Yellow Dog Enterprise Linux for CUDA (YDEL for CUDA) is an open source, Linux operating system built for faster, easier, and more reliable GPU Computing. YDEL for CUDA, released and supported by Fixstars, goes beyond the basic Linux OS and integrates support for GPUs, NVIDIA CUDA, and GPU development tools.

From the YDEL for CUDA website:

Key benefits of Yellow Dog Enterprise Linux for CUDA:

• YDEL for CUDA users can experience up to a 9% performance improvement in some applications.
• Comprehensive support is offered to paid subscriptions with our skilled team able to assist you with both Linux and CUDA.
• YDEL’s unparalleled integrations means everything you need to write and run CUDA applications is included and configured.
• YDEL includes multiple versions of CUDA and can easily switch between them via a setting in a configuration file or an environment variable.
• Never worry about updates affecting your system, Fixstars offers YDEL users greater reliability with our strenuous test procedures that validate GPU computing functionality and performance.

For more information, visit the YDEL for CUDA website.

GPULib provides a library of mathematical functions that facilitate the use of high performance computing resources available on modern graphics processing units (GPUs) by engineers, scientists, analysts, and other technical professionals with minimal modification to their existing programs. This software library executes vectorized mathematical functions on graphics processing units (GPUs) from NVIDIA, bringing high-performance numerical operations to everyday desktop computers. By providing bindings for a number of Very High Level Languages (VHLLs) including MATLAB and IDL from ITT Visual Information Solutions, GPULib can accelerate new applications or be incorporated into existing applications with minimal effort. No knowledge of GPU programming and memory management is required. For more information regarding GPULib, please visit http://GPULib.txcorp.com.

From a press release:

New Software Solution Reduces Dependency on CPUs

PORTLAND, Ore.- SC09-Nov. 18, 2009- NVIDIA Corporation (Nasdaq: NVDA) and Mellanox Technologies Ltd. today introduced new software that will increase cluster application performance by as much as 30% by reducing the latency that occurs when communicating over Mellanox InfiniBand to servers equipped with NVIDIA Tesla™ GPUs.

The system architecture of a GPU-CPU server requires the CPU to initiate and manage memory transfers between the GPU and the InfiniBand network. The new software solution will enable Tesla GPUs to transfer data to pinned system memory that a Mellanox InfiniBand solution is able to read and transmit over the network. The result is increased overall system performance and efficiency.

“NVIDIA Tesla GPUs deliver large increases in performance across each node in a cluster, but in our production runs on TSUBAME 1 we have found that network communication becomes a bottleneck when using multiple GPUs,” said Prof. Satoshi Matsuoka from Tokyo Institute of Technology. “Reducing the dependency on the CPU by using InfiniBand will deliver a major boost in performance in high performance GPU clusters, thanks to the work of NVIDIA and Mellanox, and will further enhance the architectural advances we will make in TSUBAME2.0.” Read the rest of this entry »

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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nCore Design announces the immediate availability of the NCT-300 Programming GPU Processors course. Conceived with the experienced C/C++ programmer in mind, NCT-300 covers concepts and approaches related to programming GPU processors using both CUDA and OpenCL. The course covers GPU hardware, memories, data transport, CUDA and OpenCL APIs, programming methods and performance optimization. It will enable students to understand the fundamental aspects of GPU programming and become proficient in a relatively short time. Extensive hands-on laboratories demonstrate how to apply common numerical methods using both native APIs and open source libraries. Other topics covered in the course include integrating the Intel Threading Building Blocks (TBB) abstraction layer with native GPU software APIs in addition to a GPU debugging primer.

The class brochure is available for download. To register, schedule an on-site session or contact nCore Design, go to http://www.ncoredesign.com/company/contact_us.

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.

Read the rest of this entry »

AMD announced its latest ATI Radeon™ series of graphics cards on September 23rd.  The new GPUs boast up to 2.72 GFLOP/s of single-precision floating point throughput, along with DirectX® 11 graphics (including DirectCompute) and OpenCL 1.0 support.

From the press release:

AMD (NYSE: AMD) today launched the most powerful processor ever created¹, found in its next-generation graphics cards, the ATI Radeon™ HD 5800 series graphics cards, and the world’s first and only to fully support Microsoft DirectX® 11², the new gaming and compute standard shipping shortly with Microsoft Windows® 7operating system. Boasting up to 2.72 TeraFLOPS of compute power, the ATI Radeon™ HD 5800 series effectively doubles the value consumers can expect of their graphics purchases, delivering twice the performance-per-dollar of previous generations of graphics products.³ AMD will initially release two cards: the ATI Radeon HD 5870 and the ATI Radeon HD 5850, each with 1GB GDDR5 memory. With the ATI Radeon™ HD 5800 series of graphics cards, PC users can expand their computing experience with ATI Eyefinity multi-display technology, accelerate their computing experience with ATI Stream technology, and dominate the competition with superior gaming performance and full support of Microsoft DirectX® 11, making it a “must-have” consumer purchase just in time for Microsoft Windows® 7 operating system.

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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

To assist contestants in the TopCoder and NVIDIA CUDA Superhero Challenge, from August 28th and continuing for one month, RenderStream will offer a promotional discount of up to $500 for the first ten PSC development systems they sell with  two or more C1060 cards or $800 for one S1070 integrated with a Twin Dual Quad Server (no more than two systems per customer). In addition, RenderStream will give a free NVIDIA Tesla C1060 to the customer who places highest in the contest.

For more information please visit http://www.renderstream.com/HPC.html or email info@renderstream.com.

Intel has acquired RapidMind, the company behind the RapidMind (formerly Sh) programming environment targeting multicore CPUs, AMD and NVIDIA GPUs and the Cell processor. The RapidMind Platform continues to be available, including support. In the medium term RapidMind’s technology and products will be integrated with Intel’s data-parallel products, in particular Intel’s Ct technology.

This blog entry by James Reinders from Intel describes the acquisition and future plans in more detail.