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Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. [1] Large problems can often be divided into smaller ones, which can then be solved at the same time. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism.
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 ...
Concurrency theory has been an active field of research in theoretical computer science. One of the first proposals was Carl Adam Petri 's seminal work on Petri nets in the early 1960s. In the years since, a wide variety of formalisms have been developed for modeling and reasoning about concurrency.
Task parallelism (also known as function parallelism and control parallelism) is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors.
In computer science, Linda is a coordination model that aids communication in parallel computing environments. Developed by David Gelernter, it is meant to be used alongside a full-fledged computation language like Fortran or C where Linda's role is to "create computational activities and to support communication among them". [3] [4] [5]
CUDA and OpenACC: CUDA and OpenACC (respectively) are parallel computing API platforms designed to allow a software engineer to utilize GPU's computational units for general purpose processing. Threading Building Blocks and RaftLib : Both open source programming environments that enable mixed data/task parallelism in C/C++ environments across ...
In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and their composition in programs. The value of a programming model can be judged on its generality : how well a range of different problems can be expressed for a variety of different architectures ...
[1] At the sub-routine (or procedure) level the grain size is typically a few thousand instructions. Medium-grained parallelism is achieved at sub-routine level. [1] At program-level, parallel execution of programs takes place. Granularity can be in the range of tens of thousands of instructions. [1] Coarse-grained parallelism is used at this ...