Programming Abstractions for Dynamically Partitioning and Coordinating Localized Scientific Calculations Running on Multiprocessors

Certain software abstractions help to automate load balancing during various math-physics calculations on a team of concurrently executing processors. These abstractions have been tested on a vortex method for computational fluid dynamics. Experiments exhibited good parallel speedups of 24 and 3.6,r...

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Bibliographic Details
Published in:SIAM journal on scientific and statistical computing Vol. 12; no. 1; pp. 145 - 157
Main Author: Baden, Scott B.
Format: Journal Article
Language:English
Published: Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.1991
Subjects:
Communication
Exact sciences and technology
Fluid dynamics
Mathematics
Methods of scientific computing (including symbolic computation, algebraic computation)
Numerical analysis. Scientific computation
Sciences and techniques of general use
Software upgrading
Workloads
Multiprocessor
Euler equation
Load distribution
Software tool
Numerical computation
Portability
Computing
Dynamic method
ISSN:0196-5204, 1064-8275, 2168-3417, 1095-7197
Online Access:Get full text
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Summary:Certain software abstractions help to automate load balancing during various math-physics calculations on a team of concurrently executing processors. These abstractions have been tested on a vortex method for computational fluid dynamics. Experiments exhibited good parallel speedups of 24 and 3.6,respectively, on 32 processors of the Intel iPSC-1--a message-passing hypercube architecture--and on 4 processors of a Cray X-MP--a shared-memory vector architecture. The abstractions should apply to diverse applications, including finite difference methods, and to diverse architectures without requiring that the application be reprogrammed extensively for each new architecture.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0196-5204
1064-8275
2168-3417
1095-7197
DOI:10.1137/0912008