This paper by Moss et. al shows an implementation of multi-precision arithmetic running on a 7800-GTX. The paper shows how to compute the modular exponentiation of large integers (a central operation in the RSA cryptosystem) using the restricted control flow available on a DX9 card. Both the background number theory used to express the problem in a suitable way for a streaming architecture, and the program transformation techniques used to generate the GLSL code are described in detail. Surprisingly (given the unusual nature of the problem for GPGPU) the GPU is capable of out-performing the CPU over a large enough dataset by a factor of 2x-3x depending on the CPU implementation. Unfortunately the immature state of the GLSL compiler prevents a further 2x improvement by allocating too many registers, and the large latency for setting the problem up means that over 800 exponentiations need to be performed to break-even against the CPU. (Andrew Moss, Dan Page and Nigel Smart. Toward Acceleration of RSA Using 3D Graphics Hardware. In: LNCS 4887, pages 369–388. Springer, December 2007.)
Physically correct acoustic simulations for complex and dynamic environments remain a difficult and computationally extensive task. Graphics hardware is here used for the simulation of sound wave propagation. Two different methods have been implemented, of which one uses ray tracing techniques, while the other is based on difference equations and waveguide meshes. Both techniques can efficiently be implemented within a real-time environment by concentrating on the similarities for sound and light wave propagation, and by exploiting the possibilities of using graphics hardware for non-graphics computations. Applications are discussed for real-time room acoustics, virtual reality as well as for virtual HRIR measurements based on polygonal meshes.
(Ray Acoustics using Computer Graphics Technology. Niklas Röber, Ulrich Kaminski, and Maic Masuch. Proceedings of DAFx 2007.)
(Waveguide-based Room Acoustics through Graphics Hardware. Niklas Röber, Martin Spindler, and Maic Masuch. Proceedings of ICMC 2006.)
The Workshop on General Purpose Processing on Graphics Processing Units will be held October 4, 2007 at Northeastern University, Boston, MA. This meeting will include a keynote talk by Prof. Wen-mei Hwu on “GP Computing: Hardware, Architecture Tools and Education”.
The program will include three invited talks from NVIDIA, ATI and IBM Research, and will include demos by GPU hardware and software vendors. The technical program will include 12 refereed papers. Registration is free, though you need to register for The Workshop on GPGPU at: http://censsis-db3.ece.neu.edu/RICC2007/regist.aspx
Commercial companies that are interested in presenting at The Workshop on GPGPU, please contact the organizing committee at email@example.com.
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 detectionâ€”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)
This article at Genome Technology gives a brief overview of GPGPU, with a focus on biological information processing using NVIDIA CUDA Technology. The article discusses the results from UIUC’s NAMD / VMD project and neurological simulation company Evolved Machines.
This paper by Anderson et al at Caltech describes a method to use GPUs to accelerate Quantum Monte Carlo on a GPU. QMC is among the most accurate (and expensive) methods in the quantum chemistry zoo. Primarily, this involves the investigation of tricks available to this algorithm to speed up matrix multiplication. That is, as a statistical algorithm, the authors studied the performance enhancements available when multiplying many matrices simultaneously. Additionally, the paper explores the Kahan Summation Formula to improve the accuracy of GPU matrix multiplication. (Quantum Monte Carlo on Graphical Processing Units. Amos G. Anderson, William A Goddard III, Peter Schroder. Computer Physics Communications)
gDEBugger is an OpenGL Debugger and Profiler. It provides the application behavior information a developer needs to find bugs and to optimize application performance. gDEBugger Linux brings all of gDEBugger’s debugging and profiling abilities to the Linux OpenGL developers’ world. gDEBugger Linux is now available as a final beta version. This version includes all gDEBugger’s features and supports the Linux i386 and x86_64 architectures. gDEBugger Linux official version will be released shortly after Graphic Remedy receive feedback from the field and fix any reported issues. (http://www.gremedy.com/gDEBuggerLinux.php)
This paper by Collange et al. at UniversitÃ© de Perpignan, France, decribes a prototype to be integrated into simulation codes that estimate temperature, velocity and pressure to design next generation solar receptors. Such codes delegate to GPUs the computation of heat transfer due to radiation. The authors use Monte-Carlo line-by-line ray-tracing through finite volumes. This means data-parallel arithmetic transformations on large data structures. The performance on two recent graphics cards (Nvidia 7800GTX and ATI RX1800XL) show speedups higher than 400 compared to CPU implementations leaving most of CPU computing resources available. As there were some questions pending about the accuracy of the operators implemented in GPUs, the authors start this report with a survey and some contributed tests on the various floating point units available on GPUs. (Graphic processors to speed-up simulations for the design of high performance solar receptors. S. Collange, M. Daumas, D. Defour. Proceedings of the IEEE 18th International Conference on Application-specific Systems, Architectures and Processors.)
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.
Boston, MA USA
October 4, 2007
Overview: The goal of this workshop is to provide a forum for general-purpose purpose GPU programming environments and platforms, as well as discuss applications that have been able to harness the horsepower provided by these platforms. This year’s workshop is
particularly interested in imaging applications. Papers are being sought on many aspects of GPUs, including (but not limited to):
- GPU applications
- GPU software and operating systems
- GPU programming environments
- GPU power/efficiency
- GPU architectures
- GPU benchmarking/measurements
Paper Submissions: Authors should submit an 8 page paper in IEEE double-column style to firstname.lastname@example.org.
Industry Participation: The workshop encourages participation by GPU manufacturers, software vendors, or companies which develop or market products used by the GPU community. Any company interested in participating in the workshop should contact the workshop organizer at email@example.com.
Paper submission: August 28, 2007
Author notification: September 7, 2007
Final paper: September 14, 2007
Copies of final papers will be made available at the workshop. In addition, selected papers will be invited to be part of a special issue of an ACM or IEEE journal or magazine.
For more information, see the GPGPU 2007 web page