基于pcie的高性能FPGA-GPU-CPU异构通信方法

Su ZhaoPeng, Zhou Kuanjiu, Cui Kai, Hu Shaoqi
{"title":"基于pcie的高性能FPGA-GPU-CPU异构通信方法","authors":"Su ZhaoPeng, Zhou Kuanjiu, Cui Kai, Hu Shaoqi","doi":"10.1109/IWECAI50956.2020.00020","DOIUrl":null,"url":null,"abstract":"Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"PCIE-Based High-Performance FPGA-GPU-CPU Heterogeneous Communication Method\",\"authors\":\"Su ZhaoPeng, Zhou Kuanjiu, Cui Kai, Hu Shaoqi\",\"doi\":\"10.1109/IWECAI50956.2020.00020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.\",\"PeriodicalId\":364789,\"journal\":{\"name\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWECAI50956.2020.00020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWECAI50956.2020.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

异构计算作为一种特殊的并行计算方法,可以根据计算任务的特点发挥不同计算资源的能力,在提高服务器计算性能、能效比和实时性方面具有很大的优势。FPGA-GPU-CPU异构计算是为了实时处理海量数据而诞生的。然而,不同计算单元之间的通信瓶颈限制了异构平台的计算能力。针对上述问题,本文通过PCI Express总线将GPU和FPGA设备连接起来,使这些异构计算单元之间的数据可以在不借助系统CPU内存的情况下传输。并通过GPUDirect RDMA实现了以FPGA为主控制器的PCIe通信,改善了以GPU为主控制器的PCIe通信中读取速度慢的缺点。实验表明,与基于内存共享的通信相比,我们的效率提高了1.4倍,并且数据速率最接近最大理论带宽。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
PCIE-Based High-Performance FPGA-GPU-CPU Heterogeneous Communication Method
Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Named Entity Recognition Method with Word Position Research on Application of Smart Agriculture in Cotton Production Management Path Analysis of Using Big Data to Innovate Archives Management Model and Improve Service Ability The Air-Ground Integrated MIMO Cooperative Relay Beamforming Wireless Ad-Hoc Network Technology Research That Based on Maximum Ratio Combining Research and Exploration of Virtual Simulation Laboratory in Private Colleges and Universities
×
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