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H-Rocks: CPU-GPU accelerated Heterogeneous RocksDB on Persistent Memory

Summary: H-Rocks merges CPU-GPU to accelerate RocksDB on persistent memory, offloading hot-paths to the GPU while preserving compatibility via key-value versioning. Uses sub-batching and minimizes CPU-GPU data movement, delivering 3–18x YCSB gains over CPU-based pKVS. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
7102
Venue
SIGMOD
Year
2025
Pagerank
5.2755515e-05
Overall Rank
9,376 | 35.68%
DOI
10.1145/3709694

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{pandey_sigmod25,
        title = {{H-Rocks: CPU-GPU accelerated Heterogeneous RocksDB on Persistent Memory}},
        author = {Pandey, Shweta and Basu, Arkaprava},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3709694},
        url = {https://dl.acm.org/doi/10.1145/3709694},
        year = {2025}
}

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10,876 BLAEQ: A Multigrid Index for Spatial Query on Geometry Data 2025 VLDB 5.093636e-05
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