parallel processing

ALGOL 68 par: Parallel processing 1 ALGOL 68 supports programming of parallel processing. Using the keyword par, a collateral clause is converted to a parallel clause, where the synchronisation of actions is controlled using semaphores. In A68G the parallel actions are mapped to threads when available on the hosting operating system. In A68S a different paradigm of parallel processing was implemented (see below).

Computer engineering Computer systems: architecture, parallel processing, and dependability 1 Engineers working in computer systems work on research projects that allow for reliable, secure, and high-performance computer systems. Projects such as designing processors for multi-threading and parallel processing are included in this field. Other examples of work in this field include development of new theories, algorithms, and other tools that add performance to computer systems.

Extract, transform, load - Parallel processing 1 A recent development in ETL software is the implementation of parallel processing. This has enabled a number of methods to improve overall performance of ETL processes when dealing with large volumes of data.

CPU time - CPU time and elapsed real time for parallel processing technology 1 If a program uses parallel processing, total CPU time for that program would be more than its elapsed real time. (Total CPU time)/(Number of CPUs) would be same as elapsed real time if work load is evenly distributed on each CPU and no wait is involved for I/O or other resources.

Parallel processing 1 'Parallel processing' is the ability to carry out multiple operations or tasks simultaneously. The term is used in the contexts of both human cognition, particularly in the ability of the brain to simultaneously process incoming stimuli, and in parallel computing by machines.

Parallel processing - Parallel processing by the brain 1 Parallel processing has been linked, by some experimental psychologists, to the Stroop effect

Parallel processing - Parallel processing in computers 1 Parallel computing is the simultaneous use of more than one Central processing unit|CPU or processor core to execute a program or multiple computational threads. Ideally, parallel processing makes programs run faster because there are more engines (CPUs or Cores) running it. In practice, it is often difficult to divide a program in such a way that separate CPUs or cores can execute different portions without interfering with each other.

Parallel processing - Parallel processing in computers 1 With single-CPU, single-core computers, it is possible to perform parallel processing by connecting the computers in a network. However, this type of parallel processing requires very sophisticated software called distributed processing software.

Parallel processing - Parallel processing in computers 1 Parallel processing is also called parallel computing. In the quest of cheaper computing alternatives parallel processing provides a viable option. The idle time of processor cycles across network can be used effectively by sophisticated distributed computing software.

Parallel processing - Parallel processing in computers 1 The term parallel processing is used to represent a large class of techniques which are used to provide simultaneous data processing tasks for the purpose of increasing the computational speed of a computer system.

Data loading - Parallel processing 1 A development in ETL software is the implementation of parallel processing. This has enabled a number of methods to improve overall performance of ETL processes when dealing with large volumes of data.

Shader - Parallel processing 1 Shaders are written to apply transformations to a large set of elements at a time, for example, to each pixel in an area of the screen, or for every vertex of a model. This is well suited to parallel computing|parallel processing, and most modern GPUs have multiple shader graphics pipeline|pipelines to facilitate this, vastly improving computation throughput.

Cube-connected cycles - Parallel processing application 1 Preparata and Vuillemin showed that a planar layout based on this network has optimal areatimes;time2 complexity for many parallel processing tasks.

High Efficiency Video Coding - Parallel processing tools 1 * Tiles allow for the picture to be divided into a grid of rectangular regions that can independently be decoded/encoded. The main purpose of tiles is to allow for parallel processing. Tiles can be independently decoded and can even allow for random access to specific regions of a picture in a video stream.

High Efficiency Video Coding - Parallel processing tools 1 * Wavefront parallel processing (WPP) is when a slice is divided into rows of CTUs in which the first row is decoded normally but each additional row requires that decisions be made in the previous row. WPP has the entropy encoder use information from the preceding row of CTUs and allows for a method of parallel processing that may allow for better compression than tiles.

Vertex shader - Parallel processing 1 Shaders are written to apply transformations to a large set of elements at a time, for example, to each pixel in an area of the screen, or for every vertex of a model. This is well suited to parallel computing|parallel processing, and most modern GPUs have multiple shader graphics pipeline|pipelines to facilitate this, vastly improving computation throughput.

For More Information, Visit: m/the-parallel-processing- toolkit.html m/the-parallel-processing- toolkit.html The Art of Service