In addition to the plentiful lineup of speakers and bustling exhibition floor, the GPU Technology Conference is providing attendees the opportunity to learn more about what researchers are doing on the GPU front. Displayed in the San Jose Convention Center concourse are dozens of poster boards illustrating countless research projects stretching the GPU frontiers.
There are descriptions of the impact GPUs are having on everything from cardiac function simulations and vision-enhancement systems to black hole simulations and optimized speech recognition technologies. Poster owners will be available to discuss their projects Tuesday evening at 5:00pm PT.
While I was perusing the posters, I ran into Ade Olubummo, founder of Bootpin Inc., a Chicago-based startup that’s building an activity-recognition application. He found himself drawn to a poster board detailing work Stanford University’s 3D Vision Lab has been doing in the area of motion-detection, an important component of Bootpin’s software. Olubummo said he’s been evaluating such technologies, and that what he saw convinced him that he needed to get in touch with the 3D Vision Lab to find out more.
Bootpin’s application targets functions in settings that Olubummo described as being “wherever human eyes are deployed.” That could mean anything from a warehouse security operation to a geriatric watch unit.
Elsehere, Malik Khan, a researcher in the computer science department of University of Utah, was sizing up the competition. Khan authored a poster board depicting the work he’s been doing on transferring the optimization of sequential code libraries for compatibility with GPUs. That, in turn, will allow designers of scientific applications to benefit from the performance gains of GPU technology without having to re-write their applications.
As Khan surveyed a poster board on automatic program generation produced by a team at Carnegie Mellon, he was intrigued with applicable details he could borrow from in his research. “This work seems to be focused on the same kinds of scientific applications,” he said.
Despite the competitive nature of the work, Khan said there’s a lot the two research efforts can learn from each other. This is just one example of how attendees are learning about the best and the brightest in GPU Computing, while at the GPU Technology Conference.