Carlos Coelho,

Cadence Research Laboratories


Graphical Processing Units (GPUs) boast an impressive amount of
computational power and memory bandwidth at commodity prices
driven low by volume and competition on the gaming consumer
market. Due to the introduction of high level APIs, such as
NVIDIA's Compute Unified Device Architecture (CUDA), harvesting
the computational power of the GPU for general computing
applications has become straightforward. In this talk we present
an overview of NVIDIA's current GPU architecture. A brief
introduction to CUDA and a discussion of performance issues and
optimization techniques.

Carlos Pinto Coelho received his Ph.D. in
Electrical Engineering and Computer Science from MIT in September
2007. In 2001 he joined the startup company AltraBroadband where
he worked on the development of the Nexxim circuit simulator. In
1999 and 2001 he received his engineering and masters degree in
Computer and Electrical Engineering from the Instituto Superior
Técnico, in Lisbon. His interests include simulation and modeling
of physical systems in general and biological systems in
particular, artificial intelligence, parallel programming
hardware, algorithms, mathematics and physics. Since 2007 he is a
researcher at Berkeley Cadence Research Laboratories.

Seminar organized by the
ALGOS group (


Date: 2008-Nov-03     Time: 11:30:00     Room: 336

For more information:

  • 213100399