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Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance [1] to describe a computing paradigm that researchers had been investigating since the early 1980s. [2] This paradigm is also called Independence architectures.
In computing, multiple instruction, multiple data (MIMD) is a technique employed to achieve parallelism. Machines using MIMD have a number of processor cores that function asynchronously and independently. At any time, different processors may be executing different instructions on different pieces of data.
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.
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.
The parallel random-access machine [10] The actor model; Computational bridging models such as the bulk synchronous parallel (BSP) model; Petri nets; Process calculi. Calculus of communicating systems (CCS) Communicating sequential processes (CSP) model; π-calculus; Tuple spaces, e.g., Linda; Simple Concurrent Object-Oriented Programming (SCOOP)
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, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as random-access machine .
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step.