Int. J. of Cloud Computing   »   2016 Vol.5, No.1/2

 

 

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Title: Resource allocation algorithm for GPUs in a private cloud

 

Authors: Ahmed Hosny Ibrahim; Hossam El-Deen Mostafa Faheem; Youssef Bassyouni Mahdy; Abdel-Rahman Hedar

 

Addresses:
Department of Computer Science, Faculty of Computers and Information, Assiut University, Assiut, Egypt
Department of Computer Systems, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
Department of Computer Science, Faculty of Computers and Information, Assiut University, Assiut, Egypt
Department of Computer Science, Faculty of Computers and Information, Assiut University, Assiut, Egypt

 

Abstract: Cloud computing is currently playing an important role in different applications. Deploying graphical processing units (GPUs) as a resource in clouds constitutes a major challenge. As the number and the scale of internet services increase, the services running on a cloud computing environment also increase. These services could have been efficiently improved in terms of a service level agreement (SLA) if we could make use of the GPUs architectures in the cloud infrastructure. Cloud providers currently offer GPUs as an infrastructure as a service (IaaS). Providing GPUs in another context such as software as a service (SaaS) requires a resource allocation algorithm. This paper proposes a resource allocation algorithm (RAA) for GPUs in the cloud environment. The proposed RAA will provide a way for cloud providers to offer GPUs in a SaaS context. The RAA is based on the load balancing mechanism trying to fully utilise all the GPUs resources. This paper also investigates the suitability of the RAA by conducting a video enhancement service on a private cloud. It shows that the proposed algorithm provides scalability and enhancements in terms of a SLA.

 

Keywords: graphical processing units; GPUs; cloud computing; resource allocation; cloud services; private cloud; service level agreements; SLAs; cloud infrastructure; software as a service; SaaS; video enhancement service.

 

DOI: 10.1504/IJCC.2016.075094

 

Int. J. of Cloud Computing, 2016 Vol.5, No.1/2, pp.45 - 56

 

Submission date: 30 Sep 2014
Date of acceptance: 11 Mar 2015
Available online: 02 Mar 2016

 

 

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