Power and Energy Characterization of an Open Source 25-Core Manycore Processor

Michael McKeown, Alexey Lavrov, Mohammad Shahrad, Paul J. Jackson, Yaosheng Fu, Jonathan Balkind, Tri M. Nguyen, Katie Lim, Yanqi Zhou, D. Wentzlaff
{"title":"Power and Energy Characterization of an Open Source 25-Core Manycore Processor","authors":"Michael McKeown, Alexey Lavrov, Mohammad Shahrad, Paul J. Jackson, Yaosheng Fu, Jonathan Balkind, Tri M. Nguyen, Katie Lim, Yanqi Zhou, D. Wentzlaff","doi":"10.1109/HPCA.2018.00070","DOIUrl":null,"url":null,"abstract":"The end of Dennard’s scaling and the looming power wall have made power and energy primary design goals for modern processors. Further, new applications such as cloud computing and Internet of Things (IoT) continue to necessitate increased performance and energy efficiency. Manycore processors show potential in addressing some of these issues. However, there is little detailed power and energy data on manycore processors. In this work, we carefully study detailed power and energy characteristics of Piton, a 25-core modern open source academic processor, including voltage versus frequency scaling, energy per instruction (EPI), memory system energy, network-on-chip (NoC) energy, thermal characteristics, and application performance and power consumption. This is the first detailed power and energy characterization of an open source manycore design implemented in silicon. The open source nature of the processor provides increased value, enabling detailed characterization verified against simulation and the ability to correlate results with the design and register transfer level (RTL) model. Additionally, this enables other researchers to utilize this work to build new power models, devise new research directions, and perform accurate power and energy research using the open source processor. The characterization data reveals a number of interesting insights, including that operand values have a large impact on EPI, recomputing data can be more energy efficient than loading it from memory, on-chip data transmission (NoC) energy is low, and insights on energy efficient multithreaded core design. All data collected and the hardware infrastructure used is open source and available for download at http://www.openpiton.org.","PeriodicalId":154694,"journal":{"name":"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on High Performance Computer Architecture (HPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCA.2018.00070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35

Abstract

The end of Dennard’s scaling and the looming power wall have made power and energy primary design goals for modern processors. Further, new applications such as cloud computing and Internet of Things (IoT) continue to necessitate increased performance and energy efficiency. Manycore processors show potential in addressing some of these issues. However, there is little detailed power and energy data on manycore processors. In this work, we carefully study detailed power and energy characteristics of Piton, a 25-core modern open source academic processor, including voltage versus frequency scaling, energy per instruction (EPI), memory system energy, network-on-chip (NoC) energy, thermal characteristics, and application performance and power consumption. This is the first detailed power and energy characterization of an open source manycore design implemented in silicon. The open source nature of the processor provides increased value, enabling detailed characterization verified against simulation and the ability to correlate results with the design and register transfer level (RTL) model. Additionally, this enables other researchers to utilize this work to build new power models, devise new research directions, and perform accurate power and energy research using the open source processor. The characterization data reveals a number of interesting insights, including that operand values have a large impact on EPI, recomputing data can be more energy efficient than loading it from memory, on-chip data transmission (NoC) energy is low, and insights on energy efficient multithreaded core design. All data collected and the hardware infrastructure used is open source and available for download at http://www.openpiton.org.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
开源25核多核处理器的功率和能量表征
登纳德缩放理论的终结和迫在眉睫的“功率墙”使得功耗和能耗成为现代处理器设计的首要目标。此外,云计算和物联网(IoT)等新应用继续要求提高性能和能源效率。多核处理器显示出解决这些问题的潜力。然而,关于多核处理器的详细功率和能量数据却很少。在这项工作中,我们仔细研究了Piton,一个25核现代开源学术处理器的详细功率和能量特性,包括电压与频率缩放,每条指令能量(EPI),存储系统能量,片上网络(NoC)能量,热特性,以及应用性能和功耗。这是在硅上实现的开源多核设计的第一个详细的功率和能量表征。处理器的开源特性提供了更高的价值,可以通过仿真验证详细的特性,并能够将结果与设计和注册传输级别(RTL)模型相关联。此外,这使其他研究人员能够利用这项工作建立新的功率模型,设计新的研究方向,并使用开源处理器进行准确的功率和能源研究。表征数据揭示了许多有趣的见解,包括操作数值对EPI有很大影响,重新计算数据可能比从内存加载数据更节能,片上数据传输(NoC)能量低,以及节能多线程核心设计的见解。收集的所有数据和使用的硬件基础设施都是开源的,可以从http://www.openpiton.org下载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Record-Replay Architecture as a General Security Framework LATTE-CC: Latency Tolerance Aware Adaptive Cache Compression Management for Energy Efficient GPUs Secure DIMM: Moving ORAM Primitives Closer to Memory OuterSPACE: An Outer Product Based Sparse Matrix Multiplication Accelerator WIR: Warp Instruction Reuse to Minimize Repeated Computations in GPUs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1