This talk by John Owens of UC Davis discusses trends in GPU architecture and their current and potential uses for high-performance computing. The invited talk was given at the Eighth Annual Workshop on High-Performance Embedded Computing (HPEC 2004). (GPUs: Engines for Future High-Performance Computing)

Inspired by the summer Olympics taking place this year, ShaderTech.com is hosting a shader contest this summer with three categories: Materials & Environmental Effects, Image Processing & NPR Effects, and Thinking Outside the Box (this category includes GPGPU applications!).

With over $20,000 worth of prizes available, the Shader Triathlon is a great way to show off your shader skills. Participants can win gold, silver, and bronze prizes for each category, as well as the grand prize: 3ds max, RT/Shader, and a GDC 2005 Gigapass! In addition, all entrants will be entered into a random drawing for the following prizes: 3ds max, RT/Shader, and GPU Gems books.

The Shader Triathlon is sponsored by NVIDIA, discreet, RTzen, and the Game Developers Conference 2005. (ShaderTech.com Shader Triathlon)

Established by NVIDIA Corporation, NVIDIA U is a conference developed to promote the advancement of graphics technology through industry and academic collaboration. NVIDIA U 2004 will be a highly focused, one day event. Conveniently held in Los Angeles one day before GP2 and two days prior to Siggraph 2004, it is sure to sizzle with presentations targeting current and future NVIDIA technology. NVIDIA U is an NDA only conference that provides the ideal forum for leaders in the graphics world to collaborate and share ideas and research in graphics technology. (NVIDIA U Information Page)

Given the increasing power and usage of commodity GPUs, many researchers are using them for general-purpose computation. The ACM Workshop on General-Purpose Computation on Graphics Processors (GP²), to be held the Saturday and Sunday before SIGGRAPH 2004 at one of the SIGGRAPH hotels, will explore current issues in general-purpose computing using graphics hardware. These issues include:

• Do GPUs have the potential of being a useful co-processor for a wide variety of applications?
  What are their algorithmic and architectural niches and can these be broadened?
• What are the major issues in terms of programmability, language and compiler support and software environments for GPUs?
• What are some of the future technology trends that can lead to more widespread use of GPUs?

This workshop will bring together leading researchers and practitioners from academia, research labs and industry working in computer graphics, scientific computation, high performance computing,
omputer architecture and related areas. The program will consist of invited talks, panels and poster presentations. (ACM GP² Workshop. Call for Posters.)

During the Advanced OpenGL Tutorial at the 2004 Game Developers Conference in San Jose, California, Mark Harris of NVIDIA will give a short talk on GPGPU for games. The OpenGL tutorial will be held Tuesday, March 23 from 10am until 6pm. Slides for this talk, “GPGPU : Beyond Graphics”, as well as other talks from the OpenGL Tutorial are available at this link.

This year ACM SIGGRAPH will feature a full-day course titled “GPGPU: General-Purpose Computing on Graphics Hardware”. The course, organized by Mark Harris of NVIDIA and David Luebke of the University of Virginia, will feature GPGPU experts from industry and academia. The course will discuss core computational building blocks such as sorting, searching, and linear algebra, using case studies ranging from fluid simulation to tone mapping. Particular focus will be given to tools, perils, and tricks of the trade in general-purpose GPU programming. (http://www.gpgpu.org/s2004)

This IEEE Visualization 2003 tutorial presentation by Aaron Lefohn gives a high-level overview of dynamic volume computation and visualization on GPUs. The talk is part of the tutorial Interactive Visualization of Volumetric Data on Consumer PC Hardware. The first half of the presentation discusses various memory layout options for dynamic volume computation, and the implications of each option on computation and rendering. The second half discusses optimizations and load balancing between the various computational resources: CPU, vertex processor, rasterizer, and fragment processor. (Dynamic Volume
Computation and Visualization on the GPU, by Aaron Lefohn)