5 papers
[Extended Version] ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads
Junfeng Liu, Haoxuan Xie, Siqiang Luo
Key-value stores underpin a wide range of applications due to their simplicity and efficiency. Log-Structured Merge Trees (LSM-trees) dominate as their underlying structure, excell…
On 10x Better Scalability: KV Stores Scale Up KV Cache
Weiping Yu, Ye Jiarui, He Mengke +2
Large language models (LLMs) rely on Key-Value (KV) cache to reduce time-to-first-token (TTFT) latency, but existing disk-based KV cache systems using file-per-object layouts suffe…
Evaluating Learned Indexes in LSM-tree Systems: Benchmarks,Insights and Design Choices
Junfeng Liu, Jiarui Ye, Mengshi Chen +2
LSM-tree-based data stores are widely used in industry due to their exceptional performance. However, as data volumes grow, efficiently querying large-scale databases becomes incre…
RAGDoll: Efficient Offloading-based Online RAG System on a Single GPU
Weiping Yu, Ningyi Liao, Siqiang Luo +1
Retrieval-Augmented Generation (RAG) enhances large language model (LLM) generation quality by incorporating relevant external knowledge. However, deploying RAG on consumer-grade p…
Aster: Enhancing LSM-structures for Scalable Graph Database
Dingheng Mo, Junfeng Liu, Fan Wang +1
There is a proliferation of applications requiring the management of large-scale, evolving graphs under workloads with intensive graph updates and lookups. Driven by this challenge…