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KPU: Kernel Processing Unit for in-Memory Analytical Query Processing

文献类型：期刊论文

作者Wu, Jingya2; Lu, Wenyan2,3; Fan, Haishuang1,2; Kong, Hao1,2; Li, Xiaowei2,4; Yan, Guihai2,3
刊名IEEE TRANSACTIONS ON COMPUTERS
出版日期2025-08-01
卷号74期号:8页码:2702-2716
关键词Kernel Bandwidth Hardware Central Processing Unit Query processing Programming Parallel processing Computers Satellites Database domain-specific computer architecture programmability SQL SQL
ISSN号0018-9340
DOI10.1109/TC.2025.3569163
英文摘要Domain-specific architecture has greatly improved performance and energy efficiency in in-memory databases, especially for accelerating single-functional computing logic in analytic query processing, such as sort, join and aggregation. However, as data volumes surge exponentially, these dedicated accelerators are struggling to satisfy the burgeoning demand for handling intricate and multifaceted workloads. A major challenge lies in establishing a flexible framework that engages these 'coarse-grained' units without incurring extra overheads from hardware integration, programming, compilation, runtime and operating systems. In this paper, the kernel processing unit (KPU) is proposed to optimize CPU-accelerator heterogeneous systems for in-memory databases. KPU provides a unified interface to consolidate all database query operators. In terms of KPU hardware architecture, kernel customization and data transmission are two critical bottlenecks. To address the challenges, multiple independently designed homogeneous table cores are integrated to support flexible high-performance SQL queries, and a customized efficient data management system (DMS) works collaboratively to maximize the utilization of on-chip memory bandwidth. Additionally, a database application-specific KPU instruction set architecture (KISA) dedicated to parallel analytical query processing is proposed to enable parallel KPU programming. To trade off between accelerator computing capacity and data transfer latency, KPU designs an offloading mechanism to map SQL queries between the CPU and accelerator adaptively based on a performance model and a function simulator. The experiments demonstrate that KPU surpasses the general-purpose CPU and GPU by an average of 24.5x and 8.75x, respectively.
资助项目National Natural Science Foundation of China (NSFC)[62090024] ; National Natural Science Foundation of China (NSFC)[92373206] ; National Natural Science Foundation of China (NSFC)[62002340] ; National Natural Science Foundation of China (NSFC)[62090020] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB0660100] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB44030100]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:001531375700007
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/42072]  
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
作者单位1.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, SKLP, Beijing 100190, Peoples R China
3.YUSUR Technol Co Ltd, Beijing 100086, Peoples R China
4.Zhongguancun Lab, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Jingya,Lu, Wenyan,Fan, Haishuang,et al. KPU: Kernel Processing Unit for in-Memory Analytical Query Processing[J]. IEEE TRANSACTIONS ON COMPUTERS,2025,74(8):2702-2716.
APA Wu, Jingya,Lu, Wenyan,Fan, Haishuang,Kong, Hao,Li, Xiaowei,&Yan, Guihai.(2025).KPU: Kernel Processing Unit for in-Memory Analytical Query Processing.IEEE TRANSACTIONS ON COMPUTERS,74(8),2702-2716.
MLA Wu, Jingya,et al."KPU: Kernel Processing Unit for in-Memory Analytical Query Processing".IEEE TRANSACTIONS ON COMPUTERS 74.8(2025):2702-2716.

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来源：计算技术研究所

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