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cs.CE2024
Task Scheduling for Efficient Inference of Large Language Models on Single Moderate GPU Systems
Wenxiang Lin, Xinglin Pan, Shaohuai Shi +2
Large language models~(LLMs) are known for their high demand on computing resources and memory due to their substantial model size, which leads to inefficient inference on moderate…
cs.DC2024
Parm: Efficient Training of Large Sparsely-Activated Models with Dedicated Schedules
Xinglin Pan, Wenxiang Lin, Shaohuai Shi +3
Sparsely-activated Mixture-of-Expert (MoE) layers have found practical applications in enlarging the model size of large-scale foundation models, with only a sub-linear increase in…