NVIDIA Launches New Research, Training and Certification Programs for Developers Focused on GPU Computing New Educational Initiative Will Grow CUDA Developer Ecosystem Beyond Current 350 Universities For more information, contact: FOR IMMEDIATE RELEASE: ISC 2010—HAMBURG—June 1, 2010—The ecosystem surrounding the NVIDIA® CUDA™ architecture for parallel processing got a significant boost today with the establishment of new programs to advance the field of general-purpose computing on graphics processing units (GPGPU). With thousands of research papers already published, and more than 350 universities teaching CUDA, a figure that has tripled over the past year, these new programs will expand the teaching and use of GPUs. The new programs include:
In addition, NVIDIA is launching an all new NVResearch online portal, providing information on global research projects supported by NVIDIA, as well as details on all the education and research oriented programs run by the group. The CUDA Certification program responds to the industry’s demand for qualified parallel programmers. To become an NVIDIA CUDA Certified Engineer, candidates must demonstrate good working knowledge of the CUDA architecture and programming model, ability to apply CUDA constructs to common algorithmic frameworks and strong understanding of optimization techniques to get the most performance from CUDA C based code. The CUDA Research Center program recognizes and 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. Certain statements in this press release including, but not limited to, statements as to: the intent, benefits and impact, of the new NVIDIA CUDA programs; 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: development of more efficient or faster technology; design, manufacturing or software defects; the impact of technological development and competition; changes in consumer preferences and demands; customer adoption of different standards or our competitor's products; 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 including its Form 10-Q for the fiscal period ended May 2, 2010. 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. # # # © 2010 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, and CUDA, are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice. ### Copyright© 2012 NVIDIA Corporation. All rights reserved. All company and/or product names may be trade names, trademarks, and/or registered trademarks of the respective owners with which they are associated. Features, pricing, availability, and specifications are subject to change without notice. Note to editors: If you are interested in viewing additional information on NVIDIA, please visit the NVIDIA Press Room at http://www.nvidia.com/page/press_room.html
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