[talks] Friday Feb 22 noon: Ian Buck, nVidia, "GPU Computing"

[Adam Finkelstein]

Talk announcement:

Speaker: Ian Buck, nVidia
Title: GPU Computing
Time/Place: Friday, noon, Computer Science Bldg, room 302

Abstract:

Many researchers have observed that general purpose computing with
programmable graphics hardware (GPUs) has shown promise to solve many of
the world's compute intensive problems, many orders of magnitude faster
the conventional CPUs. The challenge has been working within the
constraints of a graphics programming environment to leverage this huge
performance potential. GPU computing with CUDA is a new approach to
computing where hundreds of on-chip processor cores simultaneously
communicate and cooperate to solve complex computing problems,
transforming the GPU into a massively parallel processor. The NVIDIA
C-compiler for the GPU provides a complete development environment gives
developers the tools they need to solve new problems in
computation-intensive applications such as product design, data
analysis, technical computing, and game physics. In this talk, I will
provide a brief history of computing with GPUs, how CUDA can solve
compute intensive problems, and where GPU computing will be going in the
future.

Bio:

Ian Buck completed his Ph.D. at the Stanford Graphics Lab in 2004. His
thesis was titled "Stream Computing on Graphics Hardware," researching
programming models and computing strategies for using graphics hardware
as a general purpose computing platform. His work included developing
the "Brook" software toolchain for abstracting the GPU as a general
purpose streaming coprocessor.  Ian received is B.S.E from Princeton and
was a proud member of the Princeton CS Graphics Group.  He currently
works for NVIDIA as the GPU-Compute software manager.