1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3 4 extern PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat); 5 6 #undef __FUNCT__ 7 #define __FUNCT__ "MatFDColoringApply_MPIAIJ" 8 PetscErrorCode MatFDColoringApply_MPIAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 9 { 10 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 11 PetscErrorCode ierr; 12 PetscInt k,cstart,cend,l,row,col,nz; 13 PetscScalar dx=0.0,*y,*xx,*w3_array; 14 PetscScalar *vscale_array; 15 PetscReal epsilon=coloring->error_rel,umin=coloring->umin,unorm; 16 Vec w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale; 17 void *fctx=coloring->fctx; 18 PetscBool flg=PETSC_FALSE; 19 PetscInt ctype=coloring->ctype,nxloc; 20 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)J->data; 21 MatEntry *Jentry=coloring->matentry; 22 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 23 24 PetscFunctionBegin; 25 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 26 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 27 if (flg) { 28 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 29 } else { 30 PetscBool assembled; 31 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 32 if (assembled) { 33 ierr = MatZeroEntries(J);CHKERRQ(ierr); 34 } 35 } 36 37 /* create vscale for storing dx */ 38 if (!vscale) { 39 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 40 ierr = VecCreateGhost(PetscObjectComm((PetscObject)J),J->cmap->n,PETSC_DETERMINE,aij->B->cmap->n,aij->garray,&vscale);CHKERRQ(ierr); 41 } else if (ctype == IS_COLORING_GHOSTED) { 42 ierr = VecDuplicate(x1,&vscale);CHKERRQ(ierr); 43 } 44 coloring->vscale = vscale; 45 } 46 47 /* (1) Set w1 = F(x1) */ 48 if (!coloring->fset) { 49 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 50 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 51 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 52 } else { 53 coloring->fset = PETSC_FALSE; 54 } 55 56 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 57 if (coloring->htype[0] == 'w') { 58 /* vscale = dx is a constant scalar */ 59 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 60 dx = 1.0/((1.0 + unorm)*epsilon); 61 } else { 62 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 63 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 64 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 65 for (col=0; col<nxloc; col++) { 66 dx = xx[col]; 67 if (PetscAbsScalar(dx) < umin) { 68 if (PetscRealPart(dx) >= 0.0) dx = umin; 69 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 70 } 71 dx *= epsilon; 72 vscale_array[col] = 1.0/dx; 73 } 74 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 75 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 76 } 77 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] != 'w') { 78 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 79 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 80 } 81 82 /* (3) Loop over each color */ 83 if (!coloring->w3) { 84 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 85 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 86 } 87 w3 = coloring->w3; 88 89 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 90 if (vscale) { 91 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 92 } 93 nz = 0; 94 for (k=0; k<ncolors; k++) { 95 coloring->currentcolor = k; 96 97 /* 98 (3-1) Loop over each column associated with color 99 adding the perturbation to the vector w3 = x1 + dx. 100 */ 101 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 102 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 103 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 104 if (coloring->htype[0] == 'w') { 105 for (l=0; l<ncolumns[k]; l++) { 106 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 107 w3_array[col] += 1.0/dx; 108 } 109 } else { /* htype == 'ds' */ 110 vscale_array -= cstart; /* shift pointer so global index can be used */ 111 for (l=0; l<ncolumns[k]; l++) { 112 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 113 w3_array[col] += 1.0/vscale_array[col]; 114 } 115 vscale_array += cstart; 116 } 117 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 118 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 119 120 /* 121 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 122 w2 = F(x1 + dx) - F(x1) 123 */ 124 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 125 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 126 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 127 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 128 129 /* 130 (3-3) Loop over rows of vector, putting results into Jacobian matrix 131 */ 132 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 133 if (coloring->htype[0] == 'w') { 134 for (l=0; l<nrows[k]; l++) { 135 row = Jentry[nz].row; /* local row index */ 136 *(Jentry[nz++].valaddr) = y[row]*dx; 137 } 138 } else { /* htype == 'ds' */ 139 for (l=0; l<nrows[k]; l++) { 140 row = Jentry[nz].row; /* local row index */ 141 *(Jentry[nz].valaddr) = y[row]*vscale_array[Jentry[nz].col]; 142 nz++; 143 } 144 } 145 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 146 } 147 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 148 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 149 if (vscale) { 150 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 151 } 152 153 coloring->currentcolor = -1; 154 PetscFunctionReturn(0); 155 } 156 157 #undef __FUNCT__ 158 #define __FUNCT__ "MatFDColoringCreate_MPIAIJ_new" 159 PetscErrorCode MatFDColoringCreate_MPIAIJ_new(Mat mat,ISColoring iscoloring,MatFDColoring c) 160 { 161 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 162 PetscErrorCode ierr; 163 PetscMPIInt size,*ncolsonproc,*disp,nn; 164 PetscInt i,n,nrows,nrows_i,j,k,m,ncols,col; 165 const PetscInt *is,*A_ci,*A_cj,*B_ci,*B_cj,*row = NULL,*ltog=NULL; 166 PetscInt nis=iscoloring->n,nctot,*cols; 167 PetscInt *rowhit,cstart,cend,colb; 168 IS *isa; 169 ISLocalToGlobalMapping map=mat->cmap->mapping; 170 PetscInt ctype=c->ctype; 171 Mat A=aij->A,B=aij->B; 172 Mat_SeqAIJ *spA=(Mat_SeqAIJ*)A->data,*spB=(Mat_SeqAIJ*)B->data; 173 PetscScalar *A_val=spA->a,*B_val=spB->a; 174 PetscInt spidx; 175 PetscInt *spidxA,*spidxB,nz; 176 PetscScalar **valaddrhit; 177 MatEntry *Jentry; 178 179 PetscFunctionBegin; 180 if (ctype == IS_COLORING_GHOSTED) { 181 if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 182 ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr); 183 } 184 185 m = mat->rmap->n; 186 cstart = mat->cmap->rstart; 187 cend = mat->cmap->rend; 188 c->M = mat->rmap->N; /* set the global rows and columns and local rows */ 189 c->N = mat->cmap->N; 190 c->m = m; 191 c->rstart = mat->rmap->rstart; 192 193 c->ncolors = nis; 194 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr); 195 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr); 196 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr); 197 ierr = PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));CHKERRQ(ierr); 198 199 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 200 ierr = PetscMalloc(nz*sizeof(MatEntry),&Jentry);CHKERRQ(ierr); 201 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));CHKERRQ(ierr); 202 c->matentry = Jentry; 203 204 /* Allow access to data structures of local part of matrix 205 - creates aij->colmap which maps global column number to local number in part B */ 206 if (!aij->colmap) { 207 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 208 } 209 ierr = MatGetColumnIJ_SeqAIJ_Color(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 210 ierr = MatGetColumnIJ_SeqAIJ_Color(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 211 212 ierr = PetscMalloc2(m+1,PetscInt,&rowhit,m+1,PetscScalar*,&valaddrhit);CHKERRQ(ierr); 213 nz = 0; 214 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 215 for (i=0; i<nis; i++) { /* for each local color */ 216 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 217 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 218 219 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 220 if (n) { 221 ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr); 222 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 223 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 224 /* convert global column indices to local ones! */ 225 226 } else { 227 c->columns[i] = 0; 228 } 229 230 if (ctype == IS_COLORING_GLOBAL) { 231 /* Determine nctot, the total (parallel) number of columns of this color */ 232 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 233 ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr); 234 235 /* ncolsonproc[j]: local ncolumns on proc[j] of this color */ 236 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 237 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 238 nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j]; 239 if (!nctot) { 240 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 241 } 242 243 disp[0] = 0; 244 for (j=1; j<size; j++) { 245 disp[j] = disp[j-1] + ncolsonproc[j-1]; 246 } 247 248 /* Get cols, the complete list of columns for this color on each process */ 249 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 250 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 251 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 252 } else if (ctype == IS_COLORING_GHOSTED) { 253 /* Determine local number of columns of this color on this process, including ghost points */ 254 nctot = n; 255 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 256 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 257 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 258 259 /* Mark all rows affect by these columns */ 260 ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr); 261 nrows_i = 0; 262 for (j=0; j<nctot; j++) { /* loop over columns*/ 263 if (ctype == IS_COLORING_GHOSTED) { 264 col = ltog[cols[j]]; 265 } else { 266 col = cols[j]; 267 } 268 if (col >= cstart && col < cend) { /* column is in diagonal block of matrix A */ 269 row = A_cj + A_ci[col-cstart]; 270 nrows = A_ci[col-cstart+1] - A_ci[col-cstart]; 271 nrows_i += nrows; 272 /* loop over columns of A marking them in rowhit */ 273 for (k=0; k<nrows; k++) { 274 /* set valaddrhit for part A */ 275 spidx = spidxA[A_ci[col-cstart] + k]; 276 valaddrhit[*row] = &A_val[spidx]; 277 rowhit[*row++] = col - cstart + 1; /* local column index */ 278 } 279 } else { /* column is in off-diagonal block of matrix B */ 280 #if defined(PETSC_USE_CTABLE) 281 ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr); 282 colb--; 283 #else 284 colb = aij->colmap[col] - 1; /* local column index */ 285 #endif 286 if (colb == -1) { 287 nrows = 0; 288 } else { 289 row = B_cj + B_ci[colb]; 290 nrows = B_ci[colb+1] - B_ci[colb]; 291 } 292 nrows_i += nrows; 293 /* loop over columns of B marking them in rowhit */ 294 for (k=0; k<nrows; k++) { 295 /* set valaddrhit for part B */ 296 spidx = spidxB[B_ci[colb] + k]; 297 valaddrhit[*row] = &B_val[spidx]; 298 rowhit[*row++] = colb + 1 + cend - cstart; /* local column index */ 299 } 300 } 301 } 302 c->nrows[i] = nrows_i; 303 304 for (j=0; j<m; j++) { 305 if (rowhit[j]) { 306 Jentry[nz].row = j; /* local row index */ 307 Jentry[nz].col = rowhit[j] - 1; /* local column index */ 308 Jentry[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 309 nz++; 310 } 311 } 312 ierr = PetscFree(cols);CHKERRQ(ierr); 313 } 314 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 315 if (nz != spA->nz + spB->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"nz %d != mat->nz %d\n",nz,spA->nz+spB->nz); 316 317 ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr); 318 ierr = MatRestoreColumnIJ_SeqAIJ_Color(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 319 ierr = MatRestoreColumnIJ_SeqAIJ_Color(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 320 if (ctype == IS_COLORING_GHOSTED) { 321 ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr); 322 } 323 324 mat->ops->fdcoloringapply = MatFDColoringApply_MPIAIJ; 325 PetscFunctionReturn(0); 326 } 327 328 /*------------------------------------------------------*/ 329 #undef __FUNCT__ 330 #define __FUNCT__ "MatFDColoringCreate_MPIAIJ" 331 PetscErrorCode MatFDColoringCreate_MPIAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 332 { 333 Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data; 334 PetscErrorCode ierr; 335 PetscMPIInt size,*ncolsonproc,*disp,nn; 336 PetscInt i,n,nrows,j,k,m,ncols,col; 337 const PetscInt *is,*A_ci,*A_cj,*B_ci,*B_cj,*rows = 0,*ltog; 338 PetscInt nis = iscoloring->n,nctot,*cols; 339 PetscInt *rowhit,M,cstart,cend,colb; 340 PetscInt *columnsforrow,l; 341 IS *isa; 342 PetscBool done,flg; 343 ISLocalToGlobalMapping map = mat->cmap->mapping; 344 PetscInt ctype=c->ctype; 345 PetscBool new_impl=PETSC_FALSE; 346 347 PetscFunctionBegin; 348 ierr = PetscOptionsName("-new","using new impls","",&new_impl);CHKERRQ(ierr); 349 if (new_impl){ 350 ierr = MatFDColoringCreate_MPIAIJ_new(mat,iscoloring,c);CHKERRQ(ierr); 351 PetscFunctionReturn(0); 352 } 353 if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 354 355 if (map) {ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr);} 356 else ltog = NULL; 357 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 358 359 M = mat->rmap->n; 360 cstart = mat->cmap->rstart; 361 cend = mat->cmap->rend; 362 c->M = mat->rmap->N; /* set the global rows and columns and local rows */ 363 c->N = mat->cmap->N; 364 c->m = mat->rmap->n; 365 c->rstart = mat->rmap->rstart; 366 367 c->ncolors = nis; 368 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr); 369 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr); 370 ierr = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr); 371 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr); 372 ierr = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr); 373 ierr = PetscLogObjectMemory((PetscObject)c,5*nis*sizeof(PetscInt));CHKERRQ(ierr); 374 375 /* Allow access to data structures of local part of matrix */ 376 if (!aij->colmap) { 377 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 378 } 379 ierr = MatGetColumnIJ(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 380 ierr = MatGetColumnIJ(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 381 382 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr); 383 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr); 384 385 for (i=0; i<nis; i++) { 386 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 387 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 388 389 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 390 if (n) { 391 ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr); 392 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 393 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 394 } else { 395 c->columns[i] = 0; 396 } 397 398 if (ctype == IS_COLORING_GLOBAL) { 399 /* Determine the total (parallel) number of columns of this color */ 400 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 401 ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr); 402 403 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 404 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 405 nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j]; 406 if (!nctot) { 407 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 408 } 409 410 disp[0] = 0; 411 for (j=1; j<size; j++) { 412 disp[j] = disp[j-1] + ncolsonproc[j-1]; 413 } 414 415 /* Get complete list of columns for color on each processor */ 416 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 417 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 418 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 419 } else if (ctype == IS_COLORING_GHOSTED) { 420 /* Determine local number of columns of this color on this process, including ghost points */ 421 nctot = n; 422 ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr); 423 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 424 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 425 426 /* 427 Mark all rows affect by these columns 428 */ 429 /* Temporary option to allow for debugging/testing */ 430 flg = PETSC_FALSE; 431 ierr = PetscOptionsGetBool(NULL,"-matfdcoloring_slow",&flg,NULL);CHKERRQ(ierr); 432 if (!flg) { /*-----------------------------------------------------------------------------*/ 433 /* crude, fast version */ 434 ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr); 435 /* loop over columns*/ 436 for (j=0; j<nctot; j++) { 437 if (ctype == IS_COLORING_GHOSTED) { 438 col = ltog[cols[j]]; 439 } else { 440 col = cols[j]; 441 } 442 if (col >= cstart && col < cend) { 443 /* column is in diagonal block of matrix */ 444 rows = A_cj + A_ci[col-cstart]; 445 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 446 } else { 447 #if defined(PETSC_USE_CTABLE) 448 ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr); 449 colb--; 450 #else 451 colb = aij->colmap[col] - 1; 452 #endif 453 if (colb == -1) { 454 m = 0; 455 } else { 456 rows = B_cj + B_ci[colb]; 457 m = B_ci[colb+1] - B_ci[colb]; 458 } 459 } 460 /* loop over columns marking them in rowhit */ 461 for (k=0; k<m; k++) { 462 rowhit[*rows++] = col + 1; 463 } 464 } 465 466 /* count the number of hits */ 467 nrows = 0; 468 for (j=0; j<M; j++) { 469 if (rowhit[j]) nrows++; 470 } 471 c->nrows[i] = nrows; 472 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 473 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 474 ierr = PetscLogObjectMemory((PetscObject)c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 475 nrows = 0; 476 for (j=0; j<M; j++) { 477 if (rowhit[j]) { 478 c->rows[i][nrows] = j; /* local row index */ 479 c->columnsforrow[i][nrows] = rowhit[j] - 1; /* global column index */ 480 nrows++; 481 } 482 } 483 } else { /*-------------------------------------------------------------------------------*/ 484 /* slow version, using rowhit as a linked list */ 485 PetscInt currentcol,fm,mfm; 486 rowhit[M] = M; 487 nrows = 0; 488 /* loop over columns*/ 489 for (j=0; j<nctot; j++) { 490 if (ctype == IS_COLORING_GHOSTED) { 491 col = ltog[cols[j]]; 492 } else { 493 col = cols[j]; 494 } 495 if (col >= cstart && col < cend) { 496 /* column is in diagonal block of matrix */ 497 rows = A_cj + A_ci[col-cstart]; 498 m = A_ci[col-cstart+1] - A_ci[col-cstart]; 499 } else { 500 #if defined(PETSC_USE_CTABLE) 501 ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr); 502 colb--; 503 #else 504 colb = aij->colmap[col] - 1; 505 #endif 506 if (colb == -1) { 507 m = 0; 508 } else { 509 rows = B_cj + B_ci[colb]; 510 m = B_ci[colb+1] - B_ci[colb]; 511 } 512 } 513 514 /* loop over columns marking them in rowhit */ 515 fm = M; /* fm points to first entry in linked list */ 516 for (k=0; k<m; k++) { 517 currentcol = *rows++; 518 /* is it already in the list? */ 519 do { 520 mfm = fm; 521 fm = rowhit[fm]; 522 } while (fm < currentcol); 523 /* not in list so add it */ 524 if (fm != currentcol) { 525 nrows++; 526 columnsforrow[currentcol] = col; 527 /* next three lines insert new entry into linked list */ 528 rowhit[mfm] = currentcol; 529 rowhit[currentcol] = fm; 530 fm = currentcol; 531 /* fm points to present position in list since we know the columns are sorted */ 532 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected"); 533 } 534 } 535 c->nrows[i] = nrows; 536 537 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr); 538 ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr); 539 ierr = PetscLogObjectMemory((PetscObject)c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr); 540 /* now store the linked list of rows into c->rows[i] */ 541 nrows = 0; 542 fm = rowhit[M]; 543 do { 544 c->rows[i][nrows] = fm; 545 c->columnsforrow[i][nrows++] = columnsforrow[fm]; 546 fm = rowhit[fm]; 547 } while (fm < M); 548 } /* ---------------------------------------------------------------------------------------*/ 549 ierr = PetscFree(cols);CHKERRQ(ierr); 550 } 551 552 /* Optimize by adding the vscale, and scaleforrow[][] fields */ 553 /* 554 vscale will contain the "diagonal" on processor scalings followed by the off processor 555 */ 556 if (ctype == IS_COLORING_GLOBAL) { 557 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),aij->A->rmap->n,PETSC_DETERMINE,aij->B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr); 558 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 559 for (k=0; k<c->ncolors; k++) { 560 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 561 for (l=0; l<c->nrows[k]; l++) { 562 col = c->columnsforrow[k][l]; 563 if (col >= cstart && col < cend) { 564 /* column is in diagonal block of matrix */ 565 colb = col - cstart; 566 } else { 567 /* column is in "off-processor" part */ 568 #if defined(PETSC_USE_CTABLE) 569 ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr); 570 colb--; 571 #else 572 colb = aij->colmap[col] - 1; 573 #endif 574 colb += cend - cstart; 575 } 576 c->vscaleforrow[k][l] = colb; 577 } 578 } 579 } else if (ctype == IS_COLORING_GHOSTED) { 580 /* Get gtol mapping */ 581 PetscInt N = mat->cmap->N,nlocal,*gtol; 582 ierr = PetscMalloc((N+1)*sizeof(PetscInt),>ol);CHKERRQ(ierr); 583 for (i=0; i<N; i++) gtol[i] = -1; 584 ierr = ISLocalToGlobalMappingGetSize(map,&nlocal);CHKERRQ(ierr); 585 for (i=0; i<nlocal; i++) gtol[ltog[i]] = i; 586 587 c->vscale = 0; /* will be created in MatFDColoringApply() */ 588 ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr); 589 for (k=0; k<c->ncolors; k++) { 590 ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr); 591 for (l=0; l<c->nrows[k]; l++) { 592 col = c->columnsforrow[k][l]; /* global column index */ 593 c->vscaleforrow[k][l] = gtol[col]; /* local column index */ 594 } 595 } 596 ierr = PetscFree(gtol);CHKERRQ(ierr); 597 } 598 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 599 600 ierr = PetscFree(rowhit);CHKERRQ(ierr); 601 ierr = PetscFree(columnsforrow);CHKERRQ(ierr); 602 ierr = MatRestoreColumnIJ(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr); 603 ierr = MatRestoreColumnIJ(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr); 604 if (map) {ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr);} 605 PetscFunctionReturn(0); 606 } 607 608 609 610 611 612 613