HP MLIB User's Guide Vol. 2 7th Ed.

Chapter 11 Introduction to Distributed SuperLU 777
Solve systems of linear equations pdgssvx/ pzgssvx, pdgssvx_ABglobal/pzgssvx_ABglobal
LUstruct_t, please refer to the general man page superlu_dist.
Arguments options
(input)
The structure defines the input parameters to control
how the LU decomposition will be performed. The
following fields should be defined for this structure:
• FACT (fact_t) Specifies whether or not the factored
form of the matrix A is supplied on entry, and if not,
how the matrix A should be factorized based on the
previous history.
= DOFACT: The matrix A will be factorized from
scratch.
Inputs: A, options->Equil, options->RowPerm,
options->ColPerm, options->ReplaceTinyPivot
Outputs: modified A (possibly row and/or column
scaled and/or permuted), all of ScalePermstruct
= SamePattern
: The matrix A will be factorized
assuming that a factorization of a matrix with the
same sparsity pattern was performed prior to this
one. Therefore, this factorization will reuse column
permutation vector ScalePermstruct->perm_c and
the elimination tree LUstruct->etree.
Inputs: A, options->Equil, options->RowPerm,
options->ReplaceTinyPivot,
ScalePermstruct->perm_c, LUstruct->etree
Outputs: modified A (possibly row and/or column
scaled and/or permuted), rest of ScalePermstruct
(DiagScale, R, C, perm_r), rest of LUstruct
(GLU_persist, Llu)
= SamePattern_SameRowPerm: The matrix A will
be factorized assuming that a factorization of a
matrix with the same sparsity pattern and similar
numerical values was performed prior to this one.
Therefore, this factorization will reuse both row and
column scaling factors R and C, and both row and
column permutation vectors perm_r and perm_c,
distributed data structure set up from the previous
symbolic factorization.