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_psubcomm" 2550 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_psubcomm(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 2577 PetscFunctionBegin; 2578 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2579 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2580 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2581 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2582 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2583 2584 if (reuse == MAT_REUSE_MATRIX) { 2585 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2586 if (subsize == 1) { 2587 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2588 redund = c->redundant; 2589 } else { 2590 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2591 redund = c->redundant; 2592 } 2593 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2594 2595 nsends = redund->nsends; 2596 nrecvs = redund->nrecvs; 2597 send_rank = redund->send_rank; 2598 recv_rank = redund->recv_rank; 2599 sbuf_nz = redund->sbuf_nz; 2600 rbuf_nz = redund->rbuf_nz; 2601 sbuf_j = redund->sbuf_j; 2602 sbuf_a = redund->sbuf_a; 2603 rbuf_j = redund->rbuf_j; 2604 rbuf_a = redund->rbuf_a; 2605 } 2606 2607 if (reuse == MAT_INITIAL_MATRIX) { 2608 PetscInt nleftover,np_subcomm; 2609 2610 /* get the destination processors' id send_rank, nsends and nrecvs */ 2611 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2612 2613 np_subcomm = size/nsubcomm; 2614 nleftover = size - nsubcomm*np_subcomm; 2615 2616 nsends = 0; nrecvs = 0; 2617 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2618 /* -------------------------------------------*/ 2619 for (i=0; i<size; i++) { 2620 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2621 send_rank[nsends] = i; nsends++; 2622 recv_rank[nrecvs++] = i; 2623 /* printf("[%d] send to and recv from [%d]\n",rank,i); */ 2624 } 2625 } 2626 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2627 i = size-nleftover-1; 2628 j = 0; 2629 while (j < nsubcomm - nleftover) { 2630 send_rank[nsends++] = i; 2631 i--; j++; 2632 /* printf("[%d] send to [%d]\n",rank,i); */ 2633 } 2634 } 2635 2636 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2637 for (i=0; i<nleftover; i++) { 2638 recv_rank[nrecvs++] = size-nleftover+i; 2639 /* printf("[%d] recv from [%d]\n",rank,i); */ 2640 } 2641 } 2642 } else if (psubcomm->type == PETSC_SUBCOMM_CONTIGUOUS) { 2643 /* --------------------------------------------------*/ 2644 PetscInt color,subcommstart; 2645 subcommstart=0; 2646 for (color=0; color<nsubcomm; color++) { 2647 if (psubcomm->color != color) { 2648 for (i=0; i<psubcomm->subsize[color]; i++) { 2649 if (subrank == i) { /* my_subrank == other's subrank */ 2650 send_rank[nsends++] = subcommstart+i; 2651 recv_rank[nrecvs++] = subcommstart+i; 2652 /* printf("[%d] send to and recv from [%d]\n",rank,subcommstart+i); */ 2653 } 2654 } 2655 } 2656 subcommstart += psubcomm->subsize[color]; 2657 } 2658 if (nleftover && subrank == size/nsubcomm) { /* this proc is a leftover proc, send to subcomm that does not have leftover proc */ 2659 subcommstart=0; 2660 for (color=0; color<nsubcomm; color++) { 2661 subcommstart += psubcomm->subsize[color]; 2662 if (psubcomm->color == color) continue; 2663 if (psubcomm->subsize[color] == size/nsubcomm) { /* subcomm does not have leftover proc */ 2664 send_rank[nsends++] = subcommstart -1; /* send to the last proc of subcomm[color] */ 2665 /* printf("[%d] leftover send to [%d] \n",rank,subcommstart -1); */ 2666 } 2667 } 2668 } 2669 2670 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2671 subcommstart=0; 2672 for (color=0; color<nsubcomm; color++) { 2673 subcommstart += psubcomm->subsize[color]; 2674 if (psubcomm->subsize[color] > size/nsubcomm) { /* subcomm has leftover proc */ 2675 recv_rank[nrecvs++] = subcommstart -1; /* recv from the last proc of subcomm[color] */ 2676 /* printf("[%d] recv from [%d]\n",rank,subcommstart -1); */ 2677 } 2678 } 2679 } 2680 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for PetscSubcomm type %D",psubcomm->type); 2681 2682 /* allocate sbuf_j, sbuf_a */ 2683 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2684 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2685 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2686 /* 2687 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2688 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2689 */ 2690 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2691 2692 /* copy mat's local entries into the buffers */ 2693 if (reuse == MAT_INITIAL_MATRIX) { 2694 rownz_max = 0; 2695 rptr = sbuf_j; 2696 cols = sbuf_j + rend-rstart + 1; 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 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2704 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2705 /* load the column indices for this row into cols */ 2706 lwrite = 0; 2707 for (l=0; l<nzB; l++) { 2708 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2709 vals[lwrite] = aworkB[l]; 2710 cols[lwrite++] = ctmp; 2711 } 2712 } 2713 for (l=0; l<nzA; l++) { 2714 vals[lwrite] = aworkA[l]; 2715 cols[lwrite++] = cstart + cworkA[l]; 2716 } 2717 for (l=0; l<nzB; l++) { 2718 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2719 vals[lwrite] = aworkB[l]; 2720 cols[lwrite++] = ctmp; 2721 } 2722 } 2723 vals += ncols; 2724 cols += ncols; 2725 rptr[i+1] = rptr[i] + ncols; 2726 if (rownz_max < ncols) rownz_max = ncols; 2727 } 2728 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); 2729 } else { /* only copy matrix values into sbuf_a */ 2730 rptr = sbuf_j; 2731 vals = sbuf_a; 2732 rptr[0] = 0; 2733 for (i=0; i<rend-rstart; i++) { 2734 row = i + rstart; 2735 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2736 ncols = nzA + nzB; 2737 cworkB = b->j + b->i[i]; 2738 aworkA = a->a + a->i[i]; 2739 aworkB = b->a + b->i[i]; 2740 lwrite = 0; 2741 for (l=0; l<nzB; l++) { 2742 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2743 } 2744 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2745 for (l=0; l<nzB; l++) { 2746 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2747 } 2748 vals += ncols; 2749 rptr[i+1] = rptr[i] + ncols; 2750 } 2751 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2752 2753 /* send nzlocal to others, and recv other's nzlocal */ 2754 /*--------------------------------------------------*/ 2755 if (reuse == MAT_INITIAL_MATRIX) { 2756 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2757 2758 s_waits2 = s_waits3 + nsends; 2759 s_waits1 = s_waits2 + nsends; 2760 r_waits1 = s_waits1 + nsends; 2761 r_waits2 = r_waits1 + nrecvs; 2762 r_waits3 = r_waits2 + nrecvs; 2763 } else { 2764 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2765 2766 r_waits3 = s_waits3 + nsends; 2767 } 2768 2769 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2770 if (reuse == MAT_INITIAL_MATRIX) { 2771 /* get new tags to keep the communication clean */ 2772 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2773 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2774 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2775 2776 /* post receives of other's nzlocal */ 2777 for (i=0; i<nrecvs; i++) { 2778 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2779 } 2780 /* send nzlocal to others */ 2781 for (i=0; i<nsends; i++) { 2782 sbuf_nz[i] = nzlocal; 2783 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2784 } 2785 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2786 count = nrecvs; 2787 while (count) { 2788 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2789 2790 recv_rank[imdex] = recv_status.MPI_SOURCE; 2791 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2792 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2793 2794 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2795 2796 rbuf_nz[imdex] += i + 2; 2797 2798 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2799 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2800 count--; 2801 } 2802 /* wait on sends of nzlocal */ 2803 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2804 /* send mat->i,j to others, and recv from other's */ 2805 /*------------------------------------------------*/ 2806 for (i=0; i<nsends; i++) { 2807 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2808 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2809 } 2810 /* wait on receives of mat->i,j */ 2811 /*------------------------------*/ 2812 count = nrecvs; 2813 while (count) { 2814 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2815 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); 2816 count--; 2817 } 2818 /* wait on sends of mat->i,j */ 2819 /*---------------------------*/ 2820 if (nsends) { 2821 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2822 } 2823 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2824 2825 /* post receives, send and receive mat->a */ 2826 /*----------------------------------------*/ 2827 for (imdex=0; imdex<nrecvs; imdex++) { 2828 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2829 } 2830 for (i=0; i<nsends; i++) { 2831 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2832 } 2833 count = nrecvs; 2834 while (count) { 2835 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2836 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); 2837 count--; 2838 } 2839 if (nsends) { 2840 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2841 } 2842 2843 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2844 2845 /* create redundant matrix */ 2846 /*-------------------------*/ 2847 if (reuse == MAT_INITIAL_MATRIX) { 2848 const PetscInt *range; 2849 PetscInt rstart_sub,rend_sub,mloc_sub; 2850 2851 /* compute rownz_max for preallocation */ 2852 for (imdex=0; imdex<nrecvs; imdex++) { 2853 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2854 rptr = rbuf_j[imdex]; 2855 for (i=0; i<j; i++) { 2856 ncols = rptr[i+1] - rptr[i]; 2857 if (rownz_max < ncols) rownz_max = ncols; 2858 } 2859 } 2860 2861 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2862 2863 /* get local size of redundant matrix 2864 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2865 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2866 rstart_sub = range[nsubcomm*subrank]; 2867 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2868 rend_sub = range[nsubcomm*(subrank+1)]; 2869 } else { 2870 rend_sub = mat->rmap->N; 2871 } 2872 mloc_sub = rend_sub - rstart_sub; 2873 2874 if (M == N) { 2875 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2876 } else { /* non-square matrix */ 2877 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2878 } 2879 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2880 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2881 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2882 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2883 } else { 2884 C = *matredundant; 2885 } 2886 2887 /* insert local matrix entries */ 2888 rptr = sbuf_j; 2889 cols = sbuf_j + rend-rstart + 1; 2890 vals = sbuf_a; 2891 for (i=0; i<rend-rstart; i++) { 2892 row = i + rstart; 2893 ncols = rptr[i+1] - rptr[i]; 2894 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2895 vals += ncols; 2896 cols += ncols; 2897 } 2898 /* insert received matrix entries */ 2899 for (imdex=0; imdex<nrecvs; imdex++) { 2900 rstart = rowrange[recv_rank[imdex]]; 2901 rend = rowrange[recv_rank[imdex]+1]; 2902 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2903 rptr = rbuf_j[imdex]; 2904 cols = rbuf_j[imdex] + rend-rstart + 1; 2905 vals = rbuf_a[imdex]; 2906 for (i=0; i<rend-rstart; i++) { 2907 row = i + rstart; 2908 ncols = rptr[i+1] - rptr[i]; 2909 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2910 vals += ncols; 2911 cols += ncols; 2912 } 2913 } 2914 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2915 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2916 2917 if (reuse == MAT_INITIAL_MATRIX) { 2918 *matredundant = C; 2919 2920 /* create a supporting struct and attach it to C for reuse */ 2921 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2922 if (subsize == 1) { 2923 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2924 c->redundant = redund; 2925 } else { 2926 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2927 c->redundant = redund; 2928 } 2929 2930 redund->nzlocal = nzlocal; 2931 redund->nsends = nsends; 2932 redund->nrecvs = nrecvs; 2933 redund->send_rank = send_rank; 2934 redund->recv_rank = recv_rank; 2935 redund->sbuf_nz = sbuf_nz; 2936 redund->rbuf_nz = rbuf_nz; 2937 redund->sbuf_j = sbuf_j; 2938 redund->sbuf_a = sbuf_a; 2939 redund->rbuf_j = rbuf_j; 2940 redund->rbuf_a = rbuf_a; 2941 redund->psubcomm = NULL; 2942 2943 redund->Destroy = C->ops->destroy; 2944 C->ops->destroy = MatDestroy_MatRedundant; 2945 } 2946 PetscFunctionReturn(0); 2947 } 2948 2949 #undef __FUNCT__ 2950 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2951 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2952 { 2953 PetscErrorCode ierr; 2954 2955 PetscFunctionBegin; 2956 if (subcomm == MPI_COMM_NULL || subcomm == PETSC_COMM_SELF) { /* create psubcomm */ 2957 MPI_Comm comm; 2958 PetscSubcomm psubcomm; 2959 PetscMPIInt size,subsize; 2960 2961 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2962 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2963 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2964 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2965 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_INTERLACED);CHKERRQ(ierr); 2966 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2967 2968 ierr = MatGetRedundantMatrix_MPIAIJ_psubcomm(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2969 2970 /* free psubcomm in MatDestroy_MatRedundant() */ 2971 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2972 Mat C = *matredundant; 2973 if (subsize == 1) { 2974 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2975 c->redundant->psubcomm = psubcomm; 2976 } else { 2977 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2978 c->redundant->psubcomm = psubcomm ; 2979 } 2980 } else { 2981 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet"); 2982 } 2983 PetscFunctionReturn(0); 2984 } 2985 2986 #undef __FUNCT__ 2987 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2988 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2989 { 2990 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2991 PetscErrorCode ierr; 2992 PetscInt i,*idxb = 0; 2993 PetscScalar *va,*vb; 2994 Vec vtmp; 2995 2996 PetscFunctionBegin; 2997 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2998 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2999 if (idx) { 3000 for (i=0; i<A->rmap->n; i++) { 3001 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3002 } 3003 } 3004 3005 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3006 if (idx) { 3007 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3008 } 3009 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3010 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3011 3012 for (i=0; i<A->rmap->n; i++) { 3013 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3014 va[i] = vb[i]; 3015 if (idx) idx[i] = a->garray[idxb[i]]; 3016 } 3017 } 3018 3019 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3020 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3021 ierr = PetscFree(idxb);CHKERRQ(ierr); 3022 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3023 PetscFunctionReturn(0); 3024 } 3025 3026 #undef __FUNCT__ 3027 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3028 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3029 { 3030 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3031 PetscErrorCode ierr; 3032 PetscInt i,*idxb = 0; 3033 PetscScalar *va,*vb; 3034 Vec vtmp; 3035 3036 PetscFunctionBegin; 3037 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3038 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3039 if (idx) { 3040 for (i=0; i<A->cmap->n; i++) { 3041 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3042 } 3043 } 3044 3045 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3046 if (idx) { 3047 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3048 } 3049 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3050 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3051 3052 for (i=0; i<A->rmap->n; i++) { 3053 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3054 va[i] = vb[i]; 3055 if (idx) idx[i] = a->garray[idxb[i]]; 3056 } 3057 } 3058 3059 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3060 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3061 ierr = PetscFree(idxb);CHKERRQ(ierr); 3062 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3063 PetscFunctionReturn(0); 3064 } 3065 3066 #undef __FUNCT__ 3067 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3068 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3069 { 3070 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3071 PetscInt n = A->rmap->n; 3072 PetscInt cstart = A->cmap->rstart; 3073 PetscInt *cmap = mat->garray; 3074 PetscInt *diagIdx, *offdiagIdx; 3075 Vec diagV, offdiagV; 3076 PetscScalar *a, *diagA, *offdiagA; 3077 PetscInt r; 3078 PetscErrorCode ierr; 3079 3080 PetscFunctionBegin; 3081 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3082 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3083 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3084 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3085 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3086 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3087 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3088 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3089 for (r = 0; r < n; ++r) { 3090 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3091 a[r] = diagA[r]; 3092 idx[r] = cstart + diagIdx[r]; 3093 } else { 3094 a[r] = offdiagA[r]; 3095 idx[r] = cmap[offdiagIdx[r]]; 3096 } 3097 } 3098 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3099 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3100 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3101 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3102 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3103 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3104 PetscFunctionReturn(0); 3105 } 3106 3107 #undef __FUNCT__ 3108 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3109 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3110 { 3111 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3112 PetscInt n = A->rmap->n; 3113 PetscInt cstart = A->cmap->rstart; 3114 PetscInt *cmap = mat->garray; 3115 PetscInt *diagIdx, *offdiagIdx; 3116 Vec diagV, offdiagV; 3117 PetscScalar *a, *diagA, *offdiagA; 3118 PetscInt r; 3119 PetscErrorCode ierr; 3120 3121 PetscFunctionBegin; 3122 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3123 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3124 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3125 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3126 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3127 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3128 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3129 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3130 for (r = 0; r < n; ++r) { 3131 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3132 a[r] = diagA[r]; 3133 idx[r] = cstart + diagIdx[r]; 3134 } else { 3135 a[r] = offdiagA[r]; 3136 idx[r] = cmap[offdiagIdx[r]]; 3137 } 3138 } 3139 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3140 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3141 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3142 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3143 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3144 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3145 PetscFunctionReturn(0); 3146 } 3147 3148 #undef __FUNCT__ 3149 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3150 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3151 { 3152 PetscErrorCode ierr; 3153 Mat *dummy; 3154 3155 PetscFunctionBegin; 3156 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3157 *newmat = *dummy; 3158 ierr = PetscFree(dummy);CHKERRQ(ierr); 3159 PetscFunctionReturn(0); 3160 } 3161 3162 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3163 3164 #undef __FUNCT__ 3165 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3166 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3167 { 3168 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3169 PetscErrorCode ierr; 3170 3171 PetscFunctionBegin; 3172 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3173 PetscFunctionReturn(0); 3174 } 3175 3176 #undef __FUNCT__ 3177 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3178 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3179 { 3180 PetscErrorCode ierr; 3181 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3182 3183 PetscFunctionBegin; 3184 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3185 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3186 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3187 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3188 PetscFunctionReturn(0); 3189 } 3190 3191 /* -------------------------------------------------------------------*/ 3192 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3193 MatGetRow_MPIAIJ, 3194 MatRestoreRow_MPIAIJ, 3195 MatMult_MPIAIJ, 3196 /* 4*/ MatMultAdd_MPIAIJ, 3197 MatMultTranspose_MPIAIJ, 3198 MatMultTransposeAdd_MPIAIJ, 3199 #if defined(PETSC_HAVE_PBGL) 3200 MatSolve_MPIAIJ, 3201 #else 3202 0, 3203 #endif 3204 0, 3205 0, 3206 /*10*/ 0, 3207 0, 3208 0, 3209 MatSOR_MPIAIJ, 3210 MatTranspose_MPIAIJ, 3211 /*15*/ MatGetInfo_MPIAIJ, 3212 MatEqual_MPIAIJ, 3213 MatGetDiagonal_MPIAIJ, 3214 MatDiagonalScale_MPIAIJ, 3215 MatNorm_MPIAIJ, 3216 /*20*/ MatAssemblyBegin_MPIAIJ, 3217 MatAssemblyEnd_MPIAIJ, 3218 MatSetOption_MPIAIJ, 3219 MatZeroEntries_MPIAIJ, 3220 /*24*/ MatZeroRows_MPIAIJ, 3221 0, 3222 #if defined(PETSC_HAVE_PBGL) 3223 0, 3224 #else 3225 0, 3226 #endif 3227 0, 3228 0, 3229 /*29*/ MatSetUp_MPIAIJ, 3230 #if defined(PETSC_HAVE_PBGL) 3231 0, 3232 #else 3233 0, 3234 #endif 3235 0, 3236 0, 3237 0, 3238 /*34*/ MatDuplicate_MPIAIJ, 3239 0, 3240 0, 3241 0, 3242 0, 3243 /*39*/ MatAXPY_MPIAIJ, 3244 MatGetSubMatrices_MPIAIJ, 3245 MatIncreaseOverlap_MPIAIJ, 3246 MatGetValues_MPIAIJ, 3247 MatCopy_MPIAIJ, 3248 /*44*/ MatGetRowMax_MPIAIJ, 3249 MatScale_MPIAIJ, 3250 0, 3251 0, 3252 MatZeroRowsColumns_MPIAIJ, 3253 /*49*/ MatSetRandom_MPIAIJ, 3254 0, 3255 0, 3256 0, 3257 0, 3258 /*54*/ MatFDColoringCreate_MPIAIJ, 3259 0, 3260 MatSetUnfactored_MPIAIJ, 3261 MatPermute_MPIAIJ, 3262 0, 3263 /*59*/ MatGetSubMatrix_MPIAIJ, 3264 MatDestroy_MPIAIJ, 3265 MatView_MPIAIJ, 3266 0, 3267 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3268 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3269 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3270 0, 3271 0, 3272 0, 3273 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3274 MatGetRowMinAbs_MPIAIJ, 3275 0, 3276 MatSetColoring_MPIAIJ, 3277 0, 3278 MatSetValuesAdifor_MPIAIJ, 3279 /*75*/ MatFDColoringApply_AIJ, 3280 0, 3281 0, 3282 0, 3283 MatFindZeroDiagonals_MPIAIJ, 3284 /*80*/ 0, 3285 0, 3286 0, 3287 /*83*/ MatLoad_MPIAIJ, 3288 0, 3289 0, 3290 0, 3291 0, 3292 0, 3293 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3294 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3295 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3296 MatPtAP_MPIAIJ_MPIAIJ, 3297 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3298 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3299 0, 3300 0, 3301 0, 3302 0, 3303 /*99*/ 0, 3304 0, 3305 0, 3306 MatConjugate_MPIAIJ, 3307 0, 3308 /*104*/MatSetValuesRow_MPIAIJ, 3309 MatRealPart_MPIAIJ, 3310 MatImaginaryPart_MPIAIJ, 3311 0, 3312 0, 3313 /*109*/0, 3314 MatGetRedundantMatrix_MPIAIJ, 3315 MatGetRowMin_MPIAIJ, 3316 0, 3317 0, 3318 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3319 0, 3320 0, 3321 0, 3322 0, 3323 /*119*/0, 3324 0, 3325 0, 3326 0, 3327 MatGetMultiProcBlock_MPIAIJ, 3328 /*124*/MatFindNonzeroRows_MPIAIJ, 3329 MatGetColumnNorms_MPIAIJ, 3330 MatInvertBlockDiagonal_MPIAIJ, 3331 0, 3332 MatGetSubMatricesParallel_MPIAIJ, 3333 /*129*/0, 3334 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3335 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3336 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3337 0, 3338 /*134*/0, 3339 0, 3340 0, 3341 0, 3342 0, 3343 /*139*/0, 3344 0 3345 }; 3346 3347 /* ----------------------------------------------------------------------------------------*/ 3348 3349 #undef __FUNCT__ 3350 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3351 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3352 { 3353 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3354 PetscErrorCode ierr; 3355 3356 PetscFunctionBegin; 3357 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3358 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3359 PetscFunctionReturn(0); 3360 } 3361 3362 #undef __FUNCT__ 3363 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3364 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3365 { 3366 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3367 PetscErrorCode ierr; 3368 3369 PetscFunctionBegin; 3370 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3371 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3372 PetscFunctionReturn(0); 3373 } 3374 3375 #undef __FUNCT__ 3376 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3377 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3378 { 3379 Mat_MPIAIJ *b; 3380 PetscErrorCode ierr; 3381 3382 PetscFunctionBegin; 3383 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3384 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3385 b = (Mat_MPIAIJ*)B->data; 3386 3387 if (!B->preallocated) { 3388 /* Explicitly create 2 MATSEQAIJ matrices. */ 3389 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3390 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3391 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3392 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3393 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3394 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3395 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3396 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3397 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3398 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3399 } 3400 3401 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3402 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3403 B->preallocated = PETSC_TRUE; 3404 PetscFunctionReturn(0); 3405 } 3406 3407 #undef __FUNCT__ 3408 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3409 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3410 { 3411 Mat mat; 3412 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3413 PetscErrorCode ierr; 3414 3415 PetscFunctionBegin; 3416 *newmat = 0; 3417 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3418 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3419 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3420 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3421 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3422 a = (Mat_MPIAIJ*)mat->data; 3423 3424 mat->factortype = matin->factortype; 3425 mat->rmap->bs = matin->rmap->bs; 3426 mat->cmap->bs = matin->cmap->bs; 3427 mat->assembled = PETSC_TRUE; 3428 mat->insertmode = NOT_SET_VALUES; 3429 mat->preallocated = PETSC_TRUE; 3430 3431 a->size = oldmat->size; 3432 a->rank = oldmat->rank; 3433 a->donotstash = oldmat->donotstash; 3434 a->roworiented = oldmat->roworiented; 3435 a->rowindices = 0; 3436 a->rowvalues = 0; 3437 a->getrowactive = PETSC_FALSE; 3438 3439 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3440 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3441 3442 if (oldmat->colmap) { 3443 #if defined(PETSC_USE_CTABLE) 3444 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3445 #else 3446 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3447 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3448 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3449 #endif 3450 } else a->colmap = 0; 3451 if (oldmat->garray) { 3452 PetscInt len; 3453 len = oldmat->B->cmap->n; 3454 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3455 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3456 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3457 } else a->garray = 0; 3458 3459 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3460 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3461 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3462 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3463 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3464 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3465 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3466 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3467 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3468 *newmat = mat; 3469 PetscFunctionReturn(0); 3470 } 3471 3472 3473 3474 #undef __FUNCT__ 3475 #define __FUNCT__ "MatLoad_MPIAIJ" 3476 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3477 { 3478 PetscScalar *vals,*svals; 3479 MPI_Comm comm; 3480 PetscErrorCode ierr; 3481 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3482 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3483 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3484 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3485 PetscInt cend,cstart,n,*rowners,sizesset=1; 3486 int fd; 3487 PetscInt bs = 1; 3488 3489 PetscFunctionBegin; 3490 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3491 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3492 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3493 if (!rank) { 3494 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3495 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3496 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3497 } 3498 3499 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3500 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3501 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3502 3503 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3504 3505 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3506 M = header[1]; N = header[2]; 3507 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3508 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3509 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3510 3511 /* If global sizes are set, check if they are consistent with that given in the file */ 3512 if (sizesset) { 3513 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3514 } 3515 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); 3516 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); 3517 3518 /* determine ownership of all (block) rows */ 3519 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3520 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3521 else m = newMat->rmap->n; /* Set by user */ 3522 3523 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3524 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3525 3526 /* First process needs enough room for process with most rows */ 3527 if (!rank) { 3528 mmax = rowners[1]; 3529 for (i=2; i<=size; i++) { 3530 mmax = PetscMax(mmax, rowners[i]); 3531 } 3532 } else mmax = -1; /* unused, but compilers complain */ 3533 3534 rowners[0] = 0; 3535 for (i=2; i<=size; i++) { 3536 rowners[i] += rowners[i-1]; 3537 } 3538 rstart = rowners[rank]; 3539 rend = rowners[rank+1]; 3540 3541 /* distribute row lengths to all processors */ 3542 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3543 if (!rank) { 3544 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3545 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3546 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3547 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3548 for (j=0; j<m; j++) { 3549 procsnz[0] += ourlens[j]; 3550 } 3551 for (i=1; i<size; i++) { 3552 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3553 /* calculate the number of nonzeros on each processor */ 3554 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3555 procsnz[i] += rowlengths[j]; 3556 } 3557 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3558 } 3559 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3560 } else { 3561 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3562 } 3563 3564 if (!rank) { 3565 /* determine max buffer needed and allocate it */ 3566 maxnz = 0; 3567 for (i=0; i<size; i++) { 3568 maxnz = PetscMax(maxnz,procsnz[i]); 3569 } 3570 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3571 3572 /* read in my part of the matrix column indices */ 3573 nz = procsnz[0]; 3574 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3575 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3576 3577 /* read in every one elses and ship off */ 3578 for (i=1; i<size; i++) { 3579 nz = procsnz[i]; 3580 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3581 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3582 } 3583 ierr = PetscFree(cols);CHKERRQ(ierr); 3584 } else { 3585 /* determine buffer space needed for message */ 3586 nz = 0; 3587 for (i=0; i<m; i++) { 3588 nz += ourlens[i]; 3589 } 3590 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3591 3592 /* receive message of column indices*/ 3593 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3594 } 3595 3596 /* determine column ownership if matrix is not square */ 3597 if (N != M) { 3598 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3599 else n = newMat->cmap->n; 3600 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3601 cstart = cend - n; 3602 } else { 3603 cstart = rstart; 3604 cend = rend; 3605 n = cend - cstart; 3606 } 3607 3608 /* loop over local rows, determining number of off diagonal entries */ 3609 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3610 jj = 0; 3611 for (i=0; i<m; i++) { 3612 for (j=0; j<ourlens[i]; j++) { 3613 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3614 jj++; 3615 } 3616 } 3617 3618 for (i=0; i<m; i++) { 3619 ourlens[i] -= offlens[i]; 3620 } 3621 if (!sizesset) { 3622 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3623 } 3624 3625 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3626 3627 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3628 3629 for (i=0; i<m; i++) { 3630 ourlens[i] += offlens[i]; 3631 } 3632 3633 if (!rank) { 3634 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3635 3636 /* read in my part of the matrix numerical values */ 3637 nz = procsnz[0]; 3638 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3639 3640 /* insert into matrix */ 3641 jj = rstart; 3642 smycols = mycols; 3643 svals = vals; 3644 for (i=0; i<m; i++) { 3645 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3646 smycols += ourlens[i]; 3647 svals += ourlens[i]; 3648 jj++; 3649 } 3650 3651 /* read in other processors and ship out */ 3652 for (i=1; i<size; i++) { 3653 nz = procsnz[i]; 3654 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3655 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3656 } 3657 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3658 } else { 3659 /* receive numeric values */ 3660 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3661 3662 /* receive message of values*/ 3663 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3664 3665 /* insert into matrix */ 3666 jj = rstart; 3667 smycols = mycols; 3668 svals = vals; 3669 for (i=0; i<m; i++) { 3670 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3671 smycols += ourlens[i]; 3672 svals += ourlens[i]; 3673 jj++; 3674 } 3675 } 3676 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3677 ierr = PetscFree(vals);CHKERRQ(ierr); 3678 ierr = PetscFree(mycols);CHKERRQ(ierr); 3679 ierr = PetscFree(rowners);CHKERRQ(ierr); 3680 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3681 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3682 PetscFunctionReturn(0); 3683 } 3684 3685 #undef __FUNCT__ 3686 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3687 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3688 { 3689 PetscErrorCode ierr; 3690 IS iscol_local; 3691 PetscInt csize; 3692 3693 PetscFunctionBegin; 3694 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3695 if (call == MAT_REUSE_MATRIX) { 3696 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3697 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3698 } else { 3699 PetscInt cbs; 3700 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3701 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3702 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3703 } 3704 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3705 if (call == MAT_INITIAL_MATRIX) { 3706 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3707 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3708 } 3709 PetscFunctionReturn(0); 3710 } 3711 3712 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3713 #undef __FUNCT__ 3714 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3715 /* 3716 Not great since it makes two copies of the submatrix, first an SeqAIJ 3717 in local and then by concatenating the local matrices the end result. 3718 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3719 3720 Note: This requires a sequential iscol with all indices. 3721 */ 3722 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3723 { 3724 PetscErrorCode ierr; 3725 PetscMPIInt rank,size; 3726 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3727 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3728 PetscBool allcolumns, colflag; 3729 Mat M,Mreuse; 3730 MatScalar *vwork,*aa; 3731 MPI_Comm comm; 3732 Mat_SeqAIJ *aij; 3733 3734 PetscFunctionBegin; 3735 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3736 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3737 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3738 3739 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3740 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3741 if (colflag && ncol == mat->cmap->N) { 3742 allcolumns = PETSC_TRUE; 3743 } else { 3744 allcolumns = PETSC_FALSE; 3745 } 3746 if (call == MAT_REUSE_MATRIX) { 3747 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3748 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3749 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3750 } else { 3751 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3752 } 3753 3754 /* 3755 m - number of local rows 3756 n - number of columns (same on all processors) 3757 rstart - first row in new global matrix generated 3758 */ 3759 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3760 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3761 if (call == MAT_INITIAL_MATRIX) { 3762 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3763 ii = aij->i; 3764 jj = aij->j; 3765 3766 /* 3767 Determine the number of non-zeros in the diagonal and off-diagonal 3768 portions of the matrix in order to do correct preallocation 3769 */ 3770 3771 /* first get start and end of "diagonal" columns */ 3772 if (csize == PETSC_DECIDE) { 3773 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3774 if (mglobal == n) { /* square matrix */ 3775 nlocal = m; 3776 } else { 3777 nlocal = n/size + ((n % size) > rank); 3778 } 3779 } else { 3780 nlocal = csize; 3781 } 3782 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3783 rstart = rend - nlocal; 3784 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); 3785 3786 /* next, compute all the lengths */ 3787 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3788 olens = dlens + m; 3789 for (i=0; i<m; i++) { 3790 jend = ii[i+1] - ii[i]; 3791 olen = 0; 3792 dlen = 0; 3793 for (j=0; j<jend; j++) { 3794 if (*jj < rstart || *jj >= rend) olen++; 3795 else dlen++; 3796 jj++; 3797 } 3798 olens[i] = olen; 3799 dlens[i] = dlen; 3800 } 3801 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3802 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3803 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3804 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3805 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3806 ierr = PetscFree(dlens);CHKERRQ(ierr); 3807 } else { 3808 PetscInt ml,nl; 3809 3810 M = *newmat; 3811 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3812 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3813 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3814 /* 3815 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3816 rather than the slower MatSetValues(). 3817 */ 3818 M->was_assembled = PETSC_TRUE; 3819 M->assembled = PETSC_FALSE; 3820 } 3821 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3822 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3823 ii = aij->i; 3824 jj = aij->j; 3825 aa = aij->a; 3826 for (i=0; i<m; i++) { 3827 row = rstart + i; 3828 nz = ii[i+1] - ii[i]; 3829 cwork = jj; jj += nz; 3830 vwork = aa; aa += nz; 3831 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3832 } 3833 3834 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3835 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3836 *newmat = M; 3837 3838 /* save submatrix used in processor for next request */ 3839 if (call == MAT_INITIAL_MATRIX) { 3840 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3841 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3842 } 3843 PetscFunctionReturn(0); 3844 } 3845 3846 #undef __FUNCT__ 3847 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3848 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3849 { 3850 PetscInt m,cstart, cend,j,nnz,i,d; 3851 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3852 const PetscInt *JJ; 3853 PetscScalar *values; 3854 PetscErrorCode ierr; 3855 3856 PetscFunctionBegin; 3857 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3858 3859 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3860 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3861 m = B->rmap->n; 3862 cstart = B->cmap->rstart; 3863 cend = B->cmap->rend; 3864 rstart = B->rmap->rstart; 3865 3866 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3867 3868 #if defined(PETSC_USE_DEBUGGING) 3869 for (i=0; i<m; i++) { 3870 nnz = Ii[i+1]- Ii[i]; 3871 JJ = J + Ii[i]; 3872 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3873 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3874 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); 3875 } 3876 #endif 3877 3878 for (i=0; i<m; i++) { 3879 nnz = Ii[i+1]- Ii[i]; 3880 JJ = J + Ii[i]; 3881 nnz_max = PetscMax(nnz_max,nnz); 3882 d = 0; 3883 for (j=0; j<nnz; j++) { 3884 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3885 } 3886 d_nnz[i] = d; 3887 o_nnz[i] = nnz - d; 3888 } 3889 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3890 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3891 3892 if (v) values = (PetscScalar*)v; 3893 else { 3894 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3895 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3896 } 3897 3898 for (i=0; i<m; i++) { 3899 ii = i + rstart; 3900 nnz = Ii[i+1]- Ii[i]; 3901 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3902 } 3903 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3904 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3905 3906 if (!v) { 3907 ierr = PetscFree(values);CHKERRQ(ierr); 3908 } 3909 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3910 PetscFunctionReturn(0); 3911 } 3912 3913 #undef __FUNCT__ 3914 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3915 /*@ 3916 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3917 (the default parallel PETSc format). 3918 3919 Collective on MPI_Comm 3920 3921 Input Parameters: 3922 + B - the matrix 3923 . i - the indices into j for the start of each local row (starts with zero) 3924 . j - the column indices for each local row (starts with zero) 3925 - v - optional values in the matrix 3926 3927 Level: developer 3928 3929 Notes: 3930 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3931 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3932 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3933 3934 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3935 3936 The format which is used for the sparse matrix input, is equivalent to a 3937 row-major ordering.. i.e for the following matrix, the input data expected is 3938 as shown: 3939 3940 1 0 0 3941 2 0 3 P0 3942 ------- 3943 4 5 6 P1 3944 3945 Process0 [P0]: rows_owned=[0,1] 3946 i = {0,1,3} [size = nrow+1 = 2+1] 3947 j = {0,0,2} [size = nz = 6] 3948 v = {1,2,3} [size = nz = 6] 3949 3950 Process1 [P1]: rows_owned=[2] 3951 i = {0,3} [size = nrow+1 = 1+1] 3952 j = {0,1,2} [size = nz = 6] 3953 v = {4,5,6} [size = nz = 6] 3954 3955 .keywords: matrix, aij, compressed row, sparse, parallel 3956 3957 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3958 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3959 @*/ 3960 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3961 { 3962 PetscErrorCode ierr; 3963 3964 PetscFunctionBegin; 3965 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3966 PetscFunctionReturn(0); 3967 } 3968 3969 #undef __FUNCT__ 3970 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3971 /*@C 3972 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3973 (the default parallel PETSc format). For good matrix assembly performance 3974 the user should preallocate the matrix storage by setting the parameters 3975 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3976 performance can be increased by more than a factor of 50. 3977 3978 Collective on MPI_Comm 3979 3980 Input Parameters: 3981 + A - the matrix 3982 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3983 (same value is used for all local rows) 3984 . d_nnz - array containing the number of nonzeros in the various rows of the 3985 DIAGONAL portion of the local submatrix (possibly different for each row) 3986 or NULL, if d_nz is used to specify the nonzero structure. 3987 The size of this array is equal to the number of local rows, i.e 'm'. 3988 For matrices that will be factored, you must leave room for (and set) 3989 the diagonal entry even if it is zero. 3990 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3991 submatrix (same value is used for all local rows). 3992 - o_nnz - array containing the number of nonzeros in the various rows of the 3993 OFF-DIAGONAL portion of the local submatrix (possibly different for 3994 each row) or NULL, if o_nz is used to specify the nonzero 3995 structure. The size of this array is equal to the number 3996 of local rows, i.e 'm'. 3997 3998 If the *_nnz parameter is given then the *_nz parameter is ignored 3999 4000 The AIJ format (also called the Yale sparse matrix format or 4001 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4002 storage. The stored row and column indices begin with zero. 4003 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4004 4005 The parallel matrix is partitioned such that the first m0 rows belong to 4006 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4007 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4008 4009 The DIAGONAL portion of the local submatrix of a processor can be defined 4010 as the submatrix which is obtained by extraction the part corresponding to 4011 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4012 first row that belongs to the processor, r2 is the last row belonging to 4013 the this processor, and c1-c2 is range of indices of the local part of a 4014 vector suitable for applying the matrix to. This is an mxn matrix. In the 4015 common case of a square matrix, the row and column ranges are the same and 4016 the DIAGONAL part is also square. The remaining portion of the local 4017 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4018 4019 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4020 4021 You can call MatGetInfo() to get information on how effective the preallocation was; 4022 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4023 You can also run with the option -info and look for messages with the string 4024 malloc in them to see if additional memory allocation was needed. 4025 4026 Example usage: 4027 4028 Consider the following 8x8 matrix with 34 non-zero values, that is 4029 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4030 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4031 as follows: 4032 4033 .vb 4034 1 2 0 | 0 3 0 | 0 4 4035 Proc0 0 5 6 | 7 0 0 | 8 0 4036 9 0 10 | 11 0 0 | 12 0 4037 ------------------------------------- 4038 13 0 14 | 15 16 17 | 0 0 4039 Proc1 0 18 0 | 19 20 21 | 0 0 4040 0 0 0 | 22 23 0 | 24 0 4041 ------------------------------------- 4042 Proc2 25 26 27 | 0 0 28 | 29 0 4043 30 0 0 | 31 32 33 | 0 34 4044 .ve 4045 4046 This can be represented as a collection of submatrices as: 4047 4048 .vb 4049 A B C 4050 D E F 4051 G H I 4052 .ve 4053 4054 Where the submatrices A,B,C are owned by proc0, D,E,F are 4055 owned by proc1, G,H,I are owned by proc2. 4056 4057 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4058 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4059 The 'M','N' parameters are 8,8, and have the same values on all procs. 4060 4061 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4062 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4063 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4064 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4065 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4066 matrix, ans [DF] as another SeqAIJ matrix. 4067 4068 When d_nz, o_nz parameters are specified, d_nz storage elements are 4069 allocated for every row of the local diagonal submatrix, and o_nz 4070 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4071 One way to choose d_nz and o_nz is to use the max nonzerors per local 4072 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4073 In this case, the values of d_nz,o_nz are: 4074 .vb 4075 proc0 : dnz = 2, o_nz = 2 4076 proc1 : dnz = 3, o_nz = 2 4077 proc2 : dnz = 1, o_nz = 4 4078 .ve 4079 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4080 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4081 for proc3. i.e we are using 12+15+10=37 storage locations to store 4082 34 values. 4083 4084 When d_nnz, o_nnz parameters are specified, the storage is specified 4085 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4086 In the above case the values for d_nnz,o_nnz are: 4087 .vb 4088 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4089 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4090 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4091 .ve 4092 Here the space allocated is sum of all the above values i.e 34, and 4093 hence pre-allocation is perfect. 4094 4095 Level: intermediate 4096 4097 .keywords: matrix, aij, compressed row, sparse, parallel 4098 4099 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4100 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4101 @*/ 4102 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4103 { 4104 PetscErrorCode ierr; 4105 4106 PetscFunctionBegin; 4107 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4108 PetscValidType(B,1); 4109 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4110 PetscFunctionReturn(0); 4111 } 4112 4113 #undef __FUNCT__ 4114 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4115 /*@ 4116 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4117 CSR format the local rows. 4118 4119 Collective on MPI_Comm 4120 4121 Input Parameters: 4122 + comm - MPI communicator 4123 . m - number of local rows (Cannot be PETSC_DECIDE) 4124 . n - This value should be the same as the local size used in creating the 4125 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4126 calculated if N is given) For square matrices n is almost always m. 4127 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4128 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4129 . i - row indices 4130 . j - column indices 4131 - a - matrix values 4132 4133 Output Parameter: 4134 . mat - the matrix 4135 4136 Level: intermediate 4137 4138 Notes: 4139 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4140 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4141 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4142 4143 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4144 4145 The format which is used for the sparse matrix input, is equivalent to a 4146 row-major ordering.. i.e for the following matrix, the input data expected is 4147 as shown: 4148 4149 1 0 0 4150 2 0 3 P0 4151 ------- 4152 4 5 6 P1 4153 4154 Process0 [P0]: rows_owned=[0,1] 4155 i = {0,1,3} [size = nrow+1 = 2+1] 4156 j = {0,0,2} [size = nz = 6] 4157 v = {1,2,3} [size = nz = 6] 4158 4159 Process1 [P1]: rows_owned=[2] 4160 i = {0,3} [size = nrow+1 = 1+1] 4161 j = {0,1,2} [size = nz = 6] 4162 v = {4,5,6} [size = nz = 6] 4163 4164 .keywords: matrix, aij, compressed row, sparse, parallel 4165 4166 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4167 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4168 @*/ 4169 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4170 { 4171 PetscErrorCode ierr; 4172 4173 PetscFunctionBegin; 4174 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4175 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4176 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4177 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4178 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4179 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4180 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4181 PetscFunctionReturn(0); 4182 } 4183 4184 #undef __FUNCT__ 4185 #define __FUNCT__ "MatCreateAIJ" 4186 /*@C 4187 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4188 (the default parallel PETSc format). For good matrix assembly performance 4189 the user should preallocate the matrix storage by setting the parameters 4190 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4191 performance can be increased by more than a factor of 50. 4192 4193 Collective on MPI_Comm 4194 4195 Input Parameters: 4196 + comm - MPI communicator 4197 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4198 This value should be the same as the local size used in creating the 4199 y vector for the matrix-vector product y = Ax. 4200 . n - This value should be the same as the local size used in creating the 4201 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4202 calculated if N is given) For square matrices n is almost always m. 4203 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4204 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4205 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4206 (same value is used for all local rows) 4207 . d_nnz - array containing the number of nonzeros in the various rows of the 4208 DIAGONAL portion of the local submatrix (possibly different for each row) 4209 or NULL, if d_nz is used to specify the nonzero structure. 4210 The size of this array is equal to the number of local rows, i.e 'm'. 4211 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4212 submatrix (same value is used for all local rows). 4213 - o_nnz - array containing the number of nonzeros in the various rows of the 4214 OFF-DIAGONAL portion of the local submatrix (possibly different for 4215 each row) or NULL, if o_nz is used to specify the nonzero 4216 structure. The size of this array is equal to the number 4217 of local rows, i.e 'm'. 4218 4219 Output Parameter: 4220 . A - the matrix 4221 4222 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4223 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4224 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4225 4226 Notes: 4227 If the *_nnz parameter is given then the *_nz parameter is ignored 4228 4229 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4230 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4231 storage requirements for this matrix. 4232 4233 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4234 processor than it must be used on all processors that share the object for 4235 that argument. 4236 4237 The user MUST specify either the local or global matrix dimensions 4238 (possibly both). 4239 4240 The parallel matrix is partitioned across processors such that the 4241 first m0 rows belong to process 0, the next m1 rows belong to 4242 process 1, the next m2 rows belong to process 2 etc.. where 4243 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4244 values corresponding to [m x N] submatrix. 4245 4246 The columns are logically partitioned with the n0 columns belonging 4247 to 0th partition, the next n1 columns belonging to the next 4248 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4249 4250 The DIAGONAL portion of the local submatrix on any given processor 4251 is the submatrix corresponding to the rows and columns m,n 4252 corresponding to the given processor. i.e diagonal matrix on 4253 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4254 etc. The remaining portion of the local submatrix [m x (N-n)] 4255 constitute the OFF-DIAGONAL portion. The example below better 4256 illustrates this concept. 4257 4258 For a square global matrix we define each processor's diagonal portion 4259 to be its local rows and the corresponding columns (a square submatrix); 4260 each processor's off-diagonal portion encompasses the remainder of the 4261 local matrix (a rectangular submatrix). 4262 4263 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4264 4265 When calling this routine with a single process communicator, a matrix of 4266 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4267 type of communicator, use the construction mechanism: 4268 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4269 4270 By default, this format uses inodes (identical nodes) when possible. 4271 We search for consecutive rows with the same nonzero structure, thereby 4272 reusing matrix information to achieve increased efficiency. 4273 4274 Options Database Keys: 4275 + -mat_no_inode - Do not use inodes 4276 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4277 - -mat_aij_oneindex - Internally use indexing starting at 1 4278 rather than 0. Note that when calling MatSetValues(), 4279 the user still MUST index entries starting at 0! 4280 4281 4282 Example usage: 4283 4284 Consider the following 8x8 matrix with 34 non-zero values, that is 4285 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4286 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4287 as follows: 4288 4289 .vb 4290 1 2 0 | 0 3 0 | 0 4 4291 Proc0 0 5 6 | 7 0 0 | 8 0 4292 9 0 10 | 11 0 0 | 12 0 4293 ------------------------------------- 4294 13 0 14 | 15 16 17 | 0 0 4295 Proc1 0 18 0 | 19 20 21 | 0 0 4296 0 0 0 | 22 23 0 | 24 0 4297 ------------------------------------- 4298 Proc2 25 26 27 | 0 0 28 | 29 0 4299 30 0 0 | 31 32 33 | 0 34 4300 .ve 4301 4302 This can be represented as a collection of submatrices as: 4303 4304 .vb 4305 A B C 4306 D E F 4307 G H I 4308 .ve 4309 4310 Where the submatrices A,B,C are owned by proc0, D,E,F are 4311 owned by proc1, G,H,I are owned by proc2. 4312 4313 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4314 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4315 The 'M','N' parameters are 8,8, and have the same values on all procs. 4316 4317 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4318 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4319 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4320 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4321 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4322 matrix, ans [DF] as another SeqAIJ matrix. 4323 4324 When d_nz, o_nz parameters are specified, d_nz storage elements are 4325 allocated for every row of the local diagonal submatrix, and o_nz 4326 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4327 One way to choose d_nz and o_nz is to use the max nonzerors per local 4328 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4329 In this case, the values of d_nz,o_nz are: 4330 .vb 4331 proc0 : dnz = 2, o_nz = 2 4332 proc1 : dnz = 3, o_nz = 2 4333 proc2 : dnz = 1, o_nz = 4 4334 .ve 4335 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4336 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4337 for proc3. i.e we are using 12+15+10=37 storage locations to store 4338 34 values. 4339 4340 When d_nnz, o_nnz parameters are specified, the storage is specified 4341 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4342 In the above case the values for d_nnz,o_nnz are: 4343 .vb 4344 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4345 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4346 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4347 .ve 4348 Here the space allocated is sum of all the above values i.e 34, and 4349 hence pre-allocation is perfect. 4350 4351 Level: intermediate 4352 4353 .keywords: matrix, aij, compressed row, sparse, parallel 4354 4355 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4356 MPIAIJ, MatCreateMPIAIJWithArrays() 4357 @*/ 4358 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) 4359 { 4360 PetscErrorCode ierr; 4361 PetscMPIInt size; 4362 4363 PetscFunctionBegin; 4364 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4365 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4366 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4367 if (size > 1) { 4368 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4369 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4370 } else { 4371 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4372 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4373 } 4374 PetscFunctionReturn(0); 4375 } 4376 4377 #undef __FUNCT__ 4378 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4379 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4380 { 4381 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4382 4383 PetscFunctionBegin; 4384 *Ad = a->A; 4385 *Ao = a->B; 4386 *colmap = a->garray; 4387 PetscFunctionReturn(0); 4388 } 4389 4390 #undef __FUNCT__ 4391 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4392 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4393 { 4394 PetscErrorCode ierr; 4395 PetscInt i; 4396 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4397 4398 PetscFunctionBegin; 4399 if (coloring->ctype == IS_COLORING_GLOBAL) { 4400 ISColoringValue *allcolors,*colors; 4401 ISColoring ocoloring; 4402 4403 /* set coloring for diagonal portion */ 4404 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4405 4406 /* set coloring for off-diagonal portion */ 4407 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4408 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4409 for (i=0; i<a->B->cmap->n; i++) { 4410 colors[i] = allcolors[a->garray[i]]; 4411 } 4412 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4413 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4414 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4415 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4416 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4417 ISColoringValue *colors; 4418 PetscInt *larray; 4419 ISColoring ocoloring; 4420 4421 /* set coloring for diagonal portion */ 4422 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4423 for (i=0; i<a->A->cmap->n; i++) { 4424 larray[i] = i + A->cmap->rstart; 4425 } 4426 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4427 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4428 for (i=0; i<a->A->cmap->n; i++) { 4429 colors[i] = coloring->colors[larray[i]]; 4430 } 4431 ierr = PetscFree(larray);CHKERRQ(ierr); 4432 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4433 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4434 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4435 4436 /* set coloring for off-diagonal portion */ 4437 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4438 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4439 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4440 for (i=0; i<a->B->cmap->n; i++) { 4441 colors[i] = coloring->colors[larray[i]]; 4442 } 4443 ierr = PetscFree(larray);CHKERRQ(ierr); 4444 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4445 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4446 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4447 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4448 PetscFunctionReturn(0); 4449 } 4450 4451 #undef __FUNCT__ 4452 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4453 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4454 { 4455 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4456 PetscErrorCode ierr; 4457 4458 PetscFunctionBegin; 4459 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4460 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4461 PetscFunctionReturn(0); 4462 } 4463 4464 #undef __FUNCT__ 4465 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4466 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4467 { 4468 PetscErrorCode ierr; 4469 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4470 PetscInt *indx; 4471 4472 PetscFunctionBegin; 4473 /* This routine will ONLY return MPIAIJ type matrix */ 4474 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4475 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4476 if (n == PETSC_DECIDE) { 4477 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4478 } 4479 /* Check sum(n) = N */ 4480 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4481 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4482 4483 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4484 rstart -= m; 4485 4486 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4487 for (i=0; i<m; i++) { 4488 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4489 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4490 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4491 } 4492 4493 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4494 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4495 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4496 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4497 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4498 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4499 PetscFunctionReturn(0); 4500 } 4501 4502 #undef __FUNCT__ 4503 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4504 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4505 { 4506 PetscErrorCode ierr; 4507 PetscInt m,N,i,rstart,nnz,Ii; 4508 PetscInt *indx; 4509 PetscScalar *values; 4510 4511 PetscFunctionBegin; 4512 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4513 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4514 for (i=0; i<m; i++) { 4515 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4516 Ii = i + rstart; 4517 ierr = MatSetValues_MPIAIJ(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4518 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4519 } 4520 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4521 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4522 PetscFunctionReturn(0); 4523 } 4524 4525 #undef __FUNCT__ 4526 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4527 /*@ 4528 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4529 matrices from each processor 4530 4531 Collective on MPI_Comm 4532 4533 Input Parameters: 4534 + comm - the communicators the parallel matrix will live on 4535 . inmat - the input sequential matrices 4536 . n - number of local columns (or PETSC_DECIDE) 4537 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4538 4539 Output Parameter: 4540 . outmat - the parallel matrix generated 4541 4542 Level: advanced 4543 4544 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4545 4546 @*/ 4547 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4548 { 4549 PetscErrorCode ierr; 4550 4551 PetscFunctionBegin; 4552 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4553 if (scall == MAT_INITIAL_MATRIX) { 4554 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4555 } 4556 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4557 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4558 PetscFunctionReturn(0); 4559 } 4560 4561 #undef __FUNCT__ 4562 #define __FUNCT__ "MatFileSplit" 4563 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4564 { 4565 PetscErrorCode ierr; 4566 PetscMPIInt rank; 4567 PetscInt m,N,i,rstart,nnz; 4568 size_t len; 4569 const PetscInt *indx; 4570 PetscViewer out; 4571 char *name; 4572 Mat B; 4573 const PetscScalar *values; 4574 4575 PetscFunctionBegin; 4576 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4577 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4578 /* Should this be the type of the diagonal block of A? */ 4579 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4580 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4581 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4582 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4583 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4584 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4585 for (i=0; i<m; i++) { 4586 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4587 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4588 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4589 } 4590 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4591 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4592 4593 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4594 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4595 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4596 sprintf(name,"%s.%d",outfile,rank); 4597 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4598 ierr = PetscFree(name);CHKERRQ(ierr); 4599 ierr = MatView(B,out);CHKERRQ(ierr); 4600 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4601 ierr = MatDestroy(&B);CHKERRQ(ierr); 4602 PetscFunctionReturn(0); 4603 } 4604 4605 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4606 #undef __FUNCT__ 4607 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4608 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4609 { 4610 PetscErrorCode ierr; 4611 Mat_Merge_SeqsToMPI *merge; 4612 PetscContainer container; 4613 4614 PetscFunctionBegin; 4615 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4616 if (container) { 4617 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4618 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4619 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4620 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4621 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4622 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4623 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4624 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4625 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4626 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4627 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4628 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4629 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4630 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4631 ierr = PetscFree(merge);CHKERRQ(ierr); 4632 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4633 } 4634 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4635 PetscFunctionReturn(0); 4636 } 4637 4638 #include <../src/mat/utils/freespace.h> 4639 #include <petscbt.h> 4640 4641 #undef __FUNCT__ 4642 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4643 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4644 { 4645 PetscErrorCode ierr; 4646 MPI_Comm comm; 4647 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4648 PetscMPIInt size,rank,taga,*len_s; 4649 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4650 PetscInt proc,m; 4651 PetscInt **buf_ri,**buf_rj; 4652 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4653 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4654 MPI_Request *s_waits,*r_waits; 4655 MPI_Status *status; 4656 MatScalar *aa=a->a; 4657 MatScalar **abuf_r,*ba_i; 4658 Mat_Merge_SeqsToMPI *merge; 4659 PetscContainer container; 4660 4661 PetscFunctionBegin; 4662 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4663 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4664 4665 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4666 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4667 4668 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4669 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4670 4671 bi = merge->bi; 4672 bj = merge->bj; 4673 buf_ri = merge->buf_ri; 4674 buf_rj = merge->buf_rj; 4675 4676 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4677 owners = merge->rowmap->range; 4678 len_s = merge->len_s; 4679 4680 /* send and recv matrix values */ 4681 /*-----------------------------*/ 4682 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4683 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4684 4685 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4686 for (proc=0,k=0; proc<size; proc++) { 4687 if (!len_s[proc]) continue; 4688 i = owners[proc]; 4689 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4690 k++; 4691 } 4692 4693 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4694 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4695 ierr = PetscFree(status);CHKERRQ(ierr); 4696 4697 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4698 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4699 4700 /* insert mat values of mpimat */ 4701 /*----------------------------*/ 4702 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4703 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4704 4705 for (k=0; k<merge->nrecv; k++) { 4706 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4707 nrows = *(buf_ri_k[k]); 4708 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4709 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4710 } 4711 4712 /* set values of ba */ 4713 m = merge->rowmap->n; 4714 for (i=0; i<m; i++) { 4715 arow = owners[rank] + i; 4716 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4717 bnzi = bi[i+1] - bi[i]; 4718 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4719 4720 /* add local non-zero vals of this proc's seqmat into ba */ 4721 anzi = ai[arow+1] - ai[arow]; 4722 aj = a->j + ai[arow]; 4723 aa = a->a + ai[arow]; 4724 nextaj = 0; 4725 for (j=0; nextaj<anzi; j++) { 4726 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4727 ba_i[j] += aa[nextaj++]; 4728 } 4729 } 4730 4731 /* add received vals into ba */ 4732 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4733 /* i-th row */ 4734 if (i == *nextrow[k]) { 4735 anzi = *(nextai[k]+1) - *nextai[k]; 4736 aj = buf_rj[k] + *(nextai[k]); 4737 aa = abuf_r[k] + *(nextai[k]); 4738 nextaj = 0; 4739 for (j=0; nextaj<anzi; j++) { 4740 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4741 ba_i[j] += aa[nextaj++]; 4742 } 4743 } 4744 nextrow[k]++; nextai[k]++; 4745 } 4746 } 4747 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4748 } 4749 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4750 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4751 4752 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4753 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4754 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4755 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4756 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4757 PetscFunctionReturn(0); 4758 } 4759 4760 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4761 4762 #undef __FUNCT__ 4763 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4764 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4765 { 4766 PetscErrorCode ierr; 4767 Mat B_mpi; 4768 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4769 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4770 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4771 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4772 PetscInt len,proc,*dnz,*onz,bs,cbs; 4773 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4774 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4775 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4776 MPI_Status *status; 4777 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4778 PetscBT lnkbt; 4779 Mat_Merge_SeqsToMPI *merge; 4780 PetscContainer container; 4781 4782 PetscFunctionBegin; 4783 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4784 4785 /* make sure it is a PETSc comm */ 4786 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4787 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4788 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4789 4790 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4791 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4792 4793 /* determine row ownership */ 4794 /*---------------------------------------------------------*/ 4795 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4796 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4797 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4798 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4799 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4800 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4801 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4802 4803 m = merge->rowmap->n; 4804 owners = merge->rowmap->range; 4805 4806 /* determine the number of messages to send, their lengths */ 4807 /*---------------------------------------------------------*/ 4808 len_s = merge->len_s; 4809 4810 len = 0; /* length of buf_si[] */ 4811 merge->nsend = 0; 4812 for (proc=0; proc<size; proc++) { 4813 len_si[proc] = 0; 4814 if (proc == rank) { 4815 len_s[proc] = 0; 4816 } else { 4817 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4818 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4819 } 4820 if (len_s[proc]) { 4821 merge->nsend++; 4822 nrows = 0; 4823 for (i=owners[proc]; i<owners[proc+1]; i++) { 4824 if (ai[i+1] > ai[i]) nrows++; 4825 } 4826 len_si[proc] = 2*(nrows+1); 4827 len += len_si[proc]; 4828 } 4829 } 4830 4831 /* determine the number and length of messages to receive for ij-structure */ 4832 /*-------------------------------------------------------------------------*/ 4833 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4834 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4835 4836 /* post the Irecv of j-structure */ 4837 /*-------------------------------*/ 4838 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4839 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4840 4841 /* post the Isend of j-structure */ 4842 /*--------------------------------*/ 4843 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4844 4845 for (proc=0, k=0; proc<size; proc++) { 4846 if (!len_s[proc]) continue; 4847 i = owners[proc]; 4848 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4849 k++; 4850 } 4851 4852 /* receives and sends of j-structure are complete */ 4853 /*------------------------------------------------*/ 4854 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4855 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4856 4857 /* send and recv i-structure */ 4858 /*---------------------------*/ 4859 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4860 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4861 4862 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4863 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4864 for (proc=0,k=0; proc<size; proc++) { 4865 if (!len_s[proc]) continue; 4866 /* form outgoing message for i-structure: 4867 buf_si[0]: nrows to be sent 4868 [1:nrows]: row index (global) 4869 [nrows+1:2*nrows+1]: i-structure index 4870 */ 4871 /*-------------------------------------------*/ 4872 nrows = len_si[proc]/2 - 1; 4873 buf_si_i = buf_si + nrows+1; 4874 buf_si[0] = nrows; 4875 buf_si_i[0] = 0; 4876 nrows = 0; 4877 for (i=owners[proc]; i<owners[proc+1]; i++) { 4878 anzi = ai[i+1] - ai[i]; 4879 if (anzi) { 4880 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4881 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4882 nrows++; 4883 } 4884 } 4885 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4886 k++; 4887 buf_si += len_si[proc]; 4888 } 4889 4890 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4891 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4892 4893 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4894 for (i=0; i<merge->nrecv; i++) { 4895 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); 4896 } 4897 4898 ierr = PetscFree(len_si);CHKERRQ(ierr); 4899 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4900 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4901 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4902 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4903 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4904 ierr = PetscFree(status);CHKERRQ(ierr); 4905 4906 /* compute a local seq matrix in each processor */ 4907 /*----------------------------------------------*/ 4908 /* allocate bi array and free space for accumulating nonzero column info */ 4909 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4910 bi[0] = 0; 4911 4912 /* create and initialize a linked list */ 4913 nlnk = N+1; 4914 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4915 4916 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4917 len = ai[owners[rank+1]] - ai[owners[rank]]; 4918 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4919 4920 current_space = free_space; 4921 4922 /* determine symbolic info for each local row */ 4923 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4924 4925 for (k=0; k<merge->nrecv; k++) { 4926 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4927 nrows = *buf_ri_k[k]; 4928 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4929 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4930 } 4931 4932 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4933 len = 0; 4934 for (i=0; i<m; i++) { 4935 bnzi = 0; 4936 /* add local non-zero cols of this proc's seqmat into lnk */ 4937 arow = owners[rank] + i; 4938 anzi = ai[arow+1] - ai[arow]; 4939 aj = a->j + ai[arow]; 4940 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4941 bnzi += nlnk; 4942 /* add received col data into lnk */ 4943 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4944 if (i == *nextrow[k]) { /* i-th row */ 4945 anzi = *(nextai[k]+1) - *nextai[k]; 4946 aj = buf_rj[k] + *nextai[k]; 4947 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4948 bnzi += nlnk; 4949 nextrow[k]++; nextai[k]++; 4950 } 4951 } 4952 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4953 4954 /* if free space is not available, make more free space */ 4955 if (current_space->local_remaining<bnzi) { 4956 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4957 nspacedouble++; 4958 } 4959 /* copy data into free space, then initialize lnk */ 4960 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4961 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4962 4963 current_space->array += bnzi; 4964 current_space->local_used += bnzi; 4965 current_space->local_remaining -= bnzi; 4966 4967 bi[i+1] = bi[i] + bnzi; 4968 } 4969 4970 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4971 4972 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4973 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4974 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4975 4976 /* create symbolic parallel matrix B_mpi */ 4977 /*---------------------------------------*/ 4978 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4979 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4980 if (n==PETSC_DECIDE) { 4981 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4982 } else { 4983 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4984 } 4985 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4986 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4987 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4988 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4989 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4990 4991 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4992 B_mpi->assembled = PETSC_FALSE; 4993 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4994 merge->bi = bi; 4995 merge->bj = bj; 4996 merge->buf_ri = buf_ri; 4997 merge->buf_rj = buf_rj; 4998 merge->coi = NULL; 4999 merge->coj = NULL; 5000 merge->owners_co = NULL; 5001 5002 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5003 5004 /* attach the supporting struct to B_mpi for reuse */ 5005 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5006 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5007 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5008 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5009 *mpimat = B_mpi; 5010 5011 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5012 PetscFunctionReturn(0); 5013 } 5014 5015 #undef __FUNCT__ 5016 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5017 /*@C 5018 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5019 matrices from each processor 5020 5021 Collective on MPI_Comm 5022 5023 Input Parameters: 5024 + comm - the communicators the parallel matrix will live on 5025 . seqmat - the input sequential matrices 5026 . m - number of local rows (or PETSC_DECIDE) 5027 . n - number of local columns (or PETSC_DECIDE) 5028 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5029 5030 Output Parameter: 5031 . mpimat - the parallel matrix generated 5032 5033 Level: advanced 5034 5035 Notes: 5036 The dimensions of the sequential matrix in each processor MUST be the same. 5037 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5038 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5039 @*/ 5040 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5041 { 5042 PetscErrorCode ierr; 5043 PetscMPIInt size; 5044 5045 PetscFunctionBegin; 5046 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5047 if (size == 1) { 5048 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5049 if (scall == MAT_INITIAL_MATRIX) { 5050 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5051 } else { 5052 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5053 } 5054 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5055 PetscFunctionReturn(0); 5056 } 5057 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5058 if (scall == MAT_INITIAL_MATRIX) { 5059 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5060 } 5061 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5062 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5063 PetscFunctionReturn(0); 5064 } 5065 5066 #undef __FUNCT__ 5067 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5068 /*@ 5069 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5070 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5071 with MatGetSize() 5072 5073 Not Collective 5074 5075 Input Parameters: 5076 + A - the matrix 5077 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5078 5079 Output Parameter: 5080 . A_loc - the local sequential matrix generated 5081 5082 Level: developer 5083 5084 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5085 5086 @*/ 5087 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5088 { 5089 PetscErrorCode ierr; 5090 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5091 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5092 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5093 MatScalar *aa=a->a,*ba=b->a,*cam; 5094 PetscScalar *ca; 5095 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5096 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5097 PetscBool match; 5098 5099 PetscFunctionBegin; 5100 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5101 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5102 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5103 if (scall == MAT_INITIAL_MATRIX) { 5104 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5105 ci[0] = 0; 5106 for (i=0; i<am; i++) { 5107 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5108 } 5109 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5110 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5111 k = 0; 5112 for (i=0; i<am; i++) { 5113 ncols_o = bi[i+1] - bi[i]; 5114 ncols_d = ai[i+1] - ai[i]; 5115 /* off-diagonal portion of A */ 5116 for (jo=0; jo<ncols_o; jo++) { 5117 col = cmap[*bj]; 5118 if (col >= cstart) break; 5119 cj[k] = col; bj++; 5120 ca[k++] = *ba++; 5121 } 5122 /* diagonal portion of A */ 5123 for (j=0; j<ncols_d; j++) { 5124 cj[k] = cstart + *aj++; 5125 ca[k++] = *aa++; 5126 } 5127 /* off-diagonal portion of A */ 5128 for (j=jo; j<ncols_o; j++) { 5129 cj[k] = cmap[*bj++]; 5130 ca[k++] = *ba++; 5131 } 5132 } 5133 /* put together the new matrix */ 5134 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5135 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5136 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5137 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5138 mat->free_a = PETSC_TRUE; 5139 mat->free_ij = PETSC_TRUE; 5140 mat->nonew = 0; 5141 } else if (scall == MAT_REUSE_MATRIX) { 5142 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5143 ci = mat->i; cj = mat->j; cam = mat->a; 5144 for (i=0; i<am; i++) { 5145 /* off-diagonal portion of A */ 5146 ncols_o = bi[i+1] - bi[i]; 5147 for (jo=0; jo<ncols_o; jo++) { 5148 col = cmap[*bj]; 5149 if (col >= cstart) break; 5150 *cam++ = *ba++; bj++; 5151 } 5152 /* diagonal portion of A */ 5153 ncols_d = ai[i+1] - ai[i]; 5154 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5155 /* off-diagonal portion of A */ 5156 for (j=jo; j<ncols_o; j++) { 5157 *cam++ = *ba++; bj++; 5158 } 5159 } 5160 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5161 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5162 PetscFunctionReturn(0); 5163 } 5164 5165 #undef __FUNCT__ 5166 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5167 /*@C 5168 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5169 5170 Not Collective 5171 5172 Input Parameters: 5173 + A - the matrix 5174 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5175 - row, col - index sets of rows and columns to extract (or NULL) 5176 5177 Output Parameter: 5178 . A_loc - the local sequential matrix generated 5179 5180 Level: developer 5181 5182 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5183 5184 @*/ 5185 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5186 { 5187 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5188 PetscErrorCode ierr; 5189 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5190 IS isrowa,iscola; 5191 Mat *aloc; 5192 PetscBool match; 5193 5194 PetscFunctionBegin; 5195 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5196 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5197 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5198 if (!row) { 5199 start = A->rmap->rstart; end = A->rmap->rend; 5200 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5201 } else { 5202 isrowa = *row; 5203 } 5204 if (!col) { 5205 start = A->cmap->rstart; 5206 cmap = a->garray; 5207 nzA = a->A->cmap->n; 5208 nzB = a->B->cmap->n; 5209 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5210 ncols = 0; 5211 for (i=0; i<nzB; i++) { 5212 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5213 else break; 5214 } 5215 imark = i; 5216 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5217 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5218 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5219 } else { 5220 iscola = *col; 5221 } 5222 if (scall != MAT_INITIAL_MATRIX) { 5223 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5224 aloc[0] = *A_loc; 5225 } 5226 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5227 *A_loc = aloc[0]; 5228 ierr = PetscFree(aloc);CHKERRQ(ierr); 5229 if (!row) { 5230 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5231 } 5232 if (!col) { 5233 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5234 } 5235 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5236 PetscFunctionReturn(0); 5237 } 5238 5239 #undef __FUNCT__ 5240 #define __FUNCT__ "MatGetBrowsOfAcols" 5241 /*@C 5242 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5243 5244 Collective on Mat 5245 5246 Input Parameters: 5247 + A,B - the matrices in mpiaij format 5248 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5249 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5250 5251 Output Parameter: 5252 + rowb, colb - index sets of rows and columns of B to extract 5253 - B_seq - the sequential matrix generated 5254 5255 Level: developer 5256 5257 @*/ 5258 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5259 { 5260 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5261 PetscErrorCode ierr; 5262 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5263 IS isrowb,iscolb; 5264 Mat *bseq=NULL; 5265 5266 PetscFunctionBegin; 5267 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5268 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); 5269 } 5270 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5271 5272 if (scall == MAT_INITIAL_MATRIX) { 5273 start = A->cmap->rstart; 5274 cmap = a->garray; 5275 nzA = a->A->cmap->n; 5276 nzB = a->B->cmap->n; 5277 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5278 ncols = 0; 5279 for (i=0; i<nzB; i++) { /* row < local row index */ 5280 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5281 else break; 5282 } 5283 imark = i; 5284 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5285 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5286 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5287 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5288 } else { 5289 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5290 isrowb = *rowb; iscolb = *colb; 5291 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5292 bseq[0] = *B_seq; 5293 } 5294 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5295 *B_seq = bseq[0]; 5296 ierr = PetscFree(bseq);CHKERRQ(ierr); 5297 if (!rowb) { 5298 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5299 } else { 5300 *rowb = isrowb; 5301 } 5302 if (!colb) { 5303 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5304 } else { 5305 *colb = iscolb; 5306 } 5307 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5308 PetscFunctionReturn(0); 5309 } 5310 5311 #undef __FUNCT__ 5312 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5313 /* 5314 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5315 of the OFF-DIAGONAL portion of local A 5316 5317 Collective on Mat 5318 5319 Input Parameters: 5320 + A,B - the matrices in mpiaij format 5321 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5322 5323 Output Parameter: 5324 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5325 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5326 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5327 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5328 5329 Level: developer 5330 5331 */ 5332 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5333 { 5334 VecScatter_MPI_General *gen_to,*gen_from; 5335 PetscErrorCode ierr; 5336 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5337 Mat_SeqAIJ *b_oth; 5338 VecScatter ctx =a->Mvctx; 5339 MPI_Comm comm; 5340 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5341 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5342 PetscScalar *rvalues,*svalues; 5343 MatScalar *b_otha,*bufa,*bufA; 5344 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5345 MPI_Request *rwaits = NULL,*swaits = NULL; 5346 MPI_Status *sstatus,rstatus; 5347 PetscMPIInt jj; 5348 PetscInt *cols,sbs,rbs; 5349 PetscScalar *vals; 5350 5351 PetscFunctionBegin; 5352 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5353 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5354 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); 5355 } 5356 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5357 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5358 5359 gen_to = (VecScatter_MPI_General*)ctx->todata; 5360 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5361 rvalues = gen_from->values; /* holds the length of receiving row */ 5362 svalues = gen_to->values; /* holds the length of sending row */ 5363 nrecvs = gen_from->n; 5364 nsends = gen_to->n; 5365 5366 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5367 srow = gen_to->indices; /* local row index to be sent */ 5368 sstarts = gen_to->starts; 5369 sprocs = gen_to->procs; 5370 sstatus = gen_to->sstatus; 5371 sbs = gen_to->bs; 5372 rstarts = gen_from->starts; 5373 rprocs = gen_from->procs; 5374 rbs = gen_from->bs; 5375 5376 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5377 if (scall == MAT_INITIAL_MATRIX) { 5378 /* i-array */ 5379 /*---------*/ 5380 /* post receives */ 5381 for (i=0; i<nrecvs; i++) { 5382 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5383 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5384 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5385 } 5386 5387 /* pack the outgoing message */ 5388 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5389 5390 sstartsj[0] = 0; 5391 rstartsj[0] = 0; 5392 len = 0; /* total length of j or a array to be sent */ 5393 k = 0; 5394 for (i=0; i<nsends; i++) { 5395 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5396 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5397 for (j=0; j<nrows; j++) { 5398 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5399 for (l=0; l<sbs; l++) { 5400 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5401 5402 rowlen[j*sbs+l] = ncols; 5403 5404 len += ncols; 5405 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5406 } 5407 k++; 5408 } 5409 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5410 5411 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5412 } 5413 /* recvs and sends of i-array are completed */ 5414 i = nrecvs; 5415 while (i--) { 5416 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5417 } 5418 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5419 5420 /* allocate buffers for sending j and a arrays */ 5421 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5422 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5423 5424 /* create i-array of B_oth */ 5425 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5426 5427 b_othi[0] = 0; 5428 len = 0; /* total length of j or a array to be received */ 5429 k = 0; 5430 for (i=0; i<nrecvs; i++) { 5431 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5432 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5433 for (j=0; j<nrows; j++) { 5434 b_othi[k+1] = b_othi[k] + rowlen[j]; 5435 len += rowlen[j]; k++; 5436 } 5437 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5438 } 5439 5440 /* allocate space for j and a arrrays of B_oth */ 5441 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5442 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5443 5444 /* j-array */ 5445 /*---------*/ 5446 /* post receives of j-array */ 5447 for (i=0; i<nrecvs; i++) { 5448 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5449 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5450 } 5451 5452 /* pack the outgoing message j-array */ 5453 k = 0; 5454 for (i=0; i<nsends; i++) { 5455 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5456 bufJ = bufj+sstartsj[i]; 5457 for (j=0; j<nrows; j++) { 5458 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5459 for (ll=0; ll<sbs; ll++) { 5460 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5461 for (l=0; l<ncols; l++) { 5462 *bufJ++ = cols[l]; 5463 } 5464 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5465 } 5466 } 5467 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5468 } 5469 5470 /* recvs and sends of j-array are completed */ 5471 i = nrecvs; 5472 while (i--) { 5473 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5474 } 5475 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5476 } else if (scall == MAT_REUSE_MATRIX) { 5477 sstartsj = *startsj_s; 5478 rstartsj = *startsj_r; 5479 bufa = *bufa_ptr; 5480 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5481 b_otha = b_oth->a; 5482 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5483 5484 /* a-array */ 5485 /*---------*/ 5486 /* post receives of a-array */ 5487 for (i=0; i<nrecvs; i++) { 5488 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5489 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5490 } 5491 5492 /* pack the outgoing message a-array */ 5493 k = 0; 5494 for (i=0; i<nsends; i++) { 5495 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5496 bufA = bufa+sstartsj[i]; 5497 for (j=0; j<nrows; j++) { 5498 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5499 for (ll=0; ll<sbs; ll++) { 5500 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5501 for (l=0; l<ncols; l++) { 5502 *bufA++ = vals[l]; 5503 } 5504 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5505 } 5506 } 5507 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5508 } 5509 /* recvs and sends of a-array are completed */ 5510 i = nrecvs; 5511 while (i--) { 5512 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5513 } 5514 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5515 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5516 5517 if (scall == MAT_INITIAL_MATRIX) { 5518 /* put together the new matrix */ 5519 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5520 5521 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5522 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5523 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5524 b_oth->free_a = PETSC_TRUE; 5525 b_oth->free_ij = PETSC_TRUE; 5526 b_oth->nonew = 0; 5527 5528 ierr = PetscFree(bufj);CHKERRQ(ierr); 5529 if (!startsj_s || !bufa_ptr) { 5530 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5531 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5532 } else { 5533 *startsj_s = sstartsj; 5534 *startsj_r = rstartsj; 5535 *bufa_ptr = bufa; 5536 } 5537 } 5538 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5539 PetscFunctionReturn(0); 5540 } 5541 5542 #undef __FUNCT__ 5543 #define __FUNCT__ "MatGetCommunicationStructs" 5544 /*@C 5545 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5546 5547 Not Collective 5548 5549 Input Parameters: 5550 . A - The matrix in mpiaij format 5551 5552 Output Parameter: 5553 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5554 . colmap - A map from global column index to local index into lvec 5555 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5556 5557 Level: developer 5558 5559 @*/ 5560 #if defined(PETSC_USE_CTABLE) 5561 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5562 #else 5563 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5564 #endif 5565 { 5566 Mat_MPIAIJ *a; 5567 5568 PetscFunctionBegin; 5569 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5570 PetscValidPointer(lvec, 2); 5571 PetscValidPointer(colmap, 3); 5572 PetscValidPointer(multScatter, 4); 5573 a = (Mat_MPIAIJ*) A->data; 5574 if (lvec) *lvec = a->lvec; 5575 if (colmap) *colmap = a->colmap; 5576 if (multScatter) *multScatter = a->Mvctx; 5577 PetscFunctionReturn(0); 5578 } 5579 5580 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5581 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5582 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5583 5584 #undef __FUNCT__ 5585 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5586 /* 5587 Computes (B'*A')' since computing B*A directly is untenable 5588 5589 n p p 5590 ( ) ( ) ( ) 5591 m ( A ) * n ( B ) = m ( C ) 5592 ( ) ( ) ( ) 5593 5594 */ 5595 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5596 { 5597 PetscErrorCode ierr; 5598 Mat At,Bt,Ct; 5599 5600 PetscFunctionBegin; 5601 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5602 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5603 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5604 ierr = MatDestroy(&At);CHKERRQ(ierr); 5605 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5606 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5607 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5608 PetscFunctionReturn(0); 5609 } 5610 5611 #undef __FUNCT__ 5612 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5613 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5614 { 5615 PetscErrorCode ierr; 5616 PetscInt m=A->rmap->n,n=B->cmap->n; 5617 Mat Cmat; 5618 5619 PetscFunctionBegin; 5620 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); 5621 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5622 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5623 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5624 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5625 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5626 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5627 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5628 5629 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5630 5631 *C = Cmat; 5632 PetscFunctionReturn(0); 5633 } 5634 5635 /* ----------------------------------------------------------------*/ 5636 #undef __FUNCT__ 5637 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5638 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5639 { 5640 PetscErrorCode ierr; 5641 5642 PetscFunctionBegin; 5643 if (scall == MAT_INITIAL_MATRIX) { 5644 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5645 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5646 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5647 } 5648 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5649 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5650 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5651 PetscFunctionReturn(0); 5652 } 5653 5654 #if defined(PETSC_HAVE_MUMPS) 5655 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5656 #endif 5657 #if defined(PETSC_HAVE_PASTIX) 5658 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5659 #endif 5660 #if defined(PETSC_HAVE_SUPERLU_DIST) 5661 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5662 #endif 5663 #if defined(PETSC_HAVE_CLIQUE) 5664 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5665 #endif 5666 5667 /*MC 5668 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5669 5670 Options Database Keys: 5671 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5672 5673 Level: beginner 5674 5675 .seealso: MatCreateAIJ() 5676 M*/ 5677 5678 #undef __FUNCT__ 5679 #define __FUNCT__ "MatCreate_MPIAIJ" 5680 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5681 { 5682 Mat_MPIAIJ *b; 5683 PetscErrorCode ierr; 5684 PetscMPIInt size; 5685 5686 PetscFunctionBegin; 5687 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5688 5689 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5690 B->data = (void*)b; 5691 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5692 B->assembled = PETSC_FALSE; 5693 B->insertmode = NOT_SET_VALUES; 5694 b->size = size; 5695 5696 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5697 5698 /* build cache for off array entries formed */ 5699 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5700 5701 b->donotstash = PETSC_FALSE; 5702 b->colmap = 0; 5703 b->garray = 0; 5704 b->roworiented = PETSC_TRUE; 5705 5706 /* stuff used for matrix vector multiply */ 5707 b->lvec = NULL; 5708 b->Mvctx = NULL; 5709 5710 /* stuff for MatGetRow() */ 5711 b->rowindices = 0; 5712 b->rowvalues = 0; 5713 b->getrowactive = PETSC_FALSE; 5714 5715 /* flexible pointer used in CUSP/CUSPARSE classes */ 5716 b->spptr = NULL; 5717 5718 #if defined(PETSC_HAVE_MUMPS) 5719 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5720 #endif 5721 #if defined(PETSC_HAVE_PASTIX) 5722 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5723 #endif 5724 #if defined(PETSC_HAVE_SUPERLU_DIST) 5725 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5726 #endif 5727 #if defined(PETSC_HAVE_CLIQUE) 5728 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5729 #endif 5730 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5731 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5732 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5733 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5734 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5735 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5736 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5737 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5738 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5739 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5740 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5741 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5742 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5743 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5744 PetscFunctionReturn(0); 5745 } 5746 5747 #undef __FUNCT__ 5748 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5749 /*@ 5750 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5751 and "off-diagonal" part of the matrix in CSR format. 5752 5753 Collective on MPI_Comm 5754 5755 Input Parameters: 5756 + comm - MPI communicator 5757 . m - number of local rows (Cannot be PETSC_DECIDE) 5758 . n - This value should be the same as the local size used in creating the 5759 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5760 calculated if N is given) For square matrices n is almost always m. 5761 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5762 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5763 . i - row indices for "diagonal" portion of matrix 5764 . j - column indices 5765 . a - matrix values 5766 . oi - row indices for "off-diagonal" portion of matrix 5767 . oj - column indices 5768 - oa - matrix values 5769 5770 Output Parameter: 5771 . mat - the matrix 5772 5773 Level: advanced 5774 5775 Notes: 5776 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5777 must free the arrays once the matrix has been destroyed and not before. 5778 5779 The i and j indices are 0 based 5780 5781 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5782 5783 This sets local rows and cannot be used to set off-processor values. 5784 5785 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5786 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5787 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5788 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5789 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5790 communication if it is known that only local entries will be set. 5791 5792 .keywords: matrix, aij, compressed row, sparse, parallel 5793 5794 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5795 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5796 @*/ 5797 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) 5798 { 5799 PetscErrorCode ierr; 5800 Mat_MPIAIJ *maij; 5801 5802 PetscFunctionBegin; 5803 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5804 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5805 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5806 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5807 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5808 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5809 maij = (Mat_MPIAIJ*) (*mat)->data; 5810 5811 (*mat)->preallocated = PETSC_TRUE; 5812 5813 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5814 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5815 5816 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5817 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5818 5819 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5820 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5821 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5822 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5823 5824 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5825 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5826 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5827 PetscFunctionReturn(0); 5828 } 5829 5830 /* 5831 Special version for direct calls from Fortran 5832 */ 5833 #include <petsc-private/fortranimpl.h> 5834 5835 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5836 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5837 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5838 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5839 #endif 5840 5841 /* Change these macros so can be used in void function */ 5842 #undef CHKERRQ 5843 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5844 #undef SETERRQ2 5845 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5846 #undef SETERRQ3 5847 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5848 #undef SETERRQ 5849 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5850 5851 #undef __FUNCT__ 5852 #define __FUNCT__ "matsetvaluesmpiaij_" 5853 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) 5854 { 5855 Mat mat = *mmat; 5856 PetscInt m = *mm, n = *mn; 5857 InsertMode addv = *maddv; 5858 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5859 PetscScalar value; 5860 PetscErrorCode ierr; 5861 5862 MatCheckPreallocated(mat,1); 5863 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5864 5865 #if defined(PETSC_USE_DEBUG) 5866 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5867 #endif 5868 { 5869 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5870 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5871 PetscBool roworiented = aij->roworiented; 5872 5873 /* Some Variables required in the macro */ 5874 Mat A = aij->A; 5875 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5876 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5877 MatScalar *aa = a->a; 5878 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5879 Mat B = aij->B; 5880 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5881 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5882 MatScalar *ba = b->a; 5883 5884 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5885 PetscInt nonew = a->nonew; 5886 MatScalar *ap1,*ap2; 5887 5888 PetscFunctionBegin; 5889 for (i=0; i<m; i++) { 5890 if (im[i] < 0) continue; 5891 #if defined(PETSC_USE_DEBUG) 5892 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); 5893 #endif 5894 if (im[i] >= rstart && im[i] < rend) { 5895 row = im[i] - rstart; 5896 lastcol1 = -1; 5897 rp1 = aj + ai[row]; 5898 ap1 = aa + ai[row]; 5899 rmax1 = aimax[row]; 5900 nrow1 = ailen[row]; 5901 low1 = 0; 5902 high1 = nrow1; 5903 lastcol2 = -1; 5904 rp2 = bj + bi[row]; 5905 ap2 = ba + bi[row]; 5906 rmax2 = bimax[row]; 5907 nrow2 = bilen[row]; 5908 low2 = 0; 5909 high2 = nrow2; 5910 5911 for (j=0; j<n; j++) { 5912 if (roworiented) value = v[i*n+j]; 5913 else value = v[i+j*m]; 5914 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5915 if (in[j] >= cstart && in[j] < cend) { 5916 col = in[j] - cstart; 5917 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5918 } else if (in[j] < 0) continue; 5919 #if defined(PETSC_USE_DEBUG) 5920 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); 5921 #endif 5922 else { 5923 if (mat->was_assembled) { 5924 if (!aij->colmap) { 5925 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5926 } 5927 #if defined(PETSC_USE_CTABLE) 5928 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5929 col--; 5930 #else 5931 col = aij->colmap[in[j]] - 1; 5932 #endif 5933 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5934 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5935 col = in[j]; 5936 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5937 B = aij->B; 5938 b = (Mat_SeqAIJ*)B->data; 5939 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5940 rp2 = bj + bi[row]; 5941 ap2 = ba + bi[row]; 5942 rmax2 = bimax[row]; 5943 nrow2 = bilen[row]; 5944 low2 = 0; 5945 high2 = nrow2; 5946 bm = aij->B->rmap->n; 5947 ba = b->a; 5948 } 5949 } else col = in[j]; 5950 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5951 } 5952 } 5953 } else if (!aij->donotstash) { 5954 if (roworiented) { 5955 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5956 } else { 5957 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5958 } 5959 } 5960 } 5961 } 5962 PetscFunctionReturnVoid(); 5963 } 5964 5965