Understanding Communication Characteristics of Distributed Training

Wenxue Li, Xiangzhou Liu, Yuxuan Li, Yilun Jin, Han Tian, Zhizhen Zhong, Guyue Liu, Ying Zhang, Kai Chen

Abstract: Communication is pivotal in distributed training and a thorough understanding of its characteristics is essential for future optimizations. However, prior works are limited, either focusing on customized optimizations or conducting incomplete explorations on communication characteristics. In this work, we systematically analyze the communication characteristics of distributed training, considering two key aspects of communication: pattern and overhead, and assessing a broad spectrum of determinant factors. In particular, we extensively investigate the features of communication patterns, such as predictability, and comprehensively evaluate the impact of various factors on communication overhead. Additionally, we develop and validate an analytical formulation to estimate communication overhead, providing a mathematical understanding of models with predictability.