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    <title>2024s on STATS/BIODS 352</title>
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      <title>Schedule</title>
      <link>https://stats352.stanford.edu/2024/schedule/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
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      <description>&lt;p&gt;Any changes to the schedule will be reflected here, so we advise you to check this page often.&lt;/p&gt;&#xA;&lt;p&gt;We will use &lt;a href=&#34;https://canvas.stanford.edu/courses/188401&#34;&gt;Canvas&lt;/a&gt; for class announcements, materials and other administrivia.&lt;/p&gt;&#xA;&lt;p&gt;The class meets Wednesdays, 1:30&amp;ndash;2:50pm, in &lt;a href=&#34;http://campus-map.stanford.edu/?srch=Hewlett+Teaching+Center+Rm+101&#34;&gt;Hewlett Teaching Center, Room 101&lt;/a&gt;. (The location was changed after the first class.)&lt;/p&gt;&#xA;&lt;h2 id=&#34;april-3-24&#34;&gt;April 3, 24&lt;/h2&gt;&#xA;&lt;table&gt;&#xA;  &lt;thead&gt;&#xA;      &lt;tr&gt;&#xA;          &lt;th style=&#34;text-align: center&#34;&gt;&lt;/th&gt;&#xA;      &lt;/tr&gt;&#xA;  &lt;/thead&gt;&#xA;  &lt;tbody&gt;&#xA;      &lt;tr&gt;&#xA;          &lt;td style=&#34;text-align: center&#34;&gt;&lt;img src=&#34;https://stats352.stanford.edu/images/naras.jpg&#34; alt=&#34;&#34;&gt;&lt;/td&gt;&#xA;      &lt;/tr&gt;&#xA;  &lt;/tbody&gt;&#xA;&lt;/table&gt;&#xA;&lt;p&gt;&lt;a href=&#34;https://naras.su.domains/&#34;&gt;&lt;strong&gt;Balasubramanian Narasimhan&lt;/strong&gt;&lt;/a&gt; (Stanford University)&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Containers, Workflows and Tools for HPC&lt;/em&gt;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;Efficient High Performance Computing demands robust workflows and tools that let scientists &amp;ldquo;do the right thing&amp;rdquo; as easily as possible. Those right things include removal of drugery by recognizing repeated patterns to be exploited, yet allowing for the inevitable changes, while paying close attention to issues of reproducibility. I will discuss a number of tools that make this possible and also delve into virtualization using containers, which are essentially virtual machines or collections of them that can moved to on-prem or cloud infrastructures. These techniques will find use both in the existing Stanford HPC infrastructure (including the soon-to-be GPU cluster) and elsewhere. No background will be assumed, and I will start from the basics. These lectures will be very hands-on and details on open-source software tools that need to be installed will be provided in due course.&lt;/p&gt;</description>
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