SALLM-Tune: Leveraging fine-tuned LLMs for semantic-aware knob tuning in LSM-based KV stores
Authors:
- Tianren ZhouTZTianren Zhou
- Chao LiCLChao Li
- Xiaowei ChenXCXiaowei Chen
- Yao ChenYCYao Chen
- Qian WeiQWQian Wei
- Zhaoyan ShenZSZhaoyan Shen
- Zhiyong ZhangZZZhiyong Zhang
- 6 August 2026
- journal article
- Published by Elsevier in Journal of Systems Architecture
- Vol. 180
Abstract
No abstract availableFunding Information
- Natural Science Foundation of Shandong Province (ZR2024LZH004)
- Taishan Scholar Project of Shandong Province
- National Natural Science Foundation of China (624B2091)
- National Natural Science Foundation of China (62272271)
This publication has 12 references indexed in Scilit:
- Can Modern LLMs Tune and Configure LSM-based Key-Value Stores?2024
- A survey on large language model (LLM) security and privacy: The Good, The Bad, and The UglyHigh-Confidence Computing, 2024
- A Semantic-Integrated LSM-Tree-Based Key–Value Storage Engine for Blockchain SystemsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023
- Time-tired compaction: An elastic compaction scheme for LSM-tree based time-series databaseAdvanced Engineering Informatics, 2023
- K2vTune: A workload-aware configuration tuning for RocksDBInformation Processing & Management, 2023
- Re-LSM2022
- DremelProceedings of the ACM on Measurement and Analysis of Computing Systems, 2022
- High-Dimensional Bayesian Optimization with Multi-Task Learning for RocksDB2021
- Efficient Data and Indexing Structure for Blockchains in Enterprise Systems2018
- CassandraACM SIGOPS Operating Systems Review, 2010