These webinars cover many topics including an introduction to C for CUDA, the OpenCL™ API, and performance optimization techniques, presented by NVIDIA DevTech Engineers with additional staff online to answer questions.

Full Schedule and short abstracts can be viewed at: http://developer.nvidia.com/object/gpu_computing_online.html

AMD’s STREAM SDK v2.0 beta4 is the first release of the STREAM SDK with OpenCL support on CPUs and GPUs. The OpenCL implementation is certified OpenCL 1.0 conformant by the Khronos group. Supported platforms are Windows XP, Vista and Windows 7, and a number of Linux distributions, all in 32 and 64-bit. The implementation supports AMD and Intel multicore CPUs, as well as the two latest GPU generations from AMD.

The STREAM SDK as well as documentation and further information is available on AMD’s developer website.

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.

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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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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Slides from two full-day conference tutorials are now available:

• SPEEDUP 2009 Practical GPU Computing with NVIDIA CUDA: Lausanne, Switzerland, September 8, 2009 (Dominik Göddeke, Robert Strzodka and Christian Sigg)
• PPAM 2009 GPU and OpenCL Tutorials: Wroclaw, Poland, September 13, 2009 (Robert Strzodka, Dominik Behr and Dominik Göddeke)

Both tutorials present basics and advanced topics of scientific computing on GPUs, including ready-to-use GPU libraries, GPU architecture, case studies and many hands-on examples.

The OpenCL Visual Profiler is now available to all NVIDIA GPU Computing Registered developers, and will be included in the next public release of the CUDA Toolkit. Professional developers and researchers are invited to apply for the GPU Computing Registered Developer program.

The OpenCL Best Practices Guide is already publicly available on CUDA Zone.

Details from the press release:

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:

• Profiling of actual hardware signals, kernel efficiency, and instruction issue rate
• Timing of memory copies between system memory and GPU dedicated memory
• Customizable graphs to help developers focus in on problem areas
• Basic auto-analysis to reveal warp serialization problems
• Easy import/export to CSV for custom analysis

NVIDIA has also prepared a helpful OpenCL Best Practices Guide designed to help OpenCL developers programming for the CUDA architecture implement high performance parallel algorithms and understand best practices for GPU Computing.

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Tom’s Hardware has published a comprehensive interview with Ian Buck, NVIDIA’s Director of Software for GPU Computing.  In the interview Ian discusses the history of GPGPU (including a referral to our fair site — thanks Ian!) and his work at Stanford on Brook for GPUs.  He then goes on to discuss the development of CUDA and the teams at NVIDIA responsible; OpenCL and tradeoffs between the industry standard API and C for CUDA; and future directions for GPGPU applications.

AMD is now offering a free OpenCL for CPU beta download as part of the ATI Stream SDK v2.0 Beta Program. The beta will help programmers to more easily develop parallel software programs and take further advantage of multi-core x86 CPUs to accelerate software and deliver a better computing experience. AMD has submitted conformance logs from its Microsoft Windows and Linux CPU beta releases to the Khronos Working Group for certification.

The full press release is available here, and the SDK can be downloaded here.

These webinars cover many topics including an introduction to C for CUDA, the OpenCL™ API, and performance optimization techniques, presented by NVIDIA DevTech Engineers with additional staff online to answer questions.

Full Schedule and short abstracts can be viewed at: http://developer.nvidia.com/object/gpu_computing_online.html