GPU infrastructure and automation tools
The DeepOps project encapsulates best practices in the deployment of GPU server clusters and sharing single powerful nodes (such as NVIDIA DGX Systems). DeepOps can also be adapted or used in a modular fashion to match site-specific cluster needs. For example:
- An on-prem, air-gapped data center of NVIDIA DGX servers where DeepOps provides end-to-end capabilities to set up the entire cluster management stack
- An existing cluster running Kubernetes where DeepOps scripts are used to deploy Kubeflow and connect NFS storage
- An existing cluster that needs a resource manager / batch scheduler, where DeepOps is used to install Slurm, Kubernetes, or a hybrid of both
- A single machine where no scheduler is desired, only NVIDIA drivers, Docker, and the NVIDIA Container Runtime
Check out the video tutorial for how to use DeepOps to deploy Kubernetes and Kubeflow on a single DGX Station. This provides a good base test ground for larger deployments.
Latest release: DeepOps 19.10 Release
It is recommended to use the latest release branch for stable code (linked above). All development takes place on the master branch, which is generally functional but may change significantly between releases.
For detailed help or guidance, read through our Getting Started Guide or pick one of the deployment options documented below.
DeepOps currently supports the following Linux distributions:
- NVIDIA DGX OS 4
- Ubuntu 18.04 LTS
- CentOS 7
- Red Hat Enterprise Linux 7
Kubernetes (K8s) is an open-source system for automating deployment, scaling, and management of containerized applications.
Consult the DeepOps Kubernetes Deployment Guide for instructions on building a GPU-enabled Kubernetes cluster using DeepOps.
For more information on Kubernetes in general, refer to the official Kubernetes docs.
Slurm is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small Linux clusters.
Consult the DeepOps Slurm Deployment Guide for instructions on building a GPU-enabled Slurm cluster using DeepOps.
For more information on Slurm in general, refer to the official Slurm docs.
A hybrid cluster with both Kubernetes and Slurm can also be deployed. This is recommended for DGX POD and other setups that wish to make maximal use of the cluster.
Consult the DeepOps DGX POD Deployment Guide for step-by-step instructions on building a GPU-enabled hybrid cluster using DeepOps.
To try DeepOps before deploying it on an actual cluster, a virtualized version of DeepOps may be deployed on a single node using Vagrant. This can be used for testing, adding new features, or configuring DeepOps to meet deployment-specific needs.
Consult the Virtual DeepOps Deployment Guide to build a GPU-enabled virtual cluster with DeepOps.
To update from a previous version of DeepOps to a newer release, please consult the DeepOps Update Guide.
This project is released under the BSD 3-clause license.
NVIDIA DGX customers should file an NVES ticket via NVIDIA Enterprise Services.
Otherwise, bugs and feature requests can be made by filing a GitHub Issue.
To contribute, please issue a pull request against the master branch from a local fork.
A signed copy of the Contributor License Agreement needs to be provided to deepops@nvidia.com before any change can be accepted.