云中的fpga

G. Constantinides
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引用次数: 13

摘要

越来越多的计算和存储正在远程云中进行,据估计,到2019年,公共云服务的支出将以每年19%以上的速度增长,达到1400亿美元。除了商用处理器、网络和存储基础设施之外,传统处理器时钟频率缩放的终结意味着特定应用的加速器需要与基于云的处理器协同工作,以不断提高计算性能和能源效率。事实上,图形处理单元(gpu)以及定制asic现在在云中被广泛使用,特别是在机器学习等计算密集型高价值应用中。在这个小组中,我们打算考虑在云中广泛部署fpga的机遇和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FPGAs in the Cloud
Ever greater amounts of computing and storage are happening remotely in the cloud, and it is estimated that spending on public cloud services will grow by over 19%/year to $140B in 2019. Besides commodity processors, network and storage infrastructure, the end of clock frequency scaling in traditional processors has meant that application-specific accelerators are required in tandem with cloud-based processors to deliver continued improvements in computational performance and energy efficiency. Indeed, graphics processing units (GPUs), as well as custom ASICs, are now widely used within the cloud, particularly for compute-intensive high-value applications like machine learning. In this panel, we intend to consider the opportunities and challenges for broad deployment of FPGAs in the cloud.
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