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C, AC, Split-C, Parallel C Preprocessor Unified Parallel C ( UPC ) is an extension of the C programming language designed for high-performance computing on large-scale parallel machines , including those with a common global address space ( SMP and NUMA ) and those with distributed memory (e. g. clusters ).
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 ...
The Message Passing Interface (MPI) is a portable message-passing standard designed to function on parallel computing architectures. [1] The MPI standard defines the syntax and semantics of library routines that are useful to a wide range of users writing portable message-passing programs in C, C++, and Fortran.
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.
Multiprogramming is a computing technique that enables multiple programs to be concurrently loaded and executed into a computer's memory, allowing the CPU to switch between them swiftly. This optimizes CPU utilization by keeping it engaged with the execution of tasks, particularly useful when one program is waiting for I/O operations to complete.
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.
Concurrency refers to the ability of a system to execute multiple tasks through simultaneous execution or time-sharing (context switching), sharing resources and managing interactions.