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Toward a model for shared data abstraction with performance

delete1998-02-01
delete7
PRE
AI
D
D.M. Goodeve *
D
Dobson, SA
J
J. M. Nash
D
Davy, JR
P
Peter M. Dew
M
M. Kara
C
Christopher P. Wadsworth
DOI:10.1006/jpdc.1998.1427delete
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Abstract

Abstract

En 中文
This paper demonstrates the utility of typed shared data abstractions as an effective high-level means of structuring and coordinating parallel programs. Access to data shared by concurrent processes is expressed through operations of shared abstract data types (SADTs), SADTs abstract low-level concerns of communication and synchronization. The exposition addresses two major challenges: mismatches between representations and actual patterns of usage, and over-specified coherence. A prototype library of SADTs provides a set of implementations for each SADT, supporting stereotypical usage patterns and allowing exploitation of weakened coherence protocols, The efficacy of this approach is demonstrated on both a network of workstations and a dedicated massively parallel computer. A fine-grained irregular task-parallel computation obtained a speedup of 156 on a 256-processor Gray T3D, showing that the high levels of abstraction afforded by SADTs are compatible with efficient and scalable implementation. (C) 1998 Academic Press.

Journal

Journal of Parallel and Distributed Computing cover
Journal of Parallel and Distributed Computing
IF:
4
Papers:
3.8K
Citations:
4.8K

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