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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Image Classification at Supercomputer Scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1811.06992/</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/1811.06992/feed.xml" rel="self" type="application/rss+xml" /><item><title>Image Classification at Supercomputer Scale — mentioned by frankchn</title><link>https://news.ycombinator.com/item?id=19249680</link><guid isPermaLink="false">urn:hackerpapers:mention:1811.06992:19249680</guid><pubDate>Mon, 25 Feb 2019 21:35:43 GMT</pubDate><description>&lt;p&gt;The authors trained ResNet-50 in 7.3 minutes at 75.3% accuracy. As a comparison, a Google TPUv3 pod with 1024 chips got to 75.2% accuracy with ResNet-50 in 1.8 minutes, and 76.2% accuracy in 2.2 minutes with an optimizer change and distributed batch normalization [1]. [1]: https://arxiv.org/abs/1811.06992&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1811.06992/"&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>
