1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ 3 #include <petsc-private/vecimpl.h> 4 #include <petscblaslapack.h> 5 #include <petscsf.h> 6 7 /*MC 8 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 9 10 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 11 and MATMPIAIJ otherwise. As a result, for single process communicators, 12 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 13 for communicators controlling multiple processes. It is recommended that you call both of 14 the above preallocation routines for simplicity. 15 16 Options Database Keys: 17 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 18 19 Developer Notes: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 20 enough exist. 21 22 Level: beginner 23 24 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 25 M*/ 26 27 /*MC 28 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 29 30 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 31 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 32 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 33 for communicators controlling multiple processes. It is recommended that you call both of 34 the above preallocation routines for simplicity. 35 36 Options Database Keys: 37 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 38 39 Level: beginner 40 41 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 42 M*/ 43 44 #undef __FUNCT__ 45 #define __FUNCT__ "MatFindNonzeroRows_MPIAIJ" 46 PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows) 47 { 48 PetscErrorCode ierr; 49 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data; 50 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data; 51 Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data; 52 const PetscInt *ia,*ib; 53 const MatScalar *aa,*bb; 54 PetscInt na,nb,i,j,*rows,cnt=0,n0rows; 55 PetscInt m = M->rmap->n,rstart = M->rmap->rstart; 56 57 PetscFunctionBegin; 58 *keptrows = 0; 59 ia = a->i; 60 ib = b->i; 61 for (i=0; i<m; i++) { 62 na = ia[i+1] - ia[i]; 63 nb = ib[i+1] - ib[i]; 64 if (!na && !nb) { 65 cnt++; 66 goto ok1; 67 } 68 aa = a->a + ia[i]; 69 for (j=0; j<na; j++) { 70 if (aa[j] != 0.0) goto ok1; 71 } 72 bb = b->a + ib[i]; 73 for (j=0; j <nb; j++) { 74 if (bb[j] != 0.0) goto ok1; 75 } 76 cnt++; 77 ok1:; 78 } 79 ierr = MPI_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));CHKERRQ(ierr); 80 if (!n0rows) PetscFunctionReturn(0); 81 ierr = PetscMalloc((M->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 82 cnt = 0; 83 for (i=0; i<m; i++) { 84 na = ia[i+1] - ia[i]; 85 nb = ib[i+1] - ib[i]; 86 if (!na && !nb) continue; 87 aa = a->a + ia[i]; 88 for (j=0; j<na;j++) { 89 if (aa[j] != 0.0) { 90 rows[cnt++] = rstart + i; 91 goto ok2; 92 } 93 } 94 bb = b->a + ib[i]; 95 for (j=0; j<nb; j++) { 96 if (bb[j] != 0.0) { 97 rows[cnt++] = rstart + i; 98 goto ok2; 99 } 100 } 101 ok2:; 102 } 103 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 104 PetscFunctionReturn(0); 105 } 106 107 #undef __FUNCT__ 108 #define __FUNCT__ "MatFindZeroDiagonals_MPIAIJ" 109 PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows) 110 { 111 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data; 112 PetscErrorCode ierr; 113 PetscInt i,rstart,nrows,*rows; 114 115 PetscFunctionBegin; 116 *zrows = NULL; 117 ierr = MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);CHKERRQ(ierr); 118 ierr = MatGetOwnershipRange(M,&rstart,NULL);CHKERRQ(ierr); 119 for (i=0; i<nrows; i++) rows[i] += rstart; 120 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 121 PetscFunctionReturn(0); 122 } 123 124 #undef __FUNCT__ 125 #define __FUNCT__ "MatGetColumnNorms_MPIAIJ" 126 PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms) 127 { 128 PetscErrorCode ierr; 129 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data; 130 PetscInt i,n,*garray = aij->garray; 131 Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data; 132 Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data; 133 PetscReal *work; 134 135 PetscFunctionBegin; 136 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 137 ierr = PetscMalloc(n*sizeof(PetscReal),&work);CHKERRQ(ierr); 138 ierr = PetscMemzero(work,n*sizeof(PetscReal));CHKERRQ(ierr); 139 if (type == NORM_2) { 140 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 141 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]); 142 } 143 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 144 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]); 145 } 146 } else if (type == NORM_1) { 147 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 148 work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]); 149 } 150 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 151 work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]); 152 } 153 } else if (type == NORM_INFINITY) { 154 for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) { 155 work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]); 156 } 157 for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) { 158 work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]); 159 } 160 161 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 162 if (type == NORM_INFINITY) { 163 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 164 } else { 165 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 166 } 167 ierr = PetscFree(work);CHKERRQ(ierr); 168 if (type == NORM_2) { 169 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 170 } 171 PetscFunctionReturn(0); 172 } 173 174 #undef __FUNCT__ 175 #define __FUNCT__ "MatDistribute_MPIAIJ" 176 /* 177 Distributes a SeqAIJ matrix across a set of processes. Code stolen from 178 MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type. 179 180 Only for square matrices 181 182 Used by a preconditioner, hence PETSC_EXTERN 183 */ 184 PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat) 185 { 186 PetscMPIInt rank,size; 187 PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz,*gmataj,cnt,row,*ld,bses[2]; 188 PetscErrorCode ierr; 189 Mat mat; 190 Mat_SeqAIJ *gmata; 191 PetscMPIInt tag; 192 MPI_Status status; 193 PetscBool aij; 194 MatScalar *gmataa,*ao,*ad,*gmataarestore=0; 195 196 PetscFunctionBegin; 197 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 198 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 199 if (!rank) { 200 ierr = PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);CHKERRQ(ierr); 201 if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name); 202 } 203 if (reuse == MAT_INITIAL_MATRIX) { 204 ierr = MatCreate(comm,&mat);CHKERRQ(ierr); 205 ierr = MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 206 if (!rank) { 207 bses[0] = gmat->rmap->bs; 208 bses[1] = gmat->cmap->bs; 209 } 210 ierr = MPI_Bcast(bses,2,MPIU_INT,0,comm);CHKERRQ(ierr); 211 ierr = MatSetBlockSizes(mat,bses[0],bses[1]);CHKERRQ(ierr); 212 ierr = MatSetType(mat,MATAIJ);CHKERRQ(ierr); 213 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 214 ierr = PetscMalloc2(m,PetscInt,&dlens,m,PetscInt,&olens);CHKERRQ(ierr); 215 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 216 217 rowners[0] = 0; 218 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 219 rstart = rowners[rank]; 220 rend = rowners[rank+1]; 221 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 222 if (!rank) { 223 gmata = (Mat_SeqAIJ*) gmat->data; 224 /* send row lengths to all processors */ 225 for (i=0; i<m; i++) dlens[i] = gmata->ilen[i]; 226 for (i=1; i<size; i++) { 227 ierr = MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 228 } 229 /* determine number diagonal and off-diagonal counts */ 230 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 231 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 232 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 233 jj = 0; 234 for (i=0; i<m; i++) { 235 for (j=0; j<dlens[i]; j++) { 236 if (gmata->j[jj] < rstart) ld[i]++; 237 if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++; 238 jj++; 239 } 240 } 241 /* send column indices to other processes */ 242 for (i=1; i<size; i++) { 243 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 244 ierr = MPI_Send(&nz,1,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 245 ierr = MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 246 } 247 248 /* send numerical values to other processes */ 249 for (i=1; i<size; i++) { 250 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 251 ierr = MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 252 } 253 gmataa = gmata->a; 254 gmataj = gmata->j; 255 256 } else { 257 /* receive row lengths */ 258 ierr = MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 259 /* receive column indices */ 260 ierr = MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 261 ierr = PetscMalloc2(nz,PetscScalar,&gmataa,nz,PetscInt,&gmataj);CHKERRQ(ierr); 262 ierr = MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 263 /* determine number diagonal and off-diagonal counts */ 264 ierr = PetscMemzero(olens,m*sizeof(PetscInt));CHKERRQ(ierr); 265 ierr = PetscMalloc(m*sizeof(PetscInt),&ld);CHKERRQ(ierr); 266 ierr = PetscMemzero(ld,m*sizeof(PetscInt));CHKERRQ(ierr); 267 jj = 0; 268 for (i=0; i<m; i++) { 269 for (j=0; j<dlens[i]; j++) { 270 if (gmataj[jj] < rstart) ld[i]++; 271 if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++; 272 jj++; 273 } 274 } 275 /* receive numerical values */ 276 ierr = PetscMemzero(gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 277 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 278 } 279 /* set preallocation */ 280 for (i=0; i<m; i++) { 281 dlens[i] -= olens[i]; 282 } 283 ierr = MatSeqAIJSetPreallocation(mat,0,dlens);CHKERRQ(ierr); 284 ierr = MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);CHKERRQ(ierr); 285 286 for (i=0; i<m; i++) { 287 dlens[i] += olens[i]; 288 } 289 cnt = 0; 290 for (i=0; i<m; i++) { 291 row = rstart + i; 292 ierr = MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);CHKERRQ(ierr); 293 cnt += dlens[i]; 294 } 295 if (rank) { 296 ierr = PetscFree2(gmataa,gmataj);CHKERRQ(ierr); 297 } 298 ierr = PetscFree2(dlens,olens);CHKERRQ(ierr); 299 ierr = PetscFree(rowners);CHKERRQ(ierr); 300 301 ((Mat_MPIAIJ*)(mat->data))->ld = ld; 302 303 *inmat = mat; 304 } else { /* column indices are already set; only need to move over numerical values from process 0 */ 305 Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data; 306 Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data; 307 mat = *inmat; 308 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag);CHKERRQ(ierr); 309 if (!rank) { 310 /* send numerical values to other processes */ 311 gmata = (Mat_SeqAIJ*) gmat->data; 312 ierr = MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);CHKERRQ(ierr); 313 gmataa = gmata->a; 314 for (i=1; i<size; i++) { 315 nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]]; 316 ierr = MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);CHKERRQ(ierr); 317 } 318 nz = gmata->i[rowners[1]]-gmata->i[rowners[0]]; 319 } else { 320 /* receive numerical values from process 0*/ 321 nz = Ad->nz + Ao->nz; 322 ierr = PetscMalloc(nz*sizeof(PetscScalar),&gmataa);CHKERRQ(ierr); gmataarestore = gmataa; 323 ierr = MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);CHKERRQ(ierr); 324 } 325 /* transfer numerical values into the diagonal A and off diagonal B parts of mat */ 326 ld = ((Mat_MPIAIJ*)(mat->data))->ld; 327 ad = Ad->a; 328 ao = Ao->a; 329 if (mat->rmap->n) { 330 i = 0; 331 nz = ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 332 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 333 } 334 for (i=1; i<mat->rmap->n; i++) { 335 nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ao += nz; gmataa += nz; 336 nz = Ad->i[i+1] - Ad->i[i]; ierr = PetscMemcpy(ad,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); ad += nz; gmataa += nz; 337 } 338 i--; 339 if (mat->rmap->n) { 340 nz = Ao->i[i+1] - Ao->i[i] - ld[i]; ierr = PetscMemcpy(ao,gmataa,nz*sizeof(PetscScalar));CHKERRQ(ierr); 341 } 342 if (rank) { 343 ierr = PetscFree(gmataarestore);CHKERRQ(ierr); 344 } 345 } 346 ierr = MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 347 ierr = MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 348 PetscFunctionReturn(0); 349 } 350 351 /* 352 Local utility routine that creates a mapping from the global column 353 number to the local number in the off-diagonal part of the local 354 storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at 355 a slightly higher hash table cost; without it it is not scalable (each processor 356 has an order N integer array but is fast to acess. 357 */ 358 #undef __FUNCT__ 359 #define __FUNCT__ "MatCreateColmap_MPIAIJ_Private" 360 PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat) 361 { 362 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 363 PetscErrorCode ierr; 364 PetscInt n = aij->B->cmap->n,i; 365 366 PetscFunctionBegin; 367 if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray"); 368 #if defined(PETSC_USE_CTABLE) 369 ierr = PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);CHKERRQ(ierr); 370 for (i=0; i<n; i++) { 371 ierr = PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 372 } 373 #else 374 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscInt),&aij->colmap);CHKERRQ(ierr); 375 ierr = PetscLogObjectMemory(mat,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 376 ierr = PetscMemzero(aij->colmap,mat->cmap->N*sizeof(PetscInt));CHKERRQ(ierr); 377 for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1; 378 #endif 379 PetscFunctionReturn(0); 380 } 381 382 #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \ 383 { \ 384 if (col <= lastcol1) low1 = 0; \ 385 else high1 = nrow1; \ 386 lastcol1 = col;\ 387 while (high1-low1 > 5) { \ 388 t = (low1+high1)/2; \ 389 if (rp1[t] > col) high1 = t; \ 390 else low1 = t; \ 391 } \ 392 for (_i=low1; _i<high1; _i++) { \ 393 if (rp1[_i] > col) break; \ 394 if (rp1[_i] == col) { \ 395 if (addv == ADD_VALUES) ap1[_i] += value; \ 396 else ap1[_i] = value; \ 397 goto a_noinsert; \ 398 } \ 399 } \ 400 if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \ 401 if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \ 402 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 403 MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \ 404 N = nrow1++ - 1; a->nz++; high1++; \ 405 /* shift up all the later entries in this row */ \ 406 for (ii=N; ii>=_i; ii--) { \ 407 rp1[ii+1] = rp1[ii]; \ 408 ap1[ii+1] = ap1[ii]; \ 409 } \ 410 rp1[_i] = col; \ 411 ap1[_i] = value; \ 412 a_noinsert: ; \ 413 ailen[row] = nrow1; \ 414 } 415 416 417 #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \ 418 { \ 419 if (col <= lastcol2) low2 = 0; \ 420 else high2 = nrow2; \ 421 lastcol2 = col; \ 422 while (high2-low2 > 5) { \ 423 t = (low2+high2)/2; \ 424 if (rp2[t] > col) high2 = t; \ 425 else low2 = t; \ 426 } \ 427 for (_i=low2; _i<high2; _i++) { \ 428 if (rp2[_i] > col) break; \ 429 if (rp2[_i] == col) { \ 430 if (addv == ADD_VALUES) ap2[_i] += value; \ 431 else ap2[_i] = value; \ 432 goto b_noinsert; \ 433 } \ 434 } \ 435 if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 436 if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \ 437 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \ 438 MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \ 439 N = nrow2++ - 1; b->nz++; high2++; \ 440 /* shift up all the later entries in this row */ \ 441 for (ii=N; ii>=_i; ii--) { \ 442 rp2[ii+1] = rp2[ii]; \ 443 ap2[ii+1] = ap2[ii]; \ 444 } \ 445 rp2[_i] = col; \ 446 ap2[_i] = value; \ 447 b_noinsert: ; \ 448 bilen[row] = nrow2; \ 449 } 450 451 #undef __FUNCT__ 452 #define __FUNCT__ "MatSetValuesRow_MPIAIJ" 453 PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[]) 454 { 455 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 456 Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data; 457 PetscErrorCode ierr; 458 PetscInt l,*garray = mat->garray,diag; 459 460 PetscFunctionBegin; 461 /* code only works for square matrices A */ 462 463 /* find size of row to the left of the diagonal part */ 464 ierr = MatGetOwnershipRange(A,&diag,0);CHKERRQ(ierr); 465 row = row - diag; 466 for (l=0; l<b->i[row+1]-b->i[row]; l++) { 467 if (garray[b->j[b->i[row]+l]] > diag) break; 468 } 469 ierr = PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));CHKERRQ(ierr); 470 471 /* diagonal part */ 472 ierr = PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));CHKERRQ(ierr); 473 474 /* right of diagonal part */ 475 ierr = PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));CHKERRQ(ierr); 476 PetscFunctionReturn(0); 477 } 478 479 #undef __FUNCT__ 480 #define __FUNCT__ "MatSetValues_MPIAIJ" 481 PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv) 482 { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 484 PetscScalar value; 485 PetscErrorCode ierr; 486 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 487 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 488 PetscBool roworiented = aij->roworiented; 489 490 /* Some Variables required in the macro */ 491 Mat A = aij->A; 492 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 493 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 494 MatScalar *aa = a->a; 495 PetscBool ignorezeroentries = a->ignorezeroentries; 496 Mat B = aij->B; 497 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 498 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 499 MatScalar *ba = b->a; 500 501 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 502 PetscInt nonew; 503 MatScalar *ap1,*ap2; 504 505 PetscFunctionBegin; 506 if (v) PetscValidScalarPointer(v,6); 507 for (i=0; i<m; i++) { 508 if (im[i] < 0) continue; 509 #if defined(PETSC_USE_DEBUG) 510 if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1); 511 #endif 512 if (im[i] >= rstart && im[i] < rend) { 513 row = im[i] - rstart; 514 lastcol1 = -1; 515 rp1 = aj + ai[row]; 516 ap1 = aa + ai[row]; 517 rmax1 = aimax[row]; 518 nrow1 = ailen[row]; 519 low1 = 0; 520 high1 = nrow1; 521 lastcol2 = -1; 522 rp2 = bj + bi[row]; 523 ap2 = ba + bi[row]; 524 rmax2 = bimax[row]; 525 nrow2 = bilen[row]; 526 low2 = 0; 527 high2 = nrow2; 528 529 for (j=0; j<n; j++) { 530 if (v) { 531 if (roworiented) value = v[i*n+j]; 532 else value = v[i+j*m]; 533 } else value = 0.0; 534 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 535 if (in[j] >= cstart && in[j] < cend) { 536 col = in[j] - cstart; 537 nonew = a->nonew; 538 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 539 } else if (in[j] < 0) continue; 540 #if defined(PETSC_USE_DEBUG) 541 else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1); 542 #endif 543 else { 544 if (mat->was_assembled) { 545 if (!aij->colmap) { 546 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 547 } 548 #if defined(PETSC_USE_CTABLE) 549 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 550 col--; 551 #else 552 col = aij->colmap[in[j]] - 1; 553 #endif 554 if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) { 555 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 556 col = in[j]; 557 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 558 B = aij->B; 559 b = (Mat_SeqAIJ*)B->data; 560 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a; 561 rp2 = bj + bi[row]; 562 ap2 = ba + bi[row]; 563 rmax2 = bimax[row]; 564 nrow2 = bilen[row]; 565 low2 = 0; 566 high2 = nrow2; 567 bm = aij->B->rmap->n; 568 ba = b->a; 569 } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]); 570 } else col = in[j]; 571 nonew = b->nonew; 572 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 573 } 574 } 575 } else { 576 if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]); 577 if (!aij->donotstash) { 578 mat->assembled = PETSC_FALSE; 579 if (roworiented) { 580 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 581 } else { 582 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 583 } 584 } 585 } 586 } 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNCT__ 591 #define __FUNCT__ "MatGetValues_MPIAIJ" 592 PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 593 { 594 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 595 PetscErrorCode ierr; 596 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 597 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 598 599 PetscFunctionBegin; 600 for (i=0; i<m; i++) { 601 if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/ 602 if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1); 603 if (idxm[i] >= rstart && idxm[i] < rend) { 604 row = idxm[i] - rstart; 605 for (j=0; j<n; j++) { 606 if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */ 607 if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1); 608 if (idxn[j] >= cstart && idxn[j] < cend) { 609 col = idxn[j] - cstart; 610 ierr = MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 611 } else { 612 if (!aij->colmap) { 613 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 614 } 615 #if defined(PETSC_USE_CTABLE) 616 ierr = PetscTableFind(aij->colmap,idxn[j]+1,&col);CHKERRQ(ierr); 617 col--; 618 #else 619 col = aij->colmap[idxn[j]] - 1; 620 #endif 621 if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0; 622 else { 623 ierr = MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 624 } 625 } 626 } 627 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 628 } 629 PetscFunctionReturn(0); 630 } 631 632 extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec); 633 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatAssemblyBegin_MPIAIJ" 636 PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode) 637 { 638 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 639 PetscErrorCode ierr; 640 PetscInt nstash,reallocs; 641 InsertMode addv; 642 643 PetscFunctionBegin; 644 if (aij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0); 645 646 /* make sure all processors are either in INSERTMODE or ADDMODE */ 647 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 648 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 649 mat->insertmode = addv; /* in case this processor had no cache */ 650 651 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 652 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 653 ierr = PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 654 PetscFunctionReturn(0); 655 } 656 657 #undef __FUNCT__ 658 #define __FUNCT__ "MatAssemblyEnd_MPIAIJ" 659 PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode) 660 { 661 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data; 663 PetscErrorCode ierr; 664 PetscMPIInt n; 665 PetscInt i,j,rstart,ncols,flg; 666 PetscInt *row,*col; 667 PetscBool other_disassembled; 668 PetscScalar *val; 669 InsertMode addv = mat->insertmode; 670 671 /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */ 672 673 PetscFunctionBegin; 674 if (!aij->donotstash && !mat->nooffprocentries) { 675 while (1) { 676 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 677 if (!flg) break; 678 679 for (i=0; i<n; ) { 680 /* Now identify the consecutive vals belonging to the same row */ 681 for (j=i,rstart=row[j]; j<n; j++) { 682 if (row[j] != rstart) break; 683 } 684 if (j < n) ncols = j-i; 685 else ncols = n-i; 686 /* Now assemble all these values with a single function call */ 687 ierr = MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 688 689 i = j; 690 } 691 } 692 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 693 } 694 ierr = MatAssemblyBegin(aij->A,mode);CHKERRQ(ierr); 695 ierr = MatAssemblyEnd(aij->A,mode);CHKERRQ(ierr); 696 697 /* determine if any processor has disassembled, if so we must 698 also disassemble ourselfs, in order that we may reassemble. */ 699 /* 700 if nonzero structure of submatrix B cannot change then we know that 701 no processor disassembled thus we can skip this stuff 702 */ 703 if (!((Mat_SeqAIJ*)aij->B->data)->nonew) { 704 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 705 if (mat->was_assembled && !other_disassembled) { 706 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 707 } 708 } 709 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 710 ierr = MatSetUpMultiply_MPIAIJ(mat);CHKERRQ(ierr); 711 } 712 ierr = MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);CHKERRQ(ierr); 713 ierr = MatSetOption(aij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr); 714 ierr = MatAssemblyBegin(aij->B,mode);CHKERRQ(ierr); 715 ierr = MatAssemblyEnd(aij->B,mode);CHKERRQ(ierr); 716 717 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 718 719 aij->rowvalues = 0; 720 721 /* used by MatAXPY() */ 722 a->xtoy = 0; ((Mat_SeqAIJ*)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */ 723 a->XtoY = 0; ((Mat_SeqAIJ*)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */ 724 725 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 726 if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNCT__ 731 #define __FUNCT__ "MatZeroEntries_MPIAIJ" 732 PetscErrorCode MatZeroEntries_MPIAIJ(Mat A) 733 { 734 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 735 PetscErrorCode ierr; 736 737 PetscFunctionBegin; 738 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 739 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 740 PetscFunctionReturn(0); 741 } 742 743 #undef __FUNCT__ 744 #define __FUNCT__ "MatZeroRows_MPIAIJ" 745 PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 746 { 747 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 748 PetscErrorCode ierr; 749 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 750 PetscInt i,*owners = A->rmap->range; 751 PetscInt *nprocs,j,idx,nsends,row; 752 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 753 PetscInt *rvalues,count,base,slen,*source; 754 PetscInt *lens,*lrows,*values,rstart=A->rmap->rstart; 755 MPI_Comm comm; 756 MPI_Request *send_waits,*recv_waits; 757 MPI_Status recv_status,*send_status; 758 const PetscScalar *xx; 759 PetscScalar *bb; 760 #if defined(PETSC_DEBUG) 761 PetscBool found = PETSC_FALSE; 762 #endif 763 764 PetscFunctionBegin; 765 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 766 /* first count number of contributors to each processor */ 767 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 768 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 769 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 770 j = 0; 771 for (i=0; i<N; i++) { 772 if (lastidx > (idx = rows[i])) j = 0; 773 lastidx = idx; 774 for (; j<size; j++) { 775 if (idx >= owners[j] && idx < owners[j+1]) { 776 nprocs[2*j]++; 777 nprocs[2*j+1] = 1; 778 owner[i] = j; 779 #if defined(PETSC_DEBUG) 780 found = PETSC_TRUE; 781 #endif 782 break; 783 } 784 } 785 #if defined(PETSC_DEBUG) 786 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 787 found = PETSC_FALSE; 788 #endif 789 } 790 nsends = 0; 791 for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 792 793 if (A->nooffproczerorows) { 794 if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row"); 795 nrecvs = nsends; 796 nmax = N; 797 } else { 798 /* inform other processors of number of messages and max length*/ 799 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 800 } 801 802 /* post receives: */ 803 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 804 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 805 for (i=0; i<nrecvs; i++) { 806 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 807 } 808 809 /* do sends: 810 1) starts[i] gives the starting index in svalues for stuff going to 811 the ith processor 812 */ 813 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 814 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 815 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 816 817 starts[0] = 0; 818 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 819 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 820 821 starts[0] = 0; 822 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 823 count = 0; 824 for (i=0; i<size; i++) { 825 if (nprocs[2*i+1]) { 826 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 827 } 828 } 829 ierr = PetscFree(starts);CHKERRQ(ierr); 830 831 base = owners[rank]; 832 833 /* wait on receives */ 834 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 835 count = nrecvs; slen = 0; 836 while (count) { 837 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 838 /* unpack receives into our local space */ 839 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 840 841 source[imdex] = recv_status.MPI_SOURCE; 842 lens[imdex] = n; 843 slen += n; 844 count--; 845 } 846 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 847 848 /* move the data into the send scatter */ 849 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 850 count = 0; 851 for (i=0; i<nrecvs; i++) { 852 values = rvalues + i*nmax; 853 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 854 } 855 ierr = PetscFree(rvalues);CHKERRQ(ierr); 856 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 857 ierr = PetscFree(owner);CHKERRQ(ierr); 858 ierr = PetscFree(nprocs);CHKERRQ(ierr); 859 860 /* fix right hand side if needed */ 861 if (x && b) { 862 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 863 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 864 for (i=0; i<slen; i++) bb[lrows[i]] = diag*xx[lrows[i]]; 865 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 866 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 867 } 868 /* 869 Zero the required rows. If the "diagonal block" of the matrix 870 is square and the user wishes to set the diagonal we use separate 871 code so that MatSetValues() is not called for each diagonal allocating 872 new memory, thus calling lots of mallocs and slowing things down. 873 874 */ 875 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 876 ierr = MatZeroRows(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr); 877 if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) { 878 ierr = MatZeroRows(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr); 879 } else if (diag != 0.0) { 880 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 881 if (((Mat_SeqAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\nMAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 882 for (i = 0; i < slen; i++) { 883 row = lrows[i] + rstart; 884 ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr); 885 } 886 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 887 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 888 } else { 889 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 890 } 891 ierr = PetscFree(lrows);CHKERRQ(ierr); 892 893 /* wait on sends */ 894 if (nsends) { 895 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 896 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 897 ierr = PetscFree(send_status);CHKERRQ(ierr); 898 } 899 ierr = PetscFree(send_waits);CHKERRQ(ierr); 900 ierr = PetscFree(svalues);CHKERRQ(ierr); 901 PetscFunctionReturn(0); 902 } 903 904 #undef __FUNCT__ 905 #define __FUNCT__ "MatZeroRowsColumns_MPIAIJ" 906 PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 907 { 908 Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data; 909 PetscErrorCode ierr; 910 PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = ((PetscObject)A)->tag,lastidx = -1; 911 PetscInt i,*owners = A->rmap->range; 912 PetscInt *nprocs,j,idx,nsends; 913 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 914 PetscInt *rvalues,count,base,slen,*source; 915 PetscInt *lens,*lrows,*values,m; 916 MPI_Comm comm; 917 MPI_Request *send_waits,*recv_waits; 918 MPI_Status recv_status,*send_status; 919 const PetscScalar *xx; 920 PetscScalar *bb,*mask; 921 Vec xmask,lmask; 922 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data; 923 const PetscInt *aj, *ii,*ridx; 924 PetscScalar *aa; 925 #if defined(PETSC_DEBUG) 926 PetscBool found = PETSC_FALSE; 927 #endif 928 929 PetscFunctionBegin; 930 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 931 /* first count number of contributors to each processor */ 932 ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr); 933 ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr); 934 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr); /* see note*/ 935 j = 0; 936 for (i=0; i<N; i++) { 937 if (lastidx > (idx = rows[i])) j = 0; 938 lastidx = idx; 939 for (; j<size; j++) { 940 if (idx >= owners[j] && idx < owners[j+1]) { 941 nprocs[2*j]++; 942 nprocs[2*j+1] = 1; 943 owner[i] = j; 944 #if defined(PETSC_DEBUG) 945 found = PETSC_TRUE; 946 #endif 947 break; 948 } 949 } 950 #if defined(PETSC_DEBUG) 951 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 952 found = PETSC_FALSE; 953 #endif 954 } 955 nsends = 0; for (i=0; i<size; i++) nsends += nprocs[2*i+1]; 956 957 /* inform other processors of number of messages and max length*/ 958 ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr); 959 960 /* post receives: */ 961 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr); 962 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr); 963 for (i=0; i<nrecvs; i++) { 964 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 965 } 966 967 /* do sends: 968 1) starts[i] gives the starting index in svalues for stuff going to 969 the ith processor 970 */ 971 ierr = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr); 972 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr); 973 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr); 974 975 starts[0] = 0; 976 for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 977 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 978 979 starts[0] = 0; 980 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2]; 981 count = 0; 982 for (i=0; i<size; i++) { 983 if (nprocs[2*i+1]) { 984 ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 985 } 986 } 987 ierr = PetscFree(starts);CHKERRQ(ierr); 988 989 base = owners[rank]; 990 991 /* wait on receives */ 992 ierr = PetscMalloc2(nrecvs,PetscInt,&lens,nrecvs,PetscInt,&source);CHKERRQ(ierr); 993 count = nrecvs; slen = 0; 994 while (count) { 995 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 996 /* unpack receives into our local space */ 997 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 998 999 source[imdex] = recv_status.MPI_SOURCE; 1000 lens[imdex] = n; 1001 slen += n; 1002 count--; 1003 } 1004 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1005 1006 /* move the data into the send scatter */ 1007 ierr = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr); 1008 count = 0; 1009 for (i=0; i<nrecvs; i++) { 1010 values = rvalues + i*nmax; 1011 for (j=0; j<lens[i]; j++) lrows[count++] = values[j] - base; 1012 } 1013 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1014 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 1015 ierr = PetscFree(owner);CHKERRQ(ierr); 1016 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1017 /* lrows are the local rows to be zeroed, slen is the number of local rows */ 1018 1019 /* zero diagonal part of matrix */ 1020 ierr = MatZeroRowsColumns(l->A,slen,lrows,diag,x,b);CHKERRQ(ierr); 1021 1022 /* handle off diagonal part of matrix */ 1023 ierr = MatGetVecs(A,&xmask,NULL);CHKERRQ(ierr); 1024 ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr); 1025 ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr); 1026 for (i=0; i<slen; i++) bb[lrows[i]] = 1; 1027 ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr); 1028 ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1029 ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1030 ierr = VecDestroy(&xmask);CHKERRQ(ierr); 1031 if (x) { 1032 ierr = VecScatterBegin(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1033 ierr = VecScatterEnd(l->Mvctx,x,l->lvec,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1034 ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1035 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1036 } 1037 ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr); 1038 1039 /* remove zeroed rows of off diagonal matrix */ 1040 ii = aij->i; 1041 for (i=0; i<slen; i++) { 1042 ierr = PetscMemzero(aij->a + ii[lrows[i]],(ii[lrows[i]+1] - ii[lrows[i]])*sizeof(PetscScalar));CHKERRQ(ierr); 1043 } 1044 1045 /* loop over all elements of off process part of matrix zeroing removed columns*/ 1046 if (aij->compressedrow.use) { 1047 m = aij->compressedrow.nrows; 1048 ii = aij->compressedrow.i; 1049 ridx = aij->compressedrow.rindex; 1050 for (i=0; i<m; i++) { 1051 n = ii[i+1] - ii[i]; 1052 aj = aij->j + ii[i]; 1053 aa = aij->a + ii[i]; 1054 1055 for (j=0; j<n; j++) { 1056 if (PetscAbsScalar(mask[*aj])) { 1057 if (b) bb[*ridx] -= *aa*xx[*aj]; 1058 *aa = 0.0; 1059 } 1060 aa++; 1061 aj++; 1062 } 1063 ridx++; 1064 } 1065 } else { /* do not use compressed row format */ 1066 m = l->B->rmap->n; 1067 for (i=0; i<m; i++) { 1068 n = ii[i+1] - ii[i]; 1069 aj = aij->j + ii[i]; 1070 aa = aij->a + ii[i]; 1071 for (j=0; j<n; j++) { 1072 if (PetscAbsScalar(mask[*aj])) { 1073 if (b) bb[i] -= *aa*xx[*aj]; 1074 *aa = 0.0; 1075 } 1076 aa++; 1077 aj++; 1078 } 1079 } 1080 } 1081 if (x) { 1082 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1083 ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr); 1084 } 1085 ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr); 1086 ierr = VecDestroy(&lmask);CHKERRQ(ierr); 1087 ierr = PetscFree(lrows);CHKERRQ(ierr); 1088 1089 /* wait on sends */ 1090 if (nsends) { 1091 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr); 1092 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1093 ierr = PetscFree(send_status);CHKERRQ(ierr); 1094 } 1095 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1096 ierr = PetscFree(svalues);CHKERRQ(ierr); 1097 PetscFunctionReturn(0); 1098 } 1099 1100 #undef __FUNCT__ 1101 #define __FUNCT__ "MatMult_MPIAIJ" 1102 PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy) 1103 { 1104 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt nt; 1107 1108 PetscFunctionBegin; 1109 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1110 if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt); 1111 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1112 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 1113 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1114 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 1115 PetscFunctionReturn(0); 1116 } 1117 1118 #undef __FUNCT__ 1119 #define __FUNCT__ "MatMultDiagonalBlock_MPIAIJ" 1120 PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx) 1121 { 1122 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1123 PetscErrorCode ierr; 1124 1125 PetscFunctionBegin; 1126 ierr = MatMultDiagonalBlock(a->A,bb,xx);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 #undef __FUNCT__ 1131 #define __FUNCT__ "MatMultAdd_MPIAIJ" 1132 PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1133 { 1134 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1139 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1140 ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1141 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 1142 PetscFunctionReturn(0); 1143 } 1144 1145 #undef __FUNCT__ 1146 #define __FUNCT__ "MatMultTranspose_MPIAIJ" 1147 PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy) 1148 { 1149 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1150 PetscErrorCode ierr; 1151 PetscBool merged; 1152 1153 PetscFunctionBegin; 1154 ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr); 1155 /* do nondiagonal part */ 1156 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1157 if (!merged) { 1158 /* send it on its way */ 1159 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1160 /* do local part */ 1161 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1162 /* receive remote parts: note this assumes the values are not actually */ 1163 /* added in yy until the next line, */ 1164 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1165 } else { 1166 /* do local part */ 1167 ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr); 1168 /* send it on its way */ 1169 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1170 /* values actually were received in the Begin() but we need to call this nop */ 1171 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1172 } 1173 PetscFunctionReturn(0); 1174 } 1175 1176 #undef __FUNCT__ 1177 #define __FUNCT__ "MatIsTranspose_MPIAIJ" 1178 PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f) 1179 { 1180 MPI_Comm comm; 1181 Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij; 1182 Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs; 1183 IS Me,Notme; 1184 PetscErrorCode ierr; 1185 PetscInt M,N,first,last,*notme,i; 1186 PetscMPIInt size; 1187 1188 PetscFunctionBegin; 1189 /* Easy test: symmetric diagonal block */ 1190 Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A; 1191 ierr = MatIsTranspose(Adia,Bdia,tol,f);CHKERRQ(ierr); 1192 if (!*f) PetscFunctionReturn(0); 1193 ierr = PetscObjectGetComm((PetscObject)Amat,&comm);CHKERRQ(ierr); 1194 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1195 if (size == 1) PetscFunctionReturn(0); 1196 1197 /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */ 1198 ierr = MatGetSize(Amat,&M,&N);CHKERRQ(ierr); 1199 ierr = MatGetOwnershipRange(Amat,&first,&last);CHKERRQ(ierr); 1200 ierr = PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);CHKERRQ(ierr); 1201 for (i=0; i<first; i++) notme[i] = i; 1202 for (i=last; i<M; i++) notme[i-last+first] = i; 1203 ierr = ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);CHKERRQ(ierr); 1204 ierr = ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);CHKERRQ(ierr); 1205 ierr = MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);CHKERRQ(ierr); 1206 Aoff = Aoffs[0]; 1207 ierr = MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);CHKERRQ(ierr); 1208 Boff = Boffs[0]; 1209 ierr = MatIsTranspose(Aoff,Boff,tol,f);CHKERRQ(ierr); 1210 ierr = MatDestroyMatrices(1,&Aoffs);CHKERRQ(ierr); 1211 ierr = MatDestroyMatrices(1,&Boffs);CHKERRQ(ierr); 1212 ierr = ISDestroy(&Me);CHKERRQ(ierr); 1213 ierr = ISDestroy(&Notme);CHKERRQ(ierr); 1214 ierr = PetscFree(notme);CHKERRQ(ierr); 1215 PetscFunctionReturn(0); 1216 } 1217 1218 #undef __FUNCT__ 1219 #define __FUNCT__ "MatMultTransposeAdd_MPIAIJ" 1220 PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1221 { 1222 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1223 PetscErrorCode ierr; 1224 1225 PetscFunctionBegin; 1226 /* do nondiagonal part */ 1227 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 1228 /* send it on its way */ 1229 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1230 /* do local part */ 1231 ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 1232 /* receive remote parts */ 1233 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 1234 PetscFunctionReturn(0); 1235 } 1236 1237 /* 1238 This only works correctly for square matrices where the subblock A->A is the 1239 diagonal block 1240 */ 1241 #undef __FUNCT__ 1242 #define __FUNCT__ "MatGetDiagonal_MPIAIJ" 1243 PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v) 1244 { 1245 PetscErrorCode ierr; 1246 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1247 1248 PetscFunctionBegin; 1249 if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); 1250 if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition"); 1251 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1252 PetscFunctionReturn(0); 1253 } 1254 1255 #undef __FUNCT__ 1256 #define __FUNCT__ "MatScale_MPIAIJ" 1257 PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa) 1258 { 1259 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1260 PetscErrorCode ierr; 1261 1262 PetscFunctionBegin; 1263 ierr = MatScale(a->A,aa);CHKERRQ(ierr); 1264 ierr = MatScale(a->B,aa);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #undef __FUNCT__ 1269 #define __FUNCT__ "MatDestroy_MPIAIJ" 1270 PetscErrorCode MatDestroy_MPIAIJ(Mat mat) 1271 { 1272 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 #if defined(PETSC_USE_LOG) 1277 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 1278 #endif 1279 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 1280 ierr = VecDestroy(&aij->diag);CHKERRQ(ierr); 1281 ierr = MatDestroy(&aij->A);CHKERRQ(ierr); 1282 ierr = MatDestroy(&aij->B);CHKERRQ(ierr); 1283 #if defined(PETSC_USE_CTABLE) 1284 ierr = PetscTableDestroy(&aij->colmap);CHKERRQ(ierr); 1285 #else 1286 ierr = PetscFree(aij->colmap);CHKERRQ(ierr); 1287 #endif 1288 ierr = PetscFree(aij->garray);CHKERRQ(ierr); 1289 ierr = VecDestroy(&aij->lvec);CHKERRQ(ierr); 1290 ierr = VecScatterDestroy(&aij->Mvctx);CHKERRQ(ierr); 1291 ierr = PetscFree2(aij->rowvalues,aij->rowindices);CHKERRQ(ierr); 1292 ierr = PetscFree(aij->ld);CHKERRQ(ierr); 1293 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1294 1295 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1296 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1297 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1300 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1302 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr); 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);CHKERRQ(ierr); 1304 PetscFunctionReturn(0); 1305 } 1306 1307 #undef __FUNCT__ 1308 #define __FUNCT__ "MatView_MPIAIJ_Binary" 1309 PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer) 1310 { 1311 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1312 Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data; 1313 Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data; 1314 PetscErrorCode ierr; 1315 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 1316 int fd; 1317 PetscInt nz,header[4],*row_lengths,*range=0,rlen,i; 1318 PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz; 1319 PetscScalar *column_values; 1320 PetscInt message_count,flowcontrolcount; 1321 FILE *file; 1322 1323 PetscFunctionBegin; 1324 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1325 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 1326 nz = A->nz + B->nz; 1327 if (!rank) { 1328 header[0] = MAT_FILE_CLASSID; 1329 header[1] = mat->rmap->N; 1330 header[2] = mat->cmap->N; 1331 1332 ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1333 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1334 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1335 /* get largest number of rows any processor has */ 1336 rlen = mat->rmap->n; 1337 range = mat->rmap->range; 1338 for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]); 1339 } else { 1340 ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1341 rlen = mat->rmap->n; 1342 } 1343 1344 /* load up the local row counts */ 1345 ierr = PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);CHKERRQ(ierr); 1346 for (i=0; i<mat->rmap->n; i++) row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i]; 1347 1348 /* store the row lengths to the file */ 1349 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1350 if (!rank) { 1351 ierr = PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1352 for (i=1; i<size; i++) { 1353 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1354 rlen = range[i+1] - range[i]; 1355 ierr = MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1356 ierr = PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1357 } 1358 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1359 } else { 1360 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1361 ierr = MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1362 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1363 } 1364 ierr = PetscFree(row_lengths);CHKERRQ(ierr); 1365 1366 /* load up the local column indices */ 1367 nzmax = nz; /* th processor needs space a largest processor needs */ 1368 ierr = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1369 ierr = PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);CHKERRQ(ierr); 1370 cnt = 0; 1371 for (i=0; i<mat->rmap->n; i++) { 1372 for (j=B->i[i]; j<B->i[i+1]; j++) { 1373 if ((col = garray[B->j[j]]) > cstart) break; 1374 column_indices[cnt++] = col; 1375 } 1376 for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart; 1377 for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]]; 1378 } 1379 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1380 1381 /* store the column indices to the file */ 1382 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1383 if (!rank) { 1384 MPI_Status status; 1385 ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1386 for (i=1; i<size; i++) { 1387 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1388 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1389 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1390 ierr = MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1391 ierr = PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1392 } 1393 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1394 } else { 1395 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1396 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1397 ierr = MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1398 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1399 } 1400 ierr = PetscFree(column_indices);CHKERRQ(ierr); 1401 1402 /* load up the local column values */ 1403 ierr = PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);CHKERRQ(ierr); 1404 cnt = 0; 1405 for (i=0; i<mat->rmap->n; i++) { 1406 for (j=B->i[i]; j<B->i[i+1]; j++) { 1407 if (garray[B->j[j]] > cstart) break; 1408 column_values[cnt++] = B->a[j]; 1409 } 1410 for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k]; 1411 for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j]; 1412 } 1413 if (cnt != A->nz + B->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz); 1414 1415 /* store the column values to the file */ 1416 ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr); 1417 if (!rank) { 1418 MPI_Status status; 1419 ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1420 for (i=1; i<size; i++) { 1421 ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr); 1422 ierr = MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr); 1423 if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax); 1424 ierr = MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1425 ierr = PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr); 1426 } 1427 ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr); 1428 } else { 1429 ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr); 1430 ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1431 ierr = MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 1432 ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr); 1433 } 1434 ierr = PetscFree(column_values);CHKERRQ(ierr); 1435 1436 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 1437 if (file) fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs); 1438 PetscFunctionReturn(0); 1439 } 1440 1441 #include <petscdraw.h> 1442 #undef __FUNCT__ 1443 #define __FUNCT__ "MatView_MPIAIJ_ASCIIorDraworSocket" 1444 PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 1445 { 1446 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 1447 PetscErrorCode ierr; 1448 PetscMPIInt rank = aij->rank,size = aij->size; 1449 PetscBool isdraw,iascii,isbinary; 1450 PetscViewer sviewer; 1451 PetscViewerFormat format; 1452 1453 PetscFunctionBegin; 1454 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1455 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1456 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1457 if (iascii) { 1458 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1459 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1460 MatInfo info; 1461 PetscBool inodes; 1462 1463 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 1464 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 1465 ierr = MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);CHKERRQ(ierr); 1466 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 1467 if (!inodes) { 1468 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n", 1469 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1470 } else { 1471 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n", 1472 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 1473 } 1474 ierr = MatGetInfo(aij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 1475 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1476 ierr = MatGetInfo(aij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 1477 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr); 1478 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1479 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 1480 ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr); 1481 ierr = VecScatterView(aij->Mvctx,viewer);CHKERRQ(ierr); 1482 PetscFunctionReturn(0); 1483 } else if (format == PETSC_VIEWER_ASCII_INFO) { 1484 PetscInt inodecount,inodelimit,*inodes; 1485 ierr = MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);CHKERRQ(ierr); 1486 if (inodes) { 1487 ierr = PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);CHKERRQ(ierr); 1488 } else { 1489 ierr = PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");CHKERRQ(ierr); 1490 } 1491 PetscFunctionReturn(0); 1492 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) { 1493 PetscFunctionReturn(0); 1494 } 1495 } else if (isbinary) { 1496 if (size == 1) { 1497 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1498 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1499 } else { 1500 ierr = MatView_MPIAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1501 } 1502 PetscFunctionReturn(0); 1503 } else if (isdraw) { 1504 PetscDraw draw; 1505 PetscBool isnull; 1506 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1507 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1508 } 1509 1510 if (size == 1) { 1511 ierr = PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1512 ierr = MatView(aij->A,viewer);CHKERRQ(ierr); 1513 } else { 1514 /* assemble the entire matrix onto first processor. */ 1515 Mat A; 1516 Mat_SeqAIJ *Aloc; 1517 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,*ai,*aj,row,*cols,i,*ct; 1518 MatScalar *a; 1519 1520 if (mat->rmap->N > 1024) { 1521 PetscBool flg = PETSC_FALSE; 1522 1523 ierr = PetscOptionsGetBool(((PetscObject) mat)->prefix, "-mat_ascii_output_large", &flg,NULL);CHKERRQ(ierr); 1524 if (!flg) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_OUTOFRANGE,"ASCII matrix output not allowed for matrices with more than 1024 rows, use binary format instead.\nYou can override this restriction using -mat_ascii_output_large."); 1525 } 1526 1527 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 1528 if (!rank) { 1529 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 1530 } else { 1531 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 1532 } 1533 /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */ 1534 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 1535 ierr = MatMPIAIJSetPreallocation(A,0,NULL,0,NULL);CHKERRQ(ierr); 1536 ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 1537 ierr = PetscLogObjectParent(mat,A);CHKERRQ(ierr); 1538 1539 /* copy over the A part */ 1540 Aloc = (Mat_SeqAIJ*)aij->A->data; 1541 m = aij->A->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1542 row = mat->rmap->rstart; 1543 for (i=0; i<ai[m]; i++) aj[i] += mat->cmap->rstart; 1544 for (i=0; i<m; i++) { 1545 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);CHKERRQ(ierr); 1546 row++; 1547 a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i]; 1548 } 1549 aj = Aloc->j; 1550 for (i=0; i<ai[m]; i++) aj[i] -= mat->cmap->rstart; 1551 1552 /* copy over the B part */ 1553 Aloc = (Mat_SeqAIJ*)aij->B->data; 1554 m = aij->B->rmap->n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1555 row = mat->rmap->rstart; 1556 ierr = PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 1557 ct = cols; 1558 for (i=0; i<ai[m]; i++) cols[i] = aij->garray[aj[i]]; 1559 for (i=0; i<m; i++) { 1560 ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);CHKERRQ(ierr); 1561 row++; 1562 a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i]; 1563 } 1564 ierr = PetscFree(ct);CHKERRQ(ierr); 1565 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1566 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1567 /* 1568 Everyone has to call to draw the matrix since the graphics waits are 1569 synchronized across all processors that share the PetscDraw object 1570 */ 1571 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 1572 if (!rank) { 1573 ierr = PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 1574 /* Set the type name to MATMPIAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqAIJ_ASCII()*/ 1575 PetscStrcpy(((PetscObject)((Mat_MPIAIJ*)(A->data))->A)->type_name,MATMPIAIJ); 1576 ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 1577 } 1578 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 1579 ierr = MatDestroy(&A);CHKERRQ(ierr); 1580 } 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #undef __FUNCT__ 1585 #define __FUNCT__ "MatView_MPIAIJ" 1586 PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer) 1587 { 1588 PetscErrorCode ierr; 1589 PetscBool iascii,isdraw,issocket,isbinary; 1590 1591 PetscFunctionBegin; 1592 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1593 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1594 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1595 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 1596 if (iascii || isdraw || isbinary || issocket) { 1597 ierr = MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 1598 } 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #undef __FUNCT__ 1603 #define __FUNCT__ "MatSOR_MPIAIJ" 1604 PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1605 { 1606 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1607 PetscErrorCode ierr; 1608 Vec bb1 = 0; 1609 PetscBool hasop; 1610 1611 PetscFunctionBegin; 1612 if (flag == SOR_APPLY_UPPER) { 1613 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1614 PetscFunctionReturn(0); 1615 } 1616 1617 if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) { 1618 ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr); 1619 } 1620 1621 if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) { 1622 if (flag & SOR_ZERO_INITIAL_GUESS) { 1623 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1624 its--; 1625 } 1626 1627 while (its--) { 1628 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1629 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1630 1631 /* update rhs: bb1 = bb - B*x */ 1632 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1633 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1634 1635 /* local sweep */ 1636 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1637 } 1638 } else if (flag & SOR_LOCAL_FORWARD_SWEEP) { 1639 if (flag & SOR_ZERO_INITIAL_GUESS) { 1640 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1641 its--; 1642 } 1643 while (its--) { 1644 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1645 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1646 1647 /* update rhs: bb1 = bb - B*x */ 1648 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1649 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1650 1651 /* local sweep */ 1652 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1653 } 1654 } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) { 1655 if (flag & SOR_ZERO_INITIAL_GUESS) { 1656 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr); 1657 its--; 1658 } 1659 while (its--) { 1660 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1661 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1662 1663 /* update rhs: bb1 = bb - B*x */ 1664 ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr); 1665 ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr); 1666 1667 /* local sweep */ 1668 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr); 1669 } 1670 } else if (flag & SOR_EISENSTAT) { 1671 Vec xx1; 1672 1673 ierr = VecDuplicate(bb,&xx1);CHKERRQ(ierr); 1674 ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr); 1675 1676 ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1677 ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 1678 if (!mat->diag) { 1679 ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr); 1680 ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr); 1681 } 1682 ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr); 1683 if (hasop) { 1684 ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr); 1685 } else { 1686 ierr = VecPointwiseMult(bb1,mat->diag,xx);CHKERRQ(ierr); 1687 } 1688 ierr = VecAYPX(bb1,(omega-2.0)/omega,bb);CHKERRQ(ierr); 1689 1690 ierr = MatMultAdd(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr); 1691 1692 /* local sweep */ 1693 ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr); 1694 ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr); 1695 ierr = VecDestroy(&xx1);CHKERRQ(ierr); 1696 } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported"); 1697 1698 ierr = VecDestroy(&bb1);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatPermute_MPIAIJ" 1704 PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B) 1705 { 1706 Mat aA,aB,Aperm; 1707 const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj; 1708 PetscScalar *aa,*ba; 1709 PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest; 1710 PetscSF rowsf,sf; 1711 IS parcolp = NULL; 1712 PetscBool done; 1713 PetscErrorCode ierr; 1714 1715 PetscFunctionBegin; 1716 ierr = MatGetLocalSize(A,&m,&n);CHKERRQ(ierr); 1717 ierr = ISGetIndices(rowp,&rwant);CHKERRQ(ierr); 1718 ierr = ISGetIndices(colp,&cwant);CHKERRQ(ierr); 1719 ierr = PetscMalloc3(PetscMax(m,n),PetscInt,&work,m,PetscInt,&rdest,n,PetscInt,&cdest);CHKERRQ(ierr); 1720 1721 /* Invert row permutation to find out where my rows should go */ 1722 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);CHKERRQ(ierr); 1723 ierr = PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);CHKERRQ(ierr); 1724 ierr = PetscSFSetFromOptions(rowsf);CHKERRQ(ierr); 1725 for (i=0; i<m; i++) work[i] = A->rmap->rstart + i; 1726 ierr = PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1727 ierr = PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);CHKERRQ(ierr); 1728 1729 /* Invert column permutation to find out where my columns should go */ 1730 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1731 ierr = PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);CHKERRQ(ierr); 1732 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1733 for (i=0; i<n; i++) work[i] = A->cmap->rstart + i; 1734 ierr = PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1735 ierr = PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);CHKERRQ(ierr); 1736 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1737 1738 ierr = ISRestoreIndices(rowp,&rwant);CHKERRQ(ierr); 1739 ierr = ISRestoreIndices(colp,&cwant);CHKERRQ(ierr); 1740 ierr = MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);CHKERRQ(ierr); 1741 1742 /* Find out where my gcols should go */ 1743 ierr = MatGetSize(aB,NULL,&ng);CHKERRQ(ierr); 1744 ierr = PetscMalloc(ng*sizeof(PetscInt),&gcdest);CHKERRQ(ierr); 1745 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 1746 ierr = PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);CHKERRQ(ierr); 1747 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 1748 ierr = PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1749 ierr = PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);CHKERRQ(ierr); 1750 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 1751 1752 ierr = PetscMalloc4(m,PetscInt,&dnnz,m,PetscInt,&onnz,m,PetscInt,&tdnnz,m,PetscInt,&tonnz);CHKERRQ(ierr); 1753 ierr = PetscMemzero(dnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1754 ierr = PetscMemzero(onnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1755 ierr = MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1756 ierr = MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1757 for (i=0; i<m; i++) { 1758 PetscInt row = rdest[i],rowner; 1759 ierr = PetscLayoutFindOwner(A->rmap,row,&rowner);CHKERRQ(ierr); 1760 for (j=ai[i]; j<ai[i+1]; j++) { 1761 PetscInt cowner,col = cdest[aj[j]]; 1762 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); /* Could build an index for the columns to eliminate this search */ 1763 if (rowner == cowner) dnnz[i]++; 1764 else onnz[i]++; 1765 } 1766 for (j=bi[i]; j<bi[i+1]; j++) { 1767 PetscInt cowner,col = gcdest[bj[j]]; 1768 ierr = PetscLayoutFindOwner(A->cmap,col,&cowner);CHKERRQ(ierr); 1769 if (rowner == cowner) dnnz[i]++; 1770 else onnz[i]++; 1771 } 1772 } 1773 ierr = PetscMemzero(tdnnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1774 ierr = PetscMemzero(tonnz,m*sizeof(PetscInt));CHKERRQ(ierr); 1775 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1776 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);CHKERRQ(ierr); 1777 ierr = PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1778 ierr = PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);CHKERRQ(ierr); 1779 ierr = PetscSFDestroy(&rowsf);CHKERRQ(ierr); 1780 1781 ierr = MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);CHKERRQ(ierr); 1782 ierr = MatSeqAIJGetArray(aA,&aa);CHKERRQ(ierr); 1783 ierr = MatSeqAIJGetArray(aB,&ba);CHKERRQ(ierr); 1784 for (i=0; i<m; i++) { 1785 PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */ 1786 PetscInt rowlen; 1787 rowlen = ai[i+1] - ai[i]; 1788 for (j=0; j<rowlen; j++) acols[j] = cdest[aj[ai[i]+j]]; 1789 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,acols,aa+ai[i],INSERT_VALUES);CHKERRQ(ierr); 1790 rowlen = bi[i+1] - bi[i]; 1791 for (j=0; j<rowlen; j++) bcols[j] = gcdest[bj[bi[i]+j]]; 1792 ierr = MatSetValues(Aperm,1,&rdest[i],rowlen,bcols,ba+bi[i],INSERT_VALUES);CHKERRQ(ierr); 1793 } 1794 ierr = MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1795 ierr = MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1796 ierr = MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);CHKERRQ(ierr); 1797 ierr = MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);CHKERRQ(ierr); 1798 ierr = MatSeqAIJRestoreArray(aA,&aa);CHKERRQ(ierr); 1799 ierr = MatSeqAIJRestoreArray(aB,&ba);CHKERRQ(ierr); 1800 ierr = PetscFree4(dnnz,onnz,tdnnz,tonnz);CHKERRQ(ierr); 1801 ierr = PetscFree3(work,rdest,cdest);CHKERRQ(ierr); 1802 ierr = PetscFree(gcdest);CHKERRQ(ierr); 1803 if (parcolp) {ierr = ISDestroy(&colp);CHKERRQ(ierr);} 1804 *B = Aperm; 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_MPIAIJ" 1810 PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1813 Mat A = mat->A,B = mat->B; 1814 PetscErrorCode ierr; 1815 PetscReal isend[5],irecv[5]; 1816 1817 PetscFunctionBegin; 1818 info->block_size = 1.0; 1819 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1820 1821 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1822 isend[3] = info->memory; isend[4] = info->mallocs; 1823 1824 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1825 1826 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1827 isend[3] += info->memory; isend[4] += info->mallocs; 1828 if (flag == MAT_LOCAL) { 1829 info->nz_used = isend[0]; 1830 info->nz_allocated = isend[1]; 1831 info->nz_unneeded = isend[2]; 1832 info->memory = isend[3]; 1833 info->mallocs = isend[4]; 1834 } else if (flag == MAT_GLOBAL_MAX) { 1835 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1836 1837 info->nz_used = irecv[0]; 1838 info->nz_allocated = irecv[1]; 1839 info->nz_unneeded = irecv[2]; 1840 info->memory = irecv[3]; 1841 info->mallocs = irecv[4]; 1842 } else if (flag == MAT_GLOBAL_SUM) { 1843 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr); 1844 1845 info->nz_used = irecv[0]; 1846 info->nz_allocated = irecv[1]; 1847 info->nz_unneeded = irecv[2]; 1848 info->memory = irecv[3]; 1849 info->mallocs = irecv[4]; 1850 } 1851 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1852 info->fill_ratio_needed = 0; 1853 info->factor_mallocs = 0; 1854 PetscFunctionReturn(0); 1855 } 1856 1857 #undef __FUNCT__ 1858 #define __FUNCT__ "MatSetOption_MPIAIJ" 1859 PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg) 1860 { 1861 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 1862 PetscErrorCode ierr; 1863 1864 PetscFunctionBegin; 1865 switch (op) { 1866 case MAT_NEW_NONZERO_LOCATIONS: 1867 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1868 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1869 case MAT_KEEP_NONZERO_PATTERN: 1870 case MAT_NEW_NONZERO_LOCATION_ERR: 1871 case MAT_USE_INODES: 1872 case MAT_IGNORE_ZERO_ENTRIES: 1873 MatCheckPreallocated(A,1); 1874 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1875 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1876 break; 1877 case MAT_ROW_ORIENTED: 1878 a->roworiented = flg; 1879 1880 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1881 ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr); 1882 break; 1883 case MAT_NEW_DIAGONALS: 1884 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1885 break; 1886 case MAT_IGNORE_OFF_PROC_ENTRIES: 1887 a->donotstash = flg; 1888 break; 1889 case MAT_SPD: 1890 A->spd_set = PETSC_TRUE; 1891 A->spd = flg; 1892 if (flg) { 1893 A->symmetric = PETSC_TRUE; 1894 A->structurally_symmetric = PETSC_TRUE; 1895 A->symmetric_set = PETSC_TRUE; 1896 A->structurally_symmetric_set = PETSC_TRUE; 1897 } 1898 break; 1899 case MAT_SYMMETRIC: 1900 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1901 break; 1902 case MAT_STRUCTURALLY_SYMMETRIC: 1903 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1904 break; 1905 case MAT_HERMITIAN: 1906 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1907 break; 1908 case MAT_SYMMETRY_ETERNAL: 1909 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 1910 break; 1911 default: 1912 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1913 } 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_MPIAIJ" 1919 PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data; 1922 PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 1923 PetscErrorCode ierr; 1924 PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart; 1925 PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend; 1926 PetscInt *cmap,*idx_p; 1927 1928 PetscFunctionBegin; 1929 if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active"); 1930 mat->getrowactive = PETSC_TRUE; 1931 1932 if (!mat->rowvalues && (idx || v)) { 1933 /* 1934 allocate enough space to hold information from the longest row. 1935 */ 1936 Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data; 1937 PetscInt max = 1,tmp; 1938 for (i=0; i<matin->rmap->n; i++) { 1939 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1940 if (max < tmp) max = tmp; 1941 } 1942 ierr = PetscMalloc2(max,PetscScalar,&mat->rowvalues,max,PetscInt,&mat->rowindices);CHKERRQ(ierr); 1943 } 1944 1945 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows"); 1946 lrow = row - rstart; 1947 1948 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1949 if (!v) {pvA = 0; pvB = 0;} 1950 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1951 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1952 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1953 nztot = nzA + nzB; 1954 1955 cmap = mat->garray; 1956 if (v || idx) { 1957 if (nztot) { 1958 /* Sort by increasing column numbers, assuming A and B already sorted */ 1959 PetscInt imark = -1; 1960 if (v) { 1961 *v = v_p = mat->rowvalues; 1962 for (i=0; i<nzB; i++) { 1963 if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i]; 1964 else break; 1965 } 1966 imark = i; 1967 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1968 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1969 } 1970 if (idx) { 1971 *idx = idx_p = mat->rowindices; 1972 if (imark > -1) { 1973 for (i=0; i<imark; i++) { 1974 idx_p[i] = cmap[cworkB[i]]; 1975 } 1976 } else { 1977 for (i=0; i<nzB; i++) { 1978 if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]]; 1979 else break; 1980 } 1981 imark = i; 1982 } 1983 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i]; 1984 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]]; 1985 } 1986 } else { 1987 if (idx) *idx = 0; 1988 if (v) *v = 0; 1989 } 1990 } 1991 *nz = nztot; 1992 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1993 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatRestoreRow_MPIAIJ" 1999 PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2000 { 2001 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2002 2003 PetscFunctionBegin; 2004 if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first"); 2005 aij->getrowactive = PETSC_FALSE; 2006 PetscFunctionReturn(0); 2007 } 2008 2009 #undef __FUNCT__ 2010 #define __FUNCT__ "MatNorm_MPIAIJ" 2011 PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm) 2012 { 2013 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2014 Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data; 2015 PetscErrorCode ierr; 2016 PetscInt i,j,cstart = mat->cmap->rstart; 2017 PetscReal sum = 0.0; 2018 MatScalar *v; 2019 2020 PetscFunctionBegin; 2021 if (aij->size == 1) { 2022 ierr = MatNorm(aij->A,type,norm);CHKERRQ(ierr); 2023 } else { 2024 if (type == NORM_FROBENIUS) { 2025 v = amat->a; 2026 for (i=0; i<amat->nz; i++) { 2027 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2028 } 2029 v = bmat->a; 2030 for (i=0; i<bmat->nz; i++) { 2031 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2032 } 2033 ierr = MPI_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2034 *norm = PetscSqrtReal(*norm); 2035 } else if (type == NORM_1) { /* max column norm */ 2036 PetscReal *tmp,*tmp2; 2037 PetscInt *jj,*garray = aij->garray; 2038 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2039 ierr = PetscMalloc((mat->cmap->N+1)*sizeof(PetscReal),&tmp2);CHKERRQ(ierr); 2040 ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 2041 *norm = 0.0; 2042 v = amat->a; jj = amat->j; 2043 for (j=0; j<amat->nz; j++) { 2044 tmp[cstart + *jj++] += PetscAbsScalar(*v); v++; 2045 } 2046 v = bmat->a; jj = bmat->j; 2047 for (j=0; j<bmat->nz; j++) { 2048 tmp[garray[*jj++]] += PetscAbsScalar(*v); v++; 2049 } 2050 ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2051 for (j=0; j<mat->cmap->N; j++) { 2052 if (tmp2[j] > *norm) *norm = tmp2[j]; 2053 } 2054 ierr = PetscFree(tmp);CHKERRQ(ierr); 2055 ierr = PetscFree(tmp2);CHKERRQ(ierr); 2056 } else if (type == NORM_INFINITY) { /* max row norm */ 2057 PetscReal ntemp = 0.0; 2058 for (j=0; j<aij->A->rmap->n; j++) { 2059 v = amat->a + amat->i[j]; 2060 sum = 0.0; 2061 for (i=0; i<amat->i[j+1]-amat->i[j]; i++) { 2062 sum += PetscAbsScalar(*v); v++; 2063 } 2064 v = bmat->a + bmat->i[j]; 2065 for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) { 2066 sum += PetscAbsScalar(*v); v++; 2067 } 2068 if (sum > ntemp) ntemp = sum; 2069 } 2070 ierr = MPI_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 2071 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm"); 2072 } 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatTranspose_MPIAIJ" 2078 PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout) 2079 { 2080 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2081 Mat_SeqAIJ *Aloc=(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data; 2082 PetscErrorCode ierr; 2083 PetscInt M = A->rmap->N,N = A->cmap->N,ma,na,mb,nb,*ai,*aj,*bi,*bj,row,*cols,*cols_tmp,i; 2084 PetscInt cstart = A->cmap->rstart,ncol; 2085 Mat B; 2086 MatScalar *array; 2087 2088 PetscFunctionBegin; 2089 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2090 2091 ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n; 2092 ai = Aloc->i; aj = Aloc->j; 2093 bi = Bloc->i; bj = Bloc->j; 2094 if (reuse == MAT_INITIAL_MATRIX || *matout == A) { 2095 PetscInt *d_nnz,*g_nnz,*o_nnz; 2096 PetscSFNode *oloc; 2097 PETSC_UNUSED PetscSF sf; 2098 2099 ierr = PetscMalloc4(na,PetscInt,&d_nnz,na,PetscInt,&o_nnz,nb,PetscInt,&g_nnz,nb,PetscSFNode,&oloc);CHKERRQ(ierr); 2100 /* compute d_nnz for preallocation */ 2101 ierr = PetscMemzero(d_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2102 for (i=0; i<ai[ma]; i++) { 2103 d_nnz[aj[i]]++; 2104 aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2105 } 2106 /* compute local off-diagonal contributions */ 2107 ierr = PetscMemzero(g_nnz,nb*sizeof(PetscInt));CHKERRQ(ierr); 2108 for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++; 2109 /* map those to global */ 2110 ierr = PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);CHKERRQ(ierr); 2111 ierr = PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);CHKERRQ(ierr); 2112 ierr = PetscSFSetFromOptions(sf);CHKERRQ(ierr); 2113 ierr = PetscMemzero(o_nnz,na*sizeof(PetscInt));CHKERRQ(ierr); 2114 ierr = PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2115 ierr = PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);CHKERRQ(ierr); 2116 ierr = PetscSFDestroy(&sf);CHKERRQ(ierr); 2117 2118 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 2119 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 2120 ierr = MatSetBlockSizes(B,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2121 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2122 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 2123 ierr = PetscFree4(d_nnz,o_nnz,g_nnz,oloc);CHKERRQ(ierr); 2124 } else { 2125 B = *matout; 2126 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 2127 for (i=0; i<ai[ma]; i++) aj[i] += cstart; /* global col index to be used by MatSetValues() */ 2128 } 2129 2130 /* copy over the A part */ 2131 array = Aloc->a; 2132 row = A->rmap->rstart; 2133 for (i=0; i<ma; i++) { 2134 ncol = ai[i+1]-ai[i]; 2135 ierr = MatSetValues(B,ncol,aj,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2136 row++; 2137 array += ncol; aj += ncol; 2138 } 2139 aj = Aloc->j; 2140 for (i=0; i<ai[ma]; i++) aj[i] -= cstart; /* resume local col index */ 2141 2142 /* copy over the B part */ 2143 ierr = PetscMalloc(bi[mb]*sizeof(PetscInt),&cols);CHKERRQ(ierr); 2144 ierr = PetscMemzero(cols,bi[mb]*sizeof(PetscInt));CHKERRQ(ierr); 2145 array = Bloc->a; 2146 row = A->rmap->rstart; 2147 for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]]; 2148 cols_tmp = cols; 2149 for (i=0; i<mb; i++) { 2150 ncol = bi[i+1]-bi[i]; 2151 ierr = MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);CHKERRQ(ierr); 2152 row++; 2153 array += ncol; cols_tmp += ncol; 2154 } 2155 ierr = PetscFree(cols);CHKERRQ(ierr); 2156 2157 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2158 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2159 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 2160 *matout = B; 2161 } else { 2162 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 2163 } 2164 PetscFunctionReturn(0); 2165 } 2166 2167 #undef __FUNCT__ 2168 #define __FUNCT__ "MatDiagonalScale_MPIAIJ" 2169 PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr) 2170 { 2171 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2172 Mat a = aij->A,b = aij->B; 2173 PetscErrorCode ierr; 2174 PetscInt s1,s2,s3; 2175 2176 PetscFunctionBegin; 2177 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 2178 if (rr) { 2179 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 2180 if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 2181 /* Overlap communication with computation. */ 2182 ierr = VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2183 } 2184 if (ll) { 2185 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 2186 if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 2187 ierr = (*b->ops->diagonalscale)(b,ll,0);CHKERRQ(ierr); 2188 } 2189 /* scale the diagonal block */ 2190 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 2191 2192 if (rr) { 2193 /* Do a scatter end and then right scale the off-diagonal block */ 2194 ierr = VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2195 ierr = (*b->ops->diagonalscale)(b,0,aij->lvec);CHKERRQ(ierr); 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 #undef __FUNCT__ 2201 #define __FUNCT__ "MatSetUnfactored_MPIAIJ" 2202 PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A) 2203 { 2204 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2205 PetscErrorCode ierr; 2206 2207 PetscFunctionBegin; 2208 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 #undef __FUNCT__ 2213 #define __FUNCT__ "MatEqual_MPIAIJ" 2214 PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag) 2215 { 2216 Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data; 2217 Mat a,b,c,d; 2218 PetscBool flg; 2219 PetscErrorCode ierr; 2220 2221 PetscFunctionBegin; 2222 a = matA->A; b = matA->B; 2223 c = matB->A; d = matB->B; 2224 2225 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 2226 if (flg) { 2227 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 2228 } 2229 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 2230 PetscFunctionReturn(0); 2231 } 2232 2233 #undef __FUNCT__ 2234 #define __FUNCT__ "MatCopy_MPIAIJ" 2235 PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str) 2236 { 2237 PetscErrorCode ierr; 2238 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2239 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 2240 2241 PetscFunctionBegin; 2242 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 2243 if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) { 2244 /* because of the column compression in the off-processor part of the matrix a->B, 2245 the number of columns in a->B and b->B may be different, hence we cannot call 2246 the MatCopy() directly on the two parts. If need be, we can provide a more 2247 efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices 2248 then copying the submatrices */ 2249 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2250 } else { 2251 ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr); 2252 ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr); 2253 } 2254 PetscFunctionReturn(0); 2255 } 2256 2257 #undef __FUNCT__ 2258 #define __FUNCT__ "MatSetUp_MPIAIJ" 2259 PetscErrorCode MatSetUp_MPIAIJ(Mat A) 2260 { 2261 PetscErrorCode ierr; 2262 2263 PetscFunctionBegin; 2264 ierr = MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 2265 PetscFunctionReturn(0); 2266 } 2267 2268 #undef __FUNCT__ 2269 #define __FUNCT__ "MatAXPYGetPreallocation_MPIAIJ" 2270 /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */ 2271 static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz) 2272 { 2273 PetscInt i,m=Y->rmap->N; 2274 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2275 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2276 const PetscInt *xi = x->i,*yi = y->i; 2277 2278 PetscFunctionBegin; 2279 /* Set the number of nonzeros in the new matrix */ 2280 for (i=0; i<m; i++) { 2281 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2282 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2283 nnz[i] = 0; 2284 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2285 for (; k<nzy && yltog[yj[k]]<xltog[xj[j]]; k++) nnz[i]++; /* Catch up to X */ 2286 if (k<nzy && yltog[yj[k]]==xltog[xj[j]]) k++; /* Skip duplicate */ 2287 nnz[i]++; 2288 } 2289 for (; k<nzy; k++) nnz[i]++; 2290 } 2291 PetscFunctionReturn(0); 2292 } 2293 2294 #undef __FUNCT__ 2295 #define __FUNCT__ "MatAXPY_MPIAIJ" 2296 PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2297 { 2298 PetscErrorCode ierr; 2299 PetscInt i; 2300 Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data; 2301 PetscBLASInt bnz,one=1; 2302 Mat_SeqAIJ *x,*y; 2303 2304 PetscFunctionBegin; 2305 if (str == SAME_NONZERO_PATTERN) { 2306 PetscScalar alpha = a; 2307 x = (Mat_SeqAIJ*)xx->A->data; 2308 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2309 y = (Mat_SeqAIJ*)yy->A->data; 2310 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2311 x = (Mat_SeqAIJ*)xx->B->data; 2312 y = (Mat_SeqAIJ*)yy->B->data; 2313 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2314 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2315 } else if (str == SUBSET_NONZERO_PATTERN) { 2316 ierr = MatAXPY_SeqAIJ(yy->A,a,xx->A,str);CHKERRQ(ierr); 2317 2318 x = (Mat_SeqAIJ*)xx->B->data; 2319 y = (Mat_SeqAIJ*)yy->B->data; 2320 if (y->xtoy && y->XtoY != xx->B) { 2321 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2322 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2323 } 2324 if (!y->xtoy) { /* get xtoy */ 2325 ierr = MatAXPYGetxtoy_Private(xx->B->rmap->n,x->i,x->j,xx->garray,y->i,y->j,yy->garray,&y->xtoy);CHKERRQ(ierr); 2326 y->XtoY = xx->B; 2327 ierr = PetscObjectReference((PetscObject)xx->B);CHKERRQ(ierr); 2328 } 2329 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2330 } else { 2331 Mat B; 2332 PetscInt *nnz_d,*nnz_o; 2333 ierr = PetscMalloc(yy->A->rmap->N*sizeof(PetscInt),&nnz_d);CHKERRQ(ierr); 2334 ierr = PetscMalloc(yy->B->rmap->N*sizeof(PetscInt),&nnz_o);CHKERRQ(ierr); 2335 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2336 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2337 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 2339 ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr); 2340 ierr = MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr); 2341 ierr = MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr); 2342 ierr = MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);CHKERRQ(ierr); 2343 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2344 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2345 ierr = PetscFree(nnz_d);CHKERRQ(ierr); 2346 ierr = PetscFree(nnz_o);CHKERRQ(ierr); 2347 } 2348 PetscFunctionReturn(0); 2349 } 2350 2351 extern PetscErrorCode MatConjugate_SeqAIJ(Mat); 2352 2353 #undef __FUNCT__ 2354 #define __FUNCT__ "MatConjugate_MPIAIJ" 2355 PetscErrorCode MatConjugate_MPIAIJ(Mat mat) 2356 { 2357 #if defined(PETSC_USE_COMPLEX) 2358 PetscErrorCode ierr; 2359 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2360 2361 PetscFunctionBegin; 2362 ierr = MatConjugate_SeqAIJ(aij->A);CHKERRQ(ierr); 2363 ierr = MatConjugate_SeqAIJ(aij->B);CHKERRQ(ierr); 2364 #else 2365 PetscFunctionBegin; 2366 #endif 2367 PetscFunctionReturn(0); 2368 } 2369 2370 #undef __FUNCT__ 2371 #define __FUNCT__ "MatRealPart_MPIAIJ" 2372 PetscErrorCode MatRealPart_MPIAIJ(Mat A) 2373 { 2374 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2375 PetscErrorCode ierr; 2376 2377 PetscFunctionBegin; 2378 ierr = MatRealPart(a->A);CHKERRQ(ierr); 2379 ierr = MatRealPart(a->B);CHKERRQ(ierr); 2380 PetscFunctionReturn(0); 2381 } 2382 2383 #undef __FUNCT__ 2384 #define __FUNCT__ "MatImaginaryPart_MPIAIJ" 2385 PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A) 2386 { 2387 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2388 PetscErrorCode ierr; 2389 2390 PetscFunctionBegin; 2391 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 2392 ierr = MatImaginaryPart(a->B);CHKERRQ(ierr); 2393 PetscFunctionReturn(0); 2394 } 2395 2396 #if defined(PETSC_HAVE_PBGL) 2397 2398 #include <boost/parallel/mpi/bsp_process_group.hpp> 2399 #include <boost/graph/distributed/ilu_default_graph.hpp> 2400 #include <boost/graph/distributed/ilu_0_block.hpp> 2401 #include <boost/graph/distributed/ilu_preconditioner.hpp> 2402 #include <boost/graph/distributed/petsc/interface.hpp> 2403 #include <boost/multi_array.hpp> 2404 #include <boost/parallel/distributed_property_map->hpp> 2405 2406 #undef __FUNCT__ 2407 #define __FUNCT__ "MatILUFactorSymbolic_MPIAIJ" 2408 /* 2409 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2410 */ 2411 PetscErrorCode MatILUFactorSymbolic_MPIAIJ(Mat fact,Mat A, IS isrow, IS iscol, const MatFactorInfo *info) 2412 { 2413 namespace petsc = boost::distributed::petsc; 2414 2415 namespace graph_dist = boost::graph::distributed; 2416 using boost::graph::distributed::ilu_default::process_group_type; 2417 using boost::graph::ilu_permuted; 2418 2419 PetscBool row_identity, col_identity; 2420 PetscContainer c; 2421 PetscInt m, n, M, N; 2422 PetscErrorCode ierr; 2423 2424 PetscFunctionBegin; 2425 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for parallel ilu"); 2426 ierr = ISIdentity(isrow, &row_identity);CHKERRQ(ierr); 2427 ierr = ISIdentity(iscol, &col_identity);CHKERRQ(ierr); 2428 if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for parallel ILU"); 2429 2430 process_group_type pg; 2431 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2432 lgraph_type *lgraph_p = new lgraph_type(petsc::num_global_vertices(A), pg, petsc::matrix_distribution(A, pg)); 2433 lgraph_type& level_graph = *lgraph_p; 2434 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2435 2436 petsc::read_matrix(A, graph, get(boost::edge_weight, graph)); 2437 ilu_permuted(level_graph); 2438 2439 /* put together the new matrix */ 2440 ierr = MatCreate(PetscObjectComm((PetscObject)A), fact);CHKERRQ(ierr); 2441 ierr = MatGetLocalSize(A, &m, &n);CHKERRQ(ierr); 2442 ierr = MatGetSize(A, &M, &N);CHKERRQ(ierr); 2443 ierr = MatSetSizes(fact, m, n, M, N);CHKERRQ(ierr); 2444 ierr = MatSetBlockSizes(fact,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2445 ierr = MatSetType(fact, ((PetscObject)A)->type_name);CHKERRQ(ierr); 2446 ierr = MatAssemblyBegin(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2447 ierr = MatAssemblyEnd(fact, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2448 2449 ierr = PetscContainerCreate(PetscObjectComm((PetscObject)A), &c); 2450 ierr = PetscContainerSetPointer(c, lgraph_p); 2451 ierr = PetscObjectCompose((PetscObject) (fact), "graph", (PetscObject) c); 2452 ierr = PetscContainerDestroy(&c); 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatLUFactorNumeric_MPIAIJ" 2458 PetscErrorCode MatLUFactorNumeric_MPIAIJ(Mat B,Mat A, const MatFactorInfo *info) 2459 { 2460 PetscFunctionBegin; 2461 PetscFunctionReturn(0); 2462 } 2463 2464 #undef __FUNCT__ 2465 #define __FUNCT__ "MatSolve_MPIAIJ" 2466 /* 2467 This uses the parallel ILU factorization of Peter Gottschling <pgottsch@osl.iu.edu> 2468 */ 2469 PetscErrorCode MatSolve_MPIAIJ(Mat A, Vec b, Vec x) 2470 { 2471 namespace graph_dist = boost::graph::distributed; 2472 2473 typedef graph_dist::ilu_default::ilu_level_graph_type lgraph_type; 2474 lgraph_type *lgraph_p; 2475 PetscContainer c; 2476 PetscErrorCode ierr; 2477 2478 PetscFunctionBegin; 2479 ierr = PetscObjectQuery((PetscObject) A, "graph", (PetscObject*) &c);CHKERRQ(ierr); 2480 ierr = PetscContainerGetPointer(c, (void**) &lgraph_p);CHKERRQ(ierr); 2481 ierr = VecCopy(b, x);CHKERRQ(ierr); 2482 2483 PetscScalar *array_x; 2484 ierr = VecGetArray(x, &array_x);CHKERRQ(ierr); 2485 PetscInt sx; 2486 ierr = VecGetSize(x, &sx);CHKERRQ(ierr); 2487 2488 PetscScalar *array_b; 2489 ierr = VecGetArray(b, &array_b);CHKERRQ(ierr); 2490 PetscInt sb; 2491 ierr = VecGetSize(b, &sb);CHKERRQ(ierr); 2492 2493 lgraph_type& level_graph = *lgraph_p; 2494 graph_dist::ilu_default::graph_type& graph(level_graph.graph); 2495 2496 typedef boost::multi_array_ref<PetscScalar, 1> array_ref_type; 2497 array_ref_type ref_b(array_b, boost::extents[num_vertices(graph)]); 2498 array_ref_type ref_x(array_x, boost::extents[num_vertices(graph)]); 2499 2500 typedef boost::iterator_property_map<array_ref_type::iterator, 2501 boost::property_map<graph_dist::ilu_default::graph_type, boost::vertex_index_t>::type> gvector_type; 2502 gvector_type vector_b(ref_b.begin(), get(boost::vertex_index, graph)); 2503 gvector_type vector_x(ref_x.begin(), get(boost::vertex_index, graph)); 2504 2505 ilu_set_solve(*lgraph_p, vector_b, vector_x); 2506 PetscFunctionReturn(0); 2507 } 2508 #endif 2509 2510 #undef __FUNCT__ 2511 #define __FUNCT__ "MatDestroy_MatRedundant" 2512 PetscErrorCode MatDestroy_MatRedundant(Mat A) 2513 { 2514 PetscErrorCode ierr; 2515 Mat_Redundant *redund; 2516 PetscInt i; 2517 PetscMPIInt size; 2518 2519 PetscFunctionBegin; 2520 ierr = MPI_Comm_size(((PetscObject)A)->comm,&size);CHKERRQ(ierr); 2521 if (size == 1) { 2522 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2523 redund = a->redundant; 2524 } else { 2525 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 2526 redund = a->redundant; 2527 } 2528 if (redund){ 2529 if (redund->matseq) { /* via MatGetSubMatrices() */ 2530 ierr = ISDestroy(&redund->isrow);CHKERRQ(ierr); 2531 ierr = ISDestroy(&redund->iscol);CHKERRQ(ierr); 2532 ierr = MatDestroy(&redund->matseq[0]);CHKERRQ(ierr); 2533 ierr = PetscFree(redund->matseq);CHKERRQ(ierr); 2534 } else { 2535 ierr = PetscFree2(redund->send_rank,redund->recv_rank);CHKERRQ(ierr); 2536 ierr = PetscFree(redund->sbuf_j);CHKERRQ(ierr); 2537 ierr = PetscFree(redund->sbuf_a);CHKERRQ(ierr); 2538 for (i=0; i<redund->nrecvs; i++) { 2539 ierr = PetscFree(redund->rbuf_j[i]);CHKERRQ(ierr); 2540 ierr = PetscFree(redund->rbuf_a[i]);CHKERRQ(ierr); 2541 } 2542 ierr = PetscFree4(redund->sbuf_nz,redund->rbuf_nz,redund->rbuf_j,redund->rbuf_a);CHKERRQ(ierr); 2543 } 2544 2545 if (redund->psubcomm) { 2546 ierr = PetscSubcommDestroy(&redund->psubcomm);CHKERRQ(ierr); 2547 } 2548 ierr = redund->Destroy(A);CHKERRQ(ierr); 2549 ierr = PetscFree(redund);CHKERRQ(ierr); 2550 } 2551 PetscFunctionReturn(0); 2552 } 2553 2554 #undef __FUNCT__ 2555 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ_psubcomm" 2556 PetscErrorCode MatGetRedundantMatrix_MPIAIJ_psubcomm(Mat mat,PetscInt nsubcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2557 { 2558 PetscMPIInt rank,size; 2559 MPI_Comm comm,subcomm=psubcomm->comm; 2560 PetscErrorCode ierr; 2561 PetscInt nsends=0,nrecvs=0,i,rownz_max=0,M=mat->rmap->N,N=mat->cmap->N; 2562 PetscMPIInt *send_rank= NULL,*recv_rank=NULL,subrank,subsize; 2563 PetscInt *rowrange = mat->rmap->range; 2564 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 2565 Mat A = aij->A,B=aij->B,C=*matredundant; 2566 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b=(Mat_SeqAIJ*)B->data; 2567 PetscScalar *sbuf_a; 2568 PetscInt nzlocal=a->nz+b->nz; 2569 PetscInt j,cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,nzA,nzB,ncols,*cworkA,*cworkB; 2570 PetscInt rstart=mat->rmap->rstart,rend=mat->rmap->rend,*bmap=aij->garray; 2571 PetscInt *cols,ctmp,lwrite,*rptr,l,*sbuf_j; 2572 MatScalar *aworkA,*aworkB; 2573 PetscScalar *vals; 2574 PetscMPIInt tag1,tag2,tag3,imdex; 2575 MPI_Request *s_waits1=NULL,*s_waits2=NULL,*s_waits3=NULL; 2576 MPI_Request *r_waits1=NULL,*r_waits2=NULL,*r_waits3=NULL; 2577 MPI_Status recv_status,*send_status; 2578 PetscInt *sbuf_nz=NULL,*rbuf_nz=NULL,count; 2579 PetscInt **rbuf_j=NULL; 2580 PetscScalar **rbuf_a=NULL; 2581 Mat_Redundant *redund =NULL; 2582 2583 PetscFunctionBegin; 2584 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2585 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2586 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2587 ierr = MPI_Comm_rank(subcomm,&subrank);CHKERRQ(ierr); 2588 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2589 2590 if (reuse == MAT_REUSE_MATRIX) { 2591 if (M != mat->rmap->N || N != mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong global size"); 2592 if (subsize == 1) { 2593 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2594 redund = c->redundant; 2595 } else { 2596 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2597 redund = c->redundant; 2598 } 2599 if (nzlocal != redund->nzlocal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. Wrong nzlocal"); 2600 2601 nsends = redund->nsends; 2602 nrecvs = redund->nrecvs; 2603 send_rank = redund->send_rank; 2604 recv_rank = redund->recv_rank; 2605 sbuf_nz = redund->sbuf_nz; 2606 rbuf_nz = redund->rbuf_nz; 2607 sbuf_j = redund->sbuf_j; 2608 sbuf_a = redund->sbuf_a; 2609 rbuf_j = redund->rbuf_j; 2610 rbuf_a = redund->rbuf_a; 2611 } 2612 2613 if (reuse == MAT_INITIAL_MATRIX) { 2614 PetscInt nleftover,np_subcomm; 2615 2616 /* get the destination processors' id send_rank, nsends and nrecvs */ 2617 ierr = PetscMalloc2(size,PetscMPIInt,&send_rank,size,PetscMPIInt,&recv_rank);CHKERRQ(ierr); 2618 2619 np_subcomm = size/nsubcomm; 2620 nleftover = size - nsubcomm*np_subcomm; 2621 2622 nsends = 0; nrecvs = 0; 2623 if (psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2624 /* -------------------------------------------*/ 2625 for (i=0; i<size; i++) { 2626 if (subrank == i/nsubcomm && i != rank) { /* my_subrank == other's subrank */ 2627 send_rank[nsends] = i; nsends++; 2628 recv_rank[nrecvs++] = i; 2629 /* printf("[%d] send to and recv from [%d]\n",rank,i); */ 2630 } 2631 } 2632 if (rank >= size - nleftover) { /* this proc is a leftover processor */ 2633 i = size-nleftover-1; 2634 j = 0; 2635 while (j < nsubcomm - nleftover) { 2636 send_rank[nsends++] = i; 2637 i--; j++; 2638 /* printf("[%d] send to [%d]\n",rank,i); */ 2639 } 2640 } 2641 2642 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2643 for (i=0; i<nleftover; i++) { 2644 recv_rank[nrecvs++] = size-nleftover+i; 2645 /* printf("[%d] recv from [%d]\n",rank,i); */ 2646 } 2647 } 2648 } else if (psubcomm->type == PETSC_SUBCOMM_CONTIGUOUS) { 2649 /* --------------------------------------------------*/ 2650 PetscInt color,subcommstart; 2651 subcommstart=0; 2652 for (color=0; color<nsubcomm; color++) { 2653 if (psubcomm->color != color) { 2654 for (i=0; i<psubcomm->subsize[color]; i++) { 2655 if (subrank == i) { /* my_subrank == other's subrank */ 2656 send_rank[nsends++] = subcommstart+i; 2657 recv_rank[nrecvs++] = subcommstart+i; 2658 /* printf("[%d] send to and recv from [%d]\n",rank,subcommstart+i); */ 2659 } 2660 } 2661 } 2662 subcommstart += psubcomm->subsize[color]; 2663 } 2664 if (nleftover && subrank == size/nsubcomm) { /* this proc is a leftover proc, send to subcomm that does not have leftover proc */ 2665 subcommstart=0; 2666 for (color=0; color<nsubcomm; color++) { 2667 subcommstart += psubcomm->subsize[color]; 2668 if (psubcomm->color == color) continue; 2669 if (psubcomm->subsize[color] == size/nsubcomm) { /* subcomm does not have leftover proc */ 2670 send_rank[nsends++] = subcommstart -1; /* send to the last proc of subcomm[color] */ 2671 /* printf("[%d] leftover send to [%d] \n",rank,subcommstart -1); */ 2672 } 2673 } 2674 } 2675 2676 if (nleftover && subsize == size/nsubcomm && subrank==subsize-1) { /* this proc recvs from leftover processors */ 2677 subcommstart=0; 2678 for (color=0; color<nsubcomm; color++) { 2679 subcommstart += psubcomm->subsize[color]; 2680 if (psubcomm->subsize[color] > size/nsubcomm) { /* subcomm has leftover proc */ 2681 recv_rank[nrecvs++] = subcommstart -1; /* recv from the last proc of subcomm[color] */ 2682 /* printf("[%d] recv from [%d]\n",rank,subcommstart -1); */ 2683 } 2684 } 2685 } 2686 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for PetscSubcomm type %D",psubcomm->type); 2687 2688 /* allocate sbuf_j, sbuf_a */ 2689 i = nzlocal + rowrange[rank+1] - rowrange[rank] + 2; 2690 ierr = PetscMalloc(i*sizeof(PetscInt),&sbuf_j);CHKERRQ(ierr); 2691 ierr = PetscMalloc((nzlocal+1)*sizeof(PetscScalar),&sbuf_a);CHKERRQ(ierr); 2692 /* 2693 ierr = PetscSynchronizedPrintf(comm,"[%d] nsends %d, nrecvs %d\n",rank,nsends,nrecvs);CHKERRQ(ierr); 2694 ierr = PetscSynchronizedFlush(comm);CHKERRQ(ierr); 2695 */ 2696 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2697 2698 /* copy mat's local entries into the buffers */ 2699 if (reuse == MAT_INITIAL_MATRIX) { 2700 rownz_max = 0; 2701 rptr = sbuf_j; 2702 cols = sbuf_j + rend-rstart + 1; 2703 vals = sbuf_a; 2704 rptr[0] = 0; 2705 for (i=0; i<rend-rstart; i++) { 2706 row = i + rstart; 2707 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2708 ncols = nzA + nzB; 2709 cworkA = a->j + a->i[i]; cworkB = b->j + b->i[i]; 2710 aworkA = a->a + a->i[i]; aworkB = b->a + b->i[i]; 2711 /* load the column indices for this row into cols */ 2712 lwrite = 0; 2713 for (l=0; l<nzB; l++) { 2714 if ((ctmp = bmap[cworkB[l]]) < cstart) { 2715 vals[lwrite] = aworkB[l]; 2716 cols[lwrite++] = ctmp; 2717 } 2718 } 2719 for (l=0; l<nzA; l++) { 2720 vals[lwrite] = aworkA[l]; 2721 cols[lwrite++] = cstart + cworkA[l]; 2722 } 2723 for (l=0; l<nzB; l++) { 2724 if ((ctmp = bmap[cworkB[l]]) >= cend) { 2725 vals[lwrite] = aworkB[l]; 2726 cols[lwrite++] = ctmp; 2727 } 2728 } 2729 vals += ncols; 2730 cols += ncols; 2731 rptr[i+1] = rptr[i] + ncols; 2732 if (rownz_max < ncols) rownz_max = ncols; 2733 } 2734 if (rptr[rend-rstart] != a->nz + b->nz) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "rptr[%d] %d != %d + %d",rend-rstart,rptr[rend-rstart+1],a->nz,b->nz); 2735 } else { /* only copy matrix values into sbuf_a */ 2736 rptr = sbuf_j; 2737 vals = sbuf_a; 2738 rptr[0] = 0; 2739 for (i=0; i<rend-rstart; i++) { 2740 row = i + rstart; 2741 nzA = a->i[i+1] - a->i[i]; nzB = b->i[i+1] - b->i[i]; 2742 ncols = nzA + nzB; 2743 cworkB = b->j + b->i[i]; 2744 aworkA = a->a + a->i[i]; 2745 aworkB = b->a + b->i[i]; 2746 lwrite = 0; 2747 for (l=0; l<nzB; l++) { 2748 if ((ctmp = bmap[cworkB[l]]) < cstart) vals[lwrite++] = aworkB[l]; 2749 } 2750 for (l=0; l<nzA; l++) vals[lwrite++] = aworkA[l]; 2751 for (l=0; l<nzB; l++) { 2752 if ((ctmp = bmap[cworkB[l]]) >= cend) vals[lwrite++] = aworkB[l]; 2753 } 2754 vals += ncols; 2755 rptr[i+1] = rptr[i] + ncols; 2756 } 2757 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2758 2759 /* send nzlocal to others, and recv other's nzlocal */ 2760 /*--------------------------------------------------*/ 2761 if (reuse == MAT_INITIAL_MATRIX) { 2762 ierr = PetscMalloc2(3*(nsends + nrecvs)+1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2763 2764 s_waits2 = s_waits3 + nsends; 2765 s_waits1 = s_waits2 + nsends; 2766 r_waits1 = s_waits1 + nsends; 2767 r_waits2 = r_waits1 + nrecvs; 2768 r_waits3 = r_waits2 + nrecvs; 2769 } else { 2770 ierr = PetscMalloc2(nsends + nrecvs +1,MPI_Request,&s_waits3,nsends+1,MPI_Status,&send_status);CHKERRQ(ierr); 2771 2772 r_waits3 = s_waits3 + nsends; 2773 } 2774 2775 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag3);CHKERRQ(ierr); 2776 if (reuse == MAT_INITIAL_MATRIX) { 2777 /* get new tags to keep the communication clean */ 2778 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag1);CHKERRQ(ierr); 2779 ierr = PetscObjectGetNewTag((PetscObject)mat,&tag2);CHKERRQ(ierr); 2780 ierr = PetscMalloc4(nsends,PetscInt,&sbuf_nz,nrecvs,PetscInt,&rbuf_nz,nrecvs,PetscInt*,&rbuf_j,nrecvs,PetscScalar*,&rbuf_a);CHKERRQ(ierr); 2781 2782 /* post receives of other's nzlocal */ 2783 for (i=0; i<nrecvs; i++) { 2784 ierr = MPI_Irecv(rbuf_nz+i,1,MPIU_INT,MPI_ANY_SOURCE,tag1,comm,r_waits1+i);CHKERRQ(ierr); 2785 } 2786 /* send nzlocal to others */ 2787 for (i=0; i<nsends; i++) { 2788 sbuf_nz[i] = nzlocal; 2789 ierr = MPI_Isend(sbuf_nz+i,1,MPIU_INT,send_rank[i],tag1,comm,s_waits1+i);CHKERRQ(ierr); 2790 } 2791 /* wait on receives of nzlocal; allocate space for rbuf_j, rbuf_a */ 2792 count = nrecvs; 2793 while (count) { 2794 ierr = MPI_Waitany(nrecvs,r_waits1,&imdex,&recv_status);CHKERRQ(ierr); 2795 2796 recv_rank[imdex] = recv_status.MPI_SOURCE; 2797 /* allocate rbuf_a and rbuf_j; then post receives of rbuf_j */ 2798 ierr = PetscMalloc((rbuf_nz[imdex]+1)*sizeof(PetscScalar),&rbuf_a[imdex]);CHKERRQ(ierr); 2799 2800 i = rowrange[recv_status.MPI_SOURCE+1] - rowrange[recv_status.MPI_SOURCE]; /* number of expected mat->i */ 2801 2802 rbuf_nz[imdex] += i + 2; 2803 2804 ierr = PetscMalloc(rbuf_nz[imdex]*sizeof(PetscInt),&rbuf_j[imdex]);CHKERRQ(ierr); 2805 ierr = MPI_Irecv(rbuf_j[imdex],rbuf_nz[imdex],MPIU_INT,recv_status.MPI_SOURCE,tag2,comm,r_waits2+imdex);CHKERRQ(ierr); 2806 count--; 2807 } 2808 /* wait on sends of nzlocal */ 2809 if (nsends) {ierr = MPI_Waitall(nsends,s_waits1,send_status);CHKERRQ(ierr);} 2810 /* send mat->i,j to others, and recv from other's */ 2811 /*------------------------------------------------*/ 2812 for (i=0; i<nsends; i++) { 2813 j = nzlocal + rowrange[rank+1] - rowrange[rank] + 1; 2814 ierr = MPI_Isend(sbuf_j,j,MPIU_INT,send_rank[i],tag2,comm,s_waits2+i);CHKERRQ(ierr); 2815 } 2816 /* wait on receives of mat->i,j */ 2817 /*------------------------------*/ 2818 count = nrecvs; 2819 while (count) { 2820 ierr = MPI_Waitany(nrecvs,r_waits2,&imdex,&recv_status);CHKERRQ(ierr); 2821 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2822 count--; 2823 } 2824 /* wait on sends of mat->i,j */ 2825 /*---------------------------*/ 2826 if (nsends) { 2827 ierr = MPI_Waitall(nsends,s_waits2,send_status);CHKERRQ(ierr); 2828 } 2829 } /* endof if (reuse == MAT_INITIAL_MATRIX) */ 2830 2831 /* post receives, send and receive mat->a */ 2832 /*----------------------------------------*/ 2833 for (imdex=0; imdex<nrecvs; imdex++) { 2834 ierr = MPI_Irecv(rbuf_a[imdex],rbuf_nz[imdex],MPIU_SCALAR,recv_rank[imdex],tag3,comm,r_waits3+imdex);CHKERRQ(ierr); 2835 } 2836 for (i=0; i<nsends; i++) { 2837 ierr = MPI_Isend(sbuf_a,nzlocal,MPIU_SCALAR,send_rank[i],tag3,comm,s_waits3+i);CHKERRQ(ierr); 2838 } 2839 count = nrecvs; 2840 while (count) { 2841 ierr = MPI_Waitany(nrecvs,r_waits3,&imdex,&recv_status);CHKERRQ(ierr); 2842 if (recv_rank[imdex] != recv_status.MPI_SOURCE) SETERRQ2(PETSC_COMM_SELF,1, "recv_rank %d != MPI_SOURCE %d",recv_rank[imdex],recv_status.MPI_SOURCE); 2843 count--; 2844 } 2845 if (nsends) { 2846 ierr = MPI_Waitall(nsends,s_waits3,send_status);CHKERRQ(ierr); 2847 } 2848 2849 ierr = PetscFree2(s_waits3,send_status);CHKERRQ(ierr); 2850 2851 /* create redundant matrix */ 2852 /*-------------------------*/ 2853 if (reuse == MAT_INITIAL_MATRIX) { 2854 const PetscInt *range; 2855 PetscInt rstart_sub,rend_sub,mloc_sub; 2856 2857 /* compute rownz_max for preallocation */ 2858 for (imdex=0; imdex<nrecvs; imdex++) { 2859 j = rowrange[recv_rank[imdex]+1] - rowrange[recv_rank[imdex]]; 2860 rptr = rbuf_j[imdex]; 2861 for (i=0; i<j; i++) { 2862 ncols = rptr[i+1] - rptr[i]; 2863 if (rownz_max < ncols) rownz_max = ncols; 2864 } 2865 } 2866 2867 ierr = MatCreate(subcomm,&C);CHKERRQ(ierr); 2868 2869 /* get local size of redundant matrix 2870 - mloc_sub is chosen for PETSC_SUBCOMM_INTERLACED, works for other types, but may not efficient! */ 2871 ierr = MatGetOwnershipRanges(mat,&range);CHKERRQ(ierr); 2872 rstart_sub = range[nsubcomm*subrank]; 2873 if (subrank+1 < subsize) { /* not the last proc in subcomm */ 2874 rend_sub = range[nsubcomm*(subrank+1)]; 2875 } else { 2876 rend_sub = mat->rmap->N; 2877 } 2878 mloc_sub = rend_sub - rstart_sub; 2879 2880 if (M == N) { 2881 ierr = MatSetSizes(C,mloc_sub,mloc_sub,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 2882 } else { /* non-square matrix */ 2883 ierr = MatSetSizes(C,mloc_sub,PETSC_DECIDE,PETSC_DECIDE,mat->cmap->N);CHKERRQ(ierr); 2884 } 2885 ierr = MatSetBlockSizes(C,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2886 ierr = MatSetFromOptions(C);CHKERRQ(ierr); 2887 ierr = MatSeqAIJSetPreallocation(C,rownz_max,NULL);CHKERRQ(ierr); 2888 ierr = MatMPIAIJSetPreallocation(C,rownz_max,NULL,rownz_max,NULL);CHKERRQ(ierr); 2889 } else { 2890 C = *matredundant; 2891 } 2892 2893 /* insert local matrix entries */ 2894 rptr = sbuf_j; 2895 cols = sbuf_j + rend-rstart + 1; 2896 vals = sbuf_a; 2897 for (i=0; i<rend-rstart; i++) { 2898 row = i + rstart; 2899 ncols = rptr[i+1] - rptr[i]; 2900 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2901 vals += ncols; 2902 cols += ncols; 2903 } 2904 /* insert received matrix entries */ 2905 for (imdex=0; imdex<nrecvs; imdex++) { 2906 rstart = rowrange[recv_rank[imdex]]; 2907 rend = rowrange[recv_rank[imdex]+1]; 2908 /* printf("[%d] insert rows %d - %d\n",rank,rstart,rend-1); */ 2909 rptr = rbuf_j[imdex]; 2910 cols = rbuf_j[imdex] + rend-rstart + 1; 2911 vals = rbuf_a[imdex]; 2912 for (i=0; i<rend-rstart; i++) { 2913 row = i + rstart; 2914 ncols = rptr[i+1] - rptr[i]; 2915 ierr = MatSetValues(C,1,&row,ncols,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 2916 vals += ncols; 2917 cols += ncols; 2918 } 2919 } 2920 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2921 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2922 2923 if (reuse == MAT_INITIAL_MATRIX) { 2924 *matredundant = C; 2925 2926 /* create a supporting struct and attach it to C for reuse */ 2927 ierr = PetscNewLog(C,Mat_Redundant,&redund);CHKERRQ(ierr); 2928 if (subsize == 1) { 2929 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2930 c->redundant = redund; 2931 } else { 2932 Mat_MPIAIJ *c = (Mat_MPIAIJ*)C->data; 2933 c->redundant = redund; 2934 } 2935 2936 redund->nzlocal = nzlocal; 2937 redund->nsends = nsends; 2938 redund->nrecvs = nrecvs; 2939 redund->send_rank = send_rank; 2940 redund->recv_rank = recv_rank; 2941 redund->sbuf_nz = sbuf_nz; 2942 redund->rbuf_nz = rbuf_nz; 2943 redund->sbuf_j = sbuf_j; 2944 redund->sbuf_a = sbuf_a; 2945 redund->rbuf_j = rbuf_j; 2946 redund->rbuf_a = rbuf_a; 2947 redund->psubcomm = NULL; 2948 2949 redund->Destroy = C->ops->destroy; 2950 C->ops->destroy = MatDestroy_MatRedundant; 2951 } 2952 PetscFunctionReturn(0); 2953 } 2954 2955 #undef __FUNCT__ 2956 #define __FUNCT__ "MatGetRedundantMatrix_MPIAIJ" 2957 PetscErrorCode MatGetRedundantMatrix_MPIAIJ(Mat mat,PetscInt nsubcomm,MPI_Comm subcomm,PetscSubcomm psubcomm,MatReuse reuse,Mat *matredundant) 2958 { 2959 PetscErrorCode ierr; 2960 MPI_Comm comm; 2961 PetscMPIInt size,subsize; 2962 PetscInt mloc_sub,rstart,rend,M=mat->rmap->N,N=mat->cmap->N; 2963 Mat_Redundant *redund =NULL; 2964 PetscSubcomm psubcomm_in=psubcomm; 2965 MPI_Comm subcomm_in=subcomm; 2966 2967 PetscFunctionBegin; 2968 if (subcomm_in == MPI_COMM_NULL) { /* use psubcomm */ 2969 if (reuse == MAT_INITIAL_MATRIX) { 2970 if (psubcomm_in == NULL) { /* user does not provide psubcomm, create it here */ 2971 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 2972 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2973 ierr = PetscSubcommCreate(comm,&psubcomm);CHKERRQ(ierr); 2974 ierr = PetscSubcommSetNumber(psubcomm,nsubcomm);CHKERRQ(ierr); 2975 ierr = PetscSubcommSetType(psubcomm,PETSC_SUBCOMM_CONTIGUOUS);CHKERRQ(ierr); 2976 ierr = PetscSubcommSetFromOptions(psubcomm);CHKERRQ(ierr); 2977 } 2978 subcomm = psubcomm->comm; 2979 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2980 } else { /* retrieve psubcomm */ 2981 if (psubcomm_in == NULL) { /* user does not provide psubcomm */ 2982 ierr = PetscObjectGetComm((PetscObject)(*matredundant),&subcomm);CHKERRQ(ierr); 2983 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2984 if (subsize == 1) { 2985 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 2986 psubcomm = c->redundant->psubcomm; 2987 } else { 2988 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 2989 psubcomm = c->redundant->psubcomm; 2990 } 2991 } else { /* use psubcomm_in */ 2992 subcomm = psubcomm_in->comm; 2993 ierr = MPI_Comm_size(subcomm,&subsize);CHKERRQ(ierr); 2994 } 2995 } 2996 } 2997 2998 if (subcomm_in == MPI_COMM_NULL && psubcomm->type == PETSC_SUBCOMM_INTERLACED) { 2999 ierr = MatGetRedundantMatrix_MPIAIJ_psubcomm(mat,nsubcomm,psubcomm,reuse,matredundant);CHKERRQ(ierr); 3000 } else { 3001 /* via MatGetSubMatrices() */ 3002 Mat *matseq; 3003 IS isrow,iscol; 3004 3005 if (reuse == MAT_INITIAL_MATRIX) { 3006 /* create a local sequential matrix matseq[0] */ 3007 mloc_sub = PETSC_DECIDE; 3008 ierr = PetscSplitOwnership(subcomm,&mloc_sub,&M);CHKERRQ(ierr); 3009 ierr = MPI_Scan(&mloc_sub,&rend,1,MPIU_INT,MPI_SUM,subcomm);CHKERRQ(ierr); 3010 rstart = rend - mloc_sub; 3011 ierr = ISCreateStride(PETSC_COMM_SELF,mloc_sub,rstart,1,&isrow);CHKERRQ(ierr); 3012 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iscol);CHKERRQ(ierr); 3013 } else { /* reuse == MAT_REUSE_MATRIX */ 3014 if (subsize == 1) { 3015 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3016 redund = c->redundant; 3017 } else { 3018 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3019 redund = c->redundant; 3020 } 3021 3022 isrow = redund->isrow; 3023 iscol = redund->iscol; 3024 matseq = redund->matseq; 3025 } 3026 ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,reuse,&matseq);CHKERRQ(ierr); 3027 ierr = MatCreateMPIAIJConcatenateSeqAIJ(subcomm,matseq[0],PETSC_DECIDE,reuse,matredundant);CHKERRQ(ierr); 3028 3029 if (reuse == MAT_INITIAL_MATRIX) { 3030 /* create a supporting struct and attach it to C for reuse */ 3031 ierr = PetscNewLog(*matredundant,Mat_Redundant,&redund);CHKERRQ(ierr); 3032 if (subsize == 1) { 3033 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3034 c->redundant = redund; 3035 } else { 3036 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3037 c->redundant = redund; 3038 } 3039 redund->isrow = isrow; 3040 redund->iscol = iscol; 3041 redund->matseq = matseq; 3042 redund->psubcomm = NULL; 3043 redund->Destroy = (*matredundant)->ops->destroy; 3044 (*matredundant)->ops->destroy = MatDestroy_MatRedundant; 3045 } 3046 } 3047 3048 if (psubcomm && psubcomm_in==NULL) { 3049 /* if psubcomm is created in this routine, free it in MatDestroy_MatRedundant() */ 3050 ierr = MPI_Comm_size(psubcomm->comm,&subsize);CHKERRQ(ierr); 3051 if (subsize == 1) { 3052 Mat_SeqAIJ *c = (Mat_SeqAIJ*)(*matredundant)->data; 3053 c->redundant->psubcomm = psubcomm; 3054 } else { 3055 Mat_MPIAIJ *c = (Mat_MPIAIJ*)(*matredundant)->data; 3056 c->redundant->psubcomm = psubcomm ; 3057 } 3058 } 3059 PetscFunctionReturn(0); 3060 } 3061 3062 #undef __FUNCT__ 3063 #define __FUNCT__ "MatGetRowMaxAbs_MPIAIJ" 3064 PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3065 { 3066 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3067 PetscErrorCode ierr; 3068 PetscInt i,*idxb = 0; 3069 PetscScalar *va,*vb; 3070 Vec vtmp; 3071 3072 PetscFunctionBegin; 3073 ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr); 3074 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3075 if (idx) { 3076 for (i=0; i<A->rmap->n; i++) { 3077 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3078 } 3079 } 3080 3081 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3082 if (idx) { 3083 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3084 } 3085 ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3086 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3087 3088 for (i=0; i<A->rmap->n; i++) { 3089 if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) { 3090 va[i] = vb[i]; 3091 if (idx) idx[i] = a->garray[idxb[i]]; 3092 } 3093 } 3094 3095 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3096 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3097 ierr = PetscFree(idxb);CHKERRQ(ierr); 3098 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3099 PetscFunctionReturn(0); 3100 } 3101 3102 #undef __FUNCT__ 3103 #define __FUNCT__ "MatGetRowMinAbs_MPIAIJ" 3104 PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3105 { 3106 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 3107 PetscErrorCode ierr; 3108 PetscInt i,*idxb = 0; 3109 PetscScalar *va,*vb; 3110 Vec vtmp; 3111 3112 PetscFunctionBegin; 3113 ierr = MatGetRowMinAbs(a->A,v,idx);CHKERRQ(ierr); 3114 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 3115 if (idx) { 3116 for (i=0; i<A->cmap->n; i++) { 3117 if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart; 3118 } 3119 } 3120 3121 ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr); 3122 if (idx) { 3123 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr); 3124 } 3125 ierr = MatGetRowMinAbs(a->B,vtmp,idxb);CHKERRQ(ierr); 3126 ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr); 3127 3128 for (i=0; i<A->rmap->n; i++) { 3129 if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) { 3130 va[i] = vb[i]; 3131 if (idx) idx[i] = a->garray[idxb[i]]; 3132 } 3133 } 3134 3135 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 3136 ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr); 3137 ierr = PetscFree(idxb);CHKERRQ(ierr); 3138 ierr = VecDestroy(&vtmp);CHKERRQ(ierr); 3139 PetscFunctionReturn(0); 3140 } 3141 3142 #undef __FUNCT__ 3143 #define __FUNCT__ "MatGetRowMin_MPIAIJ" 3144 PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3145 { 3146 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3147 PetscInt n = A->rmap->n; 3148 PetscInt cstart = A->cmap->rstart; 3149 PetscInt *cmap = mat->garray; 3150 PetscInt *diagIdx, *offdiagIdx; 3151 Vec diagV, offdiagV; 3152 PetscScalar *a, *diagA, *offdiagA; 3153 PetscInt r; 3154 PetscErrorCode ierr; 3155 3156 PetscFunctionBegin; 3157 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3158 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);CHKERRQ(ierr); 3159 ierr = VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);CHKERRQ(ierr); 3160 ierr = MatGetRowMin(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3161 ierr = MatGetRowMin(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3162 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3163 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3164 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3165 for (r = 0; r < n; ++r) { 3166 if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) { 3167 a[r] = diagA[r]; 3168 idx[r] = cstart + diagIdx[r]; 3169 } else { 3170 a[r] = offdiagA[r]; 3171 idx[r] = cmap[offdiagIdx[r]]; 3172 } 3173 } 3174 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3175 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3176 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3177 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3178 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3179 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3180 PetscFunctionReturn(0); 3181 } 3182 3183 #undef __FUNCT__ 3184 #define __FUNCT__ "MatGetRowMax_MPIAIJ" 3185 PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[]) 3186 { 3187 Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data; 3188 PetscInt n = A->rmap->n; 3189 PetscInt cstart = A->cmap->rstart; 3190 PetscInt *cmap = mat->garray; 3191 PetscInt *diagIdx, *offdiagIdx; 3192 Vec diagV, offdiagV; 3193 PetscScalar *a, *diagA, *offdiagA; 3194 PetscInt r; 3195 PetscErrorCode ierr; 3196 3197 PetscFunctionBegin; 3198 ierr = PetscMalloc2(n,PetscInt,&diagIdx,n,PetscInt,&offdiagIdx);CHKERRQ(ierr); 3199 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &diagV);CHKERRQ(ierr); 3200 ierr = VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);CHKERRQ(ierr); 3201 ierr = MatGetRowMax(mat->A, diagV, diagIdx);CHKERRQ(ierr); 3202 ierr = MatGetRowMax(mat->B, offdiagV, offdiagIdx);CHKERRQ(ierr); 3203 ierr = VecGetArray(v, &a);CHKERRQ(ierr); 3204 ierr = VecGetArray(diagV, &diagA);CHKERRQ(ierr); 3205 ierr = VecGetArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3206 for (r = 0; r < n; ++r) { 3207 if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) { 3208 a[r] = diagA[r]; 3209 idx[r] = cstart + diagIdx[r]; 3210 } else { 3211 a[r] = offdiagA[r]; 3212 idx[r] = cmap[offdiagIdx[r]]; 3213 } 3214 } 3215 ierr = VecRestoreArray(v, &a);CHKERRQ(ierr); 3216 ierr = VecRestoreArray(diagV, &diagA);CHKERRQ(ierr); 3217 ierr = VecRestoreArray(offdiagV, &offdiagA);CHKERRQ(ierr); 3218 ierr = VecDestroy(&diagV);CHKERRQ(ierr); 3219 ierr = VecDestroy(&offdiagV);CHKERRQ(ierr); 3220 ierr = PetscFree2(diagIdx, offdiagIdx);CHKERRQ(ierr); 3221 PetscFunctionReturn(0); 3222 } 3223 3224 #undef __FUNCT__ 3225 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIAIJ" 3226 PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat) 3227 { 3228 PetscErrorCode ierr; 3229 Mat *dummy; 3230 3231 PetscFunctionBegin; 3232 ierr = MatGetSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);CHKERRQ(ierr); 3233 *newmat = *dummy; 3234 ierr = PetscFree(dummy);CHKERRQ(ierr); 3235 PetscFunctionReturn(0); 3236 } 3237 3238 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3239 3240 #undef __FUNCT__ 3241 #define __FUNCT__ "MatInvertBlockDiagonal_MPIAIJ" 3242 PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values) 3243 { 3244 Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data; 3245 PetscErrorCode ierr; 3246 3247 PetscFunctionBegin; 3248 ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr); 3249 PetscFunctionReturn(0); 3250 } 3251 3252 #undef __FUNCT__ 3253 #define __FUNCT__ "MatSetRandom_MPIAIJ" 3254 static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx) 3255 { 3256 PetscErrorCode ierr; 3257 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data; 3258 3259 PetscFunctionBegin; 3260 ierr = MatSetRandom(aij->A,rctx);CHKERRQ(ierr); 3261 ierr = MatSetRandom(aij->B,rctx);CHKERRQ(ierr); 3262 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3263 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3264 PetscFunctionReturn(0); 3265 } 3266 3267 /* -------------------------------------------------------------------*/ 3268 static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ, 3269 MatGetRow_MPIAIJ, 3270 MatRestoreRow_MPIAIJ, 3271 MatMult_MPIAIJ, 3272 /* 4*/ MatMultAdd_MPIAIJ, 3273 MatMultTranspose_MPIAIJ, 3274 MatMultTransposeAdd_MPIAIJ, 3275 #if defined(PETSC_HAVE_PBGL) 3276 MatSolve_MPIAIJ, 3277 #else 3278 0, 3279 #endif 3280 0, 3281 0, 3282 /*10*/ 0, 3283 0, 3284 0, 3285 MatSOR_MPIAIJ, 3286 MatTranspose_MPIAIJ, 3287 /*15*/ MatGetInfo_MPIAIJ, 3288 MatEqual_MPIAIJ, 3289 MatGetDiagonal_MPIAIJ, 3290 MatDiagonalScale_MPIAIJ, 3291 MatNorm_MPIAIJ, 3292 /*20*/ MatAssemblyBegin_MPIAIJ, 3293 MatAssemblyEnd_MPIAIJ, 3294 MatSetOption_MPIAIJ, 3295 MatZeroEntries_MPIAIJ, 3296 /*24*/ MatZeroRows_MPIAIJ, 3297 0, 3298 #if defined(PETSC_HAVE_PBGL) 3299 0, 3300 #else 3301 0, 3302 #endif 3303 0, 3304 0, 3305 /*29*/ MatSetUp_MPIAIJ, 3306 #if defined(PETSC_HAVE_PBGL) 3307 0, 3308 #else 3309 0, 3310 #endif 3311 0, 3312 0, 3313 0, 3314 /*34*/ MatDuplicate_MPIAIJ, 3315 0, 3316 0, 3317 0, 3318 0, 3319 /*39*/ MatAXPY_MPIAIJ, 3320 MatGetSubMatrices_MPIAIJ, 3321 MatIncreaseOverlap_MPIAIJ, 3322 MatGetValues_MPIAIJ, 3323 MatCopy_MPIAIJ, 3324 /*44*/ MatGetRowMax_MPIAIJ, 3325 MatScale_MPIAIJ, 3326 0, 3327 0, 3328 MatZeroRowsColumns_MPIAIJ, 3329 /*49*/ MatSetRandom_MPIAIJ, 3330 0, 3331 0, 3332 0, 3333 0, 3334 /*54*/ MatFDColoringCreate_MPIAIJ, 3335 0, 3336 MatSetUnfactored_MPIAIJ, 3337 MatPermute_MPIAIJ, 3338 0, 3339 /*59*/ MatGetSubMatrix_MPIAIJ, 3340 MatDestroy_MPIAIJ, 3341 MatView_MPIAIJ, 3342 0, 3343 MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ, 3344 /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ, 3345 MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ, 3346 0, 3347 0, 3348 0, 3349 /*69*/ MatGetRowMaxAbs_MPIAIJ, 3350 MatGetRowMinAbs_MPIAIJ, 3351 0, 3352 MatSetColoring_MPIAIJ, 3353 0, 3354 MatSetValuesAdifor_MPIAIJ, 3355 /*75*/ MatFDColoringApply_AIJ, 3356 0, 3357 0, 3358 0, 3359 MatFindZeroDiagonals_MPIAIJ, 3360 /*80*/ 0, 3361 0, 3362 0, 3363 /*83*/ MatLoad_MPIAIJ, 3364 0, 3365 0, 3366 0, 3367 0, 3368 0, 3369 /*89*/ MatMatMult_MPIAIJ_MPIAIJ, 3370 MatMatMultSymbolic_MPIAIJ_MPIAIJ, 3371 MatMatMultNumeric_MPIAIJ_MPIAIJ, 3372 MatPtAP_MPIAIJ_MPIAIJ, 3373 MatPtAPSymbolic_MPIAIJ_MPIAIJ, 3374 /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ, 3375 0, 3376 0, 3377 0, 3378 0, 3379 /*99*/ 0, 3380 0, 3381 0, 3382 MatConjugate_MPIAIJ, 3383 0, 3384 /*104*/MatSetValuesRow_MPIAIJ, 3385 MatRealPart_MPIAIJ, 3386 MatImaginaryPart_MPIAIJ, 3387 0, 3388 0, 3389 /*109*/0, 3390 MatGetRedundantMatrix_MPIAIJ, 3391 MatGetRowMin_MPIAIJ, 3392 0, 3393 0, 3394 /*114*/MatGetSeqNonzeroStructure_MPIAIJ, 3395 0, 3396 0, 3397 0, 3398 0, 3399 /*119*/0, 3400 0, 3401 0, 3402 0, 3403 MatGetMultiProcBlock_MPIAIJ, 3404 /*124*/MatFindNonzeroRows_MPIAIJ, 3405 MatGetColumnNorms_MPIAIJ, 3406 MatInvertBlockDiagonal_MPIAIJ, 3407 0, 3408 MatGetSubMatricesParallel_MPIAIJ, 3409 /*129*/0, 3410 MatTransposeMatMult_MPIAIJ_MPIAIJ, 3411 MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ, 3412 MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ, 3413 0, 3414 /*134*/0, 3415 0, 3416 0, 3417 0, 3418 0, 3419 /*139*/0, 3420 0 3421 }; 3422 3423 /* ----------------------------------------------------------------------------------------*/ 3424 3425 #undef __FUNCT__ 3426 #define __FUNCT__ "MatStoreValues_MPIAIJ" 3427 PetscErrorCode MatStoreValues_MPIAIJ(Mat mat) 3428 { 3429 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3430 PetscErrorCode ierr; 3431 3432 PetscFunctionBegin; 3433 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 3434 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 3435 PetscFunctionReturn(0); 3436 } 3437 3438 #undef __FUNCT__ 3439 #define __FUNCT__ "MatRetrieveValues_MPIAIJ" 3440 PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat) 3441 { 3442 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 3443 PetscErrorCode ierr; 3444 3445 PetscFunctionBegin; 3446 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 3447 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 3448 PetscFunctionReturn(0); 3449 } 3450 3451 #undef __FUNCT__ 3452 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJ" 3453 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 3454 { 3455 Mat_MPIAIJ *b; 3456 PetscErrorCode ierr; 3457 3458 PetscFunctionBegin; 3459 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3460 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3461 b = (Mat_MPIAIJ*)B->data; 3462 3463 if (!B->preallocated) { 3464 /* Explicitly create 2 MATSEQAIJ matrices. */ 3465 ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr); 3466 ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr); 3467 ierr = MatSetBlockSizes(b->A,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3468 ierr = MatSetType(b->A,MATSEQAIJ);CHKERRQ(ierr); 3469 ierr = PetscLogObjectParent(B,b->A);CHKERRQ(ierr); 3470 ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr); 3471 ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr); 3472 ierr = MatSetBlockSizes(b->B,B->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 3473 ierr = MatSetType(b->B,MATSEQAIJ);CHKERRQ(ierr); 3474 ierr = PetscLogObjectParent(B,b->B);CHKERRQ(ierr); 3475 } 3476 3477 ierr = MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);CHKERRQ(ierr); 3478 ierr = MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);CHKERRQ(ierr); 3479 B->preallocated = PETSC_TRUE; 3480 PetscFunctionReturn(0); 3481 } 3482 3483 #undef __FUNCT__ 3484 #define __FUNCT__ "MatDuplicate_MPIAIJ" 3485 PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 3486 { 3487 Mat mat; 3488 Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data; 3489 PetscErrorCode ierr; 3490 3491 PetscFunctionBegin; 3492 *newmat = 0; 3493 ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr); 3494 ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr); 3495 ierr = MatSetBlockSizes(mat,matin->rmap->bs,matin->cmap->bs);CHKERRQ(ierr); 3496 ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr); 3497 ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 3498 a = (Mat_MPIAIJ*)mat->data; 3499 3500 mat->factortype = matin->factortype; 3501 mat->rmap->bs = matin->rmap->bs; 3502 mat->cmap->bs = matin->cmap->bs; 3503 mat->assembled = PETSC_TRUE; 3504 mat->insertmode = NOT_SET_VALUES; 3505 mat->preallocated = PETSC_TRUE; 3506 3507 a->size = oldmat->size; 3508 a->rank = oldmat->rank; 3509 a->donotstash = oldmat->donotstash; 3510 a->roworiented = oldmat->roworiented; 3511 a->rowindices = 0; 3512 a->rowvalues = 0; 3513 a->getrowactive = PETSC_FALSE; 3514 3515 ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr); 3516 ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr); 3517 3518 if (oldmat->colmap) { 3519 #if defined(PETSC_USE_CTABLE) 3520 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 3521 #else 3522 ierr = PetscMalloc((mat->cmap->N)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr); 3523 ierr = PetscLogObjectMemory(mat,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3524 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));CHKERRQ(ierr); 3525 #endif 3526 } else a->colmap = 0; 3527 if (oldmat->garray) { 3528 PetscInt len; 3529 len = oldmat->B->cmap->n; 3530 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&a->garray);CHKERRQ(ierr); 3531 ierr = PetscLogObjectMemory(mat,len*sizeof(PetscInt));CHKERRQ(ierr); 3532 if (len) { ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr); } 3533 } else a->garray = 0; 3534 3535 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 3536 ierr = PetscLogObjectParent(mat,a->lvec);CHKERRQ(ierr); 3537 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 3538 ierr = PetscLogObjectParent(mat,a->Mvctx);CHKERRQ(ierr); 3539 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 3540 ierr = PetscLogObjectParent(mat,a->A);CHKERRQ(ierr); 3541 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 3542 ierr = PetscLogObjectParent(mat,a->B);CHKERRQ(ierr); 3543 ierr = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr); 3544 *newmat = mat; 3545 PetscFunctionReturn(0); 3546 } 3547 3548 3549 3550 #undef __FUNCT__ 3551 #define __FUNCT__ "MatLoad_MPIAIJ" 3552 PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer) 3553 { 3554 PetscScalar *vals,*svals; 3555 MPI_Comm comm; 3556 PetscErrorCode ierr; 3557 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag; 3558 PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0,grows,gcols; 3559 PetscInt header[4],*rowlengths = 0,M,N,m,*cols; 3560 PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols; 3561 PetscInt cend,cstart,n,*rowners,sizesset=1; 3562 int fd; 3563 PetscInt bs = 1; 3564 3565 PetscFunctionBegin; 3566 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3567 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3568 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3569 if (!rank) { 3570 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3571 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 3572 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 3573 } 3574 3575 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 3576 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 3577 ierr = PetscOptionsEnd();CHKERRQ(ierr); 3578 3579 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) sizesset = 0; 3580 3581 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 3582 M = header[1]; N = header[2]; 3583 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 3584 if (sizesset && newMat->rmap->N < 0) newMat->rmap->N = M; 3585 if (sizesset && newMat->cmap->N < 0) newMat->cmap->N = N; 3586 3587 /* If global sizes are set, check if they are consistent with that given in the file */ 3588 if (sizesset) { 3589 ierr = MatGetSize(newMat,&grows,&gcols);CHKERRQ(ierr); 3590 } 3591 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); 3592 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); 3593 3594 /* determine ownership of all (block) rows */ 3595 if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs); 3596 if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */ 3597 else m = newMat->rmap->n; /* Set by user */ 3598 3599 ierr = PetscMalloc((size+1)*sizeof(PetscInt),&rowners);CHKERRQ(ierr); 3600 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 3601 3602 /* First process needs enough room for process with most rows */ 3603 if (!rank) { 3604 mmax = rowners[1]; 3605 for (i=2; i<=size; i++) { 3606 mmax = PetscMax(mmax, rowners[i]); 3607 } 3608 } else mmax = -1; /* unused, but compilers complain */ 3609 3610 rowners[0] = 0; 3611 for (i=2; i<=size; i++) { 3612 rowners[i] += rowners[i-1]; 3613 } 3614 rstart = rowners[rank]; 3615 rend = rowners[rank+1]; 3616 3617 /* distribute row lengths to all processors */ 3618 ierr = PetscMalloc2(m,PetscInt,&ourlens,m,PetscInt,&offlens);CHKERRQ(ierr); 3619 if (!rank) { 3620 ierr = PetscBinaryRead(fd,ourlens,m,PETSC_INT);CHKERRQ(ierr); 3621 ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3622 ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr); 3623 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 3624 for (j=0; j<m; j++) { 3625 procsnz[0] += ourlens[j]; 3626 } 3627 for (i=1; i<size; i++) { 3628 ierr = PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],PETSC_INT);CHKERRQ(ierr); 3629 /* calculate the number of nonzeros on each processor */ 3630 for (j=0; j<rowners[i+1]-rowners[i]; j++) { 3631 procsnz[i] += rowlengths[j]; 3632 } 3633 ierr = MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3634 } 3635 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3636 } else { 3637 ierr = MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3638 } 3639 3640 if (!rank) { 3641 /* determine max buffer needed and allocate it */ 3642 maxnz = 0; 3643 for (i=0; i<size; i++) { 3644 maxnz = PetscMax(maxnz,procsnz[i]); 3645 } 3646 ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr); 3647 3648 /* read in my part of the matrix column indices */ 3649 nz = procsnz[0]; 3650 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3651 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 3652 3653 /* read in every one elses and ship off */ 3654 for (i=1; i<size; i++) { 3655 nz = procsnz[i]; 3656 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 3657 ierr = MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 3658 } 3659 ierr = PetscFree(cols);CHKERRQ(ierr); 3660 } else { 3661 /* determine buffer space needed for message */ 3662 nz = 0; 3663 for (i=0; i<m; i++) { 3664 nz += ourlens[i]; 3665 } 3666 ierr = PetscMalloc(nz*sizeof(PetscInt),&mycols);CHKERRQ(ierr); 3667 3668 /* receive message of column indices*/ 3669 ierr = MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);CHKERRQ(ierr); 3670 } 3671 3672 /* determine column ownership if matrix is not square */ 3673 if (N != M) { 3674 if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank); 3675 else n = newMat->cmap->n; 3676 ierr = MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3677 cstart = cend - n; 3678 } else { 3679 cstart = rstart; 3680 cend = rend; 3681 n = cend - cstart; 3682 } 3683 3684 /* loop over local rows, determining number of off diagonal entries */ 3685 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 3686 jj = 0; 3687 for (i=0; i<m; i++) { 3688 for (j=0; j<ourlens[i]; j++) { 3689 if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++; 3690 jj++; 3691 } 3692 } 3693 3694 for (i=0; i<m; i++) { 3695 ourlens[i] -= offlens[i]; 3696 } 3697 if (!sizesset) { 3698 ierr = MatSetSizes(newMat,m,n,M,N);CHKERRQ(ierr); 3699 } 3700 3701 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 3702 3703 ierr = MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);CHKERRQ(ierr); 3704 3705 for (i=0; i<m; i++) { 3706 ourlens[i] += offlens[i]; 3707 } 3708 3709 if (!rank) { 3710 ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3711 3712 /* read in my part of the matrix numerical values */ 3713 nz = procsnz[0]; 3714 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3715 3716 /* insert into matrix */ 3717 jj = rstart; 3718 smycols = mycols; 3719 svals = vals; 3720 for (i=0; i<m; i++) { 3721 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3722 smycols += ourlens[i]; 3723 svals += ourlens[i]; 3724 jj++; 3725 } 3726 3727 /* read in other processors and ship out */ 3728 for (i=1; i<size; i++) { 3729 nz = procsnz[i]; 3730 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 3731 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3732 } 3733 ierr = PetscFree(procsnz);CHKERRQ(ierr); 3734 } else { 3735 /* receive numeric values */ 3736 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 3737 3738 /* receive message of values*/ 3739 ierr = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);CHKERRQ(ierr); 3740 3741 /* insert into matrix */ 3742 jj = rstart; 3743 smycols = mycols; 3744 svals = vals; 3745 for (i=0; i<m; i++) { 3746 ierr = MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 3747 smycols += ourlens[i]; 3748 svals += ourlens[i]; 3749 jj++; 3750 } 3751 } 3752 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 3753 ierr = PetscFree(vals);CHKERRQ(ierr); 3754 ierr = PetscFree(mycols);CHKERRQ(ierr); 3755 ierr = PetscFree(rowners);CHKERRQ(ierr); 3756 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3757 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3758 PetscFunctionReturn(0); 3759 } 3760 3761 #undef __FUNCT__ 3762 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ" 3763 PetscErrorCode MatGetSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat) 3764 { 3765 PetscErrorCode ierr; 3766 IS iscol_local; 3767 PetscInt csize; 3768 3769 PetscFunctionBegin; 3770 ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr); 3771 if (call == MAT_REUSE_MATRIX) { 3772 ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr); 3773 if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3774 } else { 3775 PetscInt cbs; 3776 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 3777 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 3778 ierr = ISSetBlockSize(iscol_local,cbs);CHKERRQ(ierr); 3779 } 3780 ierr = MatGetSubMatrix_MPIAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr); 3781 if (call == MAT_INITIAL_MATRIX) { 3782 ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr); 3783 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 3784 } 3785 PetscFunctionReturn(0); 3786 } 3787 3788 extern PetscErrorCode MatGetSubMatrices_MPIAIJ_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,Mat*); 3789 #undef __FUNCT__ 3790 #define __FUNCT__ "MatGetSubMatrix_MPIAIJ_Private" 3791 /* 3792 Not great since it makes two copies of the submatrix, first an SeqAIJ 3793 in local and then by concatenating the local matrices the end result. 3794 Writing it directly would be much like MatGetSubMatrices_MPIAIJ() 3795 3796 Note: This requires a sequential iscol with all indices. 3797 */ 3798 PetscErrorCode MatGetSubMatrix_MPIAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat) 3799 { 3800 PetscErrorCode ierr; 3801 PetscMPIInt rank,size; 3802 PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs; 3803 PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol; 3804 PetscBool allcolumns, colflag; 3805 Mat M,Mreuse; 3806 MatScalar *vwork,*aa; 3807 MPI_Comm comm; 3808 Mat_SeqAIJ *aij; 3809 3810 PetscFunctionBegin; 3811 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 3812 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 3813 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3814 3815 ierr = ISIdentity(iscol,&colflag);CHKERRQ(ierr); 3816 ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr); 3817 if (colflag && ncol == mat->cmap->N) { 3818 allcolumns = PETSC_TRUE; 3819 } else { 3820 allcolumns = PETSC_FALSE; 3821 } 3822 if (call == MAT_REUSE_MATRIX) { 3823 ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr); 3824 if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse"); 3825 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3826 } else { 3827 ierr = MatGetSubMatrices_MPIAIJ_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&allcolumns,&Mreuse);CHKERRQ(ierr); 3828 } 3829 3830 /* 3831 m - number of local rows 3832 n - number of columns (same on all processors) 3833 rstart - first row in new global matrix generated 3834 */ 3835 ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr); 3836 ierr = MatGetBlockSizes(Mreuse,&bs,&cbs);CHKERRQ(ierr); 3837 if (call == MAT_INITIAL_MATRIX) { 3838 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3839 ii = aij->i; 3840 jj = aij->j; 3841 3842 /* 3843 Determine the number of non-zeros in the diagonal and off-diagonal 3844 portions of the matrix in order to do correct preallocation 3845 */ 3846 3847 /* first get start and end of "diagonal" columns */ 3848 if (csize == PETSC_DECIDE) { 3849 ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr); 3850 if (mglobal == n) { /* square matrix */ 3851 nlocal = m; 3852 } else { 3853 nlocal = n/size + ((n % size) > rank); 3854 } 3855 } else { 3856 nlocal = csize; 3857 } 3858 ierr = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 3859 rstart = rend - nlocal; 3860 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); 3861 3862 /* next, compute all the lengths */ 3863 ierr = PetscMalloc((2*m+1)*sizeof(PetscInt),&dlens);CHKERRQ(ierr); 3864 olens = dlens + m; 3865 for (i=0; i<m; i++) { 3866 jend = ii[i+1] - ii[i]; 3867 olen = 0; 3868 dlen = 0; 3869 for (j=0; j<jend; j++) { 3870 if (*jj < rstart || *jj >= rend) olen++; 3871 else dlen++; 3872 jj++; 3873 } 3874 olens[i] = olen; 3875 dlens[i] = dlen; 3876 } 3877 ierr = MatCreate(comm,&M);CHKERRQ(ierr); 3878 ierr = MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);CHKERRQ(ierr); 3879 ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); 3880 ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr); 3881 ierr = MatMPIAIJSetPreallocation(M,0,dlens,0,olens);CHKERRQ(ierr); 3882 ierr = PetscFree(dlens);CHKERRQ(ierr); 3883 } else { 3884 PetscInt ml,nl; 3885 3886 M = *newmat; 3887 ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr); 3888 if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request"); 3889 ierr = MatZeroEntries(M);CHKERRQ(ierr); 3890 /* 3891 The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly, 3892 rather than the slower MatSetValues(). 3893 */ 3894 M->was_assembled = PETSC_TRUE; 3895 M->assembled = PETSC_FALSE; 3896 } 3897 ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr); 3898 aij = (Mat_SeqAIJ*)(Mreuse)->data; 3899 ii = aij->i; 3900 jj = aij->j; 3901 aa = aij->a; 3902 for (i=0; i<m; i++) { 3903 row = rstart + i; 3904 nz = ii[i+1] - ii[i]; 3905 cwork = jj; jj += nz; 3906 vwork = aa; aa += nz; 3907 ierr = MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr); 3908 } 3909 3910 ierr = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3911 ierr = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3912 *newmat = M; 3913 3914 /* save submatrix used in processor for next request */ 3915 if (call == MAT_INITIAL_MATRIX) { 3916 ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr); 3917 ierr = MatDestroy(&Mreuse);CHKERRQ(ierr); 3918 } 3919 PetscFunctionReturn(0); 3920 } 3921 3922 #undef __FUNCT__ 3923 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR_MPIAIJ" 3924 PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3925 { 3926 PetscInt m,cstart, cend,j,nnz,i,d; 3927 PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii; 3928 const PetscInt *JJ; 3929 PetscScalar *values; 3930 PetscErrorCode ierr; 3931 3932 PetscFunctionBegin; 3933 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]); 3934 3935 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3936 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3937 m = B->rmap->n; 3938 cstart = B->cmap->rstart; 3939 cend = B->cmap->rend; 3940 rstart = B->rmap->rstart; 3941 3942 ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr); 3943 3944 #if defined(PETSC_USE_DEBUGGING) 3945 for (i=0; i<m; i++) { 3946 nnz = Ii[i+1]- Ii[i]; 3947 JJ = J + Ii[i]; 3948 if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz); 3949 if (nnz && (JJ[0] < 0)) SETERRRQ1(PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,j); 3950 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); 3951 } 3952 #endif 3953 3954 for (i=0; i<m; i++) { 3955 nnz = Ii[i+1]- Ii[i]; 3956 JJ = J + Ii[i]; 3957 nnz_max = PetscMax(nnz_max,nnz); 3958 d = 0; 3959 for (j=0; j<nnz; j++) { 3960 if (cstart <= JJ[j] && JJ[j] < cend) d++; 3961 } 3962 d_nnz[i] = d; 3963 o_nnz[i] = nnz - d; 3964 } 3965 ierr = MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);CHKERRQ(ierr); 3966 ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr); 3967 3968 if (v) values = (PetscScalar*)v; 3969 else { 3970 ierr = PetscMalloc((nnz_max+1)*sizeof(PetscScalar),&values);CHKERRQ(ierr); 3971 ierr = PetscMemzero(values,nnz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3972 } 3973 3974 for (i=0; i<m; i++) { 3975 ii = i + rstart; 3976 nnz = Ii[i+1]- Ii[i]; 3977 ierr = MatSetValues_MPIAIJ(B,1,&ii,nnz,J+Ii[i],values+(v ? Ii[i] : 0),INSERT_VALUES);CHKERRQ(ierr); 3978 } 3979 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3980 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3981 3982 if (!v) { 3983 ierr = PetscFree(values);CHKERRQ(ierr); 3984 } 3985 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3986 PetscFunctionReturn(0); 3987 } 3988 3989 #undef __FUNCT__ 3990 #define __FUNCT__ "MatMPIAIJSetPreallocationCSR" 3991 /*@ 3992 MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format 3993 (the default parallel PETSc format). 3994 3995 Collective on MPI_Comm 3996 3997 Input Parameters: 3998 + B - the matrix 3999 . i - the indices into j for the start of each local row (starts with zero) 4000 . j - the column indices for each local row (starts with zero) 4001 - v - optional values in the matrix 4002 4003 Level: developer 4004 4005 Notes: 4006 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4007 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4008 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4009 4010 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4011 4012 The format which is used for the sparse matrix input, is equivalent to a 4013 row-major ordering.. i.e for the following matrix, the input data expected is 4014 as shown: 4015 4016 1 0 0 4017 2 0 3 P0 4018 ------- 4019 4 5 6 P1 4020 4021 Process0 [P0]: rows_owned=[0,1] 4022 i = {0,1,3} [size = nrow+1 = 2+1] 4023 j = {0,0,2} [size = nz = 6] 4024 v = {1,2,3} [size = nz = 6] 4025 4026 Process1 [P1]: rows_owned=[2] 4027 i = {0,3} [size = nrow+1 = 1+1] 4028 j = {0,1,2} [size = nz = 6] 4029 v = {4,5,6} [size = nz = 6] 4030 4031 .keywords: matrix, aij, compressed row, sparse, parallel 4032 4033 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, 4034 MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays() 4035 @*/ 4036 PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[]) 4037 { 4038 PetscErrorCode ierr; 4039 4040 PetscFunctionBegin; 4041 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4042 PetscFunctionReturn(0); 4043 } 4044 4045 #undef __FUNCT__ 4046 #define __FUNCT__ "MatMPIAIJSetPreallocation" 4047 /*@C 4048 MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format 4049 (the default parallel PETSc format). For good matrix assembly performance 4050 the user should preallocate the matrix storage by setting the parameters 4051 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4052 performance can be increased by more than a factor of 50. 4053 4054 Collective on MPI_Comm 4055 4056 Input Parameters: 4057 + A - the matrix 4058 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4059 (same value is used for all local rows) 4060 . d_nnz - array containing the number of nonzeros in the various rows of the 4061 DIAGONAL portion of the local submatrix (possibly different for each row) 4062 or NULL, if d_nz is used to specify the nonzero structure. 4063 The size of this array is equal to the number of local rows, i.e 'm'. 4064 For matrices that will be factored, you must leave room for (and set) 4065 the diagonal entry even if it is zero. 4066 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4067 submatrix (same value is used for all local rows). 4068 - o_nnz - array containing the number of nonzeros in the various rows of the 4069 OFF-DIAGONAL portion of the local submatrix (possibly different for 4070 each row) or NULL, if o_nz is used to specify the nonzero 4071 structure. The size of this array is equal to the number 4072 of local rows, i.e 'm'. 4073 4074 If the *_nnz parameter is given then the *_nz parameter is ignored 4075 4076 The AIJ format (also called the Yale sparse matrix format or 4077 compressed row storage (CSR)), is fully compatible with standard Fortran 77 4078 storage. The stored row and column indices begin with zero. 4079 See the <A href="../../docs/manual.pdf#nameddest=ch_mat">Mat chapter of the users manual</A> for details. 4080 4081 The parallel matrix is partitioned such that the first m0 rows belong to 4082 process 0, the next m1 rows belong to process 1, the next m2 rows belong 4083 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 4084 4085 The DIAGONAL portion of the local submatrix of a processor can be defined 4086 as the submatrix which is obtained by extraction the part corresponding to 4087 the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the 4088 first row that belongs to the processor, r2 is the last row belonging to 4089 the this processor, and c1-c2 is range of indices of the local part of a 4090 vector suitable for applying the matrix to. This is an mxn matrix. In the 4091 common case of a square matrix, the row and column ranges are the same and 4092 the DIAGONAL part is also square. The remaining portion of the local 4093 submatrix (mxN) constitute the OFF-DIAGONAL portion. 4094 4095 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4096 4097 You can call MatGetInfo() to get information on how effective the preallocation was; 4098 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 4099 You can also run with the option -info and look for messages with the string 4100 malloc in them to see if additional memory allocation was needed. 4101 4102 Example usage: 4103 4104 Consider the following 8x8 matrix with 34 non-zero values, that is 4105 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4106 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4107 as follows: 4108 4109 .vb 4110 1 2 0 | 0 3 0 | 0 4 4111 Proc0 0 5 6 | 7 0 0 | 8 0 4112 9 0 10 | 11 0 0 | 12 0 4113 ------------------------------------- 4114 13 0 14 | 15 16 17 | 0 0 4115 Proc1 0 18 0 | 19 20 21 | 0 0 4116 0 0 0 | 22 23 0 | 24 0 4117 ------------------------------------- 4118 Proc2 25 26 27 | 0 0 28 | 29 0 4119 30 0 0 | 31 32 33 | 0 34 4120 .ve 4121 4122 This can be represented as a collection of submatrices as: 4123 4124 .vb 4125 A B C 4126 D E F 4127 G H I 4128 .ve 4129 4130 Where the submatrices A,B,C are owned by proc0, D,E,F are 4131 owned by proc1, G,H,I are owned by proc2. 4132 4133 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4134 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4135 The 'M','N' parameters are 8,8, and have the same values on all procs. 4136 4137 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4138 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4139 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4140 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4141 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4142 matrix, ans [DF] as another SeqAIJ matrix. 4143 4144 When d_nz, o_nz parameters are specified, d_nz storage elements are 4145 allocated for every row of the local diagonal submatrix, and o_nz 4146 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4147 One way to choose d_nz and o_nz is to use the max nonzerors per local 4148 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4149 In this case, the values of d_nz,o_nz are: 4150 .vb 4151 proc0 : dnz = 2, o_nz = 2 4152 proc1 : dnz = 3, o_nz = 2 4153 proc2 : dnz = 1, o_nz = 4 4154 .ve 4155 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4156 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4157 for proc3. i.e we are using 12+15+10=37 storage locations to store 4158 34 values. 4159 4160 When d_nnz, o_nnz parameters are specified, the storage is specified 4161 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4162 In the above case the values for d_nnz,o_nnz are: 4163 .vb 4164 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4165 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4166 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4167 .ve 4168 Here the space allocated is sum of all the above values i.e 34, and 4169 hence pre-allocation is perfect. 4170 4171 Level: intermediate 4172 4173 .keywords: matrix, aij, compressed row, sparse, parallel 4174 4175 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(), 4176 MPIAIJ, MatGetInfo(), PetscSplitOwnership() 4177 @*/ 4178 PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 4179 { 4180 PetscErrorCode ierr; 4181 4182 PetscFunctionBegin; 4183 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4184 PetscValidType(B,1); 4185 ierr = PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr); 4186 PetscFunctionReturn(0); 4187 } 4188 4189 #undef __FUNCT__ 4190 #define __FUNCT__ "MatCreateMPIAIJWithArrays" 4191 /*@ 4192 MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard 4193 CSR format the local rows. 4194 4195 Collective on MPI_Comm 4196 4197 Input Parameters: 4198 + comm - MPI communicator 4199 . m - number of local rows (Cannot be PETSC_DECIDE) 4200 . n - This value should be the same as the local size used in creating the 4201 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4202 calculated if N is given) For square matrices n is almost always m. 4203 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4204 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4205 . i - row indices 4206 . j - column indices 4207 - a - matrix values 4208 4209 Output Parameter: 4210 . mat - the matrix 4211 4212 Level: intermediate 4213 4214 Notes: 4215 The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc; 4216 thus you CANNOT change the matrix entries by changing the values of a[] after you have 4217 called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays. 4218 4219 The i and j indices are 0 based, and i indices are indices corresponding to the local j array. 4220 4221 The format which is used for the sparse matrix input, is equivalent to a 4222 row-major ordering.. i.e for the following matrix, the input data expected is 4223 as shown: 4224 4225 1 0 0 4226 2 0 3 P0 4227 ------- 4228 4 5 6 P1 4229 4230 Process0 [P0]: rows_owned=[0,1] 4231 i = {0,1,3} [size = nrow+1 = 2+1] 4232 j = {0,0,2} [size = nz = 6] 4233 v = {1,2,3} [size = nz = 6] 4234 4235 Process1 [P1]: rows_owned=[2] 4236 i = {0,3} [size = nrow+1 = 1+1] 4237 j = {0,1,2} [size = nz = 6] 4238 v = {4,5,6} [size = nz = 6] 4239 4240 .keywords: matrix, aij, compressed row, sparse, parallel 4241 4242 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4243 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays() 4244 @*/ 4245 PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat) 4246 { 4247 PetscErrorCode ierr; 4248 4249 PetscFunctionBegin; 4250 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4251 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 4252 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4253 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 4254 /* ierr = MatSetBlockSizes(M,bs,cbs);CHKERRQ(ierr); */ 4255 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 4256 ierr = MatMPIAIJSetPreallocationCSR(*mat,i,j,a);CHKERRQ(ierr); 4257 PetscFunctionReturn(0); 4258 } 4259 4260 #undef __FUNCT__ 4261 #define __FUNCT__ "MatCreateAIJ" 4262 /*@C 4263 MatCreateAIJ - Creates a sparse parallel matrix in AIJ format 4264 (the default parallel PETSc format). For good matrix assembly performance 4265 the user should preallocate the matrix storage by setting the parameters 4266 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 4267 performance can be increased by more than a factor of 50. 4268 4269 Collective on MPI_Comm 4270 4271 Input Parameters: 4272 + comm - MPI communicator 4273 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 4274 This value should be the same as the local size used in creating the 4275 y vector for the matrix-vector product y = Ax. 4276 . n - This value should be the same as the local size used in creating the 4277 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 4278 calculated if N is given) For square matrices n is almost always m. 4279 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 4280 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 4281 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 4282 (same value is used for all local rows) 4283 . d_nnz - array containing the number of nonzeros in the various rows of the 4284 DIAGONAL portion of the local submatrix (possibly different for each row) 4285 or NULL, if d_nz is used to specify the nonzero structure. 4286 The size of this array is equal to the number of local rows, i.e 'm'. 4287 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 4288 submatrix (same value is used for all local rows). 4289 - o_nnz - array containing the number of nonzeros in the various rows of the 4290 OFF-DIAGONAL portion of the local submatrix (possibly different for 4291 each row) or NULL, if o_nz is used to specify the nonzero 4292 structure. The size of this array is equal to the number 4293 of local rows, i.e 'm'. 4294 4295 Output Parameter: 4296 . A - the matrix 4297 4298 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 4299 MatXXXXSetPreallocation() paradgm instead of this routine directly. 4300 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 4301 4302 Notes: 4303 If the *_nnz parameter is given then the *_nz parameter is ignored 4304 4305 m,n,M,N parameters specify the size of the matrix, and its partitioning across 4306 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 4307 storage requirements for this matrix. 4308 4309 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 4310 processor than it must be used on all processors that share the object for 4311 that argument. 4312 4313 The user MUST specify either the local or global matrix dimensions 4314 (possibly both). 4315 4316 The parallel matrix is partitioned across processors such that the 4317 first m0 rows belong to process 0, the next m1 rows belong to 4318 process 1, the next m2 rows belong to process 2 etc.. where 4319 m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores 4320 values corresponding to [m x N] submatrix. 4321 4322 The columns are logically partitioned with the n0 columns belonging 4323 to 0th partition, the next n1 columns belonging to the next 4324 partition etc.. where n0,n1,n2... are the the input parameter 'n'. 4325 4326 The DIAGONAL portion of the local submatrix on any given processor 4327 is the submatrix corresponding to the rows and columns m,n 4328 corresponding to the given processor. i.e diagonal matrix on 4329 process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1] 4330 etc. The remaining portion of the local submatrix [m x (N-n)] 4331 constitute the OFF-DIAGONAL portion. The example below better 4332 illustrates this concept. 4333 4334 For a square global matrix we define each processor's diagonal portion 4335 to be its local rows and the corresponding columns (a square submatrix); 4336 each processor's off-diagonal portion encompasses the remainder of the 4337 local matrix (a rectangular submatrix). 4338 4339 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 4340 4341 When calling this routine with a single process communicator, a matrix of 4342 type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this 4343 type of communicator, use the construction mechanism: 4344 MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...); 4345 4346 By default, this format uses inodes (identical nodes) when possible. 4347 We search for consecutive rows with the same nonzero structure, thereby 4348 reusing matrix information to achieve increased efficiency. 4349 4350 Options Database Keys: 4351 + -mat_no_inode - Do not use inodes 4352 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 4353 - -mat_aij_oneindex - Internally use indexing starting at 1 4354 rather than 0. Note that when calling MatSetValues(), 4355 the user still MUST index entries starting at 0! 4356 4357 4358 Example usage: 4359 4360 Consider the following 8x8 matrix with 34 non-zero values, that is 4361 assembled across 3 processors. Lets assume that proc0 owns 3 rows, 4362 proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown 4363 as follows: 4364 4365 .vb 4366 1 2 0 | 0 3 0 | 0 4 4367 Proc0 0 5 6 | 7 0 0 | 8 0 4368 9 0 10 | 11 0 0 | 12 0 4369 ------------------------------------- 4370 13 0 14 | 15 16 17 | 0 0 4371 Proc1 0 18 0 | 19 20 21 | 0 0 4372 0 0 0 | 22 23 0 | 24 0 4373 ------------------------------------- 4374 Proc2 25 26 27 | 0 0 28 | 29 0 4375 30 0 0 | 31 32 33 | 0 34 4376 .ve 4377 4378 This can be represented as a collection of submatrices as: 4379 4380 .vb 4381 A B C 4382 D E F 4383 G H I 4384 .ve 4385 4386 Where the submatrices A,B,C are owned by proc0, D,E,F are 4387 owned by proc1, G,H,I are owned by proc2. 4388 4389 The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4390 The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively. 4391 The 'M','N' parameters are 8,8, and have the same values on all procs. 4392 4393 The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are 4394 submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices 4395 corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively. 4396 Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL 4397 part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ 4398 matrix, ans [DF] as another SeqAIJ matrix. 4399 4400 When d_nz, o_nz parameters are specified, d_nz storage elements are 4401 allocated for every row of the local diagonal submatrix, and o_nz 4402 storage locations are allocated for every row of the OFF-DIAGONAL submat. 4403 One way to choose d_nz and o_nz is to use the max nonzerors per local 4404 rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices. 4405 In this case, the values of d_nz,o_nz are: 4406 .vb 4407 proc0 : dnz = 2, o_nz = 2 4408 proc1 : dnz = 3, o_nz = 2 4409 proc2 : dnz = 1, o_nz = 4 4410 .ve 4411 We are allocating m*(d_nz+o_nz) storage locations for every proc. This 4412 translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10 4413 for proc3. i.e we are using 12+15+10=37 storage locations to store 4414 34 values. 4415 4416 When d_nnz, o_nnz parameters are specified, the storage is specified 4417 for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices. 4418 In the above case the values for d_nnz,o_nnz are: 4419 .vb 4420 proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2] 4421 proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1] 4422 proc2: d_nnz = [1,1] and o_nnz = [4,4] 4423 .ve 4424 Here the space allocated is sum of all the above values i.e 34, and 4425 hence pre-allocation is perfect. 4426 4427 Level: intermediate 4428 4429 .keywords: matrix, aij, compressed row, sparse, parallel 4430 4431 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 4432 MPIAIJ, MatCreateMPIAIJWithArrays() 4433 @*/ 4434 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) 4435 { 4436 PetscErrorCode ierr; 4437 PetscMPIInt size; 4438 4439 PetscFunctionBegin; 4440 ierr = MatCreate(comm,A);CHKERRQ(ierr); 4441 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 4442 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4443 if (size > 1) { 4444 ierr = MatSetType(*A,MATMPIAIJ);CHKERRQ(ierr); 4445 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 4446 } else { 4447 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 4448 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 4449 } 4450 PetscFunctionReturn(0); 4451 } 4452 4453 #undef __FUNCT__ 4454 #define __FUNCT__ "MatMPIAIJGetSeqAIJ" 4455 PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[]) 4456 { 4457 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4458 4459 PetscFunctionBegin; 4460 *Ad = a->A; 4461 *Ao = a->B; 4462 *colmap = a->garray; 4463 PetscFunctionReturn(0); 4464 } 4465 4466 #undef __FUNCT__ 4467 #define __FUNCT__ "MatSetColoring_MPIAIJ" 4468 PetscErrorCode MatSetColoring_MPIAIJ(Mat A,ISColoring coloring) 4469 { 4470 PetscErrorCode ierr; 4471 PetscInt i; 4472 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4473 4474 PetscFunctionBegin; 4475 if (coloring->ctype == IS_COLORING_GLOBAL) { 4476 ISColoringValue *allcolors,*colors; 4477 ISColoring ocoloring; 4478 4479 /* set coloring for diagonal portion */ 4480 ierr = MatSetColoring_SeqAIJ(a->A,coloring);CHKERRQ(ierr); 4481 4482 /* set coloring for off-diagonal portion */ 4483 ierr = ISAllGatherColors(PetscObjectComm((PetscObject)A),coloring->n,coloring->colors,NULL,&allcolors);CHKERRQ(ierr); 4484 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4485 for (i=0; i<a->B->cmap->n; i++) { 4486 colors[i] = allcolors[a->garray[i]]; 4487 } 4488 ierr = PetscFree(allcolors);CHKERRQ(ierr); 4489 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4490 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4491 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4492 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4493 ISColoringValue *colors; 4494 PetscInt *larray; 4495 ISColoring ocoloring; 4496 4497 /* set coloring for diagonal portion */ 4498 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4499 for (i=0; i<a->A->cmap->n; i++) { 4500 larray[i] = i + A->cmap->rstart; 4501 } 4502 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4503 ierr = PetscMalloc((a->A->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4504 for (i=0; i<a->A->cmap->n; i++) { 4505 colors[i] = coloring->colors[larray[i]]; 4506 } 4507 ierr = PetscFree(larray);CHKERRQ(ierr); 4508 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,a->A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4509 ierr = MatSetColoring_SeqAIJ(a->A,ocoloring);CHKERRQ(ierr); 4510 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4511 4512 /* set coloring for off-diagonal portion */ 4513 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4514 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,a->B->cmap->n,a->garray,NULL,larray);CHKERRQ(ierr); 4515 ierr = PetscMalloc((a->B->cmap->n+1)*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4516 for (i=0; i<a->B->cmap->n; i++) { 4517 colors[i] = coloring->colors[larray[i]]; 4518 } 4519 ierr = PetscFree(larray);CHKERRQ(ierr); 4520 ierr = ISColoringCreate(MPI_COMM_SELF,coloring->n,a->B->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4521 ierr = MatSetColoring_SeqAIJ(a->B,ocoloring);CHKERRQ(ierr); 4522 ierr = ISColoringDestroy(&ocoloring);CHKERRQ(ierr); 4523 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support ISColoringType %d",(int)coloring->ctype); 4524 PetscFunctionReturn(0); 4525 } 4526 4527 #undef __FUNCT__ 4528 #define __FUNCT__ "MatSetValuesAdifor_MPIAIJ" 4529 PetscErrorCode MatSetValuesAdifor_MPIAIJ(Mat A,PetscInt nl,void *advalues) 4530 { 4531 Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data; 4532 PetscErrorCode ierr; 4533 4534 PetscFunctionBegin; 4535 ierr = MatSetValuesAdifor_SeqAIJ(a->A,nl,advalues);CHKERRQ(ierr); 4536 ierr = MatSetValuesAdifor_SeqAIJ(a->B,nl,advalues);CHKERRQ(ierr); 4537 PetscFunctionReturn(0); 4538 } 4539 4540 #undef __FUNCT__ 4541 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJSymbolic" 4542 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJSymbolic(MPI_Comm comm,Mat inmat,PetscInt n,Mat *outmat) 4543 { 4544 PetscErrorCode ierr; 4545 PetscInt m,N,i,rstart,nnz,*dnz,*onz,sum,bs,cbs; 4546 PetscInt *indx; 4547 4548 PetscFunctionBegin; 4549 /* This routine will ONLY return MPIAIJ type matrix */ 4550 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4551 ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr); 4552 if (n == PETSC_DECIDE) { 4553 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 4554 } 4555 /* Check sum(n) = N */ 4556 ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4557 if (sum != N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",N); 4558 4559 ierr = MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 4560 rstart -= m; 4561 4562 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 4563 for (i=0; i<m; i++) { 4564 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4565 ierr = MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);CHKERRQ(ierr); 4566 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);CHKERRQ(ierr); 4567 } 4568 4569 ierr = MatCreate(comm,outmat);CHKERRQ(ierr); 4570 ierr = MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 4571 ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr); 4572 ierr = MatSetType(*outmat,MATMPIAIJ);CHKERRQ(ierr); 4573 ierr = MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);CHKERRQ(ierr); 4574 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 4575 PetscFunctionReturn(0); 4576 } 4577 4578 #undef __FUNCT__ 4579 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJNumeric" 4580 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJNumeric(MPI_Comm comm,Mat inmat,PetscInt n,Mat outmat) 4581 { 4582 PetscErrorCode ierr; 4583 PetscInt m,N,i,rstart,nnz,Ii; 4584 PetscInt *indx; 4585 PetscScalar *values; 4586 4587 PetscFunctionBegin; 4588 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 4589 ierr = MatGetOwnershipRange(outmat,&rstart,NULL);CHKERRQ(ierr); 4590 for (i=0; i<m; i++) { 4591 ierr = MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4592 Ii = i + rstart; 4593 ierr = MatSetValues(outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4594 ierr = MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr); 4595 } 4596 ierr = MatAssemblyBegin(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4597 ierr = MatAssemblyEnd(outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4598 PetscFunctionReturn(0); 4599 } 4600 4601 #undef __FUNCT__ 4602 #define __FUNCT__ "MatCreateMPIAIJConcatenateSeqAIJ" 4603 /*@ 4604 MatCreateMPIAIJConcatenateSeqAIJ - Creates a single large PETSc matrix by concatenating sequential 4605 matrices from each processor 4606 4607 Collective on MPI_Comm 4608 4609 Input Parameters: 4610 + comm - the communicators the parallel matrix will live on 4611 . inmat - the input sequential matrices 4612 . n - number of local columns (or PETSC_DECIDE) 4613 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 4614 4615 Output Parameter: 4616 . outmat - the parallel matrix generated 4617 4618 Level: advanced 4619 4620 Notes: The number of columns of the matrix in EACH processor MUST be the same. 4621 4622 @*/ 4623 PetscErrorCode MatCreateMPIAIJConcatenateSeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4624 { 4625 PetscErrorCode ierr; 4626 PetscMPIInt size; 4627 4628 PetscFunctionBegin; 4629 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4630 ierr = PetscLogEventBegin(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4631 if (size == 1) { 4632 if (scall == MAT_INITIAL_MATRIX) { 4633 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4634 } else { 4635 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4636 } 4637 } else { 4638 if (scall == MAT_INITIAL_MATRIX) { 4639 ierr = MatCreateMPIAIJConcatenateSeqAIJSymbolic(comm,inmat,n,outmat);CHKERRQ(ierr); 4640 } 4641 ierr = MatCreateMPIAIJConcatenateSeqAIJNumeric(comm,inmat,n,*outmat);CHKERRQ(ierr); 4642 } 4643 ierr = PetscLogEventEnd(MAT_Merge,inmat,0,0,0);CHKERRQ(ierr); 4644 PetscFunctionReturn(0); 4645 } 4646 4647 #undef __FUNCT__ 4648 #define __FUNCT__ "MatFileSplit" 4649 PetscErrorCode MatFileSplit(Mat A,char *outfile) 4650 { 4651 PetscErrorCode ierr; 4652 PetscMPIInt rank; 4653 PetscInt m,N,i,rstart,nnz; 4654 size_t len; 4655 const PetscInt *indx; 4656 PetscViewer out; 4657 char *name; 4658 Mat B; 4659 const PetscScalar *values; 4660 4661 PetscFunctionBegin; 4662 ierr = MatGetLocalSize(A,&m,0);CHKERRQ(ierr); 4663 ierr = MatGetSize(A,0,&N);CHKERRQ(ierr); 4664 /* Should this be the type of the diagonal block of A? */ 4665 ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr); 4666 ierr = MatSetSizes(B,m,N,m,N);CHKERRQ(ierr); 4667 ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4668 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 4669 ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); 4670 ierr = MatGetOwnershipRange(A,&rstart,0);CHKERRQ(ierr); 4671 for (i=0; i<m; i++) { 4672 ierr = MatGetRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4673 ierr = MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr); 4674 ierr = MatRestoreRow(A,i+rstart,&nnz,&indx,&values);CHKERRQ(ierr); 4675 } 4676 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4677 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4678 4679 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr); 4680 ierr = PetscStrlen(outfile,&len);CHKERRQ(ierr); 4681 ierr = PetscMalloc((len+5)*sizeof(char),&name);CHKERRQ(ierr); 4682 sprintf(name,"%s.%d",outfile,rank); 4683 ierr = PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);CHKERRQ(ierr); 4684 ierr = PetscFree(name);CHKERRQ(ierr); 4685 ierr = MatView(B,out);CHKERRQ(ierr); 4686 ierr = PetscViewerDestroy(&out);CHKERRQ(ierr); 4687 ierr = MatDestroy(&B);CHKERRQ(ierr); 4688 PetscFunctionReturn(0); 4689 } 4690 4691 extern PetscErrorCode MatDestroy_MPIAIJ(Mat); 4692 #undef __FUNCT__ 4693 #define __FUNCT__ "MatDestroy_MPIAIJ_SeqsToMPI" 4694 PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A) 4695 { 4696 PetscErrorCode ierr; 4697 Mat_Merge_SeqsToMPI *merge; 4698 PetscContainer container; 4699 4700 PetscFunctionBegin; 4701 ierr = PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4702 if (container) { 4703 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4704 ierr = PetscFree(merge->id_r);CHKERRQ(ierr); 4705 ierr = PetscFree(merge->len_s);CHKERRQ(ierr); 4706 ierr = PetscFree(merge->len_r);CHKERRQ(ierr); 4707 ierr = PetscFree(merge->bi);CHKERRQ(ierr); 4708 ierr = PetscFree(merge->bj);CHKERRQ(ierr); 4709 ierr = PetscFree(merge->buf_ri[0]);CHKERRQ(ierr); 4710 ierr = PetscFree(merge->buf_ri);CHKERRQ(ierr); 4711 ierr = PetscFree(merge->buf_rj[0]);CHKERRQ(ierr); 4712 ierr = PetscFree(merge->buf_rj);CHKERRQ(ierr); 4713 ierr = PetscFree(merge->coi);CHKERRQ(ierr); 4714 ierr = PetscFree(merge->coj);CHKERRQ(ierr); 4715 ierr = PetscFree(merge->owners_co);CHKERRQ(ierr); 4716 ierr = PetscLayoutDestroy(&merge->rowmap);CHKERRQ(ierr); 4717 ierr = PetscFree(merge);CHKERRQ(ierr); 4718 ierr = PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);CHKERRQ(ierr); 4719 } 4720 ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); 4721 PetscFunctionReturn(0); 4722 } 4723 4724 #include <../src/mat/utils/freespace.h> 4725 #include <petscbt.h> 4726 4727 #undef __FUNCT__ 4728 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJNumeric" 4729 PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat) 4730 { 4731 PetscErrorCode ierr; 4732 MPI_Comm comm; 4733 Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data; 4734 PetscMPIInt size,rank,taga,*len_s; 4735 PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj; 4736 PetscInt proc,m; 4737 PetscInt **buf_ri,**buf_rj; 4738 PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj; 4739 PetscInt nrows,**buf_ri_k,**nextrow,**nextai; 4740 MPI_Request *s_waits,*r_waits; 4741 MPI_Status *status; 4742 MatScalar *aa=a->a; 4743 MatScalar **abuf_r,*ba_i; 4744 Mat_Merge_SeqsToMPI *merge; 4745 PetscContainer container; 4746 4747 PetscFunctionBegin; 4748 ierr = PetscObjectGetComm((PetscObject)mpimat,&comm);CHKERRQ(ierr); 4749 ierr = PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4750 4751 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4752 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4753 4754 ierr = PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);CHKERRQ(ierr); 4755 ierr = PetscContainerGetPointer(container,(void**)&merge);CHKERRQ(ierr); 4756 4757 bi = merge->bi; 4758 bj = merge->bj; 4759 buf_ri = merge->buf_ri; 4760 buf_rj = merge->buf_rj; 4761 4762 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4763 owners = merge->rowmap->range; 4764 len_s = merge->len_s; 4765 4766 /* send and recv matrix values */ 4767 /*-----------------------------*/ 4768 ierr = PetscObjectGetNewTag((PetscObject)mpimat,&taga);CHKERRQ(ierr); 4769 ierr = PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);CHKERRQ(ierr); 4770 4771 ierr = PetscMalloc((merge->nsend+1)*sizeof(MPI_Request),&s_waits);CHKERRQ(ierr); 4772 for (proc=0,k=0; proc<size; proc++) { 4773 if (!len_s[proc]) continue; 4774 i = owners[proc]; 4775 ierr = MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);CHKERRQ(ierr); 4776 k++; 4777 } 4778 4779 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,r_waits,status);CHKERRQ(ierr);} 4780 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,s_waits,status);CHKERRQ(ierr);} 4781 ierr = PetscFree(status);CHKERRQ(ierr); 4782 4783 ierr = PetscFree(s_waits);CHKERRQ(ierr); 4784 ierr = PetscFree(r_waits);CHKERRQ(ierr); 4785 4786 /* insert mat values of mpimat */ 4787 /*----------------------------*/ 4788 ierr = PetscMalloc(N*sizeof(PetscScalar),&ba_i);CHKERRQ(ierr); 4789 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 4790 4791 for (k=0; k<merge->nrecv; k++) { 4792 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 4793 nrows = *(buf_ri_k[k]); 4794 nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */ 4795 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 4796 } 4797 4798 /* set values of ba */ 4799 m = merge->rowmap->n; 4800 for (i=0; i<m; i++) { 4801 arow = owners[rank] + i; 4802 bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */ 4803 bnzi = bi[i+1] - bi[i]; 4804 ierr = PetscMemzero(ba_i,bnzi*sizeof(PetscScalar));CHKERRQ(ierr); 4805 4806 /* add local non-zero vals of this proc's seqmat into ba */ 4807 anzi = ai[arow+1] - ai[arow]; 4808 aj = a->j + ai[arow]; 4809 aa = a->a + ai[arow]; 4810 nextaj = 0; 4811 for (j=0; nextaj<anzi; j++) { 4812 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4813 ba_i[j] += aa[nextaj++]; 4814 } 4815 } 4816 4817 /* add received vals into ba */ 4818 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 4819 /* i-th row */ 4820 if (i == *nextrow[k]) { 4821 anzi = *(nextai[k]+1) - *nextai[k]; 4822 aj = buf_rj[k] + *(nextai[k]); 4823 aa = abuf_r[k] + *(nextai[k]); 4824 nextaj = 0; 4825 for (j=0; nextaj<anzi; j++) { 4826 if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */ 4827 ba_i[j] += aa[nextaj++]; 4828 } 4829 } 4830 nextrow[k]++; nextai[k]++; 4831 } 4832 } 4833 ierr = MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);CHKERRQ(ierr); 4834 } 4835 ierr = MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4836 ierr = MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4837 4838 ierr = PetscFree(abuf_r[0]);CHKERRQ(ierr); 4839 ierr = PetscFree(abuf_r);CHKERRQ(ierr); 4840 ierr = PetscFree(ba_i);CHKERRQ(ierr); 4841 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 4842 ierr = PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);CHKERRQ(ierr); 4843 PetscFunctionReturn(0); 4844 } 4845 4846 extern PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat); 4847 4848 #undef __FUNCT__ 4849 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJSymbolic" 4850 PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat) 4851 { 4852 PetscErrorCode ierr; 4853 Mat B_mpi; 4854 Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data; 4855 PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri; 4856 PetscInt **buf_rj,**buf_ri,**buf_ri_k; 4857 PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j; 4858 PetscInt len,proc,*dnz,*onz,bs,cbs; 4859 PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0; 4860 PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai; 4861 MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits; 4862 MPI_Status *status; 4863 PetscFreeSpaceList free_space=NULL,current_space=NULL; 4864 PetscBT lnkbt; 4865 Mat_Merge_SeqsToMPI *merge; 4866 PetscContainer container; 4867 4868 PetscFunctionBegin; 4869 ierr = PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 4870 4871 /* make sure it is a PETSc comm */ 4872 ierr = PetscCommDuplicate(comm,&comm,NULL);CHKERRQ(ierr); 4873 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4874 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 4875 4876 ierr = PetscNew(Mat_Merge_SeqsToMPI,&merge);CHKERRQ(ierr); 4877 ierr = PetscMalloc(size*sizeof(MPI_Status),&status);CHKERRQ(ierr); 4878 4879 /* determine row ownership */ 4880 /*---------------------------------------------------------*/ 4881 ierr = PetscLayoutCreate(comm,&merge->rowmap);CHKERRQ(ierr); 4882 ierr = PetscLayoutSetLocalSize(merge->rowmap,m);CHKERRQ(ierr); 4883 ierr = PetscLayoutSetSize(merge->rowmap,M);CHKERRQ(ierr); 4884 ierr = PetscLayoutSetBlockSize(merge->rowmap,1);CHKERRQ(ierr); 4885 ierr = PetscLayoutSetUp(merge->rowmap);CHKERRQ(ierr); 4886 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&len_si);CHKERRQ(ierr); 4887 ierr = PetscMalloc(size*sizeof(PetscMPIInt),&merge->len_s);CHKERRQ(ierr); 4888 4889 m = merge->rowmap->n; 4890 owners = merge->rowmap->range; 4891 4892 /* determine the number of messages to send, their lengths */ 4893 /*---------------------------------------------------------*/ 4894 len_s = merge->len_s; 4895 4896 len = 0; /* length of buf_si[] */ 4897 merge->nsend = 0; 4898 for (proc=0; proc<size; proc++) { 4899 len_si[proc] = 0; 4900 if (proc == rank) { 4901 len_s[proc] = 0; 4902 } else { 4903 len_si[proc] = owners[proc+1] - owners[proc] + 1; 4904 len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */ 4905 } 4906 if (len_s[proc]) { 4907 merge->nsend++; 4908 nrows = 0; 4909 for (i=owners[proc]; i<owners[proc+1]; i++) { 4910 if (ai[i+1] > ai[i]) nrows++; 4911 } 4912 len_si[proc] = 2*(nrows+1); 4913 len += len_si[proc]; 4914 } 4915 } 4916 4917 /* determine the number and length of messages to receive for ij-structure */ 4918 /*-------------------------------------------------------------------------*/ 4919 ierr = PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);CHKERRQ(ierr); 4920 ierr = PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);CHKERRQ(ierr); 4921 4922 /* post the Irecv of j-structure */ 4923 /*-------------------------------*/ 4924 ierr = PetscCommGetNewTag(comm,&tagj);CHKERRQ(ierr); 4925 ierr = PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);CHKERRQ(ierr); 4926 4927 /* post the Isend of j-structure */ 4928 /*--------------------------------*/ 4929 ierr = PetscMalloc2(merge->nsend,MPI_Request,&si_waits,merge->nsend,MPI_Request,&sj_waits);CHKERRQ(ierr); 4930 4931 for (proc=0, k=0; proc<size; proc++) { 4932 if (!len_s[proc]) continue; 4933 i = owners[proc]; 4934 ierr = MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);CHKERRQ(ierr); 4935 k++; 4936 } 4937 4938 /* receives and sends of j-structure are complete */ 4939 /*------------------------------------------------*/ 4940 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,rj_waits,status);CHKERRQ(ierr);} 4941 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,sj_waits,status);CHKERRQ(ierr);} 4942 4943 /* send and recv i-structure */ 4944 /*---------------------------*/ 4945 ierr = PetscCommGetNewTag(comm,&tagi);CHKERRQ(ierr); 4946 ierr = PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);CHKERRQ(ierr); 4947 4948 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&buf_s);CHKERRQ(ierr); 4949 buf_si = buf_s; /* points to the beginning of k-th msg to be sent */ 4950 for (proc=0,k=0; proc<size; proc++) { 4951 if (!len_s[proc]) continue; 4952 /* form outgoing message for i-structure: 4953 buf_si[0]: nrows to be sent 4954 [1:nrows]: row index (global) 4955 [nrows+1:2*nrows+1]: i-structure index 4956 */ 4957 /*-------------------------------------------*/ 4958 nrows = len_si[proc]/2 - 1; 4959 buf_si_i = buf_si + nrows+1; 4960 buf_si[0] = nrows; 4961 buf_si_i[0] = 0; 4962 nrows = 0; 4963 for (i=owners[proc]; i<owners[proc+1]; i++) { 4964 anzi = ai[i+1] - ai[i]; 4965 if (anzi) { 4966 buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */ 4967 buf_si[nrows+1] = i-owners[proc]; /* local row index */ 4968 nrows++; 4969 } 4970 } 4971 ierr = MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);CHKERRQ(ierr); 4972 k++; 4973 buf_si += len_si[proc]; 4974 } 4975 4976 if (merge->nrecv) {ierr = MPI_Waitall(merge->nrecv,ri_waits,status);CHKERRQ(ierr);} 4977 if (merge->nsend) {ierr = MPI_Waitall(merge->nsend,si_waits,status);CHKERRQ(ierr);} 4978 4979 ierr = PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);CHKERRQ(ierr); 4980 for (i=0; i<merge->nrecv; i++) { 4981 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); 4982 } 4983 4984 ierr = PetscFree(len_si);CHKERRQ(ierr); 4985 ierr = PetscFree(len_ri);CHKERRQ(ierr); 4986 ierr = PetscFree(rj_waits);CHKERRQ(ierr); 4987 ierr = PetscFree2(si_waits,sj_waits);CHKERRQ(ierr); 4988 ierr = PetscFree(ri_waits);CHKERRQ(ierr); 4989 ierr = PetscFree(buf_s);CHKERRQ(ierr); 4990 ierr = PetscFree(status);CHKERRQ(ierr); 4991 4992 /* compute a local seq matrix in each processor */ 4993 /*----------------------------------------------*/ 4994 /* allocate bi array and free space for accumulating nonzero column info */ 4995 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&bi);CHKERRQ(ierr); 4996 bi[0] = 0; 4997 4998 /* create and initialize a linked list */ 4999 nlnk = N+1; 5000 ierr = PetscLLCreate(N,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 5001 5002 /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */ 5003 len = ai[owners[rank+1]] - ai[owners[rank]]; 5004 ierr = PetscFreeSpaceGet((PetscInt)(2*len+1),&free_space);CHKERRQ(ierr); 5005 5006 current_space = free_space; 5007 5008 /* determine symbolic info for each local row */ 5009 ierr = PetscMalloc3(merge->nrecv,PetscInt*,&buf_ri_k,merge->nrecv,PetscInt*,&nextrow,merge->nrecv,PetscInt*,&nextai);CHKERRQ(ierr); 5010 5011 for (k=0; k<merge->nrecv; k++) { 5012 buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */ 5013 nrows = *buf_ri_k[k]; 5014 nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */ 5015 nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */ 5016 } 5017 5018 ierr = MatPreallocateInitialize(comm,m,n,dnz,onz);CHKERRQ(ierr); 5019 len = 0; 5020 for (i=0; i<m; i++) { 5021 bnzi = 0; 5022 /* add local non-zero cols of this proc's seqmat into lnk */ 5023 arow = owners[rank] + i; 5024 anzi = ai[arow+1] - ai[arow]; 5025 aj = a->j + ai[arow]; 5026 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 5027 bnzi += nlnk; 5028 /* add received col data into lnk */ 5029 for (k=0; k<merge->nrecv; k++) { /* k-th received message */ 5030 if (i == *nextrow[k]) { /* i-th row */ 5031 anzi = *(nextai[k]+1) - *nextai[k]; 5032 aj = buf_rj[k] + *nextai[k]; 5033 ierr = PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);CHKERRQ(ierr); 5034 bnzi += nlnk; 5035 nextrow[k]++; nextai[k]++; 5036 } 5037 } 5038 if (len < bnzi) len = bnzi; /* =max(bnzi) */ 5039 5040 /* if free space is not available, make more free space */ 5041 if (current_space->local_remaining<bnzi) { 5042 ierr = PetscFreeSpaceGet(bnzi+current_space->total_array_size,¤t_space);CHKERRQ(ierr); 5043 nspacedouble++; 5044 } 5045 /* copy data into free space, then initialize lnk */ 5046 ierr = PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);CHKERRQ(ierr); 5047 ierr = MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);CHKERRQ(ierr); 5048 5049 current_space->array += bnzi; 5050 current_space->local_used += bnzi; 5051 current_space->local_remaining -= bnzi; 5052 5053 bi[i+1] = bi[i] + bnzi; 5054 } 5055 5056 ierr = PetscFree3(buf_ri_k,nextrow,nextai);CHKERRQ(ierr); 5057 5058 ierr = PetscMalloc((bi[m]+1)*sizeof(PetscInt),&bj);CHKERRQ(ierr); 5059 ierr = PetscFreeSpaceContiguous(&free_space,bj);CHKERRQ(ierr); 5060 ierr = PetscLLDestroy(lnk,lnkbt);CHKERRQ(ierr); 5061 5062 /* create symbolic parallel matrix B_mpi */ 5063 /*---------------------------------------*/ 5064 ierr = MatGetBlockSizes(seqmat,&bs,&cbs);CHKERRQ(ierr); 5065 ierr = MatCreate(comm,&B_mpi);CHKERRQ(ierr); 5066 if (n==PETSC_DECIDE) { 5067 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);CHKERRQ(ierr); 5068 } else { 5069 ierr = MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5070 } 5071 ierr = MatSetBlockSizes(B_mpi,bs,cbs);CHKERRQ(ierr); 5072 ierr = MatSetType(B_mpi,MATMPIAIJ);CHKERRQ(ierr); 5073 ierr = MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);CHKERRQ(ierr); 5074 ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr); 5075 ierr = MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr); 5076 5077 /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */ 5078 B_mpi->assembled = PETSC_FALSE; 5079 B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI; 5080 merge->bi = bi; 5081 merge->bj = bj; 5082 merge->buf_ri = buf_ri; 5083 merge->buf_rj = buf_rj; 5084 merge->coi = NULL; 5085 merge->coj = NULL; 5086 merge->owners_co = NULL; 5087 5088 ierr = PetscCommDestroy(&comm);CHKERRQ(ierr); 5089 5090 /* attach the supporting struct to B_mpi for reuse */ 5091 ierr = PetscContainerCreate(PETSC_COMM_SELF,&container);CHKERRQ(ierr); 5092 ierr = PetscContainerSetPointer(container,merge);CHKERRQ(ierr); 5093 ierr = PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);CHKERRQ(ierr); 5094 ierr = PetscContainerDestroy(&container);CHKERRQ(ierr); 5095 *mpimat = B_mpi; 5096 5097 ierr = PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);CHKERRQ(ierr); 5098 PetscFunctionReturn(0); 5099 } 5100 5101 #undef __FUNCT__ 5102 #define __FUNCT__ "MatCreateMPIAIJSumSeqAIJ" 5103 /*@C 5104 MatCreateMPIAIJSumSeqAIJ - Creates a MPIAIJ matrix by adding sequential 5105 matrices from each processor 5106 5107 Collective on MPI_Comm 5108 5109 Input Parameters: 5110 + comm - the communicators the parallel matrix will live on 5111 . seqmat - the input sequential matrices 5112 . m - number of local rows (or PETSC_DECIDE) 5113 . n - number of local columns (or PETSC_DECIDE) 5114 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5115 5116 Output Parameter: 5117 . mpimat - the parallel matrix generated 5118 5119 Level: advanced 5120 5121 Notes: 5122 The dimensions of the sequential matrix in each processor MUST be the same. 5123 The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be 5124 destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat. 5125 @*/ 5126 PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat) 5127 { 5128 PetscErrorCode ierr; 5129 PetscMPIInt size; 5130 5131 PetscFunctionBegin; 5132 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 5133 if (size == 1) { 5134 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5135 if (scall == MAT_INITIAL_MATRIX) { 5136 ierr = MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);CHKERRQ(ierr); 5137 } else { 5138 ierr = MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 5139 } 5140 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5141 PetscFunctionReturn(0); 5142 } 5143 ierr = PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5144 if (scall == MAT_INITIAL_MATRIX) { 5145 ierr = MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);CHKERRQ(ierr); 5146 } 5147 ierr = MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);CHKERRQ(ierr); 5148 ierr = PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);CHKERRQ(ierr); 5149 PetscFunctionReturn(0); 5150 } 5151 5152 #undef __FUNCT__ 5153 #define __FUNCT__ "MatMPIAIJGetLocalMat" 5154 /*@ 5155 MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MPIAIJ matrix by taking all its local rows and putting them into a sequential vector with 5156 mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained 5157 with MatGetSize() 5158 5159 Not Collective 5160 5161 Input Parameters: 5162 + A - the matrix 5163 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5164 5165 Output Parameter: 5166 . A_loc - the local sequential matrix generated 5167 5168 Level: developer 5169 5170 .seealso: MatGetOwnerShipRange(), MatMPIAIJGetLocalMatCondensed() 5171 5172 @*/ 5173 PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc) 5174 { 5175 PetscErrorCode ierr; 5176 Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data; 5177 Mat_SeqAIJ *mat,*a=(Mat_SeqAIJ*)(mpimat->A)->data,*b=(Mat_SeqAIJ*)(mpimat->B)->data; 5178 PetscInt *ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j,*cmap=mpimat->garray; 5179 MatScalar *aa=a->a,*ba=b->a,*cam; 5180 PetscScalar *ca; 5181 PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart; 5182 PetscInt *ci,*cj,col,ncols_d,ncols_o,jo; 5183 PetscBool match; 5184 5185 PetscFunctionBegin; 5186 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5187 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5188 ierr = PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5189 if (scall == MAT_INITIAL_MATRIX) { 5190 ierr = PetscMalloc((1+am)*sizeof(PetscInt),&ci);CHKERRQ(ierr); 5191 ci[0] = 0; 5192 for (i=0; i<am; i++) { 5193 ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]); 5194 } 5195 ierr = PetscMalloc((1+ci[am])*sizeof(PetscInt),&cj);CHKERRQ(ierr); 5196 ierr = PetscMalloc((1+ci[am])*sizeof(PetscScalar),&ca);CHKERRQ(ierr); 5197 k = 0; 5198 for (i=0; i<am; i++) { 5199 ncols_o = bi[i+1] - bi[i]; 5200 ncols_d = ai[i+1] - ai[i]; 5201 /* off-diagonal portion of A */ 5202 for (jo=0; jo<ncols_o; jo++) { 5203 col = cmap[*bj]; 5204 if (col >= cstart) break; 5205 cj[k] = col; bj++; 5206 ca[k++] = *ba++; 5207 } 5208 /* diagonal portion of A */ 5209 for (j=0; j<ncols_d; j++) { 5210 cj[k] = cstart + *aj++; 5211 ca[k++] = *aa++; 5212 } 5213 /* off-diagonal portion of A */ 5214 for (j=jo; j<ncols_o; j++) { 5215 cj[k] = cmap[*bj++]; 5216 ca[k++] = *ba++; 5217 } 5218 } 5219 /* put together the new matrix */ 5220 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);CHKERRQ(ierr); 5221 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5222 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5223 mat = (Mat_SeqAIJ*)(*A_loc)->data; 5224 mat->free_a = PETSC_TRUE; 5225 mat->free_ij = PETSC_TRUE; 5226 mat->nonew = 0; 5227 } else if (scall == MAT_REUSE_MATRIX) { 5228 mat=(Mat_SeqAIJ*)(*A_loc)->data; 5229 ci = mat->i; cj = mat->j; cam = mat->a; 5230 for (i=0; i<am; i++) { 5231 /* off-diagonal portion of A */ 5232 ncols_o = bi[i+1] - bi[i]; 5233 for (jo=0; jo<ncols_o; jo++) { 5234 col = cmap[*bj]; 5235 if (col >= cstart) break; 5236 *cam++ = *ba++; bj++; 5237 } 5238 /* diagonal portion of A */ 5239 ncols_d = ai[i+1] - ai[i]; 5240 for (j=0; j<ncols_d; j++) *cam++ = *aa++; 5241 /* off-diagonal portion of A */ 5242 for (j=jo; j<ncols_o; j++) { 5243 *cam++ = *ba++; bj++; 5244 } 5245 } 5246 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall); 5247 ierr = PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);CHKERRQ(ierr); 5248 PetscFunctionReturn(0); 5249 } 5250 5251 #undef __FUNCT__ 5252 #define __FUNCT__ "MatMPIAIJGetLocalMatCondensed" 5253 /*@C 5254 MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MPIAIJ matrix by taking all its local rows and NON-ZERO columns 5255 5256 Not Collective 5257 5258 Input Parameters: 5259 + A - the matrix 5260 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5261 - row, col - index sets of rows and columns to extract (or NULL) 5262 5263 Output Parameter: 5264 . A_loc - the local sequential matrix generated 5265 5266 Level: developer 5267 5268 .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat() 5269 5270 @*/ 5271 PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc) 5272 { 5273 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5274 PetscErrorCode ierr; 5275 PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx; 5276 IS isrowa,iscola; 5277 Mat *aloc; 5278 PetscBool match; 5279 5280 PetscFunctionBegin; 5281 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);CHKERRQ(ierr); 5282 if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MPIAIJ matrix as input"); 5283 ierr = PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5284 if (!row) { 5285 start = A->rmap->rstart; end = A->rmap->rend; 5286 ierr = ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);CHKERRQ(ierr); 5287 } else { 5288 isrowa = *row; 5289 } 5290 if (!col) { 5291 start = A->cmap->rstart; 5292 cmap = a->garray; 5293 nzA = a->A->cmap->n; 5294 nzB = a->B->cmap->n; 5295 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5296 ncols = 0; 5297 for (i=0; i<nzB; i++) { 5298 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5299 else break; 5300 } 5301 imark = i; 5302 for (i=0; i<nzA; i++) idx[ncols++] = start + i; 5303 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; 5304 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);CHKERRQ(ierr); 5305 } else { 5306 iscola = *col; 5307 } 5308 if (scall != MAT_INITIAL_MATRIX) { 5309 ierr = PetscMalloc(sizeof(Mat),&aloc);CHKERRQ(ierr); 5310 aloc[0] = *A_loc; 5311 } 5312 ierr = MatGetSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);CHKERRQ(ierr); 5313 *A_loc = aloc[0]; 5314 ierr = PetscFree(aloc);CHKERRQ(ierr); 5315 if (!row) { 5316 ierr = ISDestroy(&isrowa);CHKERRQ(ierr); 5317 } 5318 if (!col) { 5319 ierr = ISDestroy(&iscola);CHKERRQ(ierr); 5320 } 5321 ierr = PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);CHKERRQ(ierr); 5322 PetscFunctionReturn(0); 5323 } 5324 5325 #undef __FUNCT__ 5326 #define __FUNCT__ "MatGetBrowsOfAcols" 5327 /*@C 5328 MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A 5329 5330 Collective on Mat 5331 5332 Input Parameters: 5333 + A,B - the matrices in mpiaij format 5334 . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5335 - rowb, colb - index sets of rows and columns of B to extract (or NULL) 5336 5337 Output Parameter: 5338 + rowb, colb - index sets of rows and columns of B to extract 5339 - B_seq - the sequential matrix generated 5340 5341 Level: developer 5342 5343 @*/ 5344 PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq) 5345 { 5346 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5347 PetscErrorCode ierr; 5348 PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark; 5349 IS isrowb,iscolb; 5350 Mat *bseq=NULL; 5351 5352 PetscFunctionBegin; 5353 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5354 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); 5355 } 5356 ierr = PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5357 5358 if (scall == MAT_INITIAL_MATRIX) { 5359 start = A->cmap->rstart; 5360 cmap = a->garray; 5361 nzA = a->A->cmap->n; 5362 nzB = a->B->cmap->n; 5363 ierr = PetscMalloc((nzA+nzB)*sizeof(PetscInt), &idx);CHKERRQ(ierr); 5364 ncols = 0; 5365 for (i=0; i<nzB; i++) { /* row < local row index */ 5366 if (cmap[i] < start) idx[ncols++] = cmap[i]; 5367 else break; 5368 } 5369 imark = i; 5370 for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */ 5371 for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */ 5372 ierr = ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);CHKERRQ(ierr); 5373 ierr = ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);CHKERRQ(ierr); 5374 } else { 5375 if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX"); 5376 isrowb = *rowb; iscolb = *colb; 5377 ierr = PetscMalloc(sizeof(Mat),&bseq);CHKERRQ(ierr); 5378 bseq[0] = *B_seq; 5379 } 5380 ierr = MatGetSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);CHKERRQ(ierr); 5381 *B_seq = bseq[0]; 5382 ierr = PetscFree(bseq);CHKERRQ(ierr); 5383 if (!rowb) { 5384 ierr = ISDestroy(&isrowb);CHKERRQ(ierr); 5385 } else { 5386 *rowb = isrowb; 5387 } 5388 if (!colb) { 5389 ierr = ISDestroy(&iscolb);CHKERRQ(ierr); 5390 } else { 5391 *colb = iscolb; 5392 } 5393 ierr = PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);CHKERRQ(ierr); 5394 PetscFunctionReturn(0); 5395 } 5396 5397 #undef __FUNCT__ 5398 #define __FUNCT__ "MatGetBrowsOfAoCols_MPIAIJ" 5399 /* 5400 MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns 5401 of the OFF-DIAGONAL portion of local A 5402 5403 Collective on Mat 5404 5405 Input Parameters: 5406 + A,B - the matrices in mpiaij format 5407 - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX 5408 5409 Output Parameter: 5410 + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL) 5411 . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL) 5412 . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL) 5413 - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N 5414 5415 Level: developer 5416 5417 */ 5418 PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth) 5419 { 5420 VecScatter_MPI_General *gen_to,*gen_from; 5421 PetscErrorCode ierr; 5422 Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data; 5423 Mat_SeqAIJ *b_oth; 5424 VecScatter ctx =a->Mvctx; 5425 MPI_Comm comm; 5426 PetscMPIInt *rprocs,*sprocs,tag=((PetscObject)ctx)->tag,rank; 5427 PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj; 5428 PetscScalar *rvalues,*svalues; 5429 MatScalar *b_otha,*bufa,*bufA; 5430 PetscInt i,j,k,l,ll,nrecvs,nsends,nrows,*srow,*rstarts,*rstartsj = 0,*sstarts,*sstartsj,len; 5431 MPI_Request *rwaits = NULL,*swaits = NULL; 5432 MPI_Status *sstatus,rstatus; 5433 PetscMPIInt jj; 5434 PetscInt *cols,sbs,rbs; 5435 PetscScalar *vals; 5436 5437 PetscFunctionBegin; 5438 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 5439 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 5440 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); 5441 } 5442 ierr = PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5443 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 5444 5445 gen_to = (VecScatter_MPI_General*)ctx->todata; 5446 gen_from = (VecScatter_MPI_General*)ctx->fromdata; 5447 rvalues = gen_from->values; /* holds the length of receiving row */ 5448 svalues = gen_to->values; /* holds the length of sending row */ 5449 nrecvs = gen_from->n; 5450 nsends = gen_to->n; 5451 5452 ierr = PetscMalloc2(nrecvs,MPI_Request,&rwaits,nsends,MPI_Request,&swaits);CHKERRQ(ierr); 5453 srow = gen_to->indices; /* local row index to be sent */ 5454 sstarts = gen_to->starts; 5455 sprocs = gen_to->procs; 5456 sstatus = gen_to->sstatus; 5457 sbs = gen_to->bs; 5458 rstarts = gen_from->starts; 5459 rprocs = gen_from->procs; 5460 rbs = gen_from->bs; 5461 5462 if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX; 5463 if (scall == MAT_INITIAL_MATRIX) { 5464 /* i-array */ 5465 /*---------*/ 5466 /* post receives */ 5467 for (i=0; i<nrecvs; i++) { 5468 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5469 nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */ 5470 ierr = MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5471 } 5472 5473 /* pack the outgoing message */ 5474 ierr = PetscMalloc2(nsends+1,PetscInt,&sstartsj,nrecvs+1,PetscInt,&rstartsj);CHKERRQ(ierr); 5475 5476 sstartsj[0] = 0; 5477 rstartsj[0] = 0; 5478 len = 0; /* total length of j or a array to be sent */ 5479 k = 0; 5480 for (i=0; i<nsends; i++) { 5481 rowlen = (PetscInt*)svalues + sstarts[i]*sbs; 5482 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5483 for (j=0; j<nrows; j++) { 5484 row = srow[k] + B->rmap->range[rank]; /* global row idx */ 5485 for (l=0; l<sbs; l++) { 5486 ierr = MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); /* rowlength */ 5487 5488 rowlen[j*sbs+l] = ncols; 5489 5490 len += ncols; 5491 ierr = MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);CHKERRQ(ierr); 5492 } 5493 k++; 5494 } 5495 ierr = MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5496 5497 sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */ 5498 } 5499 /* recvs and sends of i-array are completed */ 5500 i = nrecvs; 5501 while (i--) { 5502 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5503 } 5504 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5505 5506 /* allocate buffers for sending j and a arrays */ 5507 ierr = PetscMalloc((len+1)*sizeof(PetscInt),&bufj);CHKERRQ(ierr); 5508 ierr = PetscMalloc((len+1)*sizeof(PetscScalar),&bufa);CHKERRQ(ierr); 5509 5510 /* create i-array of B_oth */ 5511 ierr = PetscMalloc((aBn+2)*sizeof(PetscInt),&b_othi);CHKERRQ(ierr); 5512 5513 b_othi[0] = 0; 5514 len = 0; /* total length of j or a array to be received */ 5515 k = 0; 5516 for (i=0; i<nrecvs; i++) { 5517 rowlen = (PetscInt*)rvalues + rstarts[i]*rbs; 5518 nrows = rbs*(rstarts[i+1]-rstarts[i]); /* num of rows to be recieved */ 5519 for (j=0; j<nrows; j++) { 5520 b_othi[k+1] = b_othi[k] + rowlen[j]; 5521 len += rowlen[j]; k++; 5522 } 5523 rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */ 5524 } 5525 5526 /* allocate space for j and a arrrays of B_oth */ 5527 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(PetscInt),&b_othj);CHKERRQ(ierr); 5528 ierr = PetscMalloc((b_othi[aBn]+1)*sizeof(MatScalar),&b_otha);CHKERRQ(ierr); 5529 5530 /* j-array */ 5531 /*---------*/ 5532 /* post receives of j-array */ 5533 for (i=0; i<nrecvs; i++) { 5534 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5535 ierr = MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5536 } 5537 5538 /* pack the outgoing message j-array */ 5539 k = 0; 5540 for (i=0; i<nsends; i++) { 5541 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5542 bufJ = bufj+sstartsj[i]; 5543 for (j=0; j<nrows; j++) { 5544 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5545 for (ll=0; ll<sbs; ll++) { 5546 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5547 for (l=0; l<ncols; l++) { 5548 *bufJ++ = cols[l]; 5549 } 5550 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);CHKERRQ(ierr); 5551 } 5552 } 5553 ierr = MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5554 } 5555 5556 /* recvs and sends of j-array are completed */ 5557 i = nrecvs; 5558 while (i--) { 5559 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5560 } 5561 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5562 } else if (scall == MAT_REUSE_MATRIX) { 5563 sstartsj = *startsj_s; 5564 rstartsj = *startsj_r; 5565 bufa = *bufa_ptr; 5566 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5567 b_otha = b_oth->a; 5568 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container"); 5569 5570 /* a-array */ 5571 /*---------*/ 5572 /* post receives of a-array */ 5573 for (i=0; i<nrecvs; i++) { 5574 nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */ 5575 ierr = MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);CHKERRQ(ierr); 5576 } 5577 5578 /* pack the outgoing message a-array */ 5579 k = 0; 5580 for (i=0; i<nsends; i++) { 5581 nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */ 5582 bufA = bufa+sstartsj[i]; 5583 for (j=0; j<nrows; j++) { 5584 row = srow[k++] + B->rmap->range[rank]; /* global row idx */ 5585 for (ll=0; ll<sbs; ll++) { 5586 ierr = MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5587 for (l=0; l<ncols; l++) { 5588 *bufA++ = vals[l]; 5589 } 5590 ierr = MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);CHKERRQ(ierr); 5591 } 5592 } 5593 ierr = MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);CHKERRQ(ierr); 5594 } 5595 /* recvs and sends of a-array are completed */ 5596 i = nrecvs; 5597 while (i--) { 5598 ierr = MPI_Waitany(nrecvs,rwaits,&jj,&rstatus);CHKERRQ(ierr); 5599 } 5600 if (nsends) {ierr = MPI_Waitall(nsends,swaits,sstatus);CHKERRQ(ierr);} 5601 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 5602 5603 if (scall == MAT_INITIAL_MATRIX) { 5604 /* put together the new matrix */ 5605 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);CHKERRQ(ierr); 5606 5607 /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */ 5608 /* Since these are PETSc arrays, change flags to free them as necessary. */ 5609 b_oth = (Mat_SeqAIJ*)(*B_oth)->data; 5610 b_oth->free_a = PETSC_TRUE; 5611 b_oth->free_ij = PETSC_TRUE; 5612 b_oth->nonew = 0; 5613 5614 ierr = PetscFree(bufj);CHKERRQ(ierr); 5615 if (!startsj_s || !bufa_ptr) { 5616 ierr = PetscFree2(sstartsj,rstartsj);CHKERRQ(ierr); 5617 ierr = PetscFree(bufa_ptr);CHKERRQ(ierr); 5618 } else { 5619 *startsj_s = sstartsj; 5620 *startsj_r = rstartsj; 5621 *bufa_ptr = bufa; 5622 } 5623 } 5624 ierr = PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);CHKERRQ(ierr); 5625 PetscFunctionReturn(0); 5626 } 5627 5628 #undef __FUNCT__ 5629 #define __FUNCT__ "MatGetCommunicationStructs" 5630 /*@C 5631 MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication. 5632 5633 Not Collective 5634 5635 Input Parameters: 5636 . A - The matrix in mpiaij format 5637 5638 Output Parameter: 5639 + lvec - The local vector holding off-process values from the argument to a matrix-vector product 5640 . colmap - A map from global column index to local index into lvec 5641 - multScatter - A scatter from the argument of a matrix-vector product to lvec 5642 5643 Level: developer 5644 5645 @*/ 5646 #if defined(PETSC_USE_CTABLE) 5647 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter) 5648 #else 5649 PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter) 5650 #endif 5651 { 5652 Mat_MPIAIJ *a; 5653 5654 PetscFunctionBegin; 5655 PetscValidHeaderSpecific(A, MAT_CLASSID, 1); 5656 PetscValidPointer(lvec, 2); 5657 PetscValidPointer(colmap, 3); 5658 PetscValidPointer(multScatter, 4); 5659 a = (Mat_MPIAIJ*) A->data; 5660 if (lvec) *lvec = a->lvec; 5661 if (colmap) *colmap = a->colmap; 5662 if (multScatter) *multScatter = a->Mvctx; 5663 PetscFunctionReturn(0); 5664 } 5665 5666 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*); 5667 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*); 5668 PETSC_EXTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*); 5669 5670 #undef __FUNCT__ 5671 #define __FUNCT__ "MatMatMultNumeric_MPIDense_MPIAIJ" 5672 /* 5673 Computes (B'*A')' since computing B*A directly is untenable 5674 5675 n p p 5676 ( ) ( ) ( ) 5677 m ( A ) * n ( B ) = m ( C ) 5678 ( ) ( ) ( ) 5679 5680 */ 5681 PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C) 5682 { 5683 PetscErrorCode ierr; 5684 Mat At,Bt,Ct; 5685 5686 PetscFunctionBegin; 5687 ierr = MatTranspose(A,MAT_INITIAL_MATRIX,&At);CHKERRQ(ierr); 5688 ierr = MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);CHKERRQ(ierr); 5689 ierr = MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);CHKERRQ(ierr); 5690 ierr = MatDestroy(&At);CHKERRQ(ierr); 5691 ierr = MatDestroy(&Bt);CHKERRQ(ierr); 5692 ierr = MatTranspose(Ct,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 5693 ierr = MatDestroy(&Ct);CHKERRQ(ierr); 5694 PetscFunctionReturn(0); 5695 } 5696 5697 #undef __FUNCT__ 5698 #define __FUNCT__ "MatMatMultSymbolic_MPIDense_MPIAIJ" 5699 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 5700 { 5701 PetscErrorCode ierr; 5702 PetscInt m=A->rmap->n,n=B->cmap->n; 5703 Mat Cmat; 5704 5705 PetscFunctionBegin; 5706 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); 5707 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 5708 ierr = MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 5709 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 5710 ierr = MatSetType(Cmat,MATMPIDENSE);CHKERRQ(ierr); 5711 ierr = MatMPIDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 5712 ierr = MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5713 ierr = MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5714 5715 Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ; 5716 5717 *C = Cmat; 5718 PetscFunctionReturn(0); 5719 } 5720 5721 /* ----------------------------------------------------------------*/ 5722 #undef __FUNCT__ 5723 #define __FUNCT__ "MatMatMult_MPIDense_MPIAIJ" 5724 PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 5725 { 5726 PetscErrorCode ierr; 5727 5728 PetscFunctionBegin; 5729 if (scall == MAT_INITIAL_MATRIX) { 5730 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5731 ierr = MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);CHKERRQ(ierr); 5732 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 5733 } 5734 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5735 ierr = MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);CHKERRQ(ierr); 5736 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 5737 PetscFunctionReturn(0); 5738 } 5739 5740 #if defined(PETSC_HAVE_MUMPS) 5741 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 5742 #endif 5743 #if defined(PETSC_HAVE_PASTIX) 5744 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_pastix(Mat,MatFactorType,Mat*); 5745 #endif 5746 #if defined(PETSC_HAVE_SUPERLU_DIST) 5747 PETSC_EXTERN PetscErrorCode MatGetFactor_mpiaij_superlu_dist(Mat,MatFactorType,Mat*); 5748 #endif 5749 #if defined(PETSC_HAVE_CLIQUE) 5750 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 5751 #endif 5752 5753 /*MC 5754 MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices. 5755 5756 Options Database Keys: 5757 . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions() 5758 5759 Level: beginner 5760 5761 .seealso: MatCreateAIJ() 5762 M*/ 5763 5764 #undef __FUNCT__ 5765 #define __FUNCT__ "MatCreate_MPIAIJ" 5766 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B) 5767 { 5768 Mat_MPIAIJ *b; 5769 PetscErrorCode ierr; 5770 PetscMPIInt size; 5771 5772 PetscFunctionBegin; 5773 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 5774 5775 ierr = PetscNewLog(B,Mat_MPIAIJ,&b);CHKERRQ(ierr); 5776 B->data = (void*)b; 5777 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 5778 B->assembled = PETSC_FALSE; 5779 B->insertmode = NOT_SET_VALUES; 5780 b->size = size; 5781 5782 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr); 5783 5784 /* build cache for off array entries formed */ 5785 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr); 5786 5787 b->donotstash = PETSC_FALSE; 5788 b->colmap = 0; 5789 b->garray = 0; 5790 b->roworiented = PETSC_TRUE; 5791 5792 /* stuff used for matrix vector multiply */ 5793 b->lvec = NULL; 5794 b->Mvctx = NULL; 5795 5796 /* stuff for MatGetRow() */ 5797 b->rowindices = 0; 5798 b->rowvalues = 0; 5799 b->getrowactive = PETSC_FALSE; 5800 5801 /* flexible pointer used in CUSP/CUSPARSE classes */ 5802 b->spptr = NULL; 5803 5804 #if defined(PETSC_HAVE_MUMPS) 5805 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 5806 #endif 5807 #if defined(PETSC_HAVE_PASTIX) 5808 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpiaij_pastix);CHKERRQ(ierr); 5809 #endif 5810 #if defined(PETSC_HAVE_SUPERLU_DIST) 5811 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_mpiaij_superlu_dist);CHKERRQ(ierr); 5812 #endif 5813 #if defined(PETSC_HAVE_CLIQUE) 5814 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 5815 #endif 5816 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);CHKERRQ(ierr); 5817 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);CHKERRQ(ierr); 5818 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIAIJ);CHKERRQ(ierr); 5819 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);CHKERRQ(ierr); 5820 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);CHKERRQ(ierr); 5821 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);CHKERRQ(ierr); 5822 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);CHKERRQ(ierr); 5823 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);CHKERRQ(ierr); 5824 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);CHKERRQ(ierr); 5825 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);CHKERRQ(ierr); 5826 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);CHKERRQ(ierr); 5827 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);CHKERRQ(ierr); 5828 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);CHKERRQ(ierr); 5829 ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);CHKERRQ(ierr); 5830 PetscFunctionReturn(0); 5831 } 5832 5833 #undef __FUNCT__ 5834 #define __FUNCT__ "MatCreateMPIAIJWithSplitArrays" 5835 /*@ 5836 MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal" 5837 and "off-diagonal" part of the matrix in CSR format. 5838 5839 Collective on MPI_Comm 5840 5841 Input Parameters: 5842 + comm - MPI communicator 5843 . m - number of local rows (Cannot be PETSC_DECIDE) 5844 . n - This value should be the same as the local size used in creating the 5845 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 5846 calculated if N is given) For square matrices n is almost always m. 5847 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 5848 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 5849 . i - row indices for "diagonal" portion of matrix 5850 . j - column indices 5851 . a - matrix values 5852 . oi - row indices for "off-diagonal" portion of matrix 5853 . oj - column indices 5854 - oa - matrix values 5855 5856 Output Parameter: 5857 . mat - the matrix 5858 5859 Level: advanced 5860 5861 Notes: 5862 The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user 5863 must free the arrays once the matrix has been destroyed and not before. 5864 5865 The i and j indices are 0 based 5866 5867 See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix 5868 5869 This sets local rows and cannot be used to set off-processor values. 5870 5871 Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a 5872 legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does 5873 not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because 5874 the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to 5875 keep track of the underlying array. Use MatSetOption(A,MAT_IGNORE_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all 5876 communication if it is known that only local entries will be set. 5877 5878 .keywords: matrix, aij, compressed row, sparse, parallel 5879 5880 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(), 5881 MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays() 5882 @*/ 5883 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) 5884 { 5885 PetscErrorCode ierr; 5886 Mat_MPIAIJ *maij; 5887 5888 PetscFunctionBegin; 5889 if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative"); 5890 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 5891 if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0"); 5892 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 5893 ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr); 5894 ierr = MatSetType(*mat,MATMPIAIJ);CHKERRQ(ierr); 5895 maij = (Mat_MPIAIJ*) (*mat)->data; 5896 5897 (*mat)->preallocated = PETSC_TRUE; 5898 5899 ierr = PetscLayoutSetUp((*mat)->rmap);CHKERRQ(ierr); 5900 ierr = PetscLayoutSetUp((*mat)->cmap);CHKERRQ(ierr); 5901 5902 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);CHKERRQ(ierr); 5903 ierr = MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);CHKERRQ(ierr); 5904 5905 ierr = MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5906 ierr = MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5907 ierr = MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5908 ierr = MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5909 5910 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5911 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 5912 ierr = MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 5913 PetscFunctionReturn(0); 5914 } 5915 5916 /* 5917 Special version for direct calls from Fortran 5918 */ 5919 #include <petsc-private/fortranimpl.h> 5920 5921 #if defined(PETSC_HAVE_FORTRAN_CAPS) 5922 #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ 5923 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 5924 #define matsetvaluesmpiaij_ matsetvaluesmpiaij 5925 #endif 5926 5927 /* Change these macros so can be used in void function */ 5928 #undef CHKERRQ 5929 #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr) 5930 #undef SETERRQ2 5931 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 5932 #undef SETERRQ3 5933 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 5934 #undef SETERRQ 5935 #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr) 5936 5937 #undef __FUNCT__ 5938 #define __FUNCT__ "matsetvaluesmpiaij_" 5939 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) 5940 { 5941 Mat mat = *mmat; 5942 PetscInt m = *mm, n = *mn; 5943 InsertMode addv = *maddv; 5944 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 5945 PetscScalar value; 5946 PetscErrorCode ierr; 5947 5948 MatCheckPreallocated(mat,1); 5949 if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv; 5950 5951 #if defined(PETSC_USE_DEBUG) 5952 else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values"); 5953 #endif 5954 { 5955 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend; 5956 PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col; 5957 PetscBool roworiented = aij->roworiented; 5958 5959 /* Some Variables required in the macro */ 5960 Mat A = aij->A; 5961 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 5962 PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j; 5963 MatScalar *aa = a->a; 5964 PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE); 5965 Mat B = aij->B; 5966 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 5967 PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n; 5968 MatScalar *ba = b->a; 5969 5970 PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2; 5971 PetscInt nonew = a->nonew; 5972 MatScalar *ap1,*ap2; 5973 5974 PetscFunctionBegin; 5975 for (i=0; i<m; i++) { 5976 if (im[i] < 0) continue; 5977 #if defined(PETSC_USE_DEBUG) 5978 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); 5979 #endif 5980 if (im[i] >= rstart && im[i] < rend) { 5981 row = im[i] - rstart; 5982 lastcol1 = -1; 5983 rp1 = aj + ai[row]; 5984 ap1 = aa + ai[row]; 5985 rmax1 = aimax[row]; 5986 nrow1 = ailen[row]; 5987 low1 = 0; 5988 high1 = nrow1; 5989 lastcol2 = -1; 5990 rp2 = bj + bi[row]; 5991 ap2 = ba + bi[row]; 5992 rmax2 = bimax[row]; 5993 nrow2 = bilen[row]; 5994 low2 = 0; 5995 high2 = nrow2; 5996 5997 for (j=0; j<n; j++) { 5998 if (roworiented) value = v[i*n+j]; 5999 else value = v[i+j*m]; 6000 if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue; 6001 if (in[j] >= cstart && in[j] < cend) { 6002 col = in[j] - cstart; 6003 MatSetValues_SeqAIJ_A_Private(row,col,value,addv); 6004 } else if (in[j] < 0) continue; 6005 #if defined(PETSC_USE_DEBUG) 6006 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); 6007 #endif 6008 else { 6009 if (mat->was_assembled) { 6010 if (!aij->colmap) { 6011 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 6012 } 6013 #if defined(PETSC_USE_CTABLE) 6014 ierr = PetscTableFind(aij->colmap,in[j]+1,&col);CHKERRQ(ierr); 6015 col--; 6016 #else 6017 col = aij->colmap[in[j]] - 1; 6018 #endif 6019 if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) { 6020 ierr = MatDisAssemble_MPIAIJ(mat);CHKERRQ(ierr); 6021 col = in[j]; 6022 /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */ 6023 B = aij->B; 6024 b = (Mat_SeqAIJ*)B->data; 6025 bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; 6026 rp2 = bj + bi[row]; 6027 ap2 = ba + bi[row]; 6028 rmax2 = bimax[row]; 6029 nrow2 = bilen[row]; 6030 low2 = 0; 6031 high2 = nrow2; 6032 bm = aij->B->rmap->n; 6033 ba = b->a; 6034 } 6035 } else col = in[j]; 6036 MatSetValues_SeqAIJ_B_Private(row,col,value,addv); 6037 } 6038 } 6039 } else if (!aij->donotstash) { 6040 if (roworiented) { 6041 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6042 } else { 6043 ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));CHKERRQ(ierr); 6044 } 6045 } 6046 } 6047 } 6048 PetscFunctionReturnVoid(); 6049 } 6050 6051