A launch event was held Monday night at Austin’s Rio Grande Mexican Restaurant in conjuntion with Supercomputing 2008, to celebrate the newly completed OpenCL specification. No live demos of OpenCL applications were shown because the OpenCL spec must first be ratified by by all members of the Khronos Group before it can be publicly released. Still, the fact that this group has completed the complex specification in less than six months is nothing less than amazing. Macworld has posted an article discussing the event including interviews with members of the OpenCL working group. More information about OpenCL is available at the Khronos Group Website.
From a press release:
World’s Most Powerful Global Computation Software Now GPU Accelerated
SC08—AUSTIN, TX—NOVEMBER 18, 2008—At SC08, Wolfram Research will demonstrate a new version of Mathematica, the world’s most powerful general computational software, that integrates CUDA®, NVIDIA’s parallel GPU computing architecture. This new version is expected to give Mathematica users an unprecedented performance increase of 10-100X in numerical computing, modeling, simulation and visual computations, without the need to learn or write C code.
“Since its initial release, Mathematica has been adopted by over 3 million professionals across the entire global technical computing community, and it has had a profound effect on how computers are used across many fields,” said Joy Costa, director of global partnerships at Wolfram Research. “The prospect of a hundred fold increase in Mathematica 7 performance is staggering. CUDA enabled Mathematica will revolutionize the world of numerical computation.”
“With Mathematica 7, researchers and scientists can easily tap the enormous parallel processing power of NVIDIA GPU’s through a familiar high level interface,” said Andy Keane, general manager of the GPU Computing business at NVIDIA. This is truly transformative, giving Mathematica users computational horsepower like never before and reducing computation time in some cases from days to a matter of minutes.”
The demonstration of the CUDA-accelerated release of Mathematica coincides with the launch of the NVIDIA® Tesla™ Personal Supercomputer at this year’s SC08. Priced in the range of traditional PC workstations, Tesla Personal Supercomputers are unrivalled in price and performance. Available in configurations of up to 4 Tesla GPUs in a single system, Tesla Personal Supercomputers deliver up to 4 Teraflops of computing performance from up to 960 parallel processing cores.
From a press release:
NVIDIA Tesla Makes Personal SuperComputing A Reality
Tesla GPUs Enable Cluster Class Performance On The Desktop at 1/10th The Power
SC08—AUSTIN, TX—NOVEMBER 18 2008— Today, scientific research is carried out on supercomputing clusters, a shared resource that consumes hundreds of kilowatts of power and costs millions of dollars to build and maintain. As a result, researchers must fight for time on these resources, slowing their work and delaying results. NVIDIA and its worldwide partners today announced the availability of the GPU-based Tesla™ Personal Supercomputer, which delivers the equivalent computing power of a cluster, at 1/100th of the price and in a form factor of a standard desktop workstation.
From a press release:
ATI Stream is a set of advanced hardware and software technologies that enable AMD graphics processors (GPU), working in concert with the system’s central processor (CPU), to accelerate many applications beyond just graphics. This enables better balanced platforms capable of running demanding computing tasks faster than ever*.
November 13 News Summary
- On December 10, AMD plans to release for download a free ATI Catalyst™ driver update that instantly unlocks new ATI Stream acceleration capabilities already built into millions of ATI Radeon™ graphics cards.
- ATI Stream-enabled software titles for entertainment, gaming and productivity are being released or are under development by a growing list of the world’s top independent software vendors (ISVs), including ArcSoft and CyberLink.
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Graphics processing units (GPUs) have become an attractive option for accelerating scientific computations as a result of advances in the performance and flexibility of GPU hardware, and due to the availability of GPU software development tools targeting general purpose and scientific computation. However, effective use of GPUs in clusters presents a number of application development and system integration challenges. We describe strategies for the decomposition and scheduling of computation among CPU cores and GPUs, and techniques for overlapping communication and CPU computation with GPU kernel execution. We report the adaptation of these techniques to NAMD, a widely-used parallel molecular dynamics simulation package, and present performance results for a 64-core 64-GPU cluster. (Adapting a message-driven parallel application to GPU-accelerated clusters. James C. Phillips, John E. Stone, and Klaus Schulten. In Proceedings of the 2008 ACM/IEEE conference on Supercomputing. Research web site)
The first GPUCamp will be held in Paris December the 6th at the well known La Cantine. This BarCamp aims at getting together the French GPGPU Community in order to start strong social and technical networking in France around this promising technology.
CAL.NET is an effort to create a library to allow existing .NET applications access ATI/AMD GPU hardware for computational and graphical purposes. Programmers are able to manage the GPU hardware and execute kernels on it transparently. It is currently supported on Windows and Linux platforms with the latest drivers.
The latest release of CUDA.NET, 2.0.3, addresses issues with the previous release and adds many features including CUDA runtime API support and Direct3D/OpenGL interoperability. It is now possible to create hybrid applications with Tao and SlimDX, and an issue with copying vector data from device memory was fixed on Windows.
Source Code for the Floating Textures algorithm presented at the Eurographics 2008 conference is now made available at Sourceforge. Floating Textures (paper and video available here) are a novel multi-view, projective texture mapping technique. While many previous multi-view texturing approaches lead to blurring and ghosting artifacts if 3D geometry and/or camera calibration are imprecise, Floating Textures warp (“float”) projected textures during run-time to preserve crisp, detailed texture appearance. The GPU implementation achieves interactive to real-time frame rates. The method is very generally applicable and can be used in combination with many image-based rendering methods or projective texturing applications. By using Floating Textures in conjunction with, e.g., visual hull rendering, light field rendering, or free-viewpoint video, improved rendering results can be obtained from fewer input images, less accurately calibrated cameras, and coarser 3D geometry proxies.
The computer-aided prediction of protein-ligand complex conformations, i.e. docking a small ligand into the active site of a protein, is an important application in the early stages of the modern drug discovery process. For this problem a new approach called PLANTS (Protein-Ligand ANT System) is presented which is based on Ant Colony Optimization (ACO). Part of the work deals with the acceleration of this approach by moving the most time-consuming steps, the transformation of the protein and ligand structure and the evaluation of the objective function, to the GPU. The combined CPU-GPU approach is able to reach a speedup of 5 on average when comparing an optimized CPU-version (single core of a dual-core Pentium 4, 3 GHz) with the GPU-accelerated version (Nvidia Geforce 8800 GTX). Especially virtual screening applications, where the complex conformations of thousands to millions of ligands need to be predicted, can benefit from this speedup.
(Efficient Ant Colony Optimization Algorithms for Structure- and Ligand-Based Drug Design. Oliver Korb, PhD thesis, University of Konstanz, 2008)