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,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm,subcomm=psubcomm->comm; 2560 PetscErrorCode ierr; 2561 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2562 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2563 PetscInt *rowrange = mat->rmap->range; 2564 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2565 Mat A = aij->A,B=aij->B,C=*matredundant; 2566 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2567 PetscScalar *sbuf_a; 2568 PetscInt nzlocal=a->nz+b->nz; 2569 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2570 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2571 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2572 MatScalar *aworkA,*aworkB; 2573 PetscScalar *vals; 2574 PetscMPIInt tag1,tag2,tag3,imdex; 2575 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2576 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2577 MPI_Status recv_status,*send_status; 2578 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2579 PetscInt **rbuf_j=NULL; 2580 PetscScalar **rbuf_a=NULL; 2581 Mat_Redundant *redund =NULL; 2582 2583 PetscFunctionBegin; 2584 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2587 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2588 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2589 2590 if (reuse == MAT_REUSE_MATRIX) { 2591 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2592 if (subsize == 1) { 2593 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2594 redund = c->redundant; 2595 } else { 2596 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2597 redund = c->redundant; 2598 } 2599 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2600 2601 nsends = redund->nsends; 2602 nrecvs = redund->nrecvs; 2603 send_rank = redund->send_rank; 2604 recv_rank = redund->recv_rank; 2605 sbuf_nz = redund->sbuf_nz; 2606 rbuf_nz = redund->rbuf_nz; 2607 sbuf_j = redund->sbuf_j; 2608 sbuf_a = redund->sbuf_a; 2609 rbuf_j = redund->rbuf_j; 2610 rbuf_a = redund->rbuf_a; 2611 } 2612 2613 if (reuse == MAT_INITIAL_MATRIX) { 2614 PetscInt nleftover,np_subcomm; 2615 2616 /* get the destination processors' id send_rank, nsends and nrecvs */ 2617 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2618 2619 np_subcomm = size/nsubcomm; 2620 nleftover = size - nsubcomm*np_subcomm; 2621 2622 /* 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,PetscSubcomm psubcomm,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_in=psubcomm; 2924 MPI_Comm subcomm_in=subcomm; 2925 2926 PetscFunctionBegin; 2927 if (subcomm_in == MPI_COMM_NULL) { /* use psubcomm */ 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 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2933 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2934 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2935 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2936 } 2937 subcomm = psubcomm->comm; 2938 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2939 } else { /* retrieve psubcomm */ 2940 if (psubcomm_in == NULL) { /* user does not provide psubcomm */ 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 psubcomm = c->redundant->psubcomm; 2946 } else { 2947 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2948 psubcomm = c->redundant->psubcomm; 2949 } 2950 } else { /* use psubcomm_in */ 2951 subcomm = psubcomm_in->comm; 2952 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2953 } 2954 } 2955 } 2956 2957 if (subcomm_in == MPI_COMM_NULL && psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2958 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 2959 } else { 2960 /* via MatGetSubMatrices() */ 2961 Mat *matseq; 2962 IS isrow,iscol; 2963 2964 if (reuse == MAT_INITIAL_MATRIX) { 2965 /* create a local sequential matrix matseq[0] */ 2966 mloc_sub = PETSC_DECIDE; 2967 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2968 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2969 rstart = rend - mloc_sub; 2970 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2971 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2972 } else { /* reuse == MAT_REUSE_MATRIX */ 2973 if (subsize == 1) { 2974 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2975 redund = c->redundant; 2976 } else { 2977 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2978 redund = c->redundant; 2979 } 2980 2981 isrow = redund->isrow; 2982 iscol = redund->iscol; 2983 matseq = redund->matseq; 2984 } 2985 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2986 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2987 2988 if (reuse == MAT_INITIAL_MATRIX) { 2989 /* create a supporting struct and attach it to C for reuse */ 2990 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 2991 if (subsize == 1) { 2992 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2993 c->redundant = redund; 2994 } else { 2995 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2996 c->redundant = redund; 2997 } 2998 redund->isrow = isrow; 2999 redund->iscol = iscol; 3000 redund->matseq = matseq; 3001 redund->psubcomm = NULL; 3002 redund->Destroy = (*matredundant)->ops->destroy; 3003 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3004 } 3005 } 3006 3007 if (psubcomm && psubcomm_in==NULL) { 3008 /* if psubcomm is created in this routine, free it in MatDestroy_MatRedundant() */ 3009 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 3010 if (subsize == 1) { 3011 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3012 c->redundant->psubcomm = psubcomm; 3013 } else { 3014 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3015 c->redundant->psubcomm = psubcomm ; 3016 } 3017 } 3018 PetscFunctionReturn(0); 3019 } 3020 3021 #undef __FUNCT__ 3022 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3023 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3024 { 3025 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3026 PetscErrorCode ierr; 3027 PetscInt i,*idxb = 0; 3028 PetscScalar *va,*vb; 3029 Vec vtmp; 3030 3031 PetscFunctionBegin; 3032 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3033 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3034 if (idx) { 3035 for (i=0; i<A->rmap->n; i++) { 3036 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3037 } 3038 } 3039 3040 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3041 if (idx) { 3042 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3043 } 3044 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3045 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3046 3047 for (i=0; i<A->rmap->n; i++) { 3048 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3049 va[i] = vb[i]; 3050 if (idx) idx[i] = a->garray[idxb[i]]; 3051 } 3052 } 3053 3054 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3055 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3056 ierr = PetscFree(idxb);CHKERRQ(ierr); 3057 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3058 PetscFunctionReturn(0); 3059 } 3060 3061 #undef __FUNCT__ 3062 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3063 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3064 { 3065 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3066 PetscErrorCode ierr; 3067 PetscInt i,*idxb = 0; 3068 PetscScalar *va,*vb; 3069 Vec vtmp; 3070 3071 PetscFunctionBegin; 3072 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3073 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3074 if (idx) { 3075 for (i=0; i<A->cmap->n; i++) { 3076 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3077 } 3078 } 3079 3080 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3081 if (idx) { 3082 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3083 } 3084 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3085 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3086 3087 for (i=0; i<A->rmap->n; i++) { 3088 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3089 va[i] = vb[i]; 3090 if (idx) idx[i] = a->garray[idxb[i]]; 3091 } 3092 } 3093 3094 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3095 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3096 ierr = PetscFree(idxb);CHKERRQ(ierr); 3097 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3098 PetscFunctionReturn(0); 3099 } 3100 3101 #undef __FUNCT__ 3102 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3103 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3104 { 3105 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3106 PetscInt n = A->rmap->n; 3107 PetscInt cstart = A->cmap->rstart; 3108 PetscInt *cmap = mat->garray; 3109 PetscInt *diagIdx, *offdiagIdx; 3110 Vec diagV, offdiagV; 3111 PetscScalar *a, *diagA, *offdiagA; 3112 PetscInt r; 3113 PetscErrorCode ierr; 3114 3115 PetscFunctionBegin; 3116 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3117 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3118 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3119 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3120 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3121 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3122 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3123 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3124 for (r = 0; r < n; ++r) { 3125 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3126 a[r] = diagA[r]; 3127 idx[r] = cstart + diagIdx[r]; 3128 } else { 3129 a[r] = offdiagA[r]; 3130 idx[r] = cmap[offdiagIdx[r]]; 3131 } 3132 } 3133 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3134 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3135 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3136 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3137 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3138 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3139 PetscFunctionReturn(0); 3140 } 3141 3142 #undef __FUNCT__ 3143 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3144 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3145 { 3146 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3147 PetscInt n = A->rmap->n; 3148 PetscInt cstart = A->cmap->rstart; 3149 PetscInt *cmap = mat->garray; 3150 PetscInt *diagIdx, *offdiagIdx; 3151 Vec diagV, offdiagV; 3152 PetscScalar *a, *diagA, *offdiagA; 3153 PetscInt r; 3154 PetscErrorCode ierr; 3155 3156 PetscFunctionBegin; 3157 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3158 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3159 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3160 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3161 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3162 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3163 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3164 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3165 for (r = 0; r < n; ++r) { 3166 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3167 a[r] = diagA[r]; 3168 idx[r] = cstart + diagIdx[r]; 3169 } else { 3170 a[r] = offdiagA[r]; 3171 idx[r] = cmap[offdiagIdx[r]]; 3172 } 3173 } 3174 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3175 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3176 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3177 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3178 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3179 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3180 PetscFunctionReturn(0); 3181 } 3182 3183 #undef __FUNCT__ 3184 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3185 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3186 { 3187 PetscErrorCode ierr; 3188 Mat *dummy; 3189 3190 PetscFunctionBegin; 3191 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3192 *newmat = *dummy; 3193 ierr = PetscFree(dummy);CHKERRQ(ierr); 3194 PetscFunctionReturn(0); 3195 } 3196 3197 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3198 3199 #undef __FUNCT__ 3200 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3201 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3202 { 3203 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3204 PetscErrorCode ierr; 3205 3206 PetscFunctionBegin; 3207 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3208 PetscFunctionReturn(0); 3209 } 3210 3211 #undef __FUNCT__ 3212 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3213 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3214 { 3215 PetscErrorCode ierr; 3216 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3217 3218 PetscFunctionBegin; 3219 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3220 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3221 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3222 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3223 PetscFunctionReturn(0); 3224 } 3225 3226 /* -------------------------------------------------------------------*/ 3227 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3228 MatGetRow_MPIAIJ, 3229 MatRestoreRow_MPIAIJ, 3230 MatMult_MPIAIJ, 3231 /* 4*/ MatMultAdd_MPIAIJ, 3232 MatMultTranspose_MPIAIJ, 3233 MatMultTransposeAdd_MPIAIJ, 3234 #if defined(PETSC_HAVE_PBGL) 3235 MatSolve_MPIAIJ, 3236 #else 3237 0, 3238 #endif 3239 0, 3240 0, 3241 /*10*/ 0, 3242 0, 3243 0, 3244 MatSOR_MPIAIJ, 3245 MatTranspose_MPIAIJ, 3246 /*15*/ MatGetInfo_MPIAIJ, 3247 MatEqual_MPIAIJ, 3248 MatGetDiagonal_MPIAIJ, 3249 MatDiagonalScale_MPIAIJ, 3250 MatNorm_MPIAIJ, 3251 /*20*/ MatAssemblyBegin_MPIAIJ, 3252 MatAssemblyEnd_MPIAIJ, 3253 MatSetOption_MPIAIJ, 3254 MatZeroEntries_MPIAIJ, 3255 /*24*/ MatZeroRows_MPIAIJ, 3256 0, 3257 #if defined(PETSC_HAVE_PBGL) 3258 0, 3259 #else 3260 0, 3261 #endif 3262 0, 3263 0, 3264 /*29*/ MatSetUp_MPIAIJ, 3265 #if defined(PETSC_HAVE_PBGL) 3266 0, 3267 #else 3268 0, 3269 #endif 3270 0, 3271 0, 3272 0, 3273 /*34*/ MatDuplicate_MPIAIJ, 3274 0, 3275 0, 3276 0, 3277 0, 3278 /*39*/ MatAXPY_MPIAIJ, 3279 MatGetSubMatrices_MPIAIJ, 3280 MatIncreaseOverlap_MPIAIJ, 3281 MatGetValues_MPIAIJ, 3282 MatCopy_MPIAIJ, 3283 /*44*/ MatGetRowMax_MPIAIJ, 3284 MatScale_MPIAIJ, 3285 0, 3286 0, 3287 MatZeroRowsColumns_MPIAIJ, 3288 /*49*/ MatSetRandom_MPIAIJ, 3289 0, 3290 0, 3291 0, 3292 0, 3293 /*54*/ MatFDColoringCreate_MPIAIJ, 3294 0, 3295 MatSetUnfactored_MPIAIJ, 3296 MatPermute_MPIAIJ, 3297 0, 3298 /*59*/ MatGetSubMatrix_MPIAIJ, 3299 MatDestroy_MPIAIJ, 3300 MatView_MPIAIJ, 3301 0, 3302 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3303 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3304 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3305 0, 3306 0, 3307 0, 3308 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3309 MatGetRowMinAbs_MPIAIJ, 3310 0, 3311 MatSetColoring_MPIAIJ, 3312 0, 3313 MatSetValuesAdifor_MPIAIJ, 3314 /*75*/ MatFDColoringApply_AIJ, 3315 0, 3316 0, 3317 0, 3318 MatFindZeroDiagonals_MPIAIJ, 3319 /*80*/ 0, 3320 0, 3321 0, 3322 /*83*/ MatLoad_MPIAIJ, 3323 0, 3324 0, 3325 0, 3326 0, 3327 0, 3328 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3329 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3330 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3331 MatPtAP_MPIAIJ_MPIAIJ, 3332 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3333 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3334 0, 3335 0, 3336 0, 3337 0, 3338 /*99*/ 0, 3339 0, 3340 0, 3341 MatConjugate_MPIAIJ, 3342 0, 3343 /*104*/MatSetValuesRow_MPIAIJ, 3344 MatRealPart_MPIAIJ, 3345 MatImaginaryPart_MPIAIJ, 3346 0, 3347 0, 3348 /*109*/0, 3349 MatGetRedundantMatrix_MPIAIJ, 3350 MatGetRowMin_MPIAIJ, 3351 0, 3352 0, 3353 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3354 0, 3355 0, 3356 0, 3357 0, 3358 /*119*/0, 3359 0, 3360 0, 3361 0, 3362 MatGetMultiProcBlock_MPIAIJ, 3363 /*124*/MatFindNonzeroRows_MPIAIJ, 3364 MatGetColumnNorms_MPIAIJ, 3365 MatInvertBlockDiagonal_MPIAIJ, 3366 0, 3367 MatGetSubMatricesParallel_MPIAIJ, 3368 /*129*/0, 3369 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3370 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3371 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3372 0, 3373 /*134*/0, 3374 0, 3375 0, 3376 0, 3377 0, 3378 /*139*/0, 3379 0 3380 }; 3381 3382 /* ----------------------------------------------------------------------------------------*/ 3383 3384 #undef __FUNCT__ 3385 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3386 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3387 { 3388 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3389 PetscErrorCode ierr; 3390 3391 PetscFunctionBegin; 3392 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3393 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3394 PetscFunctionReturn(0); 3395 } 3396 3397 #undef __FUNCT__ 3398 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3399 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3400 { 3401 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3402 PetscErrorCode ierr; 3403 3404 PetscFunctionBegin; 3405 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3406 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3407 PetscFunctionReturn(0); 3408 } 3409 3410 #undef __FUNCT__ 3411 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3412 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3413 { 3414 Mat_MPIAIJ *b; 3415 PetscErrorCode ierr; 3416 3417 PetscFunctionBegin; 3418 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3419 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3420 b = (Mat_MPIAIJ*)B->data; 3421 3422 if (!B->preallocated) { 3423 /* Explicitly create 2 MATSEQAIJ matrices. */ 3424 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3425 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3426 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3427 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3428 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3429 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3430 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3431 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3432 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3433 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3434 } 3435 3436 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3437 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3438 B->preallocated = PETSC_TRUE; 3439 PetscFunctionReturn(0); 3440 } 3441 3442 #undef __FUNCT__ 3443 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3444 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3445 { 3446 Mat mat; 3447 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3448 PetscErrorCode ierr; 3449 3450 PetscFunctionBegin; 3451 *newmat = 0; 3452 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3453 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3454 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3455 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3456 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3457 a = (Mat_MPIAIJ*)mat->data; 3458 3459 mat->factortype = matin->factortype; 3460 mat->rmap->bs = matin->rmap->bs; 3461 mat->cmap->bs = matin->cmap->bs; 3462 mat->assembled = PETSC_TRUE; 3463 mat->insertmode = NOT_SET_VALUES; 3464 mat->preallocated = PETSC_TRUE; 3465 3466 a->size = oldmat->size; 3467 a->rank = oldmat->rank; 3468 a->donotstash = oldmat->donotstash; 3469 a->roworiented = oldmat->roworiented; 3470 a->rowindices = 0; 3471 a->rowvalues = 0; 3472 a->getrowactive = PETSC_FALSE; 3473 3474 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3475 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3476 3477 if (oldmat->colmap) { 3478 #if defined(PETSC_USE_CTABLE) 3479 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3480 #else 3481 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3482 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3483 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3484 #endif 3485 } else a->colmap = 0; 3486 if (oldmat->garray) { 3487 PetscInt len; 3488 len = oldmat->B->cmap->n; 3489 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3490 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3491 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3492 } else a->garray = 0; 3493 3494 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3495 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3496 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3497 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3498 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3499 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3500 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3501 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3502 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3503 *newmat = mat; 3504 PetscFunctionReturn(0); 3505 } 3506 3507 3508 3509 #undef __FUNCT__ 3510 #define __FUNCT__ "MatLoad_MPIAIJ" 3511 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3512 { 3513 PetscScalar *vals,*svals; 3514 MPI_Comm comm; 3515 PetscErrorCode ierr; 3516 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3517 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3518 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3519 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3520 PetscInt cend,cstart,n,*rowners,sizesset=1; 3521 int fd; 3522 PetscInt bs = 1; 3523 3524 PetscFunctionBegin; 3525 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3526 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3527 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3528 if (!rank) { 3529 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3530 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3531 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3532 } 3533 3534 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3535 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3536 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3537 3538 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3539 3540 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3541 M = header[1]; N = header[2]; 3542 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3543 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3544 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3545 3546 /* If global sizes are set, check if they are consistent with that given in the file */ 3547 if (sizesset) { 3548 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3549 } 3550 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); 3551 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); 3552 3553 /* determine ownership of all (block) rows */ 3554 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3555 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3556 else m = newMat->rmap->n; /* Set by user */ 3557 3558 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3559 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3560 3561 /* First process needs enough room for process with most rows */ 3562 if (!rank) { 3563 mmax = rowners[1]; 3564 for (i=2; i<=size; i++) { 3565 mmax = PetscMax(mmax, rowners[i]); 3566 } 3567 } else mmax = -1; /* unused, but compilers complain */ 3568 3569 rowners[0] = 0; 3570 for (i=2; i<=size; i++) { 3571 rowners[i] += rowners[i-1]; 3572 } 3573 rstart = rowners[rank]; 3574 rend = rowners[rank+1]; 3575 3576 /* distribute row lengths to all processors */ 3577 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3578 if (!rank) { 3579 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3580 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3581 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3582 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3583 for (j=0; j<m; j++) { 3584 procsnz[0] += ourlens[j]; 3585 } 3586 for (i=1; i<size; i++) { 3587 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3588 /* calculate the number of nonzeros on each processor */ 3589 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3590 procsnz[i] += rowlengths[j]; 3591 } 3592 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3593 } 3594 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3595 } else { 3596 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3597 } 3598 3599 if (!rank) { 3600 /* determine max buffer needed and allocate it */ 3601 maxnz = 0; 3602 for (i=0; i<size; i++) { 3603 maxnz = PetscMax(maxnz,procsnz[i]); 3604 } 3605 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3606 3607 /* read in my part of the matrix column indices */ 3608 nz = procsnz[0]; 3609 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3610 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3611 3612 /* read in every one elses and ship off */ 3613 for (i=1; i<size; i++) { 3614 nz = procsnz[i]; 3615 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3616 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3617 } 3618 ierr = PetscFree(cols);CHKERRQ(ierr); 3619 } else { 3620 /* determine buffer space needed for message */ 3621 nz = 0; 3622 for (i=0; i<m; i++) { 3623 nz += ourlens[i]; 3624 } 3625 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3626 3627 /* receive message of column indices*/ 3628 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3629 } 3630 3631 /* determine column ownership if matrix is not square */ 3632 if (N != M) { 3633 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3634 else n = newMat->cmap->n; 3635 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3636 cstart = cend - n; 3637 } else { 3638 cstart = rstart; 3639 cend = rend; 3640 n = cend - cstart; 3641 } 3642 3643 /* loop over local rows, determining number of off diagonal entries */ 3644 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3645 jj = 0; 3646 for (i=0; i<m; i++) { 3647 for (j=0; j<ourlens[i]; j++) { 3648 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3649 jj++; 3650 } 3651 } 3652 3653 for (i=0; i<m; i++) { 3654 ourlens[i] -= offlens[i]; 3655 } 3656 if (!sizesset) { 3657 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3658 } 3659 3660 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3661 3662 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3663 3664 for (i=0; i<m; i++) { 3665 ourlens[i] += offlens[i]; 3666 } 3667 3668 if (!rank) { 3669 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3670 3671 /* read in my part of the matrix numerical values */ 3672 nz = procsnz[0]; 3673 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3674 3675 /* insert into matrix */ 3676 jj = rstart; 3677 smycols = mycols; 3678 svals = vals; 3679 for (i=0; i<m; i++) { 3680 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3681 smycols += ourlens[i]; 3682 svals += ourlens[i]; 3683 jj++; 3684 } 3685 3686 /* read in other processors and ship out */ 3687 for (i=1; i<size; i++) { 3688 nz = procsnz[i]; 3689 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3690 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3691 } 3692 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3693 } else { 3694 /* receive numeric values */ 3695 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3696 3697 /* receive message of values*/ 3698 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3699 3700 /* insert into matrix */ 3701 jj = rstart; 3702 smycols = mycols; 3703 svals = vals; 3704 for (i=0; i<m; i++) { 3705 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3706 smycols += ourlens[i]; 3707 svals += ourlens[i]; 3708 jj++; 3709 } 3710 } 3711 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3712 ierr = PetscFree(vals);CHKERRQ(ierr); 3713 ierr = PetscFree(mycols);CHKERRQ(ierr); 3714 ierr = PetscFree(rowners);CHKERRQ(ierr); 3715 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3716 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3717 PetscFunctionReturn(0); 3718 } 3719 3720 #undef __FUNCT__ 3721 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3722 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3723 { 3724 PetscErrorCode ierr; 3725 IS iscol_local; 3726 PetscInt csize; 3727 3728 PetscFunctionBegin; 3729 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3730 if (call == MAT_REUSE_MATRIX) { 3731 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3732 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3733 } else { 3734 PetscInt cbs; 3735 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3736 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3737 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3738 } 3739 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3740 if (call == MAT_INITIAL_MATRIX) { 3741 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3742 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3743 } 3744 PetscFunctionReturn(0); 3745 } 3746 3747 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3748 #undef __FUNCT__ 3749 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3750 /* 3751 Not great since it makes two copies of the submatrix, first an SeqAIJ 3752 in local and then by concatenating the local matrices the end result. 3753 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3754 3755 Note: This requires a sequential iscol with all indices. 3756 */ 3757 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3758 { 3759 PetscErrorCode ierr; 3760 PetscMPIInt rank,size; 3761 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3762 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3763 PetscBool allcolumns, colflag; 3764 Mat M,Mreuse; 3765 MatScalar *vwork,*aa; 3766 MPI_Comm comm; 3767 Mat_SeqAIJ *aij; 3768 3769 PetscFunctionBegin; 3770 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3771 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3772 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3773 3774 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3775 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3776 if (colflag && ncol == mat->cmap->N) { 3777 allcolumns = PETSC_TRUE; 3778 } else { 3779 allcolumns = PETSC_FALSE; 3780 } 3781 if (call == MAT_REUSE_MATRIX) { 3782 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3783 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3784 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3785 } else { 3786 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3787 } 3788 3789 /* 3790 m - number of local rows 3791 n - number of columns (same on all processors) 3792 rstart - first row in new global matrix generated 3793 */ 3794 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3795 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3796 if (call == MAT_INITIAL_MATRIX) { 3797 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3798 ii = aij->i; 3799 jj = aij->j; 3800 3801 /* 3802 Determine the number of non-zeros in the diagonal and off-diagonal 3803 portions of the matrix in order to do correct preallocation 3804 */ 3805 3806 /* first get start and end of "diagonal" columns */ 3807 if (csize == PETSC_DECIDE) { 3808 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3809 if (mglobal == n) { /* square matrix */ 3810 nlocal = m; 3811 } else { 3812 nlocal = n/size + ((n % size) > rank); 3813 } 3814 } else { 3815 nlocal = csize; 3816 } 3817 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3818 rstart = rend - nlocal; 3819 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); 3820 3821 /* next, compute all the lengths */ 3822 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3823 olens = dlens + m; 3824 for (i=0; i<m; i++) { 3825 jend = ii[i+1] - ii[i]; 3826 olen = 0; 3827 dlen = 0; 3828 for (j=0; j<jend; j++) { 3829 if (*jj < rstart || *jj >= rend) olen++; 3830 else dlen++; 3831 jj++; 3832 } 3833 olens[i] = olen; 3834 dlens[i] = dlen; 3835 } 3836 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3837 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3838 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3839 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3840 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3841 ierr = PetscFree(dlens);CHKERRQ(ierr); 3842 } else { 3843 PetscInt ml,nl; 3844 3845 M = *newmat; 3846 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3847 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3848 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3849 /* 3850 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3851 rather than the slower MatSetValues(). 3852 */ 3853 M->was_assembled = PETSC_TRUE; 3854 M->assembled = PETSC_FALSE; 3855 } 3856 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3857 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3858 ii = aij->i; 3859 jj = aij->j; 3860 aa = aij->a; 3861 for (i=0; i<m; i++) { 3862 row = rstart + i; 3863 nz = ii[i+1] - ii[i]; 3864 cwork = jj; jj += nz; 3865 vwork = aa; aa += nz; 3866 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3867 } 3868 3869 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3870 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3871 *newmat = M; 3872 3873 /* save submatrix used in processor for next request */ 3874 if (call == MAT_INITIAL_MATRIX) { 3875 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3876 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3877 } 3878 PetscFunctionReturn(0); 3879 } 3880 3881 #undef __FUNCT__ 3882 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3883 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3884 { 3885 PetscInt m,cstart, cend,j,nnz,i,d; 3886 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3887 const PetscInt *JJ; 3888 PetscScalar *values; 3889 PetscErrorCode ierr; 3890 3891 PetscFunctionBegin; 3892 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3893 3894 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3895 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3896 m = B->rmap->n; 3897 cstart = B->cmap->rstart; 3898 cend = B->cmap->rend; 3899 rstart = B->rmap->rstart; 3900 3901 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3902 3903 #if defined(PETSC_USE_DEBUGGING) 3904 for (i=0; i<m; i++) { 3905 nnz = Ii[i+1]- Ii[i]; 3906 JJ = J + Ii[i]; 3907 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3908 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3909 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); 3910 } 3911 #endif 3912 3913 for (i=0; i<m; i++) { 3914 nnz = Ii[i+1]- Ii[i]; 3915 JJ = J + Ii[i]; 3916 nnz_max = PetscMax(nnz_max,nnz); 3917 d = 0; 3918 for (j=0; j<nnz; j++) { 3919 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3920 } 3921 d_nnz[i] = d; 3922 o_nnz[i] = nnz - d; 3923 } 3924 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3925 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3926 3927 if (v) values = (PetscScalar*)v; 3928 else { 3929 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3930 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3931 } 3932 3933 for (i=0; i<m; i++) { 3934 ii = i + rstart; 3935 nnz = Ii[i+1]- Ii[i]; 3936 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3937 } 3938 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3939 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3940 3941 if (!v) { 3942 ierr = PetscFree(values);CHKERRQ(ierr); 3943 } 3944 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3945 PetscFunctionReturn(0); 3946 } 3947 3948 #undef __FUNCT__ 3949 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3950 /*@ 3951 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3952 (the default parallel PETSc format). 3953 3954 Collective on MPI_Comm 3955 3956 Input Parameters: 3957 + B - the matrix 3958 . i - the indices into j for the start of each local row (starts with zero) 3959 . j - the column indices for each local row (starts with zero) 3960 - v - optional values in the matrix 3961 3962 Level: developer 3963 3964 Notes: 3965 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3966 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3967 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3968 3969 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3970 3971 The format which is used for the sparse matrix input, is equivalent to a 3972 row-major ordering.. i.e for the following matrix, the input data expected is 3973 as shown: 3974 3975 1 0 0 3976 2 0 3 P0 3977 ------- 3978 4 5 6 P1 3979 3980 Process0 [P0]: rows_owned=[0,1] 3981 i = {0,1,3} [size = nrow+1 = 2+1] 3982 j = {0,0,2} [size = nz = 6] 3983 v = {1,2,3} [size = nz = 6] 3984 3985 Process1 [P1]: rows_owned=[2] 3986 i = {0,3} [size = nrow+1 = 1+1] 3987 j = {0,1,2} [size = nz = 6] 3988 v = {4,5,6} [size = nz = 6] 3989 3990 .keywords: matrix, aij, compressed row, sparse, parallel 3991 3992 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3993 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3994 @*/ 3995 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3996 { 3997 PetscErrorCode ierr; 3998 3999 PetscFunctionBegin; 4000 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4001 PetscFunctionReturn(0); 4002 } 4003 4004 #undef __FUNCT__ 4005 #define __FUNCT__ "MatMPIAIJSetPreallocation" 4006 /*@C 4007 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4008 (the default parallel PETSc format). For good matrix assembly performance 4009 the user should preallocate the matrix storage by setting the parameters 4010 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4011 performance can be increased by more than a factor of 50. 4012 4013 Collective on MPI_Comm 4014 4015 Input Parameters: 4016 + A - the matrix 4017 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4018 (same value is used for all local rows) 4019 . d_nnz - array containing the number of nonzeros in the various rows of the 4020 DIAGONAL portion of the local submatrix (possibly different for each row) 4021 or NULL, if d_nz is used to specify the nonzero structure. 4022 The size of this array is equal to the number of local rows, i.e 'm'. 4023 For matrices that will be factored, you must leave room for (and set) 4024 the diagonal entry even if it is zero. 4025 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4026 submatrix (same value is used for all local rows). 4027 - o_nnz - array containing the number of nonzeros in the various rows of the 4028 OFF-DIAGONAL portion of the local submatrix (possibly different for 4029 each row) or NULL, if o_nz is used to specify the nonzero 4030 structure. The size of this array is equal to the number 4031 of local rows, i.e 'm'. 4032 4033 If the *_nnz parameter is given then the *_nz parameter is ignored 4034 4035 The AIJ format (also called the Yale sparse matrix format or 4036 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4037 storage. The stored row and column indices begin with zero. 4038 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4039 4040 The parallel matrix is partitioned such that the first m0 rows belong to 4041 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4042 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4043 4044 The DIAGONAL portion of the local submatrix of a processor can be defined 4045 as the submatrix which is obtained by extraction the part corresponding to 4046 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4047 first row that belongs to the processor, r2 is the last row belonging to 4048 the this processor, and c1-c2 is range of indices of the local part of a 4049 vector suitable for applying the matrix to. This is an mxn matrix. In the 4050 common case of a square matrix, the row and column ranges are the same and 4051 the DIAGONAL part is also square. The remaining portion of the local 4052 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4053 4054 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4055 4056 You can call MatGetInfo() to get information on how effective the preallocation was; 4057 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4058 You can also run with the option -info and look for messages with the string 4059 malloc in them to see if additional memory allocation was needed. 4060 4061 Example usage: 4062 4063 Consider the following 8x8 matrix with 34 non-zero values, that is 4064 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4065 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4066 as follows: 4067 4068 .vb 4069 1 2 0 | 0 3 0 | 0 4 4070 Proc0 0 5 6 | 7 0 0 | 8 0 4071 9 0 10 | 11 0 0 | 12 0 4072 ------------------------------------- 4073 13 0 14 | 15 16 17 | 0 0 4074 Proc1 0 18 0 | 19 20 21 | 0 0 4075 0 0 0 | 22 23 0 | 24 0 4076 ------------------------------------- 4077 Proc2 25 26 27 | 0 0 28 | 29 0 4078 30 0 0 | 31 32 33 | 0 34 4079 .ve 4080 4081 This can be represented as a collection of submatrices as: 4082 4083 .vb 4084 A B C 4085 D E F 4086 G H I 4087 .ve 4088 4089 Where the submatrices A,B,C are owned by proc0, D,E,F are 4090 owned by proc1, G,H,I are owned by proc2. 4091 4092 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4093 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4094 The 'M','N' parameters are 8,8, and have the same values on all procs. 4095 4096 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4097 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4098 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4099 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4100 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4101 matrix, ans [DF] as another SeqAIJ matrix. 4102 4103 When d_nz, o_nz parameters are specified, d_nz storage elements are 4104 allocated for every row of the local diagonal submatrix, and o_nz 4105 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4106 One way to choose d_nz and o_nz is to use the max nonzerors per local 4107 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4108 In this case, the values of d_nz,o_nz are: 4109 .vb 4110 proc0 : dnz = 2, o_nz = 2 4111 proc1 : dnz = 3, o_nz = 2 4112 proc2 : dnz = 1, o_nz = 4 4113 .ve 4114 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4115 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4116 for proc3. i.e we are using 12+15+10=37 storage locations to store 4117 34 values. 4118 4119 When d_nnz, o_nnz parameters are specified, the storage is specified 4120 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4121 In the above case the values for d_nnz,o_nnz are: 4122 .vb 4123 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4124 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4125 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4126 .ve 4127 Here the space allocated is sum of all the above values i.e 34, and 4128 hence pre-allocation is perfect. 4129 4130 Level: intermediate 4131 4132 .keywords: matrix, aij, compressed row, sparse, parallel 4133 4134 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4135 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4136 @*/ 4137 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4138 { 4139 PetscErrorCode ierr; 4140 4141 PetscFunctionBegin; 4142 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4143 PetscValidType(B,1); 4144 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4145 PetscFunctionReturn(0); 4146 } 4147 4148 #undef __FUNCT__ 4149 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4150 /*@ 4151 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4152 CSR format the local rows. 4153 4154 Collective on MPI_Comm 4155 4156 Input Parameters: 4157 + comm - MPI communicator 4158 . m - number of local rows (Cannot be PETSC_DECIDE) 4159 . n - This value should be the same as the local size used in creating the 4160 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4161 calculated if N is given) For square matrices n is almost always m. 4162 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4163 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4164 . i - row indices 4165 . j - column indices 4166 - a - matrix values 4167 4168 Output Parameter: 4169 . mat - the matrix 4170 4171 Level: intermediate 4172 4173 Notes: 4174 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4175 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4176 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4177 4178 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4179 4180 The format which is used for the sparse matrix input, is equivalent to a 4181 row-major ordering.. i.e for the following matrix, the input data expected is 4182 as shown: 4183 4184 1 0 0 4185 2 0 3 P0 4186 ------- 4187 4 5 6 P1 4188 4189 Process0 [P0]: rows_owned=[0,1] 4190 i = {0,1,3} [size = nrow+1 = 2+1] 4191 j = {0,0,2} [size = nz = 6] 4192 v = {1,2,3} [size = nz = 6] 4193 4194 Process1 [P1]: rows_owned=[2] 4195 i = {0,3} [size = nrow+1 = 1+1] 4196 j = {0,1,2} [size = nz = 6] 4197 v = {4,5,6} [size = nz = 6] 4198 4199 .keywords: matrix, aij, compressed row, sparse, parallel 4200 4201 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4202 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4203 @*/ 4204 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4205 { 4206 PetscErrorCode ierr; 4207 4208 PetscFunctionBegin; 4209 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4210 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4211 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4212 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4213 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4214 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4215 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4216 PetscFunctionReturn(0); 4217 } 4218 4219 #undef __FUNCT__ 4220 #define __FUNCT__ "MatCreateAIJ" 4221 /*@C 4222 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4223 (the default parallel PETSc format). For good matrix assembly performance 4224 the user should preallocate the matrix storage by setting the parameters 4225 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4226 performance can be increased by more than a factor of 50. 4227 4228 Collective on MPI_Comm 4229 4230 Input Parameters: 4231 + comm - MPI communicator 4232 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4233 This value should be the same as the local size used in creating the 4234 y vector for the matrix-vector product y = Ax. 4235 . n - This value should be the same as the local size used in creating the 4236 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4237 calculated if N is given) For square matrices n is almost always m. 4238 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4239 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4240 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4241 (same value is used for all local rows) 4242 . d_nnz - array containing the number of nonzeros in the various rows of the 4243 DIAGONAL portion of the local submatrix (possibly different for each row) 4244 or NULL, if d_nz is used to specify the nonzero structure. 4245 The size of this array is equal to the number of local rows, i.e 'm'. 4246 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4247 submatrix (same value is used for all local rows). 4248 - o_nnz - array containing the number of nonzeros in the various rows of the 4249 OFF-DIAGONAL portion of the local submatrix (possibly different for 4250 each row) or NULL, if o_nz is used to specify the nonzero 4251 structure. The size of this array is equal to the number 4252 of local rows, i.e 'm'. 4253 4254 Output Parameter: 4255 . A - the matrix 4256 4257 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4258 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4259 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4260 4261 Notes: 4262 If the *_nnz parameter is given then the *_nz parameter is ignored 4263 4264 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4265 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4266 storage requirements for this matrix. 4267 4268 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4269 processor than it must be used on all processors that share the object for 4270 that argument. 4271 4272 The user MUST specify either the local or global matrix dimensions 4273 (possibly both). 4274 4275 The parallel matrix is partitioned across processors such that the 4276 first m0 rows belong to process 0, the next m1 rows belong to 4277 process 1, the next m2 rows belong to process 2 etc.. where 4278 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4279 values corresponding to [m x N] submatrix. 4280 4281 The columns are logically partitioned with the n0 columns belonging 4282 to 0th partition, the next n1 columns belonging to the next 4283 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4284 4285 The DIAGONAL portion of the local submatrix on any given processor 4286 is the submatrix corresponding to the rows and columns m,n 4287 corresponding to the given processor. i.e diagonal matrix on 4288 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4289 etc. The remaining portion of the local submatrix [m x (N-n)] 4290 constitute the OFF-DIAGONAL portion. The example below better 4291 illustrates this concept. 4292 4293 For a square global matrix we define each processor's diagonal portion 4294 to be its local rows and the corresponding columns (a square submatrix); 4295 each processor's off-diagonal portion encompasses the remainder of the 4296 local matrix (a rectangular submatrix). 4297 4298 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4299 4300 When calling this routine with a single process communicator, a matrix of 4301 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4302 type of communicator, use the construction mechanism: 4303 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4304 4305 By default, this format uses inodes (identical nodes) when possible. 4306 We search for consecutive rows with the same nonzero structure, thereby 4307 reusing matrix information to achieve increased efficiency. 4308 4309 Options Database Keys: 4310 + -mat_no_inode - Do not use inodes 4311 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4312 - -mat_aij_oneindex - Internally use indexing starting at 1 4313 rather than 0. Note that when calling MatSetValues(), 4314 the user still MUST index entries starting at 0! 4315 4316 4317 Example usage: 4318 4319 Consider the following 8x8 matrix with 34 non-zero values, that is 4320 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4321 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4322 as follows: 4323 4324 .vb 4325 1 2 0 | 0 3 0 | 0 4 4326 Proc0 0 5 6 | 7 0 0 | 8 0 4327 9 0 10 | 11 0 0 | 12 0 4328 ------------------------------------- 4329 13 0 14 | 15 16 17 | 0 0 4330 Proc1 0 18 0 | 19 20 21 | 0 0 4331 0 0 0 | 22 23 0 | 24 0 4332 ------------------------------------- 4333 Proc2 25 26 27 | 0 0 28 | 29 0 4334 30 0 0 | 31 32 33 | 0 34 4335 .ve 4336 4337 This can be represented as a collection of submatrices as: 4338 4339 .vb 4340 A B C 4341 D E F 4342 G H I 4343 .ve 4344 4345 Where the submatrices A,B,C are owned by proc0, D,E,F are 4346 owned by proc1, G,H,I are owned by proc2. 4347 4348 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4349 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4350 The 'M','N' parameters are 8,8, and have the same values on all procs. 4351 4352 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4353 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4354 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4355 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4356 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4357 matrix, ans [DF] as another SeqAIJ matrix. 4358 4359 When d_nz, o_nz parameters are specified, d_nz storage elements are 4360 allocated for every row of the local diagonal submatrix, and o_nz 4361 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4362 One way to choose d_nz and o_nz is to use the max nonzerors per local 4363 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4364 In this case, the values of d_nz,o_nz are: 4365 .vb 4366 proc0 : dnz = 2, o_nz = 2 4367 proc1 : dnz = 3, o_nz = 2 4368 proc2 : dnz = 1, o_nz = 4 4369 .ve 4370 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4371 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4372 for proc3. i.e we are using 12+15+10=37 storage locations to store 4373 34 values. 4374 4375 When d_nnz, o_nnz parameters are specified, the storage is specified 4376 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4377 In the above case the values for d_nnz,o_nnz are: 4378 .vb 4379 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4380 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4381 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4382 .ve 4383 Here the space allocated is sum of all the above values i.e 34, and 4384 hence pre-allocation is perfect. 4385 4386 Level: intermediate 4387 4388 .keywords: matrix, aij, compressed row, sparse, parallel 4389 4390 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4391 MPIAIJ, MatCreateMPIAIJWithArrays() 4392 @*/ 4393 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) 4394 { 4395 PetscErrorCode ierr; 4396 PetscMPIInt size; 4397 4398 PetscFunctionBegin; 4399 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4400 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4401 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4402 if (size > 1) { 4403 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4404 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4405 } else { 4406 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4407 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4408 } 4409 PetscFunctionReturn(0); 4410 } 4411 4412 #undef __FUNCT__ 4413 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4414 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4415 { 4416 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4417 4418 PetscFunctionBegin; 4419 *Ad = a->A; 4420 *Ao = a->B; 4421 *colmap = a->garray; 4422 PetscFunctionReturn(0); 4423 } 4424 4425 #undef __FUNCT__ 4426 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4427 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4428 { 4429 PetscErrorCode ierr; 4430 PetscInt i; 4431 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4432 4433 PetscFunctionBegin; 4434 if (coloring->ctype == IS_COLORING_GLOBAL) { 4435 ISColoringValue *allcolors,*colors; 4436 ISColoring ocoloring; 4437 4438 /* set coloring for diagonal portion */ 4439 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4440 4441 /* set coloring for off-diagonal portion */ 4442 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4443 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4444 for (i=0; i<a->B->cmap->n; i++) { 4445 colors[i] = allcolors[a->garray[i]]; 4446 } 4447 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4448 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4449 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4450 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4451 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4452 ISColoringValue *colors; 4453 PetscInt *larray; 4454 ISColoring ocoloring; 4455 4456 /* set coloring for diagonal portion */ 4457 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4458 for (i=0; i<a->A->cmap->n; i++) { 4459 larray[i] = i + A->cmap->rstart; 4460 } 4461 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4462 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4463 for (i=0; i<a->A->cmap->n; i++) { 4464 colors[i] = coloring->colors[larray[i]]; 4465 } 4466 ierr = PetscFree(larray);CHKERRQ(ierr); 4467 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4468 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4469 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4470 4471 /* set coloring for off-diagonal portion */ 4472 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4473 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4474 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4475 for (i=0; i<a->B->cmap->n; i++) { 4476 colors[i] = coloring->colors[larray[i]]; 4477 } 4478 ierr = PetscFree(larray);CHKERRQ(ierr); 4479 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4480 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4481 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4482 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4483 PetscFunctionReturn(0); 4484 } 4485 4486 #undef __FUNCT__ 4487 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4488 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4489 { 4490 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4491 PetscErrorCode ierr; 4492 4493 PetscFunctionBegin; 4494 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4495 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4496 PetscFunctionReturn(0); 4497 } 4498 4499 #undef __FUNCT__ 4500 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4501 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4502 { 4503 PetscErrorCode ierr; 4504 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4505 PetscInt *indx; 4506 4507 PetscFunctionBegin; 4508 /* This routine will ONLY return MPIAIJ type matrix */ 4509 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4510 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4511 if (n == PETSC_DECIDE) { 4512 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4513 } 4514 /* Check sum(n) = N */ 4515 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4516 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4517 4518 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4519 rstart -= m; 4520 4521 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4522 for (i=0; i<m; i++) { 4523 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4524 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4525 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4526 } 4527 4528 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4529 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4530 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4531 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4532 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4533 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4534 PetscFunctionReturn(0); 4535 } 4536 4537 #undef __FUNCT__ 4538 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4539 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4540 { 4541 PetscErrorCode ierr; 4542 PetscInt m,N,i,rstart,nnz,Ii; 4543 PetscInt *indx; 4544 PetscScalar *values; 4545 4546 PetscFunctionBegin; 4547 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4548 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4549 for (i=0; i<m; i++) { 4550 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4551 Ii = i + rstart; 4552 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4553 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4554 } 4555 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4556 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4557 PetscFunctionReturn(0); 4558 } 4559 4560 #undef __FUNCT__ 4561 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4562 /*@ 4563 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4564 matrices from each processor 4565 4566 Collective on MPI_Comm 4567 4568 Input Parameters: 4569 + comm - the communicators the parallel matrix will live on 4570 . inmat - the input sequential matrices 4571 . n - number of local columns (or PETSC_DECIDE) 4572 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4573 4574 Output Parameter: 4575 . outmat - the parallel matrix generated 4576 4577 Level: advanced 4578 4579 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4580 4581 @*/ 4582 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4583 { 4584 PetscErrorCode ierr; 4585 PetscMPIInt size; 4586 4587 PetscFunctionBegin; 4588 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4589 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4590 if (size == 1) { 4591 if (scall == MAT_INITIAL_MATRIX) { 4592 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4593 } else { 4594 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4595 } 4596 } else { 4597 if (scall == MAT_INITIAL_MATRIX) { 4598 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4599 } 4600 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4601 } 4602 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4603 PetscFunctionReturn(0); 4604 } 4605 4606 #undef __FUNCT__ 4607 #define __FUNCT__ "MatFileSplit" 4608 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4609 { 4610 PetscErrorCode ierr; 4611 PetscMPIInt rank; 4612 PetscInt m,N,i,rstart,nnz; 4613 size_t len; 4614 const PetscInt *indx; 4615 PetscViewer out; 4616 char *name; 4617 Mat B; 4618 const PetscScalar *values; 4619 4620 PetscFunctionBegin; 4621 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4622 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4623 /* Should this be the type of the diagonal block of A? */ 4624 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4625 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4626 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4627 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4628 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4629 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4630 for (i=0; i<m; i++) { 4631 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4632 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4633 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4634 } 4635 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4636 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4637 4638 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4639 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4640 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4641 sprintf(name,"%s.%d",outfile,rank); 4642 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4643 ierr = PetscFree(name);CHKERRQ(ierr); 4644 ierr = MatView(B,out);CHKERRQ(ierr); 4645 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4646 ierr = MatDestroy(&B);CHKERRQ(ierr); 4647 PetscFunctionReturn(0); 4648 } 4649 4650 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4651 #undef __FUNCT__ 4652 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4653 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4654 { 4655 PetscErrorCode ierr; 4656 Mat_Merge_SeqsToMPI *merge; 4657 PetscContainer container; 4658 4659 PetscFunctionBegin; 4660 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4661 if (container) { 4662 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4663 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4664 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4665 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4666 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4667 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4668 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4669 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4670 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4671 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4672 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4673 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4674 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4675 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4676 ierr = PetscFree(merge);CHKERRQ(ierr); 4677 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4678 } 4679 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4680 PetscFunctionReturn(0); 4681 } 4682 4683 #include <../src/mat/utils/freespace.h> 4684 #include <petscbt.h> 4685 4686 #undef __FUNCT__ 4687 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4688 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4689 { 4690 PetscErrorCode ierr; 4691 MPI_Comm comm; 4692 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4693 PetscMPIInt size,rank,taga,*len_s; 4694 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4695 PetscInt proc,m; 4696 PetscInt **buf_ri,**buf_rj; 4697 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4698 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4699 MPI_Request *s_waits,*r_waits; 4700 MPI_Status *status; 4701 MatScalar *aa=a->a; 4702 MatScalar **abuf_r,*ba_i; 4703 Mat_Merge_SeqsToMPI *merge; 4704 PetscContainer container; 4705 4706 PetscFunctionBegin; 4707 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4708 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4709 4710 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4711 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4712 4713 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4714 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4715 4716 bi = merge->bi; 4717 bj = merge->bj; 4718 buf_ri = merge->buf_ri; 4719 buf_rj = merge->buf_rj; 4720 4721 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4722 owners = merge->rowmap->range; 4723 len_s = merge->len_s; 4724 4725 /* send and recv matrix values */ 4726 /*-----------------------------*/ 4727 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4728 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4729 4730 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4731 for (proc=0,k=0; proc<size; proc++) { 4732 if (!len_s[proc]) continue; 4733 i = owners[proc]; 4734 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4735 k++; 4736 } 4737 4738 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4739 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4740 ierr = PetscFree(status);CHKERRQ(ierr); 4741 4742 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4743 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4744 4745 /* insert mat values of mpimat */ 4746 /*----------------------------*/ 4747 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4748 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4749 4750 for (k=0; k<merge->nrecv; k++) { 4751 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4752 nrows = *(buf_ri_k[k]); 4753 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4754 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4755 } 4756 4757 /* set values of ba */ 4758 m = merge->rowmap->n; 4759 for (i=0; i<m; i++) { 4760 arow = owners[rank] + i; 4761 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4762 bnzi = bi[i+1] - bi[i]; 4763 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4764 4765 /* add local non-zero vals of this proc's seqmat into ba */ 4766 anzi = ai[arow+1] - ai[arow]; 4767 aj = a->j + ai[arow]; 4768 aa = a->a + ai[arow]; 4769 nextaj = 0; 4770 for (j=0; nextaj<anzi; j++) { 4771 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4772 ba_i[j] += aa[nextaj++]; 4773 } 4774 } 4775 4776 /* add received vals into ba */ 4777 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4778 /* i-th row */ 4779 if (i == *nextrow[k]) { 4780 anzi = *(nextai[k]+1) - *nextai[k]; 4781 aj = buf_rj[k] + *(nextai[k]); 4782 aa = abuf_r[k] + *(nextai[k]); 4783 nextaj = 0; 4784 for (j=0; nextaj<anzi; j++) { 4785 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4786 ba_i[j] += aa[nextaj++]; 4787 } 4788 } 4789 nextrow[k]++; nextai[k]++; 4790 } 4791 } 4792 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4793 } 4794 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4795 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4796 4797 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4798 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4799 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4800 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4801 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4802 PetscFunctionReturn(0); 4803 } 4804 4805 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4806 4807 #undef __FUNCT__ 4808 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4809 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4810 { 4811 PetscErrorCode ierr; 4812 Mat B_mpi; 4813 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4814 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4815 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4816 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4817 PetscInt len,proc,*dnz,*onz,bs,cbs; 4818 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4819 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4820 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4821 MPI_Status *status; 4822 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4823 PetscBT lnkbt; 4824 Mat_Merge_SeqsToMPI *merge; 4825 PetscContainer container; 4826 4827 PetscFunctionBegin; 4828 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4829 4830 /* make sure it is a PETSc comm */ 4831 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4832 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4833 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4834 4835 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4836 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4837 4838 /* determine row ownership */ 4839 /*---------------------------------------------------------*/ 4840 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4841 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4842 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4843 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4844 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4845 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4846 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4847 4848 m = merge->rowmap->n; 4849 owners = merge->rowmap->range; 4850 4851 /* determine the number of messages to send, their lengths */ 4852 /*---------------------------------------------------------*/ 4853 len_s = merge->len_s; 4854 4855 len = 0; /* length of buf_si[] */ 4856 merge->nsend = 0; 4857 for (proc=0; proc<size; proc++) { 4858 len_si[proc] = 0; 4859 if (proc == rank) { 4860 len_s[proc] = 0; 4861 } else { 4862 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4863 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4864 } 4865 if (len_s[proc]) { 4866 merge->nsend++; 4867 nrows = 0; 4868 for (i=owners[proc]; i<owners[proc+1]; i++) { 4869 if (ai[i+1] > ai[i]) nrows++; 4870 } 4871 len_si[proc] = 2*(nrows+1); 4872 len += len_si[proc]; 4873 } 4874 } 4875 4876 /* determine the number and length of messages to receive for ij-structure */ 4877 /*-------------------------------------------------------------------------*/ 4878 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4879 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4880 4881 /* post the Irecv of j-structure */ 4882 /*-------------------------------*/ 4883 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4884 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4885 4886 /* post the Isend of j-structure */ 4887 /*--------------------------------*/ 4888 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4889 4890 for (proc=0, k=0; proc<size; proc++) { 4891 if (!len_s[proc]) continue; 4892 i = owners[proc]; 4893 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4894 k++; 4895 } 4896 4897 /* receives and sends of j-structure are complete */ 4898 /*------------------------------------------------*/ 4899 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4900 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4901 4902 /* send and recv i-structure */ 4903 /*---------------------------*/ 4904 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4905 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4906 4907 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4908 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4909 for (proc=0,k=0; proc<size; proc++) { 4910 if (!len_s[proc]) continue; 4911 /* form outgoing message for i-structure: 4912 buf_si[0]: nrows to be sent 4913 [1:nrows]: row index (global) 4914 [nrows+1:2*nrows+1]: i-structure index 4915 */ 4916 /*-------------------------------------------*/ 4917 nrows = len_si[proc]/2 - 1; 4918 buf_si_i = buf_si + nrows+1; 4919 buf_si[0] = nrows; 4920 buf_si_i[0] = 0; 4921 nrows = 0; 4922 for (i=owners[proc]; i<owners[proc+1]; i++) { 4923 anzi = ai[i+1] - ai[i]; 4924 if (anzi) { 4925 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4926 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4927 nrows++; 4928 } 4929 } 4930 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4931 k++; 4932 buf_si += len_si[proc]; 4933 } 4934 4935 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4936 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4937 4938 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4939 for (i=0; i<merge->nrecv; i++) { 4940 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); 4941 } 4942 4943 ierr = PetscFree(len_si);CHKERRQ(ierr); 4944 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4945 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4946 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4947 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4948 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4949 ierr = PetscFree(status);CHKERRQ(ierr); 4950 4951 /* compute a local seq matrix in each processor */ 4952 /*----------------------------------------------*/ 4953 /* allocate bi array and free space for accumulating nonzero column info */ 4954 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4955 bi[0] = 0; 4956 4957 /* create and initialize a linked list */ 4958 nlnk = N+1; 4959 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4960 4961 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4962 len = ai[owners[rank+1]] - ai[owners[rank]]; 4963 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4964 4965 current_space = free_space; 4966 4967 /* determine symbolic info for each local row */ 4968 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4969 4970 for (k=0; k<merge->nrecv; k++) { 4971 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4972 nrows = *buf_ri_k[k]; 4973 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4974 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4975 } 4976 4977 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4978 len = 0; 4979 for (i=0; i<m; i++) { 4980 bnzi = 0; 4981 /* add local non-zero cols of this proc's seqmat into lnk */ 4982 arow = owners[rank] + i; 4983 anzi = ai[arow+1] - ai[arow]; 4984 aj = a->j + ai[arow]; 4985 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4986 bnzi += nlnk; 4987 /* add received col data into lnk */ 4988 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4989 if (i == *nextrow[k]) { /* i-th row */ 4990 anzi = *(nextai[k]+1) - *nextai[k]; 4991 aj = buf_rj[k] + *nextai[k]; 4992 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4993 bnzi += nlnk; 4994 nextrow[k]++; nextai[k]++; 4995 } 4996 } 4997 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4998 4999 /* if free space is not available, make more free space */ 5000 if (current_space->local_remaining<bnzi) { 5001 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 5002 nspacedouble++; 5003 } 5004 /* copy data into free space, then initialize lnk */ 5005 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 5006 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 5007 5008 current_space->array += bnzi; 5009 current_space->local_used += bnzi; 5010 current_space->local_remaining -= bnzi; 5011 5012 bi[i+1] = bi[i] + bnzi; 5013 } 5014 5015 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5016 5017 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5018 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5019 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5020 5021 /* create symbolic parallel matrix B_mpi */ 5022 /*---------------------------------------*/ 5023 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5024 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5025 if (n==PETSC_DECIDE) { 5026 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5027 } else { 5028 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5029 } 5030 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5031 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5032 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5033 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5034 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5035 5036 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5037 B_mpi->assembled = PETSC_FALSE; 5038 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5039 merge->bi = bi; 5040 merge->bj = bj; 5041 merge->buf_ri = buf_ri; 5042 merge->buf_rj = buf_rj; 5043 merge->coi = NULL; 5044 merge->coj = NULL; 5045 merge->owners_co = NULL; 5046 5047 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5048 5049 /* attach the supporting struct to B_mpi for reuse */ 5050 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5051 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5052 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5053 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5054 *mpimat = B_mpi; 5055 5056 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5057 PetscFunctionReturn(0); 5058 } 5059 5060 #undef __FUNCT__ 5061 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5062 /*@C 5063 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5064 matrices from each processor 5065 5066 Collective on MPI_Comm 5067 5068 Input Parameters: 5069 + comm - the communicators the parallel matrix will live on 5070 . seqmat - the input sequential matrices 5071 . m - number of local rows (or PETSC_DECIDE) 5072 . n - number of local columns (or PETSC_DECIDE) 5073 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5074 5075 Output Parameter: 5076 . mpimat - the parallel matrix generated 5077 5078 Level: advanced 5079 5080 Notes: 5081 The dimensions of the sequential matrix in each processor MUST be the same. 5082 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5083 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5084 @*/ 5085 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5086 { 5087 PetscErrorCode ierr; 5088 PetscMPIInt size; 5089 5090 PetscFunctionBegin; 5091 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5092 if (size == 1) { 5093 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5094 if (scall == MAT_INITIAL_MATRIX) { 5095 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5096 } else { 5097 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5098 } 5099 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5100 PetscFunctionReturn(0); 5101 } 5102 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5103 if (scall == MAT_INITIAL_MATRIX) { 5104 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5105 } 5106 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5107 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5108 PetscFunctionReturn(0); 5109 } 5110 5111 #undef __FUNCT__ 5112 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5113 /*@ 5114 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5115 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5116 with MatGetSize() 5117 5118 Not Collective 5119 5120 Input Parameters: 5121 + A - the matrix 5122 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5123 5124 Output Parameter: 5125 . A_loc - the local sequential matrix generated 5126 5127 Level: developer 5128 5129 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5130 5131 @*/ 5132 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5133 { 5134 PetscErrorCode ierr; 5135 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5136 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5137 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5138 MatScalar *aa=a->a,*ba=b->a,*cam; 5139 PetscScalar *ca; 5140 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5141 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5142 PetscBool match; 5143 5144 PetscFunctionBegin; 5145 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5146 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5147 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5148 if (scall == MAT_INITIAL_MATRIX) { 5149 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5150 ci[0] = 0; 5151 for (i=0; i<am; i++) { 5152 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5153 } 5154 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5155 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5156 k = 0; 5157 for (i=0; i<am; i++) { 5158 ncols_o = bi[i+1] - bi[i]; 5159 ncols_d = ai[i+1] - ai[i]; 5160 /* off-diagonal portion of A */ 5161 for (jo=0; jo<ncols_o; jo++) { 5162 col = cmap[*bj]; 5163 if (col >= cstart) break; 5164 cj[k] = col; bj++; 5165 ca[k++] = *ba++; 5166 } 5167 /* diagonal portion of A */ 5168 for (j=0; j<ncols_d; j++) { 5169 cj[k] = cstart + *aj++; 5170 ca[k++] = *aa++; 5171 } 5172 /* off-diagonal portion of A */ 5173 for (j=jo; j<ncols_o; j++) { 5174 cj[k] = cmap[*bj++]; 5175 ca[k++] = *ba++; 5176 } 5177 } 5178 /* put together the new matrix */ 5179 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5180 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5181 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5182 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5183 mat->free_a = PETSC_TRUE; 5184 mat->free_ij = PETSC_TRUE; 5185 mat->nonew = 0; 5186 } else if (scall == MAT_REUSE_MATRIX) { 5187 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5188 ci = mat->i; cj = mat->j; cam = mat->a; 5189 for (i=0; i<am; i++) { 5190 /* off-diagonal portion of A */ 5191 ncols_o = bi[i+1] - bi[i]; 5192 for (jo=0; jo<ncols_o; jo++) { 5193 col = cmap[*bj]; 5194 if (col >= cstart) break; 5195 *cam++ = *ba++; bj++; 5196 } 5197 /* diagonal portion of A */ 5198 ncols_d = ai[i+1] - ai[i]; 5199 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5200 /* off-diagonal portion of A */ 5201 for (j=jo; j<ncols_o; j++) { 5202 *cam++ = *ba++; bj++; 5203 } 5204 } 5205 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5206 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5207 PetscFunctionReturn(0); 5208 } 5209 5210 #undef __FUNCT__ 5211 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5212 /*@C 5213 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5214 5215 Not Collective 5216 5217 Input Parameters: 5218 + A - the matrix 5219 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5220 - row, col - index sets of rows and columns to extract (or NULL) 5221 5222 Output Parameter: 5223 . A_loc - the local sequential matrix generated 5224 5225 Level: developer 5226 5227 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5228 5229 @*/ 5230 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5231 { 5232 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5233 PetscErrorCode ierr; 5234 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5235 IS isrowa,iscola; 5236 Mat *aloc; 5237 PetscBool match; 5238 5239 PetscFunctionBegin; 5240 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5241 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5242 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5243 if (!row) { 5244 start = A->rmap->rstart; end = A->rmap->rend; 5245 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5246 } else { 5247 isrowa = *row; 5248 } 5249 if (!col) { 5250 start = A->cmap->rstart; 5251 cmap = a->garray; 5252 nzA = a->A->cmap->n; 5253 nzB = a->B->cmap->n; 5254 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5255 ncols = 0; 5256 for (i=0; i<nzB; i++) { 5257 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5258 else break; 5259 } 5260 imark = i; 5261 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5262 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5263 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5264 } else { 5265 iscola = *col; 5266 } 5267 if (scall != MAT_INITIAL_MATRIX) { 5268 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5269 aloc[0] = *A_loc; 5270 } 5271 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5272 *A_loc = aloc[0]; 5273 ierr = PetscFree(aloc);CHKERRQ(ierr); 5274 if (!row) { 5275 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5276 } 5277 if (!col) { 5278 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5279 } 5280 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5281 PetscFunctionReturn(0); 5282 } 5283 5284 #undef __FUNCT__ 5285 #define __FUNCT__ "MatGetBrowsOfAcols" 5286 /*@C 5287 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5288 5289 Collective on Mat 5290 5291 Input Parameters: 5292 + A,B - the matrices in mpiaij format 5293 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5294 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5295 5296 Output Parameter: 5297 + rowb, colb - index sets of rows and columns of B to extract 5298 - B_seq - the sequential matrix generated 5299 5300 Level: developer 5301 5302 @*/ 5303 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5304 { 5305 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5306 PetscErrorCode ierr; 5307 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5308 IS isrowb,iscolb; 5309 Mat *bseq=NULL; 5310 5311 PetscFunctionBegin; 5312 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5313 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); 5314 } 5315 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5316 5317 if (scall == MAT_INITIAL_MATRIX) { 5318 start = A->cmap->rstart; 5319 cmap = a->garray; 5320 nzA = a->A->cmap->n; 5321 nzB = a->B->cmap->n; 5322 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5323 ncols = 0; 5324 for (i=0; i<nzB; i++) { /* row < local row index */ 5325 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5326 else break; 5327 } 5328 imark = i; 5329 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5330 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5331 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5332 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5333 } else { 5334 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5335 isrowb = *rowb; iscolb = *colb; 5336 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5337 bseq[0] = *B_seq; 5338 } 5339 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5340 *B_seq = bseq[0]; 5341 ierr = PetscFree(bseq);CHKERRQ(ierr); 5342 if (!rowb) { 5343 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5344 } else { 5345 *rowb = isrowb; 5346 } 5347 if (!colb) { 5348 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5349 } else { 5350 *colb = iscolb; 5351 } 5352 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5353 PetscFunctionReturn(0); 5354 } 5355 5356 #undef __FUNCT__ 5357 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5358 /* 5359 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5360 of the OFF-DIAGONAL portion of local A 5361 5362 Collective on Mat 5363 5364 Input Parameters: 5365 + A,B - the matrices in mpiaij format 5366 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5367 5368 Output Parameter: 5369 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5370 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5371 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5372 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5373 5374 Level: developer 5375 5376 */ 5377 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5378 { 5379 VecScatter_MPI_General *gen_to,*gen_from; 5380 PetscErrorCode ierr; 5381 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5382 Mat_SeqAIJ *b_oth; 5383 VecScatter ctx =a->Mvctx; 5384 MPI_Comm comm; 5385 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5386 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5387 PetscScalar *rvalues,*svalues; 5388 MatScalar *b_otha,*bufa,*bufA; 5389 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5390 MPI_Request *rwaits = NULL,*swaits = NULL; 5391 MPI_Status *sstatus,rstatus; 5392 PetscMPIInt jj; 5393 PetscInt *cols,sbs,rbs; 5394 PetscScalar *vals; 5395 5396 PetscFunctionBegin; 5397 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5398 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5399 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); 5400 } 5401 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5402 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5403 5404 gen_to = (VecScatter_MPI_General*)ctx->todata; 5405 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5406 rvalues = gen_from->values; /* holds the length of receiving row */ 5407 svalues = gen_to->values; /* holds the length of sending row */ 5408 nrecvs = gen_from->n; 5409 nsends = gen_to->n; 5410 5411 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5412 srow = gen_to->indices; /* local row index to be sent */ 5413 sstarts = gen_to->starts; 5414 sprocs = gen_to->procs; 5415 sstatus = gen_to->sstatus; 5416 sbs = gen_to->bs; 5417 rstarts = gen_from->starts; 5418 rprocs = gen_from->procs; 5419 rbs = gen_from->bs; 5420 5421 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5422 if (scall == MAT_INITIAL_MATRIX) { 5423 /* i-array */ 5424 /*---------*/ 5425 /* post receives */ 5426 for (i=0; i<nrecvs; i++) { 5427 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5428 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5429 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5430 } 5431 5432 /* pack the outgoing message */ 5433 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5434 5435 sstartsj[0] = 0; 5436 rstartsj[0] = 0; 5437 len = 0; /* total length of j or a array to be sent */ 5438 k = 0; 5439 for (i=0; i<nsends; i++) { 5440 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5441 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5442 for (j=0; j<nrows; j++) { 5443 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5444 for (l=0; l<sbs; l++) { 5445 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5446 5447 rowlen[j*sbs+l] = ncols; 5448 5449 len += ncols; 5450 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5451 } 5452 k++; 5453 } 5454 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5455 5456 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5457 } 5458 /* recvs and sends of i-array are completed */ 5459 i = nrecvs; 5460 while (i--) { 5461 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5462 } 5463 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5464 5465 /* allocate buffers for sending j and a arrays */ 5466 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5467 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5468 5469 /* create i-array of B_oth */ 5470 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5471 5472 b_othi[0] = 0; 5473 len = 0; /* total length of j or a array to be received */ 5474 k = 0; 5475 for (i=0; i<nrecvs; i++) { 5476 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5477 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5478 for (j=0; j<nrows; j++) { 5479 b_othi[k+1] = b_othi[k] + rowlen[j]; 5480 len += rowlen[j]; k++; 5481 } 5482 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5483 } 5484 5485 /* allocate space for j and a arrrays of B_oth */ 5486 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5487 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5488 5489 /* j-array */ 5490 /*---------*/ 5491 /* post receives of j-array */ 5492 for (i=0; i<nrecvs; i++) { 5493 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5494 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5495 } 5496 5497 /* pack the outgoing message j-array */ 5498 k = 0; 5499 for (i=0; i<nsends; i++) { 5500 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5501 bufJ = bufj+sstartsj[i]; 5502 for (j=0; j<nrows; j++) { 5503 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5504 for (ll=0; ll<sbs; ll++) { 5505 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5506 for (l=0; l<ncols; l++) { 5507 *bufJ++ = cols[l]; 5508 } 5509 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5510 } 5511 } 5512 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5513 } 5514 5515 /* recvs and sends of j-array are completed */ 5516 i = nrecvs; 5517 while (i--) { 5518 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5519 } 5520 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5521 } else if (scall == MAT_REUSE_MATRIX) { 5522 sstartsj = *startsj_s; 5523 rstartsj = *startsj_r; 5524 bufa = *bufa_ptr; 5525 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5526 b_otha = b_oth->a; 5527 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5528 5529 /* a-array */ 5530 /*---------*/ 5531 /* post receives of a-array */ 5532 for (i=0; i<nrecvs; i++) { 5533 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5534 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5535 } 5536 5537 /* pack the outgoing message a-array */ 5538 k = 0; 5539 for (i=0; i<nsends; i++) { 5540 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5541 bufA = bufa+sstartsj[i]; 5542 for (j=0; j<nrows; j++) { 5543 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5544 for (ll=0; ll<sbs; ll++) { 5545 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5546 for (l=0; l<ncols; l++) { 5547 *bufA++ = vals[l]; 5548 } 5549 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5550 } 5551 } 5552 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5553 } 5554 /* recvs and sends of a-array are completed */ 5555 i = nrecvs; 5556 while (i--) { 5557 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5558 } 5559 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5560 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5561 5562 if (scall == MAT_INITIAL_MATRIX) { 5563 /* put together the new matrix */ 5564 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5565 5566 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5567 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5568 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5569 b_oth->free_a = PETSC_TRUE; 5570 b_oth->free_ij = PETSC_TRUE; 5571 b_oth->nonew = 0; 5572 5573 ierr = PetscFree(bufj);CHKERRQ(ierr); 5574 if (!startsj_s || !bufa_ptr) { 5575 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5576 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5577 } else { 5578 *startsj_s = sstartsj; 5579 *startsj_r = rstartsj; 5580 *bufa_ptr = bufa; 5581 } 5582 } 5583 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5584 PetscFunctionReturn(0); 5585 } 5586 5587 #undef __FUNCT__ 5588 #define __FUNCT__ "MatGetCommunicationStructs" 5589 /*@C 5590 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5591 5592 Not Collective 5593 5594 Input Parameters: 5595 . A - The matrix in mpiaij format 5596 5597 Output Parameter: 5598 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5599 . colmap - A map from global column index to local index into lvec 5600 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5601 5602 Level: developer 5603 5604 @*/ 5605 #if defined(PETSC_USE_CTABLE) 5606 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5607 #else 5608 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5609 #endif 5610 { 5611 Mat_MPIAIJ *a; 5612 5613 PetscFunctionBegin; 5614 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5615 PetscValidPointer(lvec, 2); 5616 PetscValidPointer(colmap, 3); 5617 PetscValidPointer(multScatter, 4); 5618 a = (Mat_MPIAIJ*) A->data; 5619 if (lvec) *lvec = a->lvec; 5620 if (colmap) *colmap = a->colmap; 5621 if (multScatter) *multScatter = a->Mvctx; 5622 PetscFunctionReturn(0); 5623 } 5624 5625 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5626 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5627 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5628 5629 #undef __FUNCT__ 5630 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5631 /* 5632 Computes (B'*A')' since computing B*A directly is untenable 5633 5634 n p p 5635 ( ) ( ) ( ) 5636 m ( A ) * n ( B ) = m ( C ) 5637 ( ) ( ) ( ) 5638 5639 */ 5640 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5641 { 5642 PetscErrorCode ierr; 5643 Mat At,Bt,Ct; 5644 5645 PetscFunctionBegin; 5646 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5647 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5648 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5649 ierr = MatDestroy(&At);CHKERRQ(ierr); 5650 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5651 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5652 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5653 PetscFunctionReturn(0); 5654 } 5655 5656 #undef __FUNCT__ 5657 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5658 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5659 { 5660 PetscErrorCode ierr; 5661 PetscInt m=A->rmap->n,n=B->cmap->n; 5662 Mat Cmat; 5663 5664 PetscFunctionBegin; 5665 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); 5666 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5667 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5668 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5669 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5670 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5671 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5672 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5673 5674 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5675 5676 *C = Cmat; 5677 PetscFunctionReturn(0); 5678 } 5679 5680 /* ----------------------------------------------------------------*/ 5681 #undef __FUNCT__ 5682 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5683 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5684 { 5685 PetscErrorCode ierr; 5686 5687 PetscFunctionBegin; 5688 if (scall == MAT_INITIAL_MATRIX) { 5689 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5690 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5691 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5692 } 5693 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5694 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5695 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5696 PetscFunctionReturn(0); 5697 } 5698 5699 #if defined(PETSC_HAVE_MUMPS) 5700 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5701 #endif 5702 #if defined(PETSC_HAVE_PASTIX) 5703 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5704 #endif 5705 #if defined(PETSC_HAVE_SUPERLU_DIST) 5706 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5707 #endif 5708 #if defined(PETSC_HAVE_CLIQUE) 5709 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5710 #endif 5711 5712 /*MC 5713 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5714 5715 Options Database Keys: 5716 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5717 5718 Level: beginner 5719 5720 .seealso: MatCreateAIJ() 5721 M*/ 5722 5723 #undef __FUNCT__ 5724 #define __FUNCT__ "MatCreate_MPIAIJ" 5725 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5726 { 5727 Mat_MPIAIJ *b; 5728 PetscErrorCode ierr; 5729 PetscMPIInt size; 5730 5731 PetscFunctionBegin; 5732 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5733 5734 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5735 B->data = (void*)b; 5736 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5737 B->assembled = PETSC_FALSE; 5738 B->insertmode = NOT_SET_VALUES; 5739 b->size = size; 5740 5741 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5742 5743 /* build cache for off array entries formed */ 5744 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5745 5746 b->donotstash = PETSC_FALSE; 5747 b->colmap = 0; 5748 b->garray = 0; 5749 b->roworiented = PETSC_TRUE; 5750 5751 /* stuff used for matrix vector multiply */ 5752 b->lvec = NULL; 5753 b->Mvctx = NULL; 5754 5755 /* stuff for MatGetRow() */ 5756 b->rowindices = 0; 5757 b->rowvalues = 0; 5758 b->getrowactive = PETSC_FALSE; 5759 5760 /* flexible pointer used in CUSP/CUSPARSE classes */ 5761 b->spptr = NULL; 5762 5763 #if defined(PETSC_HAVE_MUMPS) 5764 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5765 #endif 5766 #if defined(PETSC_HAVE_PASTIX) 5767 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5768 #endif 5769 #if defined(PETSC_HAVE_SUPERLU_DIST) 5770 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5771 #endif 5772 #if defined(PETSC_HAVE_CLIQUE) 5773 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5774 #endif 5775 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5776 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5777 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5778 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5779 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5780 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5781 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5782 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5783 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5784 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5785 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5786 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5787 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5788 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5789 PetscFunctionReturn(0); 5790 } 5791 5792 #undef __FUNCT__ 5793 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5794 /*@ 5795 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5796 and "off-diagonal" part of the matrix in CSR format. 5797 5798 Collective on MPI_Comm 5799 5800 Input Parameters: 5801 + comm - MPI communicator 5802 . m - number of local rows (Cannot be PETSC_DECIDE) 5803 . n - This value should be the same as the local size used in creating the 5804 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5805 calculated if N is given) For square matrices n is almost always m. 5806 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5807 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5808 . i - row indices for "diagonal" portion of matrix 5809 . j - column indices 5810 . a - matrix values 5811 . oi - row indices for "off-diagonal" portion of matrix 5812 . oj - column indices 5813 - oa - matrix values 5814 5815 Output Parameter: 5816 . mat - the matrix 5817 5818 Level: advanced 5819 5820 Notes: 5821 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5822 must free the arrays once the matrix has been destroyed and not before. 5823 5824 The i and j indices are 0 based 5825 5826 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5827 5828 This sets local rows and cannot be used to set off-processor values. 5829 5830 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5831 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5832 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5833 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5834 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5835 communication if it is known that only local entries will be set. 5836 5837 .keywords: matrix, aij, compressed row, sparse, parallel 5838 5839 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5840 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5841 @*/ 5842 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) 5843 { 5844 PetscErrorCode ierr; 5845 Mat_MPIAIJ *maij; 5846 5847 PetscFunctionBegin; 5848 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5849 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5850 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5851 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5852 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5853 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5854 maij = (Mat_MPIAIJ*) (*mat)->data; 5855 5856 (*mat)->preallocated = PETSC_TRUE; 5857 5858 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5859 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5860 5861 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5862 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5863 5864 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5865 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5866 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5867 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5868 5869 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5870 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5871 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5872 PetscFunctionReturn(0); 5873 } 5874 5875 /* 5876 Special version for direct calls from Fortran 5877 */ 5878 #include <petsc-private/fortranimpl.h> 5879 5880 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5881 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5882 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5883 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5884 #endif 5885 5886 /* Change these macros so can be used in void function */ 5887 #undef CHKERRQ 5888 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5889 #undef SETERRQ2 5890 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5891 #undef SETERRQ3 5892 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5893 #undef SETERRQ 5894 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5895 5896 #undef __FUNCT__ 5897 #define __FUNCT__ "matsetvaluesmpiaij_" 5898 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) 5899 { 5900 Mat mat = *mmat; 5901 PetscInt m = *mm, n = *mn; 5902 InsertMode addv = *maddv; 5903 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5904 PetscScalar value; 5905 PetscErrorCode ierr; 5906 5907 MatCheckPreallocated(mat,1); 5908 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5909 5910 #if defined(PETSC_USE_DEBUG) 5911 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5912 #endif 5913 { 5914 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5915 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5916 PetscBool roworiented = aij->roworiented; 5917 5918 /* Some Variables required in the macro */ 5919 Mat A = aij->A; 5920 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5921 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5922 MatScalar *aa = a->a; 5923 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5924 Mat B = aij->B; 5925 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5926 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5927 MatScalar *ba = b->a; 5928 5929 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5930 PetscInt nonew = a->nonew; 5931 MatScalar *ap1,*ap2; 5932 5933 PetscFunctionBegin; 5934 for (i=0; i<m; i++) { 5935 if (im[i] < 0) continue; 5936 #if defined(PETSC_USE_DEBUG) 5937 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); 5938 #endif 5939 if (im[i] >= rstart && im[i] < rend) { 5940 row = im[i] - rstart; 5941 lastcol1 = -1; 5942 rp1 = aj + ai[row]; 5943 ap1 = aa + ai[row]; 5944 rmax1 = aimax[row]; 5945 nrow1 = ailen[row]; 5946 low1 = 0; 5947 high1 = nrow1; 5948 lastcol2 = -1; 5949 rp2 = bj + bi[row]; 5950 ap2 = ba + bi[row]; 5951 rmax2 = bimax[row]; 5952 nrow2 = bilen[row]; 5953 low2 = 0; 5954 high2 = nrow2; 5955 5956 for (j=0; j<n; j++) { 5957 if (roworiented) value = v[i*n+j]; 5958 else value = v[i+j*m]; 5959 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5960 if (in[j] >= cstart && in[j] < cend) { 5961 col = in[j] - cstart; 5962 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5963 } else if (in[j] < 0) continue; 5964 #if defined(PETSC_USE_DEBUG) 5965 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); 5966 #endif 5967 else { 5968 if (mat->was_assembled) { 5969 if (!aij->colmap) { 5970 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5971 } 5972 #if defined(PETSC_USE_CTABLE) 5973 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5974 col--; 5975 #else 5976 col = aij->colmap[in[j]] - 1; 5977 #endif 5978 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5979 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5980 col = in[j]; 5981 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5982 B = aij->B; 5983 b = (Mat_SeqAIJ*)B->data; 5984 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5985 rp2 = bj + bi[row]; 5986 ap2 = ba + bi[row]; 5987 rmax2 = bimax[row]; 5988 nrow2 = bilen[row]; 5989 low2 = 0; 5990 high2 = nrow2; 5991 bm = aij->B->rmap->n; 5992 ba = b->a; 5993 } 5994 } else col = in[j]; 5995 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5996 } 5997 } 5998 } else if (!aij->donotstash) { 5999 if (roworiented) { 6000 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6001 } else { 6002 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6003 } 6004 } 6005 } 6006 } 6007 PetscFunctionReturnVoid(); 6008 } 6009 6010