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This article lists concurrent and parallel programming languages, categorizing them by a defining paradigm.Concurrent and parallel programming languages involve multiple timelines.
A few interpreted programming languages have implementations (e.g., Ruby MRI for Ruby, CPython for Python) which support threading and concurrency but not parallel execution of threads, due to a global interpreter lock (GIL). The GIL is a mutual exclusion lock held by the interpreter that can prevent the interpreter from simultaneously ...
Thread scheduling is also a major problem in multithreading. Merging data from two processes can often incur significantly higher costs compared to processing the same data on a single thread, potentially by two or more orders of magnitude due to overheads such as inter-process communication and synchronization. [2] [3] [4]
In .NET System.Threading.Tasks.Task<T> represents a read-only view. Resolving the value can be done via System.Threading.Tasks.TaskCompletionSource<T>. Support for read-only views is consistent with the principle of least privilege, since it enables the ability to set the value to be restricted to subjects that need to set it. In a system that ...
Python 2.5 implements better support for coroutine-like functionality, based on extended generators Python 3.3 improves this ability, by supporting delegating to a subgenerator ( PEP 380 ) Python 3.4 introduces a comprehensive asynchronous I/O framework as standardized in PEP 3156 , which includes coroutines that leverage subgenerator delegation
This approach is characteristic of functional programming and is also used by the string implementations in Java, C#, and Python. (See Immutable object .) The second class of approaches are synchronization-related, and are used in situations where shared state cannot be avoided:
[3] Cooperative multitasking is similar to async/await in languages, such as JavaScript or Python , that feature a single-threaded event-loop in their runtime. This contrasts with cooperative multitasking in that await cannot be invoked from a non-async function, but only an async function, which is a kind of coroutine .
The size of a thread pool is the number of threads kept in reserve for executing tasks. It is usually a tunable parameter of the application, adjusted to optimize program performance. [3] Deciding the optimal thread pool size is crucial to optimize performance.