Comput. Chem. Eng., 21, S439-S444 (1997)
For the simulation and optimization of large-scale chemical processes,
the overall computing time is often dominated by the time needed to solve
a large sparse system of linear equations. We describe here a parallel
frontal solver which can significantly reduce the wallclock time required
to solve these linear equation systems using parallel/vector supercomputers.
The algorithm exploits both multiprocessing and vector processing by using
a multifrontal-type approach in which frontal elimination is used for the
partial factorization of each front. The algorithm is based on a bordered
block-diagonal matrix form and thus its performance depends on the extent
to which this form can be obtained. Results on several large scale process
simulation and optimization problems are presented, with emphasis on the
effect of different matrix reorderings to achieve bordered block-diagonal
form.
Comput. Chem. Eng., 21, S439-S444 (1997)
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