<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Slurm on IOPS</title><link>https://iops.gitlabpages.inria.fr/tags/slurm/</link><description>Recent content in Slurm on IOPS</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 30 May 2026 20:28:38 +0200</lastBuildDate><atom:link href="https://iops.gitlabpages.inria.fr/tags/slurm/index.xml" rel="self" type="application/rss+xml"/><item><title>Measuring the runtime overhead of an I/O interception library</title><link>https://iops.gitlabpages.inria.fr/blog/toto-overhead-analysis/</link><pubDate>Sat, 30 May 2026 00:00:00 +0000</pubDate><guid>https://iops.gitlabpages.inria.fr/blog/toto-overhead-analysis/</guid><description>&lt;blockquote>
&lt;p>This study is part of our paper &lt;strong>&amp;ldquo;TOTO: Transparent I/O Tuning for HPC Applications&amp;rdquo;&lt;/strong>, accepted at &lt;strong>ICS 2026&lt;/strong> (International Conference on Supercomputing, Belfast, July 2026). The overhead measurements below were produced with IOPS.&lt;/p>
&lt;/blockquote>
&lt;p>When you intercept I/O system calls to analyze application behavior, how much overhead do you actually add? That&amp;rsquo;s the question we needed to answer for &lt;a href="https://gitlab.inria.fr/hpc_io/toto">TOTO&lt;/a> (Transparent and Online Tool for I/O), a library that hooks into I/O calls via &lt;code>LD_PRELOAD&lt;/code> to provide runtime analysis of parallel file system access patterns.&lt;/p></description></item><item><title>Using IOPS on Grid'5000</title><link>https://iops.gitlabpages.inria.fr/blog/grid500/</link><pubDate>Mon, 26 Jan 2026 00:00:00 +0000</pubDate><guid>https://iops.gitlabpages.inria.fr/blog/grid500/</guid><description>&lt;p>&lt;a href="https://www.grid5000.fr/w/Grid5000:Home">Grid'5000&lt;/a> is a large-scale and flexible testbed for experiment-driven research in all areas of computer science, with a focus on parallel and distributed computing, including Cloud, HPC, Big Data and AI.&lt;/p>
&lt;p>On Grid'5000 platform the reservation of computing nodes and scheduling of batch jobs is managed by the &lt;a href="https://oar.readthedocs.io/en/2.5/">OAR software suite&lt;/a>, while IOPS is only supporting &lt;a href="https://slurm.schedmd.com/documentation.html">Slurm&lt;/a> as a batch scheduler.
Thankfully, the high level of similarity between OAR and Slurm (at least from a user perspective) makes it easy to &lt;strong>run IOPS on Grid'5000 front-end with OAR being used to schedule &amp;amp; control the test jobs on the computing nodes&lt;/strong>. Let&amp;rsquo;s see how&amp;hellip;&lt;/p></description></item></channel></rss>