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<?xml-stylesheet type="text/xsl" href="../assets/xml/rss.xsl" media="all"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Simon Dobson (Posts about jupyter)</title><link>https://simondobson.org/</link><description></description><atom:link href="https://simondobson.org/categories/jupyter.xml" rel="self" type="application/rss+xml"></atom:link><language>en</language><copyright>Contents © 2025 &lt;a href="mailto:simoninireland@gmail.com"&gt;Simon Dobson&lt;/a&gt; </copyright><lastBuildDate>Thu, 23 Jan 2025 17:21:40 GMT</lastBuildDate><generator>Nikola (getnikola.com)</generator><docs>http://blogs.law.harvard.edu/tech/rss</docs><item><title>Notes on using Jupyter in the cloud</title><link>https://simondobson.org/2022/12/02/jupyter-in-the-cloud/</link><dc:creator>Simon Dobson</dc:creator><description>&lt;div id="outline-container-org5aafa10" class="outline-2"&gt;
&lt;h2 id="org5aafa10"&gt;Notes on using Jupyter in the cloud&lt;/h2&gt;
&lt;div class="outline-text-2" id="text-org5aafa10"&gt;
&lt;p&gt;
I've been thinking about running &lt;a href="https://jupyter.org"&gt;Jupyter notebooks&lt;/a&gt; in the cloud for
some fairly compute-intensive simulation. Specifically I want to do
epidemic and other simulations over complex networks. These are
CPU-intensive and don't make use of GPU acceleration (yet, anyway).
Using the cloud would make things easier to scale-out, especially
for those without access to a local compute cluster.
&lt;/p&gt;

&lt;p&gt;&lt;a href="https://simondobson.org/2022/12/02/jupyter-in-the-cloud/"&gt;Read more…&lt;/a&gt; (6 min remaining to read)&lt;/p&gt;&lt;/div&gt;&lt;/div&gt;</description><category>cloud computing</category><category>computational science</category><category>epydemic</category><category>jupyter</category><category>python</category><guid>https://simondobson.org/2022/12/02/jupyter-in-the-cloud/</guid><pubDate>Fri, 02 Dec 2022 16:36:55 GMT</pubDate></item></channel></rss>