Pipeline Group Optimization on Disaggregated Systems
Summary: Group concurrent pipelines by data-access similarity to fetch shared data once from disaggregated memory to compute nodes. With caching and a fast communication layer, this reduces redundant transfers and significantly boosts multi-query performance versus isolated pipelines. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Andreas Geyer (Technical University of Dresden)
- 2. Alexander Krause (Technical University of Dresden)
- 3. Dirk Habich (Technical University of Dresden)
- 4. Wolfgang Lehner (Technical University of Dresden)
BibTeX Citation
@inproceedings{geyer_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{Pipeline Group Optimization on Disaggregated Systems}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Geyer, Andreas and Krause, Alexander and Habich, Dirk and Lehner, Wolfgang},
year = {2023}
}
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