The Task Parallel Library is part of the .NET Framework since .NET 4. It is a set of APIs to enable developers to program asynchronous applications.

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TPL Dataflow is an in-process actor library on top of the Task Parallel Library enabling more robust concurrent programming.

In general you have to know that Task.Run is more restricted version of Task.Factory.StartNew. Task.Run sets default which fit for most common cases. Task.Factory.StartNew is there for advance scenarios.

Huge volumes of data need near-supercomputer power to process and analyze it all. You can get there with the .NET Task Parallel Library.

In this article we are going to look at how we can squeeze the best performance out of an easily parallelizable problem by rewriting the same basic implementation using some of the most widely used multi-threading tools available in .NET. We will be covering different .NET technologies such as PLINQ, BlockingCollection, Parallel class as well as TPL Dataflow in conjunction with patterns such as MapReduce, ActorModel as well as ProducerConsumer while trying to achieve optimal parallelization and minimize the cost of synchronization between the threads.