In this tutorial, NVIDIA engineers and academic and industrial researchers will present CUDA and discuss its advanced use for science and engineering. The tutorial will demonstrate CUDA with traditional HPC examples including BLAS, FFT, and integration with Fortran and high-level languages (MATLAB, Mathematica, Python) and describe in detail the programming model at the heart of it all. It will then turn to advanced topics including optimizing CUDA programs, CUDA floating point performance and accuracy, and CUDA programming strategies and tips. Finally the tutorial will present detailed case studies in which domain scientists will describe their experience using CUDA to accelerate mature, deployed, real-world science codes. Scientists throughout industry and academia are already using CUDA to achieve dramatic speedups on production and research codes (see http://www.nvidia.com/cuda for a list of codes, academic papers and commercial packages based on CUDA). Presenters include Massimiliano Fatica (NVIDIA), Mark Harris (NVIDIA), Patrick LeGresley (NVIDIA), and Jim Phillips (UIUC). Follow this link to register.

Slides from the 2007 AstroGPU conference, held at the Institute for Advanced Study in Princeton last November, have been posted to the AstroGPU Website.

ARCS 2008, the 21st Conference on Architecture of Computing Systems, is proud to announce a full day GPGPU tutorial, covering concepts, building blocks and case studies with a special focus on NVIDIA CUDA GPU Computing technology. ARCS is held in Dresden, Germany, on February 25-28, 2008. For more details, please visit The ARCS 2008 Website.

On Sunday November 11 2007 at SC07 in Reno NVIDIA will host a full-day tutorial on CUDA. In this tutorial NVIDIA engineers will partner with academic and industrial researchers to present CUDA and discuss its advanced use for science and engineering domains. The morning session will introduce CUDA programming and the execution and memory models at its heart, motivate the use of CUDA with many brief examples from different HPC domains, and discuss fundamental algorithmic building blocks in CUDA. The afternoon will discuss advanced issues such as optimization and “tips & tricks”, and include real-world case studies from domain scientists using CUDA (VMD and NAMD Molecular Dynamics and Oil and Gas).
Follow this link for more information: http://sc07.supercomputing.org/schedule/event_detail.php?evid=11034.

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).

We have added links to some great introductory GPGPU tutorials to the Developer Page. These tutorials, written by Dominik Göddeke from Dortmund University, cover basic GPGPU concepts, parallel reductions, and fast data transfers.

Please join us next week in Tampa, Florida at Supercomputing 2006 for a full-day GPGPU Tutorial on Sunday, November 12 2006. This is the continuation of a series of well-regarded courses presented at the SIGGRAPH and IEEE Visualization conferences. The course at SC06 has been updated for the Supercomputing audience with the latest results and techniques. Then, on Monday November 13, plan to attend the SC06 Workshop, “General-Purpose GPU Computing: Practice and Experience”. This workshop features invited speakers and poster presenters who provide insights into current GPGPU practice and experience, and chart future directions in heterogeneous and homogeneous multi-core processor architectures and data-parallel processor architectures such as GPUs.

A half-day GPGPU tutorial session was given by Dominik Göddeke 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)