1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 for (i=1; i<mat->rmap->n; i++) { 335 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 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_psubcomm" 2556 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_psubcomm(Mat mat,PetscInt nsubcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm,subcomm=psubcomm->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 nsends = 0; nrecvs = 0; 2623 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2624 /* -------------------------------------------*/ 2625 for (i=0; i<size; i++) { 2626 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2627 send_rank[nsends] = i; nsends++; 2628 recv_rank[nrecvs++] = i; 2629 /* printf("[%d] send to and recv from [%d]\n",rank,i); */ 2630 } 2631 } 2632 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2633 i = size-nleftover-1; 2634 j = 0; 2635 while (j < nsubcomm - nleftover) { 2636 send_rank[nsends++] = i; 2637 i--; j++; 2638 /* printf("[%d] send to [%d]\n",rank,i); */ 2639 } 2640 } 2641 2642 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2643 for (i=0; i<nleftover; i++) { 2644 recv_rank[nrecvs++] = size-nleftover+i; 2645 /* printf("[%d] recv from [%d]\n",rank,i); */ 2646 } 2647 } 2648 } else if (psubcomm->type == PETSC_SUBCOMM_CONTIGUOUS) { 2649 /* --------------------------------------------------*/ 2650 PetscInt color,subcommstart; 2651 subcommstart=0; 2652 for (color=0; color<nsubcomm; color++) { 2653 if (psubcomm->color != color) { 2654 for (i=0; i<psubcomm->subsize[color]; i++) { 2655 if (subrank == i) { /* my_subrank == other's subrank */ 2656 send_rank[nsends++] = subcommstart+i; 2657 recv_rank[nrecvs++] = subcommstart+i; 2658 /* printf("[%d] send to and recv from [%d]\n",rank,subcommstart+i); */ 2659 } 2660 } 2661 } 2662 subcommstart += psubcomm->subsize[color]; 2663 } 2664 if (nleftover && subrank == size/nsubcomm) { /* this proc is a leftover proc, send to subcomm that does not have leftover proc */ 2665 subcommstart=0; 2666 for (color=0; color<nsubcomm; color++) { 2667 subcommstart += psubcomm->subsize[color]; 2668 if (psubcomm->color == color) continue; 2669 if (psubcomm->subsize[color] == size/nsubcomm) { /* subcomm does not have leftover proc */ 2670 send_rank[nsends++] = subcommstart -1; /* send to the last proc of subcomm[color] */ 2671 /* printf("[%d] leftover send to [%d] \n",rank,subcommstart -1); */ 2672 } 2673 } 2674 } 2675 2676 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2677 subcommstart=0; 2678 for (color=0; color<nsubcomm; color++) { 2679 subcommstart += psubcomm->subsize[color]; 2680 if (psubcomm->subsize[color] > size/nsubcomm) { /* subcomm has leftover proc */ 2681 recv_rank[nrecvs++] = subcommstart -1; /* recv from the last proc of subcomm[color] */ 2682 /* printf("[%d] recv from [%d]\n",rank,subcommstart -1); */ 2683 } 2684 } 2685 } 2686 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for PetscSubcomm type %D",psubcomm->type); 2687 2688 /* allocate sbuf_j, sbuf_a */ 2689 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2690 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2691 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2692 /* 2693 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2694 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2695 */ 2696 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2697 2698 /* copy mat's local entries into the buffers */ 2699 if (reuse == MAT_INITIAL_MATRIX) { 2700 rownz_max = 0; 2701 rptr = sbuf_j; 2702 cols = sbuf_j + rend-rstart + 1; 2703 vals = sbuf_a; 2704 rptr[0] = 0; 2705 for (i=0; i<rend-rstart; i++) { 2706 row = i + rstart; 2707 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2708 ncols = nzA + nzB; 2709 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2710 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2711 /* load the column indices for this row into cols */ 2712 lwrite = 0; 2713 for (l=0; l<nzB; l++) { 2714 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2715 vals[lwrite] = aworkB[l]; 2716 cols[lwrite++] = ctmp; 2717 } 2718 } 2719 for (l=0; l<nzA; l++) { 2720 vals[lwrite] = aworkA[l]; 2721 cols[lwrite++] = cstart + cworkA[l]; 2722 } 2723 for (l=0; l<nzB; l++) { 2724 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2725 vals[lwrite] = aworkB[l]; 2726 cols[lwrite++] = ctmp; 2727 } 2728 } 2729 vals += ncols; 2730 cols += ncols; 2731 rptr[i+1] = rptr[i] + ncols; 2732 if (rownz_max < ncols) rownz_max = ncols; 2733 } 2734 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); 2735 } else { /* only copy matrix values into sbuf_a */ 2736 rptr = sbuf_j; 2737 vals = sbuf_a; 2738 rptr[0] = 0; 2739 for (i=0; i<rend-rstart; i++) { 2740 row = i + rstart; 2741 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2742 ncols = nzA + nzB; 2743 cworkB = b->j + b->i[i]; 2744 aworkA = a->a + a->i[i]; 2745 aworkB = b->a + b->i[i]; 2746 lwrite = 0; 2747 for (l=0; l<nzB; l++) { 2748 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2749 } 2750 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2751 for (l=0; l<nzB; l++) { 2752 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2753 } 2754 vals += ncols; 2755 rptr[i+1] = rptr[i] + ncols; 2756 } 2757 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2758 2759 /* send nzlocal to others, and recv other's nzlocal */ 2760 /*--------------------------------------------------*/ 2761 if (reuse == MAT_INITIAL_MATRIX) { 2762 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2763 2764 s_waits2 = s_waits3 + nsends; 2765 s_waits1 = s_waits2 + nsends; 2766 r_waits1 = s_waits1 + nsends; 2767 r_waits2 = r_waits1 + nrecvs; 2768 r_waits3 = r_waits2 + nrecvs; 2769 } else { 2770 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2771 2772 r_waits3 = s_waits3 + nsends; 2773 } 2774 2775 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2776 if (reuse == MAT_INITIAL_MATRIX) { 2777 /* get new tags to keep the communication clean */ 2778 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2779 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2780 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2781 2782 /* post receives of other's nzlocal */ 2783 for (i=0; i<nrecvs; i++) { 2784 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2785 } 2786 /* send nzlocal to others */ 2787 for (i=0; i<nsends; i++) { 2788 sbuf_nz[i] = nzlocal; 2789 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2790 } 2791 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2792 count = nrecvs; 2793 while (count) { 2794 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2795 2796 recv_rank[imdex] = recv_status.MPI_SOURCE; 2797 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2798 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2799 2800 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2801 2802 rbuf_nz[imdex] += i + 2; 2803 2804 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2805 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2806 count--; 2807 } 2808 /* wait on sends of nzlocal */ 2809 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2810 /* send mat->i,j to others, and recv from other's */ 2811 /*------------------------------------------------*/ 2812 for (i=0; i<nsends; i++) { 2813 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2814 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2815 } 2816 /* wait on receives of mat->i,j */ 2817 /*------------------------------*/ 2818 count = nrecvs; 2819 while (count) { 2820 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2821 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); 2822 count--; 2823 } 2824 /* wait on sends of mat->i,j */ 2825 /*---------------------------*/ 2826 if (nsends) { 2827 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2828 } 2829 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2830 2831 /* post receives, send and receive mat->a */ 2832 /*----------------------------------------*/ 2833 for (imdex=0; imdex<nrecvs; imdex++) { 2834 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2835 } 2836 for (i=0; i<nsends; i++) { 2837 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2838 } 2839 count = nrecvs; 2840 while (count) { 2841 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2842 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); 2843 count--; 2844 } 2845 if (nsends) { 2846 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2847 } 2848 2849 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2850 2851 /* create redundant matrix */ 2852 /*-------------------------*/ 2853 if (reuse == MAT_INITIAL_MATRIX) { 2854 const PetscInt *range; 2855 PetscInt rstart_sub,rend_sub,mloc_sub; 2856 2857 /* compute rownz_max for preallocation */ 2858 for (imdex=0; imdex<nrecvs; imdex++) { 2859 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2860 rptr = rbuf_j[imdex]; 2861 for (i=0; i<j; i++) { 2862 ncols = rptr[i+1] - rptr[i]; 2863 if (rownz_max < ncols) rownz_max = ncols; 2864 } 2865 } 2866 2867 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2868 2869 /* get local size of redundant matrix 2870 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2871 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2872 rstart_sub = range[nsubcomm*subrank]; 2873 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2874 rend_sub = range[nsubcomm*(subrank+1)]; 2875 } else { 2876 rend_sub = mat->rmap->N; 2877 } 2878 mloc_sub = rend_sub - rstart_sub; 2879 2880 if (M == N) { 2881 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2882 } else { /* non-square matrix */ 2883 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2884 } 2885 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2886 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2887 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2888 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2889 } else { 2890 C = *matredundant; 2891 } 2892 2893 /* insert local matrix entries */ 2894 rptr = sbuf_j; 2895 cols = sbuf_j + rend-rstart + 1; 2896 vals = sbuf_a; 2897 for (i=0; i<rend-rstart; i++) { 2898 row = i + rstart; 2899 ncols = rptr[i+1] - rptr[i]; 2900 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2901 vals += ncols; 2902 cols += ncols; 2903 } 2904 /* insert received matrix entries */ 2905 for (imdex=0; imdex<nrecvs; imdex++) { 2906 rstart = rowrange[recv_rank[imdex]]; 2907 rend = rowrange[recv_rank[imdex]+1]; 2908 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2909 rptr = rbuf_j[imdex]; 2910 cols = rbuf_j[imdex] + rend-rstart + 1; 2911 vals = rbuf_a[imdex]; 2912 for (i=0; i<rend-rstart; i++) { 2913 row = i + rstart; 2914 ncols = rptr[i+1] - rptr[i]; 2915 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2916 vals += ncols; 2917 cols += ncols; 2918 } 2919 } 2920 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2921 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2922 2923 if (reuse == MAT_INITIAL_MATRIX) { 2924 *matredundant = C; 2925 2926 /* create a supporting struct and attach it to C for reuse */ 2927 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2928 if (subsize == 1) { 2929 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2930 c->redundant = redund; 2931 } else { 2932 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2933 c->redundant = redund; 2934 } 2935 2936 redund->nzlocal = nzlocal; 2937 redund->nsends = nsends; 2938 redund->nrecvs = nrecvs; 2939 redund->send_rank = send_rank; 2940 redund->recv_rank = recv_rank; 2941 redund->sbuf_nz = sbuf_nz; 2942 redund->rbuf_nz = rbuf_nz; 2943 redund->sbuf_j = sbuf_j; 2944 redund->sbuf_a = sbuf_a; 2945 redund->rbuf_j = rbuf_j; 2946 redund->rbuf_a = rbuf_a; 2947 redund->psubcomm = NULL; 2948 2949 redund->Destroy = C->ops->destroy; 2950 C->ops->destroy = MatDestroy_MatRedundant; 2951 } 2952 PetscFunctionReturn(0); 2953 } 2954 2955 #undef __FUNCT__ 2956 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2957 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2958 { 2959 PetscErrorCode ierr; 2960 MPI_Comm comm; 2961 PetscMPIInt size,subsize; 2962 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2963 Mat_Redundant *redund =NULL; 2964 2965 PetscFunctionBegin; 2966 if (subcomm == MPI_COMM_NULL) { /* use psubcomm */ 2967 if (reuse == MAT_INITIAL_MATRIX) { 2968 if (psubcomm == NULL) { /* create psubcomm */ 2969 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2970 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2971 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2972 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2973 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2974 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2975 } 2976 subcomm = psubcomm->comm; 2977 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2978 } else { /* retrieve psubcomm */ 2979 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2980 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2981 if (subsize == 1) { 2982 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2983 psubcomm = c->redundant->psubcomm; 2984 } else { 2985 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2986 psubcomm = c->redundant->psubcomm; 2987 } 2988 } 2989 } 2990 2991 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2992 ierr = MatGetRedundantMatrix_MPIAIJ_psubcomm(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2993 } else { 2994 /* via MatGetSubMatrices() */ 2995 Mat *matseq; 2996 IS isrow,iscol; 2997 2998 if (reuse == MAT_INITIAL_MATRIX) { 2999 /* create a local sequential matrix matseq[0] */ 3000 mloc_sub = PETSC_DECIDE; 3001 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 3002 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 3003 rstart = rend - mloc_sub; 3004 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 3005 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 3006 } else { /* reuse == MAT_REUSE_MATRIX */ 3007 if (subsize == 1) { 3008 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3009 redund = c->redundant; 3010 } else { 3011 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3012 redund = c->redundant; 3013 } 3014 3015 isrow = redund->isrow; 3016 iscol = redund->iscol; 3017 matseq = redund->matseq; 3018 } 3019 3020 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 3021 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 3022 3023 if (reuse == MAT_INITIAL_MATRIX) { 3024 /* create a supporting struct and attach it to C for reuse */ 3025 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 3026 if (subsize == 1) { 3027 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3028 c->redundant = redund; 3029 } else { 3030 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3031 c->redundant = redund; 3032 } 3033 redund->isrow = isrow; 3034 redund->iscol = iscol; 3035 redund->matseq = matseq; 3036 redund->psubcomm = NULL; 3037 redund->Destroy = (*matredundant)->ops->destroy; 3038 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3039 } 3040 } 3041 3042 if (psubcomm) { /* free psubcomm in MatDestroy_MatRedundant() */ 3043 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 3044 if (subsize == 1) { 3045 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3046 c->redundant->psubcomm = psubcomm; 3047 } else { 3048 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3049 c->redundant->psubcomm = psubcomm ; 3050 } 3051 } 3052 PetscFunctionReturn(0); 3053 } 3054 3055 #undef __FUNCT__ 3056 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3057 PetscErrorCode MatGetRowMaxAbs_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 = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3067 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3068 if (idx) { 3069 for (i=0; i<A->rmap->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 = MatGetRowMaxAbs(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__ "MatGetRowMinAbs_MPIAIJ" 3097 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3098 { 3099 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3100 PetscErrorCode ierr; 3101 PetscInt i,*idxb = 0; 3102 PetscScalar *va,*vb; 3103 Vec vtmp; 3104 3105 PetscFunctionBegin; 3106 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3107 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3108 if (idx) { 3109 for (i=0; i<A->cmap->n; i++) { 3110 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3111 } 3112 } 3113 3114 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3115 if (idx) { 3116 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3117 } 3118 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3119 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3120 3121 for (i=0; i<A->rmap->n; i++) { 3122 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3123 va[i] = vb[i]; 3124 if (idx) idx[i] = a->garray[idxb[i]]; 3125 } 3126 } 3127 3128 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3129 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3130 ierr = PetscFree(idxb);CHKERRQ(ierr); 3131 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3132 PetscFunctionReturn(0); 3133 } 3134 3135 #undef __FUNCT__ 3136 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3137 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3138 { 3139 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3140 PetscInt n = A->rmap->n; 3141 PetscInt cstart = A->cmap->rstart; 3142 PetscInt *cmap = mat->garray; 3143 PetscInt *diagIdx, *offdiagIdx; 3144 Vec diagV, offdiagV; 3145 PetscScalar *a, *diagA, *offdiagA; 3146 PetscInt r; 3147 PetscErrorCode ierr; 3148 3149 PetscFunctionBegin; 3150 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3151 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3152 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3153 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3154 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3155 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3156 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3157 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3158 for (r = 0; r < n; ++r) { 3159 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3160 a[r] = diagA[r]; 3161 idx[r] = cstart + diagIdx[r]; 3162 } else { 3163 a[r] = offdiagA[r]; 3164 idx[r] = cmap[offdiagIdx[r]]; 3165 } 3166 } 3167 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3168 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3169 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3170 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3171 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3172 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3173 PetscFunctionReturn(0); 3174 } 3175 3176 #undef __FUNCT__ 3177 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3178 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3179 { 3180 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3181 PetscInt n = A->rmap->n; 3182 PetscInt cstart = A->cmap->rstart; 3183 PetscInt *cmap = mat->garray; 3184 PetscInt *diagIdx, *offdiagIdx; 3185 Vec diagV, offdiagV; 3186 PetscScalar *a, *diagA, *offdiagA; 3187 PetscInt r; 3188 PetscErrorCode ierr; 3189 3190 PetscFunctionBegin; 3191 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3192 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3193 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3194 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3195 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3196 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3197 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3198 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3199 for (r = 0; r < n; ++r) { 3200 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3201 a[r] = diagA[r]; 3202 idx[r] = cstart + diagIdx[r]; 3203 } else { 3204 a[r] = offdiagA[r]; 3205 idx[r] = cmap[offdiagIdx[r]]; 3206 } 3207 } 3208 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3209 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3210 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3211 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3212 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3213 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3214 PetscFunctionReturn(0); 3215 } 3216 3217 #undef __FUNCT__ 3218 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3219 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3220 { 3221 PetscErrorCode ierr; 3222 Mat *dummy; 3223 3224 PetscFunctionBegin; 3225 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3226 *newmat = *dummy; 3227 ierr = PetscFree(dummy);CHKERRQ(ierr); 3228 PetscFunctionReturn(0); 3229 } 3230 3231 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3232 3233 #undef __FUNCT__ 3234 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3235 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3236 { 3237 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3238 PetscErrorCode ierr; 3239 3240 PetscFunctionBegin; 3241 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3242 PetscFunctionReturn(0); 3243 } 3244 3245 #undef __FUNCT__ 3246 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3247 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3248 { 3249 PetscErrorCode ierr; 3250 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3251 3252 PetscFunctionBegin; 3253 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3254 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3255 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3256 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3257 PetscFunctionReturn(0); 3258 } 3259 3260 /* -------------------------------------------------------------------*/ 3261 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3262 MatGetRow_MPIAIJ, 3263 MatRestoreRow_MPIAIJ, 3264 MatMult_MPIAIJ, 3265 /* 4*/ MatMultAdd_MPIAIJ, 3266 MatMultTranspose_MPIAIJ, 3267 MatMultTransposeAdd_MPIAIJ, 3268 #if defined(PETSC_HAVE_PBGL) 3269 MatSolve_MPIAIJ, 3270 #else 3271 0, 3272 #endif 3273 0, 3274 0, 3275 /*10*/ 0, 3276 0, 3277 0, 3278 MatSOR_MPIAIJ, 3279 MatTranspose_MPIAIJ, 3280 /*15*/ MatGetInfo_MPIAIJ, 3281 MatEqual_MPIAIJ, 3282 MatGetDiagonal_MPIAIJ, 3283 MatDiagonalScale_MPIAIJ, 3284 MatNorm_MPIAIJ, 3285 /*20*/ MatAssemblyBegin_MPIAIJ, 3286 MatAssemblyEnd_MPIAIJ, 3287 MatSetOption_MPIAIJ, 3288 MatZeroEntries_MPIAIJ, 3289 /*24*/ MatZeroRows_MPIAIJ, 3290 0, 3291 #if defined(PETSC_HAVE_PBGL) 3292 0, 3293 #else 3294 0, 3295 #endif 3296 0, 3297 0, 3298 /*29*/ MatSetUp_MPIAIJ, 3299 #if defined(PETSC_HAVE_PBGL) 3300 0, 3301 #else 3302 0, 3303 #endif 3304 0, 3305 0, 3306 0, 3307 /*34*/ MatDuplicate_MPIAIJ, 3308 0, 3309 0, 3310 0, 3311 0, 3312 /*39*/ MatAXPY_MPIAIJ, 3313 MatGetSubMatrices_MPIAIJ, 3314 MatIncreaseOverlap_MPIAIJ, 3315 MatGetValues_MPIAIJ, 3316 MatCopy_MPIAIJ, 3317 /*44*/ MatGetRowMax_MPIAIJ, 3318 MatScale_MPIAIJ, 3319 0, 3320 0, 3321 MatZeroRowsColumns_MPIAIJ, 3322 /*49*/ MatSetRandom_MPIAIJ, 3323 0, 3324 0, 3325 0, 3326 0, 3327 /*54*/ MatFDColoringCreate_MPIAIJ, 3328 0, 3329 MatSetUnfactored_MPIAIJ, 3330 MatPermute_MPIAIJ, 3331 0, 3332 /*59*/ MatGetSubMatrix_MPIAIJ, 3333 MatDestroy_MPIAIJ, 3334 MatView_MPIAIJ, 3335 0, 3336 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3337 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3338 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3339 0, 3340 0, 3341 0, 3342 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3343 MatGetRowMinAbs_MPIAIJ, 3344 0, 3345 MatSetColoring_MPIAIJ, 3346 0, 3347 MatSetValuesAdifor_MPIAIJ, 3348 /*75*/ MatFDColoringApply_AIJ, 3349 0, 3350 0, 3351 0, 3352 MatFindZeroDiagonals_MPIAIJ, 3353 /*80*/ 0, 3354 0, 3355 0, 3356 /*83*/ MatLoad_MPIAIJ, 3357 0, 3358 0, 3359 0, 3360 0, 3361 0, 3362 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3363 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3364 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3365 MatPtAP_MPIAIJ_MPIAIJ, 3366 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3367 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3368 0, 3369 0, 3370 0, 3371 0, 3372 /*99*/ 0, 3373 0, 3374 0, 3375 MatConjugate_MPIAIJ, 3376 0, 3377 /*104*/MatSetValuesRow_MPIAIJ, 3378 MatRealPart_MPIAIJ, 3379 MatImaginaryPart_MPIAIJ, 3380 0, 3381 0, 3382 /*109*/0, 3383 MatGetRedundantMatrix_MPIAIJ, 3384 MatGetRowMin_MPIAIJ, 3385 0, 3386 0, 3387 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3388 0, 3389 0, 3390 0, 3391 0, 3392 /*119*/0, 3393 0, 3394 0, 3395 0, 3396 MatGetMultiProcBlock_MPIAIJ, 3397 /*124*/MatFindNonzeroRows_MPIAIJ, 3398 MatGetColumnNorms_MPIAIJ, 3399 MatInvertBlockDiagonal_MPIAIJ, 3400 0, 3401 MatGetSubMatricesParallel_MPIAIJ, 3402 /*129*/0, 3403 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3404 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3405 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3406 0, 3407 /*134*/0, 3408 0, 3409 0, 3410 0, 3411 0, 3412 /*139*/0, 3413 0 3414 }; 3415 3416 /* ----------------------------------------------------------------------------------------*/ 3417 3418 #undef __FUNCT__ 3419 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3420 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3421 { 3422 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3423 PetscErrorCode ierr; 3424 3425 PetscFunctionBegin; 3426 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3427 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3428 PetscFunctionReturn(0); 3429 } 3430 3431 #undef __FUNCT__ 3432 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3433 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3434 { 3435 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3436 PetscErrorCode ierr; 3437 3438 PetscFunctionBegin; 3439 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3440 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3441 PetscFunctionReturn(0); 3442 } 3443 3444 #undef __FUNCT__ 3445 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3446 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3447 { 3448 Mat_MPIAIJ *b; 3449 PetscErrorCode ierr; 3450 3451 PetscFunctionBegin; 3452 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3453 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3454 b = (Mat_MPIAIJ*)B->data; 3455 3456 if (!B->preallocated) { 3457 /* Explicitly create 2 MATSEQAIJ matrices. */ 3458 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3459 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3460 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3461 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3462 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3463 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3464 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3465 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3466 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3467 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3468 } 3469 3470 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3471 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3472 B->preallocated = PETSC_TRUE; 3473 PetscFunctionReturn(0); 3474 } 3475 3476 #undef __FUNCT__ 3477 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3478 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3479 { 3480 Mat mat; 3481 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3482 PetscErrorCode ierr; 3483 3484 PetscFunctionBegin; 3485 *newmat = 0; 3486 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3487 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3488 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3489 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3490 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3491 a = (Mat_MPIAIJ*)mat->data; 3492 3493 mat->factortype = matin->factortype; 3494 mat->rmap->bs = matin->rmap->bs; 3495 mat->cmap->bs = matin->cmap->bs; 3496 mat->assembled = PETSC_TRUE; 3497 mat->insertmode = NOT_SET_VALUES; 3498 mat->preallocated = PETSC_TRUE; 3499 3500 a->size = oldmat->size; 3501 a->rank = oldmat->rank; 3502 a->donotstash = oldmat->donotstash; 3503 a->roworiented = oldmat->roworiented; 3504 a->rowindices = 0; 3505 a->rowvalues = 0; 3506 a->getrowactive = PETSC_FALSE; 3507 3508 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3509 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3510 3511 if (oldmat->colmap) { 3512 #if defined(PETSC_USE_CTABLE) 3513 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3514 #else 3515 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3516 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3517 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3518 #endif 3519 } else a->colmap = 0; 3520 if (oldmat->garray) { 3521 PetscInt len; 3522 len = oldmat->B->cmap->n; 3523 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3524 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3525 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3526 } else a->garray = 0; 3527 3528 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3529 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3530 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3531 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3532 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3533 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3534 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3535 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3536 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3537 *newmat = mat; 3538 PetscFunctionReturn(0); 3539 } 3540 3541 3542 3543 #undef __FUNCT__ 3544 #define __FUNCT__ "MatLoad_MPIAIJ" 3545 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3546 { 3547 PetscScalar *vals,*svals; 3548 MPI_Comm comm; 3549 PetscErrorCode ierr; 3550 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3551 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3552 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3553 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3554 PetscInt cend,cstart,n,*rowners,sizesset=1; 3555 int fd; 3556 PetscInt bs = 1; 3557 3558 PetscFunctionBegin; 3559 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3560 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3561 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3562 if (!rank) { 3563 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3564 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3565 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3566 } 3567 3568 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3569 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3570 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3571 3572 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3573 3574 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3575 M = header[1]; N = header[2]; 3576 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3577 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3578 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3579 3580 /* If global sizes are set, check if they are consistent with that given in the file */ 3581 if (sizesset) { 3582 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3583 } 3584 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); 3585 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); 3586 3587 /* determine ownership of all (block) rows */ 3588 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3589 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3590 else m = newMat->rmap->n; /* Set by user */ 3591 3592 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3593 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3594 3595 /* First process needs enough room for process with most rows */ 3596 if (!rank) { 3597 mmax = rowners[1]; 3598 for (i=2; i<=size; i++) { 3599 mmax = PetscMax(mmax, rowners[i]); 3600 } 3601 } else mmax = -1; /* unused, but compilers complain */ 3602 3603 rowners[0] = 0; 3604 for (i=2; i<=size; i++) { 3605 rowners[i] += rowners[i-1]; 3606 } 3607 rstart = rowners[rank]; 3608 rend = rowners[rank+1]; 3609 3610 /* distribute row lengths to all processors */ 3611 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3612 if (!rank) { 3613 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3614 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3615 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3616 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3617 for (j=0; j<m; j++) { 3618 procsnz[0] += ourlens[j]; 3619 } 3620 for (i=1; i<size; i++) { 3621 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3622 /* calculate the number of nonzeros on each processor */ 3623 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3624 procsnz[i] += rowlengths[j]; 3625 } 3626 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3627 } 3628 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3629 } else { 3630 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3631 } 3632 3633 if (!rank) { 3634 /* determine max buffer needed and allocate it */ 3635 maxnz = 0; 3636 for (i=0; i<size; i++) { 3637 maxnz = PetscMax(maxnz,procsnz[i]); 3638 } 3639 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3640 3641 /* read in my part of the matrix column indices */ 3642 nz = procsnz[0]; 3643 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3644 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3645 3646 /* read in every one elses and ship off */ 3647 for (i=1; i<size; i++) { 3648 nz = procsnz[i]; 3649 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3650 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3651 } 3652 ierr = PetscFree(cols);CHKERRQ(ierr); 3653 } else { 3654 /* determine buffer space needed for message */ 3655 nz = 0; 3656 for (i=0; i<m; i++) { 3657 nz += ourlens[i]; 3658 } 3659 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3660 3661 /* receive message of column indices*/ 3662 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3663 } 3664 3665 /* determine column ownership if matrix is not square */ 3666 if (N != M) { 3667 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3668 else n = newMat->cmap->n; 3669 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3670 cstart = cend - n; 3671 } else { 3672 cstart = rstart; 3673 cend = rend; 3674 n = cend - cstart; 3675 } 3676 3677 /* loop over local rows, determining number of off diagonal entries */ 3678 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3679 jj = 0; 3680 for (i=0; i<m; i++) { 3681 for (j=0; j<ourlens[i]; j++) { 3682 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3683 jj++; 3684 } 3685 } 3686 3687 for (i=0; i<m; i++) { 3688 ourlens[i] -= offlens[i]; 3689 } 3690 if (!sizesset) { 3691 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3692 } 3693 3694 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3695 3696 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3697 3698 for (i=0; i<m; i++) { 3699 ourlens[i] += offlens[i]; 3700 } 3701 3702 if (!rank) { 3703 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3704 3705 /* read in my part of the matrix numerical values */ 3706 nz = procsnz[0]; 3707 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3708 3709 /* insert into matrix */ 3710 jj = rstart; 3711 smycols = mycols; 3712 svals = vals; 3713 for (i=0; i<m; i++) { 3714 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3715 smycols += ourlens[i]; 3716 svals += ourlens[i]; 3717 jj++; 3718 } 3719 3720 /* read in other processors and ship out */ 3721 for (i=1; i<size; i++) { 3722 nz = procsnz[i]; 3723 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3724 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3725 } 3726 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3727 } else { 3728 /* receive numeric values */ 3729 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3730 3731 /* receive message of values*/ 3732 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3733 3734 /* insert into matrix */ 3735 jj = rstart; 3736 smycols = mycols; 3737 svals = vals; 3738 for (i=0; i<m; i++) { 3739 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3740 smycols += ourlens[i]; 3741 svals += ourlens[i]; 3742 jj++; 3743 } 3744 } 3745 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3746 ierr = PetscFree(vals);CHKERRQ(ierr); 3747 ierr = PetscFree(mycols);CHKERRQ(ierr); 3748 ierr = PetscFree(rowners);CHKERRQ(ierr); 3749 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3750 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3751 PetscFunctionReturn(0); 3752 } 3753 3754 #undef __FUNCT__ 3755 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3756 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3757 { 3758 PetscErrorCode ierr; 3759 IS iscol_local; 3760 PetscInt csize; 3761 3762 PetscFunctionBegin; 3763 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3764 if (call == MAT_REUSE_MATRIX) { 3765 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3766 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3767 } else { 3768 PetscInt cbs; 3769 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3770 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3771 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3772 } 3773 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3774 if (call == MAT_INITIAL_MATRIX) { 3775 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3776 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3777 } 3778 PetscFunctionReturn(0); 3779 } 3780 3781 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3782 #undef __FUNCT__ 3783 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3784 /* 3785 Not great since it makes two copies of the submatrix, first an SeqAIJ 3786 in local and then by concatenating the local matrices the end result. 3787 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3788 3789 Note: This requires a sequential iscol with all indices. 3790 */ 3791 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3792 { 3793 PetscErrorCode ierr; 3794 PetscMPIInt rank,size; 3795 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3796 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3797 PetscBool allcolumns, colflag; 3798 Mat M,Mreuse; 3799 MatScalar *vwork,*aa; 3800 MPI_Comm comm; 3801 Mat_SeqAIJ *aij; 3802 3803 PetscFunctionBegin; 3804 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3805 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3806 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3807 3808 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3809 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3810 if (colflag && ncol == mat->cmap->N) { 3811 allcolumns = PETSC_TRUE; 3812 } else { 3813 allcolumns = PETSC_FALSE; 3814 } 3815 if (call == MAT_REUSE_MATRIX) { 3816 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3817 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3818 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3819 } else { 3820 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3821 } 3822 3823 /* 3824 m - number of local rows 3825 n - number of columns (same on all processors) 3826 rstart - first row in new global matrix generated 3827 */ 3828 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3829 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3830 if (call == MAT_INITIAL_MATRIX) { 3831 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3832 ii = aij->i; 3833 jj = aij->j; 3834 3835 /* 3836 Determine the number of non-zeros in the diagonal and off-diagonal 3837 portions of the matrix in order to do correct preallocation 3838 */ 3839 3840 /* first get start and end of "diagonal" columns */ 3841 if (csize == PETSC_DECIDE) { 3842 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3843 if (mglobal == n) { /* square matrix */ 3844 nlocal = m; 3845 } else { 3846 nlocal = n/size + ((n % size) > rank); 3847 } 3848 } else { 3849 nlocal = csize; 3850 } 3851 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3852 rstart = rend - nlocal; 3853 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); 3854 3855 /* next, compute all the lengths */ 3856 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3857 olens = dlens + m; 3858 for (i=0; i<m; i++) { 3859 jend = ii[i+1] - ii[i]; 3860 olen = 0; 3861 dlen = 0; 3862 for (j=0; j<jend; j++) { 3863 if (*jj < rstart || *jj >= rend) olen++; 3864 else dlen++; 3865 jj++; 3866 } 3867 olens[i] = olen; 3868 dlens[i] = dlen; 3869 } 3870 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3871 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3872 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3873 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3874 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3875 ierr = PetscFree(dlens);CHKERRQ(ierr); 3876 } else { 3877 PetscInt ml,nl; 3878 3879 M = *newmat; 3880 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3881 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3882 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3883 /* 3884 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3885 rather than the slower MatSetValues(). 3886 */ 3887 M->was_assembled = PETSC_TRUE; 3888 M->assembled = PETSC_FALSE; 3889 } 3890 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3891 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3892 ii = aij->i; 3893 jj = aij->j; 3894 aa = aij->a; 3895 for (i=0; i<m; i++) { 3896 row = rstart + i; 3897 nz = ii[i+1] - ii[i]; 3898 cwork = jj; jj += nz; 3899 vwork = aa; aa += nz; 3900 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3901 } 3902 3903 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3904 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3905 *newmat = M; 3906 3907 /* save submatrix used in processor for next request */ 3908 if (call == MAT_INITIAL_MATRIX) { 3909 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3910 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3911 } 3912 PetscFunctionReturn(0); 3913 } 3914 3915 #undef __FUNCT__ 3916 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3917 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3918 { 3919 PetscInt m,cstart, cend,j,nnz,i,d; 3920 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3921 const PetscInt *JJ; 3922 PetscScalar *values; 3923 PetscErrorCode ierr; 3924 3925 PetscFunctionBegin; 3926 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3927 3928 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3929 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3930 m = B->rmap->n; 3931 cstart = B->cmap->rstart; 3932 cend = B->cmap->rend; 3933 rstart = B->rmap->rstart; 3934 3935 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3936 3937 #if defined(PETSC_USE_DEBUGGING) 3938 for (i=0; i<m; i++) { 3939 nnz = Ii[i+1]- Ii[i]; 3940 JJ = J + Ii[i]; 3941 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3942 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3943 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); 3944 } 3945 #endif 3946 3947 for (i=0; i<m; i++) { 3948 nnz = Ii[i+1]- Ii[i]; 3949 JJ = J + Ii[i]; 3950 nnz_max = PetscMax(nnz_max,nnz); 3951 d = 0; 3952 for (j=0; j<nnz; j++) { 3953 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3954 } 3955 d_nnz[i] = d; 3956 o_nnz[i] = nnz - d; 3957 } 3958 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3959 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3960 3961 if (v) values = (PetscScalar*)v; 3962 else { 3963 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3964 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3965 } 3966 3967 for (i=0; i<m; i++) { 3968 ii = i + rstart; 3969 nnz = Ii[i+1]- Ii[i]; 3970 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3971 } 3972 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3973 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3974 3975 if (!v) { 3976 ierr = PetscFree(values);CHKERRQ(ierr); 3977 } 3978 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3979 PetscFunctionReturn(0); 3980 } 3981 3982 #undef __FUNCT__ 3983 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3984 /*@ 3985 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3986 (the default parallel PETSc format). 3987 3988 Collective on MPI_Comm 3989 3990 Input Parameters: 3991 + B - the matrix 3992 . i - the indices into j for the start of each local row (starts with zero) 3993 . j - the column indices for each local row (starts with zero) 3994 - v - optional values in the matrix 3995 3996 Level: developer 3997 3998 Notes: 3999 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4000 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4001 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4002 4003 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4004 4005 The format which is used for the sparse matrix input, is equivalent to a 4006 row-major ordering.. i.e for the following matrix, the input data expected is 4007 as shown: 4008 4009 1 0 0 4010 2 0 3 P0 4011 ------- 4012 4 5 6 P1 4013 4014 Process0 [P0]: rows_owned=[0,1] 4015 i = {0,1,3} [size = nrow+1 = 2+1] 4016 j = {0,0,2} [size = nz = 6] 4017 v = {1,2,3} [size = nz = 6] 4018 4019 Process1 [P1]: rows_owned=[2] 4020 i = {0,3} [size = nrow+1 = 1+1] 4021 j = {0,1,2} [size = nz = 6] 4022 v = {4,5,6} [size = nz = 6] 4023 4024 .keywords: matrix, aij, compressed row, sparse, parallel 4025 4026 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 4027 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 4028 @*/ 4029 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 4030 { 4031 PetscErrorCode ierr; 4032 4033 PetscFunctionBegin; 4034 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4035 PetscFunctionReturn(0); 4036 } 4037 4038 #undef __FUNCT__ 4039 #define __FUNCT__ "MatMPIAIJSetPreallocation" 4040 /*@C 4041 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4042 (the default parallel PETSc format). For good matrix assembly performance 4043 the user should preallocate the matrix storage by setting the parameters 4044 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4045 performance can be increased by more than a factor of 50. 4046 4047 Collective on MPI_Comm 4048 4049 Input Parameters: 4050 + A - the matrix 4051 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4052 (same value is used for all local rows) 4053 . d_nnz - array containing the number of nonzeros in the various rows of the 4054 DIAGONAL portion of the local submatrix (possibly different for each row) 4055 or NULL, if d_nz is used to specify the nonzero structure. 4056 The size of this array is equal to the number of local rows, i.e 'm'. 4057 For matrices that will be factored, you must leave room for (and set) 4058 the diagonal entry even if it is zero. 4059 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4060 submatrix (same value is used for all local rows). 4061 - o_nnz - array containing the number of nonzeros in the various rows of the 4062 OFF-DIAGONAL portion of the local submatrix (possibly different for 4063 each row) or NULL, if o_nz is used to specify the nonzero 4064 structure. The size of this array is equal to the number 4065 of local rows, i.e 'm'. 4066 4067 If the *_nnz parameter is given then the *_nz parameter is ignored 4068 4069 The AIJ format (also called the Yale sparse matrix format or 4070 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4071 storage. The stored row and column indices begin with zero. 4072 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4073 4074 The parallel matrix is partitioned such that the first m0 rows belong to 4075 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4076 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4077 4078 The DIAGONAL portion of the local submatrix of a processor can be defined 4079 as the submatrix which is obtained by extraction the part corresponding to 4080 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4081 first row that belongs to the processor, r2 is the last row belonging to 4082 the this processor, and c1-c2 is range of indices of the local part of a 4083 vector suitable for applying the matrix to. This is an mxn matrix. In the 4084 common case of a square matrix, the row and column ranges are the same and 4085 the DIAGONAL part is also square. The remaining portion of the local 4086 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4087 4088 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4089 4090 You can call MatGetInfo() to get information on how effective the preallocation was; 4091 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4092 You can also run with the option -info and look for messages with the string 4093 malloc in them to see if additional memory allocation was needed. 4094 4095 Example usage: 4096 4097 Consider the following 8x8 matrix with 34 non-zero values, that is 4098 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4099 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4100 as follows: 4101 4102 .vb 4103 1 2 0 | 0 3 0 | 0 4 4104 Proc0 0 5 6 | 7 0 0 | 8 0 4105 9 0 10 | 11 0 0 | 12 0 4106 ------------------------------------- 4107 13 0 14 | 15 16 17 | 0 0 4108 Proc1 0 18 0 | 19 20 21 | 0 0 4109 0 0 0 | 22 23 0 | 24 0 4110 ------------------------------------- 4111 Proc2 25 26 27 | 0 0 28 | 29 0 4112 30 0 0 | 31 32 33 | 0 34 4113 .ve 4114 4115 This can be represented as a collection of submatrices as: 4116 4117 .vb 4118 A B C 4119 D E F 4120 G H I 4121 .ve 4122 4123 Where the submatrices A,B,C are owned by proc0, D,E,F are 4124 owned by proc1, G,H,I are owned by proc2. 4125 4126 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4127 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4128 The 'M','N' parameters are 8,8, and have the same values on all procs. 4129 4130 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4131 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4132 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4133 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4134 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4135 matrix, ans [DF] as another SeqAIJ matrix. 4136 4137 When d_nz, o_nz parameters are specified, d_nz storage elements are 4138 allocated for every row of the local diagonal submatrix, and o_nz 4139 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4140 One way to choose d_nz and o_nz is to use the max nonzerors per local 4141 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4142 In this case, the values of d_nz,o_nz are: 4143 .vb 4144 proc0 : dnz = 2, o_nz = 2 4145 proc1 : dnz = 3, o_nz = 2 4146 proc2 : dnz = 1, o_nz = 4 4147 .ve 4148 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4149 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4150 for proc3. i.e we are using 12+15+10=37 storage locations to store 4151 34 values. 4152 4153 When d_nnz, o_nnz parameters are specified, the storage is specified 4154 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4155 In the above case the values for d_nnz,o_nnz are: 4156 .vb 4157 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4158 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4159 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4160 .ve 4161 Here the space allocated is sum of all the above values i.e 34, and 4162 hence pre-allocation is perfect. 4163 4164 Level: intermediate 4165 4166 .keywords: matrix, aij, compressed row, sparse, parallel 4167 4168 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4169 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4170 @*/ 4171 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4172 { 4173 PetscErrorCode ierr; 4174 4175 PetscFunctionBegin; 4176 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4177 PetscValidType(B,1); 4178 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4179 PetscFunctionReturn(0); 4180 } 4181 4182 #undef __FUNCT__ 4183 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4184 /*@ 4185 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4186 CSR format the local rows. 4187 4188 Collective on MPI_Comm 4189 4190 Input Parameters: 4191 + comm - MPI communicator 4192 . m - number of local rows (Cannot be PETSC_DECIDE) 4193 . n - This value should be the same as the local size used in creating the 4194 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4195 calculated if N is given) For square matrices n is almost always m. 4196 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4197 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4198 . i - row indices 4199 . j - column indices 4200 - a - matrix values 4201 4202 Output Parameter: 4203 . mat - the matrix 4204 4205 Level: intermediate 4206 4207 Notes: 4208 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4209 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4210 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4211 4212 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4213 4214 The format which is used for the sparse matrix input, is equivalent to a 4215 row-major ordering.. i.e for the following matrix, the input data expected is 4216 as shown: 4217 4218 1 0 0 4219 2 0 3 P0 4220 ------- 4221 4 5 6 P1 4222 4223 Process0 [P0]: rows_owned=[0,1] 4224 i = {0,1,3} [size = nrow+1 = 2+1] 4225 j = {0,0,2} [size = nz = 6] 4226 v = {1,2,3} [size = nz = 6] 4227 4228 Process1 [P1]: rows_owned=[2] 4229 i = {0,3} [size = nrow+1 = 1+1] 4230 j = {0,1,2} [size = nz = 6] 4231 v = {4,5,6} [size = nz = 6] 4232 4233 .keywords: matrix, aij, compressed row, sparse, parallel 4234 4235 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4236 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4237 @*/ 4238 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4239 { 4240 PetscErrorCode ierr; 4241 4242 PetscFunctionBegin; 4243 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4244 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4245 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4246 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4247 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4248 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4249 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4250 PetscFunctionReturn(0); 4251 } 4252 4253 #undef __FUNCT__ 4254 #define __FUNCT__ "MatCreateAIJ" 4255 /*@C 4256 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4257 (the default parallel PETSc format). For good matrix assembly performance 4258 the user should preallocate the matrix storage by setting the parameters 4259 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4260 performance can be increased by more than a factor of 50. 4261 4262 Collective on MPI_Comm 4263 4264 Input Parameters: 4265 + comm - MPI communicator 4266 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4267 This value should be the same as the local size used in creating the 4268 y vector for the matrix-vector product y = Ax. 4269 . n - This value should be the same as the local size used in creating the 4270 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4271 calculated if N is given) For square matrices n is almost always m. 4272 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4273 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4274 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4275 (same value is used for all local rows) 4276 . d_nnz - array containing the number of nonzeros in the various rows of the 4277 DIAGONAL portion of the local submatrix (possibly different for each row) 4278 or NULL, if d_nz is used to specify the nonzero structure. 4279 The size of this array is equal to the number of local rows, i.e 'm'. 4280 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4281 submatrix (same value is used for all local rows). 4282 - o_nnz - array containing the number of nonzeros in the various rows of the 4283 OFF-DIAGONAL portion of the local submatrix (possibly different for 4284 each row) or NULL, if o_nz is used to specify the nonzero 4285 structure. The size of this array is equal to the number 4286 of local rows, i.e 'm'. 4287 4288 Output Parameter: 4289 . A - the matrix 4290 4291 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4292 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4293 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4294 4295 Notes: 4296 If the *_nnz parameter is given then the *_nz parameter is ignored 4297 4298 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4299 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4300 storage requirements for this matrix. 4301 4302 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4303 processor than it must be used on all processors that share the object for 4304 that argument. 4305 4306 The user MUST specify either the local or global matrix dimensions 4307 (possibly both). 4308 4309 The parallel matrix is partitioned across processors such that the 4310 first m0 rows belong to process 0, the next m1 rows belong to 4311 process 1, the next m2 rows belong to process 2 etc.. where 4312 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4313 values corresponding to [m x N] submatrix. 4314 4315 The columns are logically partitioned with the n0 columns belonging 4316 to 0th partition, the next n1 columns belonging to the next 4317 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4318 4319 The DIAGONAL portion of the local submatrix on any given processor 4320 is the submatrix corresponding to the rows and columns m,n 4321 corresponding to the given processor. i.e diagonal matrix on 4322 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4323 etc. The remaining portion of the local submatrix [m x (N-n)] 4324 constitute the OFF-DIAGONAL portion. The example below better 4325 illustrates this concept. 4326 4327 For a square global matrix we define each processor's diagonal portion 4328 to be its local rows and the corresponding columns (a square submatrix); 4329 each processor's off-diagonal portion encompasses the remainder of the 4330 local matrix (a rectangular submatrix). 4331 4332 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4333 4334 When calling this routine with a single process communicator, a matrix of 4335 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4336 type of communicator, use the construction mechanism: 4337 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4338 4339 By default, this format uses inodes (identical nodes) when possible. 4340 We search for consecutive rows with the same nonzero structure, thereby 4341 reusing matrix information to achieve increased efficiency. 4342 4343 Options Database Keys: 4344 + -mat_no_inode - Do not use inodes 4345 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4346 - -mat_aij_oneindex - Internally use indexing starting at 1 4347 rather than 0. Note that when calling MatSetValues(), 4348 the user still MUST index entries starting at 0! 4349 4350 4351 Example usage: 4352 4353 Consider the following 8x8 matrix with 34 non-zero values, that is 4354 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4355 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4356 as follows: 4357 4358 .vb 4359 1 2 0 | 0 3 0 | 0 4 4360 Proc0 0 5 6 | 7 0 0 | 8 0 4361 9 0 10 | 11 0 0 | 12 0 4362 ------------------------------------- 4363 13 0 14 | 15 16 17 | 0 0 4364 Proc1 0 18 0 | 19 20 21 | 0 0 4365 0 0 0 | 22 23 0 | 24 0 4366 ------------------------------------- 4367 Proc2 25 26 27 | 0 0 28 | 29 0 4368 30 0 0 | 31 32 33 | 0 34 4369 .ve 4370 4371 This can be represented as a collection of submatrices as: 4372 4373 .vb 4374 A B C 4375 D E F 4376 G H I 4377 .ve 4378 4379 Where the submatrices A,B,C are owned by proc0, D,E,F are 4380 owned by proc1, G,H,I are owned by proc2. 4381 4382 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4383 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4384 The 'M','N' parameters are 8,8, and have the same values on all procs. 4385 4386 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4387 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4388 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4389 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4390 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4391 matrix, ans [DF] as another SeqAIJ matrix. 4392 4393 When d_nz, o_nz parameters are specified, d_nz storage elements are 4394 allocated for every row of the local diagonal submatrix, and o_nz 4395 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4396 One way to choose d_nz and o_nz is to use the max nonzerors per local 4397 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4398 In this case, the values of d_nz,o_nz are: 4399 .vb 4400 proc0 : dnz = 2, o_nz = 2 4401 proc1 : dnz = 3, o_nz = 2 4402 proc2 : dnz = 1, o_nz = 4 4403 .ve 4404 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4405 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4406 for proc3. i.e we are using 12+15+10=37 storage locations to store 4407 34 values. 4408 4409 When d_nnz, o_nnz parameters are specified, the storage is specified 4410 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4411 In the above case the values for d_nnz,o_nnz are: 4412 .vb 4413 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4414 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4415 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4416 .ve 4417 Here the space allocated is sum of all the above values i.e 34, and 4418 hence pre-allocation is perfect. 4419 4420 Level: intermediate 4421 4422 .keywords: matrix, aij, compressed row, sparse, parallel 4423 4424 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4425 MPIAIJ, MatCreateMPIAIJWithArrays() 4426 @*/ 4427 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) 4428 { 4429 PetscErrorCode ierr; 4430 PetscMPIInt size; 4431 4432 PetscFunctionBegin; 4433 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4434 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4435 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4436 if (size > 1) { 4437 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4438 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4439 } else { 4440 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4441 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4442 } 4443 PetscFunctionReturn(0); 4444 } 4445 4446 #undef __FUNCT__ 4447 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4448 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4449 { 4450 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4451 4452 PetscFunctionBegin; 4453 *Ad = a->A; 4454 *Ao = a->B; 4455 *colmap = a->garray; 4456 PetscFunctionReturn(0); 4457 } 4458 4459 #undef __FUNCT__ 4460 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4461 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4462 { 4463 PetscErrorCode ierr; 4464 PetscInt i; 4465 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4466 4467 PetscFunctionBegin; 4468 if (coloring->ctype == IS_COLORING_GLOBAL) { 4469 ISColoringValue *allcolors,*colors; 4470 ISColoring ocoloring; 4471 4472 /* set coloring for diagonal portion */ 4473 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4474 4475 /* set coloring for off-diagonal portion */ 4476 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4477 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4478 for (i=0; i<a->B->cmap->n; i++) { 4479 colors[i] = allcolors[a->garray[i]]; 4480 } 4481 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4482 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4483 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4484 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4485 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4486 ISColoringValue *colors; 4487 PetscInt *larray; 4488 ISColoring ocoloring; 4489 4490 /* set coloring for diagonal portion */ 4491 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4492 for (i=0; i<a->A->cmap->n; i++) { 4493 larray[i] = i + A->cmap->rstart; 4494 } 4495 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4496 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4497 for (i=0; i<a->A->cmap->n; i++) { 4498 colors[i] = coloring->colors[larray[i]]; 4499 } 4500 ierr = PetscFree(larray);CHKERRQ(ierr); 4501 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4502 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4503 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4504 4505 /* set coloring for off-diagonal portion */ 4506 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4507 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4508 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4509 for (i=0; i<a->B->cmap->n; i++) { 4510 colors[i] = coloring->colors[larray[i]]; 4511 } 4512 ierr = PetscFree(larray);CHKERRQ(ierr); 4513 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4514 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4515 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4516 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4517 PetscFunctionReturn(0); 4518 } 4519 4520 #undef __FUNCT__ 4521 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4522 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4523 { 4524 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4525 PetscErrorCode ierr; 4526 4527 PetscFunctionBegin; 4528 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4529 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4530 PetscFunctionReturn(0); 4531 } 4532 4533 #undef __FUNCT__ 4534 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4535 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4536 { 4537 PetscErrorCode ierr; 4538 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4539 PetscInt *indx; 4540 4541 PetscFunctionBegin; 4542 /* This routine will ONLY return MPIAIJ type matrix */ 4543 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4544 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4545 if (n == PETSC_DECIDE) { 4546 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4547 } 4548 /* Check sum(n) = N */ 4549 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4550 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4551 4552 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4553 rstart -= m; 4554 4555 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4556 for (i=0; i<m; i++) { 4557 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4558 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4559 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4560 } 4561 4562 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4563 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4564 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4565 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4566 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4567 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4568 PetscFunctionReturn(0); 4569 } 4570 4571 #undef __FUNCT__ 4572 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4573 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4574 { 4575 PetscErrorCode ierr; 4576 PetscInt m,N,i,rstart,nnz,Ii; 4577 PetscInt *indx; 4578 PetscScalar *values; 4579 4580 PetscFunctionBegin; 4581 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4582 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4583 for (i=0; i<m; i++) { 4584 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4585 Ii = i + rstart; 4586 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4587 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4588 } 4589 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4590 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4591 PetscFunctionReturn(0); 4592 } 4593 4594 #undef __FUNCT__ 4595 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4596 /*@ 4597 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4598 matrices from each processor 4599 4600 Collective on MPI_Comm 4601 4602 Input Parameters: 4603 + comm - the communicators the parallel matrix will live on 4604 . inmat - the input sequential matrices 4605 . n - number of local columns (or PETSC_DECIDE) 4606 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4607 4608 Output Parameter: 4609 . outmat - the parallel matrix generated 4610 4611 Level: advanced 4612 4613 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4614 4615 @*/ 4616 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4617 { 4618 PetscErrorCode ierr; 4619 4620 PetscFunctionBegin; 4621 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4622 if (scall == MAT_INITIAL_MATRIX) { 4623 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4624 } 4625 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4626 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4627 PetscFunctionReturn(0); 4628 } 4629 4630 #undef __FUNCT__ 4631 #define __FUNCT__ "MatFileSplit" 4632 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4633 { 4634 PetscErrorCode ierr; 4635 PetscMPIInt rank; 4636 PetscInt m,N,i,rstart,nnz; 4637 size_t len; 4638 const PetscInt *indx; 4639 PetscViewer out; 4640 char *name; 4641 Mat B; 4642 const PetscScalar *values; 4643 4644 PetscFunctionBegin; 4645 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4646 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4647 /* Should this be the type of the diagonal block of A? */ 4648 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4649 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4650 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4651 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4652 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4653 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4654 for (i=0; i<m; i++) { 4655 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4656 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4657 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4658 } 4659 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4660 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4661 4662 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4663 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4664 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4665 sprintf(name,"%s.%d",outfile,rank); 4666 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4667 ierr = PetscFree(name);CHKERRQ(ierr); 4668 ierr = MatView(B,out);CHKERRQ(ierr); 4669 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4670 ierr = MatDestroy(&B);CHKERRQ(ierr); 4671 PetscFunctionReturn(0); 4672 } 4673 4674 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4675 #undef __FUNCT__ 4676 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4677 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4678 { 4679 PetscErrorCode ierr; 4680 Mat_Merge_SeqsToMPI *merge; 4681 PetscContainer container; 4682 4683 PetscFunctionBegin; 4684 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4685 if (container) { 4686 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4687 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4688 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4689 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4690 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4691 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4692 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4693 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4694 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4695 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4696 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4697 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4698 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4699 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4700 ierr = PetscFree(merge);CHKERRQ(ierr); 4701 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4702 } 4703 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4704 PetscFunctionReturn(0); 4705 } 4706 4707 #include <../src/mat/utils/freespace.h> 4708 #include <petscbt.h> 4709 4710 #undef __FUNCT__ 4711 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4712 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4713 { 4714 PetscErrorCode ierr; 4715 MPI_Comm comm; 4716 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4717 PetscMPIInt size,rank,taga,*len_s; 4718 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4719 PetscInt proc,m; 4720 PetscInt **buf_ri,**buf_rj; 4721 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4722 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4723 MPI_Request *s_waits,*r_waits; 4724 MPI_Status *status; 4725 MatScalar *aa=a->a; 4726 MatScalar **abuf_r,*ba_i; 4727 Mat_Merge_SeqsToMPI *merge; 4728 PetscContainer container; 4729 4730 PetscFunctionBegin; 4731 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4732 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4733 4734 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4735 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4736 4737 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4738 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4739 4740 bi = merge->bi; 4741 bj = merge->bj; 4742 buf_ri = merge->buf_ri; 4743 buf_rj = merge->buf_rj; 4744 4745 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4746 owners = merge->rowmap->range; 4747 len_s = merge->len_s; 4748 4749 /* send and recv matrix values */ 4750 /*-----------------------------*/ 4751 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4752 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4753 4754 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4755 for (proc=0,k=0; proc<size; proc++) { 4756 if (!len_s[proc]) continue; 4757 i = owners[proc]; 4758 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4759 k++; 4760 } 4761 4762 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4763 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4764 ierr = PetscFree(status);CHKERRQ(ierr); 4765 4766 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4767 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4768 4769 /* insert mat values of mpimat */ 4770 /*----------------------------*/ 4771 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4772 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4773 4774 for (k=0; k<merge->nrecv; k++) { 4775 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4776 nrows = *(buf_ri_k[k]); 4777 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4778 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4779 } 4780 4781 /* set values of ba */ 4782 m = merge->rowmap->n; 4783 for (i=0; i<m; i++) { 4784 arow = owners[rank] + i; 4785 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4786 bnzi = bi[i+1] - bi[i]; 4787 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4788 4789 /* add local non-zero vals of this proc's seqmat into ba */ 4790 anzi = ai[arow+1] - ai[arow]; 4791 aj = a->j + ai[arow]; 4792 aa = a->a + ai[arow]; 4793 nextaj = 0; 4794 for (j=0; nextaj<anzi; j++) { 4795 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4796 ba_i[j] += aa[nextaj++]; 4797 } 4798 } 4799 4800 /* add received vals into ba */ 4801 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4802 /* i-th row */ 4803 if (i == *nextrow[k]) { 4804 anzi = *(nextai[k]+1) - *nextai[k]; 4805 aj = buf_rj[k] + *(nextai[k]); 4806 aa = abuf_r[k] + *(nextai[k]); 4807 nextaj = 0; 4808 for (j=0; nextaj<anzi; j++) { 4809 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4810 ba_i[j] += aa[nextaj++]; 4811 } 4812 } 4813 nextrow[k]++; nextai[k]++; 4814 } 4815 } 4816 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4817 } 4818 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4819 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4820 4821 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4822 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4823 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4824 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4825 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4826 PetscFunctionReturn(0); 4827 } 4828 4829 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4830 4831 #undef __FUNCT__ 4832 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4833 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4834 { 4835 PetscErrorCode ierr; 4836 Mat B_mpi; 4837 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4838 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4839 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4840 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4841 PetscInt len,proc,*dnz,*onz,bs,cbs; 4842 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4843 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4844 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4845 MPI_Status *status; 4846 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4847 PetscBT lnkbt; 4848 Mat_Merge_SeqsToMPI *merge; 4849 PetscContainer container; 4850 4851 PetscFunctionBegin; 4852 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4853 4854 /* make sure it is a PETSc comm */ 4855 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4856 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4857 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4858 4859 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4860 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4861 4862 /* determine row ownership */ 4863 /*---------------------------------------------------------*/ 4864 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4865 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4866 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4867 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4868 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4869 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4870 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4871 4872 m = merge->rowmap->n; 4873 owners = merge->rowmap->range; 4874 4875 /* determine the number of messages to send, their lengths */ 4876 /*---------------------------------------------------------*/ 4877 len_s = merge->len_s; 4878 4879 len = 0; /* length of buf_si[] */ 4880 merge->nsend = 0; 4881 for (proc=0; proc<size; proc++) { 4882 len_si[proc] = 0; 4883 if (proc == rank) { 4884 len_s[proc] = 0; 4885 } else { 4886 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4887 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4888 } 4889 if (len_s[proc]) { 4890 merge->nsend++; 4891 nrows = 0; 4892 for (i=owners[proc]; i<owners[proc+1]; i++) { 4893 if (ai[i+1] > ai[i]) nrows++; 4894 } 4895 len_si[proc] = 2*(nrows+1); 4896 len += len_si[proc]; 4897 } 4898 } 4899 4900 /* determine the number and length of messages to receive for ij-structure */ 4901 /*-------------------------------------------------------------------------*/ 4902 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4903 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4904 4905 /* post the Irecv of j-structure */ 4906 /*-------------------------------*/ 4907 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4908 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4909 4910 /* post the Isend of j-structure */ 4911 /*--------------------------------*/ 4912 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4913 4914 for (proc=0, k=0; proc<size; proc++) { 4915 if (!len_s[proc]) continue; 4916 i = owners[proc]; 4917 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4918 k++; 4919 } 4920 4921 /* receives and sends of j-structure are complete */ 4922 /*------------------------------------------------*/ 4923 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4924 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4925 4926 /* send and recv i-structure */ 4927 /*---------------------------*/ 4928 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4929 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4930 4931 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4932 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4933 for (proc=0,k=0; proc<size; proc++) { 4934 if (!len_s[proc]) continue; 4935 /* form outgoing message for i-structure: 4936 buf_si[0]: nrows to be sent 4937 [1:nrows]: row index (global) 4938 [nrows+1:2*nrows+1]: i-structure index 4939 */ 4940 /*-------------------------------------------*/ 4941 nrows = len_si[proc]/2 - 1; 4942 buf_si_i = buf_si + nrows+1; 4943 buf_si[0] = nrows; 4944 buf_si_i[0] = 0; 4945 nrows = 0; 4946 for (i=owners[proc]; i<owners[proc+1]; i++) { 4947 anzi = ai[i+1] - ai[i]; 4948 if (anzi) { 4949 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4950 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4951 nrows++; 4952 } 4953 } 4954 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4955 k++; 4956 buf_si += len_si[proc]; 4957 } 4958 4959 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4960 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4961 4962 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4963 for (i=0; i<merge->nrecv; i++) { 4964 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); 4965 } 4966 4967 ierr = PetscFree(len_si);CHKERRQ(ierr); 4968 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4969 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4970 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4971 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4972 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4973 ierr = PetscFree(status);CHKERRQ(ierr); 4974 4975 /* compute a local seq matrix in each processor */ 4976 /*----------------------------------------------*/ 4977 /* allocate bi array and free space for accumulating nonzero column info */ 4978 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4979 bi[0] = 0; 4980 4981 /* create and initialize a linked list */ 4982 nlnk = N+1; 4983 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4984 4985 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4986 len = ai[owners[rank+1]] - ai[owners[rank]]; 4987 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4988 4989 current_space = free_space; 4990 4991 /* determine symbolic info for each local row */ 4992 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4993 4994 for (k=0; k<merge->nrecv; k++) { 4995 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4996 nrows = *buf_ri_k[k]; 4997 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4998 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4999 } 5000 5001 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 5002 len = 0; 5003 for (i=0; i<m; i++) { 5004 bnzi = 0; 5005 /* add local non-zero cols of this proc's seqmat into lnk */ 5006 arow = owners[rank] + i; 5007 anzi = ai[arow+1] - ai[arow]; 5008 aj = a->j + ai[arow]; 5009 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 5010 bnzi += nlnk; 5011 /* add received col data into lnk */ 5012 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 5013 if (i == *nextrow[k]) { /* i-th row */ 5014 anzi = *(nextai[k]+1) - *nextai[k]; 5015 aj = buf_rj[k] + *nextai[k]; 5016 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 5017 bnzi += nlnk; 5018 nextrow[k]++; nextai[k]++; 5019 } 5020 } 5021 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 5022 5023 /* if free space is not available, make more free space */ 5024 if (current_space->local_remaining<bnzi) { 5025 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 5026 nspacedouble++; 5027 } 5028 /* copy data into free space, then initialize lnk */ 5029 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 5030 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 5031 5032 current_space->array += bnzi; 5033 current_space->local_used += bnzi; 5034 current_space->local_remaining -= bnzi; 5035 5036 bi[i+1] = bi[i] + bnzi; 5037 } 5038 5039 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5040 5041 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5042 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5043 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5044 5045 /* create symbolic parallel matrix B_mpi */ 5046 /*---------------------------------------*/ 5047 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5048 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5049 if (n==PETSC_DECIDE) { 5050 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5051 } else { 5052 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5053 } 5054 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5055 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5056 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5057 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5058 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5059 5060 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5061 B_mpi->assembled = PETSC_FALSE; 5062 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5063 merge->bi = bi; 5064 merge->bj = bj; 5065 merge->buf_ri = buf_ri; 5066 merge->buf_rj = buf_rj; 5067 merge->coi = NULL; 5068 merge->coj = NULL; 5069 merge->owners_co = NULL; 5070 5071 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5072 5073 /* attach the supporting struct to B_mpi for reuse */ 5074 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5075 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5076 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5077 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5078 *mpimat = B_mpi; 5079 5080 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5081 PetscFunctionReturn(0); 5082 } 5083 5084 #undef __FUNCT__ 5085 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5086 /*@C 5087 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5088 matrices from each processor 5089 5090 Collective on MPI_Comm 5091 5092 Input Parameters: 5093 + comm - the communicators the parallel matrix will live on 5094 . seqmat - the input sequential matrices 5095 . m - number of local rows (or PETSC_DECIDE) 5096 . n - number of local columns (or PETSC_DECIDE) 5097 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5098 5099 Output Parameter: 5100 . mpimat - the parallel matrix generated 5101 5102 Level: advanced 5103 5104 Notes: 5105 The dimensions of the sequential matrix in each processor MUST be the same. 5106 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5107 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5108 @*/ 5109 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5110 { 5111 PetscErrorCode ierr; 5112 PetscMPIInt size; 5113 5114 PetscFunctionBegin; 5115 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5116 if (size == 1) { 5117 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5118 if (scall == MAT_INITIAL_MATRIX) { 5119 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5120 } else { 5121 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5122 } 5123 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5124 PetscFunctionReturn(0); 5125 } 5126 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5127 if (scall == MAT_INITIAL_MATRIX) { 5128 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5129 } 5130 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5131 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5132 PetscFunctionReturn(0); 5133 } 5134 5135 #undef __FUNCT__ 5136 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5137 /*@ 5138 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5139 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5140 with MatGetSize() 5141 5142 Not Collective 5143 5144 Input Parameters: 5145 + A - the matrix 5146 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5147 5148 Output Parameter: 5149 . A_loc - the local sequential matrix generated 5150 5151 Level: developer 5152 5153 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5154 5155 @*/ 5156 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5157 { 5158 PetscErrorCode ierr; 5159 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5160 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5161 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5162 MatScalar *aa=a->a,*ba=b->a,*cam; 5163 PetscScalar *ca; 5164 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5165 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5166 PetscBool match; 5167 5168 PetscFunctionBegin; 5169 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5170 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5171 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5172 if (scall == MAT_INITIAL_MATRIX) { 5173 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5174 ci[0] = 0; 5175 for (i=0; i<am; i++) { 5176 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5177 } 5178 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5179 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5180 k = 0; 5181 for (i=0; i<am; i++) { 5182 ncols_o = bi[i+1] - bi[i]; 5183 ncols_d = ai[i+1] - ai[i]; 5184 /* off-diagonal portion of A */ 5185 for (jo=0; jo<ncols_o; jo++) { 5186 col = cmap[*bj]; 5187 if (col >= cstart) break; 5188 cj[k] = col; bj++; 5189 ca[k++] = *ba++; 5190 } 5191 /* diagonal portion of A */ 5192 for (j=0; j<ncols_d; j++) { 5193 cj[k] = cstart + *aj++; 5194 ca[k++] = *aa++; 5195 } 5196 /* off-diagonal portion of A */ 5197 for (j=jo; j<ncols_o; j++) { 5198 cj[k] = cmap[*bj++]; 5199 ca[k++] = *ba++; 5200 } 5201 } 5202 /* put together the new matrix */ 5203 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5204 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5205 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5206 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5207 mat->free_a = PETSC_TRUE; 5208 mat->free_ij = PETSC_TRUE; 5209 mat->nonew = 0; 5210 } else if (scall == MAT_REUSE_MATRIX) { 5211 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5212 ci = mat->i; cj = mat->j; cam = mat->a; 5213 for (i=0; i<am; i++) { 5214 /* off-diagonal portion of A */ 5215 ncols_o = bi[i+1] - bi[i]; 5216 for (jo=0; jo<ncols_o; jo++) { 5217 col = cmap[*bj]; 5218 if (col >= cstart) break; 5219 *cam++ = *ba++; bj++; 5220 } 5221 /* diagonal portion of A */ 5222 ncols_d = ai[i+1] - ai[i]; 5223 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5224 /* off-diagonal portion of A */ 5225 for (j=jo; j<ncols_o; j++) { 5226 *cam++ = *ba++; bj++; 5227 } 5228 } 5229 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5230 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5231 PetscFunctionReturn(0); 5232 } 5233 5234 #undef __FUNCT__ 5235 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5236 /*@C 5237 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5238 5239 Not Collective 5240 5241 Input Parameters: 5242 + A - the matrix 5243 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5244 - row, col - index sets of rows and columns to extract (or NULL) 5245 5246 Output Parameter: 5247 . A_loc - the local sequential matrix generated 5248 5249 Level: developer 5250 5251 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5252 5253 @*/ 5254 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5255 { 5256 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5257 PetscErrorCode ierr; 5258 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5259 IS isrowa,iscola; 5260 Mat *aloc; 5261 PetscBool match; 5262 5263 PetscFunctionBegin; 5264 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5265 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5266 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5267 if (!row) { 5268 start = A->rmap->rstart; end = A->rmap->rend; 5269 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5270 } else { 5271 isrowa = *row; 5272 } 5273 if (!col) { 5274 start = A->cmap->rstart; 5275 cmap = a->garray; 5276 nzA = a->A->cmap->n; 5277 nzB = a->B->cmap->n; 5278 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5279 ncols = 0; 5280 for (i=0; i<nzB; i++) { 5281 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5282 else break; 5283 } 5284 imark = i; 5285 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5286 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5287 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5288 } else { 5289 iscola = *col; 5290 } 5291 if (scall != MAT_INITIAL_MATRIX) { 5292 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5293 aloc[0] = *A_loc; 5294 } 5295 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5296 *A_loc = aloc[0]; 5297 ierr = PetscFree(aloc);CHKERRQ(ierr); 5298 if (!row) { 5299 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5300 } 5301 if (!col) { 5302 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5303 } 5304 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5305 PetscFunctionReturn(0); 5306 } 5307 5308 #undef __FUNCT__ 5309 #define __FUNCT__ "MatGetBrowsOfAcols" 5310 /*@C 5311 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5312 5313 Collective on Mat 5314 5315 Input Parameters: 5316 + A,B - the matrices in mpiaij format 5317 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5318 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5319 5320 Output Parameter: 5321 + rowb, colb - index sets of rows and columns of B to extract 5322 - B_seq - the sequential matrix generated 5323 5324 Level: developer 5325 5326 @*/ 5327 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5328 { 5329 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5330 PetscErrorCode ierr; 5331 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5332 IS isrowb,iscolb; 5333 Mat *bseq=NULL; 5334 5335 PetscFunctionBegin; 5336 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5337 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); 5338 } 5339 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5340 5341 if (scall == MAT_INITIAL_MATRIX) { 5342 start = A->cmap->rstart; 5343 cmap = a->garray; 5344 nzA = a->A->cmap->n; 5345 nzB = a->B->cmap->n; 5346 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5347 ncols = 0; 5348 for (i=0; i<nzB; i++) { /* row < local row index */ 5349 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5350 else break; 5351 } 5352 imark = i; 5353 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5354 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5355 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5356 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5357 } else { 5358 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5359 isrowb = *rowb; iscolb = *colb; 5360 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5361 bseq[0] = *B_seq; 5362 } 5363 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5364 *B_seq = bseq[0]; 5365 ierr = PetscFree(bseq);CHKERRQ(ierr); 5366 if (!rowb) { 5367 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5368 } else { 5369 *rowb = isrowb; 5370 } 5371 if (!colb) { 5372 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5373 } else { 5374 *colb = iscolb; 5375 } 5376 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5377 PetscFunctionReturn(0); 5378 } 5379 5380 #undef __FUNCT__ 5381 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5382 /* 5383 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5384 of the OFF-DIAGONAL portion of local A 5385 5386 Collective on Mat 5387 5388 Input Parameters: 5389 + A,B - the matrices in mpiaij format 5390 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5391 5392 Output Parameter: 5393 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5394 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5395 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5396 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5397 5398 Level: developer 5399 5400 */ 5401 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5402 { 5403 VecScatter_MPI_General *gen_to,*gen_from; 5404 PetscErrorCode ierr; 5405 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5406 Mat_SeqAIJ *b_oth; 5407 VecScatter ctx =a->Mvctx; 5408 MPI_Comm comm; 5409 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5410 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5411 PetscScalar *rvalues,*svalues; 5412 MatScalar *b_otha,*bufa,*bufA; 5413 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5414 MPI_Request *rwaits = NULL,*swaits = NULL; 5415 MPI_Status *sstatus,rstatus; 5416 PetscMPIInt jj; 5417 PetscInt *cols,sbs,rbs; 5418 PetscScalar *vals; 5419 5420 PetscFunctionBegin; 5421 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5422 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5423 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); 5424 } 5425 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5426 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5427 5428 gen_to = (VecScatter_MPI_General*)ctx->todata; 5429 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5430 rvalues = gen_from->values; /* holds the length of receiving row */ 5431 svalues = gen_to->values; /* holds the length of sending row */ 5432 nrecvs = gen_from->n; 5433 nsends = gen_to->n; 5434 5435 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5436 srow = gen_to->indices; /* local row index to be sent */ 5437 sstarts = gen_to->starts; 5438 sprocs = gen_to->procs; 5439 sstatus = gen_to->sstatus; 5440 sbs = gen_to->bs; 5441 rstarts = gen_from->starts; 5442 rprocs = gen_from->procs; 5443 rbs = gen_from->bs; 5444 5445 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5446 if (scall == MAT_INITIAL_MATRIX) { 5447 /* i-array */ 5448 /*---------*/ 5449 /* post receives */ 5450 for (i=0; i<nrecvs; i++) { 5451 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5452 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5453 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5454 } 5455 5456 /* pack the outgoing message */ 5457 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5458 5459 sstartsj[0] = 0; 5460 rstartsj[0] = 0; 5461 len = 0; /* total length of j or a array to be sent */ 5462 k = 0; 5463 for (i=0; i<nsends; i++) { 5464 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5465 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5466 for (j=0; j<nrows; j++) { 5467 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5468 for (l=0; l<sbs; l++) { 5469 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5470 5471 rowlen[j*sbs+l] = ncols; 5472 5473 len += ncols; 5474 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5475 } 5476 k++; 5477 } 5478 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5479 5480 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5481 } 5482 /* recvs and sends of i-array are completed */ 5483 i = nrecvs; 5484 while (i--) { 5485 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5486 } 5487 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5488 5489 /* allocate buffers for sending j and a arrays */ 5490 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5491 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5492 5493 /* create i-array of B_oth */ 5494 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5495 5496 b_othi[0] = 0; 5497 len = 0; /* total length of j or a array to be received */ 5498 k = 0; 5499 for (i=0; i<nrecvs; i++) { 5500 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5501 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5502 for (j=0; j<nrows; j++) { 5503 b_othi[k+1] = b_othi[k] + rowlen[j]; 5504 len += rowlen[j]; k++; 5505 } 5506 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5507 } 5508 5509 /* allocate space for j and a arrrays of B_oth */ 5510 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5511 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5512 5513 /* j-array */ 5514 /*---------*/ 5515 /* post receives of j-array */ 5516 for (i=0; i<nrecvs; i++) { 5517 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5518 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5519 } 5520 5521 /* pack the outgoing message j-array */ 5522 k = 0; 5523 for (i=0; i<nsends; i++) { 5524 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5525 bufJ = bufj+sstartsj[i]; 5526 for (j=0; j<nrows; j++) { 5527 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5528 for (ll=0; ll<sbs; ll++) { 5529 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5530 for (l=0; l<ncols; l++) { 5531 *bufJ++ = cols[l]; 5532 } 5533 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5534 } 5535 } 5536 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5537 } 5538 5539 /* recvs and sends of j-array are completed */ 5540 i = nrecvs; 5541 while (i--) { 5542 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5543 } 5544 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5545 } else if (scall == MAT_REUSE_MATRIX) { 5546 sstartsj = *startsj_s; 5547 rstartsj = *startsj_r; 5548 bufa = *bufa_ptr; 5549 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5550 b_otha = b_oth->a; 5551 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5552 5553 /* a-array */ 5554 /*---------*/ 5555 /* post receives of a-array */ 5556 for (i=0; i<nrecvs; i++) { 5557 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5558 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5559 } 5560 5561 /* pack the outgoing message a-array */ 5562 k = 0; 5563 for (i=0; i<nsends; i++) { 5564 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5565 bufA = bufa+sstartsj[i]; 5566 for (j=0; j<nrows; j++) { 5567 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5568 for (ll=0; ll<sbs; ll++) { 5569 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5570 for (l=0; l<ncols; l++) { 5571 *bufA++ = vals[l]; 5572 } 5573 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5574 } 5575 } 5576 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5577 } 5578 /* recvs and sends of a-array are completed */ 5579 i = nrecvs; 5580 while (i--) { 5581 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5582 } 5583 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5584 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5585 5586 if (scall == MAT_INITIAL_MATRIX) { 5587 /* put together the new matrix */ 5588 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5589 5590 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5591 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5592 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5593 b_oth->free_a = PETSC_TRUE; 5594 b_oth->free_ij = PETSC_TRUE; 5595 b_oth->nonew = 0; 5596 5597 ierr = PetscFree(bufj);CHKERRQ(ierr); 5598 if (!startsj_s || !bufa_ptr) { 5599 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5600 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5601 } else { 5602 *startsj_s = sstartsj; 5603 *startsj_r = rstartsj; 5604 *bufa_ptr = bufa; 5605 } 5606 } 5607 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5608 PetscFunctionReturn(0); 5609 } 5610 5611 #undef __FUNCT__ 5612 #define __FUNCT__ "MatGetCommunicationStructs" 5613 /*@C 5614 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5615 5616 Not Collective 5617 5618 Input Parameters: 5619 . A - The matrix in mpiaij format 5620 5621 Output Parameter: 5622 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5623 . colmap - A map from global column index to local index into lvec 5624 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5625 5626 Level: developer 5627 5628 @*/ 5629 #if defined(PETSC_USE_CTABLE) 5630 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5631 #else 5632 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5633 #endif 5634 { 5635 Mat_MPIAIJ *a; 5636 5637 PetscFunctionBegin; 5638 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5639 PetscValidPointer(lvec, 2); 5640 PetscValidPointer(colmap, 3); 5641 PetscValidPointer(multScatter, 4); 5642 a = (Mat_MPIAIJ*) A->data; 5643 if (lvec) *lvec = a->lvec; 5644 if (colmap) *colmap = a->colmap; 5645 if (multScatter) *multScatter = a->Mvctx; 5646 PetscFunctionReturn(0); 5647 } 5648 5649 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5650 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5651 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5652 5653 #undef __FUNCT__ 5654 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5655 /* 5656 Computes (B'*A')' since computing B*A directly is untenable 5657 5658 n p p 5659 ( ) ( ) ( ) 5660 m ( A ) * n ( B ) = m ( C ) 5661 ( ) ( ) ( ) 5662 5663 */ 5664 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5665 { 5666 PetscErrorCode ierr; 5667 Mat At,Bt,Ct; 5668 5669 PetscFunctionBegin; 5670 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5671 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5672 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5673 ierr = MatDestroy(&At);CHKERRQ(ierr); 5674 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5675 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5676 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5677 PetscFunctionReturn(0); 5678 } 5679 5680 #undef __FUNCT__ 5681 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5682 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5683 { 5684 PetscErrorCode ierr; 5685 PetscInt m=A->rmap->n,n=B->cmap->n; 5686 Mat Cmat; 5687 5688 PetscFunctionBegin; 5689 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); 5690 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5691 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5692 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5693 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5694 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5695 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5696 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5697 5698 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5699 5700 *C = Cmat; 5701 PetscFunctionReturn(0); 5702 } 5703 5704 /* ----------------------------------------------------------------*/ 5705 #undef __FUNCT__ 5706 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5707 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5708 { 5709 PetscErrorCode ierr; 5710 5711 PetscFunctionBegin; 5712 if (scall == MAT_INITIAL_MATRIX) { 5713 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5714 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5715 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5716 } 5717 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5718 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5719 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5720 PetscFunctionReturn(0); 5721 } 5722 5723 #if defined(PETSC_HAVE_MUMPS) 5724 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5725 #endif 5726 #if defined(PETSC_HAVE_PASTIX) 5727 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5728 #endif 5729 #if defined(PETSC_HAVE_SUPERLU_DIST) 5730 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5731 #endif 5732 #if defined(PETSC_HAVE_CLIQUE) 5733 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5734 #endif 5735 5736 /*MC 5737 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5738 5739 Options Database Keys: 5740 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5741 5742 Level: beginner 5743 5744 .seealso: MatCreateAIJ() 5745 M*/ 5746 5747 #undef __FUNCT__ 5748 #define __FUNCT__ "MatCreate_MPIAIJ" 5749 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5750 { 5751 Mat_MPIAIJ *b; 5752 PetscErrorCode ierr; 5753 PetscMPIInt size; 5754 5755 PetscFunctionBegin; 5756 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5757 5758 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5759 B->data = (void*)b; 5760 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5761 B->assembled = PETSC_FALSE; 5762 B->insertmode = NOT_SET_VALUES; 5763 b->size = size; 5764 5765 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5766 5767 /* build cache for off array entries formed */ 5768 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5769 5770 b->donotstash = PETSC_FALSE; 5771 b->colmap = 0; 5772 b->garray = 0; 5773 b->roworiented = PETSC_TRUE; 5774 5775 /* stuff used for matrix vector multiply */ 5776 b->lvec = NULL; 5777 b->Mvctx = NULL; 5778 5779 /* stuff for MatGetRow() */ 5780 b->rowindices = 0; 5781 b->rowvalues = 0; 5782 b->getrowactive = PETSC_FALSE; 5783 5784 /* flexible pointer used in CUSP/CUSPARSE classes */ 5785 b->spptr = NULL; 5786 5787 #if defined(PETSC_HAVE_MUMPS) 5788 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5789 #endif 5790 #if defined(PETSC_HAVE_PASTIX) 5791 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5792 #endif 5793 #if defined(PETSC_HAVE_SUPERLU_DIST) 5794 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5795 #endif 5796 #if defined(PETSC_HAVE_CLIQUE) 5797 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5798 #endif 5799 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5800 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5801 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5802 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5803 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5804 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5805 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5806 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5807 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5808 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5809 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5810 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5811 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5812 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5813 PetscFunctionReturn(0); 5814 } 5815 5816 #undef __FUNCT__ 5817 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5818 /*@ 5819 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5820 and "off-diagonal" part of the matrix in CSR format. 5821 5822 Collective on MPI_Comm 5823 5824 Input Parameters: 5825 + comm - MPI communicator 5826 . m - number of local rows (Cannot be PETSC_DECIDE) 5827 . n - This value should be the same as the local size used in creating the 5828 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5829 calculated if N is given) For square matrices n is almost always m. 5830 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5831 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5832 . i - row indices for "diagonal" portion of matrix 5833 . j - column indices 5834 . a - matrix values 5835 . oi - row indices for "off-diagonal" portion of matrix 5836 . oj - column indices 5837 - oa - matrix values 5838 5839 Output Parameter: 5840 . mat - the matrix 5841 5842 Level: advanced 5843 5844 Notes: 5845 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5846 must free the arrays once the matrix has been destroyed and not before. 5847 5848 The i and j indices are 0 based 5849 5850 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5851 5852 This sets local rows and cannot be used to set off-processor values. 5853 5854 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5855 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5856 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5857 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5858 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5859 communication if it is known that only local entries will be set. 5860 5861 .keywords: matrix, aij, compressed row, sparse, parallel 5862 5863 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5864 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5865 @*/ 5866 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) 5867 { 5868 PetscErrorCode ierr; 5869 Mat_MPIAIJ *maij; 5870 5871 PetscFunctionBegin; 5872 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5873 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5874 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5875 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5876 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5877 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5878 maij = (Mat_MPIAIJ*) (*mat)->data; 5879 5880 (*mat)->preallocated = PETSC_TRUE; 5881 5882 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5883 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5884 5885 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5886 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5887 5888 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5889 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5890 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5891 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5892 5893 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5894 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5895 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5896 PetscFunctionReturn(0); 5897 } 5898 5899 /* 5900 Special version for direct calls from Fortran 5901 */ 5902 #include <petsc-private/fortranimpl.h> 5903 5904 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5905 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5906 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5907 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5908 #endif 5909 5910 /* Change these macros so can be used in void function */ 5911 #undef CHKERRQ 5912 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5913 #undef SETERRQ2 5914 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5915 #undef SETERRQ3 5916 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5917 #undef SETERRQ 5918 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5919 5920 #undef __FUNCT__ 5921 #define __FUNCT__ "matsetvaluesmpiaij_" 5922 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) 5923 { 5924 Mat mat = *mmat; 5925 PetscInt m = *mm, n = *mn; 5926 InsertMode addv = *maddv; 5927 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5928 PetscScalar value; 5929 PetscErrorCode ierr; 5930 5931 MatCheckPreallocated(mat,1); 5932 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5933 5934 #if defined(PETSC_USE_DEBUG) 5935 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5936 #endif 5937 { 5938 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5939 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5940 PetscBool roworiented = aij->roworiented; 5941 5942 /* Some Variables required in the macro */ 5943 Mat A = aij->A; 5944 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5945 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5946 MatScalar *aa = a->a; 5947 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5948 Mat B = aij->B; 5949 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5950 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5951 MatScalar *ba = b->a; 5952 5953 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5954 PetscInt nonew = a->nonew; 5955 MatScalar *ap1,*ap2; 5956 5957 PetscFunctionBegin; 5958 for (i=0; i<m; i++) { 5959 if (im[i] < 0) continue; 5960 #if defined(PETSC_USE_DEBUG) 5961 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); 5962 #endif 5963 if (im[i] >= rstart && im[i] < rend) { 5964 row = im[i] - rstart; 5965 lastcol1 = -1; 5966 rp1 = aj + ai[row]; 5967 ap1 = aa + ai[row]; 5968 rmax1 = aimax[row]; 5969 nrow1 = ailen[row]; 5970 low1 = 0; 5971 high1 = nrow1; 5972 lastcol2 = -1; 5973 rp2 = bj + bi[row]; 5974 ap2 = ba + bi[row]; 5975 rmax2 = bimax[row]; 5976 nrow2 = bilen[row]; 5977 low2 = 0; 5978 high2 = nrow2; 5979 5980 for (j=0; j<n; j++) { 5981 if (roworiented) value = v[i*n+j]; 5982 else value = v[i+j*m]; 5983 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5984 if (in[j] >= cstart && in[j] < cend) { 5985 col = in[j] - cstart; 5986 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5987 } else if (in[j] < 0) continue; 5988 #if defined(PETSC_USE_DEBUG) 5989 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); 5990 #endif 5991 else { 5992 if (mat->was_assembled) { 5993 if (!aij->colmap) { 5994 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5995 } 5996 #if defined(PETSC_USE_CTABLE) 5997 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5998 col--; 5999 #else 6000 col = aij->colmap[in[j]] - 1; 6001 #endif 6002 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 6003 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 6004 col = in[j]; 6005 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 6006 B = aij->B; 6007 b = (Mat_SeqAIJ*)B->data; 6008 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 6009 rp2 = bj + bi[row]; 6010 ap2 = ba + bi[row]; 6011 rmax2 = bimax[row]; 6012 nrow2 = bilen[row]; 6013 low2 = 0; 6014 high2 = nrow2; 6015 bm = aij->B->rmap->n; 6016 ba = b->a; 6017 } 6018 } else col = in[j]; 6019 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 6020 } 6021 } 6022 } else if (!aij->donotstash) { 6023 if (roworiented) { 6024 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6025 } else { 6026 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6027 } 6028 } 6029 } 6030 } 6031 PetscFunctionReturnVoid(); 6032 } 6033 6034