A critical computational step in large-scale process simulation using
rigorous equation-based models is the solution of a sparse linear equation
system. Traditional sparse solvers based on indirect addressing are not
effective on supercomputers because they do not vectorize well. By relying
on vectorized dense matrix kernels, the multifrontal and frontal methods
provide much better performance, as demonstrated using several examples.
These examples are also used to compare the performance of frontal and
multifrontal solvers. On problems with good initial matrix orderings the
frontal method is most effective, while without a good initial ordering
the multifrontal method is attractive.
Comput. Chem. Eng., 20, 641-646 (1996)