| Monday, July 26, 2010, Issue #31 - Newsletter Home |
| WELCOME | ||||||||||||||||||||||
Welcome to "CUDA: Week in Review," an online news summary for the worldwide CUDA and GPU Computing community.
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| GPU TECHNOLOGY CONFERENCE COUNTDOWN: 8 WEEKS! | ||||||||||||||||||||||
| GTC 2010 Sessions Posted on Web | ||||||||||||||||||||||
| Take a look at the great line-up of technical content to be presented at GTC 2010, with even more still to come. Newly-confirmed sessions include: – Faster Simulation of the National Airspace System Joseph Rios, NASA – The GPU in the Reactive Control of Industrial Robots Alan Peters, Universal Robotics – Evacuate Now? Faster than Real-Time Shallow Water Simulation Andre Brodtkorb, SINTEF |
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| CUDA NEWS | ||||||||||||||||||||||
| CUDA GPUs Accelerate Video Analysis for Russian YouTube | ||||||||||||||||||||||
| Co-founders of Russian video site RuTube (www.rutube.ru) have launched LicenZero (www.licenzero.ru), a project focused on preventing illegal posting of video on RuNet (the Russian internet). Detection of copyrighted video is challenging. The exploding popularity of streaming online video in Russia, combined with the necessity to analyze video in a fraction of a second, caused the developers at LicenZero to seek out new approaches to the problem. They found that even highly-optimized, proprietary algorithms running on CPUs were not sufficient to handle the complex computational requirements. LicenZero developers then turned to CUDA and GPU computing - with promising results. LicenZero’s CEO, Oleg Volobuev, commented: "A single NVIDIA Tesla system performed the work of 28 traditional 3GHz CPUs. We achieved a 30X speed-up, which transformed the video analysis problem into a tractable one and resulted in savings related to hardware as well as power consumption. This is a real breakthrough." | ||||||||||||||||||||||
| PEER 1 Hosting Launches First Large-Scale "GPU Cloud" | ||||||||||||||||||||||
| PEER 1 Hosting, a global online IT hosting provider, announced availability of the industry´s first large-scale GPU cloud (a cloud-hosted website operates on multiple connected servers). Hosting GPUs and software within the cloud provides an inexpensive entry point for new users and enables companies to focus on core business operations. The PEER 1 Hosting cloud is running RealityServer from mental images (a subsidiary of NVIDIA). The Reality Server platform combines NVIDIA Tesla and 3D web software for interactive, photorealistic applications. See: www.peer1.com | ||||||||||||||||||||||
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| CUDA APPS | ||||||||||||||||||||||
| NVIDIA Releases Parallel Nsight 1.0 - GPU Development Software for Microsoft Visual Studio | ||||||||||||||||||||||
| NVIDIA Parallel Nsight for Microsoft Visual Studio is now shipping and supports Windows HPC Server 2008, Windows 7 and Windows Vista. "By adding functionality specifically for GPU Computing developers, Parallel Nsight makes the power of the GPU more accessible than ever before," said Sanford Russell, GM of GPU Computing at NVIDIA. – Download Parallel Nsight: http://www.nvidia.com/object/parallel-nsight.html |
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| Up to 10X Faster HD Video Encoding with New MainConcept SDK for Developers | ||||||||||||||||||||||
| MainConcept, provider of video/audio codecs and SDKs for the consumer, broadcast and professional markets, is now shipping its first GPU-accelerated product. The CUDA H.264/AVC Encoder SDK speeds up HD video processing by up to 10X. MainConcept´s customers include Sony, Adobe, Sonic and Netflix (see recent MainConcept & CUDA webinar here). – Learn more: http://www.mainconcept.com/products/sdks/hw-acceleration/cuda-h264avc.html |
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| New CUDA Tools for Linux from Fixstars | ||||||||||||||||||||||
| Fixstars released v6.2.1 of Yellow Dog Linux (YDL) for CUDA. The upgrade includes more tools for CUDA developers, including the PGI CUDA Fortran compiler. – Download YDL for CUDA: http://www.ydl.net/ydl_cuda/downloads.shtml – For more details, see: http://www.ydl.net/ydl_cuda/ |
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| Check Out New Tesla C2050 Video on Daily Motion | ||||||||||||||||||||||
| http://www.dailymotion.com/video/xe11cr_nvidia-tesla-c2050-gpu-card_tech?start=4#from=embed | ||||||||||||||||||||||
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| CUDA DOWNLOADS | ||||||||||||||||||||||
| – Download CUDA 3.1 Toolkit: http://bit.ly/aKCENp – OpenCL v1.1 pre-release drivers and SDK code samples are available to GPU Computing registered developers. Log in or apply for an account to download. |
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| CUDA TRAINING | ||||||||||||||||||||||
| GPU Computing Webinars from NVIDIA | ||||||||||||||||||||||
| – For info on upcoming events, see: www.nvidia.com/webinars | ||||||||||||||||||||||
| Training from SagivTech | ||||||||||||||||||||||
| – NEW: "GPU Computing@30,000 feet" - a one-day workshop that introduces the world of GPU Computing to algorithm developers, mathematicians and researchers: http://www.sagivtech.com/24054.html – GPU/Image Processing course: Aug. 2-4, Ra´anana, Israel: http://www.sagivtech.com/24054.html – CUDA course: Sept. 27-29, San Francisco (following GTC 2010): http://www.sagivtech.com/36923.html – Note from a SagivTech client: "Thank you for a fantastic course. You covered the topics both from a theoretical and practical manner and helped us better understand the possibilities of speeding up image processing algorithms using CUDA!" - Conrad Bielski, Joint Research Centre, June 2010 |
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| Training from Acceleware | ||||||||||||||||||||||
| – Aug. 2-6, New York City: www.acceleware.com/aug02newyork (with Microsoft) – Sept. 13-17, Calgary: www.acceleware.com/sep13calgary |
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| Training from EMPhotonics | ||||||||||||||||||||||
| – On-site standard and customized training programs: http://www.emphotonics.com/services/cuda-training |
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| CUDA Certification | ||||||||||||||||||||||
| – New certification program for GPU computing developers: www.nvidia.com/certification | ||||||||||||||||||||||
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| CUDA and Academia | ||||||||||||||||||||||
| – Over 350 universities are teaching CUDA and GPU Computing courses around the world. – The CUDA Center of Excellence Program recognizes universities expanding the frontier of parallel computing. – The CUDA Research Center Program recognizes institutions performing leading-edge research. – The CUDA Teaching Center Program recognizes universities providing education and hands-on instruction. – The Academic Partnership Program provides support to researchers using GPUs to solve the world´s most challenging problems. – Learn more about NVIDIA´s Research and University activities at http://research.nvidia.com/ |
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| CUDA CALENDAR | ||||||||||||||||||||||
| July 2010 – SIGGRAPH
– CUDA Programming on GPUs
August 2010 – Proven Algorithmic Techniques for Many-Core Processors
– Wolfram Research 2- Mathematica in Finance and Economics
– GPU Programming for Molecular Modeling
– Symposium on Chemical Computations on GPGPUs
– Unconventional High Performance Computing 2010 (UCHPC 2010)
September 2010 – GPU Technology Conference (GTC) 2010
Future – Supercomputing 2010
– IEEE International Parallel & Distributed Processing Symposium
(To list an event, email: cuda_week_in_review@nvidia.com) |
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| CUDA RESOURCES | ||||||||||||||||||||||
| CUDA Articles in Dr. Dobb's | ||||||||||||||||||||||
| – Supercomputing for the Masses, Part 18: http://is.gd/cs6b9 – Supercomputing for the Masses, Part 17: http://is.gd/cs6eI – Supercomputing for the Masses, Part 16: http://is.gd/citaC |
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| CUDA Books | ||||||||||||||||||||||
| – Programming Massively Parallel Processors by D. Kirk, W. Hwu: http://is.gd/7bNYP – See additional books here: http://www.nvidia.com/object/cuda_books.html |
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| CUDA Documentation | ||||||||||||||||||||||
| – Download developer guides and documentation: http://developer.nvidia.com/object/gpucomputing.html |
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| CUDA ON THE WEB | ||||||||||||||||||||||
| – Read previous issues of CUDA: Week in Review: http://is.gd/cBXbg – Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing – Network with other developers: www.gpucomputing.net – Stayed tuned to GPGPU news and events: www.gpgpu.org – Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda – Read Kudos for CUDA: http://www.hpcwire.com/features/Kudos-for-CUDA-97889444.html |
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| About CUDA | ||||||||||||||||||||||
| CUDA is NVIDIA’s parallel computing hardware architecture. NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and suggestions to: cuda_week_in_review@nvidia.com |
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