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Quantifying the latency benefits of near-edge and in-network FPGA acceleration
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Cooke, Ryan A. and Fahmy, Suhaib A. (2020) Quantifying the latency benefits of near-edge and in-network FPGA acceleration. In: International Workshop on Edge Systems, Analytics and Networking (EdgeSys), Heraklion, Greece, 27 Apr 2020. Published in: EdgeSys '20: Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking pp. 7-12. ISBN 9781450371322/20/04. doi:10.1145/3378679.3394534
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Official URL: https://doi.org/10.1145/3378679.3394534
Abstract
Transmitting data to cloud datacenters in distributed IoT applications introduces significant communication latency, but is often the only feasible solution when source nodes are computationally limited. To address latency concerns, cloudlets, in-network computing, and more capable edge nodes are all being explored as a way of moving processing capability towards the edge of the network. Hardware acceleration using Field Programmable Gate Arrays (FPGAs) is also seeing increased interest due to reduced computation latency and improved efficiency. This paper evaluates the the implications of these offloading approaches using a case study neural network based image classification application, quantifying both the computation and communication latency resulting from different platform choices. We consider communication latency including the ingestion of packets for processing on the target platform, showing that this varies significantly with the choice of platform. We demonstrate that emerging in-network accelerator approaches offer much improved and predictable performance as well as better scaling to support multiple data sources.
| Item Type: | Conference Item (Paper) | |||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
| Library of Congress Subject Headings (LCSH): | Field programmable gate arrays , Cloud computing , Internet of things, Electronic data processing -- Distributed processing | |||||||||
| Journal or Publication Title: | EdgeSys '20: Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking | |||||||||
| Publisher: | Association for Computing Machinery | |||||||||
| ISBN: | 9781450371322/20/04 | |||||||||
| Official Date: | 27 April 2020 | |||||||||
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| Page Range: | pp. 7-12 | |||||||||
| DOI: | 10.1145/3378679.3394534 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Reuse Statement (publisher, data, author rights): | "© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in EdgeSys '20: Proceedings of the Third ACM International Workshop on Edge Systems, Analytics and Networking. April 2020 Pages 7–12 https://doi.org/10.1145/3378679.3394534 | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| Copyright Holders: | Association for Computing Machinery | |||||||||
| Date of first compliant deposit: | 21 April 2020 | |||||||||
| Date of first compliant Open Access: | 21 April 2020 | |||||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | |||||||||
| Title of Event: | International Workshop on Edge Systems, Analytics and Networking (EdgeSys) | |||||||||
| Type of Event: | Workshop | |||||||||
| Location of Event: | Heraklion, Greece | |||||||||
| Date(s) of Event: | 27 Apr 2020 | |||||||||
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