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 static PetscErrorCode MatFDColoringMarkHost_AIJ(Mat J) 7 { 8 PetscBool isseqAIJ, ismpiAIJ, issell; 9 PetscScalar *v; 10 11 PetscFunctionBegin; 12 PetscCall(PetscObjectBaseTypeCompare((PetscObject)J, MATMPIAIJ, &ismpiAIJ)); 13 PetscCall(PetscObjectBaseTypeCompare((PetscObject)J, MATSEQAIJ, &isseqAIJ)); 14 PetscCall(PetscObjectTypeCompareAny((PetscObject)J, &issell, MATSEQSELLCUDA, MATMPISELLCUDA, "")); 15 PetscCheck(!issell, PETSC_COMM_SELF, PETSC_ERR_SUP, "Not coded for %s. Send an email to petsc-dev@mcs.anl.gov to request this feature", ((PetscObject)J)->type_name); 16 if (isseqAIJ) { 17 PetscCall(MatSeqAIJGetArrayWrite(J, &v)); 18 PetscCall(MatSeqAIJRestoreArrayWrite(J, &v)); 19 } else if (ismpiAIJ) { 20 Mat dJ, oJ; 21 22 PetscCall(MatMPIAIJGetSeqAIJ(J, &dJ, &oJ, NULL)); 23 PetscCall(MatSeqAIJGetArrayWrite(dJ, &v)); 24 PetscCall(MatSeqAIJRestoreArrayWrite(dJ, &v)); 25 PetscCall(MatSeqAIJGetArrayWrite(oJ, &v)); 26 PetscCall(MatSeqAIJRestoreArrayWrite(oJ, &v)); 27 } 28 PetscFunctionReturn(PETSC_SUCCESS); 29 } 30 31 PetscErrorCode MatFDColoringApply_BAIJ(Mat J, MatFDColoring coloring, Vec x1, void *sctx) 32 { 33 PetscErrorCode (*f)(void *, Vec, Vec, void *) = (PetscErrorCode(*)(void *, Vec, Vec, void *))coloring->f; 34 PetscInt k, cstart, cend, l, row, col, nz, spidx, i, j; 35 PetscScalar dx = 0.0, *w3_array, *dy_i, *dy = coloring->dy; 36 PetscScalar *vscale_array; 37 const PetscScalar *xx; 38 PetscReal epsilon = coloring->error_rel, umin = coloring->umin, unorm; 39 Vec w1 = coloring->w1, w2 = coloring->w2, w3, vscale = coloring->vscale; 40 void *fctx = coloring->fctx; 41 PetscInt ctype = coloring->ctype, nxloc, nrows_k; 42 PetscScalar *valaddr; 43 MatEntry *Jentry = coloring->matentry; 44 MatEntry2 *Jentry2 = coloring->matentry2; 45 const PetscInt ncolors = coloring->ncolors, *ncolumns = coloring->ncolumns, *nrows = coloring->nrows; 46 PetscInt bs = J->rmap->bs; 47 48 PetscFunctionBegin; 49 PetscCall(VecBindToCPU(x1, PETSC_TRUE)); 50 /* (1) Set w1 = F(x1) */ 51 if (!coloring->fset) { 52 PetscCall(PetscLogEventBegin(MAT_FDColoringFunction, coloring, 0, 0, 0)); 53 PetscCall((*f)(sctx, x1, w1, fctx)); 54 PetscCall(PetscLogEventEnd(MAT_FDColoringFunction, coloring, 0, 0, 0)); 55 } else { 56 coloring->fset = PETSC_FALSE; 57 } 58 59 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 60 PetscCall(VecGetLocalSize(x1, &nxloc)); 61 if (coloring->htype[0] == 'w') { 62 /* vscale = dx is a constant scalar */ 63 PetscCall(VecNorm(x1, NORM_2, &unorm)); 64 dx = 1.0 / (PetscSqrtReal(1.0 + unorm) * epsilon); 65 } else { 66 PetscCall(VecGetArrayRead(x1, &xx)); 67 PetscCall(VecGetArray(vscale, &vscale_array)); 68 for (col = 0; col < nxloc; col++) { 69 dx = xx[col]; 70 if (PetscAbsScalar(dx) < umin) { 71 if (PetscRealPart(dx) >= 0.0) dx = umin; 72 else if (PetscRealPart(dx) < 0.0) dx = -umin; 73 } 74 dx *= epsilon; 75 vscale_array[col] = 1.0 / dx; 76 } 77 PetscCall(VecRestoreArrayRead(x1, &xx)); 78 PetscCall(VecRestoreArray(vscale, &vscale_array)); 79 } 80 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 81 PetscCall(VecGhostUpdateBegin(vscale, INSERT_VALUES, SCATTER_FORWARD)); 82 PetscCall(VecGhostUpdateEnd(vscale, INSERT_VALUES, SCATTER_FORWARD)); 83 } 84 85 /* (3) Loop over each color */ 86 if (!coloring->w3) { 87 PetscCall(VecDuplicate(x1, &coloring->w3)); 88 /* Vec is used intensively in particular piece of scalar CPU code; won't benefit from bouncing back and forth to the GPU */ 89 PetscCall(VecBindToCPU(coloring->w3, PETSC_TRUE)); 90 } 91 w3 = coloring->w3; 92 93 PetscCall(VecGetOwnershipRange(x1, &cstart, &cend)); /* used by ghosted vscale */ 94 if (vscale) PetscCall(VecGetArray(vscale, &vscale_array)); 95 nz = 0; 96 for (k = 0; k < ncolors; k++) { 97 coloring->currentcolor = k; 98 99 /* 100 (3-1) Loop over each column associated with color 101 adding the perturbation to the vector w3 = x1 + dx. 102 */ 103 PetscCall(VecCopy(x1, w3)); 104 dy_i = dy; 105 for (i = 0; i < bs; i++) { /* Loop over a block of columns */ 106 PetscCall(VecGetArray(w3, &w3_array)); 107 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 108 if (coloring->htype[0] == 'w') { 109 for (l = 0; l < ncolumns[k]; l++) { 110 col = i + bs * coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 111 w3_array[col] += 1.0 / dx; 112 if (i) w3_array[col - 1] -= 1.0 / dx; /* resume original w3[col-1] */ 113 } 114 } else { /* htype == 'ds' */ 115 vscale_array -= cstart; /* shift pointer so global index can be used */ 116 for (l = 0; l < ncolumns[k]; l++) { 117 col = i + bs * coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 118 w3_array[col] += 1.0 / vscale_array[col]; 119 if (i) w3_array[col - 1] -= 1.0 / vscale_array[col - 1]; /* resume original w3[col-1] */ 120 } 121 vscale_array += cstart; 122 } 123 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 124 PetscCall(VecRestoreArray(w3, &w3_array)); 125 126 /* 127 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 128 w2 = F(x1 + dx) - F(x1) 129 */ 130 PetscCall(PetscLogEventBegin(MAT_FDColoringFunction, 0, 0, 0, 0)); 131 PetscCall(VecPlaceArray(w2, dy_i)); /* place w2 to the array dy_i */ 132 PetscCall((*f)(sctx, w3, w2, fctx)); 133 PetscCall(PetscLogEventEnd(MAT_FDColoringFunction, 0, 0, 0, 0)); 134 PetscCall(VecAXPY(w2, -1.0, w1)); 135 PetscCall(VecResetArray(w2)); 136 dy_i += nxloc; /* points to dy+i*nxloc */ 137 } 138 139 /* 140 (3-3) Loop over rows of vector, putting results into Jacobian matrix 141 */ 142 nrows_k = nrows[k]; 143 if (coloring->htype[0] == 'w') { 144 for (l = 0; l < nrows_k; l++) { 145 row = bs * Jentry2[nz].row; /* local row index */ 146 valaddr = Jentry2[nz++].valaddr; 147 spidx = 0; 148 dy_i = dy; 149 for (i = 0; i < bs; i++) { /* column of the block */ 150 for (j = 0; j < bs; j++) { /* row of the block */ 151 valaddr[spidx++] = dy_i[row + j] * dx; 152 } 153 dy_i += nxloc; /* points to dy+i*nxloc */ 154 } 155 } 156 } else { /* htype == 'ds' */ 157 for (l = 0; l < nrows_k; l++) { 158 row = bs * Jentry[nz].row; /* local row index */ 159 col = bs * Jentry[nz].col; /* local column index */ 160 valaddr = Jentry[nz++].valaddr; 161 spidx = 0; 162 dy_i = dy; 163 for (i = 0; i < bs; i++) { /* column of the block */ 164 for (j = 0; j < bs; j++) { /* row of the block */ 165 valaddr[spidx++] = dy_i[row + j] * vscale_array[col + i]; 166 } 167 dy_i += nxloc; /* points to dy+i*nxloc */ 168 } 169 } 170 } 171 } 172 PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY)); 173 PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY)); 174 if (vscale) PetscCall(VecRestoreArray(vscale, &vscale_array)); 175 176 coloring->currentcolor = -1; 177 PetscCall(VecBindToCPU(x1, PETSC_FALSE)); 178 PetscFunctionReturn(PETSC_SUCCESS); 179 } 180 181 /* this is declared PETSC_EXTERN because it is used by MatFDColoringUseDM() which is in the DM library */ 182 PetscErrorCode MatFDColoringApply_AIJ(Mat J, MatFDColoring coloring, Vec x1, void *sctx) 183 { 184 PetscErrorCode (*f)(void *, Vec, Vec, void *) = (PetscErrorCode(*)(void *, Vec, Vec, void *))coloring->f; 185 PetscInt k, cstart, cend, l, row, col, nz; 186 PetscScalar dx = 0.0, *y, *w3_array; 187 const PetscScalar *xx; 188 PetscScalar *vscale_array; 189 PetscReal epsilon = coloring->error_rel, umin = coloring->umin, unorm; 190 Vec w1 = coloring->w1, w2 = coloring->w2, w3, vscale = coloring->vscale; 191 void *fctx = coloring->fctx; 192 ISColoringType ctype = coloring->ctype; 193 PetscInt nxloc, nrows_k; 194 MatEntry *Jentry = coloring->matentry; 195 MatEntry2 *Jentry2 = coloring->matentry2; 196 const PetscInt ncolors = coloring->ncolors, *ncolumns = coloring->ncolumns, *nrows = coloring->nrows; 197 PetscBool alreadyboundtocpu; 198 199 PetscFunctionBegin; 200 PetscCall(MatFDColoringMarkHost_AIJ(J)); 201 PetscCall(VecBoundToCPU(x1, &alreadyboundtocpu)); 202 PetscCall(VecBindToCPU(x1, PETSC_TRUE)); 203 PetscCheck(!(ctype == IS_COLORING_LOCAL) || !(J->ops->fdcoloringapply == MatFDColoringApply_AIJ), PetscObjectComm((PetscObject)J), PETSC_ERR_SUP, "Must call MatColoringUseDM() with IS_COLORING_LOCAL"); 204 /* (1) Set w1 = F(x1) */ 205 if (!coloring->fset) { 206 PetscCall(PetscLogEventBegin(MAT_FDColoringFunction, 0, 0, 0, 0)); 207 PetscCall((*f)(sctx, x1, w1, fctx)); 208 PetscCall(PetscLogEventEnd(MAT_FDColoringFunction, 0, 0, 0, 0)); 209 } else { 210 coloring->fset = PETSC_FALSE; 211 } 212 213 /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */ 214 if (coloring->htype[0] == 'w') { 215 /* vscale = 1./dx is a constant scalar */ 216 PetscCall(VecNorm(x1, NORM_2, &unorm)); 217 dx = 1.0 / (PetscSqrtReal(1.0 + unorm) * epsilon); 218 } else { 219 PetscCall(VecGetLocalSize(x1, &nxloc)); 220 PetscCall(VecGetArrayRead(x1, &xx)); 221 PetscCall(VecGetArray(vscale, &vscale_array)); 222 for (col = 0; col < nxloc; col++) { 223 dx = xx[col]; 224 if (PetscAbsScalar(dx) < umin) { 225 if (PetscRealPart(dx) >= 0.0) dx = umin; 226 else if (PetscRealPart(dx) < 0.0) dx = -umin; 227 } 228 dx *= epsilon; 229 vscale_array[col] = 1.0 / dx; 230 } 231 PetscCall(VecRestoreArrayRead(x1, &xx)); 232 PetscCall(VecRestoreArray(vscale, &vscale_array)); 233 } 234 if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') { 235 PetscCall(VecGhostUpdateBegin(vscale, INSERT_VALUES, SCATTER_FORWARD)); 236 PetscCall(VecGhostUpdateEnd(vscale, INSERT_VALUES, SCATTER_FORWARD)); 237 } 238 239 /* (3) Loop over each color */ 240 if (!coloring->w3) PetscCall(VecDuplicate(x1, &coloring->w3)); 241 w3 = coloring->w3; 242 243 PetscCall(VecGetOwnershipRange(x1, &cstart, &cend)); /* used by ghosted vscale */ 244 if (vscale) PetscCall(VecGetArray(vscale, &vscale_array)); 245 nz = 0; 246 247 if (coloring->bcols > 1) { /* use blocked insertion of Jentry */ 248 PetscInt i, m = J->rmap->n, nbcols, bcols = coloring->bcols; 249 PetscScalar *dy = coloring->dy, *dy_k; 250 251 nbcols = 0; 252 for (k = 0; k < ncolors; k += bcols) { 253 /* 254 (3-1) Loop over each column associated with color 255 adding the perturbation to the vector w3 = x1 + dx. 256 */ 257 258 dy_k = dy; 259 if (k + bcols > ncolors) bcols = ncolors - k; 260 for (i = 0; i < bcols; i++) { 261 coloring->currentcolor = k + i; 262 263 PetscCall(VecCopy(x1, w3)); 264 PetscCall(VecGetArray(w3, &w3_array)); 265 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 266 if (coloring->htype[0] == 'w') { 267 for (l = 0; l < ncolumns[k + i]; l++) { 268 col = coloring->columns[k + i][l]; /* local column (in global index!) of the matrix we are probing for */ 269 w3_array[col] += 1.0 / dx; 270 } 271 } else { /* htype == 'ds' */ 272 vscale_array -= cstart; /* shift pointer so global index can be used */ 273 for (l = 0; l < ncolumns[k + i]; l++) { 274 col = coloring->columns[k + i][l]; /* local column (in global index!) of the matrix we are probing for */ 275 w3_array[col] += 1.0 / vscale_array[col]; 276 } 277 vscale_array += cstart; 278 } 279 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 280 PetscCall(VecRestoreArray(w3, &w3_array)); 281 282 /* 283 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 284 w2 = F(x1 + dx) - F(x1) 285 */ 286 PetscCall(PetscLogEventBegin(MAT_FDColoringFunction, 0, 0, 0, 0)); 287 PetscCall(VecPlaceArray(w2, dy_k)); /* place w2 to the array dy_i */ 288 PetscCall((*f)(sctx, w3, w2, fctx)); 289 PetscCall(PetscLogEventEnd(MAT_FDColoringFunction, 0, 0, 0, 0)); 290 PetscCall(VecAXPY(w2, -1.0, w1)); 291 PetscCall(VecResetArray(w2)); 292 dy_k += m; /* points to dy+i*nxloc */ 293 } 294 295 /* 296 (3-3) Loop over block rows of vector, putting results into Jacobian matrix 297 */ 298 nrows_k = nrows[nbcols++]; 299 300 if (coloring->htype[0] == 'w') { 301 for (l = 0; l < nrows_k; l++) { 302 row = Jentry2[nz].row; /* local row index */ 303 /* The 'useless' ifdef is due to a bug in NVIDIA nvc 21.11, which triggers a segfault on this line. We write it in 304 another way, and it seems work. See https://lists.mcs.anl.gov/pipermail/petsc-users/2021-December/045158.html 305 */ 306 #if defined(PETSC_USE_COMPLEX) 307 PetscScalar *tmp = Jentry2[nz].valaddr; 308 *tmp = dy[row] * dx; 309 #else 310 *Jentry2[nz].valaddr = dy[row] * dx; 311 #endif 312 nz++; 313 } 314 } else { /* htype == 'ds' */ 315 for (l = 0; l < nrows_k; l++) { 316 row = Jentry[nz].row; /* local row index */ 317 #if defined(PETSC_USE_COMPLEX) /* See https://lists.mcs.anl.gov/pipermail/petsc-users/2021-December/045158.html */ 318 PetscScalar *tmp = Jentry[nz].valaddr; 319 *tmp = dy[row] * vscale_array[Jentry[nz].col]; 320 #else 321 *Jentry[nz].valaddr = dy[row] * vscale_array[Jentry[nz].col]; 322 #endif 323 nz++; 324 } 325 } 326 } 327 } else { /* bcols == 1 */ 328 for (k = 0; k < ncolors; k++) { 329 coloring->currentcolor = k; 330 331 /* 332 (3-1) Loop over each column associated with color 333 adding the perturbation to the vector w3 = x1 + dx. 334 */ 335 PetscCall(VecCopy(x1, w3)); 336 PetscCall(VecGetArray(w3, &w3_array)); 337 if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */ 338 if (coloring->htype[0] == 'w') { 339 for (l = 0; l < ncolumns[k]; l++) { 340 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 341 w3_array[col] += 1.0 / dx; 342 } 343 } else { /* htype == 'ds' */ 344 vscale_array -= cstart; /* shift pointer so global index can be used */ 345 for (l = 0; l < ncolumns[k]; l++) { 346 col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */ 347 w3_array[col] += 1.0 / vscale_array[col]; 348 } 349 vscale_array += cstart; 350 } 351 if (ctype == IS_COLORING_GLOBAL) w3_array += cstart; 352 PetscCall(VecRestoreArray(w3, &w3_array)); 353 354 /* 355 (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 356 w2 = F(x1 + dx) - F(x1) 357 */ 358 PetscCall(PetscLogEventBegin(MAT_FDColoringFunction, 0, 0, 0, 0)); 359 PetscCall((*f)(sctx, w3, w2, fctx)); 360 PetscCall(PetscLogEventEnd(MAT_FDColoringFunction, 0, 0, 0, 0)); 361 PetscCall(VecAXPY(w2, -1.0, w1)); 362 363 /* 364 (3-3) Loop over rows of vector, putting results into Jacobian matrix 365 */ 366 nrows_k = nrows[k]; 367 PetscCall(VecGetArray(w2, &y)); 368 if (coloring->htype[0] == 'w') { 369 for (l = 0; l < nrows_k; l++) { 370 row = Jentry2[nz].row; /* local row index */ 371 #if defined(PETSC_USE_COMPLEX) /* See https://lists.mcs.anl.gov/pipermail/petsc-users/2021-December/045158.html */ 372 PetscScalar *tmp = Jentry2[nz].valaddr; 373 *tmp = y[row] * dx; 374 #else 375 *Jentry2[nz].valaddr = y[row] * dx; 376 #endif 377 nz++; 378 } 379 } else { /* htype == 'ds' */ 380 for (l = 0; l < nrows_k; l++) { 381 row = Jentry[nz].row; /* local row index */ 382 #if defined(PETSC_USE_COMPLEX) /* See https://lists.mcs.anl.gov/pipermail/petsc-users/2021-December/045158.html */ 383 PetscScalar *tmp = Jentry[nz].valaddr; 384 *tmp = y[row] * vscale_array[Jentry[nz].col]; 385 #else 386 *Jentry[nz].valaddr = y[row] * vscale_array[Jentry[nz].col]; 387 #endif 388 nz++; 389 } 390 } 391 PetscCall(VecRestoreArray(w2, &y)); 392 } 393 } 394 395 PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY)); 396 PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY)); 397 if (vscale) PetscCall(VecRestoreArray(vscale, &vscale_array)); 398 coloring->currentcolor = -1; 399 if (!alreadyboundtocpu) PetscCall(VecBindToCPU(x1, PETSC_FALSE)); 400 PetscFunctionReturn(PETSC_SUCCESS); 401 } 402 403 PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat, ISColoring iscoloring, MatFDColoring c) 404 { 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, tmp = 0; 409 ISLocalToGlobalMapping map = mat->cmap->mapping; 410 PetscInt ctype = c->ctype, *spidxA, *spidxB, nz, bs, bs2, spidx; 411 Mat A, B; 412 PetscScalar *A_val, *B_val, **valaddrhit; 413 MatEntry *Jentry; 414 MatEntry2 *Jentry2; 415 PetscBool isBAIJ, isSELL; 416 PetscInt bcols = c->bcols; 417 #if defined(PETSC_USE_CTABLE) 418 PetscHMapI colmap = NULL; 419 #else 420 PetscInt *colmap = NULL; /* local col number of off-diag col */ 421 #endif 422 423 PetscFunctionBegin; 424 if (ctype == IS_COLORING_LOCAL) { 425 PetscCheck(map, PetscObjectComm((PetscObject)mat), PETSC_ERR_ARG_INCOMP, "When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping"); 426 PetscCall(ISLocalToGlobalMappingGetIndices(map, <og)); 427 } 428 429 PetscCall(MatGetBlockSize(mat, &bs)); 430 PetscCall(PetscObjectBaseTypeCompare((PetscObject)mat, MATMPIBAIJ, &isBAIJ)); 431 PetscCall(PetscObjectTypeCompare((PetscObject)mat, MATMPISELL, &isSELL)); 432 if (isBAIJ) { 433 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data; 434 Mat_SeqBAIJ *spA, *spB; 435 A = baij->A; 436 spA = (Mat_SeqBAIJ *)A->data; 437 A_val = spA->a; 438 B = baij->B; 439 spB = (Mat_SeqBAIJ *)B->data; 440 B_val = spB->a; 441 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 442 if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat)); 443 colmap = baij->colmap; 444 PetscCall(MatGetColumnIJ_SeqBAIJ_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 445 PetscCall(MatGetColumnIJ_SeqBAIJ_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 446 447 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 448 PetscInt *garray; 449 PetscCall(PetscMalloc1(B->cmap->n, &garray)); 450 for (i = 0; i < baij->B->cmap->n / bs; i++) { 451 for (j = 0; j < bs; j++) garray[i * bs + j] = bs * baij->garray[i] + j; 452 } 453 PetscCall(VecCreateGhost(PetscObjectComm((PetscObject)mat), mat->cmap->n, PETSC_DETERMINE, B->cmap->n, garray, &c->vscale)); 454 PetscCall(VecBindToCPU(c->vscale, PETSC_TRUE)); 455 PetscCall(PetscFree(garray)); 456 } 457 } else if (isSELL) { 458 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 459 Mat_SeqSELL *spA, *spB; 460 A = sell->A; 461 spA = (Mat_SeqSELL *)A->data; 462 A_val = spA->val; 463 B = sell->B; 464 spB = (Mat_SeqSELL *)B->data; 465 B_val = spB->val; 466 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 467 if (!sell->colmap) { 468 /* Allow access to data structures of local part of matrix 469 - creates aij->colmap which maps global column number to local number in part B */ 470 PetscCall(MatCreateColmap_MPISELL_Private(mat)); 471 } 472 colmap = sell->colmap; 473 PetscCall(MatGetColumnIJ_SeqSELL_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 474 PetscCall(MatGetColumnIJ_SeqSELL_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 475 476 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 477 478 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 479 PetscCall(VecCreateGhost(PetscObjectComm((PetscObject)mat), mat->cmap->n, PETSC_DETERMINE, B->cmap->n, sell->garray, &c->vscale)); 480 PetscCall(VecBindToCPU(c->vscale, PETSC_TRUE)); 481 } 482 } else { 483 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 484 Mat_SeqAIJ *spA, *spB; 485 A = aij->A; 486 spA = (Mat_SeqAIJ *)A->data; 487 A_val = spA->a; 488 B = aij->B; 489 spB = (Mat_SeqAIJ *)B->data; 490 B_val = spB->a; 491 nz = spA->nz + spB->nz; /* total nonzero entries of mat */ 492 if (!aij->colmap) { 493 /* Allow access to data structures of local part of matrix 494 - creates aij->colmap which maps global column number to local number in part B */ 495 PetscCall(MatCreateColmap_MPIAIJ_Private(mat)); 496 } 497 colmap = aij->colmap; 498 PetscCall(MatGetColumnIJ_SeqAIJ_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 499 PetscCall(MatGetColumnIJ_SeqAIJ_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 500 501 bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */ 502 503 if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */ 504 PetscCall(VecCreateGhost(PetscObjectComm((PetscObject)mat), mat->cmap->n, PETSC_DETERMINE, B->cmap->n, aij->garray, &c->vscale)); 505 PetscCall(VecBindToCPU(c->vscale, PETSC_TRUE)); 506 } 507 } 508 509 m = mat->rmap->n / bs; 510 cstart = mat->cmap->rstart / bs; 511 cend = mat->cmap->rend / bs; 512 513 PetscCall(PetscMalloc2(nis, &c->ncolumns, nis, &c->columns)); 514 PetscCall(PetscMalloc1(nis, &c->nrows)); 515 516 if (c->htype[0] == 'd') { 517 PetscCall(PetscMalloc1(nz, &Jentry)); 518 c->matentry = Jentry; 519 } else if (c->htype[0] == 'w') { 520 PetscCall(PetscMalloc1(nz, &Jentry2)); 521 c->matentry2 = Jentry2; 522 } else SETERRQ(PetscObjectComm((PetscObject)mat), PETSC_ERR_SUP, "htype is not supported"); 523 524 PetscCall(PetscMalloc2(m + 1, &rowhit, m + 1, &valaddrhit)); 525 nz = 0; 526 PetscCall(ISColoringGetIS(iscoloring, PETSC_OWN_POINTER, PETSC_IGNORE, &c->isa)); 527 528 if (ctype == IS_COLORING_GLOBAL) { 529 PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)mat), &size)); 530 PetscCall(PetscMalloc2(size, &ncolsonproc, size, &disp)); 531 } 532 533 for (i = 0; i < nis; i++) { /* for each local color */ 534 PetscCall(ISGetLocalSize(c->isa[i], &n)); 535 PetscCall(ISGetIndices(c->isa[i], &is)); 536 537 c->ncolumns[i] = n; /* local number of columns of this color on this process */ 538 c->columns[i] = (PetscInt *)is; 539 540 if (ctype == IS_COLORING_GLOBAL) { 541 /* Determine nctot, the total (parallel) number of columns of this color */ 542 /* ncolsonproc[j]: local ncolumns on proc[j] of this color */ 543 PetscCall(PetscMPIIntCast(n, &nn)); 544 PetscCallMPI(MPI_Allgather(&nn, 1, MPI_INT, ncolsonproc, 1, MPI_INT, PetscObjectComm((PetscObject)mat))); 545 nctot = 0; 546 for (j = 0; j < size; j++) nctot += ncolsonproc[j]; 547 if (!nctot) PetscCall(PetscInfo(mat, "Coloring of matrix has some unneeded colors with no corresponding rows\n")); 548 549 disp[0] = 0; 550 for (j = 1; j < size; j++) disp[j] = disp[j - 1] + ncolsonproc[j - 1]; 551 552 /* Get cols, the complete list of columns for this color on each process */ 553 PetscCall(PetscMalloc1(nctot + 1, &cols)); 554 PetscCallMPI(MPI_Allgatherv((void *)is, n, MPIU_INT, cols, ncolsonproc, disp, MPIU_INT, PetscObjectComm((PetscObject)mat))); 555 } else if (ctype == IS_COLORING_LOCAL) { 556 /* Determine local number of columns of this color on this process, including ghost points */ 557 nctot = n; 558 cols = (PetscInt *)is; 559 } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Not provided for this MatFDColoring type"); 560 561 /* Mark all rows affect by these columns */ 562 PetscCall(PetscArrayzero(rowhit, m)); 563 bs2 = bs * bs; 564 nrows_i = 0; 565 for (j = 0; j < nctot; j++) { /* loop over columns*/ 566 if (ctype == IS_COLORING_LOCAL) { 567 col = ltog[cols[j]]; 568 } else { 569 col = cols[j]; 570 } 571 if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */ 572 tmp = A_ci[col - cstart]; 573 row = A_cj + tmp; 574 nrows = A_ci[col - cstart + 1] - tmp; 575 nrows_i += nrows; 576 577 /* loop over columns of A marking them in rowhit */ 578 for (k = 0; k < nrows; k++) { 579 /* set valaddrhit for part A */ 580 spidx = bs2 * spidxA[tmp + k]; 581 valaddrhit[*row] = &A_val[spidx]; 582 rowhit[*row++] = col - cstart + 1; /* local column index */ 583 } 584 } else { /* column is in B, off-diagonal block of mat */ 585 #if defined(PETSC_USE_CTABLE) 586 PetscCall(PetscHMapIGetWithDefault(colmap, col + 1, 0, &colb)); 587 colb--; 588 #else 589 colb = colmap[col] - 1; /* local column index */ 590 #endif 591 if (colb == -1) { 592 nrows = 0; 593 } else { 594 colb = colb / bs; 595 tmp = B_ci[colb]; 596 row = B_cj + tmp; 597 nrows = B_ci[colb + 1] - tmp; 598 } 599 nrows_i += nrows; 600 /* loop over columns of B marking them in rowhit */ 601 for (k = 0; k < nrows; k++) { 602 /* set valaddrhit for part B */ 603 spidx = bs2 * spidxB[tmp + k]; 604 valaddrhit[*row] = &B_val[spidx]; 605 rowhit[*row++] = colb + 1 + cend - cstart; /* local column index */ 606 } 607 } 608 } 609 c->nrows[i] = nrows_i; 610 611 if (c->htype[0] == 'd') { 612 for (j = 0; j < m; j++) { 613 if (rowhit[j]) { 614 Jentry[nz].row = j; /* local row index */ 615 Jentry[nz].col = rowhit[j] - 1; /* local column index */ 616 Jentry[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 617 nz++; 618 } 619 } 620 } else { /* c->htype == 'wp' */ 621 for (j = 0; j < m; j++) { 622 if (rowhit[j]) { 623 Jentry2[nz].row = j; /* local row index */ 624 Jentry2[nz].valaddr = valaddrhit[j]; /* address of mat value for this entry */ 625 nz++; 626 } 627 } 628 } 629 if (ctype == IS_COLORING_GLOBAL) PetscCall(PetscFree(cols)); 630 } 631 if (ctype == IS_COLORING_GLOBAL) PetscCall(PetscFree2(ncolsonproc, disp)); 632 633 if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */ 634 PetscCall(MatFDColoringSetUpBlocked_AIJ_Private(mat, c, nz)); 635 } 636 637 if (isBAIJ) { 638 PetscCall(MatRestoreColumnIJ_SeqBAIJ_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 639 PetscCall(MatRestoreColumnIJ_SeqBAIJ_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 640 PetscCall(PetscMalloc1(bs * mat->rmap->n, &c->dy)); 641 } else if (isSELL) { 642 PetscCall(MatRestoreColumnIJ_SeqSELL_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 643 PetscCall(MatRestoreColumnIJ_SeqSELL_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 644 } else { 645 PetscCall(MatRestoreColumnIJ_SeqAIJ_Color(A, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &A_ci, &A_cj, &spidxA, NULL)); 646 PetscCall(MatRestoreColumnIJ_SeqAIJ_Color(B, 0, PETSC_FALSE, PETSC_FALSE, &ncols, &B_ci, &B_cj, &spidxB, NULL)); 647 } 648 649 PetscCall(ISColoringRestoreIS(iscoloring, PETSC_OWN_POINTER, &c->isa)); 650 PetscCall(PetscFree2(rowhit, valaddrhit)); 651 652 if (ctype == IS_COLORING_LOCAL) PetscCall(ISLocalToGlobalMappingRestoreIndices(map, <og)); 653 PetscCall(PetscInfo(c, "ncolors %" PetscInt_FMT ", brows %" PetscInt_FMT " and bcols %" PetscInt_FMT " are used.\n", c->ncolors, c->brows, c->bcols)); 654 PetscFunctionReturn(PETSC_SUCCESS); 655 } 656 657 PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat, ISColoring iscoloring, MatFDColoring c) 658 { 659 PetscInt bs, nis = iscoloring->n, m = mat->rmap->n; 660 PetscBool isBAIJ, isSELL; 661 662 PetscFunctionBegin; 663 /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian; 664 bcols is chosen s.t. dy-array takes 50% of memory space as mat */ 665 PetscCall(MatGetBlockSize(mat, &bs)); 666 PetscCall(PetscObjectBaseTypeCompare((PetscObject)mat, MATMPIBAIJ, &isBAIJ)); 667 PetscCall(PetscObjectTypeCompare((PetscObject)mat, MATMPISELL, &isSELL)); 668 if (isBAIJ || m == 0) { 669 c->brows = m; 670 c->bcols = 1; 671 } else if (isSELL) { 672 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 673 Mat_MPISELL *sell = (Mat_MPISELL *)mat->data; 674 Mat_SeqSELL *spA, *spB; 675 Mat A, B; 676 PetscInt nz, brows, bcols; 677 PetscReal mem; 678 679 bs = 1; /* only bs=1 is supported for MPISELL matrix */ 680 681 A = sell->A; 682 spA = (Mat_SeqSELL *)A->data; 683 B = sell->B; 684 spB = (Mat_SeqSELL *)B->data; 685 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 686 mem = nz * (sizeof(PetscScalar) + sizeof(PetscInt)) + 3 * m * sizeof(PetscInt); 687 bcols = (PetscInt)(0.5 * mem / (m * sizeof(PetscScalar))); 688 brows = 1000 / bcols; 689 if (bcols > nis) bcols = nis; 690 if (brows == 0 || brows > m) brows = m; 691 c->brows = brows; 692 c->bcols = bcols; 693 } else { /* mpiaij matrix */ 694 /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */ 695 Mat_MPIAIJ *aij = (Mat_MPIAIJ *)mat->data; 696 Mat_SeqAIJ *spA, *spB; 697 Mat A, B; 698 PetscInt nz, brows, bcols; 699 PetscReal mem; 700 701 bs = 1; /* only bs=1 is supported for MPIAIJ matrix */ 702 703 A = aij->A; 704 spA = (Mat_SeqAIJ *)A->data; 705 B = aij->B; 706 spB = (Mat_SeqAIJ *)B->data; 707 nz = spA->nz + spB->nz; /* total local nonzero entries of mat */ 708 mem = nz * (sizeof(PetscScalar) + sizeof(PetscInt)) + 3 * m * sizeof(PetscInt); 709 bcols = (PetscInt)(0.5 * mem / (m * sizeof(PetscScalar))); 710 brows = 1000 / bcols; 711 if (bcols > nis) bcols = nis; 712 if (brows == 0 || brows > m) brows = m; 713 c->brows = brows; 714 c->bcols = bcols; 715 } 716 717 c->M = mat->rmap->N / bs; /* set the global rows and columns and local rows */ 718 c->N = mat->cmap->N / bs; 719 c->m = mat->rmap->n / bs; 720 c->rstart = mat->rmap->rstart / bs; 721 c->ncolors = nis; 722 PetscFunctionReturn(PETSC_SUCCESS); 723 } 724 725 /*@C 726 MatFDColoringSetValues - takes a matrix in compressed color format and enters the matrix into a PETSc `Mat` 727 728 Collective 729 730 Input Parameters: 731 + J - the sparse matrix 732 . coloring - created with `MatFDColoringCreate()` and a local coloring 733 - y - column major storage of matrix values with one color of values per column, the number of rows of `y` should match 734 the number of local rows of `J` and the number of columns is the number of colors. 735 736 Level: intermediate 737 738 Notes: 739 The matrix in compressed color format may come from an automatic differentiation code 740 741 The code will be slightly faster if `MatFDColoringSetBlockSize`(coloring,`PETSC_DEFAULT`,nc); is called immediately after creating the coloring 742 743 .seealso: [](ch_matrices), `Mat`, `MatFDColoringCreate()`, `ISColoring`, `ISColoringCreate()`, `ISColoringSetType()`, `IS_COLORING_LOCAL`, `MatFDColoringSetBlockSize()` 744 @*/ 745 PetscErrorCode MatFDColoringSetValues(Mat J, MatFDColoring coloring, const PetscScalar y[]) 746 { 747 MatEntry2 *Jentry2; 748 PetscInt row, i, nrows_k, l, ncolors, nz = 0, bcols, nbcols = 0; 749 const PetscInt *nrows; 750 PetscBool eq; 751 752 PetscFunctionBegin; 753 PetscValidHeaderSpecific(J, MAT_CLASSID, 1); 754 PetscValidHeaderSpecific(coloring, MAT_FDCOLORING_CLASSID, 2); 755 PetscCall(PetscObjectCompareId((PetscObject)J, coloring->matid, &eq)); 756 PetscCheck(eq, PetscObjectComm((PetscObject)J), PETSC_ERR_ARG_WRONG, "Matrix used with MatFDColoringSetValues() must be that used with MatFDColoringCreate()"); 757 Jentry2 = coloring->matentry2; 758 nrows = coloring->nrows; 759 ncolors = coloring->ncolors; 760 bcols = coloring->bcols; 761 762 for (i = 0; i < ncolors; i += bcols) { 763 nrows_k = nrows[nbcols++]; 764 for (l = 0; l < nrows_k; l++) { 765 row = Jentry2[nz].row; /* local row index */ 766 *Jentry2[nz++].valaddr = y[row]; 767 } 768 y += bcols * coloring->m; 769 } 770 PetscCall(MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY)); 771 PetscCall(MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY)); 772 PetscFunctionReturn(PETSC_SUCCESS); 773 } 774