GPU数据库核心技术综述  

Survey of Key Technologies in GPU Database System

作　　者：裴威 李战怀[1] 潘巍[1] PEI Wei;LI Zhan-Huai;PAN Wei(School of Computer Science,Northwestern Polytechnical University,Xi’an 710129,China;Jinzhou Medical University,Jinzhou 121001,China)

机构地区：[1]西北工业大学计算机学院,陕西西安710129 [2]锦州医科大学,辽宁锦州121001

出　　处：《软件学报》2021年第3期859-885,共27页Journal of Software

基　　金：国家自然科学基金(61732014,61672432);中央高校基本科研业务费专项资金(3102019DX1004)。

摘　　要：GPU以其超高速计算能力和超大数据处理带宽受到数据库厂商及研究人员的青睐,以GPU计算为核心的数据库分支(GDBMS)蓬勃发展,以其吞吐量大、响应时间短、成本低廉、易于扩展的特点,与人工智能、时空数据分析、数据可视化、商务智能交互融合能力,彻底改变了数据分析领域的格局.将对GDBMS的四大核心组件——查询编译器、查询处理器、查询优化器和存储管理器进行综述,希望促进未来的GDBMS研究和商业应用.In recent years,GPU is favored by database manufacturers and researchers for its ultra-high-speed computing capacity and huge data processing bandwidth.The database branch—GPU accelerating database or GPU database(GDBMS)is developing vigorously.With the characteristics of high throughput,low response time,high cost performance,and easy to expand,integrated with artificial intelligence(AI),business intelligence(BI),spatial-temporal data analysis,data visualization,GDBMS have the potential to change the world pattern of data analysis field.This study surveys the four core components of GDBMS:query compiler,query processor,query optimizer,and storage manager,hoping to promote the future research and commercial application of GDBMS.

关 键 词：GPU 数据库 查询编译器 查询处理器 查询优化器 存储管理器 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]