loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Evaluating High-Performance Computing on Google App Engine
March/April 2012 (vol. 29 no. 2)
pp. 52-58
ASCII Text
x 
 
Radu Prodan, Michael Sperk, Simon Ostermann, "Evaluating High-Performance Computing on Google App Engine," IEEE Software, vol. 29, no. 2, pp. 52-58, March/April, 2012.
 
 
BibTex
x
 
@article{ 10.1109/MS.2011.131,
author = {Radu Prodan and Michael Sperk and Simon Ostermann},
title = {Evaluating High-Performance Computing on Google App Engine},
journal ={IEEE Software},
volume = {29},
number = {2},
issn = {0740-7459},
year = {2012},
pages = {52-58},
doi = {http://doi.ieeecomputersociety.org/10.1109/MS.2011.131},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Software
TI - Evaluating High-Performance Computing on Google App Engine
IS - 2
SN - 0740-7459
SP52
EP58
EPD - 52-58
A1 - Radu Prodan,
A1 - Michael Sperk,
A1 - Simon Ostermann,
PY - 2012
KW - cloud computing
KW - high-performance computing
KW - performance analysis
KW - Google App Engine
KW - GAE
KW - Amazon Elastic Compute Cloud
KW - Amazon EC2
KW - software engineering
VL - 29
JA - IEEE Software
ER -
 
Radu Prodan, University of Innsbruck
Michael Sperk, University of Innsbruck
Simon Ostermann, University of Innsbruck
An experimental approach employs the Google App Engine (GAE) for high-performance parallel computing. A generic master-slave framework enables fast prototyping and integration of parallel algorithms that are transparently scheduled and executed on the Google cloud infrastructure. Compared to Amazon Elastic Compute Cloud (EC2), GAE offers lower resource-provisioning overhead and is cheaper for jobs shorter than one hour. Experiments demonstrated good scalability of a Monte Carlo simulation algorithm. Although this approach produced important speedup, two main obstacles limited its performance: middleware overhead and resource quotas.
Index Terms:
cloud computing, high-performance computing, performance analysis, Google App Engine, GAE, Amazon Elastic Compute Cloud, Amazon EC2, software engineering
Citation:
Radu Prodan, Michael Sperk, Simon Ostermann, "Evaluating High-Performance Computing on Google App Engine," IEEE Software, vol. 29, no. 2, pp. 52-58, Mar./Apr. 2012, doi:10.1109/MS.2011.131
Usage of this product signifies your acceptance of the Terms of Use.