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HyperMR: Efficient Hypergraph-enhanced Matrix Storage on Compute-in-Memory Architecture

Summary: HyperMR uses hypergraph-based CIM storage; two CIM-tailored NP-hard objectives; solved by two-phase partitioning. An access-aware hypergraph generator handles diverse matrices; results show gains up to 34.9% and 29.65% on synthetic queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7041
Venue
SIGMOD
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,378 | 27.81%
DOI
10.1145/3709695

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