Distributed machine learning with Amazon ECS
Containers Blog
This article discusses how to run distributed machine learning workloads on Amazon Elastic Container Service (Amazon ECS) using PyTorch and Ray Train libraries. It covers the setup of an ECS cluster, containerized training jobs, and distributed data parallel training.
Specifically, the article covers:
- Overview of the solution architecture with an ECS cluster, Ray head service, Ray worker service, and Amazon S3 for shared storage
- Prerequisites and setup instructions using Terraform to deploy the infrastructure
- Step-by-step walkthrough of running a distributed training job with PyTorch's resnet18 model on the FashionMNIST dataset
- Explanation of logs and output from the training job
- Clean up instructions to terminate the resources
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