As Ed Essey explained in Partitioning in PLINQ, partitioning is an important step in PLINQ execution. Partitioning splits up a single input sequence into multiple sequences that can be processed in parallel. This post further explains chunk partitioning, the most general partitioning scheme that works on any IEnumerable<T>.Chunk ...
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 pattern. For a given synchronous operation Xyz, the asynchronous version ...
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 work out, and we’ve had to prioritize certain scenarios over others.One ...
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 through a static property on Task, e.g.
var t = Task.Factory.StartNew(() => { &...
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, whether it be to wait for it, to continue from it, or the like. The primary type of ...
As we’ve mentioned previously, the .NET ThreadPool has undergone some serious renovations in .NET 4, improvements on which the Task Parallel Library and PLINQ both rely. Erika Parsons and Eric Eilebrecht are the PM and developer on the CLR team for the ThreadPool, and they’re featured in a great new Channel9 video covering ...
Prior to the .NET Framework 2.0, unhandled exceptions were largely ignored by the runtime. For example, if a work item queued to the ThreadPool threw an exception that went unhandled by that work item, the ThreadPool would eat that exception and continue on its merry way. Similarly, if a finalizer running on the finalizer thread ...
We exert a good deal of effort ensuring that the APIs we provide are consistent within Parallel Extensions as well as with the rest of the .NET Framework. This is from many angles, including behavior and general design, but also naming. So when there are slight differences in naming, it raises questions.One occurrence of such a ...
(image) Here’s a simple way to look at it. On a 4-core machine, take 4 million elements, divide this into 4 partitions of 1 million elements each, and give each of the 4 cores a million elements of data to process. Assuming that the data and the processing of the data is uniform, that all of the cores operate with the same ...
Exiting out of loops early is a fairly common pattern, one that doesn’t go away when parallelism is introduced. To help simplify these use cases, the Parallel.For and Parallel.ForEach methods support several mechanisms for breaking out of loops early, each of which has different behaviors and targets different requirements....