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	<title>Commentaires sur : Exploring other concurrency models</title>
	<atom:link href="http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/feed/" rel="self" type="application/rss+xml" />
	<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/</link>
	<description>Random thoughts of Jérémie Laval</description>
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		<title>Par : GSoC: the now and the next &#171; Yet Another [a compléter]</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-138</link>
		<dc:creator>GSoC: the now and the next &#171; Yet Another [a compléter]</dc:creator>
		<pubDate>Fri, 03 Jul 2009 21:52:27 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-138</guid>
		<description>[...] this post which describes in more details the ideas behind them and some [...]</description>
		<content:encoded><![CDATA[<p>[...] this post which describes in more details the ideas behind them and some [...]</p>
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		<title>Par : Programació concurrent + OOP ~ Actors Model: molt fàcil en Groovy &#171; Guaita</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-137</link>
		<dc:creator>Programació concurrent + OOP ~ Actors Model: molt fàcil en Groovy &#171; Guaita</dc:creator>
		<pubDate>Thu, 05 Mar 2009 07:33:06 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-137</guid>
		<description>[...] Bé, sembla que aquest paradigma (que existeix des dels 70) va guanyant adeptes ara que estan de moda els multi-core: més en Groovy (1, 2) , Java, Scala, Python-Ruby, Erlang, .NET [...]</description>
		<content:encoded><![CDATA[<p>[...] Bé, sembla que aquest paradigma (que existeix des dels 70) va guanyant adeptes ara que estan de moda els multi-core: més en Groovy (1, 2) , Java, Scala, Python-Ruby, Erlang, .NET [...]</p>
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		<title>Par : garuma</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-136</link>
		<dc:creator>garuma</dc:creator>
		<pubDate>Tue, 03 Mar 2009 11:58:58 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-136</guid>
		<description>Yeah, ultimately to parallelize something you have to be able to somehow split the problem into smaller subproblems.

The nice thing is that ParallelFx can do this splitting process for you in some case like the one you describe :

&lt;code&gt;ParallelEnumerable.Range(1, 100000).Where(IsPrime).ToList();&lt;/code&gt;

where IsPrime is a Func&lt;int, bool&gt;.</description>
		<content:encoded><![CDATA[<p>Yeah, ultimately to parallelize something you have to be able to somehow split the problem into smaller subproblems.</p>
<p>The nice thing is that ParallelFx can do this splitting process for you in some case like the one you describe :</p>
<p><code>ParallelEnumerable.Range(1, 100000).Where(IsPrime).ToList();</code></p>
<p>where IsPrime is a Func&lt;int, bool&gt;.</p>
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		<title>Par : Shamal Jayakody</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-135</link>
		<dc:creator>Shamal Jayakody</dc:creator>
		<pubDate>Tue, 03 Mar 2009 01:37:12 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-135</guid>
		<description>Focus on parallel algorithms of theoretical computer science,
In computer science, a parallel algorithm, as opposed to a traditional sequential algorithm, is one which can be executed a piece at a time on many different processing devices, and then put back together again at the end to get the correct result.

Some algorithms are easy to divide up into pieces like this. For example, splitting up the job of checking all of the numbers from one to a hundred thousand to see which are primes could be done by assigning a subset of the numbers to each available processor, and then putting the list of positive results back together.</description>
		<content:encoded><![CDATA[<p>Focus on parallel algorithms of theoretical computer science,<br />
In computer science, a parallel algorithm, as opposed to a traditional sequential algorithm, is one which can be executed a piece at a time on many different processing devices, and then put back together again at the end to get the correct result.</p>
<p>Some algorithms are easy to divide up into pieces like this. For example, splitting up the job of checking all of the numbers from one to a hundred thousand to see which are primes could be done by assigning a subset of the numbers to each available processor, and then putting the list of positive results back together.</p>
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		<title>Par : garuma</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-134</link>
		<dc:creator>garuma</dc:creator>
		<pubDate>Tue, 03 Mar 2009 01:16:12 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-134</guid>
		<description>You have to check out the source from SVN at http://code.google.com/p/mono-soc-2008/source/checkout (it&#039;s in trunk/parallelfx/System.Threading.Extensions)</description>
		<content:encoded><![CDATA[<p>You have to check out the source from SVN at <a href="http://code.google.com/p/mono-soc-2008/source/checkout" rel="nofollow">http://code.google.com/p/mono-soc-2008/source/checkout</a> (it&#8217;s in trunk/parallelfx/System.Threading.Extensions)</p>
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		<title>Par : Anon</title>
		<link>http://blog.neteril.org/2009/03/02/exploring-other-concurrency-models/comment-page-1/#comment-133</link>
		<dc:creator>Anon</dc:creator>
		<pubDate>Mon, 02 Mar 2009 23:58:43 +0000</pubDate>
		<guid isPermaLink="false">http://garuma.wordpress.com/?p=438#comment-133</guid>
		<description>Where is Mono.Threading.Actors? Couldn&#039;t find any information about it.</description>
		<content:encoded><![CDATA[<p>Where is Mono.Threading.Actors? Couldn&#8217;t find any information about it.</p>
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