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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Connected Components at Scale via Local Contractions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1807.10727/</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/1807.10727/feed.xml" rel="self" type="application/rss+xml" /><item><title>Connected Components at Scale via Local Contractions — mentioned by moab</title><link>https://news.ycombinator.com/item?id=20143470</link><guid isPermaLink="false">urn:hackerpapers:mention:1807.10727:20143470</guid><pubDate>Mon, 10 Jun 2019 02:41:27 GMT</pubDate><description>&lt;p&gt;Here are a few references that solve problems on very large graphs: [1] implements work-efficient parallel algorithms for a list of fundamental graph problems. They report times on a O(200B) edge graph on a single multicore. [2] reports distributed running times for BFS, connectivity, PageRank, and SSSP on a large number of distributed hosts. The times are usually slower than the single-machine times, despite using two orders of magnitude more threads. [3] Reports connectivity times on a truly large graph that is not publicly available (several trillions of edges). My feeling is that unless…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1807.10727/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.DC</category></item></channel></rss>
