1 2 /* 3 Basic functions for basic parallel dense matrices. 4 */ 5 6 7 #include <../src/mat/impls/dense/mpi/mpidense.h> /*I "petscmat.h" I*/ 8 #include <../src/mat/impls/aij/mpi/mpiaij.h> 9 10 #undef __FUNCT__ 11 #define __FUNCT__ "MatDenseGetLocalMatrix" 12 /*@ 13 14 MatDenseGetLocalMatrix - For a MATMPIDENSE or MATSEQDENSE matrix returns the sequential 15 matrix that represents the operator. For sequential matrices it returns itself. 16 17 Input Parameter: 18 . A - the Seq or MPI dense matrix 19 20 Output Parameter: 21 . B - the inner matrix 22 23 Level: intermediate 24 25 @*/ 26 PetscErrorCode MatDenseGetLocalMatrix(Mat A,Mat *B) 27 { 28 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 29 PetscErrorCode ierr; 30 PetscBool flg; 31 32 PetscFunctionBegin; 33 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIDENSE,&flg);CHKERRQ(ierr); 34 if (flg) *B = mat->A; 35 else *B = A; 36 PetscFunctionReturn(0); 37 } 38 39 #undef __FUNCT__ 40 #define __FUNCT__ "MatGetRow_MPIDense" 41 PetscErrorCode MatGetRow_MPIDense(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 42 { 43 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 44 PetscErrorCode ierr; 45 PetscInt lrow,rstart = A->rmap->rstart,rend = A->rmap->rend; 46 47 PetscFunctionBegin; 48 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"only local rows"); 49 lrow = row - rstart; 50 ierr = MatGetRow(mat->A,lrow,nz,(const PetscInt**)idx,(const PetscScalar**)v);CHKERRQ(ierr); 51 PetscFunctionReturn(0); 52 } 53 54 #undef __FUNCT__ 55 #define __FUNCT__ "MatRestoreRow_MPIDense" 56 PetscErrorCode MatRestoreRow_MPIDense(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 57 { 58 PetscErrorCode ierr; 59 60 PetscFunctionBegin; 61 if (idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);} 62 if (v) {ierr = PetscFree(*v);CHKERRQ(ierr);} 63 PetscFunctionReturn(0); 64 } 65 66 #undef __FUNCT__ 67 #define __FUNCT__ "MatGetDiagonalBlock_MPIDense" 68 PetscErrorCode MatGetDiagonalBlock_MPIDense(Mat A,Mat *a) 69 { 70 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 71 PetscErrorCode ierr; 72 PetscInt m = A->rmap->n,rstart = A->rmap->rstart; 73 PetscScalar *array; 74 MPI_Comm comm; 75 Mat B; 76 77 PetscFunctionBegin; 78 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only square matrices supported."); 79 80 ierr = PetscObjectQuery((PetscObject)A,"DiagonalBlock",(PetscObject*)&B);CHKERRQ(ierr); 81 if (!B) { 82 ierr = PetscObjectGetComm((PetscObject)(mdn->A),&comm);CHKERRQ(ierr); 83 ierr = MatCreate(comm,&B);CHKERRQ(ierr); 84 ierr = MatSetSizes(B,m,m,m,m);CHKERRQ(ierr); 85 ierr = MatSetType(B,((PetscObject)mdn->A)->type_name);CHKERRQ(ierr); 86 ierr = MatDenseGetArray(mdn->A,&array);CHKERRQ(ierr); 87 ierr = MatSeqDenseSetPreallocation(B,array+m*rstart);CHKERRQ(ierr); 88 ierr = MatDenseRestoreArray(mdn->A,&array);CHKERRQ(ierr); 89 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 90 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 91 ierr = PetscObjectCompose((PetscObject)A,"DiagonalBlock",(PetscObject)B);CHKERRQ(ierr); 92 *a = B; 93 ierr = MatDestroy(&B);CHKERRQ(ierr); 94 } else *a = B; 95 PetscFunctionReturn(0); 96 } 97 98 #undef __FUNCT__ 99 #define __FUNCT__ "MatSetValues_MPIDense" 100 PetscErrorCode MatSetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],const PetscScalar v[],InsertMode addv) 101 { 102 Mat_MPIDense *A = (Mat_MPIDense*)mat->data; 103 PetscErrorCode ierr; 104 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row; 105 PetscBool roworiented = A->roworiented; 106 107 PetscFunctionBegin; 108 for (i=0; i<m; i++) { 109 if (idxm[i] < 0) continue; 110 if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 111 if (idxm[i] >= rstart && idxm[i] < rend) { 112 row = idxm[i] - rstart; 113 if (roworiented) { 114 ierr = MatSetValues(A->A,1,&row,n,idxn,v+i*n,addv);CHKERRQ(ierr); 115 } else { 116 for (j=0; j<n; j++) { 117 if (idxn[j] < 0) continue; 118 if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 119 ierr = MatSetValues(A->A,1,&row,1,&idxn[j],v+i+j*m,addv);CHKERRQ(ierr); 120 } 121 } 122 } else if (!A->donotstash) { 123 mat->assembled = PETSC_FALSE; 124 if (roworiented) { 125 ierr = MatStashValuesRow_Private(&mat->stash,idxm[i],n,idxn,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 126 } else { 127 ierr = MatStashValuesCol_Private(&mat->stash,idxm[i],n,idxn,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 128 } 129 } 130 } 131 PetscFunctionReturn(0); 132 } 133 134 #undef __FUNCT__ 135 #define __FUNCT__ "MatGetValues_MPIDense" 136 PetscErrorCode MatGetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 137 { 138 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 139 PetscErrorCode ierr; 140 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row; 141 142 PetscFunctionBegin; 143 for (i=0; i<m; i++) { 144 if (idxm[i] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */ 145 if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 146 if (idxm[i] >= rstart && idxm[i] < rend) { 147 row = idxm[i] - rstart; 148 for (j=0; j<n; j++) { 149 if (idxn[j] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */ 150 if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 151 ierr = MatGetValues(mdn->A,1,&row,1,&idxn[j],v+i*n+j);CHKERRQ(ierr); 152 } 153 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 154 } 155 PetscFunctionReturn(0); 156 } 157 158 #undef __FUNCT__ 159 #define __FUNCT__ "MatDenseGetArray_MPIDense" 160 PetscErrorCode MatDenseGetArray_MPIDense(Mat A,PetscScalar *array[]) 161 { 162 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 163 PetscErrorCode ierr; 164 165 PetscFunctionBegin; 166 ierr = MatDenseGetArray(a->A,array);CHKERRQ(ierr); 167 PetscFunctionReturn(0); 168 } 169 170 #undef __FUNCT__ 171 #define __FUNCT__ "MatGetSubMatrix_MPIDense" 172 static PetscErrorCode MatGetSubMatrix_MPIDense(Mat A,IS isrow,IS iscol,MatReuse scall,Mat *B) 173 { 174 Mat_MPIDense *mat = (Mat_MPIDense*)A->data,*newmatd; 175 Mat_SeqDense *lmat = (Mat_SeqDense*)mat->A->data; 176 PetscErrorCode ierr; 177 PetscInt i,j,rstart,rend,nrows,ncols,Ncols,nlrows,nlcols; 178 const PetscInt *irow,*icol; 179 PetscScalar *av,*bv,*v = lmat->v; 180 Mat newmat; 181 IS iscol_local; 182 183 PetscFunctionBegin; 184 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 185 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 186 ierr = ISGetIndices(iscol_local,&icol);CHKERRQ(ierr); 187 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 188 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 189 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); /* global number of columns, size of iscol_local */ 190 191 /* No parallel redistribution currently supported! Should really check each index set 192 to comfirm that it is OK. ... Currently supports only submatrix same partitioning as 193 original matrix! */ 194 195 ierr = MatGetLocalSize(A,&nlrows,&nlcols);CHKERRQ(ierr); 196 ierr = MatGetOwnershipRange(A,&rstart,&rend);CHKERRQ(ierr); 197 198 /* Check submatrix call */ 199 if (scall == MAT_REUSE_MATRIX) { 200 /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); */ 201 /* Really need to test rows and column sizes! */ 202 newmat = *B; 203 } else { 204 /* Create and fill new matrix */ 205 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 206 ierr = MatSetSizes(newmat,nrows,ncols,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 207 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 208 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 209 } 210 211 /* Now extract the data pointers and do the copy, column at a time */ 212 newmatd = (Mat_MPIDense*)newmat->data; 213 bv = ((Mat_SeqDense*)newmatd->A->data)->v; 214 215 for (i=0; i<Ncols; i++) { 216 av = v + ((Mat_SeqDense*)mat->A->data)->lda*icol[i]; 217 for (j=0; j<nrows; j++) { 218 *bv++ = av[irow[j] - rstart]; 219 } 220 } 221 222 /* Assemble the matrices so that the correct flags are set */ 223 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 224 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 225 226 /* Free work space */ 227 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 228 ierr = ISRestoreIndices(iscol_local,&icol);CHKERRQ(ierr); 229 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 230 *B = newmat; 231 PetscFunctionReturn(0); 232 } 233 234 #undef __FUNCT__ 235 #define __FUNCT__ "MatDenseRestoreArray_MPIDense" 236 PetscErrorCode MatDenseRestoreArray_MPIDense(Mat A,PetscScalar *array[]) 237 { 238 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 239 PetscErrorCode ierr; 240 241 PetscFunctionBegin; 242 ierr = MatDenseRestoreArray(a->A,array);CHKERRQ(ierr); 243 PetscFunctionReturn(0); 244 } 245 246 #undef __FUNCT__ 247 #define __FUNCT__ "MatAssemblyBegin_MPIDense" 248 PetscErrorCode MatAssemblyBegin_MPIDense(Mat mat,MatAssemblyType mode) 249 { 250 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 251 MPI_Comm comm; 252 PetscErrorCode ierr; 253 PetscInt nstash,reallocs; 254 InsertMode addv; 255 256 PetscFunctionBegin; 257 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 258 /* make sure all processors are either in INSERTMODE or ADDMODE */ 259 ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,comm);CHKERRQ(ierr); 260 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs"); 261 mat->insertmode = addv; /* in case this processor had no cache */ 262 263 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 264 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 265 ierr = PetscInfo2(mdn->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 266 PetscFunctionReturn(0); 267 } 268 269 #undef __FUNCT__ 270 #define __FUNCT__ "MatAssemblyEnd_MPIDense" 271 PetscErrorCode MatAssemblyEnd_MPIDense(Mat mat,MatAssemblyType mode) 272 { 273 Mat_MPIDense *mdn=(Mat_MPIDense*)mat->data; 274 PetscErrorCode ierr; 275 PetscInt i,*row,*col,flg,j,rstart,ncols; 276 PetscMPIInt n; 277 PetscScalar *val; 278 279 PetscFunctionBegin; 280 /* wait on receives */ 281 while (1) { 282 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 283 if (!flg) break; 284 285 for (i=0; i<n;) { 286 /* Now identify the consecutive vals belonging to the same row */ 287 for (j=i,rstart=row[j]; j<n; j++) { 288 if (row[j] != rstart) break; 289 } 290 if (j < n) ncols = j-i; 291 else ncols = n-i; 292 /* Now assemble all these values with a single function call */ 293 ierr = MatSetValues_MPIDense(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 294 i = j; 295 } 296 } 297 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 298 299 ierr = MatAssemblyBegin(mdn->A,mode);CHKERRQ(ierr); 300 ierr = MatAssemblyEnd(mdn->A,mode);CHKERRQ(ierr); 301 302 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 303 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 304 } 305 PetscFunctionReturn(0); 306 } 307 308 #undef __FUNCT__ 309 #define __FUNCT__ "MatZeroEntries_MPIDense" 310 PetscErrorCode MatZeroEntries_MPIDense(Mat A) 311 { 312 PetscErrorCode ierr; 313 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 314 315 PetscFunctionBegin; 316 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 317 PetscFunctionReturn(0); 318 } 319 320 /* the code does not do the diagonal entries correctly unless the 321 matrix is square and the column and row owerships are identical. 322 This is a BUG. The only way to fix it seems to be to access 323 mdn->A and mdn->B directly and not through the MatZeroRows() 324 routine. 325 */ 326 #undef __FUNCT__ 327 #define __FUNCT__ "MatZeroRows_MPIDense" 328 PetscErrorCode MatZeroRows_MPIDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 329 { 330 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 331 PetscErrorCode ierr; 332 PetscInt i,*owners = A->rmap->range; 333 PetscInt *sizes,j,idx,nsends; 334 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 335 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source; 336 PetscInt *lens,*lrows,*values; 337 PetscMPIInt n,imdex,rank = l->rank,size = l->size; 338 MPI_Comm comm; 339 MPI_Request *send_waits,*recv_waits; 340 MPI_Status recv_status,*send_status; 341 PetscBool found; 342 const PetscScalar *xx; 343 PetscScalar *bb; 344 345 PetscFunctionBegin; 346 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 347 if (A->rmap->N != A->cmap->N) SETERRQ(comm,PETSC_ERR_SUP,"Only handles square matrices"); 348 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only handles matrices with identical column and row ownership"); 349 /* first count number of contributors to each processor */ 350 ierr = PetscCalloc1(2*size,&sizes);CHKERRQ(ierr); 351 ierr = PetscMalloc1(N+1,&owner);CHKERRQ(ierr); /* see note*/ 352 for (i=0; i<N; i++) { 353 idx = rows[i]; 354 found = PETSC_FALSE; 355 for (j=0; j<size; j++) { 356 if (idx >= owners[j] && idx < owners[j+1]) { 357 sizes[2*j]++; sizes[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break; 358 } 359 } 360 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 361 } 362 nsends = 0; 363 for (i=0; i<size; i++) nsends += sizes[2*i+1]; 364 365 /* inform other processors of number of messages and max length*/ 366 ierr = PetscMaxSum(comm,sizes,&nmax,&nrecvs);CHKERRQ(ierr); 367 368 /* post receives: */ 369 ierr = PetscMalloc1((nrecvs+1)*(nmax+1),&rvalues);CHKERRQ(ierr); 370 ierr = PetscMalloc1((nrecvs+1),&recv_waits);CHKERRQ(ierr); 371 for (i=0; i<nrecvs; i++) { 372 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 373 } 374 375 /* do sends: 376 1) starts[i] gives the starting index in svalues for stuff going to 377 the ith processor 378 */ 379 ierr = PetscMalloc1((N+1),&svalues);CHKERRQ(ierr); 380 ierr = PetscMalloc1((nsends+1),&send_waits);CHKERRQ(ierr); 381 ierr = PetscMalloc1((size+1),&starts);CHKERRQ(ierr); 382 383 starts[0] = 0; 384 for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 385 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 386 387 starts[0] = 0; 388 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 389 count = 0; 390 for (i=0; i<size; i++) { 391 if (sizes[2*i+1]) { 392 ierr = MPI_Isend(svalues+starts[i],sizes[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 393 } 394 } 395 ierr = PetscFree(starts);CHKERRQ(ierr); 396 397 base = owners[rank]; 398 399 /* wait on receives */ 400 ierr = PetscMalloc2(nrecvs,&lens,nrecvs,&source);CHKERRQ(ierr); 401 count = nrecvs; 402 slen = 0; 403 while (count) { 404 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 405 /* unpack receives into our local space */ 406 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 407 408 source[imdex] = recv_status.MPI_SOURCE; 409 lens[imdex] = n; 410 slen += n; 411 count--; 412 } 413 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 414 415 /* move the data into the send scatter */ 416 ierr = PetscMalloc1((slen+1),&lrows);CHKERRQ(ierr); 417 count = 0; 418 for (i=0; i<nrecvs; i++) { 419 values = rvalues + i*nmax; 420 for (j=0; j<lens[i]; j++) { 421 lrows[count++] = values[j] - base; 422 } 423 } 424 ierr = PetscFree(rvalues);CHKERRQ(ierr); 425 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 426 ierr = PetscFree(owner);CHKERRQ(ierr); 427 ierr = PetscFree(sizes);CHKERRQ(ierr); 428 429 /* fix right hand side if needed */ 430 if (x && b) { 431 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 432 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 433 for (i=0; i<slen; i++) { 434 bb[lrows[i]] = diag*xx[lrows[i]]; 435 } 436 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 437 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 438 } 439 440 /* actually zap the local rows */ 441 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 442 if (diag != 0.0) { 443 Mat_SeqDense *ll = (Mat_SeqDense*)l->A->data; 444 PetscInt m = ll->lda, i; 445 446 for (i=0; i<slen; i++) { 447 ll->v[lrows[i] + m*(A->cmap->rstart + lrows[i])] = diag; 448 } 449 } 450 ierr = PetscFree(lrows);CHKERRQ(ierr); 451 452 /* wait on sends */ 453 if (nsends) { 454 ierr = PetscMalloc1(nsends,&send_status);CHKERRQ(ierr); 455 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 456 ierr = PetscFree(send_status);CHKERRQ(ierr); 457 } 458 ierr = PetscFree(send_waits);CHKERRQ(ierr); 459 ierr = PetscFree(svalues);CHKERRQ(ierr); 460 PetscFunctionReturn(0); 461 } 462 463 #undef __FUNCT__ 464 #define __FUNCT__ "MatMult_MPIDense" 465 PetscErrorCode MatMult_MPIDense(Mat mat,Vec xx,Vec yy) 466 { 467 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 468 PetscErrorCode ierr; 469 470 PetscFunctionBegin; 471 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 472 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 473 ierr = MatMult_SeqDense(mdn->A,mdn->lvec,yy);CHKERRQ(ierr); 474 PetscFunctionReturn(0); 475 } 476 477 #undef __FUNCT__ 478 #define __FUNCT__ "MatMultAdd_MPIDense" 479 PetscErrorCode MatMultAdd_MPIDense(Mat mat,Vec xx,Vec yy,Vec zz) 480 { 481 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 482 PetscErrorCode ierr; 483 484 PetscFunctionBegin; 485 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 486 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 487 ierr = MatMultAdd_SeqDense(mdn->A,mdn->lvec,yy,zz);CHKERRQ(ierr); 488 PetscFunctionReturn(0); 489 } 490 491 #undef __FUNCT__ 492 #define __FUNCT__ "MatMultTranspose_MPIDense" 493 PetscErrorCode MatMultTranspose_MPIDense(Mat A,Vec xx,Vec yy) 494 { 495 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 496 PetscErrorCode ierr; 497 PetscScalar zero = 0.0; 498 499 PetscFunctionBegin; 500 ierr = VecSet(yy,zero);CHKERRQ(ierr); 501 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 502 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 503 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 504 PetscFunctionReturn(0); 505 } 506 507 #undef __FUNCT__ 508 #define __FUNCT__ "MatMultTransposeAdd_MPIDense" 509 PetscErrorCode MatMultTransposeAdd_MPIDense(Mat A,Vec xx,Vec yy,Vec zz) 510 { 511 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 512 PetscErrorCode ierr; 513 514 PetscFunctionBegin; 515 ierr = VecCopy(yy,zz);CHKERRQ(ierr); 516 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 517 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 518 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 519 PetscFunctionReturn(0); 520 } 521 522 #undef __FUNCT__ 523 #define __FUNCT__ "MatGetDiagonal_MPIDense" 524 PetscErrorCode MatGetDiagonal_MPIDense(Mat A,Vec v) 525 { 526 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 527 Mat_SeqDense *aloc = (Mat_SeqDense*)a->A->data; 528 PetscErrorCode ierr; 529 PetscInt len,i,n,m = A->rmap->n,radd; 530 PetscScalar *x,zero = 0.0; 531 532 PetscFunctionBegin; 533 ierr = VecSet(v,zero);CHKERRQ(ierr); 534 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 535 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 536 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 537 len = PetscMin(a->A->rmap->n,a->A->cmap->n); 538 radd = A->rmap->rstart*m; 539 for (i=0; i<len; i++) { 540 x[i] = aloc->v[radd + i*m + i]; 541 } 542 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 543 PetscFunctionReturn(0); 544 } 545 546 #undef __FUNCT__ 547 #define __FUNCT__ "MatDestroy_MPIDense" 548 PetscErrorCode MatDestroy_MPIDense(Mat mat) 549 { 550 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 551 PetscErrorCode ierr; 552 553 PetscFunctionBegin; 554 #if defined(PETSC_USE_LOG) 555 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 556 #endif 557 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 558 ierr = MatDestroy(&mdn->A);CHKERRQ(ierr); 559 ierr = VecDestroy(&mdn->lvec);CHKERRQ(ierr); 560 ierr = VecScatterDestroy(&mdn->Mvctx);CHKERRQ(ierr); 561 562 ierr = PetscFree(mat->data);CHKERRQ(ierr); 563 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 564 565 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 566 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 567 #if defined(PETSC_HAVE_ELEMENTAL) 568 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",NULL);CHKERRQ(ierr); 569 #endif 570 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr); 571 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 572 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 573 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 574 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 575 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 576 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 577 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 578 PetscFunctionReturn(0); 579 } 580 581 #undef __FUNCT__ 582 #define __FUNCT__ "MatView_MPIDense_Binary" 583 static PetscErrorCode MatView_MPIDense_Binary(Mat mat,PetscViewer viewer) 584 { 585 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 586 PetscErrorCode ierr; 587 PetscViewerFormat format; 588 int fd; 589 PetscInt header[4],mmax,N = mat->cmap->N,i,j,m,k; 590 PetscMPIInt rank,tag = ((PetscObject)viewer)->tag,size; 591 PetscScalar *work,*v,*vv; 592 Mat_SeqDense *a = (Mat_SeqDense*)mdn->A->data; 593 594 PetscFunctionBegin; 595 if (mdn->size == 1) { 596 ierr = MatView(mdn->A,viewer);CHKERRQ(ierr); 597 } else { 598 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 599 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 600 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 601 602 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 603 if (format == PETSC_VIEWER_NATIVE) { 604 605 if (!rank) { 606 /* store the matrix as a dense matrix */ 607 header[0] = MAT_FILE_CLASSID; 608 header[1] = mat->rmap->N; 609 header[2] = N; 610 header[3] = MATRIX_BINARY_FORMAT_DENSE; 611 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 612 613 /* get largest work array needed for transposing array */ 614 mmax = mat->rmap->n; 615 for (i=1; i<size; i++) { 616 mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]); 617 } 618 ierr = PetscMalloc1(mmax*N,&work);CHKERRQ(ierr); 619 620 /* write out local array, by rows */ 621 m = mat->rmap->n; 622 v = a->v; 623 for (j=0; j<N; j++) { 624 for (i=0; i<m; i++) { 625 work[j + i*N] = *v++; 626 } 627 } 628 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 629 /* get largest work array to receive messages from other processes, excludes process zero */ 630 mmax = 0; 631 for (i=1; i<size; i++) { 632 mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]); 633 } 634 ierr = PetscMalloc1(mmax*N,&vv);CHKERRQ(ierr); 635 for (k = 1; k < size; k++) { 636 v = vv; 637 m = mat->rmap->range[k+1] - mat->rmap->range[k]; 638 ierr = MPIULong_Recv(v,m*N,MPIU_SCALAR,k,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 639 640 for (j = 0; j < N; j++) { 641 for (i = 0; i < m; i++) { 642 work[j + i*N] = *v++; 643 } 644 } 645 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 646 } 647 ierr = PetscFree(work);CHKERRQ(ierr); 648 ierr = PetscFree(vv);CHKERRQ(ierr); 649 } else { 650 ierr = MPIULong_Send(a->v,mat->rmap->n*mat->cmap->N,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 651 } 652 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"To store a parallel dense matrix you must first call PetscViewerSetFormat(viewer,PETSC_VIEWER_NATIVE)"); 653 } 654 PetscFunctionReturn(0); 655 } 656 657 extern PetscErrorCode MatView_SeqDense(Mat,PetscViewer); 658 #include <petscdraw.h> 659 #undef __FUNCT__ 660 #define __FUNCT__ "MatView_MPIDense_ASCIIorDraworSocket" 661 static PetscErrorCode MatView_MPIDense_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 662 { 663 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 664 PetscErrorCode ierr; 665 PetscMPIInt rank = mdn->rank; 666 PetscViewerType vtype; 667 PetscBool iascii,isdraw; 668 PetscViewer sviewer; 669 PetscViewerFormat format; 670 671 PetscFunctionBegin; 672 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 673 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 674 if (iascii) { 675 ierr = PetscViewerGetType(viewer,&vtype);CHKERRQ(ierr); 676 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 677 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 678 MatInfo info; 679 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 680 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); 681 ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] local rows %D nz %D nz alloced %D mem %D \n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);CHKERRQ(ierr); 682 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 683 ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); 684 ierr = VecScatterView(mdn->Mvctx,viewer);CHKERRQ(ierr); 685 PetscFunctionReturn(0); 686 } else if (format == PETSC_VIEWER_ASCII_INFO) { 687 PetscFunctionReturn(0); 688 } 689 } else if (isdraw) { 690 PetscDraw draw; 691 PetscBool isnull; 692 693 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 694 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 695 if (isnull) PetscFunctionReturn(0); 696 } 697 698 { 699 /* assemble the entire matrix onto first processor. */ 700 Mat A; 701 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,row,i,nz; 702 PetscInt *cols; 703 PetscScalar *vals; 704 705 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 706 if (!rank) { 707 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 708 } else { 709 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 710 } 711 /* Since this is a temporary matrix, MATMPIDENSE instead of ((PetscObject)A)->type_name here is probably acceptable. */ 712 ierr = MatSetType(A,MATMPIDENSE);CHKERRQ(ierr); 713 ierr = MatMPIDenseSetPreallocation(A,NULL);CHKERRQ(ierr); 714 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 715 716 /* Copy the matrix ... This isn't the most efficient means, 717 but it's quick for now */ 718 A->insertmode = INSERT_VALUES; 719 720 row = mat->rmap->rstart; 721 m = mdn->A->rmap->n; 722 for (i=0; i<m; i++) { 723 ierr = MatGetRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 724 ierr = MatSetValues_MPIDense(A,1,&row,nz,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 725 ierr = MatRestoreRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 726 row++; 727 } 728 729 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 730 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 731 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 732 if (!rank) { 733 ierr = MatView_SeqDense(((Mat_MPIDense*)(A->data))->A,sviewer);CHKERRQ(ierr); 734 } 735 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 736 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 737 ierr = MatDestroy(&A);CHKERRQ(ierr); 738 } 739 PetscFunctionReturn(0); 740 } 741 742 #undef __FUNCT__ 743 #define __FUNCT__ "MatView_MPIDense" 744 PetscErrorCode MatView_MPIDense(Mat mat,PetscViewer viewer) 745 { 746 PetscErrorCode ierr; 747 PetscBool iascii,isbinary,isdraw,issocket; 748 749 PetscFunctionBegin; 750 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 751 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 752 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 753 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 754 755 if (iascii || issocket || isdraw) { 756 ierr = MatView_MPIDense_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 757 } else if (isbinary) { 758 ierr = MatView_MPIDense_Binary(mat,viewer);CHKERRQ(ierr); 759 } 760 PetscFunctionReturn(0); 761 } 762 763 #undef __FUNCT__ 764 #define __FUNCT__ "MatGetInfo_MPIDense" 765 PetscErrorCode MatGetInfo_MPIDense(Mat A,MatInfoType flag,MatInfo *info) 766 { 767 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 768 Mat mdn = mat->A; 769 PetscErrorCode ierr; 770 PetscReal isend[5],irecv[5]; 771 772 PetscFunctionBegin; 773 info->block_size = 1.0; 774 775 ierr = MatGetInfo(mdn,MAT_LOCAL,info);CHKERRQ(ierr); 776 777 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 778 isend[3] = info->memory; isend[4] = info->mallocs; 779 if (flag == MAT_LOCAL) { 780 info->nz_used = isend[0]; 781 info->nz_allocated = isend[1]; 782 info->nz_unneeded = isend[2]; 783 info->memory = isend[3]; 784 info->mallocs = isend[4]; 785 } else if (flag == MAT_GLOBAL_MAX) { 786 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 787 788 info->nz_used = irecv[0]; 789 info->nz_allocated = irecv[1]; 790 info->nz_unneeded = irecv[2]; 791 info->memory = irecv[3]; 792 info->mallocs = irecv[4]; 793 } else if (flag == MAT_GLOBAL_SUM) { 794 ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 795 796 info->nz_used = irecv[0]; 797 info->nz_allocated = irecv[1]; 798 info->nz_unneeded = irecv[2]; 799 info->memory = irecv[3]; 800 info->mallocs = irecv[4]; 801 } 802 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 803 info->fill_ratio_needed = 0; 804 info->factor_mallocs = 0; 805 PetscFunctionReturn(0); 806 } 807 808 #undef __FUNCT__ 809 #define __FUNCT__ "MatSetOption_MPIDense" 810 PetscErrorCode MatSetOption_MPIDense(Mat A,MatOption op,PetscBool flg) 811 { 812 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 813 PetscErrorCode ierr; 814 815 PetscFunctionBegin; 816 switch (op) { 817 case MAT_NEW_NONZERO_LOCATIONS: 818 case MAT_NEW_NONZERO_LOCATION_ERR: 819 case MAT_NEW_NONZERO_ALLOCATION_ERR: 820 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 821 break; 822 case MAT_ROW_ORIENTED: 823 a->roworiented = flg; 824 825 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 826 break; 827 case MAT_NEW_DIAGONALS: 828 case MAT_KEEP_NONZERO_PATTERN: 829 case MAT_USE_HASH_TABLE: 830 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 831 break; 832 case MAT_IGNORE_OFF_PROC_ENTRIES: 833 a->donotstash = flg; 834 break; 835 case MAT_SYMMETRIC: 836 case MAT_STRUCTURALLY_SYMMETRIC: 837 case MAT_HERMITIAN: 838 case MAT_SYMMETRY_ETERNAL: 839 case MAT_IGNORE_LOWER_TRIANGULAR: 840 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 841 break; 842 default: 843 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 844 } 845 PetscFunctionReturn(0); 846 } 847 848 849 #undef __FUNCT__ 850 #define __FUNCT__ "MatDiagonalScale_MPIDense" 851 PetscErrorCode MatDiagonalScale_MPIDense(Mat A,Vec ll,Vec rr) 852 { 853 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 854 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 855 PetscScalar *l,*r,x,*v; 856 PetscErrorCode ierr; 857 PetscInt i,j,s2a,s3a,s2,s3,m=mdn->A->rmap->n,n=mdn->A->cmap->n; 858 859 PetscFunctionBegin; 860 ierr = MatGetLocalSize(A,&s2,&s3);CHKERRQ(ierr); 861 if (ll) { 862 ierr = VecGetLocalSize(ll,&s2a);CHKERRQ(ierr); 863 if (s2a != s2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector non-conforming local size, %d != %d.", s2a, s2); 864 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 865 for (i=0; i<m; i++) { 866 x = l[i]; 867 v = mat->v + i; 868 for (j=0; j<n; j++) { (*v) *= x; v+= m;} 869 } 870 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 871 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 872 } 873 if (rr) { 874 ierr = VecGetLocalSize(rr,&s3a);CHKERRQ(ierr); 875 if (s3a != s3) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec non-conforming local size, %d != %d.", s3a, s3); 876 ierr = VecScatterBegin(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 877 ierr = VecScatterEnd(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 878 ierr = VecGetArray(mdn->lvec,&r);CHKERRQ(ierr); 879 for (i=0; i<n; i++) { 880 x = r[i]; 881 v = mat->v + i*m; 882 for (j=0; j<m; j++) (*v++) *= x; 883 } 884 ierr = VecRestoreArray(mdn->lvec,&r);CHKERRQ(ierr); 885 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 886 } 887 PetscFunctionReturn(0); 888 } 889 890 #undef __FUNCT__ 891 #define __FUNCT__ "MatNorm_MPIDense" 892 PetscErrorCode MatNorm_MPIDense(Mat A,NormType type,PetscReal *nrm) 893 { 894 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 895 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 896 PetscErrorCode ierr; 897 PetscInt i,j; 898 PetscReal sum = 0.0; 899 PetscScalar *v = mat->v; 900 901 PetscFunctionBegin; 902 if (mdn->size == 1) { 903 ierr = MatNorm(mdn->A,type,nrm);CHKERRQ(ierr); 904 } else { 905 if (type == NORM_FROBENIUS) { 906 for (i=0; i<mdn->A->cmap->n*mdn->A->rmap->n; i++) { 907 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 908 } 909 ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 910 *nrm = PetscSqrtReal(*nrm); 911 ierr = PetscLogFlops(2.0*mdn->A->cmap->n*mdn->A->rmap->n);CHKERRQ(ierr); 912 } else if (type == NORM_1) { 913 PetscReal *tmp,*tmp2; 914 ierr = PetscMalloc2(A->cmap->N,&tmp,A->cmap->N,&tmp2);CHKERRQ(ierr); 915 ierr = PetscMemzero(tmp,A->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 916 ierr = PetscMemzero(tmp2,A->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 917 *nrm = 0.0; 918 v = mat->v; 919 for (j=0; j<mdn->A->cmap->n; j++) { 920 for (i=0; i<mdn->A->rmap->n; i++) { 921 tmp[j] += PetscAbsScalar(*v); v++; 922 } 923 } 924 ierr = MPI_Allreduce(tmp,tmp2,A->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 925 for (j=0; j<A->cmap->N; j++) { 926 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 927 } 928 ierr = PetscFree2(tmp,tmp);CHKERRQ(ierr); 929 ierr = PetscLogFlops(A->cmap->n*A->rmap->n);CHKERRQ(ierr); 930 } else if (type == NORM_INFINITY) { /* max row norm */ 931 PetscReal ntemp; 932 ierr = MatNorm(mdn->A,type,&ntemp);CHKERRQ(ierr); 933 ierr = MPI_Allreduce(&ntemp,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 934 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for two norm"); 935 } 936 PetscFunctionReturn(0); 937 } 938 939 #undef __FUNCT__ 940 #define __FUNCT__ "MatTranspose_MPIDense" 941 PetscErrorCode MatTranspose_MPIDense(Mat A,MatReuse reuse,Mat *matout) 942 { 943 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 944 Mat_SeqDense *Aloc = (Mat_SeqDense*)a->A->data; 945 Mat B; 946 PetscInt M = A->rmap->N,N = A->cmap->N,m,n,*rwork,rstart = A->rmap->rstart; 947 PetscErrorCode ierr; 948 PetscInt j,i; 949 PetscScalar *v; 950 951 PetscFunctionBegin; 952 if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports square matrix only in-place"); 953 if (reuse == MAT_INITIAL_MATRIX || A == *matout) { 954 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 955 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 956 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 957 ierr = MatMPIDenseSetPreallocation(B,NULL);CHKERRQ(ierr); 958 } else { 959 B = *matout; 960 } 961 962 m = a->A->rmap->n; n = a->A->cmap->n; v = Aloc->v; 963 ierr = PetscMalloc1(m,&rwork);CHKERRQ(ierr); 964 for (i=0; i<m; i++) rwork[i] = rstart + i; 965 for (j=0; j<n; j++) { 966 ierr = MatSetValues(B,1,&j,m,rwork,v,INSERT_VALUES);CHKERRQ(ierr); 967 v += m; 968 } 969 ierr = PetscFree(rwork);CHKERRQ(ierr); 970 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 971 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 972 if (reuse == MAT_INITIAL_MATRIX || *matout != A) { 973 *matout = B; 974 } else { 975 ierr = MatHeaderMerge(A,B);CHKERRQ(ierr); 976 } 977 PetscFunctionReturn(0); 978 } 979 980 981 static PetscErrorCode MatDuplicate_MPIDense(Mat,MatDuplicateOption,Mat*); 982 extern PetscErrorCode MatScale_MPIDense(Mat,PetscScalar); 983 984 #undef __FUNCT__ 985 #define __FUNCT__ "MatSetUp_MPIDense" 986 PetscErrorCode MatSetUp_MPIDense(Mat A) 987 { 988 PetscErrorCode ierr; 989 990 PetscFunctionBegin; 991 ierr = MatMPIDenseSetPreallocation(A,0);CHKERRQ(ierr); 992 PetscFunctionReturn(0); 993 } 994 995 #undef __FUNCT__ 996 #define __FUNCT__ "MatAXPY_MPIDense" 997 PetscErrorCode MatAXPY_MPIDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str) 998 { 999 PetscErrorCode ierr; 1000 Mat_MPIDense *A = (Mat_MPIDense*)Y->data, *B = (Mat_MPIDense*)X->data; 1001 1002 PetscFunctionBegin; 1003 ierr = MatAXPY(A->A,alpha,B->A,str);CHKERRQ(ierr); 1004 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 1005 PetscFunctionReturn(0); 1006 } 1007 1008 #undef __FUNCT__ 1009 #define __FUNCT__ "MatConjugate_MPIDense" 1010 PetscErrorCode MatConjugate_MPIDense(Mat mat) 1011 { 1012 Mat_MPIDense *a = (Mat_MPIDense*)mat->data; 1013 PetscErrorCode ierr; 1014 1015 PetscFunctionBegin; 1016 ierr = MatConjugate(a->A);CHKERRQ(ierr); 1017 PetscFunctionReturn(0); 1018 } 1019 1020 #undef __FUNCT__ 1021 #define __FUNCT__ "MatRealPart_MPIDense" 1022 PetscErrorCode MatRealPart_MPIDense(Mat A) 1023 { 1024 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1025 PetscErrorCode ierr; 1026 1027 PetscFunctionBegin; 1028 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1029 PetscFunctionReturn(0); 1030 } 1031 1032 #undef __FUNCT__ 1033 #define __FUNCT__ "MatImaginaryPart_MPIDense" 1034 PetscErrorCode MatImaginaryPart_MPIDense(Mat A) 1035 { 1036 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1037 PetscErrorCode ierr; 1038 1039 PetscFunctionBegin; 1040 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1041 PetscFunctionReturn(0); 1042 } 1043 1044 extern PetscErrorCode MatGetColumnNorms_SeqDense(Mat,NormType,PetscReal*); 1045 #undef __FUNCT__ 1046 #define __FUNCT__ "MatGetColumnNorms_MPIDense" 1047 PetscErrorCode MatGetColumnNorms_MPIDense(Mat A,NormType type,PetscReal *norms) 1048 { 1049 PetscErrorCode ierr; 1050 PetscInt i,n; 1051 Mat_MPIDense *a = (Mat_MPIDense*) A->data; 1052 PetscReal *work; 1053 1054 PetscFunctionBegin; 1055 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 1056 ierr = PetscMalloc1(n,&work);CHKERRQ(ierr); 1057 ierr = MatGetColumnNorms_SeqDense(a->A,type,work);CHKERRQ(ierr); 1058 if (type == NORM_2) { 1059 for (i=0; i<n; i++) work[i] *= work[i]; 1060 } 1061 if (type == NORM_INFINITY) { 1062 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 1063 } else { 1064 ierr = MPI_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 1065 } 1066 ierr = PetscFree(work);CHKERRQ(ierr); 1067 if (type == NORM_2) { 1068 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 1069 } 1070 PetscFunctionReturn(0); 1071 } 1072 1073 #undef __FUNCT__ 1074 #define __FUNCT__ "MatSetRandom_MPIDense" 1075 static PetscErrorCode MatSetRandom_MPIDense(Mat x,PetscRandom rctx) 1076 { 1077 Mat_MPIDense *d = (Mat_MPIDense*)x->data; 1078 PetscErrorCode ierr; 1079 PetscScalar *a; 1080 PetscInt m,n,i; 1081 1082 PetscFunctionBegin; 1083 ierr = MatGetSize(d->A,&m,&n);CHKERRQ(ierr); 1084 ierr = MatDenseGetArray(d->A,&a);CHKERRQ(ierr); 1085 for (i=0; i<m*n; i++) { 1086 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 1087 } 1088 ierr = MatDenseRestoreArray(d->A,&a);CHKERRQ(ierr); 1089 PetscFunctionReturn(0); 1090 } 1091 1092 /* -------------------------------------------------------------------*/ 1093 static struct _MatOps MatOps_Values = { MatSetValues_MPIDense, 1094 MatGetRow_MPIDense, 1095 MatRestoreRow_MPIDense, 1096 MatMult_MPIDense, 1097 /* 4*/ MatMultAdd_MPIDense, 1098 MatMultTranspose_MPIDense, 1099 MatMultTransposeAdd_MPIDense, 1100 0, 1101 0, 1102 0, 1103 /* 10*/ 0, 1104 0, 1105 0, 1106 0, 1107 MatTranspose_MPIDense, 1108 /* 15*/ MatGetInfo_MPIDense, 1109 MatEqual_MPIDense, 1110 MatGetDiagonal_MPIDense, 1111 MatDiagonalScale_MPIDense, 1112 MatNorm_MPIDense, 1113 /* 20*/ MatAssemblyBegin_MPIDense, 1114 MatAssemblyEnd_MPIDense, 1115 MatSetOption_MPIDense, 1116 MatZeroEntries_MPIDense, 1117 /* 24*/ MatZeroRows_MPIDense, 1118 0, 1119 0, 1120 0, 1121 0, 1122 /* 29*/ MatSetUp_MPIDense, 1123 0, 1124 0, 1125 0, 1126 0, 1127 /* 34*/ MatDuplicate_MPIDense, 1128 0, 1129 0, 1130 0, 1131 0, 1132 /* 39*/ MatAXPY_MPIDense, 1133 MatGetSubMatrices_MPIDense, 1134 0, 1135 MatGetValues_MPIDense, 1136 0, 1137 /* 44*/ 0, 1138 MatScale_MPIDense, 1139 0, 1140 0, 1141 0, 1142 /* 49*/ MatSetRandom_MPIDense, 1143 0, 1144 0, 1145 0, 1146 0, 1147 /* 54*/ 0, 1148 0, 1149 0, 1150 0, 1151 0, 1152 /* 59*/ MatGetSubMatrix_MPIDense, 1153 MatDestroy_MPIDense, 1154 MatView_MPIDense, 1155 0, 1156 0, 1157 /* 64*/ 0, 1158 0, 1159 0, 1160 0, 1161 0, 1162 /* 69*/ 0, 1163 0, 1164 0, 1165 0, 1166 0, 1167 /* 74*/ 0, 1168 0, 1169 0, 1170 0, 1171 0, 1172 /* 79*/ 0, 1173 0, 1174 0, 1175 0, 1176 /* 83*/ MatLoad_MPIDense, 1177 0, 1178 0, 1179 0, 1180 0, 1181 0, 1182 /* 89*/ 1183 0, 1184 0, 1185 0, 1186 0, 1187 0, 1188 /* 94*/ 0, 1189 0, 1190 0, 1191 0, 1192 0, 1193 /* 99*/ 0, 1194 0, 1195 0, 1196 MatConjugate_MPIDense, 1197 0, 1198 /*104*/ 0, 1199 MatRealPart_MPIDense, 1200 MatImaginaryPart_MPIDense, 1201 0, 1202 0, 1203 /*109*/ 0, 1204 0, 1205 0, 1206 0, 1207 0, 1208 /*114*/ 0, 1209 0, 1210 0, 1211 0, 1212 0, 1213 /*119*/ 0, 1214 0, 1215 0, 1216 0, 1217 0, 1218 /*124*/ 0, 1219 MatGetColumnNorms_MPIDense, 1220 0, 1221 0, 1222 0, 1223 /*129*/ 0, 1224 0, 1225 0, 1226 0, 1227 0, 1228 /*134*/ 0, 1229 0, 1230 0, 1231 0, 1232 0, 1233 /*139*/ 0, 1234 0, 1235 0 1236 }; 1237 1238 #undef __FUNCT__ 1239 #define __FUNCT__ "MatMPIDenseSetPreallocation_MPIDense" 1240 PetscErrorCode MatMPIDenseSetPreallocation_MPIDense(Mat mat,PetscScalar *data) 1241 { 1242 Mat_MPIDense *a; 1243 PetscErrorCode ierr; 1244 1245 PetscFunctionBegin; 1246 mat->preallocated = PETSC_TRUE; 1247 /* Note: For now, when data is specified above, this assumes the user correctly 1248 allocates the local dense storage space. We should add error checking. */ 1249 1250 a = (Mat_MPIDense*)mat->data; 1251 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 1252 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 1253 a->nvec = mat->cmap->n; 1254 1255 ierr = MatCreate(PETSC_COMM_SELF,&a->A);CHKERRQ(ierr); 1256 ierr = MatSetSizes(a->A,mat->rmap->n,mat->cmap->N,mat->rmap->n,mat->cmap->N);CHKERRQ(ierr); 1257 ierr = MatSetType(a->A,MATSEQDENSE);CHKERRQ(ierr); 1258 ierr = MatSeqDenseSetPreallocation(a->A,data);CHKERRQ(ierr); 1259 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1260 PetscFunctionReturn(0); 1261 } 1262 1263 #undef __FUNCT__ 1264 #define __FUNCT__ "MatConvert_MPIDense_Elemental" 1265 PETSC_EXTERN PetscErrorCode MatConvert_MPIDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 1266 { 1267 PetscFunctionBegin; 1268 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for requested operation"); 1269 PetscFunctionReturn(0); 1270 } 1271 1272 #undef __FUNCT__ 1273 #define __FUNCT__ "MatCreate_MPIDense" 1274 PETSC_EXTERN PetscErrorCode MatCreate_MPIDense(Mat mat) 1275 { 1276 Mat_MPIDense *a; 1277 PetscErrorCode ierr; 1278 1279 PetscFunctionBegin; 1280 ierr = PetscNewLog(mat,&a);CHKERRQ(ierr); 1281 mat->data = (void*)a; 1282 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1283 1284 mat->insertmode = NOT_SET_VALUES; 1285 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&a->rank);CHKERRQ(ierr); 1286 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&a->size);CHKERRQ(ierr); 1287 1288 /* build cache for off array entries formed */ 1289 a->donotstash = PETSC_FALSE; 1290 1291 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)mat),1,&mat->stash);CHKERRQ(ierr); 1292 1293 /* stuff used for matrix vector multiply */ 1294 a->lvec = 0; 1295 a->Mvctx = 0; 1296 a->roworiented = PETSC_TRUE; 1297 1298 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",MatDenseGetArray_MPIDense);CHKERRQ(ierr); 1299 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",MatDenseRestoreArray_MPIDense);CHKERRQ(ierr); 1300 #if defined(PETSC_HAVE_ELEMENTAL) 1301 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",MatConvert_MPIDense_Elemental);CHKERRQ(ierr); 1302 #endif 1303 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIDense);CHKERRQ(ierr); 1304 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",MatMPIDenseSetPreallocation_MPIDense);CHKERRQ(ierr); 1305 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",MatMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1306 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",MatMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1307 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",MatMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1308 1309 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",MatTransposeMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1310 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",MatTransposeMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1311 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",MatTransposeMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1312 ierr = PetscObjectChangeTypeName((PetscObject)mat,MATMPIDENSE);CHKERRQ(ierr); 1313 PetscFunctionReturn(0); 1314 } 1315 1316 /*MC 1317 MATDENSE - MATDENSE = "dense" - A matrix type to be used for dense matrices. 1318 1319 This matrix type is identical to MATSEQDENSE when constructed with a single process communicator, 1320 and MATMPIDENSE otherwise. 1321 1322 Options Database Keys: 1323 . -mat_type dense - sets the matrix type to "dense" during a call to MatSetFromOptions() 1324 1325 Level: beginner 1326 1327 1328 .seealso: MatCreateMPIDense,MATSEQDENSE,MATMPIDENSE 1329 M*/ 1330 1331 #undef __FUNCT__ 1332 #define __FUNCT__ "MatMPIDenseSetPreallocation" 1333 /*@C 1334 MatMPIDenseSetPreallocation - Sets the array used to store the matrix entries 1335 1336 Not collective 1337 1338 Input Parameters: 1339 . B - the matrix 1340 - data - optional location of matrix data. Set data=NULL for PETSc 1341 to control all matrix memory allocation. 1342 1343 Notes: 1344 The dense format is fully compatible with standard Fortran 77 1345 storage by columns. 1346 1347 The data input variable is intended primarily for Fortran programmers 1348 who wish to allocate their own matrix memory space. Most users should 1349 set data=NULL. 1350 1351 Level: intermediate 1352 1353 .keywords: matrix,dense, parallel 1354 1355 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1356 @*/ 1357 PetscErrorCode MatMPIDenseSetPreallocation(Mat B,PetscScalar *data) 1358 { 1359 PetscErrorCode ierr; 1360 1361 PetscFunctionBegin; 1362 ierr = PetscTryMethod(B,"MatMPIDenseSetPreallocation_C",(Mat,PetscScalar*),(B,data));CHKERRQ(ierr); 1363 PetscFunctionReturn(0); 1364 } 1365 1366 #undef __FUNCT__ 1367 #define __FUNCT__ "MatCreateDense" 1368 /*@C 1369 MatCreateDense - Creates a parallel matrix in dense format. 1370 1371 Collective on MPI_Comm 1372 1373 Input Parameters: 1374 + comm - MPI communicator 1375 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1376 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1377 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1378 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 1379 - data - optional location of matrix data. Set data=NULL (NULL_SCALAR for Fortran users) for PETSc 1380 to control all matrix memory allocation. 1381 1382 Output Parameter: 1383 . A - the matrix 1384 1385 Notes: 1386 The dense format is fully compatible with standard Fortran 77 1387 storage by columns. 1388 1389 The data input variable is intended primarily for Fortran programmers 1390 who wish to allocate their own matrix memory space. Most users should 1391 set data=NULL (NULL_SCALAR for Fortran users). 1392 1393 The user MUST specify either the local or global matrix dimensions 1394 (possibly both). 1395 1396 Level: intermediate 1397 1398 .keywords: matrix,dense, parallel 1399 1400 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1401 @*/ 1402 PetscErrorCode MatCreateDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscScalar *data,Mat *A) 1403 { 1404 PetscErrorCode ierr; 1405 PetscMPIInt size; 1406 1407 PetscFunctionBegin; 1408 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1409 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1410 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1411 if (size > 1) { 1412 ierr = MatSetType(*A,MATMPIDENSE);CHKERRQ(ierr); 1413 ierr = MatMPIDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1414 } else { 1415 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 1416 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1417 } 1418 PetscFunctionReturn(0); 1419 } 1420 1421 #undef __FUNCT__ 1422 #define __FUNCT__ "MatDuplicate_MPIDense" 1423 static PetscErrorCode MatDuplicate_MPIDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 1424 { 1425 Mat mat; 1426 Mat_MPIDense *a,*oldmat = (Mat_MPIDense*)A->data; 1427 PetscErrorCode ierr; 1428 1429 PetscFunctionBegin; 1430 *newmat = 0; 1431 ierr = MatCreate(PetscObjectComm((PetscObject)A),&mat);CHKERRQ(ierr); 1432 ierr = MatSetSizes(mat,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1433 ierr = MatSetType(mat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1434 a = (Mat_MPIDense*)mat->data; 1435 ierr = PetscMemcpy(mat->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1436 1437 mat->factortype = A->factortype; 1438 mat->assembled = PETSC_TRUE; 1439 mat->preallocated = PETSC_TRUE; 1440 1441 a->size = oldmat->size; 1442 a->rank = oldmat->rank; 1443 mat->insertmode = NOT_SET_VALUES; 1444 a->nvec = oldmat->nvec; 1445 a->donotstash = oldmat->donotstash; 1446 1447 ierr = PetscLayoutReference(A->rmap,&mat->rmap);CHKERRQ(ierr); 1448 ierr = PetscLayoutReference(A->cmap,&mat->cmap);CHKERRQ(ierr); 1449 1450 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 1451 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1452 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1453 1454 *newmat = mat; 1455 PetscFunctionReturn(0); 1456 } 1457 1458 #undef __FUNCT__ 1459 #define __FUNCT__ "MatLoad_MPIDense_DenseInFile" 1460 PetscErrorCode MatLoad_MPIDense_DenseInFile(MPI_Comm comm,PetscInt fd,PetscInt M,PetscInt N,Mat newmat,PetscInt sizesset) 1461 { 1462 PetscErrorCode ierr; 1463 PetscMPIInt rank,size; 1464 PetscInt *rowners,i,m,nz,j; 1465 PetscScalar *array,*vals,*vals_ptr; 1466 1467 PetscFunctionBegin; 1468 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1469 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1470 1471 /* determine ownership of all rows */ 1472 if (newmat->rmap->n < 0) m = M/size + ((M % size) > rank); 1473 else m = newmat->rmap->n; 1474 ierr = PetscMalloc1((size+2),&rowners);CHKERRQ(ierr); 1475 ierr = MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr); 1476 rowners[0] = 0; 1477 for (i=2; i<=size; i++) { 1478 rowners[i] += rowners[i-1]; 1479 } 1480 1481 if (!sizesset) { 1482 ierr = MatSetSizes(newmat,m,PETSC_DECIDE,M,N);CHKERRQ(ierr); 1483 } 1484 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1485 ierr = MatDenseGetArray(newmat,&array);CHKERRQ(ierr); 1486 1487 if (!rank) { 1488 ierr = PetscMalloc1(m*N,&vals);CHKERRQ(ierr); 1489 1490 /* read in my part of the matrix numerical values */ 1491 ierr = PetscBinaryRead(fd,vals,m*N,PETSC_SCALAR);CHKERRQ(ierr); 1492 1493 /* insert into matrix-by row (this is why cannot directly read into array */ 1494 vals_ptr = vals; 1495 for (i=0; i<m; i++) { 1496 for (j=0; j<N; j++) { 1497 array[i + j*m] = *vals_ptr++; 1498 } 1499 } 1500 1501 /* read in other processors and ship out */ 1502 for (i=1; i<size; i++) { 1503 nz = (rowners[i+1] - rowners[i])*N; 1504 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1505 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1506 } 1507 } else { 1508 /* receive numeric values */ 1509 ierr = PetscMalloc1(m*N,&vals);CHKERRQ(ierr); 1510 1511 /* receive message of values*/ 1512 ierr = MPIULong_Recv(vals,m*N,MPIU_SCALAR,0,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1513 1514 /* insert into matrix-by row (this is why cannot directly read into array */ 1515 vals_ptr = vals; 1516 for (i=0; i<m; i++) { 1517 for (j=0; j<N; j++) { 1518 array[i + j*m] = *vals_ptr++; 1519 } 1520 } 1521 } 1522 ierr = MatDenseRestoreArray(newmat,&array);CHKERRQ(ierr); 1523 ierr = PetscFree(rowners);CHKERRQ(ierr); 1524 ierr = PetscFree(vals);CHKERRQ(ierr); 1525 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1526 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1527 PetscFunctionReturn(0); 1528 } 1529 1530 #undef __FUNCT__ 1531 #define __FUNCT__ "MatLoad_MPIDense" 1532 PetscErrorCode MatLoad_MPIDense(Mat newmat,PetscViewer viewer) 1533 { 1534 PetscScalar *vals,*svals; 1535 MPI_Comm comm; 1536 MPI_Status status; 1537 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*rowners,*sndcounts,m,maxnz; 1538 PetscInt header[4],*rowlengths = 0,M,N,*cols; 1539 PetscInt *ourlens,*procsnz = 0,*offlens,jj,*mycols,*smycols; 1540 PetscInt i,nz,j,rstart,rend,sizesset=1,grows,gcols; 1541 int fd; 1542 PetscErrorCode ierr; 1543 1544 PetscFunctionBegin; 1545 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1546 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1547 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1548 if (!rank) { 1549 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1550 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 1551 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1552 } 1553 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0; 1554 1555 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 1556 M = header[1]; N = header[2]; nz = header[3]; 1557 1558 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 1559 if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M; 1560 if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N; 1561 1562 /* If global sizes are set, check if they are consistent with that given in the file */ 1563 if (sizesset) { 1564 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 1565 } 1566 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); 1567 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); 1568 1569 /* 1570 Handle case where matrix is stored on disk as a dense matrix 1571 */ 1572 if (nz == MATRIX_BINARY_FORMAT_DENSE) { 1573 ierr = MatLoad_MPIDense_DenseInFile(comm,fd,M,N,newmat,sizesset);CHKERRQ(ierr); 1574 PetscFunctionReturn(0); 1575 } 1576 1577 /* determine ownership of all rows */ 1578 if (newmat->rmap->n < 0) { 1579 ierr = PetscMPIIntCast(M/size + ((M % size) > rank),&m);CHKERRQ(ierr); 1580 } else { 1581 ierr = PetscMPIIntCast(newmat->rmap->n,&m);CHKERRQ(ierr); 1582 } 1583 ierr = PetscMalloc1((size+2),&rowners);CHKERRQ(ierr); 1584 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1585 rowners[0] = 0; 1586 for (i=2; i<=size; i++) { 1587 rowners[i] += rowners[i-1]; 1588 } 1589 rstart = rowners[rank]; 1590 rend = rowners[rank+1]; 1591 1592 /* distribute row lengths to all processors */ 1593 ierr = PetscMalloc2(rend-rstart,&ourlens,rend-rstart,&offlens);CHKERRQ(ierr); 1594 if (!rank) { 1595 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 1596 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1597 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 1598 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1599 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1600 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1601 } else { 1602 ierr = MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1603 } 1604 1605 if (!rank) { 1606 /* calculate the number of nonzeros on each processor */ 1607 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 1608 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 1609 for (i=0; i<size; i++) { 1610 for (j=rowners[i]; j< rowners[i+1]; j++) { 1611 procsnz[i] += rowlengths[j]; 1612 } 1613 } 1614 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1615 1616 /* determine max buffer needed and allocate it */ 1617 maxnz = 0; 1618 for (i=0; i<size; i++) { 1619 maxnz = PetscMax(maxnz,procsnz[i]); 1620 } 1621 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 1622 1623 /* read in my part of the matrix column indices */ 1624 nz = procsnz[0]; 1625 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 1626 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1627 1628 /* read in every one elses and ship off */ 1629 for (i=1; i<size; i++) { 1630 nz = procsnz[i]; 1631 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1632 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 1633 } 1634 ierr = PetscFree(cols);CHKERRQ(ierr); 1635 } else { 1636 /* determine buffer space needed for message */ 1637 nz = 0; 1638 for (i=0; i<m; i++) { 1639 nz += ourlens[i]; 1640 } 1641 ierr = PetscMalloc1((nz+1),&mycols);CHKERRQ(ierr); 1642 1643 /* receive message of column indices*/ 1644 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 1645 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 1646 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1647 } 1648 1649 /* loop over local rows, determining number of off diagonal entries */ 1650 ierr = PetscMemzero(offlens,m*sizeof(PetscInt));CHKERRQ(ierr); 1651 jj = 0; 1652 for (i=0; i<m; i++) { 1653 for (j=0; j<ourlens[i]; j++) { 1654 if (mycols[jj] < rstart || mycols[jj] >= rend) offlens[i]++; 1655 jj++; 1656 } 1657 } 1658 1659 /* create our matrix */ 1660 for (i=0; i<m; i++) ourlens[i] -= offlens[i]; 1661 1662 if (!sizesset) { 1663 ierr = MatSetSizes(newmat,m,PETSC_DECIDE,M,N);CHKERRQ(ierr); 1664 } 1665 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1666 for (i=0; i<m; i++) ourlens[i] += offlens[i]; 1667 1668 if (!rank) { 1669 ierr = PetscMalloc1(maxnz,&vals);CHKERRQ(ierr); 1670 1671 /* read in my part of the matrix numerical values */ 1672 nz = procsnz[0]; 1673 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1674 1675 /* insert into matrix */ 1676 jj = rstart; 1677 smycols = mycols; 1678 svals = vals; 1679 for (i=0; i<m; i++) { 1680 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1681 smycols += ourlens[i]; 1682 svals += ourlens[i]; 1683 jj++; 1684 } 1685 1686 /* read in other processors and ship out */ 1687 for (i=1; i<size; i++) { 1688 nz = procsnz[i]; 1689 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1690 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 1691 } 1692 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1693 } else { 1694 /* receive numeric values */ 1695 ierr = PetscMalloc1((nz+1),&vals);CHKERRQ(ierr); 1696 1697 /* receive message of values*/ 1698 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 1699 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1700 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1701 1702 /* insert into matrix */ 1703 jj = rstart; 1704 smycols = mycols; 1705 svals = vals; 1706 for (i=0; i<m; i++) { 1707 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1708 smycols += ourlens[i]; 1709 svals += ourlens[i]; 1710 jj++; 1711 } 1712 } 1713 ierr = PetscFree2(ourlens,offlens);CHKERRQ(ierr); 1714 ierr = PetscFree(vals);CHKERRQ(ierr); 1715 ierr = PetscFree(mycols);CHKERRQ(ierr); 1716 ierr = PetscFree(rowners);CHKERRQ(ierr); 1717 1718 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1719 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1720 PetscFunctionReturn(0); 1721 } 1722 1723 #undef __FUNCT__ 1724 #define __FUNCT__ "MatEqual_MPIDense" 1725 PetscErrorCode MatEqual_MPIDense(Mat A,Mat B,PetscBool *flag) 1726 { 1727 Mat_MPIDense *matB = (Mat_MPIDense*)B->data,*matA = (Mat_MPIDense*)A->data; 1728 Mat a,b; 1729 PetscBool flg; 1730 PetscErrorCode ierr; 1731 1732 PetscFunctionBegin; 1733 a = matA->A; 1734 b = matB->A; 1735 ierr = MatEqual(a,b,&flg);CHKERRQ(ierr); 1736 ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1737 PetscFunctionReturn(0); 1738 } 1739 1740