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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Learned Cache Eviction Framework with Minimal Overhead · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2301.11886/</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/2301.11886/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Learned Cache Eviction Framework with Minimal Overhead — mentioned by benlivengood</title><link>https://news.ycombinator.com/item?id=38913909</link><guid isPermaLink="false">urn:hackerpapers:mention:2301.11886:38913909</guid><pubDate>Mon, 08 Jan 2024 16:02:47 GMT</pubDate><description>&lt;p&gt;https://arxiv.org/abs/2301.11886 for storage and CDN caches achieves pretty remarkable improvements over standard heuristics by using common heuristics as a filter for ML decisions. I imagine even TLB caches might achieve some benefit from ML models with batched pre-prediction as done in MAT, but L1-3 are almost certainly too high throughout.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2301.11886/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.OS</category></item></channel></rss>
