“The Cray XC30 system at CSCS, which includes “Piz Daint”, the most energy efficient peta-scale supercomputer in operation today, has been extended with additional multi-core CPU cabinets (aka “Piz Dora”). In this heterogeneous system we unify a variety for high-end computing services – extreme scale compute, data analytics, pre- and post processing, as well as visualization – that are all important parts for the scientific workflow.”
In this video from the Nvidia booth theater at SC14, Buddy Bland from Oak Ridge National Laboratory presents: Accelerating ORNL’s Applications to the Exascale. “The Titan computer at Oak Ridge National Laboratory is delivering exceptional results for our scientific users in the U.S. Department of Energy’s Office of Science, Applied Energy programs, academia, and industry. Mr. Bland will describe the Titan system, how this system fits within the roadmap to exascale machines, and describe successes we have had with our applications using GPU accelerators.”
In this video, Satoshi Matsuoka, professor at Tokyo Institute of Technology, examines GPU’s role in the rapidly increasing data volume and processing requirements of so-called big data. Conventional cloud infrastructures will no longer be efficient. Will GPUs play a central role, or will they be peripheral?
In this video from the Nvidia booth at SC14, Terri Quinn from LLNL presents: A Livermore Perspective on Next-Generation Computing. “Terri is responsible for an organization consisting of three divisions with over 400 technical staff working in high-performance computing, computer security, and enterprise computing. Livermore Computing (LC), LLNL’s high performance computing organization, operates some of the most advanced production classified and unclassified computing environments.”
GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate scientific, analytics, engineering, consumer, and enterprise applications. Pioneered in 2007 by NVIDIA, GPU accelerators now power energy-efficient datacenters in government labs, universities, enterprises, and small-and-medium businesses around the world. GPUs are accelerating applications in platforms ranging from cars, to mobile phones and tablets, to drones and robots.