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A Survey on Graph Processing Accelerators: Challenges and Opportunities

文献类型：期刊论文

作者Liu, Cheng1,2; He, Bingsheng2; Zheng, Long3,4,5; Gui, Chuang-Yi3,4,5; Jin, Hai3,4,5; Liao, Xiao-Fei3,4,5; Chen, Xin-Yu2
刊名JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
出版日期2019-04-01
卷号34期号:2页码:339-371
关键词graph processing accelerator domain-specific architecture performance energy efficiency
ISSN号1000-9000
DOI10.1007/s11390-019-1914-z
英文摘要Graph is a well known data structure to represent the associated relationships in a variety of applications, e.g., data science and machine learning. Despite a wealth of existing efforts on developing graph processing systems for improving the performance and/or energy efficiency on traditional architectures, dedicated hardware solutions, also referred to as graph processing accelerators, are essential and emerging to provide the benefits significantly beyond what those pure software solutions can offer. In this paper, we conduct a systematical survey regarding the design and implementation of graph processing accelerators. Specifically, we review the relevant techniques in three core components toward a graph processing accelerator: preprocessing, parallel graph computation, and runtime scheduling. We also examine the benchmarks and results in existing studies for evaluating a graph processing accelerator. Interestingly, we find that there is not an absolute winner for all three aspects in graph acceleration due to the diverse characteristics of graph processing and the complexity of hardware configurations. We finally present and discuss several challenges in details, and further explore the opportunities for the future research.
资助项目National Key Research and Development Program of China[2018YFB1003502] ; National Natural Science Foundation of China[61825202] ; National Natural Science Foundation of China[61832006] ; National Natural Science Foundation of China[61628204] ; National Natural Science Foundation of China[61702201]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000462960800007
出版者SCIENCE PRESS
源URL[http://119.78.100.204/handle/2XEOYT63/4283]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zheng, Long
作者单位1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
2.Natl Univ Singapore, Sch Comp, Singapore 117418, Singapore
3.Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Cluster & Grid Comp Lab, Wuhan 430074, Hubei, Peoples R China
4.Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Serv Comp Technol & Syst Lab, Wuhan 430074, Hubei, Peoples R China
5.Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Natl Engn Res Ctr Big Data Technol & Syst, Wuhan 430074, Hubei, Peoples R China
推荐引用方式
GB/T 7714		 Liu, Cheng,He, Bingsheng,Zheng, Long,et al. A Survey on Graph Processing Accelerators: Challenges and Opportunities[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2019,34(2):339-371.
APA Liu, Cheng.,He, Bingsheng.,Zheng, Long.,Gui, Chuang-Yi.,Jin, Hai.,...&Chen, Xin-Yu.(2019).A Survey on Graph Processing Accelerators: Challenges and Opportunities.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,34(2),339-371.
MLA Liu, Cheng,et al."A Survey on Graph Processing Accelerators: Challenges and Opportunities".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 34.2(2019):339-371.

入库方式： OAI收割

来源：计算技术研究所

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