KitGuru recently interviewed the well known and highly respected AMD employee Terry Makedon. Covering ATI Stream SDK and OpenCL, among other things, Terry gives a peak into the direct AMD is going with these technologies.
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The new version of GPU Caps Viewer is available with the support of OpenGL 4.1 context and a better support of OpenCL. Now you can select the GPU that will be used to execute the kernels of the OpenCL demos. GPU Caps Viewer is an information utility focused on the OpenGL, OpenCL and CUDA API level support.
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OpenCL framework to accelerate an EMRI modeling application using the hardware accelerators – Cell BE and Tesla CUDA GPU. The main goal of this work is to evaluate an emerging computational platform, OpenCL, for scientific computation. Results show OpenCL binary on a par with CUDA SDK. Baseline is an AMD Phenom 2.5Ghz CPU.
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Enj appears to be enjoying the GTC 2010 Conference this week. He brings us an inside view of the conference, and a feel of the different talks on OpenCL and CUDA. If you have 5 minutes, pop over to enja.org, it'll be worth your time.
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ZDNet sat down with Huang at the recent GPU Technology Conference in San Jose, California to discuss CUDA, OpenCL and all things parallel computing.
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VDPAU (Video Decode and Presentation API for Unix) allows Linux systems to offload portions of video decode to the GPU. The resulting video can be post-processed with OpenGL, CUDA, or both. Watch Stephen Warren from NVIDIA explain VDPAU and demonstrate OpenGL texturing of hardware-decoded video frames. Slides (PDF) are also available.
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NVIDIA has released their CUDA Toolkit 3.2. Lots of new goodness in this version, with special note the new OpenCL support. This means you can now use one toolkit for both CUDA and OpenCL. Support is currently only for Linux and Windows.
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SiSoftware has posted two OpenCL benchmarks online. One addresses GPGPU OpenGL performance, and the second CPU OpenGL performance. The conclusion: There is no reason not to port CUDA code to OpenCL now!
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Students learn with interactive and hands-on sessions about GPU hardware, GPU languages, discovering how best to take advantage of GPUs for their computational needs. The course covers programming in both OpenCL and CUDA, pointing out the similarities and differences along the way. Topics include both the core languages and extensions including those for double precision and interfacing with OpenGL 3D graphics buffers.
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Glare Technologies have announced the release of a new version of their flagship rendering product: Indigo Renderer version 3.0, which now includes support for both OpenCL and CUDA. Indigo is an unbiased, physically based and photo-realistic renderer which simulates the physics of light to achieve near-perfect image realism. With an advanced physical camera model, a super-realistic materials system and the ability to simulate complex lighting situations through Metropolis Light Transport, Indigo is capable of producing the highest levels of realism demanded by architectural and product visualisation.
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