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Parallel Molecular Dynamics: Implications for Massively Parallel Machines by Valerie E. Taylor; Rick L. Stevens; Kathryn E. Arnold is a Computer Science article available to read on EtoBox.

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Molecular dynamics simulation is a class of applications that require reducing the execution time of fixed-size problems. This reduction in execution time is important to drug design and protein interaction studies. Many implementations of parallel molecular dynamics have been developed, but very little work has addressed issues related to the use of machines with 50,000 processors for modest-sized problems in the range of 50,000 atoms. Current massively parallel machines present a major obstacle to achieving good performance: communication overhead. In this paper we quantify the communication latency and network bandwidth necessary to achieve 30-40% efficiency on future messagepassing machines with sizes on the order of tens of thousands of processors, for executing molecular dynamics problems with the same order of atoms. We derive an analytical model of a benchmark application that simulates a system of helium atoms executing on the Intel Touchstone Delta using an interaction decomposition method. This model is validated and used to extrapolate information on the startup time and network bandwidth. The results indicate that for an MPP with a four-dimensional mesh topology using

Who reads Parallel Molecular Dynamics: Implications for Massively Parallel Machines?

Author

Valerie E. Taylor; Rick L. Stevens; Kathryn E. Arnold

Publisher

Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0743-7315)

Published

1997

Language

EN

Field

Computer Science (Physical Sciences)