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Concurrent and parallel programming languages involve multiple timelines. Such languages provide synchronization constructs whose behavior is defined by a parallel execution model. A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a ...
Kotlin, however kotlin.native.concurrent.Future is only usually used when writing Kotlin that is intended to run natively [35] Nim; Oxygene; Oz version 3 [36] Python concurrent.futures, since 3.2, [37] as proposed by the PEP 3148, and Python 3.5 added async and await [38] R (promises for lazy evaluation, still single threaded) Racket [39] Raku [40]
Implementations of the fork–join model will typically fork tasks, fibers or lightweight threads, not operating-system-level "heavyweight" threads or processes, and use a thread pool to execute these tasks: the fork primitive allows the programmer to specify potential parallelism, which the implementation then maps onto actual parallel execution. [1]
Chapel (programming language) Cilk; CMS Pipelines; Concurrent Collections; Concurrent Euclid; Concurrent ML; Constraint Handling Rules; Crystal (programming language) CS-4 (programming language) Curry (programming language)
The base goals of concurrent programming include correctness, performance and robustness. Concurrent systems such as Operating systems and Database management systems are generally designed [by whom?] to operate indefinitely, including automatic recovery from failure, and not terminate unexpectedly (see Concurrency control).
The fork–join model from the 1960s, embodied by multiprocessing tools like OpenMP, is an early example of a system ensuring all threads have completed before exit.. However, Smith argues that this model is not true structured concurrency as the programming language is unaware of the joining behavior, and is thus unable to enforce
Many concurrent programming languages have been developed more as research languages (e.g. Pict) rather than as languages for production use. However, languages such as Erlang, Limbo, and occam have seen industrial use at various times in the last 20 years. A non-exhaustive list of languages which use or provide concurrent programming facilities:
Compared to other parallel-processing models, Linda is more orthogonal in treating process coordination as a separate activity from computation, and it is more general in being able to subsume various levels of concurrency—uniprocessor, multi-threaded multiprocessor, or networked—under a single model.