NVIDIA releases their first set of display drivers (for GeForce 6, 7, 8, 9, 100, and 200-series desktop GPUs and ION desktop GPUs) that brings the public support of OpenCL (Open Computing Language). OpenCL (GPU version) is limited to GeForce 8 and later GPUs. This release includes also over 200 bug fixes.
Fixstars Corporation, a pioneering company in multi-core solutions announced that it has launched an OpenCL software service. Fixstars provides various services to develop software based on parallel computing framework which has high portability for HPC, desktop and embedded application developers.
S3 Graphics announced the OpenCL 1.0 capable Chrome 5400E GPGPU processor. The 5400E features native support of OpenCL, the industry’s best GFLOPS per watt rating including, a OpenGL 3.1 / DirectX® 10.1 graphics engine, ChromotionHD video core for HD video decode including Blu-ray, H.264, and VC-1, a video encode engine, and an OpenVG 1.1 engine. The 5400E is the most versatile GPU for embedded applications requiring longevity, customization, performance, features, and low power. Complete details are available on the S3 Graphics website.
ARM announced the launch of the ARM® Mali Developer Center. The Developer Center offers a comprehensive suite of resources for graphics and embedded applications developers working with the Khronos OpenGL ES 1.1 and 2.0, OpenVG 1.0 and 1.1, as well as other APIs. Accessing these resources as members of the Mali ecosystem will enable developers targeting Mali graphics processing unit (GPU) platforms to bring best-in-class content to market.
NVIDIA is hosting two more seminars over the next few days which cover ‘Best Practices for OpenCL Programming’, and ‘An Introduction to GPU Computing and OpenCL’. The series will cover many topics including C for CUDA, programming to the OpenCL™ API , using DirectCompute and performance optimization techniques. The Webinars are presented by NVIDIA Developer Technology Engineering team and have NVIDIA staff online to answer Questions.
ExtremeTech discusses GPGPU computing on Windows 7. “Both Nvidia and ATI are committed to supporting DirectX 11 on their newest boards; and both now have early OpenCL drivers out as well. In particular, I expect both of their Windows 7 drivers will support OpenCL.” says Michael Miller.
MacResearch has posted part 6 in their series of OpenCL tutorials. In this episode, a real-world code that has been parallelized by porting to the GPU. The use of shared memory to improve performance is covered as well as a discussion of synchronization points for coordinated work within a work-group. Source code is provided.
Vivante Corporation today announced that Arkmicro Technologies, Inc. has licensed Vivante GPU IP for its newest mobile navigation and entertainment system-on-chip (SoC) designs. “The stunning visual effects offered by OpenGL ES 2.0 and OpenVG 1.1 are driving a wide range of location based applications in markets around the globe,” said Wei-Jin Dai, President and CEO of Vivante Corporation. Peter Shi, CEO of Arkmicro Technologies, added, “Vivante GPUs give us the outstanding visual graphics quality and performance we need to extend our leading media SoC family of solutions.”
NVIDIA just released its first OpenCL-conformant graphics driver to the public. Up to now, it was only available to registered members of its GPU Computing developers program. Get your OpenCL driver today.
A new project on Google code offers up Java/Scala bindings for OpenCL. OpenCL4Java is a library that provides three levels of Java bindings for OpenCL: C-style wrappings auto-JNAerated by JNAerator; Thin Object-Oriented wrappings that hide away the complexity of the C-style wrappings; ScalaCL, which is a kind of “parallel expressions for dummies” in Scala. A thread on the OpenCL message boards is available for feedback.
NVIDIA has released the first public OpenCL conformant GPU drivers as well as a powerful performance profiling tool and an OpenCL Best Practices Guide. The OpenCL Visual Profiler uses the extensive performance instrumentation in NVIDIA’s OpenCL drivers and hardware performance signals designed into NVIDIA GPUs to provide developers with insight into performance bottlenecks and opportunities for optimization. The 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. The OpenCL drivers, Visual Profiler, and Best Practices Guide are all available on the NVIDIA developers website.
The upcoming Palm Pixi will have the new MSM7627 chipset from Qualcomm giving close to the same performance as the Pre. Featuring two ARM cores integrated as a single chip – a dedicated CPU core and a dedicated modem processor – 320MHz application DSP for multimedia supporting full 30 fps WVGA encode/decode, 200MHz hardware-accelerated 3D graphics core supporting OpenGL ES 2.0, high-resolution camera and integrated GPS.
While OpenCL is very similar in many respects to NVIDIA’s CUDA, it adds features to take advantage of other targets; and though it’s quite complex, it has the potential to deliver very high performance, and is much easier than trying to map your computation into OpenGL or graphics primitives. So says Michael Wolfe, with over 30 years in both academia and industry on developing compilers, and is now a senior compiler engineer at The Portland Group, Inc., a wholly-owned subsidiary of STMicroelectronics, Inc.
NVIDIA released a new OpenCL Visual Profiler for Windows and Linux for developers. 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. NVIDIA also released a Best Practices guide for OpenCL.
All NVIDIA CUDA-Enabled GPUs Shipped by Apple Supported under New Operating System. OpenCL on the NVIDIA® CUDA™ architecture enables applications to use the CPU and the GPU together as co-processors. NVIDIA’s integration of the CUDA architecture across its brands and segments enables it to offer Apple users a broad selection of 10 GPU models officially supported by Snow Leopard.