Publication
GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP
Nils Boeschen; Tobias Ziegler; Carsten Binnig
In: Proceedings of the ACM on Management of Data (PACMMOD), Vol. 2, No. 6, Pages 237:1-237:26, ACM Digital Library, 2024.
Abstract
In this paper, we suggest a novel GPU-in-data-path architecture that leverages a GPU to accelerate the I/O
path and thus can achieve almost in-memory bandwidth using SSDs. In this architecture, the main idea is to
stream data in heavy-weight compressed blocks from SSDs directly into the GPU and decompress it on-the-fly
as part of the table scan to inflate data before processing it by downstream query operators. Furthermore, we
employ novel GPU-optimized pruning techniques that help us further inflate the perceived read bandwidth.
In our evaluation, we show that the GPU-in-data-path architecture can achieve an effective bandwidth of up
to 100 GiB/s, surpassing existing in-memory systems’ capabilities.