University of Western Australia GPU Computing Workshop

April 29th, 2009

A GPU computing workshop and discussion forum will be held at the UWA University Club Thursday, May 7th.  The workshop aims to provide a detailed introduction to GPU computing with CUDA and NVIDIA Tesla computing solutions, and to present research in GPU and Heterogeneous computing being undertaken in Western Australia.

Mark Harris (NVIDIA) will present an introduction to the CUDA architecture, programming model, and the programming environment of C for CUDA, as well as an overview of the Tesla GPU architecture, a live programming demo, and strategies for optimizing CUDA applications for the GPU. To better enable the uptake of this technology, Dragan Dimitrovici from Xenon Systems will provide an overview of CUDA enabled hardware options. The workshop will also include brief presentations of some of the projects using CUDA within Western Australia, including a presentation from Professor Karen Haines (WASP@UWA) on parallel computing strategies required for optimizing applications for GPU and heterogeneous computing.

Please see the workshop flyer for full details.

NVIDIA First to Roll out OpenCL Drivers & SDK

April 20th, 2009

From an NVIDIA Press Release:

SANTA CLARA, CA—APRIL 20, 2009—NVIDIA Corporation, the inventor of the GPU, today announced the release of its OpenCL driver and software development kit (SDK) to developers participating in its OpenCL Early Access Program. NVIDIA is providing this release to solicit early feedback in advance of a beta release which will be made available to all GPU Computing Registered Developers in the coming months.

Developers can apply to become a GPU Computing Registered Developer at:

“The OpenCL standard was developed on NVIDIA GPUs and NVIDIA was the first company to demonstrate OpenCL code running on a GPU,” said Tony Tamasi, senior vice president of technology and content at NVIDIA. “Being the first to release an OpenCL driver to developers cements NVIDIA’s leadership in GPU Computing and is another key milestone in our ongoing strategy to make the GPU the soul of the modern PC.”

At the core of NVIDIA®’s GPU Computing strategy is the massively parallel CUDA™ architecture that NVIDIA pioneered and has been shipping since 2006. Accessible today through familiar industry standard programming environments such as C, Java, Fortran and Python, the CUDA architecture supports all manner of computational interfaces and, as such, is a perfect complement to OpenCL. Enabled on over 100 million NVIDIA GPUs, the CUDA architecture is enabling developers to innovate with the GPU and unleash never before seen performance across a wide range of applications.

Developers can apply to become a GPU Computing Registered Developer at:

eResearch South Australia Workshop: High Performance GPU Computing with NVIDIA CUDA

April 14th, 2009

This workshop,  hosted by eResearch SA and to be presented by Mark Harris (NVIDIA) with Dragan Dimitrovici (Xenon Systems), aims to provide a detailed introduction to GPU computing with CUDA and NVIDIA GPUs such as the Tesla series of high-performance computing processors.

The workshop will be held from 9:00-13:00 on Tuesday 28th April, in the Henry Ayers Room, Ayers House
288 North Terrace, Adelaide (opposite the Royal Adelaide Hospital).

CUDA is NVIDIA’s revolutionary parallel computing architecture for GPUs. The available software tools include a C compiler for developers to build applications, as well as useful libraries for high-performance computing (BLAS, FFT, etc). Several widely-used scientific applications have been ported to run on GPUs using CUDA. This half-day workshop will provide an introduction to the CUDA architecture, programming model, and the programming environment of C for CUDA, as well as an overview of the Tesla GPU architecture, a live programming demo, and strategies for optimizing CUDA applications for the GPU. The workshop will also include a brief presentation of some of the current NVIDIA hardware offerings for GPU computing using CUDA.

The workshop is free, but space is limited. For complete details and registration, visit the workshop web page or download the brochure.

Molecular dynamics on NVIDIA GPUs with speed-ups up to two orders of magnitude

April 13th, 2009

ACEMD is a production-class bio-molecular dynamics (MD) simulation program designed specifically for GPUs which is able to achieve supercomputing scale performance of 40 nanoseconds /day for all-atom protein systems with over 23,000 atoms.  With GPU technology it has become possible to run a microsecond-long trajectory for an all-atom molecular system in explicit water on a single workstation computer equipped with just 3 GPUs. This performance would have required over 100 CPU cores.  Visit the project website for details.

(M. J. Harvey, G. Giupponi, G. De Fabritiis, ACEMD: Accelerating bio-molecular dynamics in the microsecond time-scale. Link to preprint.)

NVIDIA GPU Computing Tutorial Webinar Series

April 8th, 2009

This series of free web seminars (“webinars”) starting April 15th 2009 will cover the basics of data-parallel computing on GPUs using NVIDIA’s CUDA architecture. Tutorials will be presented by the NVIDIA Developer Technology team and will cover many topics including C for CUDA, programming with the OpenCL API , using DirectX Compute and performance optimization techniques.

Webinar topics, schedules and registration information will be updated regularly. Pre-registration is required. Please follow the links provided (after clicking “read the rest of this entry”), and registration details will be emailed back upon successful registration. Read the rest of this entry »

Equalizer BOF at Eurographics next week

March 31st, 2009

Equalizer Graphics will be holding an Equalizer Birds-Of-a-Feather meeting today during Eurographics’09

Place: Eurographics 2009, TU Munich
Date: Tuesday, March 31, 15:00-16:30
Room: MI 02.13.010

Co-located with EG is the Eurographics Symposium on Parallel Graphics and Visualization, so there is yet another good reason to attend.


  • 15:00-15:20 Equalizer: Past, Present and Future, Stefan Eilemann, Eyescale Software GmbH
  • 15:20-15:40 Virtual Architecture with Equalizer and OpenSceneGraph, Julia Sigmund, University of Siegen
  • 15:40-16:00 Performance Optimizations for Image Compositing, Renato Pajarola, University of Zurich
  • 16:00-16:30 Questions and Answers, Open Discussion

gDEBugger for Apple Mac OS X launched at GDC 2009

March 31st, 2009

Graphic Remedy launched the first official version of gDEBugger Mac at this year’s Game Developers Conference, held in San Francisco, 23-27 March. On Tuesday March 24, gDEBugger Mac was demonstrated in the Khronos Developer University full-day tutorial area. A fully functional trial version of gDEBugger Mac is now available for download.

gDEBugger is an OpenGL Debugger and Profiler. It traces application activity on top of the OpenGL API, lets programmers see what is happening within the graphics system implementation to find bugs and optimize OpenGL application performance.

gDEBugger Mac brings all of gDEBugger’s Debugging and Profiling abilities to the Mac OS X OpenGL developer’s world. gDEBugger now runs on Windows, Mac OS X and Linux operating systems.


March 31st, 2009

GPU VSIPL is an implementation of Vector Signal Image Processing Library that targets Graphics Processing Units (GPUs) supporting NVIDIA’s CUDA platform. By leveraging processors capable of 900 GFLOP/s or more, your application may achieve considerable speedup without any specialized development for GPUs. The GPU VSIPL range-Doppler map application achieved a 75x speedup on the GPU simply by linking it with GPU VSIPL.

GPU VSIPL is currently released as a static library, and all releases are verified with the VSIPL Core Lite Test Suite.

GPU VSIPL was presented to the High Performance Embedded Computing Workshop 2008. Read the GPU VSIPL extended abstract [PDF].For more information, visit the GPU VSIPL Website.

GPU Programming For The Rest Of Us

March 11th, 2009

This article by Jeff Layton at ClusterMonkey summarizes the history of GPU Computing in terms of high-level programming languages and abstractions, from the early days of GPGPU programming using graphics APIs, to Stream, CUDA and OpenCL. The second half of the article provides an introduction to the PGI 8.0 Technology Preview, which allows the use of pragmas to automatically parallelize and run compute-intensive kernels in standard C and Fortran code on accelerators like GPUs. (GPU Programming For the Rest Of Us, Jeff Layton,

Java bindings for CUDA

February 27th, 2009

Alexander Heusel of the University of Frankfurt has released open source Java bindings for CUDA.  The current project state is alpha, with support for the CUDA driver API, and support for the CUBLAS and CUFFT libraries is pending.  Contributions are welcome. For more information see the project website:

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