PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks & Fast Storage
Summary: PystachIO repurposes PyTorch tensor runtimes for distributed, storage-resident OLAP on GPU clusters with RDMA and NVMe. Its execution pipeline overlaps computation, network, and storage I/O, achieving up to 3× speedups over distributed GPU query engines. (summarized by gpt-5.6-luna on Aug 17 2026)
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Authors
- 1. Jigao Luo (Technical University of Darmstadt)
- 2. Nils Boeschen (German National Research Center for Information Technology; Technical University of Darmstadt)
- 3. Muhammad El-Hindi (Technical University of Munich)
- 4. Carsten Binnig (German National Research Center for Information Technology; Hessian Center for Artificial Intelligence; Technical University of Darmstadt)
BibTeX Citation
@article{luo_vldb26,
title = {{PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks \& Fast Storage}},
author = {Luo, Jigao and Boeschen, Nils and El-Hindi, Muhammad and Binnig, Carsten},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {2494--2507},
doi = {10.14778/3819518.3819566},
url = {https://doi.org/10.14778/3819518.3819566},
year = {2026}
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