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UTK joins a select group of seven universities and research organizations in the U.S. and abroad, including Harvard University, Cambridge University and National Taiwan University, that are designated as a CUDA Center of Excellence. More than 200 universities worldwide teach the CUDA programming model within their curriculum.
CUDA is NVIDIA's computing architecture that enables its GPUs to be programmed using industry standard programming languages and APIs, opening up their massive parallel processing power to a broad range of applications beyond graphics.
"This award of a CUDA Center of Excellence underscores ICL's commitment to continue our work at the forefront of high performance, scientific computing," said Jack Dongarra, ICL's director. "We are very proud of this award and excited by the opportunity it affords to pursue our research on NVIDIA's groundbreaking platform."
Mathematical algorithms are an essential component used by computers to perform linear algebra computations, and ICL's years of experience in developing open source, mathematical software packages and systems such as LAPACK, ScaLAPACK, ATLAS, and PLASMA will be extended by the establishment of this new center. In particular, ICL's work on Matrix Algebra for GPU and Multicore Architectures (MAGMA), whose goal is to create a new generation of linear algebra libraries that dramatically cut processing times using hybrid GPU-CPU co-processing systems, will be an area of focus.
"NVIDIA technologies are now well established in the forefront of general purpose, parallel computing. Our work on the development of Linear Algebra Libraries for CUDA-based Hybrid Architectures will further enable and expand these technologies in the general area of high-performance scientific computing. MAGMA, a subset of LAPACK for CUDA-based Hybrid Architectures, is only a first step in this direction," added Dongarra.
The potential size of the communities impacted by the success of this new CUDA Center of Excellence is significant. A partial listing of the peta-scale ready applications that rely on the kind of dense and sparse linear algebra that the MAGMA libraries will encode includes: quantum chemistry, multi-physics supernova simulation, nano-materials, geophysics, computational mechanics, electronic structure of matter and fluid dynamics.
Visit the CUDA Center of Excellence program pages for more information.
About the Innovative Computing Laboratory (ICL)
The Innovative Computing Laboratory, part of the Electrical Engineering and Computer Science department in UTK's College of Engineering, is an academic world leader in enabling technology research for scientific computing. With a focus on development of numerical libraries that encode the use of linear algebra in software, tools for performance analysis and benchmarking, and tools for high performance, distributing computing, ICL is located at the heart of the University of Tennessee, Knoxville campus and has been part of the HPC community since 1989. For more information about ICL, visit http://icl.eecs.utk.edu.
About NVIDIA
NVIDIA (NASDAQ: NVDA | Quote | Chart | News | PowerRating) awakened the world to the power of computer graphics when it invented the graphics processing unit (GPU) in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from portable media players to notebooks to workstations. NVIDIA's expertise in programmable GPUs has led to breakthroughs in parallel processing which make supercomputing inexpensive and widely accessible. Fortune magazine has ranked NVIDIA #1 in innovation in the semiconductor industry for two years in a row. For more information, see www.nvidia.com.
Certain statements in this press release including, but not limited to, statements as to: the impact and effect of the establishment of the CUDA Center of Excellence; the benefits of NVIDIA's platforms and technologies; 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 July 26, 2009. 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.
Copyright 2009 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.
For more information, contact: Dr. Jack Dongarra Innovative Computing Laboratory (865) 974-8295 dongarra@eecs.utk.edu Andrew Humber NVIDIA Corporation (408) 486 8138 ahumber@nvidia.com
SOURCE: NVIDIA
mailto:dongarra@eecs.utk.edu mailto:ahumber@nvidia.com
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