Wired magazine has published an article about GPGPU by Paul Tulloch called “Supercomputing’s Next Revolution”. The article discusses recent results from the Stanford Folding@Home project and the UNC Gamma Group, whose most resent results will be presented next week at Supercomputing 2006 in Tampa, Florida.
NVIDIA Corporation today unveiled NVIDIA CUDA technology, a new architecture for computing on NVIDIA GPUs, and the industry’s first C-compiler development environment for the GPU. From the NVIDIA Press Release:
GPU computing with CUDA is a new approach to computing where hundreds of on-chip processor cores simultaneously communicate and cooperate to solve complex computing problems up to 100 times faster than traditional approaches. This breakthrough architecture is complemented by another first: the NVIDIA C-compiler for the GPU. This complete development environment gives developers the tools they need to solve new problems in computation-intensive applications such as product design, data analysis, technical computing, and game physics. CUDA-enabled GPUs offer dedicated features for computing, including the Parallel Data Cache, which allows 128, 1.35 GHz processor cores in newest generation NVIDIA GPUs to cooperate with each other while performing intricate computations. Developers access these new features through a separate computing driver that communicates with DirectX and OpenGL, and the new NVIDIA C compiler for the GPU, which obsoletes streaming languages for GPU computing.
CUDA website: http://www.nvidia.com/cuda
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.
Graphic Remedy is proud to announce the release of gDEBugger Version 3.0. This new major version supports OpenGL V2.1 standards and contains ATI Hardware Performance Counters (Percentage Hardware busy, Transform Clip Lighting unit busy, etc.) integration. These counters are displayed in the Performance Graph and Performance Dashboard Views. V3.0 also adds the option for Floating Licenses with a dedicated License Server. The new version can be downloaded from http://www.gremedy.com/download.php.
A multi-view stereo evaluation has been proposed by Steve Seitz et al. The challenge involves recovering 3D reconstructions of complete objects from a large number of views. Among the reported techniques, two out of nine make an intensive usage of GPUs, both yielding large speedups: the work by Pons, Keriven and Labatut that took part in the original competition at CVPR06, and the work by Hornung and Kobbelt. Running times, accuracy and completeness of the methods are reported here. (Steve Seitz et al. A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), New York, 2006.)
This white paper from RapidMind and HP compares the performance of BLAS dense linear algebra operations, the FFT, and European option pricing on the GPU against highly tuned CPU implementations on the fastest available CPUs. All of the GPU implementations were made using the RapidMind Development Platform, which allows the use of standard C++ programming to create high-performance parallel applications that run on the GPU. The full source for the samples is available in conjunction with a new beta version of the RapidMind development platform. The results will also be presented as a poster at SC06.
PeakStream, Inc., a leading software application platform provider for the high performance computing (HPC) market, today unveiled the PeakStream Platform. Available immediately, the PeakStream Platform makes it possible to easily program new high performance processors such as multi-core CPUs, graphics processing units (GPUs) and Cell processors, converting them into radically powerful computing engines for exponentially increased application performance and decreased time-to-solution at reduced cost. The company also announced the completion of equity financing totaling $17 million from Kleiner Perkins Caufield & Byers, Sequoia Capital and Foundation Capital. (www.peakstreaminc.com)
The computational power of GPU-based algorithms is receiving increased attention in research on Computer Vision and 3D stereo reconstruction from images. In this context one of the most important ingredients for any 3D stereo reconstruction technique is the estimation of photo consistency. This ECCV06 paper presents a new, illumination invariant photo consistency measure for high quality, volumetric 3D reconstruction from calibrated images. In contrast to current standard methods such as normalized cross-correlation it supports unconstrained camera setups and non-planar surface approximations. The paper shows how this measure as well as the other important stages of the volumetric reconstruction pipeline can be implemented in a highly efficient way by exploiting current graphics processors. The authors’ GPU implementation achieves speedups up to a factor of 85 in comparison to CPU-based algorithms, and allows reconstruction of high quality models with computation times of only a few seconds to minutes, even for large numbers of cameras and high volumetric resolutions. (Robust and Efficient Photo-Consistency Estimation for Volumetric 3D Reconstruction. Alexander Hornung and Leif Kobbelt. European Conference on Computer Vision (ECCV 2006), LNCS, vol. 3952, Springer, 179-190.)
This Supercomputing 2006 paper by Govindaraju et al. presents a memory model to analyze and improve the performance of scientific algorithms on graphics processing units (GPUs). The memory model is based on texturing hardware, which uses a 2D block-based array representation to perform the underlying computations. It incorporates many characteristics of GPU architectures including smaller cache sizes, 2D block representations, and uses the 3C’s model to analyze the cache misses. Moreover, the paper presents techniques to improve the performance of nested loops on GPUs. In order to demonstrate the effectiveness of the model, the paper highlights its performance on three memory-intensive scientific applications: sorting, Fast Fourier Transform and dense matrix multiplication. In practice, their cache-efficient algorithms for these applications are able to achieve memory throughput of 30-50 GB/s on an NVIDIA 7900 GTX GPU. The paper also compares its results with prior GPU-based and CPU-based implementations on high-end processors. In practice, they are able to achieve 2x-5x performance improvement. (A Memory Model for Scientic Algorithms on Graphics Processors)
The OpenGL ARB and Graphic Remedy have crafted an Academic Program to make the full featured gDEBugger OpenGL debug toolkit available for use in your daily work and research – free of charge! gDEBugger is a powerful OpenGL and OpenGL ES debugger and profiler delivering one of the most intuitive OpenGL development toolkits available for graphics application developers. The ARB.Graphic Remedy Academic Program will run for one year during which time any OpenGL developer who is able to confirm they are in academia will receive an Academic gDEBugger License from Graphic Remedy at no cost. This license will be valid for one year and will include all gDEBugger software updates as they become available. Academic licensees may also optionally decide to purchase an annual support contract for the software at a reduced rate. For further information, visit: