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Eckerd College Named CUDA Teaching Center by NVIDIA

posted on 06/26/2013

Eckerd College has been named a CUDA® Teaching Center by NVIDIA, the world leader in visual and high-performance computing.

NVIDIA CUDA Teaching Center logoCUDA is NVIDIA's parallel computing platform and programming model that enables dramatic increases in computing performance for a range of visual, engineering and scientific applications by leveraging the power of NVIDIA graphics processing units (GPUs).

Through a grant submitted by the computer science discipline last spring, Eckerd College joins other prestigious educational institutions, including California Polytechnic State University, Duke University and Penn State University, that have integrated parallel computing techniques into their mainstream computer programming curriculum. As a CUDA Teaching Center, Eckerd has received a teaching kit that includes textbooks, NVIDIA CUDA GPUs, software licenses, as well and support for teaching assistant training and subsequent contributions to applicable coursework during the academic year. 

"I am very excited for this opportunity and the resources available now that Eckerd College is an official CUDA Teaching Center," said Trevor Cickovski, Ph.D., Assistant Professor of Computer Science. "This year we will be incorporating GPU computing into several semester courses in the computer science department and a winter term course on Fractals in Nature as well. With the new equipment and the lab assistant we will now have a fully equipped GPU computer lab in which we can conduct interactive classroom sessions. Through this experience, students taking courses in our department will be exposed to a cutting-edge technology with enormous future implications."

While for many years the responsibility of the graphics card was localized to taking large amounts of RGB pixel data and rendering this data on the computer monitor, researchers have discovered the applicability of this computing power to accelerate general-purpose scientific and engineering applications. GPU accelerators  have already yielded orders of magnitude speedups for applications such as matrix algebra, DNA sequence analysis and weather forecasting.

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