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Related posts: What's new in Beta 2 for the Task Parallel Library (1/3) What's new in Beta 2 for the Task Parallel Library (3/3) Last week, we talked about how TPL adopted a new, better cancellation model. Today, we’ll cover a change that makes Tasks
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Related posts: What's new in Beta 2 for the Task Parallel Library? (Part 2/3) What's new in Beta 2 for the Task Parallel Library? (Part 3/3) Visual Studio 2010 and .NET 4 Beta 2 is here! In terms of completeness and readiness for production coding, Beta
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Common operations like map and filter are available in parallelized form through PLINQ, though the names differ. A map can be achieved with PLINQ’s Select operator, and a filter with PLINQ’s Where operator. For example, I could implement a ParallelMap
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The Task abstractions in .NET 4 run on instances of the TaskScheduler class. Two implementations of TaskScheduler ship as part of the .NET Framework 4. The first is the default scheduler, which is integrated with the .NET 4 ThreadPool and
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Every System.Threading.Tasks.Task instance goes through a lifecycle, and it only makes this journey once. To provide insight into where in that lifecycle a given Task is, the Task class provides an instance Status property. That property returns
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In this post, we’ll investigate some ways that Parallel Extensions can be used to introduce parallelism and asynchrony to I/O scenarios. Here’s a simple scenario. I want to retrieve data from a number of web resources. static string[] Resources = new
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One of the ways in which the Task Parallel Library achieves good performance is through “work-stealing”. Work-stealing is supported in the .NET 4 ThreadPool for access through the Task Parallel Library and its default scheduler. This manifests
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More and more, developers are realizing the significant scalability advantages that asynchronous programming can provide, especially as it relates to I/O. Consider an application that needs to copy data from one stream to another stream, such as is being
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In a previous post, it was demonstrated how for loops with very small loop bodies could be parallelized by creating an iterator over ranges, and then using Parallel.ForEach over those ranges. A similar technique can be used to write parallel loops over
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One of the great features that crosses all of Parallel Extensions types is a consistent approach to cancellation (see http://blogs.msdn.com/pfxteam/archive/2009/05/22/9635790.aspx ). In this post we explore some of the ways cancellation is used in Parallel
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As has been discussed previously, one of the new features in the Task Parallel Library is TaskCompletionSource<TResult> , which enables the creation of a Task<TResult> that represents any other asynchronous operation. There are a wide variety
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The Asynchronous Programming Model (APM) in the .NET Framework has been around since .NET 1.0 and is the most common pattern for asynchrony in the Framework. Even if you’re not familiar with the name, you’re likely familiar with the core of the
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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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The core entity in the Task Parallel Library around which everything else revolves is System.Threading.Tasks.Task. The most common way of creating a Task will be through the StartNew method on the TaskFactory class, a default instance of which is exposed
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The Task Parallel Library is centered around the Task class and its derived Task<TResult> . The main purpose of these types is to represent the execution of an asynchronous workload and to provide an object with a means to operate on that workload,
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