IEICE TRANSACTIONS on Information
Workload-Driven Analysis on the Performance Characteristics of GPU-Accelerated DBMSes
Summary :
This letter conducts an in-depth empirical analysis of the influence of various query characteristics on the performance of modern GPU DBMSes. Our analysis reveals that, although they can efficiently process concurrent queries, the GPU DBMSes we consider still should address various performance concerns including n-way joins, aggregates, and selective scans.
- Publication
- IEICE TRANSACTIONS on Information Vol.E105-D No.11 pp.1984-1989
- Publication Date
- 2022/11/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2022EDL8008
- Type of Manuscript
- LETTER
- Category
- Data Engineering, Web Information Systems
Authors
Junyoung AN
Kyungpook National University
Young-Kyoon SUH
Kyungpook National University
Byungchul TAK
Kyungpook National University
Keyword
Latest Issue
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Junyoung AN, Young-Kyoon SUH, Byungchul TAK, "Workload-Driven Analysis on the Performance Characteristics of GPU-Accelerated DBMSes" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 11, pp. 1984-1989, November 2022, doi: 10.1587/transinf.2022EDL8008.
Abstract: This letter conducts an in-depth empirical analysis of the influence of various query characteristics on the performance of modern GPU DBMSes. Our analysis reveals that, although they can efficiently process concurrent queries, the GPU DBMSes we consider still should address various performance concerns including n-way joins, aggregates, and selective scans.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2022EDL8008/_p
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@ARTICLE{e105-d_11_1984,
author={Junyoung AN, Young-Kyoon SUH, Byungchul TAK, },
journal={IEICE TRANSACTIONS on Information},
title={Workload-Driven Analysis on the Performance Characteristics of GPU-Accelerated DBMSes},
year={2022},
volume={E105-D},
number={11},
pages={1984-1989},
abstract={This letter conducts an in-depth empirical analysis of the influence of various query characteristics on the performance of modern GPU DBMSes. Our analysis reveals that, although they can efficiently process concurrent queries, the GPU DBMSes we consider still should address various performance concerns including n-way joins, aggregates, and selective scans.},
keywords={},
doi={10.1587/transinf.2022EDL8008},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - Workload-Driven Analysis on the Performance Characteristics of GPU-Accelerated DBMSes
T2 - IEICE TRANSACTIONS on Information
SP - 1984
EP - 1989
AU - Junyoung AN
AU - Young-Kyoon SUH
AU - Byungchul TAK
PY - 2022
DO - 10.1587/transinf.2022EDL8008
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2022
AB - This letter conducts an in-depth empirical analysis of the influence of various query characteristics on the performance of modern GPU DBMSes. Our analysis reveals that, although they can efficiently process concurrent queries, the GPU DBMSes we consider still should address various performance concerns including n-way joins, aggregates, and selective scans.
ER -
English
