Hardware-Conscious Stream Processing: A Survey

被引:12
|
作者
Zhang, Shuhao [1 ]
Zhang, Feng [2 ]
Wu, Yingjun [3 ]
He, Bingsheng [1 ]
Johns, Paul [1 ]
机构
[1] Natl Univ Singapore, Singapore, Singapore
[2] Renmin Univ China, Beijing, Peoples R China
[3] Amazon Web Serv, Seattle, WA USA
基金
中国国家自然科学基金;
关键词
Computer architecture - Data Analytics - Computer hardware - Computer hardware description languages - Data handling;
D O I
10.1145/3385658.3385662
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Data stream processing systems (DSPSs) enable users to express and run stream applications to continuously process data streams. To achieve real-time data analytics, recent researches keep focusing on optimizing the system latency and throughput. Witnessing the recent great achievements in the computer architecture community, researchers and practitioners have investigated the potential of adoption hardware-conscious stream processing by better utilizing modern hardware capacity in DSPSs. In this paper, we conduct a systematic survey of recent work in the field, particularly along with the following three directions: 1) computation optimization, 2) stream I/O optimization, and 3) query deployment. Finally, we advise on potential future research directions.
引用
收藏
页码:18 / 29
页数:12
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