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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Load Thresholds for Cuckoo Hashing with Overlapping Blocks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1707.06855/</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/1707.06855/feed.xml" rel="self" type="application/rss+xml" /><item><title>Load Thresholds for Cuckoo Hashing with Overlapping Blocks — mentioned by FreakLegion</title><link>https://news.ycombinator.com/item?id=28214683</link><guid isPermaLink="false">urn:hackerpapers:mention:1707.06855:28214683</guid><pubDate>Tue, 17 Aug 2021 20:49:53 GMT</pubDate><description>&lt;p&gt;Like with Bloom filters (which also draw their power from hashing items into multiple buckets), the statistical guarantees are quite strong, and things work well in practice. There are other options for the insertion algorithm than the standard random walk, too. E.g. take a look at page 18 of &amp;quot;Load Thresholds for Cuckoo Hashing with Overlapping Blocks&amp;quot; [1] for empirical data on 2-3 hash functions for 2-3 size windows. They don&amp;#x27;t show 4- or 8-size windows, but you get the gist. Like nullc says below, it&amp;#x27;s trivial to tune things for your requirements. Want fast insertions? Overprovision. Want…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1707.06855/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.DS</category></item></channel></rss>
