awslabs / awsome-distributed-ai
Best practices, reference architectures, and examples for distributed AI training and inference on AWS.
Why this job: says: best practices
What it does
This repository contains reference architectures and examples for distributed AI training and inference on Amazon SageMaker HyperPod, AWS ParallelCluster, AWS Parallel Computing Service (AWS PCS), and Amazon Elastic Kubernetes Service (Amazon EKS). The examples cover different model families and sizes, training frameworks and parallel optimizations (PyTorch DDP/FSDP, Megatron-LM, NeMo), and serving engines (vLLM, SGLang, NVIDIA Dynamo).
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit today
- Stars
- 496
- +2 this week
- Licence
- MIT-0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v2.0.0
- Released 2 months ago
- Built with
- Shell
- 62% of the code
Is it looked after?
- Contributors
- 18
- Last 90 days
- Issues
- 98% closed
- 5 still open
- Pull requests
- 824 merged
- 37 waiting
- Releases
- 6
- 4 in the last year
More: languages, topics and project record
Languages
- Shell 62%
- Python 22%
- HCL 12%
- Dockerfile 2%
Topics
- aws
- efa
- eks
- generative-ai
- gpu
- hyperpod
- parallelcluster
- distributed-training
- distributed-inference
- kubernetes
- physical-ai
- slurm
Project record
- JobLists and guides
- StatusListed
- Commits1,613
- Forks215
- Watching17
- Stars in 28 days+11
- CreatedSep 30, 2023
- First seen by usNov 7, 2026
- CheckedNov 9, 2026