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The Nvidia DGX-1 Deep Learning Supercomputer in a Box

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Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#31

Post by bgalbraith »

RussianCow wrote: post #30
bgalbraith wrote: post #29

Earlier quoted context omitted.

What monopoly? You totally have a choice, it's just that NVIDIA made a large bet on GPGPU and it is paying off for them. You don't see AMD heavily pushing their cards for compute purposes or developing computational developer relations.

You often don't have a choice because a large amount of GPGPU software is written using CUDA, which is Nvidia-specific.

NVIDIA does not have a monopoly in the traditional sense. But yes, the have a de facto one because there is no viable competition.

It's like saying MATLAB has a monopoly in academic research because so much of the code is written in it. That is slowly changing and moving over to Python now, which is great. Maybe OpenCL will get there someday, but I don't see it happening any time soon.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#32

Post by Robadob »

DeepYogurt wrote: post #20
phelm wrote: post #18

I am looking forward to OpenCL catching up with CUDA in maturity and adoption, so that NVidia's monopoly in Silicon for deep learning will come to an end.

Me too. I really want to see some benchmarks between cuda code and opencl code generated from cuda with AMDs compiler. Actually if anyone has a geforce/tesla get on this!

I haven't seen any recent benchmarks, but ones from 2011 all seemed to show CUDA and OpenCL on open footing in terms of performance when optimised properly.[1][2] CUDA simply had better library support, and a more well defined and uniform architecture to target. Whereas OpenCL is likely to require more programming to fill in the gaps for library support, and different optimisations depending on the architecture you wish to target. I'm guessing since then, the CUDA compiler may have improved somewhat in terms of optimisation based on some micro-benchmarking research I was looking the at the other day.

There's also Intel's MIC to consider now to, although that has a vastly different architecture to GPU. Again performance was similar between MIC and GPU in 2013[3], each performing better where their architecture was more suited, GPUs were capable of providing double the bandwidth for random access data.

In terms of AMD vs NVIDIA, I've not looked into it, I doubt AMD has anything to really compete with NVIDIAs current GPU accelerated compute lines. However again there was always that distinction (re bitcoin?) that AMD cards have better integer arithmetic and NVIDIA better float arithmetic.

Disclaimer: I use CUDA in my research, never tried OpenCL.

[1] http://arxiv.org/abs/1005.2581

[2] http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=604719...

[3] http://arxiv.org/abs/1311.0378

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#33

Post by sp332 »

DeepYogurt wrote: post #19
sp332 wrote: post #4

Wow, I didn't realize they were shipping HBM2 already. 720GB/s - with only 16GB of RAM, you can read it all in 22 milliseconds!

They're not. All that was mentioned in the talk was that this chip is coming soon.

There's a big green "Order Now" button about 1/3 of the way down the page.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#34

Post by Robadob »

jra101 wrote: post #11

More detail on the GPUs in the system: https://devblogs.nvidia.com/parallelforall/inside-pascal/

Have they published a copy of the video of the autonomous car trained with unsupervised learning from the keynote anywhere?

I'd love to show it to my father.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#35

Post by olympus »

nightski wrote: post #27
phelm wrote: post #18

I am looking forward to OpenCL catching up with CUDA in maturity and adoption, so that NVidia's monopoly in Silicon for deep learning will come to an end.

What hardware could OpenCL even run on that would come remotely close to what this system has to offer?

OpenCL runs on Nvidia GPUs, so you could do an apples to apples comparison on this system.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#36

Post by make3 »

bgalbraith wrote: post #31
RussianCow wrote: post #30

Earlier quoted context omitted.

You often don't have a choice because a large amount of GPGPU software is written using CUDA, which is Nvidia-specific.

NVIDIA does not have a monopoly in the traditional sense. But yes, the have a de facto one because there is no viable competition. It's like saying MATLAB has a monopoly in academic research because so much of the code is written in it. That is slowly changing and moving over to Python now, which is great. Maybe OpenCL will get there someday, but I don't see it happening any time soon.

this is wrong. No mainstream deep learning library uses openCL, and the non-mainstream ones that do are much much slower. I remember reading up to 10x slower, but I can't seem to find the reference right now.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#37

Post by make3 »

bgalbraith wrote: post #31
RussianCow wrote: post #30

Earlier quoted context omitted.

You often don't have a choice because a large amount of GPGPU software is written using CUDA, which is Nvidia-specific.

NVIDIA does not have a monopoly in the traditional sense. But yes, the have a de facto one because there is no viable competition. It's like saying MATLAB has a monopoly in academic research because so much of the code is written in it. That is slowly changing and moving over to Python now, which is great. Maybe OpenCL will get there someday, but I don't see it happening any time soon.

this is wrong. No deep mainstream deep learning library uses opencl, and the non mainstream ones are much much slower. I remember reading up to 10x slower, but I can't seem to find the reverence right now

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#38

Post by nl »

phelm wrote: post #18

I am looking forward to OpenCL catching up with CUDA in maturity and adoption, so that NVidia's monopoly in Silicon for deep learning will come to an end.

The problem is that no one[1] uses OpenCL because the performance isn't there. There is little sign of that changing, too.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#39

Post by olympus »

badminton1 wrote: post #21

Costs $129,000 and needs 3.2 kilowatts to run.

To me, $129k isn't surprising since it is only going to be bought by researchers with big budgets. Small-timers will still build 3x GTX980 systems for under $5k.

3.2 KILOwatts sounded insane to me, but I suppose you'll have your own server rack to put it in if you can afford to buy one of these.

Re: The Nvidia DGX-1 Deep Learning Supercomputer in a Box

#40

Post by DeepYogurt »

Robadob wrote: post #32
DeepYogurt wrote: post #20

Earlier quoted context omitted.

Me too. I really want to see some benchmarks between cuda code and opencl code generated from cuda with AMDs compiler. Actually if anyone has a geforce/tesla get on this!

I haven't seen any recent benchmarks, but ones from 2011 all seemed to show CUDA and OpenCL on open footing in terms of performance when optimised properly.[1][2] CUDA simply had better library support, and a more well defined and uniform architecture to target. Whereas OpenCL is likely to require more programming to fill in the gaps for library support, and different optimisations depending on the architecture you w…

Would you mind trying the AMD compiler? http://gpuopen.com/compute-product/hip-convert-cuda-to-porta... I'd be interested in seeing a benchmark between some original cuda code and the opencl output of this compiler on the same gpu.
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