探索高性能计算应用程序到云平台的性能和映射

IEEE International Symposium on High-Performance Parallel Distributed Computing Pub Date : 2012-06-18 DOI:10.1145/2287076.2287093

Abhishek K. Gupta, L. Kalé, D. Milojicic, P. Faraboschi, R. Kaufmann, Verdi March, F. Gioachin, Chun Hui Suen, Bu-Sung Lee

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引用次数: 37

摘要

本文提出了一种优化高性能计算应用到一组混合专用资源和云资源映射的方案。首先，我们在专用集群和云上对应用程序性能进行表征，以获得应用程序签名。然后，我们提出了一种将这些签名与资源匹配的算法，从而使性能最大化，成本最小化。最后，我们展示了仿真结果，显示在一个具体的场景中，与非优化配置相比，我们提出的方案在只有10-15%的性能损失的情况下降低了60%的成本。我们还发现，使用瘦管理程序或操作系统级容器可以将云中的执行开销最小化到可以忽略不计的水平。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Exploring the performance and mapping of HPC applications to platforms in the cloud

This paper presents a scheme to optimize the mapping of HPC applications to a set of hybrid dedicated and cloud resources. First, we characterize application performance on dedicated clusters and cloud to obtain application signatures. Then, we propose an algorithm to match these signatures to resources such that performance is maximized and cost is minimized. Finally, we show simulation results revealing that in a concrete scenario our proposed scheme reduces the cost by 60% at only 10-15% performance penalty vs. a non optimized configuration. We also find that the execution overhead in cloud can be minimized to a negligible level using thin hypervisors or OS-level containers.

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IEEE International Symposium on High-Performance Parallel Distributed Computing

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