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Exploiting Hardware Heterogeneity within the Same Instance Type of Amazon EC2
Zhonghong Ou, Hao Zhuang, Jukka K. Nurminen, and Antti Ylä-Jääski, Aalto University, Finland; Pan Hui, Deutsch Telekom Laboratories, Germany
Cloud computing providers might start with near-homogeneous hardware environment. Over time, the homogeneous environment will most likely evolve into heterogeneous one because of possible upgrades and replacement of outdated hardware. In turn, the hardware heterogeneity will result into performance variation. In this paper, we look into the hardware heterogeneity and the corresponding performance variation within the same instance type of Amazon Elastic Compute Cloud (Amazon EC2). Standard large instance is selected as the example. We find out that there exist three different sub-types of hardware configuration in the standard large instance. Through a set of detailed micro-benchmark and application-level benchmark measurements, we observe that the performance variation within the same sub-type of instance is relatively small, whilst the variation between different sub-types can be up to 60%. By selecting better-performing instances to complete the same task, end-users of Amazon EC2 platform can achieve up to 30% cost saving.
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