Development/Julia - Revision history

M Carmesin at 08:35, 2 December 2025

2025-12-02T08:35:16Z

← Older revision		Revision as of 10:35, 2 December 2025
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	scatterplot(vec)		scatterplot(vec)
	</pre>		</pre>


			== Recommended Packages ==

			Depending on your specific problem, you might speedup your calculations by using the drop-in replacements for the LinearAlebra routines from the Intel oneApi MKL:
			* [https://github.com/JuliaLinearAlgebra/MKL.jl MKL.jl]: dense linear algebra
			* [https://github.com/JuliaSparse/MKLSparse.jl MKLSparse.jl]: sparse linear algebra

			If you are developing some low-level numerical codes, you could profit from the package [https://github.com/JuliaSIMD/LoopVectorization.jl LoopVectorization.jl].

M Carmesin at 08:18, 2 December 2025

2025-12-02T08:18:53Z

← Older revision		Revision as of 10:18, 2 December 2025
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	There are no packages preinstalled besides the Julia language core, please use the Julia package manager to install any required Julia package.		There are no packages preinstalled besides the Julia language core, please use the Julia package manager to install any required Julia package.

	The Julia module on ~~Justus~~ ~~loads~~ suitable versions of CUDA and OpenMPI and the corresponding Julia packages CUDA.jl and MPI.jl will be automatically configured to use these libraries after being installed by the user. Any changes, either by loading modules with different MPI and/ or CUDA versions as well as using the ones that come as Julia artifacts are likely to lead to errors.		The Julia module on JUSTUS2 and bwUniCLuster 3.0 load suitable versions of CUDA and OpenMPI and the corresponding Julia packages CUDA.jl and MPI.jl will be automatically configured to use these libraries after being installed by the user. Any changes, either by loading modules with different MPI and/ or CUDA versions as well as using the ones that come as Julia artifacts are likely to lead to errors.

	== Availability ==		== Availability ==

M Carmesin at 08:14, 2 December 2025

2025-12-02T08:14:59Z

← Older revision		Revision as of 10:14, 2 December 2025
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	* [https://github.com/carstenbauer/JuliaHLRS25 Julia Workshop at HLRS]: The material of this workshop is in large parts also valid for the bwHPC clusters (on bwUniCluster and JUSTUS2 you only need the module math/julia).		* [https://github.com/carstenbauer/JuliaHLRS25 Julia Workshop at HLRS]: The material of this workshop is in large parts also valid for the bwHPC clusters (on bwUniCluster and JUSTUS2 you only need the module math/julia).

			* [https://github.com/JuliaPDE/SurveyofPDEPackages Survey of PDE packages]

			* [https://book.sciml.ai/ Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications ]
	== Tips & Tricks ==		== Tips & Tricks ==

M Carmesin: /* Further documentation */

2025-12-02T07:59:12Z

Further documentation

← Older revision		Revision as of 09:59, 2 December 2025
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	* [https://modernjuliaworkflows.org Modern Julia Workflows]: A collection of best practices		* [https://modernjuliaworkflows.org Modern Julia Workflows]: A collection of best practices

	* [https://github.com/carstenbauer/~~JuliaHLRS24~~ Julia Workshop at HLRS]: The material of this workshop is in large parts also valid for the ~~Justus~~ ~~cluster~~ (on ~~Justus~~ you only need the module math/julia).		* [https://github.com/carstenbauer/JuliaHLRS25 Julia Workshop at HLRS]: The material of this workshop is in large parts also valid for the bwHPC clusters (on bwUniCluster and JUSTUS2 you only need the module math/julia).

	== Tips & Tricks ==		== Tips & Tricks ==

M Carmesin at 10:26, 12 May 2025

2025-05-12T10:26:24Z

← Older revision		Revision as of 12:26, 12 May 2025
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	== Availability ==		== Availability ==

	On UniCluster3.0 and JUSTUS 2, Julia is available as module. Check `module avail math/julia` for the ~~provides~~ versions. In case there is no suitable version, you can install Julia to your home directory using the [https://julialang.org/install/ JuliaUP] installer.		On UniCluster3.0 and JUSTUS 2, Julia is available as module. Check <code>module avail math/julia</code> for the provided versions. In case there is no suitable version, you can install Julia to your home directory using the [https://julialang.org/install/ JuliaUP] installer.

	== Environments and Package Installation ==		== Environments and Package Installation ==

M Carmesin: /* Availability */

2025-05-12T10:25:49Z

Availability

← Older revision		Revision as of 12:25, 12 May 2025
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	== Availability ==		== Availability ==

	On UniCluster3.0 ~~ans~~ JUSTUS 2, Julia is available as module. Check `module avail math/julia` for the provides versions. In case there is no suitable version, you can install Julia to your home directory using the [https://julialang.org/install/ JuliaUP] installer.		On UniCluster3.0 and JUSTUS 2, Julia is available as module. Check `module avail math/julia` for the provides versions. In case there is no suitable version, you can install Julia to your home directory using the [https://julialang.org/install/ JuliaUP] installer.


	== Environments and Package Installation ==		== Environments and Package Installation ==

M Carmesin: Created page with "Julia is a high-level, high-performance, dynamic programming language, being designed with scientific computing in mind. Parallel programming features, such as multi-threading are included in the core language, while there also exist packages leveraging the power of MPI and CUDA. There are no packages preinstalled besides the Julia language core, please use the Julia package manager to install any required Julia package. The Julia module on Justus loads suitable versio..."

2025-05-12T10:25:34Z

Created page with "Julia is a high-level, high-performance, dynamic programming language, being designed with scientific computing in mind. Parallel programming features, such as multi-threading are included in the core language, while there also exist packages leveraging the power of MPI and CUDA. There are no packages preinstalled besides the Julia language core, please use the Julia package manager to install any required Julia package. The Julia module on Justus loads suitable versio..."

New page

Julia is a high-level, high-performance, dynamic programming language, being designed with scientific computing in mind. Parallel programming features, such as multi-threading are included in the core language, while there also exist packages leveraging the power of MPI and CUDA.

There are no packages preinstalled besides the Julia language core, please use the Julia package manager to install any required Julia package.

The Julia module on Justus loads suitable versions of CUDA and OpenMPI and the corresponding Julia packages CUDA.jl and MPI.jl will be automatically configured to use these libraries after being installed by the user. Any changes, either by loading modules with different MPI and/ or CUDA versions as well as using the ones that come as Julia artifacts are likely to lead to errors.

== Availability ==

On UniCluster3.0 ans JUSTUS 2, Julia is available as module. Check `module avail math/julia` for the provides versions. In case there is no suitable version, you can install Julia to your home directory using the [https://julialang.org/install/ JuliaUP] installer.

== Environments and Package Installation ==

It is highly recommended to use an separate Julia environment for every project. If Julia is started with the option <code>--project=.</code> the current folder will be used as environment and the <code>Project.toml</code> file containing the information on the installed packages will be created, if not yet present.

In an interactive Julia session, the [https://pkgdocs.julialang.org/v1/getting-started/#Basic-Usage package manager] is activated by entering <code>]</code>. The most importent commands are
* <code>add PACKAGENAME</code> install package PACKAGENAME in the current environment
* <code>instantiate</code>: install all packages with dependencies as stated in Project.toml and Manifest.toml, e.g. after copying the existing code to the cluster
* <code>activate PATH_TO_ENV</code>: use the environment located at the path <code>PATH_TO_ENV</code> and initialize it, if necessary.

== Interactive Example ==

Load Julia module and start interactive REPL session with 8 threads, using the environment in the current directory:

<pre>
$ module load math/julia
$ julia -t 8 --project=.
</pre>

Enter ']' to go into package manager and install package [https://github.com/JuliaPlots/UnicodePlots.jl?tab=readme-ov-file <code>UnicodePlots</code>].
<pre>
add UnicodePlots
</pre>

Leave the package manager with the backspace key.

Create a vector with 64 elements set to 0 and fill it using all 8 threads with the corresponding tread id number.

<pre>
vec = zeros(64)
Threads.@threads for i in eachindex(vec)
vec[i]= Threads.threadid()
end
</pre>

Load the <code>UnicodePlots</code> package and draw a scatter plot of the contents of <code>vec</code>

<pre>
using UnicodePlots
scatterplot(vec)
</pre>

== Further documentation ==

* [https://modernjuliaworkflows.org Modern Julia Workflows]: A collection of best practices

* [https://github.com/carstenbauer/JuliaHLRS24 Julia Workshop at HLRS]: The material of this workshop is in large parts also valid for the Justus cluster (on Justus you only need the module math/julia).

== Tips & Tricks ==

* [[JUSTUS2/Software/Julia/Parallel_Programming|Parallel Programming]]