The Future of FPGA Acceleration in Datacenters and the Cloud

C. Bobda, Joel Mandebi Mbongue, P. Chow, M. Ewais, Naif Tarafdar, Juan Camilo Vega, Ken Eguro, Dirk Koch, Suranga Handagala, M. Leeser, M. Herbordt, Hafsah Shahzad, Peter Hofste, Burkhard Ringlein, Jakub Szefer, A. Sanaullah, R. Tessier
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引用次数: 41

Abstract

In this article, we survey existing academic and commercial efforts to provide Field-Programmable Gate Array (FPGA) acceleration in datacenters and the cloud. The goal is a critical review of existing systems and a discussion of their evolution from single workstations with PCI-attached FPGAs in the early days of reconfigurable computing to the integration of FPGA farms in large-scale computing infrastructures. From the lessons learned, we discuss the future of FPGAs in datacenters and the cloud and assess the challenges likely to be encountered along the way. The article explores current architectures and discusses scalability and abstractions supported by operating systems, middleware, and virtualization. Hardware and software security becomes critical when infrastructure is shared among tenants with disparate backgrounds. We review the vulnerabilities of current systems and possible attack scenarios and discuss mitigation strategies, some of which impact FPGA architecture and technology. The viability of these architectures for popular applications is reviewed, with a particular focus on deep learning and scientific computing. This work draws from workshop discussions, panel sessions including the participation of experts in the reconfigurable computing field, and private discussions among these experts. These interactions have harmonized the terminology, taxonomy, and the important topics covered in this manuscript.
FPGA加速在数据中心和云中的未来
在本文中,我们调查了现有的学术和商业努力,以提供现场可编程门阵列(FPGA)加速数据中心和云。目标是对现有系统进行批判性的回顾,并讨论它们从可重构计算早期带有pci连接FPGA的单个工作站到大规模计算基础设施中FPGA场的集成的演变。从经验教训中,我们讨论了fpga在数据中心和云中的未来,并评估了可能遇到的挑战。本文探讨了当前的体系结构,并讨论了操作系统、中间件和虚拟化所支持的可伸缩性和抽象。当基础设施在具有不同背景的租户之间共享时,硬件和软件安全性变得至关重要。我们回顾了当前系统的漏洞和可能的攻击场景,并讨论了缓解策略,其中一些会影响FPGA架构和技术。回顾了这些架构在流行应用中的可行性,特别关注深度学习和科学计算。这项工作借鉴了研讨会讨论、小组会议(包括可重构计算领域专家的参与)以及这些专家之间的私人讨论。这些相互作用协调了术语、分类法和本文所涵盖的重要主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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