I/O limitations in parallel molecular dynamics

Authors:
Terry W. Clark;L. Ridgway Scott;Stanislaw Wlodek;J. Andrew McCammon
Affiliations:
Texas Center for Advanced Molecular Computation, University of Houston, Houston TX;Texas Center for Advanced Molecular Computation, University of Houston, Houston TX;Texas Center for Advanced Molecular Computation, University of Houston, Houston TX;Department of Chemistry and Biochemistry and Department of Pharmacology, University of California at San Diego, La Jolla, CA
Venue:
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Year:
1995

Citing 2
Cited 0

Working sets, cache sizes, and node granularity issues for large-scale multiprocessors

ISCA '93 Proceedings of the 20th annual international symposium on computer architecture
Fast parallel algorithms for short-range molecular dynamics

Journal of Computational Physics

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Abstract

We discuss data production rates and their impact on the performance of scientific applications using parallel computers. On one hand, too high rates of data production can be overwhelming, exceeding logistical capacities for transfer, storage and analysis. On the other hand, the rate limiting step in a computationally-based study should be the human-guided analysis, not the calculation. We present performance data for a biomolecular simulation of the enzyme, acetylcholinesterase, which uses the parallel molecular dynamics program EulerGROMOS. The actual production rates are compared against a typical time frame for results analysis where we show that the rate limiting step is the simulation, and that to overcome this will require improved output rates.