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 } else { 403 ierr = PetscPrintf(PETSC_COMM_SELF, " Mat conversion(PETSc->SuperLU_DIST) time: \n \ %g\n",time0);CHKERRQ(ierr); 404 } 405 PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ 406 } 407 PStatFree(&stat); 408 if (size > 1){ 409 F_diag = ((Mat_MPIAIJ *)(*F)->data)->A; 410 F_diag->assembled = PETSC_TRUE; 411 } 412 (*F)->assembled = PETSC_TRUE; 413 lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */ 414 PetscFunctionReturn(0); 415 } 416 417 /* Note the Petsc r and c permutations are ignored */ 418 #undef __FUNCT__ 419 #define __FUNCT__ "MatLUFactorSymbolic_SuperLU_DIST" 420 PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat A,IS r,IS c,MatFactorInfo *info,Mat *F) 421 { 422 Mat B; 423 Mat_SuperLU_DIST *lu; 424 PetscErrorCode ierr; 425 PetscInt M=A->rmap.N,N=A->cmap.N,indx; 426 PetscMPIInt size; 427 superlu_options_t options; 428 PetscTruth flg; 429 const char *pctype[] = {"MMD_AT_PLUS_A","NATURAL","MMD_ATA"}; 430 const char *prtype[] = {"LargeDiag","NATURAL"}; 431 const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm"}; 432 433 PetscFunctionBegin; 434 /* Create the factorization matrix */ 435 ierr = MatCreate(A->comm,&B);CHKERRQ(ierr); 436 ierr = MatSetSizes(B,A->rmap.n,A->cmap.n,M,N);CHKERRQ(ierr); 437 ierr = MatSetType(B,A->type_name);CHKERRQ(ierr); 438 ierr = MatSeqAIJSetPreallocation(B,0,PETSC_NULL); 439 ierr = MatMPIAIJSetPreallocation(B,0,PETSC_NULL,0,PETSC_NULL);CHKERRQ(ierr); 440 441 B->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST; 442 B->ops->solve = MatSolve_SuperLU_DIST; 443 B->factor = FACTOR_LU; 444 445 lu = (Mat_SuperLU_DIST*)(B->spptr); 446 447 /* Set the default input options: 448 options.Fact = DOFACT; 449 options.Equil = YES; 450 options.ColPerm = MMD_AT_PLUS_A; 451 options.RowPerm = LargeDiag; 452 options.ReplaceTinyPivot = YES; 453 options.Trans = NOTRANS; 454 options.IterRefine = DOUBLE; 455 options.SolveInitialized = NO; 456 options.RefineInitialized = NO; 457 options.PrintStat = YES; 458 */ 459 set_default_options_dist(&options); 460 461 ierr = MPI_Comm_dup(A->comm,&(lu->comm_superlu));CHKERRQ(ierr); 462 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 463 /* Default num of process columns and rows */ 464 lu->npcol = (PetscMPIInt)(0.5 + sqrt((PetscReal)size)); 465 if (!lu->npcol) lu->npcol = 1; 466 while (lu->npcol > 0) { 467 lu->nprow = (PetscMPIInt)(size/lu->npcol); 468 if (size == lu->nprow * lu->npcol) break; 469 lu->npcol --; 470 } 471 472 ierr = PetscOptionsBegin(A->comm,A->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr); 473 ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,&lu->nprow,PETSC_NULL);CHKERRQ(ierr); 474 ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,&lu->npcol,PETSC_NULL);CHKERRQ(ierr); 475 if (size != lu->nprow * lu->npcol) 476 SETERRQ3(PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol); 477 478 lu->MatInputMode = DISTRIBUTED; 479 ierr = PetscOptionsInt("-mat_superlu_dist_matinput","Matrix input mode (0: GLOBAL; 1: DISTRIBUTED)","None",lu->MatInputMode,&lu->MatInputMode,PETSC_NULL);CHKERRQ(ierr); 480 if(lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL; 481 482 ierr = PetscOptionsTruth("-mat_superlu_dist_equil","Equilibrate matrix","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 483 if (!flg) { 484 options.Equil = NO; 485 } 486 487 ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",prtype,2,prtype[0],&indx,&flg);CHKERRQ(ierr); 488 if (flg) { 489 switch (indx) { 490 case 0: 491 options.RowPerm = LargeDiag; 492 break; 493 case 1: 494 options.RowPerm = NOROWPERM; 495 break; 496 } 497 } 498 499 ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",pctype,3,pctype[0],&indx,&flg);CHKERRQ(ierr); 500 if (flg) { 501 switch (indx) { 502 case 0: 503 options.ColPerm = MMD_AT_PLUS_A; 504 break; 505 case 1: 506 options.ColPerm = NATURAL; 507 break; 508 case 2: 509 options.ColPerm = MMD_ATA; 510 break; 511 } 512 } 513 514 ierr = PetscOptionsTruth("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",PETSC_TRUE,&flg,0);CHKERRQ(ierr); 515 if (!flg) { 516 options.ReplaceTinyPivot = NO; 517 } 518 519 lu->FactPattern = SamePattern; 520 ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,2,factPattern[0],&indx,&flg);CHKERRQ(ierr); 521 if (flg) { 522 switch (indx) { 523 case 0: 524 lu->FactPattern = SamePattern; 525 break; 526 case 1: 527 lu->FactPattern = SamePattern_SameRowPerm; 528 break; 529 } 530 } 531 532 options.IterRefine = NOREFINE; 533 ierr = PetscOptionsTruth("-mat_superlu_dist_iterrefine","Use iterative refinement","None",PETSC_FALSE,&flg,0);CHKERRQ(ierr); 534 if (flg) { 535 options.IterRefine = DOUBLE; 536 } 537 538 if (PetscLogPrintInfo) { 539 options.PrintStat = YES; 540 } else { 541 options.PrintStat = NO; 542 } 543 ierr = PetscOptionsTruth("-mat_superlu_dist_statprint","Print factorization information","None", 544 (PetscTruth)options.PrintStat,(PetscTruth*)&options.PrintStat,0);CHKERRQ(ierr); 545 PetscOptionsEnd(); 546 547 /* Initialize the SuperLU process grid. */ 548 superlu_gridinit(lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid); 549 550 /* Initialize ScalePermstruct and LUstruct. */ 551 ScalePermstructInit(M, N, &lu->ScalePermstruct); 552 LUstructInit(M, N, &lu->LUstruct); 553 554 lu->options = options; 555 lu->options.Fact = DOFACT; 556 lu->CleanUpSuperLU_Dist = PETSC_TRUE; 557 *F = B; 558 PetscFunctionReturn(0); 559 } 560 561 #undef __FUNCT__ 562 #define __FUNCT__ "MatAssemblyEnd_SuperLU_DIST" 563 PetscErrorCode MatAssemblyEnd_SuperLU_DIST(Mat A,MatAssemblyType mode) { 564 PetscErrorCode ierr; 565 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 566 567 PetscFunctionBegin; 568 ierr = (*lu->MatAssemblyEnd)(A,mode);CHKERRQ(ierr); 569 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 570 A->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 571 PetscFunctionReturn(0); 572 } 573 574 #undef __FUNCT__ 575 #define __FUNCT__ "MatFactorInfo_SuperLU_DIST" 576 PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat A,PetscViewer viewer) 577 { 578 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->spptr; 579 superlu_options_t options; 580 PetscErrorCode ierr; 581 582 PetscFunctionBegin; 583 /* check if matrix is superlu_dist type */ 584 if (A->ops->solve != MatSolve_SuperLU_DIST) PetscFunctionReturn(0); 585 586 options = lu->options; 587 ierr = PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");CHKERRQ(ierr); 588 ierr = PetscViewerASCIIPrintf(viewer," Process grid nprow %D x npcol %D \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 589 ierr = PetscViewerASCIIPrintf(viewer," Equilibrate matrix %s \n",PetscTruths[options.Equil != NO]);CHKERRQ(ierr); 590 ierr = PetscViewerASCIIPrintf(viewer," Matrix input mode %d \n",lu->MatInputMode);CHKERRQ(ierr); 591 ierr = PetscViewerASCIIPrintf(viewer," Replace tiny pivots %s \n",PetscTruths[options.ReplaceTinyPivot != NO]);CHKERRQ(ierr); 592 ierr = PetscViewerASCIIPrintf(viewer," Use iterative refinement %s \n",PetscTruths[options.IterRefine == DOUBLE]);CHKERRQ(ierr); 593 ierr = PetscViewerASCIIPrintf(viewer," Processors in row %d col partition %d \n",lu->nprow,lu->npcol);CHKERRQ(ierr); 594 ierr = PetscViewerASCIIPrintf(viewer," Row permutation %s \n",(options.RowPerm == NOROWPERM) ? "NATURAL": "LargeDiag");CHKERRQ(ierr); 595 if (options.ColPerm == NATURAL) { 596 ierr = PetscViewerASCIIPrintf(viewer," Column permutation NATURAL\n");CHKERRQ(ierr); 597 } else if (options.ColPerm == MMD_AT_PLUS_A) { 598 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_AT_PLUS_A\n");CHKERRQ(ierr); 599 } else if (options.ColPerm == MMD_ATA) { 600 ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_ATA\n");CHKERRQ(ierr); 601 } else { 602 SETERRQ(PETSC_ERR_ARG_WRONG,"Unknown column permutation"); 603 } 604 605 if (lu->FactPattern == SamePattern){ 606 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern\n");CHKERRQ(ierr); 607 } else { 608 ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); 609 } 610 PetscFunctionReturn(0); 611 } 612 613 #undef __FUNCT__ 614 #define __FUNCT__ "MatView_SuperLU_DIST" 615 PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer) 616 { 617 PetscErrorCode ierr; 618 PetscTruth iascii; 619 PetscViewerFormat format; 620 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)(A->spptr); 621 622 PetscFunctionBegin; 623 ierr = (*lu->MatView)(A,viewer);CHKERRQ(ierr); 624 625 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr); 626 if (iascii) { 627 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 628 if (format == PETSC_VIEWER_ASCII_INFO) { 629 ierr = MatFactorInfo_SuperLU_DIST(A,viewer);CHKERRQ(ierr); 630 } 631 } 632 PetscFunctionReturn(0); 633 } 634 635 636 EXTERN_C_BEGIN 637 #undef __FUNCT__ 638 #define __FUNCT__ "MatConvert_AIJ_SuperLU_DIST" 639 PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_AIJ_SuperLU_DIST(Mat A,MatType type,MatReuse reuse,Mat *newmat) 640 { 641 /* This routine is only called to convert to MATSUPERLU_DIST */ 642 /* from MATSEQAIJ if A has a single process communicator */ 643 /* or MATMPIAIJ otherwise, so we will ignore 'MatType type'. */ 644 PetscErrorCode ierr; 645 PetscMPIInt size; 646 MPI_Comm comm; 647 Mat B=*newmat; 648 Mat_SuperLU_DIST *lu; 649 650 PetscFunctionBegin; 651 ierr = PetscNewLog(B,Mat_SuperLU_DIST,&lu);CHKERRQ(ierr); 652 if (reuse == MAT_INITIAL_MATRIX) { 653 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 654 lu->MatDuplicate = B->ops->duplicate; 655 lu->MatView = B->ops->view; 656 lu->MatAssemblyEnd = B->ops->assemblyend; 657 lu->MatLUFactorSymbolic = B->ops->lufactorsymbolic; 658 lu->MatDestroy = B->ops->destroy; 659 } else { 660 lu->MatDuplicate = A->ops->duplicate; 661 lu->MatView = A->ops->view; 662 lu->MatAssemblyEnd = A->ops->assemblyend; 663 lu->MatLUFactorSymbolic = A->ops->lufactorsymbolic; 664 lu->MatDestroy = A->ops->destroy; 665 } 666 lu->CleanUpSuperLU_Dist = PETSC_FALSE; 667 668 B->spptr = (void*)lu; 669 B->ops->duplicate = MatDuplicate_SuperLU_DIST; 670 B->ops->view = MatView_SuperLU_DIST; 671 B->ops->assemblyend = MatAssemblyEnd_SuperLU_DIST; 672 B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; 673 B->ops->destroy = MatDestroy_SuperLU_DIST; 674 675 ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr); 676 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);CHKERRQ(ierr); 677 if (size == 1) { 678 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_superlu_dist_C", 679 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 680 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_seqaij_C", 681 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 682 } else { 683 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_mpiaij_superlu_dist_C", 684 "MatConvert_AIJ_SuperLU_DIST",MatConvert_AIJ_SuperLU_DIST);CHKERRQ(ierr); 685 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_superlu_dist_mpiaij_C", 686 "MatConvert_SuperLU_DIST_AIJ",MatConvert_SuperLU_DIST_AIJ);CHKERRQ(ierr); 687 } 688 ierr = PetscInfo(A,"Using SuperLU_DIST for SeqAIJ LU factorization and solves.\n");CHKERRQ(ierr); 689 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSUPERLU_DIST);CHKERRQ(ierr); 690 *newmat = B; 691 PetscFunctionReturn(0); 692 } 693 EXTERN_C_END 694 695 #undef __FUNCT__ 696 #define __FUNCT__ "MatDuplicate_SuperLU_DIST" 697 PetscErrorCode MatDuplicate_SuperLU_DIST(Mat A, MatDuplicateOption op, Mat *M) { 698 PetscErrorCode ierr; 699 Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST *)A->spptr; 700 701 PetscFunctionBegin; 702 ierr = (*lu->MatDuplicate)(A,op,M);CHKERRQ(ierr); 703 ierr = PetscMemcpy((*M)->spptr,lu,sizeof(Mat_SuperLU_DIST));CHKERRQ(ierr); 704 PetscFunctionReturn(0); 705 } 706 707 /*MC 708 MATSUPERLU_DIST - MATSUPERLU_DIST = "superlu_dist" - A matrix type providing direct solvers (LU) for parallel matrices 709 via the external package SuperLU_DIST. 710 711 If SuperLU_DIST is installed (see the manual for 712 instructions on how to declare the existence of external packages), 713 a matrix type can be constructed which invokes SuperLU_DIST solvers. 714 After calling MatCreate(...,A), simply call MatSetType(A,MATSUPERLU_DIST) then 715 optionally call MatSeqAIJSetPreallocation() or MatMPIAIJSetPreallocation() DO NOT 716 call MatCreateSeqAIJ/MPIAIJ() directly or the preallocation information will be LOST! 717 718 This matrix inherits from MATSEQAIJ when constructed with a single process communicator, 719 and from MATMPIAIJ otherwise. As a result, for single process communicators, 720 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 721 for communicators controlling multiple processes. It is recommended that you call both of 722 the above preallocation routines for simplicity. One can also call MatConvert() for an inplace 723 conversion to or from the MATSEQAIJ or MATMPIAIJ type (depending on the communicator size) 724 without data copy; but this MUST be called AFTER the matrix values are set. 725 726 727 728 Options Database Keys: 729 + -mat_type superlu_dist - sets the matrix type to "superlu_dist" during a call to MatSetFromOptions() 730 . -mat_superlu_dist_r <n> - number of rows in processor partition 731 . -mat_superlu_dist_c <n> - number of columns in processor partition 732 . -mat_superlu_dist_matinput <0,1> - matrix input mode; 0=global, 1=distributed 733 . -mat_superlu_dist_equil - equilibrate the matrix 734 . -mat_superlu_dist_rowperm <LargeDiag,NATURAL> - row permutation 735 . -mat_superlu_dist_colperm <MMD_AT_PLUS_A,MMD_ATA,NATURAL> - column permutation 736 . -mat_superlu_dist_replacetinypivot - replace tiny pivots 737 . -mat_superlu_dist_fact <SamePattern> (choose one of) SamePattern SamePattern_SameRowPerm 738 . -mat_superlu_dist_iterrefine - use iterative refinement 739 - -mat_superlu_dist_statprint - print factorization information 740 741 Level: beginner 742 743 .seealso: PCLU 744 M*/ 745 746 EXTERN_C_BEGIN 747 #undef __FUNCT__ 748 #define __FUNCT__ "MatCreate_SuperLU_DIST" 749 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SuperLU_DIST(Mat A) 750 { 751 PetscErrorCode ierr; 752 PetscMPIInt size; 753 754 PetscFunctionBegin; 755 ierr = MPI_Comm_size(A->comm,&size);CHKERRQ(ierr); 756 if (size == 1) { 757 ierr = MatSetType(A,MATSEQAIJ);CHKERRQ(ierr); 758 } else { 759 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 760 /* A_diag = 0x0 ??? -- do we need it? 761 Mat A_diag = ((Mat_MPIAIJ *)A->data)->A; 762 ierr = MatConvert_AIJ_SuperLU_DIST(A_diag,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A_diag);CHKERRQ(ierr); 763 */ 764 } 765 ierr = MatConvert_AIJ_SuperLU_DIST(A,MATSUPERLU_DIST,MAT_REUSE_MATRIX,&A);CHKERRQ(ierr); 766 PetscFunctionReturn(0); 767 } 768 EXTERN_C_END 769 770