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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.
Parallel computing: Imagine solving a problem by dividing it into smaller tasks and working on them simultaneously. This is the core idea of parallel computing, explained in the book. It explores how using multiple processors can significantly speed up computations, paving the way for future computing advancements.
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 .
Sequential vs. data-parallel job execution. Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in ...
In the study of parallel algorithms, the massively parallel communication model or MPC model is a theoretical model of computing, intended as an abstraction for parallel computing systems that use frameworks such as MapReduce, and frequently applied to algorithmic problems in graph theory.
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)
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.
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 ...