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)
Incoming Non-self Citations Over Time
Authors
- 1. Shweta Pandey (Indian Institute of Science)
- 2. Arkaprava Basu (Indian Institute of Science)
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}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,278 | BLAEQ: A Multigrid Index for Spatial Query on Geometry Data | 2025 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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