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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2306.09633/</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/2306.09633/feed.xml" rel="self" type="application/rss+xml" /><item><title>The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement — mentioned by dogleg77</title><link>https://news.ycombinator.com/item?id=42299913</link><guid isPermaLink="false">urn:hackerpapers:mention:2306.09633:42299913</guid><pubDate>Mon, 02 Dec 2024 20:12:12 GMT</pubDate><description>&lt;p&gt;Markov&amp;#x27;s article has been on arxiv since 2023 before the perceived conflict. https://arxiv.org/abs/2306.09633 All his affiliations have been disclosed and likely known to Jeff Dean. Jeff is simply unable to respond to Markov&amp;#x27;s article in the technical dimension and is resorting to dirty tricks instead.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2306.09633/"&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>The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement — mentioned by vighneshiyer</title><link>https://news.ycombinator.com/item?id=41673769</link><guid isPermaLink="false">urn:hackerpapers:mention:2306.09633:41673769</guid><pubDate>Fri, 27 Sep 2024 18:05:08 GMT</pubDate><description>&lt;p&gt;This work from Google (original Nature paper: https://www.nature.com/articles/s41586-021-03544-w) has been credibly criticized by several researchers in the EDA CAD discipline. These papers are of interest: - A rebuttal by a researcher within Google who wrote this at the same time as the &amp;quot;AlphaChip&amp;quot; work was going on (&amp;quot;Stronger Baselines for Evaluating Deep Reinforcement Learning in Chip Placement&amp;quot;): http://47.190.89.225/pub/education/MLcontra.pdf - The 2023 ISPD paper from a group at UCSD (&amp;quot;Assessment of Reinforcement Learning for Macro Placement&amp;quot;)…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2306.09633/"&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>The False Dawn: Reevaluating Google's Reinforcement Learning for Chip Macro Placement — HN submission</title><link>https://news.ycombinator.com/item?id=36501194</link><guid isPermaLink="false">urn:hackerpapers:submission:2306.09633:36501194</guid><pubDate>Wed, 28 Jun 2023 01:36:31 GMT</pubDate><description>&lt;p&gt;The False Dawn: Reevaluating Google&amp;#x27;s RL for Chip Macro Placement&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;71 points; 17 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2306.09633/"&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>
