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

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Young-Kyoon Suh, Seounghyeon Kim, Joo-Young Lee, Hawon Chu, Jun Young An, Kyong-Ha Lee

Published: 2021, Last Modified: 08 Jan 2026IEICE Trans. Inf. Syst. 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
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.