1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 for (i=1; i<mat->rmap->n; i++) { 335 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 if (redund->matseq) { /* via MatGetSubMatrices() */ 2530 ierr = ISDestroy(&redund->isrow);CHKERRQ(ierr); 2531 ierr = ISDestroy(&redund->iscol);CHKERRQ(ierr); 2532 ierr = MatDestroy(&redund->matseq[0]);CHKERRQ(ierr); 2533 ierr = PetscFree(redund->matseq);CHKERRQ(ierr); 2534 } else { 2535 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2536 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2537 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2538 for (i=0; i<redund->nrecvs; i++) { 2539 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2540 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2541 } 2542 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2543 } 2544 2545 if (redund->psubcomm) { 2546 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2547 } 2548 ierr = redund->Destroy(A);CHKERRQ(ierr); 2549 ierr = PetscFree(redund);CHKERRQ(ierr); 2550 } 2551 PetscFunctionReturn(0); 2552 } 2553 2554 #undef __FUNCT__ 2555 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_interlaced" 2556 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_interlaced(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm; 2560 PetscErrorCode ierr; 2561 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2562 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2563 PetscInt *rowrange = mat->rmap->range; 2564 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2565 Mat A = aij->A,B=aij->B,C=*matredundant; 2566 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2567 PetscScalar *sbuf_a; 2568 PetscInt nzlocal=a->nz+b->nz; 2569 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2570 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2571 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2572 MatScalar *aworkA,*aworkB; 2573 PetscScalar *vals; 2574 PetscMPIInt tag1,tag2,tag3,imdex; 2575 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2576 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2577 MPI_Status recv_status,*send_status; 2578 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2579 PetscInt **rbuf_j=NULL; 2580 PetscScalar **rbuf_a=NULL; 2581 Mat_Redundant *redund =NULL; 2582 2583 PetscFunctionBegin; 2584 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2587 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2588 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2589 2590 if (reuse == MAT_REUSE_MATRIX) { 2591 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2592 if (subsize == 1) { 2593 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2594 redund = c->redundant; 2595 } else { 2596 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2597 redund = c->redundant; 2598 } 2599 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2600 2601 nsends = redund->nsends; 2602 nrecvs = redund->nrecvs; 2603 send_rank = redund->send_rank; 2604 recv_rank = redund->recv_rank; 2605 sbuf_nz = redund->sbuf_nz; 2606 rbuf_nz = redund->rbuf_nz; 2607 sbuf_j = redund->sbuf_j; 2608 sbuf_a = redund->sbuf_a; 2609 rbuf_j = redund->rbuf_j; 2610 rbuf_a = redund->rbuf_a; 2611 } 2612 2613 if (reuse == MAT_INITIAL_MATRIX) { 2614 PetscInt nleftover,np_subcomm; 2615 2616 /* get the destination processors' id send_rank, nsends and nrecvs */ 2617 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2618 2619 np_subcomm = size/nsubcomm; 2620 nleftover = size - nsubcomm*np_subcomm; 2621 2622 /* block of codes below is specific for INTERLACED */ 2623 /* ------------------------------------------------*/ 2624 nsends = 0; nrecvs = 0; 2625 for (i=0; i<size; i++) { 2626 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2627 send_rank[nsends++] = i; 2628 recv_rank[nrecvs++] = i; 2629 } 2630 } 2631 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2632 i = size-nleftover-1; 2633 j = 0; 2634 while (j < nsubcomm - nleftover) { 2635 send_rank[nsends++] = i; 2636 i--; j++; 2637 } 2638 } 2639 2640 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2641 for (i=0; i<nleftover; i++) { 2642 recv_rank[nrecvs++] = size-nleftover+i; 2643 } 2644 } 2645 /*----------------------------------------------*/ 2646 2647 /* allocate sbuf_j, sbuf_a */ 2648 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2649 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2650 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2651 /* 2652 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2653 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2654 */ 2655 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2656 2657 /* copy mat's local entries into the buffers */ 2658 if (reuse == MAT_INITIAL_MATRIX) { 2659 rownz_max = 0; 2660 rptr = sbuf_j; 2661 cols = sbuf_j + rend-rstart + 1; 2662 vals = sbuf_a; 2663 rptr[0] = 0; 2664 for (i=0; i<rend-rstart; i++) { 2665 row = i + rstart; 2666 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2667 ncols = nzA + nzB; 2668 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2669 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2670 /* load the column indices for this row into cols */ 2671 lwrite = 0; 2672 for (l=0; l<nzB; l++) { 2673 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2674 vals[lwrite] = aworkB[l]; 2675 cols[lwrite++] = ctmp; 2676 } 2677 } 2678 for (l=0; l<nzA; l++) { 2679 vals[lwrite] = aworkA[l]; 2680 cols[lwrite++] = cstart + cworkA[l]; 2681 } 2682 for (l=0; l<nzB; l++) { 2683 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2684 vals[lwrite] = aworkB[l]; 2685 cols[lwrite++] = ctmp; 2686 } 2687 } 2688 vals += ncols; 2689 cols += ncols; 2690 rptr[i+1] = rptr[i] + ncols; 2691 if (rownz_max < ncols) rownz_max = ncols; 2692 } 2693 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2694 } else { /* only copy matrix values into sbuf_a */ 2695 rptr = sbuf_j; 2696 vals = sbuf_a; 2697 rptr[0] = 0; 2698 for (i=0; i<rend-rstart; i++) { 2699 row = i + rstart; 2700 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2701 ncols = nzA + nzB; 2702 cworkB = b->j + b->i[i]; 2703 aworkA = a->a + a->i[i]; 2704 aworkB = b->a + b->i[i]; 2705 lwrite = 0; 2706 for (l=0; l<nzB; l++) { 2707 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2708 } 2709 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2710 for (l=0; l<nzB; l++) { 2711 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2712 } 2713 vals += ncols; 2714 rptr[i+1] = rptr[i] + ncols; 2715 } 2716 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2717 2718 /* send nzlocal to others, and recv other's nzlocal */ 2719 /*--------------------------------------------------*/ 2720 if (reuse == MAT_INITIAL_MATRIX) { 2721 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2722 2723 s_waits2 = s_waits3 + nsends; 2724 s_waits1 = s_waits2 + nsends; 2725 r_waits1 = s_waits1 + nsends; 2726 r_waits2 = r_waits1 + nrecvs; 2727 r_waits3 = r_waits2 + nrecvs; 2728 } else { 2729 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2730 2731 r_waits3 = s_waits3 + nsends; 2732 } 2733 2734 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2735 if (reuse == MAT_INITIAL_MATRIX) { 2736 /* get new tags to keep the communication clean */ 2737 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2738 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2739 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2740 2741 /* post receives of other's nzlocal */ 2742 for (i=0; i<nrecvs; i++) { 2743 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2744 } 2745 /* send nzlocal to others */ 2746 for (i=0; i<nsends; i++) { 2747 sbuf_nz[i] = nzlocal; 2748 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2749 } 2750 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2751 count = nrecvs; 2752 while (count) { 2753 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2754 2755 recv_rank[imdex] = recv_status.MPI_SOURCE; 2756 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2757 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2758 2759 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2760 2761 rbuf_nz[imdex] += i + 2; 2762 2763 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2764 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2765 count--; 2766 } 2767 /* wait on sends of nzlocal */ 2768 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2769 /* send mat->i,j to others, and recv from other's */ 2770 /*------------------------------------------------*/ 2771 for (i=0; i<nsends; i++) { 2772 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2773 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2774 } 2775 /* wait on receives of mat->i,j */ 2776 /*------------------------------*/ 2777 count = nrecvs; 2778 while (count) { 2779 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2780 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2781 count--; 2782 } 2783 /* wait on sends of mat->i,j */ 2784 /*---------------------------*/ 2785 if (nsends) { 2786 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2787 } 2788 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2789 2790 /* post receives, send and receive mat->a */ 2791 /*----------------------------------------*/ 2792 for (imdex=0; imdex<nrecvs; imdex++) { 2793 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2794 } 2795 for (i=0; i<nsends; i++) { 2796 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2797 } 2798 count = nrecvs; 2799 while (count) { 2800 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2801 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2802 count--; 2803 } 2804 if (nsends) { 2805 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2806 } 2807 2808 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2809 2810 /* create redundant matrix */ 2811 /*-------------------------*/ 2812 if (reuse == MAT_INITIAL_MATRIX) { 2813 const PetscInt *range; 2814 PetscInt rstart_sub,rend_sub,mloc_sub; 2815 2816 /* compute rownz_max for preallocation */ 2817 for (imdex=0; imdex<nrecvs; imdex++) { 2818 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2819 rptr = rbuf_j[imdex]; 2820 for (i=0; i<j; i++) { 2821 ncols = rptr[i+1] - rptr[i]; 2822 if (rownz_max < ncols) rownz_max = ncols; 2823 } 2824 } 2825 2826 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2827 2828 /* get local size of redundant matrix 2829 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2830 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2831 rstart_sub = range[nsubcomm*subrank]; 2832 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2833 rend_sub = range[nsubcomm*(subrank+1)]; 2834 } else { 2835 rend_sub = mat->rmap->N; 2836 } 2837 mloc_sub = rend_sub - rstart_sub; 2838 2839 if (M == N) { 2840 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2841 } else { /* non-square matrix */ 2842 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2843 } 2844 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2845 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2846 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2847 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2848 } else { 2849 C = *matredundant; 2850 } 2851 2852 /* insert local matrix entries */ 2853 rptr = sbuf_j; 2854 cols = sbuf_j + rend-rstart + 1; 2855 vals = sbuf_a; 2856 for (i=0; i<rend-rstart; i++) { 2857 row = i + rstart; 2858 ncols = rptr[i+1] - rptr[i]; 2859 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2860 vals += ncols; 2861 cols += ncols; 2862 } 2863 /* insert received matrix entries */ 2864 for (imdex=0; imdex<nrecvs; imdex++) { 2865 rstart = rowrange[recv_rank[imdex]]; 2866 rend = rowrange[recv_rank[imdex]+1]; 2867 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2868 rptr = rbuf_j[imdex]; 2869 cols = rbuf_j[imdex] + rend-rstart + 1; 2870 vals = rbuf_a[imdex]; 2871 for (i=0; i<rend-rstart; i++) { 2872 row = i + rstart; 2873 ncols = rptr[i+1] - rptr[i]; 2874 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2875 vals += ncols; 2876 cols += ncols; 2877 } 2878 } 2879 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2880 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2881 2882 if (reuse == MAT_INITIAL_MATRIX) { 2883 *matredundant = C; 2884 2885 /* create a supporting struct and attach it to C for reuse */ 2886 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2887 if (subsize == 1) { 2888 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2889 c->redundant = redund; 2890 } else { 2891 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2892 c->redundant = redund; 2893 } 2894 2895 redund->nzlocal = nzlocal; 2896 redund->nsends = nsends; 2897 redund->nrecvs = nrecvs; 2898 redund->send_rank = send_rank; 2899 redund->recv_rank = recv_rank; 2900 redund->sbuf_nz = sbuf_nz; 2901 redund->rbuf_nz = rbuf_nz; 2902 redund->sbuf_j = sbuf_j; 2903 redund->sbuf_a = sbuf_a; 2904 redund->rbuf_j = rbuf_j; 2905 redund->rbuf_a = rbuf_a; 2906 redund->psubcomm = NULL; 2907 2908 redund->Destroy = C->ops->destroy; 2909 C->ops->destroy = MatDestroy_MatRedundant; 2910 } 2911 PetscFunctionReturn(0); 2912 } 2913 2914 #undef __FUNCT__ 2915 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2916 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,MatReuse reuse,Mat *matredundant) 2917 { 2918 PetscErrorCode ierr; 2919 MPI_Comm comm; 2920 PetscMPIInt size,subsize; 2921 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2922 Mat_Redundant *redund=NULL; 2923 PetscSubcomm psubcomm=NULL; 2924 MPI_Comm subcomm_in=subcomm; 2925 Mat *matseq; 2926 IS isrow,iscol; 2927 2928 PetscFunctionBegin; 2929 if (subcomm_in == MPI_COMM_NULL) { /* user does not provide subcomm */ 2930 if (reuse == MAT_INITIAL_MATRIX) { 2931 /* create psubcomm, then get subcomm */ 2932 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2933 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2934 if (nsubcomm < 1 || nsubcomm > size) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"nsubcomm must between 1 and %D",size); 2935 2936 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2937 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2938 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2939 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2940 subcomm = psubcomm->comm; 2941 } else { /* retrieve psubcomm and subcomm */ 2942 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2943 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2944 if (subsize == 1) { 2945 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2946 redund = c->redundant; 2947 } else { 2948 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2949 redund = c->redundant; 2950 } 2951 psubcomm = redund->psubcomm; 2952 } 2953 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2954 ierr = MatGetRedundantMatrix_MPIAIJ_interlaced(mat,nsubcomm,subcomm,reuse,matredundant);CHKERRQ(ierr); 2955 if (reuse == MAT_INITIAL_MATRIX) { /* psubcomm is created in this routine, free it in MatDestroy_MatRedundant() */ 2956 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 2957 if (subsize == 1) { 2958 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2959 c->redundant->psubcomm = psubcomm; 2960 } else { 2961 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2962 c->redundant->psubcomm = psubcomm ; 2963 } 2964 } 2965 PetscFunctionReturn(0); 2966 } 2967 } 2968 2969 /* use MPI subcomm via MatGetSubMatrices(); use subcomm_in or psubcomm->comm (psubcomm->type != INTERLACED) */ 2970 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2971 if (reuse == MAT_INITIAL_MATRIX) { 2972 /* create a local sequential matrix matseq[0] */ 2973 mloc_sub = PETSC_DECIDE; 2974 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 2975 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 2976 rstart = rend - mloc_sub; 2977 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 2978 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 2979 } else { /* reuse == MAT_REUSE_MATRIX */ 2980 if (subsize == 1) { 2981 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2982 redund = c->redundant; 2983 } else { 2984 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2985 redund = c->redundant; 2986 } 2987 2988 isrow = redund->isrow; 2989 iscol = redund->iscol; 2990 matseq = redund->matseq; 2991 } 2992 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 2993 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 2994 2995 if (reuse == MAT_INITIAL_MATRIX) { 2996 /* create a supporting struct and attach it to C for reuse */ 2997 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 2998 if (subsize == 1) { 2999 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3000 c->redundant = redund; 3001 } else { 3002 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3003 c->redundant = redund; 3004 } 3005 redund->isrow = isrow; 3006 redund->iscol = iscol; 3007 redund->matseq = matseq; 3008 redund->psubcomm = psubcomm; 3009 redund->Destroy = (*matredundant)->ops->destroy; 3010 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3011 } 3012 PetscFunctionReturn(0); 3013 } 3014 3015 #undef __FUNCT__ 3016 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3017 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3018 { 3019 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3020 PetscErrorCode ierr; 3021 PetscInt i,*idxb = 0; 3022 PetscScalar *va,*vb; 3023 Vec vtmp; 3024 3025 PetscFunctionBegin; 3026 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3027 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3028 if (idx) { 3029 for (i=0; i<A->rmap->n; i++) { 3030 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3031 } 3032 } 3033 3034 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3035 if (idx) { 3036 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3037 } 3038 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3039 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3040 3041 for (i=0; i<A->rmap->n; i++) { 3042 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3043 va[i] = vb[i]; 3044 if (idx) idx[i] = a->garray[idxb[i]]; 3045 } 3046 } 3047 3048 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3049 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3050 ierr = PetscFree(idxb);CHKERRQ(ierr); 3051 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3052 PetscFunctionReturn(0); 3053 } 3054 3055 #undef __FUNCT__ 3056 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3057 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3058 { 3059 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3060 PetscErrorCode ierr; 3061 PetscInt i,*idxb = 0; 3062 PetscScalar *va,*vb; 3063 Vec vtmp; 3064 3065 PetscFunctionBegin; 3066 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3067 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3068 if (idx) { 3069 for (i=0; i<A->cmap->n; i++) { 3070 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3071 } 3072 } 3073 3074 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3075 if (idx) { 3076 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3077 } 3078 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3079 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3080 3081 for (i=0; i<A->rmap->n; i++) { 3082 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3083 va[i] = vb[i]; 3084 if (idx) idx[i] = a->garray[idxb[i]]; 3085 } 3086 } 3087 3088 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3089 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3090 ierr = PetscFree(idxb);CHKERRQ(ierr); 3091 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3092 PetscFunctionReturn(0); 3093 } 3094 3095 #undef __FUNCT__ 3096 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3097 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3098 { 3099 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3100 PetscInt n = A->rmap->n; 3101 PetscInt cstart = A->cmap->rstart; 3102 PetscInt *cmap = mat->garray; 3103 PetscInt *diagIdx, *offdiagIdx; 3104 Vec diagV, offdiagV; 3105 PetscScalar *a, *diagA, *offdiagA; 3106 PetscInt r; 3107 PetscErrorCode ierr; 3108 3109 PetscFunctionBegin; 3110 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3111 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3112 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3113 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3114 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3115 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3116 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3117 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3118 for (r = 0; r < n; ++r) { 3119 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3120 a[r] = diagA[r]; 3121 idx[r] = cstart + diagIdx[r]; 3122 } else { 3123 a[r] = offdiagA[r]; 3124 idx[r] = cmap[offdiagIdx[r]]; 3125 } 3126 } 3127 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3128 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3129 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3130 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3131 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3132 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3133 PetscFunctionReturn(0); 3134 } 3135 3136 #undef __FUNCT__ 3137 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3138 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3139 { 3140 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3141 PetscInt n = A->rmap->n; 3142 PetscInt cstart = A->cmap->rstart; 3143 PetscInt *cmap = mat->garray; 3144 PetscInt *diagIdx, *offdiagIdx; 3145 Vec diagV, offdiagV; 3146 PetscScalar *a, *diagA, *offdiagA; 3147 PetscInt r; 3148 PetscErrorCode ierr; 3149 3150 PetscFunctionBegin; 3151 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3152 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3153 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3154 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3155 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3156 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3157 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3158 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3159 for (r = 0; r < n; ++r) { 3160 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3161 a[r] = diagA[r]; 3162 idx[r] = cstart + diagIdx[r]; 3163 } else { 3164 a[r] = offdiagA[r]; 3165 idx[r] = cmap[offdiagIdx[r]]; 3166 } 3167 } 3168 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3169 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3170 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3171 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3172 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3173 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3174 PetscFunctionReturn(0); 3175 } 3176 3177 #undef __FUNCT__ 3178 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3179 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3180 { 3181 PetscErrorCode ierr; 3182 Mat *dummy; 3183 3184 PetscFunctionBegin; 3185 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3186 *newmat = *dummy; 3187 ierr = PetscFree(dummy);CHKERRQ(ierr); 3188 PetscFunctionReturn(0); 3189 } 3190 3191 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3192 3193 #undef __FUNCT__ 3194 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3195 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3196 { 3197 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3198 PetscErrorCode ierr; 3199 3200 PetscFunctionBegin; 3201 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3202 PetscFunctionReturn(0); 3203 } 3204 3205 #undef __FUNCT__ 3206 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3207 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3208 { 3209 PetscErrorCode ierr; 3210 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3211 3212 PetscFunctionBegin; 3213 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3214 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3215 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3216 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3217 PetscFunctionReturn(0); 3218 } 3219 3220 /* -------------------------------------------------------------------*/ 3221 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3222 MatGetRow_MPIAIJ, 3223 MatRestoreRow_MPIAIJ, 3224 MatMult_MPIAIJ, 3225 /* 4*/ MatMultAdd_MPIAIJ, 3226 MatMultTranspose_MPIAIJ, 3227 MatMultTransposeAdd_MPIAIJ, 3228 #if defined(PETSC_HAVE_PBGL) 3229 MatSolve_MPIAIJ, 3230 #else 3231 0, 3232 #endif 3233 0, 3234 0, 3235 /*10*/ 0, 3236 0, 3237 0, 3238 MatSOR_MPIAIJ, 3239 MatTranspose_MPIAIJ, 3240 /*15*/ MatGetInfo_MPIAIJ, 3241 MatEqual_MPIAIJ, 3242 MatGetDiagonal_MPIAIJ, 3243 MatDiagonalScale_MPIAIJ, 3244 MatNorm_MPIAIJ, 3245 /*20*/ MatAssemblyBegin_MPIAIJ, 3246 MatAssemblyEnd_MPIAIJ, 3247 MatSetOption_MPIAIJ, 3248 MatZeroEntries_MPIAIJ, 3249 /*24*/ MatZeroRows_MPIAIJ, 3250 0, 3251 #if defined(PETSC_HAVE_PBGL) 3252 0, 3253 #else 3254 0, 3255 #endif 3256 0, 3257 0, 3258 /*29*/ MatSetUp_MPIAIJ, 3259 #if defined(PETSC_HAVE_PBGL) 3260 0, 3261 #else 3262 0, 3263 #endif 3264 0, 3265 0, 3266 0, 3267 /*34*/ MatDuplicate_MPIAIJ, 3268 0, 3269 0, 3270 0, 3271 0, 3272 /*39*/ MatAXPY_MPIAIJ, 3273 MatGetSubMatrices_MPIAIJ, 3274 MatIncreaseOverlap_MPIAIJ, 3275 MatGetValues_MPIAIJ, 3276 MatCopy_MPIAIJ, 3277 /*44*/ MatGetRowMax_MPIAIJ, 3278 MatScale_MPIAIJ, 3279 0, 3280 0, 3281 MatZeroRowsColumns_MPIAIJ, 3282 /*49*/ MatSetRandom_MPIAIJ, 3283 0, 3284 0, 3285 0, 3286 0, 3287 /*54*/ MatFDColoringCreate_MPIAIJ, 3288 0, 3289 MatSetUnfactored_MPIAIJ, 3290 MatPermute_MPIAIJ, 3291 0, 3292 /*59*/ MatGetSubMatrix_MPIAIJ, 3293 MatDestroy_MPIAIJ, 3294 MatView_MPIAIJ, 3295 0, 3296 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3297 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3298 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3299 0, 3300 0, 3301 0, 3302 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3303 MatGetRowMinAbs_MPIAIJ, 3304 0, 3305 MatSetColoring_MPIAIJ, 3306 0, 3307 MatSetValuesAdifor_MPIAIJ, 3308 /*75*/ MatFDColoringApply_AIJ, 3309 0, 3310 0, 3311 0, 3312 MatFindZeroDiagonals_MPIAIJ, 3313 /*80*/ 0, 3314 0, 3315 0, 3316 /*83*/ MatLoad_MPIAIJ, 3317 0, 3318 0, 3319 0, 3320 0, 3321 0, 3322 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3323 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3324 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3325 MatPtAP_MPIAIJ_MPIAIJ, 3326 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3327 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3328 0, 3329 0, 3330 0, 3331 0, 3332 /*99*/ 0, 3333 0, 3334 0, 3335 MatConjugate_MPIAIJ, 3336 0, 3337 /*104*/MatSetValuesRow_MPIAIJ, 3338 MatRealPart_MPIAIJ, 3339 MatImaginaryPart_MPIAIJ, 3340 0, 3341 0, 3342 /*109*/0, 3343 MatGetRedundantMatrix_MPIAIJ, 3344 MatGetRowMin_MPIAIJ, 3345 0, 3346 0, 3347 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3348 0, 3349 0, 3350 0, 3351 0, 3352 /*119*/0, 3353 0, 3354 0, 3355 0, 3356 MatGetMultiProcBlock_MPIAIJ, 3357 /*124*/MatFindNonzeroRows_MPIAIJ, 3358 MatGetColumnNorms_MPIAIJ, 3359 MatInvertBlockDiagonal_MPIAIJ, 3360 0, 3361 MatGetSubMatricesParallel_MPIAIJ, 3362 /*129*/0, 3363 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3364 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3365 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3366 0, 3367 /*134*/0, 3368 0, 3369 0, 3370 0, 3371 0, 3372 /*139*/0, 3373 0 3374 }; 3375 3376 /* ----------------------------------------------------------------------------------------*/ 3377 3378 #undef __FUNCT__ 3379 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3380 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3381 { 3382 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3383 PetscErrorCode ierr; 3384 3385 PetscFunctionBegin; 3386 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3387 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3388 PetscFunctionReturn(0); 3389 } 3390 3391 #undef __FUNCT__ 3392 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3393 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3394 { 3395 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3396 PetscErrorCode ierr; 3397 3398 PetscFunctionBegin; 3399 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3400 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3401 PetscFunctionReturn(0); 3402 } 3403 3404 #undef __FUNCT__ 3405 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3406 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3407 { 3408 Mat_MPIAIJ *b; 3409 PetscErrorCode ierr; 3410 3411 PetscFunctionBegin; 3412 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3413 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3414 b = (Mat_MPIAIJ*)B->data; 3415 3416 if (!B->preallocated) { 3417 /* Explicitly create 2 MATSEQAIJ matrices. */ 3418 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3419 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3420 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3421 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3422 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3423 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3424 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3425 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3426 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3427 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3428 } 3429 3430 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3431 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3432 B->preallocated = PETSC_TRUE; 3433 PetscFunctionReturn(0); 3434 } 3435 3436 #undef __FUNCT__ 3437 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3438 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3439 { 3440 Mat mat; 3441 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3442 PetscErrorCode ierr; 3443 3444 PetscFunctionBegin; 3445 *newmat = 0; 3446 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3447 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3448 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3449 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3450 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3451 a = (Mat_MPIAIJ*)mat->data; 3452 3453 mat->factortype = matin->factortype; 3454 mat->rmap->bs = matin->rmap->bs; 3455 mat->cmap->bs = matin->cmap->bs; 3456 mat->assembled = PETSC_TRUE; 3457 mat->insertmode = NOT_SET_VALUES; 3458 mat->preallocated = PETSC_TRUE; 3459 3460 a->size = oldmat->size; 3461 a->rank = oldmat->rank; 3462 a->donotstash = oldmat->donotstash; 3463 a->roworiented = oldmat->roworiented; 3464 a->rowindices = 0; 3465 a->rowvalues = 0; 3466 a->getrowactive = PETSC_FALSE; 3467 3468 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3469 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3470 3471 if (oldmat->colmap) { 3472 #if defined(PETSC_USE_CTABLE) 3473 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3474 #else 3475 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3476 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3477 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3478 #endif 3479 } else a->colmap = 0; 3480 if (oldmat->garray) { 3481 PetscInt len; 3482 len = oldmat->B->cmap->n; 3483 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3484 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3485 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3486 } else a->garray = 0; 3487 3488 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3489 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3490 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3491 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3492 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3493 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3494 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3495 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3496 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3497 *newmat = mat; 3498 PetscFunctionReturn(0); 3499 } 3500 3501 3502 3503 #undef __FUNCT__ 3504 #define __FUNCT__ "MatLoad_MPIAIJ" 3505 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3506 { 3507 PetscScalar *vals,*svals; 3508 MPI_Comm comm; 3509 PetscErrorCode ierr; 3510 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3511 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3512 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3513 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3514 PetscInt cend,cstart,n,*rowners,sizesset=1; 3515 int fd; 3516 PetscInt bs = 1; 3517 3518 PetscFunctionBegin; 3519 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3520 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3521 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3522 if (!rank) { 3523 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3524 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3525 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3526 } 3527 3528 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3529 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3530 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3531 3532 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3533 3534 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3535 M = header[1]; N = header[2]; 3536 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3537 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3538 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3539 3540 /* If global sizes are set, check if they are consistent with that given in the file */ 3541 if (sizesset) { 3542 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3543 } 3544 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); 3545 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); 3546 3547 /* determine ownership of all (block) rows */ 3548 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3549 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3550 else m = newMat->rmap->n; /* Set by user */ 3551 3552 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3553 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3554 3555 /* First process needs enough room for process with most rows */ 3556 if (!rank) { 3557 mmax = rowners[1]; 3558 for (i=2; i<=size; i++) { 3559 mmax = PetscMax(mmax, rowners[i]); 3560 } 3561 } else mmax = -1; /* unused, but compilers complain */ 3562 3563 rowners[0] = 0; 3564 for (i=2; i<=size; i++) { 3565 rowners[i] += rowners[i-1]; 3566 } 3567 rstart = rowners[rank]; 3568 rend = rowners[rank+1]; 3569 3570 /* distribute row lengths to all processors */ 3571 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3572 if (!rank) { 3573 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3574 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3575 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3576 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3577 for (j=0; j<m; j++) { 3578 procsnz[0] += ourlens[j]; 3579 } 3580 for (i=1; i<size; i++) { 3581 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3582 /* calculate the number of nonzeros on each processor */ 3583 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3584 procsnz[i] += rowlengths[j]; 3585 } 3586 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3587 } 3588 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3589 } else { 3590 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3591 } 3592 3593 if (!rank) { 3594 /* determine max buffer needed and allocate it */ 3595 maxnz = 0; 3596 for (i=0; i<size; i++) { 3597 maxnz = PetscMax(maxnz,procsnz[i]); 3598 } 3599 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3600 3601 /* read in my part of the matrix column indices */ 3602 nz = procsnz[0]; 3603 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3604 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3605 3606 /* read in every one elses and ship off */ 3607 for (i=1; i<size; i++) { 3608 nz = procsnz[i]; 3609 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3610 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3611 } 3612 ierr = PetscFree(cols);CHKERRQ(ierr); 3613 } else { 3614 /* determine buffer space needed for message */ 3615 nz = 0; 3616 for (i=0; i<m; i++) { 3617 nz += ourlens[i]; 3618 } 3619 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3620 3621 /* receive message of column indices*/ 3622 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3623 } 3624 3625 /* determine column ownership if matrix is not square */ 3626 if (N != M) { 3627 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3628 else n = newMat->cmap->n; 3629 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3630 cstart = cend - n; 3631 } else { 3632 cstart = rstart; 3633 cend = rend; 3634 n = cend - cstart; 3635 } 3636 3637 /* loop over local rows, determining number of off diagonal entries */ 3638 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3639 jj = 0; 3640 for (i=0; i<m; i++) { 3641 for (j=0; j<ourlens[i]; j++) { 3642 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3643 jj++; 3644 } 3645 } 3646 3647 for (i=0; i<m; i++) { 3648 ourlens[i] -= offlens[i]; 3649 } 3650 if (!sizesset) { 3651 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3652 } 3653 3654 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3655 3656 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3657 3658 for (i=0; i<m; i++) { 3659 ourlens[i] += offlens[i]; 3660 } 3661 3662 if (!rank) { 3663 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3664 3665 /* read in my part of the matrix numerical values */ 3666 nz = procsnz[0]; 3667 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3668 3669 /* insert into matrix */ 3670 jj = rstart; 3671 smycols = mycols; 3672 svals = vals; 3673 for (i=0; i<m; i++) { 3674 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3675 smycols += ourlens[i]; 3676 svals += ourlens[i]; 3677 jj++; 3678 } 3679 3680 /* read in other processors and ship out */ 3681 for (i=1; i<size; i++) { 3682 nz = procsnz[i]; 3683 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3684 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3685 } 3686 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3687 } else { 3688 /* receive numeric values */ 3689 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3690 3691 /* receive message of values*/ 3692 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3693 3694 /* insert into matrix */ 3695 jj = rstart; 3696 smycols = mycols; 3697 svals = vals; 3698 for (i=0; i<m; i++) { 3699 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3700 smycols += ourlens[i]; 3701 svals += ourlens[i]; 3702 jj++; 3703 } 3704 } 3705 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3706 ierr = PetscFree(vals);CHKERRQ(ierr); 3707 ierr = PetscFree(mycols);CHKERRQ(ierr); 3708 ierr = PetscFree(rowners);CHKERRQ(ierr); 3709 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3710 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3711 PetscFunctionReturn(0); 3712 } 3713 3714 #undef __FUNCT__ 3715 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3716 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3717 { 3718 PetscErrorCode ierr; 3719 IS iscol_local; 3720 PetscInt csize; 3721 3722 PetscFunctionBegin; 3723 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3724 if (call == MAT_REUSE_MATRIX) { 3725 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3726 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3727 } else { 3728 PetscInt cbs; 3729 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3730 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3731 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3732 } 3733 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3734 if (call == MAT_INITIAL_MATRIX) { 3735 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3736 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3737 } 3738 PetscFunctionReturn(0); 3739 } 3740 3741 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3742 #undef __FUNCT__ 3743 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3744 /* 3745 Not great since it makes two copies of the submatrix, first an SeqAIJ 3746 in local and then by concatenating the local matrices the end result. 3747 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3748 3749 Note: This requires a sequential iscol with all indices. 3750 */ 3751 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3752 { 3753 PetscErrorCode ierr; 3754 PetscMPIInt rank,size; 3755 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3756 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3757 PetscBool allcolumns, colflag; 3758 Mat M,Mreuse; 3759 MatScalar *vwork,*aa; 3760 MPI_Comm comm; 3761 Mat_SeqAIJ *aij; 3762 3763 PetscFunctionBegin; 3764 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3765 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3766 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3767 3768 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3769 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3770 if (colflag && ncol == mat->cmap->N) { 3771 allcolumns = PETSC_TRUE; 3772 } else { 3773 allcolumns = PETSC_FALSE; 3774 } 3775 if (call == MAT_REUSE_MATRIX) { 3776 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3777 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3778 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3779 } else { 3780 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3781 } 3782 3783 /* 3784 m - number of local rows 3785 n - number of columns (same on all processors) 3786 rstart - first row in new global matrix generated 3787 */ 3788 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3789 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3790 if (call == MAT_INITIAL_MATRIX) { 3791 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3792 ii = aij->i; 3793 jj = aij->j; 3794 3795 /* 3796 Determine the number of non-zeros in the diagonal and off-diagonal 3797 portions of the matrix in order to do correct preallocation 3798 */ 3799 3800 /* first get start and end of "diagonal" columns */ 3801 if (csize == PETSC_DECIDE) { 3802 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3803 if (mglobal == n) { /* square matrix */ 3804 nlocal = m; 3805 } else { 3806 nlocal = n/size + ((n % size) > rank); 3807 } 3808 } else { 3809 nlocal = csize; 3810 } 3811 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3812 rstart = rend - nlocal; 3813 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); 3814 3815 /* next, compute all the lengths */ 3816 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3817 olens = dlens + m; 3818 for (i=0; i<m; i++) { 3819 jend = ii[i+1] - ii[i]; 3820 olen = 0; 3821 dlen = 0; 3822 for (j=0; j<jend; j++) { 3823 if (*jj < rstart || *jj >= rend) olen++; 3824 else dlen++; 3825 jj++; 3826 } 3827 olens[i] = olen; 3828 dlens[i] = dlen; 3829 } 3830 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3831 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3832 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3833 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3834 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3835 ierr = PetscFree(dlens);CHKERRQ(ierr); 3836 } else { 3837 PetscInt ml,nl; 3838 3839 M = *newmat; 3840 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3841 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3842 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3843 /* 3844 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3845 rather than the slower MatSetValues(). 3846 */ 3847 M->was_assembled = PETSC_TRUE; 3848 M->assembled = PETSC_FALSE; 3849 } 3850 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3851 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3852 ii = aij->i; 3853 jj = aij->j; 3854 aa = aij->a; 3855 for (i=0; i<m; i++) { 3856 row = rstart + i; 3857 nz = ii[i+1] - ii[i]; 3858 cwork = jj; jj += nz; 3859 vwork = aa; aa += nz; 3860 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3861 } 3862 3863 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3864 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3865 *newmat = M; 3866 3867 /* save submatrix used in processor for next request */ 3868 if (call == MAT_INITIAL_MATRIX) { 3869 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3870 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3871 } 3872 PetscFunctionReturn(0); 3873 } 3874 3875 #undef __FUNCT__ 3876 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3877 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3878 { 3879 PetscInt m,cstart, cend,j,nnz,i,d; 3880 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3881 const PetscInt *JJ; 3882 PetscScalar *values; 3883 PetscErrorCode ierr; 3884 3885 PetscFunctionBegin; 3886 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3887 3888 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3889 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3890 m = B->rmap->n; 3891 cstart = B->cmap->rstart; 3892 cend = B->cmap->rend; 3893 rstart = B->rmap->rstart; 3894 3895 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3896 3897 #if defined(PETSC_USE_DEBUGGING) 3898 for (i=0; i<m; i++) { 3899 nnz = Ii[i+1]- Ii[i]; 3900 JJ = J + Ii[i]; 3901 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3902 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3903 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); 3904 } 3905 #endif 3906 3907 for (i=0; i<m; i++) { 3908 nnz = Ii[i+1]- Ii[i]; 3909 JJ = J + Ii[i]; 3910 nnz_max = PetscMax(nnz_max,nnz); 3911 d = 0; 3912 for (j=0; j<nnz; j++) { 3913 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3914 } 3915 d_nnz[i] = d; 3916 o_nnz[i] = nnz - d; 3917 } 3918 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3919 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3920 3921 if (v) values = (PetscScalar*)v; 3922 else { 3923 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3924 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3925 } 3926 3927 for (i=0; i<m; i++) { 3928 ii = i + rstart; 3929 nnz = Ii[i+1]- Ii[i]; 3930 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3931 } 3932 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3933 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3934 3935 if (!v) { 3936 ierr = PetscFree(values);CHKERRQ(ierr); 3937 } 3938 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3939 PetscFunctionReturn(0); 3940 } 3941 3942 #undef __FUNCT__ 3943 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3944 /*@ 3945 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3946 (the default parallel PETSc format). 3947 3948 Collective on MPI_Comm 3949 3950 Input Parameters: 3951 + B - the matrix 3952 . i - the indices into j for the start of each local row (starts with zero) 3953 . j - the column indices for each local row (starts with zero) 3954 - v - optional values in the matrix 3955 3956 Level: developer 3957 3958 Notes: 3959 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 3960 thus you CANNOT change the matrix entries by changing the values of a[] after you have 3961 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 3962 3963 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 3964 3965 The format which is used for the sparse matrix input, is equivalent to a 3966 row-major ordering.. i.e for the following matrix, the input data expected is 3967 as shown: 3968 3969 1 0 0 3970 2 0 3 P0 3971 ------- 3972 4 5 6 P1 3973 3974 Process0 [P0]: rows_owned=[0,1] 3975 i = {0,1,3} [size = nrow+1 = 2+1] 3976 j = {0,0,2} [size = nz = 6] 3977 v = {1,2,3} [size = nz = 6] 3978 3979 Process1 [P1]: rows_owned=[2] 3980 i = {0,3} [size = nrow+1 = 1+1] 3981 j = {0,1,2} [size = nz = 6] 3982 v = {4,5,6} [size = nz = 6] 3983 3984 .keywords: matrix, aij, compressed row, sparse, parallel 3985 3986 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 3987 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 3988 @*/ 3989 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 3990 { 3991 PetscErrorCode ierr; 3992 3993 PetscFunctionBegin; 3994 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3995 PetscFunctionReturn(0); 3996 } 3997 3998 #undef __FUNCT__ 3999 #define __FUNCT__ "MatMPIAIJSetPreallocation" 4000 /*@C 4001 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4002 (the default parallel PETSc format). For good matrix assembly performance 4003 the user should preallocate the matrix storage by setting the parameters 4004 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4005 performance can be increased by more than a factor of 50. 4006 4007 Collective on MPI_Comm 4008 4009 Input Parameters: 4010 + A - the matrix 4011 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4012 (same value is used for all local rows) 4013 . d_nnz - array containing the number of nonzeros in the various rows of the 4014 DIAGONAL portion of the local submatrix (possibly different for each row) 4015 or NULL, if d_nz is used to specify the nonzero structure. 4016 The size of this array is equal to the number of local rows, i.e 'm'. 4017 For matrices that will be factored, you must leave room for (and set) 4018 the diagonal entry even if it is zero. 4019 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4020 submatrix (same value is used for all local rows). 4021 - o_nnz - array containing the number of nonzeros in the various rows of the 4022 OFF-DIAGONAL portion of the local submatrix (possibly different for 4023 each row) or NULL, if o_nz is used to specify the nonzero 4024 structure. The size of this array is equal to the number 4025 of local rows, i.e 'm'. 4026 4027 If the *_nnz parameter is given then the *_nz parameter is ignored 4028 4029 The AIJ format (also called the Yale sparse matrix format or 4030 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4031 storage. The stored row and column indices begin with zero. 4032 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4033 4034 The parallel matrix is partitioned such that the first m0 rows belong to 4035 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4036 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4037 4038 The DIAGONAL portion of the local submatrix of a processor can be defined 4039 as the submatrix which is obtained by extraction the part corresponding to 4040 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4041 first row that belongs to the processor, r2 is the last row belonging to 4042 the this processor, and c1-c2 is range of indices of the local part of a 4043 vector suitable for applying the matrix to. This is an mxn matrix. In the 4044 common case of a square matrix, the row and column ranges are the same and 4045 the DIAGONAL part is also square. The remaining portion of the local 4046 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4047 4048 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4049 4050 You can call MatGetInfo() to get information on how effective the preallocation was; 4051 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4052 You can also run with the option -info and look for messages with the string 4053 malloc in them to see if additional memory allocation was needed. 4054 4055 Example usage: 4056 4057 Consider the following 8x8 matrix with 34 non-zero values, that is 4058 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4059 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4060 as follows: 4061 4062 .vb 4063 1 2 0 | 0 3 0 | 0 4 4064 Proc0 0 5 6 | 7 0 0 | 8 0 4065 9 0 10 | 11 0 0 | 12 0 4066 ------------------------------------- 4067 13 0 14 | 15 16 17 | 0 0 4068 Proc1 0 18 0 | 19 20 21 | 0 0 4069 0 0 0 | 22 23 0 | 24 0 4070 ------------------------------------- 4071 Proc2 25 26 27 | 0 0 28 | 29 0 4072 30 0 0 | 31 32 33 | 0 34 4073 .ve 4074 4075 This can be represented as a collection of submatrices as: 4076 4077 .vb 4078 A B C 4079 D E F 4080 G H I 4081 .ve 4082 4083 Where the submatrices A,B,C are owned by proc0, D,E,F are 4084 owned by proc1, G,H,I are owned by proc2. 4085 4086 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4087 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4088 The 'M','N' parameters are 8,8, and have the same values on all procs. 4089 4090 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4091 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4092 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4093 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4094 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4095 matrix, ans [DF] as another SeqAIJ matrix. 4096 4097 When d_nz, o_nz parameters are specified, d_nz storage elements are 4098 allocated for every row of the local diagonal submatrix, and o_nz 4099 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4100 One way to choose d_nz and o_nz is to use the max nonzerors per local 4101 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4102 In this case, the values of d_nz,o_nz are: 4103 .vb 4104 proc0 : dnz = 2, o_nz = 2 4105 proc1 : dnz = 3, o_nz = 2 4106 proc2 : dnz = 1, o_nz = 4 4107 .ve 4108 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4109 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4110 for proc3. i.e we are using 12+15+10=37 storage locations to store 4111 34 values. 4112 4113 When d_nnz, o_nnz parameters are specified, the storage is specified 4114 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4115 In the above case the values for d_nnz,o_nnz are: 4116 .vb 4117 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4118 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4119 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4120 .ve 4121 Here the space allocated is sum of all the above values i.e 34, and 4122 hence pre-allocation is perfect. 4123 4124 Level: intermediate 4125 4126 .keywords: matrix, aij, compressed row, sparse, parallel 4127 4128 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4129 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4130 @*/ 4131 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4132 { 4133 PetscErrorCode ierr; 4134 4135 PetscFunctionBegin; 4136 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4137 PetscValidType(B,1); 4138 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4139 PetscFunctionReturn(0); 4140 } 4141 4142 #undef __FUNCT__ 4143 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4144 /*@ 4145 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4146 CSR format the local rows. 4147 4148 Collective on MPI_Comm 4149 4150 Input Parameters: 4151 + comm - MPI communicator 4152 . m - number of local rows (Cannot be PETSC_DECIDE) 4153 . n - This value should be the same as the local size used in creating the 4154 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4155 calculated if N is given) For square matrices n is almost always m. 4156 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4157 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4158 . i - row indices 4159 . j - column indices 4160 - a - matrix values 4161 4162 Output Parameter: 4163 . mat - the matrix 4164 4165 Level: intermediate 4166 4167 Notes: 4168 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4169 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4170 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4171 4172 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4173 4174 The format which is used for the sparse matrix input, is equivalent to a 4175 row-major ordering.. i.e for the following matrix, the input data expected is 4176 as shown: 4177 4178 1 0 0 4179 2 0 3 P0 4180 ------- 4181 4 5 6 P1 4182 4183 Process0 [P0]: rows_owned=[0,1] 4184 i = {0,1,3} [size = nrow+1 = 2+1] 4185 j = {0,0,2} [size = nz = 6] 4186 v = {1,2,3} [size = nz = 6] 4187 4188 Process1 [P1]: rows_owned=[2] 4189 i = {0,3} [size = nrow+1 = 1+1] 4190 j = {0,1,2} [size = nz = 6] 4191 v = {4,5,6} [size = nz = 6] 4192 4193 .keywords: matrix, aij, compressed row, sparse, parallel 4194 4195 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4196 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4197 @*/ 4198 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4199 { 4200 PetscErrorCode ierr; 4201 4202 PetscFunctionBegin; 4203 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4204 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4205 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4206 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4207 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4208 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4209 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4210 PetscFunctionReturn(0); 4211 } 4212 4213 #undef __FUNCT__ 4214 #define __FUNCT__ "MatCreateAIJ" 4215 /*@C 4216 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4217 (the default parallel PETSc format). For good matrix assembly performance 4218 the user should preallocate the matrix storage by setting the parameters 4219 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4220 performance can be increased by more than a factor of 50. 4221 4222 Collective on MPI_Comm 4223 4224 Input Parameters: 4225 + comm - MPI communicator 4226 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4227 This value should be the same as the local size used in creating the 4228 y vector for the matrix-vector product y = Ax. 4229 . n - This value should be the same as the local size used in creating the 4230 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4231 calculated if N is given) For square matrices n is almost always m. 4232 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4233 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4234 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4235 (same value is used for all local rows) 4236 . d_nnz - array containing the number of nonzeros in the various rows of the 4237 DIAGONAL portion of the local submatrix (possibly different for each row) 4238 or NULL, if d_nz is used to specify the nonzero structure. 4239 The size of this array is equal to the number of local rows, i.e 'm'. 4240 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4241 submatrix (same value is used for all local rows). 4242 - o_nnz - array containing the number of nonzeros in the various rows of the 4243 OFF-DIAGONAL portion of the local submatrix (possibly different for 4244 each row) or NULL, if o_nz is used to specify the nonzero 4245 structure. The size of this array is equal to the number 4246 of local rows, i.e 'm'. 4247 4248 Output Parameter: 4249 . A - the matrix 4250 4251 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4252 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4253 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4254 4255 Notes: 4256 If the *_nnz parameter is given then the *_nz parameter is ignored 4257 4258 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4259 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4260 storage requirements for this matrix. 4261 4262 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4263 processor than it must be used on all processors that share the object for 4264 that argument. 4265 4266 The user MUST specify either the local or global matrix dimensions 4267 (possibly both). 4268 4269 The parallel matrix is partitioned across processors such that the 4270 first m0 rows belong to process 0, the next m1 rows belong to 4271 process 1, the next m2 rows belong to process 2 etc.. where 4272 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4273 values corresponding to [m x N] submatrix. 4274 4275 The columns are logically partitioned with the n0 columns belonging 4276 to 0th partition, the next n1 columns belonging to the next 4277 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4278 4279 The DIAGONAL portion of the local submatrix on any given processor 4280 is the submatrix corresponding to the rows and columns m,n 4281 corresponding to the given processor. i.e diagonal matrix on 4282 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4283 etc. The remaining portion of the local submatrix [m x (N-n)] 4284 constitute the OFF-DIAGONAL portion. The example below better 4285 illustrates this concept. 4286 4287 For a square global matrix we define each processor's diagonal portion 4288 to be its local rows and the corresponding columns (a square submatrix); 4289 each processor's off-diagonal portion encompasses the remainder of the 4290 local matrix (a rectangular submatrix). 4291 4292 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4293 4294 When calling this routine with a single process communicator, a matrix of 4295 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4296 type of communicator, use the construction mechanism: 4297 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4298 4299 By default, this format uses inodes (identical nodes) when possible. 4300 We search for consecutive rows with the same nonzero structure, thereby 4301 reusing matrix information to achieve increased efficiency. 4302 4303 Options Database Keys: 4304 + -mat_no_inode - Do not use inodes 4305 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4306 - -mat_aij_oneindex - Internally use indexing starting at 1 4307 rather than 0. Note that when calling MatSetValues(), 4308 the user still MUST index entries starting at 0! 4309 4310 4311 Example usage: 4312 4313 Consider the following 8x8 matrix with 34 non-zero values, that is 4314 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4315 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4316 as follows: 4317 4318 .vb 4319 1 2 0 | 0 3 0 | 0 4 4320 Proc0 0 5 6 | 7 0 0 | 8 0 4321 9 0 10 | 11 0 0 | 12 0 4322 ------------------------------------- 4323 13 0 14 | 15 16 17 | 0 0 4324 Proc1 0 18 0 | 19 20 21 | 0 0 4325 0 0 0 | 22 23 0 | 24 0 4326 ------------------------------------- 4327 Proc2 25 26 27 | 0 0 28 | 29 0 4328 30 0 0 | 31 32 33 | 0 34 4329 .ve 4330 4331 This can be represented as a collection of submatrices as: 4332 4333 .vb 4334 A B C 4335 D E F 4336 G H I 4337 .ve 4338 4339 Where the submatrices A,B,C are owned by proc0, D,E,F are 4340 owned by proc1, G,H,I are owned by proc2. 4341 4342 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4343 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4344 The 'M','N' parameters are 8,8, and have the same values on all procs. 4345 4346 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4347 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4348 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4349 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4350 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4351 matrix, ans [DF] as another SeqAIJ matrix. 4352 4353 When d_nz, o_nz parameters are specified, d_nz storage elements are 4354 allocated for every row of the local diagonal submatrix, and o_nz 4355 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4356 One way to choose d_nz and o_nz is to use the max nonzerors per local 4357 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4358 In this case, the values of d_nz,o_nz are: 4359 .vb 4360 proc0 : dnz = 2, o_nz = 2 4361 proc1 : dnz = 3, o_nz = 2 4362 proc2 : dnz = 1, o_nz = 4 4363 .ve 4364 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4365 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4366 for proc3. i.e we are using 12+15+10=37 storage locations to store 4367 34 values. 4368 4369 When d_nnz, o_nnz parameters are specified, the storage is specified 4370 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4371 In the above case the values for d_nnz,o_nnz are: 4372 .vb 4373 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4374 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4375 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4376 .ve 4377 Here the space allocated is sum of all the above values i.e 34, and 4378 hence pre-allocation is perfect. 4379 4380 Level: intermediate 4381 4382 .keywords: matrix, aij, compressed row, sparse, parallel 4383 4384 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4385 MPIAIJ, MatCreateMPIAIJWithArrays() 4386 @*/ 4387 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) 4388 { 4389 PetscErrorCode ierr; 4390 PetscMPIInt size; 4391 4392 PetscFunctionBegin; 4393 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4394 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4395 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4396 if (size > 1) { 4397 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4398 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4399 } else { 4400 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4401 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4402 } 4403 PetscFunctionReturn(0); 4404 } 4405 4406 #undef __FUNCT__ 4407 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4408 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4409 { 4410 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4411 4412 PetscFunctionBegin; 4413 *Ad = a->A; 4414 *Ao = a->B; 4415 *colmap = a->garray; 4416 PetscFunctionReturn(0); 4417 } 4418 4419 #undef __FUNCT__ 4420 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4421 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4422 { 4423 PetscErrorCode ierr; 4424 PetscInt i; 4425 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4426 4427 PetscFunctionBegin; 4428 if (coloring->ctype == IS_COLORING_GLOBAL) { 4429 ISColoringValue *allcolors,*colors; 4430 ISColoring ocoloring; 4431 4432 /* set coloring for diagonal portion */ 4433 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4434 4435 /* set coloring for off-diagonal portion */ 4436 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4437 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4438 for (i=0; i<a->B->cmap->n; i++) { 4439 colors[i] = allcolors[a->garray[i]]; 4440 } 4441 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4442 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4443 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4444 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4445 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4446 ISColoringValue *colors; 4447 PetscInt *larray; 4448 ISColoring ocoloring; 4449 4450 /* set coloring for diagonal portion */ 4451 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4452 for (i=0; i<a->A->cmap->n; i++) { 4453 larray[i] = i + A->cmap->rstart; 4454 } 4455 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4456 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4457 for (i=0; i<a->A->cmap->n; i++) { 4458 colors[i] = coloring->colors[larray[i]]; 4459 } 4460 ierr = PetscFree(larray);CHKERRQ(ierr); 4461 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4462 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4463 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4464 4465 /* set coloring for off-diagonal portion */ 4466 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4467 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4468 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4469 for (i=0; i<a->B->cmap->n; i++) { 4470 colors[i] = coloring->colors[larray[i]]; 4471 } 4472 ierr = PetscFree(larray);CHKERRQ(ierr); 4473 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4474 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4475 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4476 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4477 PetscFunctionReturn(0); 4478 } 4479 4480 #undef __FUNCT__ 4481 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4482 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4483 { 4484 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4485 PetscErrorCode ierr; 4486 4487 PetscFunctionBegin; 4488 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4489 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4490 PetscFunctionReturn(0); 4491 } 4492 4493 #undef __FUNCT__ 4494 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4495 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4496 { 4497 PetscErrorCode ierr; 4498 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4499 PetscInt *indx; 4500 4501 PetscFunctionBegin; 4502 /* This routine will ONLY return MPIAIJ type matrix */ 4503 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4504 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4505 if (n == PETSC_DECIDE) { 4506 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4507 } 4508 /* Check sum(n) = N */ 4509 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4510 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4511 4512 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4513 rstart -= m; 4514 4515 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4516 for (i=0; i<m; i++) { 4517 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4518 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4519 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4520 } 4521 4522 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4523 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4524 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4525 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4526 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4527 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4528 PetscFunctionReturn(0); 4529 } 4530 4531 #undef __FUNCT__ 4532 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4533 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4534 { 4535 PetscErrorCode ierr; 4536 PetscInt m,N,i,rstart,nnz,Ii; 4537 PetscInt *indx; 4538 PetscScalar *values; 4539 4540 PetscFunctionBegin; 4541 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4542 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4543 for (i=0; i<m; i++) { 4544 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4545 Ii = i + rstart; 4546 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4547 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4548 } 4549 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4550 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4551 PetscFunctionReturn(0); 4552 } 4553 4554 #undef __FUNCT__ 4555 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4556 /*@ 4557 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4558 matrices from each processor 4559 4560 Collective on MPI_Comm 4561 4562 Input Parameters: 4563 + comm - the communicators the parallel matrix will live on 4564 . inmat - the input sequential matrices 4565 . n - number of local columns (or PETSC_DECIDE) 4566 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4567 4568 Output Parameter: 4569 . outmat - the parallel matrix generated 4570 4571 Level: advanced 4572 4573 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4574 4575 @*/ 4576 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4577 { 4578 PetscErrorCode ierr; 4579 PetscMPIInt size; 4580 4581 PetscFunctionBegin; 4582 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4583 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4584 if (size == 1) { 4585 if (scall == MAT_INITIAL_MATRIX) { 4586 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4587 } else { 4588 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4589 } 4590 } else { 4591 if (scall == MAT_INITIAL_MATRIX) { 4592 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4593 } 4594 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4595 } 4596 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4597 PetscFunctionReturn(0); 4598 } 4599 4600 #undef __FUNCT__ 4601 #define __FUNCT__ "MatFileSplit" 4602 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4603 { 4604 PetscErrorCode ierr; 4605 PetscMPIInt rank; 4606 PetscInt m,N,i,rstart,nnz; 4607 size_t len; 4608 const PetscInt *indx; 4609 PetscViewer out; 4610 char *name; 4611 Mat B; 4612 const PetscScalar *values; 4613 4614 PetscFunctionBegin; 4615 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4616 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4617 /* Should this be the type of the diagonal block of A? */ 4618 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4619 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4620 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4621 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4622 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4623 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4624 for (i=0; i<m; i++) { 4625 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4626 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4627 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4628 } 4629 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4630 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4631 4632 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4633 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4634 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4635 sprintf(name,"%s.%d",outfile,rank); 4636 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4637 ierr = PetscFree(name);CHKERRQ(ierr); 4638 ierr = MatView(B,out);CHKERRQ(ierr); 4639 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4640 ierr = MatDestroy(&B);CHKERRQ(ierr); 4641 PetscFunctionReturn(0); 4642 } 4643 4644 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4645 #undef __FUNCT__ 4646 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4647 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4648 { 4649 PetscErrorCode ierr; 4650 Mat_Merge_SeqsToMPI *merge; 4651 PetscContainer container; 4652 4653 PetscFunctionBegin; 4654 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4655 if (container) { 4656 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4657 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4658 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4659 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4660 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4661 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4662 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4663 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4664 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4665 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4666 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4667 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4668 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4669 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4670 ierr = PetscFree(merge);CHKERRQ(ierr); 4671 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4672 } 4673 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4674 PetscFunctionReturn(0); 4675 } 4676 4677 #include <../src/mat/utils/freespace.h> 4678 #include <petscbt.h> 4679 4680 #undef __FUNCT__ 4681 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4682 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4683 { 4684 PetscErrorCode ierr; 4685 MPI_Comm comm; 4686 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4687 PetscMPIInt size,rank,taga,*len_s; 4688 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4689 PetscInt proc,m; 4690 PetscInt **buf_ri,**buf_rj; 4691 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4692 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4693 MPI_Request *s_waits,*r_waits; 4694 MPI_Status *status; 4695 MatScalar *aa=a->a; 4696 MatScalar **abuf_r,*ba_i; 4697 Mat_Merge_SeqsToMPI *merge; 4698 PetscContainer container; 4699 4700 PetscFunctionBegin; 4701 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4702 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4703 4704 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4705 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4706 4707 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4708 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4709 4710 bi = merge->bi; 4711 bj = merge->bj; 4712 buf_ri = merge->buf_ri; 4713 buf_rj = merge->buf_rj; 4714 4715 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4716 owners = merge->rowmap->range; 4717 len_s = merge->len_s; 4718 4719 /* send and recv matrix values */ 4720 /*-----------------------------*/ 4721 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4722 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4723 4724 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4725 for (proc=0,k=0; proc<size; proc++) { 4726 if (!len_s[proc]) continue; 4727 i = owners[proc]; 4728 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4729 k++; 4730 } 4731 4732 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4733 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4734 ierr = PetscFree(status);CHKERRQ(ierr); 4735 4736 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4737 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4738 4739 /* insert mat values of mpimat */ 4740 /*----------------------------*/ 4741 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4742 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4743 4744 for (k=0; k<merge->nrecv; k++) { 4745 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4746 nrows = *(buf_ri_k[k]); 4747 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4748 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4749 } 4750 4751 /* set values of ba */ 4752 m = merge->rowmap->n; 4753 for (i=0; i<m; i++) { 4754 arow = owners[rank] + i; 4755 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4756 bnzi = bi[i+1] - bi[i]; 4757 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4758 4759 /* add local non-zero vals of this proc's seqmat into ba */ 4760 anzi = ai[arow+1] - ai[arow]; 4761 aj = a->j + ai[arow]; 4762 aa = a->a + ai[arow]; 4763 nextaj = 0; 4764 for (j=0; nextaj<anzi; j++) { 4765 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4766 ba_i[j] += aa[nextaj++]; 4767 } 4768 } 4769 4770 /* add received vals into ba */ 4771 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4772 /* i-th row */ 4773 if (i == *nextrow[k]) { 4774 anzi = *(nextai[k]+1) - *nextai[k]; 4775 aj = buf_rj[k] + *(nextai[k]); 4776 aa = abuf_r[k] + *(nextai[k]); 4777 nextaj = 0; 4778 for (j=0; nextaj<anzi; j++) { 4779 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4780 ba_i[j] += aa[nextaj++]; 4781 } 4782 } 4783 nextrow[k]++; nextai[k]++; 4784 } 4785 } 4786 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4787 } 4788 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4789 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4790 4791 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4792 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4793 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4794 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4795 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4796 PetscFunctionReturn(0); 4797 } 4798 4799 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4800 4801 #undef __FUNCT__ 4802 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4803 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4804 { 4805 PetscErrorCode ierr; 4806 Mat B_mpi; 4807 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4808 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4809 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4810 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4811 PetscInt len,proc,*dnz,*onz,bs,cbs; 4812 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4813 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4814 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4815 MPI_Status *status; 4816 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4817 PetscBT lnkbt; 4818 Mat_Merge_SeqsToMPI *merge; 4819 PetscContainer container; 4820 4821 PetscFunctionBegin; 4822 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4823 4824 /* make sure it is a PETSc comm */ 4825 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4826 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4827 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4828 4829 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4830 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4831 4832 /* determine row ownership */ 4833 /*---------------------------------------------------------*/ 4834 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4835 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4836 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4837 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4838 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4839 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4840 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4841 4842 m = merge->rowmap->n; 4843 owners = merge->rowmap->range; 4844 4845 /* determine the number of messages to send, their lengths */ 4846 /*---------------------------------------------------------*/ 4847 len_s = merge->len_s; 4848 4849 len = 0; /* length of buf_si[] */ 4850 merge->nsend = 0; 4851 for (proc=0; proc<size; proc++) { 4852 len_si[proc] = 0; 4853 if (proc == rank) { 4854 len_s[proc] = 0; 4855 } else { 4856 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4857 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4858 } 4859 if (len_s[proc]) { 4860 merge->nsend++; 4861 nrows = 0; 4862 for (i=owners[proc]; i<owners[proc+1]; i++) { 4863 if (ai[i+1] > ai[i]) nrows++; 4864 } 4865 len_si[proc] = 2*(nrows+1); 4866 len += len_si[proc]; 4867 } 4868 } 4869 4870 /* determine the number and length of messages to receive for ij-structure */ 4871 /*-------------------------------------------------------------------------*/ 4872 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4873 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4874 4875 /* post the Irecv of j-structure */ 4876 /*-------------------------------*/ 4877 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4878 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4879 4880 /* post the Isend of j-structure */ 4881 /*--------------------------------*/ 4882 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4883 4884 for (proc=0, k=0; proc<size; proc++) { 4885 if (!len_s[proc]) continue; 4886 i = owners[proc]; 4887 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4888 k++; 4889 } 4890 4891 /* receives and sends of j-structure are complete */ 4892 /*------------------------------------------------*/ 4893 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4894 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4895 4896 /* send and recv i-structure */ 4897 /*---------------------------*/ 4898 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4899 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4900 4901 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4902 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4903 for (proc=0,k=0; proc<size; proc++) { 4904 if (!len_s[proc]) continue; 4905 /* form outgoing message for i-structure: 4906 buf_si[0]: nrows to be sent 4907 [1:nrows]: row index (global) 4908 [nrows+1:2*nrows+1]: i-structure index 4909 */ 4910 /*-------------------------------------------*/ 4911 nrows = len_si[proc]/2 - 1; 4912 buf_si_i = buf_si + nrows+1; 4913 buf_si[0] = nrows; 4914 buf_si_i[0] = 0; 4915 nrows = 0; 4916 for (i=owners[proc]; i<owners[proc+1]; i++) { 4917 anzi = ai[i+1] - ai[i]; 4918 if (anzi) { 4919 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4920 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4921 nrows++; 4922 } 4923 } 4924 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4925 k++; 4926 buf_si += len_si[proc]; 4927 } 4928 4929 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4930 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4931 4932 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4933 for (i=0; i<merge->nrecv; i++) { 4934 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); 4935 } 4936 4937 ierr = PetscFree(len_si);CHKERRQ(ierr); 4938 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4939 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4940 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4941 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4942 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4943 ierr = PetscFree(status);CHKERRQ(ierr); 4944 4945 /* compute a local seq matrix in each processor */ 4946 /*----------------------------------------------*/ 4947 /* allocate bi array and free space for accumulating nonzero column info */ 4948 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4949 bi[0] = 0; 4950 4951 /* create and initialize a linked list */ 4952 nlnk = N+1; 4953 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4954 4955 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 4956 len = ai[owners[rank+1]] - ai[owners[rank]]; 4957 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 4958 4959 current_space = free_space; 4960 4961 /* determine symbolic info for each local row */ 4962 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4963 4964 for (k=0; k<merge->nrecv; k++) { 4965 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4966 nrows = *buf_ri_k[k]; 4967 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 4968 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4969 } 4970 4971 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4972 len = 0; 4973 for (i=0; i<m; i++) { 4974 bnzi = 0; 4975 /* add local non-zero cols of this proc's seqmat into lnk */ 4976 arow = owners[rank] + i; 4977 anzi = ai[arow+1] - ai[arow]; 4978 aj = a->j + ai[arow]; 4979 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4980 bnzi += nlnk; 4981 /* add received col data into lnk */ 4982 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4983 if (i == *nextrow[k]) { /* i-th row */ 4984 anzi = *(nextai[k]+1) - *nextai[k]; 4985 aj = buf_rj[k] + *nextai[k]; 4986 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 4987 bnzi += nlnk; 4988 nextrow[k]++; nextai[k]++; 4989 } 4990 } 4991 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 4992 4993 /* if free space is not available, make more free space */ 4994 if (current_space->local_remaining<bnzi) { 4995 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 4996 nspacedouble++; 4997 } 4998 /* copy data into free space, then initialize lnk */ 4999 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 5000 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 5001 5002 current_space->array += bnzi; 5003 current_space->local_used += bnzi; 5004 current_space->local_remaining -= bnzi; 5005 5006 bi[i+1] = bi[i] + bnzi; 5007 } 5008 5009 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5010 5011 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5012 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5013 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5014 5015 /* create symbolic parallel matrix B_mpi */ 5016 /*---------------------------------------*/ 5017 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5018 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5019 if (n==PETSC_DECIDE) { 5020 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5021 } else { 5022 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5023 } 5024 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5025 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5026 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5027 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5028 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5029 5030 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5031 B_mpi->assembled = PETSC_FALSE; 5032 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5033 merge->bi = bi; 5034 merge->bj = bj; 5035 merge->buf_ri = buf_ri; 5036 merge->buf_rj = buf_rj; 5037 merge->coi = NULL; 5038 merge->coj = NULL; 5039 merge->owners_co = NULL; 5040 5041 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5042 5043 /* attach the supporting struct to B_mpi for reuse */ 5044 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5045 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5046 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5047 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5048 *mpimat = B_mpi; 5049 5050 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5051 PetscFunctionReturn(0); 5052 } 5053 5054 #undef __FUNCT__ 5055 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5056 /*@C 5057 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5058 matrices from each processor 5059 5060 Collective on MPI_Comm 5061 5062 Input Parameters: 5063 + comm - the communicators the parallel matrix will live on 5064 . seqmat - the input sequential matrices 5065 . m - number of local rows (or PETSC_DECIDE) 5066 . n - number of local columns (or PETSC_DECIDE) 5067 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5068 5069 Output Parameter: 5070 . mpimat - the parallel matrix generated 5071 5072 Level: advanced 5073 5074 Notes: 5075 The dimensions of the sequential matrix in each processor MUST be the same. 5076 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5077 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5078 @*/ 5079 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5080 { 5081 PetscErrorCode ierr; 5082 PetscMPIInt size; 5083 5084 PetscFunctionBegin; 5085 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5086 if (size == 1) { 5087 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5088 if (scall == MAT_INITIAL_MATRIX) { 5089 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5090 } else { 5091 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5092 } 5093 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5094 PetscFunctionReturn(0); 5095 } 5096 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5097 if (scall == MAT_INITIAL_MATRIX) { 5098 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5099 } 5100 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5101 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5102 PetscFunctionReturn(0); 5103 } 5104 5105 #undef __FUNCT__ 5106 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5107 /*@ 5108 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5109 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5110 with MatGetSize() 5111 5112 Not Collective 5113 5114 Input Parameters: 5115 + A - the matrix 5116 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5117 5118 Output Parameter: 5119 . A_loc - the local sequential matrix generated 5120 5121 Level: developer 5122 5123 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5124 5125 @*/ 5126 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5127 { 5128 PetscErrorCode ierr; 5129 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5130 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5131 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5132 MatScalar *aa=a->a,*ba=b->a,*cam; 5133 PetscScalar *ca; 5134 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5135 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5136 PetscBool match; 5137 5138 PetscFunctionBegin; 5139 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5140 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5141 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5142 if (scall == MAT_INITIAL_MATRIX) { 5143 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5144 ci[0] = 0; 5145 for (i=0; i<am; i++) { 5146 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5147 } 5148 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5149 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5150 k = 0; 5151 for (i=0; i<am; i++) { 5152 ncols_o = bi[i+1] - bi[i]; 5153 ncols_d = ai[i+1] - ai[i]; 5154 /* off-diagonal portion of A */ 5155 for (jo=0; jo<ncols_o; jo++) { 5156 col = cmap[*bj]; 5157 if (col >= cstart) break; 5158 cj[k] = col; bj++; 5159 ca[k++] = *ba++; 5160 } 5161 /* diagonal portion of A */ 5162 for (j=0; j<ncols_d; j++) { 5163 cj[k] = cstart + *aj++; 5164 ca[k++] = *aa++; 5165 } 5166 /* off-diagonal portion of A */ 5167 for (j=jo; j<ncols_o; j++) { 5168 cj[k] = cmap[*bj++]; 5169 ca[k++] = *ba++; 5170 } 5171 } 5172 /* put together the new matrix */ 5173 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5174 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5175 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5176 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5177 mat->free_a = PETSC_TRUE; 5178 mat->free_ij = PETSC_TRUE; 5179 mat->nonew = 0; 5180 } else if (scall == MAT_REUSE_MATRIX) { 5181 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5182 ci = mat->i; cj = mat->j; cam = mat->a; 5183 for (i=0; i<am; i++) { 5184 /* off-diagonal portion of A */ 5185 ncols_o = bi[i+1] - bi[i]; 5186 for (jo=0; jo<ncols_o; jo++) { 5187 col = cmap[*bj]; 5188 if (col >= cstart) break; 5189 *cam++ = *ba++; bj++; 5190 } 5191 /* diagonal portion of A */ 5192 ncols_d = ai[i+1] - ai[i]; 5193 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5194 /* off-diagonal portion of A */ 5195 for (j=jo; j<ncols_o; j++) { 5196 *cam++ = *ba++; bj++; 5197 } 5198 } 5199 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5200 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5201 PetscFunctionReturn(0); 5202 } 5203 5204 #undef __FUNCT__ 5205 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5206 /*@C 5207 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5208 5209 Not Collective 5210 5211 Input Parameters: 5212 + A - the matrix 5213 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5214 - row, col - index sets of rows and columns to extract (or NULL) 5215 5216 Output Parameter: 5217 . A_loc - the local sequential matrix generated 5218 5219 Level: developer 5220 5221 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5222 5223 @*/ 5224 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5225 { 5226 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5227 PetscErrorCode ierr; 5228 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5229 IS isrowa,iscola; 5230 Mat *aloc; 5231 PetscBool match; 5232 5233 PetscFunctionBegin; 5234 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5235 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5236 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5237 if (!row) { 5238 start = A->rmap->rstart; end = A->rmap->rend; 5239 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5240 } else { 5241 isrowa = *row; 5242 } 5243 if (!col) { 5244 start = A->cmap->rstart; 5245 cmap = a->garray; 5246 nzA = a->A->cmap->n; 5247 nzB = a->B->cmap->n; 5248 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5249 ncols = 0; 5250 for (i=0; i<nzB; i++) { 5251 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5252 else break; 5253 } 5254 imark = i; 5255 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5256 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5257 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5258 } else { 5259 iscola = *col; 5260 } 5261 if (scall != MAT_INITIAL_MATRIX) { 5262 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5263 aloc[0] = *A_loc; 5264 } 5265 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5266 *A_loc = aloc[0]; 5267 ierr = PetscFree(aloc);CHKERRQ(ierr); 5268 if (!row) { 5269 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5270 } 5271 if (!col) { 5272 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5273 } 5274 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5275 PetscFunctionReturn(0); 5276 } 5277 5278 #undef __FUNCT__ 5279 #define __FUNCT__ "MatGetBrowsOfAcols" 5280 /*@C 5281 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5282 5283 Collective on Mat 5284 5285 Input Parameters: 5286 + A,B - the matrices in mpiaij format 5287 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5288 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5289 5290 Output Parameter: 5291 + rowb, colb - index sets of rows and columns of B to extract 5292 - B_seq - the sequential matrix generated 5293 5294 Level: developer 5295 5296 @*/ 5297 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5298 { 5299 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5300 PetscErrorCode ierr; 5301 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5302 IS isrowb,iscolb; 5303 Mat *bseq=NULL; 5304 5305 PetscFunctionBegin; 5306 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5307 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); 5308 } 5309 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5310 5311 if (scall == MAT_INITIAL_MATRIX) { 5312 start = A->cmap->rstart; 5313 cmap = a->garray; 5314 nzA = a->A->cmap->n; 5315 nzB = a->B->cmap->n; 5316 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5317 ncols = 0; 5318 for (i=0; i<nzB; i++) { /* row < local row index */ 5319 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5320 else break; 5321 } 5322 imark = i; 5323 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5324 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5325 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5326 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5327 } else { 5328 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5329 isrowb = *rowb; iscolb = *colb; 5330 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5331 bseq[0] = *B_seq; 5332 } 5333 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5334 *B_seq = bseq[0]; 5335 ierr = PetscFree(bseq);CHKERRQ(ierr); 5336 if (!rowb) { 5337 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5338 } else { 5339 *rowb = isrowb; 5340 } 5341 if (!colb) { 5342 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5343 } else { 5344 *colb = iscolb; 5345 } 5346 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5347 PetscFunctionReturn(0); 5348 } 5349 5350 #undef __FUNCT__ 5351 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5352 /* 5353 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5354 of the OFF-DIAGONAL portion of local A 5355 5356 Collective on Mat 5357 5358 Input Parameters: 5359 + A,B - the matrices in mpiaij format 5360 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5361 5362 Output Parameter: 5363 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5364 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5365 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5366 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5367 5368 Level: developer 5369 5370 */ 5371 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5372 { 5373 VecScatter_MPI_General *gen_to,*gen_from; 5374 PetscErrorCode ierr; 5375 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5376 Mat_SeqAIJ *b_oth; 5377 VecScatter ctx =a->Mvctx; 5378 MPI_Comm comm; 5379 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5380 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5381 PetscScalar *rvalues,*svalues; 5382 MatScalar *b_otha,*bufa,*bufA; 5383 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5384 MPI_Request *rwaits = NULL,*swaits = NULL; 5385 MPI_Status *sstatus,rstatus; 5386 PetscMPIInt jj; 5387 PetscInt *cols,sbs,rbs; 5388 PetscScalar *vals; 5389 5390 PetscFunctionBegin; 5391 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5392 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5393 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); 5394 } 5395 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5396 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5397 5398 gen_to = (VecScatter_MPI_General*)ctx->todata; 5399 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5400 rvalues = gen_from->values; /* holds the length of receiving row */ 5401 svalues = gen_to->values; /* holds the length of sending row */ 5402 nrecvs = gen_from->n; 5403 nsends = gen_to->n; 5404 5405 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5406 srow = gen_to->indices; /* local row index to be sent */ 5407 sstarts = gen_to->starts; 5408 sprocs = gen_to->procs; 5409 sstatus = gen_to->sstatus; 5410 sbs = gen_to->bs; 5411 rstarts = gen_from->starts; 5412 rprocs = gen_from->procs; 5413 rbs = gen_from->bs; 5414 5415 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5416 if (scall == MAT_INITIAL_MATRIX) { 5417 /* i-array */ 5418 /*---------*/ 5419 /* post receives */ 5420 for (i=0; i<nrecvs; i++) { 5421 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5422 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5423 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5424 } 5425 5426 /* pack the outgoing message */ 5427 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5428 5429 sstartsj[0] = 0; 5430 rstartsj[0] = 0; 5431 len = 0; /* total length of j or a array to be sent */ 5432 k = 0; 5433 for (i=0; i<nsends; i++) { 5434 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5435 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5436 for (j=0; j<nrows; j++) { 5437 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5438 for (l=0; l<sbs; l++) { 5439 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5440 5441 rowlen[j*sbs+l] = ncols; 5442 5443 len += ncols; 5444 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5445 } 5446 k++; 5447 } 5448 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5449 5450 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5451 } 5452 /* recvs and sends of i-array are completed */ 5453 i = nrecvs; 5454 while (i--) { 5455 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5456 } 5457 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5458 5459 /* allocate buffers for sending j and a arrays */ 5460 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5461 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5462 5463 /* create i-array of B_oth */ 5464 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5465 5466 b_othi[0] = 0; 5467 len = 0; /* total length of j or a array to be received */ 5468 k = 0; 5469 for (i=0; i<nrecvs; i++) { 5470 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5471 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5472 for (j=0; j<nrows; j++) { 5473 b_othi[k+1] = b_othi[k] + rowlen[j]; 5474 len += rowlen[j]; k++; 5475 } 5476 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5477 } 5478 5479 /* allocate space for j and a arrrays of B_oth */ 5480 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5481 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5482 5483 /* j-array */ 5484 /*---------*/ 5485 /* post receives of j-array */ 5486 for (i=0; i<nrecvs; i++) { 5487 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5488 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5489 } 5490 5491 /* pack the outgoing message j-array */ 5492 k = 0; 5493 for (i=0; i<nsends; i++) { 5494 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5495 bufJ = bufj+sstartsj[i]; 5496 for (j=0; j<nrows; j++) { 5497 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5498 for (ll=0; ll<sbs; ll++) { 5499 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5500 for (l=0; l<ncols; l++) { 5501 *bufJ++ = cols[l]; 5502 } 5503 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5504 } 5505 } 5506 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5507 } 5508 5509 /* recvs and sends of j-array are completed */ 5510 i = nrecvs; 5511 while (i--) { 5512 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5513 } 5514 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5515 } else if (scall == MAT_REUSE_MATRIX) { 5516 sstartsj = *startsj_s; 5517 rstartsj = *startsj_r; 5518 bufa = *bufa_ptr; 5519 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5520 b_otha = b_oth->a; 5521 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5522 5523 /* a-array */ 5524 /*---------*/ 5525 /* post receives of a-array */ 5526 for (i=0; i<nrecvs; i++) { 5527 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5528 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5529 } 5530 5531 /* pack the outgoing message a-array */ 5532 k = 0; 5533 for (i=0; i<nsends; i++) { 5534 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5535 bufA = bufa+sstartsj[i]; 5536 for (j=0; j<nrows; j++) { 5537 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5538 for (ll=0; ll<sbs; ll++) { 5539 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5540 for (l=0; l<ncols; l++) { 5541 *bufA++ = vals[l]; 5542 } 5543 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5544 } 5545 } 5546 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5547 } 5548 /* recvs and sends of a-array are completed */ 5549 i = nrecvs; 5550 while (i--) { 5551 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5552 } 5553 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5554 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5555 5556 if (scall == MAT_INITIAL_MATRIX) { 5557 /* put together the new matrix */ 5558 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5559 5560 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5561 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5562 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5563 b_oth->free_a = PETSC_TRUE; 5564 b_oth->free_ij = PETSC_TRUE; 5565 b_oth->nonew = 0; 5566 5567 ierr = PetscFree(bufj);CHKERRQ(ierr); 5568 if (!startsj_s || !bufa_ptr) { 5569 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5570 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5571 } else { 5572 *startsj_s = sstartsj; 5573 *startsj_r = rstartsj; 5574 *bufa_ptr = bufa; 5575 } 5576 } 5577 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5578 PetscFunctionReturn(0); 5579 } 5580 5581 #undef __FUNCT__ 5582 #define __FUNCT__ "MatGetCommunicationStructs" 5583 /*@C 5584 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5585 5586 Not Collective 5587 5588 Input Parameters: 5589 . A - The matrix in mpiaij format 5590 5591 Output Parameter: 5592 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5593 . colmap - A map from global column index to local index into lvec 5594 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5595 5596 Level: developer 5597 5598 @*/ 5599 #if defined(PETSC_USE_CTABLE) 5600 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5601 #else 5602 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5603 #endif 5604 { 5605 Mat_MPIAIJ *a; 5606 5607 PetscFunctionBegin; 5608 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5609 PetscValidPointer(lvec, 2); 5610 PetscValidPointer(colmap, 3); 5611 PetscValidPointer(multScatter, 4); 5612 a = (Mat_MPIAIJ*) A->data; 5613 if (lvec) *lvec = a->lvec; 5614 if (colmap) *colmap = a->colmap; 5615 if (multScatter) *multScatter = a->Mvctx; 5616 PetscFunctionReturn(0); 5617 } 5618 5619 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5620 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5621 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5622 5623 #undef __FUNCT__ 5624 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5625 /* 5626 Computes (B'*A')' since computing B*A directly is untenable 5627 5628 n p p 5629 ( ) ( ) ( ) 5630 m ( A ) * n ( B ) = m ( C ) 5631 ( ) ( ) ( ) 5632 5633 */ 5634 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5635 { 5636 PetscErrorCode ierr; 5637 Mat At,Bt,Ct; 5638 5639 PetscFunctionBegin; 5640 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5641 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5642 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5643 ierr = MatDestroy(&At);CHKERRQ(ierr); 5644 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5645 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5646 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5647 PetscFunctionReturn(0); 5648 } 5649 5650 #undef __FUNCT__ 5651 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5652 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5653 { 5654 PetscErrorCode ierr; 5655 PetscInt m=A->rmap->n,n=B->cmap->n; 5656 Mat Cmat; 5657 5658 PetscFunctionBegin; 5659 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); 5660 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5661 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5662 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5663 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5664 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5665 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5666 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5667 5668 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5669 5670 *C = Cmat; 5671 PetscFunctionReturn(0); 5672 } 5673 5674 /* ----------------------------------------------------------------*/ 5675 #undef __FUNCT__ 5676 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5677 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5678 { 5679 PetscErrorCode ierr; 5680 5681 PetscFunctionBegin; 5682 if (scall == MAT_INITIAL_MATRIX) { 5683 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5684 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5685 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5686 } 5687 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5688 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5689 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5690 PetscFunctionReturn(0); 5691 } 5692 5693 #if defined(PETSC_HAVE_MUMPS) 5694 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5695 #endif 5696 #if defined(PETSC_HAVE_PASTIX) 5697 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5698 #endif 5699 #if defined(PETSC_HAVE_SUPERLU_DIST) 5700 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5701 #endif 5702 #if defined(PETSC_HAVE_CLIQUE) 5703 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5704 #endif 5705 5706 /*MC 5707 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5708 5709 Options Database Keys: 5710 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5711 5712 Level: beginner 5713 5714 .seealso: MatCreateAIJ() 5715 M*/ 5716 5717 #undef __FUNCT__ 5718 #define __FUNCT__ "MatCreate_MPIAIJ" 5719 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5720 { 5721 Mat_MPIAIJ *b; 5722 PetscErrorCode ierr; 5723 PetscMPIInt size; 5724 5725 PetscFunctionBegin; 5726 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5727 5728 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5729 B->data = (void*)b; 5730 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5731 B->assembled = PETSC_FALSE; 5732 B->insertmode = NOT_SET_VALUES; 5733 b->size = size; 5734 5735 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5736 5737 /* build cache for off array entries formed */ 5738 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5739 5740 b->donotstash = PETSC_FALSE; 5741 b->colmap = 0; 5742 b->garray = 0; 5743 b->roworiented = PETSC_TRUE; 5744 5745 /* stuff used for matrix vector multiply */ 5746 b->lvec = NULL; 5747 b->Mvctx = NULL; 5748 5749 /* stuff for MatGetRow() */ 5750 b->rowindices = 0; 5751 b->rowvalues = 0; 5752 b->getrowactive = PETSC_FALSE; 5753 5754 /* flexible pointer used in CUSP/CUSPARSE classes */ 5755 b->spptr = NULL; 5756 5757 #if defined(PETSC_HAVE_MUMPS) 5758 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5759 #endif 5760 #if defined(PETSC_HAVE_PASTIX) 5761 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5762 #endif 5763 #if defined(PETSC_HAVE_SUPERLU_DIST) 5764 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5765 #endif 5766 #if defined(PETSC_HAVE_CLIQUE) 5767 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5768 #endif 5769 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5770 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5771 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5772 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5773 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5774 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5775 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5776 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5777 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5778 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5779 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5780 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5781 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5782 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5783 PetscFunctionReturn(0); 5784 } 5785 5786 #undef __FUNCT__ 5787 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5788 /*@ 5789 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5790 and "off-diagonal" part of the matrix in CSR format. 5791 5792 Collective on MPI_Comm 5793 5794 Input Parameters: 5795 + comm - MPI communicator 5796 . m - number of local rows (Cannot be PETSC_DECIDE) 5797 . n - This value should be the same as the local size used in creating the 5798 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5799 calculated if N is given) For square matrices n is almost always m. 5800 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5801 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5802 . i - row indices for "diagonal" portion of matrix 5803 . j - column indices 5804 . a - matrix values 5805 . oi - row indices for "off-diagonal" portion of matrix 5806 . oj - column indices 5807 - oa - matrix values 5808 5809 Output Parameter: 5810 . mat - the matrix 5811 5812 Level: advanced 5813 5814 Notes: 5815 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5816 must free the arrays once the matrix has been destroyed and not before. 5817 5818 The i and j indices are 0 based 5819 5820 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5821 5822 This sets local rows and cannot be used to set off-processor values. 5823 5824 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5825 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5826 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5827 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5828 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5829 communication if it is known that only local entries will be set. 5830 5831 .keywords: matrix, aij, compressed row, sparse, parallel 5832 5833 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5834 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5835 @*/ 5836 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) 5837 { 5838 PetscErrorCode ierr; 5839 Mat_MPIAIJ *maij; 5840 5841 PetscFunctionBegin; 5842 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5843 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5844 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5845 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5846 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5847 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5848 maij = (Mat_MPIAIJ*) (*mat)->data; 5849 5850 (*mat)->preallocated = PETSC_TRUE; 5851 5852 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5853 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5854 5855 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5856 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5857 5858 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5859 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5860 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5861 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5862 5863 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5864 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5865 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5866 PetscFunctionReturn(0); 5867 } 5868 5869 /* 5870 Special version for direct calls from Fortran 5871 */ 5872 #include <petsc-private/fortranimpl.h> 5873 5874 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5875 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5876 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5877 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5878 #endif 5879 5880 /* Change these macros so can be used in void function */ 5881 #undef CHKERRQ 5882 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5883 #undef SETERRQ2 5884 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5885 #undef SETERRQ3 5886 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5887 #undef SETERRQ 5888 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5889 5890 #undef __FUNCT__ 5891 #define __FUNCT__ "matsetvaluesmpiaij_" 5892 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) 5893 { 5894 Mat mat = *mmat; 5895 PetscInt m = *mm, n = *mn; 5896 InsertMode addv = *maddv; 5897 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5898 PetscScalar value; 5899 PetscErrorCode ierr; 5900 5901 MatCheckPreallocated(mat,1); 5902 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5903 5904 #if defined(PETSC_USE_DEBUG) 5905 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5906 #endif 5907 { 5908 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5909 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5910 PetscBool roworiented = aij->roworiented; 5911 5912 /* Some Variables required in the macro */ 5913 Mat A = aij->A; 5914 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5915 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5916 MatScalar *aa = a->a; 5917 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5918 Mat B = aij->B; 5919 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5920 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5921 MatScalar *ba = b->a; 5922 5923 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5924 PetscInt nonew = a->nonew; 5925 MatScalar *ap1,*ap2; 5926 5927 PetscFunctionBegin; 5928 for (i=0; i<m; i++) { 5929 if (im[i] < 0) continue; 5930 #if defined(PETSC_USE_DEBUG) 5931 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); 5932 #endif 5933 if (im[i] >= rstart && im[i] < rend) { 5934 row = im[i] - rstart; 5935 lastcol1 = -1; 5936 rp1 = aj + ai[row]; 5937 ap1 = aa + ai[row]; 5938 rmax1 = aimax[row]; 5939 nrow1 = ailen[row]; 5940 low1 = 0; 5941 high1 = nrow1; 5942 lastcol2 = -1; 5943 rp2 = bj + bi[row]; 5944 ap2 = ba + bi[row]; 5945 rmax2 = bimax[row]; 5946 nrow2 = bilen[row]; 5947 low2 = 0; 5948 high2 = nrow2; 5949 5950 for (j=0; j<n; j++) { 5951 if (roworiented) value = v[i*n+j]; 5952 else value = v[i+j*m]; 5953 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 5954 if (in[j] >= cstart && in[j] < cend) { 5955 col = in[j] - cstart; 5956 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 5957 } else if (in[j] < 0) continue; 5958 #if defined(PETSC_USE_DEBUG) 5959 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); 5960 #endif 5961 else { 5962 if (mat->was_assembled) { 5963 if (!aij->colmap) { 5964 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 5965 } 5966 #if defined(PETSC_USE_CTABLE) 5967 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 5968 col--; 5969 #else 5970 col = aij->colmap[in[j]] - 1; 5971 #endif 5972 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 5973 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 5974 col = in[j]; 5975 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 5976 B = aij->B; 5977 b = (Mat_SeqAIJ*)B->data; 5978 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 5979 rp2 = bj + bi[row]; 5980 ap2 = ba + bi[row]; 5981 rmax2 = bimax[row]; 5982 nrow2 = bilen[row]; 5983 low2 = 0; 5984 high2 = nrow2; 5985 bm = aij->B->rmap->n; 5986 ba = b->a; 5987 } 5988 } else col = in[j]; 5989 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 5990 } 5991 } 5992 } else if (!aij->donotstash) { 5993 if (roworiented) { 5994 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5995 } else { 5996 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 5997 } 5998 } 5999 } 6000 } 6001 PetscFunctionReturnVoid(); 6002 } 6003 6004