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DOE: database offloading engine for accelerating SQL processing

文献类型：期刊论文

作者Kong, Hao2,3; Lu, Wenyan1,3; Chen, Yan1; Wu, Jingya1,3; Zhang, Yu1; Yan, Guihai1,3; Li, Xiaowei3
刊名DISTRIBUTED AND PARALLEL DATABASES
出版日期2023-05-13
页码25
关键词Database Hardware software co-design Heterogeneous system Analytic query processing
ISSN号0926-8782
DOI10.1007/s10619-023-07427-z
英文摘要The CPU-Accelerator heterogeneous systems have demonstrated performance and efficiency benefits on DBMSs. However, the CPU-Cache-DRAM architecture can not fully utilize the bandwidth of DRAMs such that in-memory approach get limited improvement. To overcome this drawback, it is non-trivial to customize efficient domain-specific accelerators and efficiently shuttle data between the host memory space and accelerator. But even if high-performance accelerators are available for DBMS, it is challenging to integrate the software with accelerator non-intrusively. To address these problems, we propose a hardware-software co-designed system, database offloading engine (DOE), which contains hardware accelerator architecture-Conflux for effective SQL operation offloading, and a software DOE programming platform-DP2 for application integration and seamless harness of the computing power. We subtly partition each well-known relational operator, such as filter, join, group by, aggregate, and sort, and dynamically map these operators on multiple kernels in parallel. The DOE kernels work in streaming processing mode, over which the microarchitecture aggressively exploits data parallelism and memory bandwidth. The experiment results show that DOE achieves more than 100x and 10x performance improvement compared with PostgreSQL and MonetDB respectively.
资助项目National Natural Science Foundation of China (NSFC)[62002340] ; National Natural Science Foundation of China (NSFC)[61872336] ; National Natural Science Foundation of China (NSFC)[62090020] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB44030100] ; Youth Innovation Promotion Association CAS[Y201923]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000987909800001
出版者SPRINGER
源URL[http://119.78.100.204/handle/2XEOYT63/21195]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Lu, Wenyan; Yan, Guihai; Li, Xiaowei
作者单位1.YUSUR Technol Co Ltd, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Inst Comp Technol, Chinese Acad Sci, State Key Lab Proc, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Kong, Hao,Lu, Wenyan,Chen, Yan,et al. DOE: database offloading engine for accelerating SQL processing[J]. DISTRIBUTED AND PARALLEL DATABASES,2023:25.
APA Kong, Hao.,Lu, Wenyan.,Chen, Yan.,Wu, Jingya.,Zhang, Yu.,...&Li, Xiaowei.(2023).DOE: database offloading engine for accelerating SQL processing.DISTRIBUTED AND PARALLEL DATABASES,25.
MLA Kong, Hao,et al."DOE: database offloading engine for accelerating SQL processing".DISTRIBUTED AND PARALLEL DATABASES (2023):25.

入库方式： OAI收割

来源：计算技术研究所

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