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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Performance Comparison of CUDA and OpenCL · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1005.2581/</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/1005.2581/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Performance Comparison of CUDA and OpenCL — mentioned by Robadob</title><link>https://news.ycombinator.com/item?id=11434903</link><guid isPermaLink="false">urn:hackerpapers:mention:1005.2581:11434903</guid><pubDate>Tue, 05 Apr 2016 22:01:05 GMT</pubDate><description>&lt;p&gt;I haven&amp;#x27;t seen any recent benchmarks, but ones from 2011 all seemed to show CUDA and OpenCL on open footing in terms of performance when optimised properly.[1][2] CUDA simply had better library support, and a more well defined and uniform architecture to target. Whereas OpenCL is likely to require more programming to fill in the gaps for library support, and different optimisations depending on the architecture you wish to target. I&amp;#x27;m guessing since then, the CUDA compiler may have improved somewhat in terms of optimisation based on some micro-benchmarking research I was looking the at the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1005.2581/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.PF</category></item><item><title>A Performance Comparison of CUDA and OpenCL — mentioned by agibsonccc</title><link>https://news.ycombinator.com/item?id=10052109</link><guid isPermaLink="false">urn:hackerpapers:mention:1005.2581:10052109</guid><pubDate>Thu, 13 Aug 2015 03:22:05 GMT</pubDate><description>&lt;p&gt;Need to run empirical benchmarks. CUDA is usually faster. I&amp;#x27;d like to run my own benchmarks with nd4j though. We have our own benchmark setup that works for every backend. It allows us to do some interesting things. Cuda itself is usually faster with data transfer latency though[1]. Looking forward to running these ourselves after our opencl support kicks in (only the kernels are written =/) I plan on basing the work for open cl on our cuda work which is fairly well established at this point (mainly doing optimizations not much change in architecture) [1]: http://arxiv.org/pdf/1005.2581.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1005.2581/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.PF</category></item></channel></rss>
