An Experimental Evaluation of Datacenter Workloads On Low-Power Embedded Micro Servers

Zhao, Yiran; Li, Shen; Hu, Shaohan; Wang, Hongwei; Yao, Shuochao; Shao, Huajie; Abdelzaher, Tarek F.

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https://hdl.handle.net/2142/91670 Copy

Description

Title

An Experimental Evaluation of Datacenter Workloads On Low-Power Embedded Micro Servers

Author(s)

• Zhao, Yiran
• Li, Shen
• Hu, Shaohan
• Wang, Hongwei
• Yao, Shuochao
• Shao, Huajie
• Abdelzaher, Tarek F.

Issue Date

2016-09-04

Keyword(s)

• Intel Edison
• Micro-server
• datacenter workload
• web service
• mapreduce

Abstract

This paper presents a comprehensive evaluation of an ultra-low power cluster, built upon the Intel Edison based micro servers. The improved performance and high energy efficiency of micro servers have driven both academia and industry to explore the possibility of replacing conventional brawny servers with a larger swarm of embedded micro servers. Existing attempts mostly focus on mobile-class micro servers, whose capacities are similar to mobile phones. We, on the other hand, target on sensor-class micro servers, which are originally intended for uses in wearable technologies, sensor networks, and Internet-of-Things. Although sensor-class micro servers have much less capacity, they are touted for minimal power consumption (< 1 Watt), which opens new possibilities of achieving higher energy efficiency in datacenter workloads. Our systematic evaluation of the Edison cluster and comparisons to conventional brawny clusters involve careful workload choosing and laborious parameter tuning, which ensures maximum server utilization and thus fair comparisons. Results show that the Edison cluster achieves up to 3.5× improvement on work-done-per-joule for web service applications and data-intensive MapReduce jobs. In terms of scalability, the Edison cluster scales linearly on the throughput of web service workloads, and also shows satisfactory scalability for MapReduce workloads despite coordination overhead.

Publisher

VLDB Endowment

Series/Report Name or Number

Proceedings of the VLDB Endowment 9, no. 9 (2016): 696-707.

ISSN

2150-8097

Type of Resource

text

Language

en

Permalink

http://hdl.handle.net/2142/91670

Sponsor(s)/Grant Number(s)

This research was supported in part by NSF grant 13-20209.

Copyright and License Information

Copyright 2016 VLDB Endowment 2150-8097/16/05. The license includes right to (a) publish and distribute the Work under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License (http://creativecommons.org/licenses/by-nc-nd/4.0/) and (b) obtain a Digital Object Identifier (“DOI”) for the Work.

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