
Pascal GPUs on All Fronts Push Nvidia to New Highs - jonbaer
https://www.nextplatform.com/2016/11/12/pascal-gpus-fronts-push-nvidia-new-highs/
======
nl
Yep.

And AMD just doesn't care - literally:

 _" For the most part, because—in the case of Nvidia—they don't appear to care
that much about VR. And in the case of the dollars spent on R&D, they seem to
be very happy doing stuff in the car industry, and long may that continue—good
luck to them. We're spending our dollars in the areas we're focused on."_[1]

Everytime someone complains about how little OpenCL is used, I just think of
that quote. I'm happy to use products from a company that cares about what I
do.

(And yes, good OpenCL implementations would be great too. But the world won't
wait for AMD on this).

[1] [http://arstechnica.co.uk/gadgets/2016/04/amd-focusing-on-
vr-...](http://arstechnica.co.uk/gadgets/2016/04/amd-focusing-on-vr-mid-range-
polaris/)

~~~
erichocean
> _good OpenCL implementations would be great too_

Now that Vulkan is out, that's far less important than it used to be.

~~~
shrewduser
i wasn't even aware vulkan obviated openCL...

~~~
shmerl
They overlap to some degree. Vulkan allows access to compute queues of the GPU
(in addition to graphics ones).

~~~
pjmlp
OpenGL already does that via compute shaders and it hasn't helped.

~~~
shmerl
Hasn't helped what exactly? OpenGL can't provide proper parallelized access to
all the queues, so having compute shaders there isn't that useful.

~~~
pjmlp
To gain adoption.

NVidia doesn't care about OpenCL.

Google doesn't care, and pushes Renderscript instead.

Apple doesn't care, it created OpenCL, but since Khronos doesn't dance their
music, they rather push Metal Compute Shaders.

Microsoft has C++AMP and DX Compute.

Additionally CUDA was designed to be targeted by multiple languages, while
OpenCL had to wait for OpenCL 2.0 for it to happen.

Also the graphical debuggers for OpenCL could get some love.

I know which GPU makers I will keep giving my money to.

~~~
shmerl
When crooked interests hinder adoption, you should blame the crooked
interests, not the technology.

Anyway, Vulkan provides lower level access to the compute functionality. And
MS and Apple can get lost with their selfish NIH approach. The rest are
supporting Vulkan, including all GPU makers.

~~~
pjmlp
What rest?

So far I have only seen Vulkan on GNU/Linux and Android 7.0+ deployments.

And I am willing to bet it won't change, specially since most of us only care
about middleware engines nowadays.

Guess which API was being discussed at Unite 2016 LA? Hint: it wasn't Vulkan.

~~~
shmerl
_> What rest?_

Everyone.

 _> And I am willing to bet it won't change_

MS and Apple will sleep until they'll realize, their NIH is threatened by
competition. They don't play nice otherwise. But you expressed multiple times
that you like lock-in, so I doubt you'll appreciate it.

~~~
glaze
I don't think the lock-in in the case of graphics APIs is too bad, because
even for large codebases implementing a new graphics API support is often done
by one or two persons.

------
arcanus
I like nextplatform and nvidia did just have a great quarter. Tensorflow runs
best when accelerated by nvidia GPUs.

However, the article vastly oversells nvidia in the HPC space. Intel's MIC
platform is targeted at competing with GPUs, and cuda is a closed standard.
Nvidia is by no means dominant in HPC, and has parts in only two machines in
the top-10, and none that I'm aware of under contruction.

Finaly, Exascale architecture is likely to be radically different than present
tech. It could absolutely shake up the environment significantly.

~~~
craigyk
I believe the DOD already has plans to bring online two new computers in the
near future that will retake the crown. At least one of them with Nvidia with
a big emphasis on P100 and nvlink.

~~~
synacksynack
Summit and Sierra are two planned DOE machines with hardware developed in
collaboration with IBM and Nvidia. They're slated to feature Volta GPU, a
generation past P100's Pascal.

More details here:
[https://www.olcf.ornl.gov/summit/](https://www.olcf.ornl.gov/summit/)

~~~
craigyk
OK, that's right, was working from memory. In any case, GPUs are making big
inroads into HPC.

------
dharma1
Training - I have a feeling it's going to be NVidia for a while. AMD just
doesn't show interest in joining the party, and NVidia has been optimising
CuDNN for a while now, it will take a bit of time to play catch up. I really
don't understand what AMD have been doing the past 2 years here.

Inference - NVidia will have a much harder time enforcing a monopoly here,
because they are not, and cannot be the dominant player on all the hardware
where neural networks will run after training. ARM, Qualcomm and others in
mobile space will be pushing it hard, as will vendors running neural nets on
FPGA/ASIC designs that are now emerging.

Will be interesting to see what effect architectures using low precision or
binary weights (for both training and inference) will have too on the hardware
landscape.

SPIR-V - AFAIK Codeplay ([https://www.codeplay.com](https://www.codeplay.com))
are working on SPIR-V support for tensorflow, that should in theory help to
use TF on various hardware that supports Vulkan/SPIR-V. But I guess each
vendor will still need to tune things like convolution kernels for their
specific hardware to squeeze the best perf out

~~~
chronic6l
You realize that deep learning is such a small market and will be small in the
context of GPUs?

~~~
dharma1
could have fooled me [http://fortune.com/2016/11/10/nvidia-earnings-stock-
machine-...](http://fortune.com/2016/11/10/nvidia-earnings-stock-machine-
learning/)

~~~
muyuu
In the article there's a comparison of earnings by usage. It remains
comparatively small.

~~~
dharma1
For now. It's also hard to say, how much of the rise in their "gaming"
earnings - is in fact driven by people buying GPUs for deep learning.

Everyone I know who are doing deep learning have been buying Titan X's or GTX
1080's - their "gaming" cards. Not the datacentre or pro viz cards.

~~~
muyuu
I think you might be overestimating the worldwide impact of that, though. AMDs
are used for "mining crypto" \- they're the best for that purpose - and no,
that also is nothing to write home about. Despite being very present in my
personal circles.

The amount of people doing either is minuscule in comparison to gaming. Those
buying big for datacentres are definitely accounted for by nVidia. They don't
buy GTX cards.

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tener
Their graphs are showing a large growth in 201 __7 __which are pure
predictions. To makes matters worse they are not marked as such which is
misleading.

~~~
Maakuth
How can anything concerning future be something else than pure prediction? Do
you mean like already agreed orders with delivery dates in 2017?

~~~
B1FF_PSUVM
There are two wrinkles here:

\- "Fiscal 2017" may not be the calendar year, e.g. it could comprise
April-2016 to March-2017. (I don't know the specifics here, but accounting is
weird that way.)

\- There's booking, and "book-to-bill ratio" in the semiconductor industry.
I.e. the pre-orders are recorded quite a bit in advance, but actual shipments
(and payments) may vary.

~~~
mcbits
Right, the graph goes up to Q3 of Nvidia's fiscal 2017, which just ended on
October 30. So apparently the fiscal year will end sometime in January.
[http://nvidianews.nvidia.com/news/nvidia-announces-
financial...](http://nvidianews.nvidia.com/news/nvidia-announces-financial-
results-for-third-quarter-fiscal-2017)

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tambourine_man
I thought we'd be able to write code in Pascal for the new Nvidia GPUs.

I have found memories of the language.

~~~
pjmlp
Well it is just a matter of getting FreePascal to output PTX. :)

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touristtam
> Just like Intel arguably does not need the Core PC chip business to justify
> the existence of a very large and profitable Xeon server chip business.

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diziet
It looks like Nvidia's financial quarters are a couple of quarters ahead of
calendar quarters.

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mp3geek
Does this show PC Gaming is booming as a result?

~~~
eva1984
Shows deep learning is the new king.

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7TJx4UN4ro25
Note that the first graph is misleading - it does not provide the context the
release of their previous architecture.

