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Last Updated: October 15, 2026
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Accelerating Distributed Graph Learning GPREEMPT: GPU Preemptive Scheduling Made General and Efficient Ruwen Fan and Tingxu Ren, Tsinghua University; Minhui ... AutoCCL: Automated Collective Communication Tuning for CrossPipe: Towards Optimal Pipeline Schedules for Cross-Datacenter Training Tiancheng Chen, Ales Kubicek, Langwen Huang, ... On-Demand Container Partitioning for FlexPipe: Maximizing Training Efficiency for Transformer-based Models CLONE: Customizing LLMs for Efficient Latency-Aware Inference at the Edge Chunlin Tian, Xinpeng Qin, Kahou Tam, Li Li, Zijian ... Universal Checkpointing: A Flexible and Efficient Resource Multiplexing in Tuning and Serving Large Language Models Yongjun He and Haofeng Yang, ETH Zurich; Yao Lu, ... Weaver: Efficient Multi-LLM Serving
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