Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving
Summary: Hybrid KV+hidden-state cache expands batch size under GPU memory limits for LLM inference. Adaptive scheduling with formal optimization and guarantees tunes batch composition, yielding up to 8.8× throughput vs SOTA on 13B–66B models. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shihong Gao (Hong Kong University of Science and Technology)
- 2. Xin Zhang (Hong Kong University of Science and Technology)
- 3. Yanyan Shen (Shanghai Jiao Tong University)
- 4. Lei Chen (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{gao_sigmod25,
title = {{Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving}},
author = {Gao, Shihong and Zhang, Xin and Shen, Yanyan and Chen, Lei},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725394},
url = {https://dl.acm.org/doi/10.1145/3725394},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,432 | RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference | 2026 | VLDB | 5.8801533e-05 |
| 10,191 | AlignedServe: Orchestrating Prefix-aware Batching to Build a High-throughput and Computing-efficient LLM Serving System | 2026 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 35 of 35 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next