Issue No. 02 - March-April (2012 vol. 29)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MS.2011.131
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.
cloud computing, high-performance computing, performance analysis, Google App Engine, GAE, Amazon Elastic Compute Cloud, Amazon EC2, software engineering
R. Prodan, S. Ostermann and M. Sperk, "Evaluating High-Performance Computing on Google App Engine," in IEEE Software, vol. 29, no. , pp. 52-58, 2011.