1 citations · 1 across the 3 of their papers we have counts for
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Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda
Minxian Xu, Jingfeng Wu, Shengye Song +16
The rapid rise of Large Language Models (LLMs) has revolutionized various artificial intelligence (AI) applications, from natural language processing to code generation. However, t…
TD3-Sched: Learning to Orchestrate Container-based Cloud-Edge Resources via Distributed Reinforcement Learning
Shengye Song, Minxian Xu, Kan Hu +2
Resource scheduling in cloud-edge systems is challenging as edge nodes run latency-sensitive workloads under tight resource constraints, while existing centralized schedulers can s…
C-Koordinator: Interference-aware Management for Large-scale and Co-located Microservice Clusters
Shengye Song, Minxian Xu, Zuowei Zhang +5
Microservices transform traditional monolithic applications into lightweight, loosely coupled application components and have been widely adopted in many enterprises. Cloud platfor…
BucketServe: Bucket-Based Dynamic Batching for Smart and Efficient LLM Inference Serving
Wanyi Zheng, Minxian Xu, Shengye Song +1
Large language models (LLMs) have become increasingly popular in various areas, traditional business gradually shifting from rule-based systems to LLM-based solutions. However, the…