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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>MACKO: Sparse Matrix-Vector Multiplication for Low Sparsity · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2511.13061/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2511.13061/feed.xml" rel="self" type="application/rss+xml" /><item><title>MACKO: Sparse Matrix-Vector Multiplication for Low Sparsity — HN submission</title><link>https://news.ycombinator.com/item?id=46046106</link><guid isPermaLink="false">urn:hackerpapers:submission:2511.13061:46046106</guid><pubDate>Tue, 25 Nov 2025 14:35:00 GMT</pubDate><description>&lt;p&gt;Show HN: Sparse Matrix-Vector Multiplication that works at 30–90% sparsity&lt;/p&gt;&lt;p&gt;To get benefits from sparsity, you usually need to have very sparse matrices, impose some structure on the sparsity pattern or have specialized hardware. None of it is the case if you want to rune pruned LLMs on consumer devices. I wanted to see how far can you push it on a GPU and ended up with this. Blog: https://www.grizzlytech.dev/blog/macko-spmv Paper: https://arxiv.org/abs/2511.13061 Code (example with torch): https://github.com/vlejd/macko_spmv&lt;/p&gt;&lt;p&gt;7 points; 5 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2511.13061/"&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>
