Emerging real-world graph problems include: detecting and preventing disease in human populations; revealing community structure in large social networks; and improving the resilience of the electric power grid. Unlike traditional applications in computational science and engineering, solving these social problems at scale often raises new challenges because of the sparsity and lack of locality in the data, the need for research on scalable algorithms and development of frameworks for solving these real-world problems on high performance computers, and for improved models that capture the noise and bias inherent in the torrential data streams.

In this talk, Bader will discuss the opportunities and challenges in massive data-intensive computing for applications in social sciences, physical sciences, and engineering.

Video available here.

The main goal of the International Thermonuclear Experimental Reactor (ITER) project is the demonstration of the feasibility of future clean energy sources based on nuclear fusion in magnetically confined plasma. In the era of ITER construction, fusion plasma theory and modelling provide not only a deep understanding of a specific phenomenon, but moreover, modelling-based design is critical for ensuring active plasma control.

The most computationally demanding aspect of the project is first principles fusion plasma modelling, which relies on fluid models – such as Magneto Hydro Dynamics (MHD) – or increasingly often on kinetic models. The challenge stems from the complexity of the 3D magnetic topology, the large difference in time scales from Alfvenic (10-7s) to confinement time (hundreds of s), the large difference in space scales from micro-instabilities (mm) to the machine size (few meters), and most importantly, from the strongly non-linear nature of plasma instabilities, which need to be avoided or controlled.

The current status of first principles non-linear modelling of MHD instabilities and active methods of their control in existing machines and ITER will be presented, focusing particularly on the strong synergy between experiment, fusion plasma theory, numerical modelling and computer science in guaranteeing the success of the ITER project.

Earthquakes are highly non-linear multiscale problems, encapsulating geometry and rheology of faults within the Earth’s crust torn apart by propagating shear fracture and emanating seismic wave radiation.

This talk will focus on using physics-based scenarios, modern numerical methods and hardware specific optimizations to shed light on the dynamics, and severity, of earthquake behaviour. It will present the largest-scale dynamic earthquake rupture simulation to date, which models the 2004 Sumatra-Andaman event - an unexpected subduction zone earthquake which generated a rupture of over 1,500 km in length within the ocean floor followed by a series of devastating tsunamis.

The core components of the simulation software will be described, highlighting the benefits of strong collaborations between domain and computational scientists. Lastly, future directions in coupling the short-term elastodynamics phenomena to long-term tectonics and tsunami generation will be discussed.

Video available here.

PASC18 SPONSORED LECTURE
This event is promoted by Hewlett Packard Enterprise (PASC18 Platinum Sponsor)

Traditionally, scientific laws have been applied deductively - from predicting the performance of a pacemaker before implant, downforce of a Formula 1 car, pricing of derivatives in finance or the motion of planets for a trip to Mars. With Artificial Intelligence, we are starting to also use the data-intensive inductive approach, enabled by the re-emergence of Machine Learning which has been fueled by decades of accumulated data.

Video available here.

The European Centre for Medium-Range Weather Forecasts (ECMWF) leads a number of Horizon 2020 activities (ESCAPE) with innovation actions for developing a holistic understanding of energy-efficiency for extreme-scale applications using heterogeneous HPC architectures by: (a) defining and encapsulating the fundamental algorithmic building blocks ("Weather and Climate Dwarfs") underlying weather and climate services; (b) combining frontier research on algorithm development with hardware adaptation using DSLs; (c) developing benchmarks and cross-disciplinary Verification, Validation, and Uncertainty Quantification (VVUQ) for weather and climate applications; and (d) synthesizing the complementary skills of global numerical weather prediction with leading European researchers.

This talk will illustrate the need for and practicality of producing ensembles of km-scale simulations, summarize progress on accelerating state-of-the-art global weather and climate predictions, and discuss outstanding issues and future directions on producing and analysing big weather data while balancing time-critical customer needs with energy- and time-to-solution.

Video available here.