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<oembed><version>1.0</version><provider_name>Microsoft Research</provider_name><provider_url>https://www.microsoft.com/en-us/research</provider_url><author_name>Jeff Running</author_name><author_url>https://www.microsoft.com/en-us/research/people/jeffrunn/</author_url><title>Energy Efficient Computing - Microsoft Research</title><type>rich</type><width>600</width><height>338</height><html>&lt;blockquote class="wp-embedded-content" data-secret="2Ekl0H9hB5"&gt;&lt;a href="https://www.microsoft.com/en-us/research/video/energy-efficient-computing/"&gt;Energy Efficient Computing&lt;/a&gt;&lt;/blockquote&gt;&lt;iframe sandbox="allow-scripts" security="restricted" src="https://www.microsoft.com/en-us/research/video/energy-efficient-computing/embed/#?secret=2Ekl0H9hB5" width="600" height="338" title="&#x201C;Energy Efficient Computing&#x201D; &#x2014; Microsoft Research" data-secret="2Ekl0H9hB5" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"&gt;&lt;/iframe&gt;&lt;script type="text/javascript"&gt;
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</html><thumbnail_url>https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/energy-efficient-computing-1.jpg</thumbnail_url><thumbnail_width>320</thumbnail_width><thumbnail_height>240</thumbnail_height><description>In this talk I give an overview of the algorithms we have developed at UCSD to significantly lower the energy consumption in computing systems. We derived optimal power management strategies for stationary workloads that have been implemented both in HW and SW. Run-time adaptation can be done via an online learning algorithm that selects among [&hellip;]</description></oembed>
