1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPIU_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc1((M->rmap->n-cnt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatDiagonalSet_MPIAIJ" 109 PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is) 110 { 111 PetscErrorCode ierr; 112 Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data; 113 114 PetscFunctionBegin; 115 if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) { 116 ierr = MatDiagonalSet(aij->A,D,is);CHKERRQ(ierr); 117 } else { 118 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 119 } 120 PetscFunctionReturn(0); 121 } 122 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 126 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 127 { 128 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 129 PetscErrorCode ierr; 130 PetscInt i,rstart,nrows,*rows; 131 132 PetscFunctionBegin; 133 *zrows = NULL; 134 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 135 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 136 for (i=0; i<nrows; i++) rows[i] += rstart; 137 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 138 PetscFunctionReturn(0); 139 } 140 141 #undef __FUNCT__ 142 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 143 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 144 { 145 PetscErrorCode ierr; 146 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 147 PetscInt i,n,*garray = aij->garray; 148 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 149 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 150 PetscReal *work; 151 152 PetscFunctionBegin; 153 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 154 ierr = PetscCalloc1(n,&work);CHKERRQ(ierr); 155 if (type == NORM_2) { 156 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 157 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 158 } 159 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 160 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 161 } 162 } else if (type == NORM_1) { 163 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 164 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 165 } 166 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 167 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 168 } 169 } else if (type == NORM_INFINITY) { 170 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 171 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 172 } 173 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 174 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 175 } 176 177 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 178 if (type == NORM_INFINITY) { 179 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 180 } else { 181 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 182 } 183 ierr = PetscFree(work);CHKERRQ(ierr); 184 if (type == NORM_2) { 185 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 186 } 187 PetscFunctionReturn(0); 188 } 189 190 #undef __FUNCT__ 191 #define __FUNCT__ "MatDistribute_MPIAIJ" 192 /* 193 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 194 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 195 196 Only for square matrices 197 198 Used by a preconditioner, hence PETSC_EXTERN 199 */ 200 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 201 { 202 PetscMPIInt rank,size; 203 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2]; 204 PetscErrorCode ierr; 205 Mat mat; 206 Mat_SeqAIJ *gmata; 207 PetscMPIInt tag; 208 MPI_Status status; 209 PetscBool aij; 210 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 211 212 PetscFunctionBegin; 213 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 214 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 215 if (!rank) { 216 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 217 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 218 } 219 if (reuse == MAT_INITIAL_MATRIX) { 220 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 221 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 222 ierr = MatGetBlockSizes(gmat,&bses[0],&bses[1]);CHKERRQ(ierr); 223 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 224 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 225 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 226 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 227 ierr = PetscMalloc2(m,&dlens,m,&olens);CHKERRQ(ierr); 228 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 229 230 rowners[0] = 0; 231 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 232 rstart = rowners[rank]; 233 rend = rowners[rank+1]; 234 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 235 if (!rank) { 236 gmata = (Mat_SeqAIJ*) gmat->data; 237 /* send row lengths to all processors */ 238 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 239 for (i=1; i<size; i++) { 240 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 241 } 242 /* determine number diagonal and off-diagonal counts */ 243 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 244 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 245 jj = 0; 246 for (i=0; i<m; i++) { 247 for (j=0; j<dlens[i]; j++) { 248 if (gmata->j[jj] < rstart) ld[i]++; 249 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 250 jj++; 251 } 252 } 253 /* send column indices to other processes */ 254 for (i=1; i<size; i++) { 255 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 256 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 257 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 258 } 259 260 /* send numerical values to other processes */ 261 for (i=1; i<size; i++) { 262 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 263 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 264 } 265 gmataa = gmata->a; 266 gmataj = gmata->j; 267 268 } else { 269 /* receive row lengths */ 270 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 271 /* receive column indices */ 272 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 273 ierr = PetscMalloc2(nz,&gmataa,nz,&gmataj);CHKERRQ(ierr); 274 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 275 /* determine number diagonal and off-diagonal counts */ 276 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 277 ierr = PetscCalloc1(m,&ld);CHKERRQ(ierr); 278 jj = 0; 279 for (i=0; i<m; i++) { 280 for (j=0; j<dlens[i]; j++) { 281 if (gmataj[jj] < rstart) ld[i]++; 282 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 283 jj++; 284 } 285 } 286 /* receive numerical values */ 287 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 288 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 289 } 290 /* set preallocation */ 291 for (i=0; i<m; i++) { 292 dlens[i] -= olens[i]; 293 } 294 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 295 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 296 297 for (i=0; i<m; i++) { 298 dlens[i] += olens[i]; 299 } 300 cnt = 0; 301 for (i=0; i<m; i++) { 302 row = rstart + i; 303 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 304 cnt += dlens[i]; 305 } 306 if (rank) { 307 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 308 } 309 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 310 ierr = PetscFree(rowners);CHKERRQ(ierr); 311 312 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 313 314 *inmat = mat; 315 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 316 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 317 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 318 mat = *inmat; 319 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 320 if (!rank) { 321 /* send numerical values to other processes */ 322 gmata = (Mat_SeqAIJ*) gmat->data; 323 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 324 gmataa = gmata->a; 325 for (i=1; i<size; i++) { 326 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 327 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 328 } 329 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 330 } else { 331 /* receive numerical values from process 0*/ 332 nz = Ad->nz + Ao->nz; 333 ierr = PetscMalloc1(nz,&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 334 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 335 } 336 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 337 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 338 ad = Ad->a; 339 ao = Ao->a; 340 if (mat->rmap->n) { 341 i = 0; 342 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 343 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 344 } 345 for (i=1; i<mat->rmap->n; i++) { 346 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; 347 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 348 } 349 i--; 350 if (mat->rmap->n) { 351 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 352 } 353 if (rank) { 354 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 355 } 356 } 357 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 358 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 359 PetscFunctionReturn(0); 360 } 361 362 /* 363 Local utility routine that creates a mapping from the global column 364 number to the local number in the off-diagonal part of the local 365 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 366 a slightly higher hash table cost; without it it is not scalable (each processor 367 has an order N integer array but is fast to acess. 368 */ 369 #undef __FUNCT__ 370 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 371 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 372 { 373 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 374 PetscErrorCode ierr; 375 PetscInt n = aij->B->cmap->n,i; 376 377 PetscFunctionBegin; 378 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 379 #if defined(PETSC_USE_CTABLE) 380 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 381 for (i=0; i<n; i++) { 382 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 383 } 384 #else 385 ierr = PetscCalloc1((mat->cmap->N+1),&aij->colmap);CHKERRQ(ierr); 386 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));CHKERRQ(ierr); 387 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 388 #endif 389 PetscFunctionReturn(0); 390 } 391 392 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 393 { \ 394 if (col <= lastcol1) low1 = 0; \ 395 else high1 = nrow1; \ 396 lastcol1 = col;\ 397 while (high1-low1 > 5) { \ 398 t = (low1+high1)/2; \ 399 if (rp1[t] > col) high1 = t; \ 400 else low1 = t; \ 401 } \ 402 for (_i=low1; _i<high1; _i++) { \ 403 if (rp1[_i] > col) break; \ 404 if (rp1[_i] == col) { \ 405 if (addv == ADD_VALUES) ap1[_i] += value; \ 406 else ap1[_i] = value; \ 407 goto a_noinsert; \ 408 } \ 409 } \ 410 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 411 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 412 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 413 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 414 N = nrow1++ - 1; a->nz++; high1++; \ 415 /* shift up all the later entries in this row */ \ 416 for (ii=N; ii>=_i; ii--) { \ 417 rp1[ii+1] = rp1[ii]; \ 418 ap1[ii+1] = ap1[ii]; \ 419 } \ 420 rp1[_i] = col; \ 421 ap1[_i] = value; \ 422 A->nonzerostate++;\ 423 a_noinsert: ; \ 424 ailen[row] = nrow1; \ 425 } 426 427 428 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 429 { \ 430 if (col <= lastcol2) low2 = 0; \ 431 else high2 = nrow2; \ 432 lastcol2 = col; \ 433 while (high2-low2 > 5) { \ 434 t = (low2+high2)/2; \ 435 if (rp2[t] > col) high2 = t; \ 436 else low2 = t; \ 437 } \ 438 for (_i=low2; _i<high2; _i++) { \ 439 if (rp2[_i] > col) break; \ 440 if (rp2[_i] == col) { \ 441 if (addv == ADD_VALUES) ap2[_i] += value; \ 442 else ap2[_i] = value; \ 443 goto b_noinsert; \ 444 } \ 445 } \ 446 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 447 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 448 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 449 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 450 N = nrow2++ - 1; b->nz++; high2++; \ 451 /* shift up all the later entries in this row */ \ 452 for (ii=N; ii>=_i; ii--) { \ 453 rp2[ii+1] = rp2[ii]; \ 454 ap2[ii+1] = ap2[ii]; \ 455 } \ 456 rp2[_i] = col; \ 457 ap2[_i] = value; \ 458 B->nonzerostate++; \ 459 b_noinsert: ; \ 460 bilen[row] = nrow2; \ 461 } 462 463 #undef __FUNCT__ 464 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 465 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 466 { 467 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 468 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 469 PetscErrorCode ierr; 470 PetscInt l,*garray = mat->garray,diag; 471 472 PetscFunctionBegin; 473 /* code only works for square matrices A */ 474 475 /* find size of row to the left of the diagonal part */ 476 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 477 row = row - diag; 478 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 479 if (garray[b->j[b->i[row]+l]] > diag) break; 480 } 481 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 482 483 /* diagonal part */ 484 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 485 486 /* right of diagonal part */ 487 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); 488 PetscFunctionReturn(0); 489 } 490 491 #undef __FUNCT__ 492 #define __FUNCT__ "MatSetValues_MPIAIJ" 493 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 494 { 495 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 496 PetscScalar value; 497 PetscErrorCode ierr; 498 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 499 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 500 PetscBool roworiented = aij->roworiented; 501 502 /* Some Variables required in the macro */ 503 Mat A = aij->A; 504 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 505 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 506 MatScalar *aa = a->a; 507 PetscBool ignorezeroentries = a->ignorezeroentries; 508 Mat B = aij->B; 509 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 510 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 511 MatScalar *ba = b->a; 512 513 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 514 PetscInt nonew; 515 MatScalar *ap1,*ap2; 516 517 PetscFunctionBegin; 518 for (i=0; i<m; i++) { 519 if (im[i] < 0) continue; 520 #if defined(PETSC_USE_DEBUG) 521 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 522 #endif 523 if (im[i] >= rstart && im[i] < rend) { 524 row = im[i] - rstart; 525 lastcol1 = -1; 526 rp1 = aj + ai[row]; 527 ap1 = aa + ai[row]; 528 rmax1 = aimax[row]; 529 nrow1 = ailen[row]; 530 low1 = 0; 531 high1 = nrow1; 532 lastcol2 = -1; 533 rp2 = bj + bi[row]; 534 ap2 = ba + bi[row]; 535 rmax2 = bimax[row]; 536 nrow2 = bilen[row]; 537 low2 = 0; 538 high2 = nrow2; 539 540 for (j=0; j<n; j++) { 541 if (roworiented) value = v[i*n+j]; 542 else value = v[i+j*m]; 543 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 544 if (in[j] >= cstart && in[j] < cend) { 545 col = in[j] - cstart; 546 nonew = a->nonew; 547 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 548 } else if (in[j] < 0) continue; 549 #if defined(PETSC_USE_DEBUG) 550 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 551 #endif 552 else { 553 if (mat->was_assembled) { 554 if (!aij->colmap) { 555 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 556 } 557 #if defined(PETSC_USE_CTABLE) 558 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 559 col--; 560 #else 561 col = aij->colmap[in[j]] - 1; 562 #endif 563 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 564 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 565 col = in[j]; 566 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 567 B = aij->B; 568 b = (Mat_SeqAIJ*)B->data; 569 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 570 rp2 = bj + bi[row]; 571 ap2 = ba + bi[row]; 572 rmax2 = bimax[row]; 573 nrow2 = bilen[row]; 574 low2 = 0; 575 high2 = nrow2; 576 bm = aij->B->rmap->n; 577 ba = b->a; 578 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 579 } else col = in[j]; 580 nonew = b->nonew; 581 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 582 } 583 } 584 } else { 585 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 586 if (!aij->donotstash) { 587 mat->assembled = PETSC_FALSE; 588 if (roworiented) { 589 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 590 } else { 591 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 592 } 593 } 594 } 595 } 596 PetscFunctionReturn(0); 597 } 598 599 #undef __FUNCT__ 600 #define __FUNCT__ "MatGetValues_MPIAIJ" 601 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 602 { 603 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 604 PetscErrorCode ierr; 605 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 606 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 607 608 PetscFunctionBegin; 609 for (i=0; i<m; i++) { 610 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 611 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 612 if (idxm[i] >= rstart && idxm[i] < rend) { 613 row = idxm[i] - rstart; 614 for (j=0; j<n; j++) { 615 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 616 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 617 if (idxn[j] >= cstart && idxn[j] < cend) { 618 col = idxn[j] - cstart; 619 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 620 } else { 621 if (!aij->colmap) { 622 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 623 } 624 #if defined(PETSC_USE_CTABLE) 625 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 626 col--; 627 #else 628 col = aij->colmap[idxn[j]] - 1; 629 #endif 630 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 631 else { 632 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 633 } 634 } 635 } 636 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 637 } 638 PetscFunctionReturn(0); 639 } 640 641 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 642 643 #undef __FUNCT__ 644 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 645 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 646 { 647 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 648 PetscErrorCode ierr; 649 PetscInt nstash,reallocs; 650 InsertMode addv; 651 652 PetscFunctionBegin; 653 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 654 655 /* make sure all processors are either in INSERTMODE or ADDMODE */ 656 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 657 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 658 mat->insertmode = addv; /* in case this processor had no cache */ 659 660 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 661 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 662 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 663 PetscFunctionReturn(0); 664 } 665 666 #undef __FUNCT__ 667 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 668 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 669 { 670 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 671 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 672 PetscErrorCode ierr; 673 PetscMPIInt n; 674 PetscInt i,j,rstart,ncols,flg; 675 PetscInt *row,*col; 676 PetscBool other_disassembled; 677 PetscScalar *val; 678 InsertMode addv = mat->insertmode; 679 680 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 681 682 PetscFunctionBegin; 683 if (!aij->donotstash && !mat->nooffprocentries) { 684 while (1) { 685 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 686 if (!flg) break; 687 688 for (i=0; i<n; ) { 689 /* Now identify the consecutive vals belonging to the same row */ 690 for (j=i,rstart=row[j]; j<n; j++) { 691 if (row[j] != rstart) break; 692 } 693 if (j < n) ncols = j-i; 694 else ncols = n-i; 695 /* Now assemble all these values with a single function call */ 696 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 697 698 i = j; 699 } 700 } 701 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 702 } 703 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 704 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 705 706 /* determine if any processor has disassembled, if so we must 707 also disassemble ourselfs, in order that we may reassemble. */ 708 /* 709 if nonzero structure of submatrix B cannot change then we know that 710 no processor disassembled thus we can skip this stuff 711 */ 712 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 713 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 714 if (mat->was_assembled && !other_disassembled) { 715 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 716 } 717 } 718 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 719 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 720 } 721 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 722 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 723 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 724 725 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 726 727 aij->rowvalues = 0; 728 729 /* used by MatAXPY() */ 730 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 731 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 732 733 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 734 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 735 736 /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */ 737 if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 738 PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate; 739 ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 740 } 741 PetscFunctionReturn(0); 742 } 743 744 #undef __FUNCT__ 745 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 746 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 747 { 748 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 749 PetscErrorCode ierr; 750 751 PetscFunctionBegin; 752 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 753 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 754 PetscFunctionReturn(0); 755 } 756 757 #undef __FUNCT__ 758 #define __FUNCT__ "MatZeroRows_MPIAIJ" 759 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 760 { 761 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 762 PetscInt *owners = A->rmap->range; 763 PetscInt n = A->rmap->n; 764 PetscSF sf; 765 PetscInt *lrows; 766 PetscSFNode *rrows; 767 PetscInt r, p = 0, len = 0; 768 PetscErrorCode ierr; 769 770 PetscFunctionBegin; 771 /* Create SF where leaves are input rows and roots are owned rows */ 772 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 773 for (r = 0; r < n; ++r) lrows[r] = -1; 774 if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);} 775 for (r = 0; r < N; ++r) { 776 const PetscInt idx = rows[r]; 777 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 778 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 779 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 780 } 781 if (A->nooffproczerorows) { 782 if (p != mat->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,mat->rank); 783 lrows[len++] = idx - owners[p]; 784 } else { 785 rrows[r].rank = p; 786 rrows[r].index = rows[r] - owners[p]; 787 } 788 } 789 if (!A->nooffproczerorows) { 790 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 791 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 792 /* Collect flags for rows to be zeroed */ 793 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 794 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt*)rows, lrows, MPI_LOR);CHKERRQ(ierr); 795 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 796 /* Compress and put in row numbers */ 797 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 798 } 799 /* fix right hand side if needed */ 800 if (x && b) { 801 const PetscScalar *xx; 802 PetscScalar *bb; 803 804 ierr = VecGetArrayRead(x, &xx);CHKERRQ(ierr); 805 ierr = VecGetArray(b, &bb);CHKERRQ(ierr); 806 for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]]; 807 ierr = VecRestoreArrayRead(x, &xx);CHKERRQ(ierr); 808 ierr = VecRestoreArray(b, &bb);CHKERRQ(ierr); 809 } 810 /* Must zero l->B before l->A because the (diag) case below may put values into l->B*/ 811 ierr = MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 812 if ((diag != 0.0) && (mat->A->rmap->N == mat->A->cmap->N)) { 813 ierr = MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);CHKERRQ(ierr); 814 } else if (diag != 0.0) { 815 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 816 if (((Mat_SeqAIJ *) mat->A->data)->nonew) SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 817 for (r = 0; r < len; ++r) { 818 const PetscInt row = lrows[r] + A->rmap->rstart; 819 ierr = MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);CHKERRQ(ierr); 820 } 821 ierr = MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 822 ierr = MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 823 } else { 824 ierr = MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);CHKERRQ(ierr); 825 } 826 ierr = PetscFree(lrows);CHKERRQ(ierr); 827 828 /* only change matrix nonzero state if pattern was allowed to be changed */ 829 if (!((Mat_SeqAIJ*)(mat->A->data))->keepnonzeropattern) { 830 PetscObjectState state = mat->A->nonzerostate + mat->B->nonzerostate; 831 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 832 } 833 PetscFunctionReturn(0); 834 } 835 836 #undef __FUNCT__ 837 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 838 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 839 { 840 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 841 PetscErrorCode ierr; 842 PetscMPIInt n = A->rmap->n; 843 PetscInt i,j,r,m,p = 0,len = 0; 844 PetscInt *lrows,*owners = A->rmap->range; 845 PetscSFNode *rrows; 846 PetscSF sf; 847 const PetscScalar *xx; 848 PetscScalar *bb,*mask; 849 Vec xmask,lmask; 850 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 851 const PetscInt *aj, *ii,*ridx; 852 PetscScalar *aa; 853 854 PetscFunctionBegin; 855 /* Create SF where leaves are input rows and roots are owned rows */ 856 ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr); 857 for (r = 0; r < n; ++r) lrows[r] = -1; 858 ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr); 859 for (r = 0; r < N; ++r) { 860 const PetscInt idx = rows[r]; 861 if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N); 862 if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */ 863 ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr); 864 } 865 rrows[r].rank = p; 866 rrows[r].index = rows[r] - owners[p]; 867 } 868 ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr); 869 ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr); 870 /* Collect flags for rows to be zeroed */ 871 ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 872 ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr); 873 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 874 /* Compress and put in row numbers */ 875 for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r; 876 /* zero diagonal part of matrix */ 877 ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr); 878 /* handle off diagonal part of matrix */ 879 ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr); 880 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 881 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 882 for (i=0; i<len; i++) bb[lrows[i]] = 1; 883 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 884 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 885 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 886 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 887 if (x) { 888 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 889 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 890 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 891 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 892 } 893 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 894 /* remove zeroed rows of off diagonal matrix */ 895 ii = aij->i; 896 for (i=0; i<len; i++) { 897 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 898 } 899 /* loop over all elements of off process part of matrix zeroing removed columns*/ 900 if (aij->compressedrow.use) { 901 m = aij->compressedrow.nrows; 902 ii = aij->compressedrow.i; 903 ridx = aij->compressedrow.rindex; 904 for (i=0; i<m; i++) { 905 n = ii[i+1] - ii[i]; 906 aj = aij->j + ii[i]; 907 aa = aij->a + ii[i]; 908 909 for (j=0; j<n; j++) { 910 if (PetscAbsScalar(mask[*aj])) { 911 if (b) bb[*ridx] -= *aa*xx[*aj]; 912 *aa = 0.0; 913 } 914 aa++; 915 aj++; 916 } 917 ridx++; 918 } 919 } else { /* do not use compressed row format */ 920 m = l->B->rmap->n; 921 for (i=0; i<m; i++) { 922 n = ii[i+1] - ii[i]; 923 aj = aij->j + ii[i]; 924 aa = aij->a + ii[i]; 925 for (j=0; j<n; j++) { 926 if (PetscAbsScalar(mask[*aj])) { 927 if (b) bb[i] -= *aa*xx[*aj]; 928 *aa = 0.0; 929 } 930 aa++; 931 aj++; 932 } 933 } 934 } 935 if (x) { 936 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 937 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 938 } 939 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 940 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 941 ierr = PetscFree(lrows);CHKERRQ(ierr); 942 943 /* only change matrix nonzero state if pattern was allowed to be changed */ 944 if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) { 945 PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate; 946 ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 947 } 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNCT__ 952 #define __FUNCT__ "MatMult_MPIAIJ" 953 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 954 { 955 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 956 PetscErrorCode ierr; 957 PetscInt nt; 958 959 PetscFunctionBegin; 960 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 961 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 962 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 963 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 964 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 965 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 966 PetscFunctionReturn(0); 967 } 968 969 #undef __FUNCT__ 970 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 971 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 972 { 973 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 974 PetscErrorCode ierr; 975 976 PetscFunctionBegin; 977 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 978 PetscFunctionReturn(0); 979 } 980 981 #undef __FUNCT__ 982 #define __FUNCT__ "MatMultAdd_MPIAIJ" 983 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 984 { 985 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 986 PetscErrorCode ierr; 987 988 PetscFunctionBegin; 989 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 990 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 991 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 992 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 993 PetscFunctionReturn(0); 994 } 995 996 #undef __FUNCT__ 997 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 998 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 999 { 1000 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1001 PetscErrorCode ierr; 1002 PetscBool merged; 1003 1004 PetscFunctionBegin; 1005 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1006 /* do nondiagonal part */ 1007 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1008 if (!merged) { 1009 /* send it on its way */ 1010 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1011 /* do local part */ 1012 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1013 /* receive remote parts: note this assumes the values are not actually */ 1014 /* added in yy until the next line, */ 1015 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1016 } else { 1017 /* do local part */ 1018 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1019 /* send it on its way */ 1020 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1021 /* values actually were received in the Begin() but we need to call this nop */ 1022 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1023 } 1024 PetscFunctionReturn(0); 1025 } 1026 1027 #undef __FUNCT__ 1028 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1029 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1030 { 1031 MPI_Comm comm; 1032 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1033 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1034 IS Me,Notme; 1035 PetscErrorCode ierr; 1036 PetscInt M,N,first,last,*notme,i; 1037 PetscMPIInt size; 1038 1039 PetscFunctionBegin; 1040 /* Easy test: symmetric diagonal block */ 1041 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1042 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1043 if (!*f) PetscFunctionReturn(0); 1044 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1045 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1046 if (size == 1) PetscFunctionReturn(0); 1047 1048 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1049 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1050 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1051 ierr = PetscMalloc1((N-last+first),¬me);CHKERRQ(ierr); 1052 for (i=0; i<first; i++) notme[i] = i; 1053 for (i=last; i<M; i++) notme[i-last+first] = i; 1054 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1055 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1056 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1057 Aoff = Aoffs[0]; 1058 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1059 Boff = Boffs[0]; 1060 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1061 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1062 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1063 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1064 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1065 ierr = PetscFree(notme);CHKERRQ(ierr); 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #undef __FUNCT__ 1070 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1071 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1072 { 1073 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 /* do nondiagonal part */ 1078 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1079 /* send it on its way */ 1080 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1081 /* do local part */ 1082 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1083 /* receive remote parts */ 1084 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1085 PetscFunctionReturn(0); 1086 } 1087 1088 /* 1089 This only works correctly for square matrices where the subblock A->A is the 1090 diagonal block 1091 */ 1092 #undef __FUNCT__ 1093 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1094 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1095 { 1096 PetscErrorCode ierr; 1097 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1098 1099 PetscFunctionBegin; 1100 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1101 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1102 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1103 PetscFunctionReturn(0); 1104 } 1105 1106 #undef __FUNCT__ 1107 #define __FUNCT__ "MatScale_MPIAIJ" 1108 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1109 { 1110 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1111 PetscErrorCode ierr; 1112 1113 PetscFunctionBegin; 1114 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1115 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1116 PetscFunctionReturn(0); 1117 } 1118 1119 #undef __FUNCT__ 1120 #define __FUNCT__ "MatDestroy_Redundant" 1121 PetscErrorCode MatDestroy_Redundant(Mat_Redundant **redundant) 1122 { 1123 PetscErrorCode ierr; 1124 Mat_Redundant *redund = *redundant; 1125 PetscInt i; 1126 1127 PetscFunctionBegin; 1128 *redundant = NULL; 1129 if (redund){ 1130 if (redund->matseq) { /* via MatGetSubMatrices() */ 1131 ierr = ISDestroy(&redund->isrow);CHKERRQ(ierr); 1132 ierr = ISDestroy(&redund->iscol);CHKERRQ(ierr); 1133 ierr = MatDestroy(&redund->matseq[0]);CHKERRQ(ierr); 1134 ierr = PetscFree(redund->matseq);CHKERRQ(ierr); 1135 } else { 1136 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 1137 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 1138 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 1139 for (i=0; i<redund->nrecvs; i++) { 1140 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 1141 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 1142 } 1143 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 1144 } 1145 1146 if (redund->subcomm) { 1147 ierr = PetscCommDestroy(&redund->subcomm);CHKERRQ(ierr); 1148 } 1149 ierr = PetscFree(redund);CHKERRQ(ierr); 1150 } 1151 PetscFunctionReturn(0); 1152 } 1153 1154 #undef __FUNCT__ 1155 #define __FUNCT__ "MatDestroy_MPIAIJ" 1156 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1157 { 1158 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1159 PetscErrorCode ierr; 1160 1161 PetscFunctionBegin; 1162 #if defined(PETSC_USE_LOG) 1163 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1164 #endif 1165 ierr = MatDestroy_Redundant(&mat->redundant);CHKERRQ(ierr); 1166 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1167 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1168 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1169 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1170 #if defined(PETSC_USE_CTABLE) 1171 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1172 #else 1173 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1174 #endif 1175 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1176 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1177 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1178 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1179 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1180 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1181 1182 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1183 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1184 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1185 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1186 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1187 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1188 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1189 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1190 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1191 #if defined(PETSC_HAVE_ELEMENTAL) 1192 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);CHKERRQ(ierr); 1193 #endif 1194 PetscFunctionReturn(0); 1195 } 1196 1197 #undef __FUNCT__ 1198 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1199 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1200 { 1201 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1202 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1203 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1204 PetscErrorCode ierr; 1205 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1206 int fd; 1207 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1208 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0; 1209 PetscScalar *column_values; 1210 PetscInt message_count,flowcontrolcount; 1211 FILE *file; 1212 1213 PetscFunctionBegin; 1214 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1215 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1216 nz = A->nz + B->nz; 1217 if (!rank) { 1218 header[0] = MAT_FILE_CLASSID; 1219 header[1] = mat->rmap->N; 1220 header[2] = mat->cmap->N; 1221 1222 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1223 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1224 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1225 /* get largest number of rows any processor has */ 1226 rlen = mat->rmap->n; 1227 range = mat->rmap->range; 1228 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1229 } else { 1230 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1231 rlen = mat->rmap->n; 1232 } 1233 1234 /* load up the local row counts */ 1235 ierr = PetscMalloc1((rlen+1),&row_lengths);CHKERRQ(ierr); 1236 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1237 1238 /* store the row lengths to the file */ 1239 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1240 if (!rank) { 1241 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1242 for (i=1; i<size; i++) { 1243 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1244 rlen = range[i+1] - range[i]; 1245 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1246 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1247 } 1248 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1249 } else { 1250 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1251 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1252 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1253 } 1254 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1255 1256 /* load up the local column indices */ 1257 nzmax = nz; /* th processor needs space a largest processor needs */ 1258 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1259 ierr = PetscMalloc1((nzmax+1),&column_indices);CHKERRQ(ierr); 1260 cnt = 0; 1261 for (i=0; i<mat->rmap->n; i++) { 1262 for (j=B->i[i]; j<B->i[i+1]; j++) { 1263 if ((col = garray[B->j[j]]) > cstart) break; 1264 column_indices[cnt++] = col; 1265 } 1266 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1267 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1268 } 1269 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1270 1271 /* store the column indices to the file */ 1272 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1273 if (!rank) { 1274 MPI_Status status; 1275 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1276 for (i=1; i<size; i++) { 1277 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1278 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1279 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1280 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1281 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1282 } 1283 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1284 } else { 1285 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1286 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1287 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1288 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1289 } 1290 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1291 1292 /* load up the local column values */ 1293 ierr = PetscMalloc1((nzmax+1),&column_values);CHKERRQ(ierr); 1294 cnt = 0; 1295 for (i=0; i<mat->rmap->n; i++) { 1296 for (j=B->i[i]; j<B->i[i+1]; j++) { 1297 if (garray[B->j[j]] > cstart) break; 1298 column_values[cnt++] = B->a[j]; 1299 } 1300 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1301 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1302 } 1303 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1304 1305 /* store the column values to the file */ 1306 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1307 if (!rank) { 1308 MPI_Status status; 1309 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1310 for (i=1; i<size; i++) { 1311 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1312 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1313 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1314 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1315 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1316 } 1317 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1318 } else { 1319 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1320 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1321 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1322 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1323 } 1324 ierr = PetscFree(column_values);CHKERRQ(ierr); 1325 1326 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1327 if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs)); 1328 PetscFunctionReturn(0); 1329 } 1330 1331 #include <petscdraw.h> 1332 #undef __FUNCT__ 1333 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1334 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1335 { 1336 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1337 PetscErrorCode ierr; 1338 PetscMPIInt rank = aij->rank,size = aij->size; 1339 PetscBool isdraw,iascii,isbinary; 1340 PetscViewer sviewer; 1341 PetscViewerFormat format; 1342 1343 PetscFunctionBegin; 1344 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1345 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1346 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1347 if (iascii) { 1348 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1349 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1350 MatInfo info; 1351 PetscBool inodes; 1352 1353 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1354 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1355 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1356 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1357 if (!inodes) { 1358 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1359 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1360 } else { 1361 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1362 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1363 } 1364 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1365 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1366 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1367 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1368 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1369 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1370 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1371 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1372 PetscFunctionReturn(0); 1373 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1374 PetscInt inodecount,inodelimit,*inodes; 1375 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1376 if (inodes) { 1377 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1378 } else { 1379 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1380 } 1381 PetscFunctionReturn(0); 1382 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1383 PetscFunctionReturn(0); 1384 } 1385 } else if (isbinary) { 1386 if (size == 1) { 1387 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1388 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1389 } else { 1390 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1391 } 1392 PetscFunctionReturn(0); 1393 } else if (isdraw) { 1394 PetscDraw draw; 1395 PetscBool isnull; 1396 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1397 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1398 } 1399 1400 { 1401 /* assemble the entire matrix onto first processor. */ 1402 Mat A; 1403 Mat_SeqAIJ *Aloc; 1404 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1405 MatScalar *a; 1406 1407 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1408 if (!rank) { 1409 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1410 } else { 1411 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1412 } 1413 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1414 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1415 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1416 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1417 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 1418 1419 /* copy over the A part */ 1420 Aloc = (Mat_SeqAIJ*)aij->A->data; 1421 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1422 row = mat->rmap->rstart; 1423 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1424 for (i=0; i<m; i++) { 1425 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1426 row++; 1427 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1428 } 1429 aj = Aloc->j; 1430 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1431 1432 /* copy over the B part */ 1433 Aloc = (Mat_SeqAIJ*)aij->B->data; 1434 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1435 row = mat->rmap->rstart; 1436 ierr = PetscMalloc1((ai[m]+1),&cols);CHKERRQ(ierr); 1437 ct = cols; 1438 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1439 for (i=0; i<m; i++) { 1440 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1441 row++; 1442 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1443 } 1444 ierr = PetscFree(ct);CHKERRQ(ierr); 1445 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1446 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1447 /* 1448 Everyone has to call to draw the matrix since the graphics waits are 1449 synchronized across all processors that share the PetscDraw object 1450 */ 1451 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1452 if (!rank) { 1453 ierr = MatView_SeqAIJ(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1454 } 1455 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1456 ierr = MatDestroy(&A);CHKERRQ(ierr); 1457 } 1458 PetscFunctionReturn(0); 1459 } 1460 1461 #undef __FUNCT__ 1462 #define __FUNCT__ "MatView_MPIAIJ" 1463 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1464 { 1465 PetscErrorCode ierr; 1466 PetscBool iascii,isdraw,issocket,isbinary; 1467 1468 PetscFunctionBegin; 1469 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1470 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1471 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1472 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1473 if (iascii || isdraw || isbinary || issocket) { 1474 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1475 } 1476 PetscFunctionReturn(0); 1477 } 1478 1479 #undef __FUNCT__ 1480 #define __FUNCT__ "MatSOR_MPIAIJ" 1481 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1482 { 1483 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1484 PetscErrorCode ierr; 1485 Vec bb1 = 0; 1486 PetscBool hasop; 1487 1488 PetscFunctionBegin; 1489 if (flag == SOR_APPLY_UPPER) { 1490 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1491 PetscFunctionReturn(0); 1492 } 1493 1494 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1495 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1496 } 1497 1498 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1499 if (flag & SOR_ZERO_INITIAL_GUESS) { 1500 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1501 its--; 1502 } 1503 1504 while (its--) { 1505 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1506 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1507 1508 /* update rhs: bb1 = bb - B*x */ 1509 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1510 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1511 1512 /* local sweep */ 1513 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1514 } 1515 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1516 if (flag & SOR_ZERO_INITIAL_GUESS) { 1517 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1518 its--; 1519 } 1520 while (its--) { 1521 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1522 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1523 1524 /* update rhs: bb1 = bb - B*x */ 1525 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1526 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1527 1528 /* local sweep */ 1529 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1530 } 1531 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1532 if (flag & SOR_ZERO_INITIAL_GUESS) { 1533 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1534 its--; 1535 } 1536 while (its--) { 1537 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1538 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1539 1540 /* update rhs: bb1 = bb - B*x */ 1541 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1542 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1543 1544 /* local sweep */ 1545 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1546 } 1547 } else if (flag & SOR_EISENSTAT) { 1548 Vec xx1; 1549 1550 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1551 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1552 1553 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1554 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1555 if (!mat->diag) { 1556 ierr = MatCreateVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1557 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1558 } 1559 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1560 if (hasop) { 1561 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1562 } else { 1563 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1564 } 1565 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1566 1567 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1568 1569 /* local sweep */ 1570 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1571 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1572 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1573 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1574 1575 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1576 PetscFunctionReturn(0); 1577 } 1578 1579 #undef __FUNCT__ 1580 #define __FUNCT__ "MatPermute_MPIAIJ" 1581 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1582 { 1583 Mat aA,aB,Aperm; 1584 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1585 PetscScalar *aa,*ba; 1586 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1587 PetscSF rowsf,sf; 1588 IS parcolp = NULL; 1589 PetscBool done; 1590 PetscErrorCode ierr; 1591 1592 PetscFunctionBegin; 1593 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1594 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1595 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1596 ierr = PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);CHKERRQ(ierr); 1597 1598 /* Invert row permutation to find out where my rows should go */ 1599 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1600 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1601 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1602 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1603 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1604 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1605 1606 /* Invert column permutation to find out where my columns should go */ 1607 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1608 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1609 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1610 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1611 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1612 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1613 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1614 1615 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1616 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1617 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1618 1619 /* Find out where my gcols should go */ 1620 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1621 ierr = PetscMalloc1(ng,&gcdest);CHKERRQ(ierr); 1622 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1623 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1624 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1625 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1626 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1627 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1628 1629 ierr = PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);CHKERRQ(ierr); 1630 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1631 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1632 for (i=0; i<m; i++) { 1633 PetscInt row = rdest[i],rowner; 1634 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1635 for (j=ai[i]; j<ai[i+1]; j++) { 1636 PetscInt cowner,col = cdest[aj[j]]; 1637 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1638 if (rowner == cowner) dnnz[i]++; 1639 else onnz[i]++; 1640 } 1641 for (j=bi[i]; j<bi[i+1]; j++) { 1642 PetscInt cowner,col = gcdest[bj[j]]; 1643 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1644 if (rowner == cowner) dnnz[i]++; 1645 else onnz[i]++; 1646 } 1647 } 1648 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1649 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1650 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1651 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1652 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1653 1654 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1655 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1656 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1657 for (i=0; i<m; i++) { 1658 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1659 PetscInt j0,rowlen; 1660 rowlen = ai[i+1] - ai[i]; 1661 for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */ 1662 for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]]; 1663 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1664 } 1665 rowlen = bi[i+1] - bi[i]; 1666 for (j0=j=0; j<rowlen; j0=j) { 1667 for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]]; 1668 ierr = MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);CHKERRQ(ierr); 1669 } 1670 } 1671 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1672 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1673 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1674 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1675 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1676 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1677 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1678 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1679 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1680 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1681 *B = Aperm; 1682 PetscFunctionReturn(0); 1683 } 1684 1685 #undef __FUNCT__ 1686 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1687 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1688 { 1689 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1690 Mat A = mat->A,B = mat->B; 1691 PetscErrorCode ierr; 1692 PetscReal isend[5],irecv[5]; 1693 1694 PetscFunctionBegin; 1695 info->block_size = 1.0; 1696 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1697 1698 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1699 isend[3] = info->memory; isend[4] = info->mallocs; 1700 1701 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1702 1703 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1704 isend[3] += info->memory; isend[4] += info->mallocs; 1705 if (flag == MAT_LOCAL) { 1706 info->nz_used = isend[0]; 1707 info->nz_allocated = isend[1]; 1708 info->nz_unneeded = isend[2]; 1709 info->memory = isend[3]; 1710 info->mallocs = isend[4]; 1711 } else if (flag == MAT_GLOBAL_MAX) { 1712 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1713 1714 info->nz_used = irecv[0]; 1715 info->nz_allocated = irecv[1]; 1716 info->nz_unneeded = irecv[2]; 1717 info->memory = irecv[3]; 1718 info->mallocs = irecv[4]; 1719 } else if (flag == MAT_GLOBAL_SUM) { 1720 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1721 1722 info->nz_used = irecv[0]; 1723 info->nz_allocated = irecv[1]; 1724 info->nz_unneeded = irecv[2]; 1725 info->memory = irecv[3]; 1726 info->mallocs = irecv[4]; 1727 } 1728 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1729 info->fill_ratio_needed = 0; 1730 info->factor_mallocs = 0; 1731 PetscFunctionReturn(0); 1732 } 1733 1734 #undef __FUNCT__ 1735 #define __FUNCT__ "MatSetOption_MPIAIJ" 1736 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1737 { 1738 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1739 PetscErrorCode ierr; 1740 1741 PetscFunctionBegin; 1742 switch (op) { 1743 case MAT_NEW_NONZERO_LOCATIONS: 1744 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1745 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1746 case MAT_KEEP_NONZERO_PATTERN: 1747 case MAT_NEW_NONZERO_LOCATION_ERR: 1748 case MAT_USE_INODES: 1749 case MAT_IGNORE_ZERO_ENTRIES: 1750 MatCheckPreallocated(A,1); 1751 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1752 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1753 break; 1754 case MAT_ROW_ORIENTED: 1755 a->roworiented = flg; 1756 1757 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1758 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1759 break; 1760 case MAT_NEW_DIAGONALS: 1761 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1762 break; 1763 case MAT_IGNORE_OFF_PROC_ENTRIES: 1764 a->donotstash = flg; 1765 break; 1766 case MAT_SPD: 1767 A->spd_set = PETSC_TRUE; 1768 A->spd = flg; 1769 if (flg) { 1770 A->symmetric = PETSC_TRUE; 1771 A->structurally_symmetric = PETSC_TRUE; 1772 A->symmetric_set = PETSC_TRUE; 1773 A->structurally_symmetric_set = PETSC_TRUE; 1774 } 1775 break; 1776 case MAT_SYMMETRIC: 1777 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1778 break; 1779 case MAT_STRUCTURALLY_SYMMETRIC: 1780 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1781 break; 1782 case MAT_HERMITIAN: 1783 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1784 break; 1785 case MAT_SYMMETRY_ETERNAL: 1786 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1787 break; 1788 default: 1789 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1790 } 1791 PetscFunctionReturn(0); 1792 } 1793 1794 #undef __FUNCT__ 1795 #define __FUNCT__ "MatGetRow_MPIAIJ" 1796 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1797 { 1798 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1799 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1800 PetscErrorCode ierr; 1801 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1802 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1803 PetscInt *cmap,*idx_p; 1804 1805 PetscFunctionBegin; 1806 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1807 mat->getrowactive = PETSC_TRUE; 1808 1809 if (!mat->rowvalues && (idx || v)) { 1810 /* 1811 allocate enough space to hold information from the longest row. 1812 */ 1813 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1814 PetscInt max = 1,tmp; 1815 for (i=0; i<matin->rmap->n; i++) { 1816 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1817 if (max < tmp) max = tmp; 1818 } 1819 ierr = PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);CHKERRQ(ierr); 1820 } 1821 1822 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1823 lrow = row - rstart; 1824 1825 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1826 if (!v) {pvA = 0; pvB = 0;} 1827 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1828 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1829 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1830 nztot = nzA + nzB; 1831 1832 cmap = mat->garray; 1833 if (v || idx) { 1834 if (nztot) { 1835 /* Sort by increasing column numbers, assuming A and B already sorted */ 1836 PetscInt imark = -1; 1837 if (v) { 1838 *v = v_p = mat->rowvalues; 1839 for (i=0; i<nzB; i++) { 1840 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1841 else break; 1842 } 1843 imark = i; 1844 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1845 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1846 } 1847 if (idx) { 1848 *idx = idx_p = mat->rowindices; 1849 if (imark > -1) { 1850 for (i=0; i<imark; i++) { 1851 idx_p[i] = cmap[cworkB[i]]; 1852 } 1853 } else { 1854 for (i=0; i<nzB; i++) { 1855 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1856 else break; 1857 } 1858 imark = i; 1859 } 1860 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1861 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1862 } 1863 } else { 1864 if (idx) *idx = 0; 1865 if (v) *v = 0; 1866 } 1867 } 1868 *nz = nztot; 1869 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1870 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1871 PetscFunctionReturn(0); 1872 } 1873 1874 #undef __FUNCT__ 1875 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1876 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1877 { 1878 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1879 1880 PetscFunctionBegin; 1881 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1882 aij->getrowactive = PETSC_FALSE; 1883 PetscFunctionReturn(0); 1884 } 1885 1886 #undef __FUNCT__ 1887 #define __FUNCT__ "MatNorm_MPIAIJ" 1888 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1889 { 1890 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1891 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1892 PetscErrorCode ierr; 1893 PetscInt i,j,cstart = mat->cmap->rstart; 1894 PetscReal sum = 0.0; 1895 MatScalar *v; 1896 1897 PetscFunctionBegin; 1898 if (aij->size == 1) { 1899 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1900 } else { 1901 if (type == NORM_FROBENIUS) { 1902 v = amat->a; 1903 for (i=0; i<amat->nz; i++) { 1904 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1905 } 1906 v = bmat->a; 1907 for (i=0; i<bmat->nz; i++) { 1908 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1909 } 1910 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1911 *norm = PetscSqrtReal(*norm); 1912 } else if (type == NORM_1) { /* max column norm */ 1913 PetscReal *tmp,*tmp2; 1914 PetscInt *jj,*garray = aij->garray; 1915 ierr = PetscCalloc1((mat->cmap->N+1),&tmp);CHKERRQ(ierr); 1916 ierr = PetscMalloc1((mat->cmap->N+1),&tmp2);CHKERRQ(ierr); 1917 *norm = 0.0; 1918 v = amat->a; jj = amat->j; 1919 for (j=0; j<amat->nz; j++) { 1920 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 1921 } 1922 v = bmat->a; jj = bmat->j; 1923 for (j=0; j<bmat->nz; j++) { 1924 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 1925 } 1926 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1927 for (j=0; j<mat->cmap->N; j++) { 1928 if (tmp2[j] > *norm) *norm = tmp2[j]; 1929 } 1930 ierr = PetscFree(tmp);CHKERRQ(ierr); 1931 ierr = PetscFree(tmp2);CHKERRQ(ierr); 1932 } else if (type == NORM_INFINITY) { /* max row norm */ 1933 PetscReal ntemp = 0.0; 1934 for (j=0; j<aij->A->rmap->n; j++) { 1935 v = amat->a + amat->i[j]; 1936 sum = 0.0; 1937 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 1938 sum += PetscAbsScalar(*v); v++; 1939 } 1940 v = bmat->a + bmat->i[j]; 1941 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 1942 sum += PetscAbsScalar(*v); v++; 1943 } 1944 if (sum > ntemp) ntemp = sum; 1945 } 1946 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1947 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 1948 } 1949 PetscFunctionReturn(0); 1950 } 1951 1952 #undef __FUNCT__ 1953 #define __FUNCT__ "MatTranspose_MPIAIJ" 1954 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 1955 { 1956 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1957 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 1958 PetscErrorCode ierr; 1959 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 1960 PetscInt cstart = A->cmap->rstart,ncol; 1961 Mat B; 1962 MatScalar *array; 1963 1964 PetscFunctionBegin; 1965 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 1966 1967 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 1968 ai = Aloc->i; aj = Aloc->j; 1969 bi = Bloc->i; bj = Bloc->j; 1970 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 1971 PetscInt *d_nnz,*g_nnz,*o_nnz; 1972 PetscSFNode *oloc; 1973 PETSC_UNUSED PetscSF sf; 1974 1975 ierr = PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);CHKERRQ(ierr); 1976 /* compute d_nnz for preallocation */ 1977 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1978 for (i=0; i<ai[ma]; i++) { 1979 d_nnz[aj[i]]++; 1980 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 1981 } 1982 /* compute local off-diagonal contributions */ 1983 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 1984 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 1985 /* map those to global */ 1986 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1987 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 1988 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1989 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 1990 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1991 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 1992 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1993 1994 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 1995 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 1996 ierr = MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 1997 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 1998 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 1999 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2000 } else { 2001 B = *matout; 2002 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2003 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2004 } 2005 2006 /* copy over the A part */ 2007 array = Aloc->a; 2008 row = A->rmap->rstart; 2009 for (i=0; i<ma; i++) { 2010 ncol = ai[i+1]-ai[i]; 2011 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2012 row++; 2013 array += ncol; aj += ncol; 2014 } 2015 aj = Aloc->j; 2016 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2017 2018 /* copy over the B part */ 2019 ierr = PetscCalloc1(bi[mb],&cols);CHKERRQ(ierr); 2020 array = Bloc->a; 2021 row = A->rmap->rstart; 2022 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2023 cols_tmp = cols; 2024 for (i=0; i<mb; i++) { 2025 ncol = bi[i+1]-bi[i]; 2026 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2027 row++; 2028 array += ncol; cols_tmp += ncol; 2029 } 2030 ierr = PetscFree(cols);CHKERRQ(ierr); 2031 2032 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2033 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2034 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2035 *matout = B; 2036 } else { 2037 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2038 } 2039 PetscFunctionReturn(0); 2040 } 2041 2042 #undef __FUNCT__ 2043 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2044 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2045 { 2046 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2047 Mat a = aij->A,b = aij->B; 2048 PetscErrorCode ierr; 2049 PetscInt s1,s2,s3; 2050 2051 PetscFunctionBegin; 2052 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2053 if (rr) { 2054 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2055 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2056 /* Overlap communication with computation. */ 2057 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2058 } 2059 if (ll) { 2060 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2061 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2062 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2063 } 2064 /* scale the diagonal block */ 2065 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2066 2067 if (rr) { 2068 /* Do a scatter end and then right scale the off-diagonal block */ 2069 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2070 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2071 } 2072 PetscFunctionReturn(0); 2073 } 2074 2075 #undef __FUNCT__ 2076 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2077 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2078 { 2079 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2080 PetscErrorCode ierr; 2081 2082 PetscFunctionBegin; 2083 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2084 PetscFunctionReturn(0); 2085 } 2086 2087 #undef __FUNCT__ 2088 #define __FUNCT__ "MatEqual_MPIAIJ" 2089 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2090 { 2091 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2092 Mat a,b,c,d; 2093 PetscBool flg; 2094 PetscErrorCode ierr; 2095 2096 PetscFunctionBegin; 2097 a = matA->A; b = matA->B; 2098 c = matB->A; d = matB->B; 2099 2100 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2101 if (flg) { 2102 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2103 } 2104 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2105 PetscFunctionReturn(0); 2106 } 2107 2108 #undef __FUNCT__ 2109 #define __FUNCT__ "MatCopy_MPIAIJ" 2110 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2111 { 2112 PetscErrorCode ierr; 2113 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2114 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2115 2116 PetscFunctionBegin; 2117 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2118 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2119 /* because of the column compression in the off-processor part of the matrix a->B, 2120 the number of columns in a->B and b->B may be different, hence we cannot call 2121 the MatCopy() directly on the two parts. If need be, we can provide a more 2122 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2123 then copying the submatrices */ 2124 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2125 } else { 2126 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2127 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2128 } 2129 PetscFunctionReturn(0); 2130 } 2131 2132 #undef __FUNCT__ 2133 #define __FUNCT__ "MatSetUp_MPIAIJ" 2134 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2135 { 2136 PetscErrorCode ierr; 2137 2138 PetscFunctionBegin; 2139 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2140 PetscFunctionReturn(0); 2141 } 2142 2143 /* 2144 Computes the number of nonzeros per row needed for preallocation when X and Y 2145 have different nonzero structure. 2146 */ 2147 #undef __FUNCT__ 2148 #define __FUNCT__ "MatAXPYGetPreallocation_MPIX_private" 2149 PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *xltog,const PetscInt *yi,const PetscInt *yj,const PetscInt *yltog,PetscInt *nnz) 2150 { 2151 PetscInt i,j,k,nzx,nzy; 2152 2153 PetscFunctionBegin; 2154 /* Set the number of nonzeros in the new matrix */ 2155 for (i=0; i<m; i++) { 2156 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2157 nzx = xi[i+1] - xi[i]; 2158 nzy = yi[i+1] - yi[i]; 2159 nnz[i] = 0; 2160 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2161 for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */ 2162 if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */ 2163 nnz[i]++; 2164 } 2165 for (; k<nzy; k++) nnz[i]++; 2166 } 2167 PetscFunctionReturn(0); 2168 } 2169 2170 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2171 #undef __FUNCT__ 2172 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2173 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2174 { 2175 PetscErrorCode ierr; 2176 PetscInt m = Y->rmap->N; 2177 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2178 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2179 2180 PetscFunctionBegin; 2181 ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr); 2182 PetscFunctionReturn(0); 2183 } 2184 2185 #undef __FUNCT__ 2186 #define __FUNCT__ "MatAXPY_MPIAIJ" 2187 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2188 { 2189 PetscErrorCode ierr; 2190 PetscInt i; 2191 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2192 PetscBLASInt bnz,one=1; 2193 Mat_SeqAIJ *x,*y; 2194 2195 PetscFunctionBegin; 2196 if (str == SAME_NONZERO_PATTERN) { 2197 PetscScalar alpha = a; 2198 x = (Mat_SeqAIJ*)xx->A->data; 2199 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2200 y = (Mat_SeqAIJ*)yy->A->data; 2201 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2202 x = (Mat_SeqAIJ*)xx->B->data; 2203 y = (Mat_SeqAIJ*)yy->B->data; 2204 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2205 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2206 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2207 } else if (str == SUBSET_NONZERO_PATTERN) { 2208 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2209 2210 x = (Mat_SeqAIJ*)xx->B->data; 2211 y = (Mat_SeqAIJ*)yy->B->data; 2212 if (y->xtoy && y->XtoY != xx->B) { 2213 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2214 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2215 } 2216 if (!y->xtoy) { /* get xtoy */ 2217 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2218 y->XtoY = xx->B; 2219 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2220 } 2221 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2222 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2223 } else { 2224 Mat B; 2225 PetscInt *nnz_d,*nnz_o; 2226 ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr); 2227 ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr); 2228 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2229 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2230 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2231 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2232 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2233 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2234 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2235 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2236 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2237 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2238 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2239 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2240 } 2241 PetscFunctionReturn(0); 2242 } 2243 2244 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2245 2246 #undef __FUNCT__ 2247 #define __FUNCT__ "MatConjugate_MPIAIJ" 2248 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2249 { 2250 #if defined(PETSC_USE_COMPLEX) 2251 PetscErrorCode ierr; 2252 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2253 2254 PetscFunctionBegin; 2255 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2256 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2257 #else 2258 PetscFunctionBegin; 2259 #endif 2260 PetscFunctionReturn(0); 2261 } 2262 2263 #undef __FUNCT__ 2264 #define __FUNCT__ "MatRealPart_MPIAIJ" 2265 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2266 { 2267 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2268 PetscErrorCode ierr; 2269 2270 PetscFunctionBegin; 2271 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2272 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2273 PetscFunctionReturn(0); 2274 } 2275 2276 #undef __FUNCT__ 2277 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2278 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2279 { 2280 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2281 PetscErrorCode ierr; 2282 2283 PetscFunctionBegin; 2284 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2285 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2286 PetscFunctionReturn(0); 2287 } 2288 2289 #if defined(PETSC_HAVE_PBGL) 2290 2291 #include <boost/parallel/mpi/bsp_process_group.hpp> 2292 #include <boost/graph/distributed/ilu_default_graph.hpp> 2293 #include <boost/graph/distributed/ilu_0_block.hpp> 2294 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2295 #include <boost/graph/distributed/petsc/interface.hpp> 2296 #include <boost/multi_array.hpp> 2297 #include <boost/parallel/distributed_property_map->hpp> 2298 2299 #undef __FUNCT__ 2300 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2301 /* 2302 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2303 */ 2304 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2305 { 2306 namespace petsc = boost::distributed::petsc; 2307 2308 namespace graph_dist = boost::graph::distributed; 2309 using boost::graph::distributed::ilu_default::process_group_type; 2310 using boost::graph::ilu_permuted; 2311 2312 PetscBool row_identity, col_identity; 2313 PetscContainer c; 2314 PetscInt m, n, M, N; 2315 PetscErrorCode ierr; 2316 2317 PetscFunctionBegin; 2318 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2319 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2320 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2321 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2322 2323 process_group_type pg; 2324 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2325 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2326 lgraph_type& level_graph = *lgraph_p; 2327 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2328 2329 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2330 ilu_permuted(level_graph); 2331 2332 /* put together the new matrix */ 2333 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2334 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2335 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2336 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2337 ierr = MatSetBlockSizesFromMats(fact,A,A);CHKERRQ(ierr); 2338 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2339 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2340 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2341 2342 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2343 ierr = PetscContainerSetPointer(c, lgraph_p); 2344 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2345 ierr = PetscContainerDestroy(&c); 2346 PetscFunctionReturn(0); 2347 } 2348 2349 #undef __FUNCT__ 2350 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2351 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2352 { 2353 PetscFunctionBegin; 2354 PetscFunctionReturn(0); 2355 } 2356 2357 #undef __FUNCT__ 2358 #define __FUNCT__ "MatSolve_MPIAIJ" 2359 /* 2360 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2361 */ 2362 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2363 { 2364 namespace graph_dist = boost::graph::distributed; 2365 2366 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2367 lgraph_type *lgraph_p; 2368 PetscContainer c; 2369 PetscErrorCode ierr; 2370 2371 PetscFunctionBegin; 2372 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2373 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2374 ierr = VecCopy(b, x);CHKERRQ(ierr); 2375 2376 PetscScalar *array_x; 2377 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2378 PetscInt sx; 2379 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2380 2381 PetscScalar *array_b; 2382 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2383 PetscInt sb; 2384 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2385 2386 lgraph_type& level_graph = *lgraph_p; 2387 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2388 2389 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2390 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2391 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2392 2393 typedef boost::iterator_property_map<array_ref_type::iterator, 2394 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2395 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2396 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2397 2398 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2399 PetscFunctionReturn(0); 2400 } 2401 #endif 2402 2403 #undef __FUNCT__ 2404 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2405 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2406 { 2407 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2408 PetscErrorCode ierr; 2409 PetscInt i,*idxb = 0; 2410 PetscScalar *va,*vb; 2411 Vec vtmp; 2412 2413 PetscFunctionBegin; 2414 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2415 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2416 if (idx) { 2417 for (i=0; i<A->rmap->n; i++) { 2418 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2419 } 2420 } 2421 2422 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2423 if (idx) { 2424 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2425 } 2426 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2427 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2428 2429 for (i=0; i<A->rmap->n; i++) { 2430 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2431 va[i] = vb[i]; 2432 if (idx) idx[i] = a->garray[idxb[i]]; 2433 } 2434 } 2435 2436 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2437 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2438 ierr = PetscFree(idxb);CHKERRQ(ierr); 2439 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2440 PetscFunctionReturn(0); 2441 } 2442 2443 #undef __FUNCT__ 2444 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2445 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2446 { 2447 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2448 PetscErrorCode ierr; 2449 PetscInt i,*idxb = 0; 2450 PetscScalar *va,*vb; 2451 Vec vtmp; 2452 2453 PetscFunctionBegin; 2454 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2455 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2456 if (idx) { 2457 for (i=0; i<A->cmap->n; i++) { 2458 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2459 } 2460 } 2461 2462 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2463 if (idx) { 2464 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2465 } 2466 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2467 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2468 2469 for (i=0; i<A->rmap->n; i++) { 2470 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2471 va[i] = vb[i]; 2472 if (idx) idx[i] = a->garray[idxb[i]]; 2473 } 2474 } 2475 2476 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2477 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2478 ierr = PetscFree(idxb);CHKERRQ(ierr); 2479 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2480 PetscFunctionReturn(0); 2481 } 2482 2483 #undef __FUNCT__ 2484 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2485 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2486 { 2487 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2488 PetscInt n = A->rmap->n; 2489 PetscInt cstart = A->cmap->rstart; 2490 PetscInt *cmap = mat->garray; 2491 PetscInt *diagIdx, *offdiagIdx; 2492 Vec diagV, offdiagV; 2493 PetscScalar *a, *diagA, *offdiagA; 2494 PetscInt r; 2495 PetscErrorCode ierr; 2496 2497 PetscFunctionBegin; 2498 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2499 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2500 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2501 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2502 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2503 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2504 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2505 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2506 for (r = 0; r < n; ++r) { 2507 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2508 a[r] = diagA[r]; 2509 idx[r] = cstart + diagIdx[r]; 2510 } else { 2511 a[r] = offdiagA[r]; 2512 idx[r] = cmap[offdiagIdx[r]]; 2513 } 2514 } 2515 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2516 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2517 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2518 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2519 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2520 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2521 PetscFunctionReturn(0); 2522 } 2523 2524 #undef __FUNCT__ 2525 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2526 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2527 { 2528 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2529 PetscInt n = A->rmap->n; 2530 PetscInt cstart = A->cmap->rstart; 2531 PetscInt *cmap = mat->garray; 2532 PetscInt *diagIdx, *offdiagIdx; 2533 Vec diagV, offdiagV; 2534 PetscScalar *a, *diagA, *offdiagA; 2535 PetscInt r; 2536 PetscErrorCode ierr; 2537 2538 PetscFunctionBegin; 2539 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2540 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2541 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2542 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2543 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2544 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2545 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2546 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2547 for (r = 0; r < n; ++r) { 2548 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2549 a[r] = diagA[r]; 2550 idx[r] = cstart + diagIdx[r]; 2551 } else { 2552 a[r] = offdiagA[r]; 2553 idx[r] = cmap[offdiagIdx[r]]; 2554 } 2555 } 2556 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2557 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2558 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2559 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2560 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2561 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2562 PetscFunctionReturn(0); 2563 } 2564 2565 #undef __FUNCT__ 2566 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2567 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2568 { 2569 PetscErrorCode ierr; 2570 Mat *dummy; 2571 2572 PetscFunctionBegin; 2573 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2574 *newmat = *dummy; 2575 ierr = PetscFree(dummy);CHKERRQ(ierr); 2576 PetscFunctionReturn(0); 2577 } 2578 2579 #undef __FUNCT__ 2580 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 2581 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 2582 { 2583 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 2584 PetscErrorCode ierr; 2585 2586 PetscFunctionBegin; 2587 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 2588 PetscFunctionReturn(0); 2589 } 2590 2591 #undef __FUNCT__ 2592 #define __FUNCT__ "MatSetRandom_MPIAIJ" 2593 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 2594 { 2595 PetscErrorCode ierr; 2596 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 2597 2598 PetscFunctionBegin; 2599 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 2600 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 2601 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2602 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2603 PetscFunctionReturn(0); 2604 } 2605 2606 /* -------------------------------------------------------------------*/ 2607 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 2608 MatGetRow_MPIAIJ, 2609 MatRestoreRow_MPIAIJ, 2610 MatMult_MPIAIJ, 2611 /* 4*/ MatMultAdd_MPIAIJ, 2612 MatMultTranspose_MPIAIJ, 2613 MatMultTransposeAdd_MPIAIJ, 2614 #if defined(PETSC_HAVE_PBGL) 2615 MatSolve_MPIAIJ, 2616 #else 2617 0, 2618 #endif 2619 0, 2620 0, 2621 /*10*/ 0, 2622 0, 2623 0, 2624 MatSOR_MPIAIJ, 2625 MatTranspose_MPIAIJ, 2626 /*15*/ MatGetInfo_MPIAIJ, 2627 MatEqual_MPIAIJ, 2628 MatGetDiagonal_MPIAIJ, 2629 MatDiagonalScale_MPIAIJ, 2630 MatNorm_MPIAIJ, 2631 /*20*/ MatAssemblyBegin_MPIAIJ, 2632 MatAssemblyEnd_MPIAIJ, 2633 MatSetOption_MPIAIJ, 2634 MatZeroEntries_MPIAIJ, 2635 /*24*/ MatZeroRows_MPIAIJ, 2636 0, 2637 #if defined(PETSC_HAVE_PBGL) 2638 0, 2639 #else 2640 0, 2641 #endif 2642 0, 2643 0, 2644 /*29*/ MatSetUp_MPIAIJ, 2645 #if defined(PETSC_HAVE_PBGL) 2646 0, 2647 #else 2648 0, 2649 #endif 2650 0, 2651 0, 2652 0, 2653 /*34*/ MatDuplicate_MPIAIJ, 2654 0, 2655 0, 2656 0, 2657 0, 2658 /*39*/ MatAXPY_MPIAIJ, 2659 MatGetSubMatrices_MPIAIJ, 2660 MatIncreaseOverlap_MPIAIJ, 2661 MatGetValues_MPIAIJ, 2662 MatCopy_MPIAIJ, 2663 /*44*/ MatGetRowMax_MPIAIJ, 2664 MatScale_MPIAIJ, 2665 0, 2666 MatDiagonalSet_MPIAIJ, 2667 MatZeroRowsColumns_MPIAIJ, 2668 /*49*/ MatSetRandom_MPIAIJ, 2669 0, 2670 0, 2671 0, 2672 0, 2673 /*54*/ MatFDColoringCreate_MPIXAIJ, 2674 0, 2675 MatSetUnfactored_MPIAIJ, 2676 MatPermute_MPIAIJ, 2677 0, 2678 /*59*/ MatGetSubMatrix_MPIAIJ, 2679 MatDestroy_MPIAIJ, 2680 MatView_MPIAIJ, 2681 0, 2682 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 2683 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 2684 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 2685 0, 2686 0, 2687 0, 2688 /*69*/ MatGetRowMaxAbs_MPIAIJ, 2689 MatGetRowMinAbs_MPIAIJ, 2690 0, 2691 MatSetColoring_MPIAIJ, 2692 0, 2693 MatSetValuesAdifor_MPIAIJ, 2694 /*75*/ MatFDColoringApply_AIJ, 2695 0, 2696 0, 2697 0, 2698 MatFindZeroDiagonals_MPIAIJ, 2699 /*80*/ 0, 2700 0, 2701 0, 2702 /*83*/ MatLoad_MPIAIJ, 2703 0, 2704 0, 2705 0, 2706 0, 2707 0, 2708 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 2709 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 2710 MatMatMultNumeric_MPIAIJ_MPIAIJ, 2711 MatPtAP_MPIAIJ_MPIAIJ, 2712 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 2713 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 2714 0, 2715 0, 2716 0, 2717 0, 2718 /*99*/ 0, 2719 0, 2720 0, 2721 MatConjugate_MPIAIJ, 2722 0, 2723 /*104*/MatSetValuesRow_MPIAIJ, 2724 MatRealPart_MPIAIJ, 2725 MatImaginaryPart_MPIAIJ, 2726 0, 2727 0, 2728 /*109*/0, 2729 0, 2730 MatGetRowMin_MPIAIJ, 2731 0, 2732 0, 2733 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 2734 0, 2735 0, 2736 0, 2737 0, 2738 /*119*/0, 2739 0, 2740 0, 2741 0, 2742 MatGetMultiProcBlock_MPIAIJ, 2743 /*124*/MatFindNonzeroRows_MPIAIJ, 2744 MatGetColumnNorms_MPIAIJ, 2745 MatInvertBlockDiagonal_MPIAIJ, 2746 0, 2747 MatGetSubMatricesParallel_MPIAIJ, 2748 /*129*/0, 2749 MatTransposeMatMult_MPIAIJ_MPIAIJ, 2750 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 2751 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 2752 0, 2753 /*134*/0, 2754 0, 2755 0, 2756 0, 2757 0, 2758 /*139*/0, 2759 0, 2760 0, 2761 MatFDColoringSetUp_MPIXAIJ, 2762 0, 2763 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 2764 }; 2765 2766 /* ----------------------------------------------------------------------------------------*/ 2767 2768 #undef __FUNCT__ 2769 #define __FUNCT__ "MatStoreValues_MPIAIJ" 2770 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 2771 { 2772 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2773 PetscErrorCode ierr; 2774 2775 PetscFunctionBegin; 2776 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 2777 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 2778 PetscFunctionReturn(0); 2779 } 2780 2781 #undef __FUNCT__ 2782 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 2783 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 2784 { 2785 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2786 PetscErrorCode ierr; 2787 2788 PetscFunctionBegin; 2789 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 2790 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 2791 PetscFunctionReturn(0); 2792 } 2793 2794 #undef __FUNCT__ 2795 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 2796 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 2797 { 2798 Mat_MPIAIJ *b; 2799 PetscErrorCode ierr; 2800 2801 PetscFunctionBegin; 2802 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2803 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2804 b = (Mat_MPIAIJ*)B->data; 2805 2806 if (!B->preallocated) { 2807 /* Explicitly create 2 MATSEQAIJ matrices. */ 2808 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 2809 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 2810 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 2811 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 2812 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 2813 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 2814 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 2815 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 2816 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 2817 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 2818 } 2819 2820 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 2821 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 2822 B->preallocated = PETSC_TRUE; 2823 PetscFunctionReturn(0); 2824 } 2825 2826 #undef __FUNCT__ 2827 #define __FUNCT__ "MatDuplicate_MPIAIJ" 2828 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 2829 { 2830 Mat mat; 2831 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 2832 PetscErrorCode ierr; 2833 2834 PetscFunctionBegin; 2835 *newmat = 0; 2836 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 2837 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 2838 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 2839 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 2840 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 2841 a = (Mat_MPIAIJ*)mat->data; 2842 2843 mat->factortype = matin->factortype; 2844 mat->assembled = PETSC_TRUE; 2845 mat->insertmode = NOT_SET_VALUES; 2846 mat->preallocated = PETSC_TRUE; 2847 2848 a->size = oldmat->size; 2849 a->rank = oldmat->rank; 2850 a->donotstash = oldmat->donotstash; 2851 a->roworiented = oldmat->roworiented; 2852 a->rowindices = 0; 2853 a->rowvalues = 0; 2854 a->getrowactive = PETSC_FALSE; 2855 2856 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 2857 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 2858 2859 if (oldmat->colmap) { 2860 #if defined(PETSC_USE_CTABLE) 2861 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 2862 #else 2863 ierr = PetscMalloc1((mat->cmap->N),&a->colmap);CHKERRQ(ierr); 2864 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2865 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 2866 #endif 2867 } else a->colmap = 0; 2868 if (oldmat->garray) { 2869 PetscInt len; 2870 len = oldmat->B->cmap->n; 2871 ierr = PetscMalloc1((len+1),&a->garray);CHKERRQ(ierr); 2872 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 2873 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 2874 } else a->garray = 0; 2875 2876 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 2877 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 2878 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 2879 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 2880 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 2881 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 2882 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 2883 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 2884 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 2885 *newmat = mat; 2886 PetscFunctionReturn(0); 2887 } 2888 2889 2890 2891 #undef __FUNCT__ 2892 #define __FUNCT__ "MatLoad_MPIAIJ" 2893 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 2894 { 2895 PetscScalar *vals,*svals; 2896 MPI_Comm comm; 2897 PetscErrorCode ierr; 2898 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 2899 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 2900 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 2901 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 2902 PetscInt cend,cstart,n,*rowners,sizesset=1; 2903 int fd; 2904 PetscInt bs = 1; 2905 2906 PetscFunctionBegin; 2907 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 2908 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2909 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2910 if (!rank) { 2911 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 2912 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 2913 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 2914 } 2915 2916 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 2917 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 2918 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2919 2920 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 2921 2922 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 2923 M = header[1]; N = header[2]; 2924 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 2925 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 2926 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 2927 2928 /* If global sizes are set, check if they are consistent with that given in the file */ 2929 if (sizesset) { 2930 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 2931 } 2932 if (sizesset && newMat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows); 2933 if (sizesset && newMat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols); 2934 2935 /* determine ownership of all (block) rows */ 2936 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 2937 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 2938 else m = newMat->rmap->n; /* Set by user */ 2939 2940 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 2941 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 2942 2943 /* First process needs enough room for process with most rows */ 2944 if (!rank) { 2945 mmax = rowners[1]; 2946 for (i=2; i<=size; i++) { 2947 mmax = PetscMax(mmax, rowners[i]); 2948 } 2949 } else mmax = -1; /* unused, but compilers complain */ 2950 2951 rowners[0] = 0; 2952 for (i=2; i<=size; i++) { 2953 rowners[i] += rowners[i-1]; 2954 } 2955 rstart = rowners[rank]; 2956 rend = rowners[rank+1]; 2957 2958 /* distribute row lengths to all processors */ 2959 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 2960 if (!rank) { 2961 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 2962 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 2963 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 2964 for (j=0; j<m; j++) { 2965 procsnz[0] += ourlens[j]; 2966 } 2967 for (i=1; i<size; i++) { 2968 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 2969 /* calculate the number of nonzeros on each processor */ 2970 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 2971 procsnz[i] += rowlengths[j]; 2972 } 2973 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2974 } 2975 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2976 } else { 2977 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 2978 } 2979 2980 if (!rank) { 2981 /* determine max buffer needed and allocate it */ 2982 maxnz = 0; 2983 for (i=0; i<size; i++) { 2984 maxnz = PetscMax(maxnz,procsnz[i]); 2985 } 2986 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 2987 2988 /* read in my part of the matrix column indices */ 2989 nz = procsnz[0]; 2990 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 2991 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2992 2993 /* read in every one elses and ship off */ 2994 for (i=1; i<size; i++) { 2995 nz = procsnz[i]; 2996 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2997 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 2998 } 2999 ierr = PetscFree(cols);CHKERRQ(ierr); 3000 } else { 3001 /* determine buffer space needed for message */ 3002 nz = 0; 3003 for (i=0; i<m; i++) { 3004 nz += ourlens[i]; 3005 } 3006 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3007 3008 /* receive message of column indices*/ 3009 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3010 } 3011 3012 /* determine column ownership if matrix is not square */ 3013 if (N != M) { 3014 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3015 else n = newMat->cmap->n; 3016 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3017 cstart = cend - n; 3018 } else { 3019 cstart = rstart; 3020 cend = rend; 3021 n = cend - cstart; 3022 } 3023 3024 /* loop over local rows, determining number of off diagonal entries */ 3025 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3026 jj = 0; 3027 for (i=0; i<m; i++) { 3028 for (j=0; j<ourlens[i]; j++) { 3029 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3030 jj++; 3031 } 3032 } 3033 3034 for (i=0; i<m; i++) { 3035 ourlens[i] -= offlens[i]; 3036 } 3037 if (!sizesset) { 3038 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3039 } 3040 3041 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3042 3043 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3044 3045 for (i=0; i<m; i++) { 3046 ourlens[i] += offlens[i]; 3047 } 3048 3049 if (!rank) { 3050 ierr = PetscMalloc1((maxnz+1),&vals);CHKERRQ(ierr); 3051 3052 /* read in my part of the matrix numerical values */ 3053 nz = procsnz[0]; 3054 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3055 3056 /* insert into matrix */ 3057 jj = rstart; 3058 smycols = mycols; 3059 svals = vals; 3060 for (i=0; i<m; i++) { 3061 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3062 smycols += ourlens[i]; 3063 svals += ourlens[i]; 3064 jj++; 3065 } 3066 3067 /* read in other processors and ship out */ 3068 for (i=1; i<size; i++) { 3069 nz = procsnz[i]; 3070 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3071 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3072 } 3073 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3074 } else { 3075 /* receive numeric values */ 3076 ierr = PetscMalloc1((nz+1),&vals);CHKERRQ(ierr); 3077 3078 /* receive message of values*/ 3079 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3080 3081 /* insert into matrix */ 3082 jj = rstart; 3083 smycols = mycols; 3084 svals = vals; 3085 for (i=0; i<m; i++) { 3086 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3087 smycols += ourlens[i]; 3088 svals += ourlens[i]; 3089 jj++; 3090 } 3091 } 3092 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3093 ierr = PetscFree(vals);CHKERRQ(ierr); 3094 ierr = PetscFree(mycols);CHKERRQ(ierr); 3095 ierr = PetscFree(rowners);CHKERRQ(ierr); 3096 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3097 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3098 PetscFunctionReturn(0); 3099 } 3100 3101 #undef __FUNCT__ 3102 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3103 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3104 { 3105 PetscErrorCode ierr; 3106 IS iscol_local; 3107 PetscInt csize; 3108 3109 PetscFunctionBegin; 3110 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3111 if (call == MAT_REUSE_MATRIX) { 3112 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3113 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3114 } else { 3115 PetscInt cbs; 3116 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3117 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3118 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3119 } 3120 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3121 if (call == MAT_INITIAL_MATRIX) { 3122 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3123 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3124 } 3125 PetscFunctionReturn(0); 3126 } 3127 3128 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3129 #undef __FUNCT__ 3130 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3131 /* 3132 Not great since it makes two copies of the submatrix, first an SeqAIJ 3133 in local and then by concatenating the local matrices the end result. 3134 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3135 3136 Note: This requires a sequential iscol with all indices. 3137 */ 3138 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3139 { 3140 PetscErrorCode ierr; 3141 PetscMPIInt rank,size; 3142 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3143 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3144 PetscBool allcolumns, colflag; 3145 Mat M,Mreuse; 3146 MatScalar *vwork,*aa; 3147 MPI_Comm comm; 3148 Mat_SeqAIJ *aij; 3149 3150 PetscFunctionBegin; 3151 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3152 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3153 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3154 3155 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3156 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3157 if (colflag && ncol == mat->cmap->N) { 3158 allcolumns = PETSC_TRUE; 3159 } else { 3160 allcolumns = PETSC_FALSE; 3161 } 3162 if (call == MAT_REUSE_MATRIX) { 3163 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3164 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3165 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3166 } else { 3167 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3168 } 3169 3170 /* 3171 m - number of local rows 3172 n - number of columns (same on all processors) 3173 rstart - first row in new global matrix generated 3174 */ 3175 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3176 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3177 if (call == MAT_INITIAL_MATRIX) { 3178 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3179 ii = aij->i; 3180 jj = aij->j; 3181 3182 /* 3183 Determine the number of non-zeros in the diagonal and off-diagonal 3184 portions of the matrix in order to do correct preallocation 3185 */ 3186 3187 /* first get start and end of "diagonal" columns */ 3188 if (csize == PETSC_DECIDE) { 3189 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3190 if (mglobal == n) { /* square matrix */ 3191 nlocal = m; 3192 } else { 3193 nlocal = n/size + ((n % size) > rank); 3194 } 3195 } else { 3196 nlocal = csize; 3197 } 3198 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3199 rstart = rend - nlocal; 3200 if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n); 3201 3202 /* next, compute all the lengths */ 3203 ierr = PetscMalloc1((2*m+1),&dlens);CHKERRQ(ierr); 3204 olens = dlens + m; 3205 for (i=0; i<m; i++) { 3206 jend = ii[i+1] - ii[i]; 3207 olen = 0; 3208 dlen = 0; 3209 for (j=0; j<jend; j++) { 3210 if (*jj < rstart || *jj >= rend) olen++; 3211 else dlen++; 3212 jj++; 3213 } 3214 olens[i] = olen; 3215 dlens[i] = dlen; 3216 } 3217 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3218 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3219 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3220 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3221 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3222 ierr = PetscFree(dlens);CHKERRQ(ierr); 3223 } else { 3224 PetscInt ml,nl; 3225 3226 M = *newmat; 3227 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3228 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3229 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3230 /* 3231 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3232 rather than the slower MatSetValues(). 3233 */ 3234 M->was_assembled = PETSC_TRUE; 3235 M->assembled = PETSC_FALSE; 3236 } 3237 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3238 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3239 ii = aij->i; 3240 jj = aij->j; 3241 aa = aij->a; 3242 for (i=0; i<m; i++) { 3243 row = rstart + i; 3244 nz = ii[i+1] - ii[i]; 3245 cwork = jj; jj += nz; 3246 vwork = aa; aa += nz; 3247 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3248 } 3249 3250 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3251 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3252 *newmat = M; 3253 3254 /* save submatrix used in processor for next request */ 3255 if (call == MAT_INITIAL_MATRIX) { 3256 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3257 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3258 } 3259 PetscFunctionReturn(0); 3260 } 3261 3262 #undef __FUNCT__ 3263 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3264 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3265 { 3266 PetscInt m,cstart, cend,j,nnz,i,d; 3267 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3268 const PetscInt *JJ; 3269 PetscScalar *values; 3270 PetscErrorCode ierr; 3271 3272 PetscFunctionBegin; 3273 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3274 3275 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3276 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3277 m = B->rmap->n; 3278 cstart = B->cmap->rstart; 3279 cend = B->cmap->rend; 3280 rstart = B->rmap->rstart; 3281 3282 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3283 3284 #if defined(PETSC_USE_DEBUGGING) 3285 for (i=0; i<m; i++) { 3286 nnz = Ii[i+1]- Ii[i]; 3287 JJ = J + Ii[i]; 3288 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3289 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3290 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); 3291 } 3292 #endif 3293 3294 for (i=0; i<m; i++) { 3295 nnz = Ii[i+1]- Ii[i]; 3296 JJ = J + Ii[i]; 3297 nnz_max = PetscMax(nnz_max,nnz); 3298 d = 0; 3299 for (j=0; j<nnz; j++) { 3300 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3301 } 3302 d_nnz[i] = d; 3303 o_nnz[i] = nnz - d; 3304 } 3305 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3306 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3307 3308 if (v) values = (PetscScalar*)v; 3309 else { 3310 ierr = PetscCalloc1((nnz_max+1),&values);CHKERRQ(ierr); 3311 } 3312 3313 for (i=0; i<m; i++) { 3314 ii = i + rstart; 3315 nnz = Ii[i+1]- Ii[i]; 3316 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3317 } 3318 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3319 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3320 3321 if (!v) { 3322 ierr = PetscFree(values);CHKERRQ(ierr); 3323 } 3324 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3325 PetscFunctionReturn(0); 3326 } 3327 3328 #undef __FUNCT__ 3329 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3330 /*@ 3331 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3332 (the default parallel PETSc format). 3333 3334 Collective on MPI_Comm 3335 3336 Input Parameters: 3337 + B - the matrix 3338 . i - the indices into j for the start of each local row (starts with zero) 3339 . j - the column indices for each local row (starts with zero) 3340 - v - optional values in the matrix 3341 3342 Level: developer 3343 3344 Notes: 3345 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3346 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3347 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3348 3349 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3350 3351 The format which is used for the sparse matrix input, is equivalent to a 3352 row-major ordering.. i.e for the following matrix, the input data expected is 3353 as shown: 3354 3355 1 0 0 3356 2 0 3 P0 3357 ------- 3358 4 5 6 P1 3359 3360 Process0 [P0]: rows_owned=[0,1] 3361 i = {0,1,3} [size = nrow+1 = 2+1] 3362 j = {0,0,2} [size = nz = 6] 3363 v = {1,2,3} [size = nz = 6] 3364 3365 Process1 [P1]: rows_owned=[2] 3366 i = {0,3} [size = nrow+1 = 1+1] 3367 j = {0,1,2} [size = nz = 6] 3368 v = {4,5,6} [size = nz = 6] 3369 3370 .keywords: matrix, aij, compressed row, sparse, parallel 3371 3372 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3373 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3374 @*/ 3375 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3376 { 3377 PetscErrorCode ierr; 3378 3379 PetscFunctionBegin; 3380 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3381 PetscFunctionReturn(0); 3382 } 3383 3384 #undef __FUNCT__ 3385 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3386 /*@C 3387 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3388 (the default parallel PETSc format). For good matrix assembly performance 3389 the user should preallocate the matrix storage by setting the parameters 3390 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3391 performance can be increased by more than a factor of 50. 3392 3393 Collective on MPI_Comm 3394 3395 Input Parameters: 3396 + B - the matrix 3397 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3398 (same value is used for all local rows) 3399 . d_nnz - array containing the number of nonzeros in the various rows of the 3400 DIAGONAL portion of the local submatrix (possibly different for each row) 3401 or NULL, if d_nz is used to specify the nonzero structure. 3402 The size of this array is equal to the number of local rows, i.e 'm'. 3403 For matrices that will be factored, you must leave room for (and set) 3404 the diagonal entry even if it is zero. 3405 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3406 submatrix (same value is used for all local rows). 3407 - o_nnz - array containing the number of nonzeros in the various rows of the 3408 OFF-DIAGONAL portion of the local submatrix (possibly different for 3409 each row) or NULL, if o_nz is used to specify the nonzero 3410 structure. The size of this array is equal to the number 3411 of local rows, i.e 'm'. 3412 3413 If the *_nnz parameter is given then the *_nz parameter is ignored 3414 3415 The AIJ format (also called the Yale sparse matrix format or 3416 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3417 storage. The stored row and column indices begin with zero. 3418 See Users-Manual: ch_mat for details. 3419 3420 The parallel matrix is partitioned such that the first m0 rows belong to 3421 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3422 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3423 3424 The DIAGONAL portion of the local submatrix of a processor can be defined 3425 as the submatrix which is obtained by extraction the part corresponding to 3426 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3427 first row that belongs to the processor, r2 is the last row belonging to 3428 the this processor, and c1-c2 is range of indices of the local part of a 3429 vector suitable for applying the matrix to. This is an mxn matrix. In the 3430 common case of a square matrix, the row and column ranges are the same and 3431 the DIAGONAL part is also square. The remaining portion of the local 3432 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3433 3434 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3435 3436 You can call MatGetInfo() to get information on how effective the preallocation was; 3437 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3438 You can also run with the option -info and look for messages with the string 3439 malloc in them to see if additional memory allocation was needed. 3440 3441 Example usage: 3442 3443 Consider the following 8x8 matrix with 34 non-zero values, that is 3444 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3445 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3446 as follows: 3447 3448 .vb 3449 1 2 0 | 0 3 0 | 0 4 3450 Proc0 0 5 6 | 7 0 0 | 8 0 3451 9 0 10 | 11 0 0 | 12 0 3452 ------------------------------------- 3453 13 0 14 | 15 16 17 | 0 0 3454 Proc1 0 18 0 | 19 20 21 | 0 0 3455 0 0 0 | 22 23 0 | 24 0 3456 ------------------------------------- 3457 Proc2 25 26 27 | 0 0 28 | 29 0 3458 30 0 0 | 31 32 33 | 0 34 3459 .ve 3460 3461 This can be represented as a collection of submatrices as: 3462 3463 .vb 3464 A B C 3465 D E F 3466 G H I 3467 .ve 3468 3469 Where the submatrices A,B,C are owned by proc0, D,E,F are 3470 owned by proc1, G,H,I are owned by proc2. 3471 3472 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3473 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3474 The 'M','N' parameters are 8,8, and have the same values on all procs. 3475 3476 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3477 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3478 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3479 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3480 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3481 matrix, ans [DF] as another SeqAIJ matrix. 3482 3483 When d_nz, o_nz parameters are specified, d_nz storage elements are 3484 allocated for every row of the local diagonal submatrix, and o_nz 3485 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3486 One way to choose d_nz and o_nz is to use the max nonzerors per local 3487 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3488 In this case, the values of d_nz,o_nz are: 3489 .vb 3490 proc0 : dnz = 2, o_nz = 2 3491 proc1 : dnz = 3, o_nz = 2 3492 proc2 : dnz = 1, o_nz = 4 3493 .ve 3494 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3495 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3496 for proc3. i.e we are using 12+15+10=37 storage locations to store 3497 34 values. 3498 3499 When d_nnz, o_nnz parameters are specified, the storage is specified 3500 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3501 In the above case the values for d_nnz,o_nnz are: 3502 .vb 3503 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3504 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3505 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3506 .ve 3507 Here the space allocated is sum of all the above values i.e 34, and 3508 hence pre-allocation is perfect. 3509 3510 Level: intermediate 3511 3512 .keywords: matrix, aij, compressed row, sparse, parallel 3513 3514 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3515 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3516 @*/ 3517 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3518 { 3519 PetscErrorCode ierr; 3520 3521 PetscFunctionBegin; 3522 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3523 PetscValidType(B,1); 3524 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3525 PetscFunctionReturn(0); 3526 } 3527 3528 #undef __FUNCT__ 3529 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3530 /*@ 3531 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3532 CSR format the local rows. 3533 3534 Collective on MPI_Comm 3535 3536 Input Parameters: 3537 + comm - MPI communicator 3538 . m - number of local rows (Cannot be PETSC_DECIDE) 3539 . n - This value should be the same as the local size used in creating the 3540 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3541 calculated if N is given) For square matrices n is almost always m. 3542 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3543 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3544 . i - row indices 3545 . j - column indices 3546 - a - matrix values 3547 3548 Output Parameter: 3549 . mat - the matrix 3550 3551 Level: intermediate 3552 3553 Notes: 3554 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3555 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3556 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3557 3558 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3559 3560 The format which is used for the sparse matrix input, is equivalent to a 3561 row-major ordering.. i.e for the following matrix, the input data expected is 3562 as shown: 3563 3564 1 0 0 3565 2 0 3 P0 3566 ------- 3567 4 5 6 P1 3568 3569 Process0 [P0]: rows_owned=[0,1] 3570 i = {0,1,3} [size = nrow+1 = 2+1] 3571 j = {0,0,2} [size = nz = 6] 3572 v = {1,2,3} [size = nz = 6] 3573 3574 Process1 [P1]: rows_owned=[2] 3575 i = {0,3} [size = nrow+1 = 1+1] 3576 j = {0,1,2} [size = nz = 6] 3577 v = {4,5,6} [size = nz = 6] 3578 3579 .keywords: matrix, aij, compressed row, sparse, parallel 3580 3581 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3582 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 3583 @*/ 3584 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 3585 { 3586 PetscErrorCode ierr; 3587 3588 PetscFunctionBegin; 3589 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3590 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 3591 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3592 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 3593 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 3594 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 3595 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 3596 PetscFunctionReturn(0); 3597 } 3598 3599 #undef __FUNCT__ 3600 #define __FUNCT__ "MatCreateAIJ" 3601 /*@C 3602 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 3603 (the default parallel PETSc format). For good matrix assembly performance 3604 the user should preallocate the matrix storage by setting the parameters 3605 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3606 performance can be increased by more than a factor of 50. 3607 3608 Collective on MPI_Comm 3609 3610 Input Parameters: 3611 + comm - MPI communicator 3612 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 3613 This value should be the same as the local size used in creating the 3614 y vector for the matrix-vector product y = Ax. 3615 . n - This value should be the same as the local size used in creating the 3616 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3617 calculated if N is given) For square matrices n is almost always m. 3618 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3619 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3620 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3621 (same value is used for all local rows) 3622 . d_nnz - array containing the number of nonzeros in the various rows of the 3623 DIAGONAL portion of the local submatrix (possibly different for each row) 3624 or NULL, if d_nz is used to specify the nonzero structure. 3625 The size of this array is equal to the number of local rows, i.e 'm'. 3626 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3627 submatrix (same value is used for all local rows). 3628 - o_nnz - array containing the number of nonzeros in the various rows of the 3629 OFF-DIAGONAL portion of the local submatrix (possibly different for 3630 each row) or NULL, if o_nz is used to specify the nonzero 3631 structure. The size of this array is equal to the number 3632 of local rows, i.e 'm'. 3633 3634 Output Parameter: 3635 . A - the matrix 3636 3637 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3638 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3639 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3640 3641 Notes: 3642 If the *_nnz parameter is given then the *_nz parameter is ignored 3643 3644 m,n,M,N parameters specify the size of the matrix, and its partitioning across 3645 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 3646 storage requirements for this matrix. 3647 3648 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 3649 processor than it must be used on all processors that share the object for 3650 that argument. 3651 3652 The user MUST specify either the local or global matrix dimensions 3653 (possibly both). 3654 3655 The parallel matrix is partitioned across processors such that the 3656 first m0 rows belong to process 0, the next m1 rows belong to 3657 process 1, the next m2 rows belong to process 2 etc.. where 3658 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 3659 values corresponding to [m x N] submatrix. 3660 3661 The columns are logically partitioned with the n0 columns belonging 3662 to 0th partition, the next n1 columns belonging to the next 3663 partition etc.. where n0,n1,n2... are the input parameter 'n'. 3664 3665 The DIAGONAL portion of the local submatrix on any given processor 3666 is the submatrix corresponding to the rows and columns m,n 3667 corresponding to the given processor. i.e diagonal matrix on 3668 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 3669 etc. The remaining portion of the local submatrix [m x (N-n)] 3670 constitute the OFF-DIAGONAL portion. The example below better 3671 illustrates this concept. 3672 3673 For a square global matrix we define each processor's diagonal portion 3674 to be its local rows and the corresponding columns (a square submatrix); 3675 each processor's off-diagonal portion encompasses the remainder of the 3676 local matrix (a rectangular submatrix). 3677 3678 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3679 3680 When calling this routine with a single process communicator, a matrix of 3681 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 3682 type of communicator, use the construction mechanism: 3683 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 3684 3685 By default, this format uses inodes (identical nodes) when possible. 3686 We search for consecutive rows with the same nonzero structure, thereby 3687 reusing matrix information to achieve increased efficiency. 3688 3689 Options Database Keys: 3690 + -mat_no_inode - Do not use inodes 3691 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3692 - -mat_aij_oneindex - Internally use indexing starting at 1 3693 rather than 0. Note that when calling MatSetValues(), 3694 the user still MUST index entries starting at 0! 3695 3696 3697 Example usage: 3698 3699 Consider the following 8x8 matrix with 34 non-zero values, that is 3700 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3701 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3702 as follows: 3703 3704 .vb 3705 1 2 0 | 0 3 0 | 0 4 3706 Proc0 0 5 6 | 7 0 0 | 8 0 3707 9 0 10 | 11 0 0 | 12 0 3708 ------------------------------------- 3709 13 0 14 | 15 16 17 | 0 0 3710 Proc1 0 18 0 | 19 20 21 | 0 0 3711 0 0 0 | 22 23 0 | 24 0 3712 ------------------------------------- 3713 Proc2 25 26 27 | 0 0 28 | 29 0 3714 30 0 0 | 31 32 33 | 0 34 3715 .ve 3716 3717 This can be represented as a collection of submatrices as: 3718 3719 .vb 3720 A B C 3721 D E F 3722 G H I 3723 .ve 3724 3725 Where the submatrices A,B,C are owned by proc0, D,E,F are 3726 owned by proc1, G,H,I are owned by proc2. 3727 3728 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3729 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3730 The 'M','N' parameters are 8,8, and have the same values on all procs. 3731 3732 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3733 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3734 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3735 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3736 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3737 matrix, ans [DF] as another SeqAIJ matrix. 3738 3739 When d_nz, o_nz parameters are specified, d_nz storage elements are 3740 allocated for every row of the local diagonal submatrix, and o_nz 3741 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3742 One way to choose d_nz and o_nz is to use the max nonzerors per local 3743 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3744 In this case, the values of d_nz,o_nz are: 3745 .vb 3746 proc0 : dnz = 2, o_nz = 2 3747 proc1 : dnz = 3, o_nz = 2 3748 proc2 : dnz = 1, o_nz = 4 3749 .ve 3750 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3751 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3752 for proc3. i.e we are using 12+15+10=37 storage locations to store 3753 34 values. 3754 3755 When d_nnz, o_nnz parameters are specified, the storage is specified 3756 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3757 In the above case the values for d_nnz,o_nnz are: 3758 .vb 3759 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3760 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3761 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3762 .ve 3763 Here the space allocated is sum of all the above values i.e 34, and 3764 hence pre-allocation is perfect. 3765 3766 Level: intermediate 3767 3768 .keywords: matrix, aij, compressed row, sparse, parallel 3769 3770 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 3771 MPIAIJ, MatCreateMPIAIJWithArrays() 3772 @*/ 3773 PetscErrorCode MatCreateAIJ(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) 3774 { 3775 PetscErrorCode ierr; 3776 PetscMPIInt size; 3777 3778 PetscFunctionBegin; 3779 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3780 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 3781 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3782 if (size > 1) { 3783 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 3784 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 3785 } else { 3786 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3787 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 3788 } 3789 PetscFunctionReturn(0); 3790 } 3791 3792 #undef __FUNCT__ 3793 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 3794 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 3795 { 3796 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3797 3798 PetscFunctionBegin; 3799 if (Ad) *Ad = a->A; 3800 if (Ao) *Ao = a->B; 3801 if (colmap) *colmap = a->garray; 3802 PetscFunctionReturn(0); 3803 } 3804 3805 #undef __FUNCT__ 3806 #define __FUNCT__ "MatSetColoring_MPIAIJ" 3807 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 3808 { 3809 PetscErrorCode ierr; 3810 PetscInt i; 3811 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3812 3813 PetscFunctionBegin; 3814 if (coloring->ctype == IS_COLORING_GLOBAL) { 3815 ISColoringValue *allcolors,*colors; 3816 ISColoring ocoloring; 3817 3818 /* set coloring for diagonal portion */ 3819 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 3820 3821 /* set coloring for off-diagonal portion */ 3822 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 3823 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 3824 for (i=0; i<a->B->cmap->n; i++) { 3825 colors[i] = allcolors[a->garray[i]]; 3826 } 3827 ierr = PetscFree(allcolors);CHKERRQ(ierr); 3828 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3829 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3830 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3831 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3832 ISColoringValue *colors; 3833 PetscInt *larray; 3834 ISColoring ocoloring; 3835 3836 /* set coloring for diagonal portion */ 3837 ierr = PetscMalloc1((a->A->cmap->n+1),&larray);CHKERRQ(ierr); 3838 for (i=0; i<a->A->cmap->n; i++) { 3839 larray[i] = i + A->cmap->rstart; 3840 } 3841 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 3842 ierr = PetscMalloc1((a->A->cmap->n+1),&colors);CHKERRQ(ierr); 3843 for (i=0; i<a->A->cmap->n; i++) { 3844 colors[i] = coloring->colors[larray[i]]; 3845 } 3846 ierr = PetscFree(larray);CHKERRQ(ierr); 3847 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3848 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 3849 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3850 3851 /* set coloring for off-diagonal portion */ 3852 ierr = PetscMalloc1((a->B->cmap->n+1),&larray);CHKERRQ(ierr); 3853 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 3854 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 3855 for (i=0; i<a->B->cmap->n; i++) { 3856 colors[i] = coloring->colors[larray[i]]; 3857 } 3858 ierr = PetscFree(larray);CHKERRQ(ierr); 3859 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3860 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 3861 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 3862 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 3863 PetscFunctionReturn(0); 3864 } 3865 3866 #undef __FUNCT__ 3867 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 3868 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 3869 { 3870 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3871 PetscErrorCode ierr; 3872 3873 PetscFunctionBegin; 3874 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 3875 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 3876 PetscFunctionReturn(0); 3877 } 3878 3879 #undef __FUNCT__ 3880 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 3881 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 3882 { 3883 PetscErrorCode ierr; 3884 PetscInt m,N,i,rstart,nnz,Ii; 3885 PetscInt *indx; 3886 PetscScalar *values; 3887 3888 PetscFunctionBegin; 3889 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 3890 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 3891 PetscInt *dnz,*onz,sum,bs,cbs; 3892 3893 if (n == PETSC_DECIDE) { 3894 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 3895 } 3896 /* Check sum(n) = N */ 3897 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3898 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 3899 3900 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3901 rstart -= m; 3902 3903 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 3904 for (i=0; i<m; i++) { 3905 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3906 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 3907 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 3908 } 3909 3910 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 3911 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 3912 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 3913 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 3914 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 3915 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 3916 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 3917 } 3918 3919 /* numeric phase */ 3920 ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr); 3921 for (i=0; i<m; i++) { 3922 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3923 Ii = i + rstart; 3924 ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3925 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 3926 } 3927 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3928 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3929 PetscFunctionReturn(0); 3930 } 3931 3932 #undef __FUNCT__ 3933 #define __FUNCT__ "MatFileSplit" 3934 PetscErrorCode MatFileSplit(Mat A,char *outfile) 3935 { 3936 PetscErrorCode ierr; 3937 PetscMPIInt rank; 3938 PetscInt m,N,i,rstart,nnz; 3939 size_t len; 3940 const PetscInt *indx; 3941 PetscViewer out; 3942 char *name; 3943 Mat B; 3944 const PetscScalar *values; 3945 3946 PetscFunctionBegin; 3947 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 3948 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 3949 /* Should this be the type of the diagonal block of A? */ 3950 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 3951 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 3952 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 3953 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 3954 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 3955 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 3956 for (i=0; i<m; i++) { 3957 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3958 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 3959 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 3960 } 3961 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3962 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3963 3964 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 3965 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 3966 ierr = PetscMalloc1((len+5),&name);CHKERRQ(ierr); 3967 sprintf(name,"%s.%d",outfile,rank); 3968 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 3969 ierr = PetscFree(name);CHKERRQ(ierr); 3970 ierr = MatView(B,out);CHKERRQ(ierr); 3971 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 3972 ierr = MatDestroy(&B);CHKERRQ(ierr); 3973 PetscFunctionReturn(0); 3974 } 3975 3976 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 3977 #undef __FUNCT__ 3978 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 3979 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 3980 { 3981 PetscErrorCode ierr; 3982 Mat_Merge_SeqsToMPI *merge; 3983 PetscContainer container; 3984 3985 PetscFunctionBegin; 3986 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 3987 if (container) { 3988 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 3989 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 3990 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 3991 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 3992 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 3993 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 3994 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 3995 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 3996 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 3997 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 3998 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 3999 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4000 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4001 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4002 ierr = PetscFree(merge);CHKERRQ(ierr); 4003 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4004 } 4005 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4006 PetscFunctionReturn(0); 4007 } 4008 4009 #include <../src/mat/utils/freespace.h> 4010 #include <petscbt.h> 4011 4012 #undef __FUNCT__ 4013 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4014 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4015 { 4016 PetscErrorCode ierr; 4017 MPI_Comm comm; 4018 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4019 PetscMPIInt size,rank,taga,*len_s; 4020 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4021 PetscInt proc,m; 4022 PetscInt **buf_ri,**buf_rj; 4023 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4024 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4025 MPI_Request *s_waits,*r_waits; 4026 MPI_Status *status; 4027 MatScalar *aa=a->a; 4028 MatScalar **abuf_r,*ba_i; 4029 Mat_Merge_SeqsToMPI *merge; 4030 PetscContainer container; 4031 4032 PetscFunctionBegin; 4033 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4034 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4035 4036 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4037 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4038 4039 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4040 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4041 4042 bi = merge->bi; 4043 bj = merge->bj; 4044 buf_ri = merge->buf_ri; 4045 buf_rj = merge->buf_rj; 4046 4047 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4048 owners = merge->rowmap->range; 4049 len_s = merge->len_s; 4050 4051 /* send and recv matrix values */ 4052 /*-----------------------------*/ 4053 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4054 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4055 4056 ierr = PetscMalloc1((merge->nsend+1),&s_waits);CHKERRQ(ierr); 4057 for (proc=0,k=0; proc<size; proc++) { 4058 if (!len_s[proc]) continue; 4059 i = owners[proc]; 4060 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4061 k++; 4062 } 4063 4064 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4065 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4066 ierr = PetscFree(status);CHKERRQ(ierr); 4067 4068 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4069 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4070 4071 /* insert mat values of mpimat */ 4072 /*----------------------------*/ 4073 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4074 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4075 4076 for (k=0; k<merge->nrecv; k++) { 4077 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4078 nrows = *(buf_ri_k[k]); 4079 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4080 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4081 } 4082 4083 /* set values of ba */ 4084 m = merge->rowmap->n; 4085 for (i=0; i<m; i++) { 4086 arow = owners[rank] + i; 4087 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4088 bnzi = bi[i+1] - bi[i]; 4089 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4090 4091 /* add local non-zero vals of this proc's seqmat into ba */ 4092 anzi = ai[arow+1] - ai[arow]; 4093 aj = a->j + ai[arow]; 4094 aa = a->a + ai[arow]; 4095 nextaj = 0; 4096 for (j=0; nextaj<anzi; j++) { 4097 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4098 ba_i[j] += aa[nextaj++]; 4099 } 4100 } 4101 4102 /* add received vals into ba */ 4103 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4104 /* i-th row */ 4105 if (i == *nextrow[k]) { 4106 anzi = *(nextai[k]+1) - *nextai[k]; 4107 aj = buf_rj[k] + *(nextai[k]); 4108 aa = abuf_r[k] + *(nextai[k]); 4109 nextaj = 0; 4110 for (j=0; nextaj<anzi; j++) { 4111 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4112 ba_i[j] += aa[nextaj++]; 4113 } 4114 } 4115 nextrow[k]++; nextai[k]++; 4116 } 4117 } 4118 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4119 } 4120 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4121 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4122 4123 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4124 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4125 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4126 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4127 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4128 PetscFunctionReturn(0); 4129 } 4130 4131 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4132 4133 #undef __FUNCT__ 4134 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4135 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4136 { 4137 PetscErrorCode ierr; 4138 Mat B_mpi; 4139 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4140 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4141 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4142 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4143 PetscInt len,proc,*dnz,*onz,bs,cbs; 4144 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4145 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4146 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4147 MPI_Status *status; 4148 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4149 PetscBT lnkbt; 4150 Mat_Merge_SeqsToMPI *merge; 4151 PetscContainer container; 4152 4153 PetscFunctionBegin; 4154 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4155 4156 /* make sure it is a PETSc comm */ 4157 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4158 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4159 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4160 4161 ierr = PetscNew(&merge);CHKERRQ(ierr); 4162 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4163 4164 /* determine row ownership */ 4165 /*---------------------------------------------------------*/ 4166 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4167 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4168 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4169 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4170 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4171 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4172 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4173 4174 m = merge->rowmap->n; 4175 owners = merge->rowmap->range; 4176 4177 /* determine the number of messages to send, their lengths */ 4178 /*---------------------------------------------------------*/ 4179 len_s = merge->len_s; 4180 4181 len = 0; /* length of buf_si[] */ 4182 merge->nsend = 0; 4183 for (proc=0; proc<size; proc++) { 4184 len_si[proc] = 0; 4185 if (proc == rank) { 4186 len_s[proc] = 0; 4187 } else { 4188 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4189 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4190 } 4191 if (len_s[proc]) { 4192 merge->nsend++; 4193 nrows = 0; 4194 for (i=owners[proc]; i<owners[proc+1]; i++) { 4195 if (ai[i+1] > ai[i]) nrows++; 4196 } 4197 len_si[proc] = 2*(nrows+1); 4198 len += len_si[proc]; 4199 } 4200 } 4201 4202 /* determine the number and length of messages to receive for ij-structure */ 4203 /*-------------------------------------------------------------------------*/ 4204 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4205 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4206 4207 /* post the Irecv of j-structure */ 4208 /*-------------------------------*/ 4209 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4210 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4211 4212 /* post the Isend of j-structure */ 4213 /*--------------------------------*/ 4214 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4215 4216 for (proc=0, k=0; proc<size; proc++) { 4217 if (!len_s[proc]) continue; 4218 i = owners[proc]; 4219 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4220 k++; 4221 } 4222 4223 /* receives and sends of j-structure are complete */ 4224 /*------------------------------------------------*/ 4225 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4226 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4227 4228 /* send and recv i-structure */ 4229 /*---------------------------*/ 4230 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4231 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4232 4233 ierr = PetscMalloc1((len+1),&buf_s);CHKERRQ(ierr); 4234 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4235 for (proc=0,k=0; proc<size; proc++) { 4236 if (!len_s[proc]) continue; 4237 /* form outgoing message for i-structure: 4238 buf_si[0]: nrows to be sent 4239 [1:nrows]: row index (global) 4240 [nrows+1:2*nrows+1]: i-structure index 4241 */ 4242 /*-------------------------------------------*/ 4243 nrows = len_si[proc]/2 - 1; 4244 buf_si_i = buf_si + nrows+1; 4245 buf_si[0] = nrows; 4246 buf_si_i[0] = 0; 4247 nrows = 0; 4248 for (i=owners[proc]; i<owners[proc+1]; i++) { 4249 anzi = ai[i+1] - ai[i]; 4250 if (anzi) { 4251 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4252 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4253 nrows++; 4254 } 4255 } 4256 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4257 k++; 4258 buf_si += len_si[proc]; 4259 } 4260 4261 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4262 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4263 4264 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4265 for (i=0; i<merge->nrecv; i++) { 4266 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); 4267 } 4268 4269 ierr = PetscFree(len_si);CHKERRQ(ierr); 4270 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4271 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4272 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4273 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4274 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4275 ierr = PetscFree(status);CHKERRQ(ierr); 4276 4277 /* compute a local seq matrix in each processor */ 4278 /*----------------------------------------------*/ 4279 /* allocate bi array and free space for accumulating nonzero column info */ 4280 ierr = PetscMalloc1((m+1),&bi);CHKERRQ(ierr); 4281 bi[0] = 0; 4282 4283 /* create and initialize a linked list */ 4284 nlnk = N+1; 4285 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4286 4287 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4288 len = ai[owners[rank+1]] - ai[owners[rank]]; 4289 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4290 4291 current_space = free_space; 4292 4293 /* determine symbolic info for each local row */ 4294 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4295 4296 for (k=0; k<merge->nrecv; k++) { 4297 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4298 nrows = *buf_ri_k[k]; 4299 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4300 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4301 } 4302 4303 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4304 len = 0; 4305 for (i=0; i<m; i++) { 4306 bnzi = 0; 4307 /* add local non-zero cols of this proc's seqmat into lnk */ 4308 arow = owners[rank] + i; 4309 anzi = ai[arow+1] - ai[arow]; 4310 aj = a->j + ai[arow]; 4311 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4312 bnzi += nlnk; 4313 /* add received col data into lnk */ 4314 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4315 if (i == *nextrow[k]) { /* i-th row */ 4316 anzi = *(nextai[k]+1) - *nextai[k]; 4317 aj = buf_rj[k] + *nextai[k]; 4318 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4319 bnzi += nlnk; 4320 nextrow[k]++; nextai[k]++; 4321 } 4322 } 4323 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4324 4325 /* if free space is not available, make more free space */ 4326 if (current_space->local_remaining<bnzi) { 4327 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4328 nspacedouble++; 4329 } 4330 /* copy data into free space, then initialize lnk */ 4331 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4332 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4333 4334 current_space->array += bnzi; 4335 current_space->local_used += bnzi; 4336 current_space->local_remaining -= bnzi; 4337 4338 bi[i+1] = bi[i] + bnzi; 4339 } 4340 4341 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4342 4343 ierr = PetscMalloc1((bi[m]+1),&bj);CHKERRQ(ierr); 4344 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4345 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4346 4347 /* create symbolic parallel matrix B_mpi */ 4348 /*---------------------------------------*/ 4349 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4350 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4351 if (n==PETSC_DECIDE) { 4352 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4353 } else { 4354 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4355 } 4356 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4357 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4358 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4359 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4360 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4361 4362 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4363 B_mpi->assembled = PETSC_FALSE; 4364 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4365 merge->bi = bi; 4366 merge->bj = bj; 4367 merge->buf_ri = buf_ri; 4368 merge->buf_rj = buf_rj; 4369 merge->coi = NULL; 4370 merge->coj = NULL; 4371 merge->owners_co = NULL; 4372 4373 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4374 4375 /* attach the supporting struct to B_mpi for reuse */ 4376 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4377 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4378 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4379 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4380 *mpimat = B_mpi; 4381 4382 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4383 PetscFunctionReturn(0); 4384 } 4385 4386 #undef __FUNCT__ 4387 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4388 /*@C 4389 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4390 matrices from each processor 4391 4392 Collective on MPI_Comm 4393 4394 Input Parameters: 4395 + comm - the communicators the parallel matrix will live on 4396 . seqmat - the input sequential matrices 4397 . m - number of local rows (or PETSC_DECIDE) 4398 . n - number of local columns (or PETSC_DECIDE) 4399 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4400 4401 Output Parameter: 4402 . mpimat - the parallel matrix generated 4403 4404 Level: advanced 4405 4406 Notes: 4407 The dimensions of the sequential matrix in each processor MUST be the same. 4408 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4409 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4410 @*/ 4411 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4412 { 4413 PetscErrorCode ierr; 4414 PetscMPIInt size; 4415 4416 PetscFunctionBegin; 4417 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4418 if (size == 1) { 4419 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4420 if (scall == MAT_INITIAL_MATRIX) { 4421 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4422 } else { 4423 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4424 } 4425 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4426 PetscFunctionReturn(0); 4427 } 4428 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4429 if (scall == MAT_INITIAL_MATRIX) { 4430 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4431 } 4432 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4433 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4434 PetscFunctionReturn(0); 4435 } 4436 4437 #undef __FUNCT__ 4438 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4439 /*@ 4440 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4441 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4442 with MatGetSize() 4443 4444 Not Collective 4445 4446 Input Parameters: 4447 + A - the matrix 4448 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4449 4450 Output Parameter: 4451 . A_loc - the local sequential matrix generated 4452 4453 Level: developer 4454 4455 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4456 4457 @*/ 4458 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4459 { 4460 PetscErrorCode ierr; 4461 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4462 Mat_SeqAIJ *mat,*a,*b; 4463 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4464 MatScalar *aa,*ba,*cam; 4465 PetscScalar *ca; 4466 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4467 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4468 PetscBool match; 4469 MPI_Comm comm; 4470 PetscMPIInt size; 4471 4472 PetscFunctionBegin; 4473 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4474 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4475 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4476 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4477 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4478 4479 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4480 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4481 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4482 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4483 aa = a->a; ba = b->a; 4484 if (scall == MAT_INITIAL_MATRIX) { 4485 if (size == 1) { 4486 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4487 PetscFunctionReturn(0); 4488 } 4489 4490 ierr = PetscMalloc1((1+am),&ci);CHKERRQ(ierr); 4491 ci[0] = 0; 4492 for (i=0; i<am; i++) { 4493 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4494 } 4495 ierr = PetscMalloc1((1+ci[am]),&cj);CHKERRQ(ierr); 4496 ierr = PetscMalloc1((1+ci[am]),&ca);CHKERRQ(ierr); 4497 k = 0; 4498 for (i=0; i<am; i++) { 4499 ncols_o = bi[i+1] - bi[i]; 4500 ncols_d = ai[i+1] - ai[i]; 4501 /* off-diagonal portion of A */ 4502 for (jo=0; jo<ncols_o; jo++) { 4503 col = cmap[*bj]; 4504 if (col >= cstart) break; 4505 cj[k] = col; bj++; 4506 ca[k++] = *ba++; 4507 } 4508 /* diagonal portion of A */ 4509 for (j=0; j<ncols_d; j++) { 4510 cj[k] = cstart + *aj++; 4511 ca[k++] = *aa++; 4512 } 4513 /* off-diagonal portion of A */ 4514 for (j=jo; j<ncols_o; j++) { 4515 cj[k] = cmap[*bj++]; 4516 ca[k++] = *ba++; 4517 } 4518 } 4519 /* put together the new matrix */ 4520 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4521 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4522 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4523 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4524 mat->free_a = PETSC_TRUE; 4525 mat->free_ij = PETSC_TRUE; 4526 mat->nonew = 0; 4527 } else if (scall == MAT_REUSE_MATRIX) { 4528 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4529 ci = mat->i; cj = mat->j; cam = mat->a; 4530 for (i=0; i<am; i++) { 4531 /* off-diagonal portion of A */ 4532 ncols_o = bi[i+1] - bi[i]; 4533 for (jo=0; jo<ncols_o; jo++) { 4534 col = cmap[*bj]; 4535 if (col >= cstart) break; 4536 *cam++ = *ba++; bj++; 4537 } 4538 /* diagonal portion of A */ 4539 ncols_d = ai[i+1] - ai[i]; 4540 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4541 /* off-diagonal portion of A */ 4542 for (j=jo; j<ncols_o; j++) { 4543 *cam++ = *ba++; bj++; 4544 } 4545 } 4546 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 4547 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4548 PetscFunctionReturn(0); 4549 } 4550 4551 #undef __FUNCT__ 4552 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 4553 /*@C 4554 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 4555 4556 Not Collective 4557 4558 Input Parameters: 4559 + A - the matrix 4560 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4561 - row, col - index sets of rows and columns to extract (or NULL) 4562 4563 Output Parameter: 4564 . A_loc - the local sequential matrix generated 4565 4566 Level: developer 4567 4568 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 4569 4570 @*/ 4571 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 4572 { 4573 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4574 PetscErrorCode ierr; 4575 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 4576 IS isrowa,iscola; 4577 Mat *aloc; 4578 PetscBool match; 4579 4580 PetscFunctionBegin; 4581 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4582 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4583 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4584 if (!row) { 4585 start = A->rmap->rstart; end = A->rmap->rend; 4586 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 4587 } else { 4588 isrowa = *row; 4589 } 4590 if (!col) { 4591 start = A->cmap->rstart; 4592 cmap = a->garray; 4593 nzA = a->A->cmap->n; 4594 nzB = a->B->cmap->n; 4595 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 4596 ncols = 0; 4597 for (i=0; i<nzB; i++) { 4598 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4599 else break; 4600 } 4601 imark = i; 4602 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 4603 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 4604 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 4605 } else { 4606 iscola = *col; 4607 } 4608 if (scall != MAT_INITIAL_MATRIX) { 4609 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 4610 aloc[0] = *A_loc; 4611 } 4612 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 4613 *A_loc = aloc[0]; 4614 ierr = PetscFree(aloc);CHKERRQ(ierr); 4615 if (!row) { 4616 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 4617 } 4618 if (!col) { 4619 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 4620 } 4621 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 4622 PetscFunctionReturn(0); 4623 } 4624 4625 #undef __FUNCT__ 4626 #define __FUNCT__ "MatGetBrowsOfAcols" 4627 /*@C 4628 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 4629 4630 Collective on Mat 4631 4632 Input Parameters: 4633 + A,B - the matrices in mpiaij format 4634 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4635 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 4636 4637 Output Parameter: 4638 + rowb, colb - index sets of rows and columns of B to extract 4639 - B_seq - the sequential matrix generated 4640 4641 Level: developer 4642 4643 @*/ 4644 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 4645 { 4646 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4647 PetscErrorCode ierr; 4648 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 4649 IS isrowb,iscolb; 4650 Mat *bseq=NULL; 4651 4652 PetscFunctionBegin; 4653 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4654 SETERRQ4(PETSC_COMM_SELF,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); 4655 } 4656 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4657 4658 if (scall == MAT_INITIAL_MATRIX) { 4659 start = A->cmap->rstart; 4660 cmap = a->garray; 4661 nzA = a->A->cmap->n; 4662 nzB = a->B->cmap->n; 4663 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 4664 ncols = 0; 4665 for (i=0; i<nzB; i++) { /* row < local row index */ 4666 if (cmap[i] < start) idx[ncols++] = cmap[i]; 4667 else break; 4668 } 4669 imark = i; 4670 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 4671 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 4672 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 4673 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 4674 } else { 4675 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 4676 isrowb = *rowb; iscolb = *colb; 4677 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 4678 bseq[0] = *B_seq; 4679 } 4680 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 4681 *B_seq = bseq[0]; 4682 ierr = PetscFree(bseq);CHKERRQ(ierr); 4683 if (!rowb) { 4684 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 4685 } else { 4686 *rowb = isrowb; 4687 } 4688 if (!colb) { 4689 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 4690 } else { 4691 *colb = iscolb; 4692 } 4693 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 4694 PetscFunctionReturn(0); 4695 } 4696 4697 #undef __FUNCT__ 4698 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 4699 /* 4700 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 4701 of the OFF-DIAGONAL portion of local A 4702 4703 Collective on Mat 4704 4705 Input Parameters: 4706 + A,B - the matrices in mpiaij format 4707 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4708 4709 Output Parameter: 4710 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 4711 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 4712 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 4713 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 4714 4715 Level: developer 4716 4717 */ 4718 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 4719 { 4720 VecScatter_MPI_General *gen_to,*gen_from; 4721 PetscErrorCode ierr; 4722 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 4723 Mat_SeqAIJ *b_oth; 4724 VecScatter ctx =a->Mvctx; 4725 MPI_Comm comm; 4726 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 4727 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 4728 PetscScalar *rvalues,*svalues; 4729 MatScalar *b_otha,*bufa,*bufA; 4730 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 4731 MPI_Request *rwaits = NULL,*swaits = NULL; 4732 MPI_Status *sstatus,rstatus; 4733 PetscMPIInt jj,size; 4734 PetscInt *cols,sbs,rbs; 4735 PetscScalar *vals; 4736 4737 PetscFunctionBegin; 4738 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4739 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4740 if (size == 1) PetscFunctionReturn(0); 4741 4742 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 4743 SETERRQ4(PETSC_COMM_SELF,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); 4744 } 4745 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4746 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4747 4748 gen_to = (VecScatter_MPI_General*)ctx->todata; 4749 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 4750 rvalues = gen_from->values; /* holds the length of receiving row */ 4751 svalues = gen_to->values; /* holds the length of sending row */ 4752 nrecvs = gen_from->n; 4753 nsends = gen_to->n; 4754 4755 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 4756 srow = gen_to->indices; /* local row index to be sent */ 4757 sstarts = gen_to->starts; 4758 sprocs = gen_to->procs; 4759 sstatus = gen_to->sstatus; 4760 sbs = gen_to->bs; 4761 rstarts = gen_from->starts; 4762 rprocs = gen_from->procs; 4763 rbs = gen_from->bs; 4764 4765 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 4766 if (scall == MAT_INITIAL_MATRIX) { 4767 /* i-array */ 4768 /*---------*/ 4769 /* post receives */ 4770 for (i=0; i<nrecvs; i++) { 4771 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4772 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 4773 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4774 } 4775 4776 /* pack the outgoing message */ 4777 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 4778 4779 sstartsj[0] = 0; 4780 rstartsj[0] = 0; 4781 len = 0; /* total length of j or a array to be sent */ 4782 k = 0; 4783 for (i=0; i<nsends; i++) { 4784 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 4785 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4786 for (j=0; j<nrows; j++) { 4787 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 4788 for (l=0; l<sbs; l++) { 4789 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 4790 4791 rowlen[j*sbs+l] = ncols; 4792 4793 len += ncols; 4794 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 4795 } 4796 k++; 4797 } 4798 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4799 4800 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 4801 } 4802 /* recvs and sends of i-array are completed */ 4803 i = nrecvs; 4804 while (i--) { 4805 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4806 } 4807 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4808 4809 /* allocate buffers for sending j and a arrays */ 4810 ierr = PetscMalloc1((len+1),&bufj);CHKERRQ(ierr); 4811 ierr = PetscMalloc1((len+1),&bufa);CHKERRQ(ierr); 4812 4813 /* create i-array of B_oth */ 4814 ierr = PetscMalloc1((aBn+2),&b_othi);CHKERRQ(ierr); 4815 4816 b_othi[0] = 0; 4817 len = 0; /* total length of j or a array to be received */ 4818 k = 0; 4819 for (i=0; i<nrecvs; i++) { 4820 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 4821 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 4822 for (j=0; j<nrows; j++) { 4823 b_othi[k+1] = b_othi[k] + rowlen[j]; 4824 len += rowlen[j]; k++; 4825 } 4826 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 4827 } 4828 4829 /* allocate space for j and a arrrays of B_oth */ 4830 ierr = PetscMalloc1((b_othi[aBn]+1),&b_othj);CHKERRQ(ierr); 4831 ierr = PetscMalloc1((b_othi[aBn]+1),&b_otha);CHKERRQ(ierr); 4832 4833 /* j-array */ 4834 /*---------*/ 4835 /* post receives of j-array */ 4836 for (i=0; i<nrecvs; i++) { 4837 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4838 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4839 } 4840 4841 /* pack the outgoing message j-array */ 4842 k = 0; 4843 for (i=0; i<nsends; i++) { 4844 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4845 bufJ = bufj+sstartsj[i]; 4846 for (j=0; j<nrows; j++) { 4847 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4848 for (ll=0; ll<sbs; ll++) { 4849 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4850 for (l=0; l<ncols; l++) { 4851 *bufJ++ = cols[l]; 4852 } 4853 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 4854 } 4855 } 4856 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4857 } 4858 4859 /* recvs and sends of j-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 } else if (scall == MAT_REUSE_MATRIX) { 4866 sstartsj = *startsj_s; 4867 rstartsj = *startsj_r; 4868 bufa = *bufa_ptr; 4869 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4870 b_otha = b_oth->a; 4871 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 4872 4873 /* a-array */ 4874 /*---------*/ 4875 /* post receives of a-array */ 4876 for (i=0; i<nrecvs; i++) { 4877 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 4878 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 4879 } 4880 4881 /* pack the outgoing message a-array */ 4882 k = 0; 4883 for (i=0; i<nsends; i++) { 4884 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 4885 bufA = bufa+sstartsj[i]; 4886 for (j=0; j<nrows; j++) { 4887 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 4888 for (ll=0; ll<sbs; ll++) { 4889 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4890 for (l=0; l<ncols; l++) { 4891 *bufA++ = vals[l]; 4892 } 4893 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 4894 } 4895 } 4896 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 4897 } 4898 /* recvs and sends of a-array are completed */ 4899 i = nrecvs; 4900 while (i--) { 4901 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 4902 } 4903 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 4904 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 4905 4906 if (scall == MAT_INITIAL_MATRIX) { 4907 /* put together the new matrix */ 4908 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 4909 4910 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4911 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4912 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 4913 b_oth->free_a = PETSC_TRUE; 4914 b_oth->free_ij = PETSC_TRUE; 4915 b_oth->nonew = 0; 4916 4917 ierr = PetscFree(bufj);CHKERRQ(ierr); 4918 if (!startsj_s || !bufa_ptr) { 4919 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 4920 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 4921 } else { 4922 *startsj_s = sstartsj; 4923 *startsj_r = rstartsj; 4924 *bufa_ptr = bufa; 4925 } 4926 } 4927 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 4928 PetscFunctionReturn(0); 4929 } 4930 4931 #undef __FUNCT__ 4932 #define __FUNCT__ "MatGetCommunicationStructs" 4933 /*@C 4934 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 4935 4936 Not Collective 4937 4938 Input Parameters: 4939 . A - The matrix in mpiaij format 4940 4941 Output Parameter: 4942 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 4943 . colmap - A map from global column index to local index into lvec 4944 - multScatter - A scatter from the argument of a matrix-vector product to lvec 4945 4946 Level: developer 4947 4948 @*/ 4949 #if defined(PETSC_USE_CTABLE) 4950 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 4951 #else 4952 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 4953 #endif 4954 { 4955 Mat_MPIAIJ *a; 4956 4957 PetscFunctionBegin; 4958 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 4959 PetscValidPointer(lvec, 2); 4960 PetscValidPointer(colmap, 3); 4961 PetscValidPointer(multScatter, 4); 4962 a = (Mat_MPIAIJ*) A->data; 4963 if (lvec) *lvec = a->lvec; 4964 if (colmap) *colmap = a->colmap; 4965 if (multScatter) *multScatter = a->Mvctx; 4966 PetscFunctionReturn(0); 4967 } 4968 4969 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 4970 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 4971 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 4972 #if defined(PETSC_HAVE_ELEMENTAL) 4973 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4974 #endif 4975 4976 #undef __FUNCT__ 4977 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 4978 /* 4979 Computes (B'*A')' since computing B*A directly is untenable 4980 4981 n p p 4982 ( ) ( ) ( ) 4983 m ( A ) * n ( B ) = m ( C ) 4984 ( ) ( ) ( ) 4985 4986 */ 4987 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 4988 { 4989 PetscErrorCode ierr; 4990 Mat At,Bt,Ct; 4991 4992 PetscFunctionBegin; 4993 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 4994 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 4995 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 4996 ierr = MatDestroy(&At);CHKERRQ(ierr); 4997 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 4998 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 4999 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5000 PetscFunctionReturn(0); 5001 } 5002 5003 #undef __FUNCT__ 5004 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5005 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5006 { 5007 PetscErrorCode ierr; 5008 PetscInt m=A->rmap->n,n=B->cmap->n; 5009 Mat Cmat; 5010 5011 PetscFunctionBegin; 5012 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 5013 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5014 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5015 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5016 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5017 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5018 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5019 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5020 5021 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5022 5023 *C = Cmat; 5024 PetscFunctionReturn(0); 5025 } 5026 5027 /* ----------------------------------------------------------------*/ 5028 #undef __FUNCT__ 5029 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5030 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5031 { 5032 PetscErrorCode ierr; 5033 5034 PetscFunctionBegin; 5035 if (scall == MAT_INITIAL_MATRIX) { 5036 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5037 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5038 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5039 } 5040 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5041 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5042 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5043 PetscFunctionReturn(0); 5044 } 5045 5046 #if defined(PETSC_HAVE_MUMPS) 5047 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5048 #endif 5049 #if defined(PETSC_HAVE_PASTIX) 5050 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5051 #endif 5052 #if defined(PETSC_HAVE_SUPERLU_DIST) 5053 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5054 #endif 5055 #if defined(PETSC_HAVE_CLIQUE) 5056 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5057 #endif 5058 5059 /*MC 5060 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5061 5062 Options Database Keys: 5063 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5064 5065 Level: beginner 5066 5067 .seealso: MatCreateAIJ() 5068 M*/ 5069 5070 #undef __FUNCT__ 5071 #define __FUNCT__ "MatCreate_MPIAIJ" 5072 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5073 { 5074 Mat_MPIAIJ *b; 5075 PetscErrorCode ierr; 5076 PetscMPIInt size; 5077 5078 PetscFunctionBegin; 5079 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5080 5081 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5082 B->data = (void*)b; 5083 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5084 B->assembled = PETSC_FALSE; 5085 B->insertmode = NOT_SET_VALUES; 5086 b->size = size; 5087 5088 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5089 5090 /* build cache for off array entries formed */ 5091 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5092 5093 b->donotstash = PETSC_FALSE; 5094 b->colmap = 0; 5095 b->garray = 0; 5096 b->roworiented = PETSC_TRUE; 5097 5098 /* stuff used for matrix vector multiply */ 5099 b->lvec = NULL; 5100 b->Mvctx = NULL; 5101 5102 /* stuff for MatGetRow() */ 5103 b->rowindices = 0; 5104 b->rowvalues = 0; 5105 b->getrowactive = PETSC_FALSE; 5106 5107 /* flexible pointer used in CUSP/CUSPARSE classes */ 5108 b->spptr = NULL; 5109 5110 #if defined(PETSC_HAVE_MUMPS) 5111 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5112 #endif 5113 #if defined(PETSC_HAVE_PASTIX) 5114 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5115 #endif 5116 #if defined(PETSC_HAVE_SUPERLU_DIST) 5117 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5118 #endif 5119 #if defined(PETSC_HAVE_CLIQUE) 5120 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5121 #endif 5122 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5123 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5124 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5125 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5126 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5127 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5128 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5129 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5130 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5132 #if defined(PETSC_HAVE_ELEMENTAL) 5133 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5134 #endif 5135 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5136 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5138 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5139 PetscFunctionReturn(0); 5140 } 5141 5142 #undef __FUNCT__ 5143 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5144 /*@ 5145 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5146 and "off-diagonal" part of the matrix in CSR format. 5147 5148 Collective on MPI_Comm 5149 5150 Input Parameters: 5151 + comm - MPI communicator 5152 . m - number of local rows (Cannot be PETSC_DECIDE) 5153 . n - This value should be the same as the local size used in creating the 5154 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5155 calculated if N is given) For square matrices n is almost always m. 5156 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5157 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5158 . i - row indices for "diagonal" portion of matrix 5159 . j - column indices 5160 . a - matrix values 5161 . oi - row indices for "off-diagonal" portion of matrix 5162 . oj - column indices 5163 - oa - matrix values 5164 5165 Output Parameter: 5166 . mat - the matrix 5167 5168 Level: advanced 5169 5170 Notes: 5171 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5172 must free the arrays once the matrix has been destroyed and not before. 5173 5174 The i and j indices are 0 based 5175 5176 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5177 5178 This sets local rows and cannot be used to set off-processor values. 5179 5180 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5181 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5182 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5183 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5184 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5185 communication if it is known that only local entries will be set. 5186 5187 .keywords: matrix, aij, compressed row, sparse, parallel 5188 5189 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5190 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5191 @*/ 5192 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5193 { 5194 PetscErrorCode ierr; 5195 Mat_MPIAIJ *maij; 5196 5197 PetscFunctionBegin; 5198 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5199 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5200 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5201 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5202 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5203 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5204 maij = (Mat_MPIAIJ*) (*mat)->data; 5205 5206 (*mat)->preallocated = PETSC_TRUE; 5207 5208 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5209 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5210 5211 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5212 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5213 5214 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5215 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5216 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5217 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5218 5219 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5220 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5221 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5222 PetscFunctionReturn(0); 5223 } 5224 5225 /* 5226 Special version for direct calls from Fortran 5227 */ 5228 #include <petsc-private/fortranimpl.h> 5229 5230 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5231 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5232 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5233 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5234 #endif 5235 5236 /* Change these macros so can be used in void function */ 5237 #undef CHKERRQ 5238 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5239 #undef SETERRQ2 5240 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5241 #undef SETERRQ3 5242 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5243 #undef SETERRQ 5244 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5245 5246 #undef __FUNCT__ 5247 #define __FUNCT__ "matsetvaluesmpiaij_" 5248 PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5249 { 5250 Mat mat = *mmat; 5251 PetscInt m = *mm, n = *mn; 5252 InsertMode addv = *maddv; 5253 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5254 PetscScalar value; 5255 PetscErrorCode ierr; 5256 5257 MatCheckPreallocated(mat,1); 5258 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5259 5260 #if defined(PETSC_USE_DEBUG) 5261 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5262 #endif 5263 { 5264 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5265 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5266 PetscBool roworiented = aij->roworiented; 5267 5268 /* Some Variables required in the macro */ 5269 Mat A = aij->A; 5270 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5271 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5272 MatScalar *aa = a->a; 5273 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5274 Mat B = aij->B; 5275 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5276 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5277 MatScalar *ba = b->a; 5278 5279 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5280 PetscInt nonew = a->nonew; 5281 MatScalar *ap1,*ap2; 5282 5283 PetscFunctionBegin; 5284 for (i=0; i<m; i++) { 5285 if (im[i] < 0) continue; 5286 #if defined(PETSC_USE_DEBUG) 5287 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 5288 #endif 5289 if (im[i] >= rstart && im[i] < rend) { 5290 row = im[i] - rstart; 5291 lastcol1 = -1; 5292 rp1 = aj + ai[row]; 5293 ap1 = aa + ai[row]; 5294 rmax1 = aimax[row]; 5295 nrow1 = ailen[row]; 5296 low1 = 0; 5297 high1 = nrow1; 5298 lastcol2 = -1; 5299 rp2 = bj + bi[row]; 5300 ap2 = ba + bi[row]; 5301 rmax2 = bimax[row]; 5302 nrow2 = bilen[row]; 5303 low2 = 0; 5304 high2 = nrow2; 5305 5306 for (j=0; j<n; j++) { 5307 if (roworiented) value = v[i*n+j]; 5308 else value = v[i+j*m]; 5309 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5310 if (in[j] >= cstart && in[j] < cend) { 5311 col = in[j] - cstart; 5312 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5313 } else if (in[j] < 0) continue; 5314 #if defined(PETSC_USE_DEBUG) 5315 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 5316 #endif 5317 else { 5318 if (mat->was_assembled) { 5319 if (!aij->colmap) { 5320 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5321 } 5322 #if defined(PETSC_USE_CTABLE) 5323 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5324 col--; 5325 #else 5326 col = aij->colmap[in[j]] - 1; 5327 #endif 5328 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5329 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5330 col = in[j]; 5331 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5332 B = aij->B; 5333 b = (Mat_SeqAIJ*)B->data; 5334 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5335 rp2 = bj + bi[row]; 5336 ap2 = ba + bi[row]; 5337 rmax2 = bimax[row]; 5338 nrow2 = bilen[row]; 5339 low2 = 0; 5340 high2 = nrow2; 5341 bm = aij->B->rmap->n; 5342 ba = b->a; 5343 } 5344 } else col = in[j]; 5345 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5346 } 5347 } 5348 } else if (!aij->donotstash) { 5349 if (roworiented) { 5350 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5351 } else { 5352 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5353 } 5354 } 5355 } 5356 } 5357 PetscFunctionReturnVoid(); 5358 } 5359 5360