OpenCL tagged news

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.

The World's Premier Super Computing event, SC09, will hold its 22nd annual event in Portland Oregon this November. This year, more than 275 exhibitors with 40 participating for the first time, have the SC09 organizers expecting a full house at the Oregon Convention Center. One of the first time exhibitors includes the Khronos Group. The Khronos Group will have booth #242 this year and will undoubtedly be extolling the virtues of OpenCL. You will find complete details of tutorials, wokrshops and sessions on the Khronos website.

OpenTK is an advanced, cross-platform library that provides Mono/.Net OpenGL, OpenGL ES, OpenAL and OpenCL bindings. The latest version adds support for all OpenGL ES extensions, significantly improves the OpenCL bindings and the ARB_imaging subset of OpenGL. A new compatibility module now allows Tao framework applications to run on OpenTK and improves behavior on broken xlib implementations. Finally, this version adds support for the iPhone platform via the MonoTouch project.

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.

Apple's Snow Leopard hit the streets friday as the first major OS to support OpenCL. OpenCL, the Open Computing Language, was originally proposed by Apple to support parallel programming on GPUs and handed over to the Khronos Group, the same independent standards organization that manages the OpenGL standard for 3D rendering. Support for OpenCL may start with Snow Leopard but it will go well beyond that. AMD and Nvidia will have OpenCL drivers for their GPUs under Windows and Linux. AMD and Intel will support OpenCL on their CPUs (including Intel's Larrabee). AMD has already shipped its first OpenCL implementation for its Athlon and Opteron processors. For those folks with OpenCL already up and running on their Apple computers under Snow Leopard, there are two benchmark applications out, so you can see just what OpenCL can do for you.

PyOpenCL has been released. This OpenCL wrapper for Python has complete documentation and a wiki setup. Key features of PyOpenCL are: object cleanup tied to lifetime of objects; the full power of OpenCL’s API at your disposal with every obscure get_info() query and all CL calls are accessible; automatic error checking; base layer is written in C++; complete documentation; a liberal open-source and free for commercial, academic, and private use under the MIT/X11 license. If you have feedback on this wrapper, you can contribute to a live discussion in the Khronos Message Boards.

With the launch of Snow Leopard this Friday, now is the time to start getting revved up for some of the new technologies coming with this release. One of them, OpenCL. MacResearch.org has done a great overview of what OpenCL is and a beginners tutorial on how it works and how to use it.

Members of the Khronos Group will be presenting a half day tutorial at Hot Chips 21 this August 23rd 2009 between 1:30 and 5:30 in the Memorial Auditorium at Stanford University California. The authors include Neil Trevett from NVIDIA, Mike Houston from AMD, Tim Mattson from Intel, Chris Lamb from NVIDIA, Eric Schenk from Electronic Arts and Kari Pulli from Nokia. Registration fees range from students at $95 to non-members at $220 for the Tutorials. Registration fees for Tutorials include a printed set of tutorial notes, continental breakfast, lunch, coffee break, and invitation to the evening Wine and Cheese Reception on Sunday, August 23, 2009.

AMD announced it 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.