/* Provides an interface to the SuperLU_DIST 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 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_dist_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; PetscErrorCode MatSuperluDistGetDiagU_SuperLU_DIST(Mat F,PetscScalar *diagU) { Mat_SuperLU_DIST *lu= (Mat_SuperLU_DIST*)F->data; PetscFunctionBegin; #if defined(PETSC_USE_COMPLEX) PetscStackCall("SuperLU_DIST:pzGetDiagU",pzGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,(doublecomplex*)diagU)); #else PetscStackCall("SuperLU_DIST:pdGetDiagU",pdGetDiagU(F->rmap->N,&lu->LUstruct,&lu->grid,diagU)); #endif PetscFunctionReturn(0); } PetscErrorCode MatSuperluDistGetDiagU(Mat F,PetscScalar *diagU) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(F,MAT_CLASSID,1); ierr = PetscTryMethod(F,"MatSuperluDistGetDiagU_C",(Mat,PetscScalar*),(F,diagU));CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode MatDestroy_SuperLU_DIST(Mat A) { PetscErrorCode ierr; Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; PetscFunctionBegin; if (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->data);CHKERRQ(ierr); /* clear composed functions */ ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverType_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatSuperluDistGetDiagU_C",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } static PetscErrorCode MatSolve_SuperLU_DIST(Mat A,Vec b_mpi,Vec x) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; 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=NULL; 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; if (lu->options.Fact != FACTORED) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"SuperLU_DIST options.Fact mush equal FACTORED"); 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); } 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); } static PetscErrorCode MatMatSolve_SuperLU_DIST(Mat A,Mat B_mpi,Mat X) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)A->data; 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); } /* input: F: numeric Cholesky factor output: nneg: total number of negative pivots nzero: total number of zero pivots npos: (global dimension of F) - nneg - nzero */ static PetscErrorCode MatGetInertia_SuperLU_DIST(Mat F,PetscInt *nneg,PetscInt *nzero,PetscInt *npos) { PetscErrorCode ierr; Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data; PetscScalar *diagU=NULL; PetscInt M,i,neg=0,zero=0,pos=0; PetscReal r; PetscFunctionBegin; if (!F->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Matrix factor F is not assembled"); if (lu->options.RowPerm != NOROWPERM) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Must set NOROWPERM"); ierr = MatGetSize(F,&M,NULL);CHKERRQ(ierr); ierr = PetscMalloc1(M,&diagU);CHKERRQ(ierr); ierr = MatSuperluDistGetDiagU(F,diagU);CHKERRQ(ierr); for (i=0; iPETSC_MACHINE_EPSILON) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"diagU[%d]=%g + i %g is non-real",i,PetscRealPart(diagU[i]),r*10.0); r = PetscRealPart(diagU[i]); #else r = diagU[i]; #endif if (r > 0) { pos++; } else if (r < 0) { neg++; } else zero++; } ierr = PetscFree(diagU);CHKERRQ(ierr); if (nneg) *nneg = neg; if (nzero) *nzero = zero; if (npos) *npos = pos; PetscFunctionReturn(0); } static 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->data; 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=NULL; 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; #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 = MatCreateSubMatrices(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. */ if (lu->FactPattern == SamePattern_SameRowPerm) { lu->options.Fact = SamePattern_SameRowPerm; /* matrix has similar numerical values */ } else if (lu->FactPattern == SamePattern) { PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); /* Deallocate L and U matrices. */ lu->options.Fact = SamePattern; } else if (lu->FactPattern == DOFACT) { PetscStackCall("SuperLU_DIST:Destroy_CompRowLoc_Matrix_dist",Destroy_CompRowLoc_Matrix_dist(&lu->A_sup)); PetscStackCall("SuperLU_DIST:Destroy_LU",Destroy_LU(N, &lu->grid, &lu->LUstruct)); lu->options.Fact = DOFACT; #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 { SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"options.Fact must be one of SamePattern SamePattern_SameRowPerm DOFACT"); } } 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 (lu->options.Fact == DOFACT) { #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)); #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)); #endif } if (sinfo > 0) { if (A->erroriffailure) { SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot in row %D",sinfo); } else { if (sinfo <= lu->A_sup.ncol) { F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; ierr = PetscInfo1(F,"U(i,i) is exactly zero, i= %D\n",sinfo);CHKERRQ(ierr); } else if (sinfo > lu->A_sup.ncol) { /* number of bytes allocated when memory allocation failure occurred, plus A->ncol. */ F->factorerrortype = MAT_FACTOR_OUTMEMORY; ierr = PetscInfo1(F,"Number of bytes allocated when memory allocation fails %D\n",sinfo);CHKERRQ(ierr); } } } else if (sinfo < 0) { SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB, "info = %D, argument in p*gssvx() had an illegal value", sinfo); } 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. */ } PetscStackCall("SuperLU_DIST:PStatFree",PStatFree(&stat)); 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 */ static PetscErrorCode MatLUFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_SuperLU_DIST *lu = (Mat_SuperLU_DIST*)F->data; 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; F->ops->getinertia = NULL; if (A->symmetric || A->hermitian) { F->ops->getinertia = MatGetInertia_SuperLU_DIST; } lu->CleanUpSuperLU_Dist = PETSC_TRUE; PetscFunctionReturn(0); } static PetscErrorCode MatCholeskyFactorSymbolic_SuperLU_DIST(Mat F,Mat A,IS r,const MatFactorInfo *info) { PetscErrorCode ierr; PetscFunctionBegin; if (!A->symmetric) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Input matrix must be symmetric\n"); ierr = MatLUFactorSymbolic_SuperLU_DIST(F,A,r,r,info);CHKERRQ(ierr); F->ops->choleskyfactornumeric = MatLUFactorNumeric_SuperLU_DIST; PetscFunctionReturn(0); } static PetscErrorCode MatFactorGetSolverType_aij_superlu_dist(Mat A,MatSolverType *type) { PetscFunctionBegin; *type = MATSOLVERSUPERLU_DIST; PetscFunctionReturn(0); } static PetscErrorCode MatView_Info_SuperLU_DIST(Mat A,PetscViewer viewer) { Mat_SuperLU_DIST *lu=(Mat_SuperLU_DIST*)A->data; superlu_dist_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); switch (options.RowPerm) { case NOROWPERM: ierr = PetscViewerASCIIPrintf(viewer," Row permutation NOROWPERM\n");CHKERRQ(ierr); break; case LargeDiag_MC64: ierr = PetscViewerASCIIPrintf(viewer," Row permutation LargeDiag_MC64\n");CHKERRQ(ierr); break; case LargeDiag_AWPM: ierr = PetscViewerASCIIPrintf(viewer," Row permutation LargeDiag_AWPM\n");CHKERRQ(ierr); break; case MY_PERMR: ierr = PetscViewerASCIIPrintf(viewer," Row permutation MY_PERMR\n");CHKERRQ(ierr); break; default: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown column permutation"); } 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 if (lu->FactPattern == SamePattern_SameRowPerm) { ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization SamePattern_SameRowPerm\n");CHKERRQ(ierr); } else if (lu->FactPattern == DOFACT) { ierr = PetscViewerASCIIPrintf(viewer," Repeated factorization DOFACT\n");CHKERRQ(ierr); } else { SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown factorization pattern"); } PetscFunctionReturn(0); } static 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 = MatView_Info_SuperLU_DIST(A,viewer);CHKERRQ(ierr); } } PetscFunctionReturn(0); } static 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_dist_options_t options; PetscBool flg; const char *colperm[] = {"NATURAL","MMD_AT_PLUS_A","MMD_ATA","METIS_AT_PLUS_A","PARMETIS"}; const char *rowperm[] = {"NOROWPERM","LargeDiag_MC64","LargeDiag_AWPM","MY_PERMR"}; const char *factPattern[] = {"SamePattern","SamePattern_SameRowPerm","DOFACT"}; 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 = PetscStrallocpy("superlu_dist",&((PetscObject)B)->type_name);CHKERRQ(ierr); ierr = MatSetUp(B);CHKERRQ(ierr); B->ops->getinfo = MatGetInfo_External; B->ops->view = MatView_SuperLU_DIST; B->ops->destroy = MatDestroy_SuperLU_DIST; if (ftype == MAT_FACTOR_LU) { B->factortype = MAT_FACTOR_LU; B->ops->lufactorsymbolic = MatLUFactorSymbolic_SuperLU_DIST; } else { B->factortype = MAT_FACTOR_CHOLESKY; B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SuperLU_DIST; } /* set solvertype */ ierr = PetscFree(B->solvertype);CHKERRQ(ierr); ierr = PetscStrallocpy(MATSOLVERSUPERLU_DIST,&B->solvertype);CHKERRQ(ierr); ierr = PetscNewLog(B,&lu);CHKERRQ(ierr); B->data = lu; /* Set the default input options: options.Fact = DOFACT; options.Equil = YES; options.ParSymbFact = NO; options.ColPerm = METIS_AT_PLUS_A; options.RowPerm = LargeDiag_MC64; 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->nprow = (int_t) (0.5 + PetscSqrtReal((PetscReal)size)); if (!lu->nprow) lu->nprow = 1; while (lu->nprow > 0) { lu->npcol = (int_t) (size/lu->nprow); if (size == lu->nprow * lu->npcol) break; lu->nprow--; } 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,4,rowperm[1],&indx,&flg);CHKERRQ(ierr); if (flg) { switch (indx) { case 0: options.RowPerm = NOROWPERM; break; case 1: options.RowPerm = LargeDiag_MC64; break; case 2: options.RowPerm = LargeDiag_AWPM; break; case 3: options.RowPerm = MY_PERMR; break; default: SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown row permutation"); } } 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"); } } options.ReplaceTinyPivot = NO; 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 = YES; 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; ierr = PetscOptionsEList("-mat_superlu_dist_fact","Sparsity pattern for repeated matrix factorization","None",factPattern,3,factPattern[0],&indx,&flg);CHKERRQ(ierr); if (flg) { switch (indx) { case 0: lu->FactPattern = SamePattern; break; case 1: lu->FactPattern = SamePattern_SameRowPerm; break; case 2: lu->FactPattern = DOFACT; 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); ierr = PetscOptionsEnd();CHKERRQ(ierr); lu->options = options; lu->options.Fact = DOFACT; lu->matsolve_iscalled = PETSC_FALSE; lu->matmatsolve_iscalled = PETSC_FALSE; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverType_C",MatFactorGetSolverType_aij_superlu_dist);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatSuperluDistGetDiagU_C",MatSuperluDistGetDiagU_SuperLU_DIST);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } PETSC_EXTERN PetscErrorCode MatSolverTypeRegister_SuperLU_DIST(void) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ, MAT_FACTOR_LU,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATMPIAIJ, MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);CHKERRQ(ierr); ierr = MatSolverTypeRegister(MATSOLVERSUPERLU_DIST,MATSEQAIJ, MAT_FACTOR_CHOLESKY,MatGetFactor_aij_superlu_dist);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_type superlu_dist to use 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 DOFACT . -mat_superlu_dist_iterrefine - use iterative refinement - -mat_superlu_dist_statprint - print factorization information Level: beginner .seealso: PCLU .seealso: PCFactorSetMatSolverType(), MatSolverType M*/