From the press release:

SANTA CLARA, CA & URBANA, IL—JUNE 30, 2008—NVIDIA Corporation (Nasdaq: NVDA), the worldwide leader in visual computing technologies, and the University of Illinois at Urbana-Champaign (UIUC) today announced that UIUC has been named as the world’s first CUDA Center of Excellence. In addition to the appointment, NVIDIA has donated $500,000 to UIUC for the development of parallel computing facilities and the continuation of its research programs.

“The CUDA Center of Excellence program rewards schools that truly embrace the concept of parallel processing as the future of computing,” said Dr. David Kirk, chief scientist at NVIDIA. “Schools receiving this accreditation integrate the CUDA software environment into their curriculum to help their students harness the capabilities of these new parallel processing architectures. As one of the country’s leading schools in this field, I am personally delighted to appoint UIUC as our first CUDA Center of Excellence.”

The Theoretical and Computational Biophysics Group at UIUC was one of the first research groups to leverage the parallel architecture of the GPU to accelerate their research in the field of computational biophysics. They have successfully accelerated NAMD/VMD – a popular parallel molecular dynamics application that analyzes large biomolecular systems. It is hoped that this donation will aid this group, and others at the university, to further their work and speed them down the path to great discovery.

(Complete Press Release)

Version 1.0 alpha of CUDPP, the CUDA Data-Parallel Algorithms Library, has been released. This version adds the segmented scan algorithm and sparse matrix-vector multiplication to CUDPP's repertoire. Other new features include an improved "plan"-based configuration interface, an improved scan algorithm for higher performance, support for more inclusive scans and more scan operators, an improved stream compaction interface. In addition, CUDPP 1.0a adds support for CUDA 2.0 and the Windows Vista and Mac OS X (10.5.2 and higher) operating systems. CUDPP works with NVIDIA CUDA versions 1.1 and higher.

CUDPP is the CUDA Data Parallel Primitives Library for NVIDIA CUDA. CUDPP is a library of data-parallel algorithm primitives such as parallel-prefix-sum ("scan"), parallel sort and parallel reduction. Primitives such as these are important building blocks for a wide variety of data-parallel algorithms, including sorting, stream compaction, and building data structures such as trees and summed-area tables. The first beta release of CUDPP is now available, as is the searchable online documentation.

GPU Gems 3, the third volume of the best-selling GPU Gems series provides a snapshot of today's latest Graphics Processing Unit (GPU) programming techniques. The programmability of modern GPUs allows developers to not only distinguish themselves from one another but also to use this awesome processing power for non-graphics applications, such as physics simulation, financial analysis, and even virus detection—particularly with the CUDA architecture. Graphics remains the leading application for GPUs, and readers will find that the latest algorithms create ultra-realistic characters, better lighting, and post-rendering compositing effects. This third volume is certain to appeal to not just the many fans of the first two, but a whole new group of programmers as well. (GPU Gems 3 Page at Addison-Wesley)

Videos of all presentations in the GPGPU Tutorials held at SIGGRAPH 2004 and SIGGRAPH 2005 are online. These courses are an excellent resource for beginners in GPGPU programming. SIGGRAPH 2004 GPGPU Course (Course Web Page). SIGGRAPH 2005 GPGPU Course (Course Web Page).

A half-day GPGPU tutorial session was given by Dominik Goeddeke and Robert Strzodka in conjunction with the ICCS 2006 conference in Reading, UK. After a comprehensive introduction to the GPU programming model with many examples, possibilities to increase performance and accuracy in GPGPU applications were presented. (Slides and tutorial code)

The complete course notes have been posted for the full-day GPGPU course held at IEEE Visualization 2005. The course titled, "GPGPU: General Purpose Computing on Graphics Processors" was held on Sunday, October 23rd, 2005 in Minneapolis, Minnesota. The course begins with the architectural, economic, and programmatic motivations behind GPGPU. It then introduces the GPGPU programming model and describes GPGPU languages (Brook, Scout) as well as high-level data structures. Mathematical and algorithmic primitives are then presented, followed by descriptions of many of the low-level technical details required for effective real-world GPGPU programming. The course concludes with several case studies and a disscusion of the future architectual, application, and research possibilities for GPGPU. The course organizer was Aaron Lefohn, and the presenters were Ian Buck, Aaron Lefohn, John Owens, Tim Purcell, Patrick McCormick, and Robert Strzodka. ( "GPGPU: General Purpose Computing on Graphics Processors," IEEE Visualization 2005)

Once again 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 adaptive shadow mapping to database queries and data mining. Particular focus will be given to tools, perils, and tricks of the trade in general-purpose GPU programming. The course has been updated from SIGGRAPH 2004, with all new case studies.(http://www.gpgpu.org/s2005)

The deadline for the Special Issue of the Elsevier Journal "Simulation Practice and Theory" about Programmable Graphics Hardware has been extended until Tuesday, May 17th, 2005. Authors of papers which explore simulation studies and algorithms utilizing graphics hardware are invited to participate in the special issue. Please see the Call for Papers for more information. (http://www.cg.informatik.uni-siegen.de/News/3_SIMPRA_CFP)

A second GPU Gems 2 sample chapter, Streaming Architectures and Technology Trends (Chapter 29), by John Owens is now available.  The first sample chapter Per-Pixel Displacement with Distance Functions (Chapter 8), was released last week.

Sign up to be notified when GPU Gems 2 is available.

A Special Issue of the Elsevier Journal "Simulation Practice and Theory" about Programmable Graphics Hardware is planned for 2005. Authors of papers which explore simulation studies and algorithms utilizing graphics hardware are invited to participate in the special issue. Please see the Call for Papers for more information.

The upcoming GPU Gems 2 book is now in press and the first copies will be available at GDC 2005 in San Francisco. Several pieces of sample material from GPU Gems 2 have been released.  These include a Visual Table of Contents (shown at right, which will be inside the front cover), the foreword (by Tim Sweeney, Epic Games), the preface, and the contributor biographies.

A first sample chapter, Per-Pixel Displacement Mapping with Distance Functions, has also been released. (GPU Gems 2 Homepage.)

Suresh Venkatasubramanian will be teaching a GPGPU class at the University of Pennsylvania in Spring 2005. The class, titled "GPU Programming and Architecture" will focus on the stream programming abstraction of the GPU, and will cover the basic tools and techniques for designing and implementing algorithms for general purpose computations on the GPU. (UPenn GPGPU Course)

UNC's Professor Frederick P. Brooks, Jr., who coined the term "Computer Architecture", received the 2005 ACM/IEEE Computer Society Eckert-Mauchly Award for outstanding contributions to the field of computer and digital systems architecture. In his award acceptance speech, Dr. Brooks stated that GPUs are "...very powerful scientific computers installed in many homes... I think exploring that design space and its utilization... is one of the most exciting areas in computer architecture today." (Frederick P. Brooks, Jr. 2005 Eckert-Mauchly Award acceptance speech. Streaming Video Links)

The GPGPU group at AT&T Labs - Research conducts research on GPU applications in the areas of computational geometry, data visualization and data analysis. (AT&T Labs GPGPU Home Page)

A short course on GPGPU is given at the Department of Computer Science, University of Aarhus, Denmark by Jesper Mosegaard and Thomas Sangild Sørensen. (GPGPU_E04)

A course on general-purpose computation on graphics processors is being taught this semester by Dinesh Manocha at The University of North Carolina at Chapel Hill. This seminar course covers algorithmic and system issues as well as a number of applications. It will review the current state of the art and investigate many open issues. (GPGP)

The complete course notes have been posted for the full-day GPGPU course held at IEEE Visualization 2004. The course titled, "GPGPU: General Purpose Computing on Graphics Processors" was held on Monday, October 11th, 2004 in Austin, Texas. The course begins with the architectural, economic, and programmatic motivations behind GPGPU. It then introduces a "hello world" GPGPU example and describes the stream programming model in detail (including Brook). Mathematical and algorithmic primitives are then presented, followed by descriptions of many of the low-level technical details required for effective real-world GPGPU programming. The course concludes with several case studies and a disscusison of the future architectual, application, and research possibilities for GPGPU. The course organizer was Aaron Lefohn, and the presenters were Ian Buck, Aaron Lefohn, John Owens, and Robert Strzodka. ( "GPGPU: General Purpose Computing on Graphics Processors," IEEE Visualization 2004)

TyphoonLabs have published the Fractal Explorer v1.0, an application to explore the most common fractals (such as Julia sets, Mandelbrot sets, and some alternate Julia planes) using the GPU to compute them. It can easily be extended with new fractals written in the OpenGL Shading Language. (TyphoonLabs Fractal Explorer v1.0)

NVIDIA recently released an updated version of FX Composer with support for Shader Model 3.0 and tons of new sample shaders.  The latest version also includes many developer-requested UI improvements, support for NV4x GPU performance analysis, and a beta SDK that allows developer to write their own automation scripts, importers/exporters, etc.

The best way to view all the sample shaders is by downloading the latest NVIDIA SDK and looking at the "Effects" tab where you will find descriptions and screenshots of 250+ effects. (FX Composer Homepage)