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GPU虚拟化相关技术研究综述

余时强^1,2,3, 张为华^1,2,3

(1.复旦大学软件学院, 上海 201203;2.
复旦大学上海市数据科学重点实验室, 上海 201203;3.
复旦大学并行处理研究所, 上海 201203)

Survey of GPU Virtualization

YU Shi-Qiang^1,2,3, ZHANG Wei-Hua^1,2,3

(1.Software School, Fudan University, Shanghai 201203, China;2.
Shanghai Key Laboratory of Data Science, Fudan University, Shanghai 201203, China;3.
Parallel Processing Institute, Fudan University, Shanghai 201203, China)

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本文已被：浏览 2134次下载 7872次
Received:March 06, 2017 Revised:March 23, 2017

中文摘要: 因为计算密集型应用的增多，亚马逊和阿里巴巴等公司的云平台开始引入GPU（Graphic processing unit）加速计算. 云平台支持多用户共享GPU的使用，可以提升GPU的利用效率，降低成本；也有利于GPU的有效管理. 通过虚拟机监视器以及各种软硬件的帮助，GPU虚拟化技术为云平台共享GPU提供了一种可行方案. 本文综合分析了GPU虚拟化技术的最近进展，先根据技术框架的共同点进行分类；然后从拓展性、共享性、使用透明性、性能、扩展性等方面对比分析，最后总结了GPU虚拟化的问题和发展方向.

中文关键词: GPU 虚拟化云计算

Abstract:The emergence of HPC cloud has inspired service provider to deploy GPU in the cloud ecosystem (e.g., Amazon EC2 GPU instance, Aliyun GPU Server). GPU as a computing accelerator is playing an indispensable role in clouding computing. Due to the intrinsic sharing feature of cloud, GPU sharing does not only boost the utilization, lower the cost, but also makes it easier to manage. GPU virtualization comes to solve this problem through Hypervisor and cooperation of software and hardware. This paper collects the methodologies of GPU virtualization and makes a classification and analysis. In addition, it concludes the existing problems and proposes the future works of GPU virtualization.

keywords: GPU virtualization cloud computing

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引用文本：
余时强,张为华.GPU虚拟化相关技术研究综述.计算机系统应用,2017,26(12):25-31
YU Shi-Qiang,ZHANG Wei-Hua.Survey of GPU Virtualization.COMPUTER SYSTEMS APPLICATIONS,2017,26(12):25-31

Author Name	Affiliation
YU Shi-Qiang	Software School, Fudan University, Shanghai 201203, China Shanghai Key Laboratory of Data Science, Fudan University, Shanghai 201203, China Parallel Processing Institute, Fudan University, Shanghai 201203, China
ZHANG Wei-Hua	Software School, Fudan University, Shanghai 201203, China Shanghai Key Laboratory of Data Science, Fudan University, Shanghai 201203, China Parallel Processing Institute, Fudan University, Shanghai 201203, China

Author Name	Affiliation
YU Shi-Qiang	Software School, Fudan University, Shanghai 201203, China Shanghai Key Laboratory of Data Science, Fudan University, Shanghai 201203, China Parallel Processing Institute, Fudan University, Shanghai 201203, China
ZHANG Wei-Hua	Software School, Fudan University, Shanghai 201203, China Shanghai Key Laboratory of Data Science, Fudan University, Shanghai 201203, China Parallel Processing Institute, Fudan University, Shanghai 201203, China