Khronos Group Finalizes OpenCL 2.2 Specs, Releases Source On GitHub

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OpenCL is supported by everyone from Nvidia and AMD to Apple and Intel.
Lol, that's funny!

Nvidia has been stuck at 1.2, with no apparent interest in upgrading. Only days ago, I learned they actually have beta-level support for parts of 2.0! Support for OpenCL is still non-existent, on their Tegra mobile/embedded platform, and this in spite of OpenCL's embedded profile and the fact that they support CUDA (a functional superset) on it.

Apple, who gets credit for instigating OpenCL, back in ~2007, has favored their proprietary standard - Metal.

AMD has really been OpenCL's biggest proponent. They jumped on the bandwagon pretty early, and pretty much dropped their proprietary alternatives (except for C++ AMP, which I think is more of a Microsoft thing). More recently, they've been pushing the HSA standard, although I think they don't intend it to succeed OpenCL in all contexts.

In any case AMD has just open-sourced their entire OpenCL stack! This will mean better support for AMD's OpenCL stack on more platforms.

Intel has also been pretty good with OpenCL support - at least on their latest architectures.

Mobile support is rather spotty, with Google following Apple's lead and creating their own RenderScript. Such a shame, because they had the muscle to make OpenCL a truly standard part of the Android platform.

Khronos has delivered on its promise to make C++ a first-class kernel language in the OpenCL standard
This really is a big deal. Without this, it was difficult to write generic & reusable kernel code to implement parallel algorithms and data structures. This will be a great benefit to the OpenCL ecosystem.
 
Nvidia and Google have engaged in a public battle to say they've developed the best inferencing hardware
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it seems the Khronos Group wants OpenCL to help these companies reach their machine learning goals
Ha ha! Did you know that a VP at Nvidia chairs Khonos' OpenCL working group? If he really wanted OpenCL to factor into their deep learning strategy, you'd think they would have better support for it.

https://www.khronos.org/about/working-group-chairs/

No, what you'll find is that Nvidia has gotten in the deep learning game early, with many frameworks featuring CUDA support (even before OpenCL). Nvidia also has their own proprietary frameworks they'd be happy for you to use.

Google's Deep Learning ASICs are probably too specialized for OpenCL support. They probably added custom support for them in TensorFlow and maybe a couple other deep learning frameworks. I don't know if Google has more recently been a supporter of OpenCL, but they'd at least be in a position to benefit from it by having good support for it on Android.
 
> In any case AMD has just open-sourced their entire OpenCL stack!

Citation needed. Google turns up nothing.
 
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