image: Assistant professor Ali Akoglu of the University of Arizona Department of Electrical and Computer Engineering breaks out the giant graphics processing chips he recently received from Nvidia. view more
Credit: Pete Brown/UA College of Engineering
TUCSON, Ariz. (May 25, 2011) -- NVIDIA, the Silicon Valley-based leader in visual and parallel computing, has named the University of Arizona Department of Electrical and Computer Engineering a CUDA Teaching Center.
CUDA Teaching Centers 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.
With nearly 50 locations around the world, including Europe, China, the Middle East, and North America, CUDA Teaching Centers include some of the world's most prestigious universities, such as UCLA, MSRIT, Qingdao, and ITESM. They have integrated GPU computing techniques into their mainstream computer programming curriculum to train the next wave of parallel programmers. CUDA is NVIDIA's parallel computing architecture that enables dramatic increases in computing performance by harnessing the power of the GPU.
Parallel computing is a form of computation in which many calculations are carried out simultaneously, enabling large tasks to be divided into smaller ones, which are then solved concurrently or in parallel. The process involves harnessing the power of one or more GPU-based computing systems, which is significantly faster and more powerful than a CPU-only approach.
Today, powerful NVIDIA GPUs can be found everywhere, from the latest multitasking 4G smartphones to the fastest supercomputer in the world, the Tianhe-1A in the National Supercomputing Center in Tianjin, China.
Heading the project at the University of Arizona will be high-speed computing expert Ali Akoglu, assistant professor in the electrical and computer engineering department and BIO5 member. When he approached NVIDIA about making UA a CUDA Teaching Center, he saw an opportunity to enhance the engineering curriculum and to expand computing facilities for the entire UA campus.
"The learning center will allow parallel processing to be integrated throughout the curriculum, not just studied at a senior level." Akoglu said. "Industry needs this knowledge. If our students have this knowledge when they graduate, they are like gold to computer companies."
Akoglu also plans to have this knowledge cascade from the UA College of Engineering out to the wider UA community. "We can say to other departments, send us your students and we'll train them, and you can have supercomputer capabilities in your lab," he said. "I want to attract other departments to help them accelerate their discovery."
Akoglu is also involved in the iPlant Collaborative, which will help fund workshops. iPlant was established in 2008, when the National Science Foundation awarded a UA-led team $50 million to create a global center that would enable plant, computer and information scientists from around the world to research plant biology's biggest challenges. The CUDA Teaching Center will give UA students and researchers access to a range of NVIDIA resources, such as testing and development systems, online seminars, podcasts, and teaching materials.
NVIDIA will also provide UA with high-performance NVIDIA CUDA-enabled GPUs, as well as funding for a new teaching assistant. Akoglu's department will match the funding.
In return, NVIDIA will receive vital academic feedback to help it improve the state of parallel computing research and education, as well as a larger pool of graduates who are well-trained in parallel processing techniques. One way Akoglu will provide this feedback is by monitoring scientific papers arising from CUDA-related research by his own and other UA labs.
NVIDIA also supports CUDA Research Centers around the world, which are recognized institutions that embrace and utilize GPU Computing across multiple research fields.
"We want to build a unit that's a magnet for the UA research community, and we'll need to build a UA-wide team," Akoglu said. "If we are successful in building this team, UA would then apply to become a CUDA Research Center."
Akoglu's aim to become a CUDA Research Center reflects the long-term dream of establishing the UA as a supercomputing hub for researchers in all disciplines who need high-performance computers to do research such as gene mapping, climate modeling, and air- and spacecraft simulations.
Media contact: Pete Brown, UA Engineering Communications Director
pnb@email.arizona.edu
520-621-3754