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NVIDIA Names 20 New CUDA Research and Training Centers
Written by NVIDIA   
Wednesday, 22 December 2010

NVIDIA Names 20 New CUDA Research and Training Centers in Seven Nations

Top Universities and Training Centers Recognized for Their Groundbreaking Education and Research in Parallel Computing

NVIDIA today announced the addition of 20 new CUDA Research Centers and CUDA Teaching Centers, underscoring the continued growth of GPU computing across the globe.

The new institutions -- located in the U.S., Germany, France, Israel, Italy, Lebanon, and Turkey -- are focused on leveraging the immense parallel processing power of graphics processing units (GPUs) to address today's most challenging computing issues and drive the next wave of scientific discovery.

CUDA Research Centers are recognized institutions that embrace and utilize GPU Computing across multiple research fields. CUDA Teaching Centers have integrated GPU computing techniques into their mainstream computer programming curriculum. The new centers include:

CUDA Research Centers:

  • Boise State University
  • CASPUR (Italy)
  • Fraunhofer SCAI, University of Bonn (Germany)
  • Karlsruhe Institute of Technology (Germany)
  • North Carolina State University
  • Technische Universität München (Germany)
  • University of New Mexico

CUDA Teaching Centers:

  • Arkansas State University
  • Epitech - Game Development Lab (France)
  • Georg-August-University Goettingen, Max-Planck Institute,
    Bernstein Center for Computational Neuroscience (Germany)
  • Lebanese American University (Lebanon)
  • Middle East Technical University (Turkey)
  • North Carolina State University
  • San Jose State University
  • Technion, Israel Institute of Technology (Israel)
  • Universitat Kassel (Germany)
  • University of California, Riverside
  • University of Missouri - Columbia
  • University of Southern California - GamePipe Lab
  • University Paris Diderot (France)

(Centers without a country designation are located in the U.S.)

"Being named a CUDA Research Center is an exciting opportunity for UNM, and we really look forward to working with NVIDIA on interesting research problems that leverage the GPU-based supercomputer we are in the process of building," said Pradeep Sen, assistant professor at the University of New Mexico.

"There are more than 350 universities worldwide teaching the CUDA programming language, and more than 100,000 programmers actively developing applications on CUDA GPUs," said Bill Dally, chief scientist at NVIDIA. "We continue to see growing interest and adoption of GPU Computing across a wide variety of industries and scientific disciplines."

The CUDA Research Center Program fosters collaboration at institutions that are expanding the frontier of massively parallel computing. Among the benefits are exclusive events with key researchers and academics, a designated NVIDIA technical liaison and access to specialized online and in-person training sessions.

The CUDA Teaching Center Program is the first program of its kind to be developed and offered to universities and colleges by a hardware vendor. Among the program's benefits are the donation of teaching kits consisting of textbooks, software licenses and NVIDIA CUDATM architecture-enabled GPUs for teaching lab computers, as well as academic discounts for additional hardware, if required.

For more information on NVIDIA research activities and these programs, please visit the NVResearch site.

About NVIDIA
NVIDIA (NASDAQ: NVDA) awakened the world to the power of computer graphics when it invented the GPU in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from tablets and portable media players to notebooks and workstations. NVIDIA's expertise in programmable GPUs has led to breakthroughs in parallel processing which make supercomputing inexpensive and widely accessible. The Company holds more than 1,600 patents worldwide, including ones covering designs and insights that are essential to modern computing. For more information, see https://www.nvidia.com/.


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