@inproceedings{8ff9616d325c4af8b07a3446f04b0a07,
title = "Empirical evaluation across multiple GPU-accelerated DBMSes",
abstract = "In this paper we conduct an empirical study across modern GPU-accelerated DBMSes with TPC-H workloads. Our rigorous experiments demonstrate that the studied DBMSes appear to utilize GPU resource effectively but do not scale well with growing databases nor have full capability to process some complex analytical queries. Thus, we claim that the GPU DBMSes still need to be further engineered to achieve a better analytical performance.",
keywords = "empirical evaluation, GPU-accelerated DBMS, scalability, TPC-H",
author = "Hawon Chu and Seounghyun Kim and Lee, \{Joo Young\} and Suh, \{Young Kyoon\}",
note = "Publisher Copyright: {\textcopyright} 2020 ACM.; 16th International Workshop on Data Management on New Hardware, DaMoN 2020 ; Conference date: 15-06-2020",
year = "2020",
month = jun,
day = "15",
doi = "10.1145/3399666.3399907",
language = "English",
series = "Proceedings of the 16th International Workshop on Data Management on New Hardware, DaMoN 2020",
publisher = "Association for Computing Machinery",
booktitle = "Proceedings of the 16th International Workshop on Data Management on New Hardware, DaMoN 2020",
}