IBM Uses Deep Learning to Train Raspberry Pi EE Times

Computations requiring high performance computing (HPC) power may soon be done in the palm of your hand thanks to work done this summer by IBM Research in Dublin, Ireland. While scientists have come a long away in teaching machines how to process images for facial recognition and understand language to translate texts, IBM researchers focused on a different problem: how to use artificial intelligence (AI) techniques to forecast a physical process. In this case, the focus was on ocean waves, using traditional physics-based models driven by external forces, such as the rise and fall of tides, winds blowing in different directions, the depth and physical properties of water influence the speed and height of the waves. HPC is normally essential to resolve the differential equations that encapsulate these physical processes and their relationships, and the expense often limits the spatial resolution, physical processes and time-scales that can be investigated by a real-time forecasting platform. In an interview with EE Times, IBM Research Senior Research Manager Sean McKenna said an HPC cluster using Big Iron has generally been the solution to dealing with the heavy computational load.