Stanford EE Computer Systems Colloquium

4:15PM, Wednesday, Nov 29, 2006
NEC Auditorium, Gates Computer Science Building B03

Computing on the GPU
GeForce 8800 & NVIDIA CUDA

Ian Buck
About the talk:

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.


Download the slides for this presentation in PDF format.

About the speaker:

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. He currently works for NVIDIA as the GPU-Compute software manager.

Contact information:

Ian Buck
2701 San Tomas Expressway
Santa Clara, CA 95050