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cs.LG2023
Empowering Distributed Training with Sparsity-driven Data Synchronization
Zhuang Wang, Zhaozhuo Xu, Jingyi Xi +3
Distributed training is the de facto standard to scale up the training of deep learning models with multiple GPUs. Its performance bottleneck lies in communications for gradient sy…
cs.LG2022★ 1 cited
ByteComp: Revisiting Gradient Compression in Distributed Training
Zhuang Wang, Haibin Lin, Yibo Zhu +1
Gradient compression (GC) is a promising approach to addressing the communication bottleneck in distributed deep learning (DDL). However, it is challenging to find the optimal comp…