TY - GEN

T1 - A discrete-continuous algorithm for molecular energy minimization

AU - Maier, R. S.

AU - Rosen, J. B.

AU - Xue, G. L.

N1 - Funding Information:
This research was supported in part by the Army Research Office contract number DAAL03-89-CO038 with the University of Minnesota Army High Performance Computing Research Center, the Air Force Office of Scientific Research grant AFOSR91-0147, and the Minnesota Supercomputer Institute.

PY - 1992/12/1

Y1 - 1992/12/1

N2 - We present a parallel algorithm for minimizing molecular energy potential functions applied to the case of pure Lennard-Jones clusters. The algorithm demonstrates the combination of discrete, latticebased optimization with continuous optimization (relaxation) techniques. The suggested approach is not restricted to the Lennard-Jones potential and is aimed at problems in which the potential of interest may be significantly more costly than the Lennard-Jones. The intended audience includes researchers interested in practical computational problems involving minimum energy cluster conformation, such as may arise in catalysis, and those interested in algorithm development. The advantage of the algorithm is that the time required to find the minimum-energy structure for a relatively large cluster reduces to that of an interactive session. Our parallel implementation is capable of determining the best-known, previously published binding energies for n ≤ 150 LJ clusters in a matter of seconds and has provided new results on minimum energies for clusters of up to n - 1000 atoms using a massivelyparallel processor, the Thinking Machines CM-5.

AB - We present a parallel algorithm for minimizing molecular energy potential functions applied to the case of pure Lennard-Jones clusters. The algorithm demonstrates the combination of discrete, latticebased optimization with continuous optimization (relaxation) techniques. The suggested approach is not restricted to the Lennard-Jones potential and is aimed at problems in which the potential of interest may be significantly more costly than the Lennard-Jones. The intended audience includes researchers interested in practical computational problems involving minimum energy cluster conformation, such as may arise in catalysis, and those interested in algorithm development. The advantage of the algorithm is that the time required to find the minimum-energy structure for a relatively large cluster reduces to that of an interactive session. Our parallel implementation is capable of determining the best-known, previously published binding energies for n ≤ 150 LJ clusters in a matter of seconds and has provided new results on minimum energies for clusters of up to n - 1000 atoms using a massivelyparallel processor, the Thinking Machines CM-5.

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U2 - 10.1109/superc.1992.236685

DO - 10.1109/superc.1992.236685

M3 - Conference contribution

AN - SCOPUS:84937015081

T3 - Proceedings of the International Conference on Supercomputing

SP - 778

EP - 786

BT - Proceedings of the 1992 ACM/IEEE conference on Supercomputing, Supercomputing 1992

A2 - Werner, Robert

PB - Association for Computing Machinery

T2 - 1992 ACM/IEEE conference on Supercomputing, Supercomputing 1992

Y2 - 16 November 1992 through 20 November 1992

ER -