Author

Jin Fang

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Preprint Sep 2026

HOCCL: Offloading Collective Communication from GPU Cores to Accelerate Distributed Training

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

Preprint Sep 2026

VarioPath: Workload-Aware All-to-All Communication for PCIe GPU Clusters

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

#machine learning Preprint Sep 2026

TopoEP: Topology-Aware Load Balancing for Expert-Parallel MoE Training

A GPU-native, topology-aware load-balancing system for large-scale MoE training that converts the current routing result into hot-expert replication and token-rerouting decisions and executes the resulting plan without data-dependent host synchronization, reducing critical-path overhead.

Jia-Cheng Zhu, Xie Zhao, Gong-Ming Zhao et al. · 0 citations