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->psubcomm) { 1147 ierr = PetscSubcommDestroy(&redund->psubcomm);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,subsize; 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 2764 PetscFunctionBegin; 2765 if (subcomm_in == MPI_COMM_NULL) { /* user does not provide subcomm */ 2766 if (reuse == MAT_INITIAL_MATRIX) { 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 subcomm = psubcomm->comm; 2777 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2778 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2779 (*matredundant)->redundant->psubcomm = psubcomm; 2780 PetscFunctionReturn(0); 2781 } 2782 } else { /* retrieve psubcomm and subcomm */ 2783 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2784 redund = (*matredundant)->redundant; 2785 if (redund->type == PETSC_SUBCOMM_INTERLACED) { 2786 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2787 PetscFunctionReturn(0); 2788 } 2789 } 2790 } 2791 2792 /* use MPI subcomm via MatGetSubMatrices(); use subcomm_in or psubcomm->comm (psubcomm->type != INTERLACED) */ 2793 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2794 if (reuse == MAT_INITIAL_MATRIX) { 2795 /* create a local sequential matrix matseq[0] */ 2796 mloc_sub = PETSC_DECIDE; 2797 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2798 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2799 rstart = rend - mloc_sub; 2800 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2801 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2802 } else { /* reuse == MAT_REUSE_MATRIX */ 2803 redund = (*matredundant)->redundant; 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 redund->subcomm = subcomm; 2819 redund->type = PETSC_SUBCOMM_CONTIGUOUS; 2820 redund->psubcomm = psubcomm; 2821 } 2822 PetscFunctionReturn(0); 2823 } 2824 2825 #undef __FUNCT__ 2826 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2827 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2828 { 2829 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2830 PetscErrorCode ierr; 2831 PetscInt i,*idxb = 0; 2832 PetscScalar *va,*vb; 2833 Vec vtmp; 2834 2835 PetscFunctionBegin; 2836 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2837 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2838 if (idx) { 2839 for (i=0; i<A->rmap->n; i++) { 2840 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2841 } 2842 } 2843 2844 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2845 if (idx) { 2846 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2847 } 2848 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2849 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2850 2851 for (i=0; i<A->rmap->n; i++) { 2852 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2853 va[i] = vb[i]; 2854 if (idx) idx[i] = a->garray[idxb[i]]; 2855 } 2856 } 2857 2858 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2859 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2860 ierr = PetscFree(idxb);CHKERRQ(ierr); 2861 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2862 PetscFunctionReturn(0); 2863 } 2864 2865 #undef __FUNCT__ 2866 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2867 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2868 { 2869 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2870 PetscErrorCode ierr; 2871 PetscInt i,*idxb = 0; 2872 PetscScalar *va,*vb; 2873 Vec vtmp; 2874 2875 PetscFunctionBegin; 2876 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2877 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2878 if (idx) { 2879 for (i=0; i<A->cmap->n; i++) { 2880 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2881 } 2882 } 2883 2884 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2885 if (idx) { 2886 ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr); 2887 } 2888 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2889 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2890 2891 for (i=0; i<A->rmap->n; i++) { 2892 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2893 va[i] = vb[i]; 2894 if (idx) idx[i] = a->garray[idxb[i]]; 2895 } 2896 } 2897 2898 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2899 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2900 ierr = PetscFree(idxb);CHKERRQ(ierr); 2901 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2902 PetscFunctionReturn(0); 2903 } 2904 2905 #undef __FUNCT__ 2906 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2907 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2908 { 2909 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2910 PetscInt n = A->rmap->n; 2911 PetscInt cstart = A->cmap->rstart; 2912 PetscInt *cmap = mat->garray; 2913 PetscInt *diagIdx, *offdiagIdx; 2914 Vec diagV, offdiagV; 2915 PetscScalar *a, *diagA, *offdiagA; 2916 PetscInt r; 2917 PetscErrorCode ierr; 2918 2919 PetscFunctionBegin; 2920 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2921 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 2922 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 2923 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2924 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2925 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2926 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2927 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2928 for (r = 0; r < n; ++r) { 2929 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2930 a[r] = diagA[r]; 2931 idx[r] = cstart + diagIdx[r]; 2932 } else { 2933 a[r] = offdiagA[r]; 2934 idx[r] = cmap[offdiagIdx[r]]; 2935 } 2936 } 2937 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2938 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2939 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2940 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2941 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2942 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2943 PetscFunctionReturn(0); 2944 } 2945 2946 #undef __FUNCT__ 2947 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2948 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2949 { 2950 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 2951 PetscInt n = A->rmap->n; 2952 PetscInt cstart = A->cmap->rstart; 2953 PetscInt *cmap = mat->garray; 2954 PetscInt *diagIdx, *offdiagIdx; 2955 Vec diagV, offdiagV; 2956 PetscScalar *a, *diagA, *offdiagA; 2957 PetscInt r; 2958 PetscErrorCode ierr; 2959 2960 PetscFunctionBegin; 2961 ierr = PetscMalloc2(n,&diagIdx,n,&offdiagIdx);CHKERRQ(ierr); 2962 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 2963 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 2964 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2965 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2966 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2967 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2968 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2969 for (r = 0; r < n; ++r) { 2970 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2971 a[r] = diagA[r]; 2972 idx[r] = cstart + diagIdx[r]; 2973 } else { 2974 a[r] = offdiagA[r]; 2975 idx[r] = cmap[offdiagIdx[r]]; 2976 } 2977 } 2978 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2979 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2980 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2981 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2982 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2983 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2984 PetscFunctionReturn(0); 2985 } 2986 2987 #undef __FUNCT__ 2988 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 2989 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 2990 { 2991 PetscErrorCode ierr; 2992 Mat *dummy; 2993 2994 PetscFunctionBegin; 2995 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 2996 *newmat = *dummy; 2997 ierr = PetscFree(dummy);CHKERRQ(ierr); 2998 PetscFunctionReturn(0); 2999 } 3000 3001 #undef __FUNCT__ 3002 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3003 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3004 { 3005 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3006 PetscErrorCode ierr; 3007 3008 PetscFunctionBegin; 3009 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3010 PetscFunctionReturn(0); 3011 } 3012 3013 #undef __FUNCT__ 3014 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3015 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3016 { 3017 PetscErrorCode ierr; 3018 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3019 3020 PetscFunctionBegin; 3021 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3022 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3023 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3024 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3025 PetscFunctionReturn(0); 3026 } 3027 3028 /* -------------------------------------------------------------------*/ 3029 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3030 MatGetRow_MPIAIJ, 3031 MatRestoreRow_MPIAIJ, 3032 MatMult_MPIAIJ, 3033 /* 4*/ MatMultAdd_MPIAIJ, 3034 MatMultTranspose_MPIAIJ, 3035 MatMultTransposeAdd_MPIAIJ, 3036 #if defined(PETSC_HAVE_PBGL) 3037 MatSolve_MPIAIJ, 3038 #else 3039 0, 3040 #endif 3041 0, 3042 0, 3043 /*10*/ 0, 3044 0, 3045 0, 3046 MatSOR_MPIAIJ, 3047 MatTranspose_MPIAIJ, 3048 /*15*/ MatGetInfo_MPIAIJ, 3049 MatEqual_MPIAIJ, 3050 MatGetDiagonal_MPIAIJ, 3051 MatDiagonalScale_MPIAIJ, 3052 MatNorm_MPIAIJ, 3053 /*20*/ MatAssemblyBegin_MPIAIJ, 3054 MatAssemblyEnd_MPIAIJ, 3055 MatSetOption_MPIAIJ, 3056 MatZeroEntries_MPIAIJ, 3057 /*24*/ MatZeroRows_MPIAIJ, 3058 0, 3059 #if defined(PETSC_HAVE_PBGL) 3060 0, 3061 #else 3062 0, 3063 #endif 3064 0, 3065 0, 3066 /*29*/ MatSetUp_MPIAIJ, 3067 #if defined(PETSC_HAVE_PBGL) 3068 0, 3069 #else 3070 0, 3071 #endif 3072 0, 3073 0, 3074 0, 3075 /*34*/ MatDuplicate_MPIAIJ, 3076 0, 3077 0, 3078 0, 3079 0, 3080 /*39*/ MatAXPY_MPIAIJ, 3081 MatGetSubMatrices_MPIAIJ, 3082 MatIncreaseOverlap_MPIAIJ, 3083 MatGetValues_MPIAIJ, 3084 MatCopy_MPIAIJ, 3085 /*44*/ MatGetRowMax_MPIAIJ, 3086 MatScale_MPIAIJ, 3087 0, 3088 MatDiagonalSet_MPIAIJ, 3089 MatZeroRowsColumns_MPIAIJ, 3090 /*49*/ MatSetRandom_MPIAIJ, 3091 0, 3092 0, 3093 0, 3094 0, 3095 /*54*/ MatFDColoringCreate_MPIXAIJ, 3096 0, 3097 MatSetUnfactored_MPIAIJ, 3098 MatPermute_MPIAIJ, 3099 0, 3100 /*59*/ MatGetSubMatrix_MPIAIJ, 3101 MatDestroy_MPIAIJ, 3102 MatView_MPIAIJ, 3103 0, 3104 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3105 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3106 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3107 0, 3108 0, 3109 0, 3110 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3111 MatGetRowMinAbs_MPIAIJ, 3112 0, 3113 MatSetColoring_MPIAIJ, 3114 0, 3115 MatSetValuesAdifor_MPIAIJ, 3116 /*75*/ MatFDColoringApply_AIJ, 3117 0, 3118 0, 3119 0, 3120 MatFindZeroDiagonals_MPIAIJ, 3121 /*80*/ 0, 3122 0, 3123 0, 3124 /*83*/ MatLoad_MPIAIJ, 3125 0, 3126 0, 3127 0, 3128 0, 3129 0, 3130 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3131 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3132 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3133 MatPtAP_MPIAIJ_MPIAIJ, 3134 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3135 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3136 0, 3137 0, 3138 0, 3139 0, 3140 /*99*/ 0, 3141 0, 3142 0, 3143 MatConjugate_MPIAIJ, 3144 0, 3145 /*104*/MatSetValuesRow_MPIAIJ, 3146 MatRealPart_MPIAIJ, 3147 MatImaginaryPart_MPIAIJ, 3148 0, 3149 0, 3150 /*109*/0, 3151 MatGetRedundantMatrix_MPIAIJ, 3152 MatGetRowMin_MPIAIJ, 3153 0, 3154 0, 3155 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3156 0, 3157 0, 3158 0, 3159 0, 3160 /*119*/0, 3161 0, 3162 0, 3163 0, 3164 MatGetMultiProcBlock_MPIAIJ, 3165 /*124*/MatFindNonzeroRows_MPIAIJ, 3166 MatGetColumnNorms_MPIAIJ, 3167 MatInvertBlockDiagonal_MPIAIJ, 3168 0, 3169 MatGetSubMatricesParallel_MPIAIJ, 3170 /*129*/0, 3171 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3172 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3173 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3174 0, 3175 /*134*/0, 3176 0, 3177 0, 3178 0, 3179 0, 3180 /*139*/0, 3181 0, 3182 0, 3183 MatFDColoringSetUp_MPIXAIJ, 3184 0, 3185 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ 3186 }; 3187 3188 /* ----------------------------------------------------------------------------------------*/ 3189 3190 #undef __FUNCT__ 3191 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3192 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3193 { 3194 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3195 PetscErrorCode ierr; 3196 3197 PetscFunctionBegin; 3198 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3199 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3200 PetscFunctionReturn(0); 3201 } 3202 3203 #undef __FUNCT__ 3204 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3205 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3206 { 3207 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3208 PetscErrorCode ierr; 3209 3210 PetscFunctionBegin; 3211 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3212 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3213 PetscFunctionReturn(0); 3214 } 3215 3216 #undef __FUNCT__ 3217 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3218 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3219 { 3220 Mat_MPIAIJ *b; 3221 PetscErrorCode ierr; 3222 3223 PetscFunctionBegin; 3224 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3225 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3226 b = (Mat_MPIAIJ*)B->data; 3227 3228 if (!B->preallocated) { 3229 /* Explicitly create 2 MATSEQAIJ matrices. */ 3230 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3231 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3232 ierr = MatSetBlockSizesFromMats(b->A,B,B);CHKERRQ(ierr); 3233 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3234 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3235 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3236 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3237 ierr = MatSetBlockSizesFromMats(b->B,B,B);CHKERRQ(ierr); 3238 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3239 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3240 } 3241 3242 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3243 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3244 B->preallocated = PETSC_TRUE; 3245 PetscFunctionReturn(0); 3246 } 3247 3248 #undef __FUNCT__ 3249 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3250 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3251 { 3252 Mat mat; 3253 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3254 PetscErrorCode ierr; 3255 3256 PetscFunctionBegin; 3257 *newmat = 0; 3258 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3259 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3260 ierr = MatSetBlockSizesFromMats(mat,matin,matin);CHKERRQ(ierr); 3261 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3262 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3263 a = (Mat_MPIAIJ*)mat->data; 3264 3265 mat->factortype = matin->factortype; 3266 mat->assembled = PETSC_TRUE; 3267 mat->insertmode = NOT_SET_VALUES; 3268 mat->preallocated = PETSC_TRUE; 3269 3270 a->size = oldmat->size; 3271 a->rank = oldmat->rank; 3272 a->donotstash = oldmat->donotstash; 3273 a->roworiented = oldmat->roworiented; 3274 a->rowindices = 0; 3275 a->rowvalues = 0; 3276 a->getrowactive = PETSC_FALSE; 3277 3278 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3279 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3280 3281 if (oldmat->colmap) { 3282 #if defined(PETSC_USE_CTABLE) 3283 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3284 #else 3285 ierr = PetscMalloc1((mat->cmap->N),&a->colmap);CHKERRQ(ierr); 3286 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3287 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3288 #endif 3289 } else a->colmap = 0; 3290 if (oldmat->garray) { 3291 PetscInt len; 3292 len = oldmat->B->cmap->n; 3293 ierr = PetscMalloc1((len+1),&a->garray);CHKERRQ(ierr); 3294 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3295 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3296 } else a->garray = 0; 3297 3298 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3299 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3300 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3301 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3302 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3303 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3304 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3305 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3306 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3307 *newmat = mat; 3308 PetscFunctionReturn(0); 3309 } 3310 3311 3312 3313 #undef __FUNCT__ 3314 #define __FUNCT__ "MatLoad_MPIAIJ" 3315 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3316 { 3317 PetscScalar *vals,*svals; 3318 MPI_Comm comm; 3319 PetscErrorCode ierr; 3320 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3321 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3322 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3323 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3324 PetscInt cend,cstart,n,*rowners,sizesset=1; 3325 int fd; 3326 PetscInt bs = 1; 3327 3328 PetscFunctionBegin; 3329 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3330 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3331 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3332 if (!rank) { 3333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3334 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3335 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3336 } 3337 3338 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3339 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3340 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3341 3342 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3343 3344 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3345 M = header[1]; N = header[2]; 3346 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3347 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3348 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3349 3350 /* If global sizes are set, check if they are consistent with that given in the file */ 3351 if (sizesset) { 3352 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3353 } 3354 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); 3355 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); 3356 3357 /* determine ownership of all (block) rows */ 3358 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3359 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3360 else m = newMat->rmap->n; /* Set by user */ 3361 3362 ierr = PetscMalloc1((size+1),&rowners);CHKERRQ(ierr); 3363 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3364 3365 /* First process needs enough room for process with most rows */ 3366 if (!rank) { 3367 mmax = rowners[1]; 3368 for (i=2; i<=size; i++) { 3369 mmax = PetscMax(mmax, rowners[i]); 3370 } 3371 } else mmax = -1; /* unused, but compilers complain */ 3372 3373 rowners[0] = 0; 3374 for (i=2; i<=size; i++) { 3375 rowners[i] += rowners[i-1]; 3376 } 3377 rstart = rowners[rank]; 3378 rend = rowners[rank+1]; 3379 3380 /* distribute row lengths to all processors */ 3381 ierr = PetscMalloc2(m,&ourlens,m,&offlens);CHKERRQ(ierr); 3382 if (!rank) { 3383 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3384 ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr); 3385 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 3386 for (j=0; j<m; j++) { 3387 procsnz[0] += ourlens[j]; 3388 } 3389 for (i=1; i<size; i++) { 3390 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3391 /* calculate the number of nonzeros on each processor */ 3392 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3393 procsnz[i] += rowlengths[j]; 3394 } 3395 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3396 } 3397 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3398 } else { 3399 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3400 } 3401 3402 if (!rank) { 3403 /* determine max buffer needed and allocate it */ 3404 maxnz = 0; 3405 for (i=0; i<size; i++) { 3406 maxnz = PetscMax(maxnz,procsnz[i]); 3407 } 3408 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 3409 3410 /* read in my part of the matrix column indices */ 3411 nz = procsnz[0]; 3412 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3413 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3414 3415 /* read in every one elses and ship off */ 3416 for (i=1; i<size; i++) { 3417 nz = procsnz[i]; 3418 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3419 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3420 } 3421 ierr = PetscFree(cols);CHKERRQ(ierr); 3422 } else { 3423 /* determine buffer space needed for message */ 3424 nz = 0; 3425 for (i=0; i<m; i++) { 3426 nz += ourlens[i]; 3427 } 3428 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 3429 3430 /* receive message of column indices*/ 3431 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3432 } 3433 3434 /* determine column ownership if matrix is not square */ 3435 if (N != M) { 3436 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3437 else n = newMat->cmap->n; 3438 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3439 cstart = cend - n; 3440 } else { 3441 cstart = rstart; 3442 cend = rend; 3443 n = cend - cstart; 3444 } 3445 3446 /* loop over local rows, determining number of off diagonal entries */ 3447 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3448 jj = 0; 3449 for (i=0; i<m; i++) { 3450 for (j=0; j<ourlens[i]; j++) { 3451 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3452 jj++; 3453 } 3454 } 3455 3456 for (i=0; i<m; i++) { 3457 ourlens[i] -= offlens[i]; 3458 } 3459 if (!sizesset) { 3460 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3461 } 3462 3463 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3464 3465 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3466 3467 for (i=0; i<m; i++) { 3468 ourlens[i] += offlens[i]; 3469 } 3470 3471 if (!rank) { 3472 ierr = PetscMalloc1((maxnz+1),&vals);CHKERRQ(ierr); 3473 3474 /* read in my part of the matrix numerical values */ 3475 nz = procsnz[0]; 3476 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3477 3478 /* insert into matrix */ 3479 jj = rstart; 3480 smycols = mycols; 3481 svals = vals; 3482 for (i=0; i<m; i++) { 3483 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3484 smycols += ourlens[i]; 3485 svals += ourlens[i]; 3486 jj++; 3487 } 3488 3489 /* read in other processors and ship out */ 3490 for (i=1; i<size; i++) { 3491 nz = procsnz[i]; 3492 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3493 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3494 } 3495 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3496 } else { 3497 /* receive numeric values */ 3498 ierr = PetscMalloc1((nz+1),&vals);CHKERRQ(ierr); 3499 3500 /* receive message of values*/ 3501 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3502 3503 /* insert into matrix */ 3504 jj = rstart; 3505 smycols = mycols; 3506 svals = vals; 3507 for (i=0; i<m; i++) { 3508 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3509 smycols += ourlens[i]; 3510 svals += ourlens[i]; 3511 jj++; 3512 } 3513 } 3514 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3515 ierr = PetscFree(vals);CHKERRQ(ierr); 3516 ierr = PetscFree(mycols);CHKERRQ(ierr); 3517 ierr = PetscFree(rowners);CHKERRQ(ierr); 3518 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3519 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3520 PetscFunctionReturn(0); 3521 } 3522 3523 #undef __FUNCT__ 3524 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3525 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3526 { 3527 PetscErrorCode ierr; 3528 IS iscol_local; 3529 PetscInt csize; 3530 3531 PetscFunctionBegin; 3532 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3533 if (call == MAT_REUSE_MATRIX) { 3534 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3535 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3536 } else { 3537 PetscInt cbs; 3538 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3539 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3540 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3541 } 3542 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3543 if (call == MAT_INITIAL_MATRIX) { 3544 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3545 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3546 } 3547 PetscFunctionReturn(0); 3548 } 3549 3550 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3551 #undef __FUNCT__ 3552 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3553 /* 3554 Not great since it makes two copies of the submatrix, first an SeqAIJ 3555 in local and then by concatenating the local matrices the end result. 3556 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3557 3558 Note: This requires a sequential iscol with all indices. 3559 */ 3560 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3561 { 3562 PetscErrorCode ierr; 3563 PetscMPIInt rank,size; 3564 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3565 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3566 PetscBool allcolumns, colflag; 3567 Mat M,Mreuse; 3568 MatScalar *vwork,*aa; 3569 MPI_Comm comm; 3570 Mat_SeqAIJ *aij; 3571 3572 PetscFunctionBegin; 3573 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3574 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3575 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3576 3577 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3578 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3579 if (colflag && ncol == mat->cmap->N) { 3580 allcolumns = PETSC_TRUE; 3581 } else { 3582 allcolumns = PETSC_FALSE; 3583 } 3584 if (call == MAT_REUSE_MATRIX) { 3585 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3586 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3587 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3588 } else { 3589 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3590 } 3591 3592 /* 3593 m - number of local rows 3594 n - number of columns (same on all processors) 3595 rstart - first row in new global matrix generated 3596 */ 3597 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3598 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3599 if (call == MAT_INITIAL_MATRIX) { 3600 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3601 ii = aij->i; 3602 jj = aij->j; 3603 3604 /* 3605 Determine the number of non-zeros in the diagonal and off-diagonal 3606 portions of the matrix in order to do correct preallocation 3607 */ 3608 3609 /* first get start and end of "diagonal" columns */ 3610 if (csize == PETSC_DECIDE) { 3611 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3612 if (mglobal == n) { /* square matrix */ 3613 nlocal = m; 3614 } else { 3615 nlocal = n/size + ((n % size) > rank); 3616 } 3617 } else { 3618 nlocal = csize; 3619 } 3620 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3621 rstart = rend - nlocal; 3622 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); 3623 3624 /* next, compute all the lengths */ 3625 ierr = PetscMalloc1((2*m+1),&dlens);CHKERRQ(ierr); 3626 olens = dlens + m; 3627 for (i=0; i<m; i++) { 3628 jend = ii[i+1] - ii[i]; 3629 olen = 0; 3630 dlen = 0; 3631 for (j=0; j<jend; j++) { 3632 if (*jj < rstart || *jj >= rend) olen++; 3633 else dlen++; 3634 jj++; 3635 } 3636 olens[i] = olen; 3637 dlens[i] = dlen; 3638 } 3639 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3640 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3641 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3642 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3643 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3644 ierr = PetscFree(dlens);CHKERRQ(ierr); 3645 } else { 3646 PetscInt ml,nl; 3647 3648 M = *newmat; 3649 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3650 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3651 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3652 /* 3653 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3654 rather than the slower MatSetValues(). 3655 */ 3656 M->was_assembled = PETSC_TRUE; 3657 M->assembled = PETSC_FALSE; 3658 } 3659 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3660 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3661 ii = aij->i; 3662 jj = aij->j; 3663 aa = aij->a; 3664 for (i=0; i<m; i++) { 3665 row = rstart + i; 3666 nz = ii[i+1] - ii[i]; 3667 cwork = jj; jj += nz; 3668 vwork = aa; aa += nz; 3669 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3670 } 3671 3672 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3673 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3674 *newmat = M; 3675 3676 /* save submatrix used in processor for next request */ 3677 if (call == MAT_INITIAL_MATRIX) { 3678 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3679 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3680 } 3681 PetscFunctionReturn(0); 3682 } 3683 3684 #undef __FUNCT__ 3685 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3686 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3687 { 3688 PetscInt m,cstart, cend,j,nnz,i,d; 3689 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3690 const PetscInt *JJ; 3691 PetscScalar *values; 3692 PetscErrorCode ierr; 3693 3694 PetscFunctionBegin; 3695 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3696 3697 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3698 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3699 m = B->rmap->n; 3700 cstart = B->cmap->rstart; 3701 cend = B->cmap->rend; 3702 rstart = B->rmap->rstart; 3703 3704 ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr); 3705 3706 #if defined(PETSC_USE_DEBUGGING) 3707 for (i=0; i<m; i++) { 3708 nnz = Ii[i+1]- Ii[i]; 3709 JJ = J + Ii[i]; 3710 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3711 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3712 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); 3713 } 3714 #endif 3715 3716 for (i=0; i<m; i++) { 3717 nnz = Ii[i+1]- Ii[i]; 3718 JJ = J + Ii[i]; 3719 nnz_max = PetscMax(nnz_max,nnz); 3720 d = 0; 3721 for (j=0; j<nnz; j++) { 3722 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3723 } 3724 d_nnz[i] = d; 3725 o_nnz[i] = nnz - d; 3726 } 3727 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3728 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3729 3730 if (v) values = (PetscScalar*)v; 3731 else { 3732 ierr = PetscCalloc1((nnz_max+1),&values);CHKERRQ(ierr); 3733 } 3734 3735 for (i=0; i<m; i++) { 3736 ii = i + rstart; 3737 nnz = Ii[i+1]- Ii[i]; 3738 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3739 } 3740 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3741 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3742 3743 if (!v) { 3744 ierr = PetscFree(values);CHKERRQ(ierr); 3745 } 3746 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3747 PetscFunctionReturn(0); 3748 } 3749 3750 #undef __FUNCT__ 3751 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3752 /*@ 3753 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3754 (the default parallel PETSc format). 3755 3756 Collective on MPI_Comm 3757 3758 Input Parameters: 3759 + B - the matrix 3760 . i - the indices into j for the start of each local row (starts with zero) 3761 . j - the column indices for each local row (starts with zero) 3762 - v - optional values in the matrix 3763 3764 Level: developer 3765 3766 Notes: 3767 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3768 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3769 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3770 3771 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3772 3773 The format which is used for the sparse matrix input, is equivalent to a 3774 row-major ordering.. i.e for the following matrix, the input data expected is 3775 as shown: 3776 3777 1 0 0 3778 2 0 3 P0 3779 ------- 3780 4 5 6 P1 3781 3782 Process0 [P0]: rows_owned=[0,1] 3783 i = {0,1,3} [size = nrow+1 = 2+1] 3784 j = {0,0,2} [size = nz = 6] 3785 v = {1,2,3} [size = nz = 6] 3786 3787 Process1 [P1]: rows_owned=[2] 3788 i = {0,3} [size = nrow+1 = 1+1] 3789 j = {0,1,2} [size = nz = 6] 3790 v = {4,5,6} [size = nz = 6] 3791 3792 .keywords: matrix, aij, compressed row, sparse, parallel 3793 3794 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3795 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3796 @*/ 3797 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3798 { 3799 PetscErrorCode ierr; 3800 3801 PetscFunctionBegin; 3802 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3803 PetscFunctionReturn(0); 3804 } 3805 3806 #undef __FUNCT__ 3807 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3808 /*@C 3809 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3810 (the default parallel PETSc format). For good matrix assembly performance 3811 the user should preallocate the matrix storage by setting the parameters 3812 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3813 performance can be increased by more than a factor of 50. 3814 3815 Collective on MPI_Comm 3816 3817 Input Parameters: 3818 + B - the matrix 3819 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3820 (same value is used for all local rows) 3821 . d_nnz - array containing the number of nonzeros in the various rows of the 3822 DIAGONAL portion of the local submatrix (possibly different for each row) 3823 or NULL, if d_nz is used to specify the nonzero structure. 3824 The size of this array is equal to the number of local rows, i.e 'm'. 3825 For matrices that will be factored, you must leave room for (and set) 3826 the diagonal entry even if it is zero. 3827 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3828 submatrix (same value is used for all local rows). 3829 - o_nnz - array containing the number of nonzeros in the various rows of the 3830 OFF-DIAGONAL portion of the local submatrix (possibly different for 3831 each row) or NULL, if o_nz is used to specify the nonzero 3832 structure. The size of this array is equal to the number 3833 of local rows, i.e 'm'. 3834 3835 If the *_nnz parameter is given then the *_nz parameter is ignored 3836 3837 The AIJ format (also called the Yale sparse matrix format or 3838 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3839 storage. The stored row and column indices begin with zero. 3840 See Users-Manual: ch_mat for details. 3841 3842 The parallel matrix is partitioned such that the first m0 rows belong to 3843 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3844 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3845 3846 The DIAGONAL portion of the local submatrix of a processor can be defined 3847 as the submatrix which is obtained by extraction the part corresponding to 3848 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3849 first row that belongs to the processor, r2 is the last row belonging to 3850 the this processor, and c1-c2 is range of indices of the local part of a 3851 vector suitable for applying the matrix to. This is an mxn matrix. In the 3852 common case of a square matrix, the row and column ranges are the same and 3853 the DIAGONAL part is also square. The remaining portion of the local 3854 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3855 3856 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3857 3858 You can call MatGetInfo() to get information on how effective the preallocation was; 3859 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3860 You can also run with the option -info and look for messages with the string 3861 malloc in them to see if additional memory allocation was needed. 3862 3863 Example usage: 3864 3865 Consider the following 8x8 matrix with 34 non-zero values, that is 3866 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3867 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3868 as follows: 3869 3870 .vb 3871 1 2 0 | 0 3 0 | 0 4 3872 Proc0 0 5 6 | 7 0 0 | 8 0 3873 9 0 10 | 11 0 0 | 12 0 3874 ------------------------------------- 3875 13 0 14 | 15 16 17 | 0 0 3876 Proc1 0 18 0 | 19 20 21 | 0 0 3877 0 0 0 | 22 23 0 | 24 0 3878 ------------------------------------- 3879 Proc2 25 26 27 | 0 0 28 | 29 0 3880 30 0 0 | 31 32 33 | 0 34 3881 .ve 3882 3883 This can be represented as a collection of submatrices as: 3884 3885 .vb 3886 A B C 3887 D E F 3888 G H I 3889 .ve 3890 3891 Where the submatrices A,B,C are owned by proc0, D,E,F are 3892 owned by proc1, G,H,I are owned by proc2. 3893 3894 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3895 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3896 The 'M','N' parameters are 8,8, and have the same values on all procs. 3897 3898 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3899 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3900 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3901 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3902 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3903 matrix, ans [DF] as another SeqAIJ matrix. 3904 3905 When d_nz, o_nz parameters are specified, d_nz storage elements are 3906 allocated for every row of the local diagonal submatrix, and o_nz 3907 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3908 One way to choose d_nz and o_nz is to use the max nonzerors per local 3909 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3910 In this case, the values of d_nz,o_nz are: 3911 .vb 3912 proc0 : dnz = 2, o_nz = 2 3913 proc1 : dnz = 3, o_nz = 2 3914 proc2 : dnz = 1, o_nz = 4 3915 .ve 3916 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3917 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3918 for proc3. i.e we are using 12+15+10=37 storage locations to store 3919 34 values. 3920 3921 When d_nnz, o_nnz parameters are specified, the storage is specified 3922 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3923 In the above case the values for d_nnz,o_nnz are: 3924 .vb 3925 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3926 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3927 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3928 .ve 3929 Here the space allocated is sum of all the above values i.e 34, and 3930 hence pre-allocation is perfect. 3931 3932 Level: intermediate 3933 3934 .keywords: matrix, aij, compressed row, sparse, parallel 3935 3936 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3937 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 3938 @*/ 3939 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3940 { 3941 PetscErrorCode ierr; 3942 3943 PetscFunctionBegin; 3944 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3945 PetscValidType(B,1); 3946 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 3947 PetscFunctionReturn(0); 3948 } 3949 3950 #undef __FUNCT__ 3951 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 3952 /*@ 3953 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 3954 CSR format the local rows. 3955 3956 Collective on MPI_Comm 3957 3958 Input Parameters: 3959 + comm - MPI communicator 3960 . m - number of local rows (Cannot be PETSC_DECIDE) 3961 . n - This value should be the same as the local size used in creating the 3962 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 3963 calculated if N is given) For square matrices n is almost always m. 3964 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 3965 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 3966 . i - row indices 3967 . j - column indices 3968 - a - matrix values 3969 3970 Output Parameter: 3971 . mat - the matrix 3972 3973 Level: intermediate 3974 3975 Notes: 3976 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3977 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3978 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3979 3980 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3981 3982 The format which is used for the sparse matrix input, is equivalent to a 3983 row-major ordering.. i.e for the following matrix, the input data expected is 3984 as shown: 3985 3986 1 0 0 3987 2 0 3 P0 3988 ------- 3989 4 5 6 P1 3990 3991 Process0 [P0]: rows_owned=[0,1] 3992 i = {0,1,3} [size = nrow+1 = 2+1] 3993 j = {0,0,2} [size = nz = 6] 3994 v = {1,2,3} [size = nz = 6] 3995 3996 Process1 [P1]: rows_owned=[2] 3997 i = {0,3} [size = nrow+1 = 1+1] 3998 j = {0,1,2} [size = nz = 6] 3999 v = {4,5,6} [size = nz = 6] 4000 4001 .keywords: matrix, aij, compressed row, sparse, parallel 4002 4003 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4004 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4005 @*/ 4006 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4007 { 4008 PetscErrorCode ierr; 4009 4010 PetscFunctionBegin; 4011 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4012 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4013 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4014 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4015 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4016 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4017 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4018 PetscFunctionReturn(0); 4019 } 4020 4021 #undef __FUNCT__ 4022 #define __FUNCT__ "MatCreateAIJ" 4023 /*@C 4024 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4025 (the default parallel PETSc format). For good matrix assembly performance 4026 the user should preallocate the matrix storage by setting the parameters 4027 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4028 performance can be increased by more than a factor of 50. 4029 4030 Collective on MPI_Comm 4031 4032 Input Parameters: 4033 + comm - MPI communicator 4034 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4035 This value should be the same as the local size used in creating the 4036 y vector for the matrix-vector product y = Ax. 4037 . n - This value should be the same as the local size used in creating the 4038 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4039 calculated if N is given) For square matrices n is almost always m. 4040 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4041 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4042 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4043 (same value is used for all local rows) 4044 . d_nnz - array containing the number of nonzeros in the various rows of the 4045 DIAGONAL portion of the local submatrix (possibly different for each row) 4046 or NULL, if d_nz is used to specify the nonzero structure. 4047 The size of this array is equal to the number of local rows, i.e 'm'. 4048 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4049 submatrix (same value is used for all local rows). 4050 - o_nnz - array containing the number of nonzeros in the various rows of the 4051 OFF-DIAGONAL portion of the local submatrix (possibly different for 4052 each row) or NULL, if o_nz is used to specify the nonzero 4053 structure. The size of this array is equal to the number 4054 of local rows, i.e 'm'. 4055 4056 Output Parameter: 4057 . A - the matrix 4058 4059 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4060 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4061 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4062 4063 Notes: 4064 If the *_nnz parameter is given then the *_nz parameter is ignored 4065 4066 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4067 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4068 storage requirements for this matrix. 4069 4070 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4071 processor than it must be used on all processors that share the object for 4072 that argument. 4073 4074 The user MUST specify either the local or global matrix dimensions 4075 (possibly both). 4076 4077 The parallel matrix is partitioned across processors such that the 4078 first m0 rows belong to process 0, the next m1 rows belong to 4079 process 1, the next m2 rows belong to process 2 etc.. where 4080 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4081 values corresponding to [m x N] submatrix. 4082 4083 The columns are logically partitioned with the n0 columns belonging 4084 to 0th partition, the next n1 columns belonging to the next 4085 partition etc.. where n0,n1,n2... are the input parameter 'n'. 4086 4087 The DIAGONAL portion of the local submatrix on any given processor 4088 is the submatrix corresponding to the rows and columns m,n 4089 corresponding to the given processor. i.e diagonal matrix on 4090 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4091 etc. The remaining portion of the local submatrix [m x (N-n)] 4092 constitute the OFF-DIAGONAL portion. The example below better 4093 illustrates this concept. 4094 4095 For a square global matrix we define each processor's diagonal portion 4096 to be its local rows and the corresponding columns (a square submatrix); 4097 each processor's off-diagonal portion encompasses the remainder of the 4098 local matrix (a rectangular submatrix). 4099 4100 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4101 4102 When calling this routine with a single process communicator, a matrix of 4103 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4104 type of communicator, use the construction mechanism: 4105 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4106 4107 By default, this format uses inodes (identical nodes) when possible. 4108 We search for consecutive rows with the same nonzero structure, thereby 4109 reusing matrix information to achieve increased efficiency. 4110 4111 Options Database Keys: 4112 + -mat_no_inode - Do not use inodes 4113 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4114 - -mat_aij_oneindex - Internally use indexing starting at 1 4115 rather than 0. Note that when calling MatSetValues(), 4116 the user still MUST index entries starting at 0! 4117 4118 4119 Example usage: 4120 4121 Consider the following 8x8 matrix with 34 non-zero values, that is 4122 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4123 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4124 as follows: 4125 4126 .vb 4127 1 2 0 | 0 3 0 | 0 4 4128 Proc0 0 5 6 | 7 0 0 | 8 0 4129 9 0 10 | 11 0 0 | 12 0 4130 ------------------------------------- 4131 13 0 14 | 15 16 17 | 0 0 4132 Proc1 0 18 0 | 19 20 21 | 0 0 4133 0 0 0 | 22 23 0 | 24 0 4134 ------------------------------------- 4135 Proc2 25 26 27 | 0 0 28 | 29 0 4136 30 0 0 | 31 32 33 | 0 34 4137 .ve 4138 4139 This can be represented as a collection of submatrices as: 4140 4141 .vb 4142 A B C 4143 D E F 4144 G H I 4145 .ve 4146 4147 Where the submatrices A,B,C are owned by proc0, D,E,F are 4148 owned by proc1, G,H,I are owned by proc2. 4149 4150 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4151 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4152 The 'M','N' parameters are 8,8, and have the same values on all procs. 4153 4154 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4155 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4156 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4157 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4158 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4159 matrix, ans [DF] as another SeqAIJ matrix. 4160 4161 When d_nz, o_nz parameters are specified, d_nz storage elements are 4162 allocated for every row of the local diagonal submatrix, and o_nz 4163 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4164 One way to choose d_nz and o_nz is to use the max nonzerors per local 4165 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4166 In this case, the values of d_nz,o_nz are: 4167 .vb 4168 proc0 : dnz = 2, o_nz = 2 4169 proc1 : dnz = 3, o_nz = 2 4170 proc2 : dnz = 1, o_nz = 4 4171 .ve 4172 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4173 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4174 for proc3. i.e we are using 12+15+10=37 storage locations to store 4175 34 values. 4176 4177 When d_nnz, o_nnz parameters are specified, the storage is specified 4178 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4179 In the above case the values for d_nnz,o_nnz are: 4180 .vb 4181 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4182 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4183 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4184 .ve 4185 Here the space allocated is sum of all the above values i.e 34, and 4186 hence pre-allocation is perfect. 4187 4188 Level: intermediate 4189 4190 .keywords: matrix, aij, compressed row, sparse, parallel 4191 4192 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4193 MPIAIJ, MatCreateMPIAIJWithArrays() 4194 @*/ 4195 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) 4196 { 4197 PetscErrorCode ierr; 4198 PetscMPIInt size; 4199 4200 PetscFunctionBegin; 4201 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4202 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4203 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4204 if (size > 1) { 4205 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4206 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4207 } else { 4208 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4209 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4210 } 4211 PetscFunctionReturn(0); 4212 } 4213 4214 #undef __FUNCT__ 4215 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4216 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4217 { 4218 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4219 4220 PetscFunctionBegin; 4221 if (Ad) *Ad = a->A; 4222 if (Ao) *Ao = a->B; 4223 if (colmap) *colmap = a->garray; 4224 PetscFunctionReturn(0); 4225 } 4226 4227 #undef __FUNCT__ 4228 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4229 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4230 { 4231 PetscErrorCode ierr; 4232 PetscInt i; 4233 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4234 4235 PetscFunctionBegin; 4236 if (coloring->ctype == IS_COLORING_GLOBAL) { 4237 ISColoringValue *allcolors,*colors; 4238 ISColoring ocoloring; 4239 4240 /* set coloring for diagonal portion */ 4241 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4242 4243 /* set coloring for off-diagonal portion */ 4244 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4245 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 4246 for (i=0; i<a->B->cmap->n; i++) { 4247 colors[i] = allcolors[a->garray[i]]; 4248 } 4249 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4250 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4251 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4252 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4253 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4254 ISColoringValue *colors; 4255 PetscInt *larray; 4256 ISColoring ocoloring; 4257 4258 /* set coloring for diagonal portion */ 4259 ierr = PetscMalloc1((a->A->cmap->n+1),&larray);CHKERRQ(ierr); 4260 for (i=0; i<a->A->cmap->n; i++) { 4261 larray[i] = i + A->cmap->rstart; 4262 } 4263 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4264 ierr = PetscMalloc1((a->A->cmap->n+1),&colors);CHKERRQ(ierr); 4265 for (i=0; i<a->A->cmap->n; i++) { 4266 colors[i] = coloring->colors[larray[i]]; 4267 } 4268 ierr = PetscFree(larray);CHKERRQ(ierr); 4269 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4270 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4271 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4272 4273 /* set coloring for off-diagonal portion */ 4274 ierr = PetscMalloc1((a->B->cmap->n+1),&larray);CHKERRQ(ierr); 4275 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4276 ierr = PetscMalloc1((a->B->cmap->n+1),&colors);CHKERRQ(ierr); 4277 for (i=0; i<a->B->cmap->n; i++) { 4278 colors[i] = coloring->colors[larray[i]]; 4279 } 4280 ierr = PetscFree(larray);CHKERRQ(ierr); 4281 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4282 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4283 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4284 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4285 PetscFunctionReturn(0); 4286 } 4287 4288 #undef __FUNCT__ 4289 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4290 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4291 { 4292 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4293 PetscErrorCode ierr; 4294 4295 PetscFunctionBegin; 4296 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4297 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4298 PetscFunctionReturn(0); 4299 } 4300 4301 #undef __FUNCT__ 4302 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4303 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4304 { 4305 PetscErrorCode ierr; 4306 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4307 PetscInt *indx; 4308 4309 PetscFunctionBegin; 4310 /* This routine will ONLY return MPIAIJ type matrix */ 4311 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4312 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4313 if (n == PETSC_DECIDE) { 4314 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4315 } 4316 /* Check sum(n) = N */ 4317 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4318 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4319 4320 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4321 rstart -= m; 4322 4323 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4324 for (i=0; i<m; i++) { 4325 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4326 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4327 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4328 } 4329 4330 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4331 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4332 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4333 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4334 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4335 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4336 PetscFunctionReturn(0); 4337 } 4338 4339 #undef __FUNCT__ 4340 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4341 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4342 { 4343 PetscErrorCode ierr; 4344 PetscInt m,N,i,rstart,nnz,Ii; 4345 PetscInt *indx; 4346 PetscScalar *values; 4347 4348 PetscFunctionBegin; 4349 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4350 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4351 for (i=0; i<m; i++) { 4352 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4353 Ii = i + rstart; 4354 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4355 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4356 } 4357 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4358 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4359 PetscFunctionReturn(0); 4360 } 4361 4362 #undef __FUNCT__ 4363 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIAIJ" 4364 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4365 { 4366 PetscErrorCode ierr; 4367 PetscMPIInt size; 4368 4369 PetscFunctionBegin; 4370 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4371 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4372 if (size == 1) { 4373 if (scall == MAT_INITIAL_MATRIX) { 4374 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4375 } else { 4376 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4377 } 4378 } else { 4379 if (scall == MAT_INITIAL_MATRIX) { 4380 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4381 } 4382 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4383 } 4384 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4385 PetscFunctionReturn(0); 4386 } 4387 4388 #undef __FUNCT__ 4389 #define __FUNCT__ "MatFileSplit" 4390 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4391 { 4392 PetscErrorCode ierr; 4393 PetscMPIInt rank; 4394 PetscInt m,N,i,rstart,nnz; 4395 size_t len; 4396 const PetscInt *indx; 4397 PetscViewer out; 4398 char *name; 4399 Mat B; 4400 const PetscScalar *values; 4401 4402 PetscFunctionBegin; 4403 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4404 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4405 /* Should this be the type of the diagonal block of A? */ 4406 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4407 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4408 ierr = MatSetBlockSizesFromMats(B,A,A);CHKERRQ(ierr); 4409 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4410 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4411 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4412 for (i=0; i<m; i++) { 4413 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4414 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4415 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4416 } 4417 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4418 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4419 4420 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4421 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4422 ierr = PetscMalloc1((len+5),&name);CHKERRQ(ierr); 4423 sprintf(name,"%s.%d",outfile,rank); 4424 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4425 ierr = PetscFree(name);CHKERRQ(ierr); 4426 ierr = MatView(B,out);CHKERRQ(ierr); 4427 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4428 ierr = MatDestroy(&B);CHKERRQ(ierr); 4429 PetscFunctionReturn(0); 4430 } 4431 4432 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4433 #undef __FUNCT__ 4434 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4435 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4436 { 4437 PetscErrorCode ierr; 4438 Mat_Merge_SeqsToMPI *merge; 4439 PetscContainer container; 4440 4441 PetscFunctionBegin; 4442 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4443 if (container) { 4444 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4445 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4446 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4447 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4448 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4449 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4450 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4451 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4452 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4453 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4454 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4455 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4456 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4457 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4458 ierr = PetscFree(merge);CHKERRQ(ierr); 4459 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4460 } 4461 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4462 PetscFunctionReturn(0); 4463 } 4464 4465 #include <../src/mat/utils/freespace.h> 4466 #include <petscbt.h> 4467 4468 #undef __FUNCT__ 4469 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4470 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4471 { 4472 PetscErrorCode ierr; 4473 MPI_Comm comm; 4474 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4475 PetscMPIInt size,rank,taga,*len_s; 4476 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4477 PetscInt proc,m; 4478 PetscInt **buf_ri,**buf_rj; 4479 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4480 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4481 MPI_Request *s_waits,*r_waits; 4482 MPI_Status *status; 4483 MatScalar *aa=a->a; 4484 MatScalar **abuf_r,*ba_i; 4485 Mat_Merge_SeqsToMPI *merge; 4486 PetscContainer container; 4487 4488 PetscFunctionBegin; 4489 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4490 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4491 4492 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4493 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4494 4495 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4496 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4497 4498 bi = merge->bi; 4499 bj = merge->bj; 4500 buf_ri = merge->buf_ri; 4501 buf_rj = merge->buf_rj; 4502 4503 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4504 owners = merge->rowmap->range; 4505 len_s = merge->len_s; 4506 4507 /* send and recv matrix values */ 4508 /*-----------------------------*/ 4509 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4510 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4511 4512 ierr = PetscMalloc1((merge->nsend+1),&s_waits);CHKERRQ(ierr); 4513 for (proc=0,k=0; proc<size; proc++) { 4514 if (!len_s[proc]) continue; 4515 i = owners[proc]; 4516 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4517 k++; 4518 } 4519 4520 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4521 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4522 ierr = PetscFree(status);CHKERRQ(ierr); 4523 4524 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4525 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4526 4527 /* insert mat values of mpimat */ 4528 /*----------------------------*/ 4529 ierr = PetscMalloc1(N,&ba_i);CHKERRQ(ierr); 4530 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4531 4532 for (k=0; k<merge->nrecv; k++) { 4533 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4534 nrows = *(buf_ri_k[k]); 4535 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4536 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4537 } 4538 4539 /* set values of ba */ 4540 m = merge->rowmap->n; 4541 for (i=0; i<m; i++) { 4542 arow = owners[rank] + i; 4543 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4544 bnzi = bi[i+1] - bi[i]; 4545 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4546 4547 /* add local non-zero vals of this proc's seqmat into ba */ 4548 anzi = ai[arow+1] - ai[arow]; 4549 aj = a->j + ai[arow]; 4550 aa = a->a + ai[arow]; 4551 nextaj = 0; 4552 for (j=0; nextaj<anzi; j++) { 4553 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4554 ba_i[j] += aa[nextaj++]; 4555 } 4556 } 4557 4558 /* add received vals into ba */ 4559 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4560 /* i-th row */ 4561 if (i == *nextrow[k]) { 4562 anzi = *(nextai[k]+1) - *nextai[k]; 4563 aj = buf_rj[k] + *(nextai[k]); 4564 aa = abuf_r[k] + *(nextai[k]); 4565 nextaj = 0; 4566 for (j=0; nextaj<anzi; j++) { 4567 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4568 ba_i[j] += aa[nextaj++]; 4569 } 4570 } 4571 nextrow[k]++; nextai[k]++; 4572 } 4573 } 4574 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4575 } 4576 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4577 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4578 4579 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4580 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4581 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4582 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4583 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4584 PetscFunctionReturn(0); 4585 } 4586 4587 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4588 4589 #undef __FUNCT__ 4590 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4591 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4592 { 4593 PetscErrorCode ierr; 4594 Mat B_mpi; 4595 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4596 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4597 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4598 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4599 PetscInt len,proc,*dnz,*onz,bs,cbs; 4600 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4601 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4602 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4603 MPI_Status *status; 4604 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4605 PetscBT lnkbt; 4606 Mat_Merge_SeqsToMPI *merge; 4607 PetscContainer container; 4608 4609 PetscFunctionBegin; 4610 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4611 4612 /* make sure it is a PETSc comm */ 4613 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4614 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4615 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4616 4617 ierr = PetscNew(&merge);CHKERRQ(ierr); 4618 ierr = PetscMalloc1(size,&status);CHKERRQ(ierr); 4619 4620 /* determine row ownership */ 4621 /*---------------------------------------------------------*/ 4622 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4623 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4624 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4625 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4626 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4627 ierr = PetscMalloc1(size,&len_si);CHKERRQ(ierr); 4628 ierr = PetscMalloc1(size,&merge->len_s);CHKERRQ(ierr); 4629 4630 m = merge->rowmap->n; 4631 owners = merge->rowmap->range; 4632 4633 /* determine the number of messages to send, their lengths */ 4634 /*---------------------------------------------------------*/ 4635 len_s = merge->len_s; 4636 4637 len = 0; /* length of buf_si[] */ 4638 merge->nsend = 0; 4639 for (proc=0; proc<size; proc++) { 4640 len_si[proc] = 0; 4641 if (proc == rank) { 4642 len_s[proc] = 0; 4643 } else { 4644 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4645 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4646 } 4647 if (len_s[proc]) { 4648 merge->nsend++; 4649 nrows = 0; 4650 for (i=owners[proc]; i<owners[proc+1]; i++) { 4651 if (ai[i+1] > ai[i]) nrows++; 4652 } 4653 len_si[proc] = 2*(nrows+1); 4654 len += len_si[proc]; 4655 } 4656 } 4657 4658 /* determine the number and length of messages to receive for ij-structure */ 4659 /*-------------------------------------------------------------------------*/ 4660 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4661 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4662 4663 /* post the Irecv of j-structure */ 4664 /*-------------------------------*/ 4665 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4666 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4667 4668 /* post the Isend of j-structure */ 4669 /*--------------------------------*/ 4670 ierr = PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);CHKERRQ(ierr); 4671 4672 for (proc=0, k=0; proc<size; proc++) { 4673 if (!len_s[proc]) continue; 4674 i = owners[proc]; 4675 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4676 k++; 4677 } 4678 4679 /* receives and sends of j-structure are complete */ 4680 /*------------------------------------------------*/ 4681 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4682 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4683 4684 /* send and recv i-structure */ 4685 /*---------------------------*/ 4686 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4687 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4688 4689 ierr = PetscMalloc1((len+1),&buf_s);CHKERRQ(ierr); 4690 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4691 for (proc=0,k=0; proc<size; proc++) { 4692 if (!len_s[proc]) continue; 4693 /* form outgoing message for i-structure: 4694 buf_si[0]: nrows to be sent 4695 [1:nrows]: row index (global) 4696 [nrows+1:2*nrows+1]: i-structure index 4697 */ 4698 /*-------------------------------------------*/ 4699 nrows = len_si[proc]/2 - 1; 4700 buf_si_i = buf_si + nrows+1; 4701 buf_si[0] = nrows; 4702 buf_si_i[0] = 0; 4703 nrows = 0; 4704 for (i=owners[proc]; i<owners[proc+1]; i++) { 4705 anzi = ai[i+1] - ai[i]; 4706 if (anzi) { 4707 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4708 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4709 nrows++; 4710 } 4711 } 4712 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4713 k++; 4714 buf_si += len_si[proc]; 4715 } 4716 4717 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4718 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4719 4720 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4721 for (i=0; i<merge->nrecv; i++) { 4722 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); 4723 } 4724 4725 ierr = PetscFree(len_si);CHKERRQ(ierr); 4726 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4727 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4728 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4729 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4730 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4731 ierr = PetscFree(status);CHKERRQ(ierr); 4732 4733 /* compute a local seq matrix in each processor */ 4734 /*----------------------------------------------*/ 4735 /* allocate bi array and free space for accumulating nonzero column info */ 4736 ierr = PetscMalloc1((m+1),&bi);CHKERRQ(ierr); 4737 bi[0] = 0; 4738 4739 /* create and initialize a linked list */ 4740 nlnk = N+1; 4741 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4742 4743 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4744 len = ai[owners[rank+1]] - ai[owners[rank]]; 4745 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4746 4747 current_space = free_space; 4748 4749 /* determine symbolic info for each local row */ 4750 ierr = PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);CHKERRQ(ierr); 4751 4752 for (k=0; k<merge->nrecv; k++) { 4753 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4754 nrows = *buf_ri_k[k]; 4755 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4756 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4757 } 4758 4759 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4760 len = 0; 4761 for (i=0; i<m; i++) { 4762 bnzi = 0; 4763 /* add local non-zero cols of this proc's seqmat into lnk */ 4764 arow = owners[rank] + i; 4765 anzi = ai[arow+1] - ai[arow]; 4766 aj = a->j + ai[arow]; 4767 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4768 bnzi += nlnk; 4769 /* add received col data into lnk */ 4770 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4771 if (i == *nextrow[k]) { /* i-th row */ 4772 anzi = *(nextai[k]+1) - *nextai[k]; 4773 aj = buf_rj[k] + *nextai[k]; 4774 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4775 bnzi += nlnk; 4776 nextrow[k]++; nextai[k]++; 4777 } 4778 } 4779 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4780 4781 /* if free space is not available, make more free space */ 4782 if (current_space->local_remaining<bnzi) { 4783 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4784 nspacedouble++; 4785 } 4786 /* copy data into free space, then initialize lnk */ 4787 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4788 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4789 4790 current_space->array += bnzi; 4791 current_space->local_used += bnzi; 4792 current_space->local_remaining -= bnzi; 4793 4794 bi[i+1] = bi[i] + bnzi; 4795 } 4796 4797 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4798 4799 ierr = PetscMalloc1((bi[m]+1),&bj);CHKERRQ(ierr); 4800 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4801 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4802 4803 /* create symbolic parallel matrix B_mpi */ 4804 /*---------------------------------------*/ 4805 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4806 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4807 if (n==PETSC_DECIDE) { 4808 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4809 } else { 4810 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4811 } 4812 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4813 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4814 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4815 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4816 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4817 4818 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4819 B_mpi->assembled = PETSC_FALSE; 4820 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4821 merge->bi = bi; 4822 merge->bj = bj; 4823 merge->buf_ri = buf_ri; 4824 merge->buf_rj = buf_rj; 4825 merge->coi = NULL; 4826 merge->coj = NULL; 4827 merge->owners_co = NULL; 4828 4829 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4830 4831 /* attach the supporting struct to B_mpi for reuse */ 4832 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4833 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4834 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4835 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4836 *mpimat = B_mpi; 4837 4838 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4839 PetscFunctionReturn(0); 4840 } 4841 4842 #undef __FUNCT__ 4843 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4844 /*@C 4845 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4846 matrices from each processor 4847 4848 Collective on MPI_Comm 4849 4850 Input Parameters: 4851 + comm - the communicators the parallel matrix will live on 4852 . seqmat - the input sequential matrices 4853 . m - number of local rows (or PETSC_DECIDE) 4854 . n - number of local columns (or PETSC_DECIDE) 4855 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4856 4857 Output Parameter: 4858 . mpimat - the parallel matrix generated 4859 4860 Level: advanced 4861 4862 Notes: 4863 The dimensions of the sequential matrix in each processor MUST be the same. 4864 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4865 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4866 @*/ 4867 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4868 { 4869 PetscErrorCode ierr; 4870 PetscMPIInt size; 4871 4872 PetscFunctionBegin; 4873 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4874 if (size == 1) { 4875 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4876 if (scall == MAT_INITIAL_MATRIX) { 4877 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4878 } else { 4879 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4880 } 4881 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4882 PetscFunctionReturn(0); 4883 } 4884 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4885 if (scall == MAT_INITIAL_MATRIX) { 4886 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4887 } 4888 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4889 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4890 PetscFunctionReturn(0); 4891 } 4892 4893 #undef __FUNCT__ 4894 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4895 /*@ 4896 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4897 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4898 with MatGetSize() 4899 4900 Not Collective 4901 4902 Input Parameters: 4903 + A - the matrix 4904 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4905 4906 Output Parameter: 4907 . A_loc - the local sequential matrix generated 4908 4909 Level: developer 4910 4911 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4912 4913 @*/ 4914 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4915 { 4916 PetscErrorCode ierr; 4917 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 4918 Mat_SeqAIJ *mat,*a,*b; 4919 PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray; 4920 MatScalar *aa,*ba,*cam; 4921 PetscScalar *ca; 4922 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 4923 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 4924 PetscBool match; 4925 MPI_Comm comm; 4926 PetscMPIInt size; 4927 4928 PetscFunctionBegin; 4929 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 4930 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 4931 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 4932 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4933 if (size == 1 && scall == MAT_REUSE_MATRIX) PetscFunctionReturn(0); 4934 4935 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 4936 a = (Mat_SeqAIJ*)(mpimat->A)->data; 4937 b = (Mat_SeqAIJ*)(mpimat->B)->data; 4938 ai = a->i; aj = a->j; bi = b->i; bj = b->j; 4939 aa = a->a; ba = b->a; 4940 if (scall == MAT_INITIAL_MATRIX) { 4941 if (size == 1) { 4942 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);CHKERRQ(ierr); 4943 PetscFunctionReturn(0); 4944 } 4945 4946 ierr = PetscMalloc1((1+am),&ci);CHKERRQ(ierr); 4947 ci[0] = 0; 4948 for (i=0; i<am; i++) { 4949 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 4950 } 4951 ierr = PetscMalloc1((1+ci[am]),&cj);CHKERRQ(ierr); 4952 ierr = PetscMalloc1((1+ci[am]),&ca);CHKERRQ(ierr); 4953 k = 0; 4954 for (i=0; i<am; i++) { 4955 ncols_o = bi[i+1] - bi[i]; 4956 ncols_d = ai[i+1] - ai[i]; 4957 /* off-diagonal portion of A */ 4958 for (jo=0; jo<ncols_o; jo++) { 4959 col = cmap[*bj]; 4960 if (col >= cstart) break; 4961 cj[k] = col; bj++; 4962 ca[k++] = *ba++; 4963 } 4964 /* diagonal portion of A */ 4965 for (j=0; j<ncols_d; j++) { 4966 cj[k] = cstart + *aj++; 4967 ca[k++] = *aa++; 4968 } 4969 /* off-diagonal portion of A */ 4970 for (j=jo; j<ncols_o; j++) { 4971 cj[k] = cmap[*bj++]; 4972 ca[k++] = *ba++; 4973 } 4974 } 4975 /* put together the new matrix */ 4976 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 4977 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 4978 /* Since these are PETSc arrays, change flags to free them as necessary. */ 4979 mat = (Mat_SeqAIJ*)(*A_loc)->data; 4980 mat->free_a = PETSC_TRUE; 4981 mat->free_ij = PETSC_TRUE; 4982 mat->nonew = 0; 4983 } else if (scall == MAT_REUSE_MATRIX) { 4984 mat=(Mat_SeqAIJ*)(*A_loc)->data; 4985 ci = mat->i; cj = mat->j; cam = mat->a; 4986 for (i=0; i<am; i++) { 4987 /* off-diagonal portion of A */ 4988 ncols_o = bi[i+1] - bi[i]; 4989 for (jo=0; jo<ncols_o; jo++) { 4990 col = cmap[*bj]; 4991 if (col >= cstart) break; 4992 *cam++ = *ba++; bj++; 4993 } 4994 /* diagonal portion of A */ 4995 ncols_d = ai[i+1] - ai[i]; 4996 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 4997 /* off-diagonal portion of A */ 4998 for (j=jo; j<ncols_o; j++) { 4999 *cam++ = *ba++; bj++; 5000 } 5001 } 5002 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5003 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5004 PetscFunctionReturn(0); 5005 } 5006 5007 #undef __FUNCT__ 5008 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5009 /*@C 5010 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5011 5012 Not Collective 5013 5014 Input Parameters: 5015 + A - the matrix 5016 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5017 - row, col - index sets of rows and columns to extract (or NULL) 5018 5019 Output Parameter: 5020 . A_loc - the local sequential matrix generated 5021 5022 Level: developer 5023 5024 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5025 5026 @*/ 5027 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5028 { 5029 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5030 PetscErrorCode ierr; 5031 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5032 IS isrowa,iscola; 5033 Mat *aloc; 5034 PetscBool match; 5035 5036 PetscFunctionBegin; 5037 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5038 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5039 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5040 if (!row) { 5041 start = A->rmap->rstart; end = A->rmap->rend; 5042 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5043 } else { 5044 isrowa = *row; 5045 } 5046 if (!col) { 5047 start = A->cmap->rstart; 5048 cmap = a->garray; 5049 nzA = a->A->cmap->n; 5050 nzB = a->B->cmap->n; 5051 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 5052 ncols = 0; 5053 for (i=0; i<nzB; i++) { 5054 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5055 else break; 5056 } 5057 imark = i; 5058 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5059 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5060 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5061 } else { 5062 iscola = *col; 5063 } 5064 if (scall != MAT_INITIAL_MATRIX) { 5065 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5066 aloc[0] = *A_loc; 5067 } 5068 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5069 *A_loc = aloc[0]; 5070 ierr = PetscFree(aloc);CHKERRQ(ierr); 5071 if (!row) { 5072 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5073 } 5074 if (!col) { 5075 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5076 } 5077 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5078 PetscFunctionReturn(0); 5079 } 5080 5081 #undef __FUNCT__ 5082 #define __FUNCT__ "MatGetBrowsOfAcols" 5083 /*@C 5084 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5085 5086 Collective on Mat 5087 5088 Input Parameters: 5089 + A,B - the matrices in mpiaij format 5090 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5091 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5092 5093 Output Parameter: 5094 + rowb, colb - index sets of rows and columns of B to extract 5095 - B_seq - the sequential matrix generated 5096 5097 Level: developer 5098 5099 @*/ 5100 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5101 { 5102 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5103 PetscErrorCode ierr; 5104 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5105 IS isrowb,iscolb; 5106 Mat *bseq=NULL; 5107 5108 PetscFunctionBegin; 5109 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5110 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); 5111 } 5112 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5113 5114 if (scall == MAT_INITIAL_MATRIX) { 5115 start = A->cmap->rstart; 5116 cmap = a->garray; 5117 nzA = a->A->cmap->n; 5118 nzB = a->B->cmap->n; 5119 ierr = PetscMalloc1((nzA+nzB), &idx);CHKERRQ(ierr); 5120 ncols = 0; 5121 for (i=0; i<nzB; i++) { /* row < local row index */ 5122 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5123 else break; 5124 } 5125 imark = i; 5126 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5127 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5128 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5129 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5130 } else { 5131 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5132 isrowb = *rowb; iscolb = *colb; 5133 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5134 bseq[0] = *B_seq; 5135 } 5136 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5137 *B_seq = bseq[0]; 5138 ierr = PetscFree(bseq);CHKERRQ(ierr); 5139 if (!rowb) { 5140 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5141 } else { 5142 *rowb = isrowb; 5143 } 5144 if (!colb) { 5145 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5146 } else { 5147 *colb = iscolb; 5148 } 5149 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5150 PetscFunctionReturn(0); 5151 } 5152 5153 #undef __FUNCT__ 5154 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5155 /* 5156 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5157 of the OFF-DIAGONAL portion of local A 5158 5159 Collective on Mat 5160 5161 Input Parameters: 5162 + A,B - the matrices in mpiaij format 5163 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5164 5165 Output Parameter: 5166 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5167 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5168 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5169 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5170 5171 Level: developer 5172 5173 */ 5174 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5175 { 5176 VecScatter_MPI_General *gen_to,*gen_from; 5177 PetscErrorCode ierr; 5178 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5179 Mat_SeqAIJ *b_oth; 5180 VecScatter ctx =a->Mvctx; 5181 MPI_Comm comm; 5182 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5183 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5184 PetscScalar *rvalues,*svalues; 5185 MatScalar *b_otha,*bufa,*bufA; 5186 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5187 MPI_Request *rwaits = NULL,*swaits = NULL; 5188 MPI_Status *sstatus,rstatus; 5189 PetscMPIInt jj,size; 5190 PetscInt *cols,sbs,rbs; 5191 PetscScalar *vals; 5192 5193 PetscFunctionBegin; 5194 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5195 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5196 if (size == 1) PetscFunctionReturn(0); 5197 5198 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5199 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); 5200 } 5201 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5202 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5203 5204 gen_to = (VecScatter_MPI_General*)ctx->todata; 5205 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5206 rvalues = gen_from->values; /* holds the length of receiving row */ 5207 svalues = gen_to->values; /* holds the length of sending row */ 5208 nrecvs = gen_from->n; 5209 nsends = gen_to->n; 5210 5211 ierr = PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);CHKERRQ(ierr); 5212 srow = gen_to->indices; /* local row index to be sent */ 5213 sstarts = gen_to->starts; 5214 sprocs = gen_to->procs; 5215 sstatus = gen_to->sstatus; 5216 sbs = gen_to->bs; 5217 rstarts = gen_from->starts; 5218 rprocs = gen_from->procs; 5219 rbs = gen_from->bs; 5220 5221 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5222 if (scall == MAT_INITIAL_MATRIX) { 5223 /* i-array */ 5224 /*---------*/ 5225 /* post receives */ 5226 for (i=0; i<nrecvs; i++) { 5227 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5228 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5229 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5230 } 5231 5232 /* pack the outgoing message */ 5233 ierr = PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);CHKERRQ(ierr); 5234 5235 sstartsj[0] = 0; 5236 rstartsj[0] = 0; 5237 len = 0; /* total length of j or a array to be sent */ 5238 k = 0; 5239 for (i=0; i<nsends; i++) { 5240 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5241 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5242 for (j=0; j<nrows; j++) { 5243 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5244 for (l=0; l<sbs; l++) { 5245 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5246 5247 rowlen[j*sbs+l] = ncols; 5248 5249 len += ncols; 5250 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5251 } 5252 k++; 5253 } 5254 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5255 5256 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5257 } 5258 /* recvs and sends of i-array are completed */ 5259 i = nrecvs; 5260 while (i--) { 5261 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5262 } 5263 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5264 5265 /* allocate buffers for sending j and a arrays */ 5266 ierr = PetscMalloc1((len+1),&bufj);CHKERRQ(ierr); 5267 ierr = PetscMalloc1((len+1),&bufa);CHKERRQ(ierr); 5268 5269 /* create i-array of B_oth */ 5270 ierr = PetscMalloc1((aBn+2),&b_othi);CHKERRQ(ierr); 5271 5272 b_othi[0] = 0; 5273 len = 0; /* total length of j or a array to be received */ 5274 k = 0; 5275 for (i=0; i<nrecvs; i++) { 5276 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5277 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5278 for (j=0; j<nrows; j++) { 5279 b_othi[k+1] = b_othi[k] + rowlen[j]; 5280 len += rowlen[j]; k++; 5281 } 5282 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5283 } 5284 5285 /* allocate space for j and a arrrays of B_oth */ 5286 ierr = PetscMalloc1((b_othi[aBn]+1),&b_othj);CHKERRQ(ierr); 5287 ierr = PetscMalloc1((b_othi[aBn]+1),&b_otha);CHKERRQ(ierr); 5288 5289 /* j-array */ 5290 /*---------*/ 5291 /* post receives of j-array */ 5292 for (i=0; i<nrecvs; i++) { 5293 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5294 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5295 } 5296 5297 /* pack the outgoing message j-array */ 5298 k = 0; 5299 for (i=0; i<nsends; i++) { 5300 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5301 bufJ = bufj+sstartsj[i]; 5302 for (j=0; j<nrows; j++) { 5303 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5304 for (ll=0; ll<sbs; ll++) { 5305 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5306 for (l=0; l<ncols; l++) { 5307 *bufJ++ = cols[l]; 5308 } 5309 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5310 } 5311 } 5312 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5313 } 5314 5315 /* recvs and sends of j-array are completed */ 5316 i = nrecvs; 5317 while (i--) { 5318 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5319 } 5320 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5321 } else if (scall == MAT_REUSE_MATRIX) { 5322 sstartsj = *startsj_s; 5323 rstartsj = *startsj_r; 5324 bufa = *bufa_ptr; 5325 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5326 b_otha = b_oth->a; 5327 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5328 5329 /* a-array */ 5330 /*---------*/ 5331 /* post receives of a-array */ 5332 for (i=0; i<nrecvs; i++) { 5333 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5334 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5335 } 5336 5337 /* pack the outgoing message a-array */ 5338 k = 0; 5339 for (i=0; i<nsends; i++) { 5340 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5341 bufA = bufa+sstartsj[i]; 5342 for (j=0; j<nrows; j++) { 5343 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5344 for (ll=0; ll<sbs; ll++) { 5345 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5346 for (l=0; l<ncols; l++) { 5347 *bufA++ = vals[l]; 5348 } 5349 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5350 } 5351 } 5352 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5353 } 5354 /* recvs and sends of a-array are completed */ 5355 i = nrecvs; 5356 while (i--) { 5357 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5358 } 5359 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5360 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5361 5362 if (scall == MAT_INITIAL_MATRIX) { 5363 /* put together the new matrix */ 5364 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5365 5366 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5367 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5368 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5369 b_oth->free_a = PETSC_TRUE; 5370 b_oth->free_ij = PETSC_TRUE; 5371 b_oth->nonew = 0; 5372 5373 ierr = PetscFree(bufj);CHKERRQ(ierr); 5374 if (!startsj_s || !bufa_ptr) { 5375 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5376 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5377 } else { 5378 *startsj_s = sstartsj; 5379 *startsj_r = rstartsj; 5380 *bufa_ptr = bufa; 5381 } 5382 } 5383 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5384 PetscFunctionReturn(0); 5385 } 5386 5387 #undef __FUNCT__ 5388 #define __FUNCT__ "MatGetCommunicationStructs" 5389 /*@C 5390 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5391 5392 Not Collective 5393 5394 Input Parameters: 5395 . A - The matrix in mpiaij format 5396 5397 Output Parameter: 5398 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5399 . colmap - A map from global column index to local index into lvec 5400 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5401 5402 Level: developer 5403 5404 @*/ 5405 #if defined(PETSC_USE_CTABLE) 5406 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5407 #else 5408 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5409 #endif 5410 { 5411 Mat_MPIAIJ *a; 5412 5413 PetscFunctionBegin; 5414 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5415 PetscValidPointer(lvec, 2); 5416 PetscValidPointer(colmap, 3); 5417 PetscValidPointer(multScatter, 4); 5418 a = (Mat_MPIAIJ*) A->data; 5419 if (lvec) *lvec = a->lvec; 5420 if (colmap) *colmap = a->colmap; 5421 if (multScatter) *multScatter = a->Mvctx; 5422 PetscFunctionReturn(0); 5423 } 5424 5425 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5426 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5427 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5428 #if defined(PETSC_HAVE_ELEMENTAL) 5429 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 5430 #endif 5431 5432 #undef __FUNCT__ 5433 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5434 /* 5435 Computes (B'*A')' since computing B*A directly is untenable 5436 5437 n p p 5438 ( ) ( ) ( ) 5439 m ( A ) * n ( B ) = m ( C ) 5440 ( ) ( ) ( ) 5441 5442 */ 5443 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5444 { 5445 PetscErrorCode ierr; 5446 Mat At,Bt,Ct; 5447 5448 PetscFunctionBegin; 5449 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5450 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5451 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5452 ierr = MatDestroy(&At);CHKERRQ(ierr); 5453 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5454 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5455 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5456 PetscFunctionReturn(0); 5457 } 5458 5459 #undef __FUNCT__ 5460 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5461 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5462 { 5463 PetscErrorCode ierr; 5464 PetscInt m=A->rmap->n,n=B->cmap->n; 5465 Mat Cmat; 5466 5467 PetscFunctionBegin; 5468 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); 5469 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5470 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5471 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 5472 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5473 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5474 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5475 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5476 5477 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5478 5479 *C = Cmat; 5480 PetscFunctionReturn(0); 5481 } 5482 5483 /* ----------------------------------------------------------------*/ 5484 #undef __FUNCT__ 5485 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5486 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5487 { 5488 PetscErrorCode ierr; 5489 5490 PetscFunctionBegin; 5491 if (scall == MAT_INITIAL_MATRIX) { 5492 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5493 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5494 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5495 } 5496 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5497 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5498 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5499 PetscFunctionReturn(0); 5500 } 5501 5502 #if defined(PETSC_HAVE_MUMPS) 5503 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5504 #endif 5505 #if defined(PETSC_HAVE_PASTIX) 5506 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5507 #endif 5508 #if defined(PETSC_HAVE_SUPERLU_DIST) 5509 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5510 #endif 5511 #if defined(PETSC_HAVE_CLIQUE) 5512 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5513 #endif 5514 5515 /*MC 5516 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5517 5518 Options Database Keys: 5519 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5520 5521 Level: beginner 5522 5523 .seealso: MatCreateAIJ() 5524 M*/ 5525 5526 #undef __FUNCT__ 5527 #define __FUNCT__ "MatCreate_MPIAIJ" 5528 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5529 { 5530 Mat_MPIAIJ *b; 5531 PetscErrorCode ierr; 5532 PetscMPIInt size; 5533 5534 PetscFunctionBegin; 5535 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5536 5537 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 5538 B->data = (void*)b; 5539 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5540 B->assembled = PETSC_FALSE; 5541 B->insertmode = NOT_SET_VALUES; 5542 b->size = size; 5543 5544 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5545 5546 /* build cache for off array entries formed */ 5547 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5548 5549 b->donotstash = PETSC_FALSE; 5550 b->colmap = 0; 5551 b->garray = 0; 5552 b->roworiented = PETSC_TRUE; 5553 5554 /* stuff used for matrix vector multiply */ 5555 b->lvec = NULL; 5556 b->Mvctx = NULL; 5557 5558 /* stuff for MatGetRow() */ 5559 b->rowindices = 0; 5560 b->rowvalues = 0; 5561 b->getrowactive = PETSC_FALSE; 5562 5563 /* flexible pointer used in CUSP/CUSPARSE classes */ 5564 b->spptr = NULL; 5565 5566 #if defined(PETSC_HAVE_MUMPS) 5567 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5568 #endif 5569 #if defined(PETSC_HAVE_PASTIX) 5570 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5571 #endif 5572 #if defined(PETSC_HAVE_SUPERLU_DIST) 5573 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5574 #endif 5575 #if defined(PETSC_HAVE_CLIQUE) 5576 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5577 #endif 5578 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5579 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5580 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5581 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5582 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5583 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5584 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5585 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5586 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5587 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5588 #if defined(PETSC_HAVE_ELEMENTAL) 5589 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);CHKERRQ(ierr); 5590 #endif 5591 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5592 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5593 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5594 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5595 PetscFunctionReturn(0); 5596 } 5597 5598 #undef __FUNCT__ 5599 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5600 /*@ 5601 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5602 and "off-diagonal" part of the matrix in CSR format. 5603 5604 Collective on MPI_Comm 5605 5606 Input Parameters: 5607 + comm - MPI communicator 5608 . m - number of local rows (Cannot be PETSC_DECIDE) 5609 . n - This value should be the same as the local size used in creating the 5610 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5611 calculated if N is given) For square matrices n is almost always m. 5612 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5613 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5614 . i - row indices for "diagonal" portion of matrix 5615 . j - column indices 5616 . a - matrix values 5617 . oi - row indices for "off-diagonal" portion of matrix 5618 . oj - column indices 5619 - oa - matrix values 5620 5621 Output Parameter: 5622 . mat - the matrix 5623 5624 Level: advanced 5625 5626 Notes: 5627 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5628 must free the arrays once the matrix has been destroyed and not before. 5629 5630 The i and j indices are 0 based 5631 5632 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5633 5634 This sets local rows and cannot be used to set off-processor values. 5635 5636 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5637 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5638 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5639 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5640 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5641 communication if it is known that only local entries will be set. 5642 5643 .keywords: matrix, aij, compressed row, sparse, parallel 5644 5645 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5646 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5647 @*/ 5648 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) 5649 { 5650 PetscErrorCode ierr; 5651 Mat_MPIAIJ *maij; 5652 5653 PetscFunctionBegin; 5654 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5655 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5656 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5657 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5658 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5659 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5660 maij = (Mat_MPIAIJ*) (*mat)->data; 5661 5662 (*mat)->preallocated = PETSC_TRUE; 5663 5664 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5665 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5666 5667 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5668 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5669 5670 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5671 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5672 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5673 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5674 5675 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5676 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5677 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5678 PetscFunctionReturn(0); 5679 } 5680 5681 /* 5682 Special version for direct calls from Fortran 5683 */ 5684 #include <petsc-private/fortranimpl.h> 5685 5686 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5687 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5688 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5689 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5690 #endif 5691 5692 /* Change these macros so can be used in void function */ 5693 #undef CHKERRQ 5694 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5695 #undef SETERRQ2 5696 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5697 #undef SETERRQ3 5698 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5699 #undef SETERRQ 5700 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5701 5702 #undef __FUNCT__ 5703 #define __FUNCT__ "matsetvaluesmpiaij_" 5704 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) 5705 { 5706 Mat mat = *mmat; 5707 PetscInt m = *mm, n = *mn; 5708 InsertMode addv = *maddv; 5709 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5710 PetscScalar value; 5711 PetscErrorCode ierr; 5712 5713 MatCheckPreallocated(mat,1); 5714 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5715 5716 #if defined(PETSC_USE_DEBUG) 5717 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5718 #endif 5719 { 5720 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5721 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5722 PetscBool roworiented = aij->roworiented; 5723 5724 /* Some Variables required in the macro */ 5725 Mat A = aij->A; 5726 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5727 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5728 MatScalar *aa = a->a; 5729 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5730 Mat B = aij->B; 5731 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5732 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5733 MatScalar *ba = b->a; 5734 5735 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5736 PetscInt nonew = a->nonew; 5737 MatScalar *ap1,*ap2; 5738 5739 PetscFunctionBegin; 5740 for (i=0; i<m; i++) { 5741 if (im[i] < 0) continue; 5742 #if defined(PETSC_USE_DEBUG) 5743 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); 5744 #endif 5745 if (im[i] >= rstart && im[i] < rend) { 5746 row = im[i] - rstart; 5747 lastcol1 = -1; 5748 rp1 = aj + ai[row]; 5749 ap1 = aa + ai[row]; 5750 rmax1 = aimax[row]; 5751 nrow1 = ailen[row]; 5752 low1 = 0; 5753 high1 = nrow1; 5754 lastcol2 = -1; 5755 rp2 = bj + bi[row]; 5756 ap2 = ba + bi[row]; 5757 rmax2 = bimax[row]; 5758 nrow2 = bilen[row]; 5759 low2 = 0; 5760 high2 = nrow2; 5761 5762 for (j=0; j<n; j++) { 5763 if (roworiented) value = v[i*n+j]; 5764 else value = v[i+j*m]; 5765 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5766 if (in[j] >= cstart && in[j] < cend) { 5767 col = in[j] - cstart; 5768 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5769 } else if (in[j] < 0) continue; 5770 #if defined(PETSC_USE_DEBUG) 5771 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); 5772 #endif 5773 else { 5774 if (mat->was_assembled) { 5775 if (!aij->colmap) { 5776 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5777 } 5778 #if defined(PETSC_USE_CTABLE) 5779 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5780 col--; 5781 #else 5782 col = aij->colmap[in[j]] - 1; 5783 #endif 5784 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5785 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5786 col = in[j]; 5787 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5788 B = aij->B; 5789 b = (Mat_SeqAIJ*)B->data; 5790 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5791 rp2 = bj + bi[row]; 5792 ap2 = ba + bi[row]; 5793 rmax2 = bimax[row]; 5794 nrow2 = bilen[row]; 5795 low2 = 0; 5796 high2 = nrow2; 5797 bm = aij->B->rmap->n; 5798 ba = b->a; 5799 } 5800 } else col = in[j]; 5801 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5802 } 5803 } 5804 } else if (!aij->donotstash) { 5805 if (roworiented) { 5806 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5807 } else { 5808 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5809 } 5810 } 5811 } 5812 } 5813 PetscFunctionReturnVoid(); 5814 } 5815 5816