- Writing parallel and concurrent code in C#.
- Overview: Channels are used for producer-consumer scenarios, where one or more tasks are producing data and one or more tasks are consuming that data. They are part of the
System.Threading.Channelsnamespace introduced in .NET Core 3.0. - Usage: Channels are useful for coordinating between async operations, allowing for efficient and safe passing of data between threads or tasks.
- Data Parallelism: Involves breaking down a data set into smaller chunks and processing each chunk in parallel. This is particularly effective for operations that can be performed independently on segments of data.
- Task Parallelism: Refers to executing different tasks in parallel, where each task can perform a different operation. It’s useful when different operations can be performed concurrently.
- Overview: PLINQ extends LINQ to allow query operations to run in parallel, automatically splitting the data source across multiple threads and combining the results once all threads complete.
- Usage: Best suited for CPU-intensive query operations over large data sets. You can convert a LINQ query to PLINQ by calling the
.AsParallel()method on the data source.
- Overview: The
System.Threading.Tasks.Parallelclass provides parallel versions offorandforeachloops (Parallel.ForandParallel.ForEach), as well as a method for running a set of actions in parallel (Parallel.Invoke). - Usage: Simplifies parallelizing loops and tasks without manually managing threads or tasks.
- Overview: In .NET, task parallelism is implemented through the
TaskandTask<T>classes in theSystem.Threading.Tasksnamespace, allowing for asynchronous and parallel operations. - Usage: You can start new tasks with
Task.Run()or create tasks for parallel operations usingTask.WhenAll()orTask.WhenAny()for coordinating multiple tasks.
- Overview: The
System.Collections.Concurrentnamespace provides thread-safe collection classes likeConcurrentBag<T>,ConcurrentQueue<T>,ConcurrentStack<T>, andConcurrentDictionary<TKey,TValue>. - Usage: These collections are designed for high-performance scenarios where multiple threads are adding, removing, or updating items concurrently.
- Overview:
BlockingCollection<T>is a thread-safe collection class that provides blocking and bounding capabilities for both producer and consumer scenarios. - Usage: It is particularly useful in scenarios where producers may produce data at a faster rate than consumers can consume it, or vice versa, as it can limit the size of the collection and block adding or taking operations based on the state of the collection.