1 #define PETSCMAT_DLL 2 3 /* 4 Provides an interface to the SuperLU_DIST_2.0 sparse solver 5 */ 6 7 #include "src/mat/impls/aij/seq/aij.h" 8 #include "src/mat/impls/aij/mpi/mpiaij.h" 9 #if defined(PETSC_HAVE_STDLIB_H) /* This is to get around weird problem with SuperLU on cray */ 10 #include "stdlib.h" 11 #endif 12 13 EXTERN_C_BEGIN 14 #if defined(PETSC_USE_COMPLEX) 15 #include "superlu_zdefs.h" 16 #else 17 #include "superlu_ddefs.h" 18 #endif 19 EXTERN_C_END 20 21 typedef enum {GLOBAL,DISTRIBUTED} SuperLU_MatInputMode; 22 23 typedef struct { 24 int_t nprow,npcol,*row,*col; 25 gridinfo_t grid; 26 superlu_options_t options; 27 SuperMatrix A_sup; 28 ScalePermstruct_t ScalePermstruct; 29 LUstruct_t LUstruct; 30 int StatPrint; 31 int MatInputMode; 32 SOLVEstruct_t SOLVEstruct; 33 fact_t FactPattern; 34 MPI_Comm comm_superlu; 35 #if defined(PETSC_USE_COMPLEX) 36 doublecomplex *val; 37 #else 38 double *val; 39 #endif 40 41 /* A few function pointers for inheritance */ 42 PetscErrorCode (*MatDuplicate)(Mat,MatDuplicateOption,Mat*); 43 PetscErrorCode (*MatView)(Mat,PetscViewer); 44 PetscErrorCode (*MatAssemblyEnd)(Mat,MatAssemblyType); 45 PetscErrorCode (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*); 46 PetscErrorCode (*MatDestroy)(Mat); 47 48 /* Flag to clean up (non-global) SuperLU objects during Destroy */ 49 PetscTruth CleanUpSuperLU_Dist; 50 } Mat_SuperLU_DIST; 51 52 EXTERN PetscErrorCode MatDuplicate_SuperLU_DIST(Mat,MatDuplicateOption,Mat*); 53 extern PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat,PetscViewer); 54 extern PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat,MatFactorInfo *,Mat *); 55 extern PetscErrorCode MatDestroy_SuperLU_DIST(Mat); 56 extern PetscErrorCode MatView_SuperLU_DIST(Mat,PetscViewer); 57 extern PetscErrorCode MatAssemblyEnd_SuperLU_DIST(Mat,MatAssemblyType); 58 extern PetscErrorCode MatSolve_SuperLU_DIST(Mat,Vec,Vec); 59 extern PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat,IS,IS,MatFactorInfo *,Mat *); 60 extern PetscErrorCode MatDuplicate_SuperLU_DIST(Mat, MatDuplicateOption, Mat *); 61 62 EXTERN_C_BEGIN 63 #undef __FUNCT__ 64 #define __FUNCT__ "MatConvert_SuperLU_DIST_AIJ" 65 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SuperLU_DIST_AIJ(Mat A,MatType type,MatReuse reuse,Mat *newmat) 66 { 67 PetscErrorCode ierr; 68 Mat B=*newmat; 69 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST *)A->spptr; 70 71 PetscFunctionBegin; 72 if (reuse == MAT_INITIAL_MATRIX) { 73 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 74 } 75 /* Reset the original function pointers */ 76 B->ops->duplicate = lu->MatDuplicate; 77 B->ops->view = lu->MatView; 78 B->ops->assemblyend = lu->MatAssemblyEnd; 79 B->ops->lufactorsymbolic = lu->MatLUFactorSymbolic; 80 B->ops->destroy = lu->MatDestroy; 81 ierr = PetscFree(lu);CHKERRQ(ierr); 82 A->spptr = PETSC_NULL; 83 84 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_superlu_dist_C","",PETSC_NULL);CHKERRQ(ierr); 85 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_superlu_dist_seqaij_C","",PETSC_NULL);CHKERRQ(ierr); 86 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_superlu_dist_C","",PETSC_NULL);CHKERRQ(ierr); 87 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_superlu_dist_mpiaij_C","",PETSC_NULL);CHKERRQ(ierr); 88 89 ierr = PetscObjectChangeTypeName((PetscObject)B,type);CHKERRQ(ierr); 90 *newmat = B; 91 PetscFunctionReturn(0); 92 } 93 EXTERN_C_END 94 95 #undef __FUNCT__ 96 #define __FUNCT__ "MatDestroy_SuperLU_DIST" 97 PetscErrorCode MatDestroy_SuperLU_DIST(Mat A) 98 { 99 PetscErrorCode ierr; 100 PetscMPIInt size; 101 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; 102 103 PetscFunctionBegin; 104 if (lu->CleanUpSuperLU_Dist) { 105 /* Deallocate SuperLU_DIST storage */ 106 if (lu->MatInputMode == GLOBAL) { 107 Destroy_CompCol_Matrix_dist(&lu->A_sup); 108 } else { 109 Destroy_CompRowLoc_Matrix_dist(&lu->A_sup); 110 if ( lu->options.SolveInitialized ) { 111 #if defined(PETSC_USE_COMPLEX) 112 zSolveFinalize(&lu->options, &lu->SOLVEstruct); 113 #else 114 dSolveFinalize(&lu->options, &lu->SOLVEstruct); 115 #endif 116 } 117 } 118 Destroy_LU(A->cmap.N, &lu->grid, &lu->LUstruct); 119 ScalePermstructFree(&lu->ScalePermstruct); 120 LUstructFree(&lu->LUstruct); 121 122 /* Release the SuperLU_DIST process grid. */ 123 superlu_gridexit(&lu->grid); 124 125 ierr = MPI_Comm_free(&(lu->comm_superlu));CHKERRQ(ierr); 126 } 127 128 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 129 if (size == 1) { 130 ierr = MatConvert_SuperLU_DIST_AIJ(A,MATSEQAIJ,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 131 } else { 132 ierr = MatConvert_SuperLU_DIST_AIJ(A,MATMPIAIJ,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 133 } 134 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 135 PetscFunctionReturn(0); 136 } 137 138 #undef __FUNCT__ 139 #define __FUNCT__ "MatSolve_SuperLU_DIST" 140 PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x) 141 { 142 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; 143 PetscErrorCode ierr; 144 PetscMPIInt size; 145 PetscInt m=A->rmap.N, N=A->cmap.N; 146 SuperLUStat_t stat; 147 double berr[1]; 148 PetscScalar *bptr; 149 PetscInt info, nrhs=1; 150 Vec x_seq; 151 IS iden; 152 VecScatter scat; 153 154 PetscFunctionBegin; 155 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 156 if (size > 1) { 157 if (lu->MatInputMode == GLOBAL) { /* global mat input, convert b to x_seq */ 158 ierr = VecCreateSeq(PETSC_COMM_SELF,N,&x_seq);CHKERRQ(ierr); 159 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iden);CHKERRQ(ierr); 160 ierr = VecScatterCreate(b_mpi,iden,x_seq,iden,&scat);CHKERRQ(ierr); 161 ierr = ISDestroy(iden);CHKERRQ(ierr); 162 163 ierr = VecScatterBegin(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 164 ierr = VecScatterEnd(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 165 ierr = VecGetArray(x_seq,&bptr);CHKERRQ(ierr); 166 } else { /* distributed mat input */ 167 ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); 168 ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); 169 } 170 } else { /* size == 1 */ 171 ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); 172 ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); 173 } 174 175 if (lu->options.Fact != FACTORED) SETERRQ(PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); 176 177 PStatInit(&stat); /* Initialize the statistics variables. */ 178 if (lu->MatInputMode == GLOBAL) { 179 #if defined(PETSC_USE_COMPLEX) 180 pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,(doublecomplex*)bptr, m, nrhs, 181 &lu->grid, &lu->LUstruct, berr, &stat, &info); 182 #else 183 pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr, m, nrhs, 184 &lu->grid, &lu->LUstruct, berr, &stat, &info); 185 #endif 186 } else { /* distributed mat input */ 187 #if defined(PETSC_USE_COMPLEX) 188 pzgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, (doublecomplex*)bptr, A->rmap.N, nrhs, &lu->grid, 189 &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &info); 190 if (info) SETERRQ1(PETSC_ERR_LIB,"pzgssvx fails, info: %d\n",info); 191 #else 192 pdgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, bptr, A->rmap.N, nrhs, &lu->grid, 193 &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &info); 194 if (info) SETERRQ1(PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info); 195 #endif 196 } 197 if (lu->options.PrintStat) { 198 PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 199 } 200 PStatFree(&stat); 201 202 if (size > 1) { 203 if (lu->MatInputMode == GLOBAL){ /* convert seq x to mpi x */ 204 ierr = VecRestoreArray(x_seq,&bptr);CHKERRQ(ierr); 205 ierr = VecScatterBegin(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 206 ierr = VecScatterEnd(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); 207 ierr = VecScatterDestroy(scat);CHKERRQ(ierr); 208 ierr = VecDestroy(x_seq);CHKERRQ(ierr); 209 } else { 210 ierr = VecRestoreArray(x,&bptr);CHKERRQ(ierr); 211 } 212 } else { 213 ierr = VecRestoreArray(x,&bptr);CHKERRQ(ierr); 214 } 215 PetscFunctionReturn(0); 216 } 217 218 #undef __FUNCT__ 219 #define __FUNCT__ "MatLUFactorNumeric_SuperLU_DIST" 220 PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat A,MatFactorInfo *info,Mat *F) 221 { 222 Mat *tseq,A_seq = PETSC_NULL; 223 Mat_SeqAIJ *aa,*bb; 224 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)(*F)->spptr; 225 PetscErrorCode ierr; 226 PetscInt M=A->rmap.N,N=A->cmap.N,sinfo,i,*ai,*aj,*bi,*bj,nz,rstart,*garray, 227 m=A->rmap.n, irow,colA_start,j,jcol,jB,countA,countB,*bjj,*ajj; 228 PetscMPIInt size,rank; 229 SuperLUStat_t stat; 230 double *berr=0; 231 IS isrow; 232 PetscLogDouble time0,time,time_min,time_max; 233 Mat F_diag=PETSC_NULL; 234 #if defined(PETSC_USE_COMPLEX) 235 doublecomplex *av, *bv; 236 #else 237 double *av, *bv; 238 #endif 239 240 PetscFunctionBegin; 241 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 242 ierr = MPI_Comm_rank(A->comm,&rank);CHKERRQ(ierr); 243 244 if (lu->options.PrintStat) { /* collect time for mat conversion */ 245 ierr = MPI_Barrier(A->comm);CHKERRQ(ierr); 246 ierr = PetscGetTime(&time0);CHKERRQ(ierr); 247 } 248 249 if (lu->MatInputMode == GLOBAL) { /* global mat input */ 250 if (size > 1) { /* convert mpi A to seq mat A */ 251 ierr = ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);CHKERRQ(ierr); 252 ierr = MatGetSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);CHKERRQ(ierr); 253 ierr = ISDestroy(isrow);CHKERRQ(ierr); 254 255 A_seq = *tseq; 256 ierr = PetscFree(tseq);CHKERRQ(ierr); 257 aa = (Mat_SeqAIJ*)A_seq->data; 258 } else { 259 aa = (Mat_SeqAIJ*)A->data; 260 } 261 262 /* Convert Petsc NR matrix to SuperLU_DIST NC. 263 Note: memories of lu->val, col and row are allocated by CompRow_to_CompCol_dist()! */ 264 if (lu->options.Fact != DOFACT) {/* successive numeric factorization, sparsity pattern is reused. */ 265 if (lu->FactPattern == SamePattern_SameRowPerm){ 266 Destroy_CompCol_Matrix_dist(&lu->A_sup); 267 /* Destroy_LU(N, &lu->grid, &lu->LUstruct); Crash! Comment it out does not lead to mem leak. */ 268 lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ 269 } else { 270 Destroy_CompCol_Matrix_dist(&lu->A_sup); 271 Destroy_LU(N, &lu->grid, &lu->LUstruct); 272 lu->options.Fact = SamePattern; 273 } 274 } 275 #if defined(PETSC_USE_COMPLEX) 276 zCompRow_to_CompCol_dist(M,N,aa->nz,(doublecomplex*)aa->a,aa->j,aa->i,&lu->val,&lu->col, &lu->row); 277 #else 278 dCompRow_to_CompCol_dist(M,N,aa->nz,aa->a,aa->j,aa->i,&lu->val, &lu->col, &lu->row); 279 #endif 280 281 /* Create compressed column matrix A_sup. */ 282 #if defined(PETSC_USE_COMPLEX) 283 zCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_Z, SLU_GE); 284 #else 285 dCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_D, SLU_GE); 286 #endif 287 } else { /* distributed mat input */ 288 Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; 289 aa=(Mat_SeqAIJ*)(mat->A)->data; 290 bb=(Mat_SeqAIJ*)(mat->B)->data; 291 ai=aa->i; aj=aa->j; 292 bi=bb->i; bj=bb->j; 293 #if defined(PETSC_USE_COMPLEX) 294 av=(doublecomplex*)aa->a; 295 bv=(doublecomplex*)bb->a; 296 #else 297 av=aa->a; 298 bv=bb->a; 299 #endif 300 rstart = A->rmap.rstart; 301 nz = aa->nz + bb->nz; 302 garray = mat->garray; 303 304 if (lu->options.Fact == DOFACT) {/* first numeric factorization */ 305 #if defined(PETSC_USE_COMPLEX) 306 zallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row); 307 #else 308 dallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row); 309 #endif 310 } else { /* successive numeric factorization, sparsity pattern and perm_c are reused. */ 311 if (lu->FactPattern == SamePattern_SameRowPerm){ 312 /* Destroy_LU(N, &lu->grid, &lu->LUstruct); Crash! Comment it out does not lead to mem leak. */ 313 lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ 314 } else { 315 Destroy_LU(N, &lu->grid, &lu->LUstruct); /* Deallocate storage associated with the L and U matrices. */ 316 lu->options.Fact = SamePattern; 317 } 318 } 319 nz = 0; irow = rstart; 320 for ( i=0; i<m; i++ ) { 321 lu->row[i] = nz; 322 countA = ai[i+1] - ai[i]; 323 countB = bi[i+1] - bi[i]; 324 ajj = aj + ai[i]; /* ptr to the beginning of this row */ 325 bjj = bj + bi[i]; 326 327 /* B part, smaller col index */ 328 colA_start = rstart + ajj[0]; /* the smallest global col index of A */ 329 jB = 0; 330 for (j=0; j<countB; j++){ 331 jcol = garray[bjj[j]]; 332 if (jcol > colA_start) { 333 jB = j; 334 break; 335 } 336 lu->col[nz] = jcol; 337 lu->val[nz++] = *bv++; 338 if (j==countB-1) jB = countB; 339 } 340 341 /* A part */ 342 for (j=0; j<countA; j++){ 343 lu->col[nz] = rstart + ajj[j]; 344 lu->val[nz++] = *av++; 345 } 346 347 /* B part, larger col index */ 348 for (j=jB; j<countB; j++){ 349 lu->col[nz] = garray[bjj[j]]; 350 lu->val[nz++] = *bv++; 351 } 352 } 353 lu->row[m] = nz; 354 #if defined(PETSC_USE_COMPLEX) 355 zCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart, 356 lu->val, lu->col, lu->row, SLU_NR_loc, SLU_Z, SLU_GE); 357 #else 358 dCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart, 359 lu->val, lu->col, lu->row, SLU_NR_loc, SLU_D, SLU_GE); 360 #endif 361 } 362 if (lu->options.PrintStat) { 363 ierr = PetscGetTime(&time);CHKERRQ(ierr); 364 time0 = time - time0; 365 } 366 367 /* Factor the matrix. */ 368 PStatInit(&stat); /* Initialize the statistics variables. */ 369 370 if (lu->MatInputMode == GLOBAL) { /* global mat input */ 371 #if defined(PETSC_USE_COMPLEX) 372 pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0, 373 &lu->grid, &lu->LUstruct, berr, &stat, &sinfo); 374 #else 375 pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0, 376 &lu->grid, &lu->LUstruct, berr, &stat, &sinfo); 377 #endif 378 } else { /* distributed mat input */ 379 #if defined(PETSC_USE_COMPLEX) 380 pzgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0, &lu->grid, 381 &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo); 382 if (sinfo) SETERRQ1(PETSC_ERR_LIB,"pzgssvx fails, info: %d\n",sinfo); 383 #else 384 pdgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0, &lu->grid, 385 &lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo); 386 if (sinfo) SETERRQ1(PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",sinfo); 387 #endif 388 } 389 390 if (lu->MatInputMode == GLOBAL && size > 1){ 391 ierr = MatDestroy(A_seq);CHKERRQ(ierr); 392 } 393 394 if (lu->options.PrintStat) { 395 if (size > 1){ 396 ierr = MPI_Reduce(&time0,&time_max,1,MPI_DOUBLE,MPI_MAX,0,A->comm); 397 ierr = MPI_Reduce(&time0,&time_min,1,MPI_DOUBLE,MPI_MIN,0,A->comm); 398 ierr = MPI_Reduce(&time0,&time,1,MPI_DOUBLE,MPI_SUM,0,A->comm); 399 time = time/size; /* average time */ 400 if (!rank) { 401 ierr = PetscPrintf(PETSC_COMM_SELF, " Mat conversion(PETSc->SuperLU_DIST) time (max/min/avg): \n %g / %g / %g\n",time_max,time_min,time);CHKERRQ(ierr); 402 } 403 } else { 404 ierr = PetscPrintf(PETSC_COMM_SELF, " Mat conversion(PETSc->SuperLU_DIST) time: \n %g\n",time0);CHKERRQ(ierr); 405 } 406 PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 407 } 408 PStatFree(&stat); 409 if (size > 1){ 410 F_diag = ((Mat_MPIAIJ *)(*F)->data)->A; 411 F_diag->assembled = PETSC_TRUE; 412 } 413 (*F)->assembled = PETSC_TRUE; 414 lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */ 415 PetscFunctionReturn(0); 416 } 417 418 /* Note the Petsc r and c permutations are ignored */ 419 #undef __FUNCT__ 420 #define __FUNCT__ "MatLUFactorSymbolic_SuperLU_DIST" 421 PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F) 422 { 423 Mat B; 424 Mat_SuperLU_DIST *lu; 425 PetscErrorCode ierr; 426 PetscInt M=A->rmap.N,N=A->cmap.N,indx; 427 PetscMPIInt size; 428 superlu_options_t options; 429 PetscTruth flg; 430 const char *pctype[] = {"MMD_AT_PLUS_A","NATURAL","MMD_ATA"}; 431 const char *prtype[] = {"LargeDiag","NATURAL"}; 432 const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm"}; 433 434 PetscFunctionBegin; 435 /* Create the factorization matrix */ 436 ierr = MatCreate(A->comm,&B);CHKERRQ(ierr); 437 ierr = MatSetSizes(B,A->rmap.n,A->cmap.n,M,N);CHKERRQ(ierr); 438 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 439 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL); 440 ierr = MatMPIAIJSetPreallocation(B,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 441 442 B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST; 443 B->ops->solve = MatSolve_SuperLU_DIST; 444 B->factor = FACTOR_LU; 445 446 lu = (Mat_SuperLU_DIST*)(B->spptr); 447 448 /* Set the default input options: 449 options.Fact = DOFACT; 450 options.Equil = YES; 451 options.ColPerm = MMD_AT_PLUS_A; 452 options.RowPerm = LargeDiag; 453 options.ReplaceTinyPivot = YES; 454 options.Trans = NOTRANS; 455 options.IterRefine = DOUBLE; 456 options.SolveInitialized = NO; 457 options.RefineInitialized = NO; 458 options.PrintStat = YES; 459 */ 460 set_default_options_dist(&options); 461 462 ierr = MPI_Comm_dup(A->comm,&(lu->comm_superlu));CHKERRQ(ierr); 463 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 464 /* Default num of process columns and rows */ 465 lu->npcol = (PetscMPIInt)(0.5 + sqrt((PetscReal)size)); 466 if (!lu->npcol) lu->npcol = 1; 467 while (lu->npcol > 0) { 468 lu->nprow = (PetscMPIInt)(size/lu->npcol); 469 if (size == lu->nprow * lu->npcol) break; 470 lu->npcol --; 471 } 472 473 ierr = PetscOptionsBegin(A->comm,A->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr); 474 ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,&lu->nprow,PETSC_NULL);CHKERRQ(ierr); 475 ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,&lu->npcol,PETSC_NULL);CHKERRQ(ierr); 476 if (size != lu->nprow * lu->npcol) 477 SETERRQ3(PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol); 478 479 lu->MatInputMode = DISTRIBUTED; 480 ierr = PetscOptionsInt("-mat_superlu_dist_matinput","Matrix input mode (0: GLOBAL; 1: DISTRIBUTED)","None",lu->MatInputMode,&lu->MatInputMode,PETSC_NULL);CHKERRQ(ierr); 481 if(lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL; 482 483 ierr = PetscOptionsTruth("-mat_superlu_dist_equil","Equilibrate matrix","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 484 if (!flg) { 485 options.Equil = NO; 486 } 487 488 ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",prtype,2,prtype[0],&indx,&flg);CHKERRQ(ierr); 489 if (flg) { 490 switch (indx) { 491 case 0: 492 options.RowPerm = LargeDiag; 493 break; 494 case 1: 495 options.RowPerm = NOROWPERM; 496 break; 497 } 498 } 499 500 ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",pctype,3,pctype[0],&indx,&flg);CHKERRQ(ierr); 501 if (flg) { 502 switch (indx) { 503 case 0: 504 options.ColPerm = MMD_AT_PLUS_A; 505 break; 506 case 1: 507 options.ColPerm = NATURAL; 508 break; 509 case 2: 510 options.ColPerm = MMD_ATA; 511 break; 512 } 513 } 514 515 ierr = PetscOptionsTruth("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 516 if (!flg) { 517 options.ReplaceTinyPivot = NO; 518 } 519 520 lu->FactPattern = SamePattern; 521 ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,2,factPattern[0],&indx,&flg);CHKERRQ(ierr); 522 if (flg) { 523 switch (indx) { 524 case 0: 525 lu->FactPattern = SamePattern; 526 break; 527 case 1: 528 lu->FactPattern = SamePattern_SameRowPerm; 529 break; 530 } 531 } 532 533 options.IterRefine = NOREFINE; 534 ierr = PetscOptionsTruth("-mat_superlu_dist_iterrefine","Use iterative refinement","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); 535 if (flg) { 536 options.IterRefine = DOUBLE; 537 } 538 539 if (PetscLogPrintInfo) { 540 options.PrintStat = YES; 541 } else { 542 options.PrintStat = NO; 543 } 544 ierr = PetscOptionsTruth("-mat_superlu_dist_statprint","Print factorization information","None", 545 (PetscTruth)options.PrintStat,(PetscTruth*)&options.PrintStat,0);CHKERRQ(ierr); 546 PetscOptionsEnd(); 547 548 /* Initialize the SuperLU process grid. */ 549 superlu_gridinit(lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid); 550 551 /* Initialize ScalePermstruct and LUstruct. */ 552 ScalePermstructInit(M, N, &lu->ScalePermstruct); 553 LUstructInit(M, N, &lu->LUstruct); 554 555 lu->options = options; 556 lu->options.Fact = DOFACT; 557 lu->CleanUpSuperLU_Dist = PETSC_TRUE; 558 *F = B; 559 PetscFunctionReturn(0); 560 } 561 562 #undef __FUNCT__ 563 #define __FUNCT__ "MatAssemblyEnd_SuperLU_DIST" 564 PetscErrorCode MatAssemblyEnd_SuperLU_DIST(Mat A,MatAssemblyType mode) { 565 PetscErrorCode ierr; 566 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 567 568 PetscFunctionBegin; 569 ierr = (*lu->MatAssemblyEnd)(A,mode);CHKERRQ(ierr); 570 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 571 A->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 572 PetscFunctionReturn(0); 573 } 574 575 #undef __FUNCT__ 576 #define __FUNCT__ "MatFactorInfo_SuperLU_DIST" 577 PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat A,PetscViewer viewer) 578 { 579 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->spptr; 580 superlu_options_t options; 581 PetscErrorCode ierr; 582 583 PetscFunctionBegin; 584 /* check if matrix is superlu_dist type */ 585 if (A->ops->solve != MatSolve_SuperLU_DIST) PetscFunctionReturn(0); 586 587 options = lu->options; 588 ierr = PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");CHKERRQ(ierr); 589 ierr = PetscViewerASCIIPrintf(viewer," Process grid nprow %D x npcol %D \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 590 ierr = PetscViewerASCIIPrintf(viewer," Equilibrate matrix %s \n",PetscTruths[options.Equil != NO]);CHKERRQ(ierr); 591 ierr = PetscViewerASCIIPrintf(viewer," Matrix input mode %d \n",lu->MatInputMode);CHKERRQ(ierr); 592 ierr = PetscViewerASCIIPrintf(viewer," Replace tiny pivots %s \n",PetscTruths[options.ReplaceTinyPivot != NO]);CHKERRQ(ierr); 593 ierr = PetscViewerASCIIPrintf(viewer," Use iterative refinement %s \n",PetscTruths[options.IterRefine == DOUBLE]);CHKERRQ(ierr); 594 ierr = PetscViewerASCIIPrintf(viewer," Processors in row %d col partition %d \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 595 ierr = PetscViewerASCIIPrintf(viewer," Row permutation %s \n",(options.RowPerm == NOROWPERM) ? "NATURAL": "LargeDiag");CHKERRQ(ierr); 596 if (options.ColPerm == NATURAL) { 597 ierr = PetscViewerASCIIPrintf(viewer," Column permutation NATURAL\n");CHKERRQ(ierr); 598 } else if (options.ColPerm == MMD_AT_PLUS_A) { 599 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_AT_PLUS_A\n");CHKERRQ(ierr); 600 } else if (options.ColPerm == MMD_ATA) { 601 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_ATA\n");CHKERRQ(ierr); 602 } else { 603 SETERRQ(PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 604 } 605 606 if (lu->FactPattern == SamePattern){ 607 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern\n");CHKERRQ(ierr); 608 } else { 609 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); 610 } 611 PetscFunctionReturn(0); 612 } 613 614 #undef __FUNCT__ 615 #define __FUNCT__ "MatView_SuperLU_DIST" 616 PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer) 617 { 618 PetscErrorCode ierr; 619 PetscTruth iascii; 620 PetscViewerFormat format; 621 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 622 623 PetscFunctionBegin; 624 ierr = (*lu->MatView)(A,viewer);CHKERRQ(ierr); 625 626 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 627 if (iascii) { 628 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 629 if (format == PETSC_VIEWER_ASCII_INFO) { 630 ierr = MatFactorInfo_SuperLU_DIST(A,viewer);CHKERRQ(ierr); 631 } 632 } 633 PetscFunctionReturn(0); 634 } 635 636 637 EXTERN_C_BEGIN 638 #undef __FUNCT__ 639 #define __FUNCT__ "MatConvert_AIJ_SuperLU_DIST" 640 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_AIJ_SuperLU_DIST(Mat A,MatType type,MatReuse reuse,Mat *newmat) 641 { 642 /* This routine is only called to convert to MATSUPERLU_DIST */ 643 /* from MATSEQAIJ if A has a single process communicator */ 644 /* or MATMPIAIJ otherwise, so we will ignore 'MatType type'. */ 645 PetscErrorCode ierr; 646 PetscMPIInt size; 647 MPI_Comm comm; 648 Mat B=*newmat; 649 Mat_SuperLU_DIST *lu; 650 651 PetscFunctionBegin; 652 ierr = PetscNewLog(B,Mat_SuperLU_DIST,&lu);CHKERRQ(ierr); 653 if (reuse == MAT_INITIAL_MATRIX) { 654 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 655 lu->MatDuplicate = B->ops->duplicate; 656 lu->MatView = B->ops->view; 657 lu->MatAssemblyEnd = B->ops->assemblyend; 658 lu->MatLUFactorSymbolic = B->ops->lufactorsymbolic; 659 lu->MatDestroy = B->ops->destroy; 660 } else { 661 lu->MatDuplicate = A->ops->duplicate; 662 lu->MatView = A->ops->view; 663 lu->MatAssemblyEnd = A->ops->assemblyend; 664 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 665 lu->MatDestroy = A->ops->destroy; 666 } 667 lu->CleanUpSuperLU_Dist = PETSC_FALSE; 668 669 B->spptr = (void*)lu; 670 B->ops->duplicate = MatDuplicate_SuperLU_DIST; 671 B->ops->view = MatView_SuperLU_DIST; 672 B->ops->assemblyend = MatAssemblyEnd_SuperLU_DIST; 673 B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 674 B->ops->destroy = MatDestroy_SuperLU_DIST; 675 676 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 677 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);CHKERRQ(ierr); 678 if (size == 1) { 679 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_superlu_dist_C", 680 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 681 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_seqaij_C", 682 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 683 } else { 684 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_superlu_dist_C", 685 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 686 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_mpiaij_C", 687 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 688 } 689 ierr = PetscInfo(A,"Using SuperLU_DIST for SeqAIJ LU factorization and solves.\n");CHKERRQ(ierr); 690 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSUPERLU_DIST);CHKERRQ(ierr); 691 *newmat = B; 692 PetscFunctionReturn(0); 693 } 694 EXTERN_C_END 695 696 #undef __FUNCT__ 697 #define __FUNCT__ "MatDuplicate_SuperLU_DIST" 698 PetscErrorCode MatDuplicate_SuperLU_DIST(Mat A, MatDuplicateOption op, Mat *M) { 699 PetscErrorCode ierr; 700 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST *)A->spptr; 701 702 PetscFunctionBegin; 703 ierr = (*lu->MatDuplicate)(A,op,M);CHKERRQ(ierr); 704 ierr = PetscMemcpy((*M)->spptr,lu,sizeof(Mat_SuperLU_DIST));CHKERRQ(ierr); 705 PetscFunctionReturn(0); 706 } 707 708 /*MC 709 MATSUPERLU_DIST - MATSUPERLU_DIST = "superlu_dist" - A matrix type providing direct solvers (LU) for parallel matrices 710 via the external package SuperLU_DIST. 711 712 If SuperLU_DIST is installed (see the manual for 713 instructions on how to declare the existence of external packages), 714 a matrix type can be constructed which invokes SuperLU_DIST solvers. 715 After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU_DIST) then 716 optionally call MatSeqAIJSetPreallocation() or MatMPIAIJSetPreallocation() DO NOT 717 call MatCreateSeqAIJ/MPIAIJ() directly or the preallocation information will be LOST! 718 719 This matrix inherits from MATSEQAIJ when constructed with a single process communicator, 720 and from MATMPIAIJ otherwise. As a result, for single process communicators, 721 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 722 for communicators controlling multiple processes. It is recommended that you call both of 723 the above preallocation routines for simplicity. One can also call MatConvert() for an inplace 724 conversion to or from the MATSEQAIJ or MATMPIAIJ type (depending on the communicator size) 725 without data copy; but this MUST be called AFTER the matrix values are set. 726 727 728 729 Options Database Keys: 730 + -mat_type superlu_dist - sets the matrix type to "superlu_dist" during a call to MatSetFromOptions() 731 . -mat_superlu_dist_r <n> - number of rows in processor partition 732 . -mat_superlu_dist_c <n> - number of columns in processor partition 733 . -mat_superlu_dist_matinput <0,1> - matrix input mode; 0=global, 1=distributed 734 . -mat_superlu_dist_equil - equilibrate the matrix 735 . -mat_superlu_dist_rowperm <LargeDiag,NATURAL> - row permutation 736 . -mat_superlu_dist_colperm <MMD_AT_PLUS_A,MMD_ATA,NATURAL> - column permutation 737 . -mat_superlu_dist_replacetinypivot - replace tiny pivots 738 . -mat_superlu_dist_fact <SamePattern> (choose one of) SamePattern SamePattern_SameRowPerm 739 . -mat_superlu_dist_iterrefine - use iterative refinement 740 - -mat_superlu_dist_statprint - print factorization information 741 742 Level: beginner 743 744 .seealso: PCLU 745 M*/ 746 747 EXTERN_C_BEGIN 748 #undef __FUNCT__ 749 #define __FUNCT__ "MatCreate_SuperLU_DIST" 750 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SuperLU_DIST(Mat A) 751 { 752 PetscErrorCode ierr; 753 PetscMPIInt size; 754 755 PetscFunctionBegin; 756 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 757 if (size == 1) { 758 ierr = MatSetType(A,MATSEQAIJ);CHKERRQ(ierr); 759 } else { 760 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 761 /* A_diag = 0x0 ??? -- do we need it? 762 Mat A_diag = ((Mat_MPIAIJ *)A->data)->A; 763 ierr = MatConvert_AIJ_SuperLU_DIST(A_diag,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A_diag);CHKERRQ(ierr); 764 */ 765 } 766 ierr = MatConvert_AIJ_SuperLU_DIST(A,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 767 PetscFunctionReturn(0); 768 } 769 EXTERN_C_END 770 771