4 papers
RingStitch: Demand-Aware Optical Stitching for Fragmented TPU Clusters
Huiru Ao, Fan Yang, Binglei Wang +2
Large-scale AI training clusters increasingly use optical circuit switching (OCS) to reconfigure rack-level interconnects and create elastic accelerator slices. In multi-tenant TPU…
PLATONT: Learning a Platonic Representation for Unified Network Tomography
Chengze Du, Heng Xu, Zhiwei Yu +2
Network tomography aims to infer hidden network states, such as link performance, traffic load, and topology, from external observations. Most existing methods solve these problems…
REACH: Reinforcement Learning for Efficient Allocation in Community and Heterogeneous Networks
Zhiwei Yu, Chengze Du, Heng Xu +3
Community GPU platforms are emerging as a cost-effective and democratized alternative to centralized GPU clusters for AI workloads, aggregating idle consumer GPUs from globally dis…
Temporal-Aware GPU Resource Allocation for Distributed LLM Inference via Reinforcement Learning
Chengze Du, Zhiwei Yu, Heng Xu +3
The rapid growth of large language model (LLM) services imposes increasing demands on distributed GPU inference infrastructure. Most existing scheduling systems follow a reactive p…