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<?xml-stylesheet type="text/xsl" media="screen" href="/~d/styles/atom10full.xsl"?><?xml-stylesheet type="text/css" media="screen" href="http://feeds.feedburner.com/~d/styles/itemcontent.css"?><feed xmlns="http://www.w3.org/2005/Atom" xmlns:openSearch="http://a9.com/-/spec/opensearch/1.1/" xmlns:georss="http://www.georss.org/georss" xmlns:gd="http://schemas.google.com/g/2005" xmlns:thr="http://purl.org/syndication/thread/1.0" xmlns:feedburner="http://rssnamespace.org/feedburner/ext/1.0" gd:etag="W/&quot;DEICRH4-fSp7ImA9WhRRFE4.&quot;"><id>tag:blogger.com,1999:blog-7191846071852978576</id><updated>2011-11-27T15:29:25.055-08:00</updated><category term="CUDA" /><category term="GPU" /><category term="F#" /><category term="Parallel programming" /><category term=".Net" /><title>Alex Slesarenko's blog</title><subtitle type="html" /><link rel="http://schemas.google.com/g/2005#feed" type="application/atom+xml" href="http://slesarenko.blogspot.com/feeds/posts/default" /><link rel="alternate" type="text/html" href="http://slesarenko.blogspot.com/" /><author><name>Alex Slesarenko</name><uri>http://www.blogger.com/profile/10253205349391319347</uri><email>noreply@blogger.com</email><gd:image rel="http://schemas.google.com/g/2005#thumbnail" width="16" height="16" src="http://img2.blogblog.com/img/b16-rounded.gif" /></author><generator version="7.00" uri="http://www.blogger.com">Blogger</generator><openSearch:totalResults>2</openSearch:totalResults><openSearch:startIndex>1</openSearch:startIndex><openSearch:itemsPerPage>25</openSearch:itemsPerPage><atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="self" type="application/atom+xml" href="http://feeds.feedburner.com/AlexSlesarenkosBlog" /><feedburner:info uri="alexslesarenkosblog" /><atom10:link xmlns:atom10="http://www.w3.org/2005/Atom" rel="hub" href="http://pubsubhubbub.appspot.com/" /><entry gd:etag="W/&quot;DEINRXY_cCp7ImA9WxJVEkw.&quot;"><id>tag:blogger.com,1999:blog-7191846071852978576.post-1274450002659860128</id><published>2009-06-23T13:06:00.000-07:00</published><updated>2009-06-28T12:16:34.848-07:00</updated><app:edited xmlns:app="http://www.w3.org/2007/app">2009-06-28T12:16:34.848-07:00</app:edited><category scheme="http://www.blogger.com/atom/ns#" term="Parallel programming" /><category scheme="http://www.blogger.com/atom/ns#" term="CUDA" /><category scheme="http://www.blogger.com/atom/ns#" term="F#" /><category scheme="http://www.blogger.com/atom/ns#" term="GPU" /><category scheme="http://www.blogger.com/atom/ns#" term=".Net" /><title>CUDA programming in F#: Part 2, Accelerating Mandelbrot sample</title><link rel="replies" type="application/atom+xml" href="http://slesarenko.blogspot.com/feeds/1274450002659860128/comments/default" title="Post Comments" /><link rel="replies" type="text/html" href="http://slesarenko.blogspot.com/2009/06/cuda-programming-in-f-part-2.html#comment-form" title="1 Comments" /><link rel="edit" type="application/atom+xml" href="http://www.blogger.com/feeds/7191846071852978576/posts/default/1274450002659860128?v=2" /><link rel="self" type="application/atom+xml" href="http://www.blogger.com/feeds/7191846071852978576/posts/default/1274450002659860128?v=2" /><link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/AlexSlesarenkosBlog/~3/6tzuFgyj_eY/cuda-programming-in-f-part-2.html" title="CUDA programming in F#: Part 2, Accelerating Mandelbrot sample" /><author><name>Alex Slesarenko</name><uri>http://www.blogger.com/profile/10253205349391319347</uri><email>noreply@blogger.com</email><gd:image rel="http://schemas.google.com/g/2005#thumbnail" width="16" height="16" src="http://img2.blogblog.com/img/b16-rounded.gif" /></author><thr:total>1</thr:total><content type="html">In the previous post (CUDA programming in F#: Part 1), we talked about how to setup dev environment to get started with CUDA programming in F#.  BitonicSort sample used there is a classical parallel sorting algorithm, with non trivial GPU kernel (taken from CUDA SDK) . Unfortunately, it's not good enough to evaluate benefits of GPU acceleration as it has execution time comparable to CPU.This time
&lt;p&gt;&lt;a href="http://feedads.g.doubleclick.net/~a/1TDBNZjxPHFCwYjcKP-cqfJ6h64/0/da"&gt;&lt;img src="http://feedads.g.doubleclick.net/~a/1TDBNZjxPHFCwYjcKP-cqfJ6h64/0/di" border="0" ismap="true"&gt;&lt;/img&gt;&lt;/a&gt;&lt;br/&gt;
&lt;a href="http://feedads.g.doubleclick.net/~a/1TDBNZjxPHFCwYjcKP-cqfJ6h64/1/da"&gt;&lt;img src="http://feedads.g.doubleclick.net/~a/1TDBNZjxPHFCwYjcKP-cqfJ6h64/1/di" border="0" ismap="true"&gt;&lt;/img&gt;&lt;/a&gt;&lt;/p&gt;&lt;img src="http://feeds.feedburner.com/~r/AlexSlesarenkosBlog/~4/6tzuFgyj_eY" height="1" width="1"/&gt;</content><feedburner:origLink>http://slesarenko.blogspot.com/2009/06/cuda-programming-in-f-part-2.html</feedburner:origLink></entry><entry gd:etag="W/&quot;CUYAQHcyfCp7ImA9WxJVEUU.&quot;"><id>tag:blogger.com,1999:blog-7191846071852978576.post-6610319719357741430</id><published>2009-05-15T14:27:00.000-07:00</published><updated>2009-06-28T02:59:01.994-07:00</updated><app:edited xmlns:app="http://www.w3.org/2007/app">2009-06-28T02:59:01.994-07:00</app:edited><category scheme="http://www.blogger.com/atom/ns#" term="Parallel programming" /><category scheme="http://www.blogger.com/atom/ns#" term="CUDA" /><category scheme="http://www.blogger.com/atom/ns#" term="F#" /><category scheme="http://www.blogger.com/atom/ns#" term="GPU" /><category scheme="http://www.blogger.com/atom/ns#" term=".Net" /><title>CUDA programming in F#: Part 1, Getting started</title><link rel="replies" type="application/atom+xml" href="http://slesarenko.blogspot.com/feeds/6610319719357741430/comments/default" title="Post Comments" /><link rel="replies" type="text/html" href="http://slesarenko.blogspot.com/2009/03/cuda-programming-in-f-part-1-getting.html#comment-form" title="2 Comments" /><link rel="edit" type="application/atom+xml" href="http://www.blogger.com/feeds/7191846071852978576/posts/default/6610319719357741430?v=2" /><link rel="self" type="application/atom+xml" href="http://www.blogger.com/feeds/7191846071852978576/posts/default/6610319719357741430?v=2" /><link rel="alternate" type="text/html" href="http://feedproxy.google.com/~r/AlexSlesarenkosBlog/~3/osecX6CkZsk/cuda-programming-in-f-part-1-getting.html" title="CUDA programming in F#: Part 1, Getting started" /><author><name>Alex Slesarenko</name><uri>http://www.blogger.com/profile/10253205349391319347</uri><email>noreply@blogger.com</email><gd:image rel="http://schemas.google.com/g/2005#thumbnail" width="16" height="16" src="http://img2.blogblog.com/img/b16-rounded.gif" /></author><media:thumbnail xmlns:media="http://search.yahoo.com/mrss/" url="http://2.bp.blogspot.com/_DNDWCUefiYE/Sj0rQB6WRnI/AAAAAAAAAVY/NMgliu74Pug/s72-c/DeviceQuery.gif" height="72" width="72" /><thr:total>2</thr:total><content type="html">If you develop computationaly intensive applications, you will probably benefit from massive parallelization on CUDA devices. CUDA is a technology that can be used to harness full power of NVIDIA GPU device(s) installed on usual computer (server or desktop) for general purpose computations. Many applications can be parallelized using data-parallel algorithms and executed on CUDA enabled devices 
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