HySpeed Computing’s president, James Goodman, attended the 2012 NVIDIA GPU Computing Conference. He’s sharing his experiences, thoughts and news coming out of the convention.
A few days back in the office have given time to further digest the information and events from last week’s GTC conference. New products, new capabilities and exciting new applications were the themes of the week, highlighted by the keynote address by NVIDIA CEO Jen-Hsun Huang. It was indeed an exciting week for GPU computing. Developments in the coming year are sure to be eventful.
A notable announcement during the GTC week was the official release of the Kepler GPU, proclaimed the fastest, most efficient, most powerful GPU ever produced. With this release NVIDIA is once again redefining what can be achieved using GPU computing. Not only will the Kepler enable greater acceleration of existing GPU algorithms, but also the capacity for dynamic parallelism opens up new dimensions in computing capabilities and efficiency. Dynamic parallelism allows GPU kernels to themselves initiate other kernels. Amongst other functionality, this allows programs to dynamically adjust the resolution of analysis, allowing greater computational focus in areas requiring more detail and less computation in areas with less detail. Consider the potential this brings to fields such as fluid dynamics, finite element analysis, hydrology and geophysics.
The Kepler is also the first GPU designed specifically for the cloud. With the growing prevalence of BYOD – Bring Your Own Device – there is a corresponding need for users to be able to securely work anywhere on any device. The Kelper enables the virtualized GPU, providing an energy efficient, low-latency capability to render and stream graphics on remote displays. This means an employee can bring massive computing power with them into the field as they perform work and visit with clients. For example, running a complex computationally intensive windows application remotely on their tablet device. This improved capacity for virtualization is certain to be a driving force in the growing prevalence of cloud computing.
The list of applications that harness the power of GPU computing is impressive, including such diverse fields as animal behavior, airborne surveillance, genetic research, image processing, machine learning, molecular dynamics, ray tracing, medical imaging, and even an effort to put the first private robot on the moon. Where will GPUs take us next? Stay tuned and stay involved.