Jisc | Group Infrastructure - Academia.edu

In recent years, there has been an increased demand on Remotely Sensed Data (RSD) for multipurpose usage including industrial, commercial, military and academic research. RSD is huge and growing rapidly. RSD handling, management, storage, processing, accessing and online delivery is a challenge. RSD is usually processed by individual researchers, except for the likes of ESA and other big agencies, on local PCs, this is reflected in the usual availability of image processing software for workstations and the distinct lack of such software for High Performance Computing (HPC) environments. Image processing of RSD is time consuming and as such ripe for implementation in such an environment. Grid Computing is an environment that makes use of many computing resources large and small, accessible through a common interface or set of protocols. It has the potential to handle large datasets and perform image processing by processing images in parallel. Two barriers prevent the spread of implementation of HPC, the hurdle of applying for computing time on the services and consequently the authentication-authorisation process and the skill needed to create and manage the processing workflow on the grid.

Firstly, The National Grid Service (NGS) is one of the UK grids, with access to more than 2000 CPUs of HPC resources. The NGS offers the UK academic community access to these facilities, many of which are free at the point of use. These facilities are now accessible through the Shibboleth Access to Resources on National Grid Service (SARoNGS) Project, which allows users to securely login and use grid resources using their university’s central logging obviating the need for complex grid credentials.

Secondly: Landmap has been working on implementing the outputs of the SARoNGS Project to provide a use case of grid image processing.