Computer Science, Machine Learning, and Applied Mathematics
TimeMonday, June 2614:00 - 16:00 CEST
DescriptionDuring the last few years, applications in scientific fields such as weather forecasting and radio astronomy have evolved into complex data-centric workflows distributed over what is known as the computing continuum, i.e. all the computing resources from the Edge (captors, sensors, ...) to Cloud and HPC infrastructures. These workflows exhibit new scenarios across the domains of "modelling and simulation", "AI", "Analytics" and "Internet of things" (IoT) for which advanced data management techniques have to be devised. Achieving this goal requires adressing new data-related challenges, both within the infrastructures themselves, with ever-increasing performance and flexibility requirements, but also between geo-distributed systems. During our minisymposium, we will address these challenges from two perspectives. First, we will try to get an overview of the needs of scientific workflows through concrete examples such as the Square Kilometre Array (SKA) use-case whose goal is to build the world’s largest radio telescope, although these requirements are present in many other areas. Second, we will review the latest research on the topic of data management across the computing continuum, from the point of view of both architectures and software components.