no code implementations • 8 Jul 2020 • Siyu Wang, Yi Rong, Shiqing Fan, Zhen Zheng, Lansong Diao, Guoping Long, Jun Yang, Xiaoyong Liu, Wei. Lin
The last decade has witnessed growth in the computational requirements for training deep neural networks.
no code implementations • 23 Sep 2020 • Zhen Zheng, Pengzhan Zhao, Guoping Long, Feiwen Zhu, Kai Zhu, Wenyi Zhao, Lansong Diao, Jun Yang, Wei. Lin
We show in this work that memory intensive computations can result in severe performance problems due to off-chip memory access and CPU-GPU context switch overheads in a wide range of deep learning models.
no code implementations • 13 Feb 2023 • Shiwei Zhang, Xiaodong Yi, Lansong Diao, Chuan Wu, Siyu Wang, Wei Lin
This paper presents TAG, an automatic system to derive optimized DNN training graph and its deployment onto any device topology, for expedited training in device- and topology- heterogeneous ML clusters.
no code implementations • 16 Feb 2023 • Shiwei Zhang, Lansong Diao, Siyu Wang, Zongyan Cao, Yiliang Gu, Chang Si, Ziji Shi, Zhen Zheng, Chuan Wu, Wei Lin
We present Rhino, a system for accelerating tensor programs with automatic parallelization on AI platform for real production environment.