Difference between revisions of "Julia"
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{{#if: {{#var: exe}}|==Additional Information== | {{#if: {{#var: exe}}|==Additional Information== | ||
| + | ===Package Installation=== | ||
| + | After loading julia with <code>ml julia</code> from HPG, you can add packages to your personal Julia environment with Pkg. | ||
| − | + | julia | |
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| − | + | using Pkg | |
| − | + | Pkg.add("CSV") | |
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| + | ===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 the installation. | ||
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Revision as of 20:47, 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 julia with ml julia from HPG, you can add packages to your personal Julia environment with Pkg.
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 the installation.