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 2404 #undef __FUNCT__ 2405 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_interlaced" 2406 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2407 { 2408 PetscMPIInt rank,size; 2409 MPI_Comm comm; 2410 PetscErrorCode ierr; 2411 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2412 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2413 PetscInt *rowrange = mat->rmap->range; 2414 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2415 Mat A = aij->A,B=aij->B,C=*matredundant; 2416 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2417 PetscScalar *sbuf_a; 2418 PetscInt nzlocal=a->nz+b->nz; 2419 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2420 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2421 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2422 MatScalar *aworkA,*aworkB; 2423 PetscScalar *vals; 2424 PetscMPIInt tag1,tag2,tag3,imdex; 2425 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2426 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2427 MPI_Status recv_status,*send_status; 2428 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2429 PetscInt **rbuf_j=NULL; 2430 PetscScalar **rbuf_a=NULL; 2431 Mat_Redundant *redund =NULL; 2432 2433 PetscFunctionBegin; 2434 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2435 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2436 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2437 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2438 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2439 2440 if (reuse == MAT_REUSE_MATRIX) { 2441 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2442 2443 redund = C->redundant; 2444 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2445 2446 nsends = redund->nsends; 2447 nrecvs = redund->nrecvs; 2448 send_rank = redund->send_rank; 2449 recv_rank = redund->recv_rank; 2450 sbuf_nz = redund->sbuf_nz; 2451 rbuf_nz = redund->rbuf_nz; 2452 sbuf_j = redund->sbuf_j; 2453 sbuf_a = redund->sbuf_a; 2454 rbuf_j = redund->rbuf_j; 2455 rbuf_a = redund->rbuf_a; 2456 } 2457 2458 if (reuse == MAT_INITIAL_MATRIX) { 2459 PetscInt nleftover,np_subcomm; 2460 2461 /* get the destination processors' id send_rank, nsends and nrecvs */ 2462 ierr = PetscMalloc2(size,&send_rank,size,&recv_rank);CHKERRQ(ierr); 2463 2464 np_subcomm = size/nsubcomm; 2465 nleftover = size - nsubcomm*np_subcomm; 2466 2467 /* block of codes below is specific for INTERLACED */ 2468 /* ------------------------------------------------*/ 2469 nsends = 0; nrecvs = 0; 2470 for (i=0; i<size; i++) { 2471 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2472 send_rank[nsends++] = i; 2473 recv_rank[nrecvs++] = i; 2474 } 2475 } 2476 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2477 i = size-nleftover-1; 2478 j = 0; 2479 while (j < nsubcomm - nleftover) { 2480 send_rank[nsends++] = i; 2481 i--; j++; 2482 } 2483 } 2484 2485 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2486 for (i=0; i<nleftover; i++) { 2487 recv_rank[nrecvs++] = size-nleftover+i; 2488 } 2489 } 2490 /*----------------------------------------------*/ 2491 2492 /* allocate sbuf_j, sbuf_a */ 2493 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2494 ierr = PetscMalloc1(i,&sbuf_j);CHKERRQ(ierr); 2495 ierr = PetscMalloc1((nzlocal+1),&sbuf_a);CHKERRQ(ierr); 2496 /* 2497 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2498 ierr = PetscSynchronizedFlush(comm,PETSC_STDOUT);CHKERRQ(ierr); 2499 */ 2500 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2501 2502 /* copy mat's local entries into the buffers */ 2503 if (reuse == MAT_INITIAL_MATRIX) { 2504 rownz_max = 0; 2505 rptr = sbuf_j; 2506 cols = sbuf_j + rend-rstart + 1; 2507 vals = sbuf_a; 2508 rptr[0] = 0; 2509 for (i=0; i<rend-rstart; i++) { 2510 row = i + rstart; 2511 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2512 ncols = nzA + nzB; 2513 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2514 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2515 /* load the column indices for this row into cols */ 2516 lwrite = 0; 2517 for (l=0; l<nzB; l++) { 2518 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2519 vals[lwrite] = aworkB[l]; 2520 cols[lwrite++] = ctmp; 2521 } 2522 } 2523 for (l=0; l<nzA; l++) { 2524 vals[lwrite] = aworkA[l]; 2525 cols[lwrite++] = cstart + cworkA[l]; 2526 } 2527 for (l=0; l<nzB; l++) { 2528 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2529 vals[lwrite] = aworkB[l]; 2530 cols[lwrite++] = ctmp; 2531 } 2532 } 2533 vals += ncols; 2534 cols += ncols; 2535 rptr[i+1] = rptr[i] + ncols; 2536 if (rownz_max < ncols) rownz_max = ncols; 2537 } 2538 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2539 } else { /* only copy matrix values into sbuf_a */ 2540 rptr = sbuf_j; 2541 vals = sbuf_a; 2542 rptr[0] = 0; 2543 for (i=0; i<rend-rstart; i++) { 2544 row = i + rstart; 2545 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2546 ncols = nzA + nzB; 2547 cworkB = b->j + b->i[i]; 2548 aworkA = a->a + a->i[i]; 2549 aworkB = b->a + b->i[i]; 2550 lwrite = 0; 2551 for (l=0; l<nzB; l++) { 2552 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2553 } 2554 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2555 for (l=0; l<nzB; l++) { 2556 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2557 } 2558 vals += ncols; 2559 rptr[i+1] = rptr[i] + ncols; 2560 } 2561 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2562 2563 /* send nzlocal to others, and recv other's nzlocal */ 2564 /*--------------------------------------------------*/ 2565 if (reuse == MAT_INITIAL_MATRIX) { 2566 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,&s_waits3,nsends+1,&send_status);CHKERRQ(ierr); 2567 2568 s_waits2 = s_waits3 + nsends; 2569 s_waits1 = s_waits2 + nsends; 2570 r_waits1 = s_waits1 + nsends; 2571 r_waits2 = r_waits1 + nrecvs; 2572 r_waits3 = r_waits2 + nrecvs; 2573 } else { 2574 ierr = PetscMalloc2(nsends + nrecvs +1,&s_waits3,nsends+1,&send_status);CHKERRQ(ierr); 2575 2576 r_waits3 = s_waits3 + nsends; 2577 } 2578 2579 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2580 if (reuse == MAT_INITIAL_MATRIX) { 2581 /* get new tags to keep the communication clean */ 2582 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2583 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2584 ierr = PetscMalloc4(nsends,&sbuf_nz,nrecvs,&rbuf_nz,nrecvs,&rbuf_j,nrecvs,&rbuf_a);CHKERRQ(ierr); 2585 2586 /* post receives of other's nzlocal */ 2587 for (i=0; i<nrecvs; i++) { 2588 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2589 } 2590 /* send nzlocal to others */ 2591 for (i=0; i<nsends; i++) { 2592 sbuf_nz[i] = nzlocal; 2593 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2594 } 2595 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2596 count = nrecvs; 2597 while (count) { 2598 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2599 2600 recv_rank[imdex] = recv_status.MPI_SOURCE; 2601 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2602 ierr = PetscMalloc1((rbuf_nz[imdex]+1),&rbuf_a[imdex]);CHKERRQ(ierr); 2603 2604 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2605 2606 rbuf_nz[imdex] += i + 2; 2607 2608 ierr = PetscMalloc1(rbuf_nz[imdex],&rbuf_j[imdex]);CHKERRQ(ierr); 2609 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2610 count--; 2611 } 2612 /* wait on sends of nzlocal */ 2613 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2614 /* send mat->i,j to others, and recv from other's */ 2615 /*------------------------------------------------*/ 2616 for (i=0; i<nsends; i++) { 2617 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2618 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2619 } 2620 /* wait on receives of mat->i,j */ 2621 /*------------------------------*/ 2622 count = nrecvs; 2623 while (count) { 2624 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2625 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2626 count--; 2627 } 2628 /* wait on sends of mat->i,j */ 2629 /*---------------------------*/ 2630 if (nsends) { 2631 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2632 } 2633 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2634 2635 /* post receives, send and receive mat->a */ 2636 /*----------------------------------------*/ 2637 for (imdex=0; imdex<nrecvs; imdex++) { 2638 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2639 } 2640 for (i=0; i<nsends; i++) { 2641 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2642 } 2643 count = nrecvs; 2644 while (count) { 2645 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2646 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2647 count--; 2648 } 2649 if (nsends) { 2650 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2651 } 2652 2653 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2654 2655 /* create redundant matrix */ 2656 /*-------------------------*/ 2657 if (reuse == MAT_INITIAL_MATRIX) { 2658 const PetscInt *range; 2659 PetscInt rstart_sub,rend_sub,mloc_sub; 2660 2661 /* compute rownz_max for preallocation */ 2662 for (imdex=0; imdex<nrecvs; imdex++) { 2663 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2664 rptr = rbuf_j[imdex]; 2665 for (i=0; i<j; i++) { 2666 ncols = rptr[i+1] - rptr[i]; 2667 if (rownz_max < ncols) rownz_max = ncols; 2668 } 2669 } 2670 2671 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2672 2673 /* get local size of redundant matrix 2674 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2675 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2676 rstart_sub = range[nsubcomm*subrank]; 2677 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2678 rend_sub = range[nsubcomm*(subrank+1)]; 2679 } else { 2680 rend_sub = mat->rmap->N; 2681 } 2682 mloc_sub = rend_sub - rstart_sub; 2683 2684 if (M == N) { 2685 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2686 } else { /* non-square matrix */ 2687 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2688 } 2689 ierr = MatSetBlockSizesFromMats(C,mat,mat);CHKERRQ(ierr); 2690 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2691 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2692 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2693 } else { 2694 C = *matredundant; 2695 } 2696 2697 /* insert local matrix entries */ 2698 rptr = sbuf_j; 2699 cols = sbuf_j + rend-rstart + 1; 2700 vals = sbuf_a; 2701 for (i=0; i<rend-rstart; i++) { 2702 row = i + rstart; 2703 ncols = rptr[i+1] - rptr[i]; 2704 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2705 vals += ncols; 2706 cols += ncols; 2707 } 2708 /* insert received matrix entries */ 2709 for (imdex=0; imdex<nrecvs; imdex++) { 2710 rstart = rowrange[recv_rank[imdex]]; 2711 rend = rowrange[recv_rank[imdex]+1]; 2712 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2713 rptr = rbuf_j[imdex]; 2714 cols = rbuf_j[imdex] + rend-rstart + 1; 2715 vals = rbuf_a[imdex]; 2716 for (i=0; i<rend-rstart; i++) { 2717 row = i + rstart; 2718 ncols = rptr[i+1] - rptr[i]; 2719 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2720 vals += ncols; 2721 cols += ncols; 2722 } 2723 } 2724 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2725 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2726 2727 if (reuse == MAT_INITIAL_MATRIX) { 2728 *matredundant = C; 2729 2730 /* create a supporting struct and attach it to C for reuse */ 2731 ierr = PetscNewLog(C,&redund);CHKERRQ(ierr); 2732 C->redundant = redund; 2733 redund->nzlocal = nzlocal; 2734 redund->nsends = nsends; 2735 redund->nrecvs = nrecvs; 2736 redund->send_rank = send_rank; 2737 redund->recv_rank = recv_rank; 2738 redund->sbuf_nz = sbuf_nz; 2739 redund->rbuf_nz = rbuf_nz; 2740 redund->sbuf_j = sbuf_j; 2741 redund->sbuf_a = sbuf_a; 2742 redund->rbuf_j = rbuf_j; 2743 redund->rbuf_a = rbuf_a; 2744 redund->subcomm = subcomm; 2745 redund->type = PETSC_SUBCOMM_INTERLACED; 2746 } 2747 PetscFunctionReturn(0); 2748 } 2749 2750 #undef __FUNCT__ 2751 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2752 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2753 { 2754 PetscErrorCode ierr; 2755 MPI_Comm comm; 2756 PetscMPIInt size; 2757 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2758 Mat_Redundant *redund=NULL; 2759 PetscSubcomm psubcomm=NULL; 2760 MPI_Comm subcomm_in=subcomm; 2761 Mat *matseq; 2762 IS isrow,iscol; 2763 PetscBool newsubcomm=PETSC_FALSE; 2764 2765 PetscFunctionBegin; 2766 if (subcomm_in == MPI_COMM_NULL && reuse == MAT_INITIAL_MATRIX) { /* get subcomm if user does not provide subcomm */ 2767 /* create psubcomm, then get subcomm */ 2768 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2769 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2770 if (nsubcomm < 1 || nsubcomm > size) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"nsubcomm must between 1 and %D",size); 2771 2772 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2773 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2774 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2775 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2776 ierr = PetscCommDuplicate(psubcomm->comm,&subcomm,NULL);CHKERRQ(ierr); 2777 newsubcomm = PETSC_TRUE; 2778 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2779 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2780 ierr = PetscSubcommDestroy(&psubcomm);CHKERRQ(ierr); 2781 PetscFunctionReturn(0); 2782 } 2783 ierr = PetscSubcommDestroy(&psubcomm);CHKERRQ(ierr); 2784 } 2785 2786 /* get isrow and iscol for redund->type == PETSC_SUBCOMM_CONTIGUOUS */ 2787 if (reuse == MAT_INITIAL_MATRIX) { 2788 /* create a local sequential matrix matseq[0] */ 2789 mloc_sub = PETSC_DECIDE; 2790 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2791 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2792 rstart = rend - mloc_sub; 2793 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2794 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2795 } else { /* reuse == MAT_REUSE_MATRIX */ 2796 /* retrieve subcomm */ 2797 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2798 redund = (*matredundant)->redundant; 2799 if (redund->type == PETSC_SUBCOMM_INTERLACED) { 2800 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2801 PetscFunctionReturn(0); 2802 } 2803 2804 isrow = redund->isrow; 2805 iscol = redund->iscol; 2806 matseq = redund->matseq; 2807 } 2808 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2809 ierr = MatCreateMPIMatConcatenateSeqMat(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2810 2811 if (reuse == MAT_INITIAL_MATRIX) { 2812 /* create a supporting struct and attach it to C for reuse */ 2813 ierr = PetscNewLog(*matredundant,&redund);CHKERRQ(ierr); 2814 (*matredundant)->redundant = redund; 2815 redund->isrow = isrow; 2816 redund->iscol = iscol; 2817 redund->matseq = matseq; 2818 if (newsubcomm) { 2819 redund->subcomm = subcomm; 2820 } else { 2821 redund->subcomm = MPI_COMM_NULL; 2822 } 2823 redund->type = PETSC_SUBCOMM_CONTIGUOUS; 2824 } 2825 PetscFunctionReturn(0); 2826 } 2827 2828 #undef __FUNCT__ 2829 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2830 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2831 { 2832 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2833 PetscErrorCode ierr; 2834 PetscInt i,*idxb = 0; 2835 PetscScalar *va,*vb; 2836 Vec vtmp; 2837 2838 PetscFunctionBegin; 2839 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2840 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2841 if (idx) { 2842 for (i=0; i<A->rmap->n; i++) { 2843 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2844 } 2845 } 2846 2847 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2848 if (idx) { 2849 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2850 } 2851 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2852 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2853 2854 for (i=0; i<A->rmap->n; i++) { 2855 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2856 va[i] = vb[i]; 2857 if (idx) idx[i] = a->garray[idxb[i]]; 2858 } 2859 } 2860 2861 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2862 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2863 ierr = PetscFree(idxb);CHKERRQ(ierr); 2864 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2865 PetscFunctionReturn(0); 2866 } 2867 2868 #undef __FUNCT__ 2869 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2870 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2871 { 2872 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2873 PetscErrorCode ierr; 2874 PetscInt i,*idxb = 0; 2875 PetscScalar *va,*vb; 2876 Vec vtmp; 2877 2878 PetscFunctionBegin; 2879 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2880 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2881 if (idx) { 2882 for (i=0; i<A->cmap->n; i++) { 2883 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2884 } 2885 } 2886 2887 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2888 if (idx) { 2889 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2890 } 2891 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2892 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2893 2894 for (i=0; i<A->rmap->n; i++) { 2895 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2896 va[i] = vb[i]; 2897 if (idx) idx[i] = a->garray[idxb[i]]; 2898 } 2899 } 2900 2901 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2902 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2903 ierr = PetscFree(idxb);CHKERRQ(ierr); 2904 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2905 PetscFunctionReturn(0); 2906 } 2907 2908 #undef __FUNCT__ 2909 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2910 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2911 { 2912 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2913 PetscInt n = A->rmap->n; 2914 PetscInt cstart = A->cmap->rstart; 2915 PetscInt *cmap = mat->garray; 2916 PetscInt *diagIdx, *offdiagIdx; 2917 Vec diagV, offdiagV; 2918 PetscScalar *a, *diagA, *offdiagA; 2919 PetscInt r; 2920 PetscErrorCode ierr; 2921 2922 PetscFunctionBegin; 2923 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2924 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2925 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2926 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2927 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2928 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2929 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2930 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2931 for (r = 0; r < n; ++r) { 2932 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2933 a[r] = diagA[r]; 2934 idx[r] = cstart + diagIdx[r]; 2935 } else { 2936 a[r] = offdiagA[r]; 2937 idx[r] = cmap[offdiagIdx[r]]; 2938 } 2939 } 2940 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2941 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2942 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2943 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2944 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2945 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2946 PetscFunctionReturn(0); 2947 } 2948 2949 #undef __FUNCT__ 2950 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2951 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2952 { 2953 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2954 PetscInt n = A->rmap->n; 2955 PetscInt cstart = A->cmap->rstart; 2956 PetscInt *cmap = mat->garray; 2957 PetscInt *diagIdx, *offdiagIdx; 2958 Vec diagV, offdiagV; 2959 PetscScalar *a, *diagA, *offdiagA; 2960 PetscInt r; 2961 PetscErrorCode ierr; 2962 2963 PetscFunctionBegin; 2964 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2965 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2966 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2967 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2968 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2969 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2970 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2971 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2972 for (r = 0; r < n; ++r) { 2973 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2974 a[r] = diagA[r]; 2975 idx[r] = cstart + diagIdx[r]; 2976 } else { 2977 a[r] = offdiagA[r]; 2978 idx[r] = cmap[offdiagIdx[r]]; 2979 } 2980 } 2981 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2982 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2983 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2984 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2985 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2986 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2987 PetscFunctionReturn(0); 2988 } 2989 2990 #undef __FUNCT__ 2991 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2992 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2993 { 2994 PetscErrorCode ierr; 2995 Mat *dummy; 2996 2997 PetscFunctionBegin; 2998 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2999 *newmat = *dummy; 3000 ierr = PetscFree(dummy);CHKERRQ(ierr); 3001 PetscFunctionReturn(0); 3002 } 3003 3004 #undef __FUNCT__ 3005 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3006 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3007 { 3008 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3009 PetscErrorCode ierr; 3010 3011 PetscFunctionBegin; 3012 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3013 PetscFunctionReturn(0); 3014 } 3015 3016 #undef __FUNCT__ 3017 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3018 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3019 { 3020 PetscErrorCode ierr; 3021 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3022 3023 PetscFunctionBegin; 3024 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3025 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3026 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3027 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3028 PetscFunctionReturn(0); 3029 } 3030 3031 /* -------------------------------------------------------------------*/ 3032 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3033 MatGetRow_MPIAIJ, 3034 MatRestoreRow_MPIAIJ, 3035 MatMult_MPIAIJ, 3036 /* 4*/ MatMultAdd_MPIAIJ, 3037 MatMultTranspose_MPIAIJ, 3038 MatMultTransposeAdd_MPIAIJ, 3039 #if defined(PETSC_HAVE_PBGL) 3040 MatSolve_MPIAIJ, 3041 #else 3042 0, 3043 #endif 3044 0, 3045 0, 3046 /*10*/ 0, 3047 0, 3048 0, 3049 MatSOR_MPIAIJ, 3050 MatTranspose_MPIAIJ, 3051 /*15*/ MatGetInfo_MPIAIJ, 3052 MatEqual_MPIAIJ, 3053 MatGetDiagonal_MPIAIJ, 3054 MatDiagonalScale_MPIAIJ, 3055 MatNorm_MPIAIJ, 3056 /*20*/ MatAssemblyBegin_MPIAIJ, 3057 MatAssemblyEnd_MPIAIJ, 3058 MatSetOption_MPIAIJ, 3059 MatZeroEntries_MPIAIJ, 3060 /*24*/ MatZeroRows_MPIAIJ, 3061 0, 3062 #if defined(PETSC_HAVE_PBGL) 3063 0, 3064 #else 3065 0, 3066 #endif 3067 0, 3068 0, 3069 /*29*/ MatSetUp_MPIAIJ, 3070 #if defined(PETSC_HAVE_PBGL) 3071 0, 3072 #else 3073 0, 3074 #endif 3075 0, 3076 0, 3077 0, 3078 /*34*/ MatDuplicate_MPIAIJ, 3079 0, 3080 0, 3081 0, 3082 0, 3083 /*39*/ MatAXPY_MPIAIJ, 3084 MatGetSubMatrices_MPIAIJ, 3085 MatIncreaseOverlap_MPIAIJ, 3086 MatGetValues_MPIAIJ, 3087 MatCopy_MPIAIJ, 3088 /*44*/ MatGetRowMax_MPIAIJ, 3089 MatScale_MPIAIJ, 3090 0, 3091 MatDiagonalSet_MPIAIJ, 3092 MatZeroRowsColumns_MPIAIJ, 3093 /*49*/ MatSetRandom_MPIAIJ, 3094 0, 3095 0, 3096 0, 3097 0, 3098 /*54*/ MatFDColoringCreate_MPIXAIJ, 3099 0, 3100 MatSetUnfactored_MPIAIJ, 3101 MatPermute_MPIAIJ, 3102 0, 3103 /*59*/ MatGetSubMatrix_MPIAIJ, 3104 MatDestroy_MPIAIJ, 3105 MatView_MPIAIJ, 3106 0, 3107 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3108 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3109 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3110 0, 3111 0, 3112 0, 3113 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3114 MatGetRowMinAbs_MPIAIJ, 3115 0, 3116 MatSetColoring_MPIAIJ, 3117 0, 3118 MatSetValuesAdifor_MPIAIJ, 3119 /*75*/ MatFDColoringApply_AIJ, 3120 0, 3121 0, 3122 0, 3123 MatFindZeroDiagonals_MPIAIJ, 3124 /*80*/ 0, 3125 0, 3126 0, 3127 /*83*/ MatLoad_MPIAIJ, 3128 0, 3129 0, 3130 0, 3131 0, 3132 0, 3133 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3134 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3135 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3136 MatPtAP_MPIAIJ_MPIAIJ, 3137 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3138 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3139 0, 3140 0, 3141 0, 3142 0, 3143 /*99*/ 0, 3144 0, 3145 0, 3146 MatConjugate_MPIAIJ, 3147 0, 3148 /*104*/MatSetValuesRow_MPIAIJ, 3149 MatRealPart_MPIAIJ, 3150 MatImaginaryPart_MPIAIJ, 3151 0, 3152 0, 3153 /*109*/0, 3154 MatGetRedundantMatrix_MPIAIJ, 3155 MatGetRowMin_MPIAIJ, 3156 0, 3157 0, 3158 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3159 0, 3160 0, 3161 0, 3162 0, 3163 /*119*/0, 3164 0, 3165 0, 3166 0, 3167 MatGetMultiProcBlock_MPIAIJ, 3168 /*124*/MatFindNonzeroRows_MPIAIJ, 3169 MatGetColumnNorms_MPIAIJ, 3170 MatInvertBlockDiagonal_MPIAIJ, 3171 0, 3172 MatGetSubMatricesParallel_MPIAIJ, 3173 /*129*/0, 3174 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3175 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3176 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3177 0, 3178 /*134*/0, 3179 0, 3180 0, 3181 0, 3182 0, 3183 /*139*/0, 3184 0, 3185 0, 3186 MatFDColoringSetUp_MPIXAIJ, 3187 0, 3188 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 3189 }; 3190 3191 /* ----------------------------------------------------------------------------------------*/ 3192 3193 #undef __FUNCT__ 3194 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3195 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3196 { 3197 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3198 PetscErrorCode ierr; 3199 3200 PetscFunctionBegin; 3201 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3202 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3203 PetscFunctionReturn(0); 3204 } 3205 3206 #undef __FUNCT__ 3207 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3208 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3209 { 3210 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3211 PetscErrorCode ierr; 3212 3213 PetscFunctionBegin; 3214 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3215 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3216 PetscFunctionReturn(0); 3217 } 3218 3219 #undef __FUNCT__ 3220 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3221 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3222 { 3223 Mat_MPIAIJ *b; 3224 PetscErrorCode ierr; 3225 3226 PetscFunctionBegin; 3227 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3228 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3229 b = (Mat_MPIAIJ*)B->data; 3230 3231 if (!B->preallocated) { 3232 /* Explicitly create 2 MATSEQAIJ matrices. */ 3233 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3234 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3235 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 3236 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3237 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3238 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3239 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3240 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 3241 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3242 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3243 } 3244 3245 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3246 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3247 B->preallocated = PETSC_TRUE; 3248 PetscFunctionReturn(0); 3249 } 3250 3251 #undef __FUNCT__ 3252 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3253 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3254 { 3255 Mat mat; 3256 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3257 PetscErrorCode ierr; 3258 3259 PetscFunctionBegin; 3260 *newmat = 0; 3261 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3262 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3263 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 3264 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3265 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3266 a = (Mat_MPIAIJ*)mat->data; 3267 3268 mat->factortype = matin->factortype; 3269 mat->assembled = PETSC_TRUE; 3270 mat->insertmode = NOT_SET_VALUES; 3271 mat->preallocated = PETSC_TRUE; 3272 3273 a->size = oldmat->size; 3274 a->rank = oldmat->rank; 3275 a->donotstash = oldmat->donotstash; 3276 a->roworiented = oldmat->roworiented; 3277 a->rowindices = 0; 3278 a->rowvalues = 0; 3279 a->getrowactive = PETSC_FALSE; 3280 3281 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3282 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3283 3284 if (oldmat->colmap) { 3285 #if defined(PETSC_USE_CTABLE) 3286 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3287 #else 3288 ierr = PetscMalloc1((mat->cmap->N),&a->colmap);CHKERRQ(ierr); 3289 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3290 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3291 #endif 3292 } else a->colmap = 0; 3293 if (oldmat->garray) { 3294 PetscInt len; 3295 len = oldmat->B->cmap->n; 3296 ierr = PetscMalloc1((len+1),&a->garray);CHKERRQ(ierr); 3297 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3298 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3299 } else a->garray = 0; 3300 3301 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3302 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3303 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3304 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3305 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3306 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3307 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3308 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3309 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3310 *newmat = mat; 3311 PetscFunctionReturn(0); 3312 } 3313 3314 3315 3316 #undef __FUNCT__ 3317 #define __FUNCT__ "MatLoad_MPIAIJ" 3318 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3319 { 3320 PetscScalar *vals,*svals; 3321 MPI_Comm comm; 3322 PetscErrorCode ierr; 3323 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3324 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3325 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3326 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3327 PetscInt cend,cstart,n,*rowners,sizesset=1; 3328 int fd; 3329 PetscInt bs = 1; 3330 3331 PetscFunctionBegin; 3332 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3333 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3334 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3335 if (!rank) { 3336 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3337 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3338 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3339 } 3340 3341 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3342 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3343 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3344 3345 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3346 3347 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3348 M = header[1]; N = header[2]; 3349 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3350 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3351 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3352 3353 /* If global sizes are set, check if they are consistent with that given in the file */ 3354 if (sizesset) { 3355 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3356 } 3357 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); 3358 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); 3359 3360 /* determine ownership of all (block) rows */ 3361 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3362 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3363 else m = newMat->rmap->n; /* Set by user */ 3364 3365 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 3366 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3367 3368 /* First process needs enough room for process with most rows */ 3369 if (!rank) { 3370 mmax = rowners[1]; 3371 for (i=2; i<=size; i++) { 3372 mmax = PetscMax(mmax, rowners[i]); 3373 } 3374 } else mmax = -1; /* unused, but compilers complain */ 3375 3376 rowners[0] = 0; 3377 for (i=2; i<=size; i++) { 3378 rowners[i] += rowners[i-1]; 3379 } 3380 rstart = rowners[rank]; 3381 rend = rowners[rank+1]; 3382 3383 /* distribute row lengths to all processors */ 3384 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 3385 if (!rank) { 3386 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3387 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3388 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3389 for (j=0; j<m; j++) { 3390 procsnz[0] += ourlens[j]; 3391 } 3392 for (i=1; i<size; i++) { 3393 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3394 /* calculate the number of nonzeros on each processor */ 3395 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3396 procsnz[i] += rowlengths[j]; 3397 } 3398 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3399 } 3400 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3401 } else { 3402 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3403 } 3404 3405 if (!rank) { 3406 /* determine max buffer needed and allocate it */ 3407 maxnz = 0; 3408 for (i=0; i<size; i++) { 3409 maxnz = PetscMax(maxnz,procsnz[i]); 3410 } 3411 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3412 3413 /* read in my part of the matrix column indices */ 3414 nz = procsnz[0]; 3415 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3416 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3417 3418 /* read in every one elses and ship off */ 3419 for (i=1; i<size; i++) { 3420 nz = procsnz[i]; 3421 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3422 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3423 } 3424 ierr = PetscFree(cols);CHKERRQ(ierr); 3425 } else { 3426 /* determine buffer space needed for message */ 3427 nz = 0; 3428 for (i=0; i<m; i++) { 3429 nz += ourlens[i]; 3430 } 3431 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3432 3433 /* receive message of column indices*/ 3434 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3435 } 3436 3437 /* determine column ownership if matrix is not square */ 3438 if (N != M) { 3439 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3440 else n = newMat->cmap->n; 3441 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3442 cstart = cend - n; 3443 } else { 3444 cstart = rstart; 3445 cend = rend; 3446 n = cend - cstart; 3447 } 3448 3449 /* loop over local rows, determining number of off diagonal entries */ 3450 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3451 jj = 0; 3452 for (i=0; i<m; i++) { 3453 for (j=0; j<ourlens[i]; j++) { 3454 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3455 jj++; 3456 } 3457 } 3458 3459 for (i=0; i<m; i++) { 3460 ourlens[i] -= offlens[i]; 3461 } 3462 if (!sizesset) { 3463 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3464 } 3465 3466 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3467 3468 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3469 3470 for (i=0; i<m; i++) { 3471 ourlens[i] += offlens[i]; 3472 } 3473 3474 if (!rank) { 3475 ierr = PetscMalloc1((maxnz+1),&vals);CHKERRQ(ierr); 3476 3477 /* read in my part of the matrix numerical values */ 3478 nz = procsnz[0]; 3479 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3480 3481 /* insert into matrix */ 3482 jj = rstart; 3483 smycols = mycols; 3484 svals = vals; 3485 for (i=0; i<m; i++) { 3486 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3487 smycols += ourlens[i]; 3488 svals += ourlens[i]; 3489 jj++; 3490 } 3491 3492 /* read in other processors and ship out */ 3493 for (i=1; i<size; i++) { 3494 nz = procsnz[i]; 3495 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3496 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3497 } 3498 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3499 } else { 3500 /* receive numeric values */ 3501 ierr = PetscMalloc1((nz+1),&vals);CHKERRQ(ierr); 3502 3503 /* receive message of values*/ 3504 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3505 3506 /* insert into matrix */ 3507 jj = rstart; 3508 smycols = mycols; 3509 svals = vals; 3510 for (i=0; i<m; i++) { 3511 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3512 smycols += ourlens[i]; 3513 svals += ourlens[i]; 3514 jj++; 3515 } 3516 } 3517 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3518 ierr = PetscFree(vals);CHKERRQ(ierr); 3519 ierr = PetscFree(mycols);CHKERRQ(ierr); 3520 ierr = PetscFree(rowners);CHKERRQ(ierr); 3521 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3522 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3523 PetscFunctionReturn(0); 3524 } 3525 3526 #undef __FUNCT__ 3527 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3528 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3529 { 3530 PetscErrorCode ierr; 3531 IS iscol_local; 3532 PetscInt csize; 3533 3534 PetscFunctionBegin; 3535 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3536 if (call == MAT_REUSE_MATRIX) { 3537 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3538 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3539 } else { 3540 PetscInt cbs; 3541 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3542 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3543 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3544 } 3545 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3546 if (call == MAT_INITIAL_MATRIX) { 3547 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3548 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3549 } 3550 PetscFunctionReturn(0); 3551 } 3552 3553 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3554 #undef __FUNCT__ 3555 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3556 /* 3557 Not great since it makes two copies of the submatrix, first an SeqAIJ 3558 in local and then by concatenating the local matrices the end result. 3559 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3560 3561 Note: This requires a sequential iscol with all indices. 3562 */ 3563 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3564 { 3565 PetscErrorCode ierr; 3566 PetscMPIInt rank,size; 3567 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3568 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3569 PetscBool allcolumns, colflag; 3570 Mat M,Mreuse; 3571 MatScalar *vwork,*aa; 3572 MPI_Comm comm; 3573 Mat_SeqAIJ *aij; 3574 3575 PetscFunctionBegin; 3576 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3577 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3578 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3579 3580 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3581 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3582 if (colflag && ncol == mat->cmap->N) { 3583 allcolumns = PETSC_TRUE; 3584 } else { 3585 allcolumns = PETSC_FALSE; 3586 } 3587 if (call == MAT_REUSE_MATRIX) { 3588 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3589 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3590 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3591 } else { 3592 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3593 } 3594 3595 /* 3596 m - number of local rows 3597 n - number of columns (same on all processors) 3598 rstart - first row in new global matrix generated 3599 */ 3600 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3601 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3602 if (call == MAT_INITIAL_MATRIX) { 3603 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3604 ii = aij->i; 3605 jj = aij->j; 3606 3607 /* 3608 Determine the number of non-zeros in the diagonal and off-diagonal 3609 portions of the matrix in order to do correct preallocation 3610 */ 3611 3612 /* first get start and end of "diagonal" columns */ 3613 if (csize == PETSC_DECIDE) { 3614 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3615 if (mglobal == n) { /* square matrix */ 3616 nlocal = m; 3617 } else { 3618 nlocal = n/size + ((n % size) > rank); 3619 } 3620 } else { 3621 nlocal = csize; 3622 } 3623 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3624 rstart = rend - nlocal; 3625 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); 3626 3627 /* next, compute all the lengths */ 3628 ierr = PetscMalloc1((2*m+1),&dlens);CHKERRQ(ierr); 3629 olens = dlens + m; 3630 for (i=0; i<m; i++) { 3631 jend = ii[i+1] - ii[i]; 3632 olen = 0; 3633 dlen = 0; 3634 for (j=0; j<jend; j++) { 3635 if (*jj < rstart || *jj >= rend) olen++; 3636 else dlen++; 3637 jj++; 3638 } 3639 olens[i] = olen; 3640 dlens[i] = dlen; 3641 } 3642 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3643 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3644 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3645 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3646 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3647 ierr = PetscFree(dlens);CHKERRQ(ierr); 3648 } else { 3649 PetscInt ml,nl; 3650 3651 M = *newmat; 3652 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3653 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3654 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3655 /* 3656 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3657 rather than the slower MatSetValues(). 3658 */ 3659 M->was_assembled = PETSC_TRUE; 3660 M->assembled = PETSC_FALSE; 3661 } 3662 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3663 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3664 ii = aij->i; 3665 jj = aij->j; 3666 aa = aij->a; 3667 for (i=0; i<m; i++) { 3668 row = rstart + i; 3669 nz = ii[i+1] - ii[i]; 3670 cwork = jj; jj += nz; 3671 vwork = aa; aa += nz; 3672 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3673 } 3674 3675 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3676 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3677 *newmat = M; 3678 3679 /* save submatrix used in processor for next request */ 3680 if (call == MAT_INITIAL_MATRIX) { 3681 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3682 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3683 } 3684 PetscFunctionReturn(0); 3685 } 3686 3687 #undef __FUNCT__ 3688 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3689 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3690 { 3691 PetscInt m,cstart, cend,j,nnz,i,d; 3692 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3693 const PetscInt *JJ; 3694 PetscScalar *values; 3695 PetscErrorCode ierr; 3696 3697 PetscFunctionBegin; 3698 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3699 3700 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3701 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3702 m = B->rmap->n; 3703 cstart = B->cmap->rstart; 3704 cend = B->cmap->rend; 3705 rstart = B->rmap->rstart; 3706 3707 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3708 3709 #if defined(PETSC_USE_DEBUGGING) 3710 for (i=0; i<m; i++) { 3711 nnz = Ii[i+1]- Ii[i]; 3712 JJ = J + Ii[i]; 3713 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3714 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3715 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); 3716 } 3717 #endif 3718 3719 for (i=0; i<m; i++) { 3720 nnz = Ii[i+1]- Ii[i]; 3721 JJ = J + Ii[i]; 3722 nnz_max = PetscMax(nnz_max,nnz); 3723 d = 0; 3724 for (j=0; j<nnz; j++) { 3725 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3726 } 3727 d_nnz[i] = d; 3728 o_nnz[i] = nnz - d; 3729 } 3730 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3731 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3732 3733 if (v) values = (PetscScalar*)v; 3734 else { 3735 ierr = PetscCalloc1((nnz_max+1),&values);CHKERRQ(ierr); 3736 } 3737 3738 for (i=0; i<m; i++) { 3739 ii = i + rstart; 3740 nnz = Ii[i+1]- Ii[i]; 3741 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3742 } 3743 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3744 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3745 3746 if (!v) { 3747 ierr = PetscFree(values);CHKERRQ(ierr); 3748 } 3749 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3750 PetscFunctionReturn(0); 3751 } 3752 3753 #undef __FUNCT__ 3754 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3755 /*@ 3756 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3757 (the default parallel PETSc format). 3758 3759 Collective on MPI_Comm 3760 3761 Input Parameters: 3762 + B - the matrix 3763 . i - the indices into j for the start of each local row (starts with zero) 3764 . j - the column indices for each local row (starts with zero) 3765 - v - optional values in the matrix 3766 3767 Level: developer 3768 3769 Notes: 3770 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3771 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3772 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3773 3774 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3775 3776 The format which is used for the sparse matrix input, is equivalent to a 3777 row-major ordering.. i.e for the following matrix, the input data expected is 3778 as shown: 3779 3780 1 0 0 3781 2 0 3 P0 3782 ------- 3783 4 5 6 P1 3784 3785 Process0 [P0]: rows_owned=[0,1] 3786 i = {0,1,3} [size = nrow+1 = 2+1] 3787 j = {0,0,2} [size = nz = 6] 3788 v = {1,2,3} [size = nz = 6] 3789 3790 Process1 [P1]: rows_owned=[2] 3791 i = {0,3} [size = nrow+1 = 1+1] 3792 j = {0,1,2} [size = nz = 6] 3793 v = {4,5,6} [size = nz = 6] 3794 3795 .keywords: matrix, aij, compressed row, sparse, parallel 3796 3797 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3798 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3799 @*/ 3800 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3801 { 3802 PetscErrorCode ierr; 3803 3804 PetscFunctionBegin; 3805 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3806 PetscFunctionReturn(0); 3807 } 3808 3809 #undef __FUNCT__ 3810 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3811 /*@C 3812 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3813 (the default parallel PETSc format). For good matrix assembly performance 3814 the user should preallocate the matrix storage by setting the parameters 3815 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3816 performance can be increased by more than a factor of 50. 3817 3818 Collective on MPI_Comm 3819 3820 Input Parameters: 3821 + B - the matrix 3822 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3823 (same value is used for all local rows) 3824 . d_nnz - array containing the number of nonzeros in the various rows of the 3825 DIAGONAL portion of the local submatrix (possibly different for each row) 3826 or NULL, if d_nz is used to specify the nonzero structure. 3827 The size of this array is equal to the number of local rows, i.e 'm'. 3828 For matrices that will be factored, you must leave room for (and set) 3829 the diagonal entry even if it is zero. 3830 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3831 submatrix (same value is used for all local rows). 3832 - o_nnz - array containing the number of nonzeros in the various rows of the 3833 OFF-DIAGONAL portion of the local submatrix (possibly different for 3834 each row) or NULL, if o_nz is used to specify the nonzero 3835 structure. The size of this array is equal to the number 3836 of local rows, i.e 'm'. 3837 3838 If the *_nnz parameter is given then the *_nz parameter is ignored 3839 3840 The AIJ format (also called the Yale sparse matrix format or 3841 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3842 storage. The stored row and column indices begin with zero. 3843 See Users-Manual: ch_mat for details. 3844 3845 The parallel matrix is partitioned such that the first m0 rows belong to 3846 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3847 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3848 3849 The DIAGONAL portion of the local submatrix of a processor can be defined 3850 as the submatrix which is obtained by extraction the part corresponding to 3851 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3852 first row that belongs to the processor, r2 is the last row belonging to 3853 the this processor, and c1-c2 is range of indices of the local part of a 3854 vector suitable for applying the matrix to. This is an mxn matrix. In the 3855 common case of a square matrix, the row and column ranges are the same and 3856 the DIAGONAL part is also square. The remaining portion of the local 3857 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3858 3859 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3860 3861 You can call MatGetInfo() to get information on how effective the preallocation was; 3862 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3863 You can also run with the option -info and look for messages with the string 3864 malloc in them to see if additional memory allocation was needed. 3865 3866 Example usage: 3867 3868 Consider the following 8x8 matrix with 34 non-zero values, that is 3869 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3870 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3871 as follows: 3872 3873 .vb 3874 1 2 0 | 0 3 0 | 0 4 3875 Proc0 0 5 6 | 7 0 0 | 8 0 3876 9 0 10 | 11 0 0 | 12 0 3877 ------------------------------------- 3878 13 0 14 | 15 16 17 | 0 0 3879 Proc1 0 18 0 | 19 20 21 | 0 0 3880 0 0 0 | 22 23 0 | 24 0 3881 ------------------------------------- 3882 Proc2 25 26 27 | 0 0 28 | 29 0 3883 30 0 0 | 31 32 33 | 0 34 3884 .ve 3885 3886 This can be represented as a collection of submatrices as: 3887 3888 .vb 3889 A B C 3890 D E F 3891 G H I 3892 .ve 3893 3894 Where the submatrices A,B,C are owned by proc0, D,E,F are 3895 owned by proc1, G,H,I are owned by proc2. 3896 3897 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3898 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3899 The 'M','N' parameters are 8,8, and have the same values on all procs. 3900 3901 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3902 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3903 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3904 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3905 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3906 matrix, ans [DF] as another SeqAIJ matrix. 3907 3908 When d_nz, o_nz parameters are specified, d_nz storage elements are 3909 allocated for every row of the local diagonal submatrix, and o_nz 3910 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3911 One way to choose d_nz and o_nz is to use the max nonzerors per local 3912 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3913 In this case, the values of d_nz,o_nz are: 3914 .vb 3915 proc0 : dnz = 2, o_nz = 2 3916 proc1 : dnz = 3, o_nz = 2 3917 proc2 : dnz = 1, o_nz = 4 3918 .ve 3919 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3920 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3921 for proc3. i.e we are using 12+15+10=37 storage locations to store 3922 34 values. 3923 3924 When d_nnz, o_nnz parameters are specified, the storage is specified 3925 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3926 In the above case the values for d_nnz,o_nnz are: 3927 .vb 3928 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3929 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3930 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3931 .ve 3932 Here the space allocated is sum of all the above values i.e 34, and 3933 hence pre-allocation is perfect. 3934 3935 Level: intermediate 3936 3937 .keywords: matrix, aij, compressed row, sparse, parallel 3938 3939 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3940 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3941 @*/ 3942 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3943 { 3944 PetscErrorCode ierr; 3945 3946 PetscFunctionBegin; 3947 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3948 PetscValidType(B,1); 3949 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3950 PetscFunctionReturn(0); 3951 } 3952 3953 #undef __FUNCT__ 3954 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3955 /*@ 3956 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3957 CSR format the local rows. 3958 3959 Collective on MPI_Comm 3960 3961 Input Parameters: 3962 + comm - MPI communicator 3963 . m - number of local rows (Cannot be PETSC_DECIDE) 3964 . n - This value should be the same as the local size used in creating the 3965 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3966 calculated if N is given) For square matrices n is almost always m. 3967 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3968 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3969 . i - row indices 3970 . j - column indices 3971 - a - matrix values 3972 3973 Output Parameter: 3974 . mat - the matrix 3975 3976 Level: intermediate 3977 3978 Notes: 3979 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3980 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3981 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3982 3983 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3984 3985 The format which is used for the sparse matrix input, is equivalent to a 3986 row-major ordering.. i.e for the following matrix, the input data expected is 3987 as shown: 3988 3989 1 0 0 3990 2 0 3 P0 3991 ------- 3992 4 5 6 P1 3993 3994 Process0 [P0]: rows_owned=[0,1] 3995 i = {0,1,3} [size = nrow+1 = 2+1] 3996 j = {0,0,2} [size = nz = 6] 3997 v = {1,2,3} [size = nz = 6] 3998 3999 Process1 [P1]: rows_owned=[2] 4000 i = {0,3} [size = nrow+1 = 1+1] 4001 j = {0,1,2} [size = nz = 6] 4002 v = {4,5,6} [size = nz = 6] 4003 4004 .keywords: matrix, aij, compressed row, sparse, parallel 4005 4006 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4007 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4008 @*/ 4009 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4010 { 4011 PetscErrorCode ierr; 4012 4013 PetscFunctionBegin; 4014 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4015 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4016 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4017 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4018 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4019 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4020 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4021 PetscFunctionReturn(0); 4022 } 4023 4024 #undef __FUNCT__ 4025 #define __FUNCT__ "MatCreateAIJ" 4026 /*@C 4027 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4028 (the default parallel PETSc format). For good matrix assembly performance 4029 the user should preallocate the matrix storage by setting the parameters 4030 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4031 performance can be increased by more than a factor of 50. 4032 4033 Collective on MPI_Comm 4034 4035 Input Parameters: 4036 + comm - MPI communicator 4037 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4038 This value should be the same as the local size used in creating the 4039 y vector for the matrix-vector product y = Ax. 4040 . n - This value should be the same as the local size used in creating the 4041 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4042 calculated if N is given) For square matrices n is almost always m. 4043 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4044 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4045 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4046 (same value is used for all local rows) 4047 . d_nnz - array containing the number of nonzeros in the various rows of the 4048 DIAGONAL portion of the local submatrix (possibly different for each row) 4049 or NULL, if d_nz is used to specify the nonzero structure. 4050 The size of this array is equal to the number of local rows, i.e 'm'. 4051 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4052 submatrix (same value is used for all local rows). 4053 - o_nnz - array containing the number of nonzeros in the various rows of the 4054 OFF-DIAGONAL portion of the local submatrix (possibly different for 4055 each row) or NULL, if o_nz is used to specify the nonzero 4056 structure. The size of this array is equal to the number 4057 of local rows, i.e 'm'. 4058 4059 Output Parameter: 4060 . A - the matrix 4061 4062 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4063 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4064 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4065 4066 Notes: 4067 If the *_nnz parameter is given then the *_nz parameter is ignored 4068 4069 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4070 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4071 storage requirements for this matrix. 4072 4073 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4074 processor than it must be used on all processors that share the object for 4075 that argument. 4076 4077 The user MUST specify either the local or global matrix dimensions 4078 (possibly both). 4079 4080 The parallel matrix is partitioned across processors such that the 4081 first m0 rows belong to process 0, the next m1 rows belong to 4082 process 1, the next m2 rows belong to process 2 etc.. where 4083 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4084 values corresponding to [m x N] submatrix. 4085 4086 The columns are logically partitioned with the n0 columns belonging 4087 to 0th partition, the next n1 columns belonging to the next 4088 partition etc.. where n0,n1,n2... are the input parameter 'n'. 4089 4090 The DIAGONAL portion of the local submatrix on any given processor 4091 is the submatrix corresponding to the rows and columns m,n 4092 corresponding to the given processor. i.e diagonal matrix on 4093 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4094 etc. The remaining portion of the local submatrix [m x (N-n)] 4095 constitute the OFF-DIAGONAL portion. The example below better 4096 illustrates this concept. 4097 4098 For a square global matrix we define each processor's diagonal portion 4099 to be its local rows and the corresponding columns (a square submatrix); 4100 each processor's off-diagonal portion encompasses the remainder of the 4101 local matrix (a rectangular submatrix). 4102 4103 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4104 4105 When calling this routine with a single process communicator, a matrix of 4106 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4107 type of communicator, use the construction mechanism: 4108 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4109 4110 By default, this format uses inodes (identical nodes) when possible. 4111 We search for consecutive rows with the same nonzero structure, thereby 4112 reusing matrix information to achieve increased efficiency. 4113 4114 Options Database Keys: 4115 + -mat_no_inode - Do not use inodes 4116 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4117 - -mat_aij_oneindex - Internally use indexing starting at 1 4118 rather than 0. Note that when calling MatSetValues(), 4119 the user still MUST index entries starting at 0! 4120 4121 4122 Example usage: 4123 4124 Consider the following 8x8 matrix with 34 non-zero values, that is 4125 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4126 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4127 as follows: 4128 4129 .vb 4130 1 2 0 | 0 3 0 | 0 4 4131 Proc0 0 5 6 | 7 0 0 | 8 0 4132 9 0 10 | 11 0 0 | 12 0 4133 ------------------------------------- 4134 13 0 14 | 15 16 17 | 0 0 4135 Proc1 0 18 0 | 19 20 21 | 0 0 4136 0 0 0 | 22 23 0 | 24 0 4137 ------------------------------------- 4138 Proc2 25 26 27 | 0 0 28 | 29 0 4139 30 0 0 | 31 32 33 | 0 34 4140 .ve 4141 4142 This can be represented as a collection of submatrices as: 4143 4144 .vb 4145 A B C 4146 D E F 4147 G H I 4148 .ve 4149 4150 Where the submatrices A,B,C are owned by proc0, D,E,F are 4151 owned by proc1, G,H,I are owned by proc2. 4152 4153 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4154 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4155 The 'M','N' parameters are 8,8, and have the same values on all procs. 4156 4157 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4158 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4159 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4160 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4161 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4162 matrix, ans [DF] as another SeqAIJ matrix. 4163 4164 When d_nz, o_nz parameters are specified, d_nz storage elements are 4165 allocated for every row of the local diagonal submatrix, and o_nz 4166 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4167 One way to choose d_nz and o_nz is to use the max nonzerors per local 4168 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4169 In this case, the values of d_nz,o_nz are: 4170 .vb 4171 proc0 : dnz = 2, o_nz = 2 4172 proc1 : dnz = 3, o_nz = 2 4173 proc2 : dnz = 1, o_nz = 4 4174 .ve 4175 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4176 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4177 for proc3. i.e we are using 12+15+10=37 storage locations to store 4178 34 values. 4179 4180 When d_nnz, o_nnz parameters are specified, the storage is specified 4181 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4182 In the above case the values for d_nnz,o_nnz are: 4183 .vb 4184 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4185 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4186 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4187 .ve 4188 Here the space allocated is sum of all the above values i.e 34, and 4189 hence pre-allocation is perfect. 4190 4191 Level: intermediate 4192 4193 .keywords: matrix, aij, compressed row, sparse, parallel 4194 4195 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4196 MPIAIJ, MatCreateMPIAIJWithArrays() 4197 @*/ 4198 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) 4199 { 4200 PetscErrorCode ierr; 4201 PetscMPIInt size; 4202 4203 PetscFunctionBegin; 4204 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4205 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4206 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4207 if (size > 1) { 4208 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4209 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4210 } else { 4211 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4212 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4213 } 4214 PetscFunctionReturn(0); 4215 } 4216 4217 #undef __FUNCT__ 4218 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4219 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4220 { 4221 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4222 4223 PetscFunctionBegin; 4224 if (Ad) *Ad = a->A; 4225 if (Ao) *Ao = a->B; 4226 if (colmap) *colmap = a->garray; 4227 PetscFunctionReturn(0); 4228 } 4229 4230 #undef __FUNCT__ 4231 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4232 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4233 { 4234 PetscErrorCode ierr; 4235 PetscInt i; 4236 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4237 4238 PetscFunctionBegin; 4239 if (coloring->ctype == IS_COLORING_GLOBAL) { 4240 ISColoringValue *allcolors,*colors; 4241 ISColoring ocoloring; 4242 4243 /* set coloring for diagonal portion */ 4244 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4245 4246 /* set coloring for off-diagonal portion */ 4247 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4248 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 4249 for (i=0; i<a->B->cmap->n; i++) { 4250 colors[i] = allcolors[a->garray[i]]; 4251 } 4252 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4253 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4254 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4255 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4256 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4257 ISColoringValue *colors; 4258 PetscInt *larray; 4259 ISColoring ocoloring; 4260 4261 /* set coloring for diagonal portion */ 4262 ierr = PetscMalloc1((a->A->cmap->n+1),&larray);CHKERRQ(ierr); 4263 for (i=0; i<a->A->cmap->n; i++) { 4264 larray[i] = i + A->cmap->rstart; 4265 } 4266 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4267 ierr = PetscMalloc1((a->A->cmap->n+1),&colors);CHKERRQ(ierr); 4268 for (i=0; i<a->A->cmap->n; i++) { 4269 colors[i] = coloring->colors[larray[i]]; 4270 } 4271 ierr = PetscFree(larray);CHKERRQ(ierr); 4272 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4273 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4274 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4275 4276 /* set coloring for off-diagonal portion */ 4277 ierr = PetscMalloc1((a->B->cmap->n+1),&larray);CHKERRQ(ierr); 4278 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4279 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 4280 for (i=0; i<a->B->cmap->n; i++) { 4281 colors[i] = coloring->colors[larray[i]]; 4282 } 4283 ierr = PetscFree(larray);CHKERRQ(ierr); 4284 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4285 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4286 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4287 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4288 PetscFunctionReturn(0); 4289 } 4290 4291 #undef __FUNCT__ 4292 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4293 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4294 { 4295 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4296 PetscErrorCode ierr; 4297 4298 PetscFunctionBegin; 4299 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4300 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4301 PetscFunctionReturn(0); 4302 } 4303 4304 #undef __FUNCT__ 4305 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4306 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4307 { 4308 PetscErrorCode ierr; 4309 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4310 PetscInt *indx; 4311 4312 PetscFunctionBegin; 4313 /* This routine will ONLY return MPIAIJ type matrix */ 4314 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4315 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4316 if (n == PETSC_DECIDE) { 4317 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4318 } 4319 /* Check sum(n) = N */ 4320 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4321 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4322 4323 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4324 rstart -= m; 4325 4326 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4327 for (i=0; i<m; i++) { 4328 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4329 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4330 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4331 } 4332 4333 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4334 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4335 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4336 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4337 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4338 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4339 PetscFunctionReturn(0); 4340 } 4341 4342 #undef __FUNCT__ 4343 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4344 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4345 { 4346 PetscErrorCode ierr; 4347 PetscInt m,N,i,rstart,nnz,Ii; 4348 PetscInt *indx; 4349 PetscScalar *values; 4350 4351 PetscFunctionBegin; 4352 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4353 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4354 for (i=0; i<m; i++) { 4355 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4356 Ii = i + rstart; 4357 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4358 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4359 } 4360 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4361 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4362 PetscFunctionReturn(0); 4363 } 4364 4365 #undef __FUNCT__ 4366 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 4367 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4368 { 4369 PetscErrorCode ierr; 4370 PetscMPIInt size; 4371 4372 PetscFunctionBegin; 4373 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4374 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4375 if (size == 1) { 4376 if (scall == MAT_INITIAL_MATRIX) { 4377 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4378 } else { 4379 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4380 } 4381 } else { 4382 if (scall == MAT_INITIAL_MATRIX) { 4383 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4384 } 4385 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4386 } 4387 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4388 PetscFunctionReturn(0); 4389 } 4390 4391 #undef __FUNCT__ 4392 #define __FUNCT__ "MatFileSplit" 4393 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4394 { 4395 PetscErrorCode ierr; 4396 PetscMPIInt rank; 4397 PetscInt m,N,i,rstart,nnz; 4398 size_t len; 4399 const PetscInt *indx; 4400 PetscViewer out; 4401 char *name; 4402 Mat B; 4403 const PetscScalar *values; 4404 4405 PetscFunctionBegin; 4406 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4407 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4408 /* Should this be the type of the diagonal block of A? */ 4409 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4410 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4411 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4412 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4413 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4414 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4415 for (i=0; i<m; i++) { 4416 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4417 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4418 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4419 } 4420 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4421 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4422 4423 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4424 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4425 ierr = PetscMalloc1((len+5),&name);CHKERRQ(ierr); 4426 sprintf(name,"%s.%d",outfile,rank); 4427 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4428 ierr = PetscFree(name);CHKERRQ(ierr); 4429 ierr = MatView(B,out);CHKERRQ(ierr); 4430 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4431 ierr = MatDestroy(&B);CHKERRQ(ierr); 4432 PetscFunctionReturn(0); 4433 } 4434 4435 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4436 #undef __FUNCT__ 4437 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4438 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4439 { 4440 PetscErrorCode ierr; 4441 Mat_Merge_SeqsToMPI *merge; 4442 PetscContainer container; 4443 4444 PetscFunctionBegin; 4445 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4446 if (container) { 4447 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4448 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4449 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4450 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4451 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4452 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4453 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4454 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4455 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4456 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4457 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4458 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4459 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4460 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4461 ierr = PetscFree(merge);CHKERRQ(ierr); 4462 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4463 } 4464 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4465 PetscFunctionReturn(0); 4466 } 4467 4468 #include <../src/mat/utils/freespace.h> 4469 #include <petscbt.h> 4470 4471 #undef __FUNCT__ 4472 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4473 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4474 { 4475 PetscErrorCode ierr; 4476 MPI_Comm comm; 4477 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4478 PetscMPIInt size,rank,taga,*len_s; 4479 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4480 PetscInt proc,m; 4481 PetscInt **buf_ri,**buf_rj; 4482 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4483 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4484 MPI_Request *s_waits,*r_waits; 4485 MPI_Status *status; 4486 MatScalar *aa=a->a; 4487 MatScalar **abuf_r,*ba_i; 4488 Mat_Merge_SeqsToMPI *merge; 4489 PetscContainer container; 4490 4491 PetscFunctionBegin; 4492 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4493 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4494 4495 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4496 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4497 4498 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4499 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4500 4501 bi = merge->bi; 4502 bj = merge->bj; 4503 buf_ri = merge->buf_ri; 4504 buf_rj = merge->buf_rj; 4505 4506 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4507 owners = merge->rowmap->range; 4508 len_s = merge->len_s; 4509 4510 /* send and recv matrix values */ 4511 /*-----------------------------*/ 4512 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4513 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4514 4515 ierr = PetscMalloc1((merge->nsend+1),&s_waits);CHKERRQ(ierr); 4516 for (proc=0,k=0; proc<size; proc++) { 4517 if (!len_s[proc]) continue; 4518 i = owners[proc]; 4519 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4520 k++; 4521 } 4522 4523 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4524 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4525 ierr = PetscFree(status);CHKERRQ(ierr); 4526 4527 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4528 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4529 4530 /* insert mat values of mpimat */ 4531 /*----------------------------*/ 4532 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4533 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4534 4535 for (k=0; k<merge->nrecv; k++) { 4536 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4537 nrows = *(buf_ri_k[k]); 4538 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4539 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4540 } 4541 4542 /* set values of ba */ 4543 m = merge->rowmap->n; 4544 for (i=0; i<m; i++) { 4545 arow = owners[rank] + i; 4546 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4547 bnzi = bi[i+1] - bi[i]; 4548 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4549 4550 /* add local non-zero vals of this proc's seqmat into ba */ 4551 anzi = ai[arow+1] - ai[arow]; 4552 aj = a->j + ai[arow]; 4553 aa = a->a + ai[arow]; 4554 nextaj = 0; 4555 for (j=0; nextaj<anzi; j++) { 4556 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4557 ba_i[j] += aa[nextaj++]; 4558 } 4559 } 4560 4561 /* add received vals into ba */ 4562 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4563 /* i-th row */ 4564 if (i == *nextrow[k]) { 4565 anzi = *(nextai[k]+1) - *nextai[k]; 4566 aj = buf_rj[k] + *(nextai[k]); 4567 aa = abuf_r[k] + *(nextai[k]); 4568 nextaj = 0; 4569 for (j=0; nextaj<anzi; j++) { 4570 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4571 ba_i[j] += aa[nextaj++]; 4572 } 4573 } 4574 nextrow[k]++; nextai[k]++; 4575 } 4576 } 4577 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4578 } 4579 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4580 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4581 4582 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4583 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4584 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4585 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4586 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4587 PetscFunctionReturn(0); 4588 } 4589 4590 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4591 4592 #undef __FUNCT__ 4593 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4594 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4595 { 4596 PetscErrorCode ierr; 4597 Mat B_mpi; 4598 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4599 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4600 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4601 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4602 PetscInt len,proc,*dnz,*onz,bs,cbs; 4603 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4604 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4605 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4606 MPI_Status *status; 4607 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4608 PetscBT lnkbt; 4609 Mat_Merge_SeqsToMPI *merge; 4610 PetscContainer container; 4611 4612 PetscFunctionBegin; 4613 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4614 4615 /* make sure it is a PETSc comm */ 4616 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4617 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4618 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4619 4620 ierr = PetscNew(&merge);CHKERRQ(ierr); 4621 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4622 4623 /* determine row ownership */ 4624 /*---------------------------------------------------------*/ 4625 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4626 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4627 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4628 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4629 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4630 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4631 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4632 4633 m = merge->rowmap->n; 4634 owners = merge->rowmap->range; 4635 4636 /* determine the number of messages to send, their lengths */ 4637 /*---------------------------------------------------------*/ 4638 len_s = merge->len_s; 4639 4640 len = 0; /* length of buf_si[] */ 4641 merge->nsend = 0; 4642 for (proc=0; proc<size; proc++) { 4643 len_si[proc] = 0; 4644 if (proc == rank) { 4645 len_s[proc] = 0; 4646 } else { 4647 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4648 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4649 } 4650 if (len_s[proc]) { 4651 merge->nsend++; 4652 nrows = 0; 4653 for (i=owners[proc]; i<owners[proc+1]; i++) { 4654 if (ai[i+1] > ai[i]) nrows++; 4655 } 4656 len_si[proc] = 2*(nrows+1); 4657 len += len_si[proc]; 4658 } 4659 } 4660 4661 /* determine the number and length of messages to receive for ij-structure */ 4662 /*-------------------------------------------------------------------------*/ 4663 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4664 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4665 4666 /* post the Irecv of j-structure */ 4667 /*-------------------------------*/ 4668 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4669 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4670 4671 /* post the Isend of j-structure */ 4672 /*--------------------------------*/ 4673 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4674 4675 for (proc=0, k=0; proc<size; proc++) { 4676 if (!len_s[proc]) continue; 4677 i = owners[proc]; 4678 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4679 k++; 4680 } 4681 4682 /* receives and sends of j-structure are complete */ 4683 /*------------------------------------------------*/ 4684 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4685 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4686 4687 /* send and recv i-structure */ 4688 /*---------------------------*/ 4689 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4690 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4691 4692 ierr = PetscMalloc1((len+1),&buf_s);CHKERRQ(ierr); 4693 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4694 for (proc=0,k=0; proc<size; proc++) { 4695 if (!len_s[proc]) continue; 4696 /* form outgoing message for i-structure: 4697 buf_si[0]: nrows to be sent 4698 [1:nrows]: row index (global) 4699 [nrows+1:2*nrows+1]: i-structure index 4700 */ 4701 /*-------------------------------------------*/ 4702 nrows = len_si[proc]/2 - 1; 4703 buf_si_i = buf_si + nrows+1; 4704 buf_si[0] = nrows; 4705 buf_si_i[0] = 0; 4706 nrows = 0; 4707 for (i=owners[proc]; i<owners[proc+1]; i++) { 4708 anzi = ai[i+1] - ai[i]; 4709 if (anzi) { 4710 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4711 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4712 nrows++; 4713 } 4714 } 4715 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4716 k++; 4717 buf_si += len_si[proc]; 4718 } 4719 4720 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4721 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4722 4723 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4724 for (i=0; i<merge->nrecv; i++) { 4725 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); 4726 } 4727 4728 ierr = PetscFree(len_si);CHKERRQ(ierr); 4729 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4730 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4731 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4732 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4733 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4734 ierr = PetscFree(status);CHKERRQ(ierr); 4735 4736 /* compute a local seq matrix in each processor */ 4737 /*----------------------------------------------*/ 4738 /* allocate bi array and free space for accumulating nonzero column info */ 4739 ierr = PetscMalloc1((m+1),&bi);CHKERRQ(ierr); 4740 bi[0] = 0; 4741 4742 /* create and initialize a linked list */ 4743 nlnk = N+1; 4744 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4745 4746 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4747 len = ai[owners[rank+1]] - ai[owners[rank]]; 4748 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4749 4750 current_space = free_space; 4751 4752 /* determine symbolic info for each local row */ 4753 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4754 4755 for (k=0; k<merge->nrecv; k++) { 4756 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4757 nrows = *buf_ri_k[k]; 4758 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4759 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4760 } 4761 4762 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4763 len = 0; 4764 for (i=0; i<m; i++) { 4765 bnzi = 0; 4766 /* add local non-zero cols of this proc's seqmat into lnk */ 4767 arow = owners[rank] + i; 4768 anzi = ai[arow+1] - ai[arow]; 4769 aj = a->j + ai[arow]; 4770 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4771 bnzi += nlnk; 4772 /* add received col data into lnk */ 4773 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4774 if (i == *nextrow[k]) { /* i-th row */ 4775 anzi = *(nextai[k]+1) - *nextai[k]; 4776 aj = buf_rj[k] + *nextai[k]; 4777 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4778 bnzi += nlnk; 4779 nextrow[k]++; nextai[k]++; 4780 } 4781 } 4782 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4783 4784 /* if free space is not available, make more free space */ 4785 if (current_space->local_remaining<bnzi) { 4786 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4787 nspacedouble++; 4788 } 4789 /* copy data into free space, then initialize lnk */ 4790 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4791 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4792 4793 current_space->array += bnzi; 4794 current_space->local_used += bnzi; 4795 current_space->local_remaining -= bnzi; 4796 4797 bi[i+1] = bi[i] + bnzi; 4798 } 4799 4800 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4801 4802 ierr = PetscMalloc1((bi[m]+1),&bj);CHKERRQ(ierr); 4803 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4804 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4805 4806 /* create symbolic parallel matrix B_mpi */ 4807 /*---------------------------------------*/ 4808 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4809 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4810 if (n==PETSC_DECIDE) { 4811 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4812 } else { 4813 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4814 } 4815 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4816 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4817 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4818 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4819 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4820 4821 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4822 B_mpi->assembled = PETSC_FALSE; 4823 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4824 merge->bi = bi; 4825 merge->bj = bj; 4826 merge->buf_ri = buf_ri; 4827 merge->buf_rj = buf_rj; 4828 merge->coi = NULL; 4829 merge->coj = NULL; 4830 merge->owners_co = NULL; 4831 4832 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4833 4834 /* attach the supporting struct to B_mpi for reuse */ 4835 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4836 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4837 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4838 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4839 *mpimat = B_mpi; 4840 4841 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4842 PetscFunctionReturn(0); 4843 } 4844 4845 #undef __FUNCT__ 4846 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4847 /*@C 4848 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4849 matrices from each processor 4850 4851 Collective on MPI_Comm 4852 4853 Input Parameters: 4854 + comm - the communicators the parallel matrix will live on 4855 . seqmat - the input sequential matrices 4856 . m - number of local rows (or PETSC_DECIDE) 4857 . n - number of local columns (or PETSC_DECIDE) 4858 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4859 4860 Output Parameter: 4861 . mpimat - the parallel matrix generated 4862 4863 Level: advanced 4864 4865 Notes: 4866 The dimensions of the sequential matrix in each processor MUST be the same. 4867 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4868 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4869 @*/ 4870 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4871 { 4872 PetscErrorCode ierr; 4873 PetscMPIInt size; 4874 4875 PetscFunctionBegin; 4876 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4877 if (size == 1) { 4878 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4879 if (scall == MAT_INITIAL_MATRIX) { 4880 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4881 } else { 4882 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4883 } 4884 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4885 PetscFunctionReturn(0); 4886 } 4887 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4888 if (scall == MAT_INITIAL_MATRIX) { 4889 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4890 } 4891 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4892 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4893 PetscFunctionReturn(0); 4894 } 4895 4896 #undef __FUNCT__ 4897 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4898 /*@ 4899 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4900 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4901 with MatGetSize() 4902 4903 Not Collective 4904 4905 Input Parameters: 4906 + A - the matrix 4907 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4908 4909 Output Parameter: 4910 . A_loc - the local sequential matrix generated 4911 4912 Level: developer 4913 4914 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4915 4916 @*/ 4917 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4918 { 4919 PetscErrorCode ierr; 4920 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4921 Mat_SeqAIJ *mat,*a,*b; 4922 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4923 MatScalar *aa,*ba,*cam; 4924 PetscScalar *ca; 4925 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4926 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4927 PetscBool match; 4928 MPI_Comm comm; 4929 PetscMPIInt size; 4930 4931 PetscFunctionBegin; 4932 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4933 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4934 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4935 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4936 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4937 4938 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4939 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4940 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4941 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4942 aa = a->a; ba = b->a; 4943 if (scall == MAT_INITIAL_MATRIX) { 4944 if (size == 1) { 4945 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4946 PetscFunctionReturn(0); 4947 } 4948 4949 ierr = PetscMalloc1((1+am),&ci);CHKERRQ(ierr); 4950 ci[0] = 0; 4951 for (i=0; i<am; i++) { 4952 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4953 } 4954 ierr = PetscMalloc1((1+ci[am]),&cj);CHKERRQ(ierr); 4955 ierr = PetscMalloc1((1+ci[am]),&ca);CHKERRQ(ierr); 4956 k = 0; 4957 for (i=0; i<am; i++) { 4958 ncols_o = bi[i+1] - bi[i]; 4959 ncols_d = ai[i+1] - ai[i]; 4960 /* off-diagonal portion of A */ 4961 for (jo=0; jo<ncols_o; jo++) { 4962 col = cmap[*bj]; 4963 if (col >= cstart) break; 4964 cj[k] = col; bj++; 4965 ca[k++] = *ba++; 4966 } 4967 /* diagonal portion of A */ 4968 for (j=0; j<ncols_d; j++) { 4969 cj[k] = cstart + *aj++; 4970 ca[k++] = *aa++; 4971 } 4972 /* off-diagonal portion of A */ 4973 for (j=jo; j<ncols_o; j++) { 4974 cj[k] = cmap[*bj++]; 4975 ca[k++] = *ba++; 4976 } 4977 } 4978 /* put together the new matrix */ 4979 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4980 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4981 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4982 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4983 mat->free_a = PETSC_TRUE; 4984 mat->free_ij = PETSC_TRUE; 4985 mat->nonew = 0; 4986 } else if (scall == MAT_REUSE_MATRIX) { 4987 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4988 ci = mat->i; cj = mat->j; cam = mat->a; 4989 for (i=0; i<am; i++) { 4990 /* off-diagonal portion of A */ 4991 ncols_o = bi[i+1] - bi[i]; 4992 for (jo=0; jo<ncols_o; jo++) { 4993 col = cmap[*bj]; 4994 if (col >= cstart) break; 4995 *cam++ = *ba++; bj++; 4996 } 4997 /* diagonal portion of A */ 4998 ncols_d = ai[i+1] - ai[i]; 4999 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5000 /* off-diagonal portion of A */ 5001 for (j=jo; j<ncols_o; j++) { 5002 *cam++ = *ba++; bj++; 5003 } 5004 } 5005 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5006 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5007 PetscFunctionReturn(0); 5008 } 5009 5010 #undef __FUNCT__ 5011 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5012 /*@C 5013 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5014 5015 Not Collective 5016 5017 Input Parameters: 5018 + A - the matrix 5019 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5020 - row, col - index sets of rows and columns to extract (or NULL) 5021 5022 Output Parameter: 5023 . A_loc - the local sequential matrix generated 5024 5025 Level: developer 5026 5027 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5028 5029 @*/ 5030 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5031 { 5032 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5033 PetscErrorCode ierr; 5034 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5035 IS isrowa,iscola; 5036 Mat *aloc; 5037 PetscBool match; 5038 5039 PetscFunctionBegin; 5040 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5041 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5042 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5043 if (!row) { 5044 start = A->rmap->rstart; end = A->rmap->rend; 5045 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5046 } else { 5047 isrowa = *row; 5048 } 5049 if (!col) { 5050 start = A->cmap->rstart; 5051 cmap = a->garray; 5052 nzA = a->A->cmap->n; 5053 nzB = a->B->cmap->n; 5054 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 5055 ncols = 0; 5056 for (i=0; i<nzB; i++) { 5057 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5058 else break; 5059 } 5060 imark = i; 5061 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5062 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5063 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5064 } else { 5065 iscola = *col; 5066 } 5067 if (scall != MAT_INITIAL_MATRIX) { 5068 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5069 aloc[0] = *A_loc; 5070 } 5071 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5072 *A_loc = aloc[0]; 5073 ierr = PetscFree(aloc);CHKERRQ(ierr); 5074 if (!row) { 5075 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5076 } 5077 if (!col) { 5078 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5079 } 5080 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5081 PetscFunctionReturn(0); 5082 } 5083 5084 #undef __FUNCT__ 5085 #define __FUNCT__ "MatGetBrowsOfAcols" 5086 /*@C 5087 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5088 5089 Collective on Mat 5090 5091 Input Parameters: 5092 + A,B - the matrices in mpiaij format 5093 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5094 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5095 5096 Output Parameter: 5097 + rowb, colb - index sets of rows and columns of B to extract 5098 - B_seq - the sequential matrix generated 5099 5100 Level: developer 5101 5102 @*/ 5103 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5104 { 5105 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5106 PetscErrorCode ierr; 5107 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5108 IS isrowb,iscolb; 5109 Mat *bseq=NULL; 5110 5111 PetscFunctionBegin; 5112 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5113 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); 5114 } 5115 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5116 5117 if (scall == MAT_INITIAL_MATRIX) { 5118 start = A->cmap->rstart; 5119 cmap = a->garray; 5120 nzA = a->A->cmap->n; 5121 nzB = a->B->cmap->n; 5122 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 5123 ncols = 0; 5124 for (i=0; i<nzB; i++) { /* row < local row index */ 5125 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5126 else break; 5127 } 5128 imark = i; 5129 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5130 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5131 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5132 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5133 } else { 5134 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5135 isrowb = *rowb; iscolb = *colb; 5136 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5137 bseq[0] = *B_seq; 5138 } 5139 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5140 *B_seq = bseq[0]; 5141 ierr = PetscFree(bseq);CHKERRQ(ierr); 5142 if (!rowb) { 5143 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5144 } else { 5145 *rowb = isrowb; 5146 } 5147 if (!colb) { 5148 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5149 } else { 5150 *colb = iscolb; 5151 } 5152 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5153 PetscFunctionReturn(0); 5154 } 5155 5156 #undef __FUNCT__ 5157 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5158 /* 5159 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5160 of the OFF-DIAGONAL portion of local A 5161 5162 Collective on Mat 5163 5164 Input Parameters: 5165 + A,B - the matrices in mpiaij format 5166 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5167 5168 Output Parameter: 5169 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5170 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5171 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5172 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5173 5174 Level: developer 5175 5176 */ 5177 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5178 { 5179 VecScatter_MPI_General *gen_to,*gen_from; 5180 PetscErrorCode ierr; 5181 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5182 Mat_SeqAIJ *b_oth; 5183 VecScatter ctx =a->Mvctx; 5184 MPI_Comm comm; 5185 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5186 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5187 PetscScalar *rvalues,*svalues; 5188 MatScalar *b_otha,*bufa,*bufA; 5189 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5190 MPI_Request *rwaits = NULL,*swaits = NULL; 5191 MPI_Status *sstatus,rstatus; 5192 PetscMPIInt jj,size; 5193 PetscInt *cols,sbs,rbs; 5194 PetscScalar *vals; 5195 5196 PetscFunctionBegin; 5197 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5199 if (size == 1) PetscFunctionReturn(0); 5200 5201 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5202 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); 5203 } 5204 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5205 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5206 5207 gen_to = (VecScatter_MPI_General*)ctx->todata; 5208 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5209 rvalues = gen_from->values; /* holds the length of receiving row */ 5210 svalues = gen_to->values; /* holds the length of sending row */ 5211 nrecvs = gen_from->n; 5212 nsends = gen_to->n; 5213 5214 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 5215 srow = gen_to->indices; /* local row index to be sent */ 5216 sstarts = gen_to->starts; 5217 sprocs = gen_to->procs; 5218 sstatus = gen_to->sstatus; 5219 sbs = gen_to->bs; 5220 rstarts = gen_from->starts; 5221 rprocs = gen_from->procs; 5222 rbs = gen_from->bs; 5223 5224 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5225 if (scall == MAT_INITIAL_MATRIX) { 5226 /* i-array */ 5227 /*---------*/ 5228 /* post receives */ 5229 for (i=0; i<nrecvs; i++) { 5230 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5231 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5232 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5233 } 5234 5235 /* pack the outgoing message */ 5236 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 5237 5238 sstartsj[0] = 0; 5239 rstartsj[0] = 0; 5240 len = 0; /* total length of j or a array to be sent */ 5241 k = 0; 5242 for (i=0; i<nsends; i++) { 5243 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5244 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5245 for (j=0; j<nrows; j++) { 5246 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5247 for (l=0; l<sbs; l++) { 5248 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5249 5250 rowlen[j*sbs+l] = ncols; 5251 5252 len += ncols; 5253 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5254 } 5255 k++; 5256 } 5257 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5258 5259 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5260 } 5261 /* recvs and sends of i-array are completed */ 5262 i = nrecvs; 5263 while (i--) { 5264 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5265 } 5266 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5267 5268 /* allocate buffers for sending j and a arrays */ 5269 ierr = PetscMalloc1((len+1),&bufj);CHKERRQ(ierr); 5270 ierr = PetscMalloc1((len+1),&bufa);CHKERRQ(ierr); 5271 5272 /* create i-array of B_oth */ 5273 ierr = PetscMalloc1((aBn+2),&b_othi);CHKERRQ(ierr); 5274 5275 b_othi[0] = 0; 5276 len = 0; /* total length of j or a array to be received */ 5277 k = 0; 5278 for (i=0; i<nrecvs; i++) { 5279 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5280 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5281 for (j=0; j<nrows; j++) { 5282 b_othi[k+1] = b_othi[k] + rowlen[j]; 5283 len += rowlen[j]; k++; 5284 } 5285 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5286 } 5287 5288 /* allocate space for j and a arrrays of B_oth */ 5289 ierr = PetscMalloc1((b_othi[aBn]+1),&b_othj);CHKERRQ(ierr); 5290 ierr = PetscMalloc1((b_othi[aBn]+1),&b_otha);CHKERRQ(ierr); 5291 5292 /* j-array */ 5293 /*---------*/ 5294 /* post receives of j-array */ 5295 for (i=0; i<nrecvs; i++) { 5296 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5297 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5298 } 5299 5300 /* pack the outgoing message j-array */ 5301 k = 0; 5302 for (i=0; i<nsends; i++) { 5303 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5304 bufJ = bufj+sstartsj[i]; 5305 for (j=0; j<nrows; j++) { 5306 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5307 for (ll=0; ll<sbs; ll++) { 5308 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5309 for (l=0; l<ncols; l++) { 5310 *bufJ++ = cols[l]; 5311 } 5312 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5313 } 5314 } 5315 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5316 } 5317 5318 /* recvs and sends of j-array are completed */ 5319 i = nrecvs; 5320 while (i--) { 5321 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5322 } 5323 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5324 } else if (scall == MAT_REUSE_MATRIX) { 5325 sstartsj = *startsj_s; 5326 rstartsj = *startsj_r; 5327 bufa = *bufa_ptr; 5328 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5329 b_otha = b_oth->a; 5330 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5331 5332 /* a-array */ 5333 /*---------*/ 5334 /* post receives of a-array */ 5335 for (i=0; i<nrecvs; i++) { 5336 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5337 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5338 } 5339 5340 /* pack the outgoing message a-array */ 5341 k = 0; 5342 for (i=0; i<nsends; i++) { 5343 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5344 bufA = bufa+sstartsj[i]; 5345 for (j=0; j<nrows; j++) { 5346 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5347 for (ll=0; ll<sbs; ll++) { 5348 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5349 for (l=0; l<ncols; l++) { 5350 *bufA++ = vals[l]; 5351 } 5352 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5353 } 5354 } 5355 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5356 } 5357 /* recvs and sends of a-array are completed */ 5358 i = nrecvs; 5359 while (i--) { 5360 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5361 } 5362 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5363 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5364 5365 if (scall == MAT_INITIAL_MATRIX) { 5366 /* put together the new matrix */ 5367 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5368 5369 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5370 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5371 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5372 b_oth->free_a = PETSC_TRUE; 5373 b_oth->free_ij = PETSC_TRUE; 5374 b_oth->nonew = 0; 5375 5376 ierr = PetscFree(bufj);CHKERRQ(ierr); 5377 if (!startsj_s || !bufa_ptr) { 5378 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5379 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5380 } else { 5381 *startsj_s = sstartsj; 5382 *startsj_r = rstartsj; 5383 *bufa_ptr = bufa; 5384 } 5385 } 5386 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5387 PetscFunctionReturn(0); 5388 } 5389 5390 #undef __FUNCT__ 5391 #define __FUNCT__ "MatGetCommunicationStructs" 5392 /*@C 5393 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5394 5395 Not Collective 5396 5397 Input Parameters: 5398 . A - The matrix in mpiaij format 5399 5400 Output Parameter: 5401 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5402 . colmap - A map from global column index to local index into lvec 5403 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5404 5405 Level: developer 5406 5407 @*/ 5408 #if defined(PETSC_USE_CTABLE) 5409 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5410 #else 5411 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5412 #endif 5413 { 5414 Mat_MPIAIJ *a; 5415 5416 PetscFunctionBegin; 5417 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5418 PetscValidPointer(lvec, 2); 5419 PetscValidPointer(colmap, 3); 5420 PetscValidPointer(multScatter, 4); 5421 a = (Mat_MPIAIJ*) A->data; 5422 if (lvec) *lvec = a->lvec; 5423 if (colmap) *colmap = a->colmap; 5424 if (multScatter) *multScatter = a->Mvctx; 5425 PetscFunctionReturn(0); 5426 } 5427 5428 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5429 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5430 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5431 #if defined(PETSC_HAVE_ELEMENTAL) 5432 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5433 #endif 5434 5435 #undef __FUNCT__ 5436 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5437 /* 5438 Computes (B'*A')' since computing B*A directly is untenable 5439 5440 n p p 5441 ( ) ( ) ( ) 5442 m ( A ) * n ( B ) = m ( C ) 5443 ( ) ( ) ( ) 5444 5445 */ 5446 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5447 { 5448 PetscErrorCode ierr; 5449 Mat At,Bt,Ct; 5450 5451 PetscFunctionBegin; 5452 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5453 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5454 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5455 ierr = MatDestroy(&At);CHKERRQ(ierr); 5456 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5457 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5458 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5459 PetscFunctionReturn(0); 5460 } 5461 5462 #undef __FUNCT__ 5463 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5464 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5465 { 5466 PetscErrorCode ierr; 5467 PetscInt m=A->rmap->n,n=B->cmap->n; 5468 Mat Cmat; 5469 5470 PetscFunctionBegin; 5471 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); 5472 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5473 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5474 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5475 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5476 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5477 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5478 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5479 5480 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5481 5482 *C = Cmat; 5483 PetscFunctionReturn(0); 5484 } 5485 5486 /* ----------------------------------------------------------------*/ 5487 #undef __FUNCT__ 5488 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5489 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5490 { 5491 PetscErrorCode ierr; 5492 5493 PetscFunctionBegin; 5494 if (scall == MAT_INITIAL_MATRIX) { 5495 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5496 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5497 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5498 } 5499 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5500 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5501 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5502 PetscFunctionReturn(0); 5503 } 5504 5505 #if defined(PETSC_HAVE_MUMPS) 5506 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5507 #endif 5508 #if defined(PETSC_HAVE_PASTIX) 5509 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5510 #endif 5511 #if defined(PETSC_HAVE_SUPERLU_DIST) 5512 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5513 #endif 5514 #if defined(PETSC_HAVE_CLIQUE) 5515 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5516 #endif 5517 5518 /*MC 5519 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5520 5521 Options Database Keys: 5522 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5523 5524 Level: beginner 5525 5526 .seealso: MatCreateAIJ() 5527 M*/ 5528 5529 #undef __FUNCT__ 5530 #define __FUNCT__ "MatCreate_MPIAIJ" 5531 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5532 { 5533 Mat_MPIAIJ *b; 5534 PetscErrorCode ierr; 5535 PetscMPIInt size; 5536 5537 PetscFunctionBegin; 5538 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5539 5540 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5541 B->data = (void*)b; 5542 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5543 B->assembled = PETSC_FALSE; 5544 B->insertmode = NOT_SET_VALUES; 5545 b->size = size; 5546 5547 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5548 5549 /* build cache for off array entries formed */ 5550 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5551 5552 b->donotstash = PETSC_FALSE; 5553 b->colmap = 0; 5554 b->garray = 0; 5555 b->roworiented = PETSC_TRUE; 5556 5557 /* stuff used for matrix vector multiply */ 5558 b->lvec = NULL; 5559 b->Mvctx = NULL; 5560 5561 /* stuff for MatGetRow() */ 5562 b->rowindices = 0; 5563 b->rowvalues = 0; 5564 b->getrowactive = PETSC_FALSE; 5565 5566 /* flexible pointer used in CUSP/CUSPARSE classes */ 5567 b->spptr = NULL; 5568 5569 #if defined(PETSC_HAVE_MUMPS) 5570 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5571 #endif 5572 #if defined(PETSC_HAVE_PASTIX) 5573 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5574 #endif 5575 #if defined(PETSC_HAVE_SUPERLU_DIST) 5576 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5577 #endif 5578 #if defined(PETSC_HAVE_CLIQUE) 5579 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5580 #endif 5581 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5582 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5583 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5584 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5585 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5586 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5587 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5588 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5589 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5590 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5591 #if defined(PETSC_HAVE_ELEMENTAL) 5592 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5593 #endif 5594 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5595 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5596 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5597 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5598 PetscFunctionReturn(0); 5599 } 5600 5601 #undef __FUNCT__ 5602 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5603 /*@ 5604 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5605 and "off-diagonal" part of the matrix in CSR format. 5606 5607 Collective on MPI_Comm 5608 5609 Input Parameters: 5610 + comm - MPI communicator 5611 . m - number of local rows (Cannot be PETSC_DECIDE) 5612 . n - This value should be the same as the local size used in creating the 5613 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5614 calculated if N is given) For square matrices n is almost always m. 5615 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5616 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5617 . i - row indices for "diagonal" portion of matrix 5618 . j - column indices 5619 . a - matrix values 5620 . oi - row indices for "off-diagonal" portion of matrix 5621 . oj - column indices 5622 - oa - matrix values 5623 5624 Output Parameter: 5625 . mat - the matrix 5626 5627 Level: advanced 5628 5629 Notes: 5630 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5631 must free the arrays once the matrix has been destroyed and not before. 5632 5633 The i and j indices are 0 based 5634 5635 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5636 5637 This sets local rows and cannot be used to set off-processor values. 5638 5639 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5640 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5641 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5642 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5643 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5644 communication if it is known that only local entries will be set. 5645 5646 .keywords: matrix, aij, compressed row, sparse, parallel 5647 5648 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5649 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5650 @*/ 5651 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) 5652 { 5653 PetscErrorCode ierr; 5654 Mat_MPIAIJ *maij; 5655 5656 PetscFunctionBegin; 5657 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5658 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5659 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5660 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5661 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5662 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5663 maij = (Mat_MPIAIJ*) (*mat)->data; 5664 5665 (*mat)->preallocated = PETSC_TRUE; 5666 5667 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5668 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5669 5670 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5671 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5672 5673 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5674 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5675 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5676 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5677 5678 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5679 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5680 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5681 PetscFunctionReturn(0); 5682 } 5683 5684 /* 5685 Special version for direct calls from Fortran 5686 */ 5687 #include <petsc-private/fortranimpl.h> 5688 5689 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5690 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5691 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5692 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5693 #endif 5694 5695 /* Change these macros so can be used in void function */ 5696 #undef CHKERRQ 5697 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5698 #undef SETERRQ2 5699 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5700 #undef SETERRQ3 5701 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5702 #undef SETERRQ 5703 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5704 5705 #undef __FUNCT__ 5706 #define __FUNCT__ "matsetvaluesmpiaij_" 5707 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) 5708 { 5709 Mat mat = *mmat; 5710 PetscInt m = *mm, n = *mn; 5711 InsertMode addv = *maddv; 5712 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5713 PetscScalar value; 5714 PetscErrorCode ierr; 5715 5716 MatCheckPreallocated(mat,1); 5717 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5718 5719 #if defined(PETSC_USE_DEBUG) 5720 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5721 #endif 5722 { 5723 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5724 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5725 PetscBool roworiented = aij->roworiented; 5726 5727 /* Some Variables required in the macro */ 5728 Mat A = aij->A; 5729 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5730 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5731 MatScalar *aa = a->a; 5732 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5733 Mat B = aij->B; 5734 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5735 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5736 MatScalar *ba = b->a; 5737 5738 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5739 PetscInt nonew = a->nonew; 5740 MatScalar *ap1,*ap2; 5741 5742 PetscFunctionBegin; 5743 for (i=0; i<m; i++) { 5744 if (im[i] < 0) continue; 5745 #if defined(PETSC_USE_DEBUG) 5746 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); 5747 #endif 5748 if (im[i] >= rstart && im[i] < rend) { 5749 row = im[i] - rstart; 5750 lastcol1 = -1; 5751 rp1 = aj + ai[row]; 5752 ap1 = aa + ai[row]; 5753 rmax1 = aimax[row]; 5754 nrow1 = ailen[row]; 5755 low1 = 0; 5756 high1 = nrow1; 5757 lastcol2 = -1; 5758 rp2 = bj + bi[row]; 5759 ap2 = ba + bi[row]; 5760 rmax2 = bimax[row]; 5761 nrow2 = bilen[row]; 5762 low2 = 0; 5763 high2 = nrow2; 5764 5765 for (j=0; j<n; j++) { 5766 if (roworiented) value = v[i*n+j]; 5767 else value = v[i+j*m]; 5768 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5769 if (in[j] >= cstart && in[j] < cend) { 5770 col = in[j] - cstart; 5771 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5772 } else if (in[j] < 0) continue; 5773 #if defined(PETSC_USE_DEBUG) 5774 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); 5775 #endif 5776 else { 5777 if (mat->was_assembled) { 5778 if (!aij->colmap) { 5779 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5780 } 5781 #if defined(PETSC_USE_CTABLE) 5782 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5783 col--; 5784 #else 5785 col = aij->colmap[in[j]] - 1; 5786 #endif 5787 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5788 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5789 col = in[j]; 5790 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5791 B = aij->B; 5792 b = (Mat_SeqAIJ*)B->data; 5793 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5794 rp2 = bj + bi[row]; 5795 ap2 = ba + bi[row]; 5796 rmax2 = bimax[row]; 5797 nrow2 = bilen[row]; 5798 low2 = 0; 5799 high2 = nrow2; 5800 bm = aij->B->rmap->n; 5801 ba = b->a; 5802 } 5803 } else col = in[j]; 5804 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5805 } 5806 } 5807 } else if (!aij->donotstash) { 5808 if (roworiented) { 5809 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5810 } else { 5811 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5812 } 5813 } 5814 } 5815 } 5816 PetscFunctionReturnVoid(); 5817 } 5818 5819