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: not just for gpu's
by big_gie on Sun 12th Dec 2010 19:13 UTC in reply to "not just for gpu's "
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Yes, OpenCL is really nice. It's really a front-end to many different architectures. You program in OpenCL and it can run on GPU (nvidia and ati), CPU (amdstream), or other kind of processors. No need for porting.
The resulting programs might not be as fast as Nvidia's CUDA (I haven't seen anything proving that though) but at least it can run _everywhere_

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