https://github.com/acm-uiuc/gpu-cluster
Root repo for ACM GPU Cluster
https://github.com/acm-uiuc/gpu-cluster
ai deep-learning gpu gpu-cluster nvidia
Last synced: 10 months ago
JSON representation
Root repo for ACM GPU Cluster
- Host: GitHub
- URL: https://github.com/acm-uiuc/gpu-cluster
- Owner: acm-uiuc
- License: other
- Created: 2017-08-11T16:29:11.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2019-02-23T23:40:42.000Z (over 7 years ago)
- Last Synced: 2025-03-15T23:54:14.635Z (over 1 year ago)
- Topics: ai, deep-learning, gpu, gpu-cluster, nvidia
- Language: Shell
- Size: 21.5 KB
- Stars: 2
- Watchers: 25
- Forks: 1
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# gpu-cluster
Root repo for ACM GPU Cluster
[](https://acm-uiuc.slack.com/messages/C6XH6H85S)
## Overview
The GPU Cluster Project breaks down into a couple parts.
### Javascript
[GPU Cluster Frontend](https://github.com/acm-uiuc/gpu-cluster-frontend) - Frontend written in React, calls backend
### Python
[GPU Cluster Backend](https://github.com/acm-uiuc/gpu-cluster-backend) - Backend written in python, recieves requests and creates containers
[nvdocker](https://github.com/acm-uiuc/nvdocker) - A python package to manage interfacing with GPU enabled containers
### [Nvidia] Docker
[GPU Cluster Images](https://github.com/acm-uiuc/gpu-cluster-images) - Standard Deep Learning Containers
### Slurm
Cluster management software.
## Getting Started
Make sure you have Node.js, Yarn and Python and Docker installed before starting
[Install Node](http://til.acm.illinois.edu/nodejs/install-nvm/)
[Install Docker](https://docs.docker.com/compose/install/)
[Install nvidia-docker](https://github.com/NVIDIA/nvidia-docker)
There are a couple components of the GPU Cluster. To get all of the source run:
```
git clone --recursive git@github.com:acm-uiuc/gpu-cluster
````
You can also use repo if you like that better
1. Install repo - https://android.googlesource.com/tools/repo/
Mac OS
```sh
brew install repo
```
Ubuntu 14.04+
```sh
sudo apt install repo
```
2. Make a directory to house your GPU Cluster work
```sh
mkdir $GOPATH/src/github.com/acm-uiuc/gpu-cluster
```
3. Within this directory run the following command to start managing the projects
```sh
repo init -u git@github.com:acm-uiuc/gpu-cluster
```
4. Run the following command to grab the latest of all the repos
```sh
repo sync
```
If you are going to work on the Docker images, make sure to have an NVIDIA Graphics Card and have NVIDIA Docker installed in addition to Docker.
https://github.com/NVIDIA/nvidia-docker
To start you can build the cluster with ```./build_gpu_cluster```. Then you can use ```./gpu_cluster``` to start the interface on port 4000.
If you want to install the cluster as a daemon, place the repo in ```/usr/local/gpu-cluster``` or change gpu_cluster.ini to reflect the location of the ```./gpu_cluster``` executable.
Then install circus with
```
pip install circus
```
Then create a systemd service following these instructions and pointing to ```gpu_cluster.ini```
> http://circus.readthedocs.io/en/latest/for-ops/deployment/
Deployed as a daemon using systemd and circus