multiprocessing

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Related to pipeline processing: parallel processing, Vector processing

mul·ti·proc·ess·ing

 (mŭl′tē-prŏs′ĕs′ĭng, -prō′sĕs′ĭng, -ə-sĭng, -tī-)
n.
A method of computing in which different parts of a task are distributed between two or more similar central processing units, allowing the computer to complete operations more quickly and to handle larger, more complex procedures.

multiprocessing

(ˌmʌltɪˈprəʊsɛsɪŋ)
n
(Computer Science) computing parallel processing
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.multiprocessing - simultaneous processing by two or more processing units
data processing - (computer science) a series of operations on data by a computer in order to retrieve or transform or classify information
Translations

multiprocessing

[ˌmʌltɪˈprəʊsesɪŋ] Nmultiprocesamiento m
References in periodicals archive ?
The pipeline processing time depended on the availability and speed of the Internet.
According to a Transparency Market Research report on the global pipeline processing and pipeline services market, pipelines is an important and affordable medium to transport various kinds of products such as crude oil, petroleum products, refined petroleum products, natural gas, liquid petroleum gas, chemicals and water among others from drilling and production sites to the storage terminals and end-users.
Issues about the parallel and pipeline processing, and the design of the radar signal processing, are discussed in Section III.
Contract awarded for Gulpo intercepting pipeline processing zones (excellent tosylate) Dredging waste treatment services
General topics include parallel computing, with papers on a new execution mechanism for distributed pipeline processing, real-time systems, including a prototype of a social- and economically-based resource allocations system in grid computing, grid computing, including a fully distributed active and passive task management system, peer-to-peer computing, including a new iterative method to improve Internet distance estimation, distributed software components, scheduling and load balancing, cluster computing, programming paradigms and related issues, mobile computing, fault tolerance, and scientific computing and simulations.

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