# TonY: An Orchestrator for Distributed Machine Learning Jobs

arXiv: https://arxiv.org/abs/1904.01631 · HTML: https://mlsanity.com/paper/1904.01631/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Mar 2019.

## Built on by (most cited first, 1 of 1)

- [Apache Submarine: A Unified Machine Learning Platform Made Simple](https://mlsanity.com/paper/2108.09615/) (2021)

## Abstract (arXiv)

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.