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Showing papers by "Roger Impey published in 2010"


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TL;DR: A virtual machine resource manager (Cloud Scheduler) for distributed compute clouds that boots and manages the user-customized virtual machines in response to a user's job submission and presents results on its use on both science and commercial clouds.
Abstract: The availability of Infrastructure-as-a-Service (IaaS) computing clouds gives researchers access to a large set of new resources for running complex scientific applications. However, exploiting cloud resources for large numbers of jobs requires significant effort and expertise. In order to make it simple and transparent for researchers to deploy their applications, we have developed a virtual machine resource manager (Cloud Scheduler) for distributed compute clouds. Cloud Scheduler boots and manages the user-customized virtual machines in response to a user's job submission. We describe the motivation and design of the Cloud Scheduler and present results on its use on both science and commercial clouds.

47 citations


Journal ArticleDOI
01 Nov 2010
TL;DR: The motivation for and implementation of a distributed cloud using the Cloud Scheduler that is spread across both commercial and dedicated private sites are described, and some early results of scientific data analysis using the system are presented.
Abstract: The recent increase in availability of Infrastructure-as-a-Service (IaaS) computing clouds provides a new way for researchers to run complex scientific applications. However, using cloud resources for a large number of research jobs requires significant effort and expertise. Furthermore, running jobs on many different clouds presents even more difficulty. In order to make it easy for researchers to deploy scientific applications across many cloud resources, we have developed a virtual machine resource manager (Cloud Scheduler) for distributed compute clouds. In response to a user's job submission to a batch system, the Cloud Scheduler manages the distribution and deployment of user-customized virtual machines across multiple clouds. We describe the motivation for and implementation of a distributed cloud using the Cloud Scheduler that is spread across both commercial and dedicated private sites, and present some early results of scientific data analysis using the system.

11 citations