1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3 #include <../src/mat/impls/baij/mpi/mpibaij.h> 4 5 #undef __FUNCT__ 6 #define __FUNCT__ "MatFDColoringApply_BAIJ" 7 PetscErrorCode MatFDColoringApply_BAIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 8 { 9 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 10 PetscErrorCode ierr; 11 PetscInt k,cstart,cend,l,row,col,nz,spidx,i,j; 12 PetscScalar dx=0.0,*xx,*w3_array,*dy_i,*dy=coloring->dy; 13 PetscScalar *vscale_array; 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,0,0,0,0);CHKERRQ(ierr); 28 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 29 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);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 = VecGetArray(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 = VecRestoreArray(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 #undef __FUNCT__ 159 #define __FUNCT__ "MatFDColoringApply_AIJ" 160 PetscErrorCode MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 161 { 162 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 163 PetscErrorCode ierr; 164 PetscInt k,cstart,cend,l,row,col,nz; 165 PetscScalar dx=0.0,*y,*xx,*w3_array; 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 PetscInt ctype=coloring->ctype,nxloc,nrows_k; 171 MatEntry *Jentry=coloring->matentry; 172 MatEntry2 *Jentry2=coloring->matentry2; 173 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 174 175 PetscFunctionBegin; 176 /* (1) Set w1 = F(x1) */ 177 if (!coloring->fset) { 178 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 179 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 180 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 181 } else { 182 coloring->fset = PETSC_FALSE; 183 } 184 185 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 186 if (coloring->htype[0] == 'w') { 187 /* vscale = 1./dx is a constant scalar */ 188 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 189 dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon); 190 } else { 191 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 192 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 193 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 194 for (col=0; col<nxloc; col++) { 195 dx = xx[col]; 196 if (PetscAbsScalar(dx) < umin) { 197 if (PetscRealPart(dx) >= 0.0) dx = umin; 198 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 199 } 200 dx *= epsilon; 201 vscale_array[col] = 1.0/dx; 202 } 203 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 204 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 205 } 206 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 207 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 208 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 209 } 210 211 /* (3) Loop over each color */ 212 if (!coloring->w3) { 213 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 214 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 215 } 216 w3 = coloring->w3; 217 218 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 219 if (vscale) { 220 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 221 } 222 nz = 0; 223 224 if (coloring->bcols > 1) { /* use blocked insertion of Jentry */ 225 PetscInt i,m=J->rmap->n,nbcols,bcols=coloring->bcols; 226 PetscScalar *dy=coloring->dy,*dy_k; 227 228 nbcols = 0; 229 for (k=0; k<ncolors; k+=bcols) { 230 coloring->currentcolor = k; 231 232 /* 233 (3-1) Loop over each column associated with color 234 adding the perturbation to the vector w3 = x1 + dx. 235 */ 236 237 dy_k = dy; 238 if (k + bcols > ncolors) bcols = ncolors - k; 239 for (i=0; i<bcols; i++) { 240 241 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 242 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 243 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 244 if (coloring->htype[0] == 'w') { 245 for (l=0; l<ncolumns[k+i]; l++) { 246 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 247 w3_array[col] += 1.0/dx; 248 } 249 } else { /* htype == 'ds' */ 250 vscale_array -= cstart; /* shift pointer so global index can be used */ 251 for (l=0; l<ncolumns[k+i]; l++) { 252 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 253 w3_array[col] += 1.0/vscale_array[col]; 254 } 255 vscale_array += cstart; 256 } 257 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 258 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 259 260 /* 261 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 262 w2 = F(x1 + dx) - F(x1) 263 */ 264 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 265 ierr = VecPlaceArray(w2,dy_k);CHKERRQ(ierr); /* place w2 to the array dy_i */ 266 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 267 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 268 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 269 ierr = VecResetArray(w2);CHKERRQ(ierr); 270 dy_k += m; /* points to dy+i*nxloc */ 271 } 272 273 /* 274 (3-3) Loop over block rows of vector, putting results into Jacobian matrix 275 */ 276 nrows_k = nrows[nbcols++]; 277 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 278 279 if (coloring->htype[0] == 'w') { 280 for (l=0; l<nrows_k; l++) { 281 row = Jentry2[nz].row; /* local row index */ 282 *(Jentry2[nz++].valaddr) = dy[row]*dx; 283 } 284 } else { /* htype == 'ds' */ 285 for (l=0; l<nrows_k; l++) { 286 row = Jentry[nz].row; /* local row index */ 287 *(Jentry[nz].valaddr) = dy[row]*vscale_array[Jentry[nz].col]; 288 nz++; 289 } 290 } 291 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 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 #undef __FUNCT__ 360 #define __FUNCT__ "MatFDColoringSetUp_MPIXAIJ" 361 PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 362 { 363 PetscErrorCode ierr; 364 PetscMPIInt size,*ncolsonproc,*disp,nn; 365 PetscInt i,n,nrows,nrows_i,j,k,m,ncols,col,*rowhit,cstart,cend,colb; 366 const PetscInt *is,*A_ci,*A_cj,*B_ci,*B_cj,*row=NULL,*ltog=NULL; 367 PetscInt nis=iscoloring->n,nctot,*cols; 368 IS *isa; 369 ISLocalToGlobalMapping map=mat->cmap->mapping; 370 PetscInt ctype=c->ctype,*spidxA,*spidxB,nz,bs,bs2,spidx; 371 Mat A,B; 372 PetscScalar *A_val,*B_val,**valaddrhit; 373 MatEntry *Jentry; 374 MatEntry2 *Jentry2; 375 PetscBool isBAIJ; 376 PetscInt bcols=c->bcols; 377 #if defined(PETSC_USE_CTABLE) 378 PetscTable colmap=NULL; 379 #else 380 PetscInt *colmap=NULL; /* local col number of off-diag col */ 381 #endif 382 383 PetscFunctionBegin; 384 if (ctype == IS_COLORING_GHOSTED) { 385 if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 386 ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr); 387 } 388 389 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 390 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 391 if (isBAIJ) { 392 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 393 Mat_SeqBAIJ *spA,*spB; 394 A = baij->A; spA = (Mat_SeqBAIJ*)A->data; A_val = spA->a; 395 B = baij->B; spB = (Mat_SeqBAIJ*)B->data; B_val = spB->a; 396 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 397 if (!baij->colmap) { 398 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 399 colmap = baij->colmap; 400 } 401 ierr = MatGetColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 402 ierr = MatGetColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 403 404 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 405 PetscInt *garray; 406 ierr = PetscMalloc1(B->cmap->n,&garray);CHKERRQ(ierr); 407 for (i=0; i<baij->B->cmap->n/bs; i++) { 408 for (j=0; j<bs; j++) { 409 garray[i*bs+j] = bs*baij->garray[i]+j; 410 } 411 } 412 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 413 ierr = PetscFree(garray);CHKERRQ(ierr); 414 } 415 } else { 416 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 417 Mat_SeqAIJ *spA,*spB; 418 A = aij->A; spA = (Mat_SeqAIJ*)A->data; A_val = spA->a; 419 B = aij->B; spB = (Mat_SeqAIJ*)B->data; B_val = spB->a; 420 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 421 if (!aij->colmap) { 422 /* Allow access to data structures of local part of matrix 423 - creates aij->colmap which maps global column number to local number in part B */ 424 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 425 colmap = aij->colmap; 426 } 427 ierr = MatGetColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 428 ierr = MatGetColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 429 430 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 431 432 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 433 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr); 434 } 435 } 436 437 m = mat->rmap->n/bs; 438 cstart = mat->cmap->rstart/bs; 439 cend = mat->cmap->rend/bs; 440 441 ierr = PetscMalloc1(nis,&c->ncolumns);CHKERRQ(ierr); 442 ierr = PetscMalloc1(nis,&c->columns);CHKERRQ(ierr); 443 ierr = PetscMalloc1(nis,&c->nrows);CHKERRQ(ierr); 444 ierr = PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));CHKERRQ(ierr); 445 446 if (c->htype[0] == 'd') { 447 ierr = PetscMalloc1(nz,&Jentry);CHKERRQ(ierr); 448 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));CHKERRQ(ierr); 449 c->matentry = Jentry; 450 } else if (c->htype[0] == 'w') { 451 ierr = PetscMalloc1(nz,&Jentry2);CHKERRQ(ierr); 452 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry2));CHKERRQ(ierr); 453 c->matentry2 = Jentry2; 454 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"htype is not supported"); 455 456 ierr = PetscMalloc2(m+1,&rowhit,m+1,&valaddrhit);CHKERRQ(ierr); 457 nz = 0; 458 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 459 for (i=0; i<nis; i++) { /* for each local color */ 460 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 461 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 462 463 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 464 if (n) { 465 ierr = PetscMalloc1(n,&c->columns[i]);CHKERRQ(ierr); 466 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 467 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 468 } else { 469 c->columns[i] = 0; 470 } 471 472 if (ctype == IS_COLORING_GLOBAL) { 473 /* Determine nctot, the total (parallel) number of columns of this color */ 474 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 475 ierr = PetscMalloc2(size,&ncolsonproc,size,&disp);CHKERRQ(ierr); 476 477 /* ncolsonproc[j]: local ncolumns on proc[j] of this color */ 478 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 479 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 480 nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j]; 481 if (!nctot) { 482 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 483 } 484 485 disp[0] = 0; 486 for (j=1; j<size; j++) { 487 disp[j] = disp[j-1] + ncolsonproc[j-1]; 488 } 489 490 /* Get cols, the complete list of columns for this color on each process */ 491 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 492 ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 493 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 494 } else if (ctype == IS_COLORING_GHOSTED) { 495 /* Determine local number of columns of this color on this process, including ghost points */ 496 nctot = n; 497 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 498 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 499 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 500 501 /* Mark all rows affect by these columns */ 502 ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr); 503 bs2 = bs*bs; 504 nrows_i = 0; 505 for (j=0; j<nctot; j++) { /* loop over columns*/ 506 if (ctype == IS_COLORING_GHOSTED) { 507 col = ltog[cols[j]]; 508 } else { 509 col = cols[j]; 510 } 511 if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */ 512 row = A_cj + A_ci[col-cstart]; 513 nrows = A_ci[col-cstart+1] - A_ci[col-cstart]; 514 nrows_i += nrows; 515 /* loop over columns of A marking them in rowhit */ 516 for (k=0; k<nrows; k++) { 517 /* set valaddrhit for part A */ 518 spidx = bs2*spidxA[A_ci[col-cstart] + k]; 519 valaddrhit[*row] = &A_val[spidx]; 520 rowhit[*row++] = col - cstart + 1; /* local column index */ 521 } 522 } else { /* column is in B, off-diagonal block of mat */ 523 #if defined(PETSC_USE_CTABLE) 524 ierr = PetscTableFind(colmap,col+1,&colb);CHKERRQ(ierr); 525 colb--; 526 #else 527 colb = colmap[col] - 1; /* local column index */ 528 #endif 529 if (colb == -1) { 530 nrows = 0; 531 } else { 532 colb = colb/bs; 533 row = B_cj + B_ci[colb]; 534 nrows = B_ci[colb+1] - B_ci[colb]; 535 } 536 nrows_i += nrows; 537 /* loop over columns of B marking them in rowhit */ 538 for (k=0; k<nrows; k++) { 539 /* set valaddrhit for part B */ 540 spidx = bs2*spidxB[B_ci[colb] + k]; 541 valaddrhit[*row] = &B_val[spidx]; 542 rowhit[*row++] = colb + 1 + cend - cstart; /* local column index */ 543 } 544 } 545 } 546 c->nrows[i] = nrows_i; 547 548 if (c->htype[0] == 'd') { 549 for (j=0; j<m; j++) { 550 if (rowhit[j]) { 551 Jentry[nz].row = j; /* local row index */ 552 Jentry[nz].col = rowhit[j] - 1; /* local column index */ 553 Jentry[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 554 nz++; 555 } 556 } 557 } else { /* c->htype == 'wp' */ 558 for (j=0; j<m; j++) { 559 if (rowhit[j]) { 560 Jentry2[nz].row = j; /* local row index */ 561 Jentry2[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 562 nz++; 563 } 564 } 565 } 566 ierr = PetscFree(cols);CHKERRQ(ierr); 567 } 568 569 if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */ 570 ierr = MatFDColoringSetUpBlocked_AIJ_Private(mat,c,nz);CHKERRQ(ierr); 571 } 572 573 if (isBAIJ) { 574 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 575 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 576 ierr = PetscMalloc1(bs*mat->rmap->n,&c->dy);CHKERRQ(ierr); 577 } else { 578 ierr = MatRestoreColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 579 ierr = MatRestoreColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 580 } 581 582 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 583 ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr); 584 585 if (ctype == IS_COLORING_GHOSTED) { 586 ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr); 587 } 588 ierr = PetscInfo3(c,"ncolors %D, brows %D and bcols %D are used.\n",c->ncolors,c->brows,c->bcols);CHKERRQ(ierr); 589 PetscFunctionReturn(0); 590 } 591 592 #undef __FUNCT__ 593 #define __FUNCT__ "MatFDColoringCreate_MPIXAIJ" 594 PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 595 { 596 PetscErrorCode ierr; 597 PetscInt bs,nis=iscoloring->n,m=mat->rmap->n; 598 PetscBool isBAIJ; 599 600 PetscFunctionBegin; 601 /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian; 602 bcols is chosen s.t. dy-array takes 50% of memory space as mat */ 603 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 604 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 605 if (isBAIJ) { 606 c->brows = m; 607 c->bcols = 1; 608 } else { /* mpiaij matrix */ 609 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 610 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 611 Mat_SeqAIJ *spA,*spB; 612 Mat A,B; 613 PetscInt nz,brows,bcols; 614 PetscReal mem; 615 616 bs = 1; /* only bs=1 is supported for MPIAIJ matrix */ 617 618 A = aij->A; spA = (Mat_SeqAIJ*)A->data; 619 B = aij->B; spB = (Mat_SeqAIJ*)B->data; 620 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 621 mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt); 622 bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar))); 623 brows = 1000/bcols; 624 if (bcols > nis) bcols = nis; 625 if (brows == 0 || brows > m) brows = m; 626 c->brows = brows; 627 c->bcols = bcols; 628 } 629 630 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 631 c->N = mat->cmap->N/bs; 632 c->m = mat->rmap->n/bs; 633 c->rstart = mat->rmap->rstart/bs; 634 c->ncolors = nis; 635 PetscFunctionReturn(0); 636 } 637