Are FPGAs suitable for edge computing?

Saman Biookaghazadeh, Ming Zhao, Fengbo Ren

Research output: Contribution to conferencePaperpeer-review

58 Scopus citations


The rapid growth of Internet-of-things (IoT) and artificial intelligence applications have called forth a new computing paradigm–edge computing. In this paper, we study the suitability of deploying FPGAs for edge computing from the perspectives of throughput sensitivity to workload size, architectural adaptiveness to algorithm characteristics, and energy efficiency. This goal is accomplished by conducting comparison experiments on an Intel Arria 10 GX1150 FPGA and an Nvidia Tesla K40m GPU. The experiment results suggest that the key advantages of adopting FPGAs for edge computing over GPUs are three-fold: 1) FPGAs can provide a consistent throughput invariant to the size of application workload, which is critical to aggregating individual service requests from various IoT sensors; (2) FPGAs offer both spatial and temporal parallelism at a fine granularity and a massive scale, which guarantees a consistently high performance for accelerating both high-concurrency and high-dependency algorithms; and (3) FPGAs feature 3–4 times lower power consumption and up to 30.7 times better energy efficiency, offering better thermal stability and lower energy cost per functionality.

Original languageEnglish (US)
StatePublished - 2018
Event1st USENIX Workshop on Hot Topics in Edge Computing, HotEdge 2018, co-located with USENIX ATC 2018 - Boston, United States
Duration: Jul 10 2018 → …


Conference1st USENIX Workshop on Hot Topics in Edge Computing, HotEdge 2018, co-located with USENIX ATC 2018
Country/TerritoryUnited States
Period7/10/18 → …

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management


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