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((PetscObject)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((PetscObject)mat,(PetscObject)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 if (redund->matseq) { /* via MatGetSubMatrices() */ 2530 ierr = ISDestroy(&redund->isrow);CHKERRQ(ierr); 2531 ierr = ISDestroy(&redund->iscol);CHKERRQ(ierr); 2532 ierr = MatDestroy(&redund->matseq[0]);CHKERRQ(ierr); 2533 ierr = PetscFree(redund->matseq);CHKERRQ(ierr); 2534 } else { 2535 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2536 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2537 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2538 for (i=0; i<redund->nrecvs; i++) { 2539 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2540 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2541 } 2542 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2543 } 2544 2545 if (redund->psubcomm) { 2546 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2547 } 2548 ierr = redund->Destroy(A);CHKERRQ(ierr); 2549 ierr = PetscFree(redund);CHKERRQ(ierr); 2550 } 2551 PetscFunctionReturn(0); 2552 } 2553 2554 #undef __FUNCT__ 2555 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_interlaced" 2556 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm; 2560 PetscErrorCode ierr; 2561 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2562 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2563 PetscInt *rowrange = mat->rmap->range; 2564 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2565 Mat A = aij->A,B=aij->B,C=*matredundant; 2566 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2567 PetscScalar *sbuf_a; 2568 PetscInt nzlocal=a->nz+b->nz; 2569 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2570 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2571 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2572 MatScalar *aworkA,*aworkB; 2573 PetscScalar *vals; 2574 PetscMPIInt tag1,tag2,tag3,imdex; 2575 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2576 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2577 MPI_Status recv_status,*send_status; 2578 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2579 PetscInt **rbuf_j=NULL; 2580 PetscScalar **rbuf_a=NULL; 2581 Mat_Redundant *redund =NULL; 2582 2583 PetscFunctionBegin; 2584 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2587 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2588 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2589 2590 if (reuse == MAT_REUSE_MATRIX) { 2591 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2592 if (subsize == 1) { 2593 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2594 redund = c->redundant; 2595 } else { 2596 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2597 redund = c->redundant; 2598 } 2599 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2600 2601 nsends = redund->nsends; 2602 nrecvs = redund->nrecvs; 2603 send_rank = redund->send_rank; 2604 recv_rank = redund->recv_rank; 2605 sbuf_nz = redund->sbuf_nz; 2606 rbuf_nz = redund->rbuf_nz; 2607 sbuf_j = redund->sbuf_j; 2608 sbuf_a = redund->sbuf_a; 2609 rbuf_j = redund->rbuf_j; 2610 rbuf_a = redund->rbuf_a; 2611 } 2612 2613 if (reuse == MAT_INITIAL_MATRIX) { 2614 PetscInt nleftover,np_subcomm; 2615 2616 /* get the destination processors' id send_rank, nsends and nrecvs */ 2617 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2618 2619 np_subcomm = size/nsubcomm; 2620 nleftover = size - nsubcomm*np_subcomm; 2621 2622 /* block of codes below is specific for INTERLACED */ 2623 /* ------------------------------------------------*/ 2624 nsends = 0; nrecvs = 0; 2625 for (i=0; i<size; i++) { 2626 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2627 send_rank[nsends++] = i; 2628 recv_rank[nrecvs++] = i; 2629 } 2630 } 2631 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2632 i = size-nleftover-1; 2633 j = 0; 2634 while (j < nsubcomm - nleftover) { 2635 send_rank[nsends++] = i; 2636 i--; j++; 2637 } 2638 } 2639 2640 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2641 for (i=0; i<nleftover; i++) { 2642 recv_rank[nrecvs++] = size-nleftover+i; 2643 } 2644 } 2645 /*----------------------------------------------*/ 2646 2647 /* allocate sbuf_j, sbuf_a */ 2648 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2649 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2650 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2651 /* 2652 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2653 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2654 */ 2655 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2656 2657 /* copy mat's local entries into the buffers */ 2658 if (reuse == MAT_INITIAL_MATRIX) { 2659 rownz_max = 0; 2660 rptr = sbuf_j; 2661 cols = sbuf_j + rend-rstart + 1; 2662 vals = sbuf_a; 2663 rptr[0] = 0; 2664 for (i=0; i<rend-rstart; i++) { 2665 row = i + rstart; 2666 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2667 ncols = nzA + nzB; 2668 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2669 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2670 /* load the column indices for this row into cols */ 2671 lwrite = 0; 2672 for (l=0; l<nzB; l++) { 2673 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2674 vals[lwrite] = aworkB[l]; 2675 cols[lwrite++] = ctmp; 2676 } 2677 } 2678 for (l=0; l<nzA; l++) { 2679 vals[lwrite] = aworkA[l]; 2680 cols[lwrite++] = cstart + cworkA[l]; 2681 } 2682 for (l=0; l<nzB; l++) { 2683 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2684 vals[lwrite] = aworkB[l]; 2685 cols[lwrite++] = ctmp; 2686 } 2687 } 2688 vals += ncols; 2689 cols += ncols; 2690 rptr[i+1] = rptr[i] + ncols; 2691 if (rownz_max < ncols) rownz_max = ncols; 2692 } 2693 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); 2694 } else { /* only copy matrix values into sbuf_a */ 2695 rptr = sbuf_j; 2696 vals = sbuf_a; 2697 rptr[0] = 0; 2698 for (i=0; i<rend-rstart; i++) { 2699 row = i + rstart; 2700 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2701 ncols = nzA + nzB; 2702 cworkB = b->j + b->i[i]; 2703 aworkA = a->a + a->i[i]; 2704 aworkB = b->a + b->i[i]; 2705 lwrite = 0; 2706 for (l=0; l<nzB; l++) { 2707 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2708 } 2709 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2710 for (l=0; l<nzB; l++) { 2711 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2712 } 2713 vals += ncols; 2714 rptr[i+1] = rptr[i] + ncols; 2715 } 2716 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2717 2718 /* send nzlocal to others, and recv other's nzlocal */ 2719 /*--------------------------------------------------*/ 2720 if (reuse == MAT_INITIAL_MATRIX) { 2721 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2722 2723 s_waits2 = s_waits3 + nsends; 2724 s_waits1 = s_waits2 + nsends; 2725 r_waits1 = s_waits1 + nsends; 2726 r_waits2 = r_waits1 + nrecvs; 2727 r_waits3 = r_waits2 + nrecvs; 2728 } else { 2729 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2730 2731 r_waits3 = s_waits3 + nsends; 2732 } 2733 2734 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2735 if (reuse == MAT_INITIAL_MATRIX) { 2736 /* get new tags to keep the communication clean */ 2737 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2738 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2739 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2740 2741 /* post receives of other's nzlocal */ 2742 for (i=0; i<nrecvs; i++) { 2743 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2744 } 2745 /* send nzlocal to others */ 2746 for (i=0; i<nsends; i++) { 2747 sbuf_nz[i] = nzlocal; 2748 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2749 } 2750 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2751 count = nrecvs; 2752 while (count) { 2753 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2754 2755 recv_rank[imdex] = recv_status.MPI_SOURCE; 2756 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2757 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2758 2759 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2760 2761 rbuf_nz[imdex] += i + 2; 2762 2763 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2764 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2765 count--; 2766 } 2767 /* wait on sends of nzlocal */ 2768 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2769 /* send mat->i,j to others, and recv from other's */ 2770 /*------------------------------------------------*/ 2771 for (i=0; i<nsends; i++) { 2772 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2773 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2774 } 2775 /* wait on receives of mat->i,j */ 2776 /*------------------------------*/ 2777 count = nrecvs; 2778 while (count) { 2779 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2780 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); 2781 count--; 2782 } 2783 /* wait on sends of mat->i,j */ 2784 /*---------------------------*/ 2785 if (nsends) { 2786 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2787 } 2788 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2789 2790 /* post receives, send and receive mat->a */ 2791 /*----------------------------------------*/ 2792 for (imdex=0; imdex<nrecvs; imdex++) { 2793 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2794 } 2795 for (i=0; i<nsends; i++) { 2796 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2797 } 2798 count = nrecvs; 2799 while (count) { 2800 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2801 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); 2802 count--; 2803 } 2804 if (nsends) { 2805 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2806 } 2807 2808 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2809 2810 /* create redundant matrix */ 2811 /*-------------------------*/ 2812 if (reuse == MAT_INITIAL_MATRIX) { 2813 const PetscInt *range; 2814 PetscInt rstart_sub,rend_sub,mloc_sub; 2815 2816 /* compute rownz_max for preallocation */ 2817 for (imdex=0; imdex<nrecvs; imdex++) { 2818 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2819 rptr = rbuf_j[imdex]; 2820 for (i=0; i<j; i++) { 2821 ncols = rptr[i+1] - rptr[i]; 2822 if (rownz_max < ncols) rownz_max = ncols; 2823 } 2824 } 2825 2826 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2827 2828 /* get local size of redundant matrix 2829 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2830 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2831 rstart_sub = range[nsubcomm*subrank]; 2832 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2833 rend_sub = range[nsubcomm*(subrank+1)]; 2834 } else { 2835 rend_sub = mat->rmap->N; 2836 } 2837 mloc_sub = rend_sub - rstart_sub; 2838 2839 if (M == N) { 2840 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2841 } else { /* non-square matrix */ 2842 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2843 } 2844 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2845 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2846 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2847 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2848 } else { 2849 C = *matredundant; 2850 } 2851 2852 /* insert local matrix entries */ 2853 rptr = sbuf_j; 2854 cols = sbuf_j + rend-rstart + 1; 2855 vals = sbuf_a; 2856 for (i=0; i<rend-rstart; i++) { 2857 row = i + rstart; 2858 ncols = rptr[i+1] - rptr[i]; 2859 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2860 vals += ncols; 2861 cols += ncols; 2862 } 2863 /* insert received matrix entries */ 2864 for (imdex=0; imdex<nrecvs; imdex++) { 2865 rstart = rowrange[recv_rank[imdex]]; 2866 rend = rowrange[recv_rank[imdex]+1]; 2867 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2868 rptr = rbuf_j[imdex]; 2869 cols = rbuf_j[imdex] + rend-rstart + 1; 2870 vals = rbuf_a[imdex]; 2871 for (i=0; i<rend-rstart; i++) { 2872 row = i + rstart; 2873 ncols = rptr[i+1] - rptr[i]; 2874 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2875 vals += ncols; 2876 cols += ncols; 2877 } 2878 } 2879 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2880 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2881 2882 if (reuse == MAT_INITIAL_MATRIX) { 2883 *matredundant = C; 2884 2885 /* create a supporting struct and attach it to C for reuse */ 2886 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2887 if (subsize == 1) { 2888 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2889 c->redundant = redund; 2890 } else { 2891 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2892 c->redundant = redund; 2893 } 2894 2895 redund->nzlocal = nzlocal; 2896 redund->nsends = nsends; 2897 redund->nrecvs = nrecvs; 2898 redund->send_rank = send_rank; 2899 redund->recv_rank = recv_rank; 2900 redund->sbuf_nz = sbuf_nz; 2901 redund->rbuf_nz = rbuf_nz; 2902 redund->sbuf_j = sbuf_j; 2903 redund->sbuf_a = sbuf_a; 2904 redund->rbuf_j = rbuf_j; 2905 redund->rbuf_a = rbuf_a; 2906 redund->psubcomm = NULL; 2907 2908 redund->Destroy = C->ops->destroy; 2909 C->ops->destroy = MatDestroy_MatRedundant; 2910 } 2911 PetscFunctionReturn(0); 2912 } 2913 2914 #undef __FUNCT__ 2915 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2916 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2917 { 2918 PetscErrorCode ierr; 2919 MPI_Comm comm; 2920 PetscMPIInt size,subsize; 2921 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2922 Mat_Redundant *redund=NULL; 2923 PetscSubcomm psubcomm=NULL; 2924 MPI_Comm subcomm_in=subcomm; 2925 Mat *matseq; 2926 IS isrow,iscol; 2927 2928 PetscFunctionBegin; 2929 if (subcomm_in == MPI_COMM_NULL) { /* user does not provide subcomm */ 2930 if (reuse == MAT_INITIAL_MATRIX) { 2931 /* create psubcomm, then get subcomm */ 2932 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2933 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2934 if (nsubcomm < 1 || nsubcomm > size) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"nsubcomm must between 1 and %D",size); 2935 2936 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2937 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2938 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2939 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2940 subcomm = psubcomm->comm; 2941 } else { /* retrieve psubcomm and subcomm */ 2942 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2943 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2944 if (subsize == 1) { 2945 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2946 redund = c->redundant; 2947 } else { 2948 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2949 redund = c->redundant; 2950 } 2951 psubcomm = redund->psubcomm; 2952 } 2953 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2954 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2955 if (reuse == MAT_INITIAL_MATRIX) { /* psubcomm is created in this routine, free it in MatDestroy_MatRedundant() */ 2956 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2957 if (subsize == 1) { 2958 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2959 c->redundant->psubcomm = psubcomm; 2960 } else { 2961 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2962 c->redundant->psubcomm = psubcomm ; 2963 } 2964 } 2965 PetscFunctionReturn(0); 2966 } 2967 } 2968 2969 /* use MPI subcomm via MatGetSubMatrices(); use subcomm_in or psubcomm->comm (psubcomm->type != INTERLACED) */ 2970 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2971 if (reuse == MAT_INITIAL_MATRIX) { 2972 /* create a local sequential matrix matseq[0] */ 2973 mloc_sub = PETSC_DECIDE; 2974 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2975 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2976 rstart = rend - mloc_sub; 2977 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2978 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2979 } else { /* reuse == MAT_REUSE_MATRIX */ 2980 if (subsize == 1) { 2981 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2982 redund = c->redundant; 2983 } else { 2984 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2985 redund = c->redundant; 2986 } 2987 2988 isrow = redund->isrow; 2989 iscol = redund->iscol; 2990 matseq = redund->matseq; 2991 } 2992 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2993 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2994 2995 if (reuse == MAT_INITIAL_MATRIX) { 2996 /* create a supporting struct and attach it to C for reuse */ 2997 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 2998 if (subsize == 1) { 2999 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3000 c->redundant = redund; 3001 } else { 3002 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3003 c->redundant = redund; 3004 } 3005 redund->isrow = isrow; 3006 redund->iscol = iscol; 3007 redund->matseq = matseq; 3008 redund->psubcomm = psubcomm; 3009 redund->Destroy = (*matredundant)->ops->destroy; 3010 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3011 } 3012 PetscFunctionReturn(0); 3013 } 3014 3015 #undef __FUNCT__ 3016 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3017 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3018 { 3019 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3020 PetscErrorCode ierr; 3021 PetscInt i,*idxb = 0; 3022 PetscScalar *va,*vb; 3023 Vec vtmp; 3024 3025 PetscFunctionBegin; 3026 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3027 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3028 if (idx) { 3029 for (i=0; i<A->rmap->n; i++) { 3030 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3031 } 3032 } 3033 3034 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3035 if (idx) { 3036 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3037 } 3038 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3039 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3040 3041 for (i=0; i<A->rmap->n; i++) { 3042 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3043 va[i] = vb[i]; 3044 if (idx) idx[i] = a->garray[idxb[i]]; 3045 } 3046 } 3047 3048 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3049 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3050 ierr = PetscFree(idxb);CHKERRQ(ierr); 3051 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3052 PetscFunctionReturn(0); 3053 } 3054 3055 #undef __FUNCT__ 3056 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3057 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3058 { 3059 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3060 PetscErrorCode ierr; 3061 PetscInt i,*idxb = 0; 3062 PetscScalar *va,*vb; 3063 Vec vtmp; 3064 3065 PetscFunctionBegin; 3066 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3067 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3068 if (idx) { 3069 for (i=0; i<A->cmap->n; i++) { 3070 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3071 } 3072 } 3073 3074 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3075 if (idx) { 3076 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3077 } 3078 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3079 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3080 3081 for (i=0; i<A->rmap->n; i++) { 3082 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3083 va[i] = vb[i]; 3084 if (idx) idx[i] = a->garray[idxb[i]]; 3085 } 3086 } 3087 3088 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3089 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3090 ierr = PetscFree(idxb);CHKERRQ(ierr); 3091 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3092 PetscFunctionReturn(0); 3093 } 3094 3095 #undef __FUNCT__ 3096 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3097 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3098 { 3099 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3100 PetscInt n = A->rmap->n; 3101 PetscInt cstart = A->cmap->rstart; 3102 PetscInt *cmap = mat->garray; 3103 PetscInt *diagIdx, *offdiagIdx; 3104 Vec diagV, offdiagV; 3105 PetscScalar *a, *diagA, *offdiagA; 3106 PetscInt r; 3107 PetscErrorCode ierr; 3108 3109 PetscFunctionBegin; 3110 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3111 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3112 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3113 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3114 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3115 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3116 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3117 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3118 for (r = 0; r < n; ++r) { 3119 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3120 a[r] = diagA[r]; 3121 idx[r] = cstart + diagIdx[r]; 3122 } else { 3123 a[r] = offdiagA[r]; 3124 idx[r] = cmap[offdiagIdx[r]]; 3125 } 3126 } 3127 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3128 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3129 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3130 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3131 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3132 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3133 PetscFunctionReturn(0); 3134 } 3135 3136 #undef __FUNCT__ 3137 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3138 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3139 { 3140 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3141 PetscInt n = A->rmap->n; 3142 PetscInt cstart = A->cmap->rstart; 3143 PetscInt *cmap = mat->garray; 3144 PetscInt *diagIdx, *offdiagIdx; 3145 Vec diagV, offdiagV; 3146 PetscScalar *a, *diagA, *offdiagA; 3147 PetscInt r; 3148 PetscErrorCode ierr; 3149 3150 PetscFunctionBegin; 3151 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3152 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3153 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3154 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3155 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3156 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3157 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3158 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3159 for (r = 0; r < n; ++r) { 3160 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3161 a[r] = diagA[r]; 3162 idx[r] = cstart + diagIdx[r]; 3163 } else { 3164 a[r] = offdiagA[r]; 3165 idx[r] = cmap[offdiagIdx[r]]; 3166 } 3167 } 3168 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3169 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3170 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3171 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3172 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3173 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3174 PetscFunctionReturn(0); 3175 } 3176 3177 #undef __FUNCT__ 3178 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3179 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3180 { 3181 PetscErrorCode ierr; 3182 Mat *dummy; 3183 3184 PetscFunctionBegin; 3185 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3186 *newmat = *dummy; 3187 ierr = PetscFree(dummy);CHKERRQ(ierr); 3188 PetscFunctionReturn(0); 3189 } 3190 3191 #undef __FUNCT__ 3192 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3193 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3194 { 3195 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3196 PetscErrorCode ierr; 3197 3198 PetscFunctionBegin; 3199 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3200 PetscFunctionReturn(0); 3201 } 3202 3203 #undef __FUNCT__ 3204 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3205 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3206 { 3207 PetscErrorCode ierr; 3208 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3209 3210 PetscFunctionBegin; 3211 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3212 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3213 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3214 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3215 PetscFunctionReturn(0); 3216 } 3217 3218 /* -------------------------------------------------------------------*/ 3219 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3220 MatGetRow_MPIAIJ, 3221 MatRestoreRow_MPIAIJ, 3222 MatMult_MPIAIJ, 3223 /* 4*/ MatMultAdd_MPIAIJ, 3224 MatMultTranspose_MPIAIJ, 3225 MatMultTransposeAdd_MPIAIJ, 3226 #if defined(PETSC_HAVE_PBGL) 3227 MatSolve_MPIAIJ, 3228 #else 3229 0, 3230 #endif 3231 0, 3232 0, 3233 /*10*/ 0, 3234 0, 3235 0, 3236 MatSOR_MPIAIJ, 3237 MatTranspose_MPIAIJ, 3238 /*15*/ MatGetInfo_MPIAIJ, 3239 MatEqual_MPIAIJ, 3240 MatGetDiagonal_MPIAIJ, 3241 MatDiagonalScale_MPIAIJ, 3242 MatNorm_MPIAIJ, 3243 /*20*/ MatAssemblyBegin_MPIAIJ, 3244 MatAssemblyEnd_MPIAIJ, 3245 MatSetOption_MPIAIJ, 3246 MatZeroEntries_MPIAIJ, 3247 /*24*/ MatZeroRows_MPIAIJ, 3248 0, 3249 #if defined(PETSC_HAVE_PBGL) 3250 0, 3251 #else 3252 0, 3253 #endif 3254 0, 3255 0, 3256 /*29*/ MatSetUp_MPIAIJ, 3257 #if defined(PETSC_HAVE_PBGL) 3258 0, 3259 #else 3260 0, 3261 #endif 3262 0, 3263 0, 3264 0, 3265 /*34*/ MatDuplicate_MPIAIJ, 3266 0, 3267 0, 3268 0, 3269 0, 3270 /*39*/ MatAXPY_MPIAIJ, 3271 MatGetSubMatrices_MPIAIJ, 3272 MatIncreaseOverlap_MPIAIJ, 3273 MatGetValues_MPIAIJ, 3274 MatCopy_MPIAIJ, 3275 /*44*/ MatGetRowMax_MPIAIJ, 3276 MatScale_MPIAIJ, 3277 0, 3278 0, 3279 MatZeroRowsColumns_MPIAIJ, 3280 /*49*/ MatSetRandom_MPIAIJ, 3281 0, 3282 0, 3283 0, 3284 0, 3285 /*54*/ MatFDColoringCreate_MPIXAIJ, 3286 0, 3287 MatSetUnfactored_MPIAIJ, 3288 MatPermute_MPIAIJ, 3289 0, 3290 /*59*/ MatGetSubMatrix_MPIAIJ, 3291 MatDestroy_MPIAIJ, 3292 MatView_MPIAIJ, 3293 0, 3294 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3295 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3296 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3297 0, 3298 0, 3299 0, 3300 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3301 MatGetRowMinAbs_MPIAIJ, 3302 0, 3303 MatSetColoring_MPIAIJ, 3304 0, 3305 MatSetValuesAdifor_MPIAIJ, 3306 /*75*/ MatFDColoringApply_AIJ, 3307 0, 3308 0, 3309 0, 3310 MatFindZeroDiagonals_MPIAIJ, 3311 /*80*/ 0, 3312 0, 3313 0, 3314 /*83*/ MatLoad_MPIAIJ, 3315 0, 3316 0, 3317 0, 3318 0, 3319 0, 3320 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3321 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3322 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3323 MatPtAP_MPIAIJ_MPIAIJ, 3324 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3325 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3326 0, 3327 0, 3328 0, 3329 0, 3330 /*99*/ 0, 3331 0, 3332 0, 3333 MatConjugate_MPIAIJ, 3334 0, 3335 /*104*/MatSetValuesRow_MPIAIJ, 3336 MatRealPart_MPIAIJ, 3337 MatImaginaryPart_MPIAIJ, 3338 0, 3339 0, 3340 /*109*/0, 3341 MatGetRedundantMatrix_MPIAIJ, 3342 MatGetRowMin_MPIAIJ, 3343 0, 3344 0, 3345 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3346 0, 3347 0, 3348 0, 3349 0, 3350 /*119*/0, 3351 0, 3352 0, 3353 0, 3354 MatGetMultiProcBlock_MPIAIJ, 3355 /*124*/MatFindNonzeroRows_MPIAIJ, 3356 MatGetColumnNorms_MPIAIJ, 3357 MatInvertBlockDiagonal_MPIAIJ, 3358 0, 3359 MatGetSubMatricesParallel_MPIAIJ, 3360 /*129*/0, 3361 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3362 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3363 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3364 0, 3365 /*134*/0, 3366 0, 3367 0, 3368 0, 3369 0, 3370 /*139*/0, 3371 0 3372 }; 3373 3374 /* ----------------------------------------------------------------------------------------*/ 3375 3376 #undef __FUNCT__ 3377 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3378 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3379 { 3380 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3381 PetscErrorCode ierr; 3382 3383 PetscFunctionBegin; 3384 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3385 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3386 PetscFunctionReturn(0); 3387 } 3388 3389 #undef __FUNCT__ 3390 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3391 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3392 { 3393 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3394 PetscErrorCode ierr; 3395 3396 PetscFunctionBegin; 3397 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3398 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3399 PetscFunctionReturn(0); 3400 } 3401 3402 #undef __FUNCT__ 3403 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3404 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3405 { 3406 Mat_MPIAIJ *b; 3407 PetscErrorCode ierr; 3408 3409 PetscFunctionBegin; 3410 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3411 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3412 b = (Mat_MPIAIJ*)B->data; 3413 3414 if (!B->preallocated) { 3415 /* Explicitly create 2 MATSEQAIJ matrices. */ 3416 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3417 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3418 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3419 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3420 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr); 3421 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3422 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3423 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3424 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3425 ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr); 3426 } 3427 3428 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3429 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3430 B->preallocated = PETSC_TRUE; 3431 PetscFunctionReturn(0); 3432 } 3433 3434 #undef __FUNCT__ 3435 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3436 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3437 { 3438 Mat mat; 3439 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3440 PetscErrorCode ierr; 3441 3442 PetscFunctionBegin; 3443 *newmat = 0; 3444 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3445 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3446 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3447 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3448 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3449 a = (Mat_MPIAIJ*)mat->data; 3450 3451 mat->factortype = matin->factortype; 3452 mat->rmap->bs = matin->rmap->bs; 3453 mat->cmap->bs = matin->cmap->bs; 3454 mat->assembled = PETSC_TRUE; 3455 mat->insertmode = NOT_SET_VALUES; 3456 mat->preallocated = PETSC_TRUE; 3457 3458 a->size = oldmat->size; 3459 a->rank = oldmat->rank; 3460 a->donotstash = oldmat->donotstash; 3461 a->roworiented = oldmat->roworiented; 3462 a->rowindices = 0; 3463 a->rowvalues = 0; 3464 a->getrowactive = PETSC_FALSE; 3465 3466 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3467 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3468 3469 if (oldmat->colmap) { 3470 #if defined(PETSC_USE_CTABLE) 3471 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3472 #else 3473 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3474 ierr = PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3475 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3476 #endif 3477 } else a->colmap = 0; 3478 if (oldmat->garray) { 3479 PetscInt len; 3480 len = oldmat->B->cmap->n; 3481 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3482 ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3483 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3484 } else a->garray = 0; 3485 3486 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3487 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr); 3488 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3489 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr); 3490 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3491 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 3492 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3493 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr); 3494 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3495 *newmat = mat; 3496 PetscFunctionReturn(0); 3497 } 3498 3499 3500 3501 #undef __FUNCT__ 3502 #define __FUNCT__ "MatLoad_MPIAIJ" 3503 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3504 { 3505 PetscScalar *vals,*svals; 3506 MPI_Comm comm; 3507 PetscErrorCode ierr; 3508 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3509 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3510 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3511 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3512 PetscInt cend,cstart,n,*rowners,sizesset=1; 3513 int fd; 3514 PetscInt bs = 1; 3515 3516 PetscFunctionBegin; 3517 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3518 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3519 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3520 if (!rank) { 3521 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3522 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3523 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3524 } 3525 3526 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3527 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3528 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3529 3530 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3531 3532 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3533 M = header[1]; N = header[2]; 3534 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3535 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3536 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3537 3538 /* If global sizes are set, check if they are consistent with that given in the file */ 3539 if (sizesset) { 3540 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3541 } 3542 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); 3543 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); 3544 3545 /* determine ownership of all (block) rows */ 3546 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3547 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3548 else m = newMat->rmap->n; /* Set by user */ 3549 3550 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3551 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3552 3553 /* First process needs enough room for process with most rows */ 3554 if (!rank) { 3555 mmax = rowners[1]; 3556 for (i=2; i<=size; i++) { 3557 mmax = PetscMax(mmax, rowners[i]); 3558 } 3559 } else mmax = -1; /* unused, but compilers complain */ 3560 3561 rowners[0] = 0; 3562 for (i=2; i<=size; i++) { 3563 rowners[i] += rowners[i-1]; 3564 } 3565 rstart = rowners[rank]; 3566 rend = rowners[rank+1]; 3567 3568 /* distribute row lengths to all processors */ 3569 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3570 if (!rank) { 3571 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3572 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3573 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3574 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3575 for (j=0; j<m; j++) { 3576 procsnz[0] += ourlens[j]; 3577 } 3578 for (i=1; i<size; i++) { 3579 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3580 /* calculate the number of nonzeros on each processor */ 3581 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3582 procsnz[i] += rowlengths[j]; 3583 } 3584 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3585 } 3586 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3587 } else { 3588 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3589 } 3590 3591 if (!rank) { 3592 /* determine max buffer needed and allocate it */ 3593 maxnz = 0; 3594 for (i=0; i<size; i++) { 3595 maxnz = PetscMax(maxnz,procsnz[i]); 3596 } 3597 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3598 3599 /* read in my part of the matrix column indices */ 3600 nz = procsnz[0]; 3601 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3602 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3603 3604 /* read in every one elses and ship off */ 3605 for (i=1; i<size; i++) { 3606 nz = procsnz[i]; 3607 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3608 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3609 } 3610 ierr = PetscFree(cols);CHKERRQ(ierr); 3611 } else { 3612 /* determine buffer space needed for message */ 3613 nz = 0; 3614 for (i=0; i<m; i++) { 3615 nz += ourlens[i]; 3616 } 3617 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3618 3619 /* receive message of column indices*/ 3620 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3621 } 3622 3623 /* determine column ownership if matrix is not square */ 3624 if (N != M) { 3625 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3626 else n = newMat->cmap->n; 3627 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3628 cstart = cend - n; 3629 } else { 3630 cstart = rstart; 3631 cend = rend; 3632 n = cend - cstart; 3633 } 3634 3635 /* loop over local rows, determining number of off diagonal entries */ 3636 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3637 jj = 0; 3638 for (i=0; i<m; i++) { 3639 for (j=0; j<ourlens[i]; j++) { 3640 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3641 jj++; 3642 } 3643 } 3644 3645 for (i=0; i<m; i++) { 3646 ourlens[i] -= offlens[i]; 3647 } 3648 if (!sizesset) { 3649 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3650 } 3651 3652 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3653 3654 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3655 3656 for (i=0; i<m; i++) { 3657 ourlens[i] += offlens[i]; 3658 } 3659 3660 if (!rank) { 3661 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3662 3663 /* read in my part of the matrix numerical values */ 3664 nz = procsnz[0]; 3665 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3666 3667 /* insert into matrix */ 3668 jj = rstart; 3669 smycols = mycols; 3670 svals = vals; 3671 for (i=0; i<m; i++) { 3672 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3673 smycols += ourlens[i]; 3674 svals += ourlens[i]; 3675 jj++; 3676 } 3677 3678 /* read in other processors and ship out */ 3679 for (i=1; i<size; i++) { 3680 nz = procsnz[i]; 3681 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3682 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3683 } 3684 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3685 } else { 3686 /* receive numeric values */ 3687 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3688 3689 /* receive message of values*/ 3690 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3691 3692 /* insert into matrix */ 3693 jj = rstart; 3694 smycols = mycols; 3695 svals = vals; 3696 for (i=0; i<m; i++) { 3697 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3698 smycols += ourlens[i]; 3699 svals += ourlens[i]; 3700 jj++; 3701 } 3702 } 3703 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3704 ierr = PetscFree(vals);CHKERRQ(ierr); 3705 ierr = PetscFree(mycols);CHKERRQ(ierr); 3706 ierr = PetscFree(rowners);CHKERRQ(ierr); 3707 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3708 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3709 PetscFunctionReturn(0); 3710 } 3711 3712 #undef __FUNCT__ 3713 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3714 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3715 { 3716 PetscErrorCode ierr; 3717 IS iscol_local; 3718 PetscInt csize; 3719 3720 PetscFunctionBegin; 3721 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3722 if (call == MAT_REUSE_MATRIX) { 3723 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3724 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3725 } else { 3726 PetscInt cbs; 3727 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3728 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3729 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3730 } 3731 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3732 if (call == MAT_INITIAL_MATRIX) { 3733 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3734 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3735 } 3736 PetscFunctionReturn(0); 3737 } 3738 3739 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3740 #undef __FUNCT__ 3741 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3742 /* 3743 Not great since it makes two copies of the submatrix, first an SeqAIJ 3744 in local and then by concatenating the local matrices the end result. 3745 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3746 3747 Note: This requires a sequential iscol with all indices. 3748 */ 3749 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3750 { 3751 PetscErrorCode ierr; 3752 PetscMPIInt rank,size; 3753 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3754 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3755 PetscBool allcolumns, colflag; 3756 Mat M,Mreuse; 3757 MatScalar *vwork,*aa; 3758 MPI_Comm comm; 3759 Mat_SeqAIJ *aij; 3760 3761 PetscFunctionBegin; 3762 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3763 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3764 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3765 3766 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3767 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3768 if (colflag && ncol == mat->cmap->N) { 3769 allcolumns = PETSC_TRUE; 3770 } else { 3771 allcolumns = PETSC_FALSE; 3772 } 3773 if (call == MAT_REUSE_MATRIX) { 3774 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3775 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3776 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3777 } else { 3778 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3779 } 3780 3781 /* 3782 m - number of local rows 3783 n - number of columns (same on all processors) 3784 rstart - first row in new global matrix generated 3785 */ 3786 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3787 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3788 if (call == MAT_INITIAL_MATRIX) { 3789 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3790 ii = aij->i; 3791 jj = aij->j; 3792 3793 /* 3794 Determine the number of non-zeros in the diagonal and off-diagonal 3795 portions of the matrix in order to do correct preallocation 3796 */ 3797 3798 /* first get start and end of "diagonal" columns */ 3799 if (csize == PETSC_DECIDE) { 3800 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3801 if (mglobal == n) { /* square matrix */ 3802 nlocal = m; 3803 } else { 3804 nlocal = n/size + ((n % size) > rank); 3805 } 3806 } else { 3807 nlocal = csize; 3808 } 3809 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3810 rstart = rend - nlocal; 3811 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); 3812 3813 /* next, compute all the lengths */ 3814 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3815 olens = dlens + m; 3816 for (i=0; i<m; i++) { 3817 jend = ii[i+1] - ii[i]; 3818 olen = 0; 3819 dlen = 0; 3820 for (j=0; j<jend; j++) { 3821 if (*jj < rstart || *jj >= rend) olen++; 3822 else dlen++; 3823 jj++; 3824 } 3825 olens[i] = olen; 3826 dlens[i] = dlen; 3827 } 3828 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3829 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3830 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3831 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3832 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3833 ierr = PetscFree(dlens);CHKERRQ(ierr); 3834 } else { 3835 PetscInt ml,nl; 3836 3837 M = *newmat; 3838 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3839 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3840 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3841 /* 3842 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3843 rather than the slower MatSetValues(). 3844 */ 3845 M->was_assembled = PETSC_TRUE; 3846 M->assembled = PETSC_FALSE; 3847 } 3848 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3849 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3850 ii = aij->i; 3851 jj = aij->j; 3852 aa = aij->a; 3853 for (i=0; i<m; i++) { 3854 row = rstart + i; 3855 nz = ii[i+1] - ii[i]; 3856 cwork = jj; jj += nz; 3857 vwork = aa; aa += nz; 3858 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3859 } 3860 3861 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3862 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3863 *newmat = M; 3864 3865 /* save submatrix used in processor for next request */ 3866 if (call == MAT_INITIAL_MATRIX) { 3867 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3868 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3869 } 3870 PetscFunctionReturn(0); 3871 } 3872 3873 #undef __FUNCT__ 3874 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3875 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3876 { 3877 PetscInt m,cstart, cend,j,nnz,i,d; 3878 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3879 const PetscInt *JJ; 3880 PetscScalar *values; 3881 PetscErrorCode ierr; 3882 3883 PetscFunctionBegin; 3884 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3885 3886 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3887 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3888 m = B->rmap->n; 3889 cstart = B->cmap->rstart; 3890 cend = B->cmap->rend; 3891 rstart = B->rmap->rstart; 3892 3893 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3894 3895 #if defined(PETSC_USE_DEBUGGING) 3896 for (i=0; i<m; i++) { 3897 nnz = Ii[i+1]- Ii[i]; 3898 JJ = J + Ii[i]; 3899 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3900 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3901 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); 3902 } 3903 #endif 3904 3905 for (i=0; i<m; i++) { 3906 nnz = Ii[i+1]- Ii[i]; 3907 JJ = J + Ii[i]; 3908 nnz_max = PetscMax(nnz_max,nnz); 3909 d = 0; 3910 for (j=0; j<nnz; j++) { 3911 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3912 } 3913 d_nnz[i] = d; 3914 o_nnz[i] = nnz - d; 3915 } 3916 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3917 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3918 3919 if (v) values = (PetscScalar*)v; 3920 else { 3921 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3922 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3923 } 3924 3925 for (i=0; i<m; i++) { 3926 ii = i + rstart; 3927 nnz = Ii[i+1]- Ii[i]; 3928 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3929 } 3930 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3931 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3932 3933 if (!v) { 3934 ierr = PetscFree(values);CHKERRQ(ierr); 3935 } 3936 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3937 PetscFunctionReturn(0); 3938 } 3939 3940 #undef __FUNCT__ 3941 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3942 /*@ 3943 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3944 (the default parallel PETSc format). 3945 3946 Collective on MPI_Comm 3947 3948 Input Parameters: 3949 + B - the matrix 3950 . i - the indices into j for the start of each local row (starts with zero) 3951 . j - the column indices for each local row (starts with zero) 3952 - v - optional values in the matrix 3953 3954 Level: developer 3955 3956 Notes: 3957 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3958 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3959 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3960 3961 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3962 3963 The format which is used for the sparse matrix input, is equivalent to a 3964 row-major ordering.. i.e for the following matrix, the input data expected is 3965 as shown: 3966 3967 1 0 0 3968 2 0 3 P0 3969 ------- 3970 4 5 6 P1 3971 3972 Process0 [P0]: rows_owned=[0,1] 3973 i = {0,1,3} [size = nrow+1 = 2+1] 3974 j = {0,0,2} [size = nz = 6] 3975 v = {1,2,3} [size = nz = 6] 3976 3977 Process1 [P1]: rows_owned=[2] 3978 i = {0,3} [size = nrow+1 = 1+1] 3979 j = {0,1,2} [size = nz = 6] 3980 v = {4,5,6} [size = nz = 6] 3981 3982 .keywords: matrix, aij, compressed row, sparse, parallel 3983 3984 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3985 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3986 @*/ 3987 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3988 { 3989 PetscErrorCode ierr; 3990 3991 PetscFunctionBegin; 3992 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3993 PetscFunctionReturn(0); 3994 } 3995 3996 #undef __FUNCT__ 3997 #define __FUNCT__ "MatMPIAIJSetPreallocation" 3998 /*@C 3999 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4000 (the default parallel PETSc format). For good matrix assembly performance 4001 the user should preallocate the matrix storage by setting the parameters 4002 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4003 performance can be increased by more than a factor of 50. 4004 4005 Collective on MPI_Comm 4006 4007 Input Parameters: 4008 + A - the matrix 4009 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4010 (same value is used for all local rows) 4011 . d_nnz - array containing the number of nonzeros in the various rows of the 4012 DIAGONAL portion of the local submatrix (possibly different for each row) 4013 or NULL, if d_nz is used to specify the nonzero structure. 4014 The size of this array is equal to the number of local rows, i.e 'm'. 4015 For matrices that will be factored, you must leave room for (and set) 4016 the diagonal entry even if it is zero. 4017 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4018 submatrix (same value is used for all local rows). 4019 - o_nnz - array containing the number of nonzeros in the various rows of the 4020 OFF-DIAGONAL portion of the local submatrix (possibly different for 4021 each row) or NULL, if o_nz is used to specify the nonzero 4022 structure. The size of this array is equal to the number 4023 of local rows, i.e 'm'. 4024 4025 If the *_nnz parameter is given then the *_nz parameter is ignored 4026 4027 The AIJ format (also called the Yale sparse matrix format or 4028 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4029 storage. The stored row and column indices begin with zero. 4030 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4031 4032 The parallel matrix is partitioned such that the first m0 rows belong to 4033 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4034 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4035 4036 The DIAGONAL portion of the local submatrix of a processor can be defined 4037 as the submatrix which is obtained by extraction the part corresponding to 4038 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4039 first row that belongs to the processor, r2 is the last row belonging to 4040 the this processor, and c1-c2 is range of indices of the local part of a 4041 vector suitable for applying the matrix to. This is an mxn matrix. In the 4042 common case of a square matrix, the row and column ranges are the same and 4043 the DIAGONAL part is also square. The remaining portion of the local 4044 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4045 4046 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4047 4048 You can call MatGetInfo() to get information on how effective the preallocation was; 4049 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4050 You can also run with the option -info and look for messages with the string 4051 malloc in them to see if additional memory allocation was needed. 4052 4053 Example usage: 4054 4055 Consider the following 8x8 matrix with 34 non-zero values, that is 4056 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4057 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4058 as follows: 4059 4060 .vb 4061 1 2 0 | 0 3 0 | 0 4 4062 Proc0 0 5 6 | 7 0 0 | 8 0 4063 9 0 10 | 11 0 0 | 12 0 4064 ------------------------------------- 4065 13 0 14 | 15 16 17 | 0 0 4066 Proc1 0 18 0 | 19 20 21 | 0 0 4067 0 0 0 | 22 23 0 | 24 0 4068 ------------------------------------- 4069 Proc2 25 26 27 | 0 0 28 | 29 0 4070 30 0 0 | 31 32 33 | 0 34 4071 .ve 4072 4073 This can be represented as a collection of submatrices as: 4074 4075 .vb 4076 A B C 4077 D E F 4078 G H I 4079 .ve 4080 4081 Where the submatrices A,B,C are owned by proc0, D,E,F are 4082 owned by proc1, G,H,I are owned by proc2. 4083 4084 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4085 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4086 The 'M','N' parameters are 8,8, and have the same values on all procs. 4087 4088 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4089 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4090 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4091 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4092 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4093 matrix, ans [DF] as another SeqAIJ matrix. 4094 4095 When d_nz, o_nz parameters are specified, d_nz storage elements are 4096 allocated for every row of the local diagonal submatrix, and o_nz 4097 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4098 One way to choose d_nz and o_nz is to use the max nonzerors per local 4099 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4100 In this case, the values of d_nz,o_nz are: 4101 .vb 4102 proc0 : dnz = 2, o_nz = 2 4103 proc1 : dnz = 3, o_nz = 2 4104 proc2 : dnz = 1, o_nz = 4 4105 .ve 4106 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4107 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4108 for proc3. i.e we are using 12+15+10=37 storage locations to store 4109 34 values. 4110 4111 When d_nnz, o_nnz parameters are specified, the storage is specified 4112 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4113 In the above case the values for d_nnz,o_nnz are: 4114 .vb 4115 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4116 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4117 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4118 .ve 4119 Here the space allocated is sum of all the above values i.e 34, and 4120 hence pre-allocation is perfect. 4121 4122 Level: intermediate 4123 4124 .keywords: matrix, aij, compressed row, sparse, parallel 4125 4126 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4127 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4128 @*/ 4129 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4130 { 4131 PetscErrorCode ierr; 4132 4133 PetscFunctionBegin; 4134 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4135 PetscValidType(B,1); 4136 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4137 PetscFunctionReturn(0); 4138 } 4139 4140 #undef __FUNCT__ 4141 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4142 /*@ 4143 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4144 CSR format the local rows. 4145 4146 Collective on MPI_Comm 4147 4148 Input Parameters: 4149 + comm - MPI communicator 4150 . m - number of local rows (Cannot be PETSC_DECIDE) 4151 . n - This value should be the same as the local size used in creating the 4152 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4153 calculated if N is given) For square matrices n is almost always m. 4154 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4155 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4156 . i - row indices 4157 . j - column indices 4158 - a - matrix values 4159 4160 Output Parameter: 4161 . mat - the matrix 4162 4163 Level: intermediate 4164 4165 Notes: 4166 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4167 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4168 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4169 4170 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4171 4172 The format which is used for the sparse matrix input, is equivalent to a 4173 row-major ordering.. i.e for the following matrix, the input data expected is 4174 as shown: 4175 4176 1 0 0 4177 2 0 3 P0 4178 ------- 4179 4 5 6 P1 4180 4181 Process0 [P0]: rows_owned=[0,1] 4182 i = {0,1,3} [size = nrow+1 = 2+1] 4183 j = {0,0,2} [size = nz = 6] 4184 v = {1,2,3} [size = nz = 6] 4185 4186 Process1 [P1]: rows_owned=[2] 4187 i = {0,3} [size = nrow+1 = 1+1] 4188 j = {0,1,2} [size = nz = 6] 4189 v = {4,5,6} [size = nz = 6] 4190 4191 .keywords: matrix, aij, compressed row, sparse, parallel 4192 4193 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4194 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4195 @*/ 4196 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4197 { 4198 PetscErrorCode ierr; 4199 4200 PetscFunctionBegin; 4201 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4202 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4203 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4204 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4205 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4206 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4207 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4208 PetscFunctionReturn(0); 4209 } 4210 4211 #undef __FUNCT__ 4212 #define __FUNCT__ "MatCreateAIJ" 4213 /*@C 4214 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4215 (the default parallel PETSc format). For good matrix assembly performance 4216 the user should preallocate the matrix storage by setting the parameters 4217 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4218 performance can be increased by more than a factor of 50. 4219 4220 Collective on MPI_Comm 4221 4222 Input Parameters: 4223 + comm - MPI communicator 4224 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4225 This value should be the same as the local size used in creating the 4226 y vector for the matrix-vector product y = Ax. 4227 . n - This value should be the same as the local size used in creating the 4228 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4229 calculated if N is given) For square matrices n is almost always m. 4230 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4231 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4232 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4233 (same value is used for all local rows) 4234 . d_nnz - array containing the number of nonzeros in the various rows of the 4235 DIAGONAL portion of the local submatrix (possibly different for each row) 4236 or NULL, if d_nz is used to specify the nonzero structure. 4237 The size of this array is equal to the number of local rows, i.e 'm'. 4238 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4239 submatrix (same value is used for all local rows). 4240 - o_nnz - array containing the number of nonzeros in the various rows of the 4241 OFF-DIAGONAL portion of the local submatrix (possibly different for 4242 each row) or NULL, if o_nz is used to specify the nonzero 4243 structure. The size of this array is equal to the number 4244 of local rows, i.e 'm'. 4245 4246 Output Parameter: 4247 . A - the matrix 4248 4249 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4250 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4251 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4252 4253 Notes: 4254 If the *_nnz parameter is given then the *_nz parameter is ignored 4255 4256 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4257 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4258 storage requirements for this matrix. 4259 4260 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4261 processor than it must be used on all processors that share the object for 4262 that argument. 4263 4264 The user MUST specify either the local or global matrix dimensions 4265 (possibly both). 4266 4267 The parallel matrix is partitioned across processors such that the 4268 first m0 rows belong to process 0, the next m1 rows belong to 4269 process 1, the next m2 rows belong to process 2 etc.. where 4270 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4271 values corresponding to [m x N] submatrix. 4272 4273 The columns are logically partitioned with the n0 columns belonging 4274 to 0th partition, the next n1 columns belonging to the next 4275 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4276 4277 The DIAGONAL portion of the local submatrix on any given processor 4278 is the submatrix corresponding to the rows and columns m,n 4279 corresponding to the given processor. i.e diagonal matrix on 4280 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4281 etc. The remaining portion of the local submatrix [m x (N-n)] 4282 constitute the OFF-DIAGONAL portion. The example below better 4283 illustrates this concept. 4284 4285 For a square global matrix we define each processor's diagonal portion 4286 to be its local rows and the corresponding columns (a square submatrix); 4287 each processor's off-diagonal portion encompasses the remainder of the 4288 local matrix (a rectangular submatrix). 4289 4290 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4291 4292 When calling this routine with a single process communicator, a matrix of 4293 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4294 type of communicator, use the construction mechanism: 4295 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4296 4297 By default, this format uses inodes (identical nodes) when possible. 4298 We search for consecutive rows with the same nonzero structure, thereby 4299 reusing matrix information to achieve increased efficiency. 4300 4301 Options Database Keys: 4302 + -mat_no_inode - Do not use inodes 4303 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4304 - -mat_aij_oneindex - Internally use indexing starting at 1 4305 rather than 0. Note that when calling MatSetValues(), 4306 the user still MUST index entries starting at 0! 4307 4308 4309 Example usage: 4310 4311 Consider the following 8x8 matrix with 34 non-zero values, that is 4312 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4313 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4314 as follows: 4315 4316 .vb 4317 1 2 0 | 0 3 0 | 0 4 4318 Proc0 0 5 6 | 7 0 0 | 8 0 4319 9 0 10 | 11 0 0 | 12 0 4320 ------------------------------------- 4321 13 0 14 | 15 16 17 | 0 0 4322 Proc1 0 18 0 | 19 20 21 | 0 0 4323 0 0 0 | 22 23 0 | 24 0 4324 ------------------------------------- 4325 Proc2 25 26 27 | 0 0 28 | 29 0 4326 30 0 0 | 31 32 33 | 0 34 4327 .ve 4328 4329 This can be represented as a collection of submatrices as: 4330 4331 .vb 4332 A B C 4333 D E F 4334 G H I 4335 .ve 4336 4337 Where the submatrices A,B,C are owned by proc0, D,E,F are 4338 owned by proc1, G,H,I are owned by proc2. 4339 4340 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4341 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4342 The 'M','N' parameters are 8,8, and have the same values on all procs. 4343 4344 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4345 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4346 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4347 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4348 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4349 matrix, ans [DF] as another SeqAIJ matrix. 4350 4351 When d_nz, o_nz parameters are specified, d_nz storage elements are 4352 allocated for every row of the local diagonal submatrix, and o_nz 4353 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4354 One way to choose d_nz and o_nz is to use the max nonzerors per local 4355 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4356 In this case, the values of d_nz,o_nz are: 4357 .vb 4358 proc0 : dnz = 2, o_nz = 2 4359 proc1 : dnz = 3, o_nz = 2 4360 proc2 : dnz = 1, o_nz = 4 4361 .ve 4362 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4363 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4364 for proc3. i.e we are using 12+15+10=37 storage locations to store 4365 34 values. 4366 4367 When d_nnz, o_nnz parameters are specified, the storage is specified 4368 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4369 In the above case the values for d_nnz,o_nnz are: 4370 .vb 4371 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4372 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4373 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4374 .ve 4375 Here the space allocated is sum of all the above values i.e 34, and 4376 hence pre-allocation is perfect. 4377 4378 Level: intermediate 4379 4380 .keywords: matrix, aij, compressed row, sparse, parallel 4381 4382 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4383 MPIAIJ, MatCreateMPIAIJWithArrays() 4384 @*/ 4385 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) 4386 { 4387 PetscErrorCode ierr; 4388 PetscMPIInt size; 4389 4390 PetscFunctionBegin; 4391 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4392 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4393 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4394 if (size > 1) { 4395 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4396 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4397 } else { 4398 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4399 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4400 } 4401 PetscFunctionReturn(0); 4402 } 4403 4404 #undef __FUNCT__ 4405 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4406 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4407 { 4408 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4409 4410 PetscFunctionBegin; 4411 *Ad = a->A; 4412 *Ao = a->B; 4413 *colmap = a->garray; 4414 PetscFunctionReturn(0); 4415 } 4416 4417 #undef __FUNCT__ 4418 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4419 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4420 { 4421 PetscErrorCode ierr; 4422 PetscInt i; 4423 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4424 4425 PetscFunctionBegin; 4426 if (coloring->ctype == IS_COLORING_GLOBAL) { 4427 ISColoringValue *allcolors,*colors; 4428 ISColoring ocoloring; 4429 4430 /* set coloring for diagonal portion */ 4431 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4432 4433 /* set coloring for off-diagonal portion */ 4434 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4435 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4436 for (i=0; i<a->B->cmap->n; i++) { 4437 colors[i] = allcolors[a->garray[i]]; 4438 } 4439 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4440 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4441 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4442 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4443 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4444 ISColoringValue *colors; 4445 PetscInt *larray; 4446 ISColoring ocoloring; 4447 4448 /* set coloring for diagonal portion */ 4449 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4450 for (i=0; i<a->A->cmap->n; i++) { 4451 larray[i] = i + A->cmap->rstart; 4452 } 4453 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4454 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4455 for (i=0; i<a->A->cmap->n; i++) { 4456 colors[i] = coloring->colors[larray[i]]; 4457 } 4458 ierr = PetscFree(larray);CHKERRQ(ierr); 4459 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4460 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4461 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4462 4463 /* set coloring for off-diagonal portion */ 4464 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4465 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4466 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4467 for (i=0; i<a->B->cmap->n; i++) { 4468 colors[i] = coloring->colors[larray[i]]; 4469 } 4470 ierr = PetscFree(larray);CHKERRQ(ierr); 4471 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4472 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4473 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4474 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4475 PetscFunctionReturn(0); 4476 } 4477 4478 #undef __FUNCT__ 4479 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4480 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4481 { 4482 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4483 PetscErrorCode ierr; 4484 4485 PetscFunctionBegin; 4486 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4487 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4488 PetscFunctionReturn(0); 4489 } 4490 4491 #undef __FUNCT__ 4492 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4493 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4494 { 4495 PetscErrorCode ierr; 4496 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4497 PetscInt *indx; 4498 4499 PetscFunctionBegin; 4500 /* This routine will ONLY return MPIAIJ type matrix */ 4501 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4502 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4503 if (n == PETSC_DECIDE) { 4504 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4505 } 4506 /* Check sum(n) = N */ 4507 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4508 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4509 4510 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4511 rstart -= m; 4512 4513 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4514 for (i=0; i<m; i++) { 4515 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4516 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4517 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4518 } 4519 4520 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4521 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4522 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4523 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4524 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4525 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4526 PetscFunctionReturn(0); 4527 } 4528 4529 #undef __FUNCT__ 4530 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4531 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4532 { 4533 PetscErrorCode ierr; 4534 PetscInt m,N,i,rstart,nnz,Ii; 4535 PetscInt *indx; 4536 PetscScalar *values; 4537 4538 PetscFunctionBegin; 4539 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4540 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4541 for (i=0; i<m; i++) { 4542 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4543 Ii = i + rstart; 4544 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4545 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4546 } 4547 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4548 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4549 PetscFunctionReturn(0); 4550 } 4551 4552 #undef __FUNCT__ 4553 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4554 /*@ 4555 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4556 matrices from each processor 4557 4558 Collective on MPI_Comm 4559 4560 Input Parameters: 4561 + comm - the communicators the parallel matrix will live on 4562 . inmat - the input sequential matrices 4563 . n - number of local columns (or PETSC_DECIDE) 4564 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4565 4566 Output Parameter: 4567 . outmat - the parallel matrix generated 4568 4569 Level: advanced 4570 4571 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4572 4573 @*/ 4574 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4575 { 4576 PetscErrorCode ierr; 4577 PetscMPIInt size; 4578 4579 PetscFunctionBegin; 4580 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4581 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4582 if (size == 1) { 4583 if (scall == MAT_INITIAL_MATRIX) { 4584 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4585 } else { 4586 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4587 } 4588 } else { 4589 if (scall == MAT_INITIAL_MATRIX) { 4590 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4591 } 4592 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4593 } 4594 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4595 PetscFunctionReturn(0); 4596 } 4597 4598 #undef __FUNCT__ 4599 #define __FUNCT__ "MatFileSplit" 4600 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4601 { 4602 PetscErrorCode ierr; 4603 PetscMPIInt rank; 4604 PetscInt m,N,i,rstart,nnz; 4605 size_t len; 4606 const PetscInt *indx; 4607 PetscViewer out; 4608 char *name; 4609 Mat B; 4610 const PetscScalar *values; 4611 4612 PetscFunctionBegin; 4613 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4614 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4615 /* Should this be the type of the diagonal block of A? */ 4616 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4617 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4618 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4619 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4620 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4621 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4622 for (i=0; i<m; i++) { 4623 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4624 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4625 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4626 } 4627 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4628 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4629 4630 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4631 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4632 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4633 sprintf(name,"%s.%d",outfile,rank); 4634 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4635 ierr = PetscFree(name);CHKERRQ(ierr); 4636 ierr = MatView(B,out);CHKERRQ(ierr); 4637 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4638 ierr = MatDestroy(&B);CHKERRQ(ierr); 4639 PetscFunctionReturn(0); 4640 } 4641 4642 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4643 #undef __FUNCT__ 4644 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4645 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4646 { 4647 PetscErrorCode ierr; 4648 Mat_Merge_SeqsToMPI *merge; 4649 PetscContainer container; 4650 4651 PetscFunctionBegin; 4652 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4653 if (container) { 4654 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4655 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4656 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4657 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4658 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4659 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4660 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4661 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4662 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4663 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4664 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4665 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4666 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4667 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4668 ierr = PetscFree(merge);CHKERRQ(ierr); 4669 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4670 } 4671 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4672 PetscFunctionReturn(0); 4673 } 4674 4675 #include <../src/mat/utils/freespace.h> 4676 #include <petscbt.h> 4677 4678 #undef __FUNCT__ 4679 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4680 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4681 { 4682 PetscErrorCode ierr; 4683 MPI_Comm comm; 4684 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4685 PetscMPIInt size,rank,taga,*len_s; 4686 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4687 PetscInt proc,m; 4688 PetscInt **buf_ri,**buf_rj; 4689 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4690 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4691 MPI_Request *s_waits,*r_waits; 4692 MPI_Status *status; 4693 MatScalar *aa=a->a; 4694 MatScalar **abuf_r,*ba_i; 4695 Mat_Merge_SeqsToMPI *merge; 4696 PetscContainer container; 4697 4698 PetscFunctionBegin; 4699 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4700 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4701 4702 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4703 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4704 4705 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4706 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4707 4708 bi = merge->bi; 4709 bj = merge->bj; 4710 buf_ri = merge->buf_ri; 4711 buf_rj = merge->buf_rj; 4712 4713 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4714 owners = merge->rowmap->range; 4715 len_s = merge->len_s; 4716 4717 /* send and recv matrix values */ 4718 /*-----------------------------*/ 4719 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4720 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4721 4722 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4723 for (proc=0,k=0; proc<size; proc++) { 4724 if (!len_s[proc]) continue; 4725 i = owners[proc]; 4726 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4727 k++; 4728 } 4729 4730 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4731 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4732 ierr = PetscFree(status);CHKERRQ(ierr); 4733 4734 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4735 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4736 4737 /* insert mat values of mpimat */ 4738 /*----------------------------*/ 4739 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4740 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4741 4742 for (k=0; k<merge->nrecv; k++) { 4743 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4744 nrows = *(buf_ri_k[k]); 4745 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4746 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4747 } 4748 4749 /* set values of ba */ 4750 m = merge->rowmap->n; 4751 for (i=0; i<m; i++) { 4752 arow = owners[rank] + i; 4753 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4754 bnzi = bi[i+1] - bi[i]; 4755 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4756 4757 /* add local non-zero vals of this proc's seqmat into ba */ 4758 anzi = ai[arow+1] - ai[arow]; 4759 aj = a->j + ai[arow]; 4760 aa = a->a + ai[arow]; 4761 nextaj = 0; 4762 for (j=0; nextaj<anzi; j++) { 4763 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4764 ba_i[j] += aa[nextaj++]; 4765 } 4766 } 4767 4768 /* add received vals into ba */ 4769 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4770 /* i-th row */ 4771 if (i == *nextrow[k]) { 4772 anzi = *(nextai[k]+1) - *nextai[k]; 4773 aj = buf_rj[k] + *(nextai[k]); 4774 aa = abuf_r[k] + *(nextai[k]); 4775 nextaj = 0; 4776 for (j=0; nextaj<anzi; j++) { 4777 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4778 ba_i[j] += aa[nextaj++]; 4779 } 4780 } 4781 nextrow[k]++; nextai[k]++; 4782 } 4783 } 4784 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4785 } 4786 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4787 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4788 4789 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4790 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4791 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4792 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4793 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4794 PetscFunctionReturn(0); 4795 } 4796 4797 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4798 4799 #undef __FUNCT__ 4800 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4801 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4802 { 4803 PetscErrorCode ierr; 4804 Mat B_mpi; 4805 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4806 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4807 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4808 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4809 PetscInt len,proc,*dnz,*onz,bs,cbs; 4810 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4811 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4812 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4813 MPI_Status *status; 4814 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4815 PetscBT lnkbt; 4816 Mat_Merge_SeqsToMPI *merge; 4817 PetscContainer container; 4818 4819 PetscFunctionBegin; 4820 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4821 4822 /* make sure it is a PETSc comm */ 4823 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4824 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4825 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4826 4827 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4828 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4829 4830 /* determine row ownership */ 4831 /*---------------------------------------------------------*/ 4832 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4833 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4834 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4835 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4836 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4837 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4838 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4839 4840 m = merge->rowmap->n; 4841 owners = merge->rowmap->range; 4842 4843 /* determine the number of messages to send, their lengths */ 4844 /*---------------------------------------------------------*/ 4845 len_s = merge->len_s; 4846 4847 len = 0; /* length of buf_si[] */ 4848 merge->nsend = 0; 4849 for (proc=0; proc<size; proc++) { 4850 len_si[proc] = 0; 4851 if (proc == rank) { 4852 len_s[proc] = 0; 4853 } else { 4854 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4855 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4856 } 4857 if (len_s[proc]) { 4858 merge->nsend++; 4859 nrows = 0; 4860 for (i=owners[proc]; i<owners[proc+1]; i++) { 4861 if (ai[i+1] > ai[i]) nrows++; 4862 } 4863 len_si[proc] = 2*(nrows+1); 4864 len += len_si[proc]; 4865 } 4866 } 4867 4868 /* determine the number and length of messages to receive for ij-structure */ 4869 /*-------------------------------------------------------------------------*/ 4870 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4871 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4872 4873 /* post the Irecv of j-structure */ 4874 /*-------------------------------*/ 4875 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4876 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4877 4878 /* post the Isend of j-structure */ 4879 /*--------------------------------*/ 4880 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4881 4882 for (proc=0, k=0; proc<size; proc++) { 4883 if (!len_s[proc]) continue; 4884 i = owners[proc]; 4885 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4886 k++; 4887 } 4888 4889 /* receives and sends of j-structure are complete */ 4890 /*------------------------------------------------*/ 4891 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4892 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4893 4894 /* send and recv i-structure */ 4895 /*---------------------------*/ 4896 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4897 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4898 4899 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4900 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4901 for (proc=0,k=0; proc<size; proc++) { 4902 if (!len_s[proc]) continue; 4903 /* form outgoing message for i-structure: 4904 buf_si[0]: nrows to be sent 4905 [1:nrows]: row index (global) 4906 [nrows+1:2*nrows+1]: i-structure index 4907 */ 4908 /*-------------------------------------------*/ 4909 nrows = len_si[proc]/2 - 1; 4910 buf_si_i = buf_si + nrows+1; 4911 buf_si[0] = nrows; 4912 buf_si_i[0] = 0; 4913 nrows = 0; 4914 for (i=owners[proc]; i<owners[proc+1]; i++) { 4915 anzi = ai[i+1] - ai[i]; 4916 if (anzi) { 4917 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4918 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4919 nrows++; 4920 } 4921 } 4922 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4923 k++; 4924 buf_si += len_si[proc]; 4925 } 4926 4927 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4928 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4929 4930 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4931 for (i=0; i<merge->nrecv; i++) { 4932 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); 4933 } 4934 4935 ierr = PetscFree(len_si);CHKERRQ(ierr); 4936 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4937 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4938 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4939 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4940 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4941 ierr = PetscFree(status);CHKERRQ(ierr); 4942 4943 /* compute a local seq matrix in each processor */ 4944 /*----------------------------------------------*/ 4945 /* allocate bi array and free space for accumulating nonzero column info */ 4946 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4947 bi[0] = 0; 4948 4949 /* create and initialize a linked list */ 4950 nlnk = N+1; 4951 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4952 4953 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4954 len = ai[owners[rank+1]] - ai[owners[rank]]; 4955 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4956 4957 current_space = free_space; 4958 4959 /* determine symbolic info for each local row */ 4960 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4961 4962 for (k=0; k<merge->nrecv; k++) { 4963 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4964 nrows = *buf_ri_k[k]; 4965 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4966 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4967 } 4968 4969 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4970 len = 0; 4971 for (i=0; i<m; i++) { 4972 bnzi = 0; 4973 /* add local non-zero cols of this proc's seqmat into lnk */ 4974 arow = owners[rank] + i; 4975 anzi = ai[arow+1] - ai[arow]; 4976 aj = a->j + ai[arow]; 4977 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4978 bnzi += nlnk; 4979 /* add received col data into lnk */ 4980 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4981 if (i == *nextrow[k]) { /* i-th row */ 4982 anzi = *(nextai[k]+1) - *nextai[k]; 4983 aj = buf_rj[k] + *nextai[k]; 4984 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4985 bnzi += nlnk; 4986 nextrow[k]++; nextai[k]++; 4987 } 4988 } 4989 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4990 4991 /* if free space is not available, make more free space */ 4992 if (current_space->local_remaining<bnzi) { 4993 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4994 nspacedouble++; 4995 } 4996 /* copy data into free space, then initialize lnk */ 4997 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 4998 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 4999 5000 current_space->array += bnzi; 5001 current_space->local_used += bnzi; 5002 current_space->local_remaining -= bnzi; 5003 5004 bi[i+1] = bi[i] + bnzi; 5005 } 5006 5007 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5008 5009 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5010 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5011 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5012 5013 /* create symbolic parallel matrix B_mpi */ 5014 /*---------------------------------------*/ 5015 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5016 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5017 if (n==PETSC_DECIDE) { 5018 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5019 } else { 5020 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5021 } 5022 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5023 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5024 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5025 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5026 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5027 5028 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5029 B_mpi->assembled = PETSC_FALSE; 5030 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5031 merge->bi = bi; 5032 merge->bj = bj; 5033 merge->buf_ri = buf_ri; 5034 merge->buf_rj = buf_rj; 5035 merge->coi = NULL; 5036 merge->coj = NULL; 5037 merge->owners_co = NULL; 5038 5039 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5040 5041 /* attach the supporting struct to B_mpi for reuse */ 5042 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5043 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5044 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5045 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5046 *mpimat = B_mpi; 5047 5048 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5049 PetscFunctionReturn(0); 5050 } 5051 5052 #undef __FUNCT__ 5053 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5054 /*@C 5055 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5056 matrices from each processor 5057 5058 Collective on MPI_Comm 5059 5060 Input Parameters: 5061 + comm - the communicators the parallel matrix will live on 5062 . seqmat - the input sequential matrices 5063 . m - number of local rows (or PETSC_DECIDE) 5064 . n - number of local columns (or PETSC_DECIDE) 5065 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5066 5067 Output Parameter: 5068 . mpimat - the parallel matrix generated 5069 5070 Level: advanced 5071 5072 Notes: 5073 The dimensions of the sequential matrix in each processor MUST be the same. 5074 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5075 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5076 @*/ 5077 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5078 { 5079 PetscErrorCode ierr; 5080 PetscMPIInt size; 5081 5082 PetscFunctionBegin; 5083 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5084 if (size == 1) { 5085 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5086 if (scall == MAT_INITIAL_MATRIX) { 5087 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5088 } else { 5089 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5090 } 5091 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5092 PetscFunctionReturn(0); 5093 } 5094 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5095 if (scall == MAT_INITIAL_MATRIX) { 5096 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5097 } 5098 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5099 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5100 PetscFunctionReturn(0); 5101 } 5102 5103 #undef __FUNCT__ 5104 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5105 /*@ 5106 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5107 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5108 with MatGetSize() 5109 5110 Not Collective 5111 5112 Input Parameters: 5113 + A - the matrix 5114 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5115 5116 Output Parameter: 5117 . A_loc - the local sequential matrix generated 5118 5119 Level: developer 5120 5121 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5122 5123 @*/ 5124 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5125 { 5126 PetscErrorCode ierr; 5127 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5128 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5129 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5130 MatScalar *aa=a->a,*ba=b->a,*cam; 5131 PetscScalar *ca; 5132 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5133 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5134 PetscBool match; 5135 5136 PetscFunctionBegin; 5137 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5138 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5139 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5140 if (scall == MAT_INITIAL_MATRIX) { 5141 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5142 ci[0] = 0; 5143 for (i=0; i<am; i++) { 5144 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5145 } 5146 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5147 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5148 k = 0; 5149 for (i=0; i<am; i++) { 5150 ncols_o = bi[i+1] - bi[i]; 5151 ncols_d = ai[i+1] - ai[i]; 5152 /* off-diagonal portion of A */ 5153 for (jo=0; jo<ncols_o; jo++) { 5154 col = cmap[*bj]; 5155 if (col >= cstart) break; 5156 cj[k] = col; bj++; 5157 ca[k++] = *ba++; 5158 } 5159 /* diagonal portion of A */ 5160 for (j=0; j<ncols_d; j++) { 5161 cj[k] = cstart + *aj++; 5162 ca[k++] = *aa++; 5163 } 5164 /* off-diagonal portion of A */ 5165 for (j=jo; j<ncols_o; j++) { 5166 cj[k] = cmap[*bj++]; 5167 ca[k++] = *ba++; 5168 } 5169 } 5170 /* put together the new matrix */ 5171 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5172 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5173 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5174 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5175 mat->free_a = PETSC_TRUE; 5176 mat->free_ij = PETSC_TRUE; 5177 mat->nonew = 0; 5178 } else if (scall == MAT_REUSE_MATRIX) { 5179 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5180 ci = mat->i; cj = mat->j; cam = mat->a; 5181 for (i=0; i<am; i++) { 5182 /* off-diagonal portion of A */ 5183 ncols_o = bi[i+1] - bi[i]; 5184 for (jo=0; jo<ncols_o; jo++) { 5185 col = cmap[*bj]; 5186 if (col >= cstart) break; 5187 *cam++ = *ba++; bj++; 5188 } 5189 /* diagonal portion of A */ 5190 ncols_d = ai[i+1] - ai[i]; 5191 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5192 /* off-diagonal portion of A */ 5193 for (j=jo; j<ncols_o; j++) { 5194 *cam++ = *ba++; bj++; 5195 } 5196 } 5197 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5198 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5199 PetscFunctionReturn(0); 5200 } 5201 5202 #undef __FUNCT__ 5203 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5204 /*@C 5205 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5206 5207 Not Collective 5208 5209 Input Parameters: 5210 + A - the matrix 5211 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5212 - row, col - index sets of rows and columns to extract (or NULL) 5213 5214 Output Parameter: 5215 . A_loc - the local sequential matrix generated 5216 5217 Level: developer 5218 5219 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5220 5221 @*/ 5222 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5223 { 5224 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5225 PetscErrorCode ierr; 5226 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5227 IS isrowa,iscola; 5228 Mat *aloc; 5229 PetscBool match; 5230 5231 PetscFunctionBegin; 5232 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5233 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5234 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5235 if (!row) { 5236 start = A->rmap->rstart; end = A->rmap->rend; 5237 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5238 } else { 5239 isrowa = *row; 5240 } 5241 if (!col) { 5242 start = A->cmap->rstart; 5243 cmap = a->garray; 5244 nzA = a->A->cmap->n; 5245 nzB = a->B->cmap->n; 5246 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5247 ncols = 0; 5248 for (i=0; i<nzB; i++) { 5249 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5250 else break; 5251 } 5252 imark = i; 5253 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5254 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5255 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5256 } else { 5257 iscola = *col; 5258 } 5259 if (scall != MAT_INITIAL_MATRIX) { 5260 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5261 aloc[0] = *A_loc; 5262 } 5263 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5264 *A_loc = aloc[0]; 5265 ierr = PetscFree(aloc);CHKERRQ(ierr); 5266 if (!row) { 5267 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5268 } 5269 if (!col) { 5270 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5271 } 5272 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5273 PetscFunctionReturn(0); 5274 } 5275 5276 #undef __FUNCT__ 5277 #define __FUNCT__ "MatGetBrowsOfAcols" 5278 /*@C 5279 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5280 5281 Collective on Mat 5282 5283 Input Parameters: 5284 + A,B - the matrices in mpiaij format 5285 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5286 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5287 5288 Output Parameter: 5289 + rowb, colb - index sets of rows and columns of B to extract 5290 - B_seq - the sequential matrix generated 5291 5292 Level: developer 5293 5294 @*/ 5295 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5296 { 5297 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5298 PetscErrorCode ierr; 5299 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5300 IS isrowb,iscolb; 5301 Mat *bseq=NULL; 5302 5303 PetscFunctionBegin; 5304 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5305 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); 5306 } 5307 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5308 5309 if (scall == MAT_INITIAL_MATRIX) { 5310 start = A->cmap->rstart; 5311 cmap = a->garray; 5312 nzA = a->A->cmap->n; 5313 nzB = a->B->cmap->n; 5314 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5315 ncols = 0; 5316 for (i=0; i<nzB; i++) { /* row < local row index */ 5317 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5318 else break; 5319 } 5320 imark = i; 5321 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5322 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5323 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5324 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5325 } else { 5326 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5327 isrowb = *rowb; iscolb = *colb; 5328 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5329 bseq[0] = *B_seq; 5330 } 5331 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5332 *B_seq = bseq[0]; 5333 ierr = PetscFree(bseq);CHKERRQ(ierr); 5334 if (!rowb) { 5335 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5336 } else { 5337 *rowb = isrowb; 5338 } 5339 if (!colb) { 5340 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5341 } else { 5342 *colb = iscolb; 5343 } 5344 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5345 PetscFunctionReturn(0); 5346 } 5347 5348 #undef __FUNCT__ 5349 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5350 /* 5351 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5352 of the OFF-DIAGONAL portion of local A 5353 5354 Collective on Mat 5355 5356 Input Parameters: 5357 + A,B - the matrices in mpiaij format 5358 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5359 5360 Output Parameter: 5361 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5362 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5363 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5364 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5365 5366 Level: developer 5367 5368 */ 5369 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5370 { 5371 VecScatter_MPI_General *gen_to,*gen_from; 5372 PetscErrorCode ierr; 5373 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5374 Mat_SeqAIJ *b_oth; 5375 VecScatter ctx =a->Mvctx; 5376 MPI_Comm comm; 5377 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5378 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5379 PetscScalar *rvalues,*svalues; 5380 MatScalar *b_otha,*bufa,*bufA; 5381 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5382 MPI_Request *rwaits = NULL,*swaits = NULL; 5383 MPI_Status *sstatus,rstatus; 5384 PetscMPIInt jj; 5385 PetscInt *cols,sbs,rbs; 5386 PetscScalar *vals; 5387 5388 PetscFunctionBegin; 5389 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5390 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5391 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); 5392 } 5393 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5394 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5395 5396 gen_to = (VecScatter_MPI_General*)ctx->todata; 5397 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5398 rvalues = gen_from->values; /* holds the length of receiving row */ 5399 svalues = gen_to->values; /* holds the length of sending row */ 5400 nrecvs = gen_from->n; 5401 nsends = gen_to->n; 5402 5403 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5404 srow = gen_to->indices; /* local row index to be sent */ 5405 sstarts = gen_to->starts; 5406 sprocs = gen_to->procs; 5407 sstatus = gen_to->sstatus; 5408 sbs = gen_to->bs; 5409 rstarts = gen_from->starts; 5410 rprocs = gen_from->procs; 5411 rbs = gen_from->bs; 5412 5413 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5414 if (scall == MAT_INITIAL_MATRIX) { 5415 /* i-array */ 5416 /*---------*/ 5417 /* post receives */ 5418 for (i=0; i<nrecvs; i++) { 5419 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5420 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5421 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5422 } 5423 5424 /* pack the outgoing message */ 5425 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5426 5427 sstartsj[0] = 0; 5428 rstartsj[0] = 0; 5429 len = 0; /* total length of j or a array to be sent */ 5430 k = 0; 5431 for (i=0; i<nsends; i++) { 5432 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5433 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5434 for (j=0; j<nrows; j++) { 5435 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5436 for (l=0; l<sbs; l++) { 5437 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5438 5439 rowlen[j*sbs+l] = ncols; 5440 5441 len += ncols; 5442 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5443 } 5444 k++; 5445 } 5446 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5447 5448 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5449 } 5450 /* recvs and sends of i-array are completed */ 5451 i = nrecvs; 5452 while (i--) { 5453 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5454 } 5455 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5456 5457 /* allocate buffers for sending j and a arrays */ 5458 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5459 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5460 5461 /* create i-array of B_oth */ 5462 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5463 5464 b_othi[0] = 0; 5465 len = 0; /* total length of j or a array to be received */ 5466 k = 0; 5467 for (i=0; i<nrecvs; i++) { 5468 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5469 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5470 for (j=0; j<nrows; j++) { 5471 b_othi[k+1] = b_othi[k] + rowlen[j]; 5472 len += rowlen[j]; k++; 5473 } 5474 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5475 } 5476 5477 /* allocate space for j and a arrrays of B_oth */ 5478 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5479 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5480 5481 /* j-array */ 5482 /*---------*/ 5483 /* post receives of j-array */ 5484 for (i=0; i<nrecvs; i++) { 5485 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5486 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5487 } 5488 5489 /* pack the outgoing message j-array */ 5490 k = 0; 5491 for (i=0; i<nsends; i++) { 5492 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5493 bufJ = bufj+sstartsj[i]; 5494 for (j=0; j<nrows; j++) { 5495 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5496 for (ll=0; ll<sbs; ll++) { 5497 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5498 for (l=0; l<ncols; l++) { 5499 *bufJ++ = cols[l]; 5500 } 5501 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5502 } 5503 } 5504 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5505 } 5506 5507 /* recvs and sends of j-array are completed */ 5508 i = nrecvs; 5509 while (i--) { 5510 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5511 } 5512 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5513 } else if (scall == MAT_REUSE_MATRIX) { 5514 sstartsj = *startsj_s; 5515 rstartsj = *startsj_r; 5516 bufa = *bufa_ptr; 5517 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5518 b_otha = b_oth->a; 5519 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5520 5521 /* a-array */ 5522 /*---------*/ 5523 /* post receives of a-array */ 5524 for (i=0; i<nrecvs; i++) { 5525 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5526 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5527 } 5528 5529 /* pack the outgoing message a-array */ 5530 k = 0; 5531 for (i=0; i<nsends; i++) { 5532 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5533 bufA = bufa+sstartsj[i]; 5534 for (j=0; j<nrows; j++) { 5535 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5536 for (ll=0; ll<sbs; ll++) { 5537 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5538 for (l=0; l<ncols; l++) { 5539 *bufA++ = vals[l]; 5540 } 5541 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5542 } 5543 } 5544 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5545 } 5546 /* recvs and sends of a-array are completed */ 5547 i = nrecvs; 5548 while (i--) { 5549 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5550 } 5551 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5552 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5553 5554 if (scall == MAT_INITIAL_MATRIX) { 5555 /* put together the new matrix */ 5556 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5557 5558 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5559 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5560 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5561 b_oth->free_a = PETSC_TRUE; 5562 b_oth->free_ij = PETSC_TRUE; 5563 b_oth->nonew = 0; 5564 5565 ierr = PetscFree(bufj);CHKERRQ(ierr); 5566 if (!startsj_s || !bufa_ptr) { 5567 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5568 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5569 } else { 5570 *startsj_s = sstartsj; 5571 *startsj_r = rstartsj; 5572 *bufa_ptr = bufa; 5573 } 5574 } 5575 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5576 PetscFunctionReturn(0); 5577 } 5578 5579 #undef __FUNCT__ 5580 #define __FUNCT__ "MatGetCommunicationStructs" 5581 /*@C 5582 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5583 5584 Not Collective 5585 5586 Input Parameters: 5587 . A - The matrix in mpiaij format 5588 5589 Output Parameter: 5590 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5591 . colmap - A map from global column index to local index into lvec 5592 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5593 5594 Level: developer 5595 5596 @*/ 5597 #if defined(PETSC_USE_CTABLE) 5598 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5599 #else 5600 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5601 #endif 5602 { 5603 Mat_MPIAIJ *a; 5604 5605 PetscFunctionBegin; 5606 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5607 PetscValidPointer(lvec, 2); 5608 PetscValidPointer(colmap, 3); 5609 PetscValidPointer(multScatter, 4); 5610 a = (Mat_MPIAIJ*) A->data; 5611 if (lvec) *lvec = a->lvec; 5612 if (colmap) *colmap = a->colmap; 5613 if (multScatter) *multScatter = a->Mvctx; 5614 PetscFunctionReturn(0); 5615 } 5616 5617 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5618 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5619 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5620 5621 #undef __FUNCT__ 5622 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5623 /* 5624 Computes (B'*A')' since computing B*A directly is untenable 5625 5626 n p p 5627 ( ) ( ) ( ) 5628 m ( A ) * n ( B ) = m ( C ) 5629 ( ) ( ) ( ) 5630 5631 */ 5632 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5633 { 5634 PetscErrorCode ierr; 5635 Mat At,Bt,Ct; 5636 5637 PetscFunctionBegin; 5638 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5639 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5640 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5641 ierr = MatDestroy(&At);CHKERRQ(ierr); 5642 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5643 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5644 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5645 PetscFunctionReturn(0); 5646 } 5647 5648 #undef __FUNCT__ 5649 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5650 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5651 { 5652 PetscErrorCode ierr; 5653 PetscInt m=A->rmap->n,n=B->cmap->n; 5654 Mat Cmat; 5655 5656 PetscFunctionBegin; 5657 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); 5658 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5659 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5660 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5661 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5662 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5663 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5664 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5665 5666 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5667 5668 *C = Cmat; 5669 PetscFunctionReturn(0); 5670 } 5671 5672 /* ----------------------------------------------------------------*/ 5673 #undef __FUNCT__ 5674 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5675 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5676 { 5677 PetscErrorCode ierr; 5678 5679 PetscFunctionBegin; 5680 if (scall == MAT_INITIAL_MATRIX) { 5681 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5682 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5683 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5684 } 5685 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5686 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5687 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5688 PetscFunctionReturn(0); 5689 } 5690 5691 #if defined(PETSC_HAVE_MUMPS) 5692 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5693 #endif 5694 #if defined(PETSC_HAVE_PASTIX) 5695 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5696 #endif 5697 #if defined(PETSC_HAVE_SUPERLU_DIST) 5698 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5699 #endif 5700 #if defined(PETSC_HAVE_CLIQUE) 5701 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5702 #endif 5703 5704 /*MC 5705 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5706 5707 Options Database Keys: 5708 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5709 5710 Level: beginner 5711 5712 .seealso: MatCreateAIJ() 5713 M*/ 5714 5715 #undef __FUNCT__ 5716 #define __FUNCT__ "MatCreate_MPIAIJ" 5717 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5718 { 5719 Mat_MPIAIJ *b; 5720 PetscErrorCode ierr; 5721 PetscMPIInt size; 5722 5723 PetscFunctionBegin; 5724 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5725 5726 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5727 B->data = (void*)b; 5728 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5729 B->assembled = PETSC_FALSE; 5730 B->insertmode = NOT_SET_VALUES; 5731 b->size = size; 5732 5733 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5734 5735 /* build cache for off array entries formed */ 5736 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5737 5738 b->donotstash = PETSC_FALSE; 5739 b->colmap = 0; 5740 b->garray = 0; 5741 b->roworiented = PETSC_TRUE; 5742 5743 /* stuff used for matrix vector multiply */ 5744 b->lvec = NULL; 5745 b->Mvctx = NULL; 5746 5747 /* stuff for MatGetRow() */ 5748 b->rowindices = 0; 5749 b->rowvalues = 0; 5750 b->getrowactive = PETSC_FALSE; 5751 5752 /* flexible pointer used in CUSP/CUSPARSE classes */ 5753 b->spptr = NULL; 5754 5755 #if defined(PETSC_HAVE_MUMPS) 5756 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5757 #endif 5758 #if defined(PETSC_HAVE_PASTIX) 5759 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5760 #endif 5761 #if defined(PETSC_HAVE_SUPERLU_DIST) 5762 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5763 #endif 5764 #if defined(PETSC_HAVE_CLIQUE) 5765 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5766 #endif 5767 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5768 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5769 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5770 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5771 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5772 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5773 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5774 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5775 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5776 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5777 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5778 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5779 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5780 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5781 PetscFunctionReturn(0); 5782 } 5783 5784 #undef __FUNCT__ 5785 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5786 /*@ 5787 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5788 and "off-diagonal" part of the matrix in CSR format. 5789 5790 Collective on MPI_Comm 5791 5792 Input Parameters: 5793 + comm - MPI communicator 5794 . m - number of local rows (Cannot be PETSC_DECIDE) 5795 . n - This value should be the same as the local size used in creating the 5796 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5797 calculated if N is given) For square matrices n is almost always m. 5798 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5799 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5800 . i - row indices for "diagonal" portion of matrix 5801 . j - column indices 5802 . a - matrix values 5803 . oi - row indices for "off-diagonal" portion of matrix 5804 . oj - column indices 5805 - oa - matrix values 5806 5807 Output Parameter: 5808 . mat - the matrix 5809 5810 Level: advanced 5811 5812 Notes: 5813 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5814 must free the arrays once the matrix has been destroyed and not before. 5815 5816 The i and j indices are 0 based 5817 5818 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5819 5820 This sets local rows and cannot be used to set off-processor values. 5821 5822 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5823 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5824 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5825 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5826 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5827 communication if it is known that only local entries will be set. 5828 5829 .keywords: matrix, aij, compressed row, sparse, parallel 5830 5831 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5832 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5833 @*/ 5834 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) 5835 { 5836 PetscErrorCode ierr; 5837 Mat_MPIAIJ *maij; 5838 5839 PetscFunctionBegin; 5840 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5841 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5842 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5843 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5844 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5845 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5846 maij = (Mat_MPIAIJ*) (*mat)->data; 5847 5848 (*mat)->preallocated = PETSC_TRUE; 5849 5850 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5851 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5852 5853 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5854 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5855 5856 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5857 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5858 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5859 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5860 5861 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5862 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5863 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5864 PetscFunctionReturn(0); 5865 } 5866 5867 /* 5868 Special version for direct calls from Fortran 5869 */ 5870 #include <petsc-private/fortranimpl.h> 5871 5872 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5873 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5874 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5875 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5876 #endif 5877 5878 /* Change these macros so can be used in void function */ 5879 #undef CHKERRQ 5880 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5881 #undef SETERRQ2 5882 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5883 #undef SETERRQ3 5884 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5885 #undef SETERRQ 5886 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5887 5888 #undef __FUNCT__ 5889 #define __FUNCT__ "matsetvaluesmpiaij_" 5890 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) 5891 { 5892 Mat mat = *mmat; 5893 PetscInt m = *mm, n = *mn; 5894 InsertMode addv = *maddv; 5895 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5896 PetscScalar value; 5897 PetscErrorCode ierr; 5898 5899 MatCheckPreallocated(mat,1); 5900 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5901 5902 #if defined(PETSC_USE_DEBUG) 5903 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5904 #endif 5905 { 5906 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5907 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5908 PetscBool roworiented = aij->roworiented; 5909 5910 /* Some Variables required in the macro */ 5911 Mat A = aij->A; 5912 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5913 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5914 MatScalar *aa = a->a; 5915 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5916 Mat B = aij->B; 5917 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5918 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5919 MatScalar *ba = b->a; 5920 5921 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5922 PetscInt nonew = a->nonew; 5923 MatScalar *ap1,*ap2; 5924 5925 PetscFunctionBegin; 5926 for (i=0; i<m; i++) { 5927 if (im[i] < 0) continue; 5928 #if defined(PETSC_USE_DEBUG) 5929 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); 5930 #endif 5931 if (im[i] >= rstart && im[i] < rend) { 5932 row = im[i] - rstart; 5933 lastcol1 = -1; 5934 rp1 = aj + ai[row]; 5935 ap1 = aa + ai[row]; 5936 rmax1 = aimax[row]; 5937 nrow1 = ailen[row]; 5938 low1 = 0; 5939 high1 = nrow1; 5940 lastcol2 = -1; 5941 rp2 = bj + bi[row]; 5942 ap2 = ba + bi[row]; 5943 rmax2 = bimax[row]; 5944 nrow2 = bilen[row]; 5945 low2 = 0; 5946 high2 = nrow2; 5947 5948 for (j=0; j<n; j++) { 5949 if (roworiented) value = v[i*n+j]; 5950 else value = v[i+j*m]; 5951 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5952 if (in[j] >= cstart && in[j] < cend) { 5953 col = in[j] - cstart; 5954 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5955 } else if (in[j] < 0) continue; 5956 #if defined(PETSC_USE_DEBUG) 5957 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); 5958 #endif 5959 else { 5960 if (mat->was_assembled) { 5961 if (!aij->colmap) { 5962 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5963 } 5964 #if defined(PETSC_USE_CTABLE) 5965 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5966 col--; 5967 #else 5968 col = aij->colmap[in[j]] - 1; 5969 #endif 5970 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5971 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5972 col = in[j]; 5973 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5974 B = aij->B; 5975 b = (Mat_SeqAIJ*)B->data; 5976 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5977 rp2 = bj + bi[row]; 5978 ap2 = ba + bi[row]; 5979 rmax2 = bimax[row]; 5980 nrow2 = bilen[row]; 5981 low2 = 0; 5982 high2 = nrow2; 5983 bm = aij->B->rmap->n; 5984 ba = b->a; 5985 } 5986 } else col = in[j]; 5987 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5988 } 5989 } 5990 } else if (!aij->donotstash) { 5991 if (roworiented) { 5992 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5993 } else { 5994 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5995 } 5996 } 5997 } 5998 } 5999 PetscFunctionReturnVoid(); 6000 } 6001 6002