High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project.

Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources.

On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains.

It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities.

This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.

This open access book is the final compendium of case studies emanated from the 4-year COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications” (cHiPSet). Funded by the European Commission from 2015, cHiPSet has created a sustainable reference network linking applied research in High Performance Computing (HPC) and Modelling & Simulation to tangibly address Big Data challenges.

cHiPSet has enabled research partnerships for dozens of academics and industry practitioners located in 34 COST countries, as well as in Australia, Belarus, Brazil, China, Russia, and the USA. As a cooperation framework, cHiPSet has reached out to new audiences such as ICT professionals, commercial software developers, and the general public. At a time when Big Data has become a common household term, cHiPSet has strived to become a knowledge hub where data-driven HPC meets Modelling & Simulation.

cHiPSet has also endeavoured to use and exploit results through Open Science practices, i.e., open access publication, open access to data repositories, and open-source software development. A testament to this philosophy, this compendium is set to become a required reference for the fast-changing fields of HPC, Big Data, and Modelling & Simulation.