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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2103.10891/</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/2103.10891/feed.xml" rel="self" type="application/rss+xml" /><item><title>Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More — mentioned by gumby</title><link>https://news.ycombinator.com/item?id=26745728</link><guid isPermaLink="false">urn:hackerpapers:mention:2103.10891:26745728</guid><pubDate>Fri, 09 Apr 2021 01:08:53 GMT</pubDate><description>&lt;p&gt;Here&amp;#x27;s the new paper referred to in the article: https://arxiv.org/abs/2103.10891&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2103.10891/"&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>Accelerating SLIDE Deep Learning on Modern CPUs: Vectorization, Quantizations, Memory Optimizations, and More — mentioned by exegete</title><link>https://news.ycombinator.com/item?id=26745479</link><guid isPermaLink="false">urn:hackerpapers:mention:2103.10891:26745479</guid><pubDate>Fri, 09 Apr 2021 00:33:22 GMT</pubDate><description>&lt;p&gt;Paper: https://arxiv.org/abs/1903.03129 Code: https://github.com/keroro824/HashingDeepLearning Edit: Here is the new paper referred to https://arxiv.org/abs/2103.10891 Here is the new code: https://github.com/RUSH-LAB/SLIDE The paper I linked above was the first paper of which this is supposed to be an improvement.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2103.10891/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
