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 arround 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 22 } SuperLU_MatInputMode; 23 24 typedef struct { 25 int_t nprow,npcol,*row,*col; 26 gridinfo_t grid; 27 superlu_options_t options; 28 SuperMatrix A_sup; 29 ScalePermstruct_t ScalePermstruct; 30 LUstruct_t LUstruct; 31 int StatPrint; 32 int MatInputMode; 33 SOLVEstruct_t SOLVEstruct; 34 fact_t FactPattern; 35 MPI_Comm comm_superlu; 36 #if defined(PETSC_USE_COMPLEX) 37 doublecomplex *val; 38 #else 39 double *val; 40 #endif 41 42 /* A few function pointers for inheritance */ 43 PetscErrorCode (*MatDuplicate)(Mat,MatDuplicateOption,Mat*); 44 PetscErrorCode (*MatView)(Mat,PetscViewer); 45 PetscErrorCode (*MatAssemblyEnd)(Mat,MatAssemblyType); 46 PetscErrorCode (*MatLUFactorSymbolic)(Mat,IS,IS,MatFactorInfo*,Mat*); 47 PetscErrorCode (*MatDestroy)(Mat); 48 49 /* Flag to clean up (non-global) SuperLU objects during Destroy */ 50 PetscTruth CleanUpSuperLU_Dist; 51 } Mat_SuperLU_DIST; 52 53 EXTERN PetscErrorCode MatDuplicate_SuperLU_DIST(Mat,MatDuplicateOption,Mat*); 54 extern PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat,PetscViewer); 55 extern PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat,MatFactorInfo *,Mat *); 56 extern PetscErrorCode MatDestroy_SuperLU_DIST(Mat); 57 extern PetscErrorCode MatView_SuperLU_DIST(Mat,PetscViewer); 58 extern PetscErrorCode MatAssemblyEnd_SuperLU_DIST(Mat,MatAssemblyType); 59 extern PetscErrorCode MatSolve_SuperLU_DIST(Mat,Vec,Vec); 60 extern PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat,IS,IS,MatFactorInfo *,Mat *); 61 extern PetscErrorCode MatDuplicate_SuperLU_DIST(Mat, MatDuplicateOption, Mat *); 62 63 EXTERN_C_BEGIN 64 #undef __FUNCT__ 65 #define __FUNCT__ "MatConvert_SuperLU_DIST_AIJ" 66 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SuperLU_DIST_AIJ(Mat A,MatType type,MatReuse reuse,Mat *newmat) 67 { 68 PetscErrorCode ierr; 69 Mat B=*newmat; 70 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST *)A->spptr; 71 72 PetscFunctionBegin; 73 if (reuse == MAT_INITIAL_MATRIX) { 74 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 75 } 76 /* Reset the original function pointers */ 77 B->ops->duplicate = lu->MatDuplicate; 78 B->ops->view = lu->MatView; 79 B->ops->assemblyend = lu->MatAssemblyEnd; 80 B->ops->lufactorsymbolic = lu->MatLUFactorSymbolic; 81 B->ops->destroy = lu->MatDestroy; 82 83 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_superlu_dist_C","",PETSC_NULL);CHKERRQ(ierr); 84 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_superlu_dist_seqaij_C","",PETSC_NULL);CHKERRQ(ierr); 85 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_superlu_dist_C","",PETSC_NULL);CHKERRQ(ierr); 86 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_superlu_dist_mpiaij_C","",PETSC_NULL);CHKERRQ(ierr); 87 88 ierr = PetscObjectChangeTypeName((PetscObject)B,type);CHKERRQ(ierr); 89 *newmat = B; 90 PetscFunctionReturn(0); 91 } 92 EXTERN_C_END 93 94 #undef __FUNCT__ 95 #define __FUNCT__ "MatDestroy_SuperLU_DIST" 96 PetscErrorCode MatDestroy_SuperLU_DIST(Mat A) 97 { 98 PetscErrorCode ierr; 99 PetscMPIInt size; 100 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; 101 102 PetscFunctionBegin; 103 if (lu->CleanUpSuperLU_Dist) { 104 /* Deallocate SuperLU_DIST storage */ 105 if (lu->MatInputMode == GLOBAL) { 106 Destroy_CompCol_Matrix_dist(&lu->A_sup); 107 } else { 108 Destroy_CompRowLoc_Matrix_dist(&lu->A_sup); 109 if ( lu->options.SolveInitialized ) { 110 #if defined(PETSC_USE_COMPLEX) 111 zSolveFinalize(&lu->options, &lu->SOLVEstruct); 112 #else 113 dSolveFinalize(&lu->options, &lu->SOLVEstruct); 114 #endif 115 } 116 } 117 Destroy_LU(A->cmap.N, &lu->grid, &lu->LUstruct); 118 ScalePermstructFree(&lu->ScalePermstruct); 119 LUstructFree(&lu->LUstruct); 120 121 /* Release the SuperLU_DIST process grid. */ 122 superlu_gridexit(&lu->grid); 123 124 ierr = MPI_Comm_free(&(lu->comm_superlu));CHKERRQ(ierr); 125 } 126 127 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 128 if (size == 1) { 129 ierr = MatConvert_SuperLU_DIST_AIJ(A,MATSEQAIJ,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 130 } else { 131 ierr = MatConvert_SuperLU_DIST_AIJ(A,MATMPIAIJ,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 132 } 133 ierr = (*A->ops->destroy)(A);CHKERRQ(ierr); 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNCT__ 138 #define __FUNCT__ "MatSolve_SuperLU_DIST" 139 PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x) 140 { 141 Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; 142 PetscErrorCode ierr; 143 PetscMPIInt size; 144 PetscInt m=A->rmap.N, N=A->cmap.N; 145 SuperLUStat_t stat; 146 double berr[1]; 147 PetscScalar *bptr; 148 PetscInt info, nrhs=1; 149 Vec x_seq; 150 IS iden; 151 VecScatter scat; 152 153 PetscFunctionBegin; 154 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 155 if (size > 1) { 156 if (lu->MatInputMode == GLOBAL) { /* global mat input, convert b to x_seq */ 157 ierr = VecCreateSeq(PETSC_COMM_SELF,N,&x_seq);CHKERRQ(ierr); 158 ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iden);CHKERRQ(ierr); 159 ierr = VecScatterCreate(b_mpi,iden,x_seq,iden,&scat);CHKERRQ(ierr); 160 ierr = ISDestroy(iden);CHKERRQ(ierr); 161 162 ierr = VecScatterBegin(b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD,scat);CHKERRQ(ierr); 163 ierr = VecScatterEnd(b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD,scat);CHKERRQ(ierr); 164 ierr = VecGetArray(x_seq,&bptr);CHKERRQ(ierr); 165 } else { /* distributed mat input */ 166 ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); 167 ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); 168 } 169 } else { /* size == 1 */ 170 ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); 171 ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); 172 } 173 174 if (lu->options.Fact != FACTORED) 175 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(x_seq,x,INSERT_VALUES,SCATTER_REVERSE,scat);CHKERRQ(ierr); 206 ierr = VecScatterEnd(x_seq,x,INSERT_VALUES,SCATTER_REVERSE,scat);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 \ 402 %g / %g / %g\n",time_max,time_min,time); 403 } else { 404 ierr = PetscPrintf(PETSC_COMM_SELF, " Mat conversion(PETSc->SuperLU_DIST) time: \n \ 405 %g\n",time0); 406 } 407 408 PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 409 } 410 PStatFree(&stat); 411 if (size > 1){ 412 F_diag = ((Mat_MPIAIJ *)(*F)->data)->A; 413 F_diag->assembled = PETSC_TRUE; 414 } 415 (*F)->assembled = PETSC_TRUE; 416 lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */ 417 PetscFunctionReturn(0); 418 } 419 420 /* Note the Petsc r and c permutations are ignored */ 421 #undef __FUNCT__ 422 #define __FUNCT__ "MatLUFactorSymbolic_SuperLU_DIST" 423 PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F) 424 { 425 Mat B; 426 Mat_SuperLU_DIST *lu; 427 PetscErrorCode ierr; 428 PetscInt M=A->rmap.N,N=A->cmap.N,indx; 429 PetscMPIInt size; 430 superlu_options_t options; 431 PetscTruth flg; 432 const char *pctype[] = {"MMD_AT_PLUS_A","NATURAL","MMD_ATA"}; 433 const char *prtype[] = {"LargeDiag","NATURAL"}; 434 const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm"}; 435 436 PetscFunctionBegin; 437 /* Create the factorization matrix */ 438 ierr = MatCreate(A->comm,&B);CHKERRQ(ierr); 439 ierr = MatSetSizes(B,A->rmap.n,A->cmap.n,M,N);CHKERRQ(ierr); 440 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 441 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL); 442 ierr = MatMPIAIJSetPreallocation(B,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 443 444 B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST; 445 B->ops->solve = MatSolve_SuperLU_DIST; 446 B->factor = FACTOR_LU; 447 448 lu = (Mat_SuperLU_DIST*)(B->spptr); 449 450 /* Set the default input options: 451 options.Fact = DOFACT; 452 options.Equil = YES; 453 options.ColPerm = MMD_AT_PLUS_A; 454 options.RowPerm = LargeDiag; 455 options.ReplaceTinyPivot = YES; 456 options.Trans = NOTRANS; 457 options.IterRefine = DOUBLE; 458 options.SolveInitialized = NO; 459 options.RefineInitialized = NO; 460 options.PrintStat = YES; 461 */ 462 set_default_options_dist(&options); 463 464 ierr = MPI_Comm_dup(A->comm,&(lu->comm_superlu));CHKERRQ(ierr); 465 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 466 467 ierr = PetscOptionsBegin(A->comm,A->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr); 468 lu->npcol = (PetscMPIInt)(sqrt((PetscReal)size)); /* Default num of process columns */ 469 if (!lu->npcol) lu->npcol = 1; 470 lu->nprow = (PetscMPIInt)(size/lu->npcol); /* Default num of process rows */ 471 ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,&lu->nprow,PETSC_NULL);CHKERRQ(ierr); 472 ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,&lu->npcol,PETSC_NULL);CHKERRQ(ierr); 473 if (size != lu->nprow * lu->npcol) 474 SETERRQ3(PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol); 475 476 lu->MatInputMode = DISTRIBUTED; 477 ierr = PetscOptionsInt("-mat_superlu_dist_matinput","Matrix input mode (0: GLOBAL; 1: DISTRIBUTED)","None",lu->MatInputMode,&lu->MatInputMode,PETSC_NULL);CHKERRQ(ierr); 478 if(lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL; 479 480 ierr = PetscOptionsTruth("-mat_superlu_dist_equil","Equilibrate matrix","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 481 if (!flg) { 482 options.Equil = NO; 483 } 484 485 ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",prtype,2,prtype[0],&indx,&flg);CHKERRQ(ierr); 486 if (flg) { 487 switch (indx) { 488 case 0: 489 options.RowPerm = LargeDiag; 490 break; 491 case 1: 492 options.RowPerm = NOROWPERM; 493 break; 494 } 495 } 496 497 ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",pctype,3,pctype[0],&indx,&flg);CHKERRQ(ierr); 498 if (flg) { 499 switch (indx) { 500 case 0: 501 options.ColPerm = MMD_AT_PLUS_A; 502 break; 503 case 1: 504 options.ColPerm = NATURAL; 505 break; 506 case 2: 507 options.ColPerm = MMD_ATA; 508 break; 509 } 510 } 511 512 ierr = PetscOptionsTruth("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 513 if (!flg) { 514 options.ReplaceTinyPivot = NO; 515 } 516 517 lu->FactPattern = SamePattern; 518 ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,2,factPattern[0],&indx,&flg);CHKERRQ(ierr); 519 if (flg) { 520 switch (indx) { 521 case 0: 522 lu->FactPattern = SamePattern; 523 break; 524 case 1: 525 lu->FactPattern = SamePattern_SameRowPerm; 526 break; 527 } 528 } 529 530 options.IterRefine = NOREFINE; 531 ierr = PetscOptionsTruth("-mat_superlu_dist_iterrefine","Use iterative refinement","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); 532 if (flg) { 533 options.IterRefine = DOUBLE; 534 } 535 536 if (PetscLogPrintInfo) { 537 options.PrintStat = YES; 538 } else { 539 options.PrintStat = NO; 540 } 541 ierr = PetscOptionsTruth("-mat_superlu_dist_statprint","Print factorization information","None", 542 (PetscTruth)options.PrintStat,(PetscTruth*)&options.PrintStat,0);CHKERRQ(ierr); 543 PetscOptionsEnd(); 544 545 /* Initialize the SuperLU process grid. */ 546 superlu_gridinit(lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid); 547 548 /* Initialize ScalePermstruct and LUstruct. */ 549 ScalePermstructInit(M, N, &lu->ScalePermstruct); 550 LUstructInit(M, N, &lu->LUstruct); 551 552 lu->options = options; 553 lu->options.Fact = DOFACT; 554 lu->CleanUpSuperLU_Dist = PETSC_TRUE; 555 *F = B; 556 PetscFunctionReturn(0); 557 } 558 559 #undef __FUNCT__ 560 #define __FUNCT__ "MatAssemblyEnd_SuperLU_DIST" 561 PetscErrorCode MatAssemblyEnd_SuperLU_DIST(Mat A,MatAssemblyType mode) { 562 PetscErrorCode ierr; 563 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 564 565 PetscFunctionBegin; 566 ierr = (*lu->MatAssemblyEnd)(A,mode);CHKERRQ(ierr); 567 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 568 A->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 569 PetscFunctionReturn(0); 570 } 571 572 #undef __FUNCT__ 573 #define __FUNCT__ "MatFactorInfo_SuperLU_DIST" 574 PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat A,PetscViewer viewer) 575 { 576 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->spptr; 577 superlu_options_t options; 578 PetscErrorCode ierr; 579 580 PetscFunctionBegin; 581 /* check if matrix is superlu_dist type */ 582 if (A->ops->solve != MatSolve_SuperLU_DIST) PetscFunctionReturn(0); 583 584 options = lu->options; 585 ierr = PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");CHKERRQ(ierr); 586 ierr = PetscViewerASCIIPrintf(viewer," Equilibrate matrix %s \n",PetscTruths[options.Equil != NO]);CHKERRQ(ierr); 587 ierr = PetscViewerASCIIPrintf(viewer," Matrix input mode %d \n",lu->MatInputMode);CHKERRQ(ierr); 588 ierr = PetscViewerASCIIPrintf(viewer," Replace tiny pivots %s \n",PetscTruths[options.ReplaceTinyPivot != NO]);CHKERRQ(ierr); 589 ierr = PetscViewerASCIIPrintf(viewer," Use iterative refinement %s \n",PetscTruths[options.IterRefine == DOUBLE]);CHKERRQ(ierr); 590 ierr = PetscViewerASCIIPrintf(viewer," Processors in row %d col partition %d \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 591 ierr = PetscViewerASCIIPrintf(viewer," Row permutation %s \n",(options.RowPerm == NOROWPERM) ? "NATURAL": "LargeDiag");CHKERRQ(ierr); 592 if (options.ColPerm == NATURAL) { 593 ierr = PetscViewerASCIIPrintf(viewer," Column permutation NATURAL\n");CHKERRQ(ierr); 594 } else if (options.ColPerm == MMD_AT_PLUS_A) { 595 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_AT_PLUS_A\n");CHKERRQ(ierr); 596 } else if (options.ColPerm == MMD_ATA) { 597 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_ATA\n");CHKERRQ(ierr); 598 } else { 599 SETERRQ(PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 600 } 601 602 if (lu->FactPattern == SamePattern){ 603 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern\n");CHKERRQ(ierr); 604 } else { 605 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); 606 } 607 PetscFunctionReturn(0); 608 } 609 610 #undef __FUNCT__ 611 #define __FUNCT__ "MatView_SuperLU_DIST" 612 PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer) 613 { 614 PetscErrorCode ierr; 615 PetscTruth iascii; 616 PetscViewerFormat format; 617 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 618 619 PetscFunctionBegin; 620 ierr = (*lu->MatView)(A,viewer);CHKERRQ(ierr); 621 622 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 623 if (iascii) { 624 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 625 if (format == PETSC_VIEWER_ASCII_INFO) { 626 ierr = MatFactorInfo_SuperLU_DIST(A,viewer);CHKERRQ(ierr); 627 } 628 } 629 PetscFunctionReturn(0); 630 } 631 632 633 EXTERN_C_BEGIN 634 #undef __FUNCT__ 635 #define __FUNCT__ "MatConvert_AIJ_SuperLU_DIST" 636 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_AIJ_SuperLU_DIST(Mat A,MatType type,MatReuse reuse,Mat *newmat) 637 { 638 /* This routine is only called to convert to MATSUPERLU_DIST */ 639 /* from MATSEQAIJ if A has a single process communicator */ 640 /* or MATMPIAIJ otherwise, so we will ignore 'MatType type'. */ 641 PetscErrorCode ierr; 642 PetscMPIInt size; 643 MPI_Comm comm; 644 Mat B=*newmat; 645 Mat_SuperLU_DIST *lu; 646 647 PetscFunctionBegin; 648 if (reuse == MAT_INITIAL_MATRIX) { 649 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 650 } 651 652 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 653 ierr = PetscNew(Mat_SuperLU_DIST,&lu);CHKERRQ(ierr); 654 655 lu->MatDuplicate = A->ops->duplicate; 656 lu->MatView = A->ops->view; 657 lu->MatAssemblyEnd = A->ops->assemblyend; 658 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 659 lu->MatDestroy = A->ops->destroy; 660 lu->CleanUpSuperLU_Dist = PETSC_FALSE; 661 662 B->spptr = (void*)lu; 663 B->ops->duplicate = MatDuplicate_SuperLU_DIST; 664 B->ops->view = MatView_SuperLU_DIST; 665 B->ops->assemblyend = MatAssemblyEnd_SuperLU_DIST; 666 B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 667 B->ops->destroy = MatDestroy_SuperLU_DIST; 668 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);CHKERRQ(ierr); 669 if (size == 1) { 670 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_superlu_dist_C", 671 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 672 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_seqaij_C", 673 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 674 } else { 675 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_superlu_dist_C", 676 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 677 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_mpiaij_C", 678 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 679 } 680 ierr = PetscInfo(0,"Using SuperLU_DIST for SeqAIJ LU factorization and solves.\n");CHKERRQ(ierr); 681 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSUPERLU_DIST);CHKERRQ(ierr); 682 *newmat = B; 683 PetscFunctionReturn(0); 684 } 685 EXTERN_C_END 686 687 #undef __FUNCT__ 688 #define __FUNCT__ "MatDuplicate_SuperLU_DIST" 689 PetscErrorCode MatDuplicate_SuperLU_DIST(Mat A, MatDuplicateOption op, Mat *M) { 690 PetscErrorCode ierr; 691 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST *)A->spptr; 692 693 PetscFunctionBegin; 694 ierr = (*lu->MatDuplicate)(A,op,M);CHKERRQ(ierr); 695 ierr = PetscMemcpy((*M)->spptr,lu,sizeof(Mat_SuperLU_DIST));CHKERRQ(ierr); 696 PetscFunctionReturn(0); 697 } 698 699 /*MC 700 MATSUPERLU_DIST - MATSUPERLU_DIST = "superlu_dist" - A matrix type providing direct solvers (LU) for parallel matrices 701 via the external package SuperLU_DIST. 702 703 If SuperLU_DIST is installed (see the manual for 704 instructions on how to declare the existence of external packages), 705 a matrix type can be constructed which invokes SuperLU_DIST solvers. 706 After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU_DIST). 707 708 This matrix inherits from MATSEQAIJ when constructed with a single process communicator, 709 and from MATMPIAIJ otherwise. As a result, for single process communicators, 710 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 711 for communicators controlling multiple processes. It is recommended that you call both of 712 the above preallocation routines for simplicity. One can also call MatConvert for an inplace 713 conversion to or from the MATSEQAIJ or MATMPIAIJ type (depending on the communicator size) 714 without data copy. 715 716 Options Database Keys: 717 + -mat_type superlu_dist - sets the matrix type to "superlu_dist" during a call to MatSetFromOptions() 718 . -mat_superlu_dist_r <n> - number of rows in processor partition 719 . -mat_superlu_dist_c <n> - number of columns in processor partition 720 . -mat_superlu_dist_matinput <0,1> - matrix input mode; 0=global, 1=distributed 721 . -mat_superlu_dist_equil - equilibrate the matrix 722 . -mat_superlu_dist_rowperm <LargeDiag,NATURAL> - row permutation 723 . -mat_superlu_dist_colperm <MMD_AT_PLUS_A,MMD_ATA,NATURAL> - column permutation 724 . -mat_superlu_dist_replacetinypivot - replace tiny pivots 725 . -mat_superlu_dist_fact <SamePattern> (choose one of) SamePattern SamePattern_SameRowPerm 726 . -mat_superlu_dist_iterrefine - use iterative refinement 727 - -mat_superlu_dist_statprint - print factorization information 728 729 Level: beginner 730 731 .seealso: PCLU 732 M*/ 733 734 EXTERN_C_BEGIN 735 #undef __FUNCT__ 736 #define __FUNCT__ "MatCreate_SuperLU_DIST" 737 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SuperLU_DIST(Mat A) 738 { 739 PetscErrorCode ierr; 740 PetscMPIInt size; 741 742 PetscFunctionBegin; 743 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 744 if (size == 1) { 745 ierr = MatSetType(A,MATSEQAIJ);CHKERRQ(ierr); 746 } else { 747 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 748 /* A_diag = 0x0 ??? -- do we need it? 749 Mat A_diag = ((Mat_MPIAIJ *)A->data)->A; 750 ierr = MatConvert_AIJ_SuperLU_DIST(A_diag,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A_diag);CHKERRQ(ierr); 751 */ 752 } 753 ierr = MatConvert_AIJ_SuperLU_DIST(A,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 754 PetscFunctionReturn(0); 755 } 756 EXTERN_C_END 757 758