NVIDIA Appoints First CUDA Center of Excellence
University of Illinois at Urbana-Champaign Selected for its Pioneering Work in Parallel Computing EducationFor further information, contact:
FOR IMMEDIATE RELEASE
SANTA CLARA, CA & URBANA, IL—JUNE 30, 2008—NVIDIA Corporation (Nasdaq: NVDA), the worldwide leader in visual computing technologies, and the University of Illinois at Urbana-Champaign (UIUC) today announced that UIUC has been named as the world’s first CUDA Center of Excellence. In addition to the appointment, NVIDIA has donated $500,000 to UIUC for the development of parallel computing facilities and the continuation of its research programs.
“The CUDA Center of Excellence program rewards schools that truly embrace the concept of parallel processing as the future of computing,” said Dr. David Kirk, chief scientist at NVIDIA. “Schools receiving this accreditation integrate the CUDA software environment into their curriculum to help their students harness the capabilities of these new parallel processing architectures. As one of the country’s leading schools in this field, I am personally delighted to appoint UIUC as our first CUDA Center of Excellence.”
The Theoretical and Computational Biophysics Group at UIUC was one of the first research groups to leverage the parallel architecture of the GPU to accelerate their research in the field of computational biophysics. They have successfully accelerated NAMD/VMD – a popular parallel molecular dynamics application that analyzes large biomolecular systems. It is hoped that this donation will aid this group, and others at the university, to further their work and speed them down the path to great discovery.
“We’re very excited to partner with NVIDIA and anticipate that together we will achieve breakthroughs in biomedicine, leading to a better understanding of disease and more effective treatments,” said Klaus Schulten, Swanlund Professor of Physics and director of the Theoretical and Computational Biophysics Group at Illinois (www.ks.uiuc.edu). “This generous gift will be a great stimulus for Illinois' team of outstanding young programmers. It will help to extend their ranks and equip them with the necessary tools to advance computing in decades to come.”
Universities wishing to become CUDA Centers of Excellence must teach a CUDA™ class and use CUDA technology in their research, usually across several labs. In return, NVIDIA supports the school through funding and equipment donations, including help to set up a GPU computing cluster. The appointment of UIUC follows on from the donation last year of 32 QuadroPlex model 4 systems, containing 64 GPUs for a 16-node CUDA technology cluster. The cluster, that has an $800K value, is administered by NCSA (www.ncsa.uiuc.edu/).
The Principal Investigator of the first CUDA Center of Excellence is Prof. Wen-mei Hwu, Sanders-AMD Endowed Chair in Electrical & Computer Engineering at Illinois. Prior to this appointment, Prof. Hwu and Dr. Kirk collaborated to teach one of the nation’s first courses for advanced students in massively parallel processing (//courses.ece.uiuc.edu/ece498/al1/). According to Hwu, “Future increases in computational performance are directly rooted in massively parallel hardware such as many-core GPUs. The biggest challenge today is in parallelizing code to take advantage of the hardware most successfully. NVIDIA’s groundbreaking CUDA solution is a significant step in this direction. We are very proud to host the first CUDA Center of Excellence at Illinois and to be able to partner with an industry leader like NVIDIA as we move forward.”
NVIDIA® CUDA technology is an award-winning C-compiler and software development kit (SDK) for developing computing applications on graphics processing units (GPUs).
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Certain statements in this press release including, but not limited to, statements as to: the CUDA Center of Excellence Program; uses, benefits and impact of NVIDIA’s donation and CUDA software; and future increases in computational performance 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: our reliance on third parties to manufacture, assemble and test our products; design, manufacturing or software defects; development of faster or more efficient GPU or CPU technology; unexpected loss of performance of our products or technologies when integrated into systems; the impact of technological development and competition; customer adoption of competitors' products as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission including its Form 10-Q for the period ended April 27, 2008. Copies of reports filed with the SEC are posted on our 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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