网络集群并行仿真的自适应同步技术

Ayose Falcón, P. Faraboschi, Daniel Ortega
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引用次数: 31

摘要

计算机集群是一种非常经济有效的高性能计算方法,但是模拟一个完整的集群仍然是一个开放的研究问题。显而易见的方法——并行化单个节点模拟器——既复杂又缓慢。组合单个并行模拟器意味着同步它们的时间进度。这可以通过各种并行离散事件模拟技术来实现,但不幸的是,任何直接的方法都会引入同步开销,导致单个节点的模拟速度降低两个数量级。本文提出了一种自动调整同步边界的自适应技术。通过在最不感兴趣的计算阶段动态放松精度,我们可以在精度损失很小的情况下显着提高性能。例如,在运行NAMD(一个并行分子动力学应用程序)的8节点集群的模拟中,我们显示了比确定性“真实”模拟的26倍的加速因子,精度误差小于1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Adaptive Synchronization Technique for Parallel Simulation of Networked Clusters
Computer clusters are a very cost-effective approach for high performance computing, but simulating a complete cluster is still an open research problem. The obvious approach - to parallelize individual node simulators - is complex and slow. Combining individual parallel simulators implies synchronizing their progress of time. This can be accomplished with a variety of parallel discrete event simulation techniques, but unfortunately any straightforward approach introduces a synchronization overhead causing up two orders of magnitude of slowdown with respect to the simulation speed of an individual node. In this paper we present a novel adaptive technique that automatically adjusts the synchronization boundaries. By dynamically relaxing accuracy over the least interesting computational phases we dramatically increase performance with a marginal loss of precision. For example, in the simulation of an 8-node cluster running NAMD (a parallel molecular dynamics application) we show an acceleration factor of 26x over the deterministic "ground truth" simulation, at less than a 1% accuracy error.
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