Khawar Hasham

Kamran Munir, Saad Liaquat Kiani, Khawar Hasham et al.

Recent developments in data management and imaging technologies have significantly affected diagnostic and extrapolative research in the understanding of neurodegenerative diseases. However, the impact of these new technologies is largely dependent on the speed and reliability with which the medical data can be visualised, analysed and interpreted. The EUs neuGRID for Users (N4U) is a follow-on project to neuGRID, which aims to provide an integrated environment to carry out computational neuroscience experiments. This paper reports on the design and development of the N4U Analysis Base and related Information Services, which addresses existing research and practical challenges by offering an integrated medical data analysis environment with the necessary building blocks for neuroscientists to optimally exploit neuroscience workflows, large image datasets and algorithms in order to conduct analyses. The N4U Analysis Base enables such analyses by indexing and interlinking the neuroimaging and clinical study datasets stored on the N4U Grid infrastructure, algorithms and scientific workflow definitions along with their associated provenance information.

Khawar Hasham, Antonio Delgado Peris, Ashiq Anjum et al.

Complex scientific workflows can process large amounts of data using thousands of tasks. The turnaround times of these workflows are often affected by various latencies such as the resource discovery, scheduling and data access latencies for the individual workflow processes or actors. Minimizing these latencies will improve the overall execution time of a workflow and thus lead to a more efficient and robust processing environment. In this paper, we propose a pilot job based infrastructure that has intelligent data reuse and job execution strategies to minimize the scheduling, queuing, execution and data access latencies. The results have shown that significant improvements in the overall turnaround time of a workflow can be achieved with this approach. The proposed approach has been evaluated, first using the CMS Tier0 data processing workflow, and then simulating the workflows to evaluate its effectiveness in a controlled environment.