DMCA
ANALYSIS ON DISTRIBUTED MEMORY PARALLEL SYSTEMS
BibTeX
@MISC{Yang_analysison,
author = {Chao Yang and Padma Raghavan and Lloyd Arrowood and Donald W Noid and Bobby G Sumpter and Robert E Tuzun and Chao Yang and Padma Raghavan and Lloyd Arrowood and Donald W. Noid and Bobby G. Sumpter and Robert E. Tuzun},
title = {ANALYSIS ON DISTRIBUTED MEMORY PARALLEL SYSTEMS},
year = {}
}
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Abstract
A parallel computational scheme for analyzing large-scale molecular vibration on distributed memory computing platforms is presented in this paper. This method combines the implicitly restarted Lanczos algorithm with a state-of-art parallel sparse direct solver to compute a set of low frequency vibrational modes for molecular systems containing tens of thousands of atoms. Although the original motivation for developing such a scheme was to overcome memory limitations on traditional sequential and shared memory machines, our computational experiments show that with a careful parallel design and data partitioning scheme one can achieve scalable performance on lightly coupled distributed memory parallel systems. In particular, we demonstrate performance enhancement achieved by using the latency tolerant “selective inversion" scheme in the sparse triangular substitution phase of the computation.
Keyphrases
analysis distributed memory parallel system low frequency vibrational mode shared memory machine computational experiment latency tolerant selective inversion quot distributed memory parallel system molecular system distributed memory state-of-art parallel sparse direct solver lanczos algorithm sparse triangular substitution phase memory limitation large-scale molecular vibration parallel computational scheme performance enhancement original motivation scalable performance careful parallel design
