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DCA: A Distributed CCA Framework Based on MPI
Santa Fe, New Mexico, USA April 26-April 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HIPS.2004.1299193Ninth International Workshop on High- ...
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Felipe Bertrand, Randall Bramley, "DCA: A Distributed CCA Framework Based on MPI," High-Level Programming Models and Supportive Environments, International Workshop on, pp. 80-89, Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS'04), 2004.
 
 
BibTex
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@article{ 10.1109/HIPS.2004.1299193,
author = {Felipe Bertrand and Randall Bramley},
title = {DCA: A Distributed CCA Framework Based on MPI},
journal ={High-Level Programming Models and Supportive Environments, International Workshop on},
volume = {0},
year = {2004},
isbn = {0-7695-2151-7},
pages = {80-89},
doi = {http://doi.ieeecomputersociety.org/10.1109/HIPS.2004.1299193},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - High-Level Programming Models and Supportive Environments, International Workshop on
TI - DCA: A Distributed CCA Framework Based on MPI
SN - 0-7695-2151-7
SP80
EP89
A1 - Felipe Bertrand,
A1 - Randall Bramley,
PY - 2004
KW - null
VL - 0
JA - High-Level Programming Models and Supportive Environments, International Workshop on
ER -
 
Felipe Bertrand, Indiana University
Randall Bramley, Indiana University
The CCA is a component architecture for high-performance scientific applications. In this architecture components are parallel entities that are connected directly or in a distributed manner. The problem of communication between scientific parallel programs with differing numbers of processes is called the "MxN problem". This paper discusses problems and solutions regarding the MxN problem in the context of the CCA. We also present a prototype implementation of a distributed CCA framework with MxN capabilities. This implementation reuses many MPI concepts and constructions to build the parallel-remote port invocation mechanism. Leveraging MPI helps developers that are familiar with that communication library and bene.ts from its performance and high degree of scalability.
Citation:
Felipe Bertrand, Randall Bramley, "DCA: A Distributed CCA Framework Based on MPI," hips, pp.80-89, Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS'04), 2004
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