5 papers
CoCoScale: Leveraging Layer-wise Scaling to Unlock the Potential of Online LLM Serving
Jingfeng Wu, Yiyuan He, Minxian Xu +7
Online large language model (LLM) serving has become the backbone of modern AI applications, powering diverse downstream services through shared hardware clusters. However, modern…
SwiftCache: Efficient LLM Serving for Multi-turn Conversations with Heterogeneous KV Cache Sharing
Jianmin Hu, Minxian Xu, Sa Wang +5
Multi-turn conversation is a fundamental scenario in LLM applications, widely used in chatbots and AI agents. As the conversation evolves, historical tokens accumulate continuously…
Semantic DLM+: Improving Diffusion Language Models through Bias-variance Trade-off in Transition Kernel Design
Keyue Jiang, Yuxiang Wang, Yanan Zhao +7
Diffusion Language Models (DLMs) have demonstrated strong scaling capacity as alternatives to autoregressive language models. However, their performance is highly sensitive to the…
RTP-LLM: High-Performance Alibaba LLM Inference Engine
Boyu Tan, Jiarui Guo, Zongwei Lv +26
Large Language Models (LLMs) have revolutionized AI applications, but deploying them at scale presents significant challenges. We present RTP-LLM, a high-performance inference engi…
BanaServe: Unified KV Cache and Dynamic Module Migration for Balancing Disaggregated LLM Serving in AI Infrastructure
Yiyuan He, Minxian Xu, Jingfeng Wu +7
Large language models (LLMs) are increasingly deployed in AI infrastructure, driving the need for high throughput, resource efficient serving systems. Disaggregated LLM serving, wh…