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 if (mat->preallocated) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Matrix has already been preallocated"); 1251 mat->preallocated = PETSC_TRUE; 1252 /* Note: For now, when data is specified above, this assumes the user correctly 1253 allocates the local dense storage space. We should add error checking. */ 1254 1255 a = (Mat_MPIDense*)mat->data; 1256 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 1257 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 1258 a->nvec = mat->cmap->n; 1259 1260 ierr = MatCreate(PETSC_COMM_SELF,&a->A);CHKERRQ(ierr); 1261 ierr = MatSetSizes(a->A,mat->rmap->n,mat->cmap->N,mat->rmap->n,mat->cmap->N);CHKERRQ(ierr); 1262 ierr = MatSetType(a->A,MATSEQDENSE);CHKERRQ(ierr); 1263 ierr = MatSeqDenseSetPreallocation(a->A,data);CHKERRQ(ierr); 1264 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1265 PetscFunctionReturn(0); 1266 } 1267 1268 #if defined(PETSC_HAVE_ELEMENTAL) 1269 PETSC_INTERN PetscErrorCode MatConvert_MPIDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 1270 { 1271 Mat mat_elemental; 1272 PetscErrorCode ierr; 1273 PetscScalar *v; 1274 PetscInt m=A->rmap->n,N=A->cmap->N,rstart=A->rmap->rstart,i,*rows,*cols; 1275 1276 PetscFunctionBegin; 1277 if (reuse == MAT_REUSE_MATRIX) { 1278 mat_elemental = *newmat; 1279 ierr = MatZeroEntries(*newmat);CHKERRQ(ierr); 1280 } else { 1281 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 1282 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1283 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 1284 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 1285 ierr = MatSetOption(mat_elemental,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 1286 } 1287 1288 ierr = PetscMalloc2(m,&rows,N,&cols);CHKERRQ(ierr); 1289 for (i=0; i<N; i++) cols[i] = i; 1290 for (i=0; i<m; i++) rows[i] = rstart + i; 1291 1292 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 1293 ierr = MatDenseGetArray(A,&v);CHKERRQ(ierr); 1294 ierr = MatSetValues(mat_elemental,m,rows,N,cols,v,ADD_VALUES);CHKERRQ(ierr); 1295 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1296 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1297 ierr = MatDenseRestoreArray(A,&v);CHKERRQ(ierr); 1298 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1299 1300 if (reuse == MAT_INPLACE_MATRIX) { 1301 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 1302 } else { 1303 *newmat = mat_elemental; 1304 } 1305 PetscFunctionReturn(0); 1306 } 1307 #endif 1308 1309 static PetscErrorCode MatDenseGetColumn_MPIDense(Mat A,PetscInt col,PetscScalar **vals) 1310 { 1311 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1312 PetscErrorCode ierr; 1313 1314 PetscFunctionBegin; 1315 ierr = MatDenseGetColumn(mat->A,col,vals);CHKERRQ(ierr); 1316 PetscFunctionReturn(0); 1317 } 1318 1319 static PetscErrorCode MatDenseRestoreColumn_MPIDense(Mat A,PetscScalar **vals) 1320 { 1321 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1322 PetscErrorCode ierr; 1323 1324 PetscFunctionBegin; 1325 ierr = MatDenseRestoreColumn(mat->A,vals);CHKERRQ(ierr); 1326 PetscFunctionReturn(0); 1327 } 1328 1329 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIDense(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 1330 { 1331 PetscErrorCode ierr; 1332 Mat_MPIDense *mat; 1333 PetscInt m,nloc,N; 1334 1335 PetscFunctionBegin; 1336 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 1337 ierr = MatGetLocalSize(inmat,NULL,&nloc);CHKERRQ(ierr); 1338 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 1339 PetscInt sum; 1340 1341 if (n == PETSC_DECIDE) { 1342 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 1343 } 1344 /* Check sum(n) = N */ 1345 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 1346 if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N); 1347 1348 ierr = MatCreateDense(comm,m,n,PETSC_DETERMINE,N,NULL,outmat);CHKERRQ(ierr); 1349 } 1350 1351 /* numeric phase */ 1352 mat = (Mat_MPIDense*)(*outmat)->data; 1353 ierr = MatCopy(inmat,mat->A,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 1354 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1355 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1356 PetscFunctionReturn(0); 1357 } 1358 1359 PETSC_EXTERN PetscErrorCode MatCreate_MPIDense(Mat mat) 1360 { 1361 Mat_MPIDense *a; 1362 PetscErrorCode ierr; 1363 1364 PetscFunctionBegin; 1365 ierr = PetscNewLog(mat,&a);CHKERRQ(ierr); 1366 mat->data = (void*)a; 1367 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1368 1369 mat->insertmode = NOT_SET_VALUES; 1370 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&a->rank);CHKERRQ(ierr); 1371 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&a->size);CHKERRQ(ierr); 1372 1373 /* build cache for off array entries formed */ 1374 a->donotstash = PETSC_FALSE; 1375 1376 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)mat),1,&mat->stash);CHKERRQ(ierr); 1377 1378 /* stuff used for matrix vector multiply */ 1379 a->lvec = 0; 1380 a->Mvctx = 0; 1381 a->roworiented = PETSC_TRUE; 1382 1383 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",MatDenseGetArray_MPIDense);CHKERRQ(ierr); 1384 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",MatDenseRestoreArray_MPIDense);CHKERRQ(ierr); 1385 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArrayRead_C",MatDenseGetArrayRead_MPIDense);CHKERRQ(ierr); 1386 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArrayRead_C",MatDenseRestoreArrayRead_MPIDense);CHKERRQ(ierr); 1387 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",MatDensePlaceArray_MPIDense);CHKERRQ(ierr); 1388 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",MatDenseResetArray_MPIDense);CHKERRQ(ierr); 1389 #if defined(PETSC_HAVE_ELEMENTAL) 1390 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",MatConvert_MPIDense_Elemental);CHKERRQ(ierr); 1391 #endif 1392 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",MatMPIDenseSetPreallocation_MPIDense);CHKERRQ(ierr); 1393 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",MatMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1394 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",MatMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1395 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",MatMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1396 1397 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",MatTransposeMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1398 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",MatTransposeMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1399 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",MatTransposeMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1400 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",MatDenseGetColumn_MPIDense);CHKERRQ(ierr); 1401 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",MatDenseRestoreColumn_MPIDense);CHKERRQ(ierr); 1402 ierr = PetscObjectChangeTypeName((PetscObject)mat,MATMPIDENSE);CHKERRQ(ierr); 1403 PetscFunctionReturn(0); 1404 } 1405 1406 /*MC 1407 MATDENSE - MATDENSE = "dense" - A matrix type to be used for dense matrices. 1408 1409 This matrix type is identical to MATSEQDENSE when constructed with a single process communicator, 1410 and MATMPIDENSE otherwise. 1411 1412 Options Database Keys: 1413 . -mat_type dense - sets the matrix type to "dense" during a call to MatSetFromOptions() 1414 1415 Level: beginner 1416 1417 1418 .seealso: MatCreateMPIDense,MATSEQDENSE,MATMPIDENSE 1419 M*/ 1420 1421 /*@C 1422 MatMPIDenseSetPreallocation - Sets the array used to store the matrix entries 1423 1424 Not collective 1425 1426 Input Parameters: 1427 . B - the matrix 1428 - data - optional location of matrix data. Set data=NULL for PETSc 1429 to control all matrix memory allocation. 1430 1431 Notes: 1432 The dense format is fully compatible with standard Fortran 77 1433 storage by columns. 1434 1435 The data input variable is intended primarily for Fortran programmers 1436 who wish to allocate their own matrix memory space. Most users should 1437 set data=NULL. 1438 1439 Level: intermediate 1440 1441 .keywords: matrix,dense, parallel 1442 1443 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1444 @*/ 1445 PetscErrorCode MatMPIDenseSetPreallocation(Mat B,PetscScalar *data) 1446 { 1447 PetscErrorCode ierr; 1448 1449 PetscFunctionBegin; 1450 ierr = PetscTryMethod(B,"MatMPIDenseSetPreallocation_C",(Mat,PetscScalar*),(B,data));CHKERRQ(ierr); 1451 PetscFunctionReturn(0); 1452 } 1453 1454 /*@ 1455 MatDensePlaceArray - Allows one to replace the array in a dense array with an 1456 array provided by the user. This is useful to avoid copying an array 1457 into a matrix 1458 1459 Not Collective 1460 1461 Input Parameters: 1462 + mat - the matrix 1463 - array - the array in column major order 1464 1465 Notes: 1466 You can return to the original array with a call to MatDenseResetArray(). The user is responsible for freeing this array; it will not be 1467 freed when the matrix is destroyed. 1468 1469 Level: developer 1470 1471 .seealso: MatDenseGetArray(), MatDenseResetArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1472 1473 @*/ 1474 PetscErrorCode MatDensePlaceArray(Mat mat,const PetscScalar array[]) 1475 { 1476 PetscErrorCode ierr; 1477 PetscFunctionBegin; 1478 ierr = PetscUseMethod(mat,"MatDensePlaceArray_C",(Mat,const PetscScalar*),(mat,array));CHKERRQ(ierr); 1479 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1480 PetscFunctionReturn(0); 1481 } 1482 1483 /*@ 1484 MatDenseResetArray - Resets the matrix array to that it previously had before the call to MatDensePlaceArray() 1485 1486 Not Collective 1487 1488 Input Parameters: 1489 . mat - the matrix 1490 1491 Notes: 1492 You can only call this after a call to MatDensePlaceArray() 1493 1494 Level: developer 1495 1496 .seealso: MatDenseGetArray(), MatDensePlaceArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1497 1498 @*/ 1499 PetscErrorCode MatDenseResetArray(Mat mat) 1500 { 1501 PetscErrorCode ierr; 1502 PetscFunctionBegin; 1503 ierr = PetscUseMethod(mat,"MatDenseResetArray_C",(Mat),(mat));CHKERRQ(ierr); 1504 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1505 PetscFunctionReturn(0); 1506 } 1507 1508 /*@C 1509 MatCreateDense - Creates a parallel matrix in dense format. 1510 1511 Collective on MPI_Comm 1512 1513 Input Parameters: 1514 + comm - MPI communicator 1515 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1516 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1517 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1518 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 1519 - data - optional location of matrix data. Set data=NULL (PETSC_NULL_SCALAR for Fortran users) for PETSc 1520 to control all matrix memory allocation. 1521 1522 Output Parameter: 1523 . A - the matrix 1524 1525 Notes: 1526 The dense format is fully compatible with standard Fortran 77 1527 storage by columns. 1528 1529 The data input variable is intended primarily for Fortran programmers 1530 who wish to allocate their own matrix memory space. Most users should 1531 set data=NULL (PETSC_NULL_SCALAR for Fortran users). 1532 1533 The user MUST specify either the local or global matrix dimensions 1534 (possibly both). 1535 1536 Level: intermediate 1537 1538 .keywords: matrix,dense, parallel 1539 1540 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1541 @*/ 1542 PetscErrorCode MatCreateDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscScalar *data,Mat *A) 1543 { 1544 PetscErrorCode ierr; 1545 PetscMPIInt size; 1546 1547 PetscFunctionBegin; 1548 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1549 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1550 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1551 if (size > 1) { 1552 ierr = MatSetType(*A,MATMPIDENSE);CHKERRQ(ierr); 1553 ierr = MatMPIDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1554 if (data) { /* user provided data array, so no need to assemble */ 1555 ierr = MatSetUpMultiply_MPIDense(*A);CHKERRQ(ierr); 1556 (*A)->assembled = PETSC_TRUE; 1557 } 1558 } else { 1559 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 1560 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1561 } 1562 PetscFunctionReturn(0); 1563 } 1564 1565 static PetscErrorCode MatDuplicate_MPIDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 1566 { 1567 Mat mat; 1568 Mat_MPIDense *a,*oldmat = (Mat_MPIDense*)A->data; 1569 PetscErrorCode ierr; 1570 1571 PetscFunctionBegin; 1572 *newmat = 0; 1573 ierr = MatCreate(PetscObjectComm((PetscObject)A),&mat);CHKERRQ(ierr); 1574 ierr = MatSetSizes(mat,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1575 ierr = MatSetType(mat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1576 a = (Mat_MPIDense*)mat->data; 1577 ierr = PetscMemcpy(mat->ops,A->ops,sizeof(struct _MatOps));CHKERRQ(ierr); 1578 1579 mat->factortype = A->factortype; 1580 mat->assembled = PETSC_TRUE; 1581 mat->preallocated = PETSC_TRUE; 1582 1583 a->size = oldmat->size; 1584 a->rank = oldmat->rank; 1585 mat->insertmode = NOT_SET_VALUES; 1586 a->nvec = oldmat->nvec; 1587 a->donotstash = oldmat->donotstash; 1588 1589 ierr = PetscLayoutReference(A->rmap,&mat->rmap);CHKERRQ(ierr); 1590 ierr = PetscLayoutReference(A->cmap,&mat->cmap);CHKERRQ(ierr); 1591 1592 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 1593 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1594 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1595 1596 *newmat = mat; 1597 PetscFunctionReturn(0); 1598 } 1599 1600 PetscErrorCode MatLoad_MPIDense_DenseInFile(MPI_Comm comm,PetscInt fd,PetscInt M,PetscInt N,Mat newmat) 1601 { 1602 PetscErrorCode ierr; 1603 PetscMPIInt rank,size; 1604 const PetscInt *rowners; 1605 PetscInt i,m,n,nz,j,mMax; 1606 PetscScalar *array,*vals,*vals_ptr; 1607 Mat_MPIDense *a = (Mat_MPIDense*)newmat->data; 1608 1609 PetscFunctionBegin; 1610 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1611 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1612 1613 /* determine ownership of rows and columns */ 1614 m = (newmat->rmap->n < 0) ? PETSC_DECIDE : newmat->rmap->n; 1615 n = (newmat->cmap->n < 0) ? PETSC_DECIDE : newmat->cmap->n; 1616 1617 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1618 if (!a->A) { 1619 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1620 } 1621 ierr = MatDenseGetArray(newmat,&array);CHKERRQ(ierr); 1622 ierr = MatGetLocalSize(newmat,&m,NULL);CHKERRQ(ierr); 1623 ierr = MatGetOwnershipRanges(newmat,&rowners);CHKERRQ(ierr); 1624 ierr = MPI_Reduce(&m,&mMax,1,MPIU_INT,MPI_MAX,0,comm);CHKERRQ(ierr); 1625 if (!rank) { 1626 ierr = PetscMalloc1(mMax*N,&vals);CHKERRQ(ierr); 1627 1628 /* read in my part of the matrix numerical values */ 1629 ierr = PetscBinaryRead(fd,vals,m*N,PETSC_SCALAR);CHKERRQ(ierr); 1630 1631 /* insert into matrix-by row (this is why cannot directly read into array */ 1632 vals_ptr = vals; 1633 for (i=0; i<m; i++) { 1634 for (j=0; j<N; j++) { 1635 array[i + j*m] = *vals_ptr++; 1636 } 1637 } 1638 1639 /* read in other processors and ship out */ 1640 for (i=1; i<size; i++) { 1641 nz = (rowners[i+1] - rowners[i])*N; 1642 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1643 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1644 } 1645 } else { 1646 /* receive numeric values */ 1647 ierr = PetscMalloc1(m*N,&vals);CHKERRQ(ierr); 1648 1649 /* receive message of values*/ 1650 ierr = MPIULong_Recv(vals,m*N,MPIU_SCALAR,0,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1651 1652 /* insert into matrix-by row (this is why cannot directly read into array */ 1653 vals_ptr = vals; 1654 for (i=0; i<m; i++) { 1655 for (j=0; j<N; j++) { 1656 array[i + j*m] = *vals_ptr++; 1657 } 1658 } 1659 } 1660 ierr = MatDenseRestoreArray(newmat,&array);CHKERRQ(ierr); 1661 ierr = PetscFree(vals);CHKERRQ(ierr); 1662 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1663 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1664 PetscFunctionReturn(0); 1665 } 1666 1667 PetscErrorCode MatLoad_MPIDense(Mat newmat,PetscViewer viewer) 1668 { 1669 Mat_MPIDense *a; 1670 PetscScalar *vals,*svals; 1671 MPI_Comm comm; 1672 MPI_Status status; 1673 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*rowners,*sndcounts,m,n,maxnz; 1674 PetscInt header[4],*rowlengths = 0,M,N,*cols; 1675 PetscInt *ourlens,*procsnz = 0,jj,*mycols,*smycols; 1676 PetscInt i,nz,j,rstart,rend; 1677 int fd; 1678 PetscBool isbinary; 1679 PetscErrorCode ierr; 1680 1681 PetscFunctionBegin; 1682 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1683 if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name); 1684 1685 /* force binary viewer to load .info file if it has not yet done so */ 1686 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1687 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1688 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1689 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1690 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1691 if (!rank) { 1692 ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr); 1693 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1694 } 1695 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 1696 M = header[1]; N = header[2]; nz = header[3]; 1697 1698 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 1699 if (newmat->rmap->N < 0) newmat->rmap->N = M; 1700 if (newmat->cmap->N < 0) newmat->cmap->N = N; 1701 1702 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); 1703 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); 1704 1705 /* 1706 Handle case where matrix is stored on disk as a dense matrix 1707 */ 1708 if (nz == MATRIX_BINARY_FORMAT_DENSE) { 1709 ierr = MatLoad_MPIDense_DenseInFile(comm,fd,M,N,newmat);CHKERRQ(ierr); 1710 PetscFunctionReturn(0); 1711 } 1712 1713 /* determine ownership of all rows */ 1714 if (newmat->rmap->n < 0) { 1715 ierr = PetscMPIIntCast(M/size + ((M % size) > rank),&m);CHKERRQ(ierr); 1716 } else { 1717 ierr = PetscMPIIntCast(newmat->rmap->n,&m);CHKERRQ(ierr); 1718 } 1719 if (newmat->cmap->n < 0) { 1720 n = PETSC_DECIDE; 1721 } else { 1722 ierr = PetscMPIIntCast(newmat->cmap->n,&n);CHKERRQ(ierr); 1723 } 1724 1725 ierr = PetscMalloc1(size+2,&rowners);CHKERRQ(ierr); 1726 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1727 rowners[0] = 0; 1728 for (i=2; i<=size; i++) { 1729 rowners[i] += rowners[i-1]; 1730 } 1731 rstart = rowners[rank]; 1732 rend = rowners[rank+1]; 1733 1734 /* distribute row lengths to all processors */ 1735 ierr = PetscMalloc1(rend-rstart,&ourlens);CHKERRQ(ierr); 1736 if (!rank) { 1737 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 1738 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1739 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 1740 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1741 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1742 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1743 } else { 1744 ierr = MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1745 } 1746 1747 if (!rank) { 1748 /* calculate the number of nonzeros on each processor */ 1749 ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr); 1750 ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr); 1751 for (i=0; i<size; i++) { 1752 for (j=rowners[i]; j< rowners[i+1]; j++) { 1753 procsnz[i] += rowlengths[j]; 1754 } 1755 } 1756 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1757 1758 /* determine max buffer needed and allocate it */ 1759 maxnz = 0; 1760 for (i=0; i<size; i++) { 1761 maxnz = PetscMax(maxnz,procsnz[i]); 1762 } 1763 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 1764 1765 /* read in my part of the matrix column indices */ 1766 nz = procsnz[0]; 1767 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 1768 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 1769 1770 /* read in every one elses and ship off */ 1771 for (i=1; i<size; i++) { 1772 nz = procsnz[i]; 1773 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1774 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 1775 } 1776 ierr = PetscFree(cols);CHKERRQ(ierr); 1777 } else { 1778 /* determine buffer space needed for message */ 1779 nz = 0; 1780 for (i=0; i<m; i++) { 1781 nz += ourlens[i]; 1782 } 1783 ierr = PetscMalloc1(nz+1,&mycols);CHKERRQ(ierr); 1784 1785 /* receive message of column indices*/ 1786 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 1787 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 1788 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1789 } 1790 1791 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1792 a = (Mat_MPIDense*)newmat->data; 1793 if (!a->A) { 1794 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1795 } 1796 1797 if (!rank) { 1798 ierr = PetscMalloc1(maxnz,&vals);CHKERRQ(ierr); 1799 1800 /* read in my part of the matrix numerical values */ 1801 nz = procsnz[0]; 1802 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1803 1804 /* insert into matrix */ 1805 jj = rstart; 1806 smycols = mycols; 1807 svals = vals; 1808 for (i=0; i<m; i++) { 1809 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1810 smycols += ourlens[i]; 1811 svals += ourlens[i]; 1812 jj++; 1813 } 1814 1815 /* read in other processors and ship out */ 1816 for (i=1; i<size; i++) { 1817 nz = procsnz[i]; 1818 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1819 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 1820 } 1821 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1822 } else { 1823 /* receive numeric values */ 1824 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 1825 1826 /* receive message of values*/ 1827 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 1828 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1829 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1830 1831 /* insert into matrix */ 1832 jj = rstart; 1833 smycols = mycols; 1834 svals = vals; 1835 for (i=0; i<m; i++) { 1836 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1837 smycols += ourlens[i]; 1838 svals += ourlens[i]; 1839 jj++; 1840 } 1841 } 1842 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1843 ierr = PetscFree(vals);CHKERRQ(ierr); 1844 ierr = PetscFree(mycols);CHKERRQ(ierr); 1845 ierr = PetscFree(rowners);CHKERRQ(ierr); 1846 1847 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1848 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1849 PetscFunctionReturn(0); 1850 } 1851 1852 PetscErrorCode MatEqual_MPIDense(Mat A,Mat B,PetscBool *flag) 1853 { 1854 Mat_MPIDense *matB = (Mat_MPIDense*)B->data,*matA = (Mat_MPIDense*)A->data; 1855 Mat a,b; 1856 PetscBool flg; 1857 PetscErrorCode ierr; 1858 1859 PetscFunctionBegin; 1860 a = matA->A; 1861 b = matB->A; 1862 ierr = MatEqual(a,b,&flg);CHKERRQ(ierr); 1863 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1864 PetscFunctionReturn(0); 1865 } 1866 1867 PetscErrorCode MatDestroy_MatTransMatMult_MPIDense_MPIDense(Mat A) 1868 { 1869 PetscErrorCode ierr; 1870 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1871 Mat_TransMatMultDense *atb = a->atbdense; 1872 1873 PetscFunctionBegin; 1874 ierr = PetscFree3(atb->sendbuf,atb->atbarray,atb->recvcounts);CHKERRQ(ierr); 1875 ierr = (atb->destroy)(A);CHKERRQ(ierr); 1876 ierr = PetscFree(atb);CHKERRQ(ierr); 1877 PetscFunctionReturn(0); 1878 } 1879 1880 PetscErrorCode MatTransposeMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 1881 { 1882 Mat_MPIDense *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data; 1883 Mat_SeqDense *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data; 1884 Mat_TransMatMultDense *atb = c->atbdense; 1885 PetscErrorCode ierr; 1886 MPI_Comm comm; 1887 PetscMPIInt rank,size,*recvcounts=atb->recvcounts; 1888 PetscScalar *carray,*atbarray=atb->atbarray,*sendbuf=atb->sendbuf; 1889 PetscInt i,cN=C->cmap->N,cM=C->rmap->N,proc,k,j; 1890 PetscScalar _DOne=1.0,_DZero=0.0; 1891 PetscBLASInt am,an,bn,aN; 1892 const PetscInt *ranges; 1893 1894 PetscFunctionBegin; 1895 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1896 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1897 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1898 1899 /* compute atbarray = aseq^T * bseq */ 1900 ierr = PetscBLASIntCast(a->A->cmap->n,&an);CHKERRQ(ierr); 1901 ierr = PetscBLASIntCast(b->A->cmap->n,&bn);CHKERRQ(ierr); 1902 ierr = PetscBLASIntCast(a->A->rmap->n,&am);CHKERRQ(ierr); 1903 ierr = PetscBLASIntCast(A->cmap->N,&aN);CHKERRQ(ierr); 1904 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&an,&bn,&am,&_DOne,aseq->v,&aseq->lda,bseq->v,&bseq->lda,&_DZero,atbarray,&aN)); 1905 1906 ierr = MatGetOwnershipRanges(C,&ranges);CHKERRQ(ierr); 1907 for (i=0; i<size; i++) recvcounts[i] = (ranges[i+1] - ranges[i])*cN; 1908 1909 /* arrange atbarray into sendbuf */ 1910 k = 0; 1911 for (proc=0; proc<size; proc++) { 1912 for (j=0; j<cN; j++) { 1913 for (i=ranges[proc]; i<ranges[proc+1]; i++) sendbuf[k++] = atbarray[i+j*cM]; 1914 } 1915 } 1916 /* sum all atbarray to local values of C */ 1917 ierr = MatDenseGetArray(c->A,&carray);CHKERRQ(ierr); 1918 ierr = MPI_Reduce_scatter(sendbuf,carray,recvcounts,MPIU_SCALAR,MPIU_SUM,comm);CHKERRQ(ierr); 1919 ierr = MatDenseRestoreArray(c->A,&carray);CHKERRQ(ierr); 1920 PetscFunctionReturn(0); 1921 } 1922 1923 PetscErrorCode MatTransposeMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 1924 { 1925 PetscErrorCode ierr; 1926 Mat Cdense; 1927 MPI_Comm comm; 1928 PetscMPIInt size; 1929 PetscInt cm=A->cmap->n,cM,cN=B->cmap->N; 1930 Mat_MPIDense *c; 1931 Mat_TransMatMultDense *atb; 1932 1933 PetscFunctionBegin; 1934 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1935 if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) { 1936 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); 1937 } 1938 1939 /* create matrix product Cdense */ 1940 ierr = MatCreate(comm,&Cdense);CHKERRQ(ierr); 1941 ierr = MatSetSizes(Cdense,cm,B->cmap->n,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 1942 ierr = MatSetType(Cdense,MATMPIDENSE);CHKERRQ(ierr); 1943 ierr = MatMPIDenseSetPreallocation(Cdense,NULL);CHKERRQ(ierr); 1944 ierr = MatAssemblyBegin(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1945 ierr = MatAssemblyEnd(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1946 *C = Cdense; 1947 1948 /* create data structure for reuse Cdense */ 1949 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1950 ierr = PetscNew(&atb);CHKERRQ(ierr); 1951 cM = Cdense->rmap->N; 1952 ierr = PetscMalloc3(cM*cN,&atb->sendbuf,cM*cN,&atb->atbarray,size,&atb->recvcounts);CHKERRQ(ierr); 1953 1954 c = (Mat_MPIDense*)Cdense->data; 1955 c->atbdense = atb; 1956 atb->destroy = Cdense->ops->destroy; 1957 Cdense->ops->destroy = MatDestroy_MatTransMatMult_MPIDense_MPIDense; 1958 PetscFunctionReturn(0); 1959 } 1960 1961 PetscErrorCode MatTransposeMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1962 { 1963 PetscErrorCode ierr; 1964 1965 PetscFunctionBegin; 1966 if (scall == MAT_INITIAL_MATRIX) { 1967 ierr = MatTransposeMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 1968 } 1969 ierr = MatTransposeMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 1970 PetscFunctionReturn(0); 1971 } 1972 1973 PetscErrorCode MatDestroy_MatMatMult_MPIDense_MPIDense(Mat A) 1974 { 1975 PetscErrorCode ierr; 1976 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1977 Mat_MatMultDense *ab = a->abdense; 1978 1979 PetscFunctionBegin; 1980 ierr = MatDestroy(&ab->Ce);CHKERRQ(ierr); 1981 ierr = MatDestroy(&ab->Ae);CHKERRQ(ierr); 1982 ierr = MatDestroy(&ab->Be);CHKERRQ(ierr); 1983 1984 ierr = (ab->destroy)(A);CHKERRQ(ierr); 1985 ierr = PetscFree(ab);CHKERRQ(ierr); 1986 PetscFunctionReturn(0); 1987 } 1988 1989 #if defined(PETSC_HAVE_ELEMENTAL) 1990 PetscErrorCode MatMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 1991 { 1992 PetscErrorCode ierr; 1993 Mat_MPIDense *c=(Mat_MPIDense*)C->data; 1994 Mat_MatMultDense *ab=c->abdense; 1995 1996 PetscFunctionBegin; 1997 ierr = MatConvert_MPIDense_Elemental(A,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Ae);CHKERRQ(ierr); 1998 ierr = MatConvert_MPIDense_Elemental(B,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Be);CHKERRQ(ierr); 1999 ierr = MatMatMultNumeric(ab->Ae,ab->Be,ab->Ce);CHKERRQ(ierr); 2000 ierr = MatConvert(ab->Ce,MATMPIDENSE,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 2001 PetscFunctionReturn(0); 2002 } 2003 2004 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 2005 { 2006 PetscErrorCode ierr; 2007 Mat Ae,Be,Ce; 2008 Mat_MPIDense *c; 2009 Mat_MatMultDense *ab; 2010 2011 PetscFunctionBegin; 2012 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 2013 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); 2014 } 2015 2016 /* convert A and B to Elemental matrices Ae and Be */ 2017 ierr = MatConvert(A,MATELEMENTAL,MAT_INITIAL_MATRIX, &Ae);CHKERRQ(ierr); 2018 ierr = MatConvert(B,MATELEMENTAL,MAT_INITIAL_MATRIX, &Be);CHKERRQ(ierr); 2019 2020 /* Ce = Ae*Be */ 2021 ierr = MatMatMultSymbolic(Ae,Be,fill,&Ce);CHKERRQ(ierr); 2022 ierr = MatMatMultNumeric(Ae,Be,Ce);CHKERRQ(ierr); 2023 2024 /* convert Ce to C */ 2025 ierr = MatConvert(Ce,MATMPIDENSE,MAT_INITIAL_MATRIX,C);CHKERRQ(ierr); 2026 2027 /* create data structure for reuse Cdense */ 2028 ierr = PetscNew(&ab);CHKERRQ(ierr); 2029 c = (Mat_MPIDense*)(*C)->data; 2030 c->abdense = ab; 2031 2032 ab->Ae = Ae; 2033 ab->Be = Be; 2034 ab->Ce = Ce; 2035 ab->destroy = (*C)->ops->destroy; 2036 (*C)->ops->destroy = MatDestroy_MatMatMult_MPIDense_MPIDense; 2037 (*C)->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIDense; 2038 PetscFunctionReturn(0); 2039 } 2040 2041 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2042 { 2043 PetscErrorCode ierr; 2044 2045 PetscFunctionBegin; 2046 if (scall == MAT_INITIAL_MATRIX) { /* simbolic product includes numeric product */ 2047 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2048 ierr = MatMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 2049 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2050 } else { 2051 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2052 ierr = MatMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 2053 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2054 } 2055 PetscFunctionReturn(0); 2056 } 2057 #endif 2058 2059