<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>MFEM on Robert Carson</title><link>https://robertcarson.org/tags/mfem/</link><description>Recent content in MFEM on Robert Carson</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>© 2026 Robert Carson</copyright><lastBuildDate>Tue, 15 Apr 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://robertcarson.org/tags/mfem/index.xml" rel="self" type="application/rss+xml"/><item><title>High Performance Computing &amp; GPU-Accelerated Scientific Software</title><link>https://robertcarson.org/papers/hpc-gpu-computing/</link><pubDate>Tue, 15 Apr 2025 00:00:00 +0000</pubDate><guid>https://robertcarson.org/papers/hpc-gpu-computing/</guid><description>&lt;h2 class="relative group"&gt;Overview
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&lt;p&gt;For roughly forty years, scientific codes got faster by waiting for the next hardware generation. That era ended. Peak floating-point throughput stopped scaling the way it used to, and the compute density now available in leadership-class machines comes almost entirely from GPU accelerators — thousands of streaming multiprocessors per node, operating under a fundamentally different programming model than the CPU clusters that most production scientific software was written for.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://robertcarson.org/papers/hpc-gpu-computing/featured.svg"/></item></channel></rss>