1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 for (i=1; i<mat->rmap->n; i++) { 335 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2530 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2531 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2532 for (i=0; i<redund->nrecvs; i++) { 2533 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2534 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2535 } 2536 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2537 2538 if (redund->psubcomm) { 2539 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2540 } 2541 2542 ierr = redund->Destroy(A);CHKERRQ(ierr); 2543 ierr = PetscFree(redund);CHKERRQ(ierr); 2544 } 2545 PetscFunctionReturn(0); 2546 } 2547 2548 #undef __FUNCT__ 2549 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_psubcomm" 2550 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_psubcomm(Mat mat,PetscInt nsubcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2551 { 2552 PetscMPIInt rank,size; 2553 MPI_Comm comm,subcomm=psubcomm->comm; 2554 PetscErrorCode ierr; 2555 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2556 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2557 PetscInt *rowrange = mat->rmap->range; 2558 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2559 Mat A = aij->A,B=aij->B,C=*matredundant; 2560 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2561 PetscScalar *sbuf_a; 2562 PetscInt nzlocal=a->nz+b->nz; 2563 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2564 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2565 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2566 MatScalar *aworkA,*aworkB; 2567 PetscScalar *vals; 2568 PetscMPIInt tag1,tag2,tag3,imdex; 2569 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2570 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2571 MPI_Status recv_status,*send_status; 2572 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2573 PetscInt **rbuf_j=NULL; 2574 PetscScalar **rbuf_a=NULL; 2575 Mat_Redundant *redund =NULL; 2576 2577 PetscFunctionBegin; 2578 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2579 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2580 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2581 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2582 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2583 2584 if (reuse == MAT_REUSE_MATRIX) { 2585 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2586 if (subsize == 1) { 2587 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2588 redund = c->redundant; 2589 } else { 2590 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2591 redund = c->redundant; 2592 } 2593 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2594 2595 nsends = redund->nsends; 2596 nrecvs = redund->nrecvs; 2597 send_rank = redund->send_rank; 2598 recv_rank = redund->recv_rank; 2599 sbuf_nz = redund->sbuf_nz; 2600 rbuf_nz = redund->rbuf_nz; 2601 sbuf_j = redund->sbuf_j; 2602 sbuf_a = redund->sbuf_a; 2603 rbuf_j = redund->rbuf_j; 2604 rbuf_a = redund->rbuf_a; 2605 } 2606 2607 if (reuse == MAT_INITIAL_MATRIX) { 2608 PetscInt nleftover,np_subcomm; 2609 2610 /* get the destination processors' id send_rank, nsends and nrecvs */ 2611 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2612 2613 np_subcomm = size/nsubcomm; 2614 nleftover = size - nsubcomm*np_subcomm; 2615 2616 nsends = 0; nrecvs = 0; 2617 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2618 /* -------------------------------------------*/ 2619 for (i=0; i<size; i++) { 2620 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2621 send_rank[nsends] = i; nsends++; 2622 recv_rank[nrecvs++] = i; 2623 /* printf("[%d] send to and recv from [%d]\n",rank,i); */ 2624 } 2625 } 2626 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2627 i = size-nleftover-1; 2628 j = 0; 2629 while (j < nsubcomm - nleftover) { 2630 send_rank[nsends++] = i; 2631 i--; j++; 2632 /* printf("[%d] send to [%d]\n",rank,i); */ 2633 } 2634 } 2635 2636 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2637 for (i=0; i<nleftover; i++) { 2638 recv_rank[nrecvs++] = size-nleftover+i; 2639 /* printf("[%d] recv from [%d]\n",rank,i); */ 2640 } 2641 } 2642 } else if (psubcomm->type == PETSC_SUBCOMM_CONTIGUOUS) { 2643 /* --------------------------------------------------*/ 2644 PetscInt color,subcommstart; 2645 subcommstart=0; 2646 for (color=0; color<nsubcomm; color++) { 2647 if (psubcomm->color != color) { 2648 for (i=0; i<psubcomm->subsize[color]; i++) { 2649 if (subrank == i) { /* my_subrank == other's subrank */ 2650 send_rank[nsends++] = subcommstart+i; 2651 recv_rank[nrecvs++] = subcommstart+i; 2652 /* printf("[%d] send to and recv from [%d]\n",rank,subcommstart+i); */ 2653 } 2654 } 2655 } 2656 subcommstart += psubcomm->subsize[color]; 2657 } 2658 if (nleftover && subrank == size/nsubcomm) { /* this proc is a leftover proc, send to subcomm that does not have leftover proc */ 2659 subcommstart=0; 2660 for (color=0; color<nsubcomm; color++) { 2661 subcommstart += psubcomm->subsize[color]; 2662 if (psubcomm->color == color) continue; 2663 if (psubcomm->subsize[color] == size/nsubcomm) { /* subcomm does not have leftover proc */ 2664 send_rank[nsends++] = subcommstart -1; /* send to the last proc of subcomm[color] */ 2665 /* printf("[%d] leftover send to [%d] \n",rank,subcommstart -1); */ 2666 } 2667 } 2668 } 2669 2670 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2671 subcommstart=0; 2672 for (color=0; color<nsubcomm; color++) { 2673 subcommstart += psubcomm->subsize[color]; 2674 if (psubcomm->subsize[color] > size/nsubcomm) { /* subcomm has leftover proc */ 2675 recv_rank[nrecvs++] = subcommstart -1; /* recv from the last proc of subcomm[color] */ 2676 /* printf("[%d] recv from [%d]\n",rank,subcommstart -1); */ 2677 } 2678 } 2679 } 2680 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for PetscSubcomm type %D",psubcomm->type); 2681 2682 /* allocate sbuf_j, sbuf_a */ 2683 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2684 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2685 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2686 /* 2687 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2688 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2689 */ 2690 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2691 2692 /* copy mat's local entries into the buffers */ 2693 if (reuse == MAT_INITIAL_MATRIX) { 2694 rownz_max = 0; 2695 rptr = sbuf_j; 2696 cols = sbuf_j + rend-rstart + 1; 2697 vals = sbuf_a; 2698 rptr[0] = 0; 2699 for (i=0; i<rend-rstart; i++) { 2700 row = i + rstart; 2701 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2702 ncols = nzA + nzB; 2703 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2704 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2705 /* load the column indices for this row into cols */ 2706 lwrite = 0; 2707 for (l=0; l<nzB; l++) { 2708 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2709 vals[lwrite] = aworkB[l]; 2710 cols[lwrite++] = ctmp; 2711 } 2712 } 2713 for (l=0; l<nzA; l++) { 2714 vals[lwrite] = aworkA[l]; 2715 cols[lwrite++] = cstart + cworkA[l]; 2716 } 2717 for (l=0; l<nzB; l++) { 2718 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2719 vals[lwrite] = aworkB[l]; 2720 cols[lwrite++] = ctmp; 2721 } 2722 } 2723 vals += ncols; 2724 cols += ncols; 2725 rptr[i+1] = rptr[i] + ncols; 2726 if (rownz_max < ncols) rownz_max = ncols; 2727 } 2728 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2729 } else { /* only copy matrix values into sbuf_a */ 2730 rptr = sbuf_j; 2731 vals = sbuf_a; 2732 rptr[0] = 0; 2733 for (i=0; i<rend-rstart; i++) { 2734 row = i + rstart; 2735 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2736 ncols = nzA + nzB; 2737 cworkB = b->j + b->i[i]; 2738 aworkA = a->a + a->i[i]; 2739 aworkB = b->a + b->i[i]; 2740 lwrite = 0; 2741 for (l=0; l<nzB; l++) { 2742 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2743 } 2744 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2745 for (l=0; l<nzB; l++) { 2746 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2747 } 2748 vals += ncols; 2749 rptr[i+1] = rptr[i] + ncols; 2750 } 2751 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2752 2753 /* send nzlocal to others, and recv other's nzlocal */ 2754 /*--------------------------------------------------*/ 2755 if (reuse == MAT_INITIAL_MATRIX) { 2756 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2757 2758 s_waits2 = s_waits3 + nsends; 2759 s_waits1 = s_waits2 + nsends; 2760 r_waits1 = s_waits1 + nsends; 2761 r_waits2 = r_waits1 + nrecvs; 2762 r_waits3 = r_waits2 + nrecvs; 2763 } else { 2764 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2765 2766 r_waits3 = s_waits3 + nsends; 2767 } 2768 2769 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2770 if (reuse == MAT_INITIAL_MATRIX) { 2771 /* get new tags to keep the communication clean */ 2772 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2773 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2774 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2775 2776 /* post receives of other's nzlocal */ 2777 for (i=0; i<nrecvs; i++) { 2778 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2779 } 2780 /* send nzlocal to others */ 2781 for (i=0; i<nsends; i++) { 2782 sbuf_nz[i] = nzlocal; 2783 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2784 } 2785 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2786 count = nrecvs; 2787 while (count) { 2788 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2789 2790 recv_rank[imdex] = recv_status.MPI_SOURCE; 2791 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2792 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2793 2794 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2795 2796 rbuf_nz[imdex] += i + 2; 2797 2798 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2799 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2800 count--; 2801 } 2802 /* wait on sends of nzlocal */ 2803 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2804 /* send mat->i,j to others, and recv from other's */ 2805 /*------------------------------------------------*/ 2806 for (i=0; i<nsends; i++) { 2807 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2808 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2809 } 2810 /* wait on receives of mat->i,j */ 2811 /*------------------------------*/ 2812 count = nrecvs; 2813 while (count) { 2814 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2815 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2816 count--; 2817 } 2818 /* wait on sends of mat->i,j */ 2819 /*---------------------------*/ 2820 if (nsends) { 2821 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2822 } 2823 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2824 2825 /* post receives, send and receive mat->a */ 2826 /*----------------------------------------*/ 2827 for (imdex=0; imdex<nrecvs; imdex++) { 2828 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2829 } 2830 for (i=0; i<nsends; i++) { 2831 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2832 } 2833 count = nrecvs; 2834 while (count) { 2835 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2836 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2837 count--; 2838 } 2839 if (nsends) { 2840 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2841 } 2842 2843 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2844 2845 /* create redundant matrix */ 2846 /*-------------------------*/ 2847 if (reuse == MAT_INITIAL_MATRIX) { 2848 const PetscInt *range; 2849 PetscInt rstart_sub,rend_sub,mloc_sub; 2850 2851 /* compute rownz_max for preallocation */ 2852 for (imdex=0; imdex<nrecvs; imdex++) { 2853 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2854 rptr = rbuf_j[imdex]; 2855 for (i=0; i<j; i++) { 2856 ncols = rptr[i+1] - rptr[i]; 2857 if (rownz_max < ncols) rownz_max = ncols; 2858 } 2859 } 2860 2861 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2862 2863 /* get local size of redundant matrix 2864 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2865 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2866 rstart_sub = range[nsubcomm*subrank]; 2867 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2868 rend_sub = range[nsubcomm*(subrank+1)]; 2869 } else { 2870 rend_sub = mat->rmap->N; 2871 } 2872 mloc_sub = rend_sub - rstart_sub; 2873 2874 if (M == N) { 2875 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2876 } else { /* non-square matrix */ 2877 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2878 } 2879 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2880 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2881 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2882 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2883 } else { 2884 C = *matredundant; 2885 } 2886 2887 /* insert local matrix entries */ 2888 rptr = sbuf_j; 2889 cols = sbuf_j + rend-rstart + 1; 2890 vals = sbuf_a; 2891 for (i=0; i<rend-rstart; i++) { 2892 row = i + rstart; 2893 ncols = rptr[i+1] - rptr[i]; 2894 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2895 vals += ncols; 2896 cols += ncols; 2897 } 2898 /* insert received matrix entries */ 2899 for (imdex=0; imdex<nrecvs; imdex++) { 2900 rstart = rowrange[recv_rank[imdex]]; 2901 rend = rowrange[recv_rank[imdex]+1]; 2902 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2903 rptr = rbuf_j[imdex]; 2904 cols = rbuf_j[imdex] + rend-rstart + 1; 2905 vals = rbuf_a[imdex]; 2906 for (i=0; i<rend-rstart; i++) { 2907 row = i + rstart; 2908 ncols = rptr[i+1] - rptr[i]; 2909 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2910 vals += ncols; 2911 cols += ncols; 2912 } 2913 } 2914 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2915 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2916 2917 if (reuse == MAT_INITIAL_MATRIX) { 2918 *matredundant = C; 2919 2920 /* create a supporting struct and attach it to C for reuse */ 2921 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2922 if (subsize == 1) { 2923 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2924 c->redundant = redund; 2925 } else { 2926 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2927 c->redundant = redund; 2928 } 2929 2930 redund->nzlocal = nzlocal; 2931 redund->nsends = nsends; 2932 redund->nrecvs = nrecvs; 2933 redund->send_rank = send_rank; 2934 redund->recv_rank = recv_rank; 2935 redund->sbuf_nz = sbuf_nz; 2936 redund->rbuf_nz = rbuf_nz; 2937 redund->sbuf_j = sbuf_j; 2938 redund->sbuf_a = sbuf_a; 2939 redund->rbuf_j = rbuf_j; 2940 redund->rbuf_a = rbuf_a; 2941 redund->psubcomm = NULL; 2942 2943 redund->Destroy = C->ops->destroy; 2944 C->ops->destroy = MatDestroy_MatRedundant; 2945 } 2946 PetscFunctionReturn(0); 2947 } 2948 2949 #undef __FUNCT__ 2950 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2951 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2952 { 2953 PetscErrorCode ierr; 2954 2955 PetscFunctionBegin; 2956 if (subcomm == MPI_COMM_NULL || subcomm == PETSC_COMM_SELF) { /* create psubcomm */ 2957 MPI_Comm comm; 2958 PetscSubcomm psubcomm; 2959 PetscMPIInt size,subsize; 2960 2961 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2962 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2963 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2964 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2965 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_INTERLACED);CHKERRQ(ierr); 2966 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2967 2968 ierr = MatGetRedundantMatrix_MPIAIJ_psubcomm(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2969 2970 /* free psubcomm in MatDestroy_MatRedundant() */ 2971 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2972 if (subsize == 1) { 2973 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2974 c->redundant->psubcomm = psubcomm; 2975 } else { 2976 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2977 c->redundant->psubcomm = psubcomm ; 2978 } 2979 } else { 2980 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet"); 2981 } 2982 PetscFunctionReturn(0); 2983 } 2984 2985 #undef __FUNCT__ 2986 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 2987 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 2988 { 2989 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2990 PetscErrorCode ierr; 2991 PetscInt i,*idxb = 0; 2992 PetscScalar *va,*vb; 2993 Vec vtmp; 2994 2995 PetscFunctionBegin; 2996 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 2997 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2998 if (idx) { 2999 for (i=0; i<A->rmap->n; i++) { 3000 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3001 } 3002 } 3003 3004 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3005 if (idx) { 3006 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3007 } 3008 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3009 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3010 3011 for (i=0; i<A->rmap->n; i++) { 3012 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3013 va[i] = vb[i]; 3014 if (idx) idx[i] = a->garray[idxb[i]]; 3015 } 3016 } 3017 3018 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3019 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3020 ierr = PetscFree(idxb);CHKERRQ(ierr); 3021 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3022 PetscFunctionReturn(0); 3023 } 3024 3025 #undef __FUNCT__ 3026 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3027 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3028 { 3029 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3030 PetscErrorCode ierr; 3031 PetscInt i,*idxb = 0; 3032 PetscScalar *va,*vb; 3033 Vec vtmp; 3034 3035 PetscFunctionBegin; 3036 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3037 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3038 if (idx) { 3039 for (i=0; i<A->cmap->n; i++) { 3040 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3041 } 3042 } 3043 3044 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3045 if (idx) { 3046 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3047 } 3048 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3049 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3050 3051 for (i=0; i<A->rmap->n; i++) { 3052 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3053 va[i] = vb[i]; 3054 if (idx) idx[i] = a->garray[idxb[i]]; 3055 } 3056 } 3057 3058 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3059 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3060 ierr = PetscFree(idxb);CHKERRQ(ierr); 3061 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3062 PetscFunctionReturn(0); 3063 } 3064 3065 #undef __FUNCT__ 3066 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3067 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3068 { 3069 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3070 PetscInt n = A->rmap->n; 3071 PetscInt cstart = A->cmap->rstart; 3072 PetscInt *cmap = mat->garray; 3073 PetscInt *diagIdx, *offdiagIdx; 3074 Vec diagV, offdiagV; 3075 PetscScalar *a, *diagA, *offdiagA; 3076 PetscInt r; 3077 PetscErrorCode ierr; 3078 3079 PetscFunctionBegin; 3080 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3081 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3082 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3083 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3084 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3085 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3086 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3087 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3088 for (r = 0; r < n; ++r) { 3089 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3090 a[r] = diagA[r]; 3091 idx[r] = cstart + diagIdx[r]; 3092 } else { 3093 a[r] = offdiagA[r]; 3094 idx[r] = cmap[offdiagIdx[r]]; 3095 } 3096 } 3097 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3098 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3099 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3100 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3101 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3102 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3103 PetscFunctionReturn(0); 3104 } 3105 3106 #undef __FUNCT__ 3107 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3108 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3109 { 3110 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3111 PetscInt n = A->rmap->n; 3112 PetscInt cstart = A->cmap->rstart; 3113 PetscInt *cmap = mat->garray; 3114 PetscInt *diagIdx, *offdiagIdx; 3115 Vec diagV, offdiagV; 3116 PetscScalar *a, *diagA, *offdiagA; 3117 PetscInt r; 3118 PetscErrorCode ierr; 3119 3120 PetscFunctionBegin; 3121 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3122 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3123 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3124 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3125 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3126 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3127 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3128 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3129 for (r = 0; r < n; ++r) { 3130 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3131 a[r] = diagA[r]; 3132 idx[r] = cstart + diagIdx[r]; 3133 } else { 3134 a[r] = offdiagA[r]; 3135 idx[r] = cmap[offdiagIdx[r]]; 3136 } 3137 } 3138 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3139 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3140 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3141 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3142 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3143 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3144 PetscFunctionReturn(0); 3145 } 3146 3147 #undef __FUNCT__ 3148 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3149 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3150 { 3151 PetscErrorCode ierr; 3152 Mat *dummy; 3153 3154 PetscFunctionBegin; 3155 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3156 *newmat = *dummy; 3157 ierr = PetscFree(dummy);CHKERRQ(ierr); 3158 PetscFunctionReturn(0); 3159 } 3160 3161 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3162 3163 #undef __FUNCT__ 3164 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3165 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3166 { 3167 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3168 PetscErrorCode ierr; 3169 3170 PetscFunctionBegin; 3171 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3172 PetscFunctionReturn(0); 3173 } 3174 3175 #undef __FUNCT__ 3176 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3177 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3178 { 3179 PetscErrorCode ierr; 3180 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3181 3182 PetscFunctionBegin; 3183 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3184 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3185 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3186 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3187 PetscFunctionReturn(0); 3188 } 3189 3190 /* -------------------------------------------------------------------*/ 3191 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3192 MatGetRow_MPIAIJ, 3193 MatRestoreRow_MPIAIJ, 3194 MatMult_MPIAIJ, 3195 /* 4*/ MatMultAdd_MPIAIJ, 3196 MatMultTranspose_MPIAIJ, 3197 MatMultTransposeAdd_MPIAIJ, 3198 #if defined(PETSC_HAVE_PBGL) 3199 MatSolve_MPIAIJ, 3200 #else 3201 0, 3202 #endif 3203 0, 3204 0, 3205 /*10*/ 0, 3206 0, 3207 0, 3208 MatSOR_MPIAIJ, 3209 MatTranspose_MPIAIJ, 3210 /*15*/ MatGetInfo_MPIAIJ, 3211 MatEqual_MPIAIJ, 3212 MatGetDiagonal_MPIAIJ, 3213 MatDiagonalScale_MPIAIJ, 3214 MatNorm_MPIAIJ, 3215 /*20*/ MatAssemblyBegin_MPIAIJ, 3216 MatAssemblyEnd_MPIAIJ, 3217 MatSetOption_MPIAIJ, 3218 MatZeroEntries_MPIAIJ, 3219 /*24*/ MatZeroRows_MPIAIJ, 3220 0, 3221 #if defined(PETSC_HAVE_PBGL) 3222 0, 3223 #else 3224 0, 3225 #endif 3226 0, 3227 0, 3228 /*29*/ MatSetUp_MPIAIJ, 3229 #if defined(PETSC_HAVE_PBGL) 3230 0, 3231 #else 3232 0, 3233 #endif 3234 0, 3235 0, 3236 0, 3237 /*34*/ MatDuplicate_MPIAIJ, 3238 0, 3239 0, 3240 0, 3241 0, 3242 /*39*/ MatAXPY_MPIAIJ, 3243 MatGetSubMatrices_MPIAIJ, 3244 MatIncreaseOverlap_MPIAIJ, 3245 MatGetValues_MPIAIJ, 3246 MatCopy_MPIAIJ, 3247 /*44*/ MatGetRowMax_MPIAIJ, 3248 MatScale_MPIAIJ, 3249 0, 3250 0, 3251 MatZeroRowsColumns_MPIAIJ, 3252 /*49*/ MatSetRandom_MPIAIJ, 3253 0, 3254 0, 3255 0, 3256 0, 3257 /*54*/ MatFDColoringCreate_MPIAIJ, 3258 0, 3259 MatSetUnfactored_MPIAIJ, 3260 MatPermute_MPIAIJ, 3261 0, 3262 /*59*/ MatGetSubMatrix_MPIAIJ, 3263 MatDestroy_MPIAIJ, 3264 MatView_MPIAIJ, 3265 0, 3266 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3267 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3268 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3269 0, 3270 0, 3271 0, 3272 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3273 MatGetRowMinAbs_MPIAIJ, 3274 0, 3275 MatSetColoring_MPIAIJ, 3276 0, 3277 MatSetValuesAdifor_MPIAIJ, 3278 /*75*/ MatFDColoringApply_AIJ, 3279 0, 3280 0, 3281 0, 3282 MatFindZeroDiagonals_MPIAIJ, 3283 /*80*/ 0, 3284 0, 3285 0, 3286 /*83*/ MatLoad_MPIAIJ, 3287 0, 3288 0, 3289 0, 3290 0, 3291 0, 3292 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3293 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3294 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3295 MatPtAP_MPIAIJ_MPIAIJ, 3296 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3297 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3298 0, 3299 0, 3300 0, 3301 0, 3302 /*99*/ 0, 3303 0, 3304 0, 3305 MatConjugate_MPIAIJ, 3306 0, 3307 /*104*/MatSetValuesRow_MPIAIJ, 3308 MatRealPart_MPIAIJ, 3309 MatImaginaryPart_MPIAIJ, 3310 0, 3311 0, 3312 /*109*/0, 3313 MatGetRedundantMatrix_MPIAIJ, 3314 MatGetRowMin_MPIAIJ, 3315 0, 3316 0, 3317 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3318 0, 3319 0, 3320 0, 3321 0, 3322 /*119*/0, 3323 0, 3324 0, 3325 0, 3326 MatGetMultiProcBlock_MPIAIJ, 3327 /*124*/MatFindNonzeroRows_MPIAIJ, 3328 MatGetColumnNorms_MPIAIJ, 3329 MatInvertBlockDiagonal_MPIAIJ, 3330 0, 3331 MatGetSubMatricesParallel_MPIAIJ, 3332 /*129*/0, 3333 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3334 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3335 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3336 0, 3337 /*134*/0, 3338 0, 3339 0, 3340 0, 3341 0, 3342 /*139*/0, 3343 0 3344 }; 3345 3346 /* ----------------------------------------------------------------------------------------*/ 3347 3348 #undef __FUNCT__ 3349 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3350 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3351 { 3352 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3353 PetscErrorCode ierr; 3354 3355 PetscFunctionBegin; 3356 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3357 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3358 PetscFunctionReturn(0); 3359 } 3360 3361 #undef __FUNCT__ 3362 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3363 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3364 { 3365 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3366 PetscErrorCode ierr; 3367 3368 PetscFunctionBegin; 3369 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3370 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3371 PetscFunctionReturn(0); 3372 } 3373 3374 #undef __FUNCT__ 3375 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3376 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3377 { 3378 Mat_MPIAIJ *b; 3379 PetscErrorCode ierr; 3380 3381 PetscFunctionBegin; 3382 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3383 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3384 b = (Mat_MPIAIJ*)B->data; 3385 3386 if (!B->preallocated) { 3387 /* Explicitly create 2 MATSEQAIJ matrices. */ 3388 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3389 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3390 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3391 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3392 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3393 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3394 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3395 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3396 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3397 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3398 } 3399 3400 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3401 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3402 B->preallocated = PETSC_TRUE; 3403 PetscFunctionReturn(0); 3404 } 3405 3406 #undef __FUNCT__ 3407 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3408 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3409 { 3410 Mat mat; 3411 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3412 PetscErrorCode ierr; 3413 3414 PetscFunctionBegin; 3415 *newmat = 0; 3416 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3417 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3418 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3419 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3420 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3421 a = (Mat_MPIAIJ*)mat->data; 3422 3423 mat->factortype = matin->factortype; 3424 mat->rmap->bs = matin->rmap->bs; 3425 mat->cmap->bs = matin->cmap->bs; 3426 mat->assembled = PETSC_TRUE; 3427 mat->insertmode = NOT_SET_VALUES; 3428 mat->preallocated = PETSC_TRUE; 3429 3430 a->size = oldmat->size; 3431 a->rank = oldmat->rank; 3432 a->donotstash = oldmat->donotstash; 3433 a->roworiented = oldmat->roworiented; 3434 a->rowindices = 0; 3435 a->rowvalues = 0; 3436 a->getrowactive = PETSC_FALSE; 3437 3438 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3439 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3440 3441 if (oldmat->colmap) { 3442 #if defined(PETSC_USE_CTABLE) 3443 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3444 #else 3445 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3446 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3447 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3448 #endif 3449 } else a->colmap = 0; 3450 if (oldmat->garray) { 3451 PetscInt len; 3452 len = oldmat->B->cmap->n; 3453 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3454 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3455 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3456 } else a->garray = 0; 3457 3458 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3459 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3460 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3461 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3462 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3463 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3464 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3465 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3466 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3467 *newmat = mat; 3468 PetscFunctionReturn(0); 3469 } 3470 3471 3472 3473 #undef __FUNCT__ 3474 #define __FUNCT__ "MatLoad_MPIAIJ" 3475 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3476 { 3477 PetscScalar *vals,*svals; 3478 MPI_Comm comm; 3479 PetscErrorCode ierr; 3480 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3481 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3482 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3483 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3484 PetscInt cend,cstart,n,*rowners,sizesset=1; 3485 int fd; 3486 PetscInt bs = 1; 3487 3488 PetscFunctionBegin; 3489 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3490 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3491 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3492 if (!rank) { 3493 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3494 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3495 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3496 } 3497 3498 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3499 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3500 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3501 3502 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3503 3504 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3505 M = header[1]; N = header[2]; 3506 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3507 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3508 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3509 3510 /* If global sizes are set, check if they are consistent with that given in the file */ 3511 if (sizesset) { 3512 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3513 } 3514 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); 3515 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); 3516 3517 /* determine ownership of all (block) rows */ 3518 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3519 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3520 else m = newMat->rmap->n; /* Set by user */ 3521 3522 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3523 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3524 3525 /* First process needs enough room for process with most rows */ 3526 if (!rank) { 3527 mmax = rowners[1]; 3528 for (i=2; i<=size; i++) { 3529 mmax = PetscMax(mmax, rowners[i]); 3530 } 3531 } else mmax = -1; /* unused, but compilers complain */ 3532 3533 rowners[0] = 0; 3534 for (i=2; i<=size; i++) { 3535 rowners[i] += rowners[i-1]; 3536 } 3537 rstart = rowners[rank]; 3538 rend = rowners[rank+1]; 3539 3540 /* distribute row lengths to all processors */ 3541 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3542 if (!rank) { 3543 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3544 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3545 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3546 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3547 for (j=0; j<m; j++) { 3548 procsnz[0] += ourlens[j]; 3549 } 3550 for (i=1; i<size; i++) { 3551 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3552 /* calculate the number of nonzeros on each processor */ 3553 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3554 procsnz[i] += rowlengths[j]; 3555 } 3556 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3557 } 3558 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3559 } else { 3560 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3561 } 3562 3563 if (!rank) { 3564 /* determine max buffer needed and allocate it */ 3565 maxnz = 0; 3566 for (i=0; i<size; i++) { 3567 maxnz = PetscMax(maxnz,procsnz[i]); 3568 } 3569 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3570 3571 /* read in my part of the matrix column indices */ 3572 nz = procsnz[0]; 3573 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3574 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3575 3576 /* read in every one elses and ship off */ 3577 for (i=1; i<size; i++) { 3578 nz = procsnz[i]; 3579 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3580 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3581 } 3582 ierr = PetscFree(cols);CHKERRQ(ierr); 3583 } else { 3584 /* determine buffer space needed for message */ 3585 nz = 0; 3586 for (i=0; i<m; i++) { 3587 nz += ourlens[i]; 3588 } 3589 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3590 3591 /* receive message of column indices*/ 3592 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3593 } 3594 3595 /* determine column ownership if matrix is not square */ 3596 if (N != M) { 3597 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3598 else n = newMat->cmap->n; 3599 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3600 cstart = cend - n; 3601 } else { 3602 cstart = rstart; 3603 cend = rend; 3604 n = cend - cstart; 3605 } 3606 3607 /* loop over local rows, determining number of off diagonal entries */ 3608 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3609 jj = 0; 3610 for (i=0; i<m; i++) { 3611 for (j=0; j<ourlens[i]; j++) { 3612 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3613 jj++; 3614 } 3615 } 3616 3617 for (i=0; i<m; i++) { 3618 ourlens[i] -= offlens[i]; 3619 } 3620 if (!sizesset) { 3621 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3622 } 3623 3624 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3625 3626 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3627 3628 for (i=0; i<m; i++) { 3629 ourlens[i] += offlens[i]; 3630 } 3631 3632 if (!rank) { 3633 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3634 3635 /* read in my part of the matrix numerical values */ 3636 nz = procsnz[0]; 3637 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3638 3639 /* insert into matrix */ 3640 jj = rstart; 3641 smycols = mycols; 3642 svals = vals; 3643 for (i=0; i<m; i++) { 3644 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3645 smycols += ourlens[i]; 3646 svals += ourlens[i]; 3647 jj++; 3648 } 3649 3650 /* read in other processors and ship out */ 3651 for (i=1; i<size; i++) { 3652 nz = procsnz[i]; 3653 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3654 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3655 } 3656 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3657 } else { 3658 /* receive numeric values */ 3659 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3660 3661 /* receive message of values*/ 3662 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3663 3664 /* insert into matrix */ 3665 jj = rstart; 3666 smycols = mycols; 3667 svals = vals; 3668 for (i=0; i<m; i++) { 3669 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3670 smycols += ourlens[i]; 3671 svals += ourlens[i]; 3672 jj++; 3673 } 3674 } 3675 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3676 ierr = PetscFree(vals);CHKERRQ(ierr); 3677 ierr = PetscFree(mycols);CHKERRQ(ierr); 3678 ierr = PetscFree(rowners);CHKERRQ(ierr); 3679 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3680 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3681 PetscFunctionReturn(0); 3682 } 3683 3684 #undef __FUNCT__ 3685 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3686 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3687 { 3688 PetscErrorCode ierr; 3689 IS iscol_local; 3690 PetscInt csize; 3691 3692 PetscFunctionBegin; 3693 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3694 if (call == MAT_REUSE_MATRIX) { 3695 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3696 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3697 } else { 3698 PetscInt cbs; 3699 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3700 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3701 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3702 } 3703 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3704 if (call == MAT_INITIAL_MATRIX) { 3705 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3706 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3707 } 3708 PetscFunctionReturn(0); 3709 } 3710 3711 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3712 #undef __FUNCT__ 3713 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3714 /* 3715 Not great since it makes two copies of the submatrix, first an SeqAIJ 3716 in local and then by concatenating the local matrices the end result. 3717 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3718 3719 Note: This requires a sequential iscol with all indices. 3720 */ 3721 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3722 { 3723 PetscErrorCode ierr; 3724 PetscMPIInt rank,size; 3725 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3726 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3727 PetscBool allcolumns, colflag; 3728 Mat M,Mreuse; 3729 MatScalar *vwork,*aa; 3730 MPI_Comm comm; 3731 Mat_SeqAIJ *aij; 3732 3733 PetscFunctionBegin; 3734 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3735 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3736 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3737 3738 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3739 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3740 if (colflag && ncol == mat->cmap->N) { 3741 allcolumns = PETSC_TRUE; 3742 } else { 3743 allcolumns = PETSC_FALSE; 3744 } 3745 if (call == MAT_REUSE_MATRIX) { 3746 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3747 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3748 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3749 } else { 3750 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3751 } 3752 3753 /* 3754 m - number of local rows 3755 n - number of columns (same on all processors) 3756 rstart - first row in new global matrix generated 3757 */ 3758 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3759 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3760 if (call == MAT_INITIAL_MATRIX) { 3761 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3762 ii = aij->i; 3763 jj = aij->j; 3764 3765 /* 3766 Determine the number of non-zeros in the diagonal and off-diagonal 3767 portions of the matrix in order to do correct preallocation 3768 */ 3769 3770 /* first get start and end of "diagonal" columns */ 3771 if (csize == PETSC_DECIDE) { 3772 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3773 if (mglobal == n) { /* square matrix */ 3774 nlocal = m; 3775 } else { 3776 nlocal = n/size + ((n % size) > rank); 3777 } 3778 } else { 3779 nlocal = csize; 3780 } 3781 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3782 rstart = rend - nlocal; 3783 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); 3784 3785 /* next, compute all the lengths */ 3786 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3787 olens = dlens + m; 3788 for (i=0; i<m; i++) { 3789 jend = ii[i+1] - ii[i]; 3790 olen = 0; 3791 dlen = 0; 3792 for (j=0; j<jend; j++) { 3793 if (*jj < rstart || *jj >= rend) olen++; 3794 else dlen++; 3795 jj++; 3796 } 3797 olens[i] = olen; 3798 dlens[i] = dlen; 3799 } 3800 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3801 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3802 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3803 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3804 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3805 ierr = PetscFree(dlens);CHKERRQ(ierr); 3806 } else { 3807 PetscInt ml,nl; 3808 3809 M = *newmat; 3810 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3811 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3812 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3813 /* 3814 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3815 rather than the slower MatSetValues(). 3816 */ 3817 M->was_assembled = PETSC_TRUE; 3818 M->assembled = PETSC_FALSE; 3819 } 3820 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3821 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3822 ii = aij->i; 3823 jj = aij->j; 3824 aa = aij->a; 3825 for (i=0; i<m; i++) { 3826 row = rstart + i; 3827 nz = ii[i+1] - ii[i]; 3828 cwork = jj; jj += nz; 3829 vwork = aa; aa += nz; 3830 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3831 } 3832 3833 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3834 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3835 *newmat = M; 3836 3837 /* save submatrix used in processor for next request */ 3838 if (call == MAT_INITIAL_MATRIX) { 3839 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3840 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3841 } 3842 PetscFunctionReturn(0); 3843 } 3844 3845 #undef __FUNCT__ 3846 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3847 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3848 { 3849 PetscInt m,cstart, cend,j,nnz,i,d; 3850 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3851 const PetscInt *JJ; 3852 PetscScalar *values; 3853 PetscErrorCode ierr; 3854 3855 PetscFunctionBegin; 3856 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3857 3858 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3859 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3860 m = B->rmap->n; 3861 cstart = B->cmap->rstart; 3862 cend = B->cmap->rend; 3863 rstart = B->rmap->rstart; 3864 3865 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3866 3867 #if defined(PETSC_USE_DEBUGGING) 3868 for (i=0; i<m; i++) { 3869 nnz = Ii[i+1]- Ii[i]; 3870 JJ = J + Ii[i]; 3871 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3872 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3873 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); 3874 } 3875 #endif 3876 3877 for (i=0; i<m; i++) { 3878 nnz = Ii[i+1]- Ii[i]; 3879 JJ = J + Ii[i]; 3880 nnz_max = PetscMax(nnz_max,nnz); 3881 d = 0; 3882 for (j=0; j<nnz; j++) { 3883 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3884 } 3885 d_nnz[i] = d; 3886 o_nnz[i] = nnz - d; 3887 } 3888 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3889 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3890 3891 if (v) values = (PetscScalar*)v; 3892 else { 3893 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3894 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3895 } 3896 3897 for (i=0; i<m; i++) { 3898 ii = i + rstart; 3899 nnz = Ii[i+1]- Ii[i]; 3900 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3901 } 3902 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3903 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3904 3905 if (!v) { 3906 ierr = PetscFree(values);CHKERRQ(ierr); 3907 } 3908 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3909 PetscFunctionReturn(0); 3910 } 3911 3912 #undef __FUNCT__ 3913 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3914 /*@ 3915 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3916 (the default parallel PETSc format). 3917 3918 Collective on MPI_Comm 3919 3920 Input Parameters: 3921 + B - the matrix 3922 . i - the indices into j for the start of each local row (starts with zero) 3923 . j - the column indices for each local row (starts with zero) 3924 - v - optional values in the matrix 3925 3926 Level: developer 3927 3928 Notes: 3929 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3930 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3931 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3932 3933 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3934 3935 The format which is used for the sparse matrix input, is equivalent to a 3936 row-major ordering.. i.e for the following matrix, the input data expected is 3937 as shown: 3938 3939 1 0 0 3940 2 0 3 P0 3941 ------- 3942 4 5 6 P1 3943 3944 Process0 [P0]: rows_owned=[0,1] 3945 i = {0,1,3} [size = nrow+1 = 2+1] 3946 j = {0,0,2} [size = nz = 6] 3947 v = {1,2,3} [size = nz = 6] 3948 3949 Process1 [P1]: rows_owned=[2] 3950 i = {0,3} [size = nrow+1 = 1+1] 3951 j = {0,1,2} [size = nz = 6] 3952 v = {4,5,6} [size = nz = 6] 3953 3954 .keywords: matrix, aij, compressed row, sparse, parallel 3955 3956 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3957 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3958 @*/ 3959 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3960 { 3961 PetscErrorCode ierr; 3962 3963 PetscFunctionBegin; 3964 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3965 PetscFunctionReturn(0); 3966 } 3967 3968 #undef __FUNCT__ 3969 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3970 /*@C 3971 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 3972 (the default parallel PETSc format). For good matrix assembly performance 3973 the user should preallocate the matrix storage by setting the parameters 3974 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 3975 performance can be increased by more than a factor of 50. 3976 3977 Collective on MPI_Comm 3978 3979 Input Parameters: 3980 + A - the matrix 3981 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 3982 (same value is used for all local rows) 3983 . d_nnz - array containing the number of nonzeros in the various rows of the 3984 DIAGONAL portion of the local submatrix (possibly different for each row) 3985 or NULL, if d_nz is used to specify the nonzero structure. 3986 The size of this array is equal to the number of local rows, i.e 'm'. 3987 For matrices that will be factored, you must leave room for (and set) 3988 the diagonal entry even if it is zero. 3989 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 3990 submatrix (same value is used for all local rows). 3991 - o_nnz - array containing the number of nonzeros in the various rows of the 3992 OFF-DIAGONAL portion of the local submatrix (possibly different for 3993 each row) or NULL, if o_nz is used to specify the nonzero 3994 structure. The size of this array is equal to the number 3995 of local rows, i.e 'm'. 3996 3997 If the *_nnz parameter is given then the *_nz parameter is ignored 3998 3999 The AIJ format (also called the Yale sparse matrix format or 4000 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4001 storage. The stored row and column indices begin with zero. 4002 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4003 4004 The parallel matrix is partitioned such that the first m0 rows belong to 4005 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4006 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4007 4008 The DIAGONAL portion of the local submatrix of a processor can be defined 4009 as the submatrix which is obtained by extraction the part corresponding to 4010 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4011 first row that belongs to the processor, r2 is the last row belonging to 4012 the this processor, and c1-c2 is range of indices of the local part of a 4013 vector suitable for applying the matrix to. This is an mxn matrix. In the 4014 common case of a square matrix, the row and column ranges are the same and 4015 the DIAGONAL part is also square. The remaining portion of the local 4016 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4017 4018 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4019 4020 You can call MatGetInfo() to get information on how effective the preallocation was; 4021 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4022 You can also run with the option -info and look for messages with the string 4023 malloc in them to see if additional memory allocation was needed. 4024 4025 Example usage: 4026 4027 Consider the following 8x8 matrix with 34 non-zero values, that is 4028 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4029 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4030 as follows: 4031 4032 .vb 4033 1 2 0 | 0 3 0 | 0 4 4034 Proc0 0 5 6 | 7 0 0 | 8 0 4035 9 0 10 | 11 0 0 | 12 0 4036 ------------------------------------- 4037 13 0 14 | 15 16 17 | 0 0 4038 Proc1 0 18 0 | 19 20 21 | 0 0 4039 0 0 0 | 22 23 0 | 24 0 4040 ------------------------------------- 4041 Proc2 25 26 27 | 0 0 28 | 29 0 4042 30 0 0 | 31 32 33 | 0 34 4043 .ve 4044 4045 This can be represented as a collection of submatrices as: 4046 4047 .vb 4048 A B C 4049 D E F 4050 G H I 4051 .ve 4052 4053 Where the submatrices A,B,C are owned by proc0, D,E,F are 4054 owned by proc1, G,H,I are owned by proc2. 4055 4056 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4057 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4058 The 'M','N' parameters are 8,8, and have the same values on all procs. 4059 4060 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4061 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4062 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4063 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4064 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4065 matrix, ans [DF] as another SeqAIJ matrix. 4066 4067 When d_nz, o_nz parameters are specified, d_nz storage elements are 4068 allocated for every row of the local diagonal submatrix, and o_nz 4069 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4070 One way to choose d_nz and o_nz is to use the max nonzerors per local 4071 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4072 In this case, the values of d_nz,o_nz are: 4073 .vb 4074 proc0 : dnz = 2, o_nz = 2 4075 proc1 : dnz = 3, o_nz = 2 4076 proc2 : dnz = 1, o_nz = 4 4077 .ve 4078 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4079 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4080 for proc3. i.e we are using 12+15+10=37 storage locations to store 4081 34 values. 4082 4083 When d_nnz, o_nnz parameters are specified, the storage is specified 4084 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4085 In the above case the values for d_nnz,o_nnz are: 4086 .vb 4087 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4088 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4089 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4090 .ve 4091 Here the space allocated is sum of all the above values i.e 34, and 4092 hence pre-allocation is perfect. 4093 4094 Level: intermediate 4095 4096 .keywords: matrix, aij, compressed row, sparse, parallel 4097 4098 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4099 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4100 @*/ 4101 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4102 { 4103 PetscErrorCode ierr; 4104 4105 PetscFunctionBegin; 4106 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4107 PetscValidType(B,1); 4108 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4109 PetscFunctionReturn(0); 4110 } 4111 4112 #undef __FUNCT__ 4113 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4114 /*@ 4115 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4116 CSR format the local rows. 4117 4118 Collective on MPI_Comm 4119 4120 Input Parameters: 4121 + comm - MPI communicator 4122 . m - number of local rows (Cannot be PETSC_DECIDE) 4123 . n - This value should be the same as the local size used in creating the 4124 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4125 calculated if N is given) For square matrices n is almost always m. 4126 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4127 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4128 . i - row indices 4129 . j - column indices 4130 - a - matrix values 4131 4132 Output Parameter: 4133 . mat - the matrix 4134 4135 Level: intermediate 4136 4137 Notes: 4138 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4139 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4140 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4141 4142 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4143 4144 The format which is used for the sparse matrix input, is equivalent to a 4145 row-major ordering.. i.e for the following matrix, the input data expected is 4146 as shown: 4147 4148 1 0 0 4149 2 0 3 P0 4150 ------- 4151 4 5 6 P1 4152 4153 Process0 [P0]: rows_owned=[0,1] 4154 i = {0,1,3} [size = nrow+1 = 2+1] 4155 j = {0,0,2} [size = nz = 6] 4156 v = {1,2,3} [size = nz = 6] 4157 4158 Process1 [P1]: rows_owned=[2] 4159 i = {0,3} [size = nrow+1 = 1+1] 4160 j = {0,1,2} [size = nz = 6] 4161 v = {4,5,6} [size = nz = 6] 4162 4163 .keywords: matrix, aij, compressed row, sparse, parallel 4164 4165 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4166 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4167 @*/ 4168 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4169 { 4170 PetscErrorCode ierr; 4171 4172 PetscFunctionBegin; 4173 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4174 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4175 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4176 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4177 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4178 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4179 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4180 PetscFunctionReturn(0); 4181 } 4182 4183 #undef __FUNCT__ 4184 #define __FUNCT__ "MatCreateAIJ" 4185 /*@C 4186 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4187 (the default parallel PETSc format). For good matrix assembly performance 4188 the user should preallocate the matrix storage by setting the parameters 4189 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4190 performance can be increased by more than a factor of 50. 4191 4192 Collective on MPI_Comm 4193 4194 Input Parameters: 4195 + comm - MPI communicator 4196 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4197 This value should be the same as the local size used in creating the 4198 y vector for the matrix-vector product y = Ax. 4199 . n - This value should be the same as the local size used in creating the 4200 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4201 calculated if N is given) For square matrices n is almost always m. 4202 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4203 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4204 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4205 (same value is used for all local rows) 4206 . d_nnz - array containing the number of nonzeros in the various rows of the 4207 DIAGONAL portion of the local submatrix (possibly different for each row) 4208 or NULL, if d_nz is used to specify the nonzero structure. 4209 The size of this array is equal to the number of local rows, i.e 'm'. 4210 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4211 submatrix (same value is used for all local rows). 4212 - o_nnz - array containing the number of nonzeros in the various rows of the 4213 OFF-DIAGONAL portion of the local submatrix (possibly different for 4214 each row) or NULL, if o_nz is used to specify the nonzero 4215 structure. The size of this array is equal to the number 4216 of local rows, i.e 'm'. 4217 4218 Output Parameter: 4219 . A - the matrix 4220 4221 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4222 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4223 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4224 4225 Notes: 4226 If the *_nnz parameter is given then the *_nz parameter is ignored 4227 4228 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4229 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4230 storage requirements for this matrix. 4231 4232 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4233 processor than it must be used on all processors that share the object for 4234 that argument. 4235 4236 The user MUST specify either the local or global matrix dimensions 4237 (possibly both). 4238 4239 The parallel matrix is partitioned across processors such that the 4240 first m0 rows belong to process 0, the next m1 rows belong to 4241 process 1, the next m2 rows belong to process 2 etc.. where 4242 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4243 values corresponding to [m x N] submatrix. 4244 4245 The columns are logically partitioned with the n0 columns belonging 4246 to 0th partition, the next n1 columns belonging to the next 4247 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4248 4249 The DIAGONAL portion of the local submatrix on any given processor 4250 is the submatrix corresponding to the rows and columns m,n 4251 corresponding to the given processor. i.e diagonal matrix on 4252 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4253 etc. The remaining portion of the local submatrix [m x (N-n)] 4254 constitute the OFF-DIAGONAL portion. The example below better 4255 illustrates this concept. 4256 4257 For a square global matrix we define each processor's diagonal portion 4258 to be its local rows and the corresponding columns (a square submatrix); 4259 each processor's off-diagonal portion encompasses the remainder of the 4260 local matrix (a rectangular submatrix). 4261 4262 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4263 4264 When calling this routine with a single process communicator, a matrix of 4265 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4266 type of communicator, use the construction mechanism: 4267 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4268 4269 By default, this format uses inodes (identical nodes) when possible. 4270 We search for consecutive rows with the same nonzero structure, thereby 4271 reusing matrix information to achieve increased efficiency. 4272 4273 Options Database Keys: 4274 + -mat_no_inode - Do not use inodes 4275 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4276 - -mat_aij_oneindex - Internally use indexing starting at 1 4277 rather than 0. Note that when calling MatSetValues(), 4278 the user still MUST index entries starting at 0! 4279 4280 4281 Example usage: 4282 4283 Consider the following 8x8 matrix with 34 non-zero values, that is 4284 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4285 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4286 as follows: 4287 4288 .vb 4289 1 2 0 | 0 3 0 | 0 4 4290 Proc0 0 5 6 | 7 0 0 | 8 0 4291 9 0 10 | 11 0 0 | 12 0 4292 ------------------------------------- 4293 13 0 14 | 15 16 17 | 0 0 4294 Proc1 0 18 0 | 19 20 21 | 0 0 4295 0 0 0 | 22 23 0 | 24 0 4296 ------------------------------------- 4297 Proc2 25 26 27 | 0 0 28 | 29 0 4298 30 0 0 | 31 32 33 | 0 34 4299 .ve 4300 4301 This can be represented as a collection of submatrices as: 4302 4303 .vb 4304 A B C 4305 D E F 4306 G H I 4307 .ve 4308 4309 Where the submatrices A,B,C are owned by proc0, D,E,F are 4310 owned by proc1, G,H,I are owned by proc2. 4311 4312 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4313 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4314 The 'M','N' parameters are 8,8, and have the same values on all procs. 4315 4316 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4317 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4318 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4319 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4320 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4321 matrix, ans [DF] as another SeqAIJ matrix. 4322 4323 When d_nz, o_nz parameters are specified, d_nz storage elements are 4324 allocated for every row of the local diagonal submatrix, and o_nz 4325 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4326 One way to choose d_nz and o_nz is to use the max nonzerors per local 4327 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4328 In this case, the values of d_nz,o_nz are: 4329 .vb 4330 proc0 : dnz = 2, o_nz = 2 4331 proc1 : dnz = 3, o_nz = 2 4332 proc2 : dnz = 1, o_nz = 4 4333 .ve 4334 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4335 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4336 for proc3. i.e we are using 12+15+10=37 storage locations to store 4337 34 values. 4338 4339 When d_nnz, o_nnz parameters are specified, the storage is specified 4340 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4341 In the above case the values for d_nnz,o_nnz are: 4342 .vb 4343 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4344 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4345 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4346 .ve 4347 Here the space allocated is sum of all the above values i.e 34, and 4348 hence pre-allocation is perfect. 4349 4350 Level: intermediate 4351 4352 .keywords: matrix, aij, compressed row, sparse, parallel 4353 4354 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4355 MPIAIJ, MatCreateMPIAIJWithArrays() 4356 @*/ 4357 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) 4358 { 4359 PetscErrorCode ierr; 4360 PetscMPIInt size; 4361 4362 PetscFunctionBegin; 4363 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4364 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4365 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4366 if (size > 1) { 4367 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4368 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4369 } else { 4370 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4371 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4372 } 4373 PetscFunctionReturn(0); 4374 } 4375 4376 #undef __FUNCT__ 4377 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4378 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4379 { 4380 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4381 4382 PetscFunctionBegin; 4383 *Ad = a->A; 4384 *Ao = a->B; 4385 *colmap = a->garray; 4386 PetscFunctionReturn(0); 4387 } 4388 4389 #undef __FUNCT__ 4390 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4391 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4392 { 4393 PetscErrorCode ierr; 4394 PetscInt i; 4395 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4396 4397 PetscFunctionBegin; 4398 if (coloring->ctype == IS_COLORING_GLOBAL) { 4399 ISColoringValue *allcolors,*colors; 4400 ISColoring ocoloring; 4401 4402 /* set coloring for diagonal portion */ 4403 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4404 4405 /* set coloring for off-diagonal portion */ 4406 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4407 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4408 for (i=0; i<a->B->cmap->n; i++) { 4409 colors[i] = allcolors[a->garray[i]]; 4410 } 4411 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4412 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4413 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4414 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4415 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4416 ISColoringValue *colors; 4417 PetscInt *larray; 4418 ISColoring ocoloring; 4419 4420 /* set coloring for diagonal portion */ 4421 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4422 for (i=0; i<a->A->cmap->n; i++) { 4423 larray[i] = i + A->cmap->rstart; 4424 } 4425 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4426 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4427 for (i=0; i<a->A->cmap->n; i++) { 4428 colors[i] = coloring->colors[larray[i]]; 4429 } 4430 ierr = PetscFree(larray);CHKERRQ(ierr); 4431 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4432 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4433 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4434 4435 /* set coloring for off-diagonal portion */ 4436 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4437 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4438 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4439 for (i=0; i<a->B->cmap->n; i++) { 4440 colors[i] = coloring->colors[larray[i]]; 4441 } 4442 ierr = PetscFree(larray);CHKERRQ(ierr); 4443 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4444 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4445 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4446 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4447 PetscFunctionReturn(0); 4448 } 4449 4450 #undef __FUNCT__ 4451 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4452 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4453 { 4454 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4455 PetscErrorCode ierr; 4456 4457 PetscFunctionBegin; 4458 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4459 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4460 PetscFunctionReturn(0); 4461 } 4462 4463 #undef __FUNCT__ 4464 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4465 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4466 { 4467 PetscErrorCode ierr; 4468 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4469 PetscInt *indx; 4470 4471 PetscFunctionBegin; 4472 /* This routine will ONLY return MPIAIJ type matrix */ 4473 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4474 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4475 if (n == PETSC_DECIDE) { 4476 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4477 } 4478 /* Check sum(n) = N */ 4479 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4480 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4481 4482 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4483 rstart -= m; 4484 4485 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4486 for (i=0; i<m; i++) { 4487 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4488 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4489 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4490 } 4491 4492 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4493 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4494 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4495 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4496 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4497 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4498 PetscFunctionReturn(0); 4499 } 4500 4501 #undef __FUNCT__ 4502 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4503 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4504 { 4505 PetscErrorCode ierr; 4506 PetscInt m,N,i,rstart,nnz,Ii; 4507 PetscInt *indx; 4508 PetscScalar *values; 4509 4510 PetscFunctionBegin; 4511 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4512 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4513 for (i=0; i<m; i++) { 4514 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4515 Ii = i + rstart; 4516 ierr = MatSetValues_MPIAIJ(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4517 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4518 } 4519 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4520 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4521 PetscFunctionReturn(0); 4522 } 4523 4524 #undef __FUNCT__ 4525 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4526 /*@ 4527 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4528 matrices from each processor 4529 4530 Collective on MPI_Comm 4531 4532 Input Parameters: 4533 + comm - the communicators the parallel matrix will live on 4534 . inmat - the input sequential matrices 4535 . n - number of local columns (or PETSC_DECIDE) 4536 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4537 4538 Output Parameter: 4539 . outmat - the parallel matrix generated 4540 4541 Level: advanced 4542 4543 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4544 4545 @*/ 4546 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4547 { 4548 PetscErrorCode ierr; 4549 4550 PetscFunctionBegin; 4551 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4552 if (scall == MAT_INITIAL_MATRIX) { 4553 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4554 } 4555 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4556 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4557 PetscFunctionReturn(0); 4558 } 4559 4560 #undef __FUNCT__ 4561 #define __FUNCT__ "MatFileSplit" 4562 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4563 { 4564 PetscErrorCode ierr; 4565 PetscMPIInt rank; 4566 PetscInt m,N,i,rstart,nnz; 4567 size_t len; 4568 const PetscInt *indx; 4569 PetscViewer out; 4570 char *name; 4571 Mat B; 4572 const PetscScalar *values; 4573 4574 PetscFunctionBegin; 4575 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4576 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4577 /* Should this be the type of the diagonal block of A? */ 4578 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4579 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4580 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4581 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4582 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4583 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4584 for (i=0; i<m; i++) { 4585 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4586 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4587 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4588 } 4589 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4590 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4591 4592 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4593 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4594 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4595 sprintf(name,"%s.%d",outfile,rank); 4596 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4597 ierr = PetscFree(name);CHKERRQ(ierr); 4598 ierr = MatView(B,out);CHKERRQ(ierr); 4599 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4600 ierr = MatDestroy(&B);CHKERRQ(ierr); 4601 PetscFunctionReturn(0); 4602 } 4603 4604 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4605 #undef __FUNCT__ 4606 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4607 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4608 { 4609 PetscErrorCode ierr; 4610 Mat_Merge_SeqsToMPI *merge; 4611 PetscContainer container; 4612 4613 PetscFunctionBegin; 4614 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4615 if (container) { 4616 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4617 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4618 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4619 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4620 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4621 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4622 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4623 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4624 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4625 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4626 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4627 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4628 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4629 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4630 ierr = PetscFree(merge);CHKERRQ(ierr); 4631 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4632 } 4633 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4634 PetscFunctionReturn(0); 4635 } 4636 4637 #include <../src/mat/utils/freespace.h> 4638 #include <petscbt.h> 4639 4640 #undef __FUNCT__ 4641 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4642 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4643 { 4644 PetscErrorCode ierr; 4645 MPI_Comm comm; 4646 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4647 PetscMPIInt size,rank,taga,*len_s; 4648 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4649 PetscInt proc,m; 4650 PetscInt **buf_ri,**buf_rj; 4651 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4652 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4653 MPI_Request *s_waits,*r_waits; 4654 MPI_Status *status; 4655 MatScalar *aa=a->a; 4656 MatScalar **abuf_r,*ba_i; 4657 Mat_Merge_SeqsToMPI *merge; 4658 PetscContainer container; 4659 4660 PetscFunctionBegin; 4661 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4662 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4663 4664 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4665 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4666 4667 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4668 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4669 4670 bi = merge->bi; 4671 bj = merge->bj; 4672 buf_ri = merge->buf_ri; 4673 buf_rj = merge->buf_rj; 4674 4675 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4676 owners = merge->rowmap->range; 4677 len_s = merge->len_s; 4678 4679 /* send and recv matrix values */ 4680 /*-----------------------------*/ 4681 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4682 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4683 4684 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4685 for (proc=0,k=0; proc<size; proc++) { 4686 if (!len_s[proc]) continue; 4687 i = owners[proc]; 4688 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4689 k++; 4690 } 4691 4692 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4693 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4694 ierr = PetscFree(status);CHKERRQ(ierr); 4695 4696 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4697 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4698 4699 /* insert mat values of mpimat */ 4700 /*----------------------------*/ 4701 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4702 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4703 4704 for (k=0; k<merge->nrecv; k++) { 4705 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4706 nrows = *(buf_ri_k[k]); 4707 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4708 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4709 } 4710 4711 /* set values of ba */ 4712 m = merge->rowmap->n; 4713 for (i=0; i<m; i++) { 4714 arow = owners[rank] + i; 4715 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4716 bnzi = bi[i+1] - bi[i]; 4717 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4718 4719 /* add local non-zero vals of this proc's seqmat into ba */ 4720 anzi = ai[arow+1] - ai[arow]; 4721 aj = a->j + ai[arow]; 4722 aa = a->a + ai[arow]; 4723 nextaj = 0; 4724 for (j=0; nextaj<anzi; j++) { 4725 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4726 ba_i[j] += aa[nextaj++]; 4727 } 4728 } 4729 4730 /* add received vals into ba */ 4731 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4732 /* i-th row */ 4733 if (i == *nextrow[k]) { 4734 anzi = *(nextai[k]+1) - *nextai[k]; 4735 aj = buf_rj[k] + *(nextai[k]); 4736 aa = abuf_r[k] + *(nextai[k]); 4737 nextaj = 0; 4738 for (j=0; nextaj<anzi; j++) { 4739 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4740 ba_i[j] += aa[nextaj++]; 4741 } 4742 } 4743 nextrow[k]++; nextai[k]++; 4744 } 4745 } 4746 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4747 } 4748 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4749 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4750 4751 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4752 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4753 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4754 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4755 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4756 PetscFunctionReturn(0); 4757 } 4758 4759 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4760 4761 #undef __FUNCT__ 4762 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4763 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4764 { 4765 PetscErrorCode ierr; 4766 Mat B_mpi; 4767 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4768 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4769 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4770 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4771 PetscInt len,proc,*dnz,*onz,bs,cbs; 4772 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4773 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4774 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4775 MPI_Status *status; 4776 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4777 PetscBT lnkbt; 4778 Mat_Merge_SeqsToMPI *merge; 4779 PetscContainer container; 4780 4781 PetscFunctionBegin; 4782 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4783 4784 /* make sure it is a PETSc comm */ 4785 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4786 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4787 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4788 4789 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4790 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4791 4792 /* determine row ownership */ 4793 /*---------------------------------------------------------*/ 4794 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4795 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4796 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4797 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4798 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4799 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4800 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4801 4802 m = merge->rowmap->n; 4803 owners = merge->rowmap->range; 4804 4805 /* determine the number of messages to send, their lengths */ 4806 /*---------------------------------------------------------*/ 4807 len_s = merge->len_s; 4808 4809 len = 0; /* length of buf_si[] */ 4810 merge->nsend = 0; 4811 for (proc=0; proc<size; proc++) { 4812 len_si[proc] = 0; 4813 if (proc == rank) { 4814 len_s[proc] = 0; 4815 } else { 4816 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4817 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4818 } 4819 if (len_s[proc]) { 4820 merge->nsend++; 4821 nrows = 0; 4822 for (i=owners[proc]; i<owners[proc+1]; i++) { 4823 if (ai[i+1] > ai[i]) nrows++; 4824 } 4825 len_si[proc] = 2*(nrows+1); 4826 len += len_si[proc]; 4827 } 4828 } 4829 4830 /* determine the number and length of messages to receive for ij-structure */ 4831 /*-------------------------------------------------------------------------*/ 4832 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4833 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4834 4835 /* post the Irecv of j-structure */ 4836 /*-------------------------------*/ 4837 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4838 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4839 4840 /* post the Isend of j-structure */ 4841 /*--------------------------------*/ 4842 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4843 4844 for (proc=0, k=0; proc<size; proc++) { 4845 if (!len_s[proc]) continue; 4846 i = owners[proc]; 4847 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4848 k++; 4849 } 4850 4851 /* receives and sends of j-structure are complete */ 4852 /*------------------------------------------------*/ 4853 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4854 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4855 4856 /* send and recv i-structure */ 4857 /*---------------------------*/ 4858 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4859 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4860 4861 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4862 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4863 for (proc=0,k=0; proc<size; proc++) { 4864 if (!len_s[proc]) continue; 4865 /* form outgoing message for i-structure: 4866 buf_si[0]: nrows to be sent 4867 [1:nrows]: row index (global) 4868 [nrows+1:2*nrows+1]: i-structure index 4869 */ 4870 /*-------------------------------------------*/ 4871 nrows = len_si[proc]/2 - 1; 4872 buf_si_i = buf_si + nrows+1; 4873 buf_si[0] = nrows; 4874 buf_si_i[0] = 0; 4875 nrows = 0; 4876 for (i=owners[proc]; i<owners[proc+1]; i++) { 4877 anzi = ai[i+1] - ai[i]; 4878 if (anzi) { 4879 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4880 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4881 nrows++; 4882 } 4883 } 4884 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4885 k++; 4886 buf_si += len_si[proc]; 4887 } 4888 4889 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4890 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4891 4892 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4893 for (i=0; i<merge->nrecv; i++) { 4894 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); 4895 } 4896 4897 ierr = PetscFree(len_si);CHKERRQ(ierr); 4898 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4899 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4900 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4901 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4902 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4903 ierr = PetscFree(status);CHKERRQ(ierr); 4904 4905 /* compute a local seq matrix in each processor */ 4906 /*----------------------------------------------*/ 4907 /* allocate bi array and free space for accumulating nonzero column info */ 4908 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4909 bi[0] = 0; 4910 4911 /* create and initialize a linked list */ 4912 nlnk = N+1; 4913 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4914 4915 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4916 len = ai[owners[rank+1]] - ai[owners[rank]]; 4917 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4918 4919 current_space = free_space; 4920 4921 /* determine symbolic info for each local row */ 4922 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4923 4924 for (k=0; k<merge->nrecv; k++) { 4925 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4926 nrows = *buf_ri_k[k]; 4927 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4928 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4929 } 4930 4931 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4932 len = 0; 4933 for (i=0; i<m; i++) { 4934 bnzi = 0; 4935 /* add local non-zero cols of this proc's seqmat into lnk */ 4936 arow = owners[rank] + i; 4937 anzi = ai[arow+1] - ai[arow]; 4938 aj = a->j + ai[arow]; 4939 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4940 bnzi += nlnk; 4941 /* add received col data into lnk */ 4942 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4943 if (i == *nextrow[k]) { /* i-th row */ 4944 anzi = *(nextai[k]+1) - *nextai[k]; 4945 aj = buf_rj[k] + *nextai[k]; 4946 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4947 bnzi += nlnk; 4948 nextrow[k]++; nextai[k]++; 4949 } 4950 } 4951 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4952 4953 /* if free space is not available, make more free space */ 4954 if (current_space->local_remaining<bnzi) { 4955 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4956 nspacedouble++; 4957 } 4958 /* copy data into free space, then initialize lnk */ 4959 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4960 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4961 4962 current_space->array += bnzi; 4963 current_space->local_used += bnzi; 4964 current_space->local_remaining -= bnzi; 4965 4966 bi[i+1] = bi[i] + bnzi; 4967 } 4968 4969 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4970 4971 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 4972 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 4973 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 4974 4975 /* create symbolic parallel matrix B_mpi */ 4976 /*---------------------------------------*/ 4977 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 4978 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 4979 if (n==PETSC_DECIDE) { 4980 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 4981 } else { 4982 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4983 } 4984 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 4985 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 4986 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 4987 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4988 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 4989 4990 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 4991 B_mpi->assembled = PETSC_FALSE; 4992 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 4993 merge->bi = bi; 4994 merge->bj = bj; 4995 merge->buf_ri = buf_ri; 4996 merge->buf_rj = buf_rj; 4997 merge->coi = NULL; 4998 merge->coj = NULL; 4999 merge->owners_co = NULL; 5000 5001 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5002 5003 /* attach the supporting struct to B_mpi for reuse */ 5004 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5005 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5006 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5007 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5008 *mpimat = B_mpi; 5009 5010 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5011 PetscFunctionReturn(0); 5012 } 5013 5014 #undef __FUNCT__ 5015 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5016 /*@C 5017 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5018 matrices from each processor 5019 5020 Collective on MPI_Comm 5021 5022 Input Parameters: 5023 + comm - the communicators the parallel matrix will live on 5024 . seqmat - the input sequential matrices 5025 . m - number of local rows (or PETSC_DECIDE) 5026 . n - number of local columns (or PETSC_DECIDE) 5027 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5028 5029 Output Parameter: 5030 . mpimat - the parallel matrix generated 5031 5032 Level: advanced 5033 5034 Notes: 5035 The dimensions of the sequential matrix in each processor MUST be the same. 5036 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5037 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5038 @*/ 5039 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5040 { 5041 PetscErrorCode ierr; 5042 PetscMPIInt size; 5043 5044 PetscFunctionBegin; 5045 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5046 if (size == 1) { 5047 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5048 if (scall == MAT_INITIAL_MATRIX) { 5049 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5050 } else { 5051 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5052 } 5053 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5054 PetscFunctionReturn(0); 5055 } 5056 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5057 if (scall == MAT_INITIAL_MATRIX) { 5058 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5059 } 5060 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5061 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5062 PetscFunctionReturn(0); 5063 } 5064 5065 #undef __FUNCT__ 5066 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5067 /*@ 5068 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5069 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5070 with MatGetSize() 5071 5072 Not Collective 5073 5074 Input Parameters: 5075 + A - the matrix 5076 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5077 5078 Output Parameter: 5079 . A_loc - the local sequential matrix generated 5080 5081 Level: developer 5082 5083 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5084 5085 @*/ 5086 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5087 { 5088 PetscErrorCode ierr; 5089 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5090 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5091 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5092 MatScalar *aa=a->a,*ba=b->a,*cam; 5093 PetscScalar *ca; 5094 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5095 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5096 PetscBool match; 5097 5098 PetscFunctionBegin; 5099 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5100 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5101 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5102 if (scall == MAT_INITIAL_MATRIX) { 5103 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5104 ci[0] = 0; 5105 for (i=0; i<am; i++) { 5106 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5107 } 5108 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5109 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5110 k = 0; 5111 for (i=0; i<am; i++) { 5112 ncols_o = bi[i+1] - bi[i]; 5113 ncols_d = ai[i+1] - ai[i]; 5114 /* off-diagonal portion of A */ 5115 for (jo=0; jo<ncols_o; jo++) { 5116 col = cmap[*bj]; 5117 if (col >= cstart) break; 5118 cj[k] = col; bj++; 5119 ca[k++] = *ba++; 5120 } 5121 /* diagonal portion of A */ 5122 for (j=0; j<ncols_d; j++) { 5123 cj[k] = cstart + *aj++; 5124 ca[k++] = *aa++; 5125 } 5126 /* off-diagonal portion of A */ 5127 for (j=jo; j<ncols_o; j++) { 5128 cj[k] = cmap[*bj++]; 5129 ca[k++] = *ba++; 5130 } 5131 } 5132 /* put together the new matrix */ 5133 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5134 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5135 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5136 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5137 mat->free_a = PETSC_TRUE; 5138 mat->free_ij = PETSC_TRUE; 5139 mat->nonew = 0; 5140 } else if (scall == MAT_REUSE_MATRIX) { 5141 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5142 ci = mat->i; cj = mat->j; cam = mat->a; 5143 for (i=0; i<am; i++) { 5144 /* off-diagonal portion of A */ 5145 ncols_o = bi[i+1] - bi[i]; 5146 for (jo=0; jo<ncols_o; jo++) { 5147 col = cmap[*bj]; 5148 if (col >= cstart) break; 5149 *cam++ = *ba++; bj++; 5150 } 5151 /* diagonal portion of A */ 5152 ncols_d = ai[i+1] - ai[i]; 5153 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5154 /* off-diagonal portion of A */ 5155 for (j=jo; j<ncols_o; j++) { 5156 *cam++ = *ba++; bj++; 5157 } 5158 } 5159 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5160 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5161 PetscFunctionReturn(0); 5162 } 5163 5164 #undef __FUNCT__ 5165 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5166 /*@C 5167 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5168 5169 Not Collective 5170 5171 Input Parameters: 5172 + A - the matrix 5173 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5174 - row, col - index sets of rows and columns to extract (or NULL) 5175 5176 Output Parameter: 5177 . A_loc - the local sequential matrix generated 5178 5179 Level: developer 5180 5181 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5182 5183 @*/ 5184 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5185 { 5186 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5187 PetscErrorCode ierr; 5188 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5189 IS isrowa,iscola; 5190 Mat *aloc; 5191 PetscBool match; 5192 5193 PetscFunctionBegin; 5194 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5195 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5196 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5197 if (!row) { 5198 start = A->rmap->rstart; end = A->rmap->rend; 5199 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5200 } else { 5201 isrowa = *row; 5202 } 5203 if (!col) { 5204 start = A->cmap->rstart; 5205 cmap = a->garray; 5206 nzA = a->A->cmap->n; 5207 nzB = a->B->cmap->n; 5208 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5209 ncols = 0; 5210 for (i=0; i<nzB; i++) { 5211 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5212 else break; 5213 } 5214 imark = i; 5215 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5216 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5217 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5218 } else { 5219 iscola = *col; 5220 } 5221 if (scall != MAT_INITIAL_MATRIX) { 5222 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5223 aloc[0] = *A_loc; 5224 } 5225 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5226 *A_loc = aloc[0]; 5227 ierr = PetscFree(aloc);CHKERRQ(ierr); 5228 if (!row) { 5229 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5230 } 5231 if (!col) { 5232 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5233 } 5234 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5235 PetscFunctionReturn(0); 5236 } 5237 5238 #undef __FUNCT__ 5239 #define __FUNCT__ "MatGetBrowsOfAcols" 5240 /*@C 5241 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5242 5243 Collective on Mat 5244 5245 Input Parameters: 5246 + A,B - the matrices in mpiaij format 5247 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5248 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5249 5250 Output Parameter: 5251 + rowb, colb - index sets of rows and columns of B to extract 5252 - B_seq - the sequential matrix generated 5253 5254 Level: developer 5255 5256 @*/ 5257 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5258 { 5259 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5260 PetscErrorCode ierr; 5261 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5262 IS isrowb,iscolb; 5263 Mat *bseq=NULL; 5264 5265 PetscFunctionBegin; 5266 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5267 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); 5268 } 5269 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5270 5271 if (scall == MAT_INITIAL_MATRIX) { 5272 start = A->cmap->rstart; 5273 cmap = a->garray; 5274 nzA = a->A->cmap->n; 5275 nzB = a->B->cmap->n; 5276 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5277 ncols = 0; 5278 for (i=0; i<nzB; i++) { /* row < local row index */ 5279 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5280 else break; 5281 } 5282 imark = i; 5283 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5284 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5285 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5286 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5287 } else { 5288 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5289 isrowb = *rowb; iscolb = *colb; 5290 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5291 bseq[0] = *B_seq; 5292 } 5293 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5294 *B_seq = bseq[0]; 5295 ierr = PetscFree(bseq);CHKERRQ(ierr); 5296 if (!rowb) { 5297 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5298 } else { 5299 *rowb = isrowb; 5300 } 5301 if (!colb) { 5302 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5303 } else { 5304 *colb = iscolb; 5305 } 5306 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5307 PetscFunctionReturn(0); 5308 } 5309 5310 #undef __FUNCT__ 5311 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5312 /* 5313 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5314 of the OFF-DIAGONAL portion of local A 5315 5316 Collective on Mat 5317 5318 Input Parameters: 5319 + A,B - the matrices in mpiaij format 5320 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5321 5322 Output Parameter: 5323 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5324 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5325 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5326 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5327 5328 Level: developer 5329 5330 */ 5331 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5332 { 5333 VecScatter_MPI_General *gen_to,*gen_from; 5334 PetscErrorCode ierr; 5335 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5336 Mat_SeqAIJ *b_oth; 5337 VecScatter ctx =a->Mvctx; 5338 MPI_Comm comm; 5339 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5340 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5341 PetscScalar *rvalues,*svalues; 5342 MatScalar *b_otha,*bufa,*bufA; 5343 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5344 MPI_Request *rwaits = NULL,*swaits = NULL; 5345 MPI_Status *sstatus,rstatus; 5346 PetscMPIInt jj; 5347 PetscInt *cols,sbs,rbs; 5348 PetscScalar *vals; 5349 5350 PetscFunctionBegin; 5351 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5352 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5353 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); 5354 } 5355 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5356 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5357 5358 gen_to = (VecScatter_MPI_General*)ctx->todata; 5359 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5360 rvalues = gen_from->values; /* holds the length of receiving row */ 5361 svalues = gen_to->values; /* holds the length of sending row */ 5362 nrecvs = gen_from->n; 5363 nsends = gen_to->n; 5364 5365 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5366 srow = gen_to->indices; /* local row index to be sent */ 5367 sstarts = gen_to->starts; 5368 sprocs = gen_to->procs; 5369 sstatus = gen_to->sstatus; 5370 sbs = gen_to->bs; 5371 rstarts = gen_from->starts; 5372 rprocs = gen_from->procs; 5373 rbs = gen_from->bs; 5374 5375 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5376 if (scall == MAT_INITIAL_MATRIX) { 5377 /* i-array */ 5378 /*---------*/ 5379 /* post receives */ 5380 for (i=0; i<nrecvs; i++) { 5381 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5382 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5383 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5384 } 5385 5386 /* pack the outgoing message */ 5387 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5388 5389 sstartsj[0] = 0; 5390 rstartsj[0] = 0; 5391 len = 0; /* total length of j or a array to be sent */ 5392 k = 0; 5393 for (i=0; i<nsends; i++) { 5394 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5395 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5396 for (j=0; j<nrows; j++) { 5397 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5398 for (l=0; l<sbs; l++) { 5399 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5400 5401 rowlen[j*sbs+l] = ncols; 5402 5403 len += ncols; 5404 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5405 } 5406 k++; 5407 } 5408 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5409 5410 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5411 } 5412 /* recvs and sends of i-array are completed */ 5413 i = nrecvs; 5414 while (i--) { 5415 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5416 } 5417 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5418 5419 /* allocate buffers for sending j and a arrays */ 5420 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5421 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5422 5423 /* create i-array of B_oth */ 5424 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5425 5426 b_othi[0] = 0; 5427 len = 0; /* total length of j or a array to be received */ 5428 k = 0; 5429 for (i=0; i<nrecvs; i++) { 5430 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5431 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5432 for (j=0; j<nrows; j++) { 5433 b_othi[k+1] = b_othi[k] + rowlen[j]; 5434 len += rowlen[j]; k++; 5435 } 5436 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5437 } 5438 5439 /* allocate space for j and a arrrays of B_oth */ 5440 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5441 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5442 5443 /* j-array */ 5444 /*---------*/ 5445 /* post receives of j-array */ 5446 for (i=0; i<nrecvs; i++) { 5447 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5448 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5449 } 5450 5451 /* pack the outgoing message j-array */ 5452 k = 0; 5453 for (i=0; i<nsends; i++) { 5454 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5455 bufJ = bufj+sstartsj[i]; 5456 for (j=0; j<nrows; j++) { 5457 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5458 for (ll=0; ll<sbs; ll++) { 5459 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5460 for (l=0; l<ncols; l++) { 5461 *bufJ++ = cols[l]; 5462 } 5463 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5464 } 5465 } 5466 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5467 } 5468 5469 /* recvs and sends of j-array are completed */ 5470 i = nrecvs; 5471 while (i--) { 5472 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5473 } 5474 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5475 } else if (scall == MAT_REUSE_MATRIX) { 5476 sstartsj = *startsj_s; 5477 rstartsj = *startsj_r; 5478 bufa = *bufa_ptr; 5479 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5480 b_otha = b_oth->a; 5481 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5482 5483 /* a-array */ 5484 /*---------*/ 5485 /* post receives of a-array */ 5486 for (i=0; i<nrecvs; i++) { 5487 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5488 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5489 } 5490 5491 /* pack the outgoing message a-array */ 5492 k = 0; 5493 for (i=0; i<nsends; i++) { 5494 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5495 bufA = bufa+sstartsj[i]; 5496 for (j=0; j<nrows; j++) { 5497 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5498 for (ll=0; ll<sbs; ll++) { 5499 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5500 for (l=0; l<ncols; l++) { 5501 *bufA++ = vals[l]; 5502 } 5503 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5504 } 5505 } 5506 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5507 } 5508 /* recvs and sends of a-array are completed */ 5509 i = nrecvs; 5510 while (i--) { 5511 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5512 } 5513 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5514 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5515 5516 if (scall == MAT_INITIAL_MATRIX) { 5517 /* put together the new matrix */ 5518 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5519 5520 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5521 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5522 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5523 b_oth->free_a = PETSC_TRUE; 5524 b_oth->free_ij = PETSC_TRUE; 5525 b_oth->nonew = 0; 5526 5527 ierr = PetscFree(bufj);CHKERRQ(ierr); 5528 if (!startsj_s || !bufa_ptr) { 5529 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5530 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5531 } else { 5532 *startsj_s = sstartsj; 5533 *startsj_r = rstartsj; 5534 *bufa_ptr = bufa; 5535 } 5536 } 5537 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5538 PetscFunctionReturn(0); 5539 } 5540 5541 #undef __FUNCT__ 5542 #define __FUNCT__ "MatGetCommunicationStructs" 5543 /*@C 5544 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5545 5546 Not Collective 5547 5548 Input Parameters: 5549 . A - The matrix in mpiaij format 5550 5551 Output Parameter: 5552 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5553 . colmap - A map from global column index to local index into lvec 5554 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5555 5556 Level: developer 5557 5558 @*/ 5559 #if defined(PETSC_USE_CTABLE) 5560 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5561 #else 5562 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5563 #endif 5564 { 5565 Mat_MPIAIJ *a; 5566 5567 PetscFunctionBegin; 5568 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5569 PetscValidPointer(lvec, 2); 5570 PetscValidPointer(colmap, 3); 5571 PetscValidPointer(multScatter, 4); 5572 a = (Mat_MPIAIJ*) A->data; 5573 if (lvec) *lvec = a->lvec; 5574 if (colmap) *colmap = a->colmap; 5575 if (multScatter) *multScatter = a->Mvctx; 5576 PetscFunctionReturn(0); 5577 } 5578 5579 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5580 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5581 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5582 5583 #undef __FUNCT__ 5584 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5585 /* 5586 Computes (B'*A')' since computing B*A directly is untenable 5587 5588 n p p 5589 ( ) ( ) ( ) 5590 m ( A ) * n ( B ) = m ( C ) 5591 ( ) ( ) ( ) 5592 5593 */ 5594 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5595 { 5596 PetscErrorCode ierr; 5597 Mat At,Bt,Ct; 5598 5599 PetscFunctionBegin; 5600 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5601 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5602 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5603 ierr = MatDestroy(&At);CHKERRQ(ierr); 5604 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5605 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5606 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5607 PetscFunctionReturn(0); 5608 } 5609 5610 #undef __FUNCT__ 5611 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5612 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5613 { 5614 PetscErrorCode ierr; 5615 PetscInt m=A->rmap->n,n=B->cmap->n; 5616 Mat Cmat; 5617 5618 PetscFunctionBegin; 5619 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); 5620 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5621 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5622 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5623 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5624 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5625 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5626 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5627 5628 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5629 5630 *C = Cmat; 5631 PetscFunctionReturn(0); 5632 } 5633 5634 /* ----------------------------------------------------------------*/ 5635 #undef __FUNCT__ 5636 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5637 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5638 { 5639 PetscErrorCode ierr; 5640 5641 PetscFunctionBegin; 5642 if (scall == MAT_INITIAL_MATRIX) { 5643 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5644 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5645 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5646 } 5647 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5648 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5649 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5650 PetscFunctionReturn(0); 5651 } 5652 5653 #if defined(PETSC_HAVE_MUMPS) 5654 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5655 #endif 5656 #if defined(PETSC_HAVE_PASTIX) 5657 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5658 #endif 5659 #if defined(PETSC_HAVE_SUPERLU_DIST) 5660 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5661 #endif 5662 #if defined(PETSC_HAVE_CLIQUE) 5663 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5664 #endif 5665 5666 /*MC 5667 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5668 5669 Options Database Keys: 5670 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5671 5672 Level: beginner 5673 5674 .seealso: MatCreateAIJ() 5675 M*/ 5676 5677 #undef __FUNCT__ 5678 #define __FUNCT__ "MatCreate_MPIAIJ" 5679 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5680 { 5681 Mat_MPIAIJ *b; 5682 PetscErrorCode ierr; 5683 PetscMPIInt size; 5684 5685 PetscFunctionBegin; 5686 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5687 5688 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5689 B->data = (void*)b; 5690 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5691 B->assembled = PETSC_FALSE; 5692 B->insertmode = NOT_SET_VALUES; 5693 b->size = size; 5694 5695 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5696 5697 /* build cache for off array entries formed */ 5698 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5699 5700 b->donotstash = PETSC_FALSE; 5701 b->colmap = 0; 5702 b->garray = 0; 5703 b->roworiented = PETSC_TRUE; 5704 5705 /* stuff used for matrix vector multiply */ 5706 b->lvec = NULL; 5707 b->Mvctx = NULL; 5708 5709 /* stuff for MatGetRow() */ 5710 b->rowindices = 0; 5711 b->rowvalues = 0; 5712 b->getrowactive = PETSC_FALSE; 5713 5714 /* flexible pointer used in CUSP/CUSPARSE classes */ 5715 b->spptr = NULL; 5716 5717 #if defined(PETSC_HAVE_MUMPS) 5718 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5719 #endif 5720 #if defined(PETSC_HAVE_PASTIX) 5721 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5722 #endif 5723 #if defined(PETSC_HAVE_SUPERLU_DIST) 5724 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5725 #endif 5726 #if defined(PETSC_HAVE_CLIQUE) 5727 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5728 #endif 5729 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5730 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5731 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5732 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5733 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5734 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5735 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5736 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5737 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5738 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5739 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5740 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5741 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5742 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5743 PetscFunctionReturn(0); 5744 } 5745 5746 #undef __FUNCT__ 5747 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5748 /*@ 5749 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5750 and "off-diagonal" part of the matrix in CSR format. 5751 5752 Collective on MPI_Comm 5753 5754 Input Parameters: 5755 + comm - MPI communicator 5756 . m - number of local rows (Cannot be PETSC_DECIDE) 5757 . n - This value should be the same as the local size used in creating the 5758 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5759 calculated if N is given) For square matrices n is almost always m. 5760 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5761 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5762 . i - row indices for "diagonal" portion of matrix 5763 . j - column indices 5764 . a - matrix values 5765 . oi - row indices for "off-diagonal" portion of matrix 5766 . oj - column indices 5767 - oa - matrix values 5768 5769 Output Parameter: 5770 . mat - the matrix 5771 5772 Level: advanced 5773 5774 Notes: 5775 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5776 must free the arrays once the matrix has been destroyed and not before. 5777 5778 The i and j indices are 0 based 5779 5780 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5781 5782 This sets local rows and cannot be used to set off-processor values. 5783 5784 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5785 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5786 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5787 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5788 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5789 communication if it is known that only local entries will be set. 5790 5791 .keywords: matrix, aij, compressed row, sparse, parallel 5792 5793 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5794 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5795 @*/ 5796 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) 5797 { 5798 PetscErrorCode ierr; 5799 Mat_MPIAIJ *maij; 5800 5801 PetscFunctionBegin; 5802 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5803 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5804 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5805 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5806 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5807 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5808 maij = (Mat_MPIAIJ*) (*mat)->data; 5809 5810 (*mat)->preallocated = PETSC_TRUE; 5811 5812 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5813 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5814 5815 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5816 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5817 5818 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5819 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5820 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5821 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5822 5823 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5824 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5825 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5826 PetscFunctionReturn(0); 5827 } 5828 5829 /* 5830 Special version for direct calls from Fortran 5831 */ 5832 #include <petsc-private/fortranimpl.h> 5833 5834 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5835 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5836 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5837 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5838 #endif 5839 5840 /* Change these macros so can be used in void function */ 5841 #undef CHKERRQ 5842 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5843 #undef SETERRQ2 5844 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5845 #undef SETERRQ3 5846 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5847 #undef SETERRQ 5848 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5849 5850 #undef __FUNCT__ 5851 #define __FUNCT__ "matsetvaluesmpiaij_" 5852 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) 5853 { 5854 Mat mat = *mmat; 5855 PetscInt m = *mm, n = *mn; 5856 InsertMode addv = *maddv; 5857 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5858 PetscScalar value; 5859 PetscErrorCode ierr; 5860 5861 MatCheckPreallocated(mat,1); 5862 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5863 5864 #if defined(PETSC_USE_DEBUG) 5865 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5866 #endif 5867 { 5868 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5869 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5870 PetscBool roworiented = aij->roworiented; 5871 5872 /* Some Variables required in the macro */ 5873 Mat A = aij->A; 5874 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5875 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5876 MatScalar *aa = a->a; 5877 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5878 Mat B = aij->B; 5879 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5880 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5881 MatScalar *ba = b->a; 5882 5883 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5884 PetscInt nonew = a->nonew; 5885 MatScalar *ap1,*ap2; 5886 5887 PetscFunctionBegin; 5888 for (i=0; i<m; i++) { 5889 if (im[i] < 0) continue; 5890 #if defined(PETSC_USE_DEBUG) 5891 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); 5892 #endif 5893 if (im[i] >= rstart && im[i] < rend) { 5894 row = im[i] - rstart; 5895 lastcol1 = -1; 5896 rp1 = aj + ai[row]; 5897 ap1 = aa + ai[row]; 5898 rmax1 = aimax[row]; 5899 nrow1 = ailen[row]; 5900 low1 = 0; 5901 high1 = nrow1; 5902 lastcol2 = -1; 5903 rp2 = bj + bi[row]; 5904 ap2 = ba + bi[row]; 5905 rmax2 = bimax[row]; 5906 nrow2 = bilen[row]; 5907 low2 = 0; 5908 high2 = nrow2; 5909 5910 for (j=0; j<n; j++) { 5911 if (roworiented) value = v[i*n+j]; 5912 else value = v[i+j*m]; 5913 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5914 if (in[j] >= cstart && in[j] < cend) { 5915 col = in[j] - cstart; 5916 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5917 } else if (in[j] < 0) continue; 5918 #if defined(PETSC_USE_DEBUG) 5919 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); 5920 #endif 5921 else { 5922 if (mat->was_assembled) { 5923 if (!aij->colmap) { 5924 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5925 } 5926 #if defined(PETSC_USE_CTABLE) 5927 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5928 col--; 5929 #else 5930 col = aij->colmap[in[j]] - 1; 5931 #endif 5932 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5933 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5934 col = in[j]; 5935 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5936 B = aij->B; 5937 b = (Mat_SeqAIJ*)B->data; 5938 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5939 rp2 = bj + bi[row]; 5940 ap2 = ba + bi[row]; 5941 rmax2 = bimax[row]; 5942 nrow2 = bilen[row]; 5943 low2 = 0; 5944 high2 = nrow2; 5945 bm = aij->B->rmap->n; 5946 ba = b->a; 5947 } 5948 } else col = in[j]; 5949 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5950 } 5951 } 5952 } else if (!aij->donotstash) { 5953 if (roworiented) { 5954 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5955 } else { 5956 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5957 } 5958 } 5959 } 5960 } 5961 PetscFunctionReturnVoid(); 5962 } 5963 5964