1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petscblaslapack.h> 4 5 /*MC 6 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 7 8 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 9 and MATMPIAIJ otherwise. As a result, for single process communicators, 10 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 11 for communicators controlling multiple processes. It is recommended that you call both of 12 the above preallocation routines for simplicity. 13 14 Options Database Keys: 15 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 16 17 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 18 enough exist. 19 20 Level: beginner 21 22 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 23 M*/ 24 25 /*MC 26 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 27 28 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 29 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 30 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 31 for communicators controlling multiple processes. It is recommended that you call both of 32 the above preallocation routines for simplicity. 33 34 Options Database Keys: 35 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 36 37 Level: beginner 38 39 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 40 M*/ 41 42 #undef __FUNCT__ 43 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 44 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 45 { 46 PetscErrorCode ierr; 47 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 48 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 49 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 50 const PetscInt *ia,*ib; 51 const MatScalar *aa,*bb; 52 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 53 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 54 55 PetscFunctionBegin; 56 *keptrows = 0; 57 ia = a->i; 58 ib = b->i; 59 for (i=0; i<m; i++) { 60 na = ia[i+1] - ia[i]; 61 nb = ib[i+1] - ib[i]; 62 if (!na && !nb) { 63 cnt++; 64 goto ok1; 65 } 66 aa = a->a + ia[i]; 67 for (j=0; j<na; j++) { 68 if (aa[j] != 0.0) goto ok1; 69 } 70 bb = b->a + ib[i]; 71 for (j=0; j <nb; j++) { 72 if (bb[j] != 0.0) goto ok1; 73 } 74 cnt++; 75 ok1:; 76 } 77 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,((PetscObject)M)->comm);CHKERRQ(ierr); 78 if (!n0rows) PetscFunctionReturn(0); 79 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 80 cnt = 0; 81 for (i=0; i<m; i++) { 82 na = ia[i+1] - ia[i]; 83 nb = ib[i+1] - ib[i]; 84 if (!na && !nb) continue; 85 aa = a->a + ia[i]; 86 for (j=0; j<na;j++) { 87 if (aa[j] != 0.0) { 88 rows[cnt++] = rstart + i; 89 goto ok2; 90 } 91 } 92 bb = b->a + ib[i]; 93 for (j=0; j<nb; j++) { 94 if (bb[j] != 0.0) { 95 rows[cnt++] = rstart + i; 96 goto ok2; 97 } 98 } 99 ok2:; 100 } 101 ierr = ISCreateGeneral(((PetscObject)M)->comm,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 102 PetscFunctionReturn(0); 103 } 104 105 #undef __FUNCT__ 106 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 107 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 108 { 109 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 110 PetscErrorCode ierr; 111 PetscInt i,rstart,nrows,*rows; 112 113 PetscFunctionBegin; 114 *zrows = PETSC_NULL; 115 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 116 ierr = MatGetOwnershipRange(M,&rstart,PETSC_NULL);CHKERRQ(ierr); 117 for (i=0; i<nrows; i++) rows[i] += rstart; 118 ierr = ISCreateGeneral(((PetscObject)M)->comm,nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 119 PetscFunctionReturn(0); 120 } 121 122 #undef __FUNCT__ 123 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 124 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 125 { 126 PetscErrorCode ierr; 127 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 128 PetscInt i,n,*garray = aij->garray; 129 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 130 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 131 PetscReal *work; 132 133 PetscFunctionBegin; 134 ierr = MatGetSize(A,PETSC_NULL,&n);CHKERRQ(ierr); 135 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 136 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 137 if (type == NORM_2) { 138 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 139 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 140 } 141 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 142 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 143 } 144 } else if (type == NORM_1) { 145 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 146 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 147 } 148 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 149 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 150 } 151 } else if (type == NORM_INFINITY) { 152 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 153 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 154 } 155 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 156 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 157 } 158 159 } else SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 160 if (type == NORM_INFINITY) { 161 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 162 } else { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 164 } 165 ierr = PetscFree(work);CHKERRQ(ierr); 166 if (type == NORM_2) { 167 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 168 } 169 PetscFunctionReturn(0); 170 } 171 172 #undef __FUNCT__ 173 #define __FUNCT__ "MatDistribute_MPIAIJ" 174 /* 175 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 176 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 177 178 Only for square matrices 179 */ 180 PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 181 { 182 PetscMPIInt rank,size; 183 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 184 PetscErrorCode ierr; 185 Mat mat; 186 Mat_SeqAIJ *gmata; 187 PetscMPIInt tag; 188 MPI_Status status; 189 PetscBool aij; 190 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 191 192 PetscFunctionBegin; 193 CHKMEMQ; 194 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 195 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 196 if (!rank) { 197 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 198 if (!aij) SETERRQ1(((PetscObject)gmat)->comm,PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 199 } 200 if (reuse == MAT_INITIAL_MATRIX) { 201 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 202 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 203 if (!rank) { 204 bses[0] = gmat->rmap->bs; 205 bses[1] = gmat->cmap->bs; 206 } 207 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 208 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 209 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 210 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 211 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 212 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 213 rowners[0] = 0; 214 for (i=2; i<=size; i++) { 215 rowners[i] += rowners[i-1]; 216 } 217 rstart = rowners[rank]; 218 rend = rowners[rank+1]; 219 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 220 if (!rank) { 221 gmata = (Mat_SeqAIJ*) gmat->data; 222 /* send row lengths to all processors */ 223 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 224 for (i=1; i<size; i++) { 225 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 226 } 227 /* determine number diagonal and off-diagonal counts */ 228 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 229 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 230 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 231 jj = 0; 232 for (i=0; i<m; i++) { 233 for (j=0; j<dlens[i]; j++) { 234 if (gmata->j[jj] < rstart) ld[i]++; 235 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 236 jj++; 237 } 238 } 239 /* send column indices to other processes */ 240 for (i=1; i<size; i++) { 241 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 242 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 243 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 244 } 245 246 /* send numerical values to other processes */ 247 for (i=1; i<size; i++) { 248 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 249 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 250 } 251 gmataa = gmata->a; 252 gmataj = gmata->j; 253 254 } else { 255 /* receive row lengths */ 256 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 257 /* receive column indices */ 258 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 260 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 /* determine number diagonal and off-diagonal counts */ 262 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 263 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 264 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 265 jj = 0; 266 for (i=0; i<m; i++) { 267 for (j=0; j<dlens[i]; j++) { 268 if (gmataj[jj] < rstart) ld[i]++; 269 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 270 jj++; 271 } 272 } 273 /* receive numerical values */ 274 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 275 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 276 } 277 /* set preallocation */ 278 for (i=0; i<m; i++) { 279 dlens[i] -= olens[i]; 280 } 281 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 282 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 283 284 for (i=0; i<m; i++) { 285 dlens[i] += olens[i]; 286 } 287 cnt = 0; 288 for (i=0; i<m; i++) { 289 row = rstart + i; 290 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 291 cnt += dlens[i]; 292 } 293 if (rank) { 294 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 295 } 296 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 297 ierr = PetscFree(rowners);CHKERRQ(ierr); 298 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 299 *inmat = mat; 300 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 301 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 302 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 303 mat = *inmat; 304 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 305 if (!rank) { 306 /* send numerical values to other processes */ 307 gmata = (Mat_SeqAIJ*) gmat->data; 308 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 309 gmataa = gmata->a; 310 for (i=1; i<size; i++) { 311 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 312 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 313 } 314 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 315 } else { 316 /* receive numerical values from process 0*/ 317 nz = Ad->nz + Ao->nz; 318 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 319 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 320 } 321 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 322 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 323 ad = Ad->a; 324 ao = Ao->a; 325 if (mat->rmap->n) { 326 i = 0; 327 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 328 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 329 } 330 for (i=1; i<mat->rmap->n; i++) { 331 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; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 i--; 335 if (mat->rmap->n) { 336 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 337 } 338 if (rank) { 339 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 340 } 341 } 342 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 343 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 344 CHKMEMQ; 345 PetscFunctionReturn(0); 346 } 347 348 /* 349 Local utility routine that creates a mapping from the global column 350 number to the local number in the off-diagonal part of the local 351 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 352 a slightly higher hash table cost; without it it is not scalable (each processor 353 has an order N integer array but is fast to acess. 354 */ 355 #undef __FUNCT__ 356 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 357 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 358 { 359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 360 PetscErrorCode ierr; 361 PetscInt n = aij->B->cmap->n,i; 362 363 PetscFunctionBegin; 364 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 365 #if defined (PETSC_USE_CTABLE) 366 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 367 for (i=0; i<n; i++){ 368 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 369 } 370 #else 371 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 372 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 373 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 374 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 375 #endif 376 PetscFunctionReturn(0); 377 } 378 379 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 380 { \ 381 if (col <= lastcol1) low1 = 0; else high1 = nrow1; \ 382 lastcol1 = col;\ 383 while (high1-low1 > 5) { \ 384 t = (low1+high1)/2; \ 385 if (rp1[t] > col) high1 = t; \ 386 else low1 = t; \ 387 } \ 388 for (_i=low1; _i<high1; _i++) { \ 389 if (rp1[_i] > col) break; \ 390 if (rp1[_i] == col) { \ 391 if (addv == ADD_VALUES) ap1[_i] += value; \ 392 else ap1[_i] = value; \ 393 goto a_noinsert; \ 394 } \ 395 } \ 396 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 397 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 398 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 399 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 400 N = nrow1++ - 1; a->nz++; high1++; \ 401 /* shift up all the later entries in this row */ \ 402 for (ii=N; ii>=_i; ii--) { \ 403 rp1[ii+1] = rp1[ii]; \ 404 ap1[ii+1] = ap1[ii]; \ 405 } \ 406 rp1[_i] = col; \ 407 ap1[_i] = value; \ 408 a_noinsert: ; \ 409 ailen[row] = nrow1; \ 410 } 411 412 413 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 414 { \ 415 if (col <= lastcol2) low2 = 0; else high2 = nrow2; \ 416 lastcol2 = col;\ 417 while (high2-low2 > 5) { \ 418 t = (low2+high2)/2; \ 419 if (rp2[t] > col) high2 = t; \ 420 else low2 = t; \ 421 } \ 422 for (_i=low2; _i<high2; _i++) { \ 423 if (rp2[_i] > col) break; \ 424 if (rp2[_i] == col) { \ 425 if (addv == ADD_VALUES) ap2[_i] += value; \ 426 else ap2[_i] = value; \ 427 goto b_noinsert; \ 428 } \ 429 } \ 430 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 431 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 432 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 433 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 434 N = nrow2++ - 1; b->nz++; high2++; \ 435 /* shift up all the later entries in this row */ \ 436 for (ii=N; ii>=_i; ii--) { \ 437 rp2[ii+1] = rp2[ii]; \ 438 ap2[ii+1] = ap2[ii]; \ 439 } \ 440 rp2[_i] = col; \ 441 ap2[_i] = value; \ 442 b_noinsert: ; \ 443 bilen[row] = nrow2; \ 444 } 445 446 #undef __FUNCT__ 447 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 448 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 449 { 450 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 451 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 452 PetscErrorCode ierr; 453 PetscInt l,*garray = mat->garray,diag; 454 455 PetscFunctionBegin; 456 /* code only works for square matrices A */ 457 458 /* find size of row to the left of the diagonal part */ 459 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 460 row = row - diag; 461 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 462 if (garray[b->j[b->i[row]+l]] > diag) break; 463 } 464 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 465 466 /* diagonal part */ 467 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 468 469 /* right of diagonal part */ 470 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); 471 PetscFunctionReturn(0); 472 } 473 474 #undef __FUNCT__ 475 #define __FUNCT__ "MatSetValues_MPIAIJ" 476 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 477 { 478 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 479 PetscScalar value; 480 PetscErrorCode ierr; 481 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 482 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 483 PetscBool roworiented = aij->roworiented; 484 485 /* Some Variables required in the macro */ 486 Mat A = aij->A; 487 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 488 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 489 MatScalar *aa = a->a; 490 PetscBool ignorezeroentries = a->ignorezeroentries; 491 Mat B = aij->B; 492 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 493 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 494 MatScalar *ba = b->a; 495 496 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 497 PetscInt nonew; 498 MatScalar *ap1,*ap2; 499 500 PetscFunctionBegin; 501 if (v) PetscValidScalarPointer(v,6); 502 for (i=0; i<m; i++) { 503 if (im[i] < 0) continue; 504 #if defined(PETSC_USE_DEBUG) 505 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); 506 #endif 507 if (im[i] >= rstart && im[i] < rend) { 508 row = im[i] - rstart; 509 lastcol1 = -1; 510 rp1 = aj + ai[row]; 511 ap1 = aa + ai[row]; 512 rmax1 = aimax[row]; 513 nrow1 = ailen[row]; 514 low1 = 0; 515 high1 = nrow1; 516 lastcol2 = -1; 517 rp2 = bj + bi[row]; 518 ap2 = ba + bi[row]; 519 rmax2 = bimax[row]; 520 nrow2 = bilen[row]; 521 low2 = 0; 522 high2 = nrow2; 523 524 for (j=0; j<n; j++) { 525 if (v) {if (roworiented) value = v[i*n+j]; else value = v[i+j*m];} else value = 0.0; 526 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 527 if (in[j] >= cstart && in[j] < cend){ 528 col = in[j] - cstart; 529 nonew = a->nonew; 530 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 531 } else if (in[j] < 0) continue; 532 #if defined(PETSC_USE_DEBUG) 533 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); 534 #endif 535 else { 536 if (mat->was_assembled) { 537 if (!aij->colmap) { 538 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 539 } 540 #if defined (PETSC_USE_CTABLE) 541 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 542 col--; 543 #else 544 col = aij->colmap[in[j]] - 1; 545 #endif 546 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 547 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 548 col = in[j]; 549 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 550 B = aij->B; 551 b = (Mat_SeqAIJ*)B->data; 552 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 553 rp2 = bj + bi[row]; 554 ap2 = ba + bi[row]; 555 rmax2 = bimax[row]; 556 nrow2 = bilen[row]; 557 low2 = 0; 558 high2 = nrow2; 559 bm = aij->B->rmap->n; 560 ba = b->a; 561 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 562 } else col = in[j]; 563 nonew = b->nonew; 564 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 565 } 566 } 567 } else { 568 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]); 569 if (!aij->donotstash) { 570 mat->assembled = PETSC_FALSE; 571 if (roworiented) { 572 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 573 } else { 574 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 575 } 576 } 577 } 578 } 579 PetscFunctionReturn(0); 580 } 581 582 #undef __FUNCT__ 583 #define __FUNCT__ "MatGetValues_MPIAIJ" 584 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 585 { 586 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 587 PetscErrorCode ierr; 588 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 589 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 590 591 PetscFunctionBegin; 592 for (i=0; i<m; i++) { 593 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 594 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); 595 if (idxm[i] >= rstart && idxm[i] < rend) { 596 row = idxm[i] - rstart; 597 for (j=0; j<n; j++) { 598 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 599 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); 600 if (idxn[j] >= cstart && idxn[j] < cend){ 601 col = idxn[j] - cstart; 602 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 603 } else { 604 if (!aij->colmap) { 605 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 606 } 607 #if defined (PETSC_USE_CTABLE) 608 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 609 col --; 610 #else 611 col = aij->colmap[idxn[j]] - 1; 612 #endif 613 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 614 else { 615 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 616 } 617 } 618 } 619 } else { 620 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 621 } 622 } 623 PetscFunctionReturn(0); 624 } 625 626 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 627 628 #undef __FUNCT__ 629 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 630 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 631 { 632 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 633 PetscErrorCode ierr; 634 PetscInt nstash,reallocs; 635 InsertMode addv; 636 637 PetscFunctionBegin; 638 if (aij->donotstash || mat->nooffprocentries) { 639 PetscFunctionReturn(0); 640 } 641 642 /* make sure all processors are either in INSERTMODE or ADDMODE */ 643 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,((PetscObject)mat)->comm);CHKERRQ(ierr); 644 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 645 mat->insertmode = addv; /* in case this processor had no cache */ 646 647 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 648 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 649 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 650 PetscFunctionReturn(0); 651 } 652 653 #undef __FUNCT__ 654 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 655 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 656 { 657 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 658 Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data; 659 PetscErrorCode ierr; 660 PetscMPIInt n; 661 PetscInt i,j,rstart,ncols,flg; 662 PetscInt *row,*col; 663 PetscBool other_disassembled; 664 PetscScalar *val; 665 InsertMode addv = mat->insertmode; 666 667 /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */ 668 PetscFunctionBegin; 669 if (!aij->donotstash && !mat->nooffprocentries) { 670 while (1) { 671 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 672 if (!flg) break; 673 674 for (i=0; i<n;) { 675 /* Now identify the consecutive vals belonging to the same row */ 676 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 677 if (j < n) ncols = j-i; 678 else ncols = n-i; 679 /* Now assemble all these values with a single function call */ 680 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 681 i = j; 682 } 683 } 684 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 685 } 686 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 687 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 688 689 /* determine if any processor has disassembled, if so we must 690 also disassemble ourselfs, in order that we may reassemble. */ 691 /* 692 if nonzero structure of submatrix B cannot change then we know that 693 no processor disassembled thus we can skip this stuff 694 */ 695 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 696 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,((PetscObject)mat)->comm);CHKERRQ(ierr); 697 if (mat->was_assembled && !other_disassembled) { 698 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 699 } 700 } 701 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 702 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 703 } 704 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 705 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 706 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 707 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 708 709 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 710 aij->rowvalues = 0; 711 712 /* used by MatAXPY() */ 713 a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 714 a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 715 716 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 717 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 718 PetscFunctionReturn(0); 719 } 720 721 #undef __FUNCT__ 722 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 723 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 724 { 725 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 726 PetscErrorCode ierr; 727 728 PetscFunctionBegin; 729 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 730 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 731 PetscFunctionReturn(0); 732 } 733 734 #undef __FUNCT__ 735 #define __FUNCT__ "MatZeroRows_MPIAIJ" 736 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 737 { 738 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 739 PetscErrorCode ierr; 740 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 741 PetscInt i,*owners = A->rmap->range; 742 PetscInt *nprocs,j,idx,nsends,row; 743 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 744 PetscInt *rvalues,count,base,slen,*source; 745 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 746 MPI_Comm comm = ((PetscObject)A)->comm; 747 MPI_Request *send_waits,*recv_waits; 748 MPI_Status recv_status,*send_status; 749 const PetscScalar *xx; 750 PetscScalar *bb; 751 #if defined(PETSC_DEBUG) 752 PetscBool found = PETSC_FALSE; 753 #endif 754 755 PetscFunctionBegin; 756 /* first count number of contributors to each processor */ 757 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 758 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 759 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 760 j = 0; 761 for (i=0; i<N; i++) { 762 if (lastidx > (idx = rows[i])) j = 0; 763 lastidx = idx; 764 for (; j<size; j++) { 765 if (idx >= owners[j] && idx < owners[j+1]) { 766 nprocs[2*j]++; 767 nprocs[2*j+1] = 1; 768 owner[i] = j; 769 #if defined(PETSC_DEBUG) 770 found = PETSC_TRUE; 771 #endif 772 break; 773 } 774 } 775 #if defined(PETSC_DEBUG) 776 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 777 found = PETSC_FALSE; 778 #endif 779 } 780 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 781 782 if (A->nooffproczerorows) { 783 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 784 nrecvs = nsends; 785 nmax = N; 786 } else { 787 /* inform other processors of number of messages and max length*/ 788 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 789 } 790 791 /* post receives: */ 792 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 793 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 794 for (i=0; i<nrecvs; i++) { 795 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 796 } 797 798 /* do sends: 799 1) starts[i] gives the starting index in svalues for stuff going to 800 the ith processor 801 */ 802 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 803 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 804 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 805 starts[0] = 0; 806 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 807 for (i=0; i<N; i++) { 808 svalues[starts[owner[i]]++] = rows[i]; 809 } 810 811 starts[0] = 0; 812 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 813 count = 0; 814 for (i=0; i<size; i++) { 815 if (nprocs[2*i+1]) { 816 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 817 } 818 } 819 ierr = PetscFree(starts);CHKERRQ(ierr); 820 821 base = owners[rank]; 822 823 /* wait on receives */ 824 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 825 count = nrecvs; slen = 0; 826 while (count) { 827 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 828 /* unpack receives into our local space */ 829 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 830 source[imdex] = recv_status.MPI_SOURCE; 831 lens[imdex] = n; 832 slen += n; 833 count--; 834 } 835 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 836 837 /* move the data into the send scatter */ 838 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 839 count = 0; 840 for (i=0; i<nrecvs; i++) { 841 values = rvalues + i*nmax; 842 for (j=0; j<lens[i]; j++) { 843 lrows[count++] = values[j] - base; 844 } 845 } 846 ierr = PetscFree(rvalues);CHKERRQ(ierr); 847 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 848 ierr = PetscFree(owner);CHKERRQ(ierr); 849 ierr = PetscFree(nprocs);CHKERRQ(ierr); 850 851 /* fix right hand side if needed */ 852 if (x && b) { 853 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 854 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 855 for (i=0; i<slen; i++) { 856 bb[lrows[i]] = diag*xx[lrows[i]]; 857 } 858 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 859 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 860 } 861 /* 862 Zero the required rows. If the "diagonal block" of the matrix 863 is square and the user wishes to set the diagonal we use separate 864 code so that MatSetValues() is not called for each diagonal allocating 865 new memory, thus calling lots of mallocs and slowing things down. 866 867 */ 868 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 869 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 870 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 871 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 872 } else if (diag != 0.0) { 873 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 874 if (((Mat_SeqAIJ*)l->A->data)->nonew) { 875 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\ 876 MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 877 } 878 for (i = 0; i < slen; i++) { 879 row = lrows[i] + rstart; 880 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 881 } 882 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 883 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 884 } else { 885 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 886 } 887 ierr = PetscFree(lrows);CHKERRQ(ierr); 888 889 /* wait on sends */ 890 if (nsends) { 891 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 892 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 893 ierr = PetscFree(send_status);CHKERRQ(ierr); 894 } 895 ierr = PetscFree(send_waits);CHKERRQ(ierr); 896 ierr = PetscFree(svalues);CHKERRQ(ierr); 897 PetscFunctionReturn(0); 898 } 899 900 #undef __FUNCT__ 901 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 902 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 903 { 904 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 905 PetscErrorCode ierr; 906 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 907 PetscInt i,*owners = A->rmap->range; 908 PetscInt *nprocs,j,idx,nsends; 909 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 910 PetscInt *rvalues,count,base,slen,*source; 911 PetscInt *lens,*lrows,*values,m; 912 MPI_Comm comm = ((PetscObject)A)->comm; 913 MPI_Request *send_waits,*recv_waits; 914 MPI_Status recv_status,*send_status; 915 const PetscScalar *xx; 916 PetscScalar *bb,*mask; 917 Vec xmask,lmask; 918 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 919 const PetscInt *aj, *ii,*ridx; 920 PetscScalar *aa; 921 #if defined(PETSC_DEBUG) 922 PetscBool found = PETSC_FALSE; 923 #endif 924 925 PetscFunctionBegin; 926 /* first count number of contributors to each processor */ 927 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 928 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 929 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 930 j = 0; 931 for (i=0; i<N; i++) { 932 if (lastidx > (idx = rows[i])) j = 0; 933 lastidx = idx; 934 for (; j<size; j++) { 935 if (idx >= owners[j] && idx < owners[j+1]) { 936 nprocs[2*j]++; 937 nprocs[2*j+1] = 1; 938 owner[i] = j; 939 #if defined(PETSC_DEBUG) 940 found = PETSC_TRUE; 941 #endif 942 break; 943 } 944 } 945 #if defined(PETSC_DEBUG) 946 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 947 found = PETSC_FALSE; 948 #endif 949 } 950 nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];} 951 952 /* inform other processors of number of messages and max length*/ 953 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 954 955 /* post receives: */ 956 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 957 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 958 for (i=0; i<nrecvs; i++) { 959 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 960 } 961 962 /* do sends: 963 1) starts[i] gives the starting index in svalues for stuff going to 964 the ith processor 965 */ 966 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 967 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 968 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 969 starts[0] = 0; 970 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 971 for (i=0; i<N; i++) { 972 svalues[starts[owner[i]]++] = rows[i]; 973 } 974 975 starts[0] = 0; 976 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];} 977 count = 0; 978 for (i=0; i<size; i++) { 979 if (nprocs[2*i+1]) { 980 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 981 } 982 } 983 ierr = PetscFree(starts);CHKERRQ(ierr); 984 985 base = owners[rank]; 986 987 /* wait on receives */ 988 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 989 count = nrecvs; slen = 0; 990 while (count) { 991 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 992 /* unpack receives into our local space */ 993 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 994 source[imdex] = recv_status.MPI_SOURCE; 995 lens[imdex] = n; 996 slen += n; 997 count--; 998 } 999 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1000 1001 /* move the data into the send scatter */ 1002 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1003 count = 0; 1004 for (i=0; i<nrecvs; i++) { 1005 values = rvalues + i*nmax; 1006 for (j=0; j<lens[i]; j++) { 1007 lrows[count++] = values[j] - base; 1008 } 1009 } 1010 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1011 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1012 ierr = PetscFree(owner);CHKERRQ(ierr); 1013 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1014 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1015 1016 /* zero diagonal part of matrix */ 1017 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1018 1019 /* handle off diagonal part of matrix */ 1020 ierr = MatGetVecs(A,&xmask,PETSC_NULL);CHKERRQ(ierr); 1021 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1022 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1023 for (i=0; i<slen; i++) { 1024 bb[lrows[i]] = 1; 1025 } 1026 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1027 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1028 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1030 if (x) { 1031 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1032 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1034 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1035 } 1036 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1037 1038 /* remove zeroed rows of off diagonal matrix */ 1039 ii = aij->i; 1040 for (i=0; i<slen; i++) { 1041 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1042 } 1043 1044 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1045 if (aij->compressedrow.use){ 1046 m = aij->compressedrow.nrows; 1047 ii = aij->compressedrow.i; 1048 ridx = aij->compressedrow.rindex; 1049 for (i=0; i<m; i++){ 1050 n = ii[i+1] - ii[i]; 1051 aj = aij->j + ii[i]; 1052 aa = aij->a + ii[i]; 1053 1054 for (j=0; j<n; j++) { 1055 if (PetscAbsScalar(mask[*aj])) { 1056 if (b) bb[*ridx] -= *aa*xx[*aj]; 1057 *aa = 0.0; 1058 } 1059 aa++; 1060 aj++; 1061 } 1062 ridx++; 1063 } 1064 } else { /* do not use compressed row format */ 1065 m = l->B->rmap->n; 1066 for (i=0; i<m; i++) { 1067 n = ii[i+1] - ii[i]; 1068 aj = aij->j + ii[i]; 1069 aa = aij->a + ii[i]; 1070 for (j=0; j<n; j++) { 1071 if (PetscAbsScalar(mask[*aj])) { 1072 if (b) bb[i] -= *aa*xx[*aj]; 1073 *aa = 0.0; 1074 } 1075 aa++; 1076 aj++; 1077 } 1078 } 1079 } 1080 if (x) { 1081 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1082 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1083 } 1084 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1085 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1086 ierr = PetscFree(lrows);CHKERRQ(ierr); 1087 1088 /* wait on sends */ 1089 if (nsends) { 1090 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1091 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1092 ierr = PetscFree(send_status);CHKERRQ(ierr); 1093 } 1094 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1095 ierr = PetscFree(svalues);CHKERRQ(ierr); 1096 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 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); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 EXTERN_C_BEGIN 1177 #undef __FUNCT__ 1178 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1179 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1180 { 1181 MPI_Comm comm; 1182 Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij; 1183 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1184 IS Me,Notme; 1185 PetscErrorCode ierr; 1186 PetscInt M,N,first,last,*notme,i; 1187 PetscMPIInt size; 1188 1189 PetscFunctionBegin; 1190 1191 /* Easy test: symmetric diagonal block */ 1192 Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A; 1193 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1194 if (!*f) PetscFunctionReturn(0); 1195 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1196 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1197 if (size == 1) PetscFunctionReturn(0); 1198 1199 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1200 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1201 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1202 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1203 for (i=0; i<first; i++) notme[i] = i; 1204 for (i=last; i<M; i++) notme[i-last+first] = i; 1205 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1206 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1207 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1208 Aoff = Aoffs[0]; 1209 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1210 Boff = Boffs[0]; 1211 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1212 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1213 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1214 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1215 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1216 ierr = PetscFree(notme);CHKERRQ(ierr); 1217 PetscFunctionReturn(0); 1218 } 1219 EXTERN_C_END 1220 1221 #undef __FUNCT__ 1222 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1223 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1224 { 1225 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1226 PetscErrorCode ierr; 1227 1228 PetscFunctionBegin; 1229 /* do nondiagonal part */ 1230 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1231 /* send it on its way */ 1232 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1233 /* do local part */ 1234 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1235 /* receive remote parts */ 1236 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1237 PetscFunctionReturn(0); 1238 } 1239 1240 /* 1241 This only works correctly for square matrices where the subblock A->A is the 1242 diagonal block 1243 */ 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1246 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1247 { 1248 PetscErrorCode ierr; 1249 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1250 1251 PetscFunctionBegin; 1252 if (A->rmap->N != A->cmap->N) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1253 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"); 1254 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1255 PetscFunctionReturn(0); 1256 } 1257 1258 #undef __FUNCT__ 1259 #define __FUNCT__ "MatScale_MPIAIJ" 1260 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1261 { 1262 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1263 PetscErrorCode ierr; 1264 1265 PetscFunctionBegin; 1266 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1267 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1268 PetscFunctionReturn(0); 1269 } 1270 1271 #undef __FUNCT__ 1272 #define __FUNCT__ "MatDestroy_MPIAIJ" 1273 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1274 { 1275 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1276 PetscErrorCode ierr; 1277 1278 PetscFunctionBegin; 1279 #if defined(PETSC_USE_LOG) 1280 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1281 #endif 1282 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1283 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1284 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1285 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1286 #if defined (PETSC_USE_CTABLE) 1287 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1288 #else 1289 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1290 #endif 1291 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1292 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1293 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1294 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1295 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1296 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1297 1298 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1304 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 1305 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);CHKERRQ(ierr); 1306 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C","",PETSC_NULL);CHKERRQ(ierr); 1307 PetscFunctionReturn(0); 1308 } 1309 1310 #undef __FUNCT__ 1311 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1312 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1313 { 1314 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1315 Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data; 1316 Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data; 1317 PetscErrorCode ierr; 1318 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1319 int fd; 1320 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1321 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1322 PetscScalar *column_values; 1323 PetscInt message_count,flowcontrolcount; 1324 FILE *file; 1325 1326 PetscFunctionBegin; 1327 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1328 ierr = MPI_Comm_size(((PetscObject)mat)->comm,&size);CHKERRQ(ierr); 1329 nz = A->nz + B->nz; 1330 if (!rank) { 1331 header[0] = MAT_FILE_CLASSID; 1332 header[1] = mat->rmap->N; 1333 header[2] = mat->cmap->N; 1334 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1335 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1336 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1337 /* get largest number of rows any processor has */ 1338 rlen = mat->rmap->n; 1339 range = mat->rmap->range; 1340 for (i=1; i<size; i++) { 1341 rlen = PetscMax(rlen,range[i+1] - range[i]); 1342 } 1343 } else { 1344 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1345 rlen = mat->rmap->n; 1346 } 1347 1348 /* load up the local row counts */ 1349 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1350 for (i=0; i<mat->rmap->n; i++) { 1351 row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1352 } 1353 1354 /* store the row lengths to the file */ 1355 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1356 if (!rank) { 1357 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1358 for (i=1; i<size; i++) { 1359 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1360 rlen = range[i+1] - range[i]; 1361 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1362 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1363 } 1364 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1365 } else { 1366 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1367 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1368 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1369 } 1370 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1371 1372 /* load up the local column indices */ 1373 nzmax = nz; /* )th processor needs space a largest processor needs */ 1374 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,((PetscObject)mat)->comm);CHKERRQ(ierr); 1375 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1376 cnt = 0; 1377 for (i=0; i<mat->rmap->n; i++) { 1378 for (j=B->i[i]; j<B->i[i+1]; j++) { 1379 if ( (col = garray[B->j[j]]) > cstart) break; 1380 column_indices[cnt++] = col; 1381 } 1382 for (k=A->i[i]; k<A->i[i+1]; k++) { 1383 column_indices[cnt++] = A->j[k] + cstart; 1384 } 1385 for (; j<B->i[i+1]; j++) { 1386 column_indices[cnt++] = garray[B->j[j]]; 1387 } 1388 } 1389 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); 1390 1391 /* store the column indices to the file */ 1392 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1393 if (!rank) { 1394 MPI_Status status; 1395 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1396 for (i=1; i<size; i++) { 1397 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1398 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1399 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1400 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1401 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1402 } 1403 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1404 } else { 1405 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1406 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1407 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1408 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1409 } 1410 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1411 1412 /* load up the local column values */ 1413 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1414 cnt = 0; 1415 for (i=0; i<mat->rmap->n; i++) { 1416 for (j=B->i[i]; j<B->i[i+1]; j++) { 1417 if ( garray[B->j[j]] > cstart) break; 1418 column_values[cnt++] = B->a[j]; 1419 } 1420 for (k=A->i[i]; k<A->i[i+1]; k++) { 1421 column_values[cnt++] = A->a[k]; 1422 } 1423 for (; j<B->i[i+1]; j++) { 1424 column_values[cnt++] = B->a[j]; 1425 } 1426 } 1427 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); 1428 1429 /* store the column values to the file */ 1430 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1431 if (!rank) { 1432 MPI_Status status; 1433 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1434 for (i=1; i<size; i++) { 1435 ierr = PetscViewerFlowControlStepMaster(viewer,i,message_count,flowcontrolcount);CHKERRQ(ierr); 1436 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,((PetscObject)mat)->comm,&status);CHKERRQ(ierr); 1437 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1438 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1439 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1440 } 1441 ierr = PetscViewerFlowControlEndMaster(viewer,message_count);CHKERRQ(ierr); 1442 } else { 1443 ierr = PetscViewerFlowControlStepWorker(viewer,rank,message_count);CHKERRQ(ierr); 1444 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1445 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,((PetscObject)mat)->comm);CHKERRQ(ierr); 1446 ierr = PetscViewerFlowControlEndWorker(viewer,message_count);CHKERRQ(ierr); 1447 } 1448 ierr = PetscFree(column_values);CHKERRQ(ierr); 1449 1450 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1451 if (file) { 1452 fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1453 } 1454 1455 PetscFunctionReturn(0); 1456 } 1457 1458 #undef __FUNCT__ 1459 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1460 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1461 { 1462 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1463 PetscErrorCode ierr; 1464 PetscMPIInt rank = aij->rank,size = aij->size; 1465 PetscBool isdraw,iascii,isbinary; 1466 PetscViewer sviewer; 1467 PetscViewerFormat format; 1468 1469 PetscFunctionBegin; 1470 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1471 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1472 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1473 if (iascii) { 1474 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1475 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1476 MatInfo info; 1477 PetscBool inodes; 1478 1479 ierr = MPI_Comm_rank(((PetscObject)mat)->comm,&rank);CHKERRQ(ierr); 1480 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1481 ierr = MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);CHKERRQ(ierr); 1482 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1483 if (!inodes) { 1484 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1485 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1486 } else { 1487 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1488 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1489 } 1490 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1491 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1492 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1493 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1494 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1495 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1496 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1497 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1498 PetscFunctionReturn(0); 1499 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1500 PetscInt inodecount,inodelimit,*inodes; 1501 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1502 if (inodes) { 1503 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1504 } else { 1505 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1506 } 1507 PetscFunctionReturn(0); 1508 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1509 PetscFunctionReturn(0); 1510 } 1511 } else if (isbinary) { 1512 if (size == 1) { 1513 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1514 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1515 } else { 1516 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1517 } 1518 PetscFunctionReturn(0); 1519 } else if (isdraw) { 1520 PetscDraw draw; 1521 PetscBool isnull; 1522 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1523 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1524 } 1525 1526 if (size == 1) { 1527 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1528 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1529 } else { 1530 /* assemble the entire matrix onto first processor. */ 1531 Mat A; 1532 Mat_SeqAIJ *Aloc; 1533 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1534 MatScalar *a; 1535 1536 if (mat->rmap->N > 1024) { 1537 PetscBool flg = PETSC_FALSE; 1538 1539 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,PETSC_NULL);CHKERRQ(ierr); 1540 if (!flg) { 1541 SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1542 } 1543 } 1544 1545 ierr = MatCreate(((PetscObject)mat)->comm,&A);CHKERRQ(ierr); 1546 if (!rank) { 1547 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1548 } else { 1549 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1550 } 1551 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1552 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1553 ierr = MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 1554 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1555 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1556 1557 /* copy over the A part */ 1558 Aloc = (Mat_SeqAIJ*)aij->A->data; 1559 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1560 row = mat->rmap->rstart; 1561 for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap->rstart ;} 1562 for (i=0; i<m; i++) { 1563 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1564 row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1565 } 1566 aj = Aloc->j; 1567 for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap->rstart;} 1568 1569 /* copy over the B part */ 1570 Aloc = (Mat_SeqAIJ*)aij->B->data; 1571 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1572 row = mat->rmap->rstart; 1573 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1574 ct = cols; 1575 for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];} 1576 for (i=0; i<m; i++) { 1577 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1578 row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1579 } 1580 ierr = PetscFree(ct);CHKERRQ(ierr); 1581 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1582 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1583 /* 1584 Everyone has to call to draw the matrix since the graphics waits are 1585 synchronized across all processors that share the PetscDraw object 1586 */ 1587 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1588 if (!rank) { 1589 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1590 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1591 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1592 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1593 } 1594 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1595 ierr = MatDestroy(&A);CHKERRQ(ierr); 1596 } 1597 PetscFunctionReturn(0); 1598 } 1599 1600 #undef __FUNCT__ 1601 #define __FUNCT__ "MatView_MPIAIJ" 1602 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1603 { 1604 PetscErrorCode ierr; 1605 PetscBool iascii,isdraw,issocket,isbinary; 1606 1607 PetscFunctionBegin; 1608 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1609 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1610 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1611 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1612 if (iascii || isdraw || isbinary || issocket) { 1613 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1614 } else { 1615 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name); 1616 } 1617 PetscFunctionReturn(0); 1618 } 1619 1620 #undef __FUNCT__ 1621 #define __FUNCT__ "MatSOR_MPIAIJ" 1622 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1623 { 1624 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1625 PetscErrorCode ierr; 1626 Vec bb1 = 0; 1627 PetscBool hasop; 1628 1629 PetscFunctionBegin; 1630 if (flag == SOR_APPLY_UPPER) { 1631 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1632 PetscFunctionReturn(0); 1633 } 1634 1635 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1636 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1637 } 1638 1639 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){ 1640 if (flag & SOR_ZERO_INITIAL_GUESS) { 1641 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1642 its--; 1643 } 1644 1645 while (its--) { 1646 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1647 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1648 1649 /* update rhs: bb1 = bb - B*x */ 1650 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1651 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1652 1653 /* local sweep */ 1654 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1655 } 1656 } else if (flag & SOR_LOCAL_FORWARD_SWEEP){ 1657 if (flag & SOR_ZERO_INITIAL_GUESS) { 1658 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1659 its--; 1660 } 1661 while (its--) { 1662 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1663 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1664 1665 /* update rhs: bb1 = bb - B*x */ 1666 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1667 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1668 1669 /* local sweep */ 1670 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1671 } 1672 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){ 1673 if (flag & SOR_ZERO_INITIAL_GUESS) { 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1675 its--; 1676 } 1677 while (its--) { 1678 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1679 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1680 1681 /* update rhs: bb1 = bb - B*x */ 1682 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1683 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1684 1685 /* local sweep */ 1686 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1687 } 1688 } else if (flag & SOR_EISENSTAT) { 1689 Vec xx1; 1690 1691 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1692 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1693 1694 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1695 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1696 if (!mat->diag) { 1697 ierr = MatGetVecs(matin,&mat->diag,PETSC_NULL);CHKERRQ(ierr); 1698 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1699 } 1700 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1701 if (hasop) { 1702 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1703 } else { 1704 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1705 } 1706 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1707 1708 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1709 1710 /* local sweep */ 1711 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1712 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1713 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1714 } else SETERRQ(((PetscObject)matin)->comm,PETSC_ERR_SUP,"Parallel SOR not supported"); 1715 1716 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1717 PetscFunctionReturn(0); 1718 } 1719 1720 #undef __FUNCT__ 1721 #define __FUNCT__ "MatPermute_MPIAIJ" 1722 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1723 { 1724 MPI_Comm comm; 1725 PetscInt first,local_rowsize,local_colsize; 1726 const PetscInt *rows; 1727 IS crowp,growp,irowp,lrowp,lcolp,icolp; 1728 PetscErrorCode ierr; 1729 1730 PetscFunctionBegin; 1731 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1732 /* make a collective version of 'rowp', this is to be tolerant of users who pass serial index sets */ 1733 ierr = ISOnComm(rowp,comm,PETSC_USE_POINTER,&crowp);CHKERRQ(ierr); 1734 /* collect the global row permutation and invert it */ 1735 ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr); 1736 ierr = ISSetPermutation(growp);CHKERRQ(ierr); 1737 ierr = ISDestroy(&crowp);CHKERRQ(ierr); 1738 ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 1739 ierr = ISDestroy(&growp);CHKERRQ(ierr); 1740 /* get the local target indices */ 1741 ierr = MatGetOwnershipRange(A,&first,PETSC_NULL);CHKERRQ(ierr); 1742 ierr = MatGetLocalSize(A,&local_rowsize,&local_colsize);CHKERRQ(ierr); 1743 ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr); 1744 ierr = ISCreateGeneral(PETSC_COMM_SELF,local_rowsize,rows+first,PETSC_COPY_VALUES,&lrowp);CHKERRQ(ierr); 1745 ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr); 1746 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 1747 /* the column permutation is so much easier; 1748 make a local version of 'colp' and invert it */ 1749 ierr = ISOnComm(colp,PETSC_COMM_SELF,PETSC_USE_POINTER,&lcolp);CHKERRQ(ierr); 1750 ierr = ISSetPermutation(lcolp);CHKERRQ(ierr); 1751 ierr = ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 1752 ierr = ISDestroy(&lcolp);CHKERRQ(ierr); 1753 /* now we just get the submatrix */ 1754 ierr = MatGetSubMatrix_MPIAIJ_Private(A,lrowp,icolp,local_colsize,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr); 1755 /* clean up */ 1756 ierr = ISDestroy(&lrowp);CHKERRQ(ierr); 1757 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 1758 PetscFunctionReturn(0); 1759 } 1760 1761 #undef __FUNCT__ 1762 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1763 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1764 { 1765 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1766 Mat A = mat->A,B = mat->B; 1767 PetscErrorCode ierr; 1768 PetscReal isend[5],irecv[5]; 1769 1770 PetscFunctionBegin; 1771 info->block_size = 1.0; 1772 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1773 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1774 isend[3] = info->memory; isend[4] = info->mallocs; 1775 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1776 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1777 isend[3] += info->memory; isend[4] += info->mallocs; 1778 if (flag == MAT_LOCAL) { 1779 info->nz_used = isend[0]; 1780 info->nz_allocated = isend[1]; 1781 info->nz_unneeded = isend[2]; 1782 info->memory = isend[3]; 1783 info->mallocs = isend[4]; 1784 } else if (flag == MAT_GLOBAL_MAX) { 1785 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,((PetscObject)matin)->comm);CHKERRQ(ierr); 1786 info->nz_used = irecv[0]; 1787 info->nz_allocated = irecv[1]; 1788 info->nz_unneeded = irecv[2]; 1789 info->memory = irecv[3]; 1790 info->mallocs = irecv[4]; 1791 } else if (flag == MAT_GLOBAL_SUM) { 1792 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,((PetscObject)matin)->comm);CHKERRQ(ierr); 1793 info->nz_used = irecv[0]; 1794 info->nz_allocated = irecv[1]; 1795 info->nz_unneeded = irecv[2]; 1796 info->memory = irecv[3]; 1797 info->mallocs = irecv[4]; 1798 } 1799 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1800 info->fill_ratio_needed = 0; 1801 info->factor_mallocs = 0; 1802 PetscFunctionReturn(0); 1803 } 1804 1805 #undef __FUNCT__ 1806 #define __FUNCT__ "MatSetOption_MPIAIJ" 1807 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1808 { 1809 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1810 PetscErrorCode ierr; 1811 1812 PetscFunctionBegin; 1813 switch (op) { 1814 case MAT_NEW_NONZERO_LOCATIONS: 1815 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1816 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1817 case MAT_KEEP_NONZERO_PATTERN: 1818 case MAT_NEW_NONZERO_LOCATION_ERR: 1819 case MAT_USE_INODES: 1820 case MAT_IGNORE_ZERO_ENTRIES: 1821 MatCheckPreallocated(A,1); 1822 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1823 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1824 break; 1825 case MAT_ROW_ORIENTED: 1826 a->roworiented = flg; 1827 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1828 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1829 break; 1830 case MAT_NEW_DIAGONALS: 1831 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1832 break; 1833 case MAT_IGNORE_OFF_PROC_ENTRIES: 1834 a->donotstash = flg; 1835 break; 1836 case MAT_SPD: 1837 A->spd_set = PETSC_TRUE; 1838 A->spd = flg; 1839 if (flg) { 1840 A->symmetric = PETSC_TRUE; 1841 A->structurally_symmetric = PETSC_TRUE; 1842 A->symmetric_set = PETSC_TRUE; 1843 A->structurally_symmetric_set = PETSC_TRUE; 1844 } 1845 break; 1846 case MAT_SYMMETRIC: 1847 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1848 break; 1849 case MAT_STRUCTURALLY_SYMMETRIC: 1850 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1851 break; 1852 case MAT_HERMITIAN: 1853 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1854 break; 1855 case MAT_SYMMETRY_ETERNAL: 1856 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1857 break; 1858 default: 1859 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1860 } 1861 PetscFunctionReturn(0); 1862 } 1863 1864 #undef __FUNCT__ 1865 #define __FUNCT__ "MatGetRow_MPIAIJ" 1866 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1867 { 1868 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1869 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1870 PetscErrorCode ierr; 1871 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1872 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1873 PetscInt *cmap,*idx_p; 1874 1875 PetscFunctionBegin; 1876 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1877 mat->getrowactive = PETSC_TRUE; 1878 1879 if (!mat->rowvalues && (idx || v)) { 1880 /* 1881 allocate enough space to hold information from the longest row. 1882 */ 1883 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1884 PetscInt max = 1,tmp; 1885 for (i=0; i<matin->rmap->n; i++) { 1886 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1887 if (max < tmp) { max = tmp; } 1888 } 1889 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1890 } 1891 1892 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1893 lrow = row - rstart; 1894 1895 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1896 if (!v) {pvA = 0; pvB = 0;} 1897 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1898 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1899 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1900 nztot = nzA + nzB; 1901 1902 cmap = mat->garray; 1903 if (v || idx) { 1904 if (nztot) { 1905 /* Sort by increasing column numbers, assuming A and B already sorted */ 1906 PetscInt imark = -1; 1907 if (v) { 1908 *v = v_p = mat->rowvalues; 1909 for (i=0; i<nzB; i++) { 1910 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1911 else break; 1912 } 1913 imark = i; 1914 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1915 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1916 } 1917 if (idx) { 1918 *idx = idx_p = mat->rowindices; 1919 if (imark > -1) { 1920 for (i=0; i<imark; i++) { 1921 idx_p[i] = cmap[cworkB[i]]; 1922 } 1923 } else { 1924 for (i=0; i<nzB; i++) { 1925 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1926 else break; 1927 } 1928 imark = i; 1929 } 1930 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1931 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1932 } 1933 } else { 1934 if (idx) *idx = 0; 1935 if (v) *v = 0; 1936 } 1937 } 1938 *nz = nztot; 1939 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1940 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1941 PetscFunctionReturn(0); 1942 } 1943 1944 #undef __FUNCT__ 1945 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1946 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1947 { 1948 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1949 1950 PetscFunctionBegin; 1951 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 1952 aij->getrowactive = PETSC_FALSE; 1953 PetscFunctionReturn(0); 1954 } 1955 1956 #undef __FUNCT__ 1957 #define __FUNCT__ "MatNorm_MPIAIJ" 1958 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 1959 { 1960 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1961 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 1962 PetscErrorCode ierr; 1963 PetscInt i,j,cstart = mat->cmap->rstart; 1964 PetscReal sum = 0.0; 1965 MatScalar *v; 1966 1967 PetscFunctionBegin; 1968 if (aij->size == 1) { 1969 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 1970 } else { 1971 if (type == NORM_FROBENIUS) { 1972 v = amat->a; 1973 for (i=0; i<amat->nz; i++) { 1974 #if defined(PETSC_USE_COMPLEX) 1975 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1976 #else 1977 sum += (*v)*(*v); v++; 1978 #endif 1979 } 1980 v = bmat->a; 1981 for (i=0; i<bmat->nz; i++) { 1982 #if defined(PETSC_USE_COMPLEX) 1983 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1984 #else 1985 sum += (*v)*(*v); v++; 1986 #endif 1987 } 1988 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 1989 *norm = PetscSqrtReal(*norm); 1990 } else if (type == NORM_1) { /* max column norm */ 1991 PetscReal *tmp,*tmp2; 1992 PetscInt *jj,*garray = aij->garray; 1993 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1994 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 1995 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 1996 *norm = 0.0; 1997 v = amat->a; jj = amat->j; 1998 for (j=0; j<amat->nz; j++) { 1999 tmp[cstart + *jj++ ] += PetscAbsScalar(*v); v++; 2000 } 2001 v = bmat->a; jj = bmat->j; 2002 for (j=0; j<bmat->nz; j++) { 2003 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2004 } 2005 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,((PetscObject)mat)->comm);CHKERRQ(ierr); 2006 for (j=0; j<mat->cmap->N; j++) { 2007 if (tmp2[j] > *norm) *norm = tmp2[j]; 2008 } 2009 ierr = PetscFree(tmp);CHKERRQ(ierr); 2010 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2011 } else if (type == NORM_INFINITY) { /* max row norm */ 2012 PetscReal ntemp = 0.0; 2013 for (j=0; j<aij->A->rmap->n; j++) { 2014 v = amat->a + amat->i[j]; 2015 sum = 0.0; 2016 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2017 sum += PetscAbsScalar(*v); v++; 2018 } 2019 v = bmat->a + bmat->i[j]; 2020 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2021 sum += PetscAbsScalar(*v); v++; 2022 } 2023 if (sum > ntemp) ntemp = sum; 2024 } 2025 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,((PetscObject)mat)->comm);CHKERRQ(ierr); 2026 } else { 2027 SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"No support for two norm"); 2028 } 2029 } 2030 PetscFunctionReturn(0); 2031 } 2032 2033 #undef __FUNCT__ 2034 #define __FUNCT__ "MatTranspose_MPIAIJ" 2035 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2036 { 2037 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2038 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2039 PetscErrorCode ierr; 2040 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2041 PetscInt cstart=A->cmap->rstart,ncol; 2042 Mat B; 2043 MatScalar *array; 2044 2045 PetscFunctionBegin; 2046 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2047 2048 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2049 ai = Aloc->i; aj = Aloc->j; 2050 bi = Bloc->i; bj = Bloc->j; 2051 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2052 PetscInt *d_nnz,*g_nnz,*o_nnz; 2053 PetscSFNode *oloc; 2054 PetscSF sf; 2055 2056 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2057 /* compute d_nnz for preallocation */ 2058 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2059 for (i=0; i<ai[ma]; i++) { 2060 d_nnz[aj[i]] ++; 2061 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2062 } 2063 /* compute local off-diagonal contributions */ 2064 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2065 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2066 /* map those to global */ 2067 for (i=0; i<nb; i++) { 2068 PetscInt gcol = a->garray[i],colowner; 2069 ierr = PetscLayoutFindOwner(A->cmap,a->garray[i],&colowner);CHKERRQ(ierr); 2070 oloc[i].rank = colowner; 2071 oloc[i].index = gcol - A->cmap->range[colowner]; 2072 } 2073 ierr = PetscSFCreate(((PetscObject)A)->comm,&sf);CHKERRQ(ierr); 2074 ierr = PetscSFSetGraph(sf,na,nb,PETSC_NULL,PETSC_USE_POINTER,oloc,PETSC_USE_POINTER);CHKERRQ(ierr); 2075 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2076 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2077 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2078 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2079 2080 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 2081 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2082 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs); CHKERRQ(ierr); 2083 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2084 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2085 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2086 } else { 2087 B = *matout; 2088 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2089 for (i=0; i<ai[ma]; i++){ 2090 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2091 } 2092 } 2093 2094 /* copy over the A part */ 2095 array = Aloc->a; 2096 row = A->rmap->rstart; 2097 for (i=0; i<ma; i++) { 2098 ncol = ai[i+1]-ai[i]; 2099 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2100 row++; array += ncol; aj += ncol; 2101 } 2102 aj = Aloc->j; 2103 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2104 2105 /* copy over the B part */ 2106 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2107 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2108 array = Bloc->a; 2109 row = A->rmap->rstart; 2110 for (i=0; i<bi[mb]; i++) {cols[i] = a->garray[bj[i]];} 2111 cols_tmp = cols; 2112 for (i=0; i<mb; i++) { 2113 ncol = bi[i+1]-bi[i]; 2114 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2115 row++; array += ncol; cols_tmp += ncol; 2116 } 2117 ierr = PetscFree(cols);CHKERRQ(ierr); 2118 2119 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2120 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2121 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2122 *matout = B; 2123 } else { 2124 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2125 } 2126 PetscFunctionReturn(0); 2127 } 2128 2129 #undef __FUNCT__ 2130 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2131 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2132 { 2133 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2134 Mat a = aij->A,b = aij->B; 2135 PetscErrorCode ierr; 2136 PetscInt s1,s2,s3; 2137 2138 PetscFunctionBegin; 2139 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2140 if (rr) { 2141 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2142 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2143 /* Overlap communication with computation. */ 2144 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2145 } 2146 if (ll) { 2147 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2148 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2149 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2150 } 2151 /* scale the diagonal block */ 2152 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2153 2154 if (rr) { 2155 /* Do a scatter end and then right scale the off-diagonal block */ 2156 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2157 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2158 } 2159 2160 PetscFunctionReturn(0); 2161 } 2162 2163 #undef __FUNCT__ 2164 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2165 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2166 { 2167 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2168 PetscErrorCode ierr; 2169 2170 PetscFunctionBegin; 2171 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2172 PetscFunctionReturn(0); 2173 } 2174 2175 #undef __FUNCT__ 2176 #define __FUNCT__ "MatEqual_MPIAIJ" 2177 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2178 { 2179 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2180 Mat a,b,c,d; 2181 PetscBool flg; 2182 PetscErrorCode ierr; 2183 2184 PetscFunctionBegin; 2185 a = matA->A; b = matA->B; 2186 c = matB->A; d = matB->B; 2187 2188 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2189 if (flg) { 2190 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2191 } 2192 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,((PetscObject)A)->comm);CHKERRQ(ierr); 2193 PetscFunctionReturn(0); 2194 } 2195 2196 #undef __FUNCT__ 2197 #define __FUNCT__ "MatCopy_MPIAIJ" 2198 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2199 { 2200 PetscErrorCode ierr; 2201 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 2202 Mat_MPIAIJ *b = (Mat_MPIAIJ *)B->data; 2203 2204 PetscFunctionBegin; 2205 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2206 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2207 /* because of the column compression in the off-processor part of the matrix a->B, 2208 the number of columns in a->B and b->B may be different, hence we cannot call 2209 the MatCopy() directly on the two parts. If need be, we can provide a more 2210 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2211 then copying the submatrices */ 2212 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2213 } else { 2214 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2215 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2216 } 2217 PetscFunctionReturn(0); 2218 } 2219 2220 #undef __FUNCT__ 2221 #define __FUNCT__ "MatSetUp_MPIAIJ" 2222 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2223 { 2224 PetscErrorCode ierr; 2225 2226 PetscFunctionBegin; 2227 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2228 PetscFunctionReturn(0); 2229 } 2230 2231 #undef __FUNCT__ 2232 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2233 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2234 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt* nnz) 2235 { 2236 PetscInt i,m=Y->rmap->N; 2237 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2238 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2239 const PetscInt *xi = x->i,*yi = y->i; 2240 2241 PetscFunctionBegin; 2242 /* Set the number of nonzeros in the new matrix */ 2243 for (i=0; i<m; i++) { 2244 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2245 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2246 nnz[i] = 0; 2247 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2248 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2249 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2250 nnz[i]++; 2251 } 2252 for (; k<nzy; k++) nnz[i]++; 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatAXPY_MPIAIJ" 2259 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2260 { 2261 PetscErrorCode ierr; 2262 PetscInt i; 2263 Mat_MPIAIJ *xx = (Mat_MPIAIJ *)X->data,*yy = (Mat_MPIAIJ *)Y->data; 2264 PetscBLASInt bnz,one=1; 2265 Mat_SeqAIJ *x,*y; 2266 2267 PetscFunctionBegin; 2268 if (str == SAME_NONZERO_PATTERN) { 2269 PetscScalar alpha = a; 2270 x = (Mat_SeqAIJ *)xx->A->data; 2271 y = (Mat_SeqAIJ *)yy->A->data; 2272 bnz = PetscBLASIntCast(x->nz); 2273 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 2274 x = (Mat_SeqAIJ *)xx->B->data; 2275 y = (Mat_SeqAIJ *)yy->B->data; 2276 bnz = PetscBLASIntCast(x->nz); 2277 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 2278 } else if (str == SUBSET_NONZERO_PATTERN) { 2279 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2280 2281 x = (Mat_SeqAIJ *)xx->B->data; 2282 y = (Mat_SeqAIJ *)yy->B->data; 2283 if (y->xtoy && y->XtoY != xx->B) { 2284 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2285 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2286 } 2287 if (!y->xtoy) { /* get xtoy */ 2288 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2289 y->XtoY = xx->B; 2290 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2291 } 2292 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2293 } else { 2294 Mat B; 2295 PetscInt *nnz_d,*nnz_o; 2296 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2297 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2298 ierr = MatCreate(((PetscObject)Y)->comm,&B);CHKERRQ(ierr); 2299 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2300 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2301 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2302 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2303 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2304 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2305 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2306 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2307 ierr = MatHeaderReplace(Y,B); 2308 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2309 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2310 } 2311 PetscFunctionReturn(0); 2312 } 2313 2314 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2315 2316 #undef __FUNCT__ 2317 #define __FUNCT__ "MatConjugate_MPIAIJ" 2318 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2319 { 2320 #if defined(PETSC_USE_COMPLEX) 2321 PetscErrorCode ierr; 2322 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 2323 2324 PetscFunctionBegin; 2325 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2326 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2327 #else 2328 PetscFunctionBegin; 2329 #endif 2330 PetscFunctionReturn(0); 2331 } 2332 2333 #undef __FUNCT__ 2334 #define __FUNCT__ "MatRealPart_MPIAIJ" 2335 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2336 { 2337 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2338 PetscErrorCode ierr; 2339 2340 PetscFunctionBegin; 2341 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2342 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2343 PetscFunctionReturn(0); 2344 } 2345 2346 #undef __FUNCT__ 2347 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2348 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2349 { 2350 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2351 PetscErrorCode ierr; 2352 2353 PetscFunctionBegin; 2354 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2355 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2356 PetscFunctionReturn(0); 2357 } 2358 2359 #ifdef PETSC_HAVE_PBGL 2360 2361 #include <boost/parallel/mpi/bsp_process_group.hpp> 2362 #include <boost/graph/distributed/ilu_default_graph.hpp> 2363 #include <boost/graph/distributed/ilu_0_block.hpp> 2364 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2365 #include <boost/graph/distributed/petsc/interface.hpp> 2366 #include <boost/multi_array.hpp> 2367 #include <boost/parallel/distributed_property_map->hpp> 2368 2369 #undef __FUNCT__ 2370 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2371 /* 2372 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2373 */ 2374 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2375 { 2376 namespace petsc = boost::distributed::petsc; 2377 2378 namespace graph_dist = boost::graph::distributed; 2379 using boost::graph::distributed::ilu_default::process_group_type; 2380 using boost::graph::ilu_permuted; 2381 2382 PetscBool row_identity, col_identity; 2383 PetscContainer c; 2384 PetscInt m, n, M, N; 2385 PetscErrorCode ierr; 2386 2387 PetscFunctionBegin; 2388 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2389 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2390 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2391 if (!row_identity || !col_identity) { 2392 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2393 } 2394 2395 process_group_type pg; 2396 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2397 lgraph_type* lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2398 lgraph_type& level_graph = *lgraph_p; 2399 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2400 2401 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2402 ilu_permuted(level_graph); 2403 2404 /* put together the new matrix */ 2405 ierr = MatCreate(((PetscObject)A)->comm, fact);CHKERRQ(ierr); 2406 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2407 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2408 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2409 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs); CHKERRQ(ierr); 2410 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2411 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2412 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2413 2414 ierr = PetscContainerCreate(((PetscObject)A)->comm, &c); 2415 ierr = PetscContainerSetPointer(c, lgraph_p); 2416 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2417 ierr = PetscContainerDestroy(&c); 2418 PetscFunctionReturn(0); 2419 } 2420 2421 #undef __FUNCT__ 2422 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2423 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2424 { 2425 PetscFunctionBegin; 2426 PetscFunctionReturn(0); 2427 } 2428 2429 #undef __FUNCT__ 2430 #define __FUNCT__ "MatSolve_MPIAIJ" 2431 /* 2432 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2433 */ 2434 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2435 { 2436 namespace graph_dist = boost::graph::distributed; 2437 2438 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2439 lgraph_type* lgraph_p; 2440 PetscContainer c; 2441 PetscErrorCode ierr; 2442 2443 PetscFunctionBegin; 2444 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject *) &c);CHKERRQ(ierr); 2445 ierr = PetscContainerGetPointer(c, (void **) &lgraph_p);CHKERRQ(ierr); 2446 ierr = VecCopy(b, x);CHKERRQ(ierr); 2447 2448 PetscScalar* array_x; 2449 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2450 PetscInt sx; 2451 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2452 2453 PetscScalar* array_b; 2454 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2455 PetscInt sb; 2456 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2457 2458 lgraph_type& level_graph = *lgraph_p; 2459 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2460 2461 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2462 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]), 2463 ref_x(array_x, boost::extents[num_vertices(graph)]); 2464 2465 typedef boost::iterator_property_map<array_ref_type::iterator, 2466 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2467 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)), 2468 vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2469 2470 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2471 2472 PetscFunctionReturn(0); 2473 } 2474 #endif 2475 2476 typedef struct { /* used by MatGetRedundantMatrix() for reusing matredundant */ 2477 PetscInt nzlocal,nsends,nrecvs; 2478 PetscMPIInt *send_rank,*recv_rank; 2479 PetscInt *sbuf_nz,*rbuf_nz,*sbuf_j,**rbuf_j; 2480 PetscScalar *sbuf_a,**rbuf_a; 2481 PetscErrorCode (*Destroy)(Mat); 2482 } Mat_Redundant; 2483 2484 #undef __FUNCT__ 2485 #define __FUNCT__ "PetscContainerDestroy_MatRedundant" 2486 PetscErrorCode PetscContainerDestroy_MatRedundant(void *ptr) 2487 { 2488 PetscErrorCode ierr; 2489 Mat_Redundant *redund=(Mat_Redundant*)ptr; 2490 PetscInt i; 2491 2492 PetscFunctionBegin; 2493 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2494 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2495 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2496 for (i=0; i<redund->nrecvs; i++){ 2497 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2498 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2499 } 2500 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2501 ierr = PetscFree(redund);CHKERRQ(ierr); 2502 PetscFunctionReturn(0); 2503 } 2504 2505 #undef __FUNCT__ 2506 #define __FUNCT__ "MatDestroy_MatRedundant" 2507 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2508 { 2509 PetscErrorCode ierr; 2510 PetscContainer container; 2511 Mat_Redundant *redund=PETSC_NULL; 2512 2513 PetscFunctionBegin; 2514 ierr = PetscObjectQuery((PetscObject)A,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2515 if (!container) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Container does not exit"); 2516 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2517 A->ops->destroy = redund->Destroy; 2518 ierr = PetscObjectCompose((PetscObject)A,"Mat_Redundant",0);CHKERRQ(ierr); 2519 if (A->ops->destroy) { 2520 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 2521 } 2522 PetscFunctionReturn(0); 2523 } 2524 2525 #undef __FUNCT__ 2526 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2527 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscInt mlocal_sub,MatReuse reuse,Mat *matredundant) 2528 { 2529 PetscMPIInt rank,size; 2530 MPI_Comm comm=((PetscObject)mat)->comm; 2531 PetscErrorCode ierr; 2532 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 2533 PetscMPIInt *send_rank=PETSC_NULL,*recv_rank=PETSC_NULL; 2534 PetscInt *rowrange=mat->rmap->range; 2535 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2536 Mat A=aij->A,B=aij->B,C=*matredundant; 2537 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2538 PetscScalar *sbuf_a; 2539 PetscInt nzlocal=a->nz+b->nz; 2540 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2541 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray,M,N; 2542 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2543 MatScalar *aworkA,*aworkB; 2544 PetscScalar *vals; 2545 PetscMPIInt tag1,tag2,tag3,imdex; 2546 MPI_Request *s_waits1=PETSC_NULL,*s_waits2=PETSC_NULL,*s_waits3=PETSC_NULL, 2547 *r_waits1=PETSC_NULL,*r_waits2=PETSC_NULL,*r_waits3=PETSC_NULL; 2548 MPI_Status recv_status,*send_status; 2549 PetscInt *sbuf_nz=PETSC_NULL,*rbuf_nz=PETSC_NULL,count; 2550 PetscInt **rbuf_j=PETSC_NULL; 2551 PetscScalar **rbuf_a=PETSC_NULL; 2552 Mat_Redundant *redund=PETSC_NULL; 2553 PetscContainer container; 2554 2555 PetscFunctionBegin; 2556 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2557 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2558 2559 if (reuse == MAT_REUSE_MATRIX) { 2560 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2561 if (M != N || M != mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2562 ierr = MatGetLocalSize(C,&M,&N);CHKERRQ(ierr); 2563 if (M != N || M != mlocal_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong local size"); 2564 ierr = PetscObjectQuery((PetscObject)C,"Mat_Redundant",(PetscObject *)&container);CHKERRQ(ierr); 2565 if (!container) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Container does not exit"); 2566 ierr = PetscContainerGetPointer(container,(void **)&redund);CHKERRQ(ierr); 2567 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2568 2569 nsends = redund->nsends; 2570 nrecvs = redund->nrecvs; 2571 send_rank = redund->send_rank; 2572 recv_rank = redund->recv_rank; 2573 sbuf_nz = redund->sbuf_nz; 2574 rbuf_nz = redund->rbuf_nz; 2575 sbuf_j = redund->sbuf_j; 2576 sbuf_a = redund->sbuf_a; 2577 rbuf_j = redund->rbuf_j; 2578 rbuf_a = redund->rbuf_a; 2579 } 2580 2581 if (reuse == MAT_INITIAL_MATRIX){ 2582 PetscMPIInt subrank,subsize; 2583 PetscInt nleftover,np_subcomm; 2584 /* get the destination processors' id send_rank, nsends and nrecvs */ 2585 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2587 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank); 2588 np_subcomm = size/nsubcomm; 2589 nleftover = size - nsubcomm*np_subcomm; 2590 nsends = 0; nrecvs = 0; 2591 for (i=0; i<size; i++){ /* i=rank*/ 2592 if (subrank == i/nsubcomm && rank != i){ /* my_subrank == other's subrank */ 2593 send_rank[nsends] = i; nsends++; 2594 recv_rank[nrecvs++] = i; 2595 } 2596 } 2597 if (rank >= size - nleftover){/* this proc is a leftover processor */ 2598 i = size-nleftover-1; 2599 j = 0; 2600 while (j < nsubcomm - nleftover){ 2601 send_rank[nsends++] = i; 2602 i--; j++; 2603 } 2604 } 2605 2606 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1){ /* this proc recvs from leftover processors */ 2607 for (i=0; i<nleftover; i++){ 2608 recv_rank[nrecvs++] = size-nleftover+i; 2609 } 2610 } 2611 2612 /* allocate sbuf_j, sbuf_a */ 2613 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2614 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2615 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2616 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2617 2618 /* copy mat's local entries into the buffers */ 2619 if (reuse == MAT_INITIAL_MATRIX){ 2620 rownz_max = 0; 2621 rptr = sbuf_j; 2622 cols = sbuf_j + rend-rstart + 1; 2623 vals = sbuf_a; 2624 rptr[0] = 0; 2625 for (i=0; i<rend-rstart; i++){ 2626 row = i + rstart; 2627 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2628 ncols = nzA + nzB; 2629 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2630 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2631 /* load the column indices for this row into cols */ 2632 lwrite = 0; 2633 for (l=0; l<nzB; l++) { 2634 if ((ctmp = bmap[cworkB[l]]) < cstart){ 2635 vals[lwrite] = aworkB[l]; 2636 cols[lwrite++] = ctmp; 2637 } 2638 } 2639 for (l=0; l<nzA; l++){ 2640 vals[lwrite] = aworkA[l]; 2641 cols[lwrite++] = cstart + cworkA[l]; 2642 } 2643 for (l=0; l<nzB; l++) { 2644 if ((ctmp = bmap[cworkB[l]]) >= cend){ 2645 vals[lwrite] = aworkB[l]; 2646 cols[lwrite++] = ctmp; 2647 } 2648 } 2649 vals += ncols; 2650 cols += ncols; 2651 rptr[i+1] = rptr[i] + ncols; 2652 if (rownz_max < ncols) rownz_max = ncols; 2653 } 2654 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); 2655 } else { /* only copy matrix values into sbuf_a */ 2656 rptr = sbuf_j; 2657 vals = sbuf_a; 2658 rptr[0] = 0; 2659 for (i=0; i<rend-rstart; i++){ 2660 row = i + rstart; 2661 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2662 ncols = nzA + nzB; 2663 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2664 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2665 lwrite = 0; 2666 for (l=0; l<nzB; l++) { 2667 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2668 } 2669 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2670 for (l=0; l<nzB; l++) { 2671 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2672 } 2673 vals += ncols; 2674 rptr[i+1] = rptr[i] + ncols; 2675 } 2676 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2677 2678 /* send nzlocal to others, and recv other's nzlocal */ 2679 /*--------------------------------------------------*/ 2680 if (reuse == MAT_INITIAL_MATRIX){ 2681 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2682 s_waits2 = s_waits3 + nsends; 2683 s_waits1 = s_waits2 + nsends; 2684 r_waits1 = s_waits1 + nsends; 2685 r_waits2 = r_waits1 + nrecvs; 2686 r_waits3 = r_waits2 + nrecvs; 2687 } else { 2688 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2689 r_waits3 = s_waits3 + nsends; 2690 } 2691 2692 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2693 if (reuse == MAT_INITIAL_MATRIX){ 2694 /* get new tags to keep the communication clean */ 2695 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2696 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2697 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2698 2699 /* post receives of other's nzlocal */ 2700 for (i=0; i<nrecvs; i++){ 2701 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2702 } 2703 /* send nzlocal to others */ 2704 for (i=0; i<nsends; i++){ 2705 sbuf_nz[i] = nzlocal; 2706 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2707 } 2708 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2709 count = nrecvs; 2710 while (count) { 2711 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2712 recv_rank[imdex] = recv_status.MPI_SOURCE; 2713 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2714 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2715 2716 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2717 rbuf_nz[imdex] += i + 2; 2718 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2719 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2720 count--; 2721 } 2722 /* wait on sends of nzlocal */ 2723 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2724 /* send mat->i,j to others, and recv from other's */ 2725 /*------------------------------------------------*/ 2726 for (i=0; i<nsends; i++){ 2727 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2728 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2729 } 2730 /* wait on receives of mat->i,j */ 2731 /*------------------------------*/ 2732 count = nrecvs; 2733 while (count) { 2734 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2735 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); 2736 count--; 2737 } 2738 /* wait on sends of mat->i,j */ 2739 /*---------------------------*/ 2740 if (nsends) { 2741 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2742 } 2743 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2744 2745 /* post receives, send and receive mat->a */ 2746 /*----------------------------------------*/ 2747 for (imdex=0; imdex<nrecvs; imdex++) { 2748 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2749 } 2750 for (i=0; i<nsends; i++){ 2751 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2752 } 2753 count = nrecvs; 2754 while (count) { 2755 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2756 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); 2757 count--; 2758 } 2759 if (nsends) { 2760 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2761 } 2762 2763 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2764 2765 /* create redundant matrix */ 2766 /*-------------------------*/ 2767 if (reuse == MAT_INITIAL_MATRIX){ 2768 /* compute rownz_max for preallocation */ 2769 for (imdex=0; imdex<nrecvs; imdex++){ 2770 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2771 rptr = rbuf_j[imdex]; 2772 for (i=0; i<j; i++){ 2773 ncols = rptr[i+1] - rptr[i]; 2774 if (rownz_max < ncols) rownz_max = ncols; 2775 } 2776 } 2777 2778 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2779 ierr = MatSetSizes(C,mlocal_sub,mlocal_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2780 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs); CHKERRQ(ierr); 2781 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2782 ierr = MatSeqAIJSetPreallocation(C,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2783 ierr = MatMPIAIJSetPreallocation(C,rownz_max,PETSC_NULL,rownz_max,PETSC_NULL);CHKERRQ(ierr); 2784 } else { 2785 C = *matredundant; 2786 } 2787 2788 /* insert local matrix entries */ 2789 rptr = sbuf_j; 2790 cols = sbuf_j + rend-rstart + 1; 2791 vals = sbuf_a; 2792 for (i=0; i<rend-rstart; i++){ 2793 row = i + rstart; 2794 ncols = rptr[i+1] - rptr[i]; 2795 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2796 vals += ncols; 2797 cols += ncols; 2798 } 2799 /* insert received matrix entries */ 2800 for (imdex=0; imdex<nrecvs; imdex++){ 2801 rstart = rowrange[recv_rank[imdex]]; 2802 rend = rowrange[recv_rank[imdex]+1]; 2803 rptr = rbuf_j[imdex]; 2804 cols = rbuf_j[imdex] + rend-rstart + 1; 2805 vals = rbuf_a[imdex]; 2806 for (i=0; i<rend-rstart; i++){ 2807 row = i + rstart; 2808 ncols = rptr[i+1] - rptr[i]; 2809 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2810 vals += ncols; 2811 cols += ncols; 2812 } 2813 } 2814 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2815 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2816 ierr = MatGetSize(C,&M,&N);CHKERRQ(ierr); 2817 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"redundant mat size %d != input mat size %d",M,mat->rmap->N); 2818 if (reuse == MAT_INITIAL_MATRIX) { 2819 PetscContainer container; 2820 *matredundant = C; 2821 /* create a supporting struct and attach it to C for reuse */ 2822 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2823 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 2824 ierr = PetscContainerSetPointer(container,redund);CHKERRQ(ierr); 2825 ierr = PetscContainerSetUserDestroy(container,PetscContainerDestroy_MatRedundant);CHKERRQ(ierr); 2826 ierr = PetscObjectCompose((PetscObject)C,"Mat_Redundant",(PetscObject)container);CHKERRQ(ierr); 2827 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 2828 2829 redund->nzlocal = nzlocal; 2830 redund->nsends = nsends; 2831 redund->nrecvs = nrecvs; 2832 redund->send_rank = send_rank; 2833 redund->recv_rank = recv_rank; 2834 redund->sbuf_nz = sbuf_nz; 2835 redund->rbuf_nz = rbuf_nz; 2836 redund->sbuf_j = sbuf_j; 2837 redund->sbuf_a = sbuf_a; 2838 redund->rbuf_j = rbuf_j; 2839 redund->rbuf_a = rbuf_a; 2840 2841 redund->Destroy = C->ops->destroy; 2842 C->ops->destroy = MatDestroy_MatRedundant; 2843 } 2844 PetscFunctionReturn(0); 2845 } 2846 2847 #undef __FUNCT__ 2848 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2849 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2850 { 2851 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2852 PetscErrorCode ierr; 2853 PetscInt i,*idxb = 0; 2854 PetscScalar *va,*vb; 2855 Vec vtmp; 2856 2857 PetscFunctionBegin; 2858 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2859 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2860 if (idx) { 2861 for (i=0; i<A->rmap->n; i++) { 2862 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2863 } 2864 } 2865 2866 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2867 if (idx) { 2868 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2869 } 2870 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2871 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2872 2873 for (i=0; i<A->rmap->n; i++){ 2874 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2875 va[i] = vb[i]; 2876 if (idx) idx[i] = a->garray[idxb[i]]; 2877 } 2878 } 2879 2880 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2881 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2882 ierr = PetscFree(idxb);CHKERRQ(ierr); 2883 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2884 PetscFunctionReturn(0); 2885 } 2886 2887 #undef __FUNCT__ 2888 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2889 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2890 { 2891 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2892 PetscErrorCode ierr; 2893 PetscInt i,*idxb = 0; 2894 PetscScalar *va,*vb; 2895 Vec vtmp; 2896 2897 PetscFunctionBegin; 2898 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2899 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2900 if (idx) { 2901 for (i=0; i<A->cmap->n; i++) { 2902 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2903 } 2904 } 2905 2906 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2907 if (idx) { 2908 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2909 } 2910 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2911 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2912 2913 for (i=0; i<A->rmap->n; i++){ 2914 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 2915 va[i] = vb[i]; 2916 if (idx) idx[i] = a->garray[idxb[i]]; 2917 } 2918 } 2919 2920 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2921 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2922 ierr = PetscFree(idxb);CHKERRQ(ierr); 2923 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2924 PetscFunctionReturn(0); 2925 } 2926 2927 #undef __FUNCT__ 2928 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 2929 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2930 { 2931 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2932 PetscInt n = A->rmap->n; 2933 PetscInt cstart = A->cmap->rstart; 2934 PetscInt *cmap = mat->garray; 2935 PetscInt *diagIdx, *offdiagIdx; 2936 Vec diagV, offdiagV; 2937 PetscScalar *a, *diagA, *offdiagA; 2938 PetscInt r; 2939 PetscErrorCode ierr; 2940 2941 PetscFunctionBegin; 2942 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2943 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2944 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2945 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2946 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2947 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2948 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2949 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2950 for (r = 0; r < n; ++r) { 2951 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 2952 a[r] = diagA[r]; 2953 idx[r] = cstart + diagIdx[r]; 2954 } else { 2955 a[r] = offdiagA[r]; 2956 idx[r] = cmap[offdiagIdx[r]]; 2957 } 2958 } 2959 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 2960 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 2961 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2962 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 2963 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 2964 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 2965 PetscFunctionReturn(0); 2966 } 2967 2968 #undef __FUNCT__ 2969 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 2970 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2971 { 2972 Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data; 2973 PetscInt n = A->rmap->n; 2974 PetscInt cstart = A->cmap->rstart; 2975 PetscInt *cmap = mat->garray; 2976 PetscInt *diagIdx, *offdiagIdx; 2977 Vec diagV, offdiagV; 2978 PetscScalar *a, *diagA, *offdiagA; 2979 PetscInt r; 2980 PetscErrorCode ierr; 2981 2982 PetscFunctionBegin; 2983 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 2984 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &diagV);CHKERRQ(ierr); 2985 ierr = VecCreateSeq(((PetscObject)A)->comm, n, &offdiagV);CHKERRQ(ierr); 2986 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 2987 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 2988 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 2989 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 2990 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 2991 for (r = 0; r < n; ++r) { 2992 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 2993 a[r] = diagA[r]; 2994 idx[r] = cstart + diagIdx[r]; 2995 } else { 2996 a[r] = offdiagA[r]; 2997 idx[r] = cmap[offdiagIdx[r]]; 2998 } 2999 } 3000 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3001 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3002 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3003 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3004 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3005 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3006 PetscFunctionReturn(0); 3007 } 3008 3009 #undef __FUNCT__ 3010 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3011 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3012 { 3013 PetscErrorCode ierr; 3014 Mat *dummy; 3015 3016 PetscFunctionBegin; 3017 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3018 *newmat = *dummy; 3019 ierr = PetscFree(dummy);CHKERRQ(ierr); 3020 PetscFunctionReturn(0); 3021 } 3022 3023 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3024 3025 #undef __FUNCT__ 3026 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3027 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3028 { 3029 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3030 PetscErrorCode ierr; 3031 3032 PetscFunctionBegin; 3033 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3034 PetscFunctionReturn(0); 3035 } 3036 3037 #undef __FUNCT__ 3038 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3039 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3040 { 3041 PetscErrorCode ierr; 3042 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3043 3044 PetscFunctionBegin; 3045 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3046 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3047 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3048 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3049 PetscFunctionReturn(0); 3050 } 3051 3052 /* -------------------------------------------------------------------*/ 3053 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3054 MatGetRow_MPIAIJ, 3055 MatRestoreRow_MPIAIJ, 3056 MatMult_MPIAIJ, 3057 /* 4*/ MatMultAdd_MPIAIJ, 3058 MatMultTranspose_MPIAIJ, 3059 MatMultTransposeAdd_MPIAIJ, 3060 #ifdef PETSC_HAVE_PBGL 3061 MatSolve_MPIAIJ, 3062 #else 3063 0, 3064 #endif 3065 0, 3066 0, 3067 /*10*/ 0, 3068 0, 3069 0, 3070 MatSOR_MPIAIJ, 3071 MatTranspose_MPIAIJ, 3072 /*15*/ MatGetInfo_MPIAIJ, 3073 MatEqual_MPIAIJ, 3074 MatGetDiagonal_MPIAIJ, 3075 MatDiagonalScale_MPIAIJ, 3076 MatNorm_MPIAIJ, 3077 /*20*/ MatAssemblyBegin_MPIAIJ, 3078 MatAssemblyEnd_MPIAIJ, 3079 MatSetOption_MPIAIJ, 3080 MatZeroEntries_MPIAIJ, 3081 /*24*/ MatZeroRows_MPIAIJ, 3082 0, 3083 #ifdef PETSC_HAVE_PBGL 3084 0, 3085 #else 3086 0, 3087 #endif 3088 0, 3089 0, 3090 /*29*/ MatSetUp_MPIAIJ, 3091 #ifdef PETSC_HAVE_PBGL 3092 0, 3093 #else 3094 0, 3095 #endif 3096 0, 3097 0, 3098 0, 3099 /*34*/ MatDuplicate_MPIAIJ, 3100 0, 3101 0, 3102 0, 3103 0, 3104 /*39*/ MatAXPY_MPIAIJ, 3105 MatGetSubMatrices_MPIAIJ, 3106 MatIncreaseOverlap_MPIAIJ, 3107 MatGetValues_MPIAIJ, 3108 MatCopy_MPIAIJ, 3109 /*44*/ MatGetRowMax_MPIAIJ, 3110 MatScale_MPIAIJ, 3111 0, 3112 0, 3113 MatZeroRowsColumns_MPIAIJ, 3114 /*49*/ MatSetRandom_MPIAIJ, 3115 0, 3116 0, 3117 0, 3118 0, 3119 /*54*/ MatFDColoringCreate_MPIAIJ, 3120 0, 3121 MatSetUnfactored_MPIAIJ, 3122 0, /* MatPermute_MPIAIJ, impl currently broken */ 3123 0, 3124 /*59*/ MatGetSubMatrix_MPIAIJ, 3125 MatDestroy_MPIAIJ, 3126 MatView_MPIAIJ, 3127 0, 3128 0, 3129 /*64*/ 0, 3130 0, 3131 0, 3132 0, 3133 0, 3134 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3135 MatGetRowMinAbs_MPIAIJ, 3136 0, 3137 MatSetColoring_MPIAIJ, 3138 #if defined(PETSC_HAVE_ADIC) 3139 MatSetValuesAdic_MPIAIJ, 3140 #else 3141 0, 3142 #endif 3143 MatSetValuesAdifor_MPIAIJ, 3144 /*75*/ MatFDColoringApply_AIJ, 3145 0, 3146 0, 3147 0, 3148 MatFindZeroDiagonals_MPIAIJ, 3149 /*80*/ 0, 3150 0, 3151 0, 3152 /*83*/ MatLoad_MPIAIJ, 3153 0, 3154 0, 3155 0, 3156 0, 3157 0, 3158 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3159 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3160 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3161 MatPtAP_Basic, 3162 MatPtAPSymbolic_MPIAIJ, 3163 /*94*/ MatPtAPNumeric_MPIAIJ, 3164 0, 3165 0, 3166 0, 3167 0, 3168 /*99*/ 0, 3169 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3170 MatPtAPNumeric_MPIAIJ_MPIAIJ, 3171 MatConjugate_MPIAIJ, 3172 0, 3173 /*104*/MatSetValuesRow_MPIAIJ, 3174 MatRealPart_MPIAIJ, 3175 MatImaginaryPart_MPIAIJ, 3176 0, 3177 0, 3178 /*109*/0, 3179 MatGetRedundantMatrix_MPIAIJ, 3180 MatGetRowMin_MPIAIJ, 3181 0, 3182 0, 3183 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3184 0, 3185 0, 3186 0, 3187 0, 3188 /*119*/0, 3189 0, 3190 0, 3191 0, 3192 MatGetMultiProcBlock_MPIAIJ, 3193 /*124*/MatFindNonzeroRows_MPIAIJ, 3194 MatGetColumnNorms_MPIAIJ, 3195 MatInvertBlockDiagonal_MPIAIJ, 3196 0, 3197 MatGetSubMatricesParallel_MPIAIJ, 3198 /*129*/0, 3199 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3200 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3201 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3202 0, 3203 /*134*/0, 3204 0, 3205 0, 3206 0, 3207 0 3208 }; 3209 3210 /* ----------------------------------------------------------------------------------------*/ 3211 3212 EXTERN_C_BEGIN 3213 #undef __FUNCT__ 3214 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3215 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3216 { 3217 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 3218 PetscErrorCode ierr; 3219 3220 PetscFunctionBegin; 3221 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3222 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3223 PetscFunctionReturn(0); 3224 } 3225 EXTERN_C_END 3226 3227 EXTERN_C_BEGIN 3228 #undef __FUNCT__ 3229 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3230 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3231 { 3232 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 3233 PetscErrorCode ierr; 3234 3235 PetscFunctionBegin; 3236 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3237 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3238 PetscFunctionReturn(0); 3239 } 3240 EXTERN_C_END 3241 3242 EXTERN_C_BEGIN 3243 #undef __FUNCT__ 3244 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3245 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3246 { 3247 Mat_MPIAIJ *b; 3248 PetscErrorCode ierr; 3249 PetscInt i; 3250 PetscBool d_realalloc = PETSC_FALSE,o_realalloc = PETSC_FALSE; 3251 3252 PetscFunctionBegin; 3253 if (d_nz >= 0 || d_nnz) d_realalloc = PETSC_TRUE; 3254 if (o_nz >= 0 || o_nnz) o_realalloc = PETSC_TRUE; 3255 if (d_nz == PETSC_DEFAULT || d_nz == PETSC_DECIDE) d_nz = 5; 3256 if (o_nz == PETSC_DEFAULT || o_nz == PETSC_DECIDE) o_nz = 2; 3257 if (d_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than 0: value %D",d_nz); 3258 if (o_nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than 0: value %D",o_nz); 3259 3260 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3261 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3262 if (d_nnz) { 3263 for (i=0; i<B->rmap->n; i++) { 3264 if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than 0: local row %D value %D",i,d_nnz[i]); 3265 } 3266 } 3267 if (o_nnz) { 3268 for (i=0; i<B->rmap->n; i++) { 3269 if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than 0: local row %D value %D",i,o_nnz[i]); 3270 } 3271 } 3272 b = (Mat_MPIAIJ*)B->data; 3273 3274 if (!B->preallocated) { 3275 /* Explicitly create 2 MATSEQAIJ matrices. */ 3276 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3277 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3278 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3279 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3280 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3281 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3282 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3283 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3284 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3285 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3286 } 3287 3288 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3289 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3290 /* Do not error if the user did not give real preallocation information. Ugly because this would overwrite a previous user call to MatSetOption(). */ 3291 if (!d_realalloc) {ierr = MatSetOption(b->A,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3292 if (!o_realalloc) {ierr = MatSetOption(b->B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);} 3293 B->preallocated = PETSC_TRUE; 3294 PetscFunctionReturn(0); 3295 } 3296 EXTERN_C_END 3297 3298 #undef __FUNCT__ 3299 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3300 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3301 { 3302 Mat mat; 3303 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3304 PetscErrorCode ierr; 3305 3306 PetscFunctionBegin; 3307 *newmat = 0; 3308 ierr = MatCreate(((PetscObject)matin)->comm,&mat);CHKERRQ(ierr); 3309 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3310 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3311 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3312 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3313 a = (Mat_MPIAIJ*)mat->data; 3314 3315 mat->factortype = matin->factortype; 3316 mat->rmap->bs = matin->rmap->bs; 3317 mat->cmap->bs = matin->cmap->bs; 3318 mat->assembled = PETSC_TRUE; 3319 mat->insertmode = NOT_SET_VALUES; 3320 mat->preallocated = PETSC_TRUE; 3321 3322 a->size = oldmat->size; 3323 a->rank = oldmat->rank; 3324 a->donotstash = oldmat->donotstash; 3325 a->roworiented = oldmat->roworiented; 3326 a->rowindices = 0; 3327 a->rowvalues = 0; 3328 a->getrowactive = PETSC_FALSE; 3329 3330 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3331 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3332 3333 if (oldmat->colmap) { 3334 #if defined (PETSC_USE_CTABLE) 3335 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3336 #else 3337 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3338 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3339 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3340 #endif 3341 } else a->colmap = 0; 3342 if (oldmat->garray) { 3343 PetscInt len; 3344 len = oldmat->B->cmap->n; 3345 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3346 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3347 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3348 } else a->garray = 0; 3349 3350 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3351 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3352 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3353 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3354 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3355 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3356 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3357 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3358 ierr = PetscFListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3359 *newmat = mat; 3360 PetscFunctionReturn(0); 3361 } 3362 3363 3364 3365 #undef __FUNCT__ 3366 #define __FUNCT__ "MatLoad_MPIAIJ" 3367 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3368 { 3369 PetscScalar *vals,*svals; 3370 MPI_Comm comm = ((PetscObject)viewer)->comm; 3371 PetscErrorCode ierr; 3372 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3373 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3374 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3375 PetscInt *ourlens = PETSC_NULL,*procsnz = PETSC_NULL,*offlens = PETSC_NULL,jj,*mycols,*smycols; 3376 PetscInt cend,cstart,n,*rowners,sizesset=1; 3377 int fd; 3378 PetscInt bs = 1; 3379 3380 PetscFunctionBegin; 3381 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3382 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3383 if (!rank) { 3384 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3385 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 3386 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3387 } 3388 3389 ierr = PetscOptionsBegin(comm,PETSC_NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3390 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,PETSC_NULL);CHKERRQ(ierr); 3391 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3392 3393 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3394 3395 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3396 M = header[1]; N = header[2]; 3397 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3398 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3399 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3400 3401 /* If global sizes are set, check if they are consistent with that given in the file */ 3402 if (sizesset) { 3403 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3404 } 3405 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); 3406 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); 3407 3408 /* determine ownership of all (block) rows */ 3409 if ( M%bs ) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3410 if (newMat->rmap->n < 0 ) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3411 else m = newMat->rmap->n; /* Set by user */ 3412 3413 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3414 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3415 3416 /* First process needs enough room for process with most rows */ 3417 if (!rank) { 3418 mmax = rowners[1]; 3419 for (i=2; i<=size; i++) { 3420 mmax = PetscMax(mmax, rowners[i]); 3421 } 3422 } else mmax = m; 3423 3424 rowners[0] = 0; 3425 for (i=2; i<=size; i++) { 3426 rowners[i] += rowners[i-1]; 3427 } 3428 rstart = rowners[rank]; 3429 rend = rowners[rank+1]; 3430 3431 /* distribute row lengths to all processors */ 3432 ierr = PetscMalloc2(mmax,PetscInt,&ourlens,mmax,PetscInt,&offlens);CHKERRQ(ierr); 3433 if (!rank) { 3434 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3435 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3436 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3437 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3438 for (j=0; j<m; j++) { 3439 procsnz[0] += ourlens[j]; 3440 } 3441 for (i=1; i<size; i++) { 3442 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3443 /* calculate the number of nonzeros on each processor */ 3444 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3445 procsnz[i] += rowlengths[j]; 3446 } 3447 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3448 } 3449 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3450 } else { 3451 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3452 } 3453 3454 if (!rank) { 3455 /* determine max buffer needed and allocate it */ 3456 maxnz = 0; 3457 for (i=0; i<size; i++) { 3458 maxnz = PetscMax(maxnz,procsnz[i]); 3459 } 3460 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3461 3462 /* read in my part of the matrix column indices */ 3463 nz = procsnz[0]; 3464 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3465 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3466 3467 /* read in every one elses and ship off */ 3468 for (i=1; i<size; i++) { 3469 nz = procsnz[i]; 3470 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3471 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3472 } 3473 ierr = PetscFree(cols);CHKERRQ(ierr); 3474 } else { 3475 /* determine buffer space needed for message */ 3476 nz = 0; 3477 for (i=0; i<m; i++) { 3478 nz += ourlens[i]; 3479 } 3480 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3481 3482 /* receive message of column indices*/ 3483 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3484 } 3485 3486 /* determine column ownership if matrix is not square */ 3487 if (N != M) { 3488 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3489 else n = newMat->cmap->n; 3490 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3491 cstart = cend - n; 3492 } else { 3493 cstart = rstart; 3494 cend = rend; 3495 n = cend - cstart; 3496 } 3497 3498 /* loop over local rows, determining number of off diagonal entries */ 3499 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3500 jj = 0; 3501 for (i=0; i<m; i++) { 3502 for (j=0; j<ourlens[i]; j++) { 3503 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3504 jj++; 3505 } 3506 } 3507 3508 for (i=0; i<m; i++) { 3509 ourlens[i] -= offlens[i]; 3510 } 3511 if (!sizesset) { 3512 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3513 } 3514 3515 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3516 3517 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3518 3519 for (i=0; i<m; i++) { 3520 ourlens[i] += offlens[i]; 3521 } 3522 3523 if (!rank) { 3524 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3525 3526 /* read in my part of the matrix numerical values */ 3527 nz = procsnz[0]; 3528 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3529 3530 /* insert into matrix */ 3531 jj = rstart; 3532 smycols = mycols; 3533 svals = vals; 3534 for (i=0; i<m; i++) { 3535 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3536 smycols += ourlens[i]; 3537 svals += ourlens[i]; 3538 jj++; 3539 } 3540 3541 /* read in other processors and ship out */ 3542 for (i=1; i<size; i++) { 3543 nz = procsnz[i]; 3544 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3545 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3546 } 3547 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3548 } else { 3549 /* receive numeric values */ 3550 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3551 3552 /* receive message of values*/ 3553 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3554 3555 /* insert into matrix */ 3556 jj = rstart; 3557 smycols = mycols; 3558 svals = vals; 3559 for (i=0; i<m; i++) { 3560 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3561 smycols += ourlens[i]; 3562 svals += ourlens[i]; 3563 jj++; 3564 } 3565 } 3566 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3567 ierr = PetscFree(vals);CHKERRQ(ierr); 3568 ierr = PetscFree(mycols);CHKERRQ(ierr); 3569 ierr = PetscFree(rowners);CHKERRQ(ierr); 3570 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3571 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3572 3573 PetscFunctionReturn(0); 3574 } 3575 3576 #undef __FUNCT__ 3577 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3578 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3579 { 3580 PetscErrorCode ierr; 3581 IS iscol_local; 3582 PetscInt csize; 3583 3584 PetscFunctionBegin; 3585 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3586 if (call == MAT_REUSE_MATRIX) { 3587 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3588 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3589 } else { 3590 PetscInt cbs; 3591 ierr = ISGetBlockSize(iscol,&cbs); CHKERRQ(ierr); 3592 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3593 ierr = ISSetBlockSize(iscol_local,cbs); CHKERRQ(ierr); 3594 } 3595 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3596 if (call == MAT_INITIAL_MATRIX) { 3597 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3598 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3599 } 3600 PetscFunctionReturn(0); 3601 } 3602 3603 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3604 #undef __FUNCT__ 3605 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3606 /* 3607 Not great since it makes two copies of the submatrix, first an SeqAIJ 3608 in local and then by concatenating the local matrices the end result. 3609 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3610 3611 Note: This requires a sequential iscol with all indices. 3612 */ 3613 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3614 { 3615 PetscErrorCode ierr; 3616 PetscMPIInt rank,size; 3617 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3618 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3619 PetscBool allcolumns, colflag; 3620 Mat M,Mreuse; 3621 MatScalar *vwork,*aa; 3622 MPI_Comm comm = ((PetscObject)mat)->comm; 3623 Mat_SeqAIJ *aij; 3624 3625 3626 PetscFunctionBegin; 3627 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3628 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3629 3630 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3631 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3632 if (colflag && ncol == mat->cmap->N){ 3633 allcolumns = PETSC_TRUE; 3634 } else { 3635 allcolumns = PETSC_FALSE; 3636 } 3637 if (call == MAT_REUSE_MATRIX) { 3638 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject *)&Mreuse);CHKERRQ(ierr); 3639 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3640 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3641 } else { 3642 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3643 } 3644 3645 /* 3646 m - number of local rows 3647 n - number of columns (same on all processors) 3648 rstart - first row in new global matrix generated 3649 */ 3650 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3651 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3652 if (call == MAT_INITIAL_MATRIX) { 3653 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3654 ii = aij->i; 3655 jj = aij->j; 3656 3657 /* 3658 Determine the number of non-zeros in the diagonal and off-diagonal 3659 portions of the matrix in order to do correct preallocation 3660 */ 3661 3662 /* first get start and end of "diagonal" columns */ 3663 if (csize == PETSC_DECIDE) { 3664 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3665 if (mglobal == n) { /* square matrix */ 3666 nlocal = m; 3667 } else { 3668 nlocal = n/size + ((n % size) > rank); 3669 } 3670 } else { 3671 nlocal = csize; 3672 } 3673 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3674 rstart = rend - nlocal; 3675 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); 3676 3677 /* next, compute all the lengths */ 3678 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3679 olens = dlens + m; 3680 for (i=0; i<m; i++) { 3681 jend = ii[i+1] - ii[i]; 3682 olen = 0; 3683 dlen = 0; 3684 for (j=0; j<jend; j++) { 3685 if (*jj < rstart || *jj >= rend) olen++; 3686 else dlen++; 3687 jj++; 3688 } 3689 olens[i] = olen; 3690 dlens[i] = dlen; 3691 } 3692 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3693 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3694 ierr = MatSetBlockSizes(M,bs,cbs); CHKERRQ(ierr); 3695 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3696 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3697 ierr = PetscFree(dlens);CHKERRQ(ierr); 3698 } else { 3699 PetscInt ml,nl; 3700 3701 M = *newmat; 3702 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3703 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3704 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3705 /* 3706 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3707 rather than the slower MatSetValues(). 3708 */ 3709 M->was_assembled = PETSC_TRUE; 3710 M->assembled = PETSC_FALSE; 3711 } 3712 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3713 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3714 ii = aij->i; 3715 jj = aij->j; 3716 aa = aij->a; 3717 for (i=0; i<m; i++) { 3718 row = rstart + i; 3719 nz = ii[i+1] - ii[i]; 3720 cwork = jj; jj += nz; 3721 vwork = aa; aa += nz; 3722 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3723 } 3724 3725 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3726 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3727 *newmat = M; 3728 3729 /* save submatrix used in processor for next request */ 3730 if (call == MAT_INITIAL_MATRIX) { 3731 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3732 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3733 } 3734 3735 PetscFunctionReturn(0); 3736 } 3737 3738 EXTERN_C_BEGIN 3739 #undef __FUNCT__ 3740 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3741 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3742 { 3743 PetscInt m,cstart, cend,j,nnz,i,d; 3744 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3745 const PetscInt *JJ; 3746 PetscScalar *values; 3747 PetscErrorCode ierr; 3748 3749 PetscFunctionBegin; 3750 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3751 3752 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3753 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3754 m = B->rmap->n; 3755 cstart = B->cmap->rstart; 3756 cend = B->cmap->rend; 3757 rstart = B->rmap->rstart; 3758 3759 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3760 3761 #if defined(PETSC_USE_DEBUGGING) 3762 for (i=0; i<m; i++) { 3763 nnz = Ii[i+1]- Ii[i]; 3764 JJ = J + Ii[i]; 3765 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3766 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3767 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); 3768 } 3769 #endif 3770 3771 for (i=0; i<m; i++) { 3772 nnz = Ii[i+1]- Ii[i]; 3773 JJ = J + Ii[i]; 3774 nnz_max = PetscMax(nnz_max,nnz); 3775 d = 0; 3776 for (j=0; j<nnz; j++) { 3777 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3778 } 3779 d_nnz[i] = d; 3780 o_nnz[i] = nnz - d; 3781 } 3782 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3783 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3784 3785 if (v) values = (PetscScalar*)v; 3786 else { 3787 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3788 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3789 } 3790 3791 for (i=0; i<m; i++) { 3792 ii = i + rstart; 3793 nnz = Ii[i+1]- Ii[i]; 3794 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3795 } 3796 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3797 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3798 3799 if (!v) { 3800 ierr = PetscFree(values);CHKERRQ(ierr); 3801 } 3802 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3803 PetscFunctionReturn(0); 3804 } 3805 EXTERN_C_END 3806 3807 #undef __FUNCT__ 3808 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3809 /*@ 3810 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3811 (the default parallel PETSc format). 3812 3813 Collective on MPI_Comm 3814 3815 Input Parameters: 3816 + B - the matrix 3817 . i - the indices into j for the start of each local row (starts with zero) 3818 . j - the column indices for each local row (starts with zero) 3819 - v - optional values in the matrix 3820 3821 Level: developer 3822 3823 Notes: 3824 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3825 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3826 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3827 3828 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3829 3830 The format which is used for the sparse matrix input, is equivalent to a 3831 row-major ordering.. i.e for the following matrix, the input data expected is 3832 as shown: 3833 3834 1 0 0 3835 2 0 3 P0 3836 ------- 3837 4 5 6 P1 3838 3839 Process0 [P0]: rows_owned=[0,1] 3840 i = {0,1,3} [size = nrow+1 = 2+1] 3841 j = {0,0,2} [size = nz = 6] 3842 v = {1,2,3} [size = nz = 6] 3843 3844 Process1 [P1]: rows_owned=[2] 3845 i = {0,3} [size = nrow+1 = 1+1] 3846 j = {0,1,2} [size = nz = 6] 3847 v = {4,5,6} [size = nz = 6] 3848 3849 .keywords: matrix, aij, compressed row, sparse, parallel 3850 3851 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3852 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3853 @*/ 3854 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3855 { 3856 PetscErrorCode ierr; 3857 3858 PetscFunctionBegin; 3859 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3860 PetscFunctionReturn(0); 3861 } 3862 3863 #undef __FUNCT__ 3864 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3865 /*@C 3866 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3867 (the default parallel PETSc format). For good matrix assembly performance 3868 the user should preallocate the matrix storage by setting the parameters 3869 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3870 performance can be increased by more than a factor of 50. 3871 3872 Collective on MPI_Comm 3873 3874 Input Parameters: 3875 + A - the matrix 3876 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3877 (same value is used for all local rows) 3878 . d_nnz - array containing the number of nonzeros in the various rows of the 3879 DIAGONAL portion of the local submatrix (possibly different for each row) 3880 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 3881 The size of this array is equal to the number of local rows, i.e 'm'. 3882 For matrices that will be factored, you must leave room for (and set) 3883 the diagonal entry even if it is zero. 3884 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3885 submatrix (same value is used for all local rows). 3886 - o_nnz - array containing the number of nonzeros in the various rows of the 3887 OFF-DIAGONAL portion of the local submatrix (possibly different for 3888 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 3889 structure. The size of this array is equal to the number 3890 of local rows, i.e 'm'. 3891 3892 If the *_nnz parameter is given then the *_nz parameter is ignored 3893 3894 The AIJ format (also called the Yale sparse matrix format or 3895 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3896 storage. The stored row and column indices begin with zero. 3897 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 3898 3899 The parallel matrix is partitioned such that the first m0 rows belong to 3900 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3901 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3902 3903 The DIAGONAL portion of the local submatrix of a processor can be defined 3904 as the submatrix which is obtained by extraction the part corresponding to 3905 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3906 first row that belongs to the processor, r2 is the last row belonging to 3907 the this processor, and c1-c2 is range of indices of the local part of a 3908 vector suitable for applying the matrix to. This is an mxn matrix. In the 3909 common case of a square matrix, the row and column ranges are the same and 3910 the DIAGONAL part is also square. The remaining portion of the local 3911 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3912 3913 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3914 3915 You can call MatGetInfo() to get information on how effective the preallocation was; 3916 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3917 You can also run with the option -info and look for messages with the string 3918 malloc in them to see if additional memory allocation was needed. 3919 3920 Example usage: 3921 3922 Consider the following 8x8 matrix with 34 non-zero values, that is 3923 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3924 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3925 as follows: 3926 3927 .vb 3928 1 2 0 | 0 3 0 | 0 4 3929 Proc0 0 5 6 | 7 0 0 | 8 0 3930 9 0 10 | 11 0 0 | 12 0 3931 ------------------------------------- 3932 13 0 14 | 15 16 17 | 0 0 3933 Proc1 0 18 0 | 19 20 21 | 0 0 3934 0 0 0 | 22 23 0 | 24 0 3935 ------------------------------------- 3936 Proc2 25 26 27 | 0 0 28 | 29 0 3937 30 0 0 | 31 32 33 | 0 34 3938 .ve 3939 3940 This can be represented as a collection of submatrices as: 3941 3942 .vb 3943 A B C 3944 D E F 3945 G H I 3946 .ve 3947 3948 Where the submatrices A,B,C are owned by proc0, D,E,F are 3949 owned by proc1, G,H,I are owned by proc2. 3950 3951 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3952 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 3953 The 'M','N' parameters are 8,8, and have the same values on all procs. 3954 3955 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 3956 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 3957 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 3958 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 3959 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 3960 matrix, ans [DF] as another SeqAIJ matrix. 3961 3962 When d_nz, o_nz parameters are specified, d_nz storage elements are 3963 allocated for every row of the local diagonal submatrix, and o_nz 3964 storage locations are allocated for every row of the OFF-DIAGONAL submat. 3965 One way to choose d_nz and o_nz is to use the max nonzerors per local 3966 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 3967 In this case, the values of d_nz,o_nz are: 3968 .vb 3969 proc0 : dnz = 2, o_nz = 2 3970 proc1 : dnz = 3, o_nz = 2 3971 proc2 : dnz = 1, o_nz = 4 3972 .ve 3973 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 3974 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 3975 for proc3. i.e we are using 12+15+10=37 storage locations to store 3976 34 values. 3977 3978 When d_nnz, o_nnz parameters are specified, the storage is specified 3979 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 3980 In the above case the values for d_nnz,o_nnz are: 3981 .vb 3982 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 3983 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 3984 proc2: d_nnz = [1,1] and o_nnz = [4,4] 3985 .ve 3986 Here the space allocated is sum of all the above values i.e 34, and 3987 hence pre-allocation is perfect. 3988 3989 Level: intermediate 3990 3991 .keywords: matrix, aij, compressed row, sparse, parallel 3992 3993 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 3994 MPIAIJ, MatGetInfo() 3995 @*/ 3996 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3997 { 3998 PetscErrorCode ierr; 3999 4000 PetscFunctionBegin; 4001 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4002 PetscValidType(B,1); 4003 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4004 PetscFunctionReturn(0); 4005 } 4006 4007 #undef __FUNCT__ 4008 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4009 /*@ 4010 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4011 CSR format the local rows. 4012 4013 Collective on MPI_Comm 4014 4015 Input Parameters: 4016 + comm - MPI communicator 4017 . m - number of local rows (Cannot be PETSC_DECIDE) 4018 . n - This value should be the same as the local size used in creating the 4019 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4020 calculated if N is given) For square matrices n is almost always m. 4021 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4022 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4023 . i - row indices 4024 . j - column indices 4025 - a - matrix values 4026 4027 Output Parameter: 4028 . mat - the matrix 4029 4030 Level: intermediate 4031 4032 Notes: 4033 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4034 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4035 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4036 4037 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4038 4039 The format which is used for the sparse matrix input, is equivalent to a 4040 row-major ordering.. i.e for the following matrix, the input data expected is 4041 as shown: 4042 4043 1 0 0 4044 2 0 3 P0 4045 ------- 4046 4 5 6 P1 4047 4048 Process0 [P0]: rows_owned=[0,1] 4049 i = {0,1,3} [size = nrow+1 = 2+1] 4050 j = {0,0,2} [size = nz = 6] 4051 v = {1,2,3} [size = nz = 6] 4052 4053 Process1 [P1]: rows_owned=[2] 4054 i = {0,3} [size = nrow+1 = 1+1] 4055 j = {0,1,2} [size = nz = 6] 4056 v = {4,5,6} [size = nz = 6] 4057 4058 .keywords: matrix, aij, compressed row, sparse, parallel 4059 4060 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4061 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4062 @*/ 4063 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4064 { 4065 PetscErrorCode ierr; 4066 4067 PetscFunctionBegin; 4068 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4069 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4070 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4071 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4072 /* ierr = MatSetBlockSizes(M,bs,cbs); CHKERRQ(ierr); */ 4073 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4074 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4075 PetscFunctionReturn(0); 4076 } 4077 4078 #undef __FUNCT__ 4079 #define __FUNCT__ "MatCreateAIJ" 4080 /*@C 4081 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4082 (the default parallel PETSc format). For good matrix assembly performance 4083 the user should preallocate the matrix storage by setting the parameters 4084 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4085 performance can be increased by more than a factor of 50. 4086 4087 Collective on MPI_Comm 4088 4089 Input Parameters: 4090 + comm - MPI communicator 4091 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4092 This value should be the same as the local size used in creating the 4093 y vector for the matrix-vector product y = Ax. 4094 . n - This value should be the same as the local size used in creating the 4095 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4096 calculated if N is given) For square matrices n is almost always m. 4097 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4098 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4099 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4100 (same value is used for all local rows) 4101 . d_nnz - array containing the number of nonzeros in the various rows of the 4102 DIAGONAL portion of the local submatrix (possibly different for each row) 4103 or PETSC_NULL, if d_nz is used to specify the nonzero structure. 4104 The size of this array is equal to the number of local rows, i.e 'm'. 4105 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4106 submatrix (same value is used for all local rows). 4107 - o_nnz - array containing the number of nonzeros in the various rows of the 4108 OFF-DIAGONAL portion of the local submatrix (possibly different for 4109 each row) or PETSC_NULL, if o_nz is used to specify the nonzero 4110 structure. The size of this array is equal to the number 4111 of local rows, i.e 'm'. 4112 4113 Output Parameter: 4114 . A - the matrix 4115 4116 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4117 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4118 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4119 4120 Notes: 4121 If the *_nnz parameter is given then the *_nz parameter is ignored 4122 4123 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4124 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4125 storage requirements for this matrix. 4126 4127 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4128 processor than it must be used on all processors that share the object for 4129 that argument. 4130 4131 The user MUST specify either the local or global matrix dimensions 4132 (possibly both). 4133 4134 The parallel matrix is partitioned across processors such that the 4135 first m0 rows belong to process 0, the next m1 rows belong to 4136 process 1, the next m2 rows belong to process 2 etc.. where 4137 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4138 values corresponding to [m x N] submatrix. 4139 4140 The columns are logically partitioned with the n0 columns belonging 4141 to 0th partition, the next n1 columns belonging to the next 4142 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4143 4144 The DIAGONAL portion of the local submatrix on any given processor 4145 is the submatrix corresponding to the rows and columns m,n 4146 corresponding to the given processor. i.e diagonal matrix on 4147 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4148 etc. The remaining portion of the local submatrix [m x (N-n)] 4149 constitute the OFF-DIAGONAL portion. The example below better 4150 illustrates this concept. 4151 4152 For a square global matrix we define each processor's diagonal portion 4153 to be its local rows and the corresponding columns (a square submatrix); 4154 each processor's off-diagonal portion encompasses the remainder of the 4155 local matrix (a rectangular submatrix). 4156 4157 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4158 4159 When calling this routine with a single process communicator, a matrix of 4160 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4161 type of communicator, use the construction mechanism: 4162 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4163 4164 By default, this format uses inodes (identical nodes) when possible. 4165 We search for consecutive rows with the same nonzero structure, thereby 4166 reusing matrix information to achieve increased efficiency. 4167 4168 Options Database Keys: 4169 + -mat_no_inode - Do not use inodes 4170 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4171 - -mat_aij_oneindex - Internally use indexing starting at 1 4172 rather than 0. Note that when calling MatSetValues(), 4173 the user still MUST index entries starting at 0! 4174 4175 4176 Example usage: 4177 4178 Consider the following 8x8 matrix with 34 non-zero values, that is 4179 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4180 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4181 as follows: 4182 4183 .vb 4184 1 2 0 | 0 3 0 | 0 4 4185 Proc0 0 5 6 | 7 0 0 | 8 0 4186 9 0 10 | 11 0 0 | 12 0 4187 ------------------------------------- 4188 13 0 14 | 15 16 17 | 0 0 4189 Proc1 0 18 0 | 19 20 21 | 0 0 4190 0 0 0 | 22 23 0 | 24 0 4191 ------------------------------------- 4192 Proc2 25 26 27 | 0 0 28 | 29 0 4193 30 0 0 | 31 32 33 | 0 34 4194 .ve 4195 4196 This can be represented as a collection of submatrices as: 4197 4198 .vb 4199 A B C 4200 D E F 4201 G H I 4202 .ve 4203 4204 Where the submatrices A,B,C are owned by proc0, D,E,F are 4205 owned by proc1, G,H,I are owned by proc2. 4206 4207 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4208 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4209 The 'M','N' parameters are 8,8, and have the same values on all procs. 4210 4211 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4212 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4213 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4214 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4215 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4216 matrix, ans [DF] as another SeqAIJ matrix. 4217 4218 When d_nz, o_nz parameters are specified, d_nz storage elements are 4219 allocated for every row of the local diagonal submatrix, and o_nz 4220 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4221 One way to choose d_nz and o_nz is to use the max nonzerors per local 4222 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4223 In this case, the values of d_nz,o_nz are: 4224 .vb 4225 proc0 : dnz = 2, o_nz = 2 4226 proc1 : dnz = 3, o_nz = 2 4227 proc2 : dnz = 1, o_nz = 4 4228 .ve 4229 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4230 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4231 for proc3. i.e we are using 12+15+10=37 storage locations to store 4232 34 values. 4233 4234 When d_nnz, o_nnz parameters are specified, the storage is specified 4235 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4236 In the above case the values for d_nnz,o_nnz are: 4237 .vb 4238 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4239 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4240 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4241 .ve 4242 Here the space allocated is sum of all the above values i.e 34, and 4243 hence pre-allocation is perfect. 4244 4245 Level: intermediate 4246 4247 .keywords: matrix, aij, compressed row, sparse, parallel 4248 4249 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4250 MPIAIJ, MatCreateMPIAIJWithArrays() 4251 @*/ 4252 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) 4253 { 4254 PetscErrorCode ierr; 4255 PetscMPIInt size; 4256 4257 PetscFunctionBegin; 4258 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4259 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4260 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4261 if (size > 1) { 4262 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4263 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4264 } else { 4265 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4266 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4267 } 4268 PetscFunctionReturn(0); 4269 } 4270 4271 #undef __FUNCT__ 4272 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4273 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,PetscInt *colmap[]) 4274 { 4275 Mat_MPIAIJ *a = (Mat_MPIAIJ *)A->data; 4276 4277 PetscFunctionBegin; 4278 *Ad = a->A; 4279 *Ao = a->B; 4280 *colmap = a->garray; 4281 PetscFunctionReturn(0); 4282 } 4283 4284 #undef __FUNCT__ 4285 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4286 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4287 { 4288 PetscErrorCode ierr; 4289 PetscInt i; 4290 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4291 4292 PetscFunctionBegin; 4293 if (coloring->ctype == IS_COLORING_GLOBAL) { 4294 ISColoringValue *allcolors,*colors; 4295 ISColoring ocoloring; 4296 4297 /* set coloring for diagonal portion */ 4298 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4299 4300 /* set coloring for off-diagonal portion */ 4301 ierr = ISAllGatherColors(((PetscObject)A)->comm,coloring->n,coloring->colors,PETSC_NULL,&allcolors);CHKERRQ(ierr); 4302 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4303 for (i=0; i<a->B->cmap->n; i++) { 4304 colors[i] = allcolors[a->garray[i]]; 4305 } 4306 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4307 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4308 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4309 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4310 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4311 ISColoringValue *colors; 4312 PetscInt *larray; 4313 ISColoring ocoloring; 4314 4315 /* set coloring for diagonal portion */ 4316 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4317 for (i=0; i<a->A->cmap->n; i++) { 4318 larray[i] = i + A->cmap->rstart; 4319 } 4320 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 4321 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4322 for (i=0; i<a->A->cmap->n; i++) { 4323 colors[i] = coloring->colors[larray[i]]; 4324 } 4325 ierr = PetscFree(larray);CHKERRQ(ierr); 4326 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4327 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4328 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4329 4330 /* set coloring for off-diagonal portion */ 4331 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4332 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,PETSC_NULL,larray);CHKERRQ(ierr); 4333 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4334 for (i=0; i<a->B->cmap->n; i++) { 4335 colors[i] = coloring->colors[larray[i]]; 4336 } 4337 ierr = PetscFree(larray);CHKERRQ(ierr); 4338 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4339 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4340 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4341 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4342 4343 PetscFunctionReturn(0); 4344 } 4345 4346 #if defined(PETSC_HAVE_ADIC) 4347 #undef __FUNCT__ 4348 #define __FUNCT__ "MatSetValuesAdic_MPIAIJ" 4349 PetscErrorCode MatSetValuesAdic_MPIAIJ(Mat A,void *advalues) 4350 { 4351 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4352 PetscErrorCode ierr; 4353 4354 PetscFunctionBegin; 4355 ierr = MatSetValuesAdic_SeqAIJ(a->A,advalues);CHKERRQ(ierr); 4356 ierr = MatSetValuesAdic_SeqAIJ(a->B,advalues);CHKERRQ(ierr); 4357 PetscFunctionReturn(0); 4358 } 4359 #endif 4360 4361 #undef __FUNCT__ 4362 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4363 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4364 { 4365 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4366 PetscErrorCode ierr; 4367 4368 PetscFunctionBegin; 4369 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4370 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4371 PetscFunctionReturn(0); 4372 } 4373 4374 #undef __FUNCT__ 4375 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4376 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4377 { 4378 PetscErrorCode ierr; 4379 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4380 PetscInt *indx; 4381 4382 PetscFunctionBegin; 4383 /* This routine will ONLY return MPIAIJ type matrix */ 4384 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4385 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4386 if (n == PETSC_DECIDE){ 4387 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4388 } 4389 /* Check sum(n) = N */ 4390 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4391 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4392 4393 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4394 rstart -= m; 4395 4396 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4397 for (i=0;i<m;i++) { 4398 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 4399 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4400 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,PETSC_NULL);CHKERRQ(ierr); 4401 } 4402 4403 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4404 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE); CHKERRQ(ierr); 4405 ierr = MatSetBlockSizes(*outmat,bs,cbs); CHKERRQ(ierr); 4406 ierr = MatSetType(*outmat,MATMPIAIJ); CHKERRQ(ierr); 4407 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4408 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4409 PetscFunctionReturn(0); 4410 } 4411 4412 #undef __FUNCT__ 4413 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4414 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4415 { 4416 PetscErrorCode ierr; 4417 PetscInt m,N,i,rstart,nnz,Ii; 4418 PetscInt *indx; 4419 PetscScalar *values; 4420 4421 PetscFunctionBegin; 4422 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4423 ierr = MatGetOwnershipRange(outmat,&rstart,PETSC_NULL);CHKERRQ(ierr); 4424 for (i=0;i<m;i++) { 4425 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4426 Ii = i + rstart; 4427 ierr = MatSetValues_MPIAIJ(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4428 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4429 } 4430 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4431 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4432 PetscFunctionReturn(0); 4433 } 4434 4435 #undef __FUNCT__ 4436 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4437 /*@ 4438 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4439 matrices from each processor 4440 4441 Collective on MPI_Comm 4442 4443 Input Parameters: 4444 + comm - the communicators the parallel matrix will live on 4445 . inmat - the input sequential matrices 4446 . n - number of local columns (or PETSC_DECIDE) 4447 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4448 4449 Output Parameter: 4450 . outmat - the parallel matrix generated 4451 4452 Level: advanced 4453 4454 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4455 4456 @*/ 4457 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4458 { 4459 PetscErrorCode ierr; 4460 4461 PetscFunctionBegin; 4462 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4463 if (scall == MAT_INITIAL_MATRIX){ 4464 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4465 } 4466 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4467 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4468 PetscFunctionReturn(0); 4469 } 4470 4471 #undef __FUNCT__ 4472 #define __FUNCT__ "MatFileSplit" 4473 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4474 { 4475 PetscErrorCode ierr; 4476 PetscMPIInt rank; 4477 PetscInt m,N,i,rstart,nnz; 4478 size_t len; 4479 const PetscInt *indx; 4480 PetscViewer out; 4481 char *name; 4482 Mat B; 4483 const PetscScalar *values; 4484 4485 PetscFunctionBegin; 4486 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4487 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4488 /* Should this be the type of the diagonal block of A? */ 4489 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4490 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4491 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4492 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4493 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL);CHKERRQ(ierr); 4494 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4495 for (i=0;i<m;i++) { 4496 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4497 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4498 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4499 } 4500 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4501 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4502 4503 ierr = MPI_Comm_rank(((PetscObject)A)->comm,&rank);CHKERRQ(ierr); 4504 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4505 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4506 sprintf(name,"%s.%d",outfile,rank); 4507 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4508 ierr = PetscFree(name); 4509 ierr = MatView(B,out);CHKERRQ(ierr); 4510 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4511 ierr = MatDestroy(&B);CHKERRQ(ierr); 4512 PetscFunctionReturn(0); 4513 } 4514 4515 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4516 #undef __FUNCT__ 4517 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4518 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4519 { 4520 PetscErrorCode ierr; 4521 Mat_Merge_SeqsToMPI *merge; 4522 PetscContainer container; 4523 4524 PetscFunctionBegin; 4525 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 4526 if (container) { 4527 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 4528 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4529 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4530 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4531 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4532 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4533 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4534 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4535 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4536 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4537 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4538 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4539 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4540 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4541 ierr = PetscFree(merge);CHKERRQ(ierr); 4542 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4543 } 4544 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4545 PetscFunctionReturn(0); 4546 } 4547 4548 #include <../src/mat/utils/freespace.h> 4549 #include <petscbt.h> 4550 4551 #undef __FUNCT__ 4552 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4553 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4554 { 4555 PetscErrorCode ierr; 4556 MPI_Comm comm=((PetscObject)mpimat)->comm; 4557 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4558 PetscMPIInt size,rank,taga,*len_s; 4559 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj=a->j; 4560 PetscInt proc,m; 4561 PetscInt **buf_ri,**buf_rj; 4562 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4563 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4564 MPI_Request *s_waits,*r_waits; 4565 MPI_Status *status; 4566 MatScalar *aa=a->a; 4567 MatScalar **abuf_r,*ba_i; 4568 Mat_Merge_SeqsToMPI *merge; 4569 PetscContainer container; 4570 4571 PetscFunctionBegin; 4572 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4573 4574 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4575 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4576 4577 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject *)&container);CHKERRQ(ierr); 4578 ierr = PetscContainerGetPointer(container,(void **)&merge);CHKERRQ(ierr); 4579 4580 bi = merge->bi; 4581 bj = merge->bj; 4582 buf_ri = merge->buf_ri; 4583 buf_rj = merge->buf_rj; 4584 4585 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4586 owners = merge->rowmap->range; 4587 len_s = merge->len_s; 4588 4589 /* send and recv matrix values */ 4590 /*-----------------------------*/ 4591 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4592 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4593 4594 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4595 for (proc=0,k=0; proc<size; proc++){ 4596 if (!len_s[proc]) continue; 4597 i = owners[proc]; 4598 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4599 k++; 4600 } 4601 4602 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4603 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4604 ierr = PetscFree(status);CHKERRQ(ierr); 4605 4606 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4607 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4608 4609 /* insert mat values of mpimat */ 4610 /*----------------------------*/ 4611 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4612 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4613 4614 for (k=0; k<merge->nrecv; k++){ 4615 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4616 nrows = *(buf_ri_k[k]); 4617 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4618 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4619 } 4620 4621 /* set values of ba */ 4622 m = merge->rowmap->n; 4623 for (i=0; i<m; i++) { 4624 arow = owners[rank] + i; 4625 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4626 bnzi = bi[i+1] - bi[i]; 4627 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4628 4629 /* add local non-zero vals of this proc's seqmat into ba */ 4630 anzi = ai[arow+1] - ai[arow]; 4631 aj = a->j + ai[arow]; 4632 aa = a->a + ai[arow]; 4633 nextaj = 0; 4634 for (j=0; nextaj<anzi; j++){ 4635 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4636 ba_i[j] += aa[nextaj++]; 4637 } 4638 } 4639 4640 /* add received vals into ba */ 4641 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4642 /* i-th row */ 4643 if (i == *nextrow[k]) { 4644 anzi = *(nextai[k]+1) - *nextai[k]; 4645 aj = buf_rj[k] + *(nextai[k]); 4646 aa = abuf_r[k] + *(nextai[k]); 4647 nextaj = 0; 4648 for (j=0; nextaj<anzi; j++){ 4649 if (*(bj_i + j) == aj[nextaj]){ /* bcol == acol */ 4650 ba_i[j] += aa[nextaj++]; 4651 } 4652 } 4653 nextrow[k]++; nextai[k]++; 4654 } 4655 } 4656 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4657 } 4658 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4659 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4660 4661 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4662 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4663 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4664 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4665 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4666 PetscFunctionReturn(0); 4667 } 4668 4669 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4670 4671 #undef __FUNCT__ 4672 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4673 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4674 { 4675 PetscErrorCode ierr; 4676 Mat B_mpi; 4677 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4678 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4679 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4680 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4681 PetscInt len,proc,*dnz,*onz,bs,cbs; 4682 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4683 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4684 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4685 MPI_Status *status; 4686 PetscFreeSpaceList free_space=PETSC_NULL,current_space=PETSC_NULL; 4687 PetscBT lnkbt; 4688 Mat_Merge_SeqsToMPI *merge; 4689 PetscContainer container; 4690 4691 PetscFunctionBegin; 4692 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4693 4694 /* make sure it is a PETSc comm */ 4695 ierr = PetscCommDuplicate(comm,&comm,PETSC_NULL);CHKERRQ(ierr); 4696 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4697 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4698 4699 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4700 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4701 4702 /* determine row ownership */ 4703 /*---------------------------------------------------------*/ 4704 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4705 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4706 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4707 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4708 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4709 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4710 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4711 4712 m = merge->rowmap->n; 4713 M = merge->rowmap->N; 4714 owners = merge->rowmap->range; 4715 4716 /* determine the number of messages to send, their lengths */ 4717 /*---------------------------------------------------------*/ 4718 len_s = merge->len_s; 4719 4720 len = 0; /* length of buf_si[] */ 4721 merge->nsend = 0; 4722 for (proc=0; proc<size; proc++){ 4723 len_si[proc] = 0; 4724 if (proc == rank){ 4725 len_s[proc] = 0; 4726 } else { 4727 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4728 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4729 } 4730 if (len_s[proc]) { 4731 merge->nsend++; 4732 nrows = 0; 4733 for (i=owners[proc]; i<owners[proc+1]; i++){ 4734 if (ai[i+1] > ai[i]) nrows++; 4735 } 4736 len_si[proc] = 2*(nrows+1); 4737 len += len_si[proc]; 4738 } 4739 } 4740 4741 /* determine the number and length of messages to receive for ij-structure */ 4742 /*-------------------------------------------------------------------------*/ 4743 ierr = PetscGatherNumberOfMessages(comm,PETSC_NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4744 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4745 4746 /* post the Irecv of j-structure */ 4747 /*-------------------------------*/ 4748 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4749 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4750 4751 /* post the Isend of j-structure */ 4752 /*--------------------------------*/ 4753 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4754 4755 for (proc=0, k=0; proc<size; proc++){ 4756 if (!len_s[proc]) continue; 4757 i = owners[proc]; 4758 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4759 k++; 4760 } 4761 4762 /* receives and sends of j-structure are complete */ 4763 /*------------------------------------------------*/ 4764 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4765 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4766 4767 /* send and recv i-structure */ 4768 /*---------------------------*/ 4769 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4770 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4771 4772 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4773 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4774 for (proc=0,k=0; proc<size; proc++){ 4775 if (!len_s[proc]) continue; 4776 /* form outgoing message for i-structure: 4777 buf_si[0]: nrows to be sent 4778 [1:nrows]: row index (global) 4779 [nrows+1:2*nrows+1]: i-structure index 4780 */ 4781 /*-------------------------------------------*/ 4782 nrows = len_si[proc]/2 - 1; 4783 buf_si_i = buf_si + nrows+1; 4784 buf_si[0] = nrows; 4785 buf_si_i[0] = 0; 4786 nrows = 0; 4787 for (i=owners[proc]; i<owners[proc+1]; i++){ 4788 anzi = ai[i+1] - ai[i]; 4789 if (anzi) { 4790 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4791 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4792 nrows++; 4793 } 4794 } 4795 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4796 k++; 4797 buf_si += len_si[proc]; 4798 } 4799 4800 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4801 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4802 4803 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4804 for (i=0; i<merge->nrecv; i++){ 4805 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); 4806 } 4807 4808 ierr = PetscFree(len_si);CHKERRQ(ierr); 4809 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4810 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4811 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4812 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4813 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4814 ierr = PetscFree(status);CHKERRQ(ierr); 4815 4816 /* compute a local seq matrix in each processor */ 4817 /*----------------------------------------------*/ 4818 /* allocate bi array and free space for accumulating nonzero column info */ 4819 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4820 bi[0] = 0; 4821 4822 /* create and initialize a linked list */ 4823 nlnk = N+1; 4824 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4825 4826 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4827 len = 0; 4828 len = ai[owners[rank+1]] - ai[owners[rank]]; 4829 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4830 current_space = free_space; 4831 4832 /* determine symbolic info for each local row */ 4833 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4834 4835 for (k=0; k<merge->nrecv; k++){ 4836 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4837 nrows = *buf_ri_k[k]; 4838 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4839 nextai[k] = buf_ri_k[k] + (nrows + 1);/* poins to the next i-structure of k-th recved i-structure */ 4840 } 4841 4842 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4843 len = 0; 4844 for (i=0;i<m;i++) { 4845 bnzi = 0; 4846 /* add local non-zero cols of this proc's seqmat into lnk */ 4847 arow = owners[rank] + i; 4848 anzi = ai[arow+1] - ai[arow]; 4849 aj = a->j + ai[arow]; 4850 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4851 bnzi += nlnk; 4852 /* add received col data into lnk */ 4853 for (k=0; k<merge->nrecv; k++){ /* k-th received message */ 4854 if (i == *nextrow[k]) { /* i-th row */ 4855 anzi = *(nextai[k]+1) - *nextai[k]; 4856 aj = buf_rj[k] + *nextai[k]; 4857 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4858 bnzi += nlnk; 4859 nextrow[k]++; nextai[k]++; 4860 } 4861 } 4862 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4863 4864 /* if free space is not available, make more free space */ 4865 if (current_space->local_remaining<bnzi) { 4866 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4867 nspacedouble++; 4868 } 4869 /* copy data into free space, then initialize lnk */ 4870 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4871 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4872 4873 current_space->array += bnzi; 4874 current_space->local_used += bnzi; 4875 current_space->local_remaining -= bnzi; 4876 4877 bi[i+1] = bi[i] + bnzi; 4878 } 4879 4880 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4881 4882 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4883 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4884 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4885 4886 /* create symbolic parallel matrix B_mpi */ 4887 /*---------------------------------------*/ 4888 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4889 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4890 if (n==PETSC_DECIDE) { 4891 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4892 } else { 4893 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4894 } 4895 ierr = MatSetBlockSizes(B_mpi,bs,cbs); CHKERRQ(ierr); 4896 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4897 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4898 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4899 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4900 4901 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4902 B_mpi->assembled = PETSC_FALSE; 4903 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4904 merge->bi = bi; 4905 merge->bj = bj; 4906 merge->buf_ri = buf_ri; 4907 merge->buf_rj = buf_rj; 4908 merge->coi = PETSC_NULL; 4909 merge->coj = PETSC_NULL; 4910 merge->owners_co = PETSC_NULL; 4911 4912 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4913 4914 /* attach the supporting struct to B_mpi for reuse */ 4915 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4916 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4917 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4918 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4919 *mpimat = B_mpi; 4920 4921 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4922 PetscFunctionReturn(0); 4923 } 4924 4925 #undef __FUNCT__ 4926 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4927 /*@C 4928 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4929 matrices from each processor 4930 4931 Collective on MPI_Comm 4932 4933 Input Parameters: 4934 + comm - the communicators the parallel matrix will live on 4935 . seqmat - the input sequential matrices 4936 . m - number of local rows (or PETSC_DECIDE) 4937 . n - number of local columns (or PETSC_DECIDE) 4938 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4939 4940 Output Parameter: 4941 . mpimat - the parallel matrix generated 4942 4943 Level: advanced 4944 4945 Notes: 4946 The dimensions of the sequential matrix in each processor MUST be the same. 4947 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4948 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4949 @*/ 4950 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4951 { 4952 PetscErrorCode ierr; 4953 PetscMPIInt size; 4954 4955 PetscFunctionBegin; 4956 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4957 if (size == 1){ 4958 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4959 if (scall == MAT_INITIAL_MATRIX){ 4960 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4961 } else { 4962 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4963 } 4964 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4965 PetscFunctionReturn(0); 4966 } 4967 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4968 if (scall == MAT_INITIAL_MATRIX){ 4969 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 4970 } 4971 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 4972 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4973 PetscFunctionReturn(0); 4974 } 4975 4976 #undef __FUNCT__ 4977 #define __FUNCT__ "MatMPIAIJGetLocalMat" 4978 /*@ 4979 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 4980 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 4981 with MatGetSize() 4982 4983 Not Collective 4984 4985 Input Parameters: 4986 + A - the matrix 4987 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4988 4989 Output Parameter: 4990 . A_loc - the local sequential matrix generated 4991 4992 Level: developer 4993 4994 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 4995 4996 @*/ 4997 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 4998 { 4999 PetscErrorCode ierr; 5000 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5001 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5002 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5003 MatScalar *aa=a->a,*ba=b->a,*cam; 5004 PetscScalar *ca; 5005 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5006 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5007 PetscBool match; 5008 5009 PetscFunctionBegin; 5010 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5011 if (!match) SETERRQ(((PetscObject)A)->comm, PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5012 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5013 if (scall == MAT_INITIAL_MATRIX){ 5014 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5015 ci[0] = 0; 5016 for (i=0; i<am; i++){ 5017 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5018 } 5019 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5020 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5021 k = 0; 5022 for (i=0; i<am; i++) { 5023 ncols_o = bi[i+1] - bi[i]; 5024 ncols_d = ai[i+1] - ai[i]; 5025 /* off-diagonal portion of A */ 5026 for (jo=0; jo<ncols_o; jo++) { 5027 col = cmap[*bj]; 5028 if (col >= cstart) break; 5029 cj[k] = col; bj++; 5030 ca[k++] = *ba++; 5031 } 5032 /* diagonal portion of A */ 5033 for (j=0; j<ncols_d; j++) { 5034 cj[k] = cstart + *aj++; 5035 ca[k++] = *aa++; 5036 } 5037 /* off-diagonal portion of A */ 5038 for (j=jo; j<ncols_o; j++) { 5039 cj[k] = cmap[*bj++]; 5040 ca[k++] = *ba++; 5041 } 5042 } 5043 /* put together the new matrix */ 5044 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5045 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5046 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5047 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5048 mat->free_a = PETSC_TRUE; 5049 mat->free_ij = PETSC_TRUE; 5050 mat->nonew = 0; 5051 } else if (scall == MAT_REUSE_MATRIX){ 5052 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5053 ci = mat->i; cj = mat->j; cam = mat->a; 5054 for (i=0; i<am; i++) { 5055 /* off-diagonal portion of A */ 5056 ncols_o = bi[i+1] - bi[i]; 5057 for (jo=0; jo<ncols_o; jo++) { 5058 col = cmap[*bj]; 5059 if (col >= cstart) break; 5060 *cam++ = *ba++; bj++; 5061 } 5062 /* diagonal portion of A */ 5063 ncols_d = ai[i+1] - ai[i]; 5064 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5065 /* off-diagonal portion of A */ 5066 for (j=jo; j<ncols_o; j++) { 5067 *cam++ = *ba++; bj++; 5068 } 5069 } 5070 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5071 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5072 PetscFunctionReturn(0); 5073 } 5074 5075 #undef __FUNCT__ 5076 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5077 /*@C 5078 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5079 5080 Not Collective 5081 5082 Input Parameters: 5083 + A - the matrix 5084 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5085 - row, col - index sets of rows and columns to extract (or PETSC_NULL) 5086 5087 Output Parameter: 5088 . A_loc - the local sequential matrix generated 5089 5090 Level: developer 5091 5092 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5093 5094 @*/ 5095 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5096 { 5097 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5098 PetscErrorCode ierr; 5099 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5100 IS isrowa,iscola; 5101 Mat *aloc; 5102 PetscBool match; 5103 5104 PetscFunctionBegin; 5105 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5106 if (!match) SETERRQ(((PetscObject)A)->comm, PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5107 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5108 if (!row){ 5109 start = A->rmap->rstart; end = A->rmap->rend; 5110 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5111 } else { 5112 isrowa = *row; 5113 } 5114 if (!col){ 5115 start = A->cmap->rstart; 5116 cmap = a->garray; 5117 nzA = a->A->cmap->n; 5118 nzB = a->B->cmap->n; 5119 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5120 ncols = 0; 5121 for (i=0; i<nzB; i++) { 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; 5127 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5128 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5129 } else { 5130 iscola = *col; 5131 } 5132 if (scall != MAT_INITIAL_MATRIX){ 5133 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5134 aloc[0] = *A_loc; 5135 } 5136 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5137 *A_loc = aloc[0]; 5138 ierr = PetscFree(aloc);CHKERRQ(ierr); 5139 if (!row){ 5140 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5141 } 5142 if (!col){ 5143 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5144 } 5145 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5146 PetscFunctionReturn(0); 5147 } 5148 5149 #undef __FUNCT__ 5150 #define __FUNCT__ "MatGetBrowsOfAcols" 5151 /*@C 5152 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5153 5154 Collective on Mat 5155 5156 Input Parameters: 5157 + A,B - the matrices in mpiaij format 5158 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5159 - rowb, colb - index sets of rows and columns of B to extract (or PETSC_NULL) 5160 5161 Output Parameter: 5162 + rowb, colb - index sets of rows and columns of B to extract 5163 - B_seq - the sequential matrix generated 5164 5165 Level: developer 5166 5167 @*/ 5168 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5169 { 5170 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5171 PetscErrorCode ierr; 5172 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5173 IS isrowb,iscolb; 5174 Mat *bseq=PETSC_NULL; 5175 5176 PetscFunctionBegin; 5177 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 5178 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); 5179 } 5180 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5181 5182 if (scall == MAT_INITIAL_MATRIX){ 5183 start = A->cmap->rstart; 5184 cmap = a->garray; 5185 nzA = a->A->cmap->n; 5186 nzB = a->B->cmap->n; 5187 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5188 ncols = 0; 5189 for (i=0; i<nzB; i++) { /* row < local row index */ 5190 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5191 else break; 5192 } 5193 imark = i; 5194 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5195 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5196 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5197 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5198 } else { 5199 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5200 isrowb = *rowb; iscolb = *colb; 5201 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5202 bseq[0] = *B_seq; 5203 } 5204 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5205 *B_seq = bseq[0]; 5206 ierr = PetscFree(bseq);CHKERRQ(ierr); 5207 if (!rowb){ 5208 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5209 } else { 5210 *rowb = isrowb; 5211 } 5212 if (!colb){ 5213 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5214 } else { 5215 *colb = iscolb; 5216 } 5217 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5218 PetscFunctionReturn(0); 5219 } 5220 5221 #undef __FUNCT__ 5222 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5223 /* 5224 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5225 of the OFF-DIAGONAL portion of local A 5226 5227 Collective on Mat 5228 5229 Input Parameters: 5230 + A,B - the matrices in mpiaij format 5231 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5232 5233 Output Parameter: 5234 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or PETSC_NULL) 5235 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or PETSC_NULL) 5236 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or PETSC_NULL) 5237 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5238 5239 Level: developer 5240 5241 */ 5242 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5243 { 5244 VecScatter_MPI_General *gen_to,*gen_from; 5245 PetscErrorCode ierr; 5246 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5247 Mat_SeqAIJ *b_oth; 5248 VecScatter ctx=a->Mvctx; 5249 MPI_Comm comm=((PetscObject)ctx)->comm; 5250 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5251 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5252 PetscScalar *rvalues,*svalues; 5253 MatScalar *b_otha,*bufa,*bufA; 5254 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5255 MPI_Request *rwaits = PETSC_NULL,*swaits = PETSC_NULL; 5256 MPI_Status *sstatus,rstatus; 5257 PetscMPIInt jj; 5258 PetscInt *cols,sbs,rbs; 5259 PetscScalar *vals; 5260 5261 PetscFunctionBegin; 5262 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend){ 5263 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); 5264 } 5265 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5266 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5267 5268 gen_to = (VecScatter_MPI_General*)ctx->todata; 5269 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5270 rvalues = gen_from->values; /* holds the length of receiving row */ 5271 svalues = gen_to->values; /* holds the length of sending row */ 5272 nrecvs = gen_from->n; 5273 nsends = gen_to->n; 5274 5275 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5276 srow = gen_to->indices; /* local row index to be sent */ 5277 sstarts = gen_to->starts; 5278 sprocs = gen_to->procs; 5279 sstatus = gen_to->sstatus; 5280 sbs = gen_to->bs; 5281 rstarts = gen_from->starts; 5282 rprocs = gen_from->procs; 5283 rbs = gen_from->bs; 5284 5285 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5286 if (scall == MAT_INITIAL_MATRIX){ 5287 /* i-array */ 5288 /*---------*/ 5289 /* post receives */ 5290 for (i=0; i<nrecvs; i++){ 5291 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5292 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5293 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5294 } 5295 5296 /* pack the outgoing message */ 5297 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5298 sstartsj[0] = 0; rstartsj[0] = 0; 5299 len = 0; /* total length of j or a array to be sent */ 5300 k = 0; 5301 for (i=0; i<nsends; i++){ 5302 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5303 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5304 for (j=0; j<nrows; j++) { 5305 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5306 for (l=0; l<sbs; l++){ 5307 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); /* rowlength */ 5308 rowlen[j*sbs+l] = ncols; 5309 len += ncols; 5310 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr); 5311 } 5312 k++; 5313 } 5314 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5315 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5316 } 5317 /* recvs and sends of i-array are completed */ 5318 i = nrecvs; 5319 while (i--) { 5320 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5321 } 5322 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5323 5324 /* allocate buffers for sending j and a arrays */ 5325 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5326 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5327 5328 /* create i-array of B_oth */ 5329 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5330 b_othi[0] = 0; 5331 len = 0; /* total length of j or a array to be received */ 5332 k = 0; 5333 for (i=0; i<nrecvs; i++){ 5334 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5335 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5336 for (j=0; j<nrows; j++) { 5337 b_othi[k+1] = b_othi[k] + rowlen[j]; 5338 len += rowlen[j]; k++; 5339 } 5340 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5341 } 5342 5343 /* allocate space for j and a arrrays of B_oth */ 5344 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5345 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5346 5347 /* j-array */ 5348 /*---------*/ 5349 /* post receives of j-array */ 5350 for (i=0; i<nrecvs; i++){ 5351 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5352 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5353 } 5354 5355 /* pack the outgoing message j-array */ 5356 k = 0; 5357 for (i=0; i<nsends; i++){ 5358 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5359 bufJ = bufj+sstartsj[i]; 5360 for (j=0; j<nrows; j++) { 5361 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5362 for (ll=0; ll<sbs; ll++){ 5363 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 5364 for (l=0; l<ncols; l++){ 5365 *bufJ++ = cols[l]; 5366 } 5367 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,PETSC_NULL);CHKERRQ(ierr); 5368 } 5369 } 5370 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5371 } 5372 5373 /* recvs and sends of j-array are completed */ 5374 i = nrecvs; 5375 while (i--) { 5376 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5377 } 5378 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5379 } else if (scall == MAT_REUSE_MATRIX){ 5380 sstartsj = *startsj_s; 5381 rstartsj = *startsj_r; 5382 bufa = *bufa_ptr; 5383 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5384 b_otha = b_oth->a; 5385 } else { 5386 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5387 } 5388 5389 /* a-array */ 5390 /*---------*/ 5391 /* post receives of a-array */ 5392 for (i=0; i<nrecvs; i++){ 5393 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5394 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5395 } 5396 5397 /* pack the outgoing message a-array */ 5398 k = 0; 5399 for (i=0; i<nsends; i++){ 5400 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5401 bufA = bufa+sstartsj[i]; 5402 for (j=0; j<nrows; j++) { 5403 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5404 for (ll=0; ll<sbs; ll++){ 5405 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 5406 for (l=0; l<ncols; l++){ 5407 *bufA++ = vals[l]; 5408 } 5409 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,PETSC_NULL,&vals);CHKERRQ(ierr); 5410 } 5411 } 5412 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5413 } 5414 /* recvs and sends of a-array are completed */ 5415 i = nrecvs; 5416 while (i--) { 5417 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5418 } 5419 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5420 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5421 5422 if (scall == MAT_INITIAL_MATRIX){ 5423 /* put together the new matrix */ 5424 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5425 5426 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5427 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5428 b_oth = (Mat_SeqAIJ *)(*B_oth)->data; 5429 b_oth->free_a = PETSC_TRUE; 5430 b_oth->free_ij = PETSC_TRUE; 5431 b_oth->nonew = 0; 5432 5433 ierr = PetscFree(bufj);CHKERRQ(ierr); 5434 if (!startsj_s || !bufa_ptr){ 5435 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5436 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5437 } else { 5438 *startsj_s = sstartsj; 5439 *startsj_r = rstartsj; 5440 *bufa_ptr = bufa; 5441 } 5442 } 5443 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5444 PetscFunctionReturn(0); 5445 } 5446 5447 #undef __FUNCT__ 5448 #define __FUNCT__ "MatGetCommunicationStructs" 5449 /*@C 5450 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5451 5452 Not Collective 5453 5454 Input Parameters: 5455 . A - The matrix in mpiaij format 5456 5457 Output Parameter: 5458 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5459 . colmap - A map from global column index to local index into lvec 5460 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5461 5462 Level: developer 5463 5464 @*/ 5465 #if defined (PETSC_USE_CTABLE) 5466 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5467 #else 5468 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5469 #endif 5470 { 5471 Mat_MPIAIJ *a; 5472 5473 PetscFunctionBegin; 5474 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5475 PetscValidPointer(lvec, 2); 5476 PetscValidPointer(colmap, 3); 5477 PetscValidPointer(multScatter, 4); 5478 a = (Mat_MPIAIJ *) A->data; 5479 if (lvec) *lvec = a->lvec; 5480 if (colmap) *colmap = a->colmap; 5481 if (multScatter) *multScatter = a->Mvctx; 5482 PetscFunctionReturn(0); 5483 } 5484 5485 EXTERN_C_BEGIN 5486 extern PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5487 extern PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5488 extern PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5489 EXTERN_C_END 5490 5491 #undef __FUNCT__ 5492 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5493 /* 5494 Computes (B'*A')' since computing B*A directly is untenable 5495 5496 n p p 5497 ( ) ( ) ( ) 5498 m ( A ) * n ( B ) = m ( C ) 5499 ( ) ( ) ( ) 5500 5501 */ 5502 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5503 { 5504 PetscErrorCode ierr; 5505 Mat At,Bt,Ct; 5506 5507 PetscFunctionBegin; 5508 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5509 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5510 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5511 ierr = MatDestroy(&At);CHKERRQ(ierr); 5512 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5513 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5514 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5515 PetscFunctionReturn(0); 5516 } 5517 5518 #undef __FUNCT__ 5519 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5520 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5521 { 5522 PetscErrorCode ierr; 5523 PetscInt m=A->rmap->n,n=B->cmap->n; 5524 Mat Cmat; 5525 5526 PetscFunctionBegin; 5527 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); 5528 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 5529 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5530 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5531 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5532 ierr = MatMPIDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 5533 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5534 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5535 *C = Cmat; 5536 (*C)->ops->matmult = MatMatMult_MPIDense_MPIAIJ; 5537 PetscFunctionReturn(0); 5538 } 5539 5540 /* ----------------------------------------------------------------*/ 5541 #undef __FUNCT__ 5542 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5543 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5544 { 5545 PetscErrorCode ierr; 5546 5547 PetscFunctionBegin; 5548 if (scall == MAT_INITIAL_MATRIX){ 5549 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5550 } 5551 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5552 PetscFunctionReturn(0); 5553 } 5554 5555 EXTERN_C_BEGIN 5556 #if defined(PETSC_HAVE_MUMPS) 5557 extern PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5558 #endif 5559 #if defined(PETSC_HAVE_PASTIX) 5560 extern PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5561 #endif 5562 #if defined(PETSC_HAVE_SUPERLU_DIST) 5563 extern PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5564 #endif 5565 #if defined(PETSC_HAVE_CLIQUE) 5566 extern PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5567 #endif 5568 EXTERN_C_END 5569 5570 /*MC 5571 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5572 5573 Options Database Keys: 5574 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5575 5576 Level: beginner 5577 5578 .seealso: MatCreateAIJ() 5579 M*/ 5580 5581 EXTERN_C_BEGIN 5582 #undef __FUNCT__ 5583 #define __FUNCT__ "MatCreate_MPIAIJ" 5584 PetscErrorCode MatCreate_MPIAIJ(Mat B) 5585 { 5586 Mat_MPIAIJ *b; 5587 PetscErrorCode ierr; 5588 PetscMPIInt size; 5589 5590 PetscFunctionBegin; 5591 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 5592 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5593 B->data = (void*)b; 5594 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5595 B->assembled = PETSC_FALSE; 5596 B->insertmode = NOT_SET_VALUES; 5597 b->size = size; 5598 ierr = MPI_Comm_rank(((PetscObject)B)->comm,&b->rank);CHKERRQ(ierr); 5599 5600 /* build cache for off array entries formed */ 5601 ierr = MatStashCreate_Private(((PetscObject)B)->comm,1,&B->stash);CHKERRQ(ierr); 5602 b->donotstash = PETSC_FALSE; 5603 b->colmap = 0; 5604 b->garray = 0; 5605 b->roworiented = PETSC_TRUE; 5606 5607 /* stuff used for matrix vector multiply */ 5608 b->lvec = PETSC_NULL; 5609 b->Mvctx = PETSC_NULL; 5610 5611 /* stuff for MatGetRow() */ 5612 b->rowindices = 0; 5613 b->rowvalues = 0; 5614 b->getrowactive = PETSC_FALSE; 5615 5616 /* flexible pointer used in CUSP/CUSPARSE classes */ 5617 b->spptr = PETSC_NULL; 5618 5619 #if defined(PETSC_HAVE_MUMPS) 5620 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 5621 "MatGetFactor_aij_mumps", 5622 MatGetFactor_aij_mumps);CHKERRQ(ierr); 5623 #endif 5624 #if defined(PETSC_HAVE_PASTIX) 5625 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 5626 "MatGetFactor_mpiaij_pastix", 5627 MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5628 #endif 5629 #if defined(PETSC_HAVE_SUPERLU_DIST) 5630 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C", 5631 "MatGetFactor_mpiaij_superlu_dist", 5632 MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5633 #endif 5634 #if defined(PETSC_HAVE_CLIQUE) 5635 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_clique_C", 5636 "MatGetFactor_aij_clique", 5637 MatGetFactor_aij_clique);CHKERRQ(ierr); 5638 #endif 5639 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 5640 "MatStoreValues_MPIAIJ", 5641 MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5642 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 5643 "MatRetrieveValues_MPIAIJ", 5644 MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5645 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 5646 "MatGetDiagonalBlock_MPIAIJ", 5647 MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5648 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 5649 "MatIsTranspose_MPIAIJ", 5650 MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5651 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocation_C", 5652 "MatMPIAIJSetPreallocation_MPIAIJ", 5653 MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5654 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C", 5655 "MatMPIAIJSetPreallocationCSR_MPIAIJ", 5656 MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5657 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatDiagonalScaleLocal_C", 5658 "MatDiagonalScaleLocal_MPIAIJ", 5659 MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5660 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C", 5661 "MatConvert_MPIAIJ_MPIAIJPERM", 5662 MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5663 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C", 5664 "MatConvert_MPIAIJ_MPIAIJCRL", 5665 MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5666 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C", 5667 "MatConvert_MPIAIJ_MPISBAIJ", 5668 MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5669 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_mpidense_mpiaij_C", 5670 "MatMatMult_MPIDense_MPIAIJ", 5671 MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5672 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C", 5673 "MatMatMultSymbolic_MPIDense_MPIAIJ", 5674 MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5675 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C", 5676 "MatMatMultNumeric_MPIDense_MPIAIJ", 5677 MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5678 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5679 PetscFunctionReturn(0); 5680 } 5681 EXTERN_C_END 5682 5683 #undef __FUNCT__ 5684 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5685 /*@ 5686 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5687 and "off-diagonal" part of the matrix in CSR format. 5688 5689 Collective on MPI_Comm 5690 5691 Input Parameters: 5692 + comm - MPI communicator 5693 . m - number of local rows (Cannot be PETSC_DECIDE) 5694 . n - This value should be the same as the local size used in creating the 5695 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5696 calculated if N is given) For square matrices n is almost always m. 5697 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5698 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5699 . i - row indices for "diagonal" portion of matrix 5700 . j - column indices 5701 . a - matrix values 5702 . oi - row indices for "off-diagonal" portion of matrix 5703 . oj - column indices 5704 - oa - matrix values 5705 5706 Output Parameter: 5707 . mat - the matrix 5708 5709 Level: advanced 5710 5711 Notes: 5712 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5713 must free the arrays once the matrix has been destroyed and not before. 5714 5715 The i and j indices are 0 based 5716 5717 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5718 5719 This sets local rows and cannot be used to set off-processor values. 5720 5721 You cannot later use MatSetValues() to change values in this matrix. 5722 5723 .keywords: matrix, aij, compressed row, sparse, parallel 5724 5725 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5726 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5727 @*/ 5728 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[], 5729 PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5730 { 5731 PetscErrorCode ierr; 5732 Mat_MPIAIJ *maij; 5733 5734 PetscFunctionBegin; 5735 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5736 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5737 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5738 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5739 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5740 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5741 maij = (Mat_MPIAIJ*) (*mat)->data; 5742 maij->donotstash = PETSC_TRUE; 5743 (*mat)->preallocated = PETSC_TRUE; 5744 5745 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5746 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5747 5748 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5749 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5750 5751 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5752 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5753 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5754 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5755 5756 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5757 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5758 PetscFunctionReturn(0); 5759 } 5760 5761 /* 5762 Special version for direct calls from Fortran 5763 */ 5764 #include <petsc-private/fortranimpl.h> 5765 5766 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5767 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5768 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5769 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5770 #endif 5771 5772 /* Change these macros so can be used in void function */ 5773 #undef CHKERRQ 5774 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5775 #undef SETERRQ2 5776 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5777 #undef SETERRQ3 5778 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5779 #undef SETERRQ 5780 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5781 5782 EXTERN_C_BEGIN 5783 #undef __FUNCT__ 5784 #define __FUNCT__ "matsetvaluesmpiaij_" 5785 void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5786 { 5787 Mat mat = *mmat; 5788 PetscInt m = *mm, n = *mn; 5789 InsertMode addv = *maddv; 5790 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5791 PetscScalar value; 5792 PetscErrorCode ierr; 5793 5794 MatCheckPreallocated(mat,1); 5795 if (mat->insertmode == NOT_SET_VALUES) { 5796 mat->insertmode = addv; 5797 } 5798 #if defined(PETSC_USE_DEBUG) 5799 else if (mat->insertmode != addv) { 5800 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5801 } 5802 #endif 5803 { 5804 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5805 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5806 PetscBool roworiented = aij->roworiented; 5807 5808 /* Some Variables required in the macro */ 5809 Mat A = aij->A; 5810 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5811 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5812 MatScalar *aa = a->a; 5813 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE); 5814 Mat B = aij->B; 5815 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5816 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5817 MatScalar *ba = b->a; 5818 5819 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5820 PetscInt nonew = a->nonew; 5821 MatScalar *ap1,*ap2; 5822 5823 PetscFunctionBegin; 5824 for (i=0; i<m; i++) { 5825 if (im[i] < 0) continue; 5826 #if defined(PETSC_USE_DEBUG) 5827 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); 5828 #endif 5829 if (im[i] >= rstart && im[i] < rend) { 5830 row = im[i] - rstart; 5831 lastcol1 = -1; 5832 rp1 = aj + ai[row]; 5833 ap1 = aa + ai[row]; 5834 rmax1 = aimax[row]; 5835 nrow1 = ailen[row]; 5836 low1 = 0; 5837 high1 = nrow1; 5838 lastcol2 = -1; 5839 rp2 = bj + bi[row]; 5840 ap2 = ba + bi[row]; 5841 rmax2 = bimax[row]; 5842 nrow2 = bilen[row]; 5843 low2 = 0; 5844 high2 = nrow2; 5845 5846 for (j=0; j<n; j++) { 5847 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 5848 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5849 if (in[j] >= cstart && in[j] < cend){ 5850 col = in[j] - cstart; 5851 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5852 } else if (in[j] < 0) continue; 5853 #if defined(PETSC_USE_DEBUG) 5854 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); 5855 #endif 5856 else { 5857 if (mat->was_assembled) { 5858 if (!aij->colmap) { 5859 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5860 } 5861 #if defined (PETSC_USE_CTABLE) 5862 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5863 col--; 5864 #else 5865 col = aij->colmap[in[j]] - 1; 5866 #endif 5867 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5868 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5869 col = in[j]; 5870 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5871 B = aij->B; 5872 b = (Mat_SeqAIJ*)B->data; 5873 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5874 rp2 = bj + bi[row]; 5875 ap2 = ba + bi[row]; 5876 rmax2 = bimax[row]; 5877 nrow2 = bilen[row]; 5878 low2 = 0; 5879 high2 = nrow2; 5880 bm = aij->B->rmap->n; 5881 ba = b->a; 5882 } 5883 } else col = in[j]; 5884 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5885 } 5886 } 5887 } else { 5888 if (!aij->donotstash) { 5889 if (roworiented) { 5890 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5891 } else { 5892 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5893 } 5894 } 5895 } 5896 }} 5897 PetscFunctionReturnVoid(); 5898 } 5899 EXTERN_C_END 5900 5901