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