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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1603.07341/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1603.07341/feed.xml" rel="self" type="application/rss+xml" /><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — mentioned by cbennett</title><link>https://news.ycombinator.com/item?id=12624718</link><guid isPermaLink="false">urn:hackerpapers:mention:1603.07341:12624718</guid><pubDate>Sun, 02 Oct 2016 22:58:52 GMT</pubDate><description>&lt;p&gt;Glad to hear you find it exciting. I do too.. its a really hot field at the moment and I mean that in the good, not bad way ;) Lots of groups working in parallel on somewhat orthogonal design and architecture issues, with a variety of different considered devices, but a common basis set is emerging ;) So, here&amp;#x27;s the paper I mentioned above. I think this is very methodical and inventive and definitely one of the best yet at considering confluence of DNNs and memristive (ReRAM) devices. A quick search revealed this was already on HN. https://arxiv.org/abs/1603.07341 So, I already mentioned the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — HN submission</title><link>https://news.ycombinator.com/item?id=11400654</link><guid isPermaLink="false">urn:hackerpapers:submission:1603.07341:11400654</guid><pubDate>Thu, 31 Mar 2016 21:23:14 GMT</pubDate><description>&lt;p&gt;Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — HN submission</title><link>https://news.ycombinator.com/item?id=11367773</link><guid isPermaLink="false">urn:hackerpapers:submission:1603.07341:11367773</guid><pubDate>Sat, 26 Mar 2016 22:33:29 GMT</pubDate><description>&lt;p&gt;Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — HN submission</title><link>https://news.ycombinator.com/item?id=11364943</link><guid isPermaLink="false">urn:hackerpapers:submission:1603.07341:11364943</guid><pubDate>Sat, 26 Mar 2016 08:52:27 GMT</pubDate><description>&lt;p&gt;IBM researchers propose new Deep Learning chip 30,000X improvement&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — HN submission</title><link>https://news.ycombinator.com/item?id=11362803</link><guid isPermaLink="false">urn:hackerpapers:submission:1603.07341:11362803</guid><pubDate>Fri, 25 Mar 2016 21:27:32 GMT</pubDate><description>&lt;p&gt;Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;4 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices — HN submission</title><link>https://news.ycombinator.com/item?id=11359865</link><guid isPermaLink="false">urn:hackerpapers:submission:1603.07341:11359865</guid><pubDate>Fri, 25 Mar 2016 13:24:44 GMT</pubDate><description>&lt;p&gt;Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1603.07341/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
