GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP

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.

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Publication Details

Journal
Proceedings of the ACM on Management of Data
Published
2024-12-18
DOI
https://doi.org/10.1145/3698812
Citations
6
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
2.09
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article

GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP

Nils Boeschen, Carsten Binnig, Tobias Ziegler
6 citations
Proceedings of the ACM on Management of Data
Advanced Data Storage Technologies
2.09
article

GOLAP: A GPU-in-Data-Path Architecture for High-Speed OLAP

Nils Boeschen, Carsten Binnig, Tobias Ziegler
article en
6 citations

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.

Proceedings of the ACM on Management of DataVol. 2(6)
Hess (United States) (US), Technische Universität Darmstadt (DE)
Affordable and clean energy
Openalex Percentile: Top 12%
Advanced Data Storage Technologies
2.09
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