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An energy-efficient system on a programmable chip platform for cloud applications.

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Title: An energy-efficient system on a programmable chip platform for cloud applications.
Authors: Wang, Xu1 wang2002xu@gmail.com, Zhu, Yongxin1,2 yongxin.zhu@nus.edu.sg, Ha, Yajun3 elehy@nus.edu.sg, Qiu, Meikang4 mqiu@pace.edu, Huang, Tian1 huantian@ic.sjtu.edu.cn, Si, Xueming5 sxm@fudan.edu.cn, Wu, Jiangxing6
Source: Journal of Systems Architecture. May2017, Vol. 76, p117-132. 16p.
Subjects: Cloud computing, Programmable circuits, Performance evaluation, Energy consumption, Electronic data processing
Abstract: Traditional cloud service providers build large data-centers with a huge number of connected commodity computers to meet the ever-growing demand on performance. However, the growth potential of these data-centers is limited by their corresponding energy consumption and thermal issues. Energy efficiency becomes a key issue of building large-scale cloud computing centers. To solve this issue, we propose a standalone SOPC (System on a Programmable Chip) based platform for cloud applications. We improve the energy efficiency for cloud computing platforms with two techniques. First, we propose a massive-sessions optimized TCP/IP hardware stack using a macro-pipeline architecture. It enables the hardware acceleration of pipelining execution of network packet offloading and application level data processing. This achieves higher energy efficiency while maintaining peak performance. Second, we propose a online dynamic scheduling strategy. It can reconfigure or shut down FPGA nodes according to workload variance to reduce the runtime energy consumption in a standalone SOPC based reconfigurable cluster system. Two case studies including a webserver application and a cloud based ECG (electrocardiogram) classification application are developed to validate the effectiveness of the proposed platform. Evaluation results show that our SOPC based cloud computing platform can achieve up to 418X improvement in terms of energy efficiency over commercial cloud systems. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Systems Architecture is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 123258053
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: An energy-efficient system on a programmable chip platform for cloud applications.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Xu%22">Wang, Xu</searchLink><relatesTo>1</relatesTo><i> wang2002xu@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Zhu%2C+Yongxin%22">Zhu, Yongxin</searchLink><relatesTo>1,2</relatesTo><i> yongxin.zhu@nus.edu.sg</i><br /><searchLink fieldCode="AR" term="%22Ha%2C+Yajun%22">Ha, Yajun</searchLink><relatesTo>3</relatesTo><i> elehy@nus.edu.sg</i><br /><searchLink fieldCode="AR" term="%22Qiu%2C+Meikang%22">Qiu, Meikang</searchLink><relatesTo>4</relatesTo><i> mqiu@pace.edu</i><br /><searchLink fieldCode="AR" term="%22Huang%2C+Tian%22">Huang, Tian</searchLink><relatesTo>1</relatesTo><i> huantian@ic.sjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Si%2C+Xueming%22">Si, Xueming</searchLink><relatesTo>5</relatesTo><i> sxm@fudan.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Jiangxing%22">Wu, Jiangxing</searchLink><relatesTo>6</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Systems+Architecture%22">Journal of Systems Architecture</searchLink>. May2017, Vol. 76, p117-132. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Programmable+circuits%22">Programmable circuits</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+evaluation%22">Performance evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink>
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  Data: Traditional cloud service providers build large data-centers with a huge number of connected commodity computers to meet the ever-growing demand on performance. However, the growth potential of these data-centers is limited by their corresponding energy consumption and thermal issues. Energy efficiency becomes a key issue of building large-scale cloud computing centers. To solve this issue, we propose a standalone SOPC (System on a Programmable Chip) based platform for cloud applications. We improve the energy efficiency for cloud computing platforms with two techniques. First, we propose a massive-sessions optimized TCP/IP hardware stack using a macro-pipeline architecture. It enables the hardware acceleration of pipelining execution of network packet offloading and application level data processing. This achieves higher energy efficiency while maintaining peak performance. Second, we propose a online dynamic scheduling strategy. It can reconfigure or shut down FPGA nodes according to workload variance to reduce the runtime energy consumption in a standalone SOPC based reconfigurable cluster system. Two case studies including a webserver application and a cloud based ECG (electrocardiogram) classification application are developed to validate the effectiveness of the proposed platform. Evaluation results show that our SOPC based cloud computing platform can achieve up to 418X improvement in terms of energy efficiency over commercial cloud systems. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Systems Architecture is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.sysarc.2016.11.009
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        Text: English
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        PageCount: 16
        StartPage: 117
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      – SubjectFull: Cloud computing
        Type: general
      – SubjectFull: Programmable circuits
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      – SubjectFull: Performance evaluation
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      – SubjectFull: Energy consumption
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      – SubjectFull: Electronic data processing
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      – TitleFull: An energy-efficient system on a programmable chip platform for cloud applications.
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              Text: May2017
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