Home Strategy Activities Grants Publications People Sponsors Blog Contact Us 
  

JvpRmvRhWwIml17SaaS

J.L. Vazquez-Poletti, R. Moreno-Vozmediano, R. Han, W. Wang, I.M. Llorente. SaaS enabled admission control for MCMC simulation in cloud computing infrastructures. Computer Physics Communications, 211:88-97, 2017.

Abstract

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

Keywords

[ Tin2015-65469-p ] [ Cloud ]

Contact

Jose Luis Vazquez-Poletti
Rafael Moreno-Vozmediano
Ignacio M. Llorente

BibTex Reference

@article{JvpRmvRhWwIml17SaaS,
   Author = {Vazquez-Poletti, J.L. and Moreno-Vozmediano, R. and Han, R. and Wang, W. and Llorente, I.M.},
   Title = {SaaS enabled admission control for MCMC simulation in cloud computing infrastructures},
   Journal = {Computer Physics Communications},
   Volume = {211},
   Pages = {88--97},
   Year = {2017}
}

Admin · Log In