NVIDIA Expands CUDA Developer Ecosystem With New CUDA Research and Teaching Centers in the U.S., Canada and Europe

New Centers Recognized for GPU Computing Expertise; Add to Base of More Than 350 Universities and Training Centers Offering CUDA Courses, Conducting CUDA-Powered Research

NVIDIA today announced the addition of new research and educational centers dedicated to leveraging the immense processing power of graphics processing units (GPUs) to address today’s most challenging computing issues.

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

CUDA Research Centers:

  • Barcelona Supercomputing Center, UPC (Spain)
  • Clemson University
  • HP Labs
  • Massachusetts General Hospital - Northeastern University
  • Swinburne University of Technology (Australia)
  • University of California at Los Angeles - UCLA
  • University of Warsaw (Poland)

CUDA Teaching Centers:

  • American University of Beirut (Lebanon)
  • Florida A&M University
  • Hood College
  • McMaster University (Canada)
  • University of California at Los Angeles - UCLA
  • University of Minnesota
  • University of North Carolina at Charlotte

Launched in June 2010, the CUDA Research Center program fosters collaboration with research groups at universities and research institutes 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.

“HP Labs conducts high-impact scientific research to address the most important challenges and opportunities facing our customers and society in the next decade,” said Dr. Ren Wu, senior scientist at HP. “The CUDA architecture represents the next evolution of high-performance computing, and HP Labs has been working with NVIDIA for some time to ensure that HP’s professional computing products leverage the latest GPU computing technologies and practices. HP Labs is proud to be recognized by NVIDIA for our innovative work in massively parallel computing and the value we are providing to customers.”

The CUDA Teaching Center program, also launched in June 2010, is the first program of its kind to be developed and offered to universities and colleges by a hardware vendor. The program has many benefits, including the donation of teaching kits consisting of textbooks, software licenses and CUDA™ architecture-enabled GPUs for teaching lab computers, as well as academic discounts for additional hardware if required.

“The addition of these new educational programs underscores the tremendous interest in harnessing the power of GPUs to solve a today’s most pressing computing challenges,” said Sanford Russell, general manager of CUDA & GPU Computing at NVIDIA. “There are more than 350 universities worldwide teaching the CUDA programming model within their curriculum, and more than 100,000 programmers actively developing applications that use the GPU. With the addition of these new programs, we expect to see even broader interest and adoption of GPU computing practices across a wide variety of industries worldwide.”

Existing CUDA Research Centers include: John Hopkins University, Nanyang University (Singapore), Technical University of Ostrava (Czech Republic), CSIRO (Australia), ICHEC (Ireland) and SINTEF (Norway). Existing CUDA Teaching Centers include State University of New York, Potsdam (U.S.), California Polytechnic State University, San Luis Obispo, ITESM (Mexico), Czech Technical University (Czech Republic), and Qingdao University (China).

These programs augment the CUDA Center of Excellence program, the elite network of 11 institutes focused on advancing parallel computing on the GPU. They are: Cambridge University, Chinese Academy of Sciences, Georgia Institute of Technology, Harvard University, University of Maryland, National Taiwan University, Tokyo Tech, Tsinghua University, University of Illinois at Urbana-Champaign, University of Tennessee, and University of Utah.

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

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NVIDIA, GTC, GPU, supercomputing, parallel computing, CUDA, GPGPU, high performance computing, OpenCL, DirectCompute, GPU Computing, GPU Compute, visual computing, developers, bioscience, oil & gas, medical, finance


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 1,100 U.S. patents, including ones covering designs which are fundamental to modern computing. For more information, see www.nvidia.com.

Certain statements in this press release including, but not limited to, statements as to: the benefits of CUDA Research Center and CUDA Teaching Center; adoption of GPU computing; expertise in visual computing and parallel processing; and the impact of the company’s patents on modern computing are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of faster or more efficient technology; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission, or SEC, including its Form 10-Q for the fiscal period ended August 1, 2010. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

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David A. Bader
David A. Bader
Distinguished Professor and Director of the Institute for Data Science

David A. Bader is a Distinguished Professor in the Department of Computer Science at New Jersey Institute of Technology.