } 1865 1866 EXTERN PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat); 1867 1868 #undef __FUNCT__ 1869 #define __FUNCT__ "MatConjugate_MPIAIJ" 1870 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_MPIAIJ(Mat mat) 1871 { 1872 #if defined(PETSC_USE_COMPLEX) 1873 PetscErrorCode ierr; 1874 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 1875 1876 PetscFunctionBegin; 1877 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 1878 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 1879 #else 1880 PetscFunctionBegin; 1881 #endif 1882 PetscFunctionReturn(0); 1883 } 1884 1885 #undef __FUNCT__ 1886 #define __FUNCT__ "MatRealPart_MPIAIJ" 1887 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 1888 { 1889 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1890 PetscErrorCode ierr; 1891 1892 PetscFunctionBegin; 1893 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1894 ierr = MatRealPart(a->B);CHKERRQ(ierr); 1895 PetscFunctionReturn(0); 1896 } 1897 1898 #undef __FUNCT__ 1899 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 1900 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 1901 { 1902 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1903 PetscErrorCode ierr; 1904 1905 PetscFunctionBegin; 1906 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1907 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 1908 PetscFunctionReturn(0); 1909 } 1910 1911 #ifdef PETSC_HAVE_PBGL 1912 1913 #include <boost/parallel/mpi/bsp_process_group.hpp> 1914 #include <boost/graph/distributed/ilu_default_graph.hpp> 1915 #include <boost/graph/distributed/ilu_0_block.hpp> 1916 #include <boost/graph/distributed/ilu_preconditioner.hpp> 1917 #include <boost/graph/distributed/petsc/interface.hpp> 1918 #include <boost/multi_array.hpp> 1919 #include <boost/parallel/distributed_property_map->hpp> 1920 1921 #undef __FUNCT__ 1922 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 1923 /* 1924 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1925 */ 1926 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 1927 { 1928 namespace petsc = boost::distributed::petsc; 1929 1930 namespace graph_dist = boost::graph::distributed; 1931 using boost::graph::distributed::ilu_default::process_group_type; 1932 using boost::graph::ilu_permuted; 1933 1934 PetscTruth row_identity, col_identity; 1935 PetscContainer c; 1936 PetscInt m, n, M, N; 1937 PetscErrorCode ierr; 1938 1939 PetscFunctionBegin; 1940 if (info->levels != 0) SETERRQ(PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 1941 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 1942 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 1943 if (!row_identity || !col_identity) { 1944 SETERRQ(PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 1945 } 1946 1947 process_group_type pg; 1948 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1949 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 1950 lgraph_type& level_graph = *lgraph_p; 1951 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 1952 1953 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 1954 ilu_permuted(level_graph); 1955 1956 /* put together the new matrix */ 1957 ierr = MatCreate(((PetscObject)A)->comm, fact);CHKERRQ(ierr); 1958 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 1959 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 1960 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 1961 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 1962 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1963 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1964 1965 ierr = PetscContainerCreate(((PetscObject)A)->comm, &c); 1966 ierr = PetscContainerSetPointer(c, lgraph_p); 1967 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 1968 PetscFunctionReturn(0); 1969 } 1970 1971 #undef __FUNCT__ 1972 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 1973 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 1974 { 1975 PetscFunctionBegin; 1976 PetscFunctionReturn(0); 1977 } 1978 1979 #undef __FUNCT__ 1980 #define __FUNCT__ "MatSolve_MPIAIJ" 1981 /* 1982 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 1983 */ 1984 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 1985 { 1986 namespace graph_dist = boost::graph::distributed; 1987 1988 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 1989 lgraph_type* lgraph_p; 1990 PetscContainer c; 1991 PetscErrorCode ierr; 1992 1993 PetscFunctionBegin; 1994 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 1995 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 1996 ierr = VecCopy(b, x);CHKERRQ(ierr); 1997 1998 PetscScalar* array_x; 1999 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2000 PetscInt sx; 2001 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2002 2003 PetscScalar* array_b; 2004 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2005 PetscInt sb; 2006 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2007 2008 lgraph_type& level_graph = *lgraph_p; 2009 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2010 2011 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2012 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 2013 ref_x(array_x, boost::extents[num_vertices(graph)]); 2014 2015 typedef boost::iterator_property_map<array_ref_type::iterator, 2016 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2017 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 2018 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2019 2020 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2021 2022 PetscFunctionReturn(0); 2023 } 2024 #endif 2025 2026 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 2027 PetscInt nzlocal,nsends,nrecvs; 2028 PetscMPIInt *send_rank; 2029 PetscInt *sbuf_nz,*sbuf_j,**rbuf_j; 2030 PetscScalar *sbuf_a,**rbuf_a; 2031 PetscErrorCode (*MatDestroy)(Mat); 2032 } Mat_Redundant; 2033 2034 #undef __FUNCT__ 2035 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 2036 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 2037 { 2038 PetscErrorCode ierr; 2039 Mat_Redundant *redund=(Mat_Redundant*)ptr; 2040 PetscInt i; 2041 2042 PetscFunctionBegin; 2043 ierr = PetscFree(redund->send_rank);CHKERRQ(ierr); 2044 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2045 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2046 for (i=0; i<redund->nrecvs; i++){ 2047 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2048 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2049 } 2050 ierr = PetscFree3(redund->sbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2051 ierr = PetscFree(redund);CHKERRQ(ierr); 2052 PetscFunctionReturn(0); 2053 } 2054 2055 #undef __FUNCT__ 2056 #define __FUNCT__ "MatDestroy_MatRedundant" 2057 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2058 { 2059 PetscErrorCode ierr; 2060 PetscContainer container; 2061 Mat_Redundant *redund=PETSC_NULL; 2062 2063 PetscFunctionBegin; 2064 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2065 if (container) { 2066 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2067 } else { 2068 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2069 } 2070 A->ops->destroy = redund->MatDestroy; 2071 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 2072 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 2073 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 2074 PetscFunctionReturn(0); 2075 } 2076 2077 #undef __FUNCT__ 2078 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2079 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 2080 { 2081 PetscMPIInt rank,size; 2082 MPI_Comm comm=((PetscObject)mat)->comm; 2083 PetscErrorCode ierr; 2084 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 2085 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 2086 PetscInt *rowrange=mat->rmap->range; 2087 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2088 Mat A=aij->A,B=aij->B,C=*matredundant; 2089 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2090 PetscScalar *sbuf_a; 2091 PetscInt nzlocal=a->nz+b->nz; 2092 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2093 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray,M,N; 2094 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2095 MatScalar *aworkA,*aworkB; 2096 PetscScalar *vals; 2097 PetscMPIInt tag1,tag2,tag3,imdex; 2098 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 2099 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 2100 MPI_Status recv_status,*send_status; 2101 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 2102 PetscInt **rbuf_j=PETSC_NULL; 2103 PetscScalar **rbuf_a=PETSC_NULL; 2104 Mat_Redundant *redund=PETSC_NULL; 2105 PetscContainer container; 2106 2107 PetscFunctionBegin; 2108 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2109 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2110 2111 if (reuse == MAT_REUSE_MATRIX) { 2112 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2113 if (M != N || M != mat->rmap->N) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2114 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 2115 if (M != N || M != mlocal_sub) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 2116 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2117 if (container) { 2118 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2119 } else { 2120 SETERRQ(PETSC_ERR_PLIB,"Container does not exit"); 2121 } 2122 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2123 2124 nsends = redund->nsends; 2125 nrecvs = redund->nrecvs; 2126 send_rank = redund->send_rank; recv_rank = send_rank + size; 2127 sbuf_nz = redund->sbuf_nz; rbuf_nz = sbuf_nz + nsends; 2128 sbuf_j = redund->sbuf_j; 2129 sbuf_a = redund->sbuf_a; 2130 rbuf_j = redund->rbuf_j; 2131 rbuf_a = redund->rbuf_a; 2132 } 2133 2134 if (reuse == MAT_INITIAL_MATRIX){ 2135 PetscMPIInt subrank,subsize; 2136 PetscInt nleftover,np_subcomm; 2137 /* get the destination processors' id send_rank, nsends and nrecvs */ 2138 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2139 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2140 ierr = PetscMalloc((2*size+1)*sizeof(PetscMPIInt),&send_rank); 2141 recv_rank = send_rank + size; 2142 np_subcomm = size/nsubcomm; 2143 nleftover = size - nsubcomm*np_subcomm; 2144 nsends = 0; nrecvs = 0; 2145 for (i=0; i<size; i++){ /* i=rank*/ 2146 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 2147 send_rank[nsends] = i; nsends++; 2148 recv_rank[nrecvs++] = i; 2149 } 2150 } 2151 if (rank >= size - nleftover){/* this proc is a leftover processor */ 2152 i = size-nleftover-1; 2153 j = 0; 2154 while (j < nsubcomm - nleftover){ 2155 send_rank[nsends++] = i; 2156 i--; j++; 2157 } 2158 } 2159 2160 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 2161 for (i=0; i<nleftover; i++){ 2162 recv_rank[nrecvs++] = size-nleftover+i; 2163 } 2164 } 2165 2166 /* allocate sbuf_j, sbuf_a */ 2167 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2168 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2169 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2170 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2171 2172 /* copy mat's local entries into the buffers */ 2173 if (reuse == MAT_INITIAL_MATRIX){ 2174 rownz_max = 0; 2175 rptr = sbuf_j; 2176 cols = sbuf_j + rend-rstart + 1; 2177 vals = sbuf_a; 2178 rptr[0] = 0; 2179 for (i=0; i<rend-rstart; i++){ 2180 row = i + rstart; 2181 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2182 ncols = nzA + nzB; 2183 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2184 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2185 /* load the column indices for this row into cols */ 2186 lwrite = 0; 2187 for (l=0; l<nzB; l++) { 2188 if ((ctmp = bmap[cworkB[l]]) < cstart){ 2189 vals[lwrite] = aworkB[l]; 2190 cols[lwrite++] = ctmp; 2191 } 2192 } 2193 for (l=0; l<nzA; l++){ 2194 vals[lwrite] = aworkA[l]; 2195 cols[lwrite++] = cstart + cworkA[l]; 2196 } 2197 for (l=0; l<nzB; l++) { 2198 if ((ctmp = bmap[cworkB[l]]) >= cend){ 2199 vals[lwrite] = aworkB[l]; 2200 cols[lwrite++] = ctmp; 2201 } 2202 } 2203 vals += ncols; 2204 cols += ncols; 2205 rptr[i+1] = rptr[i] + ncols; 2206 if (rownz_max < ncols) rownz_max = ncols; 2207 } 2208 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); 2209 } else { /* only copy matrix values into sbuf_a */ 2210 rptr = sbuf_j; 2211 vals = sbuf_a; 2212 rptr[0] = 0; 2213 for (i=0; i<rend-rstart; i++){ 2214 row = i + rstart; 2215 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2216 ncols = nzA + nzB; 2217 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2218 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2219 lwrite = 0; 2220 for (l=0; l<nzB; l++) { 2221 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2222 } 2223 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2224 for (l=0; l<nzB; l++) { 2225 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2226 } 2227 vals += ncols; 2228 rptr[i+1] = rptr[i] + ncols; 2229 } 2230 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2231 2232 /* send nzlocal to others, and recv other's nzlocal */ 2233 /*--------------------------------------------------*/ 2234 if (reuse == MAT_INITIAL_MATRIX){ 2235 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2236 s_waits2 = s_waits3 + nsends; 2237 s_waits1 = s_waits2 + nsends; 2238 r_waits1 = s_waits1 + nsends; 2239 r_waits2 = r_waits1 + nrecvs; 2240 r_waits3 = r_waits2 + nrecvs; 2241 } else { 2242 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2243 r_waits3 = s_waits3 + nsends; 2244 } 2245 2246 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2247 if (reuse == MAT_INITIAL_MATRIX){ 2248 /* get new tags to keep the communication clean */ 2249 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2250 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2251 ierr = PetscMalloc3(nsends+nrecvs+1,PetscInt,&sbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2252 rbuf_nz = sbuf_nz + nsends; 2253 2254 /* post receives of other's nzlocal */ 2255 for (i=0; i<nrecvs; i++){ 2256 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2257 } 2258 /* send nzlocal to others */ 2259 for (i=0; i<nsends; i++){ 2260 sbuf_nz[i] = nzlocal; 2261 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2262 } 2263 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2264 count = nrecvs; 2265 while (count) { 2266 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2267 recv_rank[imdex] = recv_status.MPI_SOURCE; 2268 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2269 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2270 2271 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2272 rbuf_nz[imdex] += i + 2; 2273 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2274 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2275 count--; 2276 } 2277 /* wait on sends of nzlocal */ 2278 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2279 /* send mat->i,j to others, and recv from other's */ 2280 /*------------------------------------------------*/ 2281 for (i=0; i<nsends; i++){ 2282 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2283 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2284 } 2285 /* wait on receives of mat->i,j */ 2286 /*------------------------------*/ 2287 count = nrecvs; 2288 while (count) { 2289 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2290 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2291 count--; 2292 } 2293 /* wait on sends of mat->i,j */ 2294 /*---------------------------*/ 2295 if (nsends) { 2296 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2297 } 2298 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2299 2300 /* post receives, send and receive mat->a */ 2301 /*----------------------------------------*/ 2302 for (imdex=0; imdex<nrecvs; imdex++) { 2303 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2304 } 2305 for (i=0; i<nsends; i++){ 2306 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2307 } 2308 count = nrecvs; 2309 while (count) { 2310 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2311 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2312 count--; 2313 } 2314 if (nsends) { 2315 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2316 } 2317 2318 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2319 2320 /* create redundant matrix */ 2321 /*-------------------------*/ 2322 if (reuse == MAT_INITIAL_MATRIX){ 2323 /* compute rownz_max for preallocation */ 2324 for (imdex=0; imdex<nrecvs; imdex++){ 2325 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2326 rptr = rbuf_j[imdex]; 2327 for (i=0; i<j; i++){ 2328 ncols = rptr[i+1] - rptr[i]; 2329 if (rownz_max < ncols) rownz_max = ncols; 2330 } 2331 } 2332 2333 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2334 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2335 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2336 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2337 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2338 } else { 2339 C = *matredundant; 2340 } 2341 2342 /* insert local matrix entries */ 2343 rptr = sbuf_j; 2344 cols = sbuf_j + rend-rstart + 1; 2345 vals = sbuf_a; 2346 for (i=0; i<rend-rstart; i++){ 2347 row = i + rstart; 2348 ncols = rptr[i+1] - rptr[i]; 2349 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2350 vals += ncols; 2351 cols += ncols; 2352 } 2353 /* insert received matrix entries */ 2354 for (imdex=0; imdex<nrecvs; imdex++){ 2355 rstart = rowrange[recv_rank[imdex]]; 2356 rend = rowrange[recv_rank[imdex]+1]; 2357 rptr = rbuf_j[imdex]; 2358 cols = rbuf_j[imdex] + rend-rstart + 1; 2359 vals = rbuf_a[imdex]; 2360 for (i=0; i<rend-rstart; i++){ 2361 row = i + rstart; 2362 ncols = rptr[i+1] - rptr[i]; 2363 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2364 vals += ncols; 2365 cols += ncols; 2366 } 2367 } 2368 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2369 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2370 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2371 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); 2372 if (reuse == MAT_INITIAL_MATRIX){ 2373 PetscContainer container; 2374 *matredundant = C; 2375 /* create a supporting struct and attach it to C for reuse */ 2376 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2377 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2378 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2379 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2380 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2381 2382 redund->nzlocal = nzlocal; 2383 redund->nsends = nsends; 2384 redund->nrecvs = nrecvs; 2385 redund->send_rank = send_rank; 2386 redund->sbuf_nz = sbuf_nz; 2387 redund->sbuf_j = sbuf_j; 2388 redund->sbuf_a = sbuf_a; 2389 redund->rbuf_j = rbuf_j; 2390 redund->rbuf_a = rbuf_a; 2391 2392 redund->MatDestroy = C->ops->destroy; 2393 C->ops->destroy = MatDestroy_MatRedundant; 2394 } 2395 PetscFunctionReturn(0); 2396 } 2397 2398 #undef __FUNCT__ 2399 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2400 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2401 { 2402 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2403 PetscErrorCode ierr; 2404 PetscInt i,*idxb = 0; 2405 PetscScalar *va,*vb; 2406 Vec vtmp; 2407 2408 PetscFunctionBegin; 2409 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2410 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2411 if (idx) { 2412 for (i=0; i<A->rmap->n; i++) { 2413 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2414 } 2415 } 2416 2417 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2418 if (idx) { 2419 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2420 } 2421 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2422 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2423 2424 for (i=0; i<A->rmap->n; i++){ 2425 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2426 va[i] = vb[i]; 2427 if (idx) idx[i] = a->garray[idxb[i]]; 2428 } 2429 } 2430 2431 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2432 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2433 if (idxb) { 2434 ierr = PetscFree(idxb);CHKERRQ(ierr); 2435 } 2436 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 2437 PetscFunctionReturn(0); 2438 } 2439 2440 #undef __FUNCT__ 2441 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2442 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2443 { 2444 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2445 PetscErrorCode ierr; 2446 PetscInt i,*idxb = 0; 2447 PetscScalar *va,*vb; 2448 Vec vtmp; 2449 2450 PetscFunctionBegin; 2451 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2452 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2453 if (idx) { 2454 for (i=0; i<A->cmap->n; i++) { 2455 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2456 } 2457 } 2458 2459 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2460 if (idx) { 2461 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2462 } 2463 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2464 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2465 2466 for (i=0; i<A->rmap->n; i++){ 2467 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2468 va[i] = vb[i]; 2469 if (idx) idx[i] = a->garray[idxb[i]]; 2470 } 2471 } 2472 2473 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2474 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2475 if (idxb) { 2476 ierr = PetscFree(idxb);CHKERRQ(ierr); 2477 } 2478 ierr = VecDestroy(vtmp);CHKERRQ(ierr); 2479 PetscFunctionReturn(0); 2480 } 2481 2482 #undef __FUNCT__ 2483 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2484 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2485 { 2486 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2487 PetscInt n = A->rmap->n; 2488 PetscInt cstart = A->cmap->rstart; 2489 PetscInt *cmap = mat->garray; 2490 PetscInt *diagIdx, *offdiagIdx; 2491 Vec diagV, offdiagV; 2492 PetscScalar *a, *diagA, *offdiagA; 2493 PetscInt r; 2494 PetscErrorCode ierr; 2495 2496 PetscFunctionBegin; 2497 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2498 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2499 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2500 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2501 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2502 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2503 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2504 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2505 for(r = 0; r < n; ++r) { 2506 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2507 a[r] = diagA[r]; 2508 idx[r] = cstart + diagIdx[r]; 2509 } else { 2510 a[r] = offdiagA[r]; 2511 idx[r] = cmap[offdiagIdx[r]]; 2512 } 2513 } 2514 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2515 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2516 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2517 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2518 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2519 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2520 PetscFunctionReturn(0); 2521 } 2522 2523 #undef __FUNCT__ 2524 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2525 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2526 { 2527 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2528 PetscInt n = A->rmap->n; 2529 PetscInt cstart = A->cmap->rstart; 2530 PetscInt *cmap = mat->garray; 2531 PetscInt *diagIdx, *offdiagIdx; 2532 Vec diagV, offdiagV; 2533 PetscScalar *a, *diagA, *offdiagA; 2534 PetscInt r; 2535 PetscErrorCode ierr; 2536 2537 PetscFunctionBegin; 2538 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2539 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2540 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2541 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2542 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2543 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2544 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2545 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2546 for(r = 0; r < n; ++r) { 2547 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2548 a[r] = diagA[r]; 2549 idx[r] = cstart + diagIdx[r]; 2550 } else { 2551 a[r] = offdiagA[r]; 2552 idx[r] = cmap[offdiagIdx[r]]; 2553 } 2554 } 2555 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2556 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2557 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2558 ierr = VecDestroy(diagV);CHKERRQ(ierr); 2559 ierr = VecDestroy(offdiagV);CHKERRQ(ierr); 2560 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2561 PetscFunctionReturn(0); 2562 } 2563 2564 #undef __FUNCT__ 2565 #define __FUNCT__ "MatGetSeqNonzerostructure_MPIAIJ" 2566 PetscErrorCode MatGetSeqNonzerostructure_MPIAIJ(Mat mat,Mat *newmat) 2567 { 2568 PetscErrorCode ierr; 2569 Mat *dummy; 2570 2571 PetscFunctionBegin; 2572 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2573 *newmat = *dummy; 2574 ierr = PetscFree(dummy);CHKERRQ(ierr); 2575 PetscFunctionReturn(0); 2576 } 2577 2578 extern PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2579 /* -------------------------------------------------------------------*/ 2580 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2581 MatGetRow_MPIAIJ, 2582 MatRestoreRow_MPIAIJ, 2583 MatMult_MPIAIJ, 2584 /* 4*/ MatMultAdd_MPIAIJ, 2585 MatMultTranspose_MPIAIJ, 2586 MatMultTransposeAdd_MPIAIJ, 2587 #ifdef PETSC_HAVE_PBGL 2588 MatSolve_MPIAIJ, 2589 #else 2590 0, 2591 #endif 2592 0, 2593 0, 2594 /*10*/ 0, 2595 0, 2596 0, 2597 MatSOR_MPIAIJ, 2598 MatTranspose_MPIAIJ, 2599 /*15*/ MatGetInfo_MPIAIJ, 2600 MatEqual_MPIAIJ, 2601 MatGetDiagonal_MPIAIJ, 2602 MatDiagonalScale_MPIAIJ, 2603 MatNorm_MPIAIJ, 2604 /*20*/ MatAssemblyBegin_MPIAIJ, 2605 MatAssemblyEnd_MPIAIJ, 2606 MatSetOption_MPIAIJ, 2607 MatZeroEntries_MPIAIJ, 2608 /*24*/ MatZeroRows_MPIAIJ, 2609 0, 2610 #ifdef PETSC_HAVE_PBGL 2611 0, 2612 #else 2613 0, 2614 #endif 2615 0, 2616 0, 2617 /*29*/ MatSetUpPreallocation_MPIAIJ, 2618 #ifdef PETSC_HAVE_PBGL 2619 0, 2620 #else 2621 0, 2622 #endif 2623 0, 2624 0, 2625 0, 2626 /*34*/ MatDuplicate_MPIAIJ, 2627 0, 2628 0, 2629 0, 2630 0, 2631 /*39*/ MatAXPY_MPIAIJ, 2632 MatGetSubMatrices_MPIAIJ, 2633 MatIncreaseOverlap_MPIAIJ, 2634 MatGetValues_MPIAIJ, 2635 MatCopy_MPIAIJ, 2636 /*44*/ MatGetRowMax_MPIAIJ, 2637 MatScale_MPIAIJ, 2638 0, 2639 0, 2640 0, 2641 /*49*/ MatSetBlockSize_MPIAIJ, 2642 0, 2643 0, 2644 0, 2645 0, 2646 /*54*/ MatFDColoringCreate_MPIAIJ, 2647 0, 2648 MatSetUnfactored_MPIAIJ, 2649 MatPermute_MPIAIJ, 2650 0, 2651 /*59*/ MatGetSubMatrix_MPIAIJ, 2652 MatDestroy_MPIAIJ, 2653 MatView_MPIAIJ, 2654 0, 2655 0, 2656 /*64*/ 0, 2657 0, 2658 0, 2659 0, 2660 0, 2661 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2662 MatGetRowMinAbs_MPIAIJ, 2663 0, 2664 MatSetColoring_MPIAIJ, 2665 #if defined(PETSC_HAVE_ADIC) 2666 MatSetValuesAdic_MPIAIJ, 2667 #else 2668 0, 2669 #endif 2670 MatSetValuesAdifor_MPIAIJ, 2671 /*75*/ MatFDColoringApply_AIJ, 2672 0, 2673 0, 2674 0, 2675 0, 2676 /*80*/ 0, 2677 0, 2678 0, 2679 /*83*/ MatLoad_MPIAIJ, 2680 0, 2681 0, 2682 0, 2683 0, 2684 0, 2685 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2686 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2687 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2688 MatPtAP_Basic, 2689 MatPtAPSymbolic_MPIAIJ, 2690 /*94*/ MatPtAPNumeric_MPIAIJ, 2691 0, 2692 0, 2693 0, 2694 0, 2695 /*99*/ 0, 2696 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2697 MatPtAPNumeric_MPIAIJ_MPIAIJ, 2698 MatConjugate_MPIAIJ, 2699 0, 2700 /*104*/MatSetValuesRow_MPIAIJ, 2701 MatRealPart_MPIAIJ, 2702 MatImaginaryPart_MPIAIJ, 2703 0, 2704 0, 2705 /*109*/0, 2706 MatGetRedundantMatrix_MPIAIJ, 2707 MatGetRowMin_MPIAIJ, 2708 0, 2709 0, 2710 /*114*/MatGetSeqNonzerostructure_MPIAIJ, 2711 0, 2712 0, 2713 0, 2714 0, 2715 0 2716 }; 2717 2718 /* ----------------------------------------------------------------------------------------*/ 2719 2720 EXTERN_C_BEGIN 2721 #undef __FUNCT__ 2722 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2723 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_MPIAIJ(Mat mat) 2724 { 2725 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2726 PetscErrorCode ierr; 2727 2728 PetscFunctionBegin; 2729 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2730 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2731 PetscFunctionReturn(0); 2732 } 2733 EXTERN_C_END 2734 2735 EXTERN_C_BEGIN 2736 #undef __FUNCT__ 2737 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2738 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_MPIAIJ(Mat mat) 2739 { 2740 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2741 PetscErrorCode ierr; 2742 2743 PetscFunctionBegin; 2744 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2745 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2746 PetscFunctionReturn(0); 2747 } 2748 EXTERN_C_END 2749 2750 #include "petscpc.h" 2751 EXTERN_C_BEGIN 2752 #undef __FUNCT__ 2753 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2754 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2755 { 2756 Mat_MPIAIJ *b; 2757 PetscErrorCode ierr; 2758 PetscInt i; 2759 2760 PetscFunctionBegin; 2761 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 2762 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 2763 if (d_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 2764 if (o_nz < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 2765 2766 ierr = PetscLayoutSetBlockSize(B->rmap,1);CHKERRQ(ierr); 2767 ierr = PetscLayoutSetBlockSize(B->cmap,1);CHKERRQ(ierr); 2768 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2769 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2770 if (d_nnz) { 2771 for (i=0; i<B->rmap->n; i++) { 2772 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]); 2773 } 2774 } 2775 if (o_nnz) { 2776 for (i=0; i<B->rmap->n; i++) { 2777 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]); 2778 } 2779 } 2780 b = (Mat_MPIAIJ*)B->data; 2781 2782 if (!B->preallocated) { 2783 /* Explicitly create 2 MATSEQAIJ matrices. */ 2784 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2785 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2786 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2787 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 2788 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2789 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2790 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2791 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 2792 } 2793 2794 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2795 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2796 B->preallocated = PETSC_TRUE; 2797 PetscFunctionReturn(0); 2798 } 2799 EXTERN_C_END 2800 2801 #undef __FUNCT__ 2802 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2803 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2804 { 2805 Mat mat; 2806 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2807 PetscErrorCode ierr; 2808 2809 PetscFunctionBegin; 2810 *newmat = 0; 2811 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 2812 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2813 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2814 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2815 a = (Mat_MPIAIJ*)mat->data; 2816 2817 mat->factor = matin->factor; 2818 mat->rmap->bs = matin->rmap->bs; 2819 mat->assembled = PETSC_TRUE; 2820 mat->insertmode = NOT_SET_VALUES; 2821 mat->preallocated = PETSC_TRUE; 2822 2823 a->size = oldmat->size; 2824 a->rank = oldmat->rank; 2825 a->donotstash = oldmat->donotstash; 2826 a->roworiented = oldmat->roworiented; 2827 a->rowindices = 0; 2828 a->rowvalues = 0; 2829 a->getrowactive = PETSC_FALSE; 2830 2831 ierr = PetscLayoutCopy(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2832 ierr = PetscLayoutCopy(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2833 2834 ierr = MatStashCreate_Private(((PetscObject)matin)->comm,1,&mat->stash);CHKERRQ(ierr); 2835 if (oldmat->colmap) { 2836 #if defined (PETSC_USE_CTABLE) 2837 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2838 #else 2839 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 2840 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2841 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2842 #endif 2843 } else a->colmap = 0; 2844 if (oldmat->garray) { 2845 PetscInt len; 2846 len = oldmat->B->cmap->n; 2847 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 2848 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2849 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2850 } else a->garray = 0; 2851 2852 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2853 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 2854 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2855 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 2856 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2857 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 2858 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2859 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 2860 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2861 *newmat = mat; 2862 PetscFunctionReturn(0); 2863 } 2864 2865 #include "petscsys.h" 2866 2867 #undef __FUNCT__ 2868 #define __FUNCT__ "MatLoad_MPIAIJ" 2869 PetscErrorCode MatLoad_MPIAIJ(PetscViewer viewer, const MatType type,Mat *newmat) 2870 { 2871 Mat A; 2872 PetscScalar *vals,*svals; 2873 MPI_Comm comm = ((PetscObject)viewer)->comm; 2874 MPI_Status status; 2875 PetscErrorCode ierr; 2876 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,mpicnt,mpimaxnz; 2877 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0; 2878 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2879 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 2880 PetscInt cend,cstart,n,*rowners; 2881 int fd; 2882 2883 PetscFunctionBegin; 2884 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2885 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2886 if (!rank) { 2887 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2888 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 2889 if (header[0] != MAT_FILE_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2890 } 2891 2892 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2893 M = header[1]; N = header[2]; 2894 /* determine ownership of all rows */ 2895 m = M/size + ((M % size) > rank); 2896 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 2897 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2898 2899 /* First process needs enough room for process with most rows */ 2900 if (!rank) { 2901 mmax = rowners[1]; 2902 for (i=2; i<size; i++) { 2903 mmax = PetscMax(mmax,rowners[i]); 2904 } 2905 } else mmax = m; 2906 2907 rowners[0] = 0; 2908 for (i=2; i<=size; i++) { 2909 rowners[i] += rowners[i-1]; 2910 } 2911 rstart = rowners[rank]; 2912 rend = rowners[rank+1]; 2913 2914 /* distribute row lengths to all processors */ 2915 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 2916 if (!rank) { 2917 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2918 ierr = PetscMalloc(m*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 2919 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 2920 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 2921 for (j=0; j<m; j++) { 2922 procsnz[0] += ourlens[j]; 2923 } 2924 for (i=1; i<size; i++) { 2925 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2926 /* calculate the number of nonzeros on each processor */ 2927 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2928 procsnz[i] += rowlengths[j]; 2929 } 2930 mpicnt = PetscMPIIntCast(rowners[i+1]-rowners[i]); 2931 ierr = MPI_Send(rowlengths,mpicnt,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2932 } 2933 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2934 } else { 2935 mpicnt = PetscMPIIntCast(m);CHKERRQ(ierr); 2936 ierr = MPI_Recv(ourlens,mpicnt,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2937 } 2938 2939 if (!rank) { 2940 /* determine max buffer needed and allocate it */ 2941 maxnz = 0; 2942 for (i=0; i<size; i++) { 2943 maxnz = PetscMax(maxnz,procsnz[i]); 2944 } 2945 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2946 2947 /* read in my part of the matrix column indices */ 2948 nz = procsnz[0]; 2949 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2950 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2951 2952 /* read in every one elses and ship off */ 2953 for (i=1; i<size; i++) { 2954 nz = procsnz[i]; 2955 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2956 mpicnt = PetscMPIIntCast(nz); 2957 ierr = MPI_Send(cols,mpicnt,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2958 } 2959 ierr = PetscFree(cols);CHKERRQ(ierr); 2960 } else { 2961 /* determine buffer space needed for message */ 2962 nz = 0; 2963 for (i=0; i<m; i++) { 2964 nz += ourlens[i]; 2965 } 2966 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 2967 2968 /* receive message of column indices*/ 2969 mpicnt = PetscMPIIntCast(nz);CHKERRQ(ierr); 2970 ierr = MPI_Recv(mycols,mpicnt,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 2971 ierr = MPI_Get_count(&status,MPIU_INT,&mpimaxnz);CHKERRQ(ierr); 2972 if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);} 2973 else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);} 2974 else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);} 2975 } 2976 2977 /* determine column ownership if matrix is not square */ 2978 if (N != M) { 2979 n = N/size + ((N % size) > rank); 2980 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 2981 cstart = cend - n; 2982 } else { 2983 cstart = rstart; 2984 cend = rend; 2985 n = cend - cstart; 2986 } 2987 2988 /* loop over local rows, determining number of off diagonal entries */ 2989 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 2990 jj = 0; 2991 for (i=0; i<m; i++) { 2992 for (j=0; j<ourlens[i]; j++) { 2993 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 2994 jj++; 2995 } 2996 } 2997 2998 /* create our matrix */ 2999 for (i=0; i<m; i++) { 3000 ourlens[i] -= offlens[i]; 3001 } 3002 ierr = MatCreate(comm,&A);CHKERRQ(ierr); 3003 ierr = MatSetSizes(A,m,n,M,N);CHKERRQ(ierr); 3004 ierr = MatSetType(A,type);CHKERRQ(ierr); 3005 ierr = MatMPIAIJSetPreallocation(A,0,ourlens,0,offlens);CHKERRQ(ierr); 3006 3007 for (i=0; i<m; i++) { 3008 ourlens[i] += offlens[i]; 3009 } 3010 3011 if (!rank) { 3012 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3013 3014 /* read in my part of the matrix numerical values */ 3015 nz = procsnz[0]; 3016 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3017 3018 /* insert into matrix */ 3019 jj = rstart; 3020 smycols = mycols; 3021 svals = vals; 3022 for (i=0; i<m; i++) { 3023 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3024 smycols += ourlens[i]; 3025 svals += ourlens[i]; 3026 jj++; 3027 } 3028 3029 /* read in other processors and ship out */ 3030 for (i=1; i<size; i++) { 3031 nz = procsnz[i]; 3032 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3033 mpicnt = PetscMPIIntCast(nz); 3034 ierr = MPI_Send(vals,mpicnt,MPIU_SCALAR,i,((PetscObject)A)->tag,comm);CHKERRQ(ierr); 3035 } 3036 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3037 } else { 3038 /* receive numeric values */ 3039 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3040 3041 /* receive message of values*/ 3042 mpicnt = PetscMPIIntCast(nz); 3043 ierr = MPI_Recv(vals,mpicnt,MPIU_SCALAR,0,((PetscObject)A)->tag,comm,&status);CHKERRQ(ierr); 3044 ierr = MPI_Get_count(&status,MPIU_SCALAR,&mpimaxnz);CHKERRQ(ierr); 3045 if (mpimaxnz == MPI_UNDEFINED) {SETERRQ1(PETSC_ERR_LIB,"MPI_Get_count() returned MPI_UNDEFINED, expected %d",mpicnt);} 3046 else if (mpimaxnz < 0) {SETERRQ2(PETSC_ERR_LIB,"MPI_Get_count() returned impossible negative value %d, expected %d",mpimaxnz,mpicnt);} 3047 else if (mpimaxnz != mpicnt) {SETERRQ2(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file: expected %d received %d",mpicnt,mpimaxnz);} 3048 3049 /* insert into matrix */ 3050 jj = rstart; 3051 smycols = mycols; 3052 svals = vals; 3053 for (i=0; i<m; i++) { 3054 ierr = MatSetValues_MPIAIJ(A,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3055 smycols += ourlens[i]; 3056 svals += ourlens[i]; 3057 jj++; 3058 } 3059 } 3060 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3061 ierr = PetscFree(vals);CHKERRQ(ierr); 3062 ierr = PetscFree(mycols);CHKERRQ(ierr); 3063 ierr = PetscFree(rowners);CHKERRQ(ierr); 3064 3065 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3066 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3067 *newmat = A; 3068 PetscFunctionReturn(0); 3069 } 3070 3071 #undef __FUNCT__ 3072 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3073 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3074 { 3075 PetscErrorCode ierr; 3076 IS iscol_local; 3077 PetscInt csize; 3078 3079 PetscFunctionBegin; 3080 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3081 if (call == MAT_REUSE_MATRIX) { 3082 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3083 if (!iscol_local) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3084 } else { 3085 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3086 } 3087 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3088 if (call == MAT_INITIAL_MATRIX) { 3089 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3090 ierr = ISDestroy(iscol_local);CHKERRQ(ierr); 3091 } 3092 PetscFunctionReturn(0); 3093 } 3094 3095 #undef __FUNCT__ 3096 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3097 /* 3098 Not great since it makes two copies of the submatrix, first an SeqAIJ 3099 in local and then by concatenating the local matrices the end result. 3100 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3101 3102 Note: This requires a sequential iscol with all indices. 3103 */ 3104 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3105 { 3106 PetscErrorCode ierr; 3107 PetscMPIInt rank,size; 3108 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j; 3109 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal; 3110 Mat *local,M,Mreuse; 3111 MatScalar *vwork,*aa; 3112 MPI_Comm comm = ((PetscObject)mat)->comm; 3113 Mat_SeqAIJ *aij; 3114 3115 3116 PetscFunctionBegin; 3117 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3118 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3119 3120 if (call == MAT_REUSE_MATRIX) { 3121 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 3122 if (!Mreuse) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3123 local = &Mreuse; 3124 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&local);CHKERRQ(ierr); 3125 } else { 3126 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr); 3127 Mreuse = *local; 3128 ierr = PetscFree(local);CHKERRQ(ierr); 3129 } 3130 3131 /* 3132 m - number of local rows 3133 n - number of columns (same on all processors) 3134 rstart - first row in new global matrix generated 3135 */ 3136 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3137 if (call == MAT_INITIAL_MATRIX) { 3138 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3139 ii = aij->i; 3140 jj = aij->j; 3141 3142 /* 3143 Determine the number of non-zeros in the diagonal and off-diagonal 3144 portions of the matrix in order to do correct preallocation 3145 */ 3146 3147 /* first get start and end of "diagonal" columns */ 3148 if (csize == PETSC_DECIDE) { 3149 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3150 if (mglobal == n) { /* square matrix */ 3151 nlocal = m; 3152 } else { 3153 nlocal = n/size + ((n % size) > rank); 3154 } 3155 } else { 3156 nlocal = csize; 3157 } 3158 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3159 rstart = rend - nlocal; 3160 if (rank == size - 1 && rend != n) { 3161 SETERRQ2(PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3162 } 3163 3164 /* next, compute all the lengths */ 3165 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3166 olens = dlens + m; 3167 for (i=0; i<m; i++) { 3168 jend = ii[i+1] - ii[i]; 3169 olen = 0; 3170 dlen = 0; 3171 for (j=0; j<jend; j++) { 3172 if (*jj < rstart || *jj >= rend) olen++; 3173 else dlen++; 3174 jj++; 3175 } 3176 olens[i] = olen; 3177 dlens[i] = dlen; 3178 } 3179 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3180 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3181 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3182 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3183 ierr = PetscFree(dlens);CHKERRQ(ierr); 3184 } else { 3185 PetscInt ml,nl; 3186 3187 M = *newmat; 3188 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3189 if (ml != m) SETERRQ(PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3190 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3191 /* 3192 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3193 rather than the slower MatSetValues(). 3194 */ 3195 M->was_assembled = PETSC_TRUE; 3196 M->assembled = PETSC_FALSE; 3197 } 3198 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3199 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3200 ii = aij->i; 3201 jj = aij->j; 3202 aa = aij->a; 3203 for (i=0; i<m; i++) { 3204 row = rstart + i; 3205 nz = ii[i+1] - ii[i]; 3206 cwork = jj; jj += nz; 3207 vwork = aa; aa += nz; 3208 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3209 } 3210 3211 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3212 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3213 *newmat = M; 3214 3215 /* save submatrix used in processor for next request */ 3216 if (call == MAT_INITIAL_MATRIX) { 3217 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3218 ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr); 3219 } 3220 3221 PetscFunctionReturn(0); 3222 } 3223 3224 EXTERN_C_BEGIN 3225 #undef __FUNCT__ 3226 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3227 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3228 { 3229 PetscInt m,cstart, cend,j,nnz,i,d; 3230 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3231 const PetscInt *JJ; 3232 PetscScalar *values; 3233 PetscErrorCode ierr; 3234 3235 PetscFunctionBegin; 3236 if (Ii[0]) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3237 3238 ierr = PetscLayoutSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3239 ierr = PetscLayoutSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3240 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3241 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3242 m = B->rmap->n; 3243 cstart = B->cmap->rstart; 3244 cend = B->cmap->rend; 3245 rstart = B->rmap->rstart; 3246 3247 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&d_nnz);CHKERRQ(ierr); 3248 o_nnz = d_nnz + m; 3249 3250 #if defined(PETSC_USE_DEBUGGING) 3251 for (i=0; i<m; i++) { 3252 nnz = Ii[i+1]- Ii[i]; 3253 JJ = J + Ii[i]; 3254 if (nnz < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3255 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3256 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); 3257 } 3258 #endif 3259 3260 for (i=0; i<m; i++) { 3261 nnz = Ii[i+1]- Ii[i]; 3262 JJ = J + Ii[i]; 3263 nnz_max = PetscMax(nnz_max,nnz); 3264 d = 0; 3265 for (j=0; j<nnz; j++) { 3266 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3267 } 3268 d_nnz[i] = d; 3269 o_nnz[i] = nnz - d; 3270 } 3271 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3272 ierr = PetscFree(d_nnz);CHKERRQ(ierr); 3273 3274 if (v) values = (PetscScalar*)v; 3275 else { 3276 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3277 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3278 } 3279 3280 for (i=0; i<m; i++) { 3281 ii = i + rstart; 3282 nnz = Ii[i+1]- Ii[i]; 3283 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3284 } 3285 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3286 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3287 3288 if (!v) { 3289 ierr = PetscFree(values);CHKERRQ(ierr); 3290 } 3291 PetscFunctionReturn(0); 3292 } 3293 EXTERN_C_END 3294 3295 #undef __FUNCT__ 3296 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3297 /*@ 3298 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3299 (the default parallel PETSc format). 3300 3301 Collective on MPI_Comm 3302 3303 Input Parameters: 3304 + B - the matrix 3305 . i - the indices into j for the start of each local row (starts with zero) 3306 . j - the column indices for each local row (starts with zero) 3307 - v - optional values in the matrix 3308 3309 Level: developer 3310 3311 Notes: 3312 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3313 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3314 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3315 3316 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3317 3318 The format which is used for the sparse matrix input, is equivalent to a 3319 row-major ordering.. i.e for the following matrix, the input data expected is 3320 as shown: 3321 3322 1 0 0 3323 2 0 3 P0 3324 ------- 3325 4 5 6 P1 3326 3327 Process0 [P0]: rows_owned=[0,1] 3328 i = {0,1,3} [size = nrow+1 = 2+1] 3329 j = {0,0,2} [size = nz = 6] 3330 v = {1,2,3} [size = nz = 6] 3331 3332 Process1 [P1]: rows_owned=[2] 3333 i = {0,3} [size = nrow+1 = 1+1] 3334 j = {0,1,2} [size = nz = 6] 3335 v = {4,5,6} [size = nz = 6] 3336 3337 .keywords: matrix, aij, compressed row, sparse, parallel 3338 3339 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateMPIAIJ(), MPIAIJ, 3340 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3341 @*/ 3342 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3343 { 3344 PetscErrorCode ierr,(*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3345 3346 PetscFunctionBegin; 3347 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3348 if (f) { 3349 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3350 } 3351 PetscFunctionReturn(0); 3352 } 3353 3354 #undef __FUNCT__ 3355 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3356 /*@C 3357 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3358 (the default parallel PETSc format). For good matrix assembly performance 3359 the user should preallocate the matrix storage by setting the parameters 3360 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3361 performance can be increased by more than a factor of 50. 3362 3363 Collective on MPI_Comm 3364 3365 Input Parameters: 3366 + A - the matrix 3367 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3368 (same value is used for all local rows) 3369 . d_nnz - array containing the number of nonzeros in the various rows of the 3370 DIAGONAL portion of the local submatrix (possibly different for each row) 3371 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3372 The size of this array is equal to the number of local rows, i.e 'm'. 3373 You must leave room for the diagonal entry even if it is zero. 3374 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3375 submatrix (same value is used for all local rows). 3376 - o_nnz - array containing the number of nonzeros in the various rows of the 3377 OFF-DIAGONAL portion of the local submatrix (possibly different for 3378 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3379 structure. The size of this array is equal to the number 3380 of local rows, i.e 'm'. 3381 3382 If the *_nnz parameter is given then the *_nz parameter is ignored 3383 3384 The AIJ format (also called the Yale sparse matrix format or 3385 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3386 storage. The stored row and column indices begin with zero. See the users manual for details. 3387 3388 The parallel matrix is partitioned such that the first m0 rows belong to 3389 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3390 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3391 3392 The DIAGONAL portion of the local submatrix of a processor can be defined 3393 as the submatrix which is obtained by extraction the part corresponding 3394 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 3395 first row that belongs to the processor, and r2 is the last row belonging 3396 to the this processor. This is a square mxm matrix. The remaining portion 3397 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 3398 3399 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3400 3401 You can call MatGetInfo() to get information on how effective the preallocation was; 3402 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3403 You can also run with the option -info and look for messages with the string 3404 malloc in them to see if additional memory allocation was needed. 3405 3406 Example usage: 3407 3408 Consider the following 8x8 matrix with 34 non-zero values, that is 3409 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3410 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3411 as follows: 3412 3413 .vb 3414 1 2 0 | 0 3 0 | 0 4 3415 Proc0 0 5 6 | 7 0 0 | 8 0 3416 9 0 10 | 11 0 0 | 12 0 3417 ------------------------------------- 3418 13 0 14 | 15 16 17 | 0 0 3419 Proc1 0 18 0 | 19 20 21 | 0 0 3420 0 0 0 | 22 23 0 | 24 0 3421 ------------------------------------- 3422 Proc2 25 26 27 | 0 0 28 | 29 0 3423 30 0 0 | 31 32 33 | 0 34 3424 .ve 3425 3426 This can be represented as a collection of submatrices as: 3427 3428 .vb 3429 A B C 3430 D E F 3431 G H I 3432 .ve 3433 3434 Where the submatrices A,B,C are owned by proc0, D,E,F are 3435 owned by proc1, G,H,I are owned by proc2. 3436 3437 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3438 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3439 The 'M','N' parameters are 8,8, and have the same values on all procs. 3440 3441 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3442 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3443 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3444 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3445 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3446 matrix, ans [DF] as another SeqAIJ matrix. 3447 3448 When d_nz, o_nz parameters are specified, d_nz storage elements are 3449 allocated for every row of the local diagonal submatrix, and o_nz 3450 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3451 One way to choose d_nz and o_nz is to use the max nonzerors per local 3452 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3453 In this case, the values of d_nz,o_nz are: 3454 .vb 3455 proc0 : dnz = 2, o_nz = 2 3456 proc1 : dnz = 3, o_nz = 2 3457 proc2 : dnz = 1, o_nz = 4 3458 .ve 3459 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3460 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3461 for proc3. i.e we are using 12+15+10=37 storage locations to store 3462 34 values. 3463 3464 When d_nnz, o_nnz parameters are specified, the storage is specified 3465 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3466 In the above case the values for d_nnz,o_nnz are: 3467 .vb 3468 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3469 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3470 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3471 .ve 3472 Here the space allocated is sum of all the above values i.e 34, and 3473 hence pre-allocation is perfect. 3474 3475 Level: intermediate 3476 3477 .keywords: matrix, aij, compressed row, sparse, parallel 3478 3479 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateMPIAIJ(), MatMPIAIJSetPreallocationCSR(), 3480 MPIAIJ, MatGetInfo() 3481 @*/ 3482 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3483 { 3484 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]); 3485 3486 PetscFunctionBegin; 3487 ierr = PetscObjectQueryFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3488 if (f) { 3489 ierr = (*f)(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3490 } 3491 PetscFunctionReturn(0); 3492 } 3493 3494 #undef __FUNCT__ 3495 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3496 /*@ 3497 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3498 CSR format the local rows. 3499 3500 Collective on MPI_Comm 3501 3502 Input Parameters: 3503 + comm - MPI communicator 3504 . m - number of local rows (Cannot be PETSC_DECIDE) 3505 . n - This value should be the same as the local size used in creating the 3506 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3507 calculated if N is given) For square matrices n is almost always m. 3508 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3509 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3510 . i - row indices 3511 . j - column indices 3512 - a - matrix values 3513 3514 Output Parameter: 3515 . mat - the matrix 3516 3517 Level: intermediate 3518 3519 Notes: 3520 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3521 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3522 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3523 3524 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3525 3526 The format which is used for the sparse matrix input, is equivalent to a 3527 row-major ordering.. i.e for the following matrix, the input data expected is 3528 as shown: 3529 3530 1 0 0 3531 2 0 3 P0 3532 ------- 3533 4 5 6 P1 3534 3535 Process0 [P0]: rows_owned=[0,1] 3536 i = {0,1,3} [size = nrow+1 = 2+1] 3537 j = {0,0,2} [size = nz = 6] 3538 v = {1,2,3} [size = nz = 6] 3539 3540 Process1 [P1]: rows_owned=[2] 3541 i = {0,3} [size = nrow+1 = 1+1] 3542 j = {0,1,2} [size = nz = 6] 3543 v = {4,5,6} [size = nz = 6] 3544 3545 .keywords: matrix, aij, compressed row, sparse, parallel 3546 3547 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3548 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithSplitArrays() 3549 @*/ 3550 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) 3551 { 3552 PetscErrorCode ierr; 3553 3554 PetscFunctionBegin; 3555 if (i[0]) { 3556 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3557 } 3558 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3559 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3560 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3561 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3562 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3563 PetscFunctionReturn(0); 3564 } 3565 3566 #undef __FUNCT__ 3567 #define __FUNCT__ "MatCreateMPIAIJ" 3568 /*@C 3569 MatCreateMPIAIJ - Creates a sparse parallel matrix in AIJ format 3570 (the default parallel PETSc format). For good matrix assembly performance 3571 the user should preallocate the matrix storage by setting the parameters 3572 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3573 performance can be increased by more than a factor of 50. 3574 3575 Collective on MPI_Comm 3576 3577 Input Parameters: 3578 + comm - MPI communicator 3579 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3580 This value should be the same as the local size used in creating the 3581 y vector for the matrix-vector product y = Ax. 3582 . n - This value should be the same as the local size used in creating the 3583 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3584 calculated if N is given) For square matrices n is almost always m. 3585 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3586 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3587 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3588 (same value is used for all local rows) 3589 . d_nnz - array containing the number of nonzeros in the various rows of the 3590 DIAGONAL portion of the local submatrix (possibly different for each row) 3591 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3592 The size of this array is equal to the number of local rows, i.e 'm'. 3593 You must leave room for the diagonal entry even if it is zero. 3594 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3595 submatrix (same value is used for all local rows). 3596 - o_nnz - array containing the number of nonzeros in the various rows of the 3597 OFF-DIAGONAL portion of the local submatrix (possibly different for 3598 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3599 structure. The size of this array is equal to the number 3600 of local rows, i.e 'm'. 3601 3602 Output Parameter: 3603 . A - the matrix 3604 3605 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3606 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3607 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3608 3609 Notes: 3610 If the *_nnz parameter is given then the *_nz parameter is ignored 3611 3612 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3613 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3614 storage requirements for this matrix. 3615 3616 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3617 processor than it must be used on all processors that share the object for 3618 that argument. 3619 3620 The user MUST specify either the local or global matrix dimensions 3621 (possibly both). 3622 3623 The parallel matrix is partitioned across processors such that the 3624 first m0 rows belong to process 0, the next m1 rows belong to 3625 process 1, the next m2 rows belong to process 2 etc.. where 3626 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3627 values corresponding to [m x N] submatrix. 3628 3629 The columns are logically partitioned with the n0 columns belonging 3630 to 0th partition, the next n1 columns belonging to the next 3631 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 3632 3633 The DIAGONAL portion of the local submatrix on any given processor 3634 is the submatrix corresponding to the rows and columns m,n 3635 corresponding to the given processor. i.e diagonal matrix on 3636 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3637 etc. The remaining portion of the local submatrix [m x (N-n)] 3638 constitute the OFF-DIAGONAL portion. The example below better 3639 illustrates this concept. 3640 3641 For a square global matrix we define each processor's diagonal portion 3642 to be its local rows and the corresponding columns (a square submatrix); 3643 each processor's off-diagonal portion encompasses the remainder of the 3644 local matrix (a rectangular submatrix). 3645 3646 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3647 3648 When calling this routine with a single process communicator, a matrix of 3649 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3650 type of communicator, use the construction mechanism: 3651 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3652 3653 By default, this format uses inodes (identical nodes) when possible. 3654 We search for consecutive rows with the same nonzero structure, thereby 3655 reusing matrix information to achieve increased efficiency. 3656 3657 Options Database Keys: 3658 + -mat_no_inode - Do not use inodes 3659 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3660 - -mat_aij_oneindex - Internally use indexing starting at 1 3661 rather than 0. Note that when calling MatSetValues(), 3662 the user still MUST index entries starting at 0! 3663 3664 3665 Example usage: 3666 3667 Consider the following 8x8 matrix with 34 non-zero values, that is 3668 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3669 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3670 as follows: 3671 3672 .vb 3673 1 2 0 | 0 3 0 | 0 4 3674 Proc0 0 5 6 | 7 0 0 | 8 0 3675 9 0 10 | 11 0 0 | 12 0 3676 ------------------------------------- 3677 13 0 14 | 15 16 17 | 0 0 3678 Proc1 0 18 0 | 19 20 21 | 0 0 3679 0 0 0 | 22 23 0 | 24 0 3680 ------------------------------------- 3681 Proc2 25 26 27 | 0 0 28 | 29 0 3682 30 0 0 | 31 32 33 | 0 34 3683 .ve 3684 3685 This can be represented as a collection of submatrices as: 3686 3687 .vb 3688 A B C 3689 D E F 3690 G H I 3691 .ve 3692 3693 Where the submatrices A,B,C are owned by proc0, D,E,F are 3694 owned by proc1, G,H,I are owned by proc2. 3695 3696 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3697 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3698 The 'M','N' parameters are 8,8, and have the same values on all procs. 3699 3700 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3701 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3702 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3703 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3704 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3705 matrix, ans [DF] as another SeqAIJ matrix. 3706 3707 When d_nz, o_nz parameters are specified, d_nz storage elements are 3708 allocated for every row of the local diagonal submatrix, and o_nz 3709 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3710 One way to choose d_nz and o_nz is to use the max nonzerors per local 3711 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3712 In this case, the values of d_nz,o_nz are: 3713 .vb 3714 proc0 : dnz = 2, o_nz = 2 3715 proc1 : dnz = 3, o_nz = 2 3716 proc2 : dnz = 1, o_nz = 4 3717 .ve 3718 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3719 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3720 for proc3. i.e we are using 12+15+10=37 storage locations to store 3721 34 values. 3722 3723 When d_nnz, o_nnz parameters are specified, the storage is specified 3724 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3725 In the above case the values for d_nnz,o_nnz are: 3726 .vb 3727 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3728 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3729 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3730 .ve 3731 Here the space allocated is sum of all the above values i.e 34, and 3732 hence pre-allocation is perfect. 3733 3734 Level: intermediate 3735 3736 .keywords: matrix, aij, compressed row, sparse, parallel 3737 3738 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3739 MPIAIJ, MatCreateMPIAIJWithArrays() 3740 @*/ 3741 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) 3742 { 3743 PetscErrorCode ierr; 3744 PetscMPIInt size; 3745 3746 PetscFunctionBegin; 3747 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3748 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3749 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3750 if (size > 1) { 3751 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3752 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3753 } else { 3754 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3755 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3756 } 3757 PetscFunctionReturn(0); 3758 } 3759 3760 #undef __FUNCT__ 3761 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3762 PetscErrorCode PETSCMAT_DLLEXPORT MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 3763 { 3764 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 3765 3766 PetscFunctionBegin; 3767 *Ad = a->A; 3768 *Ao = a->B; 3769 *colmap = a->garray; 3770 PetscFunctionReturn(0); 3771 } 3772 3773 #undef __FUNCT__ 3774 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3775 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3776 { 3777 PetscErrorCode ierr; 3778 PetscInt i; 3779 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3780 3781 PetscFunctionBegin; 3782 if (coloring->ctype == IS_COLORING_GLOBAL) { 3783 ISColoringValue *allcolors,*colors; 3784 ISColoring ocoloring; 3785 3786 /* set coloring for diagonal portion */ 3787 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3788 3789 /* set coloring for off-diagonal portion */ 3790 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 3791 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3792 for (i=0; i<a->B->cmap->n; i++) { 3793 colors[i] = allcolors[a->garray[i]]; 3794 } 3795 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3796 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3797 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3798 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3799 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3800 ISColoringValue *colors; 3801 PetscInt *larray; 3802 ISColoring ocoloring; 3803 3804 /* set coloring for diagonal portion */ 3805 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3806 for (i=0; i<a->A->cmap->n; i++) { 3807 larray[i] = i + A->cmap->rstart; 3808 } 3809 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3810 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3811 for (i=0; i<a->A->cmap->n; i++) { 3812 colors[i] = coloring->colors[larray[i]]; 3813 } 3814 ierr = PetscFree(larray);CHKERRQ(ierr); 3815 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3816 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3817 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3818 3819 /* set coloring for off-diagonal portion */ 3820 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3821 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 3822 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3823 for (i=0; i<a->B->cmap->n; i++) { 3824 colors[i] = coloring->colors[larray[i]]; 3825 } 3826 ierr = PetscFree(larray);CHKERRQ(ierr); 3827 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3828 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3829 ierr = ISColoringDestroy(ocoloring);CHKERRQ(ierr); 3830 } else { 3831 SETERRQ1(PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3832 } 3833 3834 PetscFunctionReturn(0); 3835 } 3836 3837 #if defined(PETSC_HAVE_ADIC) 3838 #undef __FUNCT__ 3839 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 3840 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 3841 { 3842 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3843 PetscErrorCode ierr; 3844 3845 PetscFunctionBegin; 3846 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 3847 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 3848 PetscFunctionReturn(0); 3849 } 3850 #endif 3851 3852 #undef __FUNCT__ 3853 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3854 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3855 { 3856 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3857 PetscErrorCode ierr; 3858 3859 PetscFunctionBegin; 3860 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3861 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3862 PetscFunctionReturn(0); 3863 } 3864 3865 #undef __FUNCT__ 3866 #define __FUNCT__ "MatMerge" 3867 /*@ 3868 MatMerge - Creates a single large PETSc matrix by concatinating sequential 3869 matrices from each processor 3870 3871 Collective on MPI_Comm 3872 3873 Input Parameters: 3874 + comm - the communicators the parallel matrix will live on 3875 . inmat - the input sequential matrices 3876 . n - number of local columns (or PETSC_DECIDE) 3877 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 3878 3879 Output Parameter: 3880 . outmat - the parallel matrix generated 3881 3882 Level: advanced 3883 3884 Notes: The number of columns of the matrix in EACH processor MUST be the same. 3885 3886 @*/ 3887 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3888 { 3889 PetscErrorCode ierr; 3890 PetscInt m,N,i,rstart,nnz,Ii,*dnz,*onz; 3891 PetscInt *indx; 3892 PetscScalar *values; 3893 3894 PetscFunctionBegin; 3895 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3896 if (scall == MAT_INITIAL_MATRIX){ 3897 /* count nonzeros in each row, for diagonal and off diagonal portion of matrix */ 3898 if (n == PETSC_DECIDE){ 3899 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3900 } 3901 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3902 rstart -= m; 3903 3904 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3905 for (i=0;i<m;i++) { 3906 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3907 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3908 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 3909 } 3910 /* This routine will ONLY return MPIAIJ type matrix */ 3911 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3912 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3913 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3914 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3915 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3916 3917 } else if (scall == MAT_REUSE_MATRIX){ 3918 ierr = MatGetOwnershipRange(*outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 3919 } else { 3920 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 3921 } 3922 3923 for (i=0;i<m;i++) { 3924 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3925 Ii = i + rstart; 3926 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3927 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3928 } 3929 ierr = MatDestroy(inmat);CHKERRQ(ierr); 3930 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3931 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3932 3933 PetscFunctionReturn(0); 3934 } 3935 3936 #undef __FUNCT__ 3937 #define __FUNCT__ "MatFileSplit" 3938 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3939 { 3940 PetscErrorCode ierr; 3941 PetscMPIInt rank; 3942 PetscInt m,N,i,rstart,nnz; 3943 size_t len; 3944 const PetscInt *indx; 3945 PetscViewer out; 3946 char *name; 3947 Mat B; 3948 const PetscScalar *values; 3949 3950 PetscFunctionBegin; 3951 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3952 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3953 /* Should this be the type of the diagonal block of A? */ 3954 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3955 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3956 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3957 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 3958 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3959 for (i=0;i<m;i++) { 3960 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3961 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3962 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3963 } 3964 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3965 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3966 3967 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 3968 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3969 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 3970 sprintf(name,"%s.%d",outfile,rank); 3971 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3972 ierr = PetscFree(name); 3973 ierr = MatView(B,out);CHKERRQ(ierr); 3974 ierr = PetscViewerDestroy(out);CHKERRQ(ierr); 3975 ierr = MatDestroy(B);CHKERRQ(ierr); 3976 PetscFunctionReturn(0); 3977 } 3978 3979 EXTERN PetscErrorCode MatDestroy_MPIAIJ(Mat); 3980 #undef __FUNCT__ 3981 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3982 PetscErrorCode PETSCMAT_DLLEXPORT MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3983 { 3984 PetscErrorCode ierr; 3985 Mat_Merge_SeqsToMPI *merge; 3986 PetscContainer container; 3987 3988 PetscFunctionBegin; 3989 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 3990 if (container) { 3991 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 3992 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3993 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3994 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3995 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3996 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3997 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3998 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3999 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4000 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4001 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4002 ierr = PetscLayoutDestroy(merge->rowmap);CHKERRQ(ierr); 4003 4004 ierr = PetscContainerDestroy(container);CHKERRQ(ierr); 4005 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4006 } 4007 ierr = PetscFree(merge);CHKERRQ(ierr); 4008 4009 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4010 PetscFunctionReturn(0); 4011 } 4012 4013 #include "../src/mat/utils/freespace.h" 4014 #include "petscbt.h" 4015 4016 #undef __FUNCT__ 4017 #define __FUNCT__ "MatMerge_SeqsToMPINumeric" 4018 /*@C 4019 MatMerge_SeqsToMPI - Creates a MPIAIJ matrix by adding sequential 4020 matrices from each processor 4021 4022 Collective on MPI_Comm 4023 4024 Input Parameters: 4025 + comm - the communicators the parallel matrix will live on 4026 . seqmat - the input sequential matrices 4027 . m - number of local rows (or PETSC_DECIDE) 4028 . n - number of local columns (or PETSC_DECIDE) 4029 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4030 4031 Output Parameter: 4032 . mpimat - the parallel matrix generated 4033 4034 Level: advanced 4035 4036 Notes: 4037 The dimensions of the sequential matrix in each processor MUST be the same. 4038 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4039 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4040 @*/ 4041 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPINumeric(Mat seqmat,Mat mpimat) 4042 { 4043 PetscErrorCode ierr; 4044 MPI_Comm comm=((PetscObject)mpimat)->comm; 4045 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4046 PetscMPIInt size,rank,taga,*len_s; 4047 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j; 4048 PetscInt proc,m; 4049 PetscInt **buf_ri,**buf_rj; 4050 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4051 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4052 MPI_Request *s_waits,*r_waits; 4053 MPI_Status *status; 4054 MatScalar *aa=a->a; 4055 MatScalar **abuf_r,*ba_i; 4056 Mat_Merge_SeqsToMPI *merge; 4057 PetscContainer container; 4058 4059 PetscFunctionBegin; 4060 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4061 4062 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4063 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4064 4065 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 4066 if (container) { 4067 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 4068 } 4069 bi = merge->bi; 4070 bj = merge->bj; 4071 buf_ri = merge->buf_ri; 4072 buf_rj = merge->buf_rj; 4073 4074 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4075 owners = merge->rowmap->range; 4076 len_s = merge->len_s; 4077 4078 /* send and recv matrix values */ 4079 /*-----------------------------*/ 4080 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4081 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4082 4083 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4084 for (proc=0,k=0; proc<size; proc++){ 4085 if (!len_s[proc]) continue; 4086 i = owners[proc]; 4087 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4088 k++; 4089 } 4090 4091 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4092 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4093 ierr = PetscFree(status);CHKERRQ(ierr); 4094 4095 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4096 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4097 4098 /* insert mat values of mpimat */ 4099 /*----------------------------*/ 4100 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4101 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4102 nextrow = buf_ri_k + merge->nrecv; 4103 nextai = nextrow + merge->nrecv; 4104 4105 for (k=0; k<merge->nrecv; k++){ 4106 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4107 nrows = *(buf_ri_k[k]); 4108 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4109 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4110 } 4111 4112 /* set values of ba */ 4113 m = merge->rowmap->n; 4114 for (i=0; i<m; i++) { 4115 arow = owners[rank] + i; 4116 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4117 bnzi = bi[i+1] - bi[i]; 4118 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4119 4120 /* add local non-zero vals of this proc's seqmat into ba */ 4121 anzi = ai[arow+1] - ai[arow]; 4122 aj = a->j + ai[arow]; 4123 aa = a->a + ai[arow]; 4124 nextaj = 0; 4125 for (j=0; nextaj<anzi; j++){ 4126 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4127 ba_i[j] += aa[nextaj++]; 4128 } 4129 } 4130 4131 /* add received vals into ba */ 4132 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4133 /* i-th row */ 4134 if (i == *nextrow[k]) { 4135 anzi = *(nextai[k]+1) - *nextai[k]; 4136 aj = buf_rj[k] + *(nextai[k]); 4137 aa = abuf_r[k] + *(nextai[k]); 4138 nextaj = 0; 4139 for (j=0; nextaj<anzi; j++){ 4140 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4141 ba_i[j] += aa[nextaj++]; 4142 } 4143 } 4144 nextrow[k]++; nextai[k]++; 4145 } 4146 } 4147 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4148 } 4149 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4150 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4151 4152 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4153 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4154 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4155 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4156 PetscFunctionReturn(0); 4157 } 4158 4159 #undef __FUNCT__ 4160 #define __FUNCT__ "MatMerge_SeqsToMPISymbolic" 4161 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPISymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4162 { 4163 PetscErrorCode ierr; 4164 Mat B_mpi; 4165 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4166 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4167 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4168 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4169 PetscInt len,proc,*dnz,*onz; 4170 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4171 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4172 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4173 MPI_Status *status; 4174 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 4175 PetscBT lnkbt; 4176 Mat_Merge_SeqsToMPI *merge; 4177 PetscContainer container; 4178 4179 PetscFunctionBegin; 4180 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4181 4182 /* make sure it is a PETSc comm */ 4183 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4184 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4185 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4186 4187 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4188 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4189 4190 /* determine row ownership */ 4191 /*---------------------------------------------------------*/ 4192 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4193 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4194 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4195 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4196 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4197 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4198 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4199 4200 m = merge->rowmap->n; 4201 M = merge->rowmap->N; 4202 owners = merge->rowmap->range; 4203 4204 /* determine the number of messages to send, their lengths */ 4205 /*---------------------------------------------------------*/ 4206 len_s = merge->len_s; 4207 4208 len = 0; /* length of buf_si[] */ 4209 merge->nsend = 0; 4210 for (proc=0; proc<size; proc++){ 4211 len_si[proc] = 0; 4212 if (proc == rank){ 4213 len_s[proc] = 0; 4214 } else { 4215 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4216 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4217 } 4218 if (len_s[proc]) { 4219 merge->nsend++; 4220 nrows = 0; 4221 for (i=owners[proc]; i<owners[proc+1]; i++){ 4222 if (ai[i+1] > ai[i]) nrows++; 4223 } 4224 len_si[proc] = 2*(nrows+1); 4225 len += len_si[proc]; 4226 } 4227 } 4228 4229 /* determine the number and length of messages to receive for ij-structure */ 4230 /*-------------------------------------------------------------------------*/ 4231 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4232 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4233 4234 /* post the Irecv of j-structure */ 4235 /*-------------------------------*/ 4236 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4237 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4238 4239 /* post the Isend of j-structure */ 4240 /*--------------------------------*/ 4241 ierr = PetscMalloc((2*merge->nsend+1)*sizeof(MPI_Request),&si_waits);CHKERRQ(ierr); 4242 sj_waits = si_waits + merge->nsend; 4243 4244 for (proc=0, k=0; proc<size; proc++){ 4245 if (!len_s[proc]) continue; 4246 i = owners[proc]; 4247 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4248 k++; 4249 } 4250 4251 /* receives and sends of j-structure are complete */ 4252 /*------------------------------------------------*/ 4253 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4254 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4255 4256 /* send and recv i-structure */ 4257 /*---------------------------*/ 4258 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4259 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4260 4261 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4262 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4263 for (proc=0,k=0; proc<size; proc++){ 4264 if (!len_s[proc]) continue; 4265 /* form outgoing message for i-structure: 4266 buf_si[0]: nrows to be sent 4267 [1:nrows]: row index (global) 4268 [nrows+1:2*nrows+1]: i-structure index 4269 */ 4270 /*-------------------------------------------*/ 4271 nrows = len_si[proc]/2 - 1; 4272 buf_si_i = buf_si + nrows+1; 4273 buf_si[0] = nrows; 4274 buf_si_i[0] = 0; 4275 nrows = 0; 4276 for (i=owners[proc]; i<owners[proc+1]; i++){ 4277 anzi = ai[i+1] - ai[i]; 4278 if (anzi) { 4279 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4280 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4281 nrows++; 4282 } 4283 } 4284 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4285 k++; 4286 buf_si += len_si[proc]; 4287 } 4288 4289 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4290 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4291 4292 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4293 for (i=0; i<merge->nrecv; i++){ 4294 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); 4295 } 4296 4297 ierr = PetscFree(len_si);CHKERRQ(ierr); 4298 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4299 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4300 ierr = PetscFree(si_waits);CHKERRQ(ierr); 4301 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4302 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4303 ierr = PetscFree(status);CHKERRQ(ierr); 4304 4305 /* compute a local seq matrix in each processor */ 4306 /*----------------------------------------------*/ 4307 /* allocate bi array and free space for accumulating nonzero column info */ 4308 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4309 bi[0] = 0; 4310 4311 /* create and initialize a linked list */ 4312 nlnk = N+1; 4313 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4314 4315 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4316 len = 0; 4317 len = ai[owners[rank+1]] - ai[owners[rank]]; 4318 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4319 current_space = free_space; 4320 4321 /* determine symbolic info for each local row */ 4322 ierr = PetscMalloc((3*merge->nrecv+1)*sizeof(PetscInt**),&buf_ri_k);CHKERRQ(ierr); 4323 nextrow = buf_ri_k + merge->nrecv; 4324 nextai = nextrow + merge->nrecv; 4325 for (k=0; k<merge->nrecv; k++){ 4326 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4327 nrows = *buf_ri_k[k]; 4328 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4329 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4330 } 4331 4332 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4333 len = 0; 4334 for (i=0;i<m;i++) { 4335 bnzi = 0; 4336 /* add local non-zero cols of this proc's seqmat into lnk */ 4337 arow = owners[rank] + i; 4338 anzi = ai[arow+1] - ai[arow]; 4339 aj = a->j + ai[arow]; 4340 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4341 bnzi += nlnk; 4342 /* add received col data into lnk */ 4343 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4344 if (i == *nextrow[k]) { /* i-th row */ 4345 anzi = *(nextai[k]+1) - *nextai[k]; 4346 aj = buf_rj[k] + *nextai[k]; 4347 ierr = PetscLLAdd(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4348 bnzi += nlnk; 4349 nextrow[k]++; nextai[k]++; 4350 } 4351 } 4352 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4353 4354 /* if free space is not available, make more free space */ 4355 if (current_space->local_remaining<bnzi) { 4356 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4357 nspacedouble++; 4358 } 4359 /* copy data into free space, then initialize lnk */ 4360 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4361 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4362 4363 current_space->array += bnzi; 4364 current_space->local_used += bnzi; 4365 current_space->local_remaining -= bnzi; 4366 4367 bi[i+1] = bi[i] + bnzi; 4368 } 4369 4370 ierr = PetscFree(buf_ri_k);CHKERRQ(ierr); 4371 4372 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4373 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4374 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4375 4376 /* create symbolic parallel matrix B_mpi */ 4377 /*---------------------------------------*/ 4378 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4379 if (n==PETSC_DECIDE) { 4380 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4381 } else { 4382 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4383 } 4384 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4385 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4386 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4387 4388 /* B_mpi is not ready for use - assembly will be done by MatMerge_SeqsToMPINumeric() */ 4389 B_mpi->assembled = PETSC_FALSE; 4390 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4391 merge->bi = bi; 4392 merge->bj = bj; 4393 merge->buf_ri = buf_ri; 4394 merge->buf_rj = buf_rj; 4395 merge->coi = PETSC_NULL; 4396 merge->coj = PETSC_NULL; 4397 merge->owners_co = PETSC_NULL; 4398 4399 /* attach the supporting struct to B_mpi for reuse */ 4400 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4401 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4402 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4403 *mpimat = B_mpi; 4404 4405 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4406 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4407 PetscFunctionReturn(0); 4408 } 4409 4410 #undef __FUNCT__ 4411 #define __FUNCT__ "MatMerge_SeqsToMPI" 4412 PetscErrorCode PETSCMAT_DLLEXPORT MatMerge_SeqsToMPI(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4413 { 4414 PetscErrorCode ierr; 4415 4416 PetscFunctionBegin; 4417 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4418 if (scall == MAT_INITIAL_MATRIX){ 4419 ierr = MatMerge_SeqsToMPISymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4420 } 4421 ierr = MatMerge_SeqsToMPINumeric(seqmat,*mpimat);CHKERRQ(ierr); 4422 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4423 PetscFunctionReturn(0); 4424 } 4425 4426 #undef __FUNCT__ 4427 #define __FUNCT__ "MatGetLocalMat" 4428 /*@ 4429 MatGetLocalMat - Creates a SeqAIJ matrix by taking all its local rows 4430 4431 Not Collective 4432 4433 Input Parameters: 4434 + A - the matrix 4435 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4436 4437 Output Parameter: 4438 . A_loc - the local sequential matrix generated 4439 4440 Level: developer 4441 4442 @*/ 4443 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4444 { 4445 PetscErrorCode ierr; 4446 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4447 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 4448 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 4449 MatScalar *aa=a->a,*ba=b->a,*cam; 4450 PetscScalar *ca; 4451 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4452 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4453 4454 PetscFunctionBegin; 4455 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4456 if (scall == MAT_INITIAL_MATRIX){ 4457 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 4458 ci[0] = 0; 4459 for (i=0; i<am; i++){ 4460 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4461 } 4462 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 4463 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 4464 k = 0; 4465 for (i=0; i<am; i++) { 4466 ncols_o = bi[i+1] - bi[i]; 4467 ncols_d = ai[i+1] - ai[i]; 4468 /* off-diagonal portion of A */ 4469 for (jo=0; jo<ncols_o; jo++) { 4470 col = cmap[*bj]; 4471 if (col >= cstart) break; 4472 cj[k] = col; bj++; 4473 ca[k++] = *ba++; 4474 } 4475 /* diagonal portion of A */ 4476 for (j=0; j<ncols_d; j++) { 4477 cj[k] = cstart + *aj++; 4478 ca[k++] = *aa++; 4479 } 4480 /* off-diagonal portion of A */ 4481 for (j=jo; j<ncols_o; j++) { 4482 cj[k] = cmap[*bj++]; 4483 ca[k++] = *ba++; 4484 } 4485 } 4486 /* put together the new matrix */ 4487 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4488 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4489 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4490 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4491 mat->free_a = PETSC_TRUE; 4492 mat->free_ij = PETSC_TRUE; 4493 mat->nonew = 0; 4494 } else if (scall == MAT_REUSE_MATRIX){ 4495 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4496 ci = mat->i; cj = mat->j; cam = mat->a; 4497 for (i=0; i<am; i++) { 4498 /* off-diagonal portion of A */ 4499 ncols_o = bi[i+1] - bi[i]; 4500 for (jo=0; jo<ncols_o; jo++) { 4501 col = cmap[*bj]; 4502 if (col >= cstart) break; 4503 *cam++ = *ba++; bj++; 4504 } 4505 /* diagonal portion of A */ 4506 ncols_d = ai[i+1] - ai[i]; 4507 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4508 /* off-diagonal portion of A */ 4509 for (j=jo; j<ncols_o; j++) { 4510 *cam++ = *ba++; bj++; 4511 } 4512 } 4513 } else { 4514 SETERRQ1(PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4515 } 4516 4517 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4518 PetscFunctionReturn(0); 4519 } 4520 4521 #undef __FUNCT__ 4522 #define __FUNCT__ "MatGetLocalMatCondensed" 4523 /*@C 4524 MatGetLocalMatCondensed - Creates a SeqAIJ matrix by taking all its local rows and NON-ZERO columns 4525 4526 Not Collective 4527 4528 Input Parameters: 4529 + A - the matrix 4530 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4531 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 4532 4533 Output Parameter: 4534 . A_loc - the local sequential matrix generated 4535 4536 Level: developer 4537 4538 @*/ 4539 PetscErrorCode PETSCMAT_DLLEXPORT MatGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4540 { 4541 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4542 PetscErrorCode ierr; 4543 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4544 IS isrowa,iscola; 4545 Mat *aloc; 4546 4547 PetscFunctionBegin; 4548 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4549 if (!row){ 4550 start = A->rmap->rstart; end = A->rmap->rend; 4551 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4552 } else { 4553 isrowa = *row; 4554 } 4555 if (!col){ 4556 start = A->cmap->rstart; 4557 cmap = a->garray; 4558 nzA = a->A->cmap->n; 4559 nzB = a->B->cmap->n; 4560 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4561 ncols = 0; 4562 for (i=0; i<nzB; i++) { 4563 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4564 else break; 4565 } 4566 imark = i; 4567 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4568 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4569 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&iscola);CHKERRQ(ierr); 4570 ierr = PetscFree(idx);CHKERRQ(ierr); 4571 } else { 4572 iscola = *col; 4573 } 4574 if (scall != MAT_INITIAL_MATRIX){ 4575 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4576 aloc[0] = *A_loc; 4577 } 4578 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4579 *A_loc = aloc[0]; 4580 ierr = PetscFree(aloc);CHKERRQ(ierr); 4581 if (!row){ 4582 ierr = ISDestroy(isrowa);CHKERRQ(ierr); 4583 } 4584 if (!col){ 4585 ierr = ISDestroy(iscola);CHKERRQ(ierr); 4586 } 4587 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4588 PetscFunctionReturn(0); 4589 } 4590 4591 #undef __FUNCT__ 4592 #define __FUNCT__ "MatGetBrowsOfAcols" 4593 /*@C 4594 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4595 4596 Collective on Mat 4597 4598 Input Parameters: 4599 + A,B - the matrices in mpiaij format 4600 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4601 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 4602 4603 Output Parameter: 4604 + rowb, colb - index sets of rows and columns of B to extract 4605 . brstart - row index of B_seq from which next B->rmap->n rows are taken from B's local rows 4606 - B_seq - the sequential matrix generated 4607 4608 Level: developer 4609 4610 @*/ 4611 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,PetscInt *brstart,Mat *B_seq) 4612 { 4613 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4614 PetscErrorCode ierr; 4615 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4616 IS isrowb,iscolb; 4617 Mat *bseq; 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_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4624 4625 if (scall == MAT_INITIAL_MATRIX){ 4626 start = A->cmap->rstart; 4627 cmap = a->garray; 4628 nzA = a->A->cmap->n; 4629 nzB = a->B->cmap->n; 4630 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 4631 ncols = 0; 4632 for (i=0; i<nzB; i++) { /* row < local row index */ 4633 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4634 else break; 4635 } 4636 imark = i; 4637 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4638 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4639 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,&isrowb);CHKERRQ(ierr); 4640 ierr = PetscFree(idx);CHKERRQ(ierr); 4641 *brstart = imark; 4642 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4643 } else { 4644 if (!rowb || !colb) SETERRQ(PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4645 isrowb = *rowb; iscolb = *colb; 4646 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4647 bseq[0] = *B_seq; 4648 } 4649 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4650 *B_seq = bseq[0]; 4651 ierr = PetscFree(bseq);CHKERRQ(ierr); 4652 if (!rowb){ 4653 ierr = ISDestroy(isrowb);CHKERRQ(ierr); 4654 } else { 4655 *rowb = isrowb; 4656 } 4657 if (!colb){ 4658 ierr = ISDestroy(iscolb);CHKERRQ(ierr); 4659 } else { 4660 *colb = iscolb; 4661 } 4662 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4663 PetscFunctionReturn(0); 4664 } 4665 4666 #undef __FUNCT__ 4667 #define __FUNCT__ "MatGetBrowsOfAoCols" 4668 /*@C 4669 MatGetBrowsOfAoCols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4670 of the OFF-DIAGONAL portion of local A 4671 4672 Collective on Mat 4673 4674 Input Parameters: 4675 + A,B - the matrices in mpiaij format 4676 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4677 . startsj - starting point in B's sending and receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 4678 - bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 4679 4680 Output Parameter: 4681 + B_oth - the sequential matrix generated 4682 4683 Level: developer 4684 4685 @*/ 4686 PetscErrorCode PETSCMAT_DLLEXPORT MatGetBrowsOfAoCols(Mat A,Mat B,MatReuse scall,PetscInt **startsj,MatScalar **bufa_ptr,Mat *B_oth) 4687 { 4688 VecScatter_MPI_General *gen_to,*gen_from; 4689 PetscErrorCode ierr; 4690 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4691 Mat_SeqAIJ *b_oth; 4692 VecScatter ctx=a->Mvctx; 4693 MPI_Comm comm=((PetscObject)ctx)->comm; 4694 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4695 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4696 PetscScalar *rvalues,*svalues; 4697 MatScalar *b_otha,*bufa,*bufA; 4698 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4699 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 4700 MPI_Status *sstatus,rstatus; 4701 PetscMPIInt jj; 4702 PetscInt *cols,sbs,rbs; 4703 PetscScalar *vals; 4704 4705 PetscFunctionBegin; 4706 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 4707 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); 4708 } 4709 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4710 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4711 4712 gen_to = (VecScatter_MPI_General*)ctx->todata; 4713 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4714 rvalues = gen_from->values; /* holds the length of receiving row */ 4715 svalues = gen_to->values; /* holds the length of sending row */ 4716 nrecvs = gen_from->n; 4717 nsends = gen_to->n; 4718 4719 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 4720 srow = gen_to->indices; /* local row index to be sent */ 4721 sstarts = gen_to->starts; 4722 sprocs = gen_to->procs; 4723 sstatus = gen_to->sstatus; 4724 sbs = gen_to->bs; 4725 rstarts = gen_from->starts; 4726 rprocs = gen_from->procs; 4727 rbs = gen_from->bs; 4728 4729 if (!startsj || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4730 if (scall == MAT_INITIAL_MATRIX){ 4731 /* i-array */ 4732 /*---------*/ 4733 /* post receives */ 4734 for (i=0; i<nrecvs; i++){ 4735 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4736 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4737 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4738 } 4739 4740 /* pack the outgoing message */ 4741 ierr = PetscMalloc((nsends+nrecvs+3)*sizeof(PetscInt),&sstartsj);CHKERRQ(ierr); 4742 rstartsj = sstartsj + nsends +1; 4743 sstartsj[0] = 0; rstartsj[0] = 0; 4744 len = 0; /* total length of j or a array to be sent */ 4745 k = 0; 4746 for (i=0; i<nsends; i++){ 4747 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4748 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4749 for (j=0; j<nrows; j++) { 4750 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4751 for (l=0; l<sbs; l++){ 4752 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 4753 rowlen[j*sbs+l] = ncols; 4754 len += ncols; 4755 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 4756 } 4757 k++; 4758 } 4759 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4760 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4761 } 4762 /* recvs and sends of i-array are completed */ 4763 i = nrecvs; 4764 while (i--) { 4765 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4766 } 4767 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4768 4769 /* allocate buffers for sending j and a arrays */ 4770 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 4771 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 4772 4773 /* create i-array of B_oth */ 4774 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 4775 b_othi[0] = 0; 4776 len = 0; /* total length of j or a array to be received */ 4777 k = 0; 4778 for (i=0; i<nrecvs; i++){ 4779 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4780 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4781 for (j=0; j<nrows; j++) { 4782 b_othi[k+1] = b_othi[k] + rowlen[j]; 4783 len += rowlen[j]; k++; 4784 } 4785 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4786 } 4787 4788 /* allocate space for j and a arrrays of B_oth */ 4789 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 4790 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 4791 4792 /* j-array */ 4793 /*---------*/ 4794 /* post receives of j-array */ 4795 for (i=0; i<nrecvs; i++){ 4796 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4797 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4798 } 4799 4800 /* pack the outgoing message j-array */ 4801 k = 0; 4802 for (i=0; i<nsends; i++){ 4803 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4804 bufJ = bufj+sstartsj[i]; 4805 for (j=0; j<nrows; j++) { 4806 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4807 for (ll=0; ll<sbs; ll++){ 4808 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4809 for (l=0; l<ncols; l++){ 4810 *bufJ++ = cols[l]; 4811 } 4812 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 4813 } 4814 } 4815 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4816 } 4817 4818 /* recvs and sends of j-array are completed */ 4819 i = nrecvs; 4820 while (i--) { 4821 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4822 } 4823 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4824 } else if (scall == MAT_REUSE_MATRIX){ 4825 sstartsj = *startsj; 4826 rstartsj = sstartsj + nsends +1; 4827 bufa = *bufa_ptr; 4828 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4829 b_otha = b_oth->a; 4830 } else { 4831 SETERRQ(PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4832 } 4833 4834 /* a-array */ 4835 /*---------*/ 4836 /* post receives of a-array */ 4837 for (i=0; i<nrecvs; i++){ 4838 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4839 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4840 } 4841 4842 /* pack the outgoing message a-array */ 4843 k = 0; 4844 for (i=0; i<nsends; i++){ 4845 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4846 bufA = bufa+sstartsj[i]; 4847 for (j=0; j<nrows; j++) { 4848 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4849 for (ll=0; ll<sbs; ll++){ 4850 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4851 for (l=0; l<ncols; l++){ 4852 *bufA++ = vals[l]; 4853 } 4854 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 4855 } 4856 } 4857 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4858 } 4859 /* recvs and sends of a-array are completed */ 4860 i = nrecvs; 4861 while (i--) { 4862 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4863 } 4864 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4865 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4866 4867 if (scall == MAT_INITIAL_MATRIX){ 4868 /* put together the new matrix */ 4869 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4870 4871 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4872 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4873 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 4874 b_oth->free_a = PETSC_TRUE; 4875 b_oth->free_ij = PETSC_TRUE; 4876 b_oth->nonew = 0; 4877 4878 ierr = PetscFree(bufj);CHKERRQ(ierr); 4879 if (!startsj || !bufa_ptr){ 4880 ierr = PetscFree(sstartsj);CHKERRQ(ierr); 4881 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4882 } else { 4883 *startsj = sstartsj; 4884 *bufa_ptr = bufa; 4885 } 4886 } 4887 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4888 PetscFunctionReturn(0); 4889 } 4890 4891 #undef __FUNCT__ 4892 #define __FUNCT__ "MatGetCommunicationStructs" 4893 /*@C 4894 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4895 4896 Not Collective 4897 4898 Input Parameters: 4899 . A - The matrix in mpiaij format 4900 4901 Output Parameter: 4902 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4903 . colmap - A map from global column index to local index into lvec 4904 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4905 4906 Level: developer 4907 4908 @*/ 4909 #if defined (PETSC_USE_CTABLE) 4910 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4911 #else 4912 PetscErrorCode PETSCMAT_DLLEXPORT MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4913 #endif 4914 { 4915 Mat_MPIAIJ *a; 4916 4917 PetscFunctionBegin; 4918 PetscValidHeaderSpecific(A, MAT_COOKIE, 1); 4919 PetscValidPointer(lvec, 2) 4920 PetscValidPointer(colmap, 3) 4921 PetscValidPointer(multScatter, 4) 4922 a = (Mat_MPIAIJ *) A->data; 4923 if (lvec) *lvec = a->lvec; 4924 if (colmap) *colmap = a->colmap; 4925 if (multScatter) *multScatter = a->Mvctx; 4926 PetscFunctionReturn(0); 4927 } 4928 4929 EXTERN_C_BEGIN 4930 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICRL(Mat,const MatType,MatReuse,Mat*); 4931 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_MPIAIJ_MPICSRPERM(Mat,const MatType,MatReuse,Mat*); 4932 EXTERN_C_END 4933 4934 #undef __FUNCT__ 4935 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4936 /* 4937 Computes (B'*A')' since computing B*A directly is untenable 4938 4939 n p p 4940 ( ) ( ) ( ) 4941 m ( A ) * n ( B ) = m ( C ) 4942 ( ) ( ) ( ) 4943 4944 */ 4945 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4946 { 4947 PetscErrorCode ierr; 4948 Mat At,Bt,Ct; 4949 4950 PetscFunctionBegin; 4951 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4952 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4953 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4954 ierr = MatDestroy(At);CHKERRQ(ierr); 4955 ierr = MatDestroy(Bt);CHKERRQ(ierr); 4956 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4957 ierr = MatDestroy(Ct);CHKERRQ(ierr); 4958 PetscFunctionReturn(0); 4959 } 4960 4961 #undef __FUNCT__ 4962 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 4963 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4964 { 4965 PetscErrorCode ierr; 4966 PetscInt m=A->rmap->n,n=B->cmap->n; 4967 Mat Cmat; 4968 4969 PetscFunctionBegin; 4970 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); 4971 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 4972 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4973 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 4974 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 4975 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4976 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4977 *C = Cmat; 4978 PetscFunctionReturn(0); 4979 } 4980 4981 /* ----------------------------------------------------------------*/ 4982 #undef __FUNCT__ 4983 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 4984 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4985 { 4986 PetscErrorCode ierr; 4987 4988 PetscFunctionBegin; 4989 if (scall == MAT_INITIAL_MATRIX){ 4990 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 4991 } 4992 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 4993 PetscFunctionReturn(0); 4994 } 4995 4996 EXTERN_C_BEGIN 4997 #if defined(PETSC_HAVE_MUMPS) 4998 extern PetscErrorCode MatGetFactor_mpiaij_mumps(Mat,MatFactorType,Mat*); 4999 #endif 5000 #if defined(PETSC_HAVE_PASTIX) 5001 extern PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5002 #endif 5003 #if defined(PETSC_HAVE_SUPERLU_DIST) 5004 extern PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5005 #endif 5006 #if defined(PETSC_HAVE_SPOOLES) 5007 extern PetscErrorCode MatGetFactor_mpiaij_spooles(Mat,MatFactorType,Mat*); 5008 #endif 5009 EXTERN_C_END 5010 5011 /*MC 5012 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5013 5014 Options Database Keys: 5015 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5016 5017 Level: beginner 5018 5019 .seealso: MatCreateMPIAIJ() 5020 M*/ 5021 5022 EXTERN_C_BEGIN 5023 #undef __FUNCT__ 5024 #define __FUNCT__ "MatCreate_MPIAIJ" 5025 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_MPIAIJ(Mat B) 5026 { 5027 Mat_MPIAIJ *b; 5028 PetscErrorCode ierr; 5029 PetscMPIInt size; 5030 5031 PetscFunctionBegin; 5032 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 5033 5034 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5035 B->data = (void*)b; 5036 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5037 B->rmap->bs = 1; 5038 B->assembled = PETSC_FALSE; 5039 B->mapping = 0; 5040 5041 B->insertmode = NOT_SET_VALUES; 5042 b->size = size; 5043 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 5044 5045 /* build cache for off array entries formed */ 5046 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 5047 b->donotstash = PETSC_FALSE; 5048 b->colmap = 0; 5049 b->garray = 0; 5050 b->roworiented = PETSC_TRUE; 5051 5052 /* stuff used for matrix vector multiply */ 5053 b->lvec = PETSC_NULL; 5054 b->Mvctx = PETSC_NULL; 5055 5056 /* stuff for MatGetRow() */ 5057 b->rowindices = 0; 5058 b->rowvalues = 0; 5059 b->getrowactive = PETSC_FALSE; 5060 5061 #if defined(PETSC_HAVE_SPOOLES) 5062 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C", 5063 "MatGetFactor_mpiaij_spooles", 5064 MatGetFactor_mpiaij_spooles);CHKERRQ(ierr); 5065 #endif 5066 #if defined(PETSC_HAVE_MUMPS) 5067 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 5068 "MatGetFactor_mpiaij_mumps", 5069 MatGetFactor_mpiaij_mumps);CHKERRQ(ierr); 5070 #endif 5071 #if defined(PETSC_HAVE_PASTIX) 5072 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 5073 "MatGetFactor_mpiaij_pastix", 5074 MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5075 #endif 5076 #if defined(PETSC_HAVE_SUPERLU_DIST) 5077 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C", 5078 "MatGetFactor_mpiaij_superlu_dist", 5079 MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5080 #endif 5081 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 5082 "MatStoreValues_MPIAIJ", 5083 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5084 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 5085 "MatRetrieveValues_MPIAIJ", 5086 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5087 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 5088 "MatGetDiagonalBlock_MPIAIJ", 5089 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5090 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 5091 "MatIsTranspose_MPIAIJ", 5092 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5093 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 5094 "MatMPIAIJSetPreallocation_MPIAIJ", 5095 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5096 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 5097 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 5098 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5099 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 5100 "MatDiagonalScaleLocal_MPIAIJ", 5101 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5102 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicsrperm_C", 5103 "MatConvert_MPIAIJ_MPICSRPERM", 5104 MatConvert_MPIAIJ_MPICSRPERM);CHKERRQ(ierr); 5105 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpicrl_C", 5106 "MatConvert_MPIAIJ_MPICRL", 5107 MatConvert_MPIAIJ_MPICRL);CHKERRQ(ierr); 5108 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C", 5109 "MatConvert_MPIAIJ_MPISBAIJ", 5110 MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5111 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 5112 "MatMatMult_MPIDense_MPIAIJ", 5113 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5114 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 5115 "MatMatMultSymbolic_MPIDense_MPIAIJ", 5116 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5117 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 5118 "MatMatMultNumeric_MPIDense_MPIAIJ", 5119 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5120 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5121 PetscFunctionReturn(0); 5122 } 5123 EXTERN_C_END 5124 5125 #undef __FUNCT__ 5126 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5127 /*@ 5128 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5129 and "off-diagonal" part of the matrix in CSR format. 5130 5131 Collective on MPI_Comm 5132 5133 Input Parameters: 5134 + comm - MPI communicator 5135 . m - number of local rows (Cannot be PETSC_DECIDE) 5136 . n - This value should be the same as the local size used in creating the 5137 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5138 calculated if N is given) For square matrices n is almost always m. 5139 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5140 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5141 . i - row indices for "diagonal" portion of matrix 5142 . j - column indices 5143 . a - matrix values 5144 . oi - row indices for "off-diagonal" portion of matrix 5145 . oj - column indices 5146 - oa - matrix values 5147 5148 Output Parameter: 5149 . mat - the matrix 5150 5151 Level: advanced 5152 5153 Notes: 5154 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. 5155 5156 The i and j indices are 0 based 5157 5158 See MatCreateMPIAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5159 5160 This sets local rows and cannot be used to set off-processor values. 5161 5162 You cannot later use MatSetValues() to change values in this matrix. 5163 5164 .keywords: matrix, aij, compressed row, sparse, parallel 5165 5166 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5167 MPIAIJ, MatCreateMPIAIJ(), MatCreateMPIAIJWithArrays() 5168 @*/ 5169 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 5170 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5171 { 5172 PetscErrorCode ierr; 5173 Mat_MPIAIJ *maij; 5174 5175 PetscFunctionBegin; 5176 if (m < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5177 if (i[0]) { 5178 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5179 } 5180 if (oi[0]) { 5181 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5182 } 5183 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5184 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5185 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5186 maij = (Mat_MPIAIJ*) (*mat)->data; 5187 maij->donotstash = PETSC_TRUE; 5188 (*mat)->preallocated = PETSC_TRUE; 5189 5190 ierr = PetscLayoutSetBlockSize((*mat)->rmap,1);CHKERRQ(ierr); 5191 ierr = PetscLayoutSetBlockSize((*mat)->cmap,1);CHKERRQ(ierr); 5192 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5193 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5194 5195 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5196 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5197 5198 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5199 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5200 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5201 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5202 5203 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5204 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5205 PetscFunctionReturn(0); 5206 } 5207 5208 /* 5209 Special version for direct calls from Fortran 5210 */ 5211 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5212 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5213 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5214 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5215 #endif 5216 5217 /* Change these macros so can be used in void function */ 5218 #undef CHKERRQ 5219 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5220 #undef SETERRQ2 5221 #define SETERRQ2(ierr,b,c,d) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5222 #undef SETERRQ 5223 #define SETERRQ(ierr,b) CHKERRABORT(((PetscObject)mat)->comm,ierr) 5224 5225 EXTERN_C_BEGIN 5226 #undef __FUNCT__ 5227 #define __FUNCT__ "matsetvaluesmpiaij_" 5228 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5229 { 5230 Mat mat = *mmat; 5231 PetscInt m = *mm, n = *mn; 5232 InsertMode addv = *maddv; 5233 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5234 PetscScalar value; 5235 PetscErrorCode ierr; 5236 5237 ierr = MatPreallocated(mat);CHKERRQ(ierr); 5238 if (mat->insertmode == NOT_SET_VALUES) { 5239 mat->insertmode = addv; 5240 } 5241 #if defined(PETSC_USE_DEBUG) 5242 else if (mat->insertmode != addv) { 5243 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5244 } 5245 #endif 5246 { 5247 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5248 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5249 PetscTruth roworiented = aij->roworiented; 5250 5251 /* Some Variables required in the macro */ 5252 Mat A = aij->A; 5253 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5254 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5255 MatScalar *aa = a->a; 5256 PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5257 Mat B = aij->B; 5258 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5259 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5260 MatScalar *ba = b->a; 5261 5262 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5263 PetscInt nonew = a->nonew; 5264 MatScalar *ap1,*ap2; 5265 5266 PetscFunctionBegin; 5267 for (i=0; i<m; i++) { 5268 if (im[i] < 0) continue; 5269 #if defined(PETSC_USE_DEBUG) 5270 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5271 #endif 5272 if (im[i] >= rstart && im[i] < rend) { 5273 row = im[i] - rstart; 5274 lastcol1 = -1; 5275 rp1 = aj + ai[row]; 5276 ap1 = aa + ai[row]; 5277 rmax1 = aimax[row]; 5278 nrow1 = ailen[row]; 5279 low1 = 0; 5280 high1 = nrow1; 5281 lastcol2 = -1; 5282 rp2 = bj + bi[row]; 5283 ap2 = ba + bi[row]; 5284 rmax2 = bimax[row]; 5285 nrow2 = bilen[row]; 5286 low2 = 0; 5287 high2 = nrow2; 5288 5289 for (j=0; j<n; j++) { 5290 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5291 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5292 if (in[j] >= cstart && in[j] < cend){ 5293 col = in[j] - cstart; 5294 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5295 } else if (in[j] < 0) continue; 5296 #if defined(PETSC_USE_DEBUG) 5297 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);} 5298 #endif 5299 else { 5300 if (mat->was_assembled) { 5301 if (!aij->colmap) { 5302 ierr = CreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5303 } 5304 #if defined (PETSC_USE_CTABLE) 5305 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5306 col--; 5307 #else 5308 col = aij->colmap[in[j]] - 1; 5309 #endif 5310 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5311 ierr = DisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5312 col = in[j]; 5313 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5314 B = aij->B; 5315 b = (Mat_SeqAIJ*)B->data; 5316 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5317 rp2 = bj + bi[row]; 5318 ap2 = ba + bi[row]; 5319 rmax2 = bimax[row]; 5320 nrow2 = bilen[row]; 5321 low2 = 0; 5322 high2 = nrow2; 5323 bm = aij->B->rmap->n; 5324 ba = b->a; 5325 } 5326 } else col = in[j]; 5327 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5328 } 5329 } 5330 } else { 5331 if (!aij->donotstash) { 5332 if (roworiented) { 5333 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5334 } else { 5335 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscTruth)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5336 } 5337 } 5338 } 5339 }} 5340 PetscFunctionReturnVoid(); 5341 } 5342 EXTERN_C_END 5343 5344