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Data management systems on GPUs

Authors :
Anand Kumar
Ryan Wheeler
Yi-Cheng Tu
Ran Rui
Di Yu
Source :
SSDBM
Publication Year :
2013
Publisher :
ACM, 2013.

Abstract

The past decade has witnessed the popularity of push-based data management systems, in which the query executor passively receives data from either remote data sources (e.g., sensors) or I/O processes that scan database tables/files from local storage. Unlike traditional relational database management system (RDBMS) architectures that are mostly I/O-bound, push-based database systems often become heavily computation-bound since the data arrival rate could be very high. In this paper, we argue that modern multi-core hardware, especially Graphics Processing Units (GPU), provide the most cost-effective computing platform to catch up with the large amount of data streamed into a push-based database system. Based on that, we will open discussions on how to design and implement a query processing engine for such systems that run on GPUs.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Accession number :
edsair.doi...........b7c27b7f4cd58e3c8788679c8466fb41
Full Text :
https://doi.org/10.1145/2484838.2484871