- Introduction to HPC clusters
- UNIX Introduction
- HPC Class
- Condo 2017
- File Transfers
- Cloud Back-up with Rclone
- Globus Connect
- Sample Job Scripts
- Using DDT Parallel Debugger, MAP profiler and Performance Reports
- Using Matlab Parallel Server
- Using ANSYS RSM
- Nova OnDemand
- Using Julia
- LAS Machine Learning Container
- Support & Contacts
- Systems & Equipment
- FAQ: Frequently Asked Questions
- Contact Us
- Cluster Access Request
Julia is a flexible dynamic language that is intended for scientific and numerical computing. IJulia is a Julia language backend that allows users to use the Julia language in Jupyter's graphical notebook interface.
The first step to working with IJulia on ISU HPC clusters is to connect to Open OnDemand for the desired cluster. Click here for the ISU HPC Open OnDemand guide. For convenience, the links to the current, as of this guide, ISU HPC cluster Open Ondemand interfaces are provided below. Note: To connect to Open OnDemand, a user must either be on the ISU network or connected via the ISU VPN.
Once connected to Open OnDemand, a user will have to start a JupyterLab session. Follow the ISU HPC JupyterLab guide here to launch and connect to JupyterLab.
Once connected to the JupyterLab instance, click File > New > Terminal to open a shell.
Choose a location to download and build Julia. This example will use "/work/mygroup/userdir" as an example path:
Change to the directory and download the Julia source from github:
git clone https://github.com/JuliaLang/julia.git
Change to the git directory that was downloaded:
Checkout the git branch for the version of Julia to be installed. This example will use version 1.7.3:
git checkout v1.7.3
Load the modules required to build Julia:
module load gcc python perl wget m4 cmake pkgconf
Build Julia with the make command. Note: Depending on the environment, this can take a significant amount of time. The real time to run for this example was over 13 minutes.
From the Julia prompt, install IJulia:
After adding the IJulia package, a Julia kernel of the version you installed should appear in your list of available notebooks and consoles on the Jupyter Launcher. To access the launcher, click File > New Launcher.
Note: While it should display without intervention, if it is not, opening a new JupyerLab session may resolve the issue.
To open a Julia notebook interface, simply click on the corresponding notebook tile. This will open a blank notebook tab.
To test, try running the following three cells:
#Print the string 'testing println'
#Load the package 'Plots' - First time running this will take a while while it installs
#Use the Plots package to make a simple test graph
x = 1:10; y = rand(10);
Note: On the first run of Pkg.add("Plots") it will take a while to pull all of the dependancies and install them. The notebook will have considerably more output than what is shown in the above image.