Catalyst: Optimizing Cache Management for Large In-memory Key-value Systems
Summary: Catalyst addresses metadata-management bottlenecks that make fine-grained cache policies unscalable for large in-memory key-value stores. Its efficient metadata structure and GPU offloading improve Memcached throughput and latency by up to 4.3×. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kefei Wang (Gannon University)
- 2. Feng Chen (Louisiana State University)
BibTeX Citation
@article{wang_vldb23,
title = {{Catalyst: Optimizing Cache Management for Large In-memory Key-value Systems}},
author = {Wang, Kefei and Chen, Feng},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {13},
pages = {4339--4352},
doi = {10.14778/3625054.3625068},
url = {https://doi.org/10.14778/3625054.3625068},
year = {2023}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,816 | Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation | 2025 | SIGMOD | 8.0959781e-05 |
| 8,475 | Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees | 2025 | SIGMOD | 5.4171036e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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