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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)

Paper ID
7486
Venue
SIGMOD
Year
2026
Pagerank
5.093636e-05
Overall Rank
10,292 | 29.39%
DOI
10.1145/3802113

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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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