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 MatDenseGetLDA_MPIDense(Mat A,PetscInt *lda) 148 { 149 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 150 PetscErrorCode ierr; 151 152 PetscFunctionBegin; 153 ierr = MatDenseGetLDA(a->A,lda);CHKERRQ(ierr); 154 PetscFunctionReturn(0); 155 } 156 157 static PetscErrorCode MatDenseGetArray_MPIDense(Mat A,PetscScalar *array[]) 158 { 159 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 160 PetscErrorCode ierr; 161 162 PetscFunctionBegin; 163 ierr = MatDenseGetArray(a->A,array);CHKERRQ(ierr); 164 PetscFunctionReturn(0); 165 } 166 167 static PetscErrorCode MatDenseGetArrayRead_MPIDense(Mat A,const PetscScalar *array[]) 168 { 169 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 170 PetscErrorCode ierr; 171 172 PetscFunctionBegin; 173 ierr = MatDenseGetArrayRead(a->A,array);CHKERRQ(ierr); 174 PetscFunctionReturn(0); 175 } 176 177 static PetscErrorCode MatDensePlaceArray_MPIDense(Mat A,const PetscScalar array[]) 178 { 179 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 180 PetscErrorCode ierr; 181 182 PetscFunctionBegin; 183 ierr = MatDensePlaceArray(a->A,array);CHKERRQ(ierr); 184 PetscFunctionReturn(0); 185 } 186 187 static PetscErrorCode MatDenseResetArray_MPIDense(Mat A) 188 { 189 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 190 PetscErrorCode ierr; 191 192 PetscFunctionBegin; 193 ierr = MatDenseResetArray(a->A);CHKERRQ(ierr); 194 PetscFunctionReturn(0); 195 } 196 197 static PetscErrorCode MatCreateSubMatrix_MPIDense(Mat A,IS isrow,IS iscol,MatReuse scall,Mat *B) 198 { 199 Mat_MPIDense *mat = (Mat_MPIDense*)A->data,*newmatd; 200 Mat_SeqDense *lmat = (Mat_SeqDense*)mat->A->data; 201 PetscErrorCode ierr; 202 PetscInt i,j,rstart,rend,nrows,ncols,Ncols,nlrows,nlcols; 203 const PetscInt *irow,*icol; 204 PetscScalar *av,*bv,*v = lmat->v; 205 Mat newmat; 206 IS iscol_local; 207 MPI_Comm comm_is,comm_mat; 208 209 PetscFunctionBegin; 210 ierr = PetscObjectGetComm((PetscObject)A,&comm_mat);CHKERRQ(ierr); 211 ierr = PetscObjectGetComm((PetscObject)iscol,&comm_is);CHKERRQ(ierr); 212 if (comm_mat != comm_is) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMECOMM,"IS communicator must match matrix communicator"); 213 214 ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr); 215 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 216 ierr = ISGetIndices(iscol_local,&icol);CHKERRQ(ierr); 217 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 218 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 219 ierr = ISGetSize(iscol,&Ncols);CHKERRQ(ierr); /* global number of columns, size of iscol_local */ 220 221 /* No parallel redistribution currently supported! Should really check each index set 222 to comfirm that it is OK. ... Currently supports only submatrix same partitioning as 223 original matrix! */ 224 225 ierr = MatGetLocalSize(A,&nlrows,&nlcols);CHKERRQ(ierr); 226 ierr = MatGetOwnershipRange(A,&rstart,&rend);CHKERRQ(ierr); 227 228 /* Check submatrix call */ 229 if (scall == MAT_REUSE_MATRIX) { 230 /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); */ 231 /* Really need to test rows and column sizes! */ 232 newmat = *B; 233 } else { 234 /* Create and fill new matrix */ 235 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 236 ierr = MatSetSizes(newmat,nrows,ncols,PETSC_DECIDE,Ncols);CHKERRQ(ierr); 237 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 238 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 239 } 240 241 /* Now extract the data pointers and do the copy, column at a time */ 242 newmatd = (Mat_MPIDense*)newmat->data; 243 bv = ((Mat_SeqDense*)newmatd->A->data)->v; 244 245 for (i=0; i<Ncols; i++) { 246 av = v + ((Mat_SeqDense*)mat->A->data)->lda*icol[i]; 247 for (j=0; j<nrows; j++) { 248 *bv++ = av[irow[j] - rstart]; 249 } 250 } 251 252 /* Assemble the matrices so that the correct flags are set */ 253 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 254 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 255 256 /* Free work space */ 257 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 258 ierr = ISRestoreIndices(iscol_local,&icol);CHKERRQ(ierr); 259 ierr = ISDestroy(&iscol_local);CHKERRQ(ierr); 260 *B = newmat; 261 PetscFunctionReturn(0); 262 } 263 264 PetscErrorCode MatDenseRestoreArray_MPIDense(Mat A,PetscScalar *array[]) 265 { 266 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 267 PetscErrorCode ierr; 268 269 PetscFunctionBegin; 270 ierr = MatDenseRestoreArray(a->A,array);CHKERRQ(ierr); 271 PetscFunctionReturn(0); 272 } 273 274 PetscErrorCode MatDenseRestoreArrayRead_MPIDense(Mat A,const PetscScalar *array[]) 275 { 276 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 277 PetscErrorCode ierr; 278 279 PetscFunctionBegin; 280 ierr = MatDenseRestoreArrayRead(a->A,array);CHKERRQ(ierr); 281 PetscFunctionReturn(0); 282 } 283 284 PetscErrorCode MatAssemblyBegin_MPIDense(Mat mat,MatAssemblyType mode) 285 { 286 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 287 MPI_Comm comm; 288 PetscErrorCode ierr; 289 PetscInt nstash,reallocs; 290 InsertMode addv; 291 292 PetscFunctionBegin; 293 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 294 /* make sure all processors are either in INSERTMODE or ADDMODE */ 295 ierr = MPIU_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,comm);CHKERRQ(ierr); 296 if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Cannot mix adds/inserts on different procs"); 297 mat->insertmode = addv; /* in case this processor had no cache */ 298 299 ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr); 300 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 301 ierr = PetscInfo2(mdn->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr); 302 PetscFunctionReturn(0); 303 } 304 305 PetscErrorCode MatAssemblyEnd_MPIDense(Mat mat,MatAssemblyType mode) 306 { 307 Mat_MPIDense *mdn=(Mat_MPIDense*)mat->data; 308 PetscErrorCode ierr; 309 PetscInt i,*row,*col,flg,j,rstart,ncols; 310 PetscMPIInt n; 311 PetscScalar *val; 312 313 PetscFunctionBegin; 314 /* wait on receives */ 315 while (1) { 316 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 317 if (!flg) break; 318 319 for (i=0; i<n;) { 320 /* Now identify the consecutive vals belonging to the same row */ 321 for (j=i,rstart=row[j]; j<n; j++) { 322 if (row[j] != rstart) break; 323 } 324 if (j < n) ncols = j-i; 325 else ncols = n-i; 326 /* Now assemble all these values with a single function call */ 327 ierr = MatSetValues_MPIDense(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);CHKERRQ(ierr); 328 i = j; 329 } 330 } 331 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 332 333 ierr = MatAssemblyBegin(mdn->A,mode);CHKERRQ(ierr); 334 ierr = MatAssemblyEnd(mdn->A,mode);CHKERRQ(ierr); 335 336 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 337 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 338 } 339 PetscFunctionReturn(0); 340 } 341 342 PetscErrorCode MatZeroEntries_MPIDense(Mat A) 343 { 344 PetscErrorCode ierr; 345 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 346 347 PetscFunctionBegin; 348 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 349 PetscFunctionReturn(0); 350 } 351 352 /* the code does not do the diagonal entries correctly unless the 353 matrix is square and the column and row owerships are identical. 354 This is a BUG. The only way to fix it seems to be to access 355 mdn->A and mdn->B directly and not through the MatZeroRows() 356 routine. 357 */ 358 PetscErrorCode MatZeroRows_MPIDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 359 { 360 Mat_MPIDense *l = (Mat_MPIDense*)A->data; 361 PetscErrorCode ierr; 362 PetscInt i,*owners = A->rmap->range; 363 PetscInt *sizes,j,idx,nsends; 364 PetscInt nmax,*svalues,*starts,*owner,nrecvs; 365 PetscInt *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source; 366 PetscInt *lens,*lrows,*values; 367 PetscMPIInt n,imdex,rank = l->rank,size = l->size; 368 MPI_Comm comm; 369 MPI_Request *send_waits,*recv_waits; 370 MPI_Status recv_status,*send_status; 371 PetscBool found; 372 const PetscScalar *xx; 373 PetscScalar *bb; 374 375 PetscFunctionBegin; 376 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 377 if (A->rmap->N != A->cmap->N) SETERRQ(comm,PETSC_ERR_SUP,"Only handles square matrices"); 378 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only handles matrices with identical column and row ownership"); 379 /* first count number of contributors to each processor */ 380 ierr = PetscCalloc1(2*size,&sizes);CHKERRQ(ierr); 381 ierr = PetscMalloc1(N+1,&owner);CHKERRQ(ierr); /* see note*/ 382 for (i=0; i<N; i++) { 383 idx = rows[i]; 384 found = PETSC_FALSE; 385 for (j=0; j<size; j++) { 386 if (idx >= owners[j] && idx < owners[j+1]) { 387 sizes[2*j]++; sizes[2*j+1] = 1; owner[i] = j; found = PETSC_TRUE; break; 388 } 389 } 390 if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 391 } 392 nsends = 0; 393 for (i=0; i<size; i++) nsends += sizes[2*i+1]; 394 395 /* inform other processors of number of messages and max length*/ 396 ierr = PetscMaxSum(comm,sizes,&nmax,&nrecvs);CHKERRQ(ierr); 397 398 /* post receives: */ 399 ierr = PetscMalloc1((nrecvs+1)*(nmax+1),&rvalues);CHKERRQ(ierr); 400 ierr = PetscMalloc1(nrecvs+1,&recv_waits);CHKERRQ(ierr); 401 for (i=0; i<nrecvs; i++) { 402 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 403 } 404 405 /* do sends: 406 1) starts[i] gives the starting index in svalues for stuff going to 407 the ith processor 408 */ 409 ierr = PetscMalloc1(N+1,&svalues);CHKERRQ(ierr); 410 ierr = PetscMalloc1(nsends+1,&send_waits);CHKERRQ(ierr); 411 ierr = PetscMalloc1(size+1,&starts);CHKERRQ(ierr); 412 413 starts[0] = 0; 414 for (i=1; i<size; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 415 for (i=0; i<N; i++) svalues[starts[owner[i]]++] = rows[i]; 416 417 starts[0] = 0; 418 for (i=1; i<size+1; i++) starts[i] = starts[i-1] + sizes[2*i-2]; 419 count = 0; 420 for (i=0; i<size; i++) { 421 if (sizes[2*i+1]) { 422 ierr = MPI_Isend(svalues+starts[i],sizes[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 423 } 424 } 425 ierr = PetscFree(starts);CHKERRQ(ierr); 426 427 base = owners[rank]; 428 429 /* wait on receives */ 430 ierr = PetscMalloc2(nrecvs,&lens,nrecvs,&source);CHKERRQ(ierr); 431 count = nrecvs; 432 slen = 0; 433 while (count) { 434 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 435 /* unpack receives into our local space */ 436 ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr); 437 438 source[imdex] = recv_status.MPI_SOURCE; 439 lens[imdex] = n; 440 slen += n; 441 count--; 442 } 443 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 444 445 /* move the data into the send scatter */ 446 ierr = PetscMalloc1(slen+1,&lrows);CHKERRQ(ierr); 447 count = 0; 448 for (i=0; i<nrecvs; i++) { 449 values = rvalues + i*nmax; 450 for (j=0; j<lens[i]; j++) { 451 lrows[count++] = values[j] - base; 452 } 453 } 454 ierr = PetscFree(rvalues);CHKERRQ(ierr); 455 ierr = PetscFree2(lens,source);CHKERRQ(ierr); 456 ierr = PetscFree(owner);CHKERRQ(ierr); 457 ierr = PetscFree(sizes);CHKERRQ(ierr); 458 459 /* fix right hand side if needed */ 460 if (x && b) { 461 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 462 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 463 for (i=0; i<slen; i++) { 464 bb[lrows[i]] = diag*xx[lrows[i]]; 465 } 466 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 467 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 468 } 469 470 /* actually zap the local rows */ 471 ierr = MatZeroRows(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr); 472 if (diag != 0.0) { 473 Mat_SeqDense *ll = (Mat_SeqDense*)l->A->data; 474 PetscInt m = ll->lda, i; 475 476 for (i=0; i<slen; i++) { 477 ll->v[lrows[i] + m*(A->cmap->rstart + lrows[i])] = diag; 478 } 479 } 480 ierr = PetscFree(lrows);CHKERRQ(ierr); 481 482 /* wait on sends */ 483 if (nsends) { 484 ierr = PetscMalloc1(nsends,&send_status);CHKERRQ(ierr); 485 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 486 ierr = PetscFree(send_status);CHKERRQ(ierr); 487 } 488 ierr = PetscFree(send_waits);CHKERRQ(ierr); 489 ierr = PetscFree(svalues);CHKERRQ(ierr); 490 PetscFunctionReturn(0); 491 } 492 493 PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat,Vec,Vec); 494 PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat,Vec,Vec,Vec); 495 PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat,Vec,Vec); 496 PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqDense(Mat,Vec,Vec,Vec); 497 498 PetscErrorCode MatMult_MPIDense(Mat mat,Vec xx,Vec yy) 499 { 500 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 501 PetscErrorCode ierr; 502 503 PetscFunctionBegin; 504 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 505 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 506 ierr = MatMult_SeqDense(mdn->A,mdn->lvec,yy);CHKERRQ(ierr); 507 PetscFunctionReturn(0); 508 } 509 510 PetscErrorCode MatMultAdd_MPIDense(Mat mat,Vec xx,Vec yy,Vec zz) 511 { 512 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 513 PetscErrorCode ierr; 514 515 PetscFunctionBegin; 516 ierr = VecScatterBegin(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 517 ierr = VecScatterEnd(mdn->Mvctx,xx,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 518 ierr = MatMultAdd_SeqDense(mdn->A,mdn->lvec,yy,zz);CHKERRQ(ierr); 519 PetscFunctionReturn(0); 520 } 521 522 PetscErrorCode MatMultTranspose_MPIDense(Mat A,Vec xx,Vec yy) 523 { 524 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 525 PetscErrorCode ierr; 526 PetscScalar zero = 0.0; 527 528 PetscFunctionBegin; 529 ierr = VecSet(yy,zero);CHKERRQ(ierr); 530 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 531 ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 532 ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 533 PetscFunctionReturn(0); 534 } 535 536 PetscErrorCode MatMultTransposeAdd_MPIDense(Mat A,Vec xx,Vec yy,Vec zz) 537 { 538 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 539 PetscErrorCode ierr; 540 541 PetscFunctionBegin; 542 ierr = VecCopy(yy,zz);CHKERRQ(ierr); 543 ierr = MatMultTranspose_SeqDense(a->A,xx,a->lvec);CHKERRQ(ierr); 544 ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 545 ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 546 PetscFunctionReturn(0); 547 } 548 549 PetscErrorCode MatGetDiagonal_MPIDense(Mat A,Vec v) 550 { 551 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 552 Mat_SeqDense *aloc = (Mat_SeqDense*)a->A->data; 553 PetscErrorCode ierr; 554 PetscInt len,i,n,m = A->rmap->n,radd; 555 PetscScalar *x,zero = 0.0; 556 557 PetscFunctionBegin; 558 ierr = VecSet(v,zero);CHKERRQ(ierr); 559 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 560 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 561 if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 562 len = PetscMin(a->A->rmap->n,a->A->cmap->n); 563 radd = A->rmap->rstart*m; 564 for (i=0; i<len; i++) { 565 x[i] = aloc->v[radd + i*m + i]; 566 } 567 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 568 PetscFunctionReturn(0); 569 } 570 571 PetscErrorCode MatDestroy_MPIDense(Mat mat) 572 { 573 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 574 PetscErrorCode ierr; 575 576 PetscFunctionBegin; 577 #if defined(PETSC_USE_LOG) 578 PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N); 579 #endif 580 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 581 ierr = MatDestroy(&mdn->A);CHKERRQ(ierr); 582 ierr = VecDestroy(&mdn->lvec);CHKERRQ(ierr); 583 ierr = VecScatterDestroy(&mdn->Mvctx);CHKERRQ(ierr); 584 585 ierr = PetscFree(mat->data);CHKERRQ(ierr); 586 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 587 588 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetLDA_C",NULL);CHKERRQ(ierr); 589 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 590 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 591 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArrayRead_C",NULL);CHKERRQ(ierr); 592 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArrayRead_C",NULL);CHKERRQ(ierr); 593 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);CHKERRQ(ierr); 594 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);CHKERRQ(ierr); 595 #if defined(PETSC_HAVE_ELEMENTAL) 596 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",NULL);CHKERRQ(ierr); 597 #endif 598 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 599 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 600 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 601 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 602 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 603 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 604 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",NULL);CHKERRQ(ierr); 605 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",NULL);CHKERRQ(ierr); 606 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",NULL);CHKERRQ(ierr); 607 PetscFunctionReturn(0); 608 } 609 610 static PetscErrorCode MatView_MPIDense_Binary(Mat mat,PetscViewer viewer) 611 { 612 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 613 PetscErrorCode ierr; 614 PetscViewerFormat format; 615 int fd; 616 PetscInt header[4],mmax,N = mat->cmap->N,i,j,m,k; 617 PetscMPIInt rank,tag = ((PetscObject)viewer)->tag,size; 618 PetscScalar *work,*v,*vv; 619 Mat_SeqDense *a = (Mat_SeqDense*)mdn->A->data; 620 621 PetscFunctionBegin; 622 if (mdn->size == 1) { 623 ierr = MatView(mdn->A,viewer);CHKERRQ(ierr); 624 } else { 625 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 626 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr); 627 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 628 629 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 630 if (format == PETSC_VIEWER_NATIVE) { 631 632 if (!rank) { 633 /* store the matrix as a dense matrix */ 634 header[0] = MAT_FILE_CLASSID; 635 header[1] = mat->rmap->N; 636 header[2] = N; 637 header[3] = MATRIX_BINARY_FORMAT_DENSE; 638 ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 639 640 /* get largest work array needed for transposing array */ 641 mmax = mat->rmap->n; 642 for (i=1; i<size; i++) { 643 mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]); 644 } 645 ierr = PetscMalloc1(mmax*N,&work);CHKERRQ(ierr); 646 647 /* write out local array, by rows */ 648 m = mat->rmap->n; 649 v = a->v; 650 for (j=0; j<N; j++) { 651 for (i=0; i<m; i++) { 652 work[j + i*N] = *v++; 653 } 654 } 655 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 656 /* get largest work array to receive messages from other processes, excludes process zero */ 657 mmax = 0; 658 for (i=1; i<size; i++) { 659 mmax = PetscMax(mmax,mat->rmap->range[i+1] - mat->rmap->range[i]); 660 } 661 ierr = PetscMalloc1(mmax*N,&vv);CHKERRQ(ierr); 662 for (k = 1; k < size; k++) { 663 v = vv; 664 m = mat->rmap->range[k+1] - mat->rmap->range[k]; 665 ierr = MPIULong_Recv(v,m*N,MPIU_SCALAR,k,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 666 667 for (j = 0; j < N; j++) { 668 for (i = 0; i < m; i++) { 669 work[j + i*N] = *v++; 670 } 671 } 672 ierr = PetscBinaryWrite(fd,work,m*N,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 673 } 674 ierr = PetscFree(work);CHKERRQ(ierr); 675 ierr = PetscFree(vv);CHKERRQ(ierr); 676 } else { 677 ierr = MPIULong_Send(a->v,mat->rmap->n*mat->cmap->N,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 678 } 679 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"To store a parallel dense matrix you must first call PetscViewerPushFormat(viewer,PETSC_VIEWER_NATIVE)"); 680 } 681 PetscFunctionReturn(0); 682 } 683 684 extern PetscErrorCode MatView_SeqDense(Mat,PetscViewer); 685 #include <petscdraw.h> 686 static PetscErrorCode MatView_MPIDense_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 687 { 688 Mat_MPIDense *mdn = (Mat_MPIDense*)mat->data; 689 PetscErrorCode ierr; 690 PetscMPIInt rank = mdn->rank; 691 PetscViewerType vtype; 692 PetscBool iascii,isdraw; 693 PetscViewer sviewer; 694 PetscViewerFormat format; 695 696 PetscFunctionBegin; 697 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 698 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 699 if (iascii) { 700 ierr = PetscViewerGetType(viewer,&vtype);CHKERRQ(ierr); 701 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 702 if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 703 MatInfo info; 704 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 705 ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); 706 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); 707 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 708 ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr); 709 ierr = VecScatterView(mdn->Mvctx,viewer);CHKERRQ(ierr); 710 PetscFunctionReturn(0); 711 } else if (format == PETSC_VIEWER_ASCII_INFO) { 712 PetscFunctionReturn(0); 713 } 714 } else if (isdraw) { 715 PetscDraw draw; 716 PetscBool isnull; 717 718 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 719 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 720 if (isnull) PetscFunctionReturn(0); 721 } 722 723 { 724 /* assemble the entire matrix onto first processor. */ 725 Mat A; 726 PetscInt M = mat->rmap->N,N = mat->cmap->N,m,row,i,nz; 727 PetscInt *cols; 728 PetscScalar *vals; 729 730 ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr); 731 if (!rank) { 732 ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr); 733 } else { 734 ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr); 735 } 736 /* Since this is a temporary matrix, MATMPIDENSE instead of ((PetscObject)A)->type_name here is probably acceptable. */ 737 ierr = MatSetType(A,MATMPIDENSE);CHKERRQ(ierr); 738 ierr = MatMPIDenseSetPreallocation(A,NULL);CHKERRQ(ierr); 739 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr); 740 741 /* Copy the matrix ... This isn't the most efficient means, 742 but it's quick for now */ 743 A->insertmode = INSERT_VALUES; 744 745 row = mat->rmap->rstart; 746 m = mdn->A->rmap->n; 747 for (i=0; i<m; i++) { 748 ierr = MatGetRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 749 ierr = MatSetValues_MPIDense(A,1,&row,nz,cols,vals,INSERT_VALUES);CHKERRQ(ierr); 750 ierr = MatRestoreRow_MPIDense(mat,row,&nz,&cols,&vals);CHKERRQ(ierr); 751 row++; 752 } 753 754 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 755 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 756 ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 757 if (!rank) { 758 ierr = PetscObjectSetName((PetscObject)((Mat_MPIDense*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr); 759 ierr = MatView_SeqDense(((Mat_MPIDense*)(A->data))->A,sviewer);CHKERRQ(ierr); 760 } 761 ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr); 762 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 763 ierr = MatDestroy(&A);CHKERRQ(ierr); 764 } 765 PetscFunctionReturn(0); 766 } 767 768 PetscErrorCode MatView_MPIDense(Mat mat,PetscViewer viewer) 769 { 770 PetscErrorCode ierr; 771 PetscBool iascii,isbinary,isdraw,issocket; 772 773 PetscFunctionBegin; 774 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 775 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 776 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr); 777 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 778 779 if (iascii || issocket || isdraw) { 780 ierr = MatView_MPIDense_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 781 } else if (isbinary) { 782 ierr = MatView_MPIDense_Binary(mat,viewer);CHKERRQ(ierr); 783 } 784 PetscFunctionReturn(0); 785 } 786 787 PetscErrorCode MatGetInfo_MPIDense(Mat A,MatInfoType flag,MatInfo *info) 788 { 789 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 790 Mat mdn = mat->A; 791 PetscErrorCode ierr; 792 PetscReal isend[5],irecv[5]; 793 794 PetscFunctionBegin; 795 info->block_size = 1.0; 796 797 ierr = MatGetInfo(mdn,MAT_LOCAL,info);CHKERRQ(ierr); 798 799 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 800 isend[3] = info->memory; isend[4] = info->mallocs; 801 if (flag == MAT_LOCAL) { 802 info->nz_used = isend[0]; 803 info->nz_allocated = isend[1]; 804 info->nz_unneeded = isend[2]; 805 info->memory = isend[3]; 806 info->mallocs = isend[4]; 807 } else if (flag == MAT_GLOBAL_MAX) { 808 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 809 810 info->nz_used = irecv[0]; 811 info->nz_allocated = irecv[1]; 812 info->nz_unneeded = irecv[2]; 813 info->memory = irecv[3]; 814 info->mallocs = irecv[4]; 815 } else if (flag == MAT_GLOBAL_SUM) { 816 ierr = MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 817 818 info->nz_used = irecv[0]; 819 info->nz_allocated = irecv[1]; 820 info->nz_unneeded = irecv[2]; 821 info->memory = irecv[3]; 822 info->mallocs = irecv[4]; 823 } 824 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 825 info->fill_ratio_needed = 0; 826 info->factor_mallocs = 0; 827 PetscFunctionReturn(0); 828 } 829 830 PetscErrorCode MatSetOption_MPIDense(Mat A,MatOption op,PetscBool flg) 831 { 832 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 833 PetscErrorCode ierr; 834 835 PetscFunctionBegin; 836 switch (op) { 837 case MAT_NEW_NONZERO_LOCATIONS: 838 case MAT_NEW_NONZERO_LOCATION_ERR: 839 case MAT_NEW_NONZERO_ALLOCATION_ERR: 840 MatCheckPreallocated(A,1); 841 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 842 break; 843 case MAT_ROW_ORIENTED: 844 MatCheckPreallocated(A,1); 845 a->roworiented = flg; 846 ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr); 847 break; 848 case MAT_NEW_DIAGONALS: 849 case MAT_KEEP_NONZERO_PATTERN: 850 case MAT_USE_HASH_TABLE: 851 case MAT_SORTED_FULL: 852 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 853 break; 854 case MAT_IGNORE_OFF_PROC_ENTRIES: 855 a->donotstash = flg; 856 break; 857 case MAT_SYMMETRIC: 858 case MAT_STRUCTURALLY_SYMMETRIC: 859 case MAT_HERMITIAN: 860 case MAT_SYMMETRY_ETERNAL: 861 case MAT_IGNORE_LOWER_TRIANGULAR: 862 case MAT_IGNORE_ZERO_ENTRIES: 863 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 864 break; 865 default: 866 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 867 } 868 PetscFunctionReturn(0); 869 } 870 871 872 PetscErrorCode MatDiagonalScale_MPIDense(Mat A,Vec ll,Vec rr) 873 { 874 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 875 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 876 const PetscScalar *l,*r; 877 PetscScalar x,*v; 878 PetscErrorCode ierr; 879 PetscInt i,j,s2a,s3a,s2,s3,m=mdn->A->rmap->n,n=mdn->A->cmap->n; 880 881 PetscFunctionBegin; 882 ierr = MatGetLocalSize(A,&s2,&s3);CHKERRQ(ierr); 883 if (ll) { 884 ierr = VecGetLocalSize(ll,&s2a);CHKERRQ(ierr); 885 if (s2a != s2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector non-conforming local size, %d != %d.", s2a, s2); 886 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 887 for (i=0; i<m; i++) { 888 x = l[i]; 889 v = mat->v + i; 890 for (j=0; j<n; j++) { (*v) *= x; v+= m;} 891 } 892 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 893 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 894 } 895 if (rr) { 896 ierr = VecGetLocalSize(rr,&s3a);CHKERRQ(ierr); 897 if (s3a != s3) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec non-conforming local size, %d != %d.", s3a, s3); 898 ierr = VecScatterBegin(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 899 ierr = VecScatterEnd(mdn->Mvctx,rr,mdn->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 900 ierr = VecGetArrayRead(mdn->lvec,&r);CHKERRQ(ierr); 901 for (i=0; i<n; i++) { 902 x = r[i]; 903 v = mat->v + i*m; 904 for (j=0; j<m; j++) (*v++) *= x; 905 } 906 ierr = VecRestoreArrayRead(mdn->lvec,&r);CHKERRQ(ierr); 907 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 908 } 909 PetscFunctionReturn(0); 910 } 911 912 PetscErrorCode MatNorm_MPIDense(Mat A,NormType type,PetscReal *nrm) 913 { 914 Mat_MPIDense *mdn = (Mat_MPIDense*)A->data; 915 Mat_SeqDense *mat = (Mat_SeqDense*)mdn->A->data; 916 PetscErrorCode ierr; 917 PetscInt i,j; 918 PetscReal sum = 0.0; 919 PetscScalar *v = mat->v; 920 921 PetscFunctionBegin; 922 if (mdn->size == 1) { 923 ierr = MatNorm(mdn->A,type,nrm);CHKERRQ(ierr); 924 } else { 925 if (type == NORM_FROBENIUS) { 926 for (i=0; i<mdn->A->cmap->n*mdn->A->rmap->n; i++) { 927 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 928 } 929 ierr = MPIU_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 930 *nrm = PetscSqrtReal(*nrm); 931 ierr = PetscLogFlops(2.0*mdn->A->cmap->n*mdn->A->rmap->n);CHKERRQ(ierr); 932 } else if (type == NORM_1) { 933 PetscReal *tmp,*tmp2; 934 ierr = PetscCalloc2(A->cmap->N,&tmp,A->cmap->N,&tmp2);CHKERRQ(ierr); 935 *nrm = 0.0; 936 v = mat->v; 937 for (j=0; j<mdn->A->cmap->n; j++) { 938 for (i=0; i<mdn->A->rmap->n; i++) { 939 tmp[j] += PetscAbsScalar(*v); v++; 940 } 941 } 942 ierr = MPIU_Allreduce(tmp,tmp2,A->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 943 for (j=0; j<A->cmap->N; j++) { 944 if (tmp2[j] > *nrm) *nrm = tmp2[j]; 945 } 946 ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr); 947 ierr = PetscLogFlops(A->cmap->n*A->rmap->n);CHKERRQ(ierr); 948 } else if (type == NORM_INFINITY) { /* max row norm */ 949 PetscReal ntemp; 950 ierr = MatNorm(mdn->A,type,&ntemp);CHKERRQ(ierr); 951 ierr = MPIU_Allreduce(&ntemp,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 952 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"No support for two norm"); 953 } 954 PetscFunctionReturn(0); 955 } 956 957 PetscErrorCode MatTranspose_MPIDense(Mat A,MatReuse reuse,Mat *matout) 958 { 959 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 960 Mat_SeqDense *Aloc = (Mat_SeqDense*)a->A->data; 961 Mat B; 962 PetscInt M = A->rmap->N,N = A->cmap->N,m,n,*rwork,rstart = A->rmap->rstart; 963 PetscErrorCode ierr; 964 PetscInt j,i; 965 PetscScalar *v; 966 967 PetscFunctionBegin; 968 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 969 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 970 ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr); 971 ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); 972 ierr = MatMPIDenseSetPreallocation(B,NULL);CHKERRQ(ierr); 973 } else { 974 B = *matout; 975 } 976 977 m = a->A->rmap->n; n = a->A->cmap->n; v = Aloc->v; 978 ierr = PetscMalloc1(m,&rwork);CHKERRQ(ierr); 979 for (i=0; i<m; i++) rwork[i] = rstart + i; 980 for (j=0; j<n; j++) { 981 ierr = MatSetValues(B,1,&j,m,rwork,v,INSERT_VALUES);CHKERRQ(ierr); 982 v += m; 983 } 984 ierr = PetscFree(rwork);CHKERRQ(ierr); 985 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 986 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 987 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 988 *matout = B; 989 } else { 990 ierr = MatHeaderMerge(A,&B);CHKERRQ(ierr); 991 } 992 PetscFunctionReturn(0); 993 } 994 995 996 static PetscErrorCode MatDuplicate_MPIDense(Mat,MatDuplicateOption,Mat*); 997 extern PetscErrorCode MatScale_MPIDense(Mat,PetscScalar); 998 999 PetscErrorCode MatSetUp_MPIDense(Mat A) 1000 { 1001 PetscErrorCode ierr; 1002 1003 PetscFunctionBegin; 1004 ierr = MatMPIDenseSetPreallocation(A,0);CHKERRQ(ierr); 1005 PetscFunctionReturn(0); 1006 } 1007 1008 PetscErrorCode MatAXPY_MPIDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str) 1009 { 1010 PetscErrorCode ierr; 1011 Mat_MPIDense *A = (Mat_MPIDense*)Y->data, *B = (Mat_MPIDense*)X->data; 1012 1013 PetscFunctionBegin; 1014 ierr = MatAXPY(A->A,alpha,B->A,str);CHKERRQ(ierr); 1015 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 1016 PetscFunctionReturn(0); 1017 } 1018 1019 PetscErrorCode MatConjugate_MPIDense(Mat mat) 1020 { 1021 Mat_MPIDense *a = (Mat_MPIDense*)mat->data; 1022 PetscErrorCode ierr; 1023 1024 PetscFunctionBegin; 1025 ierr = MatConjugate(a->A);CHKERRQ(ierr); 1026 PetscFunctionReturn(0); 1027 } 1028 1029 PetscErrorCode MatRealPart_MPIDense(Mat A) 1030 { 1031 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1032 PetscErrorCode ierr; 1033 1034 PetscFunctionBegin; 1035 ierr = MatRealPart(a->A);CHKERRQ(ierr); 1036 PetscFunctionReturn(0); 1037 } 1038 1039 PetscErrorCode MatImaginaryPart_MPIDense(Mat A) 1040 { 1041 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1042 PetscErrorCode ierr; 1043 1044 PetscFunctionBegin; 1045 ierr = MatImaginaryPart(a->A);CHKERRQ(ierr); 1046 PetscFunctionReturn(0); 1047 } 1048 1049 static PetscErrorCode MatGetColumnVector_MPIDense(Mat A,Vec v,PetscInt col) 1050 { 1051 PetscErrorCode ierr; 1052 PetscScalar *x; 1053 const PetscScalar *a; 1054 PetscInt lda; 1055 1056 PetscFunctionBegin; 1057 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1058 ierr = MatDenseGetLDA(A,&lda);CHKERRQ(ierr); 1059 ierr = MatDenseGetArrayRead(A,&a);CHKERRQ(ierr); 1060 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1061 ierr = PetscArraycpy(x,a+col*lda,A->rmap->n);CHKERRQ(ierr); 1062 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1063 ierr = MatDenseGetArrayRead(A,&a);CHKERRQ(ierr); 1064 PetscFunctionReturn(0); 1065 } 1066 1067 extern PetscErrorCode MatGetColumnNorms_SeqDense(Mat,NormType,PetscReal*); 1068 PetscErrorCode MatGetColumnNorms_MPIDense(Mat A,NormType type,PetscReal *norms) 1069 { 1070 PetscErrorCode ierr; 1071 PetscInt i,n; 1072 Mat_MPIDense *a = (Mat_MPIDense*) A->data; 1073 PetscReal *work; 1074 1075 PetscFunctionBegin; 1076 ierr = MatGetSize(A,NULL,&n);CHKERRQ(ierr); 1077 ierr = PetscMalloc1(n,&work);CHKERRQ(ierr); 1078 ierr = MatGetColumnNorms_SeqDense(a->A,type,work);CHKERRQ(ierr); 1079 if (type == NORM_2) { 1080 for (i=0; i<n; i++) work[i] *= work[i]; 1081 } 1082 if (type == NORM_INFINITY) { 1083 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,A->hdr.comm);CHKERRQ(ierr); 1084 } else { 1085 ierr = MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,A->hdr.comm);CHKERRQ(ierr); 1086 } 1087 ierr = PetscFree(work);CHKERRQ(ierr); 1088 if (type == NORM_2) { 1089 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 1090 } 1091 PetscFunctionReturn(0); 1092 } 1093 1094 static PetscErrorCode MatSetRandom_MPIDense(Mat x,PetscRandom rctx) 1095 { 1096 Mat_MPIDense *d = (Mat_MPIDense*)x->data; 1097 PetscErrorCode ierr; 1098 PetscScalar *a; 1099 PetscInt m,n,i; 1100 1101 PetscFunctionBegin; 1102 ierr = MatGetSize(d->A,&m,&n);CHKERRQ(ierr); 1103 ierr = MatDenseGetArray(d->A,&a);CHKERRQ(ierr); 1104 for (i=0; i<m*n; i++) { 1105 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 1106 } 1107 ierr = MatDenseRestoreArray(d->A,&a);CHKERRQ(ierr); 1108 PetscFunctionReturn(0); 1109 } 1110 1111 extern PetscErrorCode MatMatMultNumeric_MPIDense(Mat A,Mat,Mat); 1112 1113 static PetscErrorCode MatMissingDiagonal_MPIDense(Mat A,PetscBool *missing,PetscInt *d) 1114 { 1115 PetscFunctionBegin; 1116 *missing = PETSC_FALSE; 1117 PetscFunctionReturn(0); 1118 } 1119 1120 static PetscErrorCode MatMatTransposeMult_MPIDense_MPIDense(Mat,Mat,MatReuse,PetscReal,Mat*); 1121 static PetscErrorCode MatMatTransposeMultSymbolic_MPIDense_MPIDense(Mat,Mat,PetscReal,Mat*); 1122 static PetscErrorCode MatMatTransposeMultNumeric_MPIDense_MPIDense(Mat,Mat,Mat); 1123 1124 /* -------------------------------------------------------------------*/ 1125 static struct _MatOps MatOps_Values = { MatSetValues_MPIDense, 1126 MatGetRow_MPIDense, 1127 MatRestoreRow_MPIDense, 1128 MatMult_MPIDense, 1129 /* 4*/ MatMultAdd_MPIDense, 1130 MatMultTranspose_MPIDense, 1131 MatMultTransposeAdd_MPIDense, 1132 0, 1133 0, 1134 0, 1135 /* 10*/ 0, 1136 0, 1137 0, 1138 0, 1139 MatTranspose_MPIDense, 1140 /* 15*/ MatGetInfo_MPIDense, 1141 MatEqual_MPIDense, 1142 MatGetDiagonal_MPIDense, 1143 MatDiagonalScale_MPIDense, 1144 MatNorm_MPIDense, 1145 /* 20*/ MatAssemblyBegin_MPIDense, 1146 MatAssemblyEnd_MPIDense, 1147 MatSetOption_MPIDense, 1148 MatZeroEntries_MPIDense, 1149 /* 24*/ MatZeroRows_MPIDense, 1150 0, 1151 0, 1152 0, 1153 0, 1154 /* 29*/ MatSetUp_MPIDense, 1155 0, 1156 0, 1157 MatGetDiagonalBlock_MPIDense, 1158 0, 1159 /* 34*/ MatDuplicate_MPIDense, 1160 0, 1161 0, 1162 0, 1163 0, 1164 /* 39*/ MatAXPY_MPIDense, 1165 MatCreateSubMatrices_MPIDense, 1166 0, 1167 MatGetValues_MPIDense, 1168 0, 1169 /* 44*/ 0, 1170 MatScale_MPIDense, 1171 MatShift_Basic, 1172 0, 1173 0, 1174 /* 49*/ MatSetRandom_MPIDense, 1175 0, 1176 0, 1177 0, 1178 0, 1179 /* 54*/ 0, 1180 0, 1181 0, 1182 0, 1183 0, 1184 /* 59*/ MatCreateSubMatrix_MPIDense, 1185 MatDestroy_MPIDense, 1186 MatView_MPIDense, 1187 0, 1188 0, 1189 /* 64*/ 0, 1190 0, 1191 0, 1192 0, 1193 0, 1194 /* 69*/ 0, 1195 0, 1196 0, 1197 0, 1198 0, 1199 /* 74*/ 0, 1200 0, 1201 0, 1202 0, 1203 0, 1204 /* 79*/ 0, 1205 0, 1206 0, 1207 0, 1208 /* 83*/ MatLoad_MPIDense, 1209 0, 1210 0, 1211 0, 1212 0, 1213 0, 1214 #if defined(PETSC_HAVE_ELEMENTAL) 1215 /* 89*/ MatMatMult_MPIDense_MPIDense, 1216 MatMatMultSymbolic_MPIDense_MPIDense, 1217 #else 1218 /* 89*/ 0, 1219 0, 1220 #endif 1221 MatMatMultNumeric_MPIDense, 1222 0, 1223 0, 1224 /* 94*/ 0, 1225 MatMatTransposeMult_MPIDense_MPIDense, 1226 MatMatTransposeMultSymbolic_MPIDense_MPIDense, 1227 MatMatTransposeMultNumeric_MPIDense_MPIDense, 1228 0, 1229 /* 99*/ 0, 1230 0, 1231 0, 1232 MatConjugate_MPIDense, 1233 0, 1234 /*104*/ 0, 1235 MatRealPart_MPIDense, 1236 MatImaginaryPart_MPIDense, 1237 0, 1238 0, 1239 /*109*/ 0, 1240 0, 1241 0, 1242 MatGetColumnVector_MPIDense, 1243 MatMissingDiagonal_MPIDense, 1244 /*114*/ 0, 1245 0, 1246 0, 1247 0, 1248 0, 1249 /*119*/ 0, 1250 0, 1251 0, 1252 0, 1253 0, 1254 /*124*/ 0, 1255 MatGetColumnNorms_MPIDense, 1256 0, 1257 0, 1258 0, 1259 /*129*/ 0, 1260 MatTransposeMatMult_MPIDense_MPIDense, 1261 MatTransposeMatMultSymbolic_MPIDense_MPIDense, 1262 MatTransposeMatMultNumeric_MPIDense_MPIDense, 1263 0, 1264 /*134*/ 0, 1265 0, 1266 0, 1267 0, 1268 0, 1269 /*139*/ 0, 1270 0, 1271 0, 1272 0, 1273 0, 1274 /*144*/ MatCreateMPIMatConcatenateSeqMat_MPIDense 1275 }; 1276 1277 PetscErrorCode MatMPIDenseSetPreallocation_MPIDense(Mat mat,PetscScalar *data) 1278 { 1279 Mat_MPIDense *a; 1280 PetscErrorCode ierr; 1281 1282 PetscFunctionBegin; 1283 if (mat->preallocated) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Matrix has already been preallocated"); 1284 mat->preallocated = PETSC_TRUE; 1285 /* Note: For now, when data is specified above, this assumes the user correctly 1286 allocates the local dense storage space. We should add error checking. */ 1287 1288 a = (Mat_MPIDense*)mat->data; 1289 ierr = PetscLayoutSetUp(mat->rmap);CHKERRQ(ierr); 1290 ierr = PetscLayoutSetUp(mat->cmap);CHKERRQ(ierr); 1291 a->nvec = mat->cmap->n; 1292 1293 ierr = MatCreate(PETSC_COMM_SELF,&a->A);CHKERRQ(ierr); 1294 ierr = MatSetSizes(a->A,mat->rmap->n,mat->cmap->N,mat->rmap->n,mat->cmap->N);CHKERRQ(ierr); 1295 ierr = MatSetType(a->A,MATSEQDENSE);CHKERRQ(ierr); 1296 ierr = MatSeqDenseSetPreallocation(a->A,data);CHKERRQ(ierr); 1297 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1298 PetscFunctionReturn(0); 1299 } 1300 1301 #if defined(PETSC_HAVE_ELEMENTAL) 1302 PETSC_INTERN PetscErrorCode MatConvert_MPIDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 1303 { 1304 Mat mat_elemental; 1305 PetscErrorCode ierr; 1306 PetscScalar *v; 1307 PetscInt m=A->rmap->n,N=A->cmap->N,rstart=A->rmap->rstart,i,*rows,*cols; 1308 1309 PetscFunctionBegin; 1310 if (reuse == MAT_REUSE_MATRIX) { 1311 mat_elemental = *newmat; 1312 ierr = MatZeroEntries(*newmat);CHKERRQ(ierr); 1313 } else { 1314 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 1315 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1316 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 1317 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 1318 ierr = MatSetOption(mat_elemental,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr); 1319 } 1320 1321 ierr = PetscMalloc2(m,&rows,N,&cols);CHKERRQ(ierr); 1322 for (i=0; i<N; i++) cols[i] = i; 1323 for (i=0; i<m; i++) rows[i] = rstart + i; 1324 1325 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 1326 ierr = MatDenseGetArray(A,&v);CHKERRQ(ierr); 1327 ierr = MatSetValues(mat_elemental,m,rows,N,cols,v,ADD_VALUES);CHKERRQ(ierr); 1328 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1329 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1330 ierr = MatDenseRestoreArray(A,&v);CHKERRQ(ierr); 1331 ierr = PetscFree2(rows,cols);CHKERRQ(ierr); 1332 1333 if (reuse == MAT_INPLACE_MATRIX) { 1334 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 1335 } else { 1336 *newmat = mat_elemental; 1337 } 1338 PetscFunctionReturn(0); 1339 } 1340 #endif 1341 1342 static PetscErrorCode MatDenseGetColumn_MPIDense(Mat A,PetscInt col,PetscScalar **vals) 1343 { 1344 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1345 PetscErrorCode ierr; 1346 1347 PetscFunctionBegin; 1348 ierr = MatDenseGetColumn(mat->A,col,vals);CHKERRQ(ierr); 1349 PetscFunctionReturn(0); 1350 } 1351 1352 static PetscErrorCode MatDenseRestoreColumn_MPIDense(Mat A,PetscScalar **vals) 1353 { 1354 Mat_MPIDense *mat = (Mat_MPIDense*)A->data; 1355 PetscErrorCode ierr; 1356 1357 PetscFunctionBegin; 1358 ierr = MatDenseRestoreColumn(mat->A,vals);CHKERRQ(ierr); 1359 PetscFunctionReturn(0); 1360 } 1361 1362 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIDense(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 1363 { 1364 PetscErrorCode ierr; 1365 Mat_MPIDense *mat; 1366 PetscInt m,nloc,N; 1367 1368 PetscFunctionBegin; 1369 ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr); 1370 ierr = MatGetLocalSize(inmat,NULL,&nloc);CHKERRQ(ierr); 1371 if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */ 1372 PetscInt sum; 1373 1374 if (n == PETSC_DECIDE) { 1375 ierr = PetscSplitOwnership(comm,&n,&N);CHKERRQ(ierr); 1376 } 1377 /* Check sum(n) = N */ 1378 ierr = MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr); 1379 if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N); 1380 1381 ierr = MatCreateDense(comm,m,n,PETSC_DETERMINE,N,NULL,outmat);CHKERRQ(ierr); 1382 } 1383 1384 /* numeric phase */ 1385 mat = (Mat_MPIDense*)(*outmat)->data; 1386 ierr = MatCopy(inmat,mat->A,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 1387 ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1388 ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1389 PetscFunctionReturn(0); 1390 } 1391 1392 PETSC_EXTERN PetscErrorCode MatCreate_MPIDense(Mat mat) 1393 { 1394 Mat_MPIDense *a; 1395 PetscErrorCode ierr; 1396 1397 PetscFunctionBegin; 1398 ierr = PetscNewLog(mat,&a);CHKERRQ(ierr); 1399 mat->data = (void*)a; 1400 ierr = PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1401 1402 mat->insertmode = NOT_SET_VALUES; 1403 ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&a->rank);CHKERRQ(ierr); 1404 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&a->size);CHKERRQ(ierr); 1405 1406 /* build cache for off array entries formed */ 1407 a->donotstash = PETSC_FALSE; 1408 1409 ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)mat),1,&mat->stash);CHKERRQ(ierr); 1410 1411 /* stuff used for matrix vector multiply */ 1412 a->lvec = 0; 1413 a->Mvctx = 0; 1414 a->roworiented = PETSC_TRUE; 1415 1416 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetLDA_C",MatDenseGetLDA_MPIDense);CHKERRQ(ierr); 1417 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",MatDenseGetArray_MPIDense);CHKERRQ(ierr); 1418 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",MatDenseRestoreArray_MPIDense);CHKERRQ(ierr); 1419 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArrayRead_C",MatDenseGetArrayRead_MPIDense);CHKERRQ(ierr); 1420 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArrayRead_C",MatDenseRestoreArrayRead_MPIDense);CHKERRQ(ierr); 1421 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",MatDensePlaceArray_MPIDense);CHKERRQ(ierr); 1422 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",MatDenseResetArray_MPIDense);CHKERRQ(ierr); 1423 #if defined(PETSC_HAVE_ELEMENTAL) 1424 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpidense_elemental_C",MatConvert_MPIDense_Elemental);CHKERRQ(ierr); 1425 #endif 1426 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIDenseSetPreallocation_C",MatMPIDenseSetPreallocation_MPIDense);CHKERRQ(ierr); 1427 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_mpiaij_mpidense_C",MatMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1428 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_mpiaij_mpidense_C",MatMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1429 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_mpiaij_mpidense_C",MatMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1430 1431 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_mpiaij_mpidense_C",MatTransposeMatMult_MPIAIJ_MPIDense);CHKERRQ(ierr); 1432 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_mpiaij_mpidense_C",MatTransposeMatMultSymbolic_MPIAIJ_MPIDense);CHKERRQ(ierr); 1433 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_mpiaij_mpidense_C",MatTransposeMatMultNumeric_MPIAIJ_MPIDense);CHKERRQ(ierr); 1434 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetColumn_C",MatDenseGetColumn_MPIDense);CHKERRQ(ierr); 1435 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreColumn_C",MatDenseRestoreColumn_MPIDense);CHKERRQ(ierr); 1436 ierr = PetscObjectChangeTypeName((PetscObject)mat,MATMPIDENSE);CHKERRQ(ierr); 1437 PetscFunctionReturn(0); 1438 } 1439 1440 /*MC 1441 MATDENSE - MATDENSE = "dense" - A matrix type to be used for dense matrices. 1442 1443 This matrix type is identical to MATSEQDENSE when constructed with a single process communicator, 1444 and MATMPIDENSE otherwise. 1445 1446 Options Database Keys: 1447 . -mat_type dense - sets the matrix type to "dense" during a call to MatSetFromOptions() 1448 1449 Level: beginner 1450 1451 1452 .seealso: MatCreateMPIDense,MATSEQDENSE,MATMPIDENSE 1453 M*/ 1454 1455 /*@C 1456 MatMPIDenseSetPreallocation - Sets the array used to store the matrix entries 1457 1458 Not collective 1459 1460 Input Parameters: 1461 . B - the matrix 1462 - data - optional location of matrix data. Set data=NULL for PETSc 1463 to control all matrix memory allocation. 1464 1465 Notes: 1466 The dense format is fully compatible with standard Fortran 77 1467 storage by columns. 1468 1469 The data input variable is intended primarily for Fortran programmers 1470 who wish to allocate their own matrix memory space. Most users should 1471 set data=NULL. 1472 1473 Level: intermediate 1474 1475 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1476 @*/ 1477 PetscErrorCode MatMPIDenseSetPreallocation(Mat B,PetscScalar *data) 1478 { 1479 PetscErrorCode ierr; 1480 1481 PetscFunctionBegin; 1482 ierr = PetscTryMethod(B,"MatMPIDenseSetPreallocation_C",(Mat,PetscScalar*),(B,data));CHKERRQ(ierr); 1483 PetscFunctionReturn(0); 1484 } 1485 1486 /*@ 1487 MatDensePlaceArray - Allows one to replace the array in a dense array with an 1488 array provided by the user. This is useful to avoid copying an array 1489 into a matrix 1490 1491 Not Collective 1492 1493 Input Parameters: 1494 + mat - the matrix 1495 - array - the array in column major order 1496 1497 Notes: 1498 You can return to the original array with a call to MatDenseResetArray(). The user is responsible for freeing this array; it will not be 1499 freed when the matrix is destroyed. 1500 1501 Level: developer 1502 1503 .seealso: MatDenseGetArray(), MatDenseResetArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1504 1505 @*/ 1506 PetscErrorCode MatDensePlaceArray(Mat mat,const PetscScalar array[]) 1507 { 1508 PetscErrorCode ierr; 1509 PetscFunctionBegin; 1510 ierr = PetscUseMethod(mat,"MatDensePlaceArray_C",(Mat,const PetscScalar*),(mat,array));CHKERRQ(ierr); 1511 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1512 PetscFunctionReturn(0); 1513 } 1514 1515 /*@ 1516 MatDenseResetArray - Resets the matrix array to that it previously had before the call to MatDensePlaceArray() 1517 1518 Not Collective 1519 1520 Input Parameters: 1521 . mat - the matrix 1522 1523 Notes: 1524 You can only call this after a call to MatDensePlaceArray() 1525 1526 Level: developer 1527 1528 .seealso: MatDenseGetArray(), MatDensePlaceArray(), VecPlaceArray(), VecGetArray(), VecRestoreArray(), VecReplaceArray(), VecResetArray() 1529 1530 @*/ 1531 PetscErrorCode MatDenseResetArray(Mat mat) 1532 { 1533 PetscErrorCode ierr; 1534 PetscFunctionBegin; 1535 ierr = PetscUseMethod(mat,"MatDenseResetArray_C",(Mat),(mat));CHKERRQ(ierr); 1536 ierr = PetscObjectStateIncrease((PetscObject)mat);CHKERRQ(ierr); 1537 PetscFunctionReturn(0); 1538 } 1539 1540 /*@C 1541 MatCreateDense - Creates a parallel matrix in dense format. 1542 1543 Collective 1544 1545 Input Parameters: 1546 + comm - MPI communicator 1547 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1548 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1549 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1550 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 1551 - data - optional location of matrix data. Set data=NULL (PETSC_NULL_SCALAR for Fortran users) for PETSc 1552 to control all matrix memory allocation. 1553 1554 Output Parameter: 1555 . A - the matrix 1556 1557 Notes: 1558 The dense format is fully compatible with standard Fortran 77 1559 storage by columns. 1560 1561 The data input variable is intended primarily for Fortran programmers 1562 who wish to allocate their own matrix memory space. Most users should 1563 set data=NULL (PETSC_NULL_SCALAR for Fortran users). 1564 1565 The user MUST specify either the local or global matrix dimensions 1566 (possibly both). 1567 1568 Level: intermediate 1569 1570 .seealso: MatCreate(), MatCreateSeqDense(), MatSetValues() 1571 @*/ 1572 PetscErrorCode MatCreateDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscScalar *data,Mat *A) 1573 { 1574 PetscErrorCode ierr; 1575 PetscMPIInt size; 1576 1577 PetscFunctionBegin; 1578 ierr = MatCreate(comm,A);CHKERRQ(ierr); 1579 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 1580 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1581 if (size > 1) { 1582 ierr = MatSetType(*A,MATMPIDENSE);CHKERRQ(ierr); 1583 ierr = MatMPIDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1584 if (data) { /* user provided data array, so no need to assemble */ 1585 ierr = MatSetUpMultiply_MPIDense(*A);CHKERRQ(ierr); 1586 (*A)->assembled = PETSC_TRUE; 1587 } 1588 } else { 1589 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 1590 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 1591 } 1592 PetscFunctionReturn(0); 1593 } 1594 1595 static PetscErrorCode MatDuplicate_MPIDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 1596 { 1597 Mat mat; 1598 Mat_MPIDense *a,*oldmat = (Mat_MPIDense*)A->data; 1599 PetscErrorCode ierr; 1600 1601 PetscFunctionBegin; 1602 *newmat = 0; 1603 ierr = MatCreate(PetscObjectComm((PetscObject)A),&mat);CHKERRQ(ierr); 1604 ierr = MatSetSizes(mat,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 1605 ierr = MatSetType(mat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1606 a = (Mat_MPIDense*)mat->data; 1607 1608 mat->factortype = A->factortype; 1609 mat->assembled = PETSC_TRUE; 1610 mat->preallocated = PETSC_TRUE; 1611 1612 a->size = oldmat->size; 1613 a->rank = oldmat->rank; 1614 mat->insertmode = NOT_SET_VALUES; 1615 a->nvec = oldmat->nvec; 1616 a->donotstash = oldmat->donotstash; 1617 1618 ierr = PetscLayoutReference(A->rmap,&mat->rmap);CHKERRQ(ierr); 1619 ierr = PetscLayoutReference(A->cmap,&mat->cmap);CHKERRQ(ierr); 1620 1621 ierr = MatSetUpMultiply_MPIDense(mat);CHKERRQ(ierr); 1622 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1623 ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr); 1624 1625 *newmat = mat; 1626 PetscFunctionReturn(0); 1627 } 1628 1629 PetscErrorCode MatLoad_MPIDense_DenseInFile(MPI_Comm comm,PetscInt fd,PetscInt M,PetscInt N,Mat newmat) 1630 { 1631 PetscErrorCode ierr; 1632 PetscMPIInt rank,size; 1633 const PetscInt *rowners; 1634 PetscInt i,m,n,nz,j,mMax; 1635 PetscScalar *array,*vals,*vals_ptr; 1636 Mat_MPIDense *a = (Mat_MPIDense*)newmat->data; 1637 1638 PetscFunctionBegin; 1639 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1640 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1641 1642 /* determine ownership of rows and columns */ 1643 m = (newmat->rmap->n < 0) ? PETSC_DECIDE : newmat->rmap->n; 1644 n = (newmat->cmap->n < 0) ? PETSC_DECIDE : newmat->cmap->n; 1645 1646 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1647 if (!a->A) { 1648 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1649 } 1650 ierr = MatDenseGetArray(newmat,&array);CHKERRQ(ierr); 1651 ierr = MatGetLocalSize(newmat,&m,NULL);CHKERRQ(ierr); 1652 ierr = MatGetOwnershipRanges(newmat,&rowners);CHKERRQ(ierr); 1653 ierr = MPI_Reduce(&m,&mMax,1,MPIU_INT,MPI_MAX,0,comm);CHKERRQ(ierr); 1654 if (!rank) { 1655 ierr = PetscMalloc1(mMax*N,&vals);CHKERRQ(ierr); 1656 1657 /* read in my part of the matrix numerical values */ 1658 ierr = PetscBinaryRead(fd,vals,m*N,NULL,PETSC_SCALAR);CHKERRQ(ierr); 1659 1660 /* insert into matrix-by row (this is why cannot directly read into array */ 1661 vals_ptr = vals; 1662 for (i=0; i<m; i++) { 1663 for (j=0; j<N; j++) { 1664 array[i + j*m] = *vals_ptr++; 1665 } 1666 } 1667 1668 /* read in other processors and ship out */ 1669 for (i=1; i<size; i++) { 1670 nz = (rowners[i+1] - rowners[i])*N; 1671 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 1672 ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1673 } 1674 } else { 1675 /* receive numeric values */ 1676 ierr = PetscMalloc1(m*N,&vals);CHKERRQ(ierr); 1677 1678 /* receive message of values*/ 1679 ierr = MPIULong_Recv(vals,m*N,MPIU_SCALAR,0,((PetscObject)(newmat))->tag,comm);CHKERRQ(ierr); 1680 1681 /* insert into matrix-by row (this is why cannot directly read into array */ 1682 vals_ptr = vals; 1683 for (i=0; i<m; i++) { 1684 for (j=0; j<N; j++) { 1685 array[i + j*m] = *vals_ptr++; 1686 } 1687 } 1688 } 1689 ierr = MatDenseRestoreArray(newmat,&array);CHKERRQ(ierr); 1690 ierr = PetscFree(vals);CHKERRQ(ierr); 1691 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1692 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1693 PetscFunctionReturn(0); 1694 } 1695 1696 PetscErrorCode MatLoad_MPIDense(Mat newmat,PetscViewer viewer) 1697 { 1698 Mat_MPIDense *a; 1699 PetscScalar *vals,*svals; 1700 MPI_Comm comm; 1701 MPI_Status status; 1702 PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*rowners,*sndcounts,m,n,maxnz; 1703 PetscInt header[4],*rowlengths = 0,M,N,*cols; 1704 PetscInt *ourlens,*procsnz = 0,jj,*mycols,*smycols; 1705 PetscInt i,nz,j,rstart,rend; 1706 int fd; 1707 PetscBool isbinary; 1708 PetscErrorCode ierr; 1709 1710 PetscFunctionBegin; 1711 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1712 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); 1713 1714 /* force binary viewer to load .info file if it has not yet done so */ 1715 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1716 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1717 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1718 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1719 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1720 if (!rank) { 1721 ierr = PetscBinaryRead(fd,(char*)header,4,NULL,PETSC_INT);CHKERRQ(ierr); 1722 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1723 } 1724 ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr); 1725 M = header[1]; N = header[2]; nz = header[3]; 1726 1727 /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */ 1728 if (newmat->rmap->N < 0) newmat->rmap->N = M; 1729 if (newmat->cmap->N < 0) newmat->cmap->N = N; 1730 1731 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); 1732 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); 1733 1734 /* 1735 Handle case where matrix is stored on disk as a dense matrix 1736 */ 1737 if (nz == MATRIX_BINARY_FORMAT_DENSE) { 1738 ierr = MatLoad_MPIDense_DenseInFile(comm,fd,M,N,newmat);CHKERRQ(ierr); 1739 PetscFunctionReturn(0); 1740 } 1741 1742 /* determine ownership of all rows */ 1743 if (newmat->rmap->n < 0) { 1744 ierr = PetscMPIIntCast(M/size + ((M % size) > rank),&m);CHKERRQ(ierr); 1745 } else { 1746 ierr = PetscMPIIntCast(newmat->rmap->n,&m);CHKERRQ(ierr); 1747 } 1748 if (newmat->cmap->n < 0) { 1749 n = PETSC_DECIDE; 1750 } else { 1751 ierr = PetscMPIIntCast(newmat->cmap->n,&n);CHKERRQ(ierr); 1752 } 1753 1754 ierr = PetscMalloc1(size+2,&rowners);CHKERRQ(ierr); 1755 ierr = MPI_Allgather(&m,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1756 rowners[0] = 0; 1757 for (i=2; i<=size; i++) { 1758 rowners[i] += rowners[i-1]; 1759 } 1760 rstart = rowners[rank]; 1761 rend = rowners[rank+1]; 1762 1763 /* distribute row lengths to all processors */ 1764 ierr = PetscMalloc1(rend-rstart,&ourlens);CHKERRQ(ierr); 1765 if (!rank) { 1766 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 1767 ierr = PetscBinaryRead(fd,rowlengths,M,NULL,PETSC_INT);CHKERRQ(ierr); 1768 ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr); 1769 for (i=0; i<size; i++) sndcounts[i] = rowners[i+1] - rowners[i]; 1770 ierr = MPI_Scatterv(rowlengths,sndcounts,rowners,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1771 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 1772 } else { 1773 ierr = MPI_Scatterv(0,0,0,MPIU_INT,ourlens,rend-rstart,MPIU_INT,0,comm);CHKERRQ(ierr); 1774 } 1775 1776 if (!rank) { 1777 /* calculate the number of nonzeros on each processor */ 1778 ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr); 1779 for (i=0; i<size; i++) { 1780 for (j=rowners[i]; j< rowners[i+1]; j++) { 1781 procsnz[i] += rowlengths[j]; 1782 } 1783 } 1784 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1785 1786 /* determine max buffer needed and allocate it */ 1787 maxnz = 0; 1788 for (i=0; i<size; i++) { 1789 maxnz = PetscMax(maxnz,procsnz[i]); 1790 } 1791 ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr); 1792 1793 /* read in my part of the matrix column indices */ 1794 nz = procsnz[0]; 1795 ierr = PetscMalloc1(nz,&mycols);CHKERRQ(ierr); 1796 ierr = PetscBinaryRead(fd,mycols,nz,NULL,PETSC_INT);CHKERRQ(ierr); 1797 1798 /* read in every one elses and ship off */ 1799 for (i=1; i<size; i++) { 1800 nz = procsnz[i]; 1801 ierr = PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);CHKERRQ(ierr); 1802 ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr); 1803 } 1804 ierr = PetscFree(cols);CHKERRQ(ierr); 1805 } else { 1806 /* determine buffer space needed for message */ 1807 nz = 0; 1808 for (i=0; i<m; i++) { 1809 nz += ourlens[i]; 1810 } 1811 ierr = PetscMalloc1(nz+1,&mycols);CHKERRQ(ierr); 1812 1813 /* receive message of column indices*/ 1814 ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr); 1815 ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr); 1816 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1817 } 1818 1819 ierr = MatSetSizes(newmat,m,n,M,N);CHKERRQ(ierr); 1820 a = (Mat_MPIDense*)newmat->data; 1821 if (!a->A) { 1822 ierr = MatMPIDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1823 } 1824 1825 if (!rank) { 1826 ierr = PetscMalloc1(maxnz,&vals);CHKERRQ(ierr); 1827 1828 /* read in my part of the matrix numerical values */ 1829 nz = procsnz[0]; 1830 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 1831 1832 /* insert into matrix */ 1833 jj = rstart; 1834 smycols = mycols; 1835 svals = vals; 1836 for (i=0; i<m; i++) { 1837 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1838 smycols += ourlens[i]; 1839 svals += ourlens[i]; 1840 jj++; 1841 } 1842 1843 /* read in other processors and ship out */ 1844 for (i=1; i<size; i++) { 1845 nz = procsnz[i]; 1846 ierr = PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);CHKERRQ(ierr); 1847 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr); 1848 } 1849 ierr = PetscFree(procsnz);CHKERRQ(ierr); 1850 } else { 1851 /* receive numeric values */ 1852 ierr = PetscMalloc1(nz+1,&vals);CHKERRQ(ierr); 1853 1854 /* receive message of values*/ 1855 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr); 1856 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 1857 if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 1858 1859 /* insert into matrix */ 1860 jj = rstart; 1861 smycols = mycols; 1862 svals = vals; 1863 for (i=0; i<m; i++) { 1864 ierr = MatSetValues(newmat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);CHKERRQ(ierr); 1865 smycols += ourlens[i]; 1866 svals += ourlens[i]; 1867 jj++; 1868 } 1869 } 1870 ierr = PetscFree(ourlens);CHKERRQ(ierr); 1871 ierr = PetscFree(vals);CHKERRQ(ierr); 1872 ierr = PetscFree(mycols);CHKERRQ(ierr); 1873 ierr = PetscFree(rowners);CHKERRQ(ierr); 1874 1875 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1876 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1877 PetscFunctionReturn(0); 1878 } 1879 1880 PetscErrorCode MatEqual_MPIDense(Mat A,Mat B,PetscBool *flag) 1881 { 1882 Mat_MPIDense *matB = (Mat_MPIDense*)B->data,*matA = (Mat_MPIDense*)A->data; 1883 Mat a,b; 1884 PetscBool flg; 1885 PetscErrorCode ierr; 1886 1887 PetscFunctionBegin; 1888 a = matA->A; 1889 b = matB->A; 1890 ierr = MatEqual(a,b,&flg);CHKERRQ(ierr); 1891 ierr = MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr); 1892 PetscFunctionReturn(0); 1893 } 1894 1895 PetscErrorCode MatDestroy_MatTransMatMult_MPIDense_MPIDense(Mat A) 1896 { 1897 PetscErrorCode ierr; 1898 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1899 Mat_TransMatMultDense *atb = a->atbdense; 1900 1901 PetscFunctionBegin; 1902 ierr = PetscFree3(atb->sendbuf,atb->atbarray,atb->recvcounts);CHKERRQ(ierr); 1903 ierr = (atb->destroy)(A);CHKERRQ(ierr); 1904 ierr = PetscFree(atb);CHKERRQ(ierr); 1905 PetscFunctionReturn(0); 1906 } 1907 1908 PetscErrorCode MatDestroy_MatMatTransMult_MPIDense_MPIDense(Mat A) 1909 { 1910 PetscErrorCode ierr; 1911 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 1912 Mat_MatTransMultDense *abt = a->abtdense; 1913 1914 PetscFunctionBegin; 1915 ierr = PetscFree2(abt->buf[0],abt->buf[1]);CHKERRQ(ierr); 1916 ierr = PetscFree2(abt->recvcounts,abt->recvdispls);CHKERRQ(ierr); 1917 ierr = (abt->destroy)(A);CHKERRQ(ierr); 1918 ierr = PetscFree(abt);CHKERRQ(ierr); 1919 PetscFunctionReturn(0); 1920 } 1921 1922 PetscErrorCode MatTransposeMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 1923 { 1924 Mat_MPIDense *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data; 1925 Mat_SeqDense *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data; 1926 Mat_TransMatMultDense *atb = c->atbdense; 1927 PetscErrorCode ierr; 1928 MPI_Comm comm; 1929 PetscMPIInt rank,size,*recvcounts=atb->recvcounts; 1930 PetscScalar *carray,*atbarray=atb->atbarray,*sendbuf=atb->sendbuf; 1931 PetscInt i,cN=C->cmap->N,cM=C->rmap->N,proc,k,j; 1932 PetscScalar _DOne=1.0,_DZero=0.0; 1933 PetscBLASInt am,an,bn,aN; 1934 const PetscInt *ranges; 1935 1936 PetscFunctionBegin; 1937 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1938 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1939 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1940 1941 /* compute atbarray = aseq^T * bseq */ 1942 ierr = PetscBLASIntCast(a->A->cmap->n,&an);CHKERRQ(ierr); 1943 ierr = PetscBLASIntCast(b->A->cmap->n,&bn);CHKERRQ(ierr); 1944 ierr = PetscBLASIntCast(a->A->rmap->n,&am);CHKERRQ(ierr); 1945 ierr = PetscBLASIntCast(A->cmap->N,&aN);CHKERRQ(ierr); 1946 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&an,&bn,&am,&_DOne,aseq->v,&aseq->lda,bseq->v,&bseq->lda,&_DZero,atbarray,&aN)); 1947 1948 ierr = MatGetOwnershipRanges(C,&ranges);CHKERRQ(ierr); 1949 for (i=0; i<size; i++) recvcounts[i] = (ranges[i+1] - ranges[i])*cN; 1950 1951 /* arrange atbarray into sendbuf */ 1952 k = 0; 1953 for (proc=0; proc<size; proc++) { 1954 for (j=0; j<cN; j++) { 1955 for (i=ranges[proc]; i<ranges[proc+1]; i++) sendbuf[k++] = atbarray[i+j*cM]; 1956 } 1957 } 1958 /* sum all atbarray to local values of C */ 1959 ierr = MatDenseGetArray(c->A,&carray);CHKERRQ(ierr); 1960 ierr = MPI_Reduce_scatter(sendbuf,carray,recvcounts,MPIU_SCALAR,MPIU_SUM,comm);CHKERRQ(ierr); 1961 ierr = MatDenseRestoreArray(c->A,&carray);CHKERRQ(ierr); 1962 PetscFunctionReturn(0); 1963 } 1964 1965 PetscErrorCode MatTransposeMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 1966 { 1967 PetscErrorCode ierr; 1968 Mat Cdense; 1969 MPI_Comm comm; 1970 PetscMPIInt size; 1971 PetscInt cm=A->cmap->n,cM,cN=B->cmap->N; 1972 Mat_MPIDense *c; 1973 Mat_TransMatMultDense *atb; 1974 1975 PetscFunctionBegin; 1976 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 1977 if (A->rmap->rstart != B->rmap->rstart || A->rmap->rend != B->rmap->rend) { 1978 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); 1979 } 1980 1981 /* create matrix product Cdense */ 1982 ierr = MatCreate(comm,&Cdense);CHKERRQ(ierr); 1983 ierr = MatSetSizes(Cdense,cm,B->cmap->n,PETSC_DECIDE,PETSC_DECIDE);CHKERRQ(ierr); 1984 ierr = MatSetType(Cdense,MATMPIDENSE);CHKERRQ(ierr); 1985 ierr = MatMPIDenseSetPreallocation(Cdense,NULL);CHKERRQ(ierr); 1986 ierr = MatAssemblyBegin(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1987 ierr = MatAssemblyEnd(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1988 *C = Cdense; 1989 1990 /* create data structure for reuse Cdense */ 1991 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1992 ierr = PetscNew(&atb);CHKERRQ(ierr); 1993 cM = Cdense->rmap->N; 1994 ierr = PetscMalloc3(cM*cN,&atb->sendbuf,cM*cN,&atb->atbarray,size,&atb->recvcounts);CHKERRQ(ierr); 1995 1996 c = (Mat_MPIDense*)Cdense->data; 1997 c->atbdense = atb; 1998 atb->destroy = Cdense->ops->destroy; 1999 Cdense->ops->destroy = MatDestroy_MatTransMatMult_MPIDense_MPIDense; 2000 PetscFunctionReturn(0); 2001 } 2002 2003 PetscErrorCode MatTransposeMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2004 { 2005 PetscErrorCode ierr; 2006 2007 PetscFunctionBegin; 2008 if (scall == MAT_INITIAL_MATRIX) { 2009 ierr = MatTransposeMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 2010 } 2011 ierr = MatTransposeMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 2012 PetscFunctionReturn(0); 2013 } 2014 2015 static PetscErrorCode MatMatTransposeMultSymbolic_MPIDense_MPIDense(Mat A, Mat B, PetscReal fill, Mat *C) 2016 { 2017 PetscErrorCode ierr; 2018 Mat Cdense; 2019 MPI_Comm comm; 2020 PetscMPIInt i, size; 2021 PetscInt maxRows, bufsiz; 2022 Mat_MPIDense *c; 2023 PetscMPIInt tag; 2024 const char *algTypes[2] = {"allgatherv","cyclic"}; 2025 PetscInt alg, nalg = 2; 2026 Mat_MatTransMultDense *abt; 2027 2028 PetscFunctionBegin; 2029 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2030 alg = 0; /* default is allgatherv */ 2031 ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MatMatTransposeMult","Mat");CHKERRQ(ierr); 2032 ierr = PetscOptionsEList("-matmattransmult_mpidense_mpidense_via","Algorithmic approach","MatMatTransposeMult",algTypes,nalg,algTypes[0],&alg,NULL);CHKERRQ(ierr); 2033 ierr = PetscOptionsEnd();CHKERRQ(ierr); 2034 if (A->cmap->N != B->cmap->N) { 2035 SETERRQ2(comm,PETSC_ERR_ARG_SIZ,"Matrix global column dimensions are incompatible, A (%D) != B (%D)",A->cmap->N,B->cmap->N); 2036 } 2037 2038 /* create matrix product Cdense */ 2039 ierr = MatCreate(comm,&Cdense);CHKERRQ(ierr); 2040 ierr = MatSetSizes(Cdense,A->rmap->n,B->rmap->n,A->rmap->N,B->rmap->N);CHKERRQ(ierr); 2041 ierr = MatSetType(Cdense,MATMPIDENSE);CHKERRQ(ierr); 2042 ierr = MatMPIDenseSetPreallocation(Cdense,NULL);CHKERRQ(ierr); 2043 ierr = PetscObjectGetNewTag((PetscObject)Cdense, &tag);CHKERRQ(ierr); 2044 ierr = MatAssemblyBegin(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2045 ierr = MatAssemblyEnd(Cdense,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2046 *C = Cdense; 2047 2048 /* create data structure for reuse Cdense */ 2049 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2050 ierr = PetscNew(&abt);CHKERRQ(ierr); 2051 abt->tag = tag; 2052 abt->alg = alg; 2053 switch (alg) { 2054 case 1: 2055 for (maxRows = 0, i = 0; i < size; i++) maxRows = PetscMax(maxRows, (B->rmap->range[i + 1] - B->rmap->range[i])); 2056 bufsiz = A->cmap->N * maxRows; 2057 ierr = PetscMalloc2(bufsiz,&(abt->buf[0]),bufsiz,&(abt->buf[1]));CHKERRQ(ierr); 2058 break; 2059 default: 2060 ierr = PetscMalloc2(B->rmap->n * B->cmap->N, &(abt->buf[0]), B->rmap->N * B->cmap->N, &(abt->buf[1]));CHKERRQ(ierr); 2061 ierr = PetscMalloc2(size,&(abt->recvcounts),size+1,&(abt->recvdispls));CHKERRQ(ierr); 2062 for (i = 0; i <= size; i++) abt->recvdispls[i] = B->rmap->range[i] * A->cmap->N; 2063 for (i = 0; i < size; i++) abt->recvcounts[i] = abt->recvdispls[i + 1] - abt->recvdispls[i]; 2064 break; 2065 } 2066 2067 c = (Mat_MPIDense*)Cdense->data; 2068 c->abtdense = abt; 2069 abt->destroy = Cdense->ops->destroy; 2070 Cdense->ops->destroy = MatDestroy_MatMatTransMult_MPIDense_MPIDense; 2071 PetscFunctionReturn(0); 2072 } 2073 2074 static PetscErrorCode MatMatTransposeMultNumeric_MPIDense_MPIDense_Cyclic(Mat A, Mat B, Mat C) 2075 { 2076 Mat_MPIDense *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data; 2077 Mat_SeqDense *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data; 2078 Mat_SeqDense *cseq=(Mat_SeqDense*)(c->A)->data; 2079 Mat_MatTransMultDense *abt = c->abtdense; 2080 PetscErrorCode ierr; 2081 MPI_Comm comm; 2082 PetscMPIInt rank,size, sendsiz, recvsiz, sendto, recvfrom, recvisfrom; 2083 PetscScalar *sendbuf, *recvbuf=0, *carray; 2084 PetscInt i,cK=A->cmap->N,k,j,bn; 2085 PetscScalar _DOne=1.0,_DZero=0.0; 2086 PetscBLASInt cm, cn, ck; 2087 MPI_Request reqs[2]; 2088 const PetscInt *ranges; 2089 2090 PetscFunctionBegin; 2091 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2092 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2093 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2094 2095 ierr = MatGetOwnershipRanges(B,&ranges);CHKERRQ(ierr); 2096 bn = B->rmap->n; 2097 if (bseq->lda == bn) { 2098 sendbuf = bseq->v; 2099 } else { 2100 sendbuf = abt->buf[0]; 2101 for (k = 0, i = 0; i < cK; i++) { 2102 for (j = 0; j < bn; j++, k++) { 2103 sendbuf[k] = bseq->v[i * bseq->lda + j]; 2104 } 2105 } 2106 } 2107 if (size > 1) { 2108 sendto = (rank + size - 1) % size; 2109 recvfrom = (rank + size + 1) % size; 2110 } else { 2111 sendto = recvfrom = 0; 2112 } 2113 ierr = PetscBLASIntCast(cK,&ck);CHKERRQ(ierr); 2114 ierr = PetscBLASIntCast(c->A->rmap->n,&cm);CHKERRQ(ierr); 2115 recvisfrom = rank; 2116 for (i = 0; i < size; i++) { 2117 /* we have finished receiving in sending, bufs can be read/modified */ 2118 PetscInt nextrecvisfrom = (recvisfrom + 1) % size; /* which process the next recvbuf will originate on */ 2119 PetscInt nextbn = ranges[nextrecvisfrom + 1] - ranges[nextrecvisfrom]; 2120 2121 if (nextrecvisfrom != rank) { 2122 /* start the cyclic sends from sendbuf, to recvbuf (which will switch to sendbuf) */ 2123 sendsiz = cK * bn; 2124 recvsiz = cK * nextbn; 2125 recvbuf = (i & 1) ? abt->buf[0] : abt->buf[1]; 2126 ierr = MPI_Isend(sendbuf, sendsiz, MPIU_SCALAR, sendto, abt->tag, comm, &reqs[0]);CHKERRQ(ierr); 2127 ierr = MPI_Irecv(recvbuf, recvsiz, MPIU_SCALAR, recvfrom, abt->tag, comm, &reqs[1]);CHKERRQ(ierr); 2128 } 2129 2130 /* local aseq * sendbuf^T */ 2131 ierr = PetscBLASIntCast(ranges[recvisfrom + 1] - ranges[recvisfrom], &cn);CHKERRQ(ierr); 2132 carray = &cseq->v[cseq->lda * ranges[recvisfrom]]; 2133 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&cm,&cn,&ck,&_DOne,aseq->v,&aseq->lda,sendbuf,&cn,&_DZero,carray,&cseq->lda)); 2134 2135 if (nextrecvisfrom != rank) { 2136 /* wait for the sends and receives to complete, swap sendbuf and recvbuf */ 2137 ierr = MPI_Waitall(2, reqs, MPI_STATUSES_IGNORE);CHKERRQ(ierr); 2138 } 2139 bn = nextbn; 2140 recvisfrom = nextrecvisfrom; 2141 sendbuf = recvbuf; 2142 } 2143 PetscFunctionReturn(0); 2144 } 2145 2146 static PetscErrorCode MatMatTransposeMultNumeric_MPIDense_MPIDense_Allgatherv(Mat A, Mat B, Mat C) 2147 { 2148 Mat_MPIDense *a=(Mat_MPIDense*)A->data, *b=(Mat_MPIDense*)B->data, *c=(Mat_MPIDense*)C->data; 2149 Mat_SeqDense *aseq=(Mat_SeqDense*)(a->A)->data, *bseq=(Mat_SeqDense*)(b->A)->data; 2150 Mat_SeqDense *cseq=(Mat_SeqDense*)(c->A)->data; 2151 Mat_MatTransMultDense *abt = c->abtdense; 2152 PetscErrorCode ierr; 2153 MPI_Comm comm; 2154 PetscMPIInt rank,size; 2155 PetscScalar *sendbuf, *recvbuf; 2156 PetscInt i,cK=A->cmap->N,k,j,bn; 2157 PetscScalar _DOne=1.0,_DZero=0.0; 2158 PetscBLASInt cm, cn, ck; 2159 2160 PetscFunctionBegin; 2161 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 2162 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 2163 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2164 2165 /* copy transpose of B into buf[0] */ 2166 bn = B->rmap->n; 2167 sendbuf = abt->buf[0]; 2168 recvbuf = abt->buf[1]; 2169 for (k = 0, j = 0; j < bn; j++) { 2170 for (i = 0; i < cK; i++, k++) { 2171 sendbuf[k] = bseq->v[i * bseq->lda + j]; 2172 } 2173 } 2174 ierr = MPI_Allgatherv(sendbuf, bn * cK, MPIU_SCALAR, recvbuf, abt->recvcounts, abt->recvdispls, MPIU_SCALAR, comm);CHKERRQ(ierr); 2175 ierr = PetscBLASIntCast(cK,&ck);CHKERRQ(ierr); 2176 ierr = PetscBLASIntCast(c->A->rmap->n,&cm);CHKERRQ(ierr); 2177 ierr = PetscBLASIntCast(c->A->cmap->n,&cn);CHKERRQ(ierr); 2178 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&cm,&cn,&ck,&_DOne,aseq->v,&aseq->lda,recvbuf,&ck,&_DZero,cseq->v,&cseq->lda)); 2179 PetscFunctionReturn(0); 2180 } 2181 2182 static PetscErrorCode MatMatTransposeMultNumeric_MPIDense_MPIDense(Mat A, Mat B, Mat C) 2183 { 2184 Mat_MPIDense *c=(Mat_MPIDense*)C->data; 2185 Mat_MatTransMultDense *abt = c->abtdense; 2186 PetscErrorCode ierr; 2187 2188 PetscFunctionBegin; 2189 switch (abt->alg) { 2190 case 1: 2191 ierr = MatMatTransposeMultNumeric_MPIDense_MPIDense_Cyclic(A, B, C);CHKERRQ(ierr); 2192 break; 2193 default: 2194 ierr = MatMatTransposeMultNumeric_MPIDense_MPIDense_Allgatherv(A, B, C);CHKERRQ(ierr); 2195 break; 2196 } 2197 PetscFunctionReturn(0); 2198 } 2199 2200 static PetscErrorCode MatMatTransposeMult_MPIDense_MPIDense(Mat A,Mat B, MatReuse scall, PetscReal fill, Mat *C) 2201 { 2202 PetscErrorCode ierr; 2203 2204 PetscFunctionBegin; 2205 if (scall == MAT_INITIAL_MATRIX) { 2206 ierr = MatMatTransposeMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 2207 } 2208 ierr = MatMatTransposeMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 2209 PetscFunctionReturn(0); 2210 } 2211 2212 PetscErrorCode MatDestroy_MatMatMult_MPIDense_MPIDense(Mat A) 2213 { 2214 PetscErrorCode ierr; 2215 Mat_MPIDense *a = (Mat_MPIDense*)A->data; 2216 Mat_MatMultDense *ab = a->abdense; 2217 2218 PetscFunctionBegin; 2219 ierr = MatDestroy(&ab->Ce);CHKERRQ(ierr); 2220 ierr = MatDestroy(&ab->Ae);CHKERRQ(ierr); 2221 ierr = MatDestroy(&ab->Be);CHKERRQ(ierr); 2222 2223 ierr = (ab->destroy)(A);CHKERRQ(ierr); 2224 ierr = PetscFree(ab);CHKERRQ(ierr); 2225 PetscFunctionReturn(0); 2226 } 2227 2228 #if defined(PETSC_HAVE_ELEMENTAL) 2229 PetscErrorCode MatMatMultNumeric_MPIDense_MPIDense(Mat A,Mat B,Mat C) 2230 { 2231 PetscErrorCode ierr; 2232 Mat_MPIDense *c=(Mat_MPIDense*)C->data; 2233 Mat_MatMultDense *ab=c->abdense; 2234 2235 PetscFunctionBegin; 2236 ierr = MatConvert_MPIDense_Elemental(A,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Ae);CHKERRQ(ierr); 2237 ierr = MatConvert_MPIDense_Elemental(B,MATELEMENTAL,MAT_REUSE_MATRIX, &ab->Be);CHKERRQ(ierr); 2238 ierr = MatMatMultNumeric(ab->Ae,ab->Be,ab->Ce);CHKERRQ(ierr); 2239 ierr = MatConvert(ab->Ce,MATMPIDENSE,MAT_REUSE_MATRIX,&C);CHKERRQ(ierr); 2240 PetscFunctionReturn(0); 2241 } 2242 2243 PetscErrorCode MatMatMultSymbolic_MPIDense_MPIDense(Mat A,Mat B,PetscReal fill,Mat *C) 2244 { 2245 PetscErrorCode ierr; 2246 Mat Ae,Be,Ce; 2247 Mat_MPIDense *c; 2248 Mat_MatMultDense *ab; 2249 2250 PetscFunctionBegin; 2251 if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) { 2252 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); 2253 } 2254 2255 /* convert A and B to Elemental matrices Ae and Be */ 2256 ierr = MatConvert(A,MATELEMENTAL,MAT_INITIAL_MATRIX, &Ae);CHKERRQ(ierr); 2257 ierr = MatConvert(B,MATELEMENTAL,MAT_INITIAL_MATRIX, &Be);CHKERRQ(ierr); 2258 2259 /* Ce = Ae*Be */ 2260 ierr = MatMatMultSymbolic(Ae,Be,fill,&Ce);CHKERRQ(ierr); 2261 ierr = MatMatMultNumeric(Ae,Be,Ce);CHKERRQ(ierr); 2262 2263 /* convert Ce to C */ 2264 ierr = MatConvert(Ce,MATMPIDENSE,MAT_INITIAL_MATRIX,C);CHKERRQ(ierr); 2265 2266 /* create data structure for reuse Cdense */ 2267 ierr = PetscNew(&ab);CHKERRQ(ierr); 2268 c = (Mat_MPIDense*)(*C)->data; 2269 c->abdense = ab; 2270 2271 ab->Ae = Ae; 2272 ab->Be = Be; 2273 ab->Ce = Ce; 2274 ab->destroy = (*C)->ops->destroy; 2275 (*C)->ops->destroy = MatDestroy_MatMatMult_MPIDense_MPIDense; 2276 (*C)->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIDense; 2277 PetscFunctionReturn(0); 2278 } 2279 2280 PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2281 { 2282 PetscErrorCode ierr; 2283 2284 PetscFunctionBegin; 2285 if (scall == MAT_INITIAL_MATRIX) { /* simbolic product includes numeric product */ 2286 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2287 ierr = MatMatMultSymbolic_MPIDense_MPIDense(A,B,fill,C);CHKERRQ(ierr); 2288 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2289 } else { 2290 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2291 ierr = MatMatMultNumeric_MPIDense_MPIDense(A,B,*C);CHKERRQ(ierr); 2292 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2293 } 2294 PetscFunctionReturn(0); 2295 } 2296 #endif 2297 2298