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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.
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".
Parallel I/O, in the context of a computer, means the performance of multiple input/output operations at the same time, for instance simultaneously outputs to storage devices and display devices. [1] It is a fundamental feature of operating systems .
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 ...
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.
Atanasoff–Berry computer, the first computer with parallel processing [1] Instruction-level parallelism (ILP) is the parallel or simultaneous execution of a sequence of instructions in a computer program. More specifically, ILP refers to the average number of instructions run per step of this parallel execution. [2]: 5
An initial version of this model was introduced, under the MapReduce name, in a 2010 paper by Howard Karloff, Siddharth Suri, and Sergei Vassilvitskii. [2] As they and others showed, it is possible to simulate algorithms for other models of parallel computation, including the bulk synchronous parallel model and the parallel RAM, in the massively parallel communication model.
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 ...