GPU-accelerated data management under the test of time
Summary: Empirical analysis showing PCIe interconnects—rather than GPU compute—dominate performance limits for GPU-accelerated DBMS and weaken benefits of late materialization and data-sharing across evolving interconnects, architectures, and workloads. Proposes a hybrid eager/lazy materialization, aggressive data-sharing, and an HTAP system design that removes software-level interference, demonstrating recovered throughput and memory-bus–friendly OLAP-style transfer optimizations. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Aunn Raza (EPFL)
- 2. Periklis Chrysogelos (EPFL)
- 3. Angelos Christos Anadiotis (EPFL)
- 4. Panagiotis Sioulas (EPFL)
- 5. Vladimir Indjic (EPFL)
- 6. Anastasia Ailamaki (EPFL; RAW Labs)
BibTeX Citation
@inproceedings{raza_cidr20,
address = {Amsterdam, Netherlands},
series = {{CIDR} '20},
title = {{GPU-accelerated data management under the test of time}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Raza, Aunn and Chrysogelos, Periklis and Anadiotis, Angelos Christos and Sioulas, Panagiotis and Indjic, Vladimir and Ailamaki, Anastasia},
year = {2020}
}
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