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Anatomy Study of Execution Time Predictions in Heterogeneous Systems
by
J. Shanthini,
K. R. Shankarkumar
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 45 - Number 7 |
| Year of Publication: 2012 |
| Authors: J. Shanthini, K. R. Shankarkumar |
10.5120/6795-9123
|
J. Shanthini, K. R. Shankarkumar . Anatomy Study of Execution Time Predictions in Heterogeneous Systems. International Journal of Computer Applications. 45, 7 ( May 2012), 39-43. DOI=10.5120/6795-9123
@article{
10.5120/6795-9123,
author = {
J. Shanthini,
K. R. Shankarkumar
},
title = { Anatomy Study of Execution Time Predictions in Heterogeneous Systems },
journal = {
International Journal of Computer Applications
},
issue_date = { May 2012 },
volume = { 45 },
number = { 7 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = {
39-43
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume45/number7/6795-9123/
},
doi = { 10.5120/6795-9123 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:00.578881+05:30
%A J. Shanthini
%A K. R. Shankarkumar
%T Anatomy Study of Execution Time Predictions in Heterogeneous Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 7
%P 39-43
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract
To make effective job placement policies for a volatile large scale heterogeneous system or in grid systems, scheduler must consider the job execution time. In most grid schedulers, execution time of job is to be known in the prior. The execution time given by user may not be more precise, execution time predictors are used in order to facilitate the dynamic scheduling. The prediction algorithms use analytical bench marking/ code profiling, historical data, and code analysis. The prediction algorithm should be nonclairvoyant in nature. This study reviews execution time prediction algorithms in a different perspective. This algorithm considers memory accessing, network performance, and fluctuation of competing CPU load and so on, as interference factors for prediction. Based on the understanding comprehensive analysis is made among them
References
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