Data‐Parallel Programming in a Multithreaded Environment

Research on programming distributed memory multiprocessors has resulted in a well‐understood programming model, namely data‐parallel programming. However, data‐parallel programming in a multithreaded environment is far less understood. For example, if multiple threads within the same process belong...

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Vydáno v:Scientific programming Ročník 6; číslo 2; s. 187 - 200
Hlavní autoři: Haines, Matthew, Mehrotra, Piyush, Cronk, David
Médium: Journal Article
Jazyk:angličtina
Vydáno: 01.01.1997
ISSN:1058-9244, 1875-919X
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Shrnutí:Research on programming distributed memory multiprocessors has resulted in a well‐understood programming model, namely data‐parallel programming. However, data‐parallel programming in a multithreaded environment is far less understood. For example, if multiple threads within the same process belong to different data‐parallel computations, then the architecture, compiler, or run‐time system must ensure that relative indexing and collective operations are handled properly and efficiently. We introduce a run‐time‐based solution for data‐parallel programming in a distributed memory environment that handles the problems of relative indexing and collective communications among thread groups. As a result, the data‐parallel programming model can now be executed in a multithreaded environment, such as a system using threads to support both task and data parallelism.
ISSN:1058-9244
1875-919X
DOI:10.1155/1997/901027