1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.DC2026
AoiZora: Topology-Aware Auto-Parallel Optimization for Inference of Diffusion Transformers
Kaijian Wang, Yuanyuan Xu, Fanjiang Ye +5
Video diffusion has quickly grown into a key generative serving workload, yet producing each clip demands many denoising iterations over large spatio-temporal latents, which puts l…
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…