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_interlaced" 2556 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm; 2560 PetscErrorCode ierr; 2561 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2562 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2563 PetscInt *rowrange = mat->rmap->range; 2564 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2565 Mat A = aij->A,B=aij->B,C=*matredundant; 2566 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2567 PetscScalar *sbuf_a; 2568 PetscInt nzlocal=a->nz+b->nz; 2569 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2570 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2571 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2572 MatScalar *aworkA,*aworkB; 2573 PetscScalar *vals; 2574 PetscMPIInt tag1,tag2,tag3,imdex; 2575 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2576 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2577 MPI_Status recv_status,*send_status; 2578 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2579 PetscInt **rbuf_j=NULL; 2580 PetscScalar **rbuf_a=NULL; 2581 Mat_Redundant *redund =NULL; 2582 2583 PetscFunctionBegin; 2584 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2587 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2588 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2589 2590 if (reuse == MAT_REUSE_MATRIX) { 2591 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2592 if (subsize == 1) { 2593 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2594 redund = c->redundant; 2595 } else { 2596 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2597 redund = c->redundant; 2598 } 2599 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2600 2601 nsends = redund->nsends; 2602 nrecvs = redund->nrecvs; 2603 send_rank = redund->send_rank; 2604 recv_rank = redund->recv_rank; 2605 sbuf_nz = redund->sbuf_nz; 2606 rbuf_nz = redund->rbuf_nz; 2607 sbuf_j = redund->sbuf_j; 2608 sbuf_a = redund->sbuf_a; 2609 rbuf_j = redund->rbuf_j; 2610 rbuf_a = redund->rbuf_a; 2611 } 2612 2613 if (reuse == MAT_INITIAL_MATRIX) { 2614 PetscInt nleftover,np_subcomm; 2615 2616 /* get the destination processors' id send_rank, nsends and nrecvs */ 2617 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2618 2619 np_subcomm = size/nsubcomm; 2620 nleftover = size - nsubcomm*np_subcomm; 2621 2622 /* block of codes below is specific for INTERLACED */ 2623 /* ------------------------------------------------*/ 2624 nsends = 0; nrecvs = 0; 2625 for (i=0; i<size; i++) { 2626 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2627 send_rank[nsends++] = i; 2628 recv_rank[nrecvs++] = i; 2629 } 2630 } 2631 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2632 i = size-nleftover-1; 2633 j = 0; 2634 while (j < nsubcomm - nleftover) { 2635 send_rank[nsends++] = i; 2636 i--; j++; 2637 } 2638 } 2639 2640 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2641 for (i=0; i<nleftover; i++) { 2642 recv_rank[nrecvs++] = size-nleftover+i; 2643 } 2644 } 2645 /*----------------------------------------------*/ 2646 2647 /* allocate sbuf_j, sbuf_a */ 2648 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2649 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2650 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2651 /* 2652 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2653 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2654 */ 2655 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2656 2657 /* copy mat's local entries into the buffers */ 2658 if (reuse == MAT_INITIAL_MATRIX) { 2659 rownz_max = 0; 2660 rptr = sbuf_j; 2661 cols = sbuf_j + rend-rstart + 1; 2662 vals = sbuf_a; 2663 rptr[0] = 0; 2664 for (i=0; i<rend-rstart; i++) { 2665 row = i + rstart; 2666 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2667 ncols = nzA + nzB; 2668 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2669 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2670 /* load the column indices for this row into cols */ 2671 lwrite = 0; 2672 for (l=0; l<nzB; l++) { 2673 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2674 vals[lwrite] = aworkB[l]; 2675 cols[lwrite++] = ctmp; 2676 } 2677 } 2678 for (l=0; l<nzA; l++) { 2679 vals[lwrite] = aworkA[l]; 2680 cols[lwrite++] = cstart + cworkA[l]; 2681 } 2682 for (l=0; l<nzB; l++) { 2683 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2684 vals[lwrite] = aworkB[l]; 2685 cols[lwrite++] = ctmp; 2686 } 2687 } 2688 vals += ncols; 2689 cols += ncols; 2690 rptr[i+1] = rptr[i] + ncols; 2691 if (rownz_max < ncols) rownz_max = ncols; 2692 } 2693 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2694 } else { /* only copy matrix values into sbuf_a */ 2695 rptr = sbuf_j; 2696 vals = sbuf_a; 2697 rptr[0] = 0; 2698 for (i=0; i<rend-rstart; i++) { 2699 row = i + rstart; 2700 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2701 ncols = nzA + nzB; 2702 cworkB = b->j + b->i[i]; 2703 aworkA = a->a + a->i[i]; 2704 aworkB = b->a + b->i[i]; 2705 lwrite = 0; 2706 for (l=0; l<nzB; l++) { 2707 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2708 } 2709 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2710 for (l=0; l<nzB; l++) { 2711 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2712 } 2713 vals += ncols; 2714 rptr[i+1] = rptr[i] + ncols; 2715 } 2716 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2717 2718 /* send nzlocal to others, and recv other's nzlocal */ 2719 /*--------------------------------------------------*/ 2720 if (reuse == MAT_INITIAL_MATRIX) { 2721 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2722 2723 s_waits2 = s_waits3 + nsends; 2724 s_waits1 = s_waits2 + nsends; 2725 r_waits1 = s_waits1 + nsends; 2726 r_waits2 = r_waits1 + nrecvs; 2727 r_waits3 = r_waits2 + nrecvs; 2728 } else { 2729 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2730 2731 r_waits3 = s_waits3 + nsends; 2732 } 2733 2734 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2735 if (reuse == MAT_INITIAL_MATRIX) { 2736 /* get new tags to keep the communication clean */ 2737 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2738 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2739 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2740 2741 /* post receives of other's nzlocal */ 2742 for (i=0; i<nrecvs; i++) { 2743 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2744 } 2745 /* send nzlocal to others */ 2746 for (i=0; i<nsends; i++) { 2747 sbuf_nz[i] = nzlocal; 2748 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2749 } 2750 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2751 count = nrecvs; 2752 while (count) { 2753 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2754 2755 recv_rank[imdex] = recv_status.MPI_SOURCE; 2756 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2757 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2758 2759 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2760 2761 rbuf_nz[imdex] += i + 2; 2762 2763 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2764 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2765 count--; 2766 } 2767 /* wait on sends of nzlocal */ 2768 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2769 /* send mat->i,j to others, and recv from other's */ 2770 /*------------------------------------------------*/ 2771 for (i=0; i<nsends; i++) { 2772 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2773 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2774 } 2775 /* wait on receives of mat->i,j */ 2776 /*------------------------------*/ 2777 count = nrecvs; 2778 while (count) { 2779 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2780 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2781 count--; 2782 } 2783 /* wait on sends of mat->i,j */ 2784 /*---------------------------*/ 2785 if (nsends) { 2786 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2787 } 2788 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2789 2790 /* post receives, send and receive mat->a */ 2791 /*----------------------------------------*/ 2792 for (imdex=0; imdex<nrecvs; imdex++) { 2793 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2794 } 2795 for (i=0; i<nsends; i++) { 2796 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2797 } 2798 count = nrecvs; 2799 while (count) { 2800 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2801 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2802 count--; 2803 } 2804 if (nsends) { 2805 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2806 } 2807 2808 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2809 2810 /* create redundant matrix */ 2811 /*-------------------------*/ 2812 if (reuse == MAT_INITIAL_MATRIX) { 2813 const PetscInt *range; 2814 PetscInt rstart_sub,rend_sub,mloc_sub; 2815 2816 /* compute rownz_max for preallocation */ 2817 for (imdex=0; imdex<nrecvs; imdex++) { 2818 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2819 rptr = rbuf_j[imdex]; 2820 for (i=0; i<j; i++) { 2821 ncols = rptr[i+1] - rptr[i]; 2822 if (rownz_max < ncols) rownz_max = ncols; 2823 } 2824 } 2825 2826 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2827 2828 /* get local size of redundant matrix 2829 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2830 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2831 rstart_sub = range[nsubcomm*subrank]; 2832 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2833 rend_sub = range[nsubcomm*(subrank+1)]; 2834 } else { 2835 rend_sub = mat->rmap->N; 2836 } 2837 mloc_sub = rend_sub - rstart_sub; 2838 2839 if (M == N) { 2840 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2841 } else { /* non-square matrix */ 2842 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2843 } 2844 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2845 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2846 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2847 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2848 } else { 2849 C = *matredundant; 2850 } 2851 2852 /* insert local matrix entries */ 2853 rptr = sbuf_j; 2854 cols = sbuf_j + rend-rstart + 1; 2855 vals = sbuf_a; 2856 for (i=0; i<rend-rstart; i++) { 2857 row = i + rstart; 2858 ncols = rptr[i+1] - rptr[i]; 2859 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2860 vals += ncols; 2861 cols += ncols; 2862 } 2863 /* insert received matrix entries */ 2864 for (imdex=0; imdex<nrecvs; imdex++) { 2865 rstart = rowrange[recv_rank[imdex]]; 2866 rend = rowrange[recv_rank[imdex]+1]; 2867 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2868 rptr = rbuf_j[imdex]; 2869 cols = rbuf_j[imdex] + rend-rstart + 1; 2870 vals = rbuf_a[imdex]; 2871 for (i=0; i<rend-rstart; i++) { 2872 row = i + rstart; 2873 ncols = rptr[i+1] - rptr[i]; 2874 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2875 vals += ncols; 2876 cols += ncols; 2877 } 2878 } 2879 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2880 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2881 2882 if (reuse == MAT_INITIAL_MATRIX) { 2883 *matredundant = C; 2884 2885 /* create a supporting struct and attach it to C for reuse */ 2886 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2887 if (subsize == 1) { 2888 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2889 c->redundant = redund; 2890 } else { 2891 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2892 c->redundant = redund; 2893 } 2894 2895 redund->nzlocal = nzlocal; 2896 redund->nsends = nsends; 2897 redund->nrecvs = nrecvs; 2898 redund->send_rank = send_rank; 2899 redund->recv_rank = recv_rank; 2900 redund->sbuf_nz = sbuf_nz; 2901 redund->rbuf_nz = rbuf_nz; 2902 redund->sbuf_j = sbuf_j; 2903 redund->sbuf_a = sbuf_a; 2904 redund->rbuf_j = rbuf_j; 2905 redund->rbuf_a = rbuf_a; 2906 redund->psubcomm = NULL; 2907 2908 redund->Destroy = C->ops->destroy; 2909 C->ops->destroy = MatDestroy_MatRedundant; 2910 } 2911 PetscFunctionReturn(0); 2912 } 2913 2914 #undef __FUNCT__ 2915 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2916 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2917 { 2918 PetscErrorCode ierr; 2919 MPI_Comm comm; 2920 PetscMPIInt size,subsize; 2921 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2922 Mat_Redundant *redund=NULL; 2923 PetscSubcomm psubcomm=NULL,psubcomm_in=NULL; 2924 MPI_Comm subcomm_in=subcomm; 2925 2926 PetscFunctionBegin; 2927 if (subcomm_in == MPI_COMM_NULL) { /* get subcomm=psubcomm->comm */ 2928 if (reuse == MAT_INITIAL_MATRIX) { 2929 if (psubcomm_in == NULL) { /* user does not provide psubcomm, create it here */ 2930 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2931 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2932 if (nsubcomm < 1 || nsubcomm > size) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"nsubcomm must between 1 and %D",size); 2933 2934 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2935 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2936 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2937 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2938 } 2939 subcomm = psubcomm->comm; 2940 } else { /* retrieve psubcomm and subcomm */ 2941 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2942 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2943 if (subsize == 1) { 2944 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2945 redund = c->redundant; 2946 } else { 2947 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2948 redund = c->redundant; 2949 } 2950 psubcomm = redund->psubcomm; 2951 } 2952 if (subcomm_in == MPI_COMM_NULL && psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2953 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2954 } 2955 } 2956 2957 if (subcomm_in != MPI_COMM_NULL) { 2958 /* use MPI subcomm_in via MatGetSubMatrices() */ 2959 Mat *matseq; 2960 IS isrow,iscol; 2961 2962 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2963 if (reuse == MAT_INITIAL_MATRIX) { 2964 /* create a local sequential matrix matseq[0] */ 2965 mloc_sub = PETSC_DECIDE; 2966 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2967 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2968 rstart = rend - mloc_sub; 2969 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2970 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2971 } else { /* reuse == MAT_REUSE_MATRIX */ 2972 if (subsize == 1) { 2973 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2974 redund = c->redundant; 2975 } else { 2976 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2977 redund = c->redundant; 2978 } 2979 2980 isrow = redund->isrow; 2981 iscol = redund->iscol; 2982 matseq = redund->matseq; 2983 } 2984 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2985 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2986 2987 if (reuse == MAT_INITIAL_MATRIX) { 2988 /* create a supporting struct and attach it to C for reuse */ 2989 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 2990 if (subsize == 1) { 2991 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2992 c->redundant = redund; 2993 } else { 2994 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2995 c->redundant = redund; 2996 } 2997 redund->isrow = isrow; 2998 redund->iscol = iscol; 2999 redund->matseq = matseq; 3000 redund->psubcomm = NULL; 3001 redund->Destroy = (*matredundant)->ops->destroy; 3002 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3003 } 3004 } 3005 3006 if (psubcomm && reuse == MAT_INITIAL_MATRIX) { 3007 /* if psubcomm is created in this routine, free it in MatDestroy_MatRedundant() */ 3008 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 3009 if (subsize == 1) { 3010 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3011 c->redundant->psubcomm = psubcomm; 3012 } else { 3013 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3014 c->redundant->psubcomm = psubcomm ; 3015 } 3016 } 3017 PetscFunctionReturn(0); 3018 } 3019 3020 #undef __FUNCT__ 3021 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3022 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3023 { 3024 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3025 PetscErrorCode ierr; 3026 PetscInt i,*idxb = 0; 3027 PetscScalar *va,*vb; 3028 Vec vtmp; 3029 3030 PetscFunctionBegin; 3031 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3032 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3033 if (idx) { 3034 for (i=0; i<A->rmap->n; i++) { 3035 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3036 } 3037 } 3038 3039 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3040 if (idx) { 3041 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3042 } 3043 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3044 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3045 3046 for (i=0; i<A->rmap->n; i++) { 3047 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3048 va[i] = vb[i]; 3049 if (idx) idx[i] = a->garray[idxb[i]]; 3050 } 3051 } 3052 3053 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3054 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3055 ierr = PetscFree(idxb);CHKERRQ(ierr); 3056 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3057 PetscFunctionReturn(0); 3058 } 3059 3060 #undef __FUNCT__ 3061 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3062 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3063 { 3064 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3065 PetscErrorCode ierr; 3066 PetscInt i,*idxb = 0; 3067 PetscScalar *va,*vb; 3068 Vec vtmp; 3069 3070 PetscFunctionBegin; 3071 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3072 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3073 if (idx) { 3074 for (i=0; i<A->cmap->n; i++) { 3075 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3076 } 3077 } 3078 3079 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3080 if (idx) { 3081 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3082 } 3083 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3084 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3085 3086 for (i=0; i<A->rmap->n; i++) { 3087 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3088 va[i] = vb[i]; 3089 if (idx) idx[i] = a->garray[idxb[i]]; 3090 } 3091 } 3092 3093 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3094 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3095 ierr = PetscFree(idxb);CHKERRQ(ierr); 3096 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3097 PetscFunctionReturn(0); 3098 } 3099 3100 #undef __FUNCT__ 3101 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3102 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3103 { 3104 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3105 PetscInt n = A->rmap->n; 3106 PetscInt cstart = A->cmap->rstart; 3107 PetscInt *cmap = mat->garray; 3108 PetscInt *diagIdx, *offdiagIdx; 3109 Vec diagV, offdiagV; 3110 PetscScalar *a, *diagA, *offdiagA; 3111 PetscInt r; 3112 PetscErrorCode ierr; 3113 3114 PetscFunctionBegin; 3115 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3116 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3117 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3118 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3119 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3120 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3121 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3122 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3123 for (r = 0; r < n; ++r) { 3124 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3125 a[r] = diagA[r]; 3126 idx[r] = cstart + diagIdx[r]; 3127 } else { 3128 a[r] = offdiagA[r]; 3129 idx[r] = cmap[offdiagIdx[r]]; 3130 } 3131 } 3132 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3133 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3134 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3135 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3136 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3137 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3138 PetscFunctionReturn(0); 3139 } 3140 3141 #undef __FUNCT__ 3142 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3143 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3144 { 3145 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3146 PetscInt n = A->rmap->n; 3147 PetscInt cstart = A->cmap->rstart; 3148 PetscInt *cmap = mat->garray; 3149 PetscInt *diagIdx, *offdiagIdx; 3150 Vec diagV, offdiagV; 3151 PetscScalar *a, *diagA, *offdiagA; 3152 PetscInt r; 3153 PetscErrorCode ierr; 3154 3155 PetscFunctionBegin; 3156 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3157 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3158 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3159 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3160 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3161 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3162 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3163 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3164 for (r = 0; r < n; ++r) { 3165 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3166 a[r] = diagA[r]; 3167 idx[r] = cstart + diagIdx[r]; 3168 } else { 3169 a[r] = offdiagA[r]; 3170 idx[r] = cmap[offdiagIdx[r]]; 3171 } 3172 } 3173 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3174 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3175 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3176 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3177 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3178 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3179 PetscFunctionReturn(0); 3180 } 3181 3182 #undef __FUNCT__ 3183 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3184 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3185 { 3186 PetscErrorCode ierr; 3187 Mat *dummy; 3188 3189 PetscFunctionBegin; 3190 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3191 *newmat = *dummy; 3192 ierr = PetscFree(dummy);CHKERRQ(ierr); 3193 PetscFunctionReturn(0); 3194 } 3195 3196 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3197 3198 #undef __FUNCT__ 3199 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3200 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3201 { 3202 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3203 PetscErrorCode ierr; 3204 3205 PetscFunctionBegin; 3206 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3207 PetscFunctionReturn(0); 3208 } 3209 3210 #undef __FUNCT__ 3211 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3212 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3213 { 3214 PetscErrorCode ierr; 3215 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3216 3217 PetscFunctionBegin; 3218 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3219 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3220 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3221 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3222 PetscFunctionReturn(0); 3223 } 3224 3225 /* -------------------------------------------------------------------*/ 3226 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3227 MatGetRow_MPIAIJ, 3228 MatRestoreRow_MPIAIJ, 3229 MatMult_MPIAIJ, 3230 /* 4*/ MatMultAdd_MPIAIJ, 3231 MatMultTranspose_MPIAIJ, 3232 MatMultTransposeAdd_MPIAIJ, 3233 #if defined(PETSC_HAVE_PBGL) 3234 MatSolve_MPIAIJ, 3235 #else 3236 0, 3237 #endif 3238 0, 3239 0, 3240 /*10*/ 0, 3241 0, 3242 0, 3243 MatSOR_MPIAIJ, 3244 MatTranspose_MPIAIJ, 3245 /*15*/ MatGetInfo_MPIAIJ, 3246 MatEqual_MPIAIJ, 3247 MatGetDiagonal_MPIAIJ, 3248 MatDiagonalScale_MPIAIJ, 3249 MatNorm_MPIAIJ, 3250 /*20*/ MatAssemblyBegin_MPIAIJ, 3251 MatAssemblyEnd_MPIAIJ, 3252 MatSetOption_MPIAIJ, 3253 MatZeroEntries_MPIAIJ, 3254 /*24*/ MatZeroRows_MPIAIJ, 3255 0, 3256 #if defined(PETSC_HAVE_PBGL) 3257 0, 3258 #else 3259 0, 3260 #endif 3261 0, 3262 0, 3263 /*29*/ MatSetUp_MPIAIJ, 3264 #if defined(PETSC_HAVE_PBGL) 3265 0, 3266 #else 3267 0, 3268 #endif 3269 0, 3270 0, 3271 0, 3272 /*34*/ MatDuplicate_MPIAIJ, 3273 0, 3274 0, 3275 0, 3276 0, 3277 /*39*/ MatAXPY_MPIAIJ, 3278 MatGetSubMatrices_MPIAIJ, 3279 MatIncreaseOverlap_MPIAIJ, 3280 MatGetValues_MPIAIJ, 3281 MatCopy_MPIAIJ, 3282 /*44*/ MatGetRowMax_MPIAIJ, 3283 MatScale_MPIAIJ, 3284 0, 3285 0, 3286 MatZeroRowsColumns_MPIAIJ, 3287 /*49*/ MatSetRandom_MPIAIJ, 3288 0, 3289 0, 3290 0, 3291 0, 3292 /*54*/ MatFDColoringCreate_MPIAIJ, 3293 0, 3294 MatSetUnfactored_MPIAIJ, 3295 MatPermute_MPIAIJ, 3296 0, 3297 /*59*/ MatGetSubMatrix_MPIAIJ, 3298 MatDestroy_MPIAIJ, 3299 MatView_MPIAIJ, 3300 0, 3301 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3302 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3303 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3304 0, 3305 0, 3306 0, 3307 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3308 MatGetRowMinAbs_MPIAIJ, 3309 0, 3310 MatSetColoring_MPIAIJ, 3311 0, 3312 MatSetValuesAdifor_MPIAIJ, 3313 /*75*/ MatFDColoringApply_AIJ, 3314 0, 3315 0, 3316 0, 3317 MatFindZeroDiagonals_MPIAIJ, 3318 /*80*/ 0, 3319 0, 3320 0, 3321 /*83*/ MatLoad_MPIAIJ, 3322 0, 3323 0, 3324 0, 3325 0, 3326 0, 3327 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3328 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3329 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3330 MatPtAP_MPIAIJ_MPIAIJ, 3331 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3332 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3333 0, 3334 0, 3335 0, 3336 0, 3337 /*99*/ 0, 3338 0, 3339 0, 3340 MatConjugate_MPIAIJ, 3341 0, 3342 /*104*/MatSetValuesRow_MPIAIJ, 3343 MatRealPart_MPIAIJ, 3344 MatImaginaryPart_MPIAIJ, 3345 0, 3346 0, 3347 /*109*/0, 3348 MatGetRedundantMatrix_MPIAIJ, 3349 MatGetRowMin_MPIAIJ, 3350 0, 3351 0, 3352 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3353 0, 3354 0, 3355 0, 3356 0, 3357 /*119*/0, 3358 0, 3359 0, 3360 0, 3361 MatGetMultiProcBlock_MPIAIJ, 3362 /*124*/MatFindNonzeroRows_MPIAIJ, 3363 MatGetColumnNorms_MPIAIJ, 3364 MatInvertBlockDiagonal_MPIAIJ, 3365 0, 3366 MatGetSubMatricesParallel_MPIAIJ, 3367 /*129*/0, 3368 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3369 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3370 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3371 0, 3372 /*134*/0, 3373 0, 3374 0, 3375 0, 3376 0, 3377 /*139*/0, 3378 0 3379 }; 3380 3381 /* ----------------------------------------------------------------------------------------*/ 3382 3383 #undef __FUNCT__ 3384 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3385 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3386 { 3387 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3388 PetscErrorCode ierr; 3389 3390 PetscFunctionBegin; 3391 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3392 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3393 PetscFunctionReturn(0); 3394 } 3395 3396 #undef __FUNCT__ 3397 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3398 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3399 { 3400 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3401 PetscErrorCode ierr; 3402 3403 PetscFunctionBegin; 3404 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3405 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3406 PetscFunctionReturn(0); 3407 } 3408 3409 #undef __FUNCT__ 3410 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3411 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3412 { 3413 Mat_MPIAIJ *b; 3414 PetscErrorCode ierr; 3415 3416 PetscFunctionBegin; 3417 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3418 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3419 b = (Mat_MPIAIJ*)B->data; 3420 3421 if (!B->preallocated) { 3422 /* Explicitly create 2 MATSEQAIJ matrices. */ 3423 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3424 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3425 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3426 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3427 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3428 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3429 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3430 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3431 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3432 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3433 } 3434 3435 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3436 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3437 B->preallocated = PETSC_TRUE; 3438 PetscFunctionReturn(0); 3439 } 3440 3441 #undef __FUNCT__ 3442 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3443 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3444 { 3445 Mat mat; 3446 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3447 PetscErrorCode ierr; 3448 3449 PetscFunctionBegin; 3450 *newmat = 0; 3451 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3452 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3453 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3454 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3455 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3456 a = (Mat_MPIAIJ*)mat->data; 3457 3458 mat->factortype = matin->factortype; 3459 mat->rmap->bs = matin->rmap->bs; 3460 mat->cmap->bs = matin->cmap->bs; 3461 mat->assembled = PETSC_TRUE; 3462 mat->insertmode = NOT_SET_VALUES; 3463 mat->preallocated = PETSC_TRUE; 3464 3465 a->size = oldmat->size; 3466 a->rank = oldmat->rank; 3467 a->donotstash = oldmat->donotstash; 3468 a->roworiented = oldmat->roworiented; 3469 a->rowindices = 0; 3470 a->rowvalues = 0; 3471 a->getrowactive = PETSC_FALSE; 3472 3473 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3474 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3475 3476 if (oldmat->colmap) { 3477 #if defined(PETSC_USE_CTABLE) 3478 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3479 #else 3480 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3481 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3482 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3483 #endif 3484 } else a->colmap = 0; 3485 if (oldmat->garray) { 3486 PetscInt len; 3487 len = oldmat->B->cmap->n; 3488 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3489 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3490 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3491 } else a->garray = 0; 3492 3493 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3494 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3495 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3496 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3497 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3498 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3499 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3500 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3501 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3502 *newmat = mat; 3503 PetscFunctionReturn(0); 3504 } 3505 3506 3507 3508 #undef __FUNCT__ 3509 #define __FUNCT__ "MatLoad_MPIAIJ" 3510 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3511 { 3512 PetscScalar *vals,*svals; 3513 MPI_Comm comm; 3514 PetscErrorCode ierr; 3515 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3516 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3517 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3518 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3519 PetscInt cend,cstart,n,*rowners,sizesset=1; 3520 int fd; 3521 PetscInt bs = 1; 3522 3523 PetscFunctionBegin; 3524 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3525 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3526 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3527 if (!rank) { 3528 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3529 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3530 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3531 } 3532 3533 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3534 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3535 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3536 3537 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3538 3539 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3540 M = header[1]; N = header[2]; 3541 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3542 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3543 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3544 3545 /* If global sizes are set, check if they are consistent with that given in the file */ 3546 if (sizesset) { 3547 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3548 } 3549 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); 3550 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); 3551 3552 /* determine ownership of all (block) rows */ 3553 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3554 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3555 else m = newMat->rmap->n; /* Set by user */ 3556 3557 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3558 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3559 3560 /* First process needs enough room for process with most rows */ 3561 if (!rank) { 3562 mmax = rowners[1]; 3563 for (i=2; i<=size; i++) { 3564 mmax = PetscMax(mmax, rowners[i]); 3565 } 3566 } else mmax = -1; /* unused, but compilers complain */ 3567 3568 rowners[0] = 0; 3569 for (i=2; i<=size; i++) { 3570 rowners[i] += rowners[i-1]; 3571 } 3572 rstart = rowners[rank]; 3573 rend = rowners[rank+1]; 3574 3575 /* distribute row lengths to all processors */ 3576 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3577 if (!rank) { 3578 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3579 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3580 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3581 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3582 for (j=0; j<m; j++) { 3583 procsnz[0] += ourlens[j]; 3584 } 3585 for (i=1; i<size; i++) { 3586 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3587 /* calculate the number of nonzeros on each processor */ 3588 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3589 procsnz[i] += rowlengths[j]; 3590 } 3591 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3592 } 3593 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3594 } else { 3595 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3596 } 3597 3598 if (!rank) { 3599 /* determine max buffer needed and allocate it */ 3600 maxnz = 0; 3601 for (i=0; i<size; i++) { 3602 maxnz = PetscMax(maxnz,procsnz[i]); 3603 } 3604 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3605 3606 /* read in my part of the matrix column indices */ 3607 nz = procsnz[0]; 3608 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3609 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3610 3611 /* read in every one elses and ship off */ 3612 for (i=1; i<size; i++) { 3613 nz = procsnz[i]; 3614 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3615 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3616 } 3617 ierr = PetscFree(cols);CHKERRQ(ierr); 3618 } else { 3619 /* determine buffer space needed for message */ 3620 nz = 0; 3621 for (i=0; i<m; i++) { 3622 nz += ourlens[i]; 3623 } 3624 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3625 3626 /* receive message of column indices*/ 3627 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3628 } 3629 3630 /* determine column ownership if matrix is not square */ 3631 if (N != M) { 3632 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3633 else n = newMat->cmap->n; 3634 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3635 cstart = cend - n; 3636 } else { 3637 cstart = rstart; 3638 cend = rend; 3639 n = cend - cstart; 3640 } 3641 3642 /* loop over local rows, determining number of off diagonal entries */ 3643 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3644 jj = 0; 3645 for (i=0; i<m; i++) { 3646 for (j=0; j<ourlens[i]; j++) { 3647 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3648 jj++; 3649 } 3650 } 3651 3652 for (i=0; i<m; i++) { 3653 ourlens[i] -= offlens[i]; 3654 } 3655 if (!sizesset) { 3656 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3657 } 3658 3659 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3660 3661 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3662 3663 for (i=0; i<m; i++) { 3664 ourlens[i] += offlens[i]; 3665 } 3666 3667 if (!rank) { 3668 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3669 3670 /* read in my part of the matrix numerical values */ 3671 nz = procsnz[0]; 3672 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3673 3674 /* insert into matrix */ 3675 jj = rstart; 3676 smycols = mycols; 3677 svals = vals; 3678 for (i=0; i<m; i++) { 3679 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3680 smycols += ourlens[i]; 3681 svals += ourlens[i]; 3682 jj++; 3683 } 3684 3685 /* read in other processors and ship out */ 3686 for (i=1; i<size; i++) { 3687 nz = procsnz[i]; 3688 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3689 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3690 } 3691 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3692 } else { 3693 /* receive numeric values */ 3694 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3695 3696 /* receive message of values*/ 3697 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3698 3699 /* insert into matrix */ 3700 jj = rstart; 3701 smycols = mycols; 3702 svals = vals; 3703 for (i=0; i<m; i++) { 3704 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3705 smycols += ourlens[i]; 3706 svals += ourlens[i]; 3707 jj++; 3708 } 3709 } 3710 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3711 ierr = PetscFree(vals);CHKERRQ(ierr); 3712 ierr = PetscFree(mycols);CHKERRQ(ierr); 3713 ierr = PetscFree(rowners);CHKERRQ(ierr); 3714 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3715 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3716 PetscFunctionReturn(0); 3717 } 3718 3719 #undef __FUNCT__ 3720 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3721 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3722 { 3723 PetscErrorCode ierr; 3724 IS iscol_local; 3725 PetscInt csize; 3726 3727 PetscFunctionBegin; 3728 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3729 if (call == MAT_REUSE_MATRIX) { 3730 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3731 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3732 } else { 3733 PetscInt cbs; 3734 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3735 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3736 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3737 } 3738 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3739 if (call == MAT_INITIAL_MATRIX) { 3740 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3741 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3742 } 3743 PetscFunctionReturn(0); 3744 } 3745 3746 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3747 #undef __FUNCT__ 3748 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3749 /* 3750 Not great since it makes two copies of the submatrix, first an SeqAIJ 3751 in local and then by concatenating the local matrices the end result. 3752 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3753 3754 Note: This requires a sequential iscol with all indices. 3755 */ 3756 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3757 { 3758 PetscErrorCode ierr; 3759 PetscMPIInt rank,size; 3760 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3761 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3762 PetscBool allcolumns, colflag; 3763 Mat M,Mreuse; 3764 MatScalar *vwork,*aa; 3765 MPI_Comm comm; 3766 Mat_SeqAIJ *aij; 3767 3768 PetscFunctionBegin; 3769 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3770 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3771 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3772 3773 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3774 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3775 if (colflag && ncol == mat->cmap->N) { 3776 allcolumns = PETSC_TRUE; 3777 } else { 3778 allcolumns = PETSC_FALSE; 3779 } 3780 if (call == MAT_REUSE_MATRIX) { 3781 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3782 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3783 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3784 } else { 3785 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3786 } 3787 3788 /* 3789 m - number of local rows 3790 n - number of columns (same on all processors) 3791 rstart - first row in new global matrix generated 3792 */ 3793 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3794 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3795 if (call == MAT_INITIAL_MATRIX) { 3796 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3797 ii = aij->i; 3798 jj = aij->j; 3799 3800 /* 3801 Determine the number of non-zeros in the diagonal and off-diagonal 3802 portions of the matrix in order to do correct preallocation 3803 */ 3804 3805 /* first get start and end of "diagonal" columns */ 3806 if (csize == PETSC_DECIDE) { 3807 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3808 if (mglobal == n) { /* square matrix */ 3809 nlocal = m; 3810 } else { 3811 nlocal = n/size + ((n % size) > rank); 3812 } 3813 } else { 3814 nlocal = csize; 3815 } 3816 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3817 rstart = rend - nlocal; 3818 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); 3819 3820 /* next, compute all the lengths */ 3821 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3822 olens = dlens + m; 3823 for (i=0; i<m; i++) { 3824 jend = ii[i+1] - ii[i]; 3825 olen = 0; 3826 dlen = 0; 3827 for (j=0; j<jend; j++) { 3828 if (*jj < rstart || *jj >= rend) olen++; 3829 else dlen++; 3830 jj++; 3831 } 3832 olens[i] = olen; 3833 dlens[i] = dlen; 3834 } 3835 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3836 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3837 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3838 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3839 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3840 ierr = PetscFree(dlens);CHKERRQ(ierr); 3841 } else { 3842 PetscInt ml,nl; 3843 3844 M = *newmat; 3845 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3846 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3847 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3848 /* 3849 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3850 rather than the slower MatSetValues(). 3851 */ 3852 M->was_assembled = PETSC_TRUE; 3853 M->assembled = PETSC_FALSE; 3854 } 3855 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3856 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3857 ii = aij->i; 3858 jj = aij->j; 3859 aa = aij->a; 3860 for (i=0; i<m; i++) { 3861 row = rstart + i; 3862 nz = ii[i+1] - ii[i]; 3863 cwork = jj; jj += nz; 3864 vwork = aa; aa += nz; 3865 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3866 } 3867 3868 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3869 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3870 *newmat = M; 3871 3872 /* save submatrix used in processor for next request */ 3873 if (call == MAT_INITIAL_MATRIX) { 3874 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3875 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3876 } 3877 PetscFunctionReturn(0); 3878 } 3879 3880 #undef __FUNCT__ 3881 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3882 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3883 { 3884 PetscInt m,cstart, cend,j,nnz,i,d; 3885 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3886 const PetscInt *JJ; 3887 PetscScalar *values; 3888 PetscErrorCode ierr; 3889 3890 PetscFunctionBegin; 3891 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3892 3893 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3894 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3895 m = B->rmap->n; 3896 cstart = B->cmap->rstart; 3897 cend = B->cmap->rend; 3898 rstart = B->rmap->rstart; 3899 3900 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3901 3902 #if defined(PETSC_USE_DEBUGGING) 3903 for (i=0; i<m; i++) { 3904 nnz = Ii[i+1]- Ii[i]; 3905 JJ = J + Ii[i]; 3906 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3907 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3908 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); 3909 } 3910 #endif 3911 3912 for (i=0; i<m; i++) { 3913 nnz = Ii[i+1]- Ii[i]; 3914 JJ = J + Ii[i]; 3915 nnz_max = PetscMax(nnz_max,nnz); 3916 d = 0; 3917 for (j=0; j<nnz; j++) { 3918 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3919 } 3920 d_nnz[i] = d; 3921 o_nnz[i] = nnz - d; 3922 } 3923 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3924 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3925 3926 if (v) values = (PetscScalar*)v; 3927 else { 3928 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3929 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3930 } 3931 3932 for (i=0; i<m; i++) { 3933 ii = i + rstart; 3934 nnz = Ii[i+1]- Ii[i]; 3935 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3936 } 3937 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3938 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3939 3940 if (!v) { 3941 ierr = PetscFree(values);CHKERRQ(ierr); 3942 } 3943 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3944 PetscFunctionReturn(0); 3945 } 3946 3947 #undef __FUNCT__ 3948 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3949 /*@ 3950 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3951 (the default parallel PETSc format). 3952 3953 Collective on MPI_Comm 3954 3955 Input Parameters: 3956 + B - the matrix 3957 . i - the indices into j for the start of each local row (starts with zero) 3958 . j - the column indices for each local row (starts with zero) 3959 - v - optional values in the matrix 3960 3961 Level: developer 3962 3963 Notes: 3964 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3965 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3966 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3967 3968 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3969 3970 The format which is used for the sparse matrix input, is equivalent to a 3971 row-major ordering.. i.e for the following matrix, the input data expected is 3972 as shown: 3973 3974 1 0 0 3975 2 0 3 P0 3976 ------- 3977 4 5 6 P1 3978 3979 Process0 [P0]: rows_owned=[0,1] 3980 i = {0,1,3} [size = nrow+1 = 2+1] 3981 j = {0,0,2} [size = nz = 6] 3982 v = {1,2,3} [size = nz = 6] 3983 3984 Process1 [P1]: rows_owned=[2] 3985 i = {0,3} [size = nrow+1 = 1+1] 3986 j = {0,1,2} [size = nz = 6] 3987 v = {4,5,6} [size = nz = 6] 3988 3989 .keywords: matrix, aij, compressed row, sparse, parallel 3990 3991 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3992 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3993 @*/ 3994 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3995 { 3996 PetscErrorCode ierr; 3997 3998 PetscFunctionBegin; 3999 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4000 PetscFunctionReturn(0); 4001 } 4002 4003 #undef __FUNCT__ 4004 #define __FUNCT__ "MatMPIAIJSetPreallocation" 4005 /*@C 4006 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4007 (the default parallel PETSc format). For good matrix assembly performance 4008 the user should preallocate the matrix storage by setting the parameters 4009 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4010 performance can be increased by more than a factor of 50. 4011 4012 Collective on MPI_Comm 4013 4014 Input Parameters: 4015 + A - the matrix 4016 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4017 (same value is used for all local rows) 4018 . d_nnz - array containing the number of nonzeros in the various rows of the 4019 DIAGONAL portion of the local submatrix (possibly different for each row) 4020 or NULL, if d_nz is used to specify the nonzero structure. 4021 The size of this array is equal to the number of local rows, i.e 'm'. 4022 For matrices that will be factored, you must leave room for (and set) 4023 the diagonal entry even if it is zero. 4024 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4025 submatrix (same value is used for all local rows). 4026 - o_nnz - array containing the number of nonzeros in the various rows of the 4027 OFF-DIAGONAL portion of the local submatrix (possibly different for 4028 each row) or NULL, if o_nz is used to specify the nonzero 4029 structure. The size of this array is equal to the number 4030 of local rows, i.e 'm'. 4031 4032 If the *_nnz parameter is given then the *_nz parameter is ignored 4033 4034 The AIJ format (also called the Yale sparse matrix format or 4035 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4036 storage. The stored row and column indices begin with zero. 4037 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4038 4039 The parallel matrix is partitioned such that the first m0 rows belong to 4040 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4041 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4042 4043 The DIAGONAL portion of the local submatrix of a processor can be defined 4044 as the submatrix which is obtained by extraction the part corresponding to 4045 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4046 first row that belongs to the processor, r2 is the last row belonging to 4047 the this processor, and c1-c2 is range of indices of the local part of a 4048 vector suitable for applying the matrix to. This is an mxn matrix. In the 4049 common case of a square matrix, the row and column ranges are the same and 4050 the DIAGONAL part is also square. The remaining portion of the local 4051 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4052 4053 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4054 4055 You can call MatGetInfo() to get information on how effective the preallocation was; 4056 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4057 You can also run with the option -info and look for messages with the string 4058 malloc in them to see if additional memory allocation was needed. 4059 4060 Example usage: 4061 4062 Consider the following 8x8 matrix with 34 non-zero values, that is 4063 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4064 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4065 as follows: 4066 4067 .vb 4068 1 2 0 | 0 3 0 | 0 4 4069 Proc0 0 5 6 | 7 0 0 | 8 0 4070 9 0 10 | 11 0 0 | 12 0 4071 ------------------------------------- 4072 13 0 14 | 15 16 17 | 0 0 4073 Proc1 0 18 0 | 19 20 21 | 0 0 4074 0 0 0 | 22 23 0 | 24 0 4075 ------------------------------------- 4076 Proc2 25 26 27 | 0 0 28 | 29 0 4077 30 0 0 | 31 32 33 | 0 34 4078 .ve 4079 4080 This can be represented as a collection of submatrices as: 4081 4082 .vb 4083 A B C 4084 D E F 4085 G H I 4086 .ve 4087 4088 Where the submatrices A,B,C are owned by proc0, D,E,F are 4089 owned by proc1, G,H,I are owned by proc2. 4090 4091 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4092 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4093 The 'M','N' parameters are 8,8, and have the same values on all procs. 4094 4095 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4096 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4097 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4098 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4099 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4100 matrix, ans [DF] as another SeqAIJ matrix. 4101 4102 When d_nz, o_nz parameters are specified, d_nz storage elements are 4103 allocated for every row of the local diagonal submatrix, and o_nz 4104 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4105 One way to choose d_nz and o_nz is to use the max nonzerors per local 4106 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4107 In this case, the values of d_nz,o_nz are: 4108 .vb 4109 proc0 : dnz = 2, o_nz = 2 4110 proc1 : dnz = 3, o_nz = 2 4111 proc2 : dnz = 1, o_nz = 4 4112 .ve 4113 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4114 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4115 for proc3. i.e we are using 12+15+10=37 storage locations to store 4116 34 values. 4117 4118 When d_nnz, o_nnz parameters are specified, the storage is specified 4119 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4120 In the above case the values for d_nnz,o_nnz are: 4121 .vb 4122 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4123 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4124 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4125 .ve 4126 Here the space allocated is sum of all the above values i.e 34, and 4127 hence pre-allocation is perfect. 4128 4129 Level: intermediate 4130 4131 .keywords: matrix, aij, compressed row, sparse, parallel 4132 4133 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4134 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4135 @*/ 4136 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4137 { 4138 PetscErrorCode ierr; 4139 4140 PetscFunctionBegin; 4141 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4142 PetscValidType(B,1); 4143 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4144 PetscFunctionReturn(0); 4145 } 4146 4147 #undef __FUNCT__ 4148 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4149 /*@ 4150 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4151 CSR format the local rows. 4152 4153 Collective on MPI_Comm 4154 4155 Input Parameters: 4156 + comm - MPI communicator 4157 . m - number of local rows (Cannot be PETSC_DECIDE) 4158 . n - This value should be the same as the local size used in creating the 4159 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4160 calculated if N is given) For square matrices n is almost always m. 4161 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4162 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4163 . i - row indices 4164 . j - column indices 4165 - a - matrix values 4166 4167 Output Parameter: 4168 . mat - the matrix 4169 4170 Level: intermediate 4171 4172 Notes: 4173 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4174 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4175 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4176 4177 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4178 4179 The format which is used for the sparse matrix input, is equivalent to a 4180 row-major ordering.. i.e for the following matrix, the input data expected is 4181 as shown: 4182 4183 1 0 0 4184 2 0 3 P0 4185 ------- 4186 4 5 6 P1 4187 4188 Process0 [P0]: rows_owned=[0,1] 4189 i = {0,1,3} [size = nrow+1 = 2+1] 4190 j = {0,0,2} [size = nz = 6] 4191 v = {1,2,3} [size = nz = 6] 4192 4193 Process1 [P1]: rows_owned=[2] 4194 i = {0,3} [size = nrow+1 = 1+1] 4195 j = {0,1,2} [size = nz = 6] 4196 v = {4,5,6} [size = nz = 6] 4197 4198 .keywords: matrix, aij, compressed row, sparse, parallel 4199 4200 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4201 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4202 @*/ 4203 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4204 { 4205 PetscErrorCode ierr; 4206 4207 PetscFunctionBegin; 4208 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4209 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4210 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4211 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4212 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4213 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4214 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4215 PetscFunctionReturn(0); 4216 } 4217 4218 #undef __FUNCT__ 4219 #define __FUNCT__ "MatCreateAIJ" 4220 /*@C 4221 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4222 (the default parallel PETSc format). For good matrix assembly performance 4223 the user should preallocate the matrix storage by setting the parameters 4224 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4225 performance can be increased by more than a factor of 50. 4226 4227 Collective on MPI_Comm 4228 4229 Input Parameters: 4230 + comm - MPI communicator 4231 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4232 This value should be the same as the local size used in creating the 4233 y vector for the matrix-vector product y = Ax. 4234 . n - This value should be the same as the local size used in creating the 4235 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4236 calculated if N is given) For square matrices n is almost always m. 4237 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4238 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4239 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4240 (same value is used for all local rows) 4241 . d_nnz - array containing the number of nonzeros in the various rows of the 4242 DIAGONAL portion of the local submatrix (possibly different for each row) 4243 or NULL, if d_nz is used to specify the nonzero structure. 4244 The size of this array is equal to the number of local rows, i.e 'm'. 4245 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4246 submatrix (same value is used for all local rows). 4247 - o_nnz - array containing the number of nonzeros in the various rows of the 4248 OFF-DIAGONAL portion of the local submatrix (possibly different for 4249 each row) or NULL, if o_nz is used to specify the nonzero 4250 structure. The size of this array is equal to the number 4251 of local rows, i.e 'm'. 4252 4253 Output Parameter: 4254 . A - the matrix 4255 4256 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4257 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4258 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4259 4260 Notes: 4261 If the *_nnz parameter is given then the *_nz parameter is ignored 4262 4263 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4264 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4265 storage requirements for this matrix. 4266 4267 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4268 processor than it must be used on all processors that share the object for 4269 that argument. 4270 4271 The user MUST specify either the local or global matrix dimensions 4272 (possibly both). 4273 4274 The parallel matrix is partitioned across processors such that the 4275 first m0 rows belong to process 0, the next m1 rows belong to 4276 process 1, the next m2 rows belong to process 2 etc.. where 4277 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4278 values corresponding to [m x N] submatrix. 4279 4280 The columns are logically partitioned with the n0 columns belonging 4281 to 0th partition, the next n1 columns belonging to the next 4282 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4283 4284 The DIAGONAL portion of the local submatrix on any given processor 4285 is the submatrix corresponding to the rows and columns m,n 4286 corresponding to the given processor. i.e diagonal matrix on 4287 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4288 etc. The remaining portion of the local submatrix [m x (N-n)] 4289 constitute the OFF-DIAGONAL portion. The example below better 4290 illustrates this concept. 4291 4292 For a square global matrix we define each processor's diagonal portion 4293 to be its local rows and the corresponding columns (a square submatrix); 4294 each processor's off-diagonal portion encompasses the remainder of the 4295 local matrix (a rectangular submatrix). 4296 4297 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4298 4299 When calling this routine with a single process communicator, a matrix of 4300 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4301 type of communicator, use the construction mechanism: 4302 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4303 4304 By default, this format uses inodes (identical nodes) when possible. 4305 We search for consecutive rows with the same nonzero structure, thereby 4306 reusing matrix information to achieve increased efficiency. 4307 4308 Options Database Keys: 4309 + -mat_no_inode - Do not use inodes 4310 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4311 - -mat_aij_oneindex - Internally use indexing starting at 1 4312 rather than 0. Note that when calling MatSetValues(), 4313 the user still MUST index entries starting at 0! 4314 4315 4316 Example usage: 4317 4318 Consider the following 8x8 matrix with 34 non-zero values, that is 4319 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4320 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4321 as follows: 4322 4323 .vb 4324 1 2 0 | 0 3 0 | 0 4 4325 Proc0 0 5 6 | 7 0 0 | 8 0 4326 9 0 10 | 11 0 0 | 12 0 4327 ------------------------------------- 4328 13 0 14 | 15 16 17 | 0 0 4329 Proc1 0 18 0 | 19 20 21 | 0 0 4330 0 0 0 | 22 23 0 | 24 0 4331 ------------------------------------- 4332 Proc2 25 26 27 | 0 0 28 | 29 0 4333 30 0 0 | 31 32 33 | 0 34 4334 .ve 4335 4336 This can be represented as a collection of submatrices as: 4337 4338 .vb 4339 A B C 4340 D E F 4341 G H I 4342 .ve 4343 4344 Where the submatrices A,B,C are owned by proc0, D,E,F are 4345 owned by proc1, G,H,I are owned by proc2. 4346 4347 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4348 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4349 The 'M','N' parameters are 8,8, and have the same values on all procs. 4350 4351 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4352 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4353 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4354 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4355 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4356 matrix, ans [DF] as another SeqAIJ matrix. 4357 4358 When d_nz, o_nz parameters are specified, d_nz storage elements are 4359 allocated for every row of the local diagonal submatrix, and o_nz 4360 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4361 One way to choose d_nz and o_nz is to use the max nonzerors per local 4362 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4363 In this case, the values of d_nz,o_nz are: 4364 .vb 4365 proc0 : dnz = 2, o_nz = 2 4366 proc1 : dnz = 3, o_nz = 2 4367 proc2 : dnz = 1, o_nz = 4 4368 .ve 4369 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4370 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4371 for proc3. i.e we are using 12+15+10=37 storage locations to store 4372 34 values. 4373 4374 When d_nnz, o_nnz parameters are specified, the storage is specified 4375 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4376 In the above case the values for d_nnz,o_nnz are: 4377 .vb 4378 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4379 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4380 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4381 .ve 4382 Here the space allocated is sum of all the above values i.e 34, and 4383 hence pre-allocation is perfect. 4384 4385 Level: intermediate 4386 4387 .keywords: matrix, aij, compressed row, sparse, parallel 4388 4389 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4390 MPIAIJ, MatCreateMPIAIJWithArrays() 4391 @*/ 4392 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) 4393 { 4394 PetscErrorCode ierr; 4395 PetscMPIInt size; 4396 4397 PetscFunctionBegin; 4398 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4399 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4400 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4401 if (size > 1) { 4402 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4403 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4404 } else { 4405 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4406 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4407 } 4408 PetscFunctionReturn(0); 4409 } 4410 4411 #undef __FUNCT__ 4412 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4413 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4414 { 4415 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4416 4417 PetscFunctionBegin; 4418 *Ad = a->A; 4419 *Ao = a->B; 4420 *colmap = a->garray; 4421 PetscFunctionReturn(0); 4422 } 4423 4424 #undef __FUNCT__ 4425 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4426 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4427 { 4428 PetscErrorCode ierr; 4429 PetscInt i; 4430 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4431 4432 PetscFunctionBegin; 4433 if (coloring->ctype == IS_COLORING_GLOBAL) { 4434 ISColoringValue *allcolors,*colors; 4435 ISColoring ocoloring; 4436 4437 /* set coloring for diagonal portion */ 4438 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4439 4440 /* set coloring for off-diagonal portion */ 4441 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4442 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4443 for (i=0; i<a->B->cmap->n; i++) { 4444 colors[i] = allcolors[a->garray[i]]; 4445 } 4446 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4447 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4448 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4449 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4450 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4451 ISColoringValue *colors; 4452 PetscInt *larray; 4453 ISColoring ocoloring; 4454 4455 /* set coloring for diagonal portion */ 4456 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4457 for (i=0; i<a->A->cmap->n; i++) { 4458 larray[i] = i + A->cmap->rstart; 4459 } 4460 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4461 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4462 for (i=0; i<a->A->cmap->n; i++) { 4463 colors[i] = coloring->colors[larray[i]]; 4464 } 4465 ierr = PetscFree(larray);CHKERRQ(ierr); 4466 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4467 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4468 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4469 4470 /* set coloring for off-diagonal portion */ 4471 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4472 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4473 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4474 for (i=0; i<a->B->cmap->n; i++) { 4475 colors[i] = coloring->colors[larray[i]]; 4476 } 4477 ierr = PetscFree(larray);CHKERRQ(ierr); 4478 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4479 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4480 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4481 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4482 PetscFunctionReturn(0); 4483 } 4484 4485 #undef __FUNCT__ 4486 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4487 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4488 { 4489 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4490 PetscErrorCode ierr; 4491 4492 PetscFunctionBegin; 4493 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4494 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4495 PetscFunctionReturn(0); 4496 } 4497 4498 #undef __FUNCT__ 4499 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4500 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4501 { 4502 PetscErrorCode ierr; 4503 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4504 PetscInt *indx; 4505 4506 PetscFunctionBegin; 4507 /* This routine will ONLY return MPIAIJ type matrix */ 4508 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4509 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4510 if (n == PETSC_DECIDE) { 4511 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4512 } 4513 /* Check sum(n) = N */ 4514 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4515 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4516 4517 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4518 rstart -= m; 4519 4520 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4521 for (i=0; i<m; i++) { 4522 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4523 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4524 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4525 } 4526 4527 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4528 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4529 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4530 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4531 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4532 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4533 PetscFunctionReturn(0); 4534 } 4535 4536 #undef __FUNCT__ 4537 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4538 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4539 { 4540 PetscErrorCode ierr; 4541 PetscInt m,N,i,rstart,nnz,Ii; 4542 PetscInt *indx; 4543 PetscScalar *values; 4544 4545 PetscFunctionBegin; 4546 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4547 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4548 for (i=0; i<m; i++) { 4549 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4550 Ii = i + rstart; 4551 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4552 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4553 } 4554 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4555 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4556 PetscFunctionReturn(0); 4557 } 4558 4559 #undef __FUNCT__ 4560 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4561 /*@ 4562 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4563 matrices from each processor 4564 4565 Collective on MPI_Comm 4566 4567 Input Parameters: 4568 + comm - the communicators the parallel matrix will live on 4569 . inmat - the input sequential matrices 4570 . n - number of local columns (or PETSC_DECIDE) 4571 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4572 4573 Output Parameter: 4574 . outmat - the parallel matrix generated 4575 4576 Level: advanced 4577 4578 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4579 4580 @*/ 4581 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4582 { 4583 PetscErrorCode ierr; 4584 PetscMPIInt size; 4585 4586 PetscFunctionBegin; 4587 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4588 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4589 if (size == 1) { 4590 if (scall == MAT_INITIAL_MATRIX) { 4591 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4592 } else { 4593 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4594 } 4595 } else { 4596 if (scall == MAT_INITIAL_MATRIX) { 4597 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4598 } 4599 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4600 } 4601 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4602 PetscFunctionReturn(0); 4603 } 4604 4605 #undef __FUNCT__ 4606 #define __FUNCT__ "MatFileSplit" 4607 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4608 { 4609 PetscErrorCode ierr; 4610 PetscMPIInt rank; 4611 PetscInt m,N,i,rstart,nnz; 4612 size_t len; 4613 const PetscInt *indx; 4614 PetscViewer out; 4615 char *name; 4616 Mat B; 4617 const PetscScalar *values; 4618 4619 PetscFunctionBegin; 4620 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4621 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4622 /* Should this be the type of the diagonal block of A? */ 4623 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4624 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4625 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4626 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4627 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4628 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4629 for (i=0; i<m; i++) { 4630 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4631 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4632 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4633 } 4634 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4635 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4636 4637 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4638 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4639 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4640 sprintf(name,"%s.%d",outfile,rank); 4641 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4642 ierr = PetscFree(name);CHKERRQ(ierr); 4643 ierr = MatView(B,out);CHKERRQ(ierr); 4644 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4645 ierr = MatDestroy(&B);CHKERRQ(ierr); 4646 PetscFunctionReturn(0); 4647 } 4648 4649 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4650 #undef __FUNCT__ 4651 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4652 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4653 { 4654 PetscErrorCode ierr; 4655 Mat_Merge_SeqsToMPI *merge; 4656 PetscContainer container; 4657 4658 PetscFunctionBegin; 4659 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4660 if (container) { 4661 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4662 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4663 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4664 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4665 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4666 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4667 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4668 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4669 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4670 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4671 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4672 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4673 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4674 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4675 ierr = PetscFree(merge);CHKERRQ(ierr); 4676 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4677 } 4678 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4679 PetscFunctionReturn(0); 4680 } 4681 4682 #include <../src/mat/utils/freespace.h> 4683 #include <petscbt.h> 4684 4685 #undef __FUNCT__ 4686 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4687 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4688 { 4689 PetscErrorCode ierr; 4690 MPI_Comm comm; 4691 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4692 PetscMPIInt size,rank,taga,*len_s; 4693 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4694 PetscInt proc,m; 4695 PetscInt **buf_ri,**buf_rj; 4696 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4697 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4698 MPI_Request *s_waits,*r_waits; 4699 MPI_Status *status; 4700 MatScalar *aa=a->a; 4701 MatScalar **abuf_r,*ba_i; 4702 Mat_Merge_SeqsToMPI *merge; 4703 PetscContainer container; 4704 4705 PetscFunctionBegin; 4706 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4707 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4708 4709 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4710 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4711 4712 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4713 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4714 4715 bi = merge->bi; 4716 bj = merge->bj; 4717 buf_ri = merge->buf_ri; 4718 buf_rj = merge->buf_rj; 4719 4720 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4721 owners = merge->rowmap->range; 4722 len_s = merge->len_s; 4723 4724 /* send and recv matrix values */ 4725 /*-----------------------------*/ 4726 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4727 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4728 4729 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4730 for (proc=0,k=0; proc<size; proc++) { 4731 if (!len_s[proc]) continue; 4732 i = owners[proc]; 4733 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4734 k++; 4735 } 4736 4737 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4738 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4739 ierr = PetscFree(status);CHKERRQ(ierr); 4740 4741 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4742 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4743 4744 /* insert mat values of mpimat */ 4745 /*----------------------------*/ 4746 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4747 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4748 4749 for (k=0; k<merge->nrecv; k++) { 4750 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4751 nrows = *(buf_ri_k[k]); 4752 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4753 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4754 } 4755 4756 /* set values of ba */ 4757 m = merge->rowmap->n; 4758 for (i=0; i<m; i++) { 4759 arow = owners[rank] + i; 4760 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4761 bnzi = bi[i+1] - bi[i]; 4762 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4763 4764 /* add local non-zero vals of this proc's seqmat into ba */ 4765 anzi = ai[arow+1] - ai[arow]; 4766 aj = a->j + ai[arow]; 4767 aa = a->a + ai[arow]; 4768 nextaj = 0; 4769 for (j=0; nextaj<anzi; j++) { 4770 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4771 ba_i[j] += aa[nextaj++]; 4772 } 4773 } 4774 4775 /* add received vals into ba */ 4776 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4777 /* i-th row */ 4778 if (i == *nextrow[k]) { 4779 anzi = *(nextai[k]+1) - *nextai[k]; 4780 aj = buf_rj[k] + *(nextai[k]); 4781 aa = abuf_r[k] + *(nextai[k]); 4782 nextaj = 0; 4783 for (j=0; nextaj<anzi; j++) { 4784 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4785 ba_i[j] += aa[nextaj++]; 4786 } 4787 } 4788 nextrow[k]++; nextai[k]++; 4789 } 4790 } 4791 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4792 } 4793 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4794 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4795 4796 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4797 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4798 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4799 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4800 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4801 PetscFunctionReturn(0); 4802 } 4803 4804 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4805 4806 #undef __FUNCT__ 4807 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4808 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4809 { 4810 PetscErrorCode ierr; 4811 Mat B_mpi; 4812 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4813 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4814 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4815 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4816 PetscInt len,proc,*dnz,*onz,bs,cbs; 4817 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4818 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4819 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4820 MPI_Status *status; 4821 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4822 PetscBT lnkbt; 4823 Mat_Merge_SeqsToMPI *merge; 4824 PetscContainer container; 4825 4826 PetscFunctionBegin; 4827 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4828 4829 /* make sure it is a PETSc comm */ 4830 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4831 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4832 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4833 4834 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4835 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4836 4837 /* determine row ownership */ 4838 /*---------------------------------------------------------*/ 4839 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4840 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4841 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4842 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4843 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4844 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4845 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4846 4847 m = merge->rowmap->n; 4848 owners = merge->rowmap->range; 4849 4850 /* determine the number of messages to send, their lengths */ 4851 /*---------------------------------------------------------*/ 4852 len_s = merge->len_s; 4853 4854 len = 0; /* length of buf_si[] */ 4855 merge->nsend = 0; 4856 for (proc=0; proc<size; proc++) { 4857 len_si[proc] = 0; 4858 if (proc == rank) { 4859 len_s[proc] = 0; 4860 } else { 4861 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4862 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4863 } 4864 if (len_s[proc]) { 4865 merge->nsend++; 4866 nrows = 0; 4867 for (i=owners[proc]; i<owners[proc+1]; i++) { 4868 if (ai[i+1] > ai[i]) nrows++; 4869 } 4870 len_si[proc] = 2*(nrows+1); 4871 len += len_si[proc]; 4872 } 4873 } 4874 4875 /* determine the number and length of messages to receive for ij-structure */ 4876 /*-------------------------------------------------------------------------*/ 4877 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4878 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4879 4880 /* post the Irecv of j-structure */ 4881 /*-------------------------------*/ 4882 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4883 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4884 4885 /* post the Isend of j-structure */ 4886 /*--------------------------------*/ 4887 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4888 4889 for (proc=0, k=0; proc<size; proc++) { 4890 if (!len_s[proc]) continue; 4891 i = owners[proc]; 4892 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4893 k++; 4894 } 4895 4896 /* receives and sends of j-structure are complete */ 4897 /*------------------------------------------------*/ 4898 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4899 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4900 4901 /* send and recv i-structure */ 4902 /*---------------------------*/ 4903 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4904 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4905 4906 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4907 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4908 for (proc=0,k=0; proc<size; proc++) { 4909 if (!len_s[proc]) continue; 4910 /* form outgoing message for i-structure: 4911 buf_si[0]: nrows to be sent 4912 [1:nrows]: row index (global) 4913 [nrows+1:2*nrows+1]: i-structure index 4914 */ 4915 /*-------------------------------------------*/ 4916 nrows = len_si[proc]/2 - 1; 4917 buf_si_i = buf_si + nrows+1; 4918 buf_si[0] = nrows; 4919 buf_si_i[0] = 0; 4920 nrows = 0; 4921 for (i=owners[proc]; i<owners[proc+1]; i++) { 4922 anzi = ai[i+1] - ai[i]; 4923 if (anzi) { 4924 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4925 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4926 nrows++; 4927 } 4928 } 4929 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4930 k++; 4931 buf_si += len_si[proc]; 4932 } 4933 4934 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4935 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4936 4937 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4938 for (i=0; i<merge->nrecv; i++) { 4939 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); 4940 } 4941 4942 ierr = PetscFree(len_si);CHKERRQ(ierr); 4943 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4944 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4945 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4946 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4947 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4948 ierr = PetscFree(status);CHKERRQ(ierr); 4949 4950 /* compute a local seq matrix in each processor */ 4951 /*----------------------------------------------*/ 4952 /* allocate bi array and free space for accumulating nonzero column info */ 4953 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4954 bi[0] = 0; 4955 4956 /* create and initialize a linked list */ 4957 nlnk = N+1; 4958 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4959 4960 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4961 len = ai[owners[rank+1]] - ai[owners[rank]]; 4962 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4963 4964 current_space = free_space; 4965 4966 /* determine symbolic info for each local row */ 4967 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4968 4969 for (k=0; k<merge->nrecv; k++) { 4970 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4971 nrows = *buf_ri_k[k]; 4972 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4973 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4974 } 4975 4976 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4977 len = 0; 4978 for (i=0; i<m; i++) { 4979 bnzi = 0; 4980 /* add local non-zero cols of this proc's seqmat into lnk */ 4981 arow = owners[rank] + i; 4982 anzi = ai[arow+1] - ai[arow]; 4983 aj = a->j + ai[arow]; 4984 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4985 bnzi += nlnk; 4986 /* add received col data into lnk */ 4987 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4988 if (i == *nextrow[k]) { /* i-th row */ 4989 anzi = *(nextai[k]+1) - *nextai[k]; 4990 aj = buf_rj[k] + *nextai[k]; 4991 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4992 bnzi += nlnk; 4993 nextrow[k]++; nextai[k]++; 4994 } 4995 } 4996 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4997 4998 /* if free space is not available, make more free space */ 4999 if (current_space->local_remaining<bnzi) { 5000 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 5001 nspacedouble++; 5002 } 5003 /* copy data into free space, then initialize lnk */ 5004 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 5005 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 5006 5007 current_space->array += bnzi; 5008 current_space->local_used += bnzi; 5009 current_space->local_remaining -= bnzi; 5010 5011 bi[i+1] = bi[i] + bnzi; 5012 } 5013 5014 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5015 5016 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5017 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5018 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5019 5020 /* create symbolic parallel matrix B_mpi */ 5021 /*---------------------------------------*/ 5022 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5023 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5024 if (n==PETSC_DECIDE) { 5025 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5026 } else { 5027 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5028 } 5029 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5030 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5031 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5032 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5033 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5034 5035 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5036 B_mpi->assembled = PETSC_FALSE; 5037 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5038 merge->bi = bi; 5039 merge->bj = bj; 5040 merge->buf_ri = buf_ri; 5041 merge->buf_rj = buf_rj; 5042 merge->coi = NULL; 5043 merge->coj = NULL; 5044 merge->owners_co = NULL; 5045 5046 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5047 5048 /* attach the supporting struct to B_mpi for reuse */ 5049 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5050 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5051 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5052 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5053 *mpimat = B_mpi; 5054 5055 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5056 PetscFunctionReturn(0); 5057 } 5058 5059 #undef __FUNCT__ 5060 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5061 /*@C 5062 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5063 matrices from each processor 5064 5065 Collective on MPI_Comm 5066 5067 Input Parameters: 5068 + comm - the communicators the parallel matrix will live on 5069 . seqmat - the input sequential matrices 5070 . m - number of local rows (or PETSC_DECIDE) 5071 . n - number of local columns (or PETSC_DECIDE) 5072 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5073 5074 Output Parameter: 5075 . mpimat - the parallel matrix generated 5076 5077 Level: advanced 5078 5079 Notes: 5080 The dimensions of the sequential matrix in each processor MUST be the same. 5081 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5082 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5083 @*/ 5084 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5085 { 5086 PetscErrorCode ierr; 5087 PetscMPIInt size; 5088 5089 PetscFunctionBegin; 5090 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5091 if (size == 1) { 5092 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5093 if (scall == MAT_INITIAL_MATRIX) { 5094 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5095 } else { 5096 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5097 } 5098 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5099 PetscFunctionReturn(0); 5100 } 5101 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5102 if (scall == MAT_INITIAL_MATRIX) { 5103 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5104 } 5105 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5106 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5107 PetscFunctionReturn(0); 5108 } 5109 5110 #undef __FUNCT__ 5111 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5112 /*@ 5113 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5114 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5115 with MatGetSize() 5116 5117 Not Collective 5118 5119 Input Parameters: 5120 + A - the matrix 5121 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5122 5123 Output Parameter: 5124 . A_loc - the local sequential matrix generated 5125 5126 Level: developer 5127 5128 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5129 5130 @*/ 5131 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5132 { 5133 PetscErrorCode ierr; 5134 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5135 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5136 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5137 MatScalar *aa=a->a,*ba=b->a,*cam; 5138 PetscScalar *ca; 5139 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5140 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5141 PetscBool match; 5142 5143 PetscFunctionBegin; 5144 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5145 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5146 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5147 if (scall == MAT_INITIAL_MATRIX) { 5148 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5149 ci[0] = 0; 5150 for (i=0; i<am; i++) { 5151 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5152 } 5153 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5154 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5155 k = 0; 5156 for (i=0; i<am; i++) { 5157 ncols_o = bi[i+1] - bi[i]; 5158 ncols_d = ai[i+1] - ai[i]; 5159 /* off-diagonal portion of A */ 5160 for (jo=0; jo<ncols_o; jo++) { 5161 col = cmap[*bj]; 5162 if (col >= cstart) break; 5163 cj[k] = col; bj++; 5164 ca[k++] = *ba++; 5165 } 5166 /* diagonal portion of A */ 5167 for (j=0; j<ncols_d; j++) { 5168 cj[k] = cstart + *aj++; 5169 ca[k++] = *aa++; 5170 } 5171 /* off-diagonal portion of A */ 5172 for (j=jo; j<ncols_o; j++) { 5173 cj[k] = cmap[*bj++]; 5174 ca[k++] = *ba++; 5175 } 5176 } 5177 /* put together the new matrix */ 5178 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5179 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5180 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5181 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5182 mat->free_a = PETSC_TRUE; 5183 mat->free_ij = PETSC_TRUE; 5184 mat->nonew = 0; 5185 } else if (scall == MAT_REUSE_MATRIX) { 5186 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5187 ci = mat->i; cj = mat->j; cam = mat->a; 5188 for (i=0; i<am; i++) { 5189 /* off-diagonal portion of A */ 5190 ncols_o = bi[i+1] - bi[i]; 5191 for (jo=0; jo<ncols_o; jo++) { 5192 col = cmap[*bj]; 5193 if (col >= cstart) break; 5194 *cam++ = *ba++; bj++; 5195 } 5196 /* diagonal portion of A */ 5197 ncols_d = ai[i+1] - ai[i]; 5198 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5199 /* off-diagonal portion of A */ 5200 for (j=jo; j<ncols_o; j++) { 5201 *cam++ = *ba++; bj++; 5202 } 5203 } 5204 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5205 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5206 PetscFunctionReturn(0); 5207 } 5208 5209 #undef __FUNCT__ 5210 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5211 /*@C 5212 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5213 5214 Not Collective 5215 5216 Input Parameters: 5217 + A - the matrix 5218 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5219 - row, col - index sets of rows and columns to extract (or NULL) 5220 5221 Output Parameter: 5222 . A_loc - the local sequential matrix generated 5223 5224 Level: developer 5225 5226 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5227 5228 @*/ 5229 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5230 { 5231 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5232 PetscErrorCode ierr; 5233 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5234 IS isrowa,iscola; 5235 Mat *aloc; 5236 PetscBool match; 5237 5238 PetscFunctionBegin; 5239 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5240 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5241 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5242 if (!row) { 5243 start = A->rmap->rstart; end = A->rmap->rend; 5244 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5245 } else { 5246 isrowa = *row; 5247 } 5248 if (!col) { 5249 start = A->cmap->rstart; 5250 cmap = a->garray; 5251 nzA = a->A->cmap->n; 5252 nzB = a->B->cmap->n; 5253 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5254 ncols = 0; 5255 for (i=0; i<nzB; i++) { 5256 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5257 else break; 5258 } 5259 imark = i; 5260 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5261 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5262 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5263 } else { 5264 iscola = *col; 5265 } 5266 if (scall != MAT_INITIAL_MATRIX) { 5267 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5268 aloc[0] = *A_loc; 5269 } 5270 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5271 *A_loc = aloc[0]; 5272 ierr = PetscFree(aloc);CHKERRQ(ierr); 5273 if (!row) { 5274 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5275 } 5276 if (!col) { 5277 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5278 } 5279 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5280 PetscFunctionReturn(0); 5281 } 5282 5283 #undef __FUNCT__ 5284 #define __FUNCT__ "MatGetBrowsOfAcols" 5285 /*@C 5286 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5287 5288 Collective on Mat 5289 5290 Input Parameters: 5291 + A,B - the matrices in mpiaij format 5292 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5293 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5294 5295 Output Parameter: 5296 + rowb, colb - index sets of rows and columns of B to extract 5297 - B_seq - the sequential matrix generated 5298 5299 Level: developer 5300 5301 @*/ 5302 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5303 { 5304 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5305 PetscErrorCode ierr; 5306 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5307 IS isrowb,iscolb; 5308 Mat *bseq=NULL; 5309 5310 PetscFunctionBegin; 5311 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5312 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); 5313 } 5314 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5315 5316 if (scall == MAT_INITIAL_MATRIX) { 5317 start = A->cmap->rstart; 5318 cmap = a->garray; 5319 nzA = a->A->cmap->n; 5320 nzB = a->B->cmap->n; 5321 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5322 ncols = 0; 5323 for (i=0; i<nzB; i++) { /* row < local row index */ 5324 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5325 else break; 5326 } 5327 imark = i; 5328 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5329 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5330 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5331 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5332 } else { 5333 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5334 isrowb = *rowb; iscolb = *colb; 5335 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5336 bseq[0] = *B_seq; 5337 } 5338 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5339 *B_seq = bseq[0]; 5340 ierr = PetscFree(bseq);CHKERRQ(ierr); 5341 if (!rowb) { 5342 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5343 } else { 5344 *rowb = isrowb; 5345 } 5346 if (!colb) { 5347 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5348 } else { 5349 *colb = iscolb; 5350 } 5351 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5352 PetscFunctionReturn(0); 5353 } 5354 5355 #undef __FUNCT__ 5356 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5357 /* 5358 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5359 of the OFF-DIAGONAL portion of local A 5360 5361 Collective on Mat 5362 5363 Input Parameters: 5364 + A,B - the matrices in mpiaij format 5365 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5366 5367 Output Parameter: 5368 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5369 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5370 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5371 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5372 5373 Level: developer 5374 5375 */ 5376 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5377 { 5378 VecScatter_MPI_General *gen_to,*gen_from; 5379 PetscErrorCode ierr; 5380 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5381 Mat_SeqAIJ *b_oth; 5382 VecScatter ctx =a->Mvctx; 5383 MPI_Comm comm; 5384 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5385 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5386 PetscScalar *rvalues,*svalues; 5387 MatScalar *b_otha,*bufa,*bufA; 5388 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5389 MPI_Request *rwaits = NULL,*swaits = NULL; 5390 MPI_Status *sstatus,rstatus; 5391 PetscMPIInt jj; 5392 PetscInt *cols,sbs,rbs; 5393 PetscScalar *vals; 5394 5395 PetscFunctionBegin; 5396 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5397 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5398 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); 5399 } 5400 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5401 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5402 5403 gen_to = (VecScatter_MPI_General*)ctx->todata; 5404 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5405 rvalues = gen_from->values; /* holds the length of receiving row */ 5406 svalues = gen_to->values; /* holds the length of sending row */ 5407 nrecvs = gen_from->n; 5408 nsends = gen_to->n; 5409 5410 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5411 srow = gen_to->indices; /* local row index to be sent */ 5412 sstarts = gen_to->starts; 5413 sprocs = gen_to->procs; 5414 sstatus = gen_to->sstatus; 5415 sbs = gen_to->bs; 5416 rstarts = gen_from->starts; 5417 rprocs = gen_from->procs; 5418 rbs = gen_from->bs; 5419 5420 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5421 if (scall == MAT_INITIAL_MATRIX) { 5422 /* i-array */ 5423 /*---------*/ 5424 /* post receives */ 5425 for (i=0; i<nrecvs; i++) { 5426 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5427 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5428 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5429 } 5430 5431 /* pack the outgoing message */ 5432 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5433 5434 sstartsj[0] = 0; 5435 rstartsj[0] = 0; 5436 len = 0; /* total length of j or a array to be sent */ 5437 k = 0; 5438 for (i=0; i<nsends; i++) { 5439 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5440 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5441 for (j=0; j<nrows; j++) { 5442 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5443 for (l=0; l<sbs; l++) { 5444 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5445 5446 rowlen[j*sbs+l] = ncols; 5447 5448 len += ncols; 5449 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5450 } 5451 k++; 5452 } 5453 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5454 5455 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5456 } 5457 /* recvs and sends of i-array are completed */ 5458 i = nrecvs; 5459 while (i--) { 5460 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5461 } 5462 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5463 5464 /* allocate buffers for sending j and a arrays */ 5465 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5466 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5467 5468 /* create i-array of B_oth */ 5469 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5470 5471 b_othi[0] = 0; 5472 len = 0; /* total length of j or a array to be received */ 5473 k = 0; 5474 for (i=0; i<nrecvs; i++) { 5475 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5476 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5477 for (j=0; j<nrows; j++) { 5478 b_othi[k+1] = b_othi[k] + rowlen[j]; 5479 len += rowlen[j]; k++; 5480 } 5481 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5482 } 5483 5484 /* allocate space for j and a arrrays of B_oth */ 5485 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5486 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5487 5488 /* j-array */ 5489 /*---------*/ 5490 /* post receives of j-array */ 5491 for (i=0; i<nrecvs; i++) { 5492 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5493 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5494 } 5495 5496 /* pack the outgoing message j-array */ 5497 k = 0; 5498 for (i=0; i<nsends; i++) { 5499 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5500 bufJ = bufj+sstartsj[i]; 5501 for (j=0; j<nrows; j++) { 5502 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5503 for (ll=0; ll<sbs; ll++) { 5504 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5505 for (l=0; l<ncols; l++) { 5506 *bufJ++ = cols[l]; 5507 } 5508 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5509 } 5510 } 5511 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5512 } 5513 5514 /* recvs and sends of j-array are completed */ 5515 i = nrecvs; 5516 while (i--) { 5517 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5518 } 5519 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5520 } else if (scall == MAT_REUSE_MATRIX) { 5521 sstartsj = *startsj_s; 5522 rstartsj = *startsj_r; 5523 bufa = *bufa_ptr; 5524 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5525 b_otha = b_oth->a; 5526 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5527 5528 /* a-array */ 5529 /*---------*/ 5530 /* post receives of a-array */ 5531 for (i=0; i<nrecvs; i++) { 5532 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5533 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5534 } 5535 5536 /* pack the outgoing message a-array */ 5537 k = 0; 5538 for (i=0; i<nsends; i++) { 5539 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5540 bufA = bufa+sstartsj[i]; 5541 for (j=0; j<nrows; j++) { 5542 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5543 for (ll=0; ll<sbs; ll++) { 5544 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5545 for (l=0; l<ncols; l++) { 5546 *bufA++ = vals[l]; 5547 } 5548 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5549 } 5550 } 5551 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5552 } 5553 /* recvs and sends of a-array are completed */ 5554 i = nrecvs; 5555 while (i--) { 5556 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5557 } 5558 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5559 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5560 5561 if (scall == MAT_INITIAL_MATRIX) { 5562 /* put together the new matrix */ 5563 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5564 5565 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5566 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5567 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5568 b_oth->free_a = PETSC_TRUE; 5569 b_oth->free_ij = PETSC_TRUE; 5570 b_oth->nonew = 0; 5571 5572 ierr = PetscFree(bufj);CHKERRQ(ierr); 5573 if (!startsj_s || !bufa_ptr) { 5574 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5575 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5576 } else { 5577 *startsj_s = sstartsj; 5578 *startsj_r = rstartsj; 5579 *bufa_ptr = bufa; 5580 } 5581 } 5582 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5583 PetscFunctionReturn(0); 5584 } 5585 5586 #undef __FUNCT__ 5587 #define __FUNCT__ "MatGetCommunicationStructs" 5588 /*@C 5589 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5590 5591 Not Collective 5592 5593 Input Parameters: 5594 . A - The matrix in mpiaij format 5595 5596 Output Parameter: 5597 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5598 . colmap - A map from global column index to local index into lvec 5599 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5600 5601 Level: developer 5602 5603 @*/ 5604 #if defined(PETSC_USE_CTABLE) 5605 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5606 #else 5607 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5608 #endif 5609 { 5610 Mat_MPIAIJ *a; 5611 5612 PetscFunctionBegin; 5613 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5614 PetscValidPointer(lvec, 2); 5615 PetscValidPointer(colmap, 3); 5616 PetscValidPointer(multScatter, 4); 5617 a = (Mat_MPIAIJ*) A->data; 5618 if (lvec) *lvec = a->lvec; 5619 if (colmap) *colmap = a->colmap; 5620 if (multScatter) *multScatter = a->Mvctx; 5621 PetscFunctionReturn(0); 5622 } 5623 5624 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5625 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5626 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5627 5628 #undef __FUNCT__ 5629 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5630 /* 5631 Computes (B'*A')' since computing B*A directly is untenable 5632 5633 n p p 5634 ( ) ( ) ( ) 5635 m ( A ) * n ( B ) = m ( C ) 5636 ( ) ( ) ( ) 5637 5638 */ 5639 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5640 { 5641 PetscErrorCode ierr; 5642 Mat At,Bt,Ct; 5643 5644 PetscFunctionBegin; 5645 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5646 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5647 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5648 ierr = MatDestroy(&At);CHKERRQ(ierr); 5649 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5650 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5651 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5652 PetscFunctionReturn(0); 5653 } 5654 5655 #undef __FUNCT__ 5656 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5657 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5658 { 5659 PetscErrorCode ierr; 5660 PetscInt m=A->rmap->n,n=B->cmap->n; 5661 Mat Cmat; 5662 5663 PetscFunctionBegin; 5664 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); 5665 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5666 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5667 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5668 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5669 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5670 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5671 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5672 5673 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5674 5675 *C = Cmat; 5676 PetscFunctionReturn(0); 5677 } 5678 5679 /* ----------------------------------------------------------------*/ 5680 #undef __FUNCT__ 5681 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5682 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5683 { 5684 PetscErrorCode ierr; 5685 5686 PetscFunctionBegin; 5687 if (scall == MAT_INITIAL_MATRIX) { 5688 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5689 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5690 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5691 } 5692 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5693 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5694 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5695 PetscFunctionReturn(0); 5696 } 5697 5698 #if defined(PETSC_HAVE_MUMPS) 5699 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5700 #endif 5701 #if defined(PETSC_HAVE_PASTIX) 5702 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5703 #endif 5704 #if defined(PETSC_HAVE_SUPERLU_DIST) 5705 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5706 #endif 5707 #if defined(PETSC_HAVE_CLIQUE) 5708 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5709 #endif 5710 5711 /*MC 5712 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5713 5714 Options Database Keys: 5715 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5716 5717 Level: beginner 5718 5719 .seealso: MatCreateAIJ() 5720 M*/ 5721 5722 #undef __FUNCT__ 5723 #define __FUNCT__ "MatCreate_MPIAIJ" 5724 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5725 { 5726 Mat_MPIAIJ *b; 5727 PetscErrorCode ierr; 5728 PetscMPIInt size; 5729 5730 PetscFunctionBegin; 5731 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5732 5733 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5734 B->data = (void*)b; 5735 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5736 B->assembled = PETSC_FALSE; 5737 B->insertmode = NOT_SET_VALUES; 5738 b->size = size; 5739 5740 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5741 5742 /* build cache for off array entries formed */ 5743 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5744 5745 b->donotstash = PETSC_FALSE; 5746 b->colmap = 0; 5747 b->garray = 0; 5748 b->roworiented = PETSC_TRUE; 5749 5750 /* stuff used for matrix vector multiply */ 5751 b->lvec = NULL; 5752 b->Mvctx = NULL; 5753 5754 /* stuff for MatGetRow() */ 5755 b->rowindices = 0; 5756 b->rowvalues = 0; 5757 b->getrowactive = PETSC_FALSE; 5758 5759 /* flexible pointer used in CUSP/CUSPARSE classes */ 5760 b->spptr = NULL; 5761 5762 #if defined(PETSC_HAVE_MUMPS) 5763 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5764 #endif 5765 #if defined(PETSC_HAVE_PASTIX) 5766 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5767 #endif 5768 #if defined(PETSC_HAVE_SUPERLU_DIST) 5769 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5770 #endif 5771 #if defined(PETSC_HAVE_CLIQUE) 5772 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5773 #endif 5774 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5775 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5776 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5777 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5778 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5779 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5780 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5781 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5782 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5783 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5784 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5785 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5786 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5787 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5788 PetscFunctionReturn(0); 5789 } 5790 5791 #undef __FUNCT__ 5792 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5793 /*@ 5794 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5795 and "off-diagonal" part of the matrix in CSR format. 5796 5797 Collective on MPI_Comm 5798 5799 Input Parameters: 5800 + comm - MPI communicator 5801 . m - number of local rows (Cannot be PETSC_DECIDE) 5802 . n - This value should be the same as the local size used in creating the 5803 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5804 calculated if N is given) For square matrices n is almost always m. 5805 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5806 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5807 . i - row indices for "diagonal" portion of matrix 5808 . j - column indices 5809 . a - matrix values 5810 . oi - row indices for "off-diagonal" portion of matrix 5811 . oj - column indices 5812 - oa - matrix values 5813 5814 Output Parameter: 5815 . mat - the matrix 5816 5817 Level: advanced 5818 5819 Notes: 5820 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5821 must free the arrays once the matrix has been destroyed and not before. 5822 5823 The i and j indices are 0 based 5824 5825 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5826 5827 This sets local rows and cannot be used to set off-processor values. 5828 5829 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5830 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5831 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5832 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5833 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5834 communication if it is known that only local entries will be set. 5835 5836 .keywords: matrix, aij, compressed row, sparse, parallel 5837 5838 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5839 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5840 @*/ 5841 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) 5842 { 5843 PetscErrorCode ierr; 5844 Mat_MPIAIJ *maij; 5845 5846 PetscFunctionBegin; 5847 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5848 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5849 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5850 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5851 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5852 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5853 maij = (Mat_MPIAIJ*) (*mat)->data; 5854 5855 (*mat)->preallocated = PETSC_TRUE; 5856 5857 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5858 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5859 5860 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5861 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5862 5863 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5864 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5865 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5866 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5867 5868 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5869 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5870 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5871 PetscFunctionReturn(0); 5872 } 5873 5874 /* 5875 Special version for direct calls from Fortran 5876 */ 5877 #include <petsc-private/fortranimpl.h> 5878 5879 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5880 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5881 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5882 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5883 #endif 5884 5885 /* Change these macros so can be used in void function */ 5886 #undef CHKERRQ 5887 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5888 #undef SETERRQ2 5889 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5890 #undef SETERRQ3 5891 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5892 #undef SETERRQ 5893 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5894 5895 #undef __FUNCT__ 5896 #define __FUNCT__ "matsetvaluesmpiaij_" 5897 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) 5898 { 5899 Mat mat = *mmat; 5900 PetscInt m = *mm, n = *mn; 5901 InsertMode addv = *maddv; 5902 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5903 PetscScalar value; 5904 PetscErrorCode ierr; 5905 5906 MatCheckPreallocated(mat,1); 5907 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5908 5909 #if defined(PETSC_USE_DEBUG) 5910 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5911 #endif 5912 { 5913 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5914 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5915 PetscBool roworiented = aij->roworiented; 5916 5917 /* Some Variables required in the macro */ 5918 Mat A = aij->A; 5919 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5920 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5921 MatScalar *aa = a->a; 5922 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5923 Mat B = aij->B; 5924 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5925 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5926 MatScalar *ba = b->a; 5927 5928 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5929 PetscInt nonew = a->nonew; 5930 MatScalar *ap1,*ap2; 5931 5932 PetscFunctionBegin; 5933 for (i=0; i<m; i++) { 5934 if (im[i] < 0) continue; 5935 #if defined(PETSC_USE_DEBUG) 5936 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); 5937 #endif 5938 if (im[i] >= rstart && im[i] < rend) { 5939 row = im[i] - rstart; 5940 lastcol1 = -1; 5941 rp1 = aj + ai[row]; 5942 ap1 = aa + ai[row]; 5943 rmax1 = aimax[row]; 5944 nrow1 = ailen[row]; 5945 low1 = 0; 5946 high1 = nrow1; 5947 lastcol2 = -1; 5948 rp2 = bj + bi[row]; 5949 ap2 = ba + bi[row]; 5950 rmax2 = bimax[row]; 5951 nrow2 = bilen[row]; 5952 low2 = 0; 5953 high2 = nrow2; 5954 5955 for (j=0; j<n; j++) { 5956 if (roworiented) value = v[i*n+j]; 5957 else value = v[i+j*m]; 5958 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5959 if (in[j] >= cstart && in[j] < cend) { 5960 col = in[j] - cstart; 5961 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5962 } else if (in[j] < 0) continue; 5963 #if defined(PETSC_USE_DEBUG) 5964 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); 5965 #endif 5966 else { 5967 if (mat->was_assembled) { 5968 if (!aij->colmap) { 5969 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5970 } 5971 #if defined(PETSC_USE_CTABLE) 5972 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5973 col--; 5974 #else 5975 col = aij->colmap[in[j]] - 1; 5976 #endif 5977 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5978 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5979 col = in[j]; 5980 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5981 B = aij->B; 5982 b = (Mat_SeqAIJ*)B->data; 5983 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5984 rp2 = bj + bi[row]; 5985 ap2 = ba + bi[row]; 5986 rmax2 = bimax[row]; 5987 nrow2 = bilen[row]; 5988 low2 = 0; 5989 high2 = nrow2; 5990 bm = aij->B->rmap->n; 5991 ba = b->a; 5992 } 5993 } else col = in[j]; 5994 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5995 } 5996 } 5997 } else if (!aij->donotstash) { 5998 if (roworiented) { 5999 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6000 } else { 6001 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6002 } 6003 } 6004 } 6005 } 6006 PetscFunctionReturnVoid(); 6007 } 6008 6009