1 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 #undef __FUNCT__ 7 #define __FUNCT__ "MatFDColoringApply_BAIJ" 8 PetscErrorCode MatFDColoringApply_BAIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 9 { 10 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 11 PetscErrorCode ierr; 12 PetscInt k,cstart,cend,l,row,col,nz,spidx,i,j; 13 PetscScalar dx=0.0,*w3_array,*dy_i,*dy=coloring->dy; 14 PetscScalar *vscale_array; 15 const PetscScalar *xx; 16 PetscReal epsilon=coloring->error_rel,umin=coloring->umin,unorm; 17 Vec w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale; 18 void *fctx=coloring->fctx; 19 PetscInt ctype=coloring->ctype,nxloc,nrows_k; 20 PetscScalar *valaddr; 21 MatEntry *Jentry=coloring->matentry; 22 MatEntry2 *Jentry2=coloring->matentry2; 23 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 24 PetscInt bs=J->rmap->bs; 25 26 PetscFunctionBegin; 27 /* (1) Set w1 = F(x1) */ 28 if (!coloring->fset) { 29 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 30 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 31 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 32 } else { 33 coloring->fset = PETSC_FALSE; 34 } 35 36 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 37 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 38 if (coloring->htype[0] == 'w') { 39 /* vscale = dx is a constant scalar */ 40 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 41 dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon); 42 } else { 43 ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr); 44 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 45 for (col=0; col<nxloc; col++) { 46 dx = xx[col]; 47 if (PetscAbsScalar(dx) < umin) { 48 if (PetscRealPart(dx) >= 0.0) dx = umin; 49 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 50 } 51 dx *= epsilon; 52 vscale_array[col] = 1.0/dx; 53 } 54 ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr); 55 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 56 } 57 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 58 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 59 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 60 } 61 62 /* (3) Loop over each color */ 63 if (!coloring->w3) { 64 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 65 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 66 } 67 w3 = coloring->w3; 68 69 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 70 if (vscale) { 71 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 72 } 73 nz = 0; 74 for (k=0; k<ncolors; k++) { 75 coloring->currentcolor = k; 76 77 /* 78 (3-1) Loop over each column associated with color 79 adding the perturbation to the vector w3 = x1 + dx. 80 */ 81 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 82 dy_i = dy; 83 for (i=0; i<bs; i++) { /* Loop over a block of columns */ 84 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 85 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 86 if (coloring->htype[0] == 'w') { 87 for (l=0; l<ncolumns[k]; l++) { 88 col = i + bs*coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 89 w3_array[col] += 1.0/dx; 90 if (i) w3_array[col-1] -= 1.0/dx; /* resume original w3[col-1] */ 91 } 92 } else { /* htype == 'ds' */ 93 vscale_array -= cstart; /* shift pointer so global index can be used */ 94 for (l=0; l<ncolumns[k]; l++) { 95 col = i + bs*coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 96 w3_array[col] += 1.0/vscale_array[col]; 97 if (i) w3_array[col-1] -= 1.0/vscale_array[col-1]; /* resume original w3[col-1] */ 98 } 99 vscale_array += cstart; 100 } 101 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 102 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 103 104 /* 105 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 106 w2 = F(x1 + dx) - F(x1) 107 */ 108 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 109 ierr = VecPlaceArray(w2,dy_i);CHKERRQ(ierr); /* place w2 to the array dy_i */ 110 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 111 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 112 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 113 ierr = VecResetArray(w2);CHKERRQ(ierr); 114 dy_i += nxloc; /* points to dy+i*nxloc */ 115 } 116 117 /* 118 (3-3) Loop over rows of vector, putting results into Jacobian matrix 119 */ 120 nrows_k = nrows[k]; 121 if (coloring->htype[0] == 'w') { 122 for (l=0; l<nrows_k; l++) { 123 row = bs*Jentry2[nz].row; /* local row index */ 124 valaddr = Jentry2[nz++].valaddr; 125 spidx = 0; 126 dy_i = dy; 127 for (i=0; i<bs; i++) { /* column of the block */ 128 for (j=0; j<bs; j++) { /* row of the block */ 129 valaddr[spidx++] = dy_i[row+j]*dx; 130 } 131 dy_i += nxloc; /* points to dy+i*nxloc */ 132 } 133 } 134 } else { /* htype == 'ds' */ 135 for (l=0; l<nrows_k; l++) { 136 row = bs*Jentry[nz].row; /* local row index */ 137 col = bs*Jentry[nz].col; /* local column index */ 138 valaddr = Jentry[nz++].valaddr; 139 spidx = 0; 140 dy_i = dy; 141 for (i=0; i<bs; i++) { /* column of the block */ 142 for (j=0; j<bs; j++) { /* row of the block */ 143 valaddr[spidx++] = dy_i[row+j]*vscale_array[col+i]; 144 } 145 dy_i += nxloc; /* points to dy+i*nxloc */ 146 } 147 } 148 } 149 } 150 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 151 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 152 if (vscale) { 153 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 154 } 155 156 coloring->currentcolor = -1; 157 PetscFunctionReturn(0); 158 } 159 160 #undef __FUNCT__ 161 #define __FUNCT__ "MatFDColoringApply_AIJ" 162 PetscErrorCode MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx) 163 { 164 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 165 PetscErrorCode ierr; 166 PetscInt k,cstart,cend,l,row,col,nz; 167 PetscScalar dx=0.0,*y,*w3_array; 168 const PetscScalar *xx; 169 PetscScalar *vscale_array; 170 PetscReal epsilon=coloring->error_rel,umin=coloring->umin,unorm; 171 Vec w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale; 172 void *fctx=coloring->fctx; 173 PetscInt ctype=coloring->ctype,nxloc,nrows_k; 174 MatEntry *Jentry=coloring->matentry; 175 MatEntry2 *Jentry2=coloring->matentry2; 176 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 177 178 PetscFunctionBegin; 179 /* (1) Set w1 = F(x1) */ 180 if (!coloring->fset) { 181 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 182 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 183 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 184 } else { 185 coloring->fset = PETSC_FALSE; 186 } 187 188 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 189 if (coloring->htype[0] == 'w') { 190 /* vscale = 1./dx is a constant scalar */ 191 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 192 dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon); 193 } else { 194 ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr); 195 ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr); 196 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 197 for (col=0; col<nxloc; col++) { 198 dx = xx[col]; 199 if (PetscAbsScalar(dx) < umin) { 200 if (PetscRealPart(dx) >= 0.0) dx = umin; 201 else if (PetscRealPart(dx) < 0.0 ) dx = -umin; 202 } 203 dx *= epsilon; 204 vscale_array[col] = 1.0/dx; 205 } 206 ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr); 207 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 208 } 209 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 210 ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 211 ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 212 } 213 214 /* (3) Loop over each color */ 215 if (!coloring->w3) { 216 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 217 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 218 } 219 w3 = coloring->w3; 220 221 ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */ 222 if (vscale) { 223 ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr); 224 } 225 nz = 0; 226 227 if (coloring->bcols > 1) { /* use blocked insertion of Jentry */ 228 PetscInt i,m=J->rmap->n,nbcols,bcols=coloring->bcols; 229 PetscScalar *dy=coloring->dy,*dy_k; 230 231 nbcols = 0; 232 for (k=0; k<ncolors; k+=bcols) { 233 coloring->currentcolor = k; 234 235 /* 236 (3-1) Loop over each column associated with color 237 adding the perturbation to the vector w3 = x1 + dx. 238 */ 239 240 dy_k = dy; 241 if (k + bcols > ncolors) bcols = ncolors - k; 242 for (i=0; i<bcols; i++) { 243 244 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 245 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 246 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 247 if (coloring->htype[0] == 'w') { 248 for (l=0; l<ncolumns[k+i]; l++) { 249 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 250 w3_array[col] += 1.0/dx; 251 } 252 } else { /* htype == 'ds' */ 253 vscale_array -= cstart; /* shift pointer so global index can be used */ 254 for (l=0; l<ncolumns[k+i]; l++) { 255 col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */ 256 w3_array[col] += 1.0/vscale_array[col]; 257 } 258 vscale_array += cstart; 259 } 260 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 261 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 262 263 /* 264 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 265 w2 = F(x1 + dx) - F(x1) 266 */ 267 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 268 ierr = VecPlaceArray(w2,dy_k);CHKERRQ(ierr); /* place w2 to the array dy_i */ 269 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 270 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 271 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 272 ierr = VecResetArray(w2);CHKERRQ(ierr); 273 dy_k += m; /* points to dy+i*nxloc */ 274 } 275 276 /* 277 (3-3) Loop over block rows of vector, putting results into Jacobian matrix 278 */ 279 nrows_k = nrows[nbcols++]; 280 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 281 282 if (coloring->htype[0] == 'w') { 283 for (l=0; l<nrows_k; l++) { 284 row = Jentry2[nz].row; /* local row index */ 285 *(Jentry2[nz++].valaddr) = dy[row]*dx; 286 } 287 } else { /* htype == 'ds' */ 288 for (l=0; l<nrows_k; l++) { 289 row = Jentry[nz].row; /* local row index */ 290 *(Jentry[nz].valaddr) = dy[row]*vscale_array[Jentry[nz].col]; 291 nz++; 292 } 293 } 294 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 295 } 296 } else { /* bcols == 1 */ 297 for (k=0; k<ncolors; k++) { 298 coloring->currentcolor = k; 299 300 /* 301 (3-1) Loop over each column associated with color 302 adding the perturbation to the vector w3 = x1 + dx. 303 */ 304 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 305 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 306 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 307 if (coloring->htype[0] == 'w') { 308 for (l=0; l<ncolumns[k]; l++) { 309 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 310 w3_array[col] += 1.0/dx; 311 } 312 } else { /* htype == 'ds' */ 313 vscale_array -= cstart; /* shift pointer so global index can be used */ 314 for (l=0; l<ncolumns[k]; l++) { 315 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 316 w3_array[col] += 1.0/vscale_array[col]; 317 } 318 vscale_array += cstart; 319 } 320 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 321 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 322 323 /* 324 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 325 w2 = F(x1 + dx) - F(x1) 326 */ 327 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 328 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 329 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 330 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 331 332 /* 333 (3-3) Loop over rows of vector, putting results into Jacobian matrix 334 */ 335 nrows_k = nrows[k]; 336 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 337 if (coloring->htype[0] == 'w') { 338 for (l=0; l<nrows_k; l++) { 339 row = Jentry2[nz].row; /* local row index */ 340 *(Jentry2[nz++].valaddr) = y[row]*dx; 341 } 342 } else { /* htype == 'ds' */ 343 for (l=0; l<nrows_k; l++) { 344 row = Jentry[nz].row; /* local row index */ 345 *(Jentry[nz].valaddr) = y[row]*vscale_array[Jentry[nz].col]; 346 nz++; 347 } 348 } 349 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 350 } 351 } 352 353 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 354 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 355 if (vscale) { 356 ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr); 357 } 358 coloring->currentcolor = -1; 359 PetscFunctionReturn(0); 360 } 361 362 /* 363 MarkRowsForCol_private - Mark all rows affect by the input columns 364 Input Parameters: 365 nctot - number of columns 366 cols - column indices 367 mat, ...,colmap - data structures in MatFDColoringSetUp_MPIXAIJ() 368 nrows_i_out - num of rows marked 369 370 Output Parameters: 371 nrows_i_out - updated num of rows marked 372 */ 373 #undef __FUNCT__ 374 #define __FUNCT__ "MarkRowsForCol_private" 375 PETSC_STATIC_INLINE PetscErrorCode MarkRowsForCol_private(PetscInt nctot,PetscInt *cols, 376 Mat mat,ISColoring iscoloring,MatFDColoring c,const PetscInt *ltog,PetscInt bs, 377 const PetscInt *A_ci,const PetscInt *A_cj,PetscScalar *A_val, 378 const PetscInt *B_ci,const PetscInt *B_cj,PetscScalar *B_val,PetscInt *spidxA,PetscInt *spidxB, 379 PetscInt *rowhit,PetscScalar **valaddrhit,PetscInt *nrows_i_out) 380 { 381 PetscErrorCode ierr; 382 PetscInt ctype=c->ctype; 383 PetscInt j,col,nrows,k,spidx,colb,nrows_i; 384 const PetscInt *row=NULL; 385 PetscInt cstart,cend; 386 PetscBool isBAIJ; 387 #if defined(PETSC_USE_CTABLE) 388 PetscTable colmap=NULL; 389 #else 390 PetscInt *colmap=NULL; /* local col number of off-diag col */ 391 #endif 392 393 PetscFunctionBegin; 394 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 395 if (isBAIJ) { 396 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 397 colmap = baij->colmap; 398 } else { 399 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 400 colmap = aij->colmap; 401 } 402 403 cstart = mat->cmap->rstart/bs; 404 cend = mat->cmap->rend/bs; 405 406 nrows_i = *nrows_i_out; 407 for (j=0; j<nctot; j++) { /* loop over columns*/ 408 if (ctype == IS_COLORING_GHOSTED) { 409 col = ltog[cols[j]]; 410 } else { 411 col = cols[j]; 412 } 413 414 if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */ 415 row = A_cj + A_ci[col-cstart]; 416 nrows = A_ci[col-cstart+1] - A_ci[col-cstart]; 417 nrows_i += nrows; 418 419 /* loop over columns of A marking them in rowhit */ 420 for (k=0; k<nrows; k++) { 421 /* set valaddrhit for part A */ 422 spidx = bs*bs*spidxA[A_ci[col-cstart] + k]; 423 valaddrhit[*row] = &A_val[spidx]; 424 rowhit[*row++] = col - cstart + 1; /* local column index */ 425 } 426 } else { /* column is in B, off-diagonal block of mat */ 427 #if defined(PETSC_USE_CTABLE) 428 ierr = PetscTableFind(colmap,col+1,&colb);CHKERRQ(ierr); 429 colb--; 430 #else 431 colb = colmap[col] - 1; /* local column index */ 432 #endif 433 if (colb == -1) { 434 nrows = 0; 435 } else { 436 colb = colb/bs; 437 row = B_cj + B_ci[colb]; 438 nrows = B_ci[colb+1] - B_ci[colb]; 439 } 440 nrows_i += nrows; 441 442 /* loop over columns of B marking them in rowhit */ 443 for (k=0; k<nrows; k++) { 444 /* set valaddrhit for part B */ 445 spidx = bs*bs*spidxB[B_ci[colb] + k]; 446 valaddrhit[*row] = &B_val[spidx]; 447 rowhit[*row++] = colb + 1 + cend - cstart; /* local column index */ 448 } 449 } 450 } 451 *nrows_i_out = nrows_i; 452 PetscFunctionReturn(0); 453 } 454 455 #undef __FUNCT__ 456 #define __FUNCT__ "MatFDColoringSetUp_MPIXAIJ" 457 PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 458 { 459 PetscErrorCode ierr; 460 PetscMPIInt size,*ncolsonproc,*disp,nn,rank; 461 PetscInt i,n,nrows_i,j,k,m,ncols,*rowhit; 462 const PetscInt *is,*A_ci,*A_cj,*B_ci,*B_cj,*ltog=NULL; 463 PetscInt nis=iscoloring->n,nctot,*cols; 464 IS *isa; 465 ISLocalToGlobalMapping map=mat->cmap->mapping; 466 PetscInt ctype=c->ctype,*spidxA,*spidxB,nz,bs; 467 Mat A,B; 468 PetscScalar *A_val,*B_val,**valaddrhit; 469 MatEntry *Jentry; 470 MatEntry2 *Jentry2; 471 PetscBool isBAIJ; 472 PetscInt bcols=c->bcols; 473 MPI_Comm comm; 474 PetscMPIInt tag,nrecvs,nsends,proc; 475 MPI_Request *rwaits = NULL,*swaits = NULL; 476 MPI_Status status; 477 478 PetscFunctionBegin; 479 ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr); 480 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 481 482 if (ctype == IS_COLORING_GHOSTED) { 483 if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 484 ierr = ISLocalToGlobalMappingGetIndices(map,<og);CHKERRQ(ierr); 485 } 486 487 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 488 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 489 if (isBAIJ) { 490 Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data; 491 Mat_SeqBAIJ *spA,*spB; 492 A = baij->A; spA = (Mat_SeqBAIJ*)A->data; A_val = spA->a; 493 B = baij->B; spB = (Mat_SeqBAIJ*)B->data; B_val = spB->a; 494 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 495 if (!baij->colmap) { 496 ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 497 } 498 ierr = MatGetColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 499 ierr = MatGetColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 500 501 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 502 PetscInt *garray; 503 ierr = PetscMalloc1(B->cmap->n,&garray);CHKERRQ(ierr); 504 for (i=0; i<baij->B->cmap->n/bs; i++) { 505 for (j=0; j<bs; j++) { 506 garray[i*bs+j] = bs*baij->garray[i]+j; 507 } 508 } 509 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,garray,&c->vscale);CHKERRQ(ierr); 510 ierr = PetscFree(garray);CHKERRQ(ierr); 511 } 512 } else { 513 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 514 Mat_SeqAIJ *spA,*spB; 515 A = aij->A; spA = (Mat_SeqAIJ*)A->data; A_val = spA->a; 516 B = aij->B; spB = (Mat_SeqAIJ*)B->data; B_val = spB->a; 517 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 518 if (!aij->colmap) { 519 /* Allow access to data structures of local part of matrix 520 - creates aij->colmap which maps global column number to local number in part B */ 521 ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr); 522 } 523 ierr = MatGetColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 524 ierr = MatGetColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 525 526 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 527 528 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 529 ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr); 530 } 531 } 532 533 ierr = PetscMalloc1(nis,&c->ncolumns);CHKERRQ(ierr); 534 ierr = PetscMalloc1(nis,&c->columns);CHKERRQ(ierr); 535 ierr = PetscMalloc1(nis,&c->nrows);CHKERRQ(ierr); 536 ierr = PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));CHKERRQ(ierr); 537 538 if (c->htype[0] == 'd') { 539 ierr = PetscMalloc1(nz,&Jentry);CHKERRQ(ierr); 540 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));CHKERRQ(ierr); 541 c->matentry = Jentry; 542 } else if (c->htype[0] == 'w') { 543 ierr = PetscMalloc1(nz,&Jentry2);CHKERRQ(ierr); 544 ierr = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry2));CHKERRQ(ierr); 545 c->matentry2 = Jentry2; 546 } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"htype is not supported"); 547 548 m = mat->rmap->n/bs; 549 ierr = PetscMalloc2(m+1,&rowhit,m+1,&valaddrhit);CHKERRQ(ierr); 550 nz = 0; 551 ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr); 552 for (i=0; i<nis; i++) { /* for each local color */ 553 ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr); 554 ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr); 555 556 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 557 if (n) { 558 ierr = PetscMalloc1(n,&c->columns[i]);CHKERRQ(ierr); 559 ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr); 560 ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr); 561 } else { 562 c->columns[i] = 0; 563 } 564 565 if (ctype == IS_COLORING_GLOBAL) { 566 /* Determine nctot, the total (parallel) number of columns of this color */ 567 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr); 568 ierr = PetscMalloc2(size,&ncolsonproc,size,&disp);CHKERRQ(ierr); 569 570 /* ncolsonproc[j]: local ncolumns on proc[j] of this color */ 571 ierr = PetscMPIIntCast(n,&nn);CHKERRQ(ierr); 572 ierr = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); 573 nctot = 0; 574 for (j=0; j<size; j++) nctot += ncolsonproc[j]; 575 if (!nctot) { 576 ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr); 577 } 578 579 disp[0] = 0; 580 for (j=1; j<size; j++) { 581 disp[j] = disp[j-1] + ncolsonproc[j-1]; 582 } 583 584 /* Get cols, the complete list of columns for this color on each process */ 585 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 586 587 /* replace non-scalable MPI_Allgatherv with MPI_Isend/MPI_Isend/MPI_Waitany */ 588 /* ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); */ 589 590 nrecvs = size-1; 591 ierr = PetscCommGetNewTag(comm,&tag);CHKERRQ(ierr); 592 ierr = PetscMalloc2(nrecvs,&rwaits,nrecvs,&swaits);CHKERRQ(ierr); 593 594 nrecvs = 0; 595 for (proc=0; proc<size; proc++) { 596 if (proc == rank || ncolsonproc[proc] == 0 ) continue; 597 ierr = MPI_Irecv(cols+disp[proc],ncolsonproc[proc],MPIU_INT,proc,tag,comm,rwaits+nrecvs);CHKERRQ(ierr); 598 nrecvs++; 599 } 600 601 nsends = 0; 602 for (proc=0; proc<size; proc++) { 603 if (proc == rank || n == 0) continue; 604 ierr = MPI_Isend((void*)is,n,MPIU_INT,proc,tag,comm,swaits+nsends);CHKERRQ(ierr); 605 nsends++; 606 } 607 608 /* initialize rowhit and nrows_i for MarkRowsForCol_private() */ 609 nrows_i = 0; 610 ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr); 611 612 /* MarkRowsForCol for is in this proc */ 613 ierr = MarkRowsForCol_private(ncolsonproc[rank],(PetscInt *)is,mat,iscoloring,c,ltog,bs,A_ci,A_cj,A_val,B_ci,B_cj,B_val,spidxA,spidxB,rowhit,valaddrhit,&nrows_i);CHKERRQ(ierr); 614 615 j = nrecvs; 616 while (j--) { 617 ierr = MPI_Waitany(nrecvs,rwaits,&k,&status);CHKERRQ(ierr); 618 619 /* MarkRowsForCol for received cols */ 620 proc = status.MPI_SOURCE; 621 ierr = MarkRowsForCol_private(ncolsonproc[proc],cols+disp[proc],mat,iscoloring,c,ltog,bs,A_ci,A_cj,A_val,B_ci,B_cj,B_val,spidxA,spidxB,rowhit,valaddrhit,&nrows_i);CHKERRQ(ierr); 622 } 623 if (nsends) {ierr = MPI_Waitall(nrecvs,swaits,MPI_STATUSES_IGNORE);CHKERRQ(ierr);} 624 625 ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr); 626 ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr); 627 } else if (ctype == IS_COLORING_GHOSTED) { 628 /* Determine local number of columns of this color on this process, including ghost points */ 629 nctot = n; 630 ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr); 631 ierr = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr); 632 633 /* initialize rowhit and nrows_i for MarkRowsForCol_private() */ 634 nrows_i = 0; 635 ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr); 636 637 /* Mark all rows affect by these columns */ 638 ierr = MarkRowsForCol_private(nctot,cols,mat,iscoloring,c,ltog,bs,A_ci,A_cj,A_val,B_ci,B_cj,B_val,spidxA,spidxB,rowhit,valaddrhit,&nrows_i);CHKERRQ(ierr); 639 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type"); 640 641 c->nrows[i] = nrows_i; 642 ierr = PetscFree(cols);CHKERRQ(ierr); 643 644 if (c->htype[0] == 'd') { 645 for (j=0; j<m; j++) { 646 if (rowhit[j]) { 647 Jentry[nz].row = j; /* local row index */ 648 Jentry[nz].col = rowhit[j] - 1; /* local column index */ 649 Jentry[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 650 nz++; 651 } 652 } 653 } else { /* c->htype == 'wp' */ 654 for (j=0; j<m; j++) { 655 if (rowhit[j]) { 656 Jentry2[nz].row = j; /* local row index */ 657 Jentry2[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 658 nz++; 659 } 660 } 661 } 662 } 663 664 if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */ 665 ierr = MatFDColoringSetUpBlocked_AIJ_Private(mat,c,nz);CHKERRQ(ierr); 666 } 667 668 if (isBAIJ) { 669 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 670 ierr = MatRestoreColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 671 ierr = PetscMalloc1(bs*mat->rmap->n,&c->dy);CHKERRQ(ierr); 672 } else { 673 ierr = MatRestoreColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr); 674 ierr = MatRestoreColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr); 675 } 676 677 ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr); 678 ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr); 679 680 if (ctype == IS_COLORING_GHOSTED) { 681 ierr = ISLocalToGlobalMappingRestoreIndices(map,<og);CHKERRQ(ierr); 682 } 683 ierr = PetscInfo3(c,"ncolors %D, brows %D and bcols %D are used.\n",c->ncolors,c->brows,c->bcols);CHKERRQ(ierr); 684 PetscFunctionReturn(0); 685 } 686 687 #undef __FUNCT__ 688 #define __FUNCT__ "MatFDColoringCreate_MPIXAIJ" 689 PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c) 690 { 691 PetscErrorCode ierr; 692 PetscInt bs,nis=iscoloring->n,m=mat->rmap->n; 693 PetscBool isBAIJ; 694 695 PetscFunctionBegin; 696 /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian; 697 bcols is chosen s.t. dy-array takes 50% of memory space as mat */ 698 ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr); 699 ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr); 700 if (isBAIJ || m == 0) { 701 c->brows = m; 702 c->bcols = 1; 703 } else { /* mpiaij matrix */ 704 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 705 Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data; 706 Mat_SeqAIJ *spA,*spB; 707 Mat A,B; 708 PetscInt nz,brows,bcols; 709 PetscReal mem; 710 711 bs = 1; /* only bs=1 is supported for MPIAIJ matrix */ 712 713 A = aij->A; spA = (Mat_SeqAIJ*)A->data; 714 B = aij->B; spB = (Mat_SeqAIJ*)B->data; 715 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 716 mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt); 717 bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar))); 718 brows = 1000/bcols; 719 if (bcols > nis) bcols = nis; 720 if (brows == 0 || brows > m) brows = m; 721 c->brows = brows; 722 c->bcols = bcols; 723 } 724 725 c->M = mat->rmap->N/bs; /* set the global rows and columns and local rows */ 726 c->N = mat->cmap->N/bs; 727 c->m = mat->rmap->n/bs; 728 c->rstart = mat->rmap->rstart/bs; 729 c->ncolors = nis; 730 PetscFunctionReturn(0); 731 } 732