Linked by Thom Holwerda on Sat 11th Dec 2010 18:35 UTC
General Development "Using a GPU for computational workloads is not a new concept. The first work in this area dates back to academic research in 2003, but it took the advent of unified shaders in the DX10 generation for GPU computing to be a plausible future. Around that time, Nvidia and ATI began releasing proprietary compute APIs for their graphics processors, and a number of companies were working on tools to leverage GPUs and other alternative architectures. The landscape back then was incredibly fragmented and almost every option required a proprietary solution - either software, hardware or both. Some of the engineers at Apple looked at the situation and decided that GPU computing had potential - but they wanted a standard API that would let them write code and run on many different hardware platforms. It was clear that Microsoft would eventually create one for Windows (ultimately DirectCompute), but what about Linux, and OS X? Thus an internal project was born, that would eventually become OpenCL."
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RE: CUDA platform support on x86
by CodeMonkey on Mon 13th Dec 2010 16:11 UTC in reply to "CUDA platform support on x86"
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I wonder how the integrated GPU/CPU chips coming out next year (Intel'sandy Bridge and AMD Fusion) is going to affect these developments.

While these integrated chips are on a single package, theyr'e still two discrete components being placed inside a single box. From the OpenCL perspective, whether the devices are integrated or on discretely seperate PCIe bus lanes, the programming API is unchanged. The OS and the framework still see them as two logically seperate devices. When retrieving the list of available OpenCL devices, you'd get get a CPU device and a GPU device. The physical integration into a single package is invisible to the API.

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