Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 07029 | |
Number of page(s) | 8 | |
Section | T7 - Clouds, virtualisation & containers | |
DOI | https://doi.org/10.1051/epjconf/201921407029 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921407029
FaaM: FPGA-as-a-Microservice - A Case Study for Data Compression
1
University of Florida, Electrical and Computer Engineering,
Gainesville,
FL 32608,
USA
2
Dell EMC, 1 Dell Way, Round Rock,
TX 78682,
USA
* Corresponding author: davido@ufl.edu
Published online: 17 September 2019
Field-programmable gate arrays (FPGAs) have largely been used in communication and high-performance computing and given the recent advances in big data and emerging trends in cloud computing (e.g., serverless [18]), FPGAs are increasingly being introduced into these domains (e.g., Microsoft’s datacenters [6] and Amazon Web Services [10]). To address these domains’ processing needs, recent research has focused on using FPGAs to accelerate workloads, ranging from analytics and machine learning to databases and network function virtualization. In this paper, we present an ongoing effort to realize a high-performance FPGA-as-a-microservice (FaaM) architecture for the cloud. We discuss some of the technical challenges and propose several solutions for efficiently integrating FPGAs into virtualized environments. Our case study deploying a multithreaded, multi-user compression as a microservice using the FaaM architecture indicate that microservices-based FPGA acceleration can sustain high-performance compared to straightforward implementation with minimal to no communication overhead despite the hardware abstraction.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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