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

Proceedings, MSVSCC 2018

Proceedings of the 12th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2018 at VMASC in Suffolk, Virginia. 155 pp

Low mass hybrid pixel detectors for the high luminosity LHC upgrade

Reducing material in silicon trackers is of major importance for a good overall detector performance, and poses severe challenges to the design of the tracking system. To match the low mass constraints for trackers in High Energy Physics experiments at high luminosity, dedicated technological developments are required. This dissertation presents three technologies to design low mass hybrid pixel detectors for the high luminosity upgrades of the LHC. The work targets specifically the reduction of the material from the detector services and modules, with novel powering schemes, flip chip and interconnection technologies. A serial powering scheme is prototyped, featuring a new regulator concept, a control and protection element, and AC-coupled data transmission. A modified flip chip technology is developed for thin, large area Front-End chips, and a via last Through Silicon Via process is demonstrated on existing pixel modules. These technologies, their developments, and the achievable material reduction are discussed using the upgrades of the ATLAS pixel detector as a case study