1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 for (i=1; i<mat->rmap->n; i++) { 335 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2530 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2531 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2532 for (i=0; i<redund->nrecvs; i++) { 2533 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2534 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2535 } 2536 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2537 2538 if (redund->psubcomm) { 2539 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2540 } 2541 2542 ierr = redund->Destroy(A);CHKERRQ(ierr); 2543 ierr = PetscFree(redund);CHKERRQ(ierr); 2544 } 2545 PetscFunctionReturn(0); 2546 } 2547 2548 #undef __FUNCT__ 2549 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_interlaced" 2550 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2551 { 2552 PetscMPIInt rank,size; 2553 MPI_Comm comm,subcomm=psubcomm->comm; 2554 PetscErrorCode ierr; 2555 PetscInt nsends=0,nrecvs=0,i,rownz_max=0; 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,M,N; 2565 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2566 MatScalar *aworkA,*aworkB; 2567 PetscScalar *vals; 2568 PetscMPIInt tag1,tag2,tag3,imdex; 2569 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2570 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2571 MPI_Status recv_status,*send_status; 2572 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2573 PetscInt **rbuf_j=NULL; 2574 PetscScalar **rbuf_a=NULL; 2575 Mat_Redundant *redund =NULL; 2576 PetscInt rstart_sub,rend_sub,mloc_sub; 2577 2578 PetscFunctionBegin; 2579 if (psubcomm->type != PETSC_SUBCOMM_INTERLACED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"Input psubcomm must be PETSC_SUBCOMM_INTERLACED type"); 2580 ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr); 2581 if (M != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for non-square matrix yet, rows %D columns %D",M,N); 2582 2583 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2584 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2585 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2586 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2587 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2588 2589 if (reuse == MAT_REUSE_MATRIX) { 2590 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2591 if (subsize == 1) { 2592 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2593 redund = c->redundant; 2594 } else { 2595 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2596 redund = c->redundant; 2597 } 2598 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2599 2600 nsends = redund->nsends; 2601 nrecvs = redund->nrecvs; 2602 send_rank = redund->send_rank; 2603 recv_rank = redund->recv_rank; 2604 sbuf_nz = redund->sbuf_nz; 2605 rbuf_nz = redund->rbuf_nz; 2606 sbuf_j = redund->sbuf_j; 2607 sbuf_a = redund->sbuf_a; 2608 rbuf_j = redund->rbuf_j; 2609 rbuf_a = redund->rbuf_a; 2610 } 2611 2612 if (reuse == MAT_INITIAL_MATRIX) { 2613 PetscInt nleftover,np_subcomm; 2614 2615 /* get local size of redundant matrix */ 2616 const PetscInt *range; 2617 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2618 rstart_sub = range[nsubcomm*subrank]; 2619 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2620 rend_sub = range[nsubcomm*(subrank+1)]; 2621 } else { 2622 rend_sub = mat->rmap->N; 2623 } 2624 mloc_sub = rend_sub - rstart_sub; 2625 2626 /* get the destination processors' id send_rank, nsends and nrecvs */ 2627 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2628 2629 np_subcomm = size/nsubcomm; 2630 nleftover = size - nsubcomm*np_subcomm; 2631 2632 nsends = 0; nrecvs = 0; 2633 for (i=0; i<size; i++) { 2634 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2635 send_rank[nsends] = i; nsends++; 2636 recv_rank[nrecvs++] = i; 2637 } 2638 } 2639 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2640 i = size-nleftover-1; 2641 j = 0; 2642 while (j < nsubcomm - nleftover) { 2643 send_rank[nsends++] = i; 2644 i--; j++; 2645 } 2646 } 2647 2648 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2649 for (i=0; i<nleftover; i++) { 2650 recv_rank[nrecvs++] = size-nleftover+i; 2651 } 2652 } 2653 2654 /* allocate sbuf_j, sbuf_a */ 2655 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2656 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2657 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2658 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2659 2660 /* copy mat's local entries into the buffers */ 2661 if (reuse == MAT_INITIAL_MATRIX) { 2662 rownz_max = 0; 2663 rptr = sbuf_j; 2664 cols = sbuf_j + rend-rstart + 1; 2665 vals = sbuf_a; 2666 rptr[0] = 0; 2667 for (i=0; i<rend-rstart; i++) { 2668 row = i + rstart; 2669 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2670 ncols = nzA + nzB; 2671 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2672 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2673 /* load the column indices for this row into cols */ 2674 lwrite = 0; 2675 for (l=0; l<nzB; l++) { 2676 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2677 vals[lwrite] = aworkB[l]; 2678 cols[lwrite++] = ctmp; 2679 } 2680 } 2681 for (l=0; l<nzA; l++) { 2682 vals[lwrite] = aworkA[l]; 2683 cols[lwrite++] = cstart + cworkA[l]; 2684 } 2685 for (l=0; l<nzB; l++) { 2686 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2687 vals[lwrite] = aworkB[l]; 2688 cols[lwrite++] = ctmp; 2689 } 2690 } 2691 vals += ncols; 2692 cols += ncols; 2693 rptr[i+1] = rptr[i] + ncols; 2694 if (rownz_max < ncols) rownz_max = ncols; 2695 } 2696 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); 2697 } else { /* only copy matrix values into sbuf_a */ 2698 rptr = sbuf_j; 2699 vals = sbuf_a; 2700 rptr[0] = 0; 2701 for (i=0; i<rend-rstart; i++) { 2702 row = i + rstart; 2703 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2704 ncols = nzA + nzB; 2705 cworkB = b->j + b->i[i]; 2706 aworkA = a->a + a->i[i]; 2707 aworkB = b->a + b->i[i]; 2708 lwrite = 0; 2709 for (l=0; l<nzB; l++) { 2710 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2711 } 2712 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2713 for (l=0; l<nzB; l++) { 2714 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2715 } 2716 vals += ncols; 2717 rptr[i+1] = rptr[i] + ncols; 2718 } 2719 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2720 2721 /* send nzlocal to others, and recv other's nzlocal */ 2722 /*--------------------------------------------------*/ 2723 if (reuse == MAT_INITIAL_MATRIX) { 2724 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2725 2726 s_waits2 = s_waits3 + nsends; 2727 s_waits1 = s_waits2 + nsends; 2728 r_waits1 = s_waits1 + nsends; 2729 r_waits2 = r_waits1 + nrecvs; 2730 r_waits3 = r_waits2 + nrecvs; 2731 } else { 2732 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2733 2734 r_waits3 = s_waits3 + nsends; 2735 } 2736 2737 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2738 if (reuse == MAT_INITIAL_MATRIX) { 2739 /* get new tags to keep the communication clean */ 2740 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2741 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2742 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2743 2744 /* post receives of other's nzlocal */ 2745 for (i=0; i<nrecvs; i++) { 2746 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2747 } 2748 /* send nzlocal to others */ 2749 for (i=0; i<nsends; i++) { 2750 sbuf_nz[i] = nzlocal; 2751 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2752 } 2753 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2754 count = nrecvs; 2755 while (count) { 2756 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2757 2758 recv_rank[imdex] = recv_status.MPI_SOURCE; 2759 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2760 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2761 2762 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2763 2764 rbuf_nz[imdex] += i + 2; 2765 2766 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2767 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2768 count--; 2769 } 2770 /* wait on sends of nzlocal */ 2771 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2772 /* send mat->i,j to others, and recv from other's */ 2773 /*------------------------------------------------*/ 2774 for (i=0; i<nsends; i++) { 2775 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2776 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2777 } 2778 /* wait on receives of mat->i,j */ 2779 /*------------------------------*/ 2780 count = nrecvs; 2781 while (count) { 2782 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2783 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); 2784 count--; 2785 } 2786 /* wait on sends of mat->i,j */ 2787 /*---------------------------*/ 2788 if (nsends) { 2789 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2790 } 2791 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2792 2793 /* post receives, send and receive mat->a */ 2794 /*----------------------------------------*/ 2795 for (imdex=0; imdex<nrecvs; imdex++) { 2796 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2797 } 2798 for (i=0; i<nsends; i++) { 2799 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2800 } 2801 count = nrecvs; 2802 while (count) { 2803 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2804 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); 2805 count--; 2806 } 2807 if (nsends) { 2808 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2809 } 2810 2811 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2812 2813 /* create redundant matrix */ 2814 /*-------------------------*/ 2815 if (reuse == MAT_INITIAL_MATRIX) { 2816 /* compute rownz_max for preallocation */ 2817 for (imdex=0; imdex<nrecvs; imdex++) { 2818 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2819 rptr = rbuf_j[imdex]; 2820 for (i=0; i<j; i++) { 2821 ncols = rptr[i+1] - rptr[i]; 2822 if (rownz_max < ncols) rownz_max = ncols; 2823 } 2824 } 2825 2826 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2827 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2828 /* ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DETERMINE,mat->cmap->N);CHKERRQ(ierr); -- give incorrect local column! */ 2829 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2830 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2831 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2832 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2833 } else { 2834 C = *matredundant; 2835 } 2836 2837 /* insert local matrix entries */ 2838 rptr = sbuf_j; 2839 cols = sbuf_j + rend-rstart + 1; 2840 vals = sbuf_a; 2841 for (i=0; i<rend-rstart; i++) { 2842 row = i + rstart; 2843 ncols = rptr[i+1] - rptr[i]; 2844 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2845 vals += ncols; 2846 cols += ncols; 2847 } 2848 /* insert received matrix entries */ 2849 for (imdex=0; imdex<nrecvs; imdex++) { 2850 rstart = rowrange[recv_rank[imdex]]; 2851 rend = rowrange[recv_rank[imdex]+1]; 2852 rptr = rbuf_j[imdex]; 2853 cols = rbuf_j[imdex] + rend-rstart + 1; 2854 vals = rbuf_a[imdex]; 2855 for (i=0; i<rend-rstart; i++) { 2856 row = i + rstart; 2857 ncols = rptr[i+1] - rptr[i]; 2858 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2859 vals += ncols; 2860 cols += ncols; 2861 } 2862 } 2863 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2864 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2865 2866 if (reuse == MAT_INITIAL_MATRIX) { 2867 *matredundant = C; 2868 2869 /* create a supporting struct and attach it to C for reuse */ 2870 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2871 if (subsize == 1) { 2872 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2873 c->redundant = redund; 2874 } else { 2875 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2876 c->redundant = redund; 2877 } 2878 2879 redund->nzlocal = nzlocal; 2880 redund->nsends = nsends; 2881 redund->nrecvs = nrecvs; 2882 redund->send_rank = send_rank; 2883 redund->recv_rank = recv_rank; 2884 redund->sbuf_nz = sbuf_nz; 2885 redund->rbuf_nz = rbuf_nz; 2886 redund->sbuf_j = sbuf_j; 2887 redund->sbuf_a = sbuf_a; 2888 redund->rbuf_j = rbuf_j; 2889 redund->rbuf_a = rbuf_a; 2890 redund->psubcomm = NULL; 2891 2892 redund->Destroy = C->ops->destroy; 2893 C->ops->destroy = MatDestroy_MatRedundant; 2894 } 2895 PetscFunctionReturn(0); 2896 } 2897 2898 #undef __FUNCT__ 2899 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2900 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2901 { 2902 PetscErrorCode ierr; 2903 2904 PetscFunctionBegin; 2905 /* Only MatGetRedundantMatrix_MPIAIJ_interlaced() is written now */ 2906 if (!subcomm || subcomm == PETSC_COMM_SELF) { /* create psubcomm */ 2907 MPI_Comm comm; 2908 PetscSubcomm psubcomm; 2909 PetscMPIInt size,subsize; 2910 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2911 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2912 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2913 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2914 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_INTERLACED);CHKERRQ(ierr); 2915 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2916 2917 /* free psubcomm in MatDestroy_MatRedundant() */ 2918 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2919 Mat C = *matredundant; 2920 if (subsize == 1) { 2921 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2922 c->redundant->psubcomm = psubcomm; 2923 } else { 2924 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2925 c->redundant->psubcomm = psubcomm ; 2926 } 2927 } else { 2928 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet"); 2929 } 2930 PetscFunctionReturn(0); 2931 } 2932 2933 #undef __FUNCT__ 2934 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2935 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2936 { 2937 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2938 PetscErrorCode ierr; 2939 PetscInt i,*idxb = 0; 2940 PetscScalar *va,*vb; 2941 Vec vtmp; 2942 2943 PetscFunctionBegin; 2944 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2945 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2946 if (idx) { 2947 for (i=0; i<A->rmap->n; i++) { 2948 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2949 } 2950 } 2951 2952 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2953 if (idx) { 2954 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2955 } 2956 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2957 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2958 2959 for (i=0; i<A->rmap->n; i++) { 2960 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 2961 va[i] = vb[i]; 2962 if (idx) idx[i] = a->garray[idxb[i]]; 2963 } 2964 } 2965 2966 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2967 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 2968 ierr = PetscFree(idxb);CHKERRQ(ierr); 2969 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 2970 PetscFunctionReturn(0); 2971 } 2972 2973 #undef __FUNCT__ 2974 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 2975 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2976 { 2977 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2978 PetscErrorCode ierr; 2979 PetscInt i,*idxb = 0; 2980 PetscScalar *va,*vb; 2981 Vec vtmp; 2982 2983 PetscFunctionBegin; 2984 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 2985 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2986 if (idx) { 2987 for (i=0; i<A->cmap->n; i++) { 2988 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 2989 } 2990 } 2991 2992 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 2993 if (idx) { 2994 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 2995 } 2996 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 2997 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 2998 2999 for (i=0; i<A->rmap->n; i++) { 3000 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3001 va[i] = vb[i]; 3002 if (idx) idx[i] = a->garray[idxb[i]]; 3003 } 3004 } 3005 3006 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3007 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3008 ierr = PetscFree(idxb);CHKERRQ(ierr); 3009 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3010 PetscFunctionReturn(0); 3011 } 3012 3013 #undef __FUNCT__ 3014 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3015 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3016 { 3017 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3018 PetscInt n = A->rmap->n; 3019 PetscInt cstart = A->cmap->rstart; 3020 PetscInt *cmap = mat->garray; 3021 PetscInt *diagIdx, *offdiagIdx; 3022 Vec diagV, offdiagV; 3023 PetscScalar *a, *diagA, *offdiagA; 3024 PetscInt r; 3025 PetscErrorCode ierr; 3026 3027 PetscFunctionBegin; 3028 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3029 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3030 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3031 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3032 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3033 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3034 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3035 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3036 for (r = 0; r < n; ++r) { 3037 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3038 a[r] = diagA[r]; 3039 idx[r] = cstart + diagIdx[r]; 3040 } else { 3041 a[r] = offdiagA[r]; 3042 idx[r] = cmap[offdiagIdx[r]]; 3043 } 3044 } 3045 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3046 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3047 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3048 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3049 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3050 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3051 PetscFunctionReturn(0); 3052 } 3053 3054 #undef __FUNCT__ 3055 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3056 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3057 { 3058 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3059 PetscInt n = A->rmap->n; 3060 PetscInt cstart = A->cmap->rstart; 3061 PetscInt *cmap = mat->garray; 3062 PetscInt *diagIdx, *offdiagIdx; 3063 Vec diagV, offdiagV; 3064 PetscScalar *a, *diagA, *offdiagA; 3065 PetscInt r; 3066 PetscErrorCode ierr; 3067 3068 PetscFunctionBegin; 3069 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3070 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3071 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3072 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3073 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3074 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3075 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3076 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3077 for (r = 0; r < n; ++r) { 3078 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3079 a[r] = diagA[r]; 3080 idx[r] = cstart + diagIdx[r]; 3081 } else { 3082 a[r] = offdiagA[r]; 3083 idx[r] = cmap[offdiagIdx[r]]; 3084 } 3085 } 3086 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3087 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3088 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3089 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3090 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3091 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3092 PetscFunctionReturn(0); 3093 } 3094 3095 #undef __FUNCT__ 3096 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3097 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3098 { 3099 PetscErrorCode ierr; 3100 Mat *dummy; 3101 3102 PetscFunctionBegin; 3103 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3104 *newmat = *dummy; 3105 ierr = PetscFree(dummy);CHKERRQ(ierr); 3106 PetscFunctionReturn(0); 3107 } 3108 3109 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3110 3111 #undef __FUNCT__ 3112 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3113 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3114 { 3115 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3116 PetscErrorCode ierr; 3117 3118 PetscFunctionBegin; 3119 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3120 PetscFunctionReturn(0); 3121 } 3122 3123 #undef __FUNCT__ 3124 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3125 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3126 { 3127 PetscErrorCode ierr; 3128 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3129 3130 PetscFunctionBegin; 3131 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3132 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3133 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3134 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3135 PetscFunctionReturn(0); 3136 } 3137 3138 /* -------------------------------------------------------------------*/ 3139 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3140 MatGetRow_MPIAIJ, 3141 MatRestoreRow_MPIAIJ, 3142 MatMult_MPIAIJ, 3143 /* 4*/ MatMultAdd_MPIAIJ, 3144 MatMultTranspose_MPIAIJ, 3145 MatMultTransposeAdd_MPIAIJ, 3146 #if defined(PETSC_HAVE_PBGL) 3147 MatSolve_MPIAIJ, 3148 #else 3149 0, 3150 #endif 3151 0, 3152 0, 3153 /*10*/ 0, 3154 0, 3155 0, 3156 MatSOR_MPIAIJ, 3157 MatTranspose_MPIAIJ, 3158 /*15*/ MatGetInfo_MPIAIJ, 3159 MatEqual_MPIAIJ, 3160 MatGetDiagonal_MPIAIJ, 3161 MatDiagonalScale_MPIAIJ, 3162 MatNorm_MPIAIJ, 3163 /*20*/ MatAssemblyBegin_MPIAIJ, 3164 MatAssemblyEnd_MPIAIJ, 3165 MatSetOption_MPIAIJ, 3166 MatZeroEntries_MPIAIJ, 3167 /*24*/ MatZeroRows_MPIAIJ, 3168 0, 3169 #if defined(PETSC_HAVE_PBGL) 3170 0, 3171 #else 3172 0, 3173 #endif 3174 0, 3175 0, 3176 /*29*/ MatSetUp_MPIAIJ, 3177 #if defined(PETSC_HAVE_PBGL) 3178 0, 3179 #else 3180 0, 3181 #endif 3182 0, 3183 0, 3184 0, 3185 /*34*/ MatDuplicate_MPIAIJ, 3186 0, 3187 0, 3188 0, 3189 0, 3190 /*39*/ MatAXPY_MPIAIJ, 3191 MatGetSubMatrices_MPIAIJ, 3192 MatIncreaseOverlap_MPIAIJ, 3193 MatGetValues_MPIAIJ, 3194 MatCopy_MPIAIJ, 3195 /*44*/ MatGetRowMax_MPIAIJ, 3196 MatScale_MPIAIJ, 3197 0, 3198 0, 3199 MatZeroRowsColumns_MPIAIJ, 3200 /*49*/ MatSetRandom_MPIAIJ, 3201 0, 3202 0, 3203 0, 3204 0, 3205 /*54*/ MatFDColoringCreate_MPIAIJ, 3206 0, 3207 MatSetUnfactored_MPIAIJ, 3208 MatPermute_MPIAIJ, 3209 0, 3210 /*59*/ MatGetSubMatrix_MPIAIJ, 3211 MatDestroy_MPIAIJ, 3212 MatView_MPIAIJ, 3213 0, 3214 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3215 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3216 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3217 0, 3218 0, 3219 0, 3220 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3221 MatGetRowMinAbs_MPIAIJ, 3222 0, 3223 MatSetColoring_MPIAIJ, 3224 0, 3225 MatSetValuesAdifor_MPIAIJ, 3226 /*75*/ MatFDColoringApply_AIJ, 3227 0, 3228 0, 3229 0, 3230 MatFindZeroDiagonals_MPIAIJ, 3231 /*80*/ 0, 3232 0, 3233 0, 3234 /*83*/ MatLoad_MPIAIJ, 3235 0, 3236 0, 3237 0, 3238 0, 3239 0, 3240 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3241 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3242 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3243 MatPtAP_MPIAIJ_MPIAIJ, 3244 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3245 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3246 0, 3247 0, 3248 0, 3249 0, 3250 /*99*/ 0, 3251 0, 3252 0, 3253 MatConjugate_MPIAIJ, 3254 0, 3255 /*104*/MatSetValuesRow_MPIAIJ, 3256 MatRealPart_MPIAIJ, 3257 MatImaginaryPart_MPIAIJ, 3258 0, 3259 0, 3260 /*109*/0, 3261 MatGetRedundantMatrix_MPIAIJ, 3262 MatGetRowMin_MPIAIJ, 3263 0, 3264 0, 3265 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3266 0, 3267 0, 3268 0, 3269 0, 3270 /*119*/0, 3271 0, 3272 0, 3273 0, 3274 MatGetMultiProcBlock_MPIAIJ, 3275 /*124*/MatFindNonzeroRows_MPIAIJ, 3276 MatGetColumnNorms_MPIAIJ, 3277 MatInvertBlockDiagonal_MPIAIJ, 3278 0, 3279 MatGetSubMatricesParallel_MPIAIJ, 3280 /*129*/0, 3281 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3282 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3283 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3284 0, 3285 /*134*/0, 3286 0, 3287 0, 3288 0, 3289 0, 3290 /*139*/0, 3291 0 3292 }; 3293 3294 /* ----------------------------------------------------------------------------------------*/ 3295 3296 #undef __FUNCT__ 3297 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3298 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3299 { 3300 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3301 PetscErrorCode ierr; 3302 3303 PetscFunctionBegin; 3304 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3305 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3306 PetscFunctionReturn(0); 3307 } 3308 3309 #undef __FUNCT__ 3310 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3311 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3312 { 3313 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3314 PetscErrorCode ierr; 3315 3316 PetscFunctionBegin; 3317 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3318 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3319 PetscFunctionReturn(0); 3320 } 3321 3322 #undef __FUNCT__ 3323 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3324 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3325 { 3326 Mat_MPIAIJ *b; 3327 PetscErrorCode ierr; 3328 3329 PetscFunctionBegin; 3330 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3331 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3332 b = (Mat_MPIAIJ*)B->data; 3333 3334 if (!B->preallocated) { 3335 /* Explicitly create 2 MATSEQAIJ matrices. */ 3336 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3337 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3338 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3339 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3340 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3341 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3342 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3343 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3344 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3345 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3346 } 3347 3348 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3349 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3350 B->preallocated = PETSC_TRUE; 3351 PetscFunctionReturn(0); 3352 } 3353 3354 #undef __FUNCT__ 3355 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3356 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3357 { 3358 Mat mat; 3359 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3360 PetscErrorCode ierr; 3361 3362 PetscFunctionBegin; 3363 *newmat = 0; 3364 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3365 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3366 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3367 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3368 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3369 a = (Mat_MPIAIJ*)mat->data; 3370 3371 mat->factortype = matin->factortype; 3372 mat->rmap->bs = matin->rmap->bs; 3373 mat->cmap->bs = matin->cmap->bs; 3374 mat->assembled = PETSC_TRUE; 3375 mat->insertmode = NOT_SET_VALUES; 3376 mat->preallocated = PETSC_TRUE; 3377 3378 a->size = oldmat->size; 3379 a->rank = oldmat->rank; 3380 a->donotstash = oldmat->donotstash; 3381 a->roworiented = oldmat->roworiented; 3382 a->rowindices = 0; 3383 a->rowvalues = 0; 3384 a->getrowactive = PETSC_FALSE; 3385 3386 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3387 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3388 3389 if (oldmat->colmap) { 3390 #if defined(PETSC_USE_CTABLE) 3391 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3392 #else 3393 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3394 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3395 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3396 #endif 3397 } else a->colmap = 0; 3398 if (oldmat->garray) { 3399 PetscInt len; 3400 len = oldmat->B->cmap->n; 3401 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3402 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3403 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3404 } else a->garray = 0; 3405 3406 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3407 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3408 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3409 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3410 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3411 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3412 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3413 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3414 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3415 *newmat = mat; 3416 PetscFunctionReturn(0); 3417 } 3418 3419 3420 3421 #undef __FUNCT__ 3422 #define __FUNCT__ "MatLoad_MPIAIJ" 3423 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3424 { 3425 PetscScalar *vals,*svals; 3426 MPI_Comm comm; 3427 PetscErrorCode ierr; 3428 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3429 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3430 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3431 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3432 PetscInt cend,cstart,n,*rowners,sizesset=1; 3433 int fd; 3434 PetscInt bs = 1; 3435 3436 PetscFunctionBegin; 3437 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3438 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3439 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3440 if (!rank) { 3441 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3442 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3443 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3444 } 3445 3446 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3447 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3448 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3449 3450 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3451 3452 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3453 M = header[1]; N = header[2]; 3454 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3455 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3456 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3457 3458 /* If global sizes are set, check if they are consistent with that given in the file */ 3459 if (sizesset) { 3460 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3461 } 3462 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); 3463 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); 3464 3465 /* determine ownership of all (block) rows */ 3466 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3467 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3468 else m = newMat->rmap->n; /* Set by user */ 3469 3470 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3471 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3472 3473 /* First process needs enough room for process with most rows */ 3474 if (!rank) { 3475 mmax = rowners[1]; 3476 for (i=2; i<=size; i++) { 3477 mmax = PetscMax(mmax, rowners[i]); 3478 } 3479 } else mmax = -1; /* unused, but compilers complain */ 3480 3481 rowners[0] = 0; 3482 for (i=2; i<=size; i++) { 3483 rowners[i] += rowners[i-1]; 3484 } 3485 rstart = rowners[rank]; 3486 rend = rowners[rank+1]; 3487 3488 /* distribute row lengths to all processors */ 3489 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3490 if (!rank) { 3491 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3492 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3493 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3494 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3495 for (j=0; j<m; j++) { 3496 procsnz[0] += ourlens[j]; 3497 } 3498 for (i=1; i<size; i++) { 3499 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3500 /* calculate the number of nonzeros on each processor */ 3501 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3502 procsnz[i] += rowlengths[j]; 3503 } 3504 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3505 } 3506 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3507 } else { 3508 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3509 } 3510 3511 if (!rank) { 3512 /* determine max buffer needed and allocate it */ 3513 maxnz = 0; 3514 for (i=0; i<size; i++) { 3515 maxnz = PetscMax(maxnz,procsnz[i]); 3516 } 3517 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3518 3519 /* read in my part of the matrix column indices */ 3520 nz = procsnz[0]; 3521 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3522 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3523 3524 /* read in every one elses and ship off */ 3525 for (i=1; i<size; i++) { 3526 nz = procsnz[i]; 3527 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3528 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3529 } 3530 ierr = PetscFree(cols);CHKERRQ(ierr); 3531 } else { 3532 /* determine buffer space needed for message */ 3533 nz = 0; 3534 for (i=0; i<m; i++) { 3535 nz += ourlens[i]; 3536 } 3537 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3538 3539 /* receive message of column indices*/ 3540 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3541 } 3542 3543 /* determine column ownership if matrix is not square */ 3544 if (N != M) { 3545 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3546 else n = newMat->cmap->n; 3547 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3548 cstart = cend - n; 3549 } else { 3550 cstart = rstart; 3551 cend = rend; 3552 n = cend - cstart; 3553 } 3554 3555 /* loop over local rows, determining number of off diagonal entries */ 3556 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3557 jj = 0; 3558 for (i=0; i<m; i++) { 3559 for (j=0; j<ourlens[i]; j++) { 3560 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3561 jj++; 3562 } 3563 } 3564 3565 for (i=0; i<m; i++) { 3566 ourlens[i] -= offlens[i]; 3567 } 3568 if (!sizesset) { 3569 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3570 } 3571 3572 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3573 3574 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3575 3576 for (i=0; i<m; i++) { 3577 ourlens[i] += offlens[i]; 3578 } 3579 3580 if (!rank) { 3581 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3582 3583 /* read in my part of the matrix numerical values */ 3584 nz = procsnz[0]; 3585 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3586 3587 /* insert into matrix */ 3588 jj = rstart; 3589 smycols = mycols; 3590 svals = vals; 3591 for (i=0; i<m; i++) { 3592 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3593 smycols += ourlens[i]; 3594 svals += ourlens[i]; 3595 jj++; 3596 } 3597 3598 /* read in other processors and ship out */ 3599 for (i=1; i<size; i++) { 3600 nz = procsnz[i]; 3601 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3602 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3603 } 3604 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3605 } else { 3606 /* receive numeric values */ 3607 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3608 3609 /* receive message of values*/ 3610 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3611 3612 /* insert into matrix */ 3613 jj = rstart; 3614 smycols = mycols; 3615 svals = vals; 3616 for (i=0; i<m; i++) { 3617 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3618 smycols += ourlens[i]; 3619 svals += ourlens[i]; 3620 jj++; 3621 } 3622 } 3623 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3624 ierr = PetscFree(vals);CHKERRQ(ierr); 3625 ierr = PetscFree(mycols);CHKERRQ(ierr); 3626 ierr = PetscFree(rowners);CHKERRQ(ierr); 3627 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3628 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3629 PetscFunctionReturn(0); 3630 } 3631 3632 #undef __FUNCT__ 3633 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3634 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3635 { 3636 PetscErrorCode ierr; 3637 IS iscol_local; 3638 PetscInt csize; 3639 3640 PetscFunctionBegin; 3641 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3642 if (call == MAT_REUSE_MATRIX) { 3643 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3644 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3645 } else { 3646 PetscInt cbs; 3647 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3648 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3649 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3650 } 3651 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3652 if (call == MAT_INITIAL_MATRIX) { 3653 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3654 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3655 } 3656 PetscFunctionReturn(0); 3657 } 3658 3659 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3660 #undef __FUNCT__ 3661 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3662 /* 3663 Not great since it makes two copies of the submatrix, first an SeqAIJ 3664 in local and then by concatenating the local matrices the end result. 3665 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3666 3667 Note: This requires a sequential iscol with all indices. 3668 */ 3669 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3670 { 3671 PetscErrorCode ierr; 3672 PetscMPIInt rank,size; 3673 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3674 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3675 PetscBool allcolumns, colflag; 3676 Mat M,Mreuse; 3677 MatScalar *vwork,*aa; 3678 MPI_Comm comm; 3679 Mat_SeqAIJ *aij; 3680 3681 PetscFunctionBegin; 3682 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3683 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3684 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3685 3686 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3687 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3688 if (colflag && ncol == mat->cmap->N) { 3689 allcolumns = PETSC_TRUE; 3690 } else { 3691 allcolumns = PETSC_FALSE; 3692 } 3693 if (call == MAT_REUSE_MATRIX) { 3694 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3695 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3696 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3697 } else { 3698 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3699 } 3700 3701 /* 3702 m - number of local rows 3703 n - number of columns (same on all processors) 3704 rstart - first row in new global matrix generated 3705 */ 3706 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3707 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3708 if (call == MAT_INITIAL_MATRIX) { 3709 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3710 ii = aij->i; 3711 jj = aij->j; 3712 3713 /* 3714 Determine the number of non-zeros in the diagonal and off-diagonal 3715 portions of the matrix in order to do correct preallocation 3716 */ 3717 3718 /* first get start and end of "diagonal" columns */ 3719 if (csize == PETSC_DECIDE) { 3720 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3721 if (mglobal == n) { /* square matrix */ 3722 nlocal = m; 3723 } else { 3724 nlocal = n/size + ((n % size) > rank); 3725 } 3726 } else { 3727 nlocal = csize; 3728 } 3729 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3730 rstart = rend - nlocal; 3731 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); 3732 3733 /* next, compute all the lengths */ 3734 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3735 olens = dlens + m; 3736 for (i=0; i<m; i++) { 3737 jend = ii[i+1] - ii[i]; 3738 olen = 0; 3739 dlen = 0; 3740 for (j=0; j<jend; j++) { 3741 if (*jj < rstart || *jj >= rend) olen++; 3742 else dlen++; 3743 jj++; 3744 } 3745 olens[i] = olen; 3746 dlens[i] = dlen; 3747 } 3748 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3749 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3750 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3751 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3752 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3753 ierr = PetscFree(dlens);CHKERRQ(ierr); 3754 } else { 3755 PetscInt ml,nl; 3756 3757 M = *newmat; 3758 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3759 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3760 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3761 /* 3762 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3763 rather than the slower MatSetValues(). 3764 */ 3765 M->was_assembled = PETSC_TRUE; 3766 M->assembled = PETSC_FALSE; 3767 } 3768 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3769 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3770 ii = aij->i; 3771 jj = aij->j; 3772 aa = aij->a; 3773 for (i=0; i<m; i++) { 3774 row = rstart + i; 3775 nz = ii[i+1] - ii[i]; 3776 cwork = jj; jj += nz; 3777 vwork = aa; aa += nz; 3778 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3779 } 3780 3781 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3782 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3783 *newmat = M; 3784 3785 /* save submatrix used in processor for next request */ 3786 if (call == MAT_INITIAL_MATRIX) { 3787 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3788 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3789 } 3790 PetscFunctionReturn(0); 3791 } 3792 3793 #undef __FUNCT__ 3794 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3795 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3796 { 3797 PetscInt m,cstart, cend,j,nnz,i,d; 3798 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3799 const PetscInt *JJ; 3800 PetscScalar *values; 3801 PetscErrorCode ierr; 3802 3803 PetscFunctionBegin; 3804 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3805 3806 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3807 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3808 m = B->rmap->n; 3809 cstart = B->cmap->rstart; 3810 cend = B->cmap->rend; 3811 rstart = B->rmap->rstart; 3812 3813 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3814 3815 #if defined(PETSC_USE_DEBUGGING) 3816 for (i=0; i<m; i++) { 3817 nnz = Ii[i+1]- Ii[i]; 3818 JJ = J + Ii[i]; 3819 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3820 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3821 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); 3822 } 3823 #endif 3824 3825 for (i=0; i<m; i++) { 3826 nnz = Ii[i+1]- Ii[i]; 3827 JJ = J + Ii[i]; 3828 nnz_max = PetscMax(nnz_max,nnz); 3829 d = 0; 3830 for (j=0; j<nnz; j++) { 3831 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3832 } 3833 d_nnz[i] = d; 3834 o_nnz[i] = nnz - d; 3835 } 3836 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3837 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3838 3839 if (v) values = (PetscScalar*)v; 3840 else { 3841 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3842 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3843 } 3844 3845 for (i=0; i<m; i++) { 3846 ii = i + rstart; 3847 nnz = Ii[i+1]- Ii[i]; 3848 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3849 } 3850 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3851 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3852 3853 if (!v) { 3854 ierr = PetscFree(values);CHKERRQ(ierr); 3855 } 3856 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3857 PetscFunctionReturn(0); 3858 } 3859 3860 #undef __FUNCT__ 3861 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3862 /*@ 3863 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3864 (the default parallel PETSc format). 3865 3866 Collective on MPI_Comm 3867 3868 Input Parameters: 3869 + B - the matrix 3870 . i - the indices into j for the start of each local row (starts with zero) 3871 . j - the column indices for each local row (starts with zero) 3872 - v - optional values in the matrix 3873 3874 Level: developer 3875 3876 Notes: 3877 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3878 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3879 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3880 3881 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3882 3883 The format which is used for the sparse matrix input, is equivalent to a 3884 row-major ordering.. i.e for the following matrix, the input data expected is 3885 as shown: 3886 3887 1 0 0 3888 2 0 3 P0 3889 ------- 3890 4 5 6 P1 3891 3892 Process0 [P0]: rows_owned=[0,1] 3893 i = {0,1,3} [size = nrow+1 = 2+1] 3894 j = {0,0,2} [size = nz = 6] 3895 v = {1,2,3} [size = nz = 6] 3896 3897 Process1 [P1]: rows_owned=[2] 3898 i = {0,3} [size = nrow+1 = 1+1] 3899 j = {0,1,2} [size = nz = 6] 3900 v = {4,5,6} [size = nz = 6] 3901 3902 .keywords: matrix, aij, compressed row, sparse, parallel 3903 3904 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3905 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3906 @*/ 3907 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3908 { 3909 PetscErrorCode ierr; 3910 3911 PetscFunctionBegin; 3912 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3913 PetscFunctionReturn(0); 3914 } 3915 3916 #undef __FUNCT__ 3917 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3918 /*@C 3919 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3920 (the default parallel PETSc format). For good matrix assembly performance 3921 the user should preallocate the matrix storage by setting the parameters 3922 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3923 performance can be increased by more than a factor of 50. 3924 3925 Collective on MPI_Comm 3926 3927 Input Parameters: 3928 + A - the matrix 3929 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3930 (same value is used for all local rows) 3931 . d_nnz - array containing the number of nonzeros in the various rows of the 3932 DIAGONAL portion of the local submatrix (possibly different for each row) 3933 or NULL, if d_nz is used to specify the nonzero structure. 3934 The size of this array is equal to the number of local rows, i.e 'm'. 3935 For matrices that will be factored, you must leave room for (and set) 3936 the diagonal entry even if it is zero. 3937 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3938 submatrix (same value is used for all local rows). 3939 - o_nnz - array containing the number of nonzeros in the various rows of the 3940 OFF-DIAGONAL portion of the local submatrix (possibly different for 3941 each row) or NULL, if o_nz is used to specify the nonzero 3942 structure. The size of this array is equal to the number 3943 of local rows, i.e 'm'. 3944 3945 If the *_nnz parameter is given then the *_nz parameter is ignored 3946 3947 The AIJ format (also called the Yale sparse matrix format or 3948 compressed row storage (CSR)), is fully compatible with standard Fortran 77 3949 storage. The stored row and column indices begin with zero. 3950 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 3951 3952 The parallel matrix is partitioned such that the first m0 rows belong to 3953 process 0, the next m1 rows belong to process 1, the next m2 rows belong 3954 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 3955 3956 The DIAGONAL portion of the local submatrix of a processor can be defined 3957 as the submatrix which is obtained by extraction the part corresponding to 3958 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 3959 first row that belongs to the processor, r2 is the last row belonging to 3960 the this processor, and c1-c2 is range of indices of the local part of a 3961 vector suitable for applying the matrix to. This is an mxn matrix. In the 3962 common case of a square matrix, the row and column ranges are the same and 3963 the DIAGONAL part is also square. The remaining portion of the local 3964 submatrix (mxN) constitute the OFF-DIAGONAL portion. 3965 3966 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 3967 3968 You can call MatGetInfo() to get information on how effective the preallocation was; 3969 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3970 You can also run with the option -info and look for messages with the string 3971 malloc in them to see if additional memory allocation was needed. 3972 3973 Example usage: 3974 3975 Consider the following 8x8 matrix with 34 non-zero values, that is 3976 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 3977 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 3978 as follows: 3979 3980 .vb 3981 1 2 0 | 0 3 0 | 0 4 3982 Proc0 0 5 6 | 7 0 0 | 8 0 3983 9 0 10 | 11 0 0 | 12 0 3984 ------------------------------------- 3985 13 0 14 | 15 16 17 | 0 0 3986 Proc1 0 18 0 | 19 20 21 | 0 0 3987 0 0 0 | 22 23 0 | 24 0 3988 ------------------------------------- 3989 Proc2 25 26 27 | 0 0 28 | 29 0 3990 30 0 0 | 31 32 33 | 0 34 3991 .ve 3992 3993 This can be represented as a collection of submatrices as: 3994 3995 .vb 3996 A B C 3997 D E F 3998 G H I 3999 .ve 4000 4001 Where the submatrices A,B,C are owned by proc0, D,E,F are 4002 owned by proc1, G,H,I are owned by proc2. 4003 4004 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4005 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4006 The 'M','N' parameters are 8,8, and have the same values on all procs. 4007 4008 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4009 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4010 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4011 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4012 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4013 matrix, ans [DF] as another SeqAIJ matrix. 4014 4015 When d_nz, o_nz parameters are specified, d_nz storage elements are 4016 allocated for every row of the local diagonal submatrix, and o_nz 4017 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4018 One way to choose d_nz and o_nz is to use the max nonzerors per local 4019 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4020 In this case, the values of d_nz,o_nz are: 4021 .vb 4022 proc0 : dnz = 2, o_nz = 2 4023 proc1 : dnz = 3, o_nz = 2 4024 proc2 : dnz = 1, o_nz = 4 4025 .ve 4026 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4027 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4028 for proc3. i.e we are using 12+15+10=37 storage locations to store 4029 34 values. 4030 4031 When d_nnz, o_nnz parameters are specified, the storage is specified 4032 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4033 In the above case the values for d_nnz,o_nnz are: 4034 .vb 4035 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4036 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4037 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4038 .ve 4039 Here the space allocated is sum of all the above values i.e 34, and 4040 hence pre-allocation is perfect. 4041 4042 Level: intermediate 4043 4044 .keywords: matrix, aij, compressed row, sparse, parallel 4045 4046 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4047 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4048 @*/ 4049 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4050 { 4051 PetscErrorCode ierr; 4052 4053 PetscFunctionBegin; 4054 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4055 PetscValidType(B,1); 4056 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4057 PetscFunctionReturn(0); 4058 } 4059 4060 #undef __FUNCT__ 4061 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4062 /*@ 4063 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4064 CSR format the local rows. 4065 4066 Collective on MPI_Comm 4067 4068 Input Parameters: 4069 + comm - MPI communicator 4070 . m - number of local rows (Cannot be PETSC_DECIDE) 4071 . n - This value should be the same as the local size used in creating the 4072 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4073 calculated if N is given) For square matrices n is almost always m. 4074 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4075 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4076 . i - row indices 4077 . j - column indices 4078 - a - matrix values 4079 4080 Output Parameter: 4081 . mat - the matrix 4082 4083 Level: intermediate 4084 4085 Notes: 4086 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4087 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4088 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4089 4090 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4091 4092 The format which is used for the sparse matrix input, is equivalent to a 4093 row-major ordering.. i.e for the following matrix, the input data expected is 4094 as shown: 4095 4096 1 0 0 4097 2 0 3 P0 4098 ------- 4099 4 5 6 P1 4100 4101 Process0 [P0]: rows_owned=[0,1] 4102 i = {0,1,3} [size = nrow+1 = 2+1] 4103 j = {0,0,2} [size = nz = 6] 4104 v = {1,2,3} [size = nz = 6] 4105 4106 Process1 [P1]: rows_owned=[2] 4107 i = {0,3} [size = nrow+1 = 1+1] 4108 j = {0,1,2} [size = nz = 6] 4109 v = {4,5,6} [size = nz = 6] 4110 4111 .keywords: matrix, aij, compressed row, sparse, parallel 4112 4113 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4114 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4115 @*/ 4116 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4117 { 4118 PetscErrorCode ierr; 4119 4120 PetscFunctionBegin; 4121 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4122 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4123 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4124 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4125 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4126 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4127 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4128 PetscFunctionReturn(0); 4129 } 4130 4131 #undef __FUNCT__ 4132 #define __FUNCT__ "MatCreateAIJ" 4133 /*@C 4134 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4135 (the default parallel PETSc format). For good matrix assembly performance 4136 the user should preallocate the matrix storage by setting the parameters 4137 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4138 performance can be increased by more than a factor of 50. 4139 4140 Collective on MPI_Comm 4141 4142 Input Parameters: 4143 + comm - MPI communicator 4144 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4145 This value should be the same as the local size used in creating the 4146 y vector for the matrix-vector product y = Ax. 4147 . n - This value should be the same as the local size used in creating the 4148 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4149 calculated if N is given) For square matrices n is almost always m. 4150 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4151 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4152 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4153 (same value is used for all local rows) 4154 . d_nnz - array containing the number of nonzeros in the various rows of the 4155 DIAGONAL portion of the local submatrix (possibly different for each row) 4156 or NULL, if d_nz is used to specify the nonzero structure. 4157 The size of this array is equal to the number of local rows, i.e 'm'. 4158 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4159 submatrix (same value is used for all local rows). 4160 - o_nnz - array containing the number of nonzeros in the various rows of the 4161 OFF-DIAGONAL portion of the local submatrix (possibly different for 4162 each row) or NULL, if o_nz is used to specify the nonzero 4163 structure. The size of this array is equal to the number 4164 of local rows, i.e 'm'. 4165 4166 Output Parameter: 4167 . A - the matrix 4168 4169 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4170 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4171 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4172 4173 Notes: 4174 If the *_nnz parameter is given then the *_nz parameter is ignored 4175 4176 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4177 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4178 storage requirements for this matrix. 4179 4180 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4181 processor than it must be used on all processors that share the object for 4182 that argument. 4183 4184 The user MUST specify either the local or global matrix dimensions 4185 (possibly both). 4186 4187 The parallel matrix is partitioned across processors such that the 4188 first m0 rows belong to process 0, the next m1 rows belong to 4189 process 1, the next m2 rows belong to process 2 etc.. where 4190 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4191 values corresponding to [m x N] submatrix. 4192 4193 The columns are logically partitioned with the n0 columns belonging 4194 to 0th partition, the next n1 columns belonging to the next 4195 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4196 4197 The DIAGONAL portion of the local submatrix on any given processor 4198 is the submatrix corresponding to the rows and columns m,n 4199 corresponding to the given processor. i.e diagonal matrix on 4200 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4201 etc. The remaining portion of the local submatrix [m x (N-n)] 4202 constitute the OFF-DIAGONAL portion. The example below better 4203 illustrates this concept. 4204 4205 For a square global matrix we define each processor's diagonal portion 4206 to be its local rows and the corresponding columns (a square submatrix); 4207 each processor's off-diagonal portion encompasses the remainder of the 4208 local matrix (a rectangular submatrix). 4209 4210 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4211 4212 When calling this routine with a single process communicator, a matrix of 4213 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4214 type of communicator, use the construction mechanism: 4215 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4216 4217 By default, this format uses inodes (identical nodes) when possible. 4218 We search for consecutive rows with the same nonzero structure, thereby 4219 reusing matrix information to achieve increased efficiency. 4220 4221 Options Database Keys: 4222 + -mat_no_inode - Do not use inodes 4223 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4224 - -mat_aij_oneindex - Internally use indexing starting at 1 4225 rather than 0. Note that when calling MatSetValues(), 4226 the user still MUST index entries starting at 0! 4227 4228 4229 Example usage: 4230 4231 Consider the following 8x8 matrix with 34 non-zero values, that is 4232 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4233 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4234 as follows: 4235 4236 .vb 4237 1 2 0 | 0 3 0 | 0 4 4238 Proc0 0 5 6 | 7 0 0 | 8 0 4239 9 0 10 | 11 0 0 | 12 0 4240 ------------------------------------- 4241 13 0 14 | 15 16 17 | 0 0 4242 Proc1 0 18 0 | 19 20 21 | 0 0 4243 0 0 0 | 22 23 0 | 24 0 4244 ------------------------------------- 4245 Proc2 25 26 27 | 0 0 28 | 29 0 4246 30 0 0 | 31 32 33 | 0 34 4247 .ve 4248 4249 This can be represented as a collection of submatrices as: 4250 4251 .vb 4252 A B C 4253 D E F 4254 G H I 4255 .ve 4256 4257 Where the submatrices A,B,C are owned by proc0, D,E,F are 4258 owned by proc1, G,H,I are owned by proc2. 4259 4260 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4261 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4262 The 'M','N' parameters are 8,8, and have the same values on all procs. 4263 4264 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4265 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4266 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4267 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4268 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4269 matrix, ans [DF] as another SeqAIJ matrix. 4270 4271 When d_nz, o_nz parameters are specified, d_nz storage elements are 4272 allocated for every row of the local diagonal submatrix, and o_nz 4273 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4274 One way to choose d_nz and o_nz is to use the max nonzerors per local 4275 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4276 In this case, the values of d_nz,o_nz are: 4277 .vb 4278 proc0 : dnz = 2, o_nz = 2 4279 proc1 : dnz = 3, o_nz = 2 4280 proc2 : dnz = 1, o_nz = 4 4281 .ve 4282 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4283 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4284 for proc3. i.e we are using 12+15+10=37 storage locations to store 4285 34 values. 4286 4287 When d_nnz, o_nnz parameters are specified, the storage is specified 4288 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4289 In the above case the values for d_nnz,o_nnz are: 4290 .vb 4291 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4292 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4293 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4294 .ve 4295 Here the space allocated is sum of all the above values i.e 34, and 4296 hence pre-allocation is perfect. 4297 4298 Level: intermediate 4299 4300 .keywords: matrix, aij, compressed row, sparse, parallel 4301 4302 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4303 MPIAIJ, MatCreateMPIAIJWithArrays() 4304 @*/ 4305 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) 4306 { 4307 PetscErrorCode ierr; 4308 PetscMPIInt size; 4309 4310 PetscFunctionBegin; 4311 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4312 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4313 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4314 if (size > 1) { 4315 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4316 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4317 } else { 4318 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4319 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4320 } 4321 PetscFunctionReturn(0); 4322 } 4323 4324 #undef __FUNCT__ 4325 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4326 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4327 { 4328 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4329 4330 PetscFunctionBegin; 4331 *Ad = a->A; 4332 *Ao = a->B; 4333 *colmap = a->garray; 4334 PetscFunctionReturn(0); 4335 } 4336 4337 #undef __FUNCT__ 4338 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4339 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4340 { 4341 PetscErrorCode ierr; 4342 PetscInt i; 4343 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4344 4345 PetscFunctionBegin; 4346 if (coloring->ctype == IS_COLORING_GLOBAL) { 4347 ISColoringValue *allcolors,*colors; 4348 ISColoring ocoloring; 4349 4350 /* set coloring for diagonal portion */ 4351 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4352 4353 /* set coloring for off-diagonal portion */ 4354 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4355 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4356 for (i=0; i<a->B->cmap->n; i++) { 4357 colors[i] = allcolors[a->garray[i]]; 4358 } 4359 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4360 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4361 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4362 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4363 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4364 ISColoringValue *colors; 4365 PetscInt *larray; 4366 ISColoring ocoloring; 4367 4368 /* set coloring for diagonal portion */ 4369 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4370 for (i=0; i<a->A->cmap->n; i++) { 4371 larray[i] = i + A->cmap->rstart; 4372 } 4373 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4374 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4375 for (i=0; i<a->A->cmap->n; i++) { 4376 colors[i] = coloring->colors[larray[i]]; 4377 } 4378 ierr = PetscFree(larray);CHKERRQ(ierr); 4379 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4380 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4381 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4382 4383 /* set coloring for off-diagonal portion */ 4384 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4385 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4386 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4387 for (i=0; i<a->B->cmap->n; i++) { 4388 colors[i] = coloring->colors[larray[i]]; 4389 } 4390 ierr = PetscFree(larray);CHKERRQ(ierr); 4391 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4392 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4393 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4394 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4395 PetscFunctionReturn(0); 4396 } 4397 4398 #undef __FUNCT__ 4399 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4400 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4401 { 4402 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4403 PetscErrorCode ierr; 4404 4405 PetscFunctionBegin; 4406 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4407 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4408 PetscFunctionReturn(0); 4409 } 4410 4411 #undef __FUNCT__ 4412 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4413 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4414 { 4415 PetscErrorCode ierr; 4416 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4417 PetscInt *indx; 4418 4419 PetscFunctionBegin; 4420 /* This routine will ONLY return MPIAIJ type matrix */ 4421 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4422 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4423 if (n == PETSC_DECIDE) { 4424 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4425 } 4426 /* Check sum(n) = N */ 4427 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4428 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4429 4430 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4431 rstart -= m; 4432 4433 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4434 for (i=0; i<m; i++) { 4435 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4436 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4437 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4438 } 4439 4440 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4441 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4442 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4443 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4444 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4445 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4446 PetscFunctionReturn(0); 4447 } 4448 4449 #undef __FUNCT__ 4450 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4451 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4452 { 4453 PetscErrorCode ierr; 4454 PetscInt m,N,i,rstart,nnz,Ii; 4455 PetscInt *indx; 4456 PetscScalar *values; 4457 4458 PetscFunctionBegin; 4459 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4460 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4461 for (i=0; i<m; i++) { 4462 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4463 Ii = i + rstart; 4464 ierr = MatSetValues_MPIAIJ(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4465 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4466 } 4467 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4468 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4469 PetscFunctionReturn(0); 4470 } 4471 4472 #undef __FUNCT__ 4473 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4474 /*@ 4475 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4476 matrices from each processor 4477 4478 Collective on MPI_Comm 4479 4480 Input Parameters: 4481 + comm - the communicators the parallel matrix will live on 4482 . inmat - the input sequential matrices 4483 . n - number of local columns (or PETSC_DECIDE) 4484 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4485 4486 Output Parameter: 4487 . outmat - the parallel matrix generated 4488 4489 Level: advanced 4490 4491 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4492 4493 @*/ 4494 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4495 { 4496 PetscErrorCode ierr; 4497 4498 PetscFunctionBegin; 4499 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4500 if (scall == MAT_INITIAL_MATRIX) { 4501 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4502 } 4503 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4504 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4505 PetscFunctionReturn(0); 4506 } 4507 4508 #undef __FUNCT__ 4509 #define __FUNCT__ "MatFileSplit" 4510 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4511 { 4512 PetscErrorCode ierr; 4513 PetscMPIInt rank; 4514 PetscInt m,N,i,rstart,nnz; 4515 size_t len; 4516 const PetscInt *indx; 4517 PetscViewer out; 4518 char *name; 4519 Mat B; 4520 const PetscScalar *values; 4521 4522 PetscFunctionBegin; 4523 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4524 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4525 /* Should this be the type of the diagonal block of A? */ 4526 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4527 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4528 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4529 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4530 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4531 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4532 for (i=0; i<m; i++) { 4533 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4534 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4535 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4536 } 4537 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4538 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4539 4540 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4541 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4542 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4543 sprintf(name,"%s.%d",outfile,rank); 4544 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4545 ierr = PetscFree(name);CHKERRQ(ierr); 4546 ierr = MatView(B,out);CHKERRQ(ierr); 4547 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4548 ierr = MatDestroy(&B);CHKERRQ(ierr); 4549 PetscFunctionReturn(0); 4550 } 4551 4552 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4553 #undef __FUNCT__ 4554 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4555 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4556 { 4557 PetscErrorCode ierr; 4558 Mat_Merge_SeqsToMPI *merge; 4559 PetscContainer container; 4560 4561 PetscFunctionBegin; 4562 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4563 if (container) { 4564 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4565 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4566 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4567 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4568 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4569 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4570 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4571 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4572 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4573 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4574 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4575 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4576 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4577 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4578 ierr = PetscFree(merge);CHKERRQ(ierr); 4579 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4580 } 4581 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4582 PetscFunctionReturn(0); 4583 } 4584 4585 #include <../src/mat/utils/freespace.h> 4586 #include <petscbt.h> 4587 4588 #undef __FUNCT__ 4589 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4590 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4591 { 4592 PetscErrorCode ierr; 4593 MPI_Comm comm; 4594 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4595 PetscMPIInt size,rank,taga,*len_s; 4596 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4597 PetscInt proc,m; 4598 PetscInt **buf_ri,**buf_rj; 4599 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4600 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4601 MPI_Request *s_waits,*r_waits; 4602 MPI_Status *status; 4603 MatScalar *aa=a->a; 4604 MatScalar **abuf_r,*ba_i; 4605 Mat_Merge_SeqsToMPI *merge; 4606 PetscContainer container; 4607 4608 PetscFunctionBegin; 4609 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4610 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4611 4612 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4613 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4614 4615 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4616 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4617 4618 bi = merge->bi; 4619 bj = merge->bj; 4620 buf_ri = merge->buf_ri; 4621 buf_rj = merge->buf_rj; 4622 4623 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4624 owners = merge->rowmap->range; 4625 len_s = merge->len_s; 4626 4627 /* send and recv matrix values */ 4628 /*-----------------------------*/ 4629 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4630 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4631 4632 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4633 for (proc=0,k=0; proc<size; proc++) { 4634 if (!len_s[proc]) continue; 4635 i = owners[proc]; 4636 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4637 k++; 4638 } 4639 4640 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4641 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4642 ierr = PetscFree(status);CHKERRQ(ierr); 4643 4644 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4645 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4646 4647 /* insert mat values of mpimat */ 4648 /*----------------------------*/ 4649 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4650 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4651 4652 for (k=0; k<merge->nrecv; k++) { 4653 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4654 nrows = *(buf_ri_k[k]); 4655 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4656 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4657 } 4658 4659 /* set values of ba */ 4660 m = merge->rowmap->n; 4661 for (i=0; i<m; i++) { 4662 arow = owners[rank] + i; 4663 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4664 bnzi = bi[i+1] - bi[i]; 4665 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4666 4667 /* add local non-zero vals of this proc's seqmat into ba */ 4668 anzi = ai[arow+1] - ai[arow]; 4669 aj = a->j + ai[arow]; 4670 aa = a->a + ai[arow]; 4671 nextaj = 0; 4672 for (j=0; nextaj<anzi; j++) { 4673 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4674 ba_i[j] += aa[nextaj++]; 4675 } 4676 } 4677 4678 /* add received vals into ba */ 4679 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4680 /* i-th row */ 4681 if (i == *nextrow[k]) { 4682 anzi = *(nextai[k]+1) - *nextai[k]; 4683 aj = buf_rj[k] + *(nextai[k]); 4684 aa = abuf_r[k] + *(nextai[k]); 4685 nextaj = 0; 4686 for (j=0; nextaj<anzi; j++) { 4687 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4688 ba_i[j] += aa[nextaj++]; 4689 } 4690 } 4691 nextrow[k]++; nextai[k]++; 4692 } 4693 } 4694 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4695 } 4696 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4697 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4698 4699 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4700 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4701 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4702 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4703 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4704 PetscFunctionReturn(0); 4705 } 4706 4707 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4708 4709 #undef __FUNCT__ 4710 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4711 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4712 { 4713 PetscErrorCode ierr; 4714 Mat B_mpi; 4715 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4716 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4717 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4718 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4719 PetscInt len,proc,*dnz,*onz,bs,cbs; 4720 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4721 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4722 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4723 MPI_Status *status; 4724 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4725 PetscBT lnkbt; 4726 Mat_Merge_SeqsToMPI *merge; 4727 PetscContainer container; 4728 4729 PetscFunctionBegin; 4730 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4731 4732 /* make sure it is a PETSc comm */ 4733 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4734 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4735 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4736 4737 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4738 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4739 4740 /* determine row ownership */ 4741 /*---------------------------------------------------------*/ 4742 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4743 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4744 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4745 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4746 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4747 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4748 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4749 4750 m = merge->rowmap->n; 4751 owners = merge->rowmap->range; 4752 4753 /* determine the number of messages to send, their lengths */ 4754 /*---------------------------------------------------------*/ 4755 len_s = merge->len_s; 4756 4757 len = 0; /* length of buf_si[] */ 4758 merge->nsend = 0; 4759 for (proc=0; proc<size; proc++) { 4760 len_si[proc] = 0; 4761 if (proc == rank) { 4762 len_s[proc] = 0; 4763 } else { 4764 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4765 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4766 } 4767 if (len_s[proc]) { 4768 merge->nsend++; 4769 nrows = 0; 4770 for (i=owners[proc]; i<owners[proc+1]; i++) { 4771 if (ai[i+1] > ai[i]) nrows++; 4772 } 4773 len_si[proc] = 2*(nrows+1); 4774 len += len_si[proc]; 4775 } 4776 } 4777 4778 /* determine the number and length of messages to receive for ij-structure */ 4779 /*-------------------------------------------------------------------------*/ 4780 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4781 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4782 4783 /* post the Irecv of j-structure */ 4784 /*-------------------------------*/ 4785 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4786 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4787 4788 /* post the Isend of j-structure */ 4789 /*--------------------------------*/ 4790 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4791 4792 for (proc=0, k=0; proc<size; proc++) { 4793 if (!len_s[proc]) continue; 4794 i = owners[proc]; 4795 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4796 k++; 4797 } 4798 4799 /* receives and sends of j-structure are complete */ 4800 /*------------------------------------------------*/ 4801 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4802 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4803 4804 /* send and recv i-structure */ 4805 /*---------------------------*/ 4806 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4807 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4808 4809 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4810 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4811 for (proc=0,k=0; proc<size; proc++) { 4812 if (!len_s[proc]) continue; 4813 /* form outgoing message for i-structure: 4814 buf_si[0]: nrows to be sent 4815 [1:nrows]: row index (global) 4816 [nrows+1:2*nrows+1]: i-structure index 4817 */ 4818 /*-------------------------------------------*/ 4819 nrows = len_si[proc]/2 - 1; 4820 buf_si_i = buf_si + nrows+1; 4821 buf_si[0] = nrows; 4822 buf_si_i[0] = 0; 4823 nrows = 0; 4824 for (i=owners[proc]; i<owners[proc+1]; i++) { 4825 anzi = ai[i+1] - ai[i]; 4826 if (anzi) { 4827 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4828 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4829 nrows++; 4830 } 4831 } 4832 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4833 k++; 4834 buf_si += len_si[proc]; 4835 } 4836 4837 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4838 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4839 4840 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4841 for (i=0; i<merge->nrecv; i++) { 4842 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); 4843 } 4844 4845 ierr = PetscFree(len_si);CHKERRQ(ierr); 4846 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4847 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4848 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4849 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4850 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4851 ierr = PetscFree(status);CHKERRQ(ierr); 4852 4853 /* compute a local seq matrix in each processor */ 4854 /*----------------------------------------------*/ 4855 /* allocate bi array and free space for accumulating nonzero column info */ 4856 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4857 bi[0] = 0; 4858 4859 /* create and initialize a linked list */ 4860 nlnk = N+1; 4861 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4862 4863 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4864 len = ai[owners[rank+1]] - ai[owners[rank]]; 4865 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4866 4867 current_space = free_space; 4868 4869 /* determine symbolic info for each local row */ 4870 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4871 4872 for (k=0; k<merge->nrecv; k++) { 4873 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4874 nrows = *buf_ri_k[k]; 4875 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4876 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4877 } 4878 4879 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4880 len = 0; 4881 for (i=0; i<m; i++) { 4882 bnzi = 0; 4883 /* add local non-zero cols of this proc's seqmat into lnk */ 4884 arow = owners[rank] + i; 4885 anzi = ai[arow+1] - ai[arow]; 4886 aj = a->j + ai[arow]; 4887 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4888 bnzi += nlnk; 4889 /* add received col data into lnk */ 4890 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4891 if (i == *nextrow[k]) { /* i-th row */ 4892 anzi = *(nextai[k]+1) - *nextai[k]; 4893 aj = buf_rj[k] + *nextai[k]; 4894 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4895 bnzi += nlnk; 4896 nextrow[k]++; nextai[k]++; 4897 } 4898 } 4899 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4900 4901 /* if free space is not available, make more free space */ 4902 if (current_space->local_remaining<bnzi) { 4903 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4904 nspacedouble++; 4905 } 4906 /* copy data into free space, then initialize lnk */ 4907 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4908 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4909 4910 current_space->array += bnzi; 4911 current_space->local_used += bnzi; 4912 current_space->local_remaining -= bnzi; 4913 4914 bi[i+1] = bi[i] + bnzi; 4915 } 4916 4917 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4918 4919 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4920 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4921 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4922 4923 /* create symbolic parallel matrix B_mpi */ 4924 /*---------------------------------------*/ 4925 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4926 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4927 if (n==PETSC_DECIDE) { 4928 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4929 } else { 4930 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4931 } 4932 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4933 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4934 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4935 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4936 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4937 4938 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4939 B_mpi->assembled = PETSC_FALSE; 4940 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4941 merge->bi = bi; 4942 merge->bj = bj; 4943 merge->buf_ri = buf_ri; 4944 merge->buf_rj = buf_rj; 4945 merge->coi = NULL; 4946 merge->coj = NULL; 4947 merge->owners_co = NULL; 4948 4949 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 4950 4951 /* attach the supporting struct to B_mpi for reuse */ 4952 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 4953 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 4954 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 4955 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 4956 *mpimat = B_mpi; 4957 4958 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4959 PetscFunctionReturn(0); 4960 } 4961 4962 #undef __FUNCT__ 4963 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 4964 /*@C 4965 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 4966 matrices from each processor 4967 4968 Collective on MPI_Comm 4969 4970 Input Parameters: 4971 + comm - the communicators the parallel matrix will live on 4972 . seqmat - the input sequential matrices 4973 . m - number of local rows (or PETSC_DECIDE) 4974 . n - number of local columns (or PETSC_DECIDE) 4975 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4976 4977 Output Parameter: 4978 . mpimat - the parallel matrix generated 4979 4980 Level: advanced 4981 4982 Notes: 4983 The dimensions of the sequential matrix in each processor MUST be the same. 4984 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 4985 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 4986 @*/ 4987 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 4988 { 4989 PetscErrorCode ierr; 4990 PetscMPIInt size; 4991 4992 PetscFunctionBegin; 4993 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4994 if (size == 1) { 4995 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 4996 if (scall == MAT_INITIAL_MATRIX) { 4997 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 4998 } else { 4999 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5000 } 5001 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5002 PetscFunctionReturn(0); 5003 } 5004 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5005 if (scall == MAT_INITIAL_MATRIX) { 5006 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5007 } 5008 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5009 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5010 PetscFunctionReturn(0); 5011 } 5012 5013 #undef __FUNCT__ 5014 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5015 /*@ 5016 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5017 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5018 with MatGetSize() 5019 5020 Not Collective 5021 5022 Input Parameters: 5023 + A - the matrix 5024 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5025 5026 Output Parameter: 5027 . A_loc - the local sequential matrix generated 5028 5029 Level: developer 5030 5031 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5032 5033 @*/ 5034 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5035 { 5036 PetscErrorCode ierr; 5037 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5038 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5039 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5040 MatScalar *aa=a->a,*ba=b->a,*cam; 5041 PetscScalar *ca; 5042 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5043 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5044 PetscBool match; 5045 5046 PetscFunctionBegin; 5047 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5048 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5049 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5050 if (scall == MAT_INITIAL_MATRIX) { 5051 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5052 ci[0] = 0; 5053 for (i=0; i<am; i++) { 5054 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5055 } 5056 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5057 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5058 k = 0; 5059 for (i=0; i<am; i++) { 5060 ncols_o = bi[i+1] - bi[i]; 5061 ncols_d = ai[i+1] - ai[i]; 5062 /* off-diagonal portion of A */ 5063 for (jo=0; jo<ncols_o; jo++) { 5064 col = cmap[*bj]; 5065 if (col >= cstart) break; 5066 cj[k] = col; bj++; 5067 ca[k++] = *ba++; 5068 } 5069 /* diagonal portion of A */ 5070 for (j=0; j<ncols_d; j++) { 5071 cj[k] = cstart + *aj++; 5072 ca[k++] = *aa++; 5073 } 5074 /* off-diagonal portion of A */ 5075 for (j=jo; j<ncols_o; j++) { 5076 cj[k] = cmap[*bj++]; 5077 ca[k++] = *ba++; 5078 } 5079 } 5080 /* put together the new matrix */ 5081 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5082 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5083 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5084 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5085 mat->free_a = PETSC_TRUE; 5086 mat->free_ij = PETSC_TRUE; 5087 mat->nonew = 0; 5088 } else if (scall == MAT_REUSE_MATRIX) { 5089 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5090 ci = mat->i; cj = mat->j; cam = mat->a; 5091 for (i=0; i<am; i++) { 5092 /* off-diagonal portion of A */ 5093 ncols_o = bi[i+1] - bi[i]; 5094 for (jo=0; jo<ncols_o; jo++) { 5095 col = cmap[*bj]; 5096 if (col >= cstart) break; 5097 *cam++ = *ba++; bj++; 5098 } 5099 /* diagonal portion of A */ 5100 ncols_d = ai[i+1] - ai[i]; 5101 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5102 /* off-diagonal portion of A */ 5103 for (j=jo; j<ncols_o; j++) { 5104 *cam++ = *ba++; bj++; 5105 } 5106 } 5107 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5108 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5109 PetscFunctionReturn(0); 5110 } 5111 5112 #undef __FUNCT__ 5113 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5114 /*@C 5115 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5116 5117 Not Collective 5118 5119 Input Parameters: 5120 + A - the matrix 5121 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5122 - row, col - index sets of rows and columns to extract (or NULL) 5123 5124 Output Parameter: 5125 . A_loc - the local sequential matrix generated 5126 5127 Level: developer 5128 5129 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5130 5131 @*/ 5132 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5133 { 5134 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5135 PetscErrorCode ierr; 5136 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5137 IS isrowa,iscola; 5138 Mat *aloc; 5139 PetscBool match; 5140 5141 PetscFunctionBegin; 5142 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5143 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5144 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5145 if (!row) { 5146 start = A->rmap->rstart; end = A->rmap->rend; 5147 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5148 } else { 5149 isrowa = *row; 5150 } 5151 if (!col) { 5152 start = A->cmap->rstart; 5153 cmap = a->garray; 5154 nzA = a->A->cmap->n; 5155 nzB = a->B->cmap->n; 5156 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5157 ncols = 0; 5158 for (i=0; i<nzB; i++) { 5159 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5160 else break; 5161 } 5162 imark = i; 5163 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5164 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5165 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5166 } else { 5167 iscola = *col; 5168 } 5169 if (scall != MAT_INITIAL_MATRIX) { 5170 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5171 aloc[0] = *A_loc; 5172 } 5173 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5174 *A_loc = aloc[0]; 5175 ierr = PetscFree(aloc);CHKERRQ(ierr); 5176 if (!row) { 5177 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5178 } 5179 if (!col) { 5180 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5181 } 5182 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5183 PetscFunctionReturn(0); 5184 } 5185 5186 #undef __FUNCT__ 5187 #define __FUNCT__ "MatGetBrowsOfAcols" 5188 /*@C 5189 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5190 5191 Collective on Mat 5192 5193 Input Parameters: 5194 + A,B - the matrices in mpiaij format 5195 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5196 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5197 5198 Output Parameter: 5199 + rowb, colb - index sets of rows and columns of B to extract 5200 - B_seq - the sequential matrix generated 5201 5202 Level: developer 5203 5204 @*/ 5205 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5206 { 5207 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5208 PetscErrorCode ierr; 5209 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5210 IS isrowb,iscolb; 5211 Mat *bseq=NULL; 5212 5213 PetscFunctionBegin; 5214 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5215 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); 5216 } 5217 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5218 5219 if (scall == MAT_INITIAL_MATRIX) { 5220 start = A->cmap->rstart; 5221 cmap = a->garray; 5222 nzA = a->A->cmap->n; 5223 nzB = a->B->cmap->n; 5224 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5225 ncols = 0; 5226 for (i=0; i<nzB; i++) { /* row < local row index */ 5227 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5228 else break; 5229 } 5230 imark = i; 5231 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5232 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5233 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5234 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5235 } else { 5236 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5237 isrowb = *rowb; iscolb = *colb; 5238 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5239 bseq[0] = *B_seq; 5240 } 5241 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5242 *B_seq = bseq[0]; 5243 ierr = PetscFree(bseq);CHKERRQ(ierr); 5244 if (!rowb) { 5245 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5246 } else { 5247 *rowb = isrowb; 5248 } 5249 if (!colb) { 5250 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5251 } else { 5252 *colb = iscolb; 5253 } 5254 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5255 PetscFunctionReturn(0); 5256 } 5257 5258 #undef __FUNCT__ 5259 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5260 /* 5261 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5262 of the OFF-DIAGONAL portion of local A 5263 5264 Collective on Mat 5265 5266 Input Parameters: 5267 + A,B - the matrices in mpiaij format 5268 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5269 5270 Output Parameter: 5271 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5272 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5273 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5274 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5275 5276 Level: developer 5277 5278 */ 5279 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5280 { 5281 VecScatter_MPI_General *gen_to,*gen_from; 5282 PetscErrorCode ierr; 5283 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5284 Mat_SeqAIJ *b_oth; 5285 VecScatter ctx =a->Mvctx; 5286 MPI_Comm comm; 5287 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5288 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5289 PetscScalar *rvalues,*svalues; 5290 MatScalar *b_otha,*bufa,*bufA; 5291 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5292 MPI_Request *rwaits = NULL,*swaits = NULL; 5293 MPI_Status *sstatus,rstatus; 5294 PetscMPIInt jj; 5295 PetscInt *cols,sbs,rbs; 5296 PetscScalar *vals; 5297 5298 PetscFunctionBegin; 5299 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5300 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5301 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); 5302 } 5303 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5304 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5305 5306 gen_to = (VecScatter_MPI_General*)ctx->todata; 5307 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5308 rvalues = gen_from->values; /* holds the length of receiving row */ 5309 svalues = gen_to->values; /* holds the length of sending row */ 5310 nrecvs = gen_from->n; 5311 nsends = gen_to->n; 5312 5313 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5314 srow = gen_to->indices; /* local row index to be sent */ 5315 sstarts = gen_to->starts; 5316 sprocs = gen_to->procs; 5317 sstatus = gen_to->sstatus; 5318 sbs = gen_to->bs; 5319 rstarts = gen_from->starts; 5320 rprocs = gen_from->procs; 5321 rbs = gen_from->bs; 5322 5323 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5324 if (scall == MAT_INITIAL_MATRIX) { 5325 /* i-array */ 5326 /*---------*/ 5327 /* post receives */ 5328 for (i=0; i<nrecvs; i++) { 5329 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5330 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5331 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5332 } 5333 5334 /* pack the outgoing message */ 5335 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5336 5337 sstartsj[0] = 0; 5338 rstartsj[0] = 0; 5339 len = 0; /* total length of j or a array to be sent */ 5340 k = 0; 5341 for (i=0; i<nsends; i++) { 5342 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5343 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5344 for (j=0; j<nrows; j++) { 5345 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5346 for (l=0; l<sbs; l++) { 5347 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5348 5349 rowlen[j*sbs+l] = ncols; 5350 5351 len += ncols; 5352 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5353 } 5354 k++; 5355 } 5356 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5357 5358 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5359 } 5360 /* recvs and sends of i-array are completed */ 5361 i = nrecvs; 5362 while (i--) { 5363 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5364 } 5365 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5366 5367 /* allocate buffers for sending j and a arrays */ 5368 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5369 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5370 5371 /* create i-array of B_oth */ 5372 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5373 5374 b_othi[0] = 0; 5375 len = 0; /* total length of j or a array to be received */ 5376 k = 0; 5377 for (i=0; i<nrecvs; i++) { 5378 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5379 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5380 for (j=0; j<nrows; j++) { 5381 b_othi[k+1] = b_othi[k] + rowlen[j]; 5382 len += rowlen[j]; k++; 5383 } 5384 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5385 } 5386 5387 /* allocate space for j and a arrrays of B_oth */ 5388 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5389 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5390 5391 /* j-array */ 5392 /*---------*/ 5393 /* post receives of j-array */ 5394 for (i=0; i<nrecvs; i++) { 5395 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5396 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5397 } 5398 5399 /* pack the outgoing message j-array */ 5400 k = 0; 5401 for (i=0; i<nsends; i++) { 5402 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5403 bufJ = bufj+sstartsj[i]; 5404 for (j=0; j<nrows; j++) { 5405 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5406 for (ll=0; ll<sbs; ll++) { 5407 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5408 for (l=0; l<ncols; l++) { 5409 *bufJ++ = cols[l]; 5410 } 5411 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5412 } 5413 } 5414 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5415 } 5416 5417 /* recvs and sends of j-array are completed */ 5418 i = nrecvs; 5419 while (i--) { 5420 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5421 } 5422 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5423 } else if (scall == MAT_REUSE_MATRIX) { 5424 sstartsj = *startsj_s; 5425 rstartsj = *startsj_r; 5426 bufa = *bufa_ptr; 5427 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5428 b_otha = b_oth->a; 5429 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5430 5431 /* a-array */ 5432 /*---------*/ 5433 /* post receives of a-array */ 5434 for (i=0; i<nrecvs; i++) { 5435 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5436 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5437 } 5438 5439 /* pack the outgoing message a-array */ 5440 k = 0; 5441 for (i=0; i<nsends; i++) { 5442 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5443 bufA = bufa+sstartsj[i]; 5444 for (j=0; j<nrows; j++) { 5445 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5446 for (ll=0; ll<sbs; ll++) { 5447 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5448 for (l=0; l<ncols; l++) { 5449 *bufA++ = vals[l]; 5450 } 5451 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5452 } 5453 } 5454 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5455 } 5456 /* recvs and sends of a-array are completed */ 5457 i = nrecvs; 5458 while (i--) { 5459 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5460 } 5461 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5462 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5463 5464 if (scall == MAT_INITIAL_MATRIX) { 5465 /* put together the new matrix */ 5466 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5467 5468 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5469 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5470 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5471 b_oth->free_a = PETSC_TRUE; 5472 b_oth->free_ij = PETSC_TRUE; 5473 b_oth->nonew = 0; 5474 5475 ierr = PetscFree(bufj);CHKERRQ(ierr); 5476 if (!startsj_s || !bufa_ptr) { 5477 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5478 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5479 } else { 5480 *startsj_s = sstartsj; 5481 *startsj_r = rstartsj; 5482 *bufa_ptr = bufa; 5483 } 5484 } 5485 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5486 PetscFunctionReturn(0); 5487 } 5488 5489 #undef __FUNCT__ 5490 #define __FUNCT__ "MatGetCommunicationStructs" 5491 /*@C 5492 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5493 5494 Not Collective 5495 5496 Input Parameters: 5497 . A - The matrix in mpiaij format 5498 5499 Output Parameter: 5500 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5501 . colmap - A map from global column index to local index into lvec 5502 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5503 5504 Level: developer 5505 5506 @*/ 5507 #if defined(PETSC_USE_CTABLE) 5508 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5509 #else 5510 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5511 #endif 5512 { 5513 Mat_MPIAIJ *a; 5514 5515 PetscFunctionBegin; 5516 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5517 PetscValidPointer(lvec, 2); 5518 PetscValidPointer(colmap, 3); 5519 PetscValidPointer(multScatter, 4); 5520 a = (Mat_MPIAIJ*) A->data; 5521 if (lvec) *lvec = a->lvec; 5522 if (colmap) *colmap = a->colmap; 5523 if (multScatter) *multScatter = a->Mvctx; 5524 PetscFunctionReturn(0); 5525 } 5526 5527 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5528 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5529 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5530 5531 #undef __FUNCT__ 5532 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5533 /* 5534 Computes (B'*A')' since computing B*A directly is untenable 5535 5536 n p p 5537 ( ) ( ) ( ) 5538 m ( A ) * n ( B ) = m ( C ) 5539 ( ) ( ) ( ) 5540 5541 */ 5542 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5543 { 5544 PetscErrorCode ierr; 5545 Mat At,Bt,Ct; 5546 5547 PetscFunctionBegin; 5548 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5549 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5550 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5551 ierr = MatDestroy(&At);CHKERRQ(ierr); 5552 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5553 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5554 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5555 PetscFunctionReturn(0); 5556 } 5557 5558 #undef __FUNCT__ 5559 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5560 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5561 { 5562 PetscErrorCode ierr; 5563 PetscInt m=A->rmap->n,n=B->cmap->n; 5564 Mat Cmat; 5565 5566 PetscFunctionBegin; 5567 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); 5568 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5569 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5570 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5571 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5572 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5573 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5574 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5575 5576 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5577 5578 *C = Cmat; 5579 PetscFunctionReturn(0); 5580 } 5581 5582 /* ----------------------------------------------------------------*/ 5583 #undef __FUNCT__ 5584 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5585 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5586 { 5587 PetscErrorCode ierr; 5588 5589 PetscFunctionBegin; 5590 if (scall == MAT_INITIAL_MATRIX) { 5591 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5592 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5593 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5594 } 5595 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5596 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5597 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5598 PetscFunctionReturn(0); 5599 } 5600 5601 #if defined(PETSC_HAVE_MUMPS) 5602 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5603 #endif 5604 #if defined(PETSC_HAVE_PASTIX) 5605 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5606 #endif 5607 #if defined(PETSC_HAVE_SUPERLU_DIST) 5608 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5609 #endif 5610 #if defined(PETSC_HAVE_CLIQUE) 5611 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5612 #endif 5613 5614 /*MC 5615 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5616 5617 Options Database Keys: 5618 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5619 5620 Level: beginner 5621 5622 .seealso: MatCreateAIJ() 5623 M*/ 5624 5625 #undef __FUNCT__ 5626 #define __FUNCT__ "MatCreate_MPIAIJ" 5627 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5628 { 5629 Mat_MPIAIJ *b; 5630 PetscErrorCode ierr; 5631 PetscMPIInt size; 5632 5633 PetscFunctionBegin; 5634 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5635 5636 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5637 B->data = (void*)b; 5638 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5639 B->assembled = PETSC_FALSE; 5640 B->insertmode = NOT_SET_VALUES; 5641 b->size = size; 5642 5643 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5644 5645 /* build cache for off array entries formed */ 5646 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5647 5648 b->donotstash = PETSC_FALSE; 5649 b->colmap = 0; 5650 b->garray = 0; 5651 b->roworiented = PETSC_TRUE; 5652 5653 /* stuff used for matrix vector multiply */ 5654 b->lvec = NULL; 5655 b->Mvctx = NULL; 5656 5657 /* stuff for MatGetRow() */ 5658 b->rowindices = 0; 5659 b->rowvalues = 0; 5660 b->getrowactive = PETSC_FALSE; 5661 5662 /* flexible pointer used in CUSP/CUSPARSE classes */ 5663 b->spptr = NULL; 5664 5665 #if defined(PETSC_HAVE_MUMPS) 5666 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5667 #endif 5668 #if defined(PETSC_HAVE_PASTIX) 5669 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5670 #endif 5671 #if defined(PETSC_HAVE_SUPERLU_DIST) 5672 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5673 #endif 5674 #if defined(PETSC_HAVE_CLIQUE) 5675 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5676 #endif 5677 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5678 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5679 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5680 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5681 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5682 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5683 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5684 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5685 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5686 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5687 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5688 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5689 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5690 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5691 PetscFunctionReturn(0); 5692 } 5693 5694 #undef __FUNCT__ 5695 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5696 /*@ 5697 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5698 and "off-diagonal" part of the matrix in CSR format. 5699 5700 Collective on MPI_Comm 5701 5702 Input Parameters: 5703 + comm - MPI communicator 5704 . m - number of local rows (Cannot be PETSC_DECIDE) 5705 . n - This value should be the same as the local size used in creating the 5706 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5707 calculated if N is given) For square matrices n is almost always m. 5708 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5709 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5710 . i - row indices for "diagonal" portion of matrix 5711 . j - column indices 5712 . a - matrix values 5713 . oi - row indices for "off-diagonal" portion of matrix 5714 . oj - column indices 5715 - oa - matrix values 5716 5717 Output Parameter: 5718 . mat - the matrix 5719 5720 Level: advanced 5721 5722 Notes: 5723 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5724 must free the arrays once the matrix has been destroyed and not before. 5725 5726 The i and j indices are 0 based 5727 5728 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5729 5730 This sets local rows and cannot be used to set off-processor values. 5731 5732 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5733 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5734 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5735 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5736 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5737 communication if it is known that only local entries will be set. 5738 5739 .keywords: matrix, aij, compressed row, sparse, parallel 5740 5741 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5742 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5743 @*/ 5744 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) 5745 { 5746 PetscErrorCode ierr; 5747 Mat_MPIAIJ *maij; 5748 5749 PetscFunctionBegin; 5750 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5751 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5752 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5753 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5754 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5755 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5756 maij = (Mat_MPIAIJ*) (*mat)->data; 5757 5758 (*mat)->preallocated = PETSC_TRUE; 5759 5760 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5761 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5762 5763 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5764 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5765 5766 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5767 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5768 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5769 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5770 5771 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5772 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5773 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5774 PetscFunctionReturn(0); 5775 } 5776 5777 /* 5778 Special version for direct calls from Fortran 5779 */ 5780 #include <petsc-private/fortranimpl.h> 5781 5782 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5783 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5784 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5785 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5786 #endif 5787 5788 /* Change these macros so can be used in void function */ 5789 #undef CHKERRQ 5790 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5791 #undef SETERRQ2 5792 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5793 #undef SETERRQ3 5794 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5795 #undef SETERRQ 5796 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5797 5798 #undef __FUNCT__ 5799 #define __FUNCT__ "matsetvaluesmpiaij_" 5800 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) 5801 { 5802 Mat mat = *mmat; 5803 PetscInt m = *mm, n = *mn; 5804 InsertMode addv = *maddv; 5805 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5806 PetscScalar value; 5807 PetscErrorCode ierr; 5808 5809 MatCheckPreallocated(mat,1); 5810 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5811 5812 #if defined(PETSC_USE_DEBUG) 5813 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5814 #endif 5815 { 5816 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5817 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5818 PetscBool roworiented = aij->roworiented; 5819 5820 /* Some Variables required in the macro */ 5821 Mat A = aij->A; 5822 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5823 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5824 MatScalar *aa = a->a; 5825 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5826 Mat B = aij->B; 5827 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5828 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5829 MatScalar *ba = b->a; 5830 5831 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5832 PetscInt nonew = a->nonew; 5833 MatScalar *ap1,*ap2; 5834 5835 PetscFunctionBegin; 5836 for (i=0; i<m; i++) { 5837 if (im[i] < 0) continue; 5838 #if defined(PETSC_USE_DEBUG) 5839 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); 5840 #endif 5841 if (im[i] >= rstart && im[i] < rend) { 5842 row = im[i] - rstart; 5843 lastcol1 = -1; 5844 rp1 = aj + ai[row]; 5845 ap1 = aa + ai[row]; 5846 rmax1 = aimax[row]; 5847 nrow1 = ailen[row]; 5848 low1 = 0; 5849 high1 = nrow1; 5850 lastcol2 = -1; 5851 rp2 = bj + bi[row]; 5852 ap2 = ba + bi[row]; 5853 rmax2 = bimax[row]; 5854 nrow2 = bilen[row]; 5855 low2 = 0; 5856 high2 = nrow2; 5857 5858 for (j=0; j<n; j++) { 5859 if (roworiented) value = v[i*n+j]; 5860 else value = v[i+j*m]; 5861 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5862 if (in[j] >= cstart && in[j] < cend) { 5863 col = in[j] - cstart; 5864 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5865 } else if (in[j] < 0) continue; 5866 #if defined(PETSC_USE_DEBUG) 5867 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); 5868 #endif 5869 else { 5870 if (mat->was_assembled) { 5871 if (!aij->colmap) { 5872 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5873 } 5874 #if defined(PETSC_USE_CTABLE) 5875 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5876 col--; 5877 #else 5878 col = aij->colmap[in[j]] - 1; 5879 #endif 5880 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5881 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5882 col = in[j]; 5883 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5884 B = aij->B; 5885 b = (Mat_SeqAIJ*)B->data; 5886 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5887 rp2 = bj + bi[row]; 5888 ap2 = ba + bi[row]; 5889 rmax2 = bimax[row]; 5890 nrow2 = bilen[row]; 5891 low2 = 0; 5892 high2 = nrow2; 5893 bm = aij->B->rmap->n; 5894 ba = b->a; 5895 } 5896 } else col = in[j]; 5897 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5898 } 5899 } 5900 } else if (!aij->donotstash) { 5901 if (roworiented) { 5902 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5903 } else { 5904 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5905 } 5906 } 5907 } 5908 } 5909 PetscFunctionReturnVoid(); 5910 } 5911 5912