Advances in Asynchronous Parallel and Distributed Optimization

Proceedings of the IEEE


Motivated by large-scale optimization problems arising in the context of machine learning, there have been several advances in the study of asynchronous parallel and distributed optimization methods during the past decade. Asynchronous methods do not require all processors to maintain a consistent view of the optimization variables. Consequently, they generally can make more efficient use of computational resources than synchronous methods, and they are not sensitive to issues like stragglers (i.e., slow nodes) and unreliable communication links. Mathematical modeling of asynchronous methods involves proper accounting of information delays, which makes their analysis challenging. This article reviews recent developments in the design and analysis of asynchronous optimization methods, covering both centralized methods, where all processors update a master copy of the optimization variables, and decentralized methods, where each processor maintains a local copy of the variables. The analysis provides insights as to how the degree of asynchrony impacts convergence rates, especially in stochastic optimization methods.

Related Publications

All Publications

SIGGRAPH - August 9, 2021

Control Strategies for Physically Simulated Characters Performing Two-player Competitive Sports

Jungdam Won, Deepak Gopinath, Jessica Hodgins

CVPR - June 20, 2021

Ego-Exo: Transferring Visual Representations from Third-person to First-person Videos

Yanghao Li, Tushar Nagarajan, Bo Xiong, Kristen Grauman

ICML - July 18, 2021

Align, then memorise: the dynamics of learning with feedback alignment

Maria Refinetti, St├ęphane d'Ascoli, Ruben Ohana, Sebastian Goldt

CVPR - June 19, 2021

Intentonomy: a Dataset and Study towards Human Intent Understanding

Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie, Ser-Nam Lim

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy