/* Provides an interface to the MUMPS sparse solver */ #include <../src/mat/impls/aij/mpi/mpiaij.h> /*I "petscmat.h" I*/ #include <../src/mat/impls/sbaij/mpi/mpisbaij.h> EXTERN_C_BEGIN #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) #include #else #include #endif #else #if defined(PETSC_USE_REAL_SINGLE) #include #else #include #endif #endif EXTERN_C_END #define JOB_INIT -1 #define JOB_FACTSYMBOLIC 1 #define JOB_FACTNUMERIC 2 #define JOB_SOLVE 3 #define JOB_END -2 /* calls to MUMPS */ #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) #define PetscMUMPS_c cmumps_c #else #define PetscMUMPS_c zmumps_c #endif #else #if defined(PETSC_USE_REAL_SINGLE) #define PetscMUMPS_c smumps_c #else #define PetscMUMPS_c dmumps_c #endif #endif /* macros s.t. indices match MUMPS documentation */ #define ICNTL(I) icntl[(I)-1] #define CNTL(I) cntl[(I)-1] #define INFOG(I) infog[(I)-1] #define INFO(I) info[(I)-1] #define RINFOG(I) rinfog[(I)-1] #define RINFO(I) rinfo[(I)-1] typedef struct { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) CMUMPS_STRUC_C id; #else ZMUMPS_STRUC_C id; #endif #else #if defined(PETSC_USE_REAL_SINGLE) SMUMPS_STRUC_C id; #else DMUMPS_STRUC_C id; #endif #endif MatStructure matstruc; PetscMPIInt myid,size; PetscInt *irn,*jcn,nz,sym; PetscScalar *val; MPI_Comm comm_mumps; VecScatter scat_rhs, scat_sol; PetscBool isAIJ,CleanUpMUMPS; Vec b_seq,x_seq; PetscInt ICNTL9_pre; /* check if ICNTL(9) is changed from previous MatSolve */ PetscErrorCode (*Destroy)(Mat); PetscErrorCode (*ConvertToTriples)(Mat, int, MatReuse, int*, int**, int**, PetscScalar**); } Mat_MUMPS; extern PetscErrorCode MatDuplicate_MUMPS(Mat,MatDuplicateOption,Mat*); /* MatConvertToTriples_A_B */ /*convert Petsc matrix to triples: row[nz], col[nz], val[nz] */ /* input: A - matrix in aij,baij or sbaij (bs=1) format shift - 0: C style output triple; 1: Fortran style output triple. reuse - MAT_INITIAL_MATRIX: spaces are allocated and values are set for the triple MAT_REUSE_MATRIX: only the values in v array are updated output: nnz - dim of r, c, and v (number of local nonzero entries of A) r, c, v - row and col index, matrix values (matrix triples) The returned values r, c, and sometimes v are obtained in a single PetscMalloc(). Then in MatDestroy_MUMPS() it is freed with PetscFree((mumps->irn); This is not ideal code, the fact that v is ONLY sometimes part of mumps->irn means that the PetscMalloc() cannot easily be replaced with a PetscMalloc3(). */ #undef __FUNCT__ #define __FUNCT__ "MatConvertToTriples_seqaij_seqaij" PetscErrorCode MatConvertToTriples_seqaij_seqaij(Mat A,int shift,MatReuse reuse,int *nnz,int **r, int **c, PetscScalar **v) { const PetscInt *ai,*aj,*ajj,M=A->rmap->n; PetscInt nz,rnz,i,j; PetscErrorCode ierr; PetscInt *row,*col; Mat_SeqAIJ *aa=(Mat_SeqAIJ*)A->data; PetscFunctionBegin; *v=aa->a; if (reuse == MAT_INITIAL_MATRIX) { nz = aa->nz; ai = aa->i; aj = aa->j; *nnz = nz; ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); col = row + nz; nz = 0; for (i=0; idata; const PetscInt *ai,*aj,*ajj,bs2 = aa->bs2; PetscInt bs,M,nz,idx=0,rnz,i,j,k,m; PetscErrorCode ierr; PetscInt *row,*col; PetscFunctionBegin; ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); M = A->rmap->N/bs; *v = aa->a; if (reuse == MAT_INITIAL_MATRIX) { ai = aa->i; aj = aa->j; nz = bs2*aa->nz; *nnz = nz; ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); col = row + nz; for (i=0; irmap->n; PetscInt nz,rnz,i,j; PetscErrorCode ierr; PetscInt *row,*col; Mat_SeqSBAIJ *aa=(Mat_SeqSBAIJ*)A->data; PetscFunctionBegin; *v = aa->a; if (reuse == MAT_INITIAL_MATRIX) { nz = aa->nz; ai = aa->i; aj = aa->j; *v = aa->a; *nnz = nz; ierr = PetscMalloc1(2*nz, &row);CHKERRQ(ierr); col = row + nz; nz = 0; for (i=0; irmap->n; PetscInt nz,rnz,i,j; const PetscScalar *av,*v1; PetscScalar *val; PetscErrorCode ierr; PetscInt *row,*col; Mat_SeqSBAIJ *aa=(Mat_SeqSBAIJ*)A->data; PetscFunctionBegin; ai =aa->i; aj=aa->j;av=aa->a; adiag=aa->diag; if (reuse == MAT_INITIAL_MATRIX) { nz = M + (aa->nz-M)/2; *nnz = nz; ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); col = row + nz; val = (PetscScalar*)(col + nz); nz = 0; for (i=0; irmap->n,*ajj,*bjj; PetscErrorCode ierr; PetscInt rstart,nz,i,j,jj,irow,countA,countB; PetscInt *row,*col; const PetscScalar *av, *bv,*v1,*v2; PetscScalar *val; Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)A->data; Mat_SeqSBAIJ *aa = (Mat_SeqSBAIJ*)(mat->A)->data; Mat_SeqBAIJ *bb = (Mat_SeqBAIJ*)(mat->B)->data; PetscFunctionBegin; ai=aa->i; aj=aa->j; bi=bb->i; bj=bb->j; rstart= A->rmap->rstart; av=aa->a; bv=bb->a; garray = mat->garray; if (reuse == MAT_INITIAL_MATRIX) { nz = aa->nz + bb->nz; *nnz = nz; ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); col = row + nz; val = (PetscScalar*)(col + nz); *r = row; *c = col; *v = val; } else { row = *r; col = *c; val = *v; } jj = 0; irow = rstart; for (i=0; irmap->n,*ajj,*bjj; PetscErrorCode ierr; PetscInt rstart,nz,i,j,jj,irow,countA,countB; PetscInt *row,*col; const PetscScalar *av, *bv,*v1,*v2; PetscScalar *val; Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; Mat_SeqAIJ *aa = (Mat_SeqAIJ*)(mat->A)->data; Mat_SeqAIJ *bb = (Mat_SeqAIJ*)(mat->B)->data; PetscFunctionBegin; ai=aa->i; aj=aa->j; bi=bb->i; bj=bb->j; rstart= A->rmap->rstart; av=aa->a; bv=bb->a; garray = mat->garray; if (reuse == MAT_INITIAL_MATRIX) { nz = aa->nz + bb->nz; *nnz = nz; ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); col = row + nz; val = (PetscScalar*)(col + nz); *r = row; *c = col; *v = val; } else { row = *r; col = *c; val = *v; } jj = 0; irow = rstart; for (i=0; idata; Mat_SeqBAIJ *aa = (Mat_SeqBAIJ*)(mat->A)->data; Mat_SeqBAIJ *bb = (Mat_SeqBAIJ*)(mat->B)->data; const PetscInt *ai = aa->i, *bi = bb->i, *aj = aa->j, *bj = bb->j,*ajj, *bjj; const PetscInt *garray = mat->garray,mbs=mat->mbs,rstart=A->rmap->rstart; const PetscInt bs2=mat->bs2; PetscErrorCode ierr; PetscInt bs,nz,i,j,k,n,jj,irow,countA,countB,idx; PetscInt *row,*col; const PetscScalar *av=aa->a, *bv=bb->a,*v1,*v2; PetscScalar *val; PetscFunctionBegin; ierr = MatGetBlockSize(A,&bs);CHKERRQ(ierr); if (reuse == MAT_INITIAL_MATRIX) { nz = bs2*(aa->nz + bb->nz); *nnz = nz; ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); col = row + nz; val = (PetscScalar*)(col + nz); *r = row; *c = col; *v = val; } else { row = *r; col = *c; val = *v; } jj = 0; irow = rstart; for (i=0; irmap->n,*ajj,*bjj; PetscErrorCode ierr; PetscInt rstart,nz,nza,nzb,i,j,jj,irow,countA,countB; PetscInt *row,*col; const PetscScalar *av, *bv,*v1,*v2; PetscScalar *val; Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data; Mat_SeqAIJ *aa =(Mat_SeqAIJ*)(mat->A)->data; Mat_SeqAIJ *bb =(Mat_SeqAIJ*)(mat->B)->data; PetscFunctionBegin; ai=aa->i; aj=aa->j; adiag=aa->diag; bi=bb->i; bj=bb->j; garray = mat->garray; av=aa->a; bv=bb->a; rstart = A->rmap->rstart; if (reuse == MAT_INITIAL_MATRIX) { nza = 0; /* num of upper triangular entries in mat->A, including diagonals */ nzb = 0; /* num of upper triangular entries in mat->B */ for (i=0; i rstart) nzb++; } } nz = nza + nzb; /* total nz of upper triangular part of mat */ *nnz = nz; ierr = PetscMalloc((2*nz*sizeof(PetscInt)+nz*sizeof(PetscScalar)), &row);CHKERRQ(ierr); col = row + nz; val = (PetscScalar*)(col + nz); *r = row; *c = col; *v = val; } else { row = *r; col = *c; val = *v; } jj = 0; irow = rstart; for (i=0; i rstart) { if (reuse == MAT_INITIAL_MATRIX) { row[jj] = irow + shift; col[jj] = garray[bjj[j]] + shift; } val[jj++] = v2[j]; } } irow++; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDestroy_MUMPS" PetscErrorCode MatDestroy_MUMPS(Mat A) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->spptr; PetscErrorCode ierr; PetscFunctionBegin; if (mumps->CleanUpMUMPS) { /* Terminate instance, deallocate memories */ ierr = PetscFree2(mumps->id.sol_loc,mumps->id.isol_loc);CHKERRQ(ierr); ierr = VecScatterDestroy(&mumps->scat_rhs);CHKERRQ(ierr); ierr = VecDestroy(&mumps->b_seq);CHKERRQ(ierr); ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); ierr = VecDestroy(&mumps->x_seq);CHKERRQ(ierr); ierr = PetscFree(mumps->id.perm_in);CHKERRQ(ierr); ierr = PetscFree(mumps->irn);CHKERRQ(ierr); mumps->id.job = JOB_END; PetscMUMPS_c(&mumps->id); ierr = MPI_Comm_free(&(mumps->comm_mumps));CHKERRQ(ierr); } if (mumps->Destroy) { ierr = (mumps->Destroy)(A);CHKERRQ(ierr); } ierr = PetscFree(A->spptr);CHKERRQ(ierr); /* clear composed functions */ ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetIcntl_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetCntl_C",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolve_MUMPS" PetscErrorCode MatSolve_MUMPS(Mat A,Vec b,Vec x) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->spptr; PetscScalar *array; Vec b_seq; IS is_iden,is_petsc; PetscErrorCode ierr; PetscInt i; static PetscBool cite1 = PETSC_FALSE,cite2 = PETSC_FALSE; PetscFunctionBegin; ierr = PetscCitationsRegister("@article{MUMPS01,\n author = {P.~R. Amestoy and I.~S. Duff and J.-Y. L'Excellent and J. Koster},\n title = {A fully asynchronous multifrontal solver using distributed dynamic scheduling},\n journal = {SIAM Journal on Matrix Analysis and Applications},\n volume = {23},\n number = {1},\n pages = {15--41},\n year = {2001}\n}\n",&cite1);CHKERRQ(ierr); ierr = PetscCitationsRegister("@article{MUMPS02,\n author = {P.~R. Amestoy and A. Guermouche and J.-Y. L'Excellent and S. Pralet},\n title = {Hybrid scheduling for the parallel solution of linear systems},\n journal = {Parallel Computing},\n volume = {32},\n number = {2},\n pages = {136--156},\n year = {2006}\n}\n",&cite2);CHKERRQ(ierr); mumps->id.nrhs = 1; b_seq = mumps->b_seq; if (mumps->size > 1) { /* MUMPS only supports centralized rhs. Scatter b into a seqential rhs vector */ ierr = VecScatterBegin(mumps->scat_rhs,b,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterEnd(mumps->scat_rhs,b,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); if (!mumps->myid) {ierr = VecGetArray(b_seq,&array);CHKERRQ(ierr);} } else { /* size == 1 */ ierr = VecCopy(b,x);CHKERRQ(ierr); ierr = VecGetArray(x,&array);CHKERRQ(ierr); } if (!mumps->myid) { /* define rhs on the host */ mumps->id.nrhs = 1; #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.rhs = (mumps_complex*)array; #else mumps->id.rhs = (mumps_double_complex*)array; #endif #else mumps->id.rhs = array; #endif } /* solve phase */ /*-------------*/ mumps->id.job = JOB_SOLVE; PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in solve phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); if (mumps->size > 1) { /* convert mumps distributed solution to petsc mpi x */ if (mumps->scat_sol && mumps->ICNTL9_pre != mumps->id.ICNTL(9)) { /* when id.ICNTL(9) changes, the contents of lsol_loc may change (not its size, lsol_loc), recreates scat_sol */ ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); } if (!mumps->scat_sol) { /* create scatter scat_sol */ ierr = ISCreateStride(PETSC_COMM_SELF,mumps->id.lsol_loc,0,1,&is_iden);CHKERRQ(ierr); /* from */ for (i=0; iid.lsol_loc; i++) { mumps->id.isol_loc[i] -= 1; /* change Fortran style to C style */ } ierr = ISCreateGeneral(PETSC_COMM_SELF,mumps->id.lsol_loc,mumps->id.isol_loc,PETSC_COPY_VALUES,&is_petsc);CHKERRQ(ierr); /* to */ ierr = VecScatterCreate(mumps->x_seq,is_iden,x,is_petsc,&mumps->scat_sol);CHKERRQ(ierr); ierr = ISDestroy(&is_iden);CHKERRQ(ierr); ierr = ISDestroy(&is_petsc);CHKERRQ(ierr); mumps->ICNTL9_pre = mumps->id.ICNTL(9); /* save current value of id.ICNTL(9) */ } ierr = VecScatterBegin(mumps->scat_sol,mumps->x_seq,x,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = VecScatterEnd(mumps->scat_sol,mumps->x_seq,x,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSolveTranspose_MUMPS" PetscErrorCode MatSolveTranspose_MUMPS(Mat A,Vec b,Vec x) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->spptr; PetscErrorCode ierr; PetscFunctionBegin; mumps->id.ICNTL(9) = 0; ierr = MatSolve_MUMPS(A,b,x);CHKERRQ(ierr); mumps->id.ICNTL(9) = 1; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMatSolve_MUMPS" PetscErrorCode MatMatSolve_MUMPS(Mat A,Mat B,Mat X) { PetscErrorCode ierr; PetscBool flg; PetscFunctionBegin; ierr = PetscObjectTypeCompareAny((PetscObject)B,&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"); SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatMatSolve_MUMPS() is not implemented yet"); PetscFunctionReturn(0); } #if !defined(PETSC_USE_COMPLEX) /* input: F: numeric factor output: nneg: total number of negative pivots nzero: 0 npos: (global dimension of F) - nneg */ #undef __FUNCT__ #define __FUNCT__ "MatGetInertia_SBAIJMUMPS" PetscErrorCode MatGetInertia_SBAIJMUMPS(Mat F,int *nneg,int *nzero,int *npos) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->spptr; PetscErrorCode ierr; PetscMPIInt size; PetscFunctionBegin; ierr = MPI_Comm_size(PetscObjectComm((PetscObject)F),&size);CHKERRQ(ierr); /* MUMPS 4.3.1 calls ScaLAPACK when ICNTL(13)=0 (default), which does not offer the possibility to compute the inertia of a dense matrix. Set ICNTL(13)=1 to skip ScaLAPACK */ if (size > 1 && mumps->id.ICNTL(13) != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"ICNTL(13)=%d. -mat_mumps_icntl_13 must be set as 1 for correct global matrix inertia\n",mumps->id.INFOG(13)); if (nneg) { if (!mumps->myid) { *nneg = mumps->id.INFOG(12); } ierr = MPI_Bcast(nneg,1,MPI_INT,0,mumps->comm_mumps);CHKERRQ(ierr); } if (nzero) *nzero = 0; if (npos) *npos = F->rmap->N - (*nneg); PetscFunctionReturn(0); } #endif /* !defined(PETSC_USE_COMPLEX) */ #undef __FUNCT__ #define __FUNCT__ "MatFactorNumeric_MUMPS" PetscErrorCode MatFactorNumeric_MUMPS(Mat F,Mat A,const MatFactorInfo *info) { Mat_MUMPS *mumps =(Mat_MUMPS*)(F)->spptr; PetscErrorCode ierr; Mat F_diag; PetscBool isMPIAIJ; PetscFunctionBegin; ierr = (*mumps->ConvertToTriples)(A, 1, MAT_REUSE_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); /* numerical factorization phase */ /*-------------------------------*/ mumps->id.job = JOB_FACTNUMERIC; if (!mumps->id.ICNTL(18)) { if (!mumps->myid) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a = (mumps_complex*)mumps->val; #else mumps->id.a = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a = mumps->val; #endif } } else { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a_loc = (mumps_complex*)mumps->val; #else mumps->id.a_loc = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a_loc = mumps->val; #endif } PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) { if (mumps->id.INFO(1) == -13) { if (mumps->id.INFO(2) < 0) { SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in numerical factorization phase: Cannot allocate required memory %d megabytes\n",-mumps->id.INFO(2)); } else { SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in numerical factorization phase: Cannot allocate required memory %d bytes\n",mumps->id.INFO(2)); } } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in numerical factorization phase: INFO(1)=%d, INFO(2)=%d\n",mumps->id.INFO(1),mumps->id.INFO(2)); } if (!mumps->myid && mumps->id.ICNTL(16) > 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB," mumps->id.ICNTL(16):=%d\n",mumps->id.INFOG(16)); if (mumps->size > 1) { ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);CHKERRQ(ierr); if (isMPIAIJ) F_diag = ((Mat_MPIAIJ*)(F)->data)->A; else F_diag = ((Mat_MPISBAIJ*)(F)->data)->A; F_diag->assembled = PETSC_TRUE; if (mumps->scat_sol) { ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); ierr = PetscFree2(mumps->id.sol_loc,mumps->id.isol_loc);CHKERRQ(ierr); ierr = VecDestroy(&mumps->x_seq);CHKERRQ(ierr); } } (F)->assembled = PETSC_TRUE; mumps->matstruc = SAME_NONZERO_PATTERN; mumps->CleanUpMUMPS = PETSC_TRUE; if (mumps->size > 1) { /* distributed solution */ if (!mumps->scat_sol) { /* Create x_seq=sol_loc for repeated use */ PetscInt lsol_loc; PetscScalar *sol_loc; lsol_loc = mumps->id.INFO(23); /* length of sol_loc */ ierr = PetscMalloc2(lsol_loc,&sol_loc,lsol_loc,&mumps->id.isol_loc);CHKERRQ(ierr); mumps->id.lsol_loc = lsol_loc; #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.sol_loc = (mumps_complex*)sol_loc; #else mumps->id.sol_loc = (mumps_double_complex*)sol_loc; #endif #else mumps->id.sol_loc = sol_loc; #endif ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,lsol_loc,sol_loc,&mumps->x_seq);CHKERRQ(ierr); } } PetscFunctionReturn(0); } /* Sets MUMPS options from the options database */ #undef __FUNCT__ #define __FUNCT__ "PetscSetMUMPSFromOptions" PetscErrorCode PetscSetMUMPSFromOptions(Mat F, Mat A) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->spptr; PetscErrorCode ierr; PetscInt icntl; PetscBool flg; PetscFunctionBegin; ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)A),((PetscObject)A)->prefix,"MUMPS Options","Mat");CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_1","ICNTL(1): output stream for error messages","None",mumps->id.ICNTL(1),&icntl,&flg);CHKERRQ(ierr); if (flg) mumps->id.ICNTL(1) = icntl; ierr = PetscOptionsInt("-mat_mumps_icntl_2","ICNTL(2): output stream for diagnostic printing, statistics, and warning","None",mumps->id.ICNTL(2),&icntl,&flg);CHKERRQ(ierr); if (flg) mumps->id.ICNTL(2) = icntl; ierr = PetscOptionsInt("-mat_mumps_icntl_3","ICNTL(3): output stream for global information, collected on the host","None",mumps->id.ICNTL(3),&icntl,&flg);CHKERRQ(ierr); if (flg) mumps->id.ICNTL(3) = icntl; ierr = PetscOptionsInt("-mat_mumps_icntl_4","ICNTL(4): level of printing (0 to 4)","None",mumps->id.ICNTL(4),&icntl,&flg);CHKERRQ(ierr); if (flg) mumps->id.ICNTL(4) = icntl; if (mumps->id.ICNTL(4) || PetscLogPrintInfo) mumps->id.ICNTL(3) = 6; /* resume MUMPS default id.ICNTL(3) = 6 */ ierr = PetscOptionsInt("-mat_mumps_icntl_6","ICNTL(6): permuting and/or scaling the matrix (0 to 7)","None",mumps->id.ICNTL(6),&icntl,&flg);CHKERRQ(ierr); if (flg) mumps->id.ICNTL(6) = icntl; ierr = PetscOptionsInt("-mat_mumps_icntl_7","ICNTL(7): matrix ordering (0 to 7). 3=Scotch, 4=PORD, 5=Metis","None",mumps->id.ICNTL(7),&icntl,&flg);CHKERRQ(ierr); if (flg) { if (icntl== 1 && mumps->size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"pivot order be set by the user in PERM_IN -- not supported by the PETSc/MUMPS interface\n"); else mumps->id.ICNTL(7) = icntl; } ierr = PetscOptionsInt("-mat_mumps_icntl_8","ICNTL(8): scaling strategy (-2 to 8 or 77)","None",mumps->id.ICNTL(8),&mumps->id.ICNTL(8),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_10","ICNTL(10): max num of refinements","None",mumps->id.ICNTL(10),&mumps->id.ICNTL(10),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_11","ICNTL(11): statistics related to the linear system solved (via -ksp_view)","None",mumps->id.ICNTL(11),&mumps->id.ICNTL(11),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_12","ICNTL(12): efficiency control: defines the ordering strategy with scaling constraints (0 to 3)","None",mumps->id.ICNTL(12),&mumps->id.ICNTL(12),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_13","ICNTL(13): efficiency control: with or without ScaLAPACK","None",mumps->id.ICNTL(13),&mumps->id.ICNTL(13),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_14","ICNTL(14): percentage of estimated workspace increase","None",mumps->id.ICNTL(14),&mumps->id.ICNTL(14),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_19","ICNTL(19): Schur complement","None",mumps->id.ICNTL(19),&mumps->id.ICNTL(19),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_22","ICNTL(22): in-core/out-of-core facility (0 or 1)","None",mumps->id.ICNTL(22),&mumps->id.ICNTL(22),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_23","ICNTL(23): max size of the working memory (MB) that can allocate per processor","None",mumps->id.ICNTL(23),&mumps->id.ICNTL(23),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_24","ICNTL(24): detection of null pivot rows (0 or 1)","None",mumps->id.ICNTL(24),&mumps->id.ICNTL(24),NULL);CHKERRQ(ierr); if (mumps->id.ICNTL(24)) { mumps->id.ICNTL(13) = 1; /* turn-off ScaLAPACK to help with the correct detection of null pivots */ } ierr = PetscOptionsInt("-mat_mumps_icntl_25","ICNTL(25): computation of a null space basis","None",mumps->id.ICNTL(25),&mumps->id.ICNTL(25),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_26","ICNTL(26): Schur options for right-hand side or solution vector","None",mumps->id.ICNTL(26),&mumps->id.ICNTL(26),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_27","ICNTL(27): experimental parameter","None",mumps->id.ICNTL(27),&mumps->id.ICNTL(27),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_28","ICNTL(28): use 1 for sequential analysis and ictnl(7) ordering, or 2 for parallel analysis and ictnl(29) ordering","None",mumps->id.ICNTL(28),&mumps->id.ICNTL(28),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_29","ICNTL(29): parallel ordering 1 = ptscotch 2 = parmetis","None",mumps->id.ICNTL(29),&mumps->id.ICNTL(29),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_30","ICNTL(30): compute user-specified set of entries in inv(A)","None",mumps->id.ICNTL(30),&mumps->id.ICNTL(30),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_31","ICNTL(31): factors can be discarded in the solve phase","None",mumps->id.ICNTL(31),&mumps->id.ICNTL(31),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_33","ICNTL(33): compute determinant","None",mumps->id.ICNTL(33),&mumps->id.ICNTL(33),NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_mumps_cntl_1","CNTL(1): relative pivoting threshold","None",mumps->id.CNTL(1),&mumps->id.CNTL(1),NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_mumps_cntl_2","CNTL(2): stopping criterion of refinement","None",mumps->id.CNTL(2),&mumps->id.CNTL(2),NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_mumps_cntl_3","CNTL(3): absolute pivoting threshold","None",mumps->id.CNTL(3),&mumps->id.CNTL(3),NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_mumps_cntl_4","CNTL(4): value for static pivoting","None",mumps->id.CNTL(4),&mumps->id.CNTL(4),NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-mat_mumps_cntl_5","CNTL(5): fixation for null pivots","None",mumps->id.CNTL(5),&mumps->id.CNTL(5),NULL);CHKERRQ(ierr); ierr = PetscOptionsString("-mat_mumps_ooc_tmpdir", "out of core directory", "None", mumps->id.ooc_tmpdir, mumps->id.ooc_tmpdir, 256, NULL); PetscOptionsEnd(); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "PetscInitializeMUMPS" PetscErrorCode PetscInitializeMUMPS(Mat A,Mat_MUMPS *mumps) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A), &mumps->myid); ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&mumps->size);CHKERRQ(ierr); ierr = MPI_Comm_dup(PetscObjectComm((PetscObject)A),&(mumps->comm_mumps));CHKERRQ(ierr); mumps->id.comm_fortran = MPI_Comm_c2f(mumps->comm_mumps); mumps->id.job = JOB_INIT; mumps->id.par = 1; /* host participates factorizaton and solve */ mumps->id.sym = mumps->sym; PetscMUMPS_c(&mumps->id); mumps->CleanUpMUMPS = PETSC_FALSE; mumps->scat_rhs = NULL; mumps->scat_sol = NULL; /* set PETSc-MUMPS default options - override MUMPS default */ mumps->id.ICNTL(3) = 0; mumps->id.ICNTL(4) = 0; if (mumps->size == 1) { mumps->id.ICNTL(18) = 0; /* centralized assembled matrix input */ } else { mumps->id.ICNTL(18) = 3; /* distributed assembled matrix input */ mumps->id.ICNTL(21) = 1; /* distributed solution */ } PetscFunctionReturn(0); } /* Note Petsc r(=c) permutation is used when mumps->id.ICNTL(7)==1 with centralized assembled matrix input; otherwise r and c are ignored */ #undef __FUNCT__ #define __FUNCT__ "MatLUFactorSymbolic_AIJMUMPS" PetscErrorCode MatLUFactorSymbolic_AIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->spptr; PetscErrorCode ierr; Vec b; IS is_iden; const PetscInt M = A->rmap->N; PetscFunctionBegin; mumps->matstruc = DIFFERENT_NONZERO_PATTERN; /* Set MUMPS options from the options database */ ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); /* analysis phase */ /*----------------*/ mumps->id.job = JOB_FACTSYMBOLIC; mumps->id.n = M; switch (mumps->id.ICNTL(18)) { case 0: /* centralized assembled matrix input */ if (!mumps->myid) { mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a = (mumps_complex*)mumps->val; #else mumps->id.a = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a = mumps->val; #endif } if (mumps->id.ICNTL(7) == 1) { /* use user-provide matrix ordering - assuming r = c ordering */ /* PetscBool flag; ierr = ISEqual(r,c,&flag);CHKERRQ(ierr); if (!flag) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"row_perm != col_perm"); ierr = ISView(r,PETSC_VIEWER_STDOUT_SELF); */ if (!mumps->myid) { const PetscInt *idx; PetscInt i,*perm_in; ierr = PetscMalloc1(M,&perm_in);CHKERRQ(ierr); ierr = ISGetIndices(r,&idx);CHKERRQ(ierr); mumps->id.perm_in = perm_in; for (i=0; i1) */ mumps->id.nz_loc = mumps->nz; mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a_loc = (mumps_complex*)mumps->val; #else mumps->id.a_loc = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a_loc = mumps->val; #endif } /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ if (!mumps->myid) { ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr); } else { ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); } ierr = MatGetVecs(A,NULL,&b);CHKERRQ(ierr); ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); ierr = ISDestroy(&is_iden);CHKERRQ(ierr); ierr = VecDestroy(&b);CHKERRQ(ierr); break; } PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in analysis phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); F->ops->lufactornumeric = MatFactorNumeric_MUMPS; F->ops->solve = MatSolve_MUMPS; F->ops->solvetranspose = MatSolveTranspose_MUMPS; F->ops->matsolve = 0; /* use MatMatSolve_Basic() until mumps supports distributed rhs */ PetscFunctionReturn(0); } /* Note the Petsc r and c permutations are ignored */ #undef __FUNCT__ #define __FUNCT__ "MatLUFactorSymbolic_BAIJMUMPS" PetscErrorCode MatLUFactorSymbolic_BAIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->spptr; PetscErrorCode ierr; Vec b; IS is_iden; const PetscInt M = A->rmap->N; PetscFunctionBegin; mumps->matstruc = DIFFERENT_NONZERO_PATTERN; /* Set MUMPS options from the options database */ ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); /* analysis phase */ /*----------------*/ mumps->id.job = JOB_FACTSYMBOLIC; mumps->id.n = M; switch (mumps->id.ICNTL(18)) { case 0: /* centralized assembled matrix input */ if (!mumps->myid) { mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a = (mumps_complex*)mumps->val; #else mumps->id.a = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a = mumps->val; #endif } } break; case 3: /* distributed assembled matrix input (size>1) */ mumps->id.nz_loc = mumps->nz; mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a_loc = (mumps_complex*)mumps->val; #else mumps->id.a_loc = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a_loc = mumps->val; #endif } /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ if (!mumps->myid) { ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr); } else { ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); } ierr = MatGetVecs(A,NULL,&b);CHKERRQ(ierr); ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); ierr = ISDestroy(&is_iden);CHKERRQ(ierr); ierr = VecDestroy(&b);CHKERRQ(ierr); break; } PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in analysis phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); F->ops->lufactornumeric = MatFactorNumeric_MUMPS; F->ops->solve = MatSolve_MUMPS; F->ops->solvetranspose = MatSolveTranspose_MUMPS; PetscFunctionReturn(0); } /* Note the Petsc r permutation and factor info are ignored */ #undef __FUNCT__ #define __FUNCT__ "MatCholeskyFactorSymbolic_MUMPS" PetscErrorCode MatCholeskyFactorSymbolic_MUMPS(Mat F,Mat A,IS r,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->spptr; PetscErrorCode ierr; Vec b; IS is_iden; const PetscInt M = A->rmap->N; PetscFunctionBegin; mumps->matstruc = DIFFERENT_NONZERO_PATTERN; /* Set MUMPS options from the options database */ ierr = PetscSetMUMPSFromOptions(F,A);CHKERRQ(ierr); ierr = (*mumps->ConvertToTriples)(A, 1, MAT_INITIAL_MATRIX, &mumps->nz, &mumps->irn, &mumps->jcn, &mumps->val);CHKERRQ(ierr); /* analysis phase */ /*----------------*/ mumps->id.job = JOB_FACTSYMBOLIC; mumps->id.n = M; switch (mumps->id.ICNTL(18)) { case 0: /* centralized assembled matrix input */ if (!mumps->myid) { mumps->id.nz =mumps->nz; mumps->id.irn=mumps->irn; mumps->id.jcn=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a = (mumps_complex*)mumps->val; #else mumps->id.a = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a = mumps->val; #endif } } break; case 3: /* distributed assembled matrix input (size>1) */ mumps->id.nz_loc = mumps->nz; mumps->id.irn_loc=mumps->irn; mumps->id.jcn_loc=mumps->jcn; if (mumps->id.ICNTL(6)>1) { #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) mumps->id.a_loc = (mumps_complex*)mumps->val; #else mumps->id.a_loc = (mumps_double_complex*)mumps->val; #endif #else mumps->id.a_loc = mumps->val; #endif } /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ if (!mumps->myid) { ierr = VecCreateSeq(PETSC_COMM_SELF,A->cmap->N,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,A->cmap->N,0,1,&is_iden);CHKERRQ(ierr); } else { ierr = VecCreateSeq(PETSC_COMM_SELF,0,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_iden);CHKERRQ(ierr); } ierr = MatGetVecs(A,NULL,&b);CHKERRQ(ierr); ierr = VecScatterCreate(b,is_iden,mumps->b_seq,is_iden,&mumps->scat_rhs);CHKERRQ(ierr); ierr = ISDestroy(&is_iden);CHKERRQ(ierr); ierr = VecDestroy(&b);CHKERRQ(ierr); break; } PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in analysis phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); F->ops->choleskyfactornumeric = MatFactorNumeric_MUMPS; F->ops->solve = MatSolve_MUMPS; F->ops->solvetranspose = MatSolve_MUMPS; F->ops->matsolve = 0; /* use MatMatSolve_Basic() until mumps supports distributed rhs */ #if !defined(PETSC_USE_COMPLEX) F->ops->getinertia = MatGetInertia_SBAIJMUMPS; #else F->ops->getinertia = NULL; #endif PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_MUMPS" PetscErrorCode MatView_MUMPS(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscBool iascii; PetscViewerFormat format; Mat_MUMPS *mumps=(Mat_MUMPS*)A->spptr; PetscFunctionBegin; /* check if matrix is mumps type */ if (A->ops->solve != MatSolve_MUMPS) PetscFunctionReturn(0); ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); if (iascii) { ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format == PETSC_VIEWER_ASCII_INFO) { ierr = PetscViewerASCIIPrintf(viewer,"MUMPS run parameters:\n");CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," SYM (matrix type): %d \n",mumps->id.sym);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," PAR (host participation): %d \n",mumps->id.par);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(1) (output for error): %d \n",mumps->id.ICNTL(1));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(2) (output of diagnostic msg): %d \n",mumps->id.ICNTL(2));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(3) (output for global info): %d \n",mumps->id.ICNTL(3));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(4) (level of printing): %d \n",mumps->id.ICNTL(4));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(5) (input mat struct): %d \n",mumps->id.ICNTL(5));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(6) (matrix prescaling): %d \n",mumps->id.ICNTL(6));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(7) (sequentia matrix ordering):%d \n",mumps->id.ICNTL(7));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(8) (scalling strategy): %d \n",mumps->id.ICNTL(8));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(10) (max num of refinements): %d \n",mumps->id.ICNTL(10));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(11) (error analysis): %d \n",mumps->id.ICNTL(11));CHKERRQ(ierr); if (mumps->id.ICNTL(11)>0) { ierr = PetscViewerASCIIPrintf(viewer," RINFOG(4) (inf norm of input mat): %g\n",mumps->id.RINFOG(4));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(5) (inf norm of solution): %g\n",mumps->id.RINFOG(5));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(6) (inf norm of residual): %g\n",mumps->id.RINFOG(6));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(7),RINFOG(8) (backward error est): %g, %g\n",mumps->id.RINFOG(7),mumps->id.RINFOG(8));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(9) (error estimate): %g \n",mumps->id.RINFOG(9));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(10),RINFOG(11)(condition numbers): %g, %g\n",mumps->id.RINFOG(10),mumps->id.RINFOG(11));CHKERRQ(ierr); } ierr = PetscViewerASCIIPrintf(viewer," ICNTL(12) (efficiency control): %d \n",mumps->id.ICNTL(12));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(13) (efficiency control): %d \n",mumps->id.ICNTL(13));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(14) (percentage of estimated workspace increase): %d \n",mumps->id.ICNTL(14));CHKERRQ(ierr); /* ICNTL(15-17) not used */ ierr = PetscViewerASCIIPrintf(viewer," ICNTL(18) (input mat struct): %d \n",mumps->id.ICNTL(18));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(19) (Shur complement info): %d \n",mumps->id.ICNTL(19));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(20) (rhs sparse pattern): %d \n",mumps->id.ICNTL(20));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(21) (somumpstion struct): %d \n",mumps->id.ICNTL(21));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(22) (in-core/out-of-core facility): %d \n",mumps->id.ICNTL(22));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(23) (max size of memory can be allocated locally):%d \n",mumps->id.ICNTL(23));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(24) (detection of null pivot rows): %d \n",mumps->id.ICNTL(24));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(25) (computation of a null space basis): %d \n",mumps->id.ICNTL(25));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(26) (Schur options for rhs or solution): %d \n",mumps->id.ICNTL(26));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(27) (experimental parameter): %d \n",mumps->id.ICNTL(27));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(28) (use parallel or sequential ordering): %d \n",mumps->id.ICNTL(28));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(29) (parallel ordering): %d \n",mumps->id.ICNTL(29));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(30) (user-specified set of entries in inv(A)): %d \n",mumps->id.ICNTL(30));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(31) (factors is discarded in the solve phase): %d \n",mumps->id.ICNTL(31));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(33) (compute determinant): %d \n",mumps->id.ICNTL(33));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(1) (relative pivoting threshold): %g \n",mumps->id.CNTL(1));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(2) (stopping criterion of refinement): %g \n",mumps->id.CNTL(2));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(3) (absomumpste pivoting threshold): %g \n",mumps->id.CNTL(3));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(4) (vamumpse of static pivoting): %g \n",mumps->id.CNTL(4));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(5) (fixation for null pivots): %g \n",mumps->id.CNTL(5));CHKERRQ(ierr); /* infomation local to each processor */ ierr = PetscViewerASCIIPrintf(viewer, " RINFO(1) (local estimated flops for the elimination after analysis): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(1));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIIPrintf(viewer, " RINFO(2) (local estimated flops for the assembly after factorization): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(2));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIIPrintf(viewer, " RINFO(3) (local estimated flops for the elimination after factorization): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(3));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIIPrintf(viewer, " INFO(15) (estimated size of (in MB) MUMPS internal data for running numerical factorization): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(15));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIIPrintf(viewer, " INFO(16) (size of (in MB) MUMPS internal data used during numerical factorization): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(16));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIIPrintf(viewer, " INFO(23) (num of pivots eliminated on this processor after factorization): \n");CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(23));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer); ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr); if (!mumps->myid) { /* information from the host */ ierr = PetscViewerASCIIPrintf(viewer," RINFOG(1) (global estimated flops for the elimination after analysis): %g \n",mumps->id.RINFOG(1));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(2) (global estimated flops for the assembly after factorization): %g \n",mumps->id.RINFOG(2));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," RINFOG(3) (global estimated flops for the elimination after factorization): %g \n",mumps->id.RINFOG(3));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant): (%g,%g)*(2^%d)\n",mumps->id.RINFOG(12),mumps->id.RINFOG(13),mumps->id.INFOG(34));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(3) (estimated real workspace for factors on all processors after analysis): %d \n",mumps->id.INFOG(3));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(4) (estimated integer workspace for factors on all processors after analysis): %d \n",mumps->id.INFOG(4));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(5) (estimated maximum front size in the complete tree): %d \n",mumps->id.INFOG(5));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(6) (number of nodes in the complete tree): %d \n",mumps->id.INFOG(6));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(7) (ordering option effectively use after analysis): %d \n",mumps->id.INFOG(7));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(8) (structural symmetry in percent of the permuted matrix after analysis): %d \n",mumps->id.INFOG(8));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(9) (total real/complex workspace to store the matrix factors after factorization): %d \n",mumps->id.INFOG(9));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(10) (total integer space store the matrix factors after factorization): %d \n",mumps->id.INFOG(10));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(11) (order of largest frontal matrix after factorization): %d \n",mumps->id.INFOG(11));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(12) (number of off-diagonal pivots): %d \n",mumps->id.INFOG(12));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(13) (number of delayed pivots after factorization): %d \n",mumps->id.INFOG(13));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(14) (number of memory compress after factorization): %d \n",mumps->id.INFOG(14));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(15) (number of steps of iterative refinement after solution): %d \n",mumps->id.INFOG(15));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(16) (estimated size (in MB) of all MUMPS internal data for factorization after analysis: value on the most memory consuming processor): %d \n",mumps->id.INFOG(16));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(17) (estimated size of all MUMPS internal data for factorization after analysis: sum over all processors): %d \n",mumps->id.INFOG(17));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(18) (size of all MUMPS internal data allocated during factorization: value on the most memory consuming processor): %d \n",mumps->id.INFOG(18));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(19) (size of all MUMPS internal data allocated during factorization: sum over all processors): %d \n",mumps->id.INFOG(19));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(20) (estimated number of entries in the factors): %d \n",mumps->id.INFOG(20));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(21) (size in MB of memory effectively used during factorization - value on the most memory consuming processor): %d \n",mumps->id.INFOG(21));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(22) (size in MB of memory effectively used during factorization - sum over all processors): %d \n",mumps->id.INFOG(22));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(23) (after analysis: value of ICNTL(6) effectively used): %d \n",mumps->id.INFOG(23));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(24) (after analysis: value of ICNTL(12) effectively used): %d \n",mumps->id.INFOG(24));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(25) (after factorization: number of pivots modified by static pivoting): %d \n",mumps->id.INFOG(25));CHKERRQ(ierr); } } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetInfo_MUMPS" PetscErrorCode MatGetInfo_MUMPS(Mat A,MatInfoType flag,MatInfo *info) { Mat_MUMPS *mumps =(Mat_MUMPS*)A->spptr; PetscFunctionBegin; info->block_size = 1.0; info->nz_allocated = mumps->id.INFOG(20); info->nz_used = mumps->id.INFOG(20); info->nz_unneeded = 0.0; info->assemblies = 0.0; info->mallocs = 0.0; info->memory = 0.0; info->fill_ratio_given = 0; info->fill_ratio_needed = 0; info->factor_mallocs = 0; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "MatMumpsSetIcntl_MUMPS" PetscErrorCode MatMumpsSetIcntl_MUMPS(Mat F,PetscInt icntl,PetscInt ival) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->spptr; PetscFunctionBegin; mumps->id.ICNTL(icntl) = ival; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMumpsSetIcntl" /*@ MatMumpsSetIcntl - Set MUMPS parameter ICNTL() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface . icntl - index of MUMPS parameter array ICNTL() - ival - value of MUMPS ICNTL(icntl) Options Database: . -mat_mumps_icntl_ Level: beginner References: MUMPS Users' Guide .seealso: MatGetFactor() @*/ PetscErrorCode MatMumpsSetIcntl(Mat F,PetscInt icntl,PetscInt ival) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidLogicalCollectiveInt(F,ival,3); ierr = PetscTryMethod(F,"MatMumpsSetIcntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "MatMumpsSetCntl_MUMPS" PetscErrorCode MatMumpsSetCntl_MUMPS(Mat F,PetscInt icntl,PetscReal val) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->spptr; PetscFunctionBegin; mumps->id.CNTL(icntl) = val; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMumpsSetCntl" /*@ MatMumpsSetCntl - Set MUMPS parameter CNTL() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface . icntl - index of MUMPS parameter array CNTL() - val - value of MUMPS CNTL(icntl) Options Database: . -mat_mumps_cntl_ Level: beginner References: MUMPS Users' Guide .seealso: MatGetFactor() @*/ PetscErrorCode MatMumpsSetCntl(Mat F,PetscInt icntl,PetscReal val) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidLogicalCollectiveInt(F,val,3); ierr = PetscTryMethod(F,"MatMumpsSetCntl_C",(Mat,PetscInt,PetscReal),(F,icntl,val));CHKERRQ(ierr); PetscFunctionReturn(0); } /*MC MATSOLVERMUMPS - A matrix type providing direct solvers (LU and Cholesky) for distributed and sequential matrices via the external package MUMPS. Works with MATAIJ and MATSBAIJ matrices Options Database Keys: + -mat_mumps_icntl_4 <0,...,4> - print level . -mat_mumps_icntl_6 <0,...,7> - matrix prescaling options (see MUMPS User's Guide) . -mat_mumps_icntl_7 <0,...,7> - matrix orderings (see MUMPS User's Guidec) . -mat_mumps_icntl_9 <1,2> - A or A^T x=b to be solved: 1 denotes A, 2 denotes A^T . -mat_mumps_icntl_10 - maximum number of iterative refinements . -mat_mumps_icntl_11 - error analysis, a positive value returns statistics during -ksp_view . -mat_mumps_icntl_12 - efficiency control (see MUMPS User's Guide) . -mat_mumps_icntl_13 - efficiency control (see MUMPS User's Guide) . -mat_mumps_icntl_14 - efficiency control (see MUMPS User's Guide) . -mat_mumps_icntl_15 - efficiency control (see MUMPS User's Guide) . -mat_mumps_cntl_1 - relative pivoting threshold . -mat_mumps_cntl_2 - stopping criterion for refinement - -mat_mumps_cntl_3 - absolute pivoting threshold Level: beginner .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage M*/ #undef __FUNCT__ #define __FUNCT__ "MatFactorGetSolverPackage_mumps" static PetscErrorCode MatFactorGetSolverPackage_mumps(Mat A,const MatSolverPackage *type) { PetscFunctionBegin; *type = MATSOLVERMUMPS; PetscFunctionReturn(0); } /* MatGetFactor for Seq and MPI AIJ matrices */ #undef __FUNCT__ #define __FUNCT__ "MatGetFactor_aij_mumps" PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat A,MatFactorType ftype,Mat *F) { Mat B; PetscErrorCode ierr; Mat_MUMPS *mumps; PetscBool isSeqAIJ; PetscFunctionBegin; /* Create the factorization matrix */ ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&isSeqAIJ);CHKERRQ(ierr); ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); if (isSeqAIJ) { ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr); } else { ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr); } ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); B->ops->view = MatView_MUMPS; B->ops->getinfo = MatGetInfo_MUMPS; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); if (ftype == MAT_FACTOR_LU) { B->ops->lufactorsymbolic = MatLUFactorSymbolic_AIJMUMPS; B->factortype = MAT_FACTOR_LU; if (isSeqAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqaij_seqaij; else mumps->ConvertToTriples = MatConvertToTriples_mpiaij_mpiaij; mumps->sym = 0; } else { B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MUMPS; B->factortype = MAT_FACTOR_CHOLESKY; if (isSeqAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqaij_seqsbaij; else mumps->ConvertToTriples = MatConvertToTriples_mpiaij_mpisbaij; if (A->spd_set && A->spd) mumps->sym = 1; else mumps->sym = 2; } mumps->isAIJ = PETSC_TRUE; mumps->Destroy = B->ops->destroy; B->ops->destroy = MatDestroy_MUMPS; B->spptr = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } /* MatGetFactor for Seq and MPI SBAIJ matrices */ #undef __FUNCT__ #define __FUNCT__ "MatGetFactor_sbaij_mumps" PETSC_EXTERN PetscErrorCode MatGetFactor_sbaij_mumps(Mat A,MatFactorType ftype,Mat *F) { Mat B; PetscErrorCode ierr; Mat_MUMPS *mumps; PetscBool isSeqSBAIJ; PetscFunctionBegin; if (ftype != MAT_FACTOR_CHOLESKY) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with MUMPS LU, use AIJ matrix"); if (A->rmap->bs > 1) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot use PETSc SBAIJ matrices with block size > 1 with MUMPS Cholesky, use AIJ matrix instead"); ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQSBAIJ,&isSeqSBAIJ);CHKERRQ(ierr); /* Create the factorization matrix */ ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); if (isSeqSBAIJ) { ierr = MatSeqSBAIJSetPreallocation(B,1,0,NULL);CHKERRQ(ierr); mumps->ConvertToTriples = MatConvertToTriples_seqsbaij_seqsbaij; } else { ierr = MatMPISBAIJSetPreallocation(B,1,0,NULL,0,NULL);CHKERRQ(ierr); mumps->ConvertToTriples = MatConvertToTriples_mpisbaij_mpisbaij; } B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MUMPS; B->ops->view = MatView_MUMPS; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl);CHKERRQ(ierr); B->factortype = MAT_FACTOR_CHOLESKY; if (A->spd_set && A->spd) mumps->sym = 1; else mumps->sym = 2; mumps->isAIJ = PETSC_FALSE; mumps->Destroy = B->ops->destroy; B->ops->destroy = MatDestroy_MUMPS; B->spptr = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetFactor_baij_mumps" PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat A,MatFactorType ftype,Mat *F) { Mat B; PetscErrorCode ierr; Mat_MUMPS *mumps; PetscBool isSeqBAIJ; PetscFunctionBegin; /* Create the factorization matrix */ ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQBAIJ,&isSeqBAIJ);CHKERRQ(ierr); ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr); if (isSeqBAIJ) { ierr = MatSeqBAIJSetPreallocation(B,A->rmap->bs,0,NULL);CHKERRQ(ierr); } else { ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr); } ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); if (ftype == MAT_FACTOR_LU) { B->ops->lufactorsymbolic = MatLUFactorSymbolic_BAIJMUMPS; B->factortype = MAT_FACTOR_LU; if (isSeqBAIJ) mumps->ConvertToTriples = MatConvertToTriples_seqbaij_seqaij; else mumps->ConvertToTriples = MatConvertToTriples_mpibaij_mpiaij; mumps->sym = 0; } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot use PETSc BAIJ matrices with MUMPS Cholesky, use SBAIJ or AIJ matrix instead\n"); B->ops->view = MatView_MUMPS; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); mumps->isAIJ = PETSC_TRUE; mumps->Destroy = B->ops->destroy; B->ops->destroy = MatDestroy_MUMPS; B->spptr = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); }