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The Parallel class represents a significant advancement in parallelizing managed loops. For many common scenarios, it just works, resulting in terrific speedups. However, while ideally Parallel.For could be all things to all people, such things rarely
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It’s very common in a parallel application to need random numbers for this or that operation. For situations where random numbers don’t need to be cryptographically-strong, the System.Random class is typically a fast-enough mechanism for generating values
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Thanks to everyone who attended our PDC pre-conference session yesterday on parallelism and concurrency! We had a wonderful turnout at the event, and David, Joe, and I all had a terrific time. Attached to this post are the slides we presented. (It turns
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One of the primary reasons we've released CTPs of Parallel Extensions is to solicit feedback on the design and functionality it provides. Does it provide all of the APIs you need to get your job done? Are there scenarios you wished the APIs
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We've received several questions on the MSDN Forums for Parallel Extensions about the performance of the Parallel class, and specifically of the loop constructs we provided in the CTP. We're very much aware that the performance of Parallel.For/ForEach
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Frequently when attempting to do multiple operations in parallel, ordering becomes an issue. Consider an application where I'm rendering and writing out to a video file frames of a movie: for ( int i = 0; i < numberOfFrames; i++) { var frame = GenerateFrame(i);
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Charles from Channel 9 sat down with several of us from the Parallel Computing Platform team to discuss the Task Parallel Library component of Parallel Extensions. A video of the conversation is now available on Channel9: http://channel9.msdn.com/Showpost.aspx?postid=384229
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When teaching recursion in an introductory computer science course, one of the most common examples used involves a tree data structure. Trees are useful in this regard as they are simple and recursive in nature, with a tree's children also being trees,
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