P-MOSS: Scheduling Main-Memory Indexes Over NUMA Servers Using Next Token Prediction
Summary: P-MOSS learns NUMA-aware query/core/data placement for main-memory B+-trees, using PMU statistics plus a Decision Transformer framed as next-token prediction. Unlike hand-tuned schedulers, it adapts across hardware/workloads and reports up to 6x throughput over traditional schedules. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Yeasir Rayhan (Purdue University)
- 2. Walid G. Aref (Purdue University)
BibTeX Citation
@inproceedings{rayhan_sigmod26,
title = {{P-MOSS: Scheduling Main-Memory Indexes Over NUMA Servers Using Next Token Prediction}},
author = {Rayhan, Yeasir and Aref, Walid G.},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786675},
url = {https://dl.acm.org/doi/10.1145/3786675},
year = {2026}
}
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