NDLI: Exploring Memory Hierarchy to Improve Scientific Data Read Performance

Content Provider	IEEE Xplore Digital Library
Author	Wenzhao Zhang Houjun Tang Xiaocheng Zou Harenberg, S. Qing Liu Klasky, S. Samatova, N.F.
Copyright Year	2015
Description	Author affiliation: Comput. Sci. & Math. Div., Oak Ridge Nat. Lab., Oak Ridge, TN, USA (Qing Liu; Klasky, S.) \|\| Dept. of Comput. Sci., North Carolina State Univ., Raleigh, NC, USA (Wenzhao Zhang; Houjun Tang; Xiaocheng Zou; Harenberg, S.; Samatova, N.F.)
Abstract	Improving read performance is one of the major challenges with speeding up scientific data analytic applications. Utilizing the memory hierarchy is one major line of researches to address the read performance bottleneck. Related methods usually combine solide-state-drives(SSDs) with dynamic random-access memory(DRAM) and/or parallel file system(PFS) to mitigate the speed and space gap between DRAM and PFS. However, these methods are unable to handle key performance issues plaguing SSDs, namely read contention that may cause up to 50% performance reduction. In this paper, we propose a framework that exploits the memory hierarchy resource to address the read contention issues involved with SSDs. The framework employs a general purpose online read algorithm that able to detect and utilize memory hierarchy resource to relieve the problem. To maintain a near optimal operating environment for SSDs, the framework is able to orchastrate data chunks across different memory layers to facilitate the read algorithm. Compared to existing tools, our framework achieves up to 50% read performance improvement when tested on datasets from real-world scientific simulations.
Starting Page	66
Ending Page	69
File Size	588284
Page Count	4
File Format	PDF
ISBN	9781467365987
DOI	10.1109/CLUSTER.2015.18
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Random access memory Predictive models Computational modeling Mathematical model Data models Combustion Hydrodynamics SSD scientific data read contention memory hierarchy
Content Type	Text
Resource Type	Article

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