of parallel computing: bit-level, instruction-level, data, and task parallelism. Parallelism has long been employed in high-performance computing, but...

computations in parallel. GPUs are massively parallel architecture with tens of thousands of threads. One approach is grid computing, where the processing...

In parallel computing, granularity (or grain size) of a task is a measure of the amount of work (or computation) which is performed by that task. Another...

and scheduled by software. The newest manifestation of cluster computing is cloud computing. The components of a cluster are usually connected to each other...

Concurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with...

motion planning, computational biology, computational geometry and parallel computing. Amato is the Abel Bliss Professor of Engineering and Head of the...

common goal for their work. The terms "concurrent computing", "parallel computing", and "distributed computing" have much overlap, and no clear distinction...

Explicitly parallel instruction computing (EPIC) is a term coined in 1997 by the HP–Intel alliance to describe a computing paradigm that researchers had...

In parallel computing, an embarrassingly parallel workload or problem (also called embarrassingly parallelizable, perfectly parallel, delightfully parallel...

Gelernter is known for contributions to parallel computation in the 1980s, and for books on topics such as computed worlds (Mirror Worlds). Gelernter is...

High-performance computing High-performance technical computing Jungle computing Metacomputing Nvidia Tesla Personal Supercomputer Parallel computing Supercomputing...

and create high performance computing systems. Recently[when?], HPC systems have shifted from supercomputing to computing clusters and grids. Because...

Complexity Cybernetics Dennett's three stances Granular computing Granularity (parallel computing) High- and low-level Levels of analysis Meta-system Multiple...

Tools for parallel computing. IPython is a NumFOCUS fiscally sponsored project. IPython is based on an architecture that provides parallel and distributed...

introduced the DirectCompute GPU computing API, released with the DirectX 11 API. Alea GPU, created by QuantAlea, introduces native GPU computing capabilities...

Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes...

parallel programming model supports both inclusive and exclusive scan support beginning with Version 5.0. There are two key algorithms for computing a...

an implicitly parallel programming language that allows writing scripts that distribute program execution across distributed computing resources, including...

EPCC, formerly the Edinburgh Parallel Computing Centre, is a supercomputing centre based at the University of Edinburgh. Since its foundation in 1990,...

Optical computing or photonic computing uses light waves produced by lasers or incoherent sources for data processing, data storage or data communication...

Grid computing is the use of widely distributed computer resources to reach a common goal. A computing grid can be thought of as a distributed system...

In computing, a parallel programming model is an abstraction of parallel computer architecture, with which it is convenient to express algorithms and...

In computing, load balancing is the process of distributing a set of tasks over a set of resources (computing units), with the aim of making their overall...

Parallel slowdown is a phenomenon in parallel computing where parallelization of a parallel algorithm beyond a certain point causes the program to run...

Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different...

Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and...

of a sequence of computing processes (commands, program runs, tasks, threads, procedures, etc.), conceptually executed in parallel, with the output stream...

Unconventional computing (also known as alternative computing or nonstandard computation) is computing by any of a wide range of new or unusual methods...

Proceedings of International Conference on Parallel Computing Technologies. Novosibirsk. 1991. David M. W. Powers, Parallel Unification: Practical Complexity,...

In computing, CUDA (Compute Unified Device Architecture) is a proprietary parallel computing platform and application programming interface (API) that...