An Experimental Study across GPU DBMSes toward Cost-Effective Analytical Processing

Young-Kyoon SUH; Seounghyeon KIM; Joo-Young LEE; Hawon CHU; Junyoung AN; Kyong-Ha LEE

doi:10.1587/transinf.2020DAL0001

Special Section on Data Engineering and Information Management

An Experimental Study across GPU DBMSes toward Cost-Effective Analytical Processing

Young-Kyoon SUH, Seounghyeon KIM, Joo-Young LEE, Hawon CHU, Junyoung AN, Kyong-Ha LEE

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Keywords: GPU, database management systems (DBMS), analytical processing, cost-effectiveness, economic perspectives

JOURNAL FREE ACCESS

2021 Volume E104.D Issue 5 Pages 551-555

DOI https://doi.org/10.1587/transinf.2020DAL0001

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Abstract

In this letter we analyze the economic worth of GPU on analytical processing of GPU-accelerated database management systems (DBMSes). To this end, we conducted rigorous experiments with TPC-H across three popular GPU DBMSes. Consequently, we show that co-processing with CPU and GPU in the GPU DBMSes was cost-effective despite exposed concerns.

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