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Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
In computer programming, foreach loop (or for-each loop) is a control flow statement for traversing items in a collection. foreach is usually used in place of a standard for loop statement . Unlike other for loop constructs, however, foreach loops [ 1 ] usually maintain no explicit counter: they essentially say "do this to everything in this ...
PowerShell is a task automation and configuration management program from Microsoft, consisting of a command-line shell and the associated scripting language.Initially a Windows component only, known as Windows PowerShell, it was made open-source and cross-platform on August 18, 2016, with the introduction of PowerShell Core. [5]
Parallel Extensions was the development name for a managed concurrency library developed by a collaboration between Microsoft Research and the CLR team at Microsoft. The library was released in version 4.0 of the .NET Framework. [1] It is composed of two parts: Parallel LINQ (PLINQ) and Task Parallel Library (TPL).
In these examples, if N < 1 then the body of loop may execute once (with I having value 1) or not at all, depending on the programming language. In many programming languages, only integers can be reliably used in a count-controlled loop. Floating-point numbers are represented imprecisely due to hardware constraints, so a loop such as
Through parallel processing, it is possible to reduce the total execution time of a program through sharing the processing load among multiple processors. The process of organizing statements to allow multiple processors to work on different portions of a loop is often referred to as parallelization .
The goal of the program is to do some net total task ("A+B"). If we write the code as above and launch it on a 2-processor system, then the runtime environment will execute it as follows. In an SPMD (single program, multiple data) system, both CPUs will execute the code. In a parallel environment, both will have access to the same data.
In the above code, we can execute all iterations of each "i" loop concurrently, i.e., turn each into a parallel loop. In such cases, it is often possible to make effective use of twice as many processors for a problem of array size 2N as for a problem of array size N. As in this example, scalable parallelism is typically a form of data parallelism.