Keeneland: National Institute for Experimental Computing

Many-core processor architectures are rapidly emerging in many computing environments. One of their attractions is the ability to speed up significantly computation for certain classes of algorithm. In addition, they typically offer lower energy consumption per unit of computation. Several recent studies have identified the development of effective methods for efficiently programming many-core architectures as a major challenge. This project will make available, as experimental platforms, two systems in which one form of many-core processor with very high memory bandwidth, a graphics processing unit, is deployed at scale for use as an accelerator for high-performance parallel computing.

The Georgia Institute of Technology (Georgia Tech) and its partners, the University of Tennessee at Knoxville and the Oak Ridge National Laboratory will initially acquire and deploy a small, experimental, high-performance computing system consisting of an HP system with NVIDIA Tesla accelerators attached. This will be integrated into the TeraGrid. The project team will use this system to develop scientific libraries and programming tools to facilitate the development of science and engineering research applications. The project team will also provide consulting support to researchers who wish to develop applications for the system using OpenCL or to port applications to the system.

In 2012, the project will upgrade the heterogeneous system to a larger and more powerful system based on a next-generation platform and NVIDIA accelerators. It is anticipated that the final system will have a peak performance of roughly 2 petaflops/s. The project will operate the upgraded system as a TeraGrid resource for a further two years.

The final system has the potential to support many different science areas. Possible areas of impact include some of the scientific domains in which GPU-based acceleration has already been demonstrated to have an impact at smaller scale; for example, chemistry and biochemistry, materials science, atmospheric science and combustion science.

In addition to providing infrastructure for science and engineering research and education, the project partners will educate and train the next-generation of computational scientists on cutting-edge computing architectures and emerging programming environments, using the experimental computing resource as one example.