High-performance modelling and simulation for big data applications

Modelling and simulation are widely considered essential for the analysis of complex systems and natural phenomena in science and engineering. They often require a significant amount of computational resources with large data sets, typically scattered across different geographical locations with dissimilar computational infrastructures. Moreover, recent approaches in high performance computing for Big Data applications show a continuous demand for the intelligent combination of complex computing systems with novel data mining methods to handle the increasing amount of data. Data-intensive modelling and simulation can therefore be construed as an interdisciplinary area which requires the efficient exploitation of distributed and high-performance computing resources via novel parallel programming, task scheduling, and data handling to leverage large applicative environments. The development of such complex modelling and simulation environments usually requires collaborative efforts from researchers and practitioners with different domain knowledge and expertise