“The notion of High Performance Computing is evolving over time. So what was deemed a leadership class computer five years ago is a little bit obsolete. We are talking about the evolution not only in the hardware but also in the programming models because there are more and more cores available. Orchestrating the calculations in the way that can effectively take advantage of parallelism takes a lot of thinking and a lot of redesign of the algorithms behind the calculations.”
The Southern California Earthquake Center (SCEC), using the power of the petascale Blue Waters Supercomputer at the National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, has developed a physics-based model called CyberShake that simulates how an earthquake works rather than approximating the tremors based on observations.
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.