DRAF: A Low-Power DRAM-Based Reconfigurable Acceleration Fabric

Mingyu Gao, Christina Delimitrou, Dimin Niu, Krishna T. Malladi, Hongzhong Zheng, Bob Brennan, C. Kozyrakis
{"title":"DRAF: A Low-Power DRAM-Based Reconfigurable Acceleration Fabric","authors":"Mingyu Gao, Christina Delimitrou, Dimin Niu, Krishna T. Malladi, Hongzhong Zheng, Bob Brennan, C. Kozyrakis","doi":"10.1145/3007787.3001191","DOIUrl":null,"url":null,"abstract":"FPGAs are a popular target for application-specific accelerators because they lead to a good balance between flexibility and energy efficiency. However, FPGA lookup tables introduce significant area and power overheads, making it difficult to use FPGA devices in environments with tight cost and power constraints. This is the case for datacenter servers, where a modestly-sized FPGA cannot accommodate the large number of diverse accelerators that datacenter applications need. This paper introduces DRAF, an architecture for bit-level reconfigurable logic that uses DRAM subarrays to implement dense lookup tables. DRAF overlaps DRAM operations like bitline precharge and charge restoration with routing within the reconfigurable routing fabric to minimize the impact of DRAM latency. It also supports multiple configuration contexts that can be used to quickly switch between different accelerators with minimal latency. Overall, DRAF trades off some of the performance of FPGAs for significant gains in area and power. DRAF improves area density by 10x over FPGAs and power consumption by more than 3x, enabling DRAF to satisfy demanding applications within strict power and cost constraints. While accelerators mapped to DRAF are 2-3x slower than those in FPGAs, they still deliver a 13x speedup and an 11x reduction in power consumption over a Xeon core for a wide range of datacenter tasks, including analytics and interactive services like speech recognition.","PeriodicalId":6634,"journal":{"name":"2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA)","volume":"28 1","pages":"506-518"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3007787.3001191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

FPGAs are a popular target for application-specific accelerators because they lead to a good balance between flexibility and energy efficiency. However, FPGA lookup tables introduce significant area and power overheads, making it difficult to use FPGA devices in environments with tight cost and power constraints. This is the case for datacenter servers, where a modestly-sized FPGA cannot accommodate the large number of diverse accelerators that datacenter applications need. This paper introduces DRAF, an architecture for bit-level reconfigurable logic that uses DRAM subarrays to implement dense lookup tables. DRAF overlaps DRAM operations like bitline precharge and charge restoration with routing within the reconfigurable routing fabric to minimize the impact of DRAM latency. It also supports multiple configuration contexts that can be used to quickly switch between different accelerators with minimal latency. Overall, DRAF trades off some of the performance of FPGAs for significant gains in area and power. DRAF improves area density by 10x over FPGAs and power consumption by more than 3x, enabling DRAF to satisfy demanding applications within strict power and cost constraints. While accelerators mapped to DRAF are 2-3x slower than those in FPGAs, they still deliver a 13x speedup and an 11x reduction in power consumption over a Xeon core for a wide range of datacenter tasks, including analytics and interactive services like speech recognition.
草案:基于低功耗dram的可重构加速结构
fpga是特定应用加速器的热门目标,因为它们在灵活性和能源效率之间取得了良好的平衡。然而,FPGA查找表引入了大量的面积和功耗开销,使得在成本和功耗限制严格的环境中使用FPGA器件变得困难。这就是数据中心服务器的情况,一个中等大小的FPGA无法容纳数据中心应用程序所需的大量不同的加速器。本文介绍了位级可重构逻辑的架构draft,该架构使用DRAM子阵列实现密集查找表。DRAF将位线预充和充电恢复等DRAM操作与可重构路由结构中的路由重叠,以最大限度地减少DRAM延迟的影响。它还支持多个配置上下文,可用于以最小的延迟在不同的加速器之间快速切换。总的来说,draft牺牲了fpga的一些性能,在面积和功率方面获得了显著的收益。与fpga相比,draft的面积密度提高了10倍,功耗降低了3倍以上,使draft能够在严格的功率和成本限制下满足苛刻的应用。虽然映射到draft的加速器比fpga慢2-3倍,但它们仍然比至强核心提供13倍的加速和11倍的功耗降低,用于广泛的数据中心任务,包括分析和语音识别等交互服务。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信