DOE: database offloading engine for accelerating SQL processing

doi:10.1007/s10619-023-07427-z

	DOE: database offloading engine for accelerating SQL processing
	Kong, Hao 1,2; Lu, Wenyan 1,3; Chen, Yan 3; Wu, Jingya 1,3; Zhang, Yu 3; Yan, Guihai 1,3; Li, Xiaowei 1
	2023-05-13
发表期刊	DISTRIBUTED AND PARALLEL DATABASES
ISSN	0926-8782
页码	25
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.
关键词	Database Hardware software co-design Heterogeneous system Analytic query processing
DOI	10.1007/s10619-023-07427-z
收录类别	SCI
语种	英语
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
WOS类目	Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS记录号	WOS:000987909800001
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21196
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.Inst Comp Technol, Chinese Acad Sci, State Key Lab Proc, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.YUSUR Technol Co Ltd, 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.