SPALM: A Sparsity-Pattern-Adaptive Library for Matrices
Summary: SPALM brings matrix multiplication into database workflows via a sparsity-pattern-adaptive algorithm that selects techniques per fine-grained region without prior pattern knowledge. It delivers up to 34× CPU speedups and integrates declaratively with DuckDB, avoiding data movement and privacy costs. (summarized by gpt-5.6-luna on Jul 26 2026)
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Authors
- 1. Junyoung Kim (Columbia University)
- 2. Kenneth A. Ross (Columbia University)
BibTeX Citation
@inproceedings{kim_sigmod26,
title = {{SPALM: A Sparsity-Pattern-Adaptive Library for Matrices}},
author = {Kim, Junyoung and Ross, Kenneth A.},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3802113},
url = {https://dl.acm.org/doi/10.1145/3802113},
year = {2026}
}
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