Difference between revisions of "Julia"

Latest revision as of 20:49, 21 October 2022

Description

Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. Julia’s Base library, largely written in Julia itself, also integrates mature, best-of-breed open source C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing. In addition, the Julia developer community is contributing a number of external packages through Julia’s built-in package manager at a rapid pace. IJulia, a collaboration between the IPython and Julia communities, provides a powerful browser-based graphical notebook interface to Julia.

Environment Modules

Run module spider julia to find out what environment modules are available for this application.

System Variables

HPC_JULIA_DIR - installation directory
HPC_JULIA_BIN - executable directory
HPC_JULIA_MAN - manual directory

Additional Information

Package Installation

After loading the julia environment module you can add packages to your personal Julia environment with Pkg. E.g.

$ module load julia
$ julia
> using Pkg
> Pkg.add("CSV")

Jupyter Kernel

To create a personal Julia Jupyter kernel load the julia environment module and add the 'IJulia' package.
Pkg.add("IJulia")

The kernel should be visible in your new jupyterlab session after a successful installation.

@@ Line 33: / Line 33: @@
 <!--Run-->
 {{#if: {{#var: exe}}|==Additional Information==
+===Package Installation===
+After loading the julia environment module you can add packages to your personal Julia environment with Pkg. E.g.
-If you encounter an SSL certificate issue when installing a Julia package with Pkg you can work around the issue by adding an 'insecure'  line to the curl initialization file ~/.curlrc file. Do this if you trust the package source. E.g.
+  $ module load julia
+  $ julia
-  $ echo 'insecure' >> ~/.curlrc
+  > using Pkg
+  > Pkg.add("CSV")
-Julia installs packages to your home directory. This means that all of the packages are manual self installs. Follow the basic Julia installation steps
-  using Pkg
-  Pkg.add("name")
-|}}
-== Using Julia in Jupyter ==
-=== Download Julia ===
-As of May 2022, there is a bug in the Julia available via conda, so download the binary from https://julialang.org/downloads/ you want the 64-bit (glibc) version of the current stable release.
-# Log into HiPerGator
-# Download the latest version of Julia, this command was from May 2022: <code>wget https://julialang-s3.julialang.org/bin/linux/x64/1.7/julia-1.7.3-linux-x86_64.tar.gz</code>
-# Extract the zip file: <code>tar xvf julia-1.7.3-linux-x86_64.tar.gz</code>
-# Test that Julia works: <code>julia-1.7.3/bin/julia </code>
-=== Install IJulia ===
-You will need IJulia to use Julia in a Jupyter Notebook.
-# Open your Julia application: <code>julia-1.7.3/bin/julia</code>
-# Using the directions from [https://julialang.github.io/IJulia.jl/stable/manual/installation/ IJulia]:
-<pre>
-using Pkg
-Pkg.add("IJulia")
-</pre>
-Installing IJulia will create a kernel file for you at <code>~/.local/share/jupyter/kernels</code>.
-Launch a Jupyter session and you should be set!
+===Jupyter Kernel===
+ To create a personal Julia Jupyter kernel load the julia environment module and add the 'IJulia' package.
+ Pkg.add("IJulia")
+The kernel should be visible in your new jupyterlab session after a successful installation.
+}}
 <!--PBS scripts-->
 {{#if: {{#var: pbs}}|==PBS Script Examples==
@@ Line 102: / Line 77: @@
 <!--Turn the Table of Contents and Edit paragraph links ON/OFF-->
 __NOTOC____NOEDITSECTION__
-=Validation=
-* Validate 4/5/2018