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The Beowulf Analysis Symbolic INterface: Interactive Parallel Data Analysis for Everyone
March/April 2009 (vol. 11 no. 2)
pp. 45-51
ASCII Text
x 
 
Enrico Vesperini, David M. Goldberg, Stephen L.W. McMillan, James Dura, Douglas Jones, "The Beowulf Analysis Symbolic INterface: Interactive Parallel Data Analysis for Everyone," Computing in Science and Engineering, vol. 11, no. 2, pp. 45-51, March/April, 2009.
 
 
BibTex
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@article{ 10.1109/MCSE.2009.39,
author = {Enrico Vesperini and David M. Goldberg and Stephen L.W. McMillan and James Dura and Douglas Jones},
title = {The Beowulf Analysis Symbolic INterface: Interactive Parallel Data Analysis for Everyone},
journal ={Computing in Science and Engineering},
volume = {11},
number = {2},
issn = {1521-9615},
year = {2009},
pages = {45-51},
doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2009.39},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - Computing in Science and Engineering
TI - The Beowulf Analysis Symbolic INterface: Interactive Parallel Data Analysis for Everyone
IS - 2
SN - 1521-9615
SP45
EP51
EPD - 45-51
A1 - Enrico Vesperini,
A1 - David M. Goldberg,
A1 - Stephen L.W. McMillan,
A1 - James Dura,
A1 - Douglas Jones,
PY - 2009
KW - parallel computing
KW - Boewulf clusters
KW - interactive parallel data analysis
KW - computational astrophysics
VL - 11
JA - Computing in Science and Engineering
ER -
 
Enrico Vesperini, Drexel University
David M. Goldberg, Drexel University
Stephen L.W. McMillan, Drexel University
James Dura, Drexel University
Douglas Jones, Drexel University
The advent of affordable parallel computers such as Beowulf PC clusters and, more recently, multicore PCs has been highly beneficial for a large number of scientists and smaller institutions that might not otherwise have access to substantial computing facilities. However, there hasn't been an analogous progress in the development and dissemination of parallel software—scientists need the expertise to develop parallel codes and must invest a significant amount of time in the development of tools even for the most common data-analysis tasks. The authors describe the Beowulf Analysis Symbolic INterface (BASIN), a multiuser parallel data analysis and visualization framework. BASIN is aimed at providing scientists with a suite of parallel libraries for astrophysical data analysis along with general tools for data distribution and parallel operations on distributed data that lets them easily develop new parallel libraries for their specific tasks.

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Index Terms:
parallel computing, Boewulf clusters, interactive parallel data analysis, computational astrophysics
Citation:
Enrico Vesperini, David M. Goldberg, Stephen L.W. McMillan, James Dura, Douglas Jones, "The Beowulf Analysis Symbolic INterface: Interactive Parallel Data Analysis for Everyone," Computing in Science and Engineering, vol. 11, no. 2, pp. 45-51, Mar./Apr. 2009, doi:10.1109/MCSE.2009.39
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