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Parallel Algorithms for Sparse Matrix Multiplication and Join-Aggregate Queries

Summary: Massively parallel algorithms for sparse matrix multiplication and for join-aggregate queries with tree-structured join hypergraphs and arbitrary output attributes. Achieves asymptotic improvements over prior work, with matrix multiplication optimal in the semiring model. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1820
Venue
PODS
Year
2020
Pagerank
5.6915726e-05
Overall Rank
7,143 | 51.00%
DOI
10.1145/3375395.3387657

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{hu_pods20,
        address = {New York, NY, USA},
        series = {{PODS} '20},
        title = {{Parallel Algorithms for Sparse Matrix Multiplication and Join-Aggregate Queries}},
        url = {https://dl.acm.org/doi/10.1145/3375395.3387657},
        doi = {10.1145/3375395.3387657},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Hu, Xiao and Yi, Ke},
        year = {2020}
}

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