Abstract
Cloud computing infrastructures provide a way for researchers to source the computational and storage resources they require to conduct their work and to collaborate within distributed research teams. We provide an overview of a cloud-based elastic virtual infrastructure for research applications that we have established to provide researchers with a collaborative research environment that automatically allocates cloud resources as required. We describe how we have used this infrastructure to support research on the Sun’s corona and how the elasticity provided by cloud infrastructures can be leveraged to provide high-throughput computing resources using a set of off-the-shelf technologies and a small number of additional tools that are simple to deploy and use. The resulting infrastructure has a number of advantages for the researchers compared to traditional clusters or grid computing environments that we discuss in the conclusions.
Highlights
Many problems at the forefront of science, engineering, medicine, arts, humanities and the social sciences require the integration of large-scale data and computing resources at unprecedented scales to yield insights, discover correlations, and drive scientific discovery
While a recent report for the European Commission [5] suggests that cloud computing may “contribute up to e250 billion to EU GDP in 2020 and 3.8 million jobs”, the same report highlights the fact that adoption is currently very uneven and ‘shallow’ and growth is dependent on a number of barriers being overcome
Requirements and functionality we describe some of the key requirements for ELVIRA and show how they have been met for the case of the Astrophysics application using the ELVIRA tools, the functionality provided by cloud infrastructures and a number of additional off-the-shelf components
Summary
Many problems at the forefront of science, engineering, medicine, arts, humanities and the social sciences require the integration of large-scale data and computing resources at unprecedented scales to yield insights, discover correlations, and drive scientific discovery. Predictions of rapid growth of the cloud computing market abound (cf [4]) but so far it would seem that adoption is often limited to specific applications. While a recent report for the European Commission [5] suggests that cloud computing may “contribute up to e250 billion to EU GDP in 2020 and 3.8 million jobs”, the same report highlights the fact that adoption is currently very uneven and ‘shallow’ (limited to specific applications such as email) and growth is dependent on a number of barriers being overcome. The (lack of ) usability of tools and fit with users’ working practices played a crucial role in limiting the uptake of grid computing but there was lack of a pathway from the demonstration of benefits through to early stages of skills acquisition and adoption through to routine use [6]. There is a danger that the adoption of cloud computing for research purposes might be held back by similar issues and might be limited to those who are already users of advanced e-Infrastructures such as clusters, HPC resources or grid computing
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