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Abstract

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. A new parallel frontal solver that can significantly reduce the wallclock time required to solve these linear equation systems using parallel/vector supercomputers is presented. The algorithm exploits both multiprocessing and vector processing by using a multilevel approach in which frontal elimination is used for the partial factorization of each front. Results of several large-scale process simulation and optimization problems are presented.