1 #include <../src/mat/impls/sell/mpi/mpisell.h> 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3 #include <../src/mat/impls/baij/mpi/mpibaij.h> 4 #include <petsc/private/isimpl.h> 5 6 PetscErrorCode MatFDColoringApply_BAIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 7 { 8 PetscErrorCode (*f)(void*,Vec,Vec,void*)=(PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 9 PetscErrorCode ierr; 10 PetscInt k,cstart,cend,l,row,col,nz,spidx,i,j; 11 PetscScalar dx=0.0,*w3_array,*dy_i,*dy=coloring->dy; 12 PetscScalar *vscale_array; 13 const PetscScalar *xx; 14 PetscReal epsilon=coloring->error_rel,umin=coloring->umin,unorm; 15 Vec w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale; 16 void *fctx=coloring->fctx; 17 PetscInt ctype=coloring->ctype,nxloc,nrows_k; 18 PetscScalar *valaddr; 19 MatEntry *Jentry=coloring->matentry; 20 MatEntry2 *Jentry2=coloring->matentry2; 21 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 22 PetscInt bs=J->rmap->bs; 23 24 PetscFunctionBegin; 25 /* (1) Set w1 = F(x1) */ 26 if (!coloring->fset) { 27 ierr = PetscLogEventBegin(MAT_FDColoringFunction,coloring,0,0,0);CHKERRQ(ierr); 28 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 29 ierr = PetscLogEventEnd(MAT_FDColoringFunction,coloring,0,0,0);CHKERRQ(ierr); 30 } else { 31 coloring->fset = PETSC_FALSE; 32 } 33 34 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 35 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 36 if (coloring->htype[0] == 'w') { 37 /* vscale = dx is a constant scalar */ 38 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 39 dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon); 40 } else { 41 ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr); 42 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 43 for (col=0; col<nxloc; col++) { 44 dx = xx[col]; 45 if (PetscAbsScalar(dx) < umin) { 46 if (PetscRealPart(dx) >= 0.0) dx = umin; 47 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 48 } 49 dx *= epsilon; 50 vscale_array[col] = 1.0/dx; 51 } 52 ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr); 53 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 54 } 55 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 56 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 57 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 58 } 59 60 /* (3) Loop over each color */ 61 if (!coloring->w3) { 62 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 63 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 64 } 65 w3 = coloring->w3; 66 67 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 68 if (vscale) { 69 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 70 } 71 nz = 0; 72 for (k=0; k<ncolors; k++) { 73 coloring->currentcolor = k; 74 75 /* 76 (3-1) Loop over each column associated with color 77 adding the perturbation to the vector w3 = x1 + dx. 78 */ 79 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 80 dy_i = dy; 81 for (i=0; i<bs; i++) { /* Loop over a block of columns */ 82 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 83 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 84 if (coloring->htype[0] == 'w') { 85 for (l=0; l<ncolumns[k]; l++) { 86 col = i + bs*coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 87 w3_array[col] += 1.0/dx; 88 if (i) w3_array[col-1] -= 1.0/dx; /* resume original w3[col-1] */ 89 } 90 } else { /* htype == 'ds' */ 91 vscale_array -= cstart; /* shift pointer so global index can be used */ 92 for (l=0; l<ncolumns[k]; l++) { 93 col = i + bs*coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 94 w3_array[col] += 1.0/vscale_array[col]; 95 if (i) w3_array[col-1] -= 1.0/vscale_array[col-1]; /* resume original w3[col-1] */ 96 } 97 vscale_array += cstart; 98 } 99 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 100 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 101 102 /* 103 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 104 w2 = F(x1 + dx) - F(x1) 105 */ 106 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 107 ierr = VecPlaceArray(w2,dy_i);CHKERRQ(ierr); /* place w2 to the array dy_i */ 108 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 109 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 110 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 111 ierr = VecResetArray(w2);CHKERRQ(ierr); 112 dy_i += nxloc; /* points to dy+i*nxloc */ 113 } 114 115 /* 116 (3-3) Loop over rows of vector, putting results into Jacobian matrix 117 */ 118 nrows_k = nrows[k]; 119 if (coloring->htype[0] == 'w') { 120 for (l=0; l<nrows_k; l++) { 121 row = bs*Jentry2[nz].row; /* local row index */ 122 valaddr = Jentry2[nz++].valaddr; 123 spidx = 0; 124 dy_i = dy; 125 for (i=0; i<bs; i++) { /* column of the block */ 126 for (j=0; j<bs; j++) { /* row of the block */ 127 valaddr[spidx++] = dy_i[row+j]*dx; 128 } 129 dy_i += nxloc; /* points to dy+i*nxloc */ 130 } 131 } 132 } else { /* htype == 'ds' */ 133 for (l=0; l<nrows_k; l++) { 134 row = bs*Jentry[nz].row; /* local row index */ 135 col = bs*Jentry[nz].col; /* local column index */ 136 valaddr = Jentry[nz++].valaddr; 137 spidx = 0; 138 dy_i = dy; 139 for (i=0; i<bs; i++) { /* column of the block */ 140 for (j=0; j<bs; j++) { /* row of the block */ 141 valaddr[spidx++] = dy_i[row+j]*vscale_array[col+i]; 142 } 143 dy_i += nxloc; /* points to dy+i*nxloc */ 144 } 145 } 146 } 147 } 148 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 149 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 150 if (vscale) { 151 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 152 } 153 154 coloring->currentcolor = -1; 155 PetscFunctionReturn(0); 156 } 157 158 /* this is declared PETSC_EXTERN because it is used by MatFDColoringUseDM() which is in the DM library */ 159 PetscErrorCode MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 160 { 161 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 162 PetscErrorCode ierr; 163 PetscInt k,cstart,cend,l,row,col,nz; 164 PetscScalar dx=0.0,*y,*w3_array; 165 const PetscScalar *xx; 166 PetscScalar *vscale_array; 167 PetscReal epsilon=coloring->error_rel,umin=coloring->umin,unorm; 168 Vec w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale; 169 void *fctx=coloring->fctx; 170 ISColoringType ctype=coloring->ctype; 171 PetscInt nxloc,nrows_k; 172 MatEntry *Jentry=coloring->matentry; 173 MatEntry2 *Jentry2=coloring->matentry2; 174 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 175 176 PetscFunctionBegin; 177 if ((ctype == IS_COLORING_LOCAL) && (J->ops->fdcoloringapply == MatFDColoringApply_AIJ)) SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_SUP,"Must call MatColoringUseDM() with IS_COLORING_LOCAL"); 178 /* (1) Set w1 = F(x1) */ 179 if (!coloring->fset) { 180 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 181 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 182 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 183 } else { 184 coloring->fset = PETSC_FALSE; 185 } 186 187 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 188 if (coloring->htype[0] == 'w') { 189 /* vscale = 1./dx is a constant scalar */ 190 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 191 dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon); 192 } else { 193 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 194 ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr); 195 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 196 for (col=0; col<nxloc; col++) { 197 dx = xx[col]; 198 if (PetscAbsScalar(dx) < umin) { 199 if (PetscRealPart(dx) >= 0.0) dx = umin; 200 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 201 } 202 dx *= epsilon; 203 vscale_array[col] = 1.0/dx; 204 } 205 ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr); 206 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 207 } 208 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 209 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 210 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 211 } 212 213 /* (3) Loop over each color */ 214 if (!coloring->w3) { 215 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 216 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 217 } 218 w3 = coloring->w3; 219 220 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 221 if (vscale) { 222 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 223 } 224 nz = 0; 225 226 if (coloring->bcols > 1) { /* use blocked insertion of Jentry */ 227 PetscInt i,m=J->rmap->n,nbcols,bcols=coloring->bcols; 228 PetscScalar *dy=coloring->dy,*dy_k; 229 230 nbcols = 0; 231 for (k=0; k<ncolors; k+=bcols) { 232 233 /* 234 (3-1) Loop over each column associated with color 235 adding the perturbation to the vector w3 = x1 + dx. 236 */ 237 238 dy_k = dy; 239 if (k + bcols > ncolors) bcols = ncolors - k; 240 for (i=0; i<bcols; i++) { 241 coloring->currentcolor = k+i; 242 243 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 244 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 245 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 246 if (coloring->htype[0] == 'w') { 247 for (l=0; l<ncolumns[k+i]; l++) { 248 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 249 w3_array[col] += 1.0/dx; 250 } 251 } else { /* htype == 'ds' */ 252 vscale_array -= cstart; /* shift pointer so global index can be used */ 253 for (l=0; l<ncolumns[k+i]; l++) { 254 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 255 w3_array[col] += 1.0/vscale_array[col]; 256 } 257 vscale_array += cstart; 258 } 259 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 260 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 261 262 /* 263 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 264 w2 = F(x1 + dx) - F(x1) 265 */ 266 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 267 ierr = VecPlaceArray(w2,dy_k);CHKERRQ(ierr); /* place w2 to the array dy_i */ 268 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 269 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 270 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 271 ierr = VecResetArray(w2);CHKERRQ(ierr); 272 dy_k += m; /* points to dy+i*nxloc */ 273 } 274 275 /* 276 (3-3) Loop over block rows of vector, putting results into Jacobian matrix 277 */ 278 nrows_k = nrows[nbcols++]; 279 280 if (coloring->htype[0] == 'w') { 281 for (l=0; l<nrows_k; l++) { 282 row = Jentry2[nz].row; /* local row index */ 283 *(Jentry2[nz++].valaddr) = dy[row]*dx; 284 } 285 } else { /* htype == 'ds' */ 286 for (l=0; l<nrows_k; l++) { 287 row = Jentry[nz].row; /* local row index */ 288 *(Jentry[nz].valaddr) = dy[row]*vscale_array[Jentry[nz].col]; 289 nz++; 290 } 291 } 292 } 293 } else { /* bcols == 1 */ 294 for (k=0; k<ncolors; k++) { 295 coloring->currentcolor = k; 296 297 /* 298 (3-1) Loop over each column associated with color 299 adding the perturbation to the vector w3 = x1 + dx. 300 */ 301 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 302 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 303 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 304 if (coloring->htype[0] == 'w') { 305 for (l=0; l<ncolumns[k]; l++) { 306 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 307 w3_array[col] += 1.0/dx; 308 } 309 } else { /* htype == 'ds' */ 310 vscale_array -= cstart; /* shift pointer so global index can be used */ 311 for (l=0; l<ncolumns[k]; l++) { 312 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 313 w3_array[col] += 1.0/vscale_array[col]; 314 } 315 vscale_array += cstart; 316 } 317 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 318 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 319 320 /* 321 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 322 w2 = F(x1 + dx) - F(x1) 323 */ 324 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 325 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 326 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 327 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 328 329 /* 330 (3-3) Loop over rows of vector, putting results into Jacobian matrix 331 */ 332 nrows_k = nrows[k]; 333 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 334 if (coloring->htype[0] == 'w') { 335 for (l=0; l<nrows_k; l++) { 336 row = Jentry2[nz].row; /* local row index */ 337 *(Jentry2[nz++].valaddr) = y[row]*dx; 338 } 339 } else { /* htype == 'ds' */ 340 for (l=0; l<nrows_k; l++) { 341 row = Jentry[nz].row; /* local row index */ 342 *(Jentry[nz].valaddr) = y[row]*vscale_array[Jentry[nz].col]; 343 nz++; 344 } 345 } 346 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 347 } 348 } 349 350 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 351 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 352 if (vscale) { 353 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 354 } 355 coloring->currentcolor = -1; 356 PetscFunctionReturn(0); 357 } 358 359 PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 360 { 361 PetscErrorCode ierr; 362 PetscMPIInt size,*ncolsonproc,*disp,nn; 363 PetscInt i,n,nrows,nrows_i,j,k,m,ncols,col,*rowhit,cstart,cend,colb; 364 const PetscInt *is,*A_ci,*A_cj,*B_ci,*B_cj,*row=NULL,*ltog=NULL; 365 PetscInt nis=iscoloring->n,nctot,*cols; 366 IS *isa; 367 ISLocalToGlobalMapping map=mat->cmap->mapping; 368 PetscInt ctype=c->ctype,*spidxA,*spidxB,nz,bs,bs2,spidx; 369 Mat A,B; 370 PetscScalar *A_val,*B_val,**valaddrhit; 371 MatEntry *Jentry; 372 MatEntry2 *Jentry2; 373 PetscBool isBAIJ,isSELL; 374 PetscInt bcols=c->bcols; 375 #if defined(PETSC_USE_CTABLE) 376 PetscTable colmap=NULL; 377 #else 378 PetscInt *colmap=NULL; /* local col number of off-diag col */ 379 #endif 380 381 PetscFunctionBegin; 382 if (ctype == IS_COLORING_LOCAL) { 383 if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 384 ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr); 385 } 386 387 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 388 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 389 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPISELL,&isSELL);CHKERRQ(ierr); 390 if (isBAIJ) { 391 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 392 Mat_SeqBAIJ *spA,*spB; 393 A = baij->A; spA = (Mat_SeqBAIJ*)A->data; A_val = spA->a; 394 B = baij->B; spB = (Mat_SeqBAIJ*)B->data; B_val = spB->a; 395 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 396 if (!baij->colmap) { 397 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 398 } 399 colmap = baij->colmap; 400 ierr = MatGetColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 401 ierr = MatGetColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 402 403 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 404 PetscInt *garray; 405 ierr = PetscMalloc1(B->cmap->n,&garray);CHKERRQ(ierr); 406 for (i=0; i<baij->B->cmap->n/bs; i++) { 407 for (j=0; j<bs; j++) { 408 garray[i*bs+j] = bs*baij->garray[i]+j; 409 } 410 } 411 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 412 ierr = PetscFree(garray);CHKERRQ(ierr); 413 } 414 } else if (isSELL) { 415 Mat_MPISELL *sell=(Mat_MPISELL*)mat->data; 416 Mat_SeqSELL *spA,*spB; 417 A = sell->A; spA = (Mat_SeqSELL*)A->data; A_val = spA->val; 418 B = sell->B; spB = (Mat_SeqSELL*)B->data; B_val = spB->val; 419 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 420 if (!sell->colmap) { 421 /* Allow access to data structures of local part of matrix 422 - creates aij->colmap which maps global column number to local number in part B */ 423 ierr = MatCreateColmap_MPISELL_Private(mat);CHKERRQ(ierr); 424 } 425 colmap = sell->colmap; 426 ierr = MatGetColumnIJ_SeqSELL_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 427 ierr = MatGetColumnIJ_SeqSELL_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 428 429 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 430 431 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 432 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,sell->garray,&c->vscale);CHKERRQ(ierr); 433 } 434 } else { 435 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 436 Mat_SeqAIJ *spA,*spB; 437 A = aij->A; spA = (Mat_SeqAIJ*)A->data; A_val = spA->a; 438 B = aij->B; spB = (Mat_SeqAIJ*)B->data; B_val = spB->a; 439 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 440 if (!aij->colmap) { 441 /* Allow access to data structures of local part of matrix 442 - creates aij->colmap which maps global column number to local number in part B */ 443 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 444 } 445 colmap = aij->colmap; 446 ierr = MatGetColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 447 ierr = MatGetColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 448 449 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 450 451 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 452 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr); 453 } 454 } 455 456 m = mat->rmap->n/bs; 457 cstart = mat->cmap->rstart/bs; 458 cend = mat->cmap->rend/bs; 459 460 ierr = PetscMalloc1(nis,&c->ncolumns);CHKERRQ(ierr); 461 ierr = PetscMalloc1(nis,&c->columns);CHKERRQ(ierr); 462 ierr = PetscCalloc1(nis,&c->nrows);CHKERRQ(ierr); 463 ierr = PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));CHKERRQ(ierr); 464 465 if (c->htype[0] == 'd') { 466 ierr = PetscMalloc1(nz,&Jentry);CHKERRQ(ierr); 467 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));CHKERRQ(ierr); 468 c->matentry = Jentry; 469 } else if (c->htype[0] == 'w') { 470 ierr = PetscMalloc1(nz,&Jentry2);CHKERRQ(ierr); 471 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry2));CHKERRQ(ierr); 472 c->matentry2 = Jentry2; 473 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"htype is not supported"); 474 475 ierr = PetscMalloc2(m+1,&rowhit,m+1,&valaddrhit);CHKERRQ(ierr); 476 nz = 0; 477 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 478 for (i=0; i<nis; i++) { /* for each local color */ 479 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 480 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 481 482 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 483 if (n) { 484 ierr = PetscMalloc1(n,&c->columns[i]);CHKERRQ(ierr); 485 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 486 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 487 } else { 488 c->columns[i] = 0; 489 } 490 491 if (ctype == IS_COLORING_GLOBAL) { 492 /* Determine nctot, the total (parallel) number of columns of this color */ 493 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 494 ierr = PetscMalloc2(size,&ncolsonproc,size,&disp);CHKERRQ(ierr); 495 496 /* ncolsonproc[j]: local ncolumns on proc[j] of this color */ 497 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 498 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 499 nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j]; 500 if (!nctot) { 501 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 502 } 503 504 disp[0] = 0; 505 for (j=1; j<size; j++) { 506 disp[j] = disp[j-1] + ncolsonproc[j-1]; 507 } 508 509 /* Get cols, the complete list of columns for this color on each process */ 510 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 511 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 512 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 513 } else if (ctype == IS_COLORING_LOCAL) { 514 /* Determine local number of columns of this color on this process, including ghost points */ 515 nctot = n; 516 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 517 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 518 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 519 520 /* Mark all rows affect by these columns */ 521 ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr); 522 bs2 = bs*bs; 523 nrows_i = 0; 524 for (j=0; j<nctot; j++) { /* loop over columns*/ 525 if (ctype == IS_COLORING_LOCAL) { 526 col = ltog[cols[j]]; 527 } else { 528 col = cols[j]; 529 } 530 if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */ 531 row = A_cj + A_ci[col-cstart]; 532 nrows = A_ci[col-cstart+1] - A_ci[col-cstart]; 533 nrows_i += nrows; 534 /* loop over columns of A marking them in rowhit */ 535 for (k=0; k<nrows; k++) { 536 /* set valaddrhit for part A */ 537 spidx = bs2*spidxA[A_ci[col-cstart] + k]; 538 valaddrhit[*row] = &A_val[spidx]; 539 rowhit[*row++] = col - cstart + 1; /* local column index */ 540 } 541 } else { /* column is in B, off-diagonal block of mat */ 542 #if defined(PETSC_USE_CTABLE) 543 ierr = PetscTableFind(colmap,col+1,&colb);CHKERRQ(ierr); 544 colb--; 545 #else 546 colb = colmap[col] - 1; /* local column index */ 547 #endif 548 if (colb == -1) { 549 nrows = 0; 550 } else { 551 colb = colb/bs; 552 row = B_cj + B_ci[colb]; 553 nrows = B_ci[colb+1] - B_ci[colb]; 554 } 555 nrows_i += nrows; 556 /* loop over columns of B marking them in rowhit */ 557 for (k=0; k<nrows; k++) { 558 /* set valaddrhit for part B */ 559 spidx = bs2*spidxB[B_ci[colb] + k]; 560 valaddrhit[*row] = &B_val[spidx]; 561 rowhit[*row++] = colb + 1 + cend - cstart; /* local column index */ 562 } 563 } 564 } 565 c->nrows[i] = nrows_i; 566 567 if (c->htype[0] == 'd') { 568 for (j=0; j<m; j++) { 569 if (rowhit[j]) { 570 Jentry[nz].row = j; /* local row index */ 571 Jentry[nz].col = rowhit[j] - 1; /* local column index */ 572 Jentry[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 573 nz++; 574 } 575 } 576 } else { /* c->htype == 'wp' */ 577 for (j=0; j<m; j++) { 578 if (rowhit[j]) { 579 Jentry2[nz].row = j; /* local row index */ 580 Jentry2[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 581 nz++; 582 } 583 } 584 } 585 ierr = PetscFree(cols);CHKERRQ(ierr); 586 } 587 588 if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */ 589 ierr = MatFDColoringSetUpBlocked_AIJ_Private(mat,c,nz);CHKERRQ(ierr); 590 } 591 592 if (isBAIJ) { 593 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 594 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 595 ierr = PetscMalloc1(bs*mat->rmap->n,&c->dy);CHKERRQ(ierr); 596 } else if (isSELL) { 597 ierr = MatRestoreColumnIJ_SeqSELL_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 598 ierr = MatRestoreColumnIJ_SeqSELL_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 599 }else { 600 ierr = MatRestoreColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 601 ierr = MatRestoreColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 602 } 603 604 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 605 ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr); 606 607 if (ctype == IS_COLORING_LOCAL) { 608 ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr); 609 } 610 ierr = PetscInfo3(c,"ncolors %D, brows %D and bcols %D are used.\n",c->ncolors,c->brows,c->bcols);CHKERRQ(ierr); 611 PetscFunctionReturn(0); 612 } 613 614 PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 615 { 616 PetscErrorCode ierr; 617 PetscInt bs,nis=iscoloring->n,m=mat->rmap->n; 618 PetscBool isBAIJ,isSELL; 619 620 PetscFunctionBegin; 621 /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian; 622 bcols is chosen s.t. dy-array takes 50% of memory space as mat */ 623 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 624 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 625 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPISELL,&isSELL);CHKERRQ(ierr); 626 if (isBAIJ || m == 0) { 627 c->brows = m; 628 c->bcols = 1; 629 } else if (isSELL) { 630 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 631 Mat_MPISELL *sell=(Mat_MPISELL*)mat->data; 632 Mat_SeqSELL *spA,*spB; 633 Mat A,B; 634 PetscInt nz,brows,bcols; 635 PetscReal mem; 636 637 bs = 1; /* only bs=1 is supported for MPISELL matrix */ 638 639 A = sell->A; spA = (Mat_SeqSELL*)A->data; 640 B = sell->B; spB = (Mat_SeqSELL*)B->data; 641 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 642 mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt); 643 bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar))); 644 brows = 1000/bcols; 645 if (bcols > nis) bcols = nis; 646 if (brows == 0 || brows > m) brows = m; 647 c->brows = brows; 648 c->bcols = bcols; 649 } else { /* mpiaij matrix */ 650 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 651 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 652 Mat_SeqAIJ *spA,*spB; 653 Mat A,B; 654 PetscInt nz,brows,bcols; 655 PetscReal mem; 656 657 bs = 1; /* only bs=1 is supported for MPIAIJ matrix */ 658 659 A = aij->A; spA = (Mat_SeqAIJ*)A->data; 660 B = aij->B; spB = (Mat_SeqAIJ*)B->data; 661 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 662 mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt); 663 bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar))); 664 brows = 1000/bcols; 665 if (bcols > nis) bcols = nis; 666 if (brows == 0 || brows > m) brows = m; 667 c->brows = brows; 668 c->bcols = bcols; 669 } 670 671 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 672 c->N = mat->cmap->N/bs; 673 c->m = mat->rmap->n/bs; 674 c->rstart = mat->rmap->rstart/bs; 675 c->ncolors = nis; 676 PetscFunctionReturn(0); 677 } 678