Large language model training involves massive computation on GPU streaming multiprocessors (SMs), the primary compute units of GPUs. Since SMs host specialized accelerators such as Tensor Cores, their efficient utilization is critical to training efficiency. Unfortunately, existing collective communication systems com...
Yao Fei, Gong-Ming Zhao, Hong-Li Xu et al.· 0 citations
AlltoAllv communication is a critical primitive in distributed large-model inference, particularly for mixture-of-experts (MoE) models. The growing adoption of PCIe GPU systems for cost-efficient inference makes AlltoAllv performance on these systems increasingly important. Without a dedicated scale-up interconnect (e....
Yao Fei, Jin Fang, Si-Ze Zheng et al.· 0 citations
A lightweight utility-guided orchestration framework that formulates agent control as a costaware sequential decision problem over a compact action space, intended as an inspectable control layer for practical LLM services rather than a universally dominant accuracy optimizer.
Bo-Yang Liu, Gongming Zhao, Hong-Liu Xu et al.· Fall Joint Computer Conferen...· 4 citations
Tool-augmented large language model (LLM) services can solve complex tasks through retrieval and external tools, but current execution paradigms often trade adaptability for efficiency. Fixed workflows are predictable but rigid, while freeform reasoning loops such as ReAct may over-execute and issue redundant tool call...
Bo-Yang Liu, Gongming Zhao, Hongliu Xu et al.· Fall Joint Computer Conferen...· 0 citations
Hestia is proposed, a framework that achieves long-term stable oversubscription through workload aggregation through a smoothing-based method to classify workloads suitable for aggregation according to their periodicity, and an aggregation algorithm to minimize the overall MCV.
Baoqing Wang, Gongming Zhao, Hongli Xu et al.· Conference on Applications,...· 0 citations
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