NDLI: System-Level Characterization of Datacenter Applications

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System-Level Characterization of Datacenter Applications

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System-Level Characterization of Datacenter Applications

Content Provider	ACM Digital Library
Author	Suri, Tameesh Awasthi, Manu Guz, Zvika Ghosh, Mrinmoy Balakrishnan, Vijay Shayesteh, Anahita
Abstract	In recent years, a number of benchmark suites have been created for the ``Big Data'' domain, and a number of such applications fit the client-server paradigm. A large volume of recent literature in characterizing ``Big Data'' applications have largely focused on two extremes of the characterization spectrum. On one hand, multiple studies have focused on client-side performance. These involve fine-tuning server-side parameters for an application to get the best client-side performance. On the other extreme, characterization focuses on picking one set of client-side parameters and then reporting the server microarchitectural statistics under those assumptions. While the two ends of the spectrum present interesting results, this paper argues that they are not enough, and in some cases, undesirable, to drive system-wide architectural decisions in datacenter design. This paper shows that for the purposes of designing an efficient datacenter, detailed microarchitectural characterization of ``Big Data'' applications is an overkill. It identifies four main system-level macro-architectural features and shows that these features are more representative of an application's system level behavior. To this end, a number of datacenter applications from a variety of benchmark suites are evaluated and classified into these previously identified macro-architectural features. Based on this analysis, the paper further shows that each application class will benefit from a very different server configuration leading to a highly efficient, cost-effective datacenter.
Starting Page	27
Ending Page	38
Page Count	12
File Format	PDF
ISBN	9781450332484
DOI	10.1145/2668930.2688059
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-01-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cassandra Datacenter performance Hadoop Workload characterization Datacenter Benchmarking Redis Performance measurement Memcache
Content Type	Text
Resource Type	Article

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