GPU Computing: Past, Present and Future (47 mins, ~21 MB)

The past five years have seen the use of graphical processing units for computation grow from being the interest of handful of early adopters to a mainstream technology used in the world’s largest supercomputers. The CUDA GPU programming ecosystem today provides all that a developer needs to accelerate scientific applications with GPUs. The architecture of a GPU has much to offer to the future of large-scale computing where energy-efficiency is paramount. NVIDIA is the lead contractor for the DARPA-funded Echelon project investigating efficient parallel computer architectures for the exascale era. Timothy Lanfear is a Solution Architect in NVIDIA’s Professional Solutions Group, promoting the use of the NVIDIA Tesla(TM) computing solution for high-performance computing. He has twenty years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London. Talk slides