SaaS enabled admission control for MCMC simulation in cloud computing infrastructures
| Autor: | Jose Luis Vazquez-Poletti, Ignacio M. Llorente, Rui Han, Rafael Moreno-Vozmediano, W. Wang |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Process (engineering) Computer science Software as a service Distributed computing General Physics and Astronomy 020206 networking & telecommunications Markov chain Monte Carlo Cloud computing 02 engineering and technology Admission control Field (computer science) symbols.namesake Resource (project management) Utility computing Hardware and Architecture 0202 electrical engineering electronic engineering information engineering symbols 020201 artificial intelligence & image processing business |
| Zdroj: | Computer Physics Communications. 211:88-97 |
| ISSN: | 0010-4655 |
| DOI: | 10.1016/j.cpc.2016.07.004 |
| Popis: | Markov Chain Monte Carlo (MCMC) methods are widely used in the field of simulation and modelling of materials, producing applications that require a great amount of computational resources. Cloud computing represents a seamless source for these resources in the form of HPC. However, resource over-consumption can be an important drawback, specially if the cloud provision process is not appropriately optimized. In the present contribution we propose a two-level solution that, on one hand, takes advantage of approximate computing for reducing the resource demand and on the other, uses admission control policies for guaranteeing an optimal provision to running applications. |
| Databáze: | OpenAIRE |
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