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An Analytic Performance Model of Parallel Systems that Perform N Tasks Using P Processors That Can Fail
Cambridge, Massachusette October 08-October 10
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/NCA.2001.962547IEEE International Symposium on Netwo ...
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Gehan Weerasinghe, Imad Antonios, Lester Lipsky, "An Analytic Performance Model of Parallel Systems that Perform N Tasks Using P Processors That Can Fail," Network Computing and Applications, IEEE International Symposium on, pp. 0310, IEEE International Symposium on Network Computing and Applications (NCA'01), 2001.
 
 
BibTex
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@article{ 10.1109/NCA.2001.962547,
author = {Gehan Weerasinghe and Imad Antonios and Lester Lipsky},
title = {An Analytic Performance Model of Parallel Systems that Perform N Tasks Using P Processors That Can Fail},
journal ={Network Computing and Applications, IEEE International Symposium on},
volume = {0},
year = {2001},
isbn = {0-7695-1432-4},
pages = {0310},
doi = {http://doi.ieeecomputersociety.org/10.1109/NCA.2001.962547},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Network Computing and Applications, IEEE International Symposium on
TI - An Analytic Performance Model of Parallel Systems that Perform N Tasks Using P Processors That Can Fail
SN - 0-7695-1432-4
SP
EP
A1 - Gehan Weerasinghe,
A1 - Imad Antonios,
A1 - Lester Lipsky,
PY - 2001
KW - Parallel computing
KW - distributed computing
KW - Markov Model
KW - Performance
KW - Processor Failures
VL - 0
JA - Network Computing and Applications, IEEE International Symposium on
ER -
 
Gehan Weerasinghe, University of Connecticut
Imad Antonios, University of Connecticut
Lester Lipsky, University of Connecticut
We present a Markov model for analyzing the performance of parallel -distributed processors that execute a job consisting of N independent tasks in parallel using P processors. The model is a Markov Chain with states representing service and failure rates with k (0 < k <= P) active processors. The task-times and processor failures are both exponentially distributed. We derive a number of expressions to determine the mean execution time, probability of success, work, and other measurable quantities, all conditioned on the job finishing successfully. A prototype, implemented using an extended version of ACMPI, is used for actual experiments that are based on simulated task-times and processor failures. We present our results comparing the analytic model with the prototype for a range of values of processor failure rates. We also discuss extensions of the model and issues related to communication costs, approximations and effect of task-time distributions.
Index Terms:
Parallel computing, distributed computing, Markov Model, Performance, Processor Failures
Citation:
Gehan Weerasinghe, Imad Antonios, Lester Lipsky, "An Analytic Performance Model of Parallel Systems that Perform N Tasks Using P Processors That Can Fail," nca, pp.0310, IEEE International Symposium on Network Computing and Applications (NCA'01), 2001
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