j (invalid.delete@this.example.org) on August 2, 2018 11:41 pm wrote:
> Simon Farnsworth (simon.delete@this.farnz.org.uk) on August 1, 2018 3:50 am wrote:
> > SoftwareEngineer (soft.delete@this.ware.com) on August 1, 2018 2:15 am wrote:
> > > It's all a horribly fragile hack on top of a language which was never built to support vectorization.
> > > You just don't get these sorts of problems working in CUDA. Intel's ispc seemed promising, but it
> > > never felt like it had official blessing, and it didn't have a very well developed tool chain. It
> > > always felt like it might get abandoned at a moment's notice if the wrong guy left/was fired.
> >
> > You might want to read the story of ispc; it'll explain why
> > you had the feelings you did, and why it seemed promising.
> >
> > There's an index of all twelve entries, too, for anyone who's seen some
> > of the story and wants to pluck out a given entry for consideration later.
>
> I'm not familiar with ispc beyond reading that set of history posts, how is the programming model
> different from OpenCL? Based on the examples in those blog posts, it seems quite similar?
>
> Or for that matter, a hypothetical CUDA targeting CPU's rather than Nvidia GPU's?

Maybe this is a question, coming from a total amateur, but nonetheless, for what it's worth.

This is from the developer zone conversation of 12 months ago. It doesn't look promising.

https://software.intel.com/en-us/forums/intel-many-integrated-core/topic/737882

I've got a question that I've been trying to phrase about all of this too. Like back in 2003, one had people coding for chess artificial intelligence projects, and they were trying to use Intel's C++ compiler fifteen years ago, and not getting very far with it, trying to compile for use on ordinary single core x86 CPU's back then. I guess, one could have termed that very small sub-set, or niche community of developers back then who were trying to work with the Intel tools provided, as the early pioneers in artificial intelligence programming on the desktop products.

But the question that I'd have, is that if those developers had Xeon Phi, or nVidia CUDA back then, would they have abandoned trying to work with CPU's entirely, and opted instead for a faster way to achieve their goals. Would they have abandoned trying to build chess AI on x86 processors entirely? Maybe, not because of the hardware, but because the compilers for the x86 processors at the time, weren't making it easy for them?

And turn that question on it's head to today. What if any reason would there be today for a member of the same kind of community of developers in artificial intelligence for chess games, to choose to develop their projects on top of generic x86 processor technology at all? And not just chess game artificial intelligence. There are tonnes of difficult problems that can yield to the investigations using AI. At one stage, I was very interested in problems to do with Logistics, for example.

https://blogs.nvidia.com/blog/2018/03/28/self-learning-ai-for-logistics/

There are 'open' solutions and age-old technologies such as C++ (a knowledge of an object-oriented programming language, is still demanded as a minimum for any post graduate research positions at my local university for example, and these skills are still useful to have). And there are other proprietary tools, that are intended to foster the development quickly of talent working around proprietary nVidia hardware. And while, I'm all for generic tools and means of accomplishing tasks in computers,... judging between the 'community' that is suggested by the Intel link overhead, or being a part of the community as is suggested by the nVidia link instead,... if you were a young kid now today in a post-graduate position, looking to actually finish writing your thesis, which one would you choose?

And for all of the many flaws and failings of those systems of long ago:

https://www.realworldtech.com/forum/?threadid=138897&curpostid=178980

There certainly was a vibrant community of scientists that worked around languages and technology of Fortran too in the past. Is that the part, the actual 'level of support', for that kind of community that nVidia identified had become missing in the modern day era of personal computers? I.e. Getting back to my point above, where chess game artificial intelligence researchers were forced back to working on very inappropriate tools and technology, say 15 years ago? Because there was very little alternative.

https://www.realworldtech.com/forum/?threadid=16463&curpostid=16579

Above, is the question that I'd like to ask Eric again perhaps if he's around. Has Intel really done the best job that it could, out of making a place in which post-grad students on various campuses around the world, in key centers of learning could rally around a community based on Intel's solutions, for that particular niche? And not just in 2018, but going right back as I mentioned to 2003 and further back even? On the one hand, Intel has succeeded beyond all expectations in putting a laptop computer in the rucksack of all of those students, who needed to type up reports and browse websites. But that's not the same thing as doing analytics, and crunching data, to back up the research that they're going to write about?

Maybe Intel wasn't the right company in order to provide the later, and maybe that is the answer. But was there a chance, that Intel could have been a greater part of artificial intelligence and support for the same? Were there opportunities missed?