Concurrent approach to Flynn’s MPSD classification through Java

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Názov: Concurrent approach to Flynn’s MPSD classification through Java
Autori: Bala Dhandayuthapani Veerasamy, Key Words
Prispievatelia: The Pennsylvania State University CiteSeerX Archives
Zdroj: http://paper.ijcsns.org/07_book/201001/20100117.pdf.
Zbierka: CiteSeerX
Predmety: Concurrent, Flynn’s Taxonomy, Single processor Environment, Java Development Kit, Parallel
Popis: Parallel programming models exist as an abstraction of hardware and memory architectures. There are several parallel programming models in commonly use; they are shared memory model, thread model, message passing model, data parallel model, hybrid model, Flynn’s models, embarrassingly parallel computations model, pipelined computations model. These models are not specific to a particular type of machine or memory architecture. This paper focuses the concurrent approach to Flynn’s MPSD classification in single processing environment through java program.
Druh dokumentu: text
Popis súboru: application/pdf
Jazyk: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.424.2208; http://paper.ijcsns.org/07_book/201001/20100117.pdf
Dostupnosť: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.424.2208
http://paper.ijcsns.org/07_book/201001/20100117.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Prístupové číslo: edsbas.805621F4
Databáza: BASE
Popis
Abstrakt:Parallel programming models exist as an abstraction of hardware and memory architectures. There are several parallel programming models in commonly use; they are shared memory model, thread model, message passing model, data parallel model, hybrid model, Flynn’s models, embarrassingly parallel computations model, pipelined computations model. These models are not specific to a particular type of machine or memory architecture. This paper focuses the concurrent approach to Flynn’s MPSD classification in single processing environment through java program.