/* Provides an interface to the SuperLU_DIST_2.2 sparse solver */ #include <../src/mat/impls/aij/seq/aij.h> #include <../src/mat/impls/aij/mpi/mpiaij.h> #if defined(PETSC_HAVE_STDLIB_H) /* This is to get around weird problem with SuperLU on cray */ #include #endif #if defined(PETSC_USE_64BIT_INDICES) /* ugly SuperLU_Dist variable telling it to use long long int */ #define _LONGINT #endif EXTERN_C_BEGIN #if defined(PETSC_USE_COMPLEX) #include #else #include #endif EXTERN_C_END /* GLOBAL - The sparse matrix and right hand side are all stored initially on process 0. Should be called centralized DISTRIBUTED - The sparse matrix and right hand size are initially stored across the entire MPI communicator. */ typedef enum {GLOBAL,DISTRIBUTED} SuperLU_MatInputMode; const char *SuperLU_MatInputModes[] = {"GLOBAL","DISTRIBUTED","SuperLU_MatInputMode","PETSC_",0}; typedef struct { int_t nprow,npcol,*row,*col; gridinfo_t grid; superlu_options_t options; SuperMatrix A_sup; ScalePermstruct_t ScalePermstruct; LUstruct_t LUstruct; int StatPrint; SuperLU_MatInputMode MatInputMode; SOLVEstruct_t SOLVEstruct; fact_t FactPattern; MPI_Comm comm_superlu; #if defined(PETSC_USE_COMPLEX) doublecomplex *val; #else double *val; #endif PetscBool matsolve_iscalled,matmatsolve_iscalled; PetscBool CleanUpSuperLU_Dist; /* Flag to clean up (non-global) SuperLU objects during Destroy */ } Mat_SuperLU_DIST; extern PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat,PetscViewer); extern PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat,Mat,const MatFactorInfo*); extern PetscErrorCode MatDestroy_SuperLU_DIST(Mat); extern PetscErrorCode MatView_SuperLU_DIST(Mat,PetscViewer); extern PetscErrorCode MatSolve_SuperLU_DIST(Mat,Vec,Vec); extern PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat,Mat,IS,IS,const MatFactorInfo*); extern PetscErrorCode MatDestroy_MPIAIJ(Mat); #undef __FUNCT__ #define __FUNCT__ "MatGetDiagonal_SuperLU_DIST" PetscErrorCode MatGetDiagonal_SuperLU_DIST(Mat A,Vec v) { PetscFunctionBegin; SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Mat type: SuperLU_DIST factor"); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDestroy_SuperLU_DIST" PetscErrorCode MatDestroy_SuperLU_DIST(Mat A) { PetscErrorCode ierr; Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; PetscBool flg; PetscFunctionBegin; if (lu && lu->CleanUpSuperLU_Dist) { /* Deallocate SuperLU_DIST storage */ if (lu->MatInputMode == GLOBAL) { PetscStackCall("SuperLU_DIST:Destroy_CompCol_Matrix_dist",Destroy_CompCol_Matrix_dist(&lu->A_sup)); } else { PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup)); if (lu->options.SolveInitialized) { #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); #else PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); #endif } } PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(A->cmap->N, &lu->grid, &lu->LUstruct)); PetscStackCall("SuperLU_DIST:ScalePermstructFree",ScalePermstructFree(&lu->ScalePermstruct)); PetscStackCall("SuperLU_DIST:LUstructFree",LUstructFree(&lu->LUstruct)); /* Release the SuperLU_DIST process grid. */ PetscStackCall("SuperLU_DIST:superlu_gridexit",superlu_gridexit(&lu->grid)); ierr = MPI_Comm_free(&(lu->comm_superlu));CHKERRQ(ierr); } ierr = PetscFree(A->spptr);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);CHKERRQ(ierr); if (flg) { ierr = MatDestroy_SeqAIJ(A);CHKERRQ(ierr); } else { ierr = MatDestroy_MPIAIJ(A);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolve_SuperLU_DIST" PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; PetscErrorCode ierr; PetscMPIInt size; PetscInt m=A->rmap->n,M=A->rmap->N,N=A->cmap->N; SuperLUStat_t stat; double berr[1]; PetscScalar *bptr; PetscInt nrhs=1; Vec x_seq; IS iden; VecScatter scat; int info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */ static PetscBool cite = PETSC_FALSE; PetscFunctionBegin; ierr = PetscCitationsRegister("@article{lidemmel03,\n author = {Xiaoye S. Li and James W. Demmel},\n title = {{SuperLU_DIST}: A Scalable Distributed-Memory Sparse Direct\n Solver for Unsymmetric Linear Systems},\n journal = {ACM Trans. Mathematical Software},\n volume = {29},\n number = {2},\n pages = {110-140},\n year = 2003\n}\n",&cite);CHKERRQ(ierr); ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); if (size > 1 && lu->MatInputMode == GLOBAL) { /* global mat input, convert b to x_seq */ ierr = VecCreateSeq(PETSC_COMM_SELF,N,&x_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,N,0,1,&iden);CHKERRQ(ierr); ierr = VecScatterCreate(b_mpi,iden,x_seq,iden,&scat);CHKERRQ(ierr); ierr = ISDestroy(&iden);CHKERRQ(ierr); ierr = VecScatterBegin(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterEnd(scat,b_mpi,x_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecGetArray(x_seq,&bptr);CHKERRQ(ierr); } else { /* size==1 || distributed mat input */ if (lu->options.SolveInitialized && !lu->matsolve_iscalled) { /* see comments in MatMatSolve() */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); #else PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); #endif lu->options.SolveInitialized = NO; } ierr = VecCopy(b_mpi,x);CHKERRQ(ierr); ierr = VecGetArray(x,&bptr);CHKERRQ(ierr); } if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ if (lu->MatInputMode == GLOBAL) { #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,M,nrhs,&lu->grid,&lu->LUstruct,berr,&stat,&info)); #else PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr,M,nrhs,&lu->grid,&lu->LUstruct,berr,&stat,&info)); #endif } else { /* distributed mat input */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); #else PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); #endif } if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info); if (lu->options.PrintStat) PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); if (size > 1 && lu->MatInputMode == GLOBAL) { /* convert seq x to mpi x */ ierr = VecRestoreArray(x_seq,&bptr);CHKERRQ(ierr); ierr = VecScatterBegin(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); ierr = VecScatterEnd(scat,x_seq,x,INSERT_VALUES,SCATTER_REVERSE);CHKERRQ(ierr); ierr = VecScatterDestroy(&scat);CHKERRQ(ierr); ierr = VecDestroy(&x_seq);CHKERRQ(ierr); } else { ierr = VecRestoreArray(x,&bptr);CHKERRQ(ierr); lu->matsolve_iscalled = PETSC_TRUE; lu->matmatsolve_iscalled = PETSC_FALSE; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMatSolve_SuperLU_DIST" PetscErrorCode MatMatSolve_SuperLU_DIST(Mat A,Mat B_mpi,Mat X) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->spptr; PetscErrorCode ierr; PetscMPIInt size; PetscInt M=A->rmap->N,m=A->rmap->n,nrhs; SuperLUStat_t stat; double berr[1]; PetscScalar *bptr; int info; /* SuperLU_Dist info code is ALWAYS an int, even with long long indices */ PetscBool flg; PetscFunctionBegin; if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); ierr = PetscObjectTypeCompareAny((PetscObject)B_mpi,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); if (size > 1 && lu->MatInputMode == GLOBAL) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatInputMode=GLOBAL for nproc %d>1 is not supported",size); /* size==1 or distributed mat input */ if (lu->options.SolveInitialized && !lu->matmatsolve_iscalled) { /* communication pattern of SOLVEstruct is unlikely created for matmatsolve, thus destroy it and create a new SOLVEstruct. Otherwise it may result in memory corruption or incorrect solution See src/mat/examples/tests/ex125.c */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zSolveFinalize",zSolveFinalize(&lu->options, &lu->SOLVEstruct)); #else PetscStackCall("SuperLU_DIST:dSolveFinalize",dSolveFinalize(&lu->options, &lu->SOLVEstruct)); #endif lu->options.SolveInitialized = NO; } ierr = MatCopy(B_mpi,X,SAME_NONZERO_PATTERN);CHKERRQ(ierr); ierr = MatGetSize(B_mpi,NULL,&nrhs);CHKERRQ(ierr); PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ ierr = MatDenseGetArray(X,&bptr);CHKERRQ(ierr); if (lu->MatInputMode == GLOBAL) { /* size == 1 */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,(doublecomplex*)bptr, M, nrhs,&lu->grid, &lu->LUstruct, berr, &stat, &info)); #else PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct,bptr, M, nrhs, &lu->grid, &lu->LUstruct, berr, &stat, &info)); #endif } else { /* distributed mat input */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,(doublecomplex*)bptr,m,nrhs,&lu->grid, &lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); #else PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options,&lu->A_sup,&lu->ScalePermstruct,bptr,m,nrhs,&lu->grid,&lu->LUstruct,&lu->SOLVEstruct,berr,&stat,&info)); #endif } if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",info); ierr = MatDenseRestoreArray(X,&bptr);CHKERRQ(ierr); if (lu->options.PrintStat) PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); lu->matsolve_iscalled = PETSC_FALSE; lu->matmatsolve_iscalled = PETSC_TRUE; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatLUFactorNumeric_SuperLU_DIST" PetscErrorCode MatLUFactorNumeric_SuperLU_DIST(Mat F,Mat A,const MatFactorInfo *info) { Mat *tseq,A_seq = NULL; Mat_SeqAIJ *aa,*bb; Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)(F)->spptr; PetscErrorCode ierr; PetscInt M=A->rmap->N,N=A->cmap->N,i,*ai,*aj,*bi,*bj,nz,rstart,*garray, m=A->rmap->n, colA_start,j,jcol,jB,countA,countB,*bjj,*ajj; int sinfo; /* SuperLU_Dist info flag is always an int even with long long indices */ PetscMPIInt size; SuperLUStat_t stat; double *berr=0; IS isrow; Mat F_diag=NULL; #if defined(PETSC_USE_COMPLEX) doublecomplex *av, *bv; #else double *av, *bv; #endif PetscFunctionBegin; ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); if (lu->MatInputMode == GLOBAL) { /* global mat input */ if (size > 1) { /* convert mpi A to seq mat A */ ierr = ISCreateStride(PETSC_COMM_SELF,M,0,1,&isrow);CHKERRQ(ierr); ierr = MatGetSubMatrices(A,1,&isrow,&isrow,MAT_INITIAL_MATRIX,&tseq);CHKERRQ(ierr); ierr = ISDestroy(&isrow);CHKERRQ(ierr); A_seq = *tseq; ierr = PetscFree(tseq);CHKERRQ(ierr); aa = (Mat_SeqAIJ*)A_seq->data; } else { PetscBool flg; ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&flg);CHKERRQ(ierr); if (flg) { Mat_MPIAIJ *At = (Mat_MPIAIJ*)A->data; A = At->A; } aa = (Mat_SeqAIJ*)A->data; } /* Convert Petsc NR matrix to SuperLU_DIST NC. Note: memories of lu->val, col and row are allocated by CompRow_to_CompCol_dist()! */ if (lu->options.Fact != DOFACT) {/* successive numeric factorization, sparsity pattern is reused. */ PetscStackCall("SuperLU_DIST:Destroy_CompCol_Matrix_dist",Destroy_CompCol_Matrix_dist(&lu->A_sup)); if (lu->FactPattern == SamePattern_SameRowPerm) { lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ } else { /* lu->FactPattern == SamePattern */ PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); lu->options.Fact = SamePattern; } } #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zCompRow_to_CompCol_dist",zCompRow_to_CompCol_dist(M,N,aa->nz,(doublecomplex*)aa->a,(int_t*)aa->j,(int_t*)aa->i,&lu->val,&lu->col, &lu->row)); #else PetscStackCall("SuperLU_DIST:dCompRow_to_CompCol_dist",dCompRow_to_CompCol_dist(M,N,aa->nz,aa->a,(int_t*)aa->j,(int_t*)aa->i,&lu->val, &lu->col, &lu->row)); #endif /* Create compressed column matrix A_sup. */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zCreate_CompCol_Matrix_dist",zCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_Z, SLU_GE)); #else PetscStackCall("SuperLU_DIST:dCreate_CompCol_Matrix_dist",dCreate_CompCol_Matrix_dist(&lu->A_sup, M, N, aa->nz, lu->val, lu->col, lu->row, SLU_NC, SLU_D, SLU_GE)); #endif } else { /* distributed mat input */ Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; aa=(Mat_SeqAIJ*)(mat->A)->data; bb=(Mat_SeqAIJ*)(mat->B)->data; ai=aa->i; aj=aa->j; bi=bb->i; bj=bb->j; #if defined(PETSC_USE_COMPLEX) av=(doublecomplex*)aa->a; bv=(doublecomplex*)bb->a; #else av=aa->a; bv=bb->a; #endif rstart = A->rmap->rstart; nz = aa->nz + bb->nz; garray = mat->garray; if (lu->options.Fact == DOFACT) { /* first numeric factorization */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zallocateA_dist",zallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); #else PetscStackCall("SuperLU_DIST:dallocateA_dist",dallocateA_dist(m, nz, &lu->val, &lu->col, &lu->row)); #endif } else { /* successive numeric factorization, sparsity pattern and perm_c are reused. */ /* Destroy_CompRowLoc_Matrix_dist(&lu->A_sup); */ /* this leads to crash! However, see SuperLU_DIST_2.5/EXAMPLE/pzdrive2.c */ if (lu->FactPattern == SamePattern_SameRowPerm) { lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ } else { PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); /* Deallocate storage associated with the L and U matrices. */ lu->options.Fact = SamePattern; } } nz = 0; for (i=0; irow[i] = nz; countA = ai[i+1] - ai[i]; countB = bi[i+1] - bi[i]; if (aj) { ajj = aj + ai[i]; /* ptr to the beginning of this row */ } else { ajj = NULL; } bjj = bj + bi[i]; /* B part, smaller col index */ if (aj) { colA_start = rstart + ajj[0]; /* the smallest global col index of A */ } else { /* superlu_dist does not require matrix has diagonal entries, thus aj=NULL would work */ colA_start = rstart; } jB = 0; for (j=0; j colA_start) { jB = j; break; } lu->col[nz] = jcol; lu->val[nz++] = *bv++; if (j==countB-1) jB = countB; } /* A part */ for (j=0; jcol[nz] = rstart + ajj[j]; lu->val[nz++] = *av++; } /* B part, larger col index */ for (j=jB; jcol[nz] = garray[bjj[j]]; lu->val[nz++] = *bv++; } } lu->row[m] = nz; #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:zCreate_CompRowLoc_Matrix_dist",zCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart,lu->val, lu->col, lu->row, SLU_NR_loc, SLU_Z, SLU_GE)); #else PetscStackCall("SuperLU_DIST:dCreate_CompRowLoc_Matrix_dist",dCreate_CompRowLoc_Matrix_dist(&lu->A_sup, M, N, nz, m, rstart,lu->val, lu->col, lu->row, SLU_NR_loc, SLU_D, SLU_GE)); #endif } /* Factor the matrix. */ PetscStackCall("SuperLU_DIST:PStatInit",PStatInit(&stat)); /* Initialize the statistics variables. */ if (lu->MatInputMode == GLOBAL) { /* global mat input */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx_ABglobal",pzgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0,&lu->grid, &lu->LUstruct, berr, &stat, &sinfo)); #else PetscStackCall("SuperLU_DIST:pdgssvx_ABglobal",pdgssvx_ABglobal(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, M, 0,&lu->grid, &lu->LUstruct, berr, &stat, &sinfo)); #endif } else { /* distributed mat input */ #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzgssvx",pzgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, m, 0, &lu->grid,&lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo)); if (sinfo) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pzgssvx fails, info: %d\n",sinfo); #else PetscStackCall("SuperLU_DIST:pdgssvx",pdgssvx(&lu->options, &lu->A_sup, &lu->ScalePermstruct, 0, m, 0, &lu->grid,&lu->LUstruct, &lu->SOLVEstruct, berr, &stat, &sinfo)); if (sinfo) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"pdgssvx fails, info: %d\n",sinfo); #endif } if (lu->MatInputMode == GLOBAL && size > 1) { ierr = MatDestroy(&A_seq);CHKERRQ(ierr); } if (lu->options.PrintStat) { PStatPrint(&lu->options, &stat, &lu->grid); /* Print the statistics. */ } PStatFree(&stat); if (size > 1) { F_diag = ((Mat_MPIAIJ*)(F)->data)->A; F_diag->assembled = PETSC_TRUE; } (F)->assembled = PETSC_TRUE; (F)->preallocated = PETSC_TRUE; lu->options.Fact = FACTORED; /* The factored form of A is supplied. Local option used by this func. only */ PetscFunctionReturn(0); } /* Note the Petsc r and c permutations are ignored */ #undef __FUNCT__ #define __FUNCT__ "MatLUFactorSymbolic_SuperLU_DIST" PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->spptr; PetscInt M = A->rmap->N,N=A->cmap->N; PetscFunctionBegin; /* Initialize the SuperLU process grid. */ PetscStackCall("SuperLU_DIST:superlu_gridinit",superlu_gridinit(lu->comm_superlu, lu->nprow, lu->npcol, &lu->grid)); /* Initialize ScalePermstruct and LUstruct. */ PetscStackCall("SuperLU_DIST:ScalePermstructInit",ScalePermstructInit(M, N, &lu->ScalePermstruct)); PetscStackCall("SuperLU_DIST:LUstructInit",LUstructInit(N, &lu->LUstruct)); F->ops->lufactornumeric = MatLUFactorNumeric_SuperLU_DIST; F->ops->solve = MatSolve_SuperLU_DIST; F->ops->matsolve = MatMatSolve_SuperLU_DIST; lu->CleanUpSuperLU_Dist = PETSC_TRUE; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFactorGetSolverPackage_aij_superlu_dist" PetscErrorCode MatFactorGetSolverPackage_aij_superlu_dist(Mat A,const MatSolverPackage *type) { PetscFunctionBegin; *type = MATSOLVERSUPERLU_DIST; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetFactor_aij_superlu_dist" PETSC_EXTERN PetscErrorCode MatGetFactor_aij_superlu_dist(Mat A,MatFactorType ftype,Mat *F) { Mat B; Mat_SuperLU_DIST *lu; PetscErrorCode ierr; PetscInt M=A->rmap->N,N=A->cmap->N,indx; PetscMPIInt size; superlu_options_t options; PetscBool flg; const char *colperm[] = {"NATURAL","MMD_AT_PLUS_A","MMD_ATA","METIS_AT_PLUS_A","PARMETIS"}; const char *rowperm[] = {"LargeDiag","NATURAL"}; const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm"}; PetscBool set; PetscFunctionBegin; /* Create the factorization matrix */ ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,M,N);CHKERRQ(ierr); ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation(B,0,NULL); ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; B->ops->view = MatView_SuperLU_DIST; B->ops->destroy = MatDestroy_SuperLU_DIST; B->ops->getdiagonal = MatGetDiagonal_SuperLU_DIST; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_aij_superlu_dist);CHKERRQ(ierr); B->factortype = MAT_FACTOR_LU; ierr = PetscNewLog(B,&lu);CHKERRQ(ierr); B->spptr = lu; /* Set the default input options: options.Fact = DOFACT; options.Equil = YES; options.ParSymbFact = NO; options.ColPerm = METIS_AT_PLUS_A; options.RowPerm = LargeDiag; options.ReplaceTinyPivot = YES; options.IterRefine = DOUBLE; options.Trans = NOTRANS; options.SolveInitialized = NO; -hold the communication pattern used MatSolve() and MatMatSolve() options.RefineInitialized = NO; options.PrintStat = YES; */ set_default_options_dist(&options); ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(lu->comm_superlu));CHKERRQ(ierr); ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr); /* Default num of process columns and rows */ lu->npcol = (int_t) (0.5 + PetscSqrtReal((PetscReal)size)); if (!lu->npcol) lu->npcol = 1; while (lu->npcol > 0) { lu->nprow = (int_t) (size/lu->npcol); if (size == lu->nprow * lu->npcol) break; lu->npcol--; } ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"SuperLU_Dist Options","Mat");CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_superlu_dist_r","Number rows in processor partition","None",lu->nprow,(PetscInt*)&lu->nprow,NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_superlu_dist_c","Number columns in processor partition","None",lu->npcol,(PetscInt*)&lu->npcol,NULL);CHKERRQ(ierr); if (size != lu->nprow * lu->npcol) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number of processes %d must equal to nprow %d * npcol %d",size,lu->nprow,lu->npcol); lu->MatInputMode = DISTRIBUTED; ierr = PetscOptionsEnum("-mat_superlu_dist_matinput","Matrix input mode (global or distributed)","None",SuperLU_MatInputModes,(PetscEnum)lu->MatInputMode,(PetscEnum*)&lu->MatInputMode,NULL);CHKERRQ(ierr); if (lu->MatInputMode == DISTRIBUTED && size == 1) lu->MatInputMode = GLOBAL; ierr = PetscOptionsBool("-mat_superlu_dist_equil","Equilibrate matrix","None",options.Equil ? PETSC_TRUE : PETSC_FALSE,&flg,&set);CHKERRQ(ierr); if (set && !flg) options.Equil = NO; ierr = PetscOptionsEList("-mat_superlu_dist_rowperm","Row permutation","None",rowperm,2,rowperm[0],&indx,&flg);CHKERRQ(ierr); if (flg) { switch (indx) { case 0: options.RowPerm = LargeDiag; break; case 1: options.RowPerm = NOROWPERM; break; } } ierr = PetscOptionsEList("-mat_superlu_dist_colperm","Column permutation","None",colperm,5,colperm[3],&indx,&flg);CHKERRQ(ierr); if (flg) { switch (indx) { case 0: options.ColPerm = NATURAL; break; case 1: options.ColPerm = MMD_AT_PLUS_A; break; case 2: options.ColPerm = MMD_ATA; break; case 3: options.ColPerm = METIS_AT_PLUS_A; break; case 4: options.ColPerm = PARMETIS; /* only works for np>1 */ break; default: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); } } ierr = PetscOptionsBool("-mat_superlu_dist_replacetinypivot","Replace tiny pivots","None",options.ReplaceTinyPivot ? PETSC_TRUE : PETSC_FALSE,&flg,&set);CHKERRQ(ierr); if (set && !flg) options.ReplaceTinyPivot = NO; options.ParSymbFact = NO; ierr = PetscOptionsBool("-mat_superlu_dist_parsymbfact","Parallel symbolic factorization","None",PETSC_FALSE,&flg,&set);CHKERRQ(ierr); if (set && flg && size>1) { if (lu->MatInputMode == GLOBAL) { #if defined(PETSC_USE_INFO) ierr = PetscInfo(A,"Warning: '-mat_superlu_dist_parsymbfact' is ignored because MatInputMode=GLOBAL\n");CHKERRQ(ierr); #endif } else { #if defined(PETSC_HAVE_PARMETIS) options.ParSymbFact = YES; options.ColPerm = PARMETIS; /* in v2.2, PARMETIS is forced for ParSymbFact regardless of user ordering setting */ #else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"parsymbfact needs PARMETIS"); #endif } } lu->FactPattern = SamePattern_SameRowPerm; ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,2,factPattern[1],&indx,&flg);CHKERRQ(ierr); if (flg) { switch (indx) { case 0: lu->FactPattern = SamePattern; break; case 1: lu->FactPattern = SamePattern_SameRowPerm; break; } } options.IterRefine = NOREFINE; ierr = PetscOptionsBool("-mat_superlu_dist_iterrefine","Use iterative refinement","None",options.IterRefine == NOREFINE ? PETSC_FALSE : PETSC_TRUE ,&flg,&set);CHKERRQ(ierr); if (set) { if (flg) options.IterRefine = SLU_DOUBLE; else options.IterRefine = NOREFINE; } if (PetscLogPrintInfo) options.PrintStat = YES; else options.PrintStat = NO; ierr = PetscOptionsBool("-mat_superlu_dist_statprint","Print factorization information","None",(PetscBool)options.PrintStat,(PetscBool*)&options.PrintStat,NULL);CHKERRQ(ierr); PetscOptionsEnd(); lu->options = options; lu->options.Fact = DOFACT; lu->matsolve_iscalled = PETSC_FALSE; lu->matmatsolve_iscalled = PETSC_FALSE; *F = B; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolverPackageRegister_SuperLU_DIST" PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_SuperLU_DIST(void) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatSolverPackageRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFactorInfo_SuperLU_DIST" PetscErrorCode MatFactorInfo_SuperLU_DIST(Mat A,PetscViewer viewer) { Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->spptr; superlu_options_t options; PetscErrorCode ierr; PetscFunctionBegin; /* check if matrix is superlu_dist type */ if (A->ops->solve != MatSolve_SuperLU_DIST) PetscFunctionReturn(0); options = lu->options; ierr = PetscViewerASCIIPrintf(viewer,"SuperLU_DIST run parameters:\n");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Process grid nprow %D x npcol %D \n",lu->nprow,lu->npcol);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Equilibrate matrix %s \n",PetscBools[options.Equil != NO]);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Matrix input mode %d \n",lu->MatInputMode);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Replace tiny pivots %s \n",PetscBools[options.ReplaceTinyPivot != NO]);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Use iterative refinement %s \n",PetscBools[options.IterRefine == SLU_DOUBLE]);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Processors in row %d col partition %d \n",lu->nprow,lu->npcol);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," Row permutation %s \n",(options.RowPerm == NOROWPERM) ? "NATURAL" : "LargeDiag");CHKERRQ(ierr); switch (options.ColPerm) { case NATURAL: ierr = PetscViewerASCIIPrintf(viewer," Column permutation NATURAL\n");CHKERRQ(ierr); break; case MMD_AT_PLUS_A: ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_AT_PLUS_A\n");CHKERRQ(ierr); break; case MMD_ATA: ierr = PetscViewerASCIIPrintf(viewer," Column permutation MMD_ATA\n");CHKERRQ(ierr); break; case METIS_AT_PLUS_A: ierr = PetscViewerASCIIPrintf(viewer," Column permutation METIS_AT_PLUS_A\n");CHKERRQ(ierr); break; case PARMETIS: ierr = PetscViewerASCIIPrintf(viewer," Column permutation PARMETIS\n");CHKERRQ(ierr); break; default: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); } ierr = PetscViewerASCIIPrintf(viewer," Parallel symbolic factorization %s \n",PetscBools[options.ParSymbFact != NO]);CHKERRQ(ierr); if (lu->FactPattern == SamePattern) { ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern\n");CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SuperLU_DIST" PetscErrorCode MatView_SuperLU_DIST(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscBool iascii; PetscViewerFormat format; PetscFunctionBegin; ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); if (iascii) { ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format == PETSC_VIEWER_ASCII_INFO) { ierr = MatFactorInfo_SuperLU_DIST(A,viewer);CHKERRQ(ierr); } } PetscFunctionReturn(0); } /*MC MATSOLVERSUPERLU_DIST - Parallel direct solver package for LU factorization Use ./configure --download-superlu_dist --download-parmetis --download-metis --download-ptscotch to have PETSc installed with SuperLU_DIST Use -pc_type lu -pc_factor_mat_solver_package superlu_dist to us this direct solver Works with AIJ matrices Options Database Keys: + -mat_superlu_dist_r - number of rows in processor partition . -mat_superlu_dist_c - number of columns in processor partition . -mat_superlu_dist_matinput <0,1> - matrix input mode; 0=global, 1=distributed . -mat_superlu_dist_equil - equilibrate the matrix . -mat_superlu_dist_rowperm - row permutation . -mat_superlu_dist_colperm - column permutation . -mat_superlu_dist_replacetinypivot - replace tiny pivots . -mat_superlu_dist_fact - (choose one of) SamePattern SamePattern_SameRowPerm . -mat_superlu_dist_iterrefine - use iterative refinement - -mat_superlu_dist_statprint - print factorization information Level: beginner .seealso: PCLU .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage M*/