TonY: An Orchestrator for Distributed Machine Learning Jobs [article]

Anthony Hsu, Keqiu Hu, Jonathan Hung, Arun Suresh, Zhe Zhang
2019 arXiv   pre-print
Training machine learning (ML) models on large datasets requires considerable computing power. To speed up training, it is typical to distribute training across several machines, often with specialized hardware like GPUs or TPUs. Managing a distributed training job is complex and requires dealing with resource contention, distributed configurations, monitoring, and fault tolerance. In this paper, we describe TonY, an open-source orchestrator for distributed ML jobs built at LinkedIn to address these challenges.
arXiv:1904.01631v1 fatcat:phazpymk4ra3vjs7utkwhuahp4