NVIDIA Names University Of Maryland A CUDA Center Of Excellence
NVIDIA Corp. announced that it has recognized the University of Maryland as a CUDA Center of Excellence, placing it in an elite grouping of 9 other universities and research organizations worldwide. CUDA™ is NVIDIA’s computing architecture that enables its graphics processing units (GPUs) to be programmed using industry standard programming languages and application programming interface (APIs), opening up their massive parallel processing power to a broad range of applications beyond graphics.
The University of Maryland was selected for its pioneering use of GPU computing and the CUDA programming model across research and teaching efforts within multiple science and engineering departments.
Other CUDA Centers of Excellence in the U.S. and abroad include Cambridge University, Chinese Academy of Sciences, Harvard University, National Taiwan University, Tokyo Institute of Technology, Tsinghua University, University of Illinois at Urbana-Champaign, University of Tennessee and University of Utah.
Researchers at the University of Maryland have been exploring the use of GPUs for general-purpose computing for the past five years, when they have demonstrated how to map a number of problems in science, engineering, and medicine to GPUs. Maryland researchers have also published papers that use the CUDA™ architecture of NVIDIA® GPUs to enable entirely new computational techniques in these disparate fields, ranging from the astrophysical simulation of colliding black holes to the real-time analysis of the acoustic properties of concert halls.
The CUDA Center of Excellence at University of Maryland will support several new projects that make extensive use of GPUs such as DNA sequencing. There has been a dramatic increase in the volume of sequence data that can be analyzed, thanks to GPUs, and sequence alignment programs such as MUMmer, a system developed by University of Maryland with the support of the National Institute of Health, have proven essential to this process.
Visit the CUDA Center of Excellence program pages for more information.
February 10, 2010