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 #include <petscblaslapack.h> 10 11 /*@ 12 13 MatDenseGetLocalMatrix - For a MATMPIDENSE or MATSEQDENSE matrix returns the sequential 14 matrix that represents the operator. For sequential matrices it returns itself. 15 16 Input Parameter: 17 . A - the Seq or MPI dense matrix 18 19 Output Parameter: 20 . B - the inner matrix 21 22 Level: intermediate 23 24 @*/ 25 PetscErrorCode MatDenseGetLocalMatrix(Mat A,Mat *B) 26 { 27 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 28 PetscErrorCode ierr; 29 PetscBool flg; 30 31 PetscFunctionBegin; 32 ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIDENSE,&flg);CHKERRQ(ierr); 33 if (flg) *B = mat->A; 34 else *B = A; 35 PetscFunctionReturn(0); 36 } 37 38 PetscErrorCode MatGetRow_MPIDense(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 39 { 40 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 41 PetscErrorCode ierr; 42 PetscInt lrow,rstart = A->rmap->rstart,rend = A->rmap->rend; 43 44 PetscFunctionBegin; 45 if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"only local rows"); 46 lrow = row - rstart; 47 ierr = MatGetRow(mat->A,lrow,nz,(const PetscInt**)idx,(const PetscScalar**)v);CHKERRQ(ierr); 48 PetscFunctionReturn(0); 49 } 50 51 PetscErrorCode MatRestoreRow_MPIDense(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 52 { 53 PetscErrorCode ierr; 54 55 PetscFunctionBegin; 56 if (idx) {ierr = PetscFree(*idx);CHKERRQ(ierr);} 57 if (v) {ierr = PetscFree(*v);CHKERRQ(ierr);} 58 PetscFunctionReturn(0); 59 } 60 61 PetscErrorCode MatGetDiagonalBlock_MPIDense(Mat A,Mat *a) 62 { 63 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 64 PetscErrorCode ierr; 65 PetscInt m = A->rmap->n,rstart = A->rmap->rstart; 66 PetscScalar *array; 67 MPI_Comm comm; 68 Mat B; 69 70 PetscFunctionBegin; 71 if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only square matrices supported."); 72 73 ierr = PetscObjectQuery((PetscObject)A,"DiagonalBlock",(PetscObject*)&B);CHKERRQ(ierr); 74 if (!B) { 75 ierr = PetscObjectGetComm((PetscObject)(mdn->A),&comm);CHKERRQ(ierr); 76 ierr = MatCreate(comm,&B);CHKERRQ(ierr); 77 ierr = MatSetSizes(B,m,m,m,m);CHKERRQ(ierr); 78 ierr = MatSetType(B,((PetscObject)mdn->A)->type_name);CHKERRQ(ierr); 79 ierr = MatDenseGetArray(mdn->A,&array);CHKERRQ(ierr); 80 ierr = MatSeqDenseSetPreallocation(B,array+m*rstart);CHKERRQ(ierr); 81 ierr = MatDenseRestoreArray(mdn->A,&array);CHKERRQ(ierr); 82 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 83 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 84 ierr = PetscObjectCompose((PetscObject)A,"DiagonalBlock",(PetscObject)B);CHKERRQ(ierr); 85 *a = B; 86 ierr = MatDestroy(&B);CHKERRQ(ierr); 87 } else *a = B; 88 PetscFunctionReturn(0); 89 } 90 91 PetscErrorCode MatSetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],const PetscScalar v[],InsertMode addv) 92 { 93 Mat_MPIDense *A = (Mat_MPIDense*)mat->data; 94 PetscErrorCode ierr; 95 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row; 96 PetscBool roworiented = A->roworiented; 97 98 PetscFunctionBegin; 99 for (i=0; i<m; i++) { 100 if (idxm[i] < 0) continue; 101 if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 102 if (idxm[i] >= rstart && idxm[i] < rend) { 103 row = idxm[i] - rstart; 104 if (roworiented) { 105 ierr = MatSetValues(A->A,1,&row,n,idxn,v+i*n,addv);CHKERRQ(ierr); 106 } else { 107 for (j=0; j<n; j++) { 108 if (idxn[j] < 0) continue; 109 if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 110 ierr = MatSetValues(A->A,1,&row,1,&idxn[j],v+i+j*m,addv);CHKERRQ(ierr); 111 } 112 } 113 } else if (!A->donotstash) { 114 mat->assembled = PETSC_FALSE; 115 if (roworiented) { 116 ierr = MatStashValuesRow_Private(&mat->stash,idxm[i],n,idxn,v+i*n,PETSC_FALSE);CHKERRQ(ierr); 117 } else { 118 ierr = MatStashValuesCol_Private(&mat->stash,idxm[i],n,idxn,v+i,m,PETSC_FALSE);CHKERRQ(ierr); 119 } 120 } 121 } 122 PetscFunctionReturn(0); 123 } 124 125 PetscErrorCode MatGetValues_MPIDense(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[]) 126 { 127 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 128 PetscErrorCode ierr; 129 PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend,row; 130 131 PetscFunctionBegin; 132 for (i=0; i<m; i++) { 133 if (idxm[i] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */ 134 if (idxm[i] >= mat->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 135 if (idxm[i] >= rstart && idxm[i] < rend) { 136 row = idxm[i] - rstart; 137 for (j=0; j<n; j++) { 138 if (idxn[j] < 0) continue; /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */ 139 if (idxn[j] >= mat->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 140 ierr = MatGetValues(mdn->A,1,&row,1,&idxn[j],v+i*n+j);CHKERRQ(ierr); 141 } 142 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported"); 143 } 144 PetscFunctionReturn(0); 145 } 146 147 static PetscErrorCode MatDenseGetArray_MPIDense(Mat A,PetscScalar *array[]) 148 { 149 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 150 PetscErrorCode ierr; 151 152 PetscFunctionBegin; 153 ierr = MatDenseGetArray(a->A,array);CHKERRQ(ierr); 154 PetscFunctionReturn(0); 155 } 156 157 static PetscErrorCode MatDenseGetArrayRead_MPIDense(Mat A,const PetscScalar *array[]) 158 { 159 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 160 PetscErrorCode ierr; 161 162 PetscFunctionBegin; 163 ierr = MatDenseGetArrayRead(a->A,array);CHKERRQ(ierr); 164 PetscFunctionReturn(0); 165 } 166 167 static PetscErrorCode MatDensePlaceArray_MPIDense(Mat A,const PetscScalar array[]) 168 { 169 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 170 PetscErrorCode ierr; 171 172 PetscFunctionBegin; 173 ierr = MatDensePlaceArray(a->A,array);CHKERRQ(ierr); 174 PetscFunctionReturn(0); 175 } 176 177 static PetscErrorCode MatDenseResetArray_MPIDense(Mat A) 178 { 179 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 180 PetscErrorCode ierr; 181 182 PetscFunctionBegin; 183 ierr = MatDenseResetArray(a->A);CHKERRQ(ierr); 184 PetscFunctionReturn(0); 185 } 186 187 static PetscErrorCode MatCreateSubMatrix_MPIDense(Mat A,IS isrow,IS iscol,MatReuse scall,Mat *B) 188 { 189 Mat_MPIDense *mat = (Mat_MPIDense*)A->data,*newmatd; 190 Mat_SeqDense *lmat = (Mat_SeqDense*)mat->A->data; 191 PetscErrorCode ierr; 192 PetscInt i,j,rstart,rend,nrows,ncols,Ncols,nlrows,nlcols; 193 const PetscInt *irow,*icol; 194 PetscScalar *av,*bv,*v = lmat->v; 195 Mat newmat; 196 IS iscol_local; 197 MPI_Comm comm_is,comm_mat; 198 199 PetscFunctionBegin; 200 ierr = PetscObjectGetComm((PetscObject)A,&comm_mat);CHKERRQ(ierr); 201 ierr = PetscObjectGetComm((PetscObject)iscol,&comm_is);CHKERRQ(ierr); 202 if (comm_mat != comm_is) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMECOMM,"IS communicator must match matrix communicator"); 203 204 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 205 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 206 ierr = ISGetIndices(iscol_local,&icol);CHKERRQ(ierr); 207 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 208 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 209 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); /* global number of columns, size of iscol_local */ 210 211 /* No parallel redistribution currently supported! Should really check each index set 212 to comfirm that it is OK. ... Currently supports only submatrix same partitioning as 213 original matrix! */ 214 215 ierr = MatGetLocalSize(A,&nlrows,&nlcols);CHKERRQ(ierr); 216 ierr = MatGetOwnershipRange(A,&rstart,&rend);CHKERRQ(ierr); 217 218 /* Check submatrix call */ 219 if (scall == MAT_REUSE_MATRIX) { 220 /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); */ 221 /* Really need to test rows and column sizes! */ 222 newmat = *B; 223 } else { 224 /* Create and fill new matrix */ 225 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 226 ierr = MatSetSizes(newmat,nrows,ncols,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 227 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 228 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 229 } 230 231 /* Now extract the data pointers and do the copy, column at a time */ 232 newmatd = (Mat_MPIDense*)newmat->data; 233 bv = ((Mat_SeqDense*)newmatd->A->data)->v; 234 235 for (i=0; i<Ncols; i++) { 236 av = v + ((Mat_SeqDense*)mat->A->data)->lda*icol[i]; 237 for (j=0; j<nrows; j++) { 238 *bv++ = av[irow[j] - rstart]; 239 } 240 } 241 242 /* Assemble the matrices so that the correct flags are set */ 243 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 244 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 245 246 /* Free work space */ 247 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 248 ierr = ISRestoreIndices(iscol_local,&icol);CHKERRQ(ierr); 249 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 250 *B = newmat; 251 PetscFunctionReturn(0); 252 } 253 254 PetscErrorCode MatDenseRestoreArray_MPIDense(Mat A,PetscScalar *array[]) 255 { 256 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 257 PetscErrorCode ierr; 258 259 PetscFunctionBegin; 260 ierr = MatDenseRestoreArray(a->A,array);CHKERRQ(ierr); 261 PetscFunctionReturn(0); 262 } 263 264 PetscErrorCode MatDenseRestoreArrayRead_MPIDense(Mat A,const PetscScalar *array[]) 265 { 266 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 267 PetscErrorCode ierr; 268 269 PetscFunctionBegin; 270 ierr = MatDenseRestoreArrayRead(a->A,array);CHKERRQ(ierr); 271 PetscFunctionReturn(0); 272 } 273 274 PetscErrorCode MatAssemblyBegin_MPIDense(Mat mat,MatAssemblyType mode) 275 { 276 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 277 MPI_Comm comm; 278 PetscErrorCode ierr; 279 PetscInt nstash,reallocs; 280 InsertMode addv; 281 282 PetscFunctionBegin; 283 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 284 /* make sure all processors are either in INSERTMODE or ADDMODE */ 285 ierr = MPIU_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,comm);CHKERRQ(ierr); 286 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs"); 287 mat->insertmode = addv; /* in case this processor had no cache */ 288 289 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 290 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 291 ierr = PetscInfo2(mdn->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 292 PetscFunctionReturn(0); 293 } 294 295 PetscErrorCode MatAssemblyEnd_MPIDense(Mat mat,MatAssemblyType mode) 296 { 297 Mat_MPIDense *mdn=(Mat_MPIDense*)mat->data; 298 PetscErrorCode ierr; 299 PetscInt i,*row,*col,flg,j,rstart,ncols; 300 PetscMPIInt n; 301 PetscScalar *val; 302 303 PetscFunctionBegin; 304 /* wait on receives */ 305 while (1) { 306 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 307 if (!flg) break; 308 309 for (i=0; i<n;) { 310 /* Now identify the consecutive vals belonging to the same row */ 311 for (j=i,rstart=row[j]; j<n; j++) { 312 if (row[j] != rstart) break; 313 } 314 if (j < n) ncols = j-i; 315 else ncols = n-i; 316 /* Now assemble all these values with a single function call */ 317 ierr = MatSetValues_MPIDense(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 318 i = j; 319 } 320 } 321 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 322 323 ierr = MatAssemblyBegin(mdn->A,mode);CHKERRQ(ierr); 324 ierr = MatAssemblyEnd(mdn->A,mode);CHKERRQ(ierr); 325 326 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 327 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 328 } 329 PetscFunctionReturn(0); 330 } 331 332 PetscErrorCode MatZeroEntries_MPIDense(Mat A) 333 { 334 PetscErrorCode ierr; 335 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 336 337 PetscFunctionBegin; 338 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 339 PetscFunctionReturn(0); 340 } 341 342 /* the code does not do the diagonal entries correctly unless the 343 matrix is square and the column and row owerships are identical. 344 This is a BUG. The only way to fix it seems to be to access 345 mdn->A and mdn->B directly and not through the MatZeroRows() 346 routine. 347 */ 348 PetscErrorCode MatZeroRows_MPIDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 349 { 350 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 351 PetscErrorCode ierr; 352 PetscInt i,*owners = A->rmap->range; 353 PetscInt *sizes,j,idx,nsends; 354 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 355 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source; 356 PetscInt *lens,*lrows,*values; 357 PetscMPIInt n,imdex,rank = l->rank,size = l->size; 358 MPI_Comm comm; 359 MPI_Request *send_waits,*recv_waits; 360 MPI_Status recv_status,*send_status; 361 PetscBool found; 362 const PetscScalar *xx; 363 PetscScalar *bb; 364 365 PetscFunctionBegin; 366 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 367 if (A->rmap->N != A->cmap->N) SETERRQ(comm,PETSC_ERR_SUP,"Only handles square matrices"); 368 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only handles matrices with identical column and row ownership"); 369 /* first count number of contributors to each processor */ 370 ierr = PetscCalloc1(2*size,&sizes);CHKERRQ(ierr); 371 ierr = PetscMalloc1(N+1,&owner);CHKERRQ(ierr); /* see note*/ 372 for (i=0; i<N; i++) { 373 idx = rows[i]; 374 found = PETSC_FALSE; 375 for (j=0; j<size; j++) { 376 if (idx >= owners[j] && idx < owners[j+1]) { 377 sizes[2*j]++; sizes[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break; 378 } 379 } 380 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 381 } 382 nsends = 0; 383 for (i=0; i<size; i++) nsends += sizes[2*i+1]; 384 385 /* inform other processors of number of messages and max length*/ 386 ierr = PetscMaxSum(comm,sizes,&nmax,&nrecvs);CHKERRQ(ierr); 387 388 /* post receives: */ 389 ierr = PetscMalloc1((nrecvs+1)*(nmax+1),&rvalues);CHKERRQ(ierr); 390 ierr = PetscMalloc1(nrecvs+1,&recv_waits);CHKERRQ(ierr); 391 for (i=0; i<nrecvs; i++) { 392 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 393 } 394 395 /* do sends: 396 1) starts[i] gives the starting index in svalues for stuff going to 397 the ith processor 398 */ 399 ierr = PetscMalloc1(N+1,&svalues);CHKERRQ(ierr); 400 ierr = PetscMalloc1(nsends+1,&send_waits);CHKERRQ(ierr); 401 ierr = PetscMalloc1(size+1,&starts);CHKERRQ(ierr); 402 403 starts[0] = 0; 404 for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 405 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 406 407 starts[0] = 0; 408 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 409 count = 0; 410 for (i=0; i<size; i++) { 411 if (sizes[2*i+1]) { 412 ierr = MPI_Isend(svalues+starts[i],sizes[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 413 } 414 } 415 ierr = PetscFree(starts);CHKERRQ(ierr); 416 417 base = owners[rank]; 418 419 /* wait on receives */ 420 ierr = PetscMalloc2(nrecvs,&lens,nrecvs,&source);CHKERRQ(ierr); 421 count = nrecvs; 422 slen = 0; 423 while (count) { 424 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 425 /* unpack receives into our local space */ 426 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 427 428 source[imdex] = recv_status.MPI_SOURCE; 429 lens[imdex] = n; 430 slen += n; 431 count--; 432 } 433 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 434 435 /* move the data into the send scatter */ 436 ierr = PetscMalloc1(slen+1,&lrows);CHKERRQ(ierr); 437 count = 0; 438 for (i=0; i<nrecvs; i++) { 439 values = rvalues + i*nmax; 440 for (j=0; j<lens[i]; j++) { 441 lrows[count++] = values[j] - base; 442 } 443 } 444 ierr = PetscFree(rvalues);CHKERRQ(ierr); 445 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 446 ierr = PetscFree(owner);CHKERRQ(ierr); 447 ierr = PetscFree(sizes);CHKERRQ(ierr); 448 449 /* fix right hand side if needed */ 450 if (x && b) { 451 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 452 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 453 for (i=0; i<slen; i++) { 454 bb[lrows[i]] = diag*xx[lrows[i]]; 455 } 456 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 457 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 458 } 459 460 /* actually zap the local rows */ 461 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 462 if (diag != 0.0) { 463 Mat_SeqDense *ll = (Mat_SeqDense*)l->A->data; 464 PetscInt m = ll->lda, i; 465 466 for (i=0; i<slen; i++) { 467 ll->v[lrows[i] + m*(A->cmap->rstart + lrows[i])] = diag; 468 } 469 } 470 ierr = PetscFree(lrows);CHKERRQ(ierr); 471 472 /* wait on sends */ 473 if (nsends) { 474 ierr = PetscMalloc1(nsends,&send_status);CHKERRQ(ierr); 475 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 476 ierr = PetscFree(send_status);CHKERRQ(ierr); 477 } 478 ierr = PetscFree(send_waits);CHKERRQ(ierr); 479 ierr = PetscFree(svalues);CHKERRQ(ierr); 480 PetscFunctionReturn(0); 481 } 482 483 PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat,Vec,Vec); 484 PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat,Vec,Vec,Vec); 485 PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat,Vec,Vec); 486 PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqDense(Mat,Vec,Vec,Vec); 487 488 PetscErrorCode MatMult_MPIDense(Mat mat,Vec xx,Vec yy) 489 { 490 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 491 PetscErrorCode ierr; 492 493 PetscFunctionBegin; 494 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 495 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 496 ierr = MatMult_SeqDense(mdn->A,mdn->lvec,yy);CHKERRQ(ierr); 497 PetscFunctionReturn(0); 498 } 499 500 PetscErrorCode MatMultAdd_MPIDense(Mat mat,Vec xx,Vec yy,Vec zz) 501 { 502 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 503 PetscErrorCode ierr; 504 505 PetscFunctionBegin; 506 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 507 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 508 ierr = MatMultAdd_SeqDense(mdn->A,mdn->lvec,yy,zz);CHKERRQ(ierr); 509 PetscFunctionReturn(0); 510 } 511 512 PetscErrorCode MatMultTranspose_MPIDense(Mat A,Vec xx,Vec yy) 513 { 514 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 515 PetscErrorCode ierr; 516 PetscScalar zero = 0.0; 517 518 PetscFunctionBegin; 519 ierr = VecSet(yy,zero);CHKERRQ(ierr); 520 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 521 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 522 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 523 PetscFunctionReturn(0); 524 } 525 526 PetscErrorCode MatMultTransposeAdd_MPIDense(Mat A,Vec xx,Vec yy,Vec zz) 527 { 528 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 529 PetscErrorCode ierr; 530 531 PetscFunctionBegin; 532 ierr = VecCopy(yy,zz);CHKERRQ(ierr); 533 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 534 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 535 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 536 PetscFunctionReturn(0); 537 } 538 539 PetscErrorCode MatGetDiagonal_MPIDense(Mat A,Vec v) 540 { 541 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 542 Mat_SeqDense *aloc = (Mat_SeqDense*)a->A->data; 543 PetscErrorCode ierr; 544 PetscInt len,i,n,m = A->rmap->n,radd; 545 PetscScalar *x,zero = 0.0; 546 547 PetscFunctionBegin; 548 ierr = VecSet(v,zero);CHKERRQ(ierr); 549 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 550 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 551 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 552 len = PetscMin(a->A->rmap->n,a->A->cmap->n); 553 radd = A->rmap->rstart*m; 554 for (i=0; i<len; i++) { 555 x[i] = aloc->v[radd + i*m + i]; 556 } 557 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 558 PetscFunctionReturn(0); 559 } 560 561 PetscErrorCode MatDestroy_MPIDense(Mat mat) 562 { 563 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 564 PetscErrorCode ierr; 565 566 PetscFunctionBegin; 567 #if defined(PETSC_USE_LOG) 568 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 569 #endif 570 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 571 ierr = MatDestroy(&mdn->A);CHKERRQ(ierr); 572 ierr = VecDestroy(&mdn->lvec);CHKERRQ(ierr); 573 ierr = VecScatterDestroy(&mdn->Mvctx);CHKERRQ(ierr); 574 575 ierr = PetscFree(mat->data);CHKERRQ(ierr); 576 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 577 578 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 579 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 580 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArrayRead_C",NULL);CHKERRQ(ierr); 581 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArrayRead_C",NULL);CHKERRQ(ierr); 582 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);CHKERRQ(ierr); 583 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);CHKERRQ(ierr); 584 #if defined(PETSC_HAVE_ELEMENTAL) 585 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",NULL);CHKERRQ(ierr); 586 #endif 587 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 588 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 589 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 590 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 591 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 592 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 593 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 594 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",NULL);CHKERRQ(ierr); 595 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",NULL);CHKERRQ(ierr); 596 PetscFunctionReturn(0); 597 } 598 599 static PetscErrorCode MatView_MPIDense_Binary(Mat mat,PetscViewer viewer) 600 { 601 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 602 PetscErrorCode ierr; 603 PetscViewerFormat format; 604 int fd; 605 PetscInt header[4],mmax,N = mat->cmap->N,i,j,m,k; 606 PetscMPIInt rank,tag = ((PetscObject)viewer)->tag,size; 607 PetscScalar *work,*v,*vv; 608 Mat_SeqDense *a = (Mat_SeqDense*)mdn->A->data; 609 610 PetscFunctionBegin; 611 if (mdn->size == 1) { 612 ierr = MatView(mdn->A,viewer);CHKERRQ(ierr); 613 } else { 614 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 615 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 616 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 617 618 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 619 if (format == PETSC_VIEWER_NATIVE) { 620 621 if (!rank) { 622 /* store the matrix as a dense matrix */ 623 header[0] = MAT_FILE_CLASSID; 624 header[1] = mat->rmap->N; 625 header[2] = N; 626 header[3] = MATRIX_BINARY_FORMAT_DENSE; 627 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 628 629 /* get largest work array needed for transposing array */ 630 mmax = mat->rmap->n; 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,&work);CHKERRQ(ierr); 635 636 /* write out local array, by rows */ 637 m = mat->rmap->n; 638 v = a->v; 639 for (j=0; j<N; j++) { 640 for (i=0; i<m; i++) { 641 work[j + i*N] = *v++; 642 } 643 } 644 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 645 /* get largest work array to receive messages from other processes, excludes process zero */ 646 mmax = 0; 647 for (i=1; i<size; i++) { 648 mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]); 649 } 650 ierr = PetscMalloc1(mmax*N,&vv);CHKERRQ(ierr); 651 for (k = 1; k < size; k++) { 652 v = vv; 653 m = mat->rmap->range[k+1] - mat->rmap->range[k]; 654 ierr = MPIULong_Recv(v,m*N,MPIU_SCALAR,k,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 655 656 for (j = 0; j < N; j++) { 657 for (i = 0; i < m; i++) { 658 work[j + i*N] = *v++; 659 } 660 } 661 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 662 } 663 ierr = PetscFree(work);CHKERRQ(ierr); 664 ierr = PetscFree(vv);CHKERRQ(ierr); 665 } else { 666 ierr = MPIULong_Send(a->v,mat->rmap->n*mat->cmap->N,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 667 } 668 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"To store a parallel dense matrix you must first call PetscViewerPushFormat(viewer,PETSC_VIEWER_NATIVE)"); 669 } 670 PetscFunctionReturn(0); 671 } 672 673 extern PetscErrorCode MatView_SeqDense(Mat,PetscViewer); 674 #include <petscdraw.h> 675 static PetscErrorCode MatView_MPIDense_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 676 { 677 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 678 PetscErrorCode ierr; 679 PetscMPIInt rank = mdn->rank; 680 PetscViewerType vtype; 681 PetscBool iascii,isdraw; 682 PetscViewer sviewer; 683 PetscViewerFormat format; 684 685 PetscFunctionBegin; 686 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 687 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 688 if (iascii) { 689 ierr = PetscViewerGetType(viewer,&vtype);CHKERRQ(ierr); 690 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 691 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 692 MatInfo info; 693 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 694 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 695 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); 696 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 697 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 698 ierr = VecScatterView(mdn->Mvctx,viewer);CHKERRQ(ierr); 699 PetscFunctionReturn(0); 700 } else if (format == PETSC_VIEWER_ASCII_INFO) { 701 PetscFunctionReturn(0); 702 } 703 } else if (isdraw) { 704 PetscDraw draw; 705 PetscBool isnull; 706 707 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 708 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 709 if (isnull) PetscFunctionReturn(0); 710 } 711 712 { 713 /* assemble the entire matrix onto first processor. */ 714 Mat A; 715 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,row,i,nz; 716 PetscInt *cols; 717 PetscScalar *vals; 718 719 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 720 if (!rank) { 721 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 722 } else { 723 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 724 } 725 /* Since this is a temporary matrix, MATMPIDENSE instead of ((PetscObject)A)->type_name here is probably acceptable. */ 726 ierr = MatSetType(A,MATMPIDENSE);CHKERRQ(ierr); 727 ierr = MatMPIDenseSetPreallocation(A,NULL);CHKERRQ(ierr); 728 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 729 730 /* Copy the matrix ... This isn't the most efficient means, 731 but it's quick for now */ 732 A->insertmode = INSERT_VALUES; 733 734 row = mat->rmap->rstart; 735 m = mdn->A->rmap->n; 736 for (i=0; i<m; i++) { 737 ierr = MatGetRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 738 ierr = MatSetValues_MPIDense(A,1,&row,nz,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 739 ierr = MatRestoreRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 740 row++; 741 } 742 743 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 744 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 745 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 746 if (!rank) { 747 ierr = PetscObjectSetName((PetscObject)((Mat_MPIDense*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 748 ierr = MatView_SeqDense(((Mat_MPIDense*)(A->data))->A,sviewer);CHKERRQ(ierr); 749 } 750 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 751 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 752 ierr = MatDestroy(&A);CHKERRQ(ierr); 753 } 754 PetscFunctionReturn(0); 755 } 756 757 PetscErrorCode MatView_MPIDense(Mat mat,PetscViewer viewer) 758 { 759 PetscErrorCode ierr; 760 PetscBool iascii,isbinary,isdraw,issocket; 761 762 PetscFunctionBegin; 763 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 764 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 765 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 766 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 767 768 if (iascii || issocket || isdraw) { 769 ierr = MatView_MPIDense_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 770 } else if (isbinary) { 771 ierr = MatView_MPIDense_Binary(mat,viewer);CHKERRQ(ierr); 772 } 773 PetscFunctionReturn(0); 774 } 775 776 PetscErrorCode MatGetInfo_MPIDense(Mat A,MatInfoType flag,MatInfo *info) 777 { 778 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 779 Mat mdn = mat->A; 780 PetscErrorCode ierr; 781 PetscReal isend[5],irecv[5]; 782 783 PetscFunctionBegin; 784 info->block_size = 1.0; 785 786 ierr = MatGetInfo(mdn,MAT_LOCAL,info);CHKERRQ(ierr); 787 788 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 789 isend[3] = info->memory; isend[4] = info->mallocs; 790 if (flag == MAT_LOCAL) { 791 info->nz_used = isend[0]; 792 info->nz_allocated = isend[1]; 793 info->nz_unneeded = isend[2]; 794 info->memory = isend[3]; 795 info->mallocs = isend[4]; 796 } else if (flag == MAT_GLOBAL_MAX) { 797 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 798 799 info->nz_used = irecv[0]; 800 info->nz_allocated = irecv[1]; 801 info->nz_unneeded = irecv[2]; 802 info->memory = irecv[3]; 803 info->mallocs = irecv[4]; 804 } else if (flag == MAT_GLOBAL_SUM) { 805 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 806 807 info->nz_used = irecv[0]; 808 info->nz_allocated = irecv[1]; 809 info->nz_unneeded = irecv[2]; 810 info->memory = irecv[3]; 811 info->mallocs = irecv[4]; 812 } 813 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 814 info->fill_ratio_needed = 0; 815 info->factor_mallocs = 0; 816 PetscFunctionReturn(0); 817 } 818 819 PetscErrorCode MatSetOption_MPIDense(Mat A,MatOption op,PetscBool flg) 820 { 821 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 822 PetscErrorCode ierr; 823 824 PetscFunctionBegin; 825 switch (op) { 826 case MAT_NEW_NONZERO_LOCATIONS: 827 case MAT_NEW_NONZERO_LOCATION_ERR: 828 case MAT_NEW_NONZERO_ALLOCATION_ERR: 829 MatCheckPreallocated(A,1); 830 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 831 break; 832 case MAT_ROW_ORIENTED: 833 MatCheckPreallocated(A,1); 834 a->roworiented = flg; 835 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 836 break; 837 case MAT_NEW_DIAGONALS: 838 case MAT_KEEP_NONZERO_PATTERN: 839 case MAT_USE_HASH_TABLE: 840 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 841 break; 842 case MAT_IGNORE_OFF_PROC_ENTRIES: 843 a->donotstash = flg; 844 break; 845 case MAT_SYMMETRIC: 846 case MAT_STRUCTURALLY_SYMMETRIC: 847 case MAT_HERMITIAN: 848 case MAT_SYMMETRY_ETERNAL: 849 case MAT_IGNORE_LOWER_TRIANGULAR: 850 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 851 break; 852 default: 853 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 854 } 855 PetscFunctionReturn(0); 856 } 857 858 859 PetscErrorCode MatDiagonalScale_MPIDense(Mat A,Vec ll,Vec rr) 860 { 861 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 862 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 863 const PetscScalar *l,*r; 864 PetscScalar x,*v; 865 PetscErrorCode ierr; 866 PetscInt i,j,s2a,s3a,s2,s3,m=mdn->A->rmap->n,n=mdn->A->cmap->n; 867 868 PetscFunctionBegin; 869 ierr = MatGetLocalSize(A,&s2,&s3);CHKERRQ(ierr); 870 if (ll) { 871 ierr = VecGetLocalSize(ll,&s2a);CHKERRQ(ierr); 872 if (s2a != s2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector non-conforming local size, %d != %d.", s2a, s2); 873 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 874 for (i=0; i<m; i++) { 875 x = l[i]; 876 v = mat->v + i; 877 for (j=0; j<n; j++) { (*v) *= x; v+= m;} 878 } 879 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 880 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 881 } 882 if (rr) { 883 ierr = VecGetLocalSize(rr,&s3a);CHKERRQ(ierr); 884 if (s3a != s3) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec non-conforming local size, %d != %d.", s3a, s3); 885 ierr = VecScatterBegin(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 886 ierr = VecScatterEnd(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 887 ierr = VecGetArrayRead(mdn->lvec,&r);CHKERRQ(ierr); 888 for (i=0; i<n; i++) { 889 x = r[i]; 890 v = mat->v + i*m; 891 for (j=0; j<m; j++) (*v++) *= x; 892 } 893 ierr = VecRestoreArrayRead(mdn->lvec,&r);CHKERRQ(ierr); 894 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 895 } 896 PetscFunctionReturn(0); 897 } 898 899 PetscErrorCode MatNorm_MPIDense(Mat A,NormType type,PetscReal *nrm) 900 { 901 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 902 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 903 PetscErrorCode ierr; 904 PetscInt i,j; 905 PetscReal sum = 0.0; 906 PetscScalar *v = mat->v; 907 908 PetscFunctionBegin; 909 if (mdn->size == 1) { 910 ierr = MatNorm(mdn->A,type,nrm);CHKERRQ(ierr); 911 } else { 912 if (type == NORM_FROBENIUS) { 913 for (i=0; i<mdn->A->cmap->n*mdn->A->rmap->n; i++) { 914 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 915 } 916 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 917 *nrm = PetscSqrtReal(*nrm); 918 ierr = PetscLogFlops(2.0*mdn->A->cmap->n*mdn->A->rmap->n);CHKERRQ(ierr); 919 } else if (type == NORM_1) { 920 PetscReal *tmp,*tmp2; 921 ierr = PetscMalloc2(A->cmap->N,&tmp,A->cmap->N,&tmp2);CHKERRQ(ierr); 922 ierr = PetscMemzero(tmp,A->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 923 ierr = PetscMemzero(tmp2,A->cmap->N*sizeof(PetscReal));CHKERRQ(ierr); 924 *nrm = 0.0; 925 v = mat->v; 926 for (j=0; j<mdn->A->cmap->n; j++) { 927 for (i=0; i<mdn->A->rmap->n; i++) { 928 tmp[j] += PetscAbsScalar(*v); v++; 929 } 930 } 931 ierr = MPIU_Allreduce(tmp,tmp2,A->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 932 for (j=0; j<A->cmap->N; j++) { 933 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 934 } 935 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 936 ierr = PetscLogFlops(A->cmap->n*A->rmap->n);CHKERRQ(ierr); 937 } else if (type == NORM_INFINITY) { /* max row norm */ 938 PetscReal ntemp; 939 ierr = MatNorm(mdn->A,type,&ntemp);CHKERRQ(ierr); 940 ierr = MPIU_Allreduce(&ntemp,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 941 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for two norm"); 942 } 943 PetscFunctionReturn(0); 944 } 945 946 PetscErrorCode MatTranspose_MPIDense(Mat A,MatReuse reuse,Mat *matout) 947 { 948 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 949 Mat_SeqDense *Aloc = (Mat_SeqDense*)a->A->data; 950 Mat B; 951 PetscInt M = A->rmap->N,N = A->cmap->N,m,n,*rwork,rstart = A->rmap->rstart; 952 PetscErrorCode ierr; 953 PetscInt j,i; 954 PetscScalar *v; 955 956 PetscFunctionBegin; 957 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 958 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 959 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 960 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 961 ierr = MatMPIDenseSetPreallocation(B,NULL);CHKERRQ(ierr); 962 } else { 963 B = *matout; 964 } 965 966 m = a->A->rmap->n; n = a->A->cmap->n; v = Aloc->v; 967 ierr = PetscMalloc1(m,&rwork);CHKERRQ(ierr); 968 for (i=0; i<m; i++) rwork[i] = rstart + i; 969 for (j=0; j<n; j++) { 970 ierr = MatSetValues(B,1,&j,m,rwork,v,INSERT_VALUES);CHKERRQ(ierr); 971 v += m; 972 } 973 ierr = PetscFree(rwork);CHKERRQ(ierr); 974 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 975 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 976 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 977 *matout = B; 978 } else { 979 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 980 } 981 PetscFunctionReturn(0); 982 } 983 984 985 static PetscErrorCode MatDuplicate_MPIDense(Mat,MatDuplicateOption,Mat*); 986 extern PetscErrorCode MatScale_MPIDense(Mat,PetscScalar); 987 988 PetscErrorCode MatSetUp_MPIDense(Mat A) 989 { 990 PetscErrorCode ierr; 991 992 PetscFunctionBegin; 993 ierr = MatMPIDenseSetPreallocation(A,0);CHKERRQ(ierr); 994 PetscFunctionReturn(0); 995 } 996 997 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 PetscErrorCode MatConjugate_MPIDense(Mat mat) 1009 { 1010 Mat_MPIDense *a = (Mat_MPIDense*)mat->data; 1011 PetscErrorCode ierr; 1012 1013 PetscFunctionBegin; 1014 ierr = MatConjugate(a->A);CHKERRQ(ierr); 1015 PetscFunctionReturn(0); 1016 } 1017 1018 PetscErrorCode MatRealPart_MPIDense(Mat A) 1019 { 1020 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1021 PetscErrorCode ierr; 1022 1023 PetscFunctionBegin; 1024 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1025 PetscFunctionReturn(0); 1026 } 1027 1028 PetscErrorCode MatImaginaryPart_MPIDense(Mat A) 1029 { 1030 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1031 PetscErrorCode ierr; 1032 1033 PetscFunctionBegin; 1034 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1035 PetscFunctionReturn(0); 1036 } 1037 1038 extern PetscErrorCode MatGetColumnNorms_SeqDense(Mat,NormType,PetscReal*); 1039 PetscErrorCode MatGetColumnNorms_MPIDense(Mat A,NormType type,PetscReal *norms) 1040 { 1041 PetscErrorCode ierr; 1042 PetscInt i,n; 1043 Mat_MPIDense *a = (Mat_MPIDense*) A->data; 1044 PetscReal *work; 1045 1046 PetscFunctionBegin; 1047 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 1048 ierr = PetscMalloc1(n,&work);CHKERRQ(ierr); 1049 ierr = MatGetColumnNorms_SeqDense(a->A,type,work);CHKERRQ(ierr); 1050 if (type == NORM_2) { 1051 for (i=0; i<n; i++) work[i] *= work[i]; 1052 } 1053 if (type == NORM_INFINITY) { 1054 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 1055 } else { 1056 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 1057 } 1058 ierr = PetscFree(work);CHKERRQ(ierr); 1059 if (type == NORM_2) { 1060 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 1061 } 1062 PetscFunctionReturn(0); 1063 } 1064 1065 static PetscErrorCode MatSetRandom_MPIDense(Mat x,PetscRandom rctx) 1066 { 1067 Mat_MPIDense *d = (Mat_MPIDense*)x->data; 1068 PetscErrorCode ierr; 1069 PetscScalar *a; 1070 PetscInt m,n,i; 1071 1072 PetscFunctionBegin; 1073 ierr = MatGetSize(d->A,&m,&n);CHKERRQ(ierr); 1074 ierr = MatDenseGetArray(d->A,&a);CHKERRQ(ierr); 1075 for (i=0; i<m*n; i++) { 1076 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 1077 } 1078 ierr = MatDenseRestoreArray(d->A,&a);CHKERRQ(ierr); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 extern PetscErrorCode MatMatMultNumeric_MPIDense(Mat A,Mat,Mat); 1083 1084 static PetscErrorCode MatMissingDiagonal_MPIDense(Mat A,PetscBool *missing,PetscInt *d) 1085 { 1086 PetscFunctionBegin; 1087 *missing = PETSC_FALSE; 1088 PetscFunctionReturn(0); 1089 } 1090 1091 /* -------------------------------------------------------------------*/ 1092 static struct _MatOps MatOps_Values = { MatSetValues_MPIDense, 1093 MatGetRow_MPIDense, 1094 MatRestoreRow_MPIDense, 1095 MatMult_MPIDense, 1096 /* 4*/ MatMultAdd_MPIDense, 1097 MatMultTranspose_MPIDense, 1098 MatMultTransposeAdd_MPIDense, 1099 0, 1100 0, 1101 0, 1102 /* 10*/ 0, 1103 0, 1104 0, 1105 0, 1106 MatTranspose_MPIDense, 1107 /* 15*/ MatGetInfo_MPIDense, 1108 MatEqual_MPIDense, 1109 MatGetDiagonal_MPIDense, 1110 MatDiagonalScale_MPIDense, 1111 MatNorm_MPIDense, 1112 /* 20*/ MatAssemblyBegin_MPIDense, 1113 MatAssemblyEnd_MPIDense, 1114 MatSetOption_MPIDense, 1115 MatZeroEntries_MPIDense, 1116 /* 24*/ MatZeroRows_MPIDense, 1117 0, 1118 0, 1119 0, 1120 0, 1121 /* 29*/ MatSetUp_MPIDense, 1122 0, 1123 0, 1124 MatGetDiagonalBlock_MPIDense, 1125 0, 1126 /* 34*/ MatDuplicate_MPIDense, 1127 0, 1128 0, 1129 0, 1130 0, 1131 /* 39*/ MatAXPY_MPIDense, 1132 MatCreateSubMatrices_MPIDense, 1133 0, 1134 MatGetValues_MPIDense, 1135 0, 1136 /* 44*/ 0, 1137 MatScale_MPIDense, 1138 MatShift_Basic, 1139 0, 1140 0, 1141 /* 49*/ MatSetRandom_MPIDense, 1142 0, 1143 0, 1144 0, 1145 0, 1146 /* 54*/ 0, 1147 0, 1148 0, 1149 0, 1150 0, 1151 /* 59*/ MatCreateSubMatrix_MPIDense, 1152 MatDestroy_MPIDense, 1153 MatView_MPIDense, 1154 0, 1155 0, 1156 /* 64*/ 0, 1157 0, 1158 0, 1159 0, 1160 0, 1161 /* 69*/ 0, 1162 0, 1163 0, 1164 0, 1165 0, 1166 /* 74*/ 0, 1167 0, 1168 0, 1169 0, 1170 0, 1171 /* 79*/ 0, 1172 0, 1173 0, 1174 0, 1175 /* 83*/ MatLoad_MPIDense, 1176 0, 1177 0, 1178 0, 1179 0, 1180 0, 1181 #if defined(PETSC_HAVE_ELEMENTAL) 1182 /* 89*/ MatMatMult_MPIDense_MPIDense, 1183 MatMatMultSymbolic_MPIDense_MPIDense, 1184 #else 1185 /* 89*/ 0, 1186 0, 1187 #endif 1188 MatMatMultNumeric_MPIDense, 1189 0, 1190 0, 1191 /* 94*/ 0, 1192 0, 1193 0, 1194 0, 1195 0, 1196 /* 99*/ 0, 1197 0, 1198 0, 1199 MatConjugate_MPIDense, 1200 0, 1201 /*104*/ 0, 1202 MatRealPart_MPIDense, 1203 MatImaginaryPart_MPIDense, 1204 0, 1205 0, 1206 /*109*/ 0, 1207 0, 1208 0, 1209 0, 1210 MatMissingDiagonal_MPIDense, 1211 /*114*/ 0, 1212 0, 1213 0, 1214 0, 1215 0, 1216 /*119*/ 0, 1217 0, 1218 0, 1219 0, 1220 0, 1221 /*124*/ 0, 1222 MatGetColumnNorms_MPIDense, 1223 0, 1224 0, 1225 0, 1226 /*129*/ 0, 1227 MatTransposeMatMult_MPIDense_MPIDense, 1228 MatTransposeMatMultSymbolic_MPIDense_MPIDense, 1229 MatTransposeMatMultNumeric_MPIDense_MPIDense, 1230 0, 1231 /*134*/ 0, 1232 0, 1233 0, 1234 0, 1235 0, 1236 /*139*/ 0, 1237 0, 1238 0, 1239 0, 1240 0, 1241 /*144*/ MatCreateMPIMatConcatenateSeqMat_MPIDense 1242 }; 1243 1244 PetscErrorCode MatMPIDenseSetPreallocation_MPIDense(Mat mat,PetscScalar *data) 1245 { 1246 Mat_MPIDense *a; 1247 PetscErrorCode ierr; 1248 1249 PetscFunctionBegin; 1250 mat->preallocated = PETSC_TRUE; 1251 /* Note: For now, when data is specified above, this assumes the user correctly 1252 allocates the local dense storage space. We should add error checking. */ 1253 1254 a = (Mat_MPIDense*)mat->data; 1255 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 1256 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 1257 a->nvec = mat->cmap->n; 1258 1259 ierr = MatCreate(PETSC_COMM_SELF,&a->A);CHKERRQ(ierr); 1260 ierr = MatSetSizes(a->A,mat->rmap->n,mat->cmap->N,mat->rmap->n,mat->cmap->N);CHKERRQ(ierr); 1261 ierr = MatSetType(a->A,MATSEQDENSE);CHKERRQ(ierr); 1262 ierr = MatSeqDenseSetPreallocation(a->A,data);CHKERRQ(ierr); 1263 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1264 PetscFunctionReturn(0); 1265 } 1266 1267 #if defined(PETSC_HAVE_ELEMENTAL) 1268 PETSC_INTERN PetscErrorCode MatConvert_MPIDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 1269 { 1270 Mat mat_elemental; 1271 PetscErrorCode ierr; 1272 PetscScalar *v; 1273 PetscInt m=A->rmap->n,N=A->cmap->N,rstart=A->rmap->rstart,i,*rows,*cols; 1274 1275 PetscFunctionBegin; 1276 if (reuse == MAT_REUSE_MATRIX) { 1277 mat_elemental = *newmat; 1278 ierr = MatZeroEntries(*newmat);CHKERRQ(ierr); 1279 } else { 1280 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 1281 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1282 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 1283 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 1284 ierr = MatSetOption(mat_elemental,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 1285 } 1286 1287 ierr = PetscMalloc2(m,&rows,N,&cols);CHKERRQ(ierr); 1288 for (i=0; i<N; i++) cols[i] = i; 1289 for (i=0; i<m; i++) rows[i] = rstart + i; 1290 1291 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 1292 ierr = MatDenseGetArray(A,&v);CHKERRQ(ierr); 1293 ierr = MatSetValues(mat_elemental,m,rows,N,cols,v,ADD_VALUES);CHKERRQ(ierr); 1294 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1295 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1296 ierr = MatDenseRestoreArray(A,&v);CHKERRQ(ierr); 1297 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1298 1299 if (reuse == MAT_INPLACE_MATRIX) { 1300 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 1301 } else { 1302 *newmat = mat_elemental; 1303 } 1304 PetscFunctionReturn(0); 1305 } 1306 #endif 1307 1308 static PetscErrorCode MatDenseGetColumn_MPIDense(Mat A,PetscInt col,PetscScalar **vals) 1309 { 1310 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1311 PetscErrorCode ierr; 1312 1313 PetscFunctionBegin; 1314 ierr = MatDenseGetColumn(mat->A,col,vals);CHKERRQ(ierr); 1315 PetscFunctionReturn(0); 1316 } 1317 1318 static PetscErrorCode MatDenseRestoreColumn_MPIDense(Mat A,PetscScalar **vals) 1319 { 1320 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1321 PetscErrorCode ierr; 1322 1323 PetscFunctionBegin; 1324 ierr = MatDenseRestoreColumn(mat->A,vals);CHKERRQ(ierr); 1325 PetscFunctionReturn(0); 1326 } 1327 1328 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIDense(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 1329 { 1330 PetscErrorCode ierr; 1331 Mat_MPIDense *mat; 1332 PetscInt m,nloc,N; 1333 1334 PetscFunctionBegin; 1335 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 1336 ierr = MatGetLocalSize(inmat,NULL,&nloc);CHKERRQ(ierr); 1337 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 1338 PetscInt sum; 1339 1340 if (n == PETSC_DECIDE) { 1341 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 1342 } 1343 /* Check sum(n) = N */ 1344 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 1345 if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N); 1346 1347 ierr = MatCreateDense(comm,m,n,PETSC_DETERMINE,N,NULL,outmat);CHKERRQ(ierr); 1348 } 1349 1350 /* numeric phase */ 1351 mat = (Mat_MPIDense*)(*outmat)->data; 1352 ierr = MatCopy(inmat,mat->A,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 1353 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1354 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1355 PetscFunctionReturn(0); 1356 } 1357 1358 PETSC_EXTERN PetscErrorCode MatCreate_MPIDense(Mat mat) 1359 { 1360 Mat_MPIDense *a; 1361 PetscErrorCode ierr; 1362 1363 PetscFunctionBegin; 1364 ierr = PetscNewLog(mat,&a);CHKERRQ(ierr); 1365 mat->data = (void*)a; 1366 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1367 1368 mat->insertmode = NOT_SET_VALUES; 1369 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&a->rank);CHKERRQ(ierr); 1370 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&a->size);CHKERRQ(ierr); 1371 1372 /* build cache for off array entries formed */ 1373 a->donotstash = PETSC_FALSE; 1374 1375 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)mat),1,&mat->stash);CHKERRQ(ierr); 1376 1377 /* stuff used for matrix vector multiply */ 1378 a->lvec = 0; 1379 a->Mvctx = 0; 1380 a->roworiented = PETSC_TRUE; 1381 1382 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",MatDenseGetArray_MPIDense);CHKERRQ(ierr); 1383 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",MatDenseRestoreArray_MPIDense);CHKERRQ(ierr); 1384 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArrayRead_C",MatDenseGetArrayRead_MPIDense);CHKERRQ(ierr); 1385 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArrayRead_C",MatDenseRestoreArrayRead_MPIDense);CHKERRQ(ierr); 1386 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",MatDensePlaceArray_MPIDense);CHKERRQ(ierr); 1387 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",MatDenseResetArray_MPIDense);CHKERRQ(ierr); 1388 #if defined(PETSC_HAVE_ELEMENTAL) 1389 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",MatConvert_MPIDense_Elemental);CHKERRQ(ierr); 1390 #endif 1391 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",MatMPIDenseSetPreallocation_MPIDense);CHKERRQ(ierr); 1392 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",MatMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1393 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",MatMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1394 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",MatMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1395 1396 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",MatTransposeMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1397 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",MatTransposeMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1398 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",MatTransposeMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1399 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",MatDenseGetColumn_MPIDense);CHKERRQ(ierr); 1400 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",MatDenseRestoreColumn_MPIDense);CHKERRQ(ierr); 1401 ierr = PetscObjectChangeTypeName((PetscObject)mat,MATMPIDENSE);CHKERRQ(ierr); 1402 PetscFunctionReturn(0); 1403 } 1404 1405 /*MC 1406 MATDENSE - MATDENSE = "dense" - A matrix type to be used for dense matrices. 1407 1408 This matrix type is identical to MATSEQDENSE when constructed with a single process communicator, 1409 and MATMPIDENSE otherwise. 1410 1411 Options Database Keys: 1412 . -mat_type dense - sets the matrix type to "dense" during a call to MatSetFromOptions() 1413 1414 Level: beginner 1415 1416 1417 .seealso: MatCreateMPIDense,MATSEQDENSE,MATMPIDENSE 1418 M*/ 1419 1420 /*@C 1421 MatMPIDenseSetPreallocation - Sets the array used to store the matrix entries 1422 1423 Not collective 1424 1425 Input Parameters: 1426 . B - the matrix 1427 - data - optional location of matrix data. Set data=NULL for PETSc 1428 to control all matrix memory allocation. 1429 1430 Notes: 1431 The dense format is fully compatible with standard Fortran 77 1432 storage by columns. 1433 1434 The data input variable is intended primarily for Fortran programmers 1435 who wish to allocate their own matrix memory space. Most users should 1436 set data=NULL. 1437 1438 Level: intermediate 1439 1440 .keywords: matrix,dense, parallel 1441 1442 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1443 @*/ 1444 PetscErrorCode MatMPIDenseSetPreallocation(Mat B,PetscScalar *data) 1445 { 1446 PetscErrorCode ierr; 1447 1448 PetscFunctionBegin; 1449 ierr = PetscTryMethod(B,"MatMPIDenseSetPreallocation_C",(Mat,PetscScalar*),(B,data));CHKERRQ(ierr); 1450 PetscFunctionReturn(0); 1451 } 1452 1453 /*@ 1454 MatDensePlaceArray - Allows one to replace the array in a dense array with an 1455 array provided by the user. This is useful to avoid copying an array 1456 into a matrix 1457 1458 Not Collective 1459 1460 Input Parameters: 1461 + mat - the matrix 1462 - array - the array in column major order 1463 1464 Notes: 1465 You can return to the original array with a call to MatDenseResetArray(). The user is responsible for freeing this array; it will not be 1466 freed when the matrix is destroyed. 1467 1468 Level: developer 1469 1470 .seealso: MatDenseGetArray(), MatDenseResetArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1471 1472 @*/ 1473 PetscErrorCode MatDensePlaceArray(Mat mat,const PetscScalar array[]) 1474 { 1475 PetscErrorCode ierr; 1476 PetscFunctionBegin; 1477 ierr = PetscUseMethod(mat,"MatDensePlaceArray_C",(Mat,const PetscScalar*),(mat,array));CHKERRQ(ierr); 1478 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1479 PetscFunctionReturn(0); 1480 } 1481 1482 /*@ 1483 MatDenseResetArray - Resets the matrix array to that it previously had before the call to MatDensePlaceArray() 1484 1485 Not Collective 1486 1487 Input Parameters: 1488 . mat - the matrix 1489 1490 Notes: 1491 You can only call this after a call to MatDensePlaceArray() 1492 1493 Level: developer 1494 1495 .seealso: MatDenseGetArray(), MatDensePlaceArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1496 1497 @*/ 1498 PetscErrorCode MatDenseResetArray(Mat mat) 1499 { 1500 PetscErrorCode ierr; 1501 PetscFunctionBegin; 1502 ierr = PetscUseMethod(mat,"MatDenseResetArray_C",(Mat),(mat));CHKERRQ(ierr); 1503 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1504 PetscFunctionReturn(0); 1505 } 1506 1507 /*@C 1508 MatCreateDense - Creates a parallel matrix in dense format. 1509 1510 Collective on MPI_Comm 1511 1512 Input Parameters: 1513 + comm - MPI communicator 1514 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1515 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1516 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1517 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 1518 - data - optional location of matrix data. Set data=NULL (PETSC_NULL_SCALAR for Fortran users) for PETSc 1519 to control all matrix memory allocation. 1520 1521 Output Parameter: 1522 . A - the matrix 1523 1524 Notes: 1525 The dense format is fully compatible with standard Fortran 77 1526 storage by columns. 1527 1528 The data input variable is intended primarily for Fortran programmers 1529 who wish to allocate their own matrix memory space. Most users should 1530 set data=NULL (PETSC_NULL_SCALAR for Fortran users). 1531 1532 The user MUST specify either the local or global matrix dimensions 1533 (possibly both). 1534 1535 Level: intermediate 1536 1537 .keywords: matrix,dense, parallel 1538 1539 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1540 @*/ 1541 PetscErrorCode MatCreateDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscScalar *data,Mat *A) 1542 { 1543 PetscErrorCode ierr; 1544 PetscMPIInt size; 1545 1546 PetscFunctionBegin; 1547 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1548 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1549 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1550 if (size > 1) { 1551 ierr = MatSetType(*A,MATMPIDENSE);CHKERRQ(ierr); 1552 ierr = MatMPIDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1553 if (data) { /* user provided data array, so no need to assemble */ 1554 ierr = MatSetUpMultiply_MPIDense(*A);CHKERRQ(ierr); 1555 (*A)->assembled = PETSC_TRUE; 1556 } 1557 } else { 1558 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 1559 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1560 } 1561 PetscFunctionReturn(0); 1562 } 1563 1564 static PetscErrorCode MatDuplicate_MPIDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 1565 { 1566 Mat mat; 1567 Mat_MPIDense *a,*oldmat = (Mat_MPIDense*)A->data; 1568 PetscErrorCode ierr; 1569 1570 PetscFunctionBegin; 1571 *newmat = 0; 1572 ierr = MatCreate(PetscObjectComm((PetscObject)A),&mat);CHKERRQ(ierr); 1573 ierr = MatSetSizes(mat,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1574 ierr = MatSetType(mat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1575 a = (Mat_MPIDense*)mat->data; 1576 ierr = PetscMemcpy(mat->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1577 1578 mat->factortype = A->factortype; 1579 mat->assembled = PETSC_TRUE; 1580 mat->preallocated = PETSC_TRUE; 1581 1582 a->size = oldmat->size; 1583 a->rank = oldmat->rank; 1584 mat->insertmode = NOT_SET_VALUES; 1585 a->nvec = oldmat->nvec; 1586 a->donotstash = oldmat->donotstash; 1587 1588 ierr = PetscLayoutReference(A->rmap,&mat->rmap);CHKERRQ(ierr); 1589 ierr = PetscLayoutReference(A->cmap,&mat->cmap);CHKERRQ(ierr); 1590 1591 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 1592 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1593 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1594 1595 *newmat = mat; 1596 PetscFunctionReturn(0); 1597 } 1598 1599 PetscErrorCode MatLoad_MPIDense_DenseInFile(MPI_Comm comm,PetscInt fd,PetscInt M,PetscInt N,Mat newmat) 1600 { 1601 PetscErrorCode ierr; 1602 PetscMPIInt rank,size; 1603 const PetscInt *rowners; 1604 PetscInt i,m,n,nz,j,mMax; 1605 PetscScalar *array,*vals,*vals_ptr; 1606 Mat_MPIDense *a = (Mat_MPIDense*)newmat->data; 1607 1608 PetscFunctionBegin; 1609 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1610 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1611 1612 /* determine ownership of rows and columns */ 1613 m = (newmat->rmap->n < 0) ? PETSC_DECIDE : newmat->rmap->n; 1614 n = (newmat->cmap->n < 0) ? PETSC_DECIDE : newmat->cmap->n; 1615 1616 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1617 if (!a->A || !((Mat_SeqDense*)(a->A->data))->user_alloc) { 1618 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1619 } 1620 ierr = MatDenseGetArray(newmat,&array);CHKERRQ(ierr); 1621 ierr = MatGetLocalSize(newmat,&m,NULL);CHKERRQ(ierr); 1622 ierr = MatGetOwnershipRanges(newmat,&rowners);CHKERRQ(ierr); 1623 ierr = MPI_Reduce(&m,&mMax,1,MPIU_INT,MPI_MAX,0,comm);CHKERRQ(ierr); 1624 if (!rank) { 1625 ierr = PetscMalloc1(mMax*N,&vals);CHKERRQ(ierr); 1626 1627 /* read in my part of the matrix numerical values */ 1628 ierr = PetscBinaryRead(fd,vals,m*N,PETSC_SCALAR);CHKERRQ(ierr); 1629 1630 /* insert into matrix-by row (this is why cannot directly read into array */ 1631 vals_ptr = vals; 1632 for (i=0; i<m; i++) { 1633 for (j=0; j<N; j++) { 1634 array[i + j*m] = *vals_ptr++; 1635 } 1636 } 1637 1638 /* read in other processors and ship out */ 1639 for (i=1; i<size; i++) { 1640 nz = (rowners[i+1] - rowners[i])*N; 1641 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1642 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1643 } 1644 } else { 1645 /* receive numeric values */ 1646 ierr = PetscMalloc1(m*N,&vals);CHKERRQ(ierr); 1647 1648 /* receive message of values*/ 1649 ierr = MPIULong_Recv(vals,m*N,MPIU_SCALAR,0,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1650 1651 /* insert into matrix-by row (this is why cannot directly read into array */ 1652 vals_ptr = vals; 1653 for (i=0; i<m; i++) { 1654 for (j=0; j<N; j++) { 1655 array[i + j*m] = *vals_ptr++; 1656 } 1657 } 1658 } 1659 ierr = MatDenseRestoreArray(newmat,&array);CHKERRQ(ierr); 1660 ierr = PetscFree(vals);CHKERRQ(ierr); 1661 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1662 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1663 PetscFunctionReturn(0); 1664 } 1665 1666 PetscErrorCode MatLoad_MPIDense(Mat newmat,PetscViewer viewer) 1667 { 1668 Mat_MPIDense *a; 1669 PetscScalar *vals,*svals; 1670 MPI_Comm comm; 1671 MPI_Status status; 1672 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*rowners,*sndcounts,m,n,maxnz; 1673 PetscInt header[4],*rowlengths = 0,M,N,*cols; 1674 PetscInt *ourlens,*procsnz = 0,jj,*mycols,*smycols; 1675 PetscInt i,nz,j,rstart,rend; 1676 int fd; 1677 PetscErrorCode ierr; 1678 1679 PetscFunctionBegin; 1680 /* force binary viewer to load .info file if it has not yet done so */ 1681 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1682 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1683 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1684 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1685 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1686 if (!rank) { 1687 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 1688 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1689 } 1690 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 1691 M = header[1]; N = header[2]; nz = header[3]; 1692 1693 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 1694 if (newmat->rmap->N < 0) newmat->rmap->N = M; 1695 if (newmat->cmap->N < 0) newmat->cmap->N = N; 1696 1697 if (newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",M,newmat->rmap->N); 1698 if (newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",N,newmat->cmap->N); 1699 1700 /* 1701 Handle case where matrix is stored on disk as a dense matrix 1702 */ 1703 if (nz == MATRIX_BINARY_FORMAT_DENSE) { 1704 ierr = MatLoad_MPIDense_DenseInFile(comm,fd,M,N,newmat);CHKERRQ(ierr); 1705 PetscFunctionReturn(0); 1706 } 1707 1708 /* determine ownership of all rows */ 1709 if (newmat->rmap->n < 0) { 1710 ierr = PetscMPIIntCast(M/size + ((M % size) > rank),&m);CHKERRQ(ierr); 1711 } else { 1712 ierr = PetscMPIIntCast(newmat->rmap->n,&m);CHKERRQ(ierr); 1713 } 1714 if (newmat->cmap->n < 0) { 1715 n = PETSC_DECIDE; 1716 } else { 1717 ierr = PetscMPIIntCast(newmat->cmap->n,&n);CHKERRQ(ierr); 1718 } 1719 1720 ierr = PetscMalloc1(size+2,&rowners);CHKERRQ(ierr); 1721 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1722 rowners[0] = 0; 1723 for (i=2; i<=size; i++) { 1724 rowners[i] += rowners[i-1]; 1725 } 1726 rstart = rowners[rank]; 1727 rend = rowners[rank+1]; 1728 1729 /* distribute row lengths to all processors */ 1730 ierr = PetscMalloc1(rend-rstart,&ourlens);CHKERRQ(ierr); 1731 if (!rank) { 1732 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 1733 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1734 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 1735 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1736 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1737 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1738 } else { 1739 ierr = MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1740 } 1741 1742 if (!rank) { 1743 /* calculate the number of nonzeros on each processor */ 1744 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 1745 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 1746 for (i=0; i<size; i++) { 1747 for (j=rowners[i]; j< rowners[i+1]; j++) { 1748 procsnz[i] += rowlengths[j]; 1749 } 1750 } 1751 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1752 1753 /* determine max buffer needed and allocate it */ 1754 maxnz = 0; 1755 for (i=0; i<size; i++) { 1756 maxnz = PetscMax(maxnz,procsnz[i]); 1757 } 1758 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 1759 1760 /* read in my part of the matrix column indices */ 1761 nz = procsnz[0]; 1762 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 1763 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1764 1765 /* read in every one elses and ship off */ 1766 for (i=1; i<size; i++) { 1767 nz = procsnz[i]; 1768 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1769 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 1770 } 1771 ierr = PetscFree(cols);CHKERRQ(ierr); 1772 } else { 1773 /* determine buffer space needed for message */ 1774 nz = 0; 1775 for (i=0; i<m; i++) { 1776 nz += ourlens[i]; 1777 } 1778 ierr = PetscMalloc1(nz+1,&mycols);CHKERRQ(ierr); 1779 1780 /* receive message of column indices*/ 1781 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 1782 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 1783 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1784 } 1785 1786 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1787 a = (Mat_MPIDense*)newmat->data; 1788 if (!a->A || !((Mat_SeqDense*)(a->A->data))->user_alloc) { 1789 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1790 } 1791 1792 if (!rank) { 1793 ierr = PetscMalloc1(maxnz,&vals);CHKERRQ(ierr); 1794 1795 /* read in my part of the matrix numerical values */ 1796 nz = procsnz[0]; 1797 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1798 1799 /* insert into matrix */ 1800 jj = rstart; 1801 smycols = mycols; 1802 svals = vals; 1803 for (i=0; i<m; i++) { 1804 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1805 smycols += ourlens[i]; 1806 svals += ourlens[i]; 1807 jj++; 1808 } 1809 1810 /* read in other processors and ship out */ 1811 for (i=1; i<size; i++) { 1812 nz = procsnz[i]; 1813 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1814 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 1815 } 1816 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1817 } else { 1818 /* receive numeric values */ 1819 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 1820 1821 /* receive message of values*/ 1822 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 1823 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1824 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1825 1826 /* insert into matrix */ 1827 jj = rstart; 1828 smycols = mycols; 1829 svals = vals; 1830 for (i=0; i<m; i++) { 1831 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1832 smycols += ourlens[i]; 1833 svals += ourlens[i]; 1834 jj++; 1835 } 1836 } 1837 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1838 ierr = PetscFree(vals);CHKERRQ(ierr); 1839 ierr = PetscFree(mycols);CHKERRQ(ierr); 1840 ierr = PetscFree(rowners);CHKERRQ(ierr); 1841 1842 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1843 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1844 PetscFunctionReturn(0); 1845 } 1846 1847 PetscErrorCode MatEqual_MPIDense(Mat A,Mat B,PetscBool *flag) 1848 { 1849 Mat_MPIDense *matB = (Mat_MPIDense*)B->data,*matA = (Mat_MPIDense*)A->data; 1850 Mat a,b; 1851 PetscBool flg; 1852 PetscErrorCode ierr; 1853 1854 PetscFunctionBegin; 1855 a = matA->A; 1856 b = matB->A; 1857 ierr = MatEqual(a,b,&flg);CHKERRQ(ierr); 1858 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1859 PetscFunctionReturn(0); 1860 } 1861 1862 PetscErrorCode MatDestroy_MatTransMatMult_MPIDense_MPIDense(Mat A) 1863 { 1864 PetscErrorCode ierr; 1865 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1866 Mat_TransMatMultDense *atb = a->atbdense; 1867 1868 PetscFunctionBegin; 1869 ierr = PetscFree3(atb->sendbuf,atb->atbarray,atb->recvcounts);CHKERRQ(ierr); 1870 ierr = (atb->destroy)(A);CHKERRQ(ierr); 1871 ierr = PetscFree(atb);CHKERRQ(ierr); 1872 PetscFunctionReturn(0); 1873 } 1874 1875 PetscErrorCode MatTransposeMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 1876 { 1877 Mat_MPIDense *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data; 1878 Mat_SeqDense *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data; 1879 Mat_TransMatMultDense *atb = c->atbdense; 1880 PetscErrorCode ierr; 1881 MPI_Comm comm; 1882 PetscMPIInt rank,size,*recvcounts=atb->recvcounts; 1883 PetscScalar *carray,*atbarray=atb->atbarray,*sendbuf=atb->sendbuf; 1884 PetscInt i,cN=C->cmap->N,cM=C->rmap->N,proc,k,j; 1885 PetscScalar _DOne=1.0,_DZero=0.0; 1886 PetscBLASInt am,an,bn,aN; 1887 const PetscInt *ranges; 1888 1889 PetscFunctionBegin; 1890 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1891 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1892 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1893 1894 /* compute atbarray = aseq^T * bseq */ 1895 ierr = PetscBLASIntCast(a->A->cmap->n,&an);CHKERRQ(ierr); 1896 ierr = PetscBLASIntCast(b->A->cmap->n,&bn);CHKERRQ(ierr); 1897 ierr = PetscBLASIntCast(a->A->rmap->n,&am);CHKERRQ(ierr); 1898 ierr = PetscBLASIntCast(A->cmap->N,&aN);CHKERRQ(ierr); 1899 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&an,&bn,&am,&_DOne,aseq->v,&aseq->lda,bseq->v,&bseq->lda,&_DZero,atbarray,&aN)); 1900 1901 ierr = MatGetOwnershipRanges(C,&ranges);CHKERRQ(ierr); 1902 for (i=0; i<size; i++) recvcounts[i] = (ranges[i+1] - ranges[i])*cN; 1903 1904 /* arrange atbarray into sendbuf */ 1905 k = 0; 1906 for (proc=0; proc<size; proc++) { 1907 for (j=0; j<cN; j++) { 1908 for (i=ranges[proc]; i<ranges[proc+1]; i++) sendbuf[k++] = atbarray[i+j*cM]; 1909 } 1910 } 1911 /* sum all atbarray to local values of C */ 1912 ierr = MatDenseGetArray(c->A,&carray);CHKERRQ(ierr); 1913 ierr = MPI_Reduce_scatter(sendbuf,carray,recvcounts,MPIU_SCALAR,MPIU_SUM,comm);CHKERRQ(ierr); 1914 ierr = MatDenseRestoreArray(c->A,&carray);CHKERRQ(ierr); 1915 PetscFunctionReturn(0); 1916 } 1917 1918 PetscErrorCode MatTransposeMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 1919 { 1920 PetscErrorCode ierr; 1921 Mat Cdense; 1922 MPI_Comm comm; 1923 PetscMPIInt size; 1924 PetscInt cm=A->cmap->n,cM,cN=B->cmap->N; 1925 Mat_MPIDense *c; 1926 Mat_TransMatMultDense *atb; 1927 1928 PetscFunctionBegin; 1929 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1930 if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) { 1931 SETERRQ4(comm,PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != B (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend); 1932 } 1933 1934 /* create matrix product Cdense */ 1935 ierr = MatCreate(comm,&Cdense);CHKERRQ(ierr); 1936 ierr = MatSetSizes(Cdense,cm,B->cmap->n,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 1937 ierr = MatSetType(Cdense,MATMPIDENSE);CHKERRQ(ierr); 1938 ierr = MatMPIDenseSetPreallocation(Cdense,NULL);CHKERRQ(ierr); 1939 ierr = MatAssemblyBegin(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1940 ierr = MatAssemblyEnd(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1941 *C = Cdense; 1942 1943 /* create data structure for reuse Cdense */ 1944 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1945 ierr = PetscNew(&atb);CHKERRQ(ierr); 1946 cM = Cdense->rmap->N; 1947 ierr = PetscMalloc3(cM*cN,&atb->sendbuf,cM*cN,&atb->atbarray,size,&atb->recvcounts);CHKERRQ(ierr); 1948 1949 c = (Mat_MPIDense*)Cdense->data; 1950 c->atbdense = atb; 1951 atb->destroy = Cdense->ops->destroy; 1952 Cdense->ops->destroy = MatDestroy_MatTransMatMult_MPIDense_MPIDense; 1953 PetscFunctionReturn(0); 1954 } 1955 1956 PetscErrorCode MatTransposeMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1957 { 1958 PetscErrorCode ierr; 1959 1960 PetscFunctionBegin; 1961 if (scall == MAT_INITIAL_MATRIX) { 1962 ierr = MatTransposeMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 1963 } 1964 ierr = MatTransposeMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 1965 PetscFunctionReturn(0); 1966 } 1967 1968 PetscErrorCode MatDestroy_MatMatMult_MPIDense_MPIDense(Mat A) 1969 { 1970 PetscErrorCode ierr; 1971 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1972 Mat_MatMultDense *ab = a->abdense; 1973 1974 PetscFunctionBegin; 1975 ierr = MatDestroy(&ab->Ce);CHKERRQ(ierr); 1976 ierr = MatDestroy(&ab->Ae);CHKERRQ(ierr); 1977 ierr = MatDestroy(&ab->Be);CHKERRQ(ierr); 1978 1979 ierr = (ab->destroy)(A);CHKERRQ(ierr); 1980 ierr = PetscFree(ab);CHKERRQ(ierr); 1981 PetscFunctionReturn(0); 1982 } 1983 1984 #if defined(PETSC_HAVE_ELEMENTAL) 1985 PetscErrorCode MatMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 1986 { 1987 PetscErrorCode ierr; 1988 Mat_MPIDense *c=(Mat_MPIDense*)C->data; 1989 Mat_MatMultDense *ab=c->abdense; 1990 1991 PetscFunctionBegin; 1992 ierr = MatConvert_MPIDense_Elemental(A,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Ae);CHKERRQ(ierr); 1993 ierr = MatConvert_MPIDense_Elemental(B,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Be);CHKERRQ(ierr); 1994 ierr = MatMatMultNumeric(ab->Ae,ab->Be,ab->Ce);CHKERRQ(ierr); 1995 ierr = MatConvert(ab->Ce,MATMPIDENSE,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 1996 PetscFunctionReturn(0); 1997 } 1998 1999 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 2000 { 2001 PetscErrorCode ierr; 2002 Mat Ae,Be,Ce; 2003 Mat_MPIDense *c; 2004 Mat_MatMultDense *ab; 2005 2006 PetscFunctionBegin; 2007 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 2008 SETERRQ4(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Matrix local dimensions are incompatible, A (%D, %D) != B (%D,%D)",A->rmap->rstart,A->rmap->rend,B->rmap->rstart,B->rmap->rend); 2009 } 2010 2011 /* convert A and B to Elemental matrices Ae and Be */ 2012 ierr = MatConvert(A,MATELEMENTAL,MAT_INITIAL_MATRIX, &Ae);CHKERRQ(ierr); 2013 ierr = MatConvert(B,MATELEMENTAL,MAT_INITIAL_MATRIX, &Be);CHKERRQ(ierr); 2014 2015 /* Ce = Ae*Be */ 2016 ierr = MatMatMultSymbolic(Ae,Be,fill,&Ce);CHKERRQ(ierr); 2017 ierr = MatMatMultNumeric(Ae,Be,Ce);CHKERRQ(ierr); 2018 2019 /* convert Ce to C */ 2020 ierr = MatConvert(Ce,MATMPIDENSE,MAT_INITIAL_MATRIX,C);CHKERRQ(ierr); 2021 2022 /* create data structure for reuse Cdense */ 2023 ierr = PetscNew(&ab);CHKERRQ(ierr); 2024 c = (Mat_MPIDense*)(*C)->data; 2025 c->abdense = ab; 2026 2027 ab->Ae = Ae; 2028 ab->Be = Be; 2029 ab->Ce = Ce; 2030 ab->destroy = (*C)->ops->destroy; 2031 (*C)->ops->destroy = MatDestroy_MatMatMult_MPIDense_MPIDense; 2032 (*C)->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIDense; 2033 PetscFunctionReturn(0); 2034 } 2035 2036 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2037 { 2038 PetscErrorCode ierr; 2039 2040 PetscFunctionBegin; 2041 if (scall == MAT_INITIAL_MATRIX) { /* simbolic product includes numeric product */ 2042 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2043 ierr = MatMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 2044 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2045 } else { 2046 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2047 ierr = MatMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 2048 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2049 } 2050 PetscFunctionReturn(0); 2051 } 2052 #endif 2053 2054