gpu-cluster

Root repo for ACM GPU Cluster

Overview

The GPU Cluster Project breaks down into a couple parts.

Javascript

GPU Cluster Frontend - Frontend written in React, calls backend

Python

GPU Cluster Backend - Backend written in python, recieves requests and creates containers

nvdocker - A python package to manage interfacing with GPU enabled containers

[Nvidia] Docker

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

Install Docker

Install nvidia-docker

There are a couple components of the GPU Cluster. To get all of the source run:

git clone --recursive [email protected]: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

   brew install repo 

   Ubuntu 14.04+

   sudo apt install repo
   

2. Make a directory to house your GPU Cluster work

   mkdir $GOPATH/src/github.com/acm-uiuc/gpu-cluster

3. Within this directory run the following command to start managing the projects

   repo init -u [email protected]:acm-uiuc/gpu-cluster

4. Run the following command to grab the latest of all the repos

   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