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cs.LG2024
QSync: Quantization-Minimized Synchronous Distributed Training Across Hybrid Devices
Juntao Zhao, Borui Wan, Yanghua Peng +3
A number of production deep learning clusters have attempted to explore inference hardware for DNN training, at the off-peak serving hours with many inference GPUs idling. Conducti…
cs.AI2024
ByteCheckpoint: A Unified Checkpointing System for Large Foundation Model Development
Borui Wan, Mingji Han, Yiyao Sheng +9
Checkpointing to preserve training states is crucial during the development of Large Foundation Models (LFMs), for training resumption upon various failures or changes in GPU resou…
cs.LG2024★ 3 cited
LLM-PQ: Serving LLM on Heterogeneous Clusters with Phase-Aware Partition and Adaptive Quantization
Juntao Zhao, Borui Wan, Yanghua Peng +2
Recent breakthroughs in Large-scale language models (LLMs) have demonstrated impressive performance on various tasks. The immense sizes of LLMs have led to very high resource deman…