<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fortran on Jorgen Wu</title><link>https://wujorgen.github.io/tags/fortran/</link><description>Recent content in Fortran on Jorgen Wu</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 28 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://wujorgen.github.io/tags/fortran/index.xml" rel="self" type="application/rss+xml"/><item><title>Iterative Methods and Parallelization for Solving PDEs</title><link>https://wujorgen.github.io/posts/iterative-methods-parallelization/</link><pubDate>Sun, 28 Jun 2026 00:00:00 +0000</pubDate><guid>https://wujorgen.github.io/posts/iterative-methods-parallelization/</guid><description>&lt;h1 id="background"&gt;
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&lt;p&gt;Elliptic PDEs are the most expensive type of PDE to solve as they require a global solve
Unfortunately, they commonly appear in many simulations.
This post will cover solution some iterative solution methods for elliptic PDEs.
Those are, in order:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Jacobi Iteration&lt;/li&gt;
&lt;li&gt;Gauss Seidel&lt;/li&gt;
&lt;li&gt;Successive Over-Relaxation (SOR)&lt;/li&gt;
&lt;li&gt;Red-Black Parallelization&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;The Fortran programming language will be used instead of C or C++ due to its native support for multi-dimensional arrays.
The codes will be compiled with &lt;code&gt;gfortran&lt;/code&gt;.
The results will be written out to CSV files and visualized using Matplotlib in Python.&lt;/p&gt;</description></item></channel></rss>