跨多个gpu加速dbms的经验评估

Proceedings of the 16th International Workshop on Data Management on New Hardware Pub Date : 2020-06-14 DOI:10.1145/3399666.3399907

Hawon Chu, Seounghyun Kim, Joo-Young Lee, Young-Kyoon Suh

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引用次数: 5

摘要

在本文中，我们对具有TPC-H工作负载的现代gpu加速dbms进行了实证研究。我们严格的实验表明，所研究的dbms似乎可以有效地利用GPU资源，但不能很好地扩展数据库，也不能完全处理一些复杂的分析查询。因此，我们声称GPU dbms仍然需要进一步设计以实现更好的分析性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Empirical evaluation across multiple GPU-accelerated DBMSes

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.

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Proceedings of the 16th International Workshop on Data Management on New Hardware

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