/* 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> #include 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 /* declare MumpsScalar */ #if defined(PETSC_USE_COMPLEX) #if defined(PETSC_USE_REAL_SINGLE) #define MumpsScalar mumps_complex #else #define MumpsScalar mumps_double_complex #endif #else #define MumpsScalar PetscScalar #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; PetscBool isAIJ; PetscInt ICNTL9_pre; /* check if ICNTL(9) is changed from previous MatSolve */ VecScatter scat_rhs, scat_sol; /* used by MatSolve() */ Vec b_seq,x_seq; PetscInt ninfo,*info; /* display INFO */ PetscInt sizeredrhs; PetscInt *schur_pivots; PetscInt schur_B_lwork; PetscScalar *schur_work; PetscScalar *schur_sol; PetscInt schur_sizesol; PetscBool schur_factored; PetscBool schur_inverted; PetscInt schur_sym; PetscErrorCode (*ConvertToTriples)(Mat, int, MatReuse, int*, int**, int**, PetscScalar**); } Mat_MUMPS; extern PetscErrorCode MatDuplicate_MUMPS(Mat,MatDuplicateOption,Mat*); static PetscErrorCode MatMumpsResetSchur_Private(Mat_MUMPS* mumps) { PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscFree2(mumps->id.listvar_schur,mumps->id.schur);CHKERRQ(ierr); ierr = PetscFree(mumps->id.redrhs);CHKERRQ(ierr); ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); ierr = PetscFree(mumps->schur_pivots);CHKERRQ(ierr); ierr = PetscFree(mumps->schur_work);CHKERRQ(ierr); mumps->id.size_schur = 0; mumps->id.ICNTL(19) = 0; PetscFunctionReturn(0); } static PetscErrorCode MatMumpsFactorSchur_Private(Mat_MUMPS* mumps) { PetscBLASInt B_N,B_ierr,B_slda; PetscErrorCode ierr; PetscFunctionBegin; if (mumps->schur_factored) { PetscFunctionReturn(0); } ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ if (!mumps->schur_pivots) { ierr = PetscMalloc1(B_N,&mumps->schur_pivots);CHKERRQ(ierr); } ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&B_N,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRF Lapack routine %d",(int)B_ierr); } else { /* either full or lower-triangular (not packed) */ char ord[2]; if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ sprintf(ord,"L"); } else { /* ICNTL(19) == 1 lower triangular stored by rows */ sprintf(ord,"U"); } if (mumps->schur_sym == 2) { if (!mumps->schur_pivots) { PetscScalar lwork; ierr = PetscMalloc1(B_N,&mumps->schur_pivots);CHKERRQ(ierr); mumps->schur_B_lwork=-1; ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,&lwork,&mumps->schur_B_lwork,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to SYTRF Lapack routine %d",(int)B_ierr); ierr = PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&mumps->schur_B_lwork);CHKERRQ(ierr); ierr = PetscMalloc1(mumps->schur_B_lwork,&mumps->schur_work);CHKERRQ(ierr); } ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,mumps->schur_work,&mumps->schur_B_lwork,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRF Lapack routine %d",(int)B_ierr); } else { ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_slda,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRF Lapack routine %d",(int)B_ierr); } } mumps->schur_factored = PETSC_TRUE; PetscFunctionReturn(0); } static PetscErrorCode MatMumpsInvertSchur_Private(Mat_MUMPS* mumps) { PetscBLASInt B_N,B_ierr,B_slda; PetscErrorCode ierr; PetscFunctionBegin; ierr = MatMumpsFactorSchur_Private(mumps);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ if (!mumps->schur_work) { PetscScalar lwork; mumps->schur_B_lwork = -1; ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,&lwork,&mumps->schur_B_lwork,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in query to GETRI Lapack routine %d",(int)B_ierr); ierr = PetscBLASIntCast((PetscInt)PetscRealPart(lwork),&mumps->schur_B_lwork);CHKERRQ(ierr); ierr = PetscMalloc1(mumps->schur_B_lwork,&mumps->schur_work);CHKERRQ(ierr); } ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,mumps->schur_work,&mumps->schur_B_lwork,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRI Lapack routine %d",(int)B_ierr); } else { /* either full or lower-triangular (not packed) */ char ord[2]; if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ sprintf(ord,"L"); } else { /* ICNTL(19) == 1 lower triangular stored by rows */ sprintf(ord,"U"); } if (mumps->schur_sym == 2) { ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_N,mumps->schur_pivots,mumps->schur_work,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRI Lapack routine %d",(int)B_ierr); } else { ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_(ord,&B_N,(PetscScalar*)mumps->id.schur,&B_N,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRI Lapack routine %d",(int)B_ierr); } } mumps->schur_inverted = PETSC_TRUE; PetscFunctionReturn(0); } static PetscErrorCode MatMumpsSolveSchur_Private(Mat_MUMPS* mumps, PetscBool sol_in_redrhs) { PetscBLASInt B_N,B_Nrhs,B_ierr,B_slda,B_rlda; PetscScalar one=1.,zero=0.; PetscErrorCode ierr; PetscFunctionBegin; ierr = MatMumpsFactorSchur_Private(mumps);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.size_schur,&B_N);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.schur_lld,&B_slda);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.nrhs,&B_Nrhs);CHKERRQ(ierr); ierr = PetscBLASIntCast(mumps->id.lredrhs,&B_rlda);CHKERRQ(ierr); if (mumps->schur_inverted) { PetscInt sizesol = B_Nrhs*B_N; if (!mumps->schur_sol || sizesol > mumps->schur_sizesol) { ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); ierr = PetscMalloc1(sizesol,&mumps->schur_sol);CHKERRQ(ierr); mumps->schur_sizesol = sizesol; } if (!mumps->sym) { char type[2]; if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ if (!mumps->id.ICNTL(9)) { /* transpose solve */ sprintf(type,"N"); } else { sprintf(type,"T"); } } else { /* stored by columns */ if (!mumps->id.ICNTL(9)) { /* transpose solve */ sprintf(type,"T"); } else { sprintf(type,"N"); } } PetscStackCallBLAS("BLASgemm",BLASgemm_(type,"N",&B_N,&B_Nrhs,&B_N,&one,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&zero,mumps->schur_sol,&B_rlda)); } else { char ord[2]; if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ sprintf(ord,"L"); } else { /* ICNTL(19) == 1 lower triangular stored by rows */ sprintf(ord,"U"); } PetscStackCallBLAS("BLASsymm",BLASsymm_("L",ord,&B_N,&B_Nrhs,&one,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&zero,mumps->schur_sol,&B_rlda)); } if (sol_in_redrhs) { ierr = PetscMemcpy(mumps->id.redrhs,mumps->schur_sol,sizesol*sizeof(PetscScalar));CHKERRQ(ierr); } } else { /* Schur complement has not yet been inverted */ MumpsScalar *orhs=NULL; if (!sol_in_redrhs) { PetscInt sizesol = B_Nrhs*B_N; if (!mumps->schur_sol || sizesol > mumps->schur_sizesol) { ierr = PetscFree(mumps->schur_sol);CHKERRQ(ierr); ierr = PetscMalloc1(sizesol,&mumps->schur_sol);CHKERRQ(ierr); mumps->schur_sizesol = sizesol; } orhs = mumps->id.redrhs; ierr = PetscMemcpy(mumps->schur_sol,mumps->id.redrhs,sizesol*sizeof(PetscScalar));CHKERRQ(ierr); mumps->id.redrhs = (MumpsScalar*)mumps->schur_sol; } if (!mumps->sym) { /* MUMPS always return a full Schur matrix */ char type[2]; if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ if (!mumps->id.ICNTL(9)) { /* transpose solve */ sprintf(type,"N"); } else { sprintf(type,"T"); } } else { /* stored by columns */ if (!mumps->id.ICNTL(9)) { /* transpose solve */ sprintf(type,"T"); } else { sprintf(type,"N"); } } ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_(type,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in GETRS Lapack routine %d",(int)B_ierr); } else { /* either full or lower-triangular (not packed) */ char ord[2]; if (mumps->id.ICNTL(19) == 2 || mumps->id.ICNTL(19) == 3) { /* lower triangular stored by columns or full matrix */ sprintf(ord,"L"); } else { /* ICNTL(19) == 1 lower triangular stored by rows */ sprintf(ord,"U"); } if (mumps->schur_sym == 2) { ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_(ord,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,mumps->schur_pivots,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in SYTRS Lapack routine %d",(int)B_ierr); } else { ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_(ord,&B_N,&B_Nrhs,(PetscScalar*)mumps->id.schur,&B_slda,(PetscScalar*)mumps->id.redrhs,&B_rlda,&B_ierr)); ierr = PetscFPTrapPop();CHKERRQ(ierr); if (B_ierr) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error in POTRS Lapack routine %d",(int)B_ierr); } } if (!sol_in_redrhs) { mumps->id.redrhs = orhs; } } PetscFunctionReturn(0); } static PetscErrorCode MatMumpsHandleSchur_Private(Mat_MUMPS* mumps, PetscBool expansion) { PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) { /* do nothing when Schur complement has not been computed */ PetscFunctionReturn(0); } if (!expansion) { /* prepare for the condensation step */ PetscInt sizeredrhs = mumps->id.nrhs*mumps->id.size_schur; /* allocate MUMPS internal array to store reduced right-hand sides */ if (!mumps->id.redrhs || sizeredrhs > mumps->sizeredrhs) { ierr = PetscFree(mumps->id.redrhs);CHKERRQ(ierr); mumps->id.lredrhs = mumps->id.size_schur; ierr = PetscMalloc1(mumps->id.nrhs*mumps->id.lredrhs,&mumps->id.redrhs);CHKERRQ(ierr); mumps->sizeredrhs = mumps->id.nrhs*mumps->id.lredrhs; } mumps->id.ICNTL(26) = 1; /* condensation phase */ } else { /* prepare for the expansion step */ /* solve Schur complement (this has to be done by the MUMPS user, so basically us) */ ierr = MatMumpsSolveSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); mumps->id.ICNTL(26) = 2; /* expansion phase */ 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)); /* restore defaults */ mumps->id.ICNTL(26) = -1; /* free MUMPS internal array for redrhs if we have solved for multiple rhs in order to save memory space */ if (mumps->id.nrhs > 1) { ierr = PetscFree(mumps->id.redrhs);CHKERRQ(ierr); mumps->id.lredrhs = 0; mumps->sizeredrhs = 0; } } PetscFunctionReturn(0); } /* 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(). */ 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_SeqAIJ *aa=(Mat_SeqAIJ*)A->data; PetscBool missing; PetscFunctionBegin; ai =aa->i; aj=aa->j;av=aa->a; adiag=aa->diag; ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&i);CHKERRQ(ierr); if (reuse == MAT_INITIAL_MATRIX) { /* count nz in the uppper triangular part of A */ nz = 0; if (missing) { for (i=0; i= ai[i+1])) { for (j=ai[i];j= ai[i+1])) { for (j=ai[i];j= ai[i+1])) { for (j=ai[i];jrmap->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); } PetscErrorCode MatDestroy_MUMPS(Mat A) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscFree2(mumps->id.sol_loc,mumps->id.isol_loc);CHKERRQ(ierr); ierr = VecScatterDestroy(&mumps->scat_rhs);CHKERRQ(ierr); ierr = VecScatterDestroy(&mumps->scat_sol);CHKERRQ(ierr); ierr = VecDestroy(&mumps->b_seq);CHKERRQ(ierr); ierr = VecDestroy(&mumps->x_seq);CHKERRQ(ierr); ierr = PetscFree(mumps->id.perm_in);CHKERRQ(ierr); ierr = PetscFree(mumps->irn);CHKERRQ(ierr); ierr = PetscFree(mumps->info);CHKERRQ(ierr); ierr = MatMumpsResetSchur_Private(mumps);CHKERRQ(ierr); mumps->id.job = JOB_END; PetscMUMPS_c(&mumps->id); ierr = MPI_Comm_free(&mumps->comm_mumps);CHKERRQ(ierr); ierr = PetscFree(A->data);CHKERRQ(ierr); /* clear composed functions */ ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSolverPackage_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurIS_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorInvertSchurComplement_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorCreateSchurComplement_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorGetSchurComplement_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplement_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSolveSchurComplementTranspose_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorFactorizeSchurComplement_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatFactorSetSchurComplementSolverType_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetIcntl_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetIcntl_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsSetCntl_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetCntl_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetInfo_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetInfog_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetRinfo_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatMumpsGetRinfog_C",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } PetscErrorCode MatSolve_MUMPS(Mat A,Vec b,Vec x) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; PetscScalar *array; Vec b_seq; IS is_iden,is_petsc; PetscErrorCode ierr; PetscInt i; PetscBool second_solve = PETSC_FALSE; 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); if (A->factorerrortype) { ierr = PetscInfo2(A,"MatSolve is called with singular matrix factor, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); ierr = VecSetInf(x);CHKERRQ(ierr); PetscFunctionReturn(0); } 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; mumps->id.rhs = (MumpsScalar*)array; } /* handle condensation step of Schur complement (if any) We set by default ICNTL(26) == -1 when Schur indices have been provided by the user. According to MUMPS (5.0.0) manual, any value should be harmful during the factorization phase Unless the user provides a valid value for ICNTL(26), MatSolve and MatMatSolve routines solve the full system. This requires an extra call to PetscMUMPS_c and the computation of the factors for S */ if (mumps->id.ICNTL(26) < 0 || mumps->id.ICNTL(26) > 2) { if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Parallel Schur complements not yet supported from PETSc\n"); second_solve = PETSC_TRUE; ierr = MatMumpsHandleSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); } /* 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)); /* handle expansion step of Schur complement (if any) */ if (second_solve) { ierr = MatMumpsHandleSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); } 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); } PetscErrorCode MatSolveTranspose_MUMPS(Mat A,Vec b,Vec x) { Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; PetscErrorCode ierr; PetscFunctionBegin; mumps->id.ICNTL(9) = 0; ierr = MatSolve_MUMPS(A,b,x);CHKERRQ(ierr); mumps->id.ICNTL(9) = 1; PetscFunctionReturn(0); } PetscErrorCode MatMatSolve_MUMPS(Mat A,Mat B,Mat X) { PetscErrorCode ierr; Mat Bt = NULL; PetscBool flg, flgT; Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; PetscInt i,nrhs,M; PetscScalar *array,*bray; PetscFunctionBegin; ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)B,MATTRANSPOSEMAT,&flgT);CHKERRQ(ierr); if (flgT) { if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); ierr = MatTransposeGetMat(B,&Bt);CHKERRQ(ierr); } else { if (!flg) SETERRQ(PetscObjectComm((PetscObject)B),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)X),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); if (B->rmap->n != X->rmap->n) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_WRONG,"Matrix B and X must have same row distribution"); ierr = MatGetSize(B,&M,&nrhs);CHKERRQ(ierr); mumps->id.nrhs = nrhs; mumps->id.lrhs = M; if (mumps->size == 1) { PetscScalar *aa; PetscInt spnr,*ia,*ja; PetscBool second_solve = PETSC_FALSE; /* copy B to X */ ierr = MatDenseGetArray(X,&array);CHKERRQ(ierr); mumps->id.rhs = (MumpsScalar*)array; if (!Bt) { ierr = MatDenseGetArray(B,&bray);CHKERRQ(ierr); ierr = PetscMemcpy(array,bray,M*nrhs*sizeof(PetscScalar));CHKERRQ(ierr); ierr = MatDenseRestoreArray(B,&bray);CHKERRQ(ierr); } else { PetscBool done; ierr = MatSeqAIJGetArray(Bt,&aa);CHKERRQ(ierr); ierr = MatGetRowIJ(Bt,1,PETSC_FALSE,PETSC_FALSE,&spnr,(const PetscInt**)&ia,(const PetscInt**)&ja,&done);CHKERRQ(ierr); if (!done) SETERRQ(PetscObjectComm((PetscObject)Bt),PETSC_ERR_ARG_WRONG,"Cannot get IJ structure"); mumps->id.irhs_ptr = ia; mumps->id.irhs_sparse = ja; mumps->id.nz_rhs = ia[spnr] - 1; mumps->id.rhs_sparse = (MumpsScalar*)aa; mumps->id.ICNTL(20) = 1; } /* handle condensation step of Schur complement (if any) */ if (mumps->id.ICNTL(26) < 0 || mumps->id.ICNTL(26) > 2) { second_solve = PETSC_TRUE; ierr = MatMumpsHandleSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); } /* 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)); /* handle expansion step of Schur complement (if any) */ if (second_solve) { ierr = MatMumpsHandleSchur_Private(mumps,PETSC_TRUE);CHKERRQ(ierr); } if (Bt) { PetscBool done; ierr = MatSeqAIJRestoreArray(Bt,&aa);CHKERRQ(ierr); ierr = MatRestoreRowIJ(Bt,1,PETSC_FALSE,PETSC_FALSE,&spnr,(const PetscInt**)&ia,(const PetscInt**)&ja,&done);CHKERRQ(ierr); if (!done) SETERRQ(PetscObjectComm((PetscObject)Bt),PETSC_ERR_ARG_WRONG,"Cannot restore IJ structure"); mumps->id.ICNTL(20) = 0; } ierr = MatDenseRestoreArray(X,&array);CHKERRQ(ierr); } else { /*--------- parallel case --------*/ PetscInt lsol_loc,nlsol_loc,*isol_loc,*idx,*iidx,*idxx,*isol_loc_save; MumpsScalar *sol_loc,*sol_loc_save; IS is_to,is_from; PetscInt k,proc,j,m; const PetscInt *rstart; Vec v_mpi,b_seq,x_seq; VecScatter scat_rhs,scat_sol; if (mumps->size > 1 && mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Parallel Schur complements not yet supported from PETSc\n"); /* create x_seq to hold local solution */ isol_loc_save = mumps->id.isol_loc; /* save it for MatSovle() */ sol_loc_save = mumps->id.sol_loc; lsol_loc = mumps->id.INFO(23); nlsol_loc = nrhs*lsol_loc; /* length of sol_loc */ ierr = PetscMalloc2(nlsol_loc,&sol_loc,nlsol_loc,&isol_loc);CHKERRQ(ierr); mumps->id.sol_loc = (MumpsScalar*)sol_loc; mumps->id.isol_loc = isol_loc; ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nlsol_loc,(PetscScalar*)sol_loc,&x_seq);CHKERRQ(ierr); /* copy rhs matrix B into vector v_mpi */ ierr = MatGetLocalSize(B,&m,NULL);CHKERRQ(ierr); ierr = MatDenseGetArray(B,&bray);CHKERRQ(ierr); ierr = VecCreateMPIWithArray(PetscObjectComm((PetscObject)B),1,nrhs*m,nrhs*M,(const PetscScalar*)bray,&v_mpi);CHKERRQ(ierr); ierr = MatDenseRestoreArray(B,&bray);CHKERRQ(ierr); /* scatter v_mpi to b_seq because MUMPS only supports centralized rhs */ /* idx: maps from k-th index of v_mpi to (i,j)-th global entry of B; iidx: inverse of idx, will be used by scattering xx_seq -> X */ ierr = PetscMalloc2(nrhs*M,&idx,nrhs*M,&iidx);CHKERRQ(ierr); ierr = MatGetOwnershipRanges(B,&rstart);CHKERRQ(ierr); k = 0; for (proc=0; procsize; proc++){ for (j=0; jmyid) { ierr = VecCreateSeq(PETSC_COMM_SELF,nrhs*M,&b_seq);CHKERRQ(ierr); ierr = ISCreateGeneral(PETSC_COMM_SELF,nrhs*M,idx,PETSC_COPY_VALUES,&is_to);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,nrhs*M,0,1,&is_from);CHKERRQ(ierr); } else { ierr = VecCreateSeq(PETSC_COMM_SELF,0,&b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_to);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,0,0,1,&is_from);CHKERRQ(ierr); } ierr = VecScatterCreate(v_mpi,is_from,b_seq,is_to,&scat_rhs);CHKERRQ(ierr); ierr = VecScatterBegin(scat_rhs,v_mpi,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); ierr = ISDestroy(&is_to);CHKERRQ(ierr); ierr = ISDestroy(&is_from);CHKERRQ(ierr); ierr = VecScatterEnd(scat_rhs,v_mpi,b_seq,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); if (!mumps->myid) { /* define rhs on the host */ ierr = VecGetArray(b_seq,&bray);CHKERRQ(ierr); mumps->id.rhs = (MumpsScalar*)bray; ierr = VecRestoreArray(b_seq,&bray);CHKERRQ(ierr); } /* 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)); /* scatter mumps distributed solution to petsc vector v_mpi, which shares local arrays with solution matrix X */ ierr = MatDenseGetArray(X,&array);CHKERRQ(ierr); ierr = VecPlaceArray(v_mpi,array);CHKERRQ(ierr); /* create scatter scat_sol */ ierr = PetscMalloc1(nlsol_loc,&idxx);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,nlsol_loc,0,1,&is_from);CHKERRQ(ierr); for (i=0; iid.sol_loc = sol_loc_save; mumps->id.isol_loc = isol_loc_save; ierr = PetscFree2(sol_loc,isol_loc);CHKERRQ(ierr); ierr = PetscFree2(idx,iidx);CHKERRQ(ierr); ierr = PetscFree(idxx);CHKERRQ(ierr); ierr = VecDestroy(&x_seq);CHKERRQ(ierr); ierr = VecDestroy(&v_mpi);CHKERRQ(ierr); ierr = VecDestroy(&b_seq);CHKERRQ(ierr); ierr = VecScatterDestroy(&scat_rhs);CHKERRQ(ierr); ierr = VecScatterDestroy(&scat_sol);CHKERRQ(ierr); } PetscFunctionReturn(0); } #if !defined(PETSC_USE_COMPLEX) /* input: F: numeric factor output: nneg: total number of negative pivots nzero: total number of zero pivots npos: (global dimension of F) - nneg - nzero */ PetscErrorCode MatGetInertia_SBAIJMUMPS(Mat F,int *nneg,int *nzero,int *npos) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; 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) *nneg = mumps->id.INFOG(12); if (nzero || npos) { if (mumps->id.ICNTL(24) != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"-mat_mumps_icntl_24 must be set as 1 for null pivot row detection"); if (nzero) *nzero = mumps->id.INFOG(28); if (npos) *npos = F->rmap->N - (mumps->id.INFOG(12) + mumps->id.INFOG(28)); } PetscFunctionReturn(0); } #endif PetscErrorCode MatFactorNumeric_MUMPS(Mat F,Mat A,const MatFactorInfo *info) { Mat_MUMPS *mumps =(Mat_MUMPS*)(F)->data; PetscErrorCode ierr; PetscBool isMPIAIJ; PetscFunctionBegin; if (mumps->id.INFOG(1) < 0) { if (mumps->id.INFOG(1) == -6) { ierr = PetscInfo2(A,"MatFactorNumeric is called with singular matrix structure, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); } ierr = PetscInfo2(A,"MatFactorNumeric is called after analysis phase fails, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); PetscFunctionReturn(0); } 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)) { /* A is centralized */ if (!mumps->myid) { mumps->id.a = (MumpsScalar*)mumps->val; } } else { mumps->id.a_loc = (MumpsScalar*)mumps->val; } PetscMUMPS_c(&mumps->id); if (mumps->id.INFOG(1) < 0) { if (A->erroriffailure) { SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2)); } else { if (mumps->id.INFOG(1) == -10) { /* numerically singular matrix */ ierr = PetscInfo2(F,"matrix is numerically singular, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; } else if (mumps->id.INFOG(1) == -13) { ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, cannot allocate required memory %d megabytes\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_OUTMEMORY; } else if (mumps->id.INFOG(1) == -8 || mumps->id.INFOG(1) == -9 || (-16 < mumps->id.INFOG(1) && mumps->id.INFOG(1) < -10) ) { ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d, problem with workarray \n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_OUTMEMORY; } else { ierr = PetscInfo2(F,"MUMPS in numerical factorization phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_OTHER; } } } 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)); (F)->assembled = PETSC_TRUE; mumps->matstruc = SAME_NONZERO_PATTERN; mumps->schur_factored = PETSC_FALSE; mumps->schur_inverted = PETSC_FALSE; /* just to be sure that ICNTL(19) value returned by a call from MatMumpsGetIcntl is always consistent */ if (!mumps->sym && mumps->id.ICNTL(19) && mumps->id.ICNTL(19) != 1) mumps->id.ICNTL(19) = 3; if (mumps->size > 1) { PetscInt lsol_loc; PetscScalar *sol_loc; ierr = PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&isMPIAIJ);CHKERRQ(ierr); /* distributed solution; Create x_seq=sol_loc for repeated use */ if (mumps->x_seq) { 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); } 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; mumps->id.sol_loc = (MumpsScalar*)sol_loc; ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,lsol_loc,sol_loc,&mumps->x_seq);CHKERRQ(ierr); } PetscFunctionReturn(0); } /* Sets MUMPS options from the options database */ PetscErrorCode PetscSetMUMPSFromOptions(Mat F, Mat A) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; PetscErrorCode ierr; PetscInt icntl,info[40],i,ninfo=40; 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): permutes to a zero-free diagonal and/or scale 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): computes a symmetric permutation in sequential analysis (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_9","ICNTL(9): computes the solution using A or A^T","None",mumps->id.ICNTL(9),&mumps->id.ICNTL(9),NULL);CHKERRQ(ierr); handled by MatSolveTranspose_MUMPS() */ 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 an error analysis (via -ksp_view)","None",mumps->id.ICNTL(11),&mumps->id.ICNTL(11),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_12","ICNTL(12): an ordering strategy for symmetric matrices (0 to 3)","None",mumps->id.ICNTL(12),&mumps->id.ICNTL(12),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_13","ICNTL(13): parallelism of the root node (enable ScaLAPACK) and its splitting","None",mumps->id.ICNTL(13),&mumps->id.ICNTL(13),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_14","ICNTL(14): percentage increase in the estimated working space","None",mumps->id.ICNTL(14),&mumps->id.ICNTL(14),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_19","ICNTL(19): computes the Schur complement","None",mumps->id.ICNTL(19),&mumps->id.ICNTL(19),NULL);CHKERRQ(ierr); if (mumps->id.ICNTL(19) <= 0 || mumps->id.ICNTL(19) > 3) { /* reset any schur data (if any) */ ierr = MatMumpsResetSchur_Private(mumps);CHKERRQ(ierr); } /* ierr = PetscOptionsInt("-mat_mumps_icntl_20","ICNTL(20): the format (dense or sparse) of the right-hand sides","None",mumps->id.ICNTL(20),&mumps->id.ICNTL(20),NULL);CHKERRQ(ierr); -- sparse rhs is not supported in PETSc API */ /* ierr = PetscOptionsInt("-mat_mumps_icntl_21","ICNTL(21): the distribution (centralized or distributed) of the solution vectors","None",mumps->id.ICNTL(21),&mumps->id.ICNTL(21),NULL);CHKERRQ(ierr); we only use distributed solution vector */ ierr = PetscOptionsInt("-mat_mumps_icntl_22","ICNTL(22): in-core/out-of-core factorization and solve (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): compute a solution of a deficient matrix and a null space basis","None",mumps->id.ICNTL(25),&mumps->id.ICNTL(25),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_26","ICNTL(26): drives the solution phase if a Schur complement matrix","None",mumps->id.ICNTL(26),&mumps->id.ICNTL(26),NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-mat_mumps_icntl_27","ICNTL(27): the blocking size for multiple right-hand sides","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): indicates which factors may be discarded during factorization","None",mumps->id.ICNTL(31),&mumps->id.ICNTL(31),NULL);CHKERRQ(ierr); /* ierr = PetscOptionsInt("-mat_mumps_icntl_32","ICNTL(32): performs the forward elemination of the right-hand sides during factorization","None",mumps->id.ICNTL(32),&mumps->id.ICNTL(32),NULL);CHKERRQ(ierr); -- not supported by PETSc API */ 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);CHKERRQ(ierr); ierr = PetscOptionsIntArray("-mat_mumps_view_info","request INFO local to each processor","",info,&ninfo,NULL);CHKERRQ(ierr); if (ninfo) { if (ninfo > 40) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_USER,"number of INFO %d must <= 40\n",ninfo); ierr = PetscMalloc1(ninfo,&mumps->info);CHKERRQ(ierr); mumps->ninfo = ninfo; for (i=0; i40) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_USER,"index of INFO %d must between 1 and 40\n",ninfo); else mumps->info[i] = info[i]; } } ierr = PetscOptionsEnd();CHKERRQ(ierr); PetscFunctionReturn(0); } PetscErrorCode PetscInitializeMUMPS(Mat A,Mat_MUMPS *mumps) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A), &mumps->myid);CHKERRQ(ierr); 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->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(20) = 0; /* rhs is in dense format */ mumps->id.ICNTL(21) = 1; /* distributed solution */ } /* schur */ mumps->id.size_schur = 0; mumps->id.listvar_schur = NULL; mumps->id.schur = NULL; mumps->sizeredrhs = 0; mumps->schur_pivots = NULL; mumps->schur_work = NULL; mumps->schur_sol = NULL; mumps->schur_sizesol = 0; mumps->schur_factored = PETSC_FALSE; mumps->schur_inverted = PETSC_FALSE; mumps->schur_sym = mumps->id.sym; PetscFunctionReturn(0); } PetscErrorCode MatFactorSymbolic_MUMPS_ReportIfError(Mat F,Mat A,const MatFactorInfo *info,Mat_MUMPS *mumps) { PetscErrorCode ierr; PetscFunctionBegin; if (mumps->id.INFOG(1) < 0) { if (A->erroriffailure) { SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_LIB,"Error reported by MUMPS in analysis phase: INFOG(1)=%d\n",mumps->id.INFOG(1)); } else { if (mumps->id.INFOG(1) == -6) { ierr = PetscInfo2(F,"matrix is singular in structure, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_STRUCT_ZEROPIVOT; } else if (mumps->id.INFOG(1) == -5 || mumps->id.INFOG(1) == -7) { ierr = PetscInfo2(F,"problem of workspace, INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_OUTMEMORY; } else { ierr = PetscInfo2(F,"Error reported by MUMPS in analysis phase: INFOG(1)=%d, INFO(2)=%d\n",mumps->id.INFOG(1),mumps->id.INFO(2));CHKERRQ(ierr); F->factorerrortype = MAT_FACTOR_OTHER; } } } 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 */ PetscErrorCode MatLUFactorSymbolic_AIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 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) { mumps->id.a = (MumpsScalar*)mumps->val; } 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) { mumps->id.a_loc = (MumpsScalar*)mumps->val; } /* MUMPS only supports centralized rhs. Create scatter scat_rhs for repeated use in MatSolve() */ if (!mumps->myid) { ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->N,&mumps->b_seq);CHKERRQ(ierr); ierr = ISCreateStride(PETSC_COMM_SELF,A->rmap->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 = MatCreateVecs(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); ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); F->ops->lufactornumeric = MatFactorNumeric_MUMPS; F->ops->solve = MatSolve_MUMPS; F->ops->solvetranspose = MatSolveTranspose_MUMPS; F->ops->matsolve = MatMatSolve_MUMPS; PetscFunctionReturn(0); } /* Note the Petsc r and c permutations are ignored */ PetscErrorCode MatLUFactorSymbolic_BAIJMUMPS(Mat F,Mat A,IS r,IS c,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 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) { mumps->id.a = (MumpsScalar*)mumps->val; } } 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) { mumps->id.a_loc = (MumpsScalar*)mumps->val; } /* 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 = MatCreateVecs(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); ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); 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 */ PetscErrorCode MatCholeskyFactorSymbolic_MUMPS(Mat F,Mat A,IS r,const MatFactorInfo *info) { Mat_MUMPS *mumps = (Mat_MUMPS*)F->data; 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) { mumps->id.a = (MumpsScalar*)mumps->val; } } 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) { mumps->id.a_loc = (MumpsScalar*)mumps->val; } /* 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 = MatCreateVecs(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); ierr = MatFactorSymbolic_MUMPS_ReportIfError(F,A,info,mumps);CHKERRQ(ierr); F->ops->choleskyfactornumeric = MatFactorNumeric_MUMPS; F->ops->solve = MatSolve_MUMPS; F->ops->solvetranspose = MatSolve_MUMPS; F->ops->matsolve = MatMatSolve_MUMPS; #if defined(PETSC_USE_COMPLEX) F->ops->getinertia = NULL; #else F->ops->getinertia = MatGetInertia_SBAIJMUMPS; #endif PetscFunctionReturn(0); } PetscErrorCode MatView_MUMPS(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscBool iascii; PetscViewerFormat format; Mat_MUMPS *mumps=(Mat_MUMPS*)A->data; 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) (sequential matrix ordering):%d \n",mumps->id.ICNTL(7));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," ICNTL(8) (scaling 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) (Schur 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) (solution 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) (absolute pivoting threshold): %g \n",mumps->id.CNTL(3));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," CNTL(4) (value 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 = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %g \n",mumps->myid,mumps->id.RINFO(1));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 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);CHKERRQ(ierr); 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);CHKERRQ(ierr); 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);CHKERRQ(ierr); 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);CHKERRQ(ierr); 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);CHKERRQ(ierr); if (mumps->ninfo && mumps->ninfo <= 40){ PetscInt i; for (i=0; ininfo; i++){ ierr = PetscViewerASCIIPrintf(viewer, " INFO(%d): \n",mumps->info[i]);CHKERRQ(ierr); ierr = PetscViewerASCIISynchronizedPrintf(viewer," [%d] %d \n",mumps->myid,mumps->id.INFO(mumps->info[i]));CHKERRQ(ierr); ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); } } ierr = PetscViewerASCIIPopSynchronized(viewer);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); ierr = PetscViewerASCIIPrintf(viewer," INFOG(28) (after factorization: number of null pivots encountered): %d\n",mumps->id.INFOG(28));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(29) (after factorization: effective number of entries in the factors (sum over all processors)): %d\n",mumps->id.INFOG(29));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(30, 31) (after solution: size in Mbytes of memory used during solution phase): %d, %d\n",mumps->id.INFOG(30),mumps->id.INFOG(31));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(32) (after analysis: type of analysis done): %d\n",mumps->id.INFOG(32));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(33) (value used for ICNTL(8)): %d\n",mumps->id.INFOG(33));CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer," INFOG(34) (exponent of the determinant if determinant is requested): %d\n",mumps->id.INFOG(34));CHKERRQ(ierr); } } } PetscFunctionReturn(0); } PetscErrorCode MatGetInfo_MUMPS(Mat A,MatInfoType flag,MatInfo *info) { Mat_MUMPS *mumps =(Mat_MUMPS*)A->data; 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); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorSetSchurIS_MUMPS(Mat F, IS is) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; const PetscInt *idxs; PetscInt size,i; PetscErrorCode ierr; PetscFunctionBegin; if (mumps->size > 1) { PetscBool ls,gs; ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); ls = mumps->myid ? (size ? PETSC_FALSE : PETSC_TRUE) : PETSC_TRUE; ierr = MPI_Allreduce(&ls,&gs,1,MPIU_BOOL,MPI_LAND,mumps->comm_mumps);CHKERRQ(ierr); if (!gs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MUMPS distributed parallel Schur complements not yet supported from PETSc\n"); } ierr = ISGetLocalSize(is,&size);CHKERRQ(ierr); if (mumps->id.size_schur != size) { ierr = PetscFree2(mumps->id.listvar_schur,mumps->id.schur);CHKERRQ(ierr); mumps->id.size_schur = size; mumps->id.schur_lld = size; ierr = PetscMalloc2(size,&mumps->id.listvar_schur,size*size,&mumps->id.schur);CHKERRQ(ierr); } ierr = ISGetIndices(is,&idxs);CHKERRQ(ierr); ierr = PetscMemcpy(mumps->id.listvar_schur,idxs,size*sizeof(PetscInt));CHKERRQ(ierr); /* MUMPS expects Fortran style indices */ for (i=0;iid.listvar_schur[i]++; ierr = ISRestoreIndices(is,&idxs);CHKERRQ(ierr); if (mumps->size > 1) { mumps->id.ICNTL(19) = 1; /* MUMPS returns Schur centralized on the host */ } else { if (F->factortype == MAT_FACTOR_LU) { mumps->id.ICNTL(19) = 3; /* MUMPS returns full matrix */ } else { mumps->id.ICNTL(19) = 2; /* MUMPS returns lower triangular part */ } } /* set a special value of ICNTL (not handled my MUMPS) to be used in the solve phase by PETSc */ mumps->id.ICNTL(26) = -1; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorCreateSchurComplement_MUMPS(Mat F,Mat* S) { Mat St; Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscScalar *array; #if defined(PETSC_USE_COMPLEX) PetscScalar im = PetscSqrtScalar((PetscScalar)-1.0); #endif PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); ierr = MatCreate(PETSC_COMM_SELF,&St);CHKERRQ(ierr); ierr = MatSetSizes(St,PETSC_DECIDE,PETSC_DECIDE,mumps->id.size_schur,mumps->id.size_schur);CHKERRQ(ierr); ierr = MatSetType(St,MATDENSE);CHKERRQ(ierr); ierr = MatSetUp(St);CHKERRQ(ierr); ierr = MatDenseGetArray(St,&array);CHKERRQ(ierr); if (!mumps->sym) { /* MUMPS always return a full matrix */ if (mumps->id.ICNTL(19) == 1) { /* stored by rows */ PetscInt i,j,N=mumps->id.size_schur; for (i=0;iid.schur[i*N+j]; #else PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; #endif array[j*N+i] = val; } } } else { /* stored by columns */ ierr = PetscMemcpy(array,mumps->id.schur,mumps->id.size_schur*mumps->id.size_schur*sizeof(PetscScalar));CHKERRQ(ierr); } } else { /* either full or lower-triangular (not packed) */ if (mumps->id.ICNTL(19) == 2) { /* lower triangular stored by columns */ PetscInt i,j,N=mumps->id.size_schur; for (i=0;iid.schur[i*N+j]; #else PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; #endif array[i*N+j] = val; array[j*N+i] = val; } } } else if (mumps->id.ICNTL(19) == 3) { /* full matrix */ ierr = PetscMemcpy(array,mumps->id.schur,mumps->id.size_schur*mumps->id.size_schur*sizeof(PetscScalar));CHKERRQ(ierr); } else { /* ICNTL(19) == 1 lower triangular stored by rows */ PetscInt i,j,N=mumps->id.size_schur; for (i=0;iid.schur[i*N+j]; #else PetscScalar val = mumps->id.schur[i*N+j].r + im*mumps->id.schur[i*N+j].i; #endif array[i*N+j] = val; array[j*N+i] = val; } } } } ierr = MatDenseRestoreArray(St,&array);CHKERRQ(ierr); *S = St; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorGetSchurComplement_MUMPS(Mat F,Mat* S) { Mat St; Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); /* It should be the responsibility of the user to handle different ICNTL(19) cases and factorization stages if they want to work with the raw data */ ierr = MatCreateSeqDense(PETSC_COMM_SELF,mumps->id.size_schur,mumps->id.size_schur,(PetscScalar*)mumps->id.schur,&St);CHKERRQ(ierr); *S = St; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorFactorizeSchurComplement_MUMPS(Mat F) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) { /* do nothing */ PetscFunctionReturn(0); } if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Parallel Schur complement not yet supported from PETSc"); ierr = MatMumpsFactorSchur_Private(mumps);CHKERRQ(ierr); PetscFunctionReturn(0); } PetscErrorCode MatFactorInvertSchurComplement_MUMPS(Mat F) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) { /* do nothing */ PetscFunctionReturn(0); } if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Parallel Schur complement not yet supported from PETSc"); ierr = MatMumpsInvertSchur_Private(mumps);CHKERRQ(ierr); PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorSolveSchurComplement_MUMPS(Mat F, Vec rhs, Vec sol) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; MumpsScalar *orhs; PetscScalar *osol,*nrhs,*nsol; PetscInt orhs_size,osol_size,olrhs_size; PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Parallel Schur complement not yet supported from PETSc"); /* swap pointers */ orhs = mumps->id.redrhs; olrhs_size = mumps->id.lredrhs; orhs_size = mumps->sizeredrhs; osol = mumps->schur_sol; osol_size = mumps->schur_sizesol; ierr = VecGetArray(rhs,&nrhs);CHKERRQ(ierr); ierr = VecGetArray(sol,&nsol);CHKERRQ(ierr); mumps->id.redrhs = (MumpsScalar*)nrhs; ierr = VecGetLocalSize(rhs,&mumps->sizeredrhs);CHKERRQ(ierr); mumps->id.lredrhs = mumps->sizeredrhs; mumps->schur_sol = nsol; ierr = VecGetLocalSize(sol,&mumps->schur_sizesol);CHKERRQ(ierr); /* solve Schur complement */ mumps->id.nrhs = 1; ierr = MatMumpsSolveSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); /* restore pointers */ ierr = VecRestoreArray(rhs,&nrhs);CHKERRQ(ierr); ierr = VecRestoreArray(sol,&nsol);CHKERRQ(ierr); mumps->id.redrhs = orhs; mumps->id.lredrhs = olrhs_size; mumps->sizeredrhs = orhs_size; mumps->schur_sol = osol; mumps->schur_sizesol = osol_size; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorSolveSchurComplementTranspose_MUMPS(Mat F, Vec rhs, Vec sol) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; MumpsScalar *orhs; PetscScalar *osol,*nrhs,*nsol; PetscInt orhs_size,osol_size; PetscErrorCode ierr; PetscFunctionBegin; if (!mumps->id.ICNTL(19)) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ORDER,"Schur complement mode not selected! You should call MatFactorSetSchurIS to enable it"); if (mumps->size > 1) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_SUP,"Parallel Schur complement not yet supported from PETSc"); /* swap pointers */ orhs = mumps->id.redrhs; orhs_size = mumps->sizeredrhs; osol = mumps->schur_sol; osol_size = mumps->schur_sizesol; ierr = VecGetArray(rhs,&nrhs);CHKERRQ(ierr); ierr = VecGetArray(sol,&nsol);CHKERRQ(ierr); mumps->id.redrhs = (MumpsScalar*)nrhs; ierr = VecGetLocalSize(rhs,&mumps->sizeredrhs);CHKERRQ(ierr); mumps->schur_sol = nsol; ierr = VecGetLocalSize(sol,&mumps->schur_sizesol);CHKERRQ(ierr); /* solve Schur complement */ mumps->id.nrhs = 1; mumps->id.ICNTL(9) = 0; ierr = MatMumpsSolveSchur_Private(mumps,PETSC_FALSE);CHKERRQ(ierr); mumps->id.ICNTL(9) = 1; /* restore pointers */ ierr = VecRestoreArray(rhs,&nrhs);CHKERRQ(ierr); ierr = VecRestoreArray(sol,&nsol);CHKERRQ(ierr); mumps->id.redrhs = orhs; mumps->sizeredrhs = orhs_size; mumps->schur_sol = osol; mumps->schur_sizesol = osol_size; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatFactorSetSchurComplementSolverType_MUMPS(Mat F, PetscInt sym) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; if (mumps->schur_factored && mumps->sym != mumps->schur_sym) { SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONG,"Cannot change the Schur solver! Schur complement data has been already factored"); } mumps->schur_sym = sym; PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatMumpsSetIcntl_MUMPS(Mat F,PetscInt icntl,PetscInt ival) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; mumps->id.ICNTL(icntl) = ival; PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetIcntl_MUMPS(Mat F,PetscInt icntl,PetscInt *ival) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *ival = mumps->id.ICNTL(icntl); PetscFunctionReturn(0); } /*@ 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(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsSetIcntl(Mat F,PetscInt icntl,PetscInt ival) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidLogicalCollectiveInt(F,ival,3); ierr = PetscTryMethod(F,"MatMumpsSetIcntl_C",(Mat,PetscInt,PetscInt),(F,icntl,ival));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ MatMumpsGetIcntl - Get 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() Output Parameter: . ival - value of MUMPS ICNTL(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetIcntl(Mat F,PetscInt icntl,PetscInt *ival) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidIntPointer(ival,3); ierr = PetscUseMethod(F,"MatMumpsGetIcntl_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); PetscFunctionReturn(0); } /* -------------------------------------------------------------------------------------------*/ PetscErrorCode MatMumpsSetCntl_MUMPS(Mat F,PetscInt icntl,PetscReal val) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; mumps->id.CNTL(icntl) = val; PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetCntl_MUMPS(Mat F,PetscInt icntl,PetscReal *val) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *val = mumps->id.CNTL(icntl); PetscFunctionReturn(0); } /*@ 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(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsSetCntl(Mat F,PetscInt icntl,PetscReal val) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidLogicalCollectiveReal(F,val,3); ierr = PetscTryMethod(F,"MatMumpsSetCntl_C",(Mat,PetscInt,PetscReal),(F,icntl,val));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ MatMumpsGetCntl - Get 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() Output Parameter: . val - value of MUMPS CNTL(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetCntl(Mat F,PetscInt icntl,PetscReal *val) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidLogicalCollectiveInt(F,icntl,2); PetscValidRealPointer(val,3); ierr = PetscUseMethod(F,"MatMumpsGetCntl_C",(Mat,PetscInt,PetscReal*),(F,icntl,val));CHKERRQ(ierr); PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetInfo_MUMPS(Mat F,PetscInt icntl,PetscInt *info) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *info = mumps->id.INFO(icntl); PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetInfog_MUMPS(Mat F,PetscInt icntl,PetscInt *infog) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *infog = mumps->id.INFOG(icntl); PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetRinfo_MUMPS(Mat F,PetscInt icntl,PetscReal *rinfo) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *rinfo = mumps->id.RINFO(icntl); PetscFunctionReturn(0); } PetscErrorCode MatMumpsGetRinfog_MUMPS(Mat F,PetscInt icntl,PetscReal *rinfog) { Mat_MUMPS *mumps =(Mat_MUMPS*)F->data; PetscFunctionBegin; *rinfog = mumps->id.RINFOG(icntl); PetscFunctionReturn(0); } /*@ MatMumpsGetInfo - Get MUMPS parameter INFO() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface - icntl - index of MUMPS parameter array INFO() Output Parameter: . ival - value of MUMPS INFO(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetInfo(Mat F,PetscInt icntl,PetscInt *ival) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidIntPointer(ival,3); ierr = PetscUseMethod(F,"MatMumpsGetInfo_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ MatMumpsGetInfog - Get MUMPS parameter INFOG() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface - icntl - index of MUMPS parameter array INFOG() Output Parameter: . ival - value of MUMPS INFOG(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetInfog(Mat F,PetscInt icntl,PetscInt *ival) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidIntPointer(ival,3); ierr = PetscUseMethod(F,"MatMumpsGetInfog_C",(Mat,PetscInt,PetscInt*),(F,icntl,ival));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ MatMumpsGetRinfo - Get MUMPS parameter RINFO() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface - icntl - index of MUMPS parameter array RINFO() Output Parameter: . val - value of MUMPS RINFO(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetRinfo(Mat F,PetscInt icntl,PetscReal *val) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidRealPointer(val,3); ierr = PetscUseMethod(F,"MatMumpsGetRinfo_C",(Mat,PetscInt,PetscReal*),(F,icntl,val));CHKERRQ(ierr); PetscFunctionReturn(0); } /*@ MatMumpsGetRinfog - Get MUMPS parameter RINFOG() Logically Collective on Mat Input Parameters: + F - the factored matrix obtained by calling MatGetFactor() from PETSc-MUMPS interface - icntl - index of MUMPS parameter array RINFOG() Output Parameter: . val - value of MUMPS RINFOG(icntl) Level: beginner References: . MUMPS Users' Guide .seealso: MatGetFactor(), MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog() @*/ PetscErrorCode MatMumpsGetRinfog(Mat F,PetscInt icntl,PetscReal *val) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidType(F,1); if (!F->factortype) SETERRQ(PetscObjectComm((PetscObject)F),PETSC_ERR_ARG_WRONGSTATE,"Only for factored matrix"); PetscValidRealPointer(val,3); ierr = PetscUseMethod(F,"MatMumpsGetRinfog_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 Use ./configure --download-mumps --download-scalapack --download-parmetis --download-metis --download-ptscotch to have PETSc installed with MUMPS Use -pc_type cholesky or lu -pc_factor_mat_solver_package mumps to us this direct solver Options Database Keys: + -mat_mumps_icntl_1 - ICNTL(1): output stream for error messages . -mat_mumps_icntl_2 - ICNTL(2): output stream for diagnostic printing, statistics, and warning . -mat_mumps_icntl_3 - ICNTL(3): output stream for global information, collected on the host . -mat_mumps_icntl_4 - ICNTL(4): level of printing (0 to 4) . -mat_mumps_icntl_6 - ICNTL(6): permutes to a zero-free diagonal and/or scale the matrix (0 to 7) . -mat_mumps_icntl_7 - ICNTL(7): computes a symmetric permutation in sequential analysis (0 to 7). 3=Scotch, 4=PORD, 5=Metis . -mat_mumps_icntl_8 - ICNTL(8): scaling strategy (-2 to 8 or 77) . -mat_mumps_icntl_10 - ICNTL(10): max num of refinements . -mat_mumps_icntl_11 - ICNTL(11): statistics related to an error analysis (via -ksp_view) . -mat_mumps_icntl_12 - ICNTL(12): an ordering strategy for symmetric matrices (0 to 3) . -mat_mumps_icntl_13 - ICNTL(13): parallelism of the root node (enable ScaLAPACK) and its splitting . -mat_mumps_icntl_14 - ICNTL(14): percentage increase in the estimated working space . -mat_mumps_icntl_19 - ICNTL(19): computes the Schur complement . -mat_mumps_icntl_22 - ICNTL(22): in-core/out-of-core factorization and solve (0 or 1) . -mat_mumps_icntl_23 - ICNTL(23): max size of the working memory (MB) that can allocate per processor . -mat_mumps_icntl_24 - ICNTL(24): detection of null pivot rows (0 or 1) . -mat_mumps_icntl_25 - ICNTL(25): compute a solution of a deficient matrix and a null space basis . -mat_mumps_icntl_26 - ICNTL(26): drives the solution phase if a Schur complement matrix . -mat_mumps_icntl_28 - ICNTL(28): use 1 for sequential analysis and ictnl(7) ordering, or 2 for parallel analysis and ictnl(29) ordering . -mat_mumps_icntl_29 - ICNTL(29): parallel ordering 1 = ptscotch, 2 = parmetis . -mat_mumps_icntl_30 - ICNTL(30): compute user-specified set of entries in inv(A) . -mat_mumps_icntl_31 - ICNTL(31): indicates which factors may be discarded during factorization . -mat_mumps_icntl_33 - ICNTL(33): compute determinant . -mat_mumps_cntl_1 - CNTL(1): relative pivoting threshold . -mat_mumps_cntl_2 - CNTL(2): stopping criterion of refinement . -mat_mumps_cntl_3 - CNTL(3): absolute pivoting threshold . -mat_mumps_cntl_4 - CNTL(4): value for static pivoting - -mat_mumps_cntl_5 - CNTL(5): fixation for null pivots Level: beginner Notes: When a MUMPS factorization fails inside a KSP solve, for example with a KSP_DIVERGED_PCSETUP_FAILED, one can find the MUMPS information about the failure by calling $ KSPGetPC(ksp,&pc); $ PCFactorGetMatrix(pc,&mat); $ MatMumpsGetInfo(mat,....); $ MatMumpsGetInfog(mat,....); etc. Or you can run with -ksp_error_if_not_converged and the program will be stopped and the information printed in the error message. .seealso: PCFactorSetMatSolverPackage(), MatSolverPackage, MatMumpsSetICntl(), MatMumpsGetIcntl(), MatMumpsSetCntl(), MatMumpsGetCntl(), MatMumpsGetInfo(), MatMumpsGetInfog(), MatMumpsGetRinfo(), MatMumpsGetRinfog(), KSPGetPC(), PCGetFactor(), PCFactorGetMatrix() M*/ static PetscErrorCode MatFactorGetSolverPackage_mumps(Mat A,const MatSolverPackage *type) { PetscFunctionBegin; *type = MATSOLVERMUMPS; PetscFunctionReturn(0); } /* MatGetFactor for Seq and MPI AIJ matrices */ static 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 = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); ierr = MatSetUp(B);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,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorFactorizeSchurComplement_C",MatFactorFactorizeSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurComplementSolverType_C",MatFactorSetSchurComplementSolverType_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_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 defined(PETSC_USE_COMPLEX) mumps->sym = 2; #else if (A->spd_set && A->spd) mumps->sym = 1; else mumps->sym = 2; #endif } /* set solvertype */ ierr = PetscFree(B->solvertype);CHKERRQ(ierr); ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); mumps->isAIJ = PETSC_TRUE; B->ops->destroy = MatDestroy_MUMPS; B->data = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } /* MatGetFactor for Seq and MPI SBAIJ matrices */ static 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 = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); ierr = MatSetUp(B);CHKERRQ(ierr); ierr = PetscNewLog(B,&mumps);CHKERRQ(ierr); if (isSeqSBAIJ) { mumps->ConvertToTriples = MatConvertToTriples_seqsbaij_seqsbaij; } else { mumps->ConvertToTriples = MatConvertToTriples_mpisbaij_mpisbaij; } B->ops->getinfo = MatGetInfo_External; B->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_MUMPS; B->ops->view = MatView_MUMPS; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorFactorizeSchurComplement_C",MatFactorFactorizeSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurComplementSolverType_C",MatFactorSetSchurComplementSolverType_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_MUMPS);CHKERRQ(ierr); B->factortype = MAT_FACTOR_CHOLESKY; #if defined(PETSC_USE_COMPLEX) mumps->sym = 2; #else if (A->spd_set && A->spd) mumps->sym = 1; else mumps->sym = 2; #endif /* set solvertype */ ierr = PetscFree(B->solvertype);CHKERRQ(ierr); ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); mumps->isAIJ = PETSC_FALSE; B->ops->destroy = MatDestroy_MUMPS; B->data = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } static 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 = PetscStrallocpy("mumps",&((PetscObject)B)->type_name);CHKERRQ(ierr); ierr = MatSetUp(B);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->getinfo = MatGetInfo_External; B->ops->view = MatView_MUMPS; ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSolverPackage_C",MatFactorGetSolverPackage_mumps);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurIS_C",MatFactorSetSchurIS_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorInvertSchurComplement_C",MatFactorInvertSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorCreateSchurComplement_C",MatFactorCreateSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorGetSchurComplement_C",MatFactorGetSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplement_C",MatFactorSolveSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSolveSchurComplementTranspose_C",MatFactorSolveSchurComplementTranspose_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorFactorizeSchurComplement_C",MatFactorFactorizeSchurComplement_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatFactorSetSchurComplementSolverType_C",MatFactorSetSchurComplementSolverType_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetIcntl_C",MatMumpsSetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetIcntl_C",MatMumpsGetIcntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsSetCntl_C",MatMumpsSetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetCntl_C",MatMumpsGetCntl_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfo_C",MatMumpsGetInfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetInfog_C",MatMumpsGetInfog_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfo_C",MatMumpsGetRinfo_MUMPS);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMumpsGetRinfog_C",MatMumpsGetRinfog_MUMPS);CHKERRQ(ierr); /* set solvertype */ ierr = PetscFree(B->solvertype);CHKERRQ(ierr); ierr = PetscStrallocpy(MATSOLVERMUMPS,&B->solvertype);CHKERRQ(ierr); mumps->isAIJ = PETSC_TRUE; B->ops->destroy = MatDestroy_MUMPS; B->data = (void*)mumps; ierr = PetscInitializeMUMPS(A,mumps);CHKERRQ(ierr); *F = B; PetscFunctionReturn(0); } PETSC_EXTERN PetscErrorCode MatSolverPackageRegister_MUMPS(void) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIBAIJ,MAT_FACTOR_LU,MatGetFactor_baij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPIBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_baij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATMPISBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_sbaij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQAIJ,MAT_FACTOR_LU,MatGetFactor_aij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_aij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQBAIJ,MAT_FACTOR_LU,MatGetFactor_baij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_baij_mumps);CHKERRQ(ierr); ierr = MatSolverPackageRegister(MATSOLVERMUMPS,MATSEQSBAIJ,MAT_FACTOR_CHOLESKY,MatGetFactor_sbaij_mumps);CHKERRQ(ierr); PetscFunctionReturn(0); }