3 papers
cs.DC2026
Collective Communication for Distributed LLM Systems: Planning, Runtime Adaptation, and Computation Coordination
Xuebin Song, Menghao Zhang, Yuezheng Liu +5
Distributed large language model (LLM) systems increasingly rely on collective communication primitives such as AllReduce (AR), ReduceScatter (RS), AllGather (AG), and AlltoAll (A2…
cs.DC2026
SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving
Yihui Zhang, Tianyu Wo, Jinghao Wang +7
As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces a fundamental tension between…
cs.DC2025
An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Mingjun Zhang, Xiaohe Hu, Menghao Zhang +21
Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU train…