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Parallel programming models are closely related to models of computation. A model of parallel computation is an abstraction used to analyze the cost of computational processes, but it does not necessarily need to be practical, in that it can be implemented efficiently in hardware and/or software. A programming model, in contrast, does ...
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 ...
Such parallel programming models can be classified according to abstractions that reflect the hardware, such as shared memory, distributed memory with message passing, notions of place visible in the code, and so forth. These can be considered flavors of programming paradigm that apply to only parallel languages and programming models.
A concise reference for the programming paradigms listed in this article. Concurrent programming – have language constructs for concurrency, these may involve multi-threading, support for distributed computing, message passing, shared resources (including shared memory), or futures
Concurrent programming languages, libraries, APIs, and parallel programming models (such as algorithmic skeletons) have been created for programming parallel computers. These can generally be divided into classes based on the assumptions they make about the underlying memory architecture—shared memory, distributed memory, or shared ...
Go—for system programming, with a concurrent programming model based on CSP; Haskell—concurrent, and parallel functional programming language [13] Hume—functional, concurrent, for bounded space and time environments where automata processes are described by synchronous channels patterns and message passing; Io—actor-based concurrency
In computer science, stream processing (also known as event stream processing, data stream processing, or distributed stream processing) is a programming paradigm which views streams, or sequences of events in time, as the central input and output objects of computation.
The MIMD-based paradigms category subsumes systems in which a specific programming or execution paradigm is at least as fundamental to the architectural design as structural considerations are. Thus, the design of dataflow architectures and reduction machines is as much the product of supporting their distinctive execution paradigm as it is a ...