AUSTIN, TX - 24 Sep 2007: Today at the 2007 Power Architecture Developer Conference (PADC), IBM (NYSE: IBM) announced the winners of its first annual Cell Broadband Engine™ (Cell/B.E.) Processor University Challenge. From the thousands of innovative entries, winning designs featured never-before-seen uses of the Cell/B.E. technology, including large-scale modeling of the human brain; a system for mapping massive amounts of real-time data; a path to deliver complex, 3-D medical images to a desktop computer; and a new way to detect extremely fast-moving objects.

Nearly 80,000 students from 25 countries competed in the Challenge, which consisted of online trivia about Cell/B.E. -- originally designed by IBM, Sony Group and Toshiba Corp., for use in consumer devices such as Sony Computer Entertainment's PLAYSTATION©3 -- followed by an opportunity to invent their own applications using this powerful processor. Students' designs included everything from applications-oriented solutions (e.g., visualization, medical imaging, seismic computing, etc.) to High Performance Computing (HPC) to industry-wide programmability tools.

"This contest provided a growth opportunity for students to gain real-life, multi-disciplinary skills to apply to their futures as they move from the classroom to the workforce," said Nick Donofrio, IBM executive vice president, Innovation and Technology. "This challenge also proved the true power, potential and promise of student innovations."

Fourth Place -- A new way developed to detect fast-moving objects. A project by students Robert Hiramatsu and Jussara Kofuji at the University of São Paulo (Brazil) re-implemented rapid object detection on an Open Computer Visual library (OpenCV) and used efficient ways to process on the SPEs of CELL/B.E. OpenCV has direct relevance to cutting-edge visualization applications such as facial recognition. In the team's implementation, they used a specific approach of classifiers that restricted use of an image reference of 24 x 24 pixels and worked with a stump-based classifier algorithm to reduce data structure for classifiers.

More details about FaceDetect Project

IBM, SONY AND SCEI POWER-ON CELL PROCESSOR-BASED WORKSTATION PROTOTYPE