1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = 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 for (i=1; i<mat->rmap->n; i++) { 335 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; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 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); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 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); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 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); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 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]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 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); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 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); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 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"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 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 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 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"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 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); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 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); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),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."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2530 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2531 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2532 for (i=0; i<redund->nrecvs; i++) { 2533 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2534 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2535 } 2536 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2537 2538 if (redund->psubcomm) { 2539 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2540 } 2541 2542 ierr = redund->Destroy(A);CHKERRQ(ierr); 2543 ierr = PetscFree(redund);CHKERRQ(ierr); 2544 } 2545 PetscFunctionReturn(0); 2546 } 2547 2548 #undef __FUNCT__ 2549 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_interlaced" 2550 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2551 { 2552 PetscMPIInt rank,size; 2553 MPI_Comm comm,subcomm=psubcomm->comm; 2554 PetscErrorCode ierr; 2555 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2556 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2557 PetscInt *rowrange = mat->rmap->range; 2558 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2559 Mat A = aij->A,B=aij->B,C=*matredundant; 2560 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2561 PetscScalar *sbuf_a; 2562 PetscInt nzlocal=a->nz+b->nz; 2563 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2564 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2565 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2566 MatScalar *aworkA,*aworkB; 2567 PetscScalar *vals; 2568 PetscMPIInt tag1,tag2,tag3,imdex; 2569 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2570 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2571 MPI_Status recv_status,*send_status; 2572 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2573 PetscInt **rbuf_j=NULL; 2574 PetscScalar **rbuf_a=NULL; 2575 Mat_Redundant *redund =NULL; 2576 PetscInt rstart_sub,rend_sub,mloc_sub; 2577 2578 PetscFunctionBegin; 2579 if (psubcomm->type != PETSC_SUBCOMM_INTERLACED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"Input psubcomm must be PETSC_SUBCOMM_INTERLACED type"); 2580 2581 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2582 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2583 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2584 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2585 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2586 2587 if (reuse == MAT_REUSE_MATRIX) { 2588 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2589 if (subsize == 1) { 2590 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2591 redund = c->redundant; 2592 } else { 2593 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2594 redund = c->redundant; 2595 } 2596 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2597 2598 nsends = redund->nsends; 2599 nrecvs = redund->nrecvs; 2600 send_rank = redund->send_rank; 2601 recv_rank = redund->recv_rank; 2602 sbuf_nz = redund->sbuf_nz; 2603 rbuf_nz = redund->rbuf_nz; 2604 sbuf_j = redund->sbuf_j; 2605 sbuf_a = redund->sbuf_a; 2606 rbuf_j = redund->rbuf_j; 2607 rbuf_a = redund->rbuf_a; 2608 } 2609 2610 if (reuse == MAT_INITIAL_MATRIX) { 2611 PetscInt nleftover,np_subcomm; 2612 2613 /* get local size of redundant matrix */ 2614 const PetscInt *range; 2615 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2616 rstart_sub = range[nsubcomm*subrank]; 2617 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2618 rend_sub = range[nsubcomm*(subrank+1)]; 2619 } else { 2620 rend_sub = mat->rmap->N; 2621 } 2622 mloc_sub = rend_sub - rstart_sub; 2623 2624 /* get the destination processors' id send_rank, nsends and nrecvs */ 2625 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2626 2627 np_subcomm = size/nsubcomm; 2628 nleftover = size - nsubcomm*np_subcomm; 2629 2630 nsends = 0; nrecvs = 0; 2631 for (i=0; i<size; i++) { 2632 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2633 send_rank[nsends] = i; nsends++; 2634 recv_rank[nrecvs++] = i; 2635 } 2636 } 2637 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2638 i = size-nleftover-1; 2639 j = 0; 2640 while (j < nsubcomm - nleftover) { 2641 send_rank[nsends++] = i; 2642 i--; j++; 2643 } 2644 } 2645 2646 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2647 for (i=0; i<nleftover; i++) { 2648 recv_rank[nrecvs++] = size-nleftover+i; 2649 } 2650 } 2651 2652 /* allocate sbuf_j, sbuf_a */ 2653 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2654 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2655 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2656 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2657 2658 /* copy mat's local entries into the buffers */ 2659 if (reuse == MAT_INITIAL_MATRIX) { 2660 rownz_max = 0; 2661 rptr = sbuf_j; 2662 cols = sbuf_j + rend-rstart + 1; 2663 vals = sbuf_a; 2664 rptr[0] = 0; 2665 for (i=0; i<rend-rstart; i++) { 2666 row = i + rstart; 2667 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2668 ncols = nzA + nzB; 2669 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2670 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2671 /* load the column indices for this row into cols */ 2672 lwrite = 0; 2673 for (l=0; l<nzB; l++) { 2674 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2675 vals[lwrite] = aworkB[l]; 2676 cols[lwrite++] = ctmp; 2677 } 2678 } 2679 for (l=0; l<nzA; l++) { 2680 vals[lwrite] = aworkA[l]; 2681 cols[lwrite++] = cstart + cworkA[l]; 2682 } 2683 for (l=0; l<nzB; l++) { 2684 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2685 vals[lwrite] = aworkB[l]; 2686 cols[lwrite++] = ctmp; 2687 } 2688 } 2689 vals += ncols; 2690 cols += ncols; 2691 rptr[i+1] = rptr[i] + ncols; 2692 if (rownz_max < ncols) rownz_max = ncols; 2693 } 2694 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); 2695 } else { /* only copy matrix values into sbuf_a */ 2696 rptr = sbuf_j; 2697 vals = sbuf_a; 2698 rptr[0] = 0; 2699 for (i=0; i<rend-rstart; i++) { 2700 row = i + rstart; 2701 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2702 ncols = nzA + nzB; 2703 cworkB = b->j + b->i[i]; 2704 aworkA = a->a + a->i[i]; 2705 aworkB = b->a + b->i[i]; 2706 lwrite = 0; 2707 for (l=0; l<nzB; l++) { 2708 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2709 } 2710 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2711 for (l=0; l<nzB; l++) { 2712 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2713 } 2714 vals += ncols; 2715 rptr[i+1] = rptr[i] + ncols; 2716 } 2717 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2718 2719 /* send nzlocal to others, and recv other's nzlocal */ 2720 /*--------------------------------------------------*/ 2721 if (reuse == MAT_INITIAL_MATRIX) { 2722 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2723 2724 s_waits2 = s_waits3 + nsends; 2725 s_waits1 = s_waits2 + nsends; 2726 r_waits1 = s_waits1 + nsends; 2727 r_waits2 = r_waits1 + nrecvs; 2728 r_waits3 = r_waits2 + nrecvs; 2729 } else { 2730 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2731 2732 r_waits3 = s_waits3 + nsends; 2733 } 2734 2735 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2736 if (reuse == MAT_INITIAL_MATRIX) { 2737 /* get new tags to keep the communication clean */ 2738 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2739 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2740 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2741 2742 /* post receives of other's nzlocal */ 2743 for (i=0; i<nrecvs; i++) { 2744 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2745 } 2746 /* send nzlocal to others */ 2747 for (i=0; i<nsends; i++) { 2748 sbuf_nz[i] = nzlocal; 2749 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2750 } 2751 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2752 count = nrecvs; 2753 while (count) { 2754 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2755 2756 recv_rank[imdex] = recv_status.MPI_SOURCE; 2757 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2758 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2759 2760 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2761 2762 rbuf_nz[imdex] += i + 2; 2763 2764 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2765 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2766 count--; 2767 } 2768 /* wait on sends of nzlocal */ 2769 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2770 /* send mat->i,j to others, and recv from other's */ 2771 /*------------------------------------------------*/ 2772 for (i=0; i<nsends; i++) { 2773 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2774 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2775 } 2776 /* wait on receives of mat->i,j */ 2777 /*------------------------------*/ 2778 count = nrecvs; 2779 while (count) { 2780 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2781 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); 2782 count--; 2783 } 2784 /* wait on sends of mat->i,j */ 2785 /*---------------------------*/ 2786 if (nsends) { 2787 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2788 } 2789 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2790 2791 /* post receives, send and receive mat->a */ 2792 /*----------------------------------------*/ 2793 for (imdex=0; imdex<nrecvs; imdex++) { 2794 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2795 } 2796 for (i=0; i<nsends; i++) { 2797 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2798 } 2799 count = nrecvs; 2800 while (count) { 2801 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2802 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); 2803 count--; 2804 } 2805 if (nsends) { 2806 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2807 } 2808 2809 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2810 2811 /* create redundant matrix */ 2812 /*-------------------------*/ 2813 if (reuse == MAT_INITIAL_MATRIX) { 2814 /* compute rownz_max for preallocation */ 2815 for (imdex=0; imdex<nrecvs; imdex++) { 2816 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2817 rptr = rbuf_j[imdex]; 2818 for (i=0; i<j; i++) { 2819 ncols = rptr[i+1] - rptr[i]; 2820 if (rownz_max < ncols) rownz_max = ncols; 2821 } 2822 } 2823 2824 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2825 if (M == N) { 2826 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2827 } else { /* non-square matrix */ 2828 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2829 } 2830 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2831 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2832 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2833 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2834 } else { 2835 C = *matredundant; 2836 } 2837 2838 /* insert local matrix entries */ 2839 rptr = sbuf_j; 2840 cols = sbuf_j + rend-rstart + 1; 2841 vals = sbuf_a; 2842 for (i=0; i<rend-rstart; i++) { 2843 row = i + rstart; 2844 ncols = rptr[i+1] - rptr[i]; 2845 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2846 vals += ncols; 2847 cols += ncols; 2848 } 2849 /* insert received matrix entries */ 2850 for (imdex=0; imdex<nrecvs; imdex++) { 2851 rstart = rowrange[recv_rank[imdex]]; 2852 rend = rowrange[recv_rank[imdex]+1]; 2853 rptr = rbuf_j[imdex]; 2854 cols = rbuf_j[imdex] + rend-rstart + 1; 2855 vals = rbuf_a[imdex]; 2856 for (i=0; i<rend-rstart; i++) { 2857 row = i + rstart; 2858 ncols = rptr[i+1] - rptr[i]; 2859 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2860 vals += ncols; 2861 cols += ncols; 2862 } 2863 } 2864 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2865 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2866 2867 if (reuse == MAT_INITIAL_MATRIX) { 2868 *matredundant = C; 2869 2870 /* create a supporting struct and attach it to C for reuse */ 2871 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2872 if (subsize == 1) { 2873 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2874 c->redundant = redund; 2875 } else { 2876 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2877 c->redundant = redund; 2878 } 2879 2880 redund->nzlocal = nzlocal; 2881 redund->nsends = nsends; 2882 redund->nrecvs = nrecvs; 2883 redund->send_rank = send_rank; 2884 redund->recv_rank = recv_rank; 2885 redund->sbuf_nz = sbuf_nz; 2886 redund->rbuf_nz = rbuf_nz; 2887 redund->sbuf_j = sbuf_j; 2888 redund->sbuf_a = sbuf_a; 2889 redund->rbuf_j = rbuf_j; 2890 redund->rbuf_a = rbuf_a; 2891 redund->psubcomm = NULL; 2892 2893 redund->Destroy = C->ops->destroy; 2894 C->ops->destroy = MatDestroy_MatRedundant; 2895 } 2896 PetscFunctionReturn(0); 2897 } 2898 2899 #undef __FUNCT__ 2900 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2901 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2902 { 2903 PetscErrorCode ierr; 2904 2905 PetscFunctionBegin; 2906 /* Only MatGetRedundantMatrix_MPIAIJ_interlaced() is written now */ 2907 if (subcomm == MPI_COMM_NULL || subcomm == PETSC_COMM_SELF) { /* create psubcomm */ 2908 MPI_Comm comm; 2909 PetscSubcomm psubcomm; 2910 PetscMPIInt size,subsize; 2911 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2912 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2913 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2914 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2915 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_INTERLACED);CHKERRQ(ierr); 2916 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2917 2918 /* free psubcomm in MatDestroy_MatRedundant() */ 2919 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2920 Mat C = *matredundant; 2921 if (subsize == 1) { 2922 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2923 c->redundant->psubcomm = psubcomm; 2924 } else { 2925 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2926 c->redundant->psubcomm = psubcomm ; 2927 } 2928 } else { 2929 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet"); 2930 } 2931 PetscFunctionReturn(0); 2932 } 2933 2934 #undef __FUNCT__ 2935 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2936 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2937 { 2938 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2939 PetscErrorCode ierr; 2940 PetscInt i,*idxb = 0; 2941 PetscScalar *va,*vb; 2942 Vec vtmp; 2943 2944 PetscFunctionBegin; 2945 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2946 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2947 if (idx) { 2948 for (i=0; i<A->rmap->n; i++) { 2949 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2950 } 2951 } 2952 2953 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2954 if (idx) { 2955 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2956 } 2957 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2958 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2959 2960 for (i=0; i<A->rmap->n; i++) { 2961 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2962 va[i] = vb[i]; 2963 if (idx) idx[i] = a->garray[idxb[i]]; 2964 } 2965 } 2966 2967 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2968 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2969 ierr = PetscFree(idxb);CHKERRQ(ierr); 2970 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2971 PetscFunctionReturn(0); 2972 } 2973 2974 #undef __FUNCT__ 2975 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2976 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2977 { 2978 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2979 PetscErrorCode ierr; 2980 PetscInt i,*idxb = 0; 2981 PetscScalar *va,*vb; 2982 Vec vtmp; 2983 2984 PetscFunctionBegin; 2985 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2986 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2987 if (idx) { 2988 for (i=0; i<A->cmap->n; i++) { 2989 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2990 } 2991 } 2992 2993 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2994 if (idx) { 2995 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2996 } 2997 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2998 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2999 3000 for (i=0; i<A->rmap->n; i++) { 3001 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3002 va[i] = vb[i]; 3003 if (idx) idx[i] = a->garray[idxb[i]]; 3004 } 3005 } 3006 3007 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3008 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3009 ierr = PetscFree(idxb);CHKERRQ(ierr); 3010 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3011 PetscFunctionReturn(0); 3012 } 3013 3014 #undef __FUNCT__ 3015 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3016 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3017 { 3018 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3019 PetscInt n = A->rmap->n; 3020 PetscInt cstart = A->cmap->rstart; 3021 PetscInt *cmap = mat->garray; 3022 PetscInt *diagIdx, *offdiagIdx; 3023 Vec diagV, offdiagV; 3024 PetscScalar *a, *diagA, *offdiagA; 3025 PetscInt r; 3026 PetscErrorCode ierr; 3027 3028 PetscFunctionBegin; 3029 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3030 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3031 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3032 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3033 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3034 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3035 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3036 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3037 for (r = 0; r < n; ++r) { 3038 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3039 a[r] = diagA[r]; 3040 idx[r] = cstart + diagIdx[r]; 3041 } else { 3042 a[r] = offdiagA[r]; 3043 idx[r] = cmap[offdiagIdx[r]]; 3044 } 3045 } 3046 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3047 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3048 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3049 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3050 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3051 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3052 PetscFunctionReturn(0); 3053 } 3054 3055 #undef __FUNCT__ 3056 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3057 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3058 { 3059 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3060 PetscInt n = A->rmap->n; 3061 PetscInt cstart = A->cmap->rstart; 3062 PetscInt *cmap = mat->garray; 3063 PetscInt *diagIdx, *offdiagIdx; 3064 Vec diagV, offdiagV; 3065 PetscScalar *a, *diagA, *offdiagA; 3066 PetscInt r; 3067 PetscErrorCode ierr; 3068 3069 PetscFunctionBegin; 3070 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3071 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3072 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3073 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3074 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3075 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3076 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3077 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3078 for (r = 0; r < n; ++r) { 3079 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3080 a[r] = diagA[r]; 3081 idx[r] = cstart + diagIdx[r]; 3082 } else { 3083 a[r] = offdiagA[r]; 3084 idx[r] = cmap[offdiagIdx[r]]; 3085 } 3086 } 3087 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3088 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3089 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3090 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3091 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3092 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3093 PetscFunctionReturn(0); 3094 } 3095 3096 #undef __FUNCT__ 3097 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3098 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3099 { 3100 PetscErrorCode ierr; 3101 Mat *dummy; 3102 3103 PetscFunctionBegin; 3104 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3105 *newmat = *dummy; 3106 ierr = PetscFree(dummy);CHKERRQ(ierr); 3107 PetscFunctionReturn(0); 3108 } 3109 3110 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3111 3112 #undef __FUNCT__ 3113 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3114 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3115 { 3116 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3117 PetscErrorCode ierr; 3118 3119 PetscFunctionBegin; 3120 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3121 PetscFunctionReturn(0); 3122 } 3123 3124 #undef __FUNCT__ 3125 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3126 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3127 { 3128 PetscErrorCode ierr; 3129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3130 3131 PetscFunctionBegin; 3132 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3133 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3134 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3135 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3136 PetscFunctionReturn(0); 3137 } 3138 3139 /* -------------------------------------------------------------------*/ 3140 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3141 MatGetRow_MPIAIJ, 3142 MatRestoreRow_MPIAIJ, 3143 MatMult_MPIAIJ, 3144 /* 4*/ MatMultAdd_MPIAIJ, 3145 MatMultTranspose_MPIAIJ, 3146 MatMultTransposeAdd_MPIAIJ, 3147 #if defined(PETSC_HAVE_PBGL) 3148 MatSolve_MPIAIJ, 3149 #else 3150 0, 3151 #endif 3152 0, 3153 0, 3154 /*10*/ 0, 3155 0, 3156 0, 3157 MatSOR_MPIAIJ, 3158 MatTranspose_MPIAIJ, 3159 /*15*/ MatGetInfo_MPIAIJ, 3160 MatEqual_MPIAIJ, 3161 MatGetDiagonal_MPIAIJ, 3162 MatDiagonalScale_MPIAIJ, 3163 MatNorm_MPIAIJ, 3164 /*20*/ MatAssemblyBegin_MPIAIJ, 3165 MatAssemblyEnd_MPIAIJ, 3166 MatSetOption_MPIAIJ, 3167 MatZeroEntries_MPIAIJ, 3168 /*24*/ MatZeroRows_MPIAIJ, 3169 0, 3170 #if defined(PETSC_HAVE_PBGL) 3171 0, 3172 #else 3173 0, 3174 #endif 3175 0, 3176 0, 3177 /*29*/ MatSetUp_MPIAIJ, 3178 #if defined(PETSC_HAVE_PBGL) 3179 0, 3180 #else 3181 0, 3182 #endif 3183 0, 3184 0, 3185 0, 3186 /*34*/ MatDuplicate_MPIAIJ, 3187 0, 3188 0, 3189 0, 3190 0, 3191 /*39*/ MatAXPY_MPIAIJ, 3192 MatGetSubMatrices_MPIAIJ, 3193 MatIncreaseOverlap_MPIAIJ, 3194 MatGetValues_MPIAIJ, 3195 MatCopy_MPIAIJ, 3196 /*44*/ MatGetRowMax_MPIAIJ, 3197 MatScale_MPIAIJ, 3198 0, 3199 0, 3200 MatZeroRowsColumns_MPIAIJ, 3201 /*49*/ MatSetRandom_MPIAIJ, 3202 0, 3203 0, 3204 0, 3205 0, 3206 /*54*/ MatFDColoringCreate_MPIAIJ, 3207 0, 3208 MatSetUnfactored_MPIAIJ, 3209 MatPermute_MPIAIJ, 3210 0, 3211 /*59*/ MatGetSubMatrix_MPIAIJ, 3212 MatDestroy_MPIAIJ, 3213 MatView_MPIAIJ, 3214 0, 3215 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3216 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3217 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3218 0, 3219 0, 3220 0, 3221 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3222 MatGetRowMinAbs_MPIAIJ, 3223 0, 3224 MatSetColoring_MPIAIJ, 3225 0, 3226 MatSetValuesAdifor_MPIAIJ, 3227 /*75*/ MatFDColoringApply_AIJ, 3228 0, 3229 0, 3230 0, 3231 MatFindZeroDiagonals_MPIAIJ, 3232 /*80*/ 0, 3233 0, 3234 0, 3235 /*83*/ MatLoad_MPIAIJ, 3236 0, 3237 0, 3238 0, 3239 0, 3240 0, 3241 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3242 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3243 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3244 MatPtAP_MPIAIJ_MPIAIJ, 3245 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3246 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3247 0, 3248 0, 3249 0, 3250 0, 3251 /*99*/ 0, 3252 0, 3253 0, 3254 MatConjugate_MPIAIJ, 3255 0, 3256 /*104*/MatSetValuesRow_MPIAIJ, 3257 MatRealPart_MPIAIJ, 3258 MatImaginaryPart_MPIAIJ, 3259 0, 3260 0, 3261 /*109*/0, 3262 MatGetRedundantMatrix_MPIAIJ, 3263 MatGetRowMin_MPIAIJ, 3264 0, 3265 0, 3266 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3267 0, 3268 0, 3269 0, 3270 0, 3271 /*119*/0, 3272 0, 3273 0, 3274 0, 3275 MatGetMultiProcBlock_MPIAIJ, 3276 /*124*/MatFindNonzeroRows_MPIAIJ, 3277 MatGetColumnNorms_MPIAIJ, 3278 MatInvertBlockDiagonal_MPIAIJ, 3279 0, 3280 MatGetSubMatricesParallel_MPIAIJ, 3281 /*129*/0, 3282 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3283 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3284 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3285 0, 3286 /*134*/0, 3287 0, 3288 0, 3289 0, 3290 0, 3291 /*139*/0, 3292 0 3293 }; 3294 3295 /* ----------------------------------------------------------------------------------------*/ 3296 3297 #undef __FUNCT__ 3298 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3299 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3300 { 3301 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3302 PetscErrorCode ierr; 3303 3304 PetscFunctionBegin; 3305 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3306 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3307 PetscFunctionReturn(0); 3308 } 3309 3310 #undef __FUNCT__ 3311 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3312 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3313 { 3314 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3315 PetscErrorCode ierr; 3316 3317 PetscFunctionBegin; 3318 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3319 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3320 PetscFunctionReturn(0); 3321 } 3322 3323 #undef __FUNCT__ 3324 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3325 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3326 { 3327 Mat_MPIAIJ *b; 3328 PetscErrorCode ierr; 3329 3330 PetscFunctionBegin; 3331 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3332 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3333 b = (Mat_MPIAIJ*)B->data; 3334 3335 if (!B->preallocated) { 3336 /* Explicitly create 2 MATSEQAIJ matrices. */ 3337 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3338 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3339 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3340 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3341 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3342 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3343 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3344 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3345 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3346 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3347 } 3348 3349 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3350 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3351 B->preallocated = PETSC_TRUE; 3352 PetscFunctionReturn(0); 3353 } 3354 3355 #undef __FUNCT__ 3356 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3357 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3358 { 3359 Mat mat; 3360 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3361 PetscErrorCode ierr; 3362 3363 PetscFunctionBegin; 3364 *newmat = 0; 3365 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3366 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3367 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3368 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3369 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3370 a = (Mat_MPIAIJ*)mat->data; 3371 3372 mat->factortype = matin->factortype; 3373 mat->rmap->bs = matin->rmap->bs; 3374 mat->cmap->bs = matin->cmap->bs; 3375 mat->assembled = PETSC_TRUE; 3376 mat->insertmode = NOT_SET_VALUES; 3377 mat->preallocated = PETSC_TRUE; 3378 3379 a->size = oldmat->size; 3380 a->rank = oldmat->rank; 3381 a->donotstash = oldmat->donotstash; 3382 a->roworiented = oldmat->roworiented; 3383 a->rowindices = 0; 3384 a->rowvalues = 0; 3385 a->getrowactive = PETSC_FALSE; 3386 3387 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3388 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3389 3390 if (oldmat->colmap) { 3391 #if defined(PETSC_USE_CTABLE) 3392 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3393 #else 3394 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3395 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3396 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3397 #endif 3398 } else a->colmap = 0; 3399 if (oldmat->garray) { 3400 PetscInt len; 3401 len = oldmat->B->cmap->n; 3402 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3403 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3404 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3405 } else a->garray = 0; 3406 3407 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3408 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3409 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3410 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3411 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3412 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3413 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3414 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3415 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3416 *newmat = mat; 3417 PetscFunctionReturn(0); 3418 } 3419 3420 3421 3422 #undef __FUNCT__ 3423 #define __FUNCT__ "MatLoad_MPIAIJ" 3424 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3425 { 3426 PetscScalar *vals,*svals; 3427 MPI_Comm comm; 3428 PetscErrorCode ierr; 3429 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3430 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3431 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3432 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3433 PetscInt cend,cstart,n,*rowners,sizesset=1; 3434 int fd; 3435 PetscInt bs = 1; 3436 3437 PetscFunctionBegin; 3438 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3439 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3440 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3441 if (!rank) { 3442 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3443 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3444 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3445 } 3446 3447 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3448 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3449 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3450 3451 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3452 3453 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3454 M = header[1]; N = header[2]; 3455 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3456 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3457 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3458 3459 /* If global sizes are set, check if they are consistent with that given in the file */ 3460 if (sizesset) { 3461 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3462 } 3463 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); 3464 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); 3465 3466 /* determine ownership of all (block) rows */ 3467 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3468 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3469 else m = newMat->rmap->n; /* Set by user */ 3470 3471 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3472 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3473 3474 /* First process needs enough room for process with most rows */ 3475 if (!rank) { 3476 mmax = rowners[1]; 3477 for (i=2; i<=size; i++) { 3478 mmax = PetscMax(mmax, rowners[i]); 3479 } 3480 } else mmax = -1; /* unused, but compilers complain */ 3481 3482 rowners[0] = 0; 3483 for (i=2; i<=size; i++) { 3484 rowners[i] += rowners[i-1]; 3485 } 3486 rstart = rowners[rank]; 3487 rend = rowners[rank+1]; 3488 3489 /* distribute row lengths to all processors */ 3490 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3491 if (!rank) { 3492 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3493 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3494 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3495 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3496 for (j=0; j<m; j++) { 3497 procsnz[0] += ourlens[j]; 3498 } 3499 for (i=1; i<size; i++) { 3500 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3501 /* calculate the number of nonzeros on each processor */ 3502 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3503 procsnz[i] += rowlengths[j]; 3504 } 3505 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3506 } 3507 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3508 } else { 3509 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3510 } 3511 3512 if (!rank) { 3513 /* determine max buffer needed and allocate it */ 3514 maxnz = 0; 3515 for (i=0; i<size; i++) { 3516 maxnz = PetscMax(maxnz,procsnz[i]); 3517 } 3518 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3519 3520 /* read in my part of the matrix column indices */ 3521 nz = procsnz[0]; 3522 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3523 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3524 3525 /* read in every one elses and ship off */ 3526 for (i=1; i<size; i++) { 3527 nz = procsnz[i]; 3528 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3529 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3530 } 3531 ierr = PetscFree(cols);CHKERRQ(ierr); 3532 } else { 3533 /* determine buffer space needed for message */ 3534 nz = 0; 3535 for (i=0; i<m; i++) { 3536 nz += ourlens[i]; 3537 } 3538 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3539 3540 /* receive message of column indices*/ 3541 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3542 } 3543 3544 /* determine column ownership if matrix is not square */ 3545 if (N != M) { 3546 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3547 else n = newMat->cmap->n; 3548 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3549 cstart = cend - n; 3550 } else { 3551 cstart = rstart; 3552 cend = rend; 3553 n = cend - cstart; 3554 } 3555 3556 /* loop over local rows, determining number of off diagonal entries */ 3557 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3558 jj = 0; 3559 for (i=0; i<m; i++) { 3560 for (j=0; j<ourlens[i]; j++) { 3561 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3562 jj++; 3563 } 3564 } 3565 3566 for (i=0; i<m; i++) { 3567 ourlens[i] -= offlens[i]; 3568 } 3569 if (!sizesset) { 3570 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3571 } 3572 3573 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3574 3575 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3576 3577 for (i=0; i<m; i++) { 3578 ourlens[i] += offlens[i]; 3579 } 3580 3581 if (!rank) { 3582 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3583 3584 /* read in my part of the matrix numerical values */ 3585 nz = procsnz[0]; 3586 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3587 3588 /* insert into matrix */ 3589 jj = rstart; 3590 smycols = mycols; 3591 svals = vals; 3592 for (i=0; i<m; i++) { 3593 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3594 smycols += ourlens[i]; 3595 svals += ourlens[i]; 3596 jj++; 3597 } 3598 3599 /* read in other processors and ship out */ 3600 for (i=1; i<size; i++) { 3601 nz = procsnz[i]; 3602 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3603 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3604 } 3605 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3606 } else { 3607 /* receive numeric values */ 3608 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3609 3610 /* receive message of values*/ 3611 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3612 3613 /* insert into matrix */ 3614 jj = rstart; 3615 smycols = mycols; 3616 svals = vals; 3617 for (i=0; i<m; i++) { 3618 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3619 smycols += ourlens[i]; 3620 svals += ourlens[i]; 3621 jj++; 3622 } 3623 } 3624 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3625 ierr = PetscFree(vals);CHKERRQ(ierr); 3626 ierr = PetscFree(mycols);CHKERRQ(ierr); 3627 ierr = PetscFree(rowners);CHKERRQ(ierr); 3628 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3629 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3630 PetscFunctionReturn(0); 3631 } 3632 3633 #undef __FUNCT__ 3634 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3635 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3636 { 3637 PetscErrorCode ierr; 3638 IS iscol_local; 3639 PetscInt csize; 3640 3641 PetscFunctionBegin; 3642 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3643 if (call == MAT_REUSE_MATRIX) { 3644 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3645 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3646 } else { 3647 PetscInt cbs; 3648 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3649 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3650 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3651 } 3652 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3653 if (call == MAT_INITIAL_MATRIX) { 3654 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3655 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3656 } 3657 PetscFunctionReturn(0); 3658 } 3659 3660 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3661 #undef __FUNCT__ 3662 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3663 /* 3664 Not great since it makes two copies of the submatrix, first an SeqAIJ 3665 in local and then by concatenating the local matrices the end result. 3666 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3667 3668 Note: This requires a sequential iscol with all indices. 3669 */ 3670 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3671 { 3672 PetscErrorCode ierr; 3673 PetscMPIInt rank,size; 3674 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3675 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3676 PetscBool allcolumns, colflag; 3677 Mat M,Mreuse; 3678 MatScalar *vwork,*aa; 3679 MPI_Comm comm; 3680 Mat_SeqAIJ *aij; 3681 3682 PetscFunctionBegin; 3683 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3684 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3685 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3686 3687 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3688 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3689 if (colflag && ncol == mat->cmap->N) { 3690 allcolumns = PETSC_TRUE; 3691 } else { 3692 allcolumns = PETSC_FALSE; 3693 } 3694 if (call == MAT_REUSE_MATRIX) { 3695 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3696 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3697 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3698 } else { 3699 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3700 } 3701 3702 /* 3703 m - number of local rows 3704 n - number of columns (same on all processors) 3705 rstart - first row in new global matrix generated 3706 */ 3707 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3708 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3709 if (call == MAT_INITIAL_MATRIX) { 3710 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3711 ii = aij->i; 3712 jj = aij->j; 3713 3714 /* 3715 Determine the number of non-zeros in the diagonal and off-diagonal 3716 portions of the matrix in order to do correct preallocation 3717 */ 3718 3719 /* first get start and end of "diagonal" columns */ 3720 if (csize == PETSC_DECIDE) { 3721 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3722 if (mglobal == n) { /* square matrix */ 3723 nlocal = m; 3724 } else { 3725 nlocal = n/size + ((n % size) > rank); 3726 } 3727 } else { 3728 nlocal = csize; 3729 } 3730 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3731 rstart = rend - nlocal; 3732 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); 3733 3734 /* next, compute all the lengths */ 3735 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3736 olens = dlens + m; 3737 for (i=0; i<m; i++) { 3738 jend = ii[i+1] - ii[i]; 3739 olen = 0; 3740 dlen = 0; 3741 for (j=0; j<jend; j++) { 3742 if (*jj < rstart || *jj >= rend) olen++; 3743 else dlen++; 3744 jj++; 3745 } 3746 olens[i] = olen; 3747 dlens[i] = dlen; 3748 } 3749 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3750 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3751 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3752 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3753 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3754 ierr = PetscFree(dlens);CHKERRQ(ierr); 3755 } else { 3756 PetscInt ml,nl; 3757 3758 M = *newmat; 3759 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3760 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3761 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3762 /* 3763 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3764 rather than the slower MatSetValues(). 3765 */ 3766 M->was_assembled = PETSC_TRUE; 3767 M->assembled = PETSC_FALSE; 3768 } 3769 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3770 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3771 ii = aij->i; 3772 jj = aij->j; 3773 aa = aij->a; 3774 for (i=0; i<m; i++) { 3775 row = rstart + i; 3776 nz = ii[i+1] - ii[i]; 3777 cwork = jj; jj += nz; 3778 vwork = aa; aa += nz; 3779 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3780 } 3781 3782 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3783 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3784 *newmat = M; 3785 3786 /* save submatrix used in processor for next request */ 3787 if (call == MAT_INITIAL_MATRIX) { 3788 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3789 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3790 } 3791 PetscFunctionReturn(0); 3792 } 3793 3794 #undef __FUNCT__ 3795 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3796 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3797 { 3798 PetscInt m,cstart, cend,j,nnz,i,d; 3799 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3800 const PetscInt *JJ; 3801 PetscScalar *values; 3802 PetscErrorCode ierr; 3803 3804 PetscFunctionBegin; 3805 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3806 3807 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3808 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3809 m = B->rmap->n; 3810 cstart = B->cmap->rstart; 3811 cend = B->cmap->rend; 3812 rstart = B->rmap->rstart; 3813 3814 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3815 3816 #if defined(PETSC_USE_DEBUGGING) 3817 for (i=0; i<m; i++) { 3818 nnz = Ii[i+1]- Ii[i]; 3819 JJ = J + Ii[i]; 3820 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3821 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3822 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); 3823 } 3824 #endif 3825 3826 for (i=0; i<m; i++) { 3827 nnz = Ii[i+1]- Ii[i]; 3828 JJ = J + Ii[i]; 3829 nnz_max = PetscMax(nnz_max,nnz); 3830 d = 0; 3831 for (j=0; j<nnz; j++) { 3832 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3833 } 3834 d_nnz[i] = d; 3835 o_nnz[i] = nnz - d; 3836 } 3837 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3838 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3839 3840 if (v) values = (PetscScalar*)v; 3841 else { 3842 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3843 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3844 } 3845 3846 for (i=0; i<m; i++) { 3847 ii = i + rstart; 3848 nnz = Ii[i+1]- Ii[i]; 3849 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3850 } 3851 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3852 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3853 3854 if (!v) { 3855 ierr = PetscFree(values);CHKERRQ(ierr); 3856 } 3857 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3858 PetscFunctionReturn(0); 3859 } 3860 3861 #undef __FUNCT__ 3862 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3863 /*@ 3864 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3865 (the default parallel PETSc format). 3866 3867 Collective on MPI_Comm 3868 3869 Input Parameters: 3870 + B - the matrix 3871 . i - the indices into j for the start of each local row (starts with zero) 3872 . j - the column indices for each local row (starts with zero) 3873 - v - optional values in the matrix 3874 3875 Level: developer 3876 3877 Notes: 3878 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3879 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3880 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3881 3882 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3883 3884 The format which is used for the sparse matrix input, is equivalent to a 3885 row-major ordering.. i.e for the following matrix, the input data expected is 3886 as shown: 3887 3888 1 0 0 3889 2 0 3 P0 3890 ------- 3891 4 5 6 P1 3892 3893 Process0 [P0]: rows_owned=[0,1] 3894 i = {0,1,3} [size = nrow+1 = 2+1] 3895 j = {0,0,2} [size = nz = 6] 3896 v = {1,2,3} [size = nz = 6] 3897 3898 Process1 [P1]: rows_owned=[2] 3899 i = {0,3} [size = nrow+1 = 1+1] 3900 j = {0,1,2} [size = nz = 6] 3901 v = {4,5,6} [size = nz = 6] 3902 3903 .keywords: matrix, aij, compressed row, sparse, parallel 3904 3905 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3906 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3907 @*/ 3908 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3909 { 3910 PetscErrorCode ierr; 3911 3912 PetscFunctionBegin; 3913 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3914 PetscFunctionReturn(0); 3915 } 3916 3917 #undef __FUNCT__ 3918 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3919 /*@C 3920 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3921 (the default parallel PETSc format). For good matrix assembly performance 3922 the user should preallocate the matrix storage by setting the parameters 3923 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3924 performance can be increased by more than a factor of 50. 3925 3926 Collective on MPI_Comm 3927 3928 Input Parameters: 3929 + A - the matrix 3930 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3931 (same value is used for all local rows) 3932 . d_nnz - array containing the number of nonzeros in the various rows of the 3933 DIAGONAL portion of the local submatrix (possibly different for each row) 3934 or NULL, if d_nz is used to specify the nonzero structure. 3935 The size of this array is equal to the number of local rows, i.e 'm'. 3936 For matrices that will be factored, you must leave room for (and set) 3937 the diagonal entry even if it is zero. 3938 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3939 submatrix (same value is used for all local rows). 3940 - o_nnz - array containing the number of nonzeros in the various rows of the 3941 OFF-DIAGONAL portion of the local submatrix (possibly different for 3942 each row) or NULL, if o_nz is used to specify the nonzero 3943 structure. The size of this array is equal to the number 3944 of local rows, i.e 'm'. 3945 3946 If the *_nnz parameter is given then the *_nz parameter is ignored 3947 3948 The AIJ format (also called the Yale sparse matrix format or 3949 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3950 storage. The stored row and column indices begin with zero. 3951 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 3952 3953 The parallel matrix is partitioned such that the first m0 rows belong to 3954 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3955 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3956 3957 The DIAGONAL portion of the local submatrix of a processor can be defined 3958 as the submatrix which is obtained by extraction the part corresponding to 3959 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3960 first row that belongs to the processor, r2 is the last row belonging to 3961 the this processor, and c1-c2 is range of indices of the local part of a 3962 vector suitable for applying the matrix to. This is an mxn matrix. In the 3963 common case of a square matrix, the row and column ranges are the same and 3964 the DIAGONAL part is also square. The remaining portion of the local 3965 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3966 3967 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3968 3969 You can call MatGetInfo() to get information on how effective the preallocation was; 3970 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3971 You can also run with the option -info and look for messages with the string 3972 malloc in them to see if additional memory allocation was needed. 3973 3974 Example usage: 3975 3976 Consider the following 8x8 matrix with 34 non-zero values, that is 3977 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3978 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3979 as follows: 3980 3981 .vb 3982 1 2 0 | 0 3 0 | 0 4 3983 Proc0 0 5 6 | 7 0 0 | 8 0 3984 9 0 10 | 11 0 0 | 12 0 3985 ------------------------------------- 3986 13 0 14 | 15 16 17 | 0 0 3987 Proc1 0 18 0 | 19 20 21 | 0 0 3988 0 0 0 | 22 23 0 | 24 0 3989 ------------------------------------- 3990 Proc2 25 26 27 | 0 0 28 | 29 0 3991 30 0 0 | 31 32 33 | 0 34 3992 .ve 3993 3994 This can be represented as a collection of submatrices as: 3995 3996 .vb 3997 A B C 3998 D E F 3999 G H I 4000 .ve 4001 4002 Where the submatrices A,B,C are owned by proc0, D,E,F are 4003 owned by proc1, G,H,I are owned by proc2. 4004 4005 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4006 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4007 The 'M','N' parameters are 8,8, and have the same values on all procs. 4008 4009 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4010 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4011 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4012 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4013 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4014 matrix, ans [DF] as another SeqAIJ matrix. 4015 4016 When d_nz, o_nz parameters are specified, d_nz storage elements are 4017 allocated for every row of the local diagonal submatrix, and o_nz 4018 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4019 One way to choose d_nz and o_nz is to use the max nonzerors per local 4020 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4021 In this case, the values of d_nz,o_nz are: 4022 .vb 4023 proc0 : dnz = 2, o_nz = 2 4024 proc1 : dnz = 3, o_nz = 2 4025 proc2 : dnz = 1, o_nz = 4 4026 .ve 4027 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4028 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4029 for proc3. i.e we are using 12+15+10=37 storage locations to store 4030 34 values. 4031 4032 When d_nnz, o_nnz parameters are specified, the storage is specified 4033 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4034 In the above case the values for d_nnz,o_nnz are: 4035 .vb 4036 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4037 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4038 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4039 .ve 4040 Here the space allocated is sum of all the above values i.e 34, and 4041 hence pre-allocation is perfect. 4042 4043 Level: intermediate 4044 4045 .keywords: matrix, aij, compressed row, sparse, parallel 4046 4047 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4048 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4049 @*/ 4050 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4051 { 4052 PetscErrorCode ierr; 4053 4054 PetscFunctionBegin; 4055 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4056 PetscValidType(B,1); 4057 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4058 PetscFunctionReturn(0); 4059 } 4060 4061 #undef __FUNCT__ 4062 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4063 /*@ 4064 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4065 CSR format the local rows. 4066 4067 Collective on MPI_Comm 4068 4069 Input Parameters: 4070 + comm - MPI communicator 4071 . m - number of local rows (Cannot be PETSC_DECIDE) 4072 . n - This value should be the same as the local size used in creating the 4073 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4074 calculated if N is given) For square matrices n is almost always m. 4075 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4076 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4077 . i - row indices 4078 . j - column indices 4079 - a - matrix values 4080 4081 Output Parameter: 4082 . mat - the matrix 4083 4084 Level: intermediate 4085 4086 Notes: 4087 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4088 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4089 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4090 4091 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4092 4093 The format which is used for the sparse matrix input, is equivalent to a 4094 row-major ordering.. i.e for the following matrix, the input data expected is 4095 as shown: 4096 4097 1 0 0 4098 2 0 3 P0 4099 ------- 4100 4 5 6 P1 4101 4102 Process0 [P0]: rows_owned=[0,1] 4103 i = {0,1,3} [size = nrow+1 = 2+1] 4104 j = {0,0,2} [size = nz = 6] 4105 v = {1,2,3} [size = nz = 6] 4106 4107 Process1 [P1]: rows_owned=[2] 4108 i = {0,3} [size = nrow+1 = 1+1] 4109 j = {0,1,2} [size = nz = 6] 4110 v = {4,5,6} [size = nz = 6] 4111 4112 .keywords: matrix, aij, compressed row, sparse, parallel 4113 4114 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4115 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4116 @*/ 4117 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4118 { 4119 PetscErrorCode ierr; 4120 4121 PetscFunctionBegin; 4122 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4123 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4124 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4125 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4126 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4127 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4128 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4129 PetscFunctionReturn(0); 4130 } 4131 4132 #undef __FUNCT__ 4133 #define __FUNCT__ "MatCreateAIJ" 4134 /*@C 4135 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4136 (the default parallel PETSc format). For good matrix assembly performance 4137 the user should preallocate the matrix storage by setting the parameters 4138 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4139 performance can be increased by more than a factor of 50. 4140 4141 Collective on MPI_Comm 4142 4143 Input Parameters: 4144 + comm - MPI communicator 4145 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4146 This value should be the same as the local size used in creating the 4147 y vector for the matrix-vector product y = Ax. 4148 . n - This value should be the same as the local size used in creating the 4149 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4150 calculated if N is given) For square matrices n is almost always m. 4151 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4152 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4153 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4154 (same value is used for all local rows) 4155 . d_nnz - array containing the number of nonzeros in the various rows of the 4156 DIAGONAL portion of the local submatrix (possibly different for each row) 4157 or NULL, if d_nz is used to specify the nonzero structure. 4158 The size of this array is equal to the number of local rows, i.e 'm'. 4159 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4160 submatrix (same value is used for all local rows). 4161 - o_nnz - array containing the number of nonzeros in the various rows of the 4162 OFF-DIAGONAL portion of the local submatrix (possibly different for 4163 each row) or NULL, if o_nz is used to specify the nonzero 4164 structure. The size of this array is equal to the number 4165 of local rows, i.e 'm'. 4166 4167 Output Parameter: 4168 . A - the matrix 4169 4170 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4171 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4172 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4173 4174 Notes: 4175 If the *_nnz parameter is given then the *_nz parameter is ignored 4176 4177 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4178 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4179 storage requirements for this matrix. 4180 4181 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4182 processor than it must be used on all processors that share the object for 4183 that argument. 4184 4185 The user MUST specify either the local or global matrix dimensions 4186 (possibly both). 4187 4188 The parallel matrix is partitioned across processors such that the 4189 first m0 rows belong to process 0, the next m1 rows belong to 4190 process 1, the next m2 rows belong to process 2 etc.. where 4191 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4192 values corresponding to [m x N] submatrix. 4193 4194 The columns are logically partitioned with the n0 columns belonging 4195 to 0th partition, the next n1 columns belonging to the next 4196 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4197 4198 The DIAGONAL portion of the local submatrix on any given processor 4199 is the submatrix corresponding to the rows and columns m,n 4200 corresponding to the given processor. i.e diagonal matrix on 4201 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4202 etc. The remaining portion of the local submatrix [m x (N-n)] 4203 constitute the OFF-DIAGONAL portion. The example below better 4204 illustrates this concept. 4205 4206 For a square global matrix we define each processor's diagonal portion 4207 to be its local rows and the corresponding columns (a square submatrix); 4208 each processor's off-diagonal portion encompasses the remainder of the 4209 local matrix (a rectangular submatrix). 4210 4211 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4212 4213 When calling this routine with a single process communicator, a matrix of 4214 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4215 type of communicator, use the construction mechanism: 4216 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4217 4218 By default, this format uses inodes (identical nodes) when possible. 4219 We search for consecutive rows with the same nonzero structure, thereby 4220 reusing matrix information to achieve increased efficiency. 4221 4222 Options Database Keys: 4223 + -mat_no_inode - Do not use inodes 4224 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4225 - -mat_aij_oneindex - Internally use indexing starting at 1 4226 rather than 0. Note that when calling MatSetValues(), 4227 the user still MUST index entries starting at 0! 4228 4229 4230 Example usage: 4231 4232 Consider the following 8x8 matrix with 34 non-zero values, that is 4233 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4234 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4235 as follows: 4236 4237 .vb 4238 1 2 0 | 0 3 0 | 0 4 4239 Proc0 0 5 6 | 7 0 0 | 8 0 4240 9 0 10 | 11 0 0 | 12 0 4241 ------------------------------------- 4242 13 0 14 | 15 16 17 | 0 0 4243 Proc1 0 18 0 | 19 20 21 | 0 0 4244 0 0 0 | 22 23 0 | 24 0 4245 ------------------------------------- 4246 Proc2 25 26 27 | 0 0 28 | 29 0 4247 30 0 0 | 31 32 33 | 0 34 4248 .ve 4249 4250 This can be represented as a collection of submatrices as: 4251 4252 .vb 4253 A B C 4254 D E F 4255 G H I 4256 .ve 4257 4258 Where the submatrices A,B,C are owned by proc0, D,E,F are 4259 owned by proc1, G,H,I are owned by proc2. 4260 4261 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4262 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4263 The 'M','N' parameters are 8,8, and have the same values on all procs. 4264 4265 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4266 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4267 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4268 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4269 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4270 matrix, ans [DF] as another SeqAIJ matrix. 4271 4272 When d_nz, o_nz parameters are specified, d_nz storage elements are 4273 allocated for every row of the local diagonal submatrix, and o_nz 4274 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4275 One way to choose d_nz and o_nz is to use the max nonzerors per local 4276 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4277 In this case, the values of d_nz,o_nz are: 4278 .vb 4279 proc0 : dnz = 2, o_nz = 2 4280 proc1 : dnz = 3, o_nz = 2 4281 proc2 : dnz = 1, o_nz = 4 4282 .ve 4283 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4284 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4285 for proc3. i.e we are using 12+15+10=37 storage locations to store 4286 34 values. 4287 4288 When d_nnz, o_nnz parameters are specified, the storage is specified 4289 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4290 In the above case the values for d_nnz,o_nnz are: 4291 .vb 4292 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4293 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4294 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4295 .ve 4296 Here the space allocated is sum of all the above values i.e 34, and 4297 hence pre-allocation is perfect. 4298 4299 Level: intermediate 4300 4301 .keywords: matrix, aij, compressed row, sparse, parallel 4302 4303 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4304 MPIAIJ, MatCreateMPIAIJWithArrays() 4305 @*/ 4306 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) 4307 { 4308 PetscErrorCode ierr; 4309 PetscMPIInt size; 4310 4311 PetscFunctionBegin; 4312 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4313 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4314 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4315 if (size > 1) { 4316 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4317 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4318 } else { 4319 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4320 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4321 } 4322 PetscFunctionReturn(0); 4323 } 4324 4325 #undef __FUNCT__ 4326 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4327 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4328 { 4329 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4330 4331 PetscFunctionBegin; 4332 *Ad = a->A; 4333 *Ao = a->B; 4334 *colmap = a->garray; 4335 PetscFunctionReturn(0); 4336 } 4337 4338 #undef __FUNCT__ 4339 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4340 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4341 { 4342 PetscErrorCode ierr; 4343 PetscInt i; 4344 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4345 4346 PetscFunctionBegin; 4347 if (coloring->ctype == IS_COLORING_GLOBAL) { 4348 ISColoringValue *allcolors,*colors; 4349 ISColoring ocoloring; 4350 4351 /* set coloring for diagonal portion */ 4352 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4353 4354 /* set coloring for off-diagonal portion */ 4355 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4356 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4357 for (i=0; i<a->B->cmap->n; i++) { 4358 colors[i] = allcolors[a->garray[i]]; 4359 } 4360 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4361 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4362 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4363 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4364 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4365 ISColoringValue *colors; 4366 PetscInt *larray; 4367 ISColoring ocoloring; 4368 4369 /* set coloring for diagonal portion */ 4370 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4371 for (i=0; i<a->A->cmap->n; i++) { 4372 larray[i] = i + A->cmap->rstart; 4373 } 4374 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4375 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4376 for (i=0; i<a->A->cmap->n; i++) { 4377 colors[i] = coloring->colors[larray[i]]; 4378 } 4379 ierr = PetscFree(larray);CHKERRQ(ierr); 4380 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4381 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4382 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4383 4384 /* set coloring for off-diagonal portion */ 4385 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4386 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4387 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4388 for (i=0; i<a->B->cmap->n; i++) { 4389 colors[i] = coloring->colors[larray[i]]; 4390 } 4391 ierr = PetscFree(larray);CHKERRQ(ierr); 4392 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4393 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4394 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4395 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4396 PetscFunctionReturn(0); 4397 } 4398 4399 #undef __FUNCT__ 4400 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4401 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4402 { 4403 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4404 PetscErrorCode ierr; 4405 4406 PetscFunctionBegin; 4407 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4408 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4409 PetscFunctionReturn(0); 4410 } 4411 4412 #undef __FUNCT__ 4413 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4414 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4415 { 4416 PetscErrorCode ierr; 4417 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4418 PetscInt *indx; 4419 4420 PetscFunctionBegin; 4421 /* This routine will ONLY return MPIAIJ type matrix */ 4422 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4423 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4424 if (n == PETSC_DECIDE) { 4425 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4426 } 4427 /* Check sum(n) = N */ 4428 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4429 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4430 4431 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4432 rstart -= m; 4433 4434 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4435 for (i=0; i<m; i++) { 4436 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4437 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4438 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4439 } 4440 4441 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4442 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4443 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4444 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4445 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4446 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4447 PetscFunctionReturn(0); 4448 } 4449 4450 #undef __FUNCT__ 4451 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4452 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4453 { 4454 PetscErrorCode ierr; 4455 PetscInt m,N,i,rstart,nnz,Ii; 4456 PetscInt *indx; 4457 PetscScalar *values; 4458 4459 PetscFunctionBegin; 4460 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4461 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4462 for (i=0; i<m; i++) { 4463 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4464 Ii = i + rstart; 4465 ierr = MatSetValues_MPIAIJ(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4466 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4467 } 4468 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4469 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4470 PetscFunctionReturn(0); 4471 } 4472 4473 #undef __FUNCT__ 4474 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4475 /*@ 4476 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4477 matrices from each processor 4478 4479 Collective on MPI_Comm 4480 4481 Input Parameters: 4482 + comm - the communicators the parallel matrix will live on 4483 . inmat - the input sequential matrices 4484 . n - number of local columns (or PETSC_DECIDE) 4485 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4486 4487 Output Parameter: 4488 . outmat - the parallel matrix generated 4489 4490 Level: advanced 4491 4492 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4493 4494 @*/ 4495 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4496 { 4497 PetscErrorCode ierr; 4498 4499 PetscFunctionBegin; 4500 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4501 if (scall == MAT_INITIAL_MATRIX) { 4502 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4503 } 4504 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4505 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4506 PetscFunctionReturn(0); 4507 } 4508 4509 #undef __FUNCT__ 4510 #define __FUNCT__ "MatFileSplit" 4511 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4512 { 4513 PetscErrorCode ierr; 4514 PetscMPIInt rank; 4515 PetscInt m,N,i,rstart,nnz; 4516 size_t len; 4517 const PetscInt *indx; 4518 PetscViewer out; 4519 char *name; 4520 Mat B; 4521 const PetscScalar *values; 4522 4523 PetscFunctionBegin; 4524 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4525 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4526 /* Should this be the type of the diagonal block of A? */ 4527 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4528 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4529 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4530 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4531 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4532 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4533 for (i=0; i<m; i++) { 4534 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4535 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4536 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4537 } 4538 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4539 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4540 4541 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4542 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4543 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4544 sprintf(name,"%s.%d",outfile,rank); 4545 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4546 ierr = PetscFree(name);CHKERRQ(ierr); 4547 ierr = MatView(B,out);CHKERRQ(ierr); 4548 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4549 ierr = MatDestroy(&B);CHKERRQ(ierr); 4550 PetscFunctionReturn(0); 4551 } 4552 4553 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4554 #undef __FUNCT__ 4555 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4556 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4557 { 4558 PetscErrorCode ierr; 4559 Mat_Merge_SeqsToMPI *merge; 4560 PetscContainer container; 4561 4562 PetscFunctionBegin; 4563 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4564 if (container) { 4565 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4566 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4567 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4568 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4569 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4570 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4571 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4572 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4573 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4574 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4575 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4576 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4577 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4578 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4579 ierr = PetscFree(merge);CHKERRQ(ierr); 4580 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4581 } 4582 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4583 PetscFunctionReturn(0); 4584 } 4585 4586 #include <../src/mat/utils/freespace.h> 4587 #include <petscbt.h> 4588 4589 #undef __FUNCT__ 4590 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4591 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4592 { 4593 PetscErrorCode ierr; 4594 MPI_Comm comm; 4595 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4596 PetscMPIInt size,rank,taga,*len_s; 4597 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4598 PetscInt proc,m; 4599 PetscInt **buf_ri,**buf_rj; 4600 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4601 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4602 MPI_Request *s_waits,*r_waits; 4603 MPI_Status *status; 4604 MatScalar *aa=a->a; 4605 MatScalar **abuf_r,*ba_i; 4606 Mat_Merge_SeqsToMPI *merge; 4607 PetscContainer container; 4608 4609 PetscFunctionBegin; 4610 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4611 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4612 4613 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4614 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4615 4616 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4617 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4618 4619 bi = merge->bi; 4620 bj = merge->bj; 4621 buf_ri = merge->buf_ri; 4622 buf_rj = merge->buf_rj; 4623 4624 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4625 owners = merge->rowmap->range; 4626 len_s = merge->len_s; 4627 4628 /* send and recv matrix values */ 4629 /*-----------------------------*/ 4630 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4631 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4632 4633 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4634 for (proc=0,k=0; proc<size; proc++) { 4635 if (!len_s[proc]) continue; 4636 i = owners[proc]; 4637 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4638 k++; 4639 } 4640 4641 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4642 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4643 ierr = PetscFree(status);CHKERRQ(ierr); 4644 4645 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4646 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4647 4648 /* insert mat values of mpimat */ 4649 /*----------------------------*/ 4650 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4651 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4652 4653 for (k=0; k<merge->nrecv; k++) { 4654 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4655 nrows = *(buf_ri_k[k]); 4656 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4657 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4658 } 4659 4660 /* set values of ba */ 4661 m = merge->rowmap->n; 4662 for (i=0; i<m; i++) { 4663 arow = owners[rank] + i; 4664 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4665 bnzi = bi[i+1] - bi[i]; 4666 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4667 4668 /* add local non-zero vals of this proc's seqmat into ba */ 4669 anzi = ai[arow+1] - ai[arow]; 4670 aj = a->j + ai[arow]; 4671 aa = a->a + ai[arow]; 4672 nextaj = 0; 4673 for (j=0; nextaj<anzi; j++) { 4674 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4675 ba_i[j] += aa[nextaj++]; 4676 } 4677 } 4678 4679 /* add received vals into ba */ 4680 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4681 /* i-th row */ 4682 if (i == *nextrow[k]) { 4683 anzi = *(nextai[k]+1) - *nextai[k]; 4684 aj = buf_rj[k] + *(nextai[k]); 4685 aa = abuf_r[k] + *(nextai[k]); 4686 nextaj = 0; 4687 for (j=0; nextaj<anzi; j++) { 4688 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4689 ba_i[j] += aa[nextaj++]; 4690 } 4691 } 4692 nextrow[k]++; nextai[k]++; 4693 } 4694 } 4695 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4696 } 4697 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4698 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4699 4700 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4701 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4702 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4703 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4704 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4705 PetscFunctionReturn(0); 4706 } 4707 4708 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4709 4710 #undef __FUNCT__ 4711 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4712 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4713 { 4714 PetscErrorCode ierr; 4715 Mat B_mpi; 4716 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4717 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4718 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4719 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4720 PetscInt len,proc,*dnz,*onz,bs,cbs; 4721 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4722 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4723 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4724 MPI_Status *status; 4725 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4726 PetscBT lnkbt; 4727 Mat_Merge_SeqsToMPI *merge; 4728 PetscContainer container; 4729 4730 PetscFunctionBegin; 4731 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4732 4733 /* make sure it is a PETSc comm */ 4734 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4735 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4736 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4737 4738 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4739 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4740 4741 /* determine row ownership */ 4742 /*---------------------------------------------------------*/ 4743 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4744 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4745 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4746 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4747 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4748 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4749 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4750 4751 m = merge->rowmap->n; 4752 owners = merge->rowmap->range; 4753 4754 /* determine the number of messages to send, their lengths */ 4755 /*---------------------------------------------------------*/ 4756 len_s = merge->len_s; 4757 4758 len = 0; /* length of buf_si[] */ 4759 merge->nsend = 0; 4760 for (proc=0; proc<size; proc++) { 4761 len_si[proc] = 0; 4762 if (proc == rank) { 4763 len_s[proc] = 0; 4764 } else { 4765 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4766 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4767 } 4768 if (len_s[proc]) { 4769 merge->nsend++; 4770 nrows = 0; 4771 for (i=owners[proc]; i<owners[proc+1]; i++) { 4772 if (ai[i+1] > ai[i]) nrows++; 4773 } 4774 len_si[proc] = 2*(nrows+1); 4775 len += len_si[proc]; 4776 } 4777 } 4778 4779 /* determine the number and length of messages to receive for ij-structure */ 4780 /*-------------------------------------------------------------------------*/ 4781 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4782 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4783 4784 /* post the Irecv of j-structure */ 4785 /*-------------------------------*/ 4786 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4787 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4788 4789 /* post the Isend of j-structure */ 4790 /*--------------------------------*/ 4791 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4792 4793 for (proc=0, k=0; proc<size; proc++) { 4794 if (!len_s[proc]) continue; 4795 i = owners[proc]; 4796 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4797 k++; 4798 } 4799 4800 /* receives and sends of j-structure are complete */ 4801 /*------------------------------------------------*/ 4802 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4803 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4804 4805 /* send and recv i-structure */ 4806 /*---------------------------*/ 4807 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4808 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4809 4810 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4811 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4812 for (proc=0,k=0; proc<size; proc++) { 4813 if (!len_s[proc]) continue; 4814 /* form outgoing message for i-structure: 4815 buf_si[0]: nrows to be sent 4816 [1:nrows]: row index (global) 4817 [nrows+1:2*nrows+1]: i-structure index 4818 */ 4819 /*-------------------------------------------*/ 4820 nrows = len_si[proc]/2 - 1; 4821 buf_si_i = buf_si + nrows+1; 4822 buf_si[0] = nrows; 4823 buf_si_i[0] = 0; 4824 nrows = 0; 4825 for (i=owners[proc]; i<owners[proc+1]; i++) { 4826 anzi = ai[i+1] - ai[i]; 4827 if (anzi) { 4828 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4829 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4830 nrows++; 4831 } 4832 } 4833 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4834 k++; 4835 buf_si += len_si[proc]; 4836 } 4837 4838 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4839 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4840 4841 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4842 for (i=0; i<merge->nrecv; i++) { 4843 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); 4844 } 4845 4846 ierr = PetscFree(len_si);CHKERRQ(ierr); 4847 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4848 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4849 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4850 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4851 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4852 ierr = PetscFree(status);CHKERRQ(ierr); 4853 4854 /* compute a local seq matrix in each processor */ 4855 /*----------------------------------------------*/ 4856 /* allocate bi array and free space for accumulating nonzero column info */ 4857 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4858 bi[0] = 0; 4859 4860 /* create and initialize a linked list */ 4861 nlnk = N+1; 4862 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4863 4864 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4865 len = ai[owners[rank+1]] - ai[owners[rank]]; 4866 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4867 4868 current_space = free_space; 4869 4870 /* determine symbolic info for each local row */ 4871 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4872 4873 for (k=0; k<merge->nrecv; k++) { 4874 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4875 nrows = *buf_ri_k[k]; 4876 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4877 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4878 } 4879 4880 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4881 len = 0; 4882 for (i=0; i<m; i++) { 4883 bnzi = 0; 4884 /* add local non-zero cols of this proc's seqmat into lnk */ 4885 arow = owners[rank] + i; 4886 anzi = ai[arow+1] - ai[arow]; 4887 aj = a->j + ai[arow]; 4888 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4889 bnzi += nlnk; 4890 /* add received col data into lnk */ 4891 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4892 if (i == *nextrow[k]) { /* i-th row */ 4893 anzi = *(nextai[k]+1) - *nextai[k]; 4894 aj = buf_rj[k] + *nextai[k]; 4895 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4896 bnzi += nlnk; 4897 nextrow[k]++; nextai[k]++; 4898 } 4899 } 4900 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4901 4902 /* if free space is not available, make more free space */ 4903 if (current_space->local_remaining<bnzi) { 4904 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4905 nspacedouble++; 4906 } 4907 /* copy data into free space, then initialize lnk */ 4908 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4909 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4910 4911 current_space->array += bnzi; 4912 current_space->local_used += bnzi; 4913 current_space->local_remaining -= bnzi; 4914 4915 bi[i+1] = bi[i] + bnzi; 4916 } 4917 4918 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4919 4920 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4921 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4922 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4923 4924 /* create symbolic parallel matrix B_mpi */ 4925 /*---------------------------------------*/ 4926 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4927 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4928 if (n==PETSC_DECIDE) { 4929 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4930 } else { 4931 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4932 } 4933 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4934 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4935 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4936 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4937 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4938 4939 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4940 B_mpi->assembled = PETSC_FALSE; 4941 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4942 merge->bi = bi; 4943 merge->bj = bj; 4944 merge->buf_ri = buf_ri; 4945 merge->buf_rj = buf_rj; 4946 merge->coi = NULL; 4947 merge->coj = NULL; 4948 merge->owners_co = NULL; 4949 4950 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4951 4952 /* attach the supporting struct to B_mpi for reuse */ 4953 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4954 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4955 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4956 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4957 *mpimat = B_mpi; 4958 4959 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4960 PetscFunctionReturn(0); 4961 } 4962 4963 #undef __FUNCT__ 4964 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4965 /*@C 4966 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4967 matrices from each processor 4968 4969 Collective on MPI_Comm 4970 4971 Input Parameters: 4972 + comm - the communicators the parallel matrix will live on 4973 . seqmat - the input sequential matrices 4974 . m - number of local rows (or PETSC_DECIDE) 4975 . n - number of local columns (or PETSC_DECIDE) 4976 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4977 4978 Output Parameter: 4979 . mpimat - the parallel matrix generated 4980 4981 Level: advanced 4982 4983 Notes: 4984 The dimensions of the sequential matrix in each processor MUST be the same. 4985 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4986 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4987 @*/ 4988 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4989 { 4990 PetscErrorCode ierr; 4991 PetscMPIInt size; 4992 4993 PetscFunctionBegin; 4994 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4995 if (size == 1) { 4996 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4997 if (scall == MAT_INITIAL_MATRIX) { 4998 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4999 } else { 5000 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5001 } 5002 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5003 PetscFunctionReturn(0); 5004 } 5005 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5006 if (scall == MAT_INITIAL_MATRIX) { 5007 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5008 } 5009 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5010 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5011 PetscFunctionReturn(0); 5012 } 5013 5014 #undef __FUNCT__ 5015 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5016 /*@ 5017 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5018 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5019 with MatGetSize() 5020 5021 Not Collective 5022 5023 Input Parameters: 5024 + A - the matrix 5025 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5026 5027 Output Parameter: 5028 . A_loc - the local sequential matrix generated 5029 5030 Level: developer 5031 5032 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5033 5034 @*/ 5035 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5036 { 5037 PetscErrorCode ierr; 5038 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5039 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5040 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5041 MatScalar *aa=a->a,*ba=b->a,*cam; 5042 PetscScalar *ca; 5043 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5044 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5045 PetscBool match; 5046 5047 PetscFunctionBegin; 5048 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5049 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5050 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5051 if (scall == MAT_INITIAL_MATRIX) { 5052 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5053 ci[0] = 0; 5054 for (i=0; i<am; i++) { 5055 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5056 } 5057 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5058 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5059 k = 0; 5060 for (i=0; i<am; i++) { 5061 ncols_o = bi[i+1] - bi[i]; 5062 ncols_d = ai[i+1] - ai[i]; 5063 /* off-diagonal portion of A */ 5064 for (jo=0; jo<ncols_o; jo++) { 5065 col = cmap[*bj]; 5066 if (col >= cstart) break; 5067 cj[k] = col; bj++; 5068 ca[k++] = *ba++; 5069 } 5070 /* diagonal portion of A */ 5071 for (j=0; j<ncols_d; j++) { 5072 cj[k] = cstart + *aj++; 5073 ca[k++] = *aa++; 5074 } 5075 /* off-diagonal portion of A */ 5076 for (j=jo; j<ncols_o; j++) { 5077 cj[k] = cmap[*bj++]; 5078 ca[k++] = *ba++; 5079 } 5080 } 5081 /* put together the new matrix */ 5082 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5083 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5084 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5085 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5086 mat->free_a = PETSC_TRUE; 5087 mat->free_ij = PETSC_TRUE; 5088 mat->nonew = 0; 5089 } else if (scall == MAT_REUSE_MATRIX) { 5090 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5091 ci = mat->i; cj = mat->j; cam = mat->a; 5092 for (i=0; i<am; i++) { 5093 /* off-diagonal portion of A */ 5094 ncols_o = bi[i+1] - bi[i]; 5095 for (jo=0; jo<ncols_o; jo++) { 5096 col = cmap[*bj]; 5097 if (col >= cstart) break; 5098 *cam++ = *ba++; bj++; 5099 } 5100 /* diagonal portion of A */ 5101 ncols_d = ai[i+1] - ai[i]; 5102 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5103 /* off-diagonal portion of A */ 5104 for (j=jo; j<ncols_o; j++) { 5105 *cam++ = *ba++; bj++; 5106 } 5107 } 5108 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5109 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5110 PetscFunctionReturn(0); 5111 } 5112 5113 #undef __FUNCT__ 5114 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5115 /*@C 5116 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5117 5118 Not Collective 5119 5120 Input Parameters: 5121 + A - the matrix 5122 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5123 - row, col - index sets of rows and columns to extract (or NULL) 5124 5125 Output Parameter: 5126 . A_loc - the local sequential matrix generated 5127 5128 Level: developer 5129 5130 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5131 5132 @*/ 5133 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5134 { 5135 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5136 PetscErrorCode ierr; 5137 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5138 IS isrowa,iscola; 5139 Mat *aloc; 5140 PetscBool match; 5141 5142 PetscFunctionBegin; 5143 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5144 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5145 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5146 if (!row) { 5147 start = A->rmap->rstart; end = A->rmap->rend; 5148 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5149 } else { 5150 isrowa = *row; 5151 } 5152 if (!col) { 5153 start = A->cmap->rstart; 5154 cmap = a->garray; 5155 nzA = a->A->cmap->n; 5156 nzB = a->B->cmap->n; 5157 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5158 ncols = 0; 5159 for (i=0; i<nzB; i++) { 5160 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5161 else break; 5162 } 5163 imark = i; 5164 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5165 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5166 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5167 } else { 5168 iscola = *col; 5169 } 5170 if (scall != MAT_INITIAL_MATRIX) { 5171 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5172 aloc[0] = *A_loc; 5173 } 5174 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5175 *A_loc = aloc[0]; 5176 ierr = PetscFree(aloc);CHKERRQ(ierr); 5177 if (!row) { 5178 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5179 } 5180 if (!col) { 5181 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5182 } 5183 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5184 PetscFunctionReturn(0); 5185 } 5186 5187 #undef __FUNCT__ 5188 #define __FUNCT__ "MatGetBrowsOfAcols" 5189 /*@C 5190 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5191 5192 Collective on Mat 5193 5194 Input Parameters: 5195 + A,B - the matrices in mpiaij format 5196 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5197 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5198 5199 Output Parameter: 5200 + rowb, colb - index sets of rows and columns of B to extract 5201 - B_seq - the sequential matrix generated 5202 5203 Level: developer 5204 5205 @*/ 5206 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5207 { 5208 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5209 PetscErrorCode ierr; 5210 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5211 IS isrowb,iscolb; 5212 Mat *bseq=NULL; 5213 5214 PetscFunctionBegin; 5215 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5216 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); 5217 } 5218 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5219 5220 if (scall == MAT_INITIAL_MATRIX) { 5221 start = A->cmap->rstart; 5222 cmap = a->garray; 5223 nzA = a->A->cmap->n; 5224 nzB = a->B->cmap->n; 5225 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5226 ncols = 0; 5227 for (i=0; i<nzB; i++) { /* row < local row index */ 5228 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5229 else break; 5230 } 5231 imark = i; 5232 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5233 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5234 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5235 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5236 } else { 5237 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5238 isrowb = *rowb; iscolb = *colb; 5239 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5240 bseq[0] = *B_seq; 5241 } 5242 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5243 *B_seq = bseq[0]; 5244 ierr = PetscFree(bseq);CHKERRQ(ierr); 5245 if (!rowb) { 5246 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5247 } else { 5248 *rowb = isrowb; 5249 } 5250 if (!colb) { 5251 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5252 } else { 5253 *colb = iscolb; 5254 } 5255 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5256 PetscFunctionReturn(0); 5257 } 5258 5259 #undef __FUNCT__ 5260 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5261 /* 5262 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5263 of the OFF-DIAGONAL portion of local A 5264 5265 Collective on Mat 5266 5267 Input Parameters: 5268 + A,B - the matrices in mpiaij format 5269 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5270 5271 Output Parameter: 5272 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5273 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5274 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5275 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5276 5277 Level: developer 5278 5279 */ 5280 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5281 { 5282 VecScatter_MPI_General *gen_to,*gen_from; 5283 PetscErrorCode ierr; 5284 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5285 Mat_SeqAIJ *b_oth; 5286 VecScatter ctx =a->Mvctx; 5287 MPI_Comm comm; 5288 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5289 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5290 PetscScalar *rvalues,*svalues; 5291 MatScalar *b_otha,*bufa,*bufA; 5292 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5293 MPI_Request *rwaits = NULL,*swaits = NULL; 5294 MPI_Status *sstatus,rstatus; 5295 PetscMPIInt jj; 5296 PetscInt *cols,sbs,rbs; 5297 PetscScalar *vals; 5298 5299 PetscFunctionBegin; 5300 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5301 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5302 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); 5303 } 5304 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5305 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5306 5307 gen_to = (VecScatter_MPI_General*)ctx->todata; 5308 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5309 rvalues = gen_from->values; /* holds the length of receiving row */ 5310 svalues = gen_to->values; /* holds the length of sending row */ 5311 nrecvs = gen_from->n; 5312 nsends = gen_to->n; 5313 5314 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5315 srow = gen_to->indices; /* local row index to be sent */ 5316 sstarts = gen_to->starts; 5317 sprocs = gen_to->procs; 5318 sstatus = gen_to->sstatus; 5319 sbs = gen_to->bs; 5320 rstarts = gen_from->starts; 5321 rprocs = gen_from->procs; 5322 rbs = gen_from->bs; 5323 5324 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5325 if (scall == MAT_INITIAL_MATRIX) { 5326 /* i-array */ 5327 /*---------*/ 5328 /* post receives */ 5329 for (i=0; i<nrecvs; i++) { 5330 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5331 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5332 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5333 } 5334 5335 /* pack the outgoing message */ 5336 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5337 5338 sstartsj[0] = 0; 5339 rstartsj[0] = 0; 5340 len = 0; /* total length of j or a array to be sent */ 5341 k = 0; 5342 for (i=0; i<nsends; i++) { 5343 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5344 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5345 for (j=0; j<nrows; j++) { 5346 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5347 for (l=0; l<sbs; l++) { 5348 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5349 5350 rowlen[j*sbs+l] = ncols; 5351 5352 len += ncols; 5353 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5354 } 5355 k++; 5356 } 5357 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5358 5359 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5360 } 5361 /* recvs and sends of i-array are completed */ 5362 i = nrecvs; 5363 while (i--) { 5364 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5365 } 5366 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5367 5368 /* allocate buffers for sending j and a arrays */ 5369 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5370 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5371 5372 /* create i-array of B_oth */ 5373 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5374 5375 b_othi[0] = 0; 5376 len = 0; /* total length of j or a array to be received */ 5377 k = 0; 5378 for (i=0; i<nrecvs; i++) { 5379 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5380 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5381 for (j=0; j<nrows; j++) { 5382 b_othi[k+1] = b_othi[k] + rowlen[j]; 5383 len += rowlen[j]; k++; 5384 } 5385 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5386 } 5387 5388 /* allocate space for j and a arrrays of B_oth */ 5389 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5390 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5391 5392 /* j-array */ 5393 /*---------*/ 5394 /* post receives of j-array */ 5395 for (i=0; i<nrecvs; i++) { 5396 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5397 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5398 } 5399 5400 /* pack the outgoing message j-array */ 5401 k = 0; 5402 for (i=0; i<nsends; i++) { 5403 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5404 bufJ = bufj+sstartsj[i]; 5405 for (j=0; j<nrows; j++) { 5406 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5407 for (ll=0; ll<sbs; ll++) { 5408 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5409 for (l=0; l<ncols; l++) { 5410 *bufJ++ = cols[l]; 5411 } 5412 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5413 } 5414 } 5415 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5416 } 5417 5418 /* recvs and sends of j-array are completed */ 5419 i = nrecvs; 5420 while (i--) { 5421 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5422 } 5423 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5424 } else if (scall == MAT_REUSE_MATRIX) { 5425 sstartsj = *startsj_s; 5426 rstartsj = *startsj_r; 5427 bufa = *bufa_ptr; 5428 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5429 b_otha = b_oth->a; 5430 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5431 5432 /* a-array */ 5433 /*---------*/ 5434 /* post receives of a-array */ 5435 for (i=0; i<nrecvs; i++) { 5436 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5437 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5438 } 5439 5440 /* pack the outgoing message a-array */ 5441 k = 0; 5442 for (i=0; i<nsends; i++) { 5443 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5444 bufA = bufa+sstartsj[i]; 5445 for (j=0; j<nrows; j++) { 5446 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5447 for (ll=0; ll<sbs; ll++) { 5448 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5449 for (l=0; l<ncols; l++) { 5450 *bufA++ = vals[l]; 5451 } 5452 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5453 } 5454 } 5455 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5456 } 5457 /* recvs and sends of a-array are completed */ 5458 i = nrecvs; 5459 while (i--) { 5460 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5461 } 5462 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5463 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5464 5465 if (scall == MAT_INITIAL_MATRIX) { 5466 /* put together the new matrix */ 5467 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5468 5469 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5470 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5471 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5472 b_oth->free_a = PETSC_TRUE; 5473 b_oth->free_ij = PETSC_TRUE; 5474 b_oth->nonew = 0; 5475 5476 ierr = PetscFree(bufj);CHKERRQ(ierr); 5477 if (!startsj_s || !bufa_ptr) { 5478 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5479 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5480 } else { 5481 *startsj_s = sstartsj; 5482 *startsj_r = rstartsj; 5483 *bufa_ptr = bufa; 5484 } 5485 } 5486 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5487 PetscFunctionReturn(0); 5488 } 5489 5490 #undef __FUNCT__ 5491 #define __FUNCT__ "MatGetCommunicationStructs" 5492 /*@C 5493 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5494 5495 Not Collective 5496 5497 Input Parameters: 5498 . A - The matrix in mpiaij format 5499 5500 Output Parameter: 5501 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5502 . colmap - A map from global column index to local index into lvec 5503 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5504 5505 Level: developer 5506 5507 @*/ 5508 #if defined(PETSC_USE_CTABLE) 5509 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5510 #else 5511 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5512 #endif 5513 { 5514 Mat_MPIAIJ *a; 5515 5516 PetscFunctionBegin; 5517 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5518 PetscValidPointer(lvec, 2); 5519 PetscValidPointer(colmap, 3); 5520 PetscValidPointer(multScatter, 4); 5521 a = (Mat_MPIAIJ*) A->data; 5522 if (lvec) *lvec = a->lvec; 5523 if (colmap) *colmap = a->colmap; 5524 if (multScatter) *multScatter = a->Mvctx; 5525 PetscFunctionReturn(0); 5526 } 5527 5528 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5529 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5530 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5531 5532 #undef __FUNCT__ 5533 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5534 /* 5535 Computes (B'*A')' since computing B*A directly is untenable 5536 5537 n p p 5538 ( ) ( ) ( ) 5539 m ( A ) * n ( B ) = m ( C ) 5540 ( ) ( ) ( ) 5541 5542 */ 5543 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5544 { 5545 PetscErrorCode ierr; 5546 Mat At,Bt,Ct; 5547 5548 PetscFunctionBegin; 5549 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5550 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5551 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5552 ierr = MatDestroy(&At);CHKERRQ(ierr); 5553 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5554 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5555 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5556 PetscFunctionReturn(0); 5557 } 5558 5559 #undef __FUNCT__ 5560 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5561 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5562 { 5563 PetscErrorCode ierr; 5564 PetscInt m=A->rmap->n,n=B->cmap->n; 5565 Mat Cmat; 5566 5567 PetscFunctionBegin; 5568 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); 5569 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5570 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5571 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5572 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5573 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5574 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5575 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5576 5577 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5578 5579 *C = Cmat; 5580 PetscFunctionReturn(0); 5581 } 5582 5583 /* ----------------------------------------------------------------*/ 5584 #undef __FUNCT__ 5585 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5586 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5587 { 5588 PetscErrorCode ierr; 5589 5590 PetscFunctionBegin; 5591 if (scall == MAT_INITIAL_MATRIX) { 5592 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5593 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5594 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5595 } 5596 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5597 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5598 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5599 PetscFunctionReturn(0); 5600 } 5601 5602 #if defined(PETSC_HAVE_MUMPS) 5603 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5604 #endif 5605 #if defined(PETSC_HAVE_PASTIX) 5606 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5607 #endif 5608 #if defined(PETSC_HAVE_SUPERLU_DIST) 5609 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5610 #endif 5611 #if defined(PETSC_HAVE_CLIQUE) 5612 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5613 #endif 5614 5615 /*MC 5616 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5617 5618 Options Database Keys: 5619 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5620 5621 Level: beginner 5622 5623 .seealso: MatCreateAIJ() 5624 M*/ 5625 5626 #undef __FUNCT__ 5627 #define __FUNCT__ "MatCreate_MPIAIJ" 5628 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5629 { 5630 Mat_MPIAIJ *b; 5631 PetscErrorCode ierr; 5632 PetscMPIInt size; 5633 5634 PetscFunctionBegin; 5635 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5636 5637 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5638 B->data = (void*)b; 5639 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5640 B->assembled = PETSC_FALSE; 5641 B->insertmode = NOT_SET_VALUES; 5642 b->size = size; 5643 5644 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5645 5646 /* build cache for off array entries formed */ 5647 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5648 5649 b->donotstash = PETSC_FALSE; 5650 b->colmap = 0; 5651 b->garray = 0; 5652 b->roworiented = PETSC_TRUE; 5653 5654 /* stuff used for matrix vector multiply */ 5655 b->lvec = NULL; 5656 b->Mvctx = NULL; 5657 5658 /* stuff for MatGetRow() */ 5659 b->rowindices = 0; 5660 b->rowvalues = 0; 5661 b->getrowactive = PETSC_FALSE; 5662 5663 /* flexible pointer used in CUSP/CUSPARSE classes */ 5664 b->spptr = NULL; 5665 5666 #if defined(PETSC_HAVE_MUMPS) 5667 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5668 #endif 5669 #if defined(PETSC_HAVE_PASTIX) 5670 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5671 #endif 5672 #if defined(PETSC_HAVE_SUPERLU_DIST) 5673 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5674 #endif 5675 #if defined(PETSC_HAVE_CLIQUE) 5676 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5677 #endif 5678 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5679 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5680 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5681 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5682 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5683 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5684 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5685 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5686 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5687 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5688 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5689 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5690 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5691 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5692 PetscFunctionReturn(0); 5693 } 5694 5695 #undef __FUNCT__ 5696 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5697 /*@ 5698 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5699 and "off-diagonal" part of the matrix in CSR format. 5700 5701 Collective on MPI_Comm 5702 5703 Input Parameters: 5704 + comm - MPI communicator 5705 . m - number of local rows (Cannot be PETSC_DECIDE) 5706 . n - This value should be the same as the local size used in creating the 5707 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5708 calculated if N is given) For square matrices n is almost always m. 5709 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5710 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5711 . i - row indices for "diagonal" portion of matrix 5712 . j - column indices 5713 . a - matrix values 5714 . oi - row indices for "off-diagonal" portion of matrix 5715 . oj - column indices 5716 - oa - matrix values 5717 5718 Output Parameter: 5719 . mat - the matrix 5720 5721 Level: advanced 5722 5723 Notes: 5724 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5725 must free the arrays once the matrix has been destroyed and not before. 5726 5727 The i and j indices are 0 based 5728 5729 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5730 5731 This sets local rows and cannot be used to set off-processor values. 5732 5733 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5734 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5735 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5736 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5737 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5738 communication if it is known that only local entries will be set. 5739 5740 .keywords: matrix, aij, compressed row, sparse, parallel 5741 5742 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5743 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5744 @*/ 5745 PetscErrorCode MatCreateMPIAIJWithSplitArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt i[],PetscInt j[],PetscScalar a[],PetscInt oi[], PetscInt oj[],PetscScalar oa[],Mat *mat) 5746 { 5747 PetscErrorCode ierr; 5748 Mat_MPIAIJ *maij; 5749 5750 PetscFunctionBegin; 5751 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5752 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5753 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5754 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5755 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5756 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5757 maij = (Mat_MPIAIJ*) (*mat)->data; 5758 5759 (*mat)->preallocated = PETSC_TRUE; 5760 5761 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5762 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5763 5764 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5765 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5766 5767 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5768 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5769 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5770 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5771 5772 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5773 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5774 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5775 PetscFunctionReturn(0); 5776 } 5777 5778 /* 5779 Special version for direct calls from Fortran 5780 */ 5781 #include <petsc-private/fortranimpl.h> 5782 5783 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5784 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5785 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5786 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5787 #endif 5788 5789 /* Change these macros so can be used in void function */ 5790 #undef CHKERRQ 5791 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5792 #undef SETERRQ2 5793 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5794 #undef SETERRQ3 5795 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5796 #undef SETERRQ 5797 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5798 5799 #undef __FUNCT__ 5800 #define __FUNCT__ "matsetvaluesmpiaij_" 5801 PETSC_EXTERN void PETSC_STDCALL matsetvaluesmpiaij_(Mat *mmat,PetscInt *mm,const PetscInt im[],PetscInt *mn,const PetscInt in[],const PetscScalar v[],InsertMode *maddv,PetscErrorCode *_ierr) 5802 { 5803 Mat mat = *mmat; 5804 PetscInt m = *mm, n = *mn; 5805 InsertMode addv = *maddv; 5806 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5807 PetscScalar value; 5808 PetscErrorCode ierr; 5809 5810 MatCheckPreallocated(mat,1); 5811 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5812 5813 #if defined(PETSC_USE_DEBUG) 5814 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5815 #endif 5816 { 5817 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5818 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5819 PetscBool roworiented = aij->roworiented; 5820 5821 /* Some Variables required in the macro */ 5822 Mat A = aij->A; 5823 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5824 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5825 MatScalar *aa = a->a; 5826 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5827 Mat B = aij->B; 5828 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5829 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5830 MatScalar *ba = b->a; 5831 5832 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5833 PetscInt nonew = a->nonew; 5834 MatScalar *ap1,*ap2; 5835 5836 PetscFunctionBegin; 5837 for (i=0; i<m; i++) { 5838 if (im[i] < 0) continue; 5839 #if defined(PETSC_USE_DEBUG) 5840 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); 5841 #endif 5842 if (im[i] >= rstart && im[i] < rend) { 5843 row = im[i] - rstart; 5844 lastcol1 = -1; 5845 rp1 = aj + ai[row]; 5846 ap1 = aa + ai[row]; 5847 rmax1 = aimax[row]; 5848 nrow1 = ailen[row]; 5849 low1 = 0; 5850 high1 = nrow1; 5851 lastcol2 = -1; 5852 rp2 = bj + bi[row]; 5853 ap2 = ba + bi[row]; 5854 rmax2 = bimax[row]; 5855 nrow2 = bilen[row]; 5856 low2 = 0; 5857 high2 = nrow2; 5858 5859 for (j=0; j<n; j++) { 5860 if (roworiented) value = v[i*n+j]; 5861 else value = v[i+j*m]; 5862 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5863 if (in[j] >= cstart && in[j] < cend) { 5864 col = in[j] - cstart; 5865 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5866 } else if (in[j] < 0) continue; 5867 #if defined(PETSC_USE_DEBUG) 5868 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); 5869 #endif 5870 else { 5871 if (mat->was_assembled) { 5872 if (!aij->colmap) { 5873 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5874 } 5875 #if defined(PETSC_USE_CTABLE) 5876 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5877 col--; 5878 #else 5879 col = aij->colmap[in[j]] - 1; 5880 #endif 5881 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5882 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5883 col = in[j]; 5884 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5885 B = aij->B; 5886 b = (Mat_SeqAIJ*)B->data; 5887 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5888 rp2 = bj + bi[row]; 5889 ap2 = ba + bi[row]; 5890 rmax2 = bimax[row]; 5891 nrow2 = bilen[row]; 5892 low2 = 0; 5893 high2 = nrow2; 5894 bm = aij->B->rmap->n; 5895 ba = b->a; 5896 } 5897 } else col = in[j]; 5898 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5899 } 5900 } 5901 } else if (!aij->donotstash) { 5902 if (roworiented) { 5903 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5904 } else { 5905 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5906 } 5907 } 5908 } 5909 } 5910 PetscFunctionReturnVoid(); 5911 } 5912 5913