Year: 1996
Type: article
Abstract: 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.
Source: Scientific Programming
DOI: 10.1155/1997/901027
Authors: Matthew Haines, Piyush Mehrotra, David Cronk
Institutions: University of Wyoming, Langley Research Center
Language: English
Subfield: Hardware and Architecture
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,000
OpenAlex ID: W2023088489