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HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Summary: HetCache co-optimizes data placement and access paths across NVMe, host DRAM and GPU memory for heterogeneous CPU–GPU servers, treating bandwidth/costs as access-path- and device-dependent. Using proportional, access-path-aware caching, it yields 1.14–1.78× speedups on NVMe-resident workloads and near in-memory performance for hybrid CPU–GPU execution while greatly improving memory efficiency. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
497
Venue
CIDR
Year
2023
Pagerank
5.8651793e-05
Overall Rank
6,487 | 55.50%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{nicholson_cidr23,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '23},
        title = {{HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Nicholson, Hamish and Raza, Aunn and Chrysogelos, Periklis and Ailamaki, Anastasia},
        year = {2023}
}

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