Two leading computing visionaries will speak at the GPU Technology Conference (GTC) in September. Prof. Klaus Schulten, renowned computational biologist from the University of Illinois at Urbana-Champaign, will deliver a keynote highlighting discoveries made using the ‘computational microscope.’ Prof. Sebastian Thrun, robotics pioneer at Stanford University and distinguished engineer at Google, will speak on advances in GPU computing in computer vision and robotics. Registration is still open at www.nvidia.com/gtc.

At the ISC 2010 conference in Hamburg, Germany, this week, NVIDIA announced new programs for the growing CUDA/GPGPU developer community:

• CUDA Certification Program – Driven by demand for qualified GPGPU engineers, this is the first program to certify expertise in massively parallel programming on GPUs.
• CUDA Research Centers – Recognizes institutions that embrace GPU Computing across multiple research fields.
• CUDA Teaching Centers – Recognizes institutions that have integrated GPU Computing techniques into their mainstream computer programming curriculum.

These programs complement the existing CUDA Center of Excellence program, which has recognized 10 premier institutions around the world. More details are available here: http://www.nvidia.com/object/io_1275409333119.html

This year’s GPU Technology Conference (GTC 2010) will take place on Monday, Sept. 20 to Thursday, Sept. 23 at the San Jose Convention Center in San Jose, California.

Building on last year’s inaugural conference, GTC 2010 will feature an even broader and deeper selection of technical sessions, interactive tutorials, technology previews, and industry and academic presentations.

Three concurrent GPU-focused summits will occur under one roof:

• Emerging Companies Summit: A showcase for innovative startups to demonstrate products and network with VC’s and other investors.
• GPU Developers Summit: Sessions, tutorials, and presentations for developers, engineers, and scientists.
• NVIDIA Research Summit: A unique opportunity for students, professors, and researchers to present their findings and collaborate.

For more information:

• Join the GTC 2010 mailing list for updates.
• See GTC Call for Submissions to learn about submitting content.
• To inquire about being a sponsor or exhibitor, visit GTC Sponsors/Exhibitors.

NVIDIA and Editor-in-Chief  Professor Wen-mei Hwu of the University of Illinois, Urbana-Champaign invite you to submit articles for GPU Computing Gems, a contribution-based book that will focus on practical techniques for GPU computing. This is a continuation of the popular GPU Gems series.

The full Call for Participation is available here.

RIKEN, one of the most prestigious research institutes in Japan, is the site of an upcoming computing workshop to be keynoted by NVIDIA CEO Jen–Hsun Huang. RIKEN conducts research across a wide range of fields, including physics, chemistry, medical science, biology, and engineering. The workshop will be held 1/28/10 – 1/29/10. See https://reg-nvidia.jp/public/seminar/view/3 for full details.  In addition to keynote speeches by Jen-Hsun Huang and Professor Takayuki Aoki from Tokyo Institute of Technology, guest speakers at the event include Prof. Lorena Barba from Boston University, Mr. Mr. Eiji Fujii from Square ENIX, Dr. Mark Harris from NVIDIA (and GPGPU.org), and Dr. James Phillips from The University of Illinois at Urbana-Champaign.

From the workshop webpage:

“Accelerated Computing” is an old concept that is recently redefined in High-Performance Computing. It was started by dedicated machines like GRAPEs, but a great revolution has been occurring fueled by recent advancement in GPU Computing, both in hardware and in software such as CUDA C and OpenCL. This conference aims to review cutting edge technologies and scientific applications, as well as to discuss the future of the “Accelerator” approach in scientific and industrial HPC. Please join the conference for fruitful discussions on the future of HPC with highly-parallel processors.

From the press release:

NVIDIA Corp. today introduced NVIDIA® Nexus, the industry’s first development environment for massively parallel computing that is integrated into Microsoft Visual Studio, the world’s most popular development environment for Windows-based solutions and Web applications and services.

“NVIDIA Nexus is going to improve programmer productivity immediately,” said Tarek El Dokor at Edge 3 Technologies. “An integrated GPU and CPU development solution is something Edge 3 has needed for a long time. The fact that it’s integrated into the Visual Studio development environment drastically reduces the learning curve.”

NVIDIA Nexus radically improves productivity by enabling developers of GPU computing applications to use the popular Microsoft Visual Studio-based tools and workflow in a transparent manner, without having to create a separate version of the application that incorporates diagnostic software calls. NVIDIA Nexus also includes the ability to run the code remotely on a different computer. Nexus includes advanced tools for simultaneously analyzing efficiency, performance, and speed of both the graphics processing unit (GPU) and central processing unit (CPU) to give developers immediate insight into how co-processing affects their applications.

Nexus is composed of three components:

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On September 30th NVIDIA unveiled its latest GPU architecture, codenamed “Fermi”.  The first Fermi GPUs will contain 512 “CUDA Cores”, capable of more than 8x the double precision floating-point throughput of its predecessor, the GT200 GPU.  The GPU also incorporates error correcting (ECC) memories and caches, a new cache hierarchy, increased shared memory and register file sizes, and the ability to execute C++ programs.

From the press release:

SANTA CLARA, Calif. -Sep. 30, 2009- NVIDIA Corp. today introduced its next generation CUDA™ GPU architecture, codenamed “Fermi”. An entirely new ground-up design, the “Fermi”™ architecture is the foundation for the world’s first computational graphics processing units (GPUs), delivering breakthroughs in both graphics and GPU computing.

“NVIDIA and the Fermi team have taken a giant step towards making GPUs attractive for a broader class of programs,” said Dave Patterson, director Parallel Computing Research Laboratory, U.C. Berkeley and co-author of Computer Architecture: A Quantitative Approach. “I believe history will record Fermi as a significant milestone.”

Presented at the company’s inaugural GPU Technology Conference, in San Jose, California, “Fermi” delivers a feature set that accelerates performance on a wider array of computational applications than ever before. Joining NVIDIA’s press conference was Oak Ridge National Laboratorywho announced plans for a new supercomputer that will use NVIDIA® GPUs based on the “Fermi” architecture. “Fermi” also garnered the support of leading organizations including Bloomberg, Cray, Dell, HP, IBM and Microsoft.

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If you can’t make it to NVIDIA’s inaugural GPU Technology Conference, taking place Sept. 30 to Oct. 2, 2009 in San Jose, CA, you can watch a live webcast here.

Links for the live webcast, event coverage complete with blogs, photos and video interviews, and more details around the conference, including conference schedule, session abstracts and speaker bios can be found at www.nvidia.com/gtc.

The schedule of live webcasts is as follows:

• Wed. Sept 30 – 1:00 PM to 2:30 PM: Opening Keynote with Jen-Hsun Huang, CEO and Co-Founder, NVIDIA
• Wed. Sept 30 – 3:00 PM to 4:15 PM: General Session on Important Trends in Visual Computing
• Wed. Sept 30 – 4:30 PM to 5:45 PM: General Session on Breakthroughs in High Performance Computing
• Thurs. Oct 1 – 9:00 AM to 10:30 AM: Day 2 Keynote with Hanspeter Pfister, Professor and Computing Visionary, Harvard University
• Fri. Oct 2 – 8:30 AM to 10:00 AM: Day 3 Keynote with Richard Kerris, CTO, Lucasfilm

NVIDIA has released public OpenCL GPU Drivers and an OpenCL performance profiler for Windows, available for free download fromthe NVIDIA OpenCL Download Page.  From an NVIDIA press release:

SANTA CLARA, Calif. -Sep. 28, 2009- NVIDIA today released the first public OpenCL conformant GPU drivers for Windows and Linux. In addition to the drivers themselves, NVIDIA has released a powerful performance profiling tool and an OpenCL Best Practices Guide.

NVIDIA was the first to release beta OpenCL GPU drivers to developers in April 2009.This public release is fully conformant with the OpenCL v1.0 specification and supports the OpenCL Images features of the specification that, while optional for other vendors, provides significant performance benefits across many image processing disciplines such as medical imaging, video transcoding applications, machine vision and facial detection.

Leveraging the extensive performance instrumentation in NVIDIA’s OpenCL drivers and hardware performance signals designed into NVIDIA GPUs, the OpenCL Visual Profiler provides developers with insight into performance bottlenecks and opportunities for optimization.

Key features include:

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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: www.nvidia.com/opencl

“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: www.nvidia.com/opencl