If you do them you’ll get different numbers but you should have the same relative performance and resource usage. NOTE: all the examples below are done on a single machine and in the same conditions. These windows show something only when the application is in debug mode and in Break All state.įor more info on how to use the Parallel Stacks feature please check the Official MSDN Walkthrough: Debugging a Parallel Application in Visual Studio. This is pointless (we’re not even storing the result), but is a great example of a CPU bound operation: for ( int i = 0 i Debug -> Windows -> Parallel Stacks and Tasks. One such example (maybe not the best one, but it illustrates my point exactly) would be calculating the sine of an angle. CPU bound or compute bound means that you have a problem to solve/calculate and you actively need to use the processor to perform the calculation. Sometimes concepts are difficult to follow without proper examples. CPU bound operations? - then expose it as a synchronous/plain implementation, the caller/user of the operation will wrap it in a Task.Run if needed.I/O-bound operations? - then await asynchronous I/O methods provided by the.Source: the TAP.docx document (check in the resources below) Language-based asynchrony support hides callbacks by allowing asynchronous operations to be awaited within normal control flow, with compiler-generated code targeting this same API-level support. For Tasks, this is achieved through methods like ContinueWith. If a method is purely compute-bound, it should be exposed only as a synchronous implementation a consumer may then choose whether to wrap an invocation of that synchronous method into a Task for their own purposes of offloading the work to another thread and/or to achieve parallelism.Īt the API level, the way to achieve waiting without blocking is to provide callbacks. However, when exposed publicly from a library, TAP implementations should only be provided for workloads that involve I/O-bound operations (they may also involve computation, but should not be purely computation). Here’s what Stephen Toub has to say about this:īoth compute-bound and I/O-bound asynchronous operations may be implemented as TAP methods. There are 2 types of operations that have to be considered: CPU bound and I/O bound when deciding what to use. This post is about asynchronous programming in C# with the Task-based Asynchronous Pattern, so let’s see when and how to use it. Source: Stackoverflow When to use synchronous/asynchronous? Parallelism is when tasks literally run at the same time, e.g., on a multicore processor. For example, multitasking on a single-core machine. It doesn’t necessarily mean they’ll ever both be running at the same instant. Source: Wikipedia Concurrency vs ParallelismĬoncurrency is when two or more tasks can start, run, and complete in overlapping time periods. Multithreading is the ability of a central processing unit (CPU) or a single core in a multi-core processor to execute multiple processes or threads concurrently, appropriately supported by the operating system. When you execute something asynchronously, you can move on to another task before it finishes. When you execute something synchronously, you wait for it to finish before moving on to another task. To clear up the confusion we’re going to see what all the fancy words below actually mean: This post compiles my research on this subject so you’ll see lots of quotes from various sources (official and trusted third parties). Asynchronous programming causes a lot of confusion because the documentation is a bit lacking and this results in awfully bad implementations.
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