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