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Nvidia's Project Digits is a 'personal AI supercomputer'

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Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#381

Post by JoshTko »

bloomingkales wrote: post #194
Karupan wrote: post #6

I feel this is bigger than the 5x series GPUs. Given the craze around AI/LLMs, this can also potentially eat into Apple’s slice of the enthusiast AI dev segment once the M4 Max/Ultra Mac minis are released. I sure wished I held some Nvidia stocks, they seem to be doing everything right in the last few years!

Jensen did say in recent interview, paraphrasing, “they are trying to kill my company”. Those Macs with unified memory is a threat he is immediately addressing. Jensen is a wartime ceo from the looks of it, he’s not joking. No wonder AMD is staying out of the high end space, since NVIDIA is going head on with Apple (and AMD is not in the business of competing with Apple).

Which interview was this?

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#382

Post by diggan »

adolph wrote: post #294
diggan wrote: post #267

Earlier quoted context omitted.

Damn, you're right. I didn't even consider looking at the monitor itself as "They can't be so lazy they don't even use a real screenshot" while faking the rest kind of makes sense, otherwise you need a studio setup. Never underestimate how lazy companies with a ~$3 trillion market cap can be.

Lazy? This is Nvidia eating their own dogfood. They put in lots of work to get to the point where someone can call it "lazy."

> Lazy? This is Nvidia eating their own dogfood

Absolutely, I'm all for dogfooding! But when you do, make sure you get and use good results, not something that looks like it was generated by someone who just learned about Stable Diffusion :)

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#383

Post by sangnoir »

stabbles wrote: post #305
lolinder wrote: post #301

Earlier quoted context omitted.

This is a very important point. In general, Nvidia's relationship with Linux has been... complicated. On the one hand, at least they offer drivers for it. On the other, I have found few more reliable ways to irreparably break a Linux installation than trying to install or upgrade those drivers. They don't seem to prioritize it as a first class citizen, more just tolerate it the bare minimum required to claim it works…

Now that the majority of their revenue is from data centers instead of Windows gaming PCs, you'd think their relationship with Linux should improve or already has.

Nvidia segments its big iron AI hardware from the consumer/prosumer segment. They do this by forbidding the use of GeForce drivers in datacenters[1]. All that to say, it is possible for the H100 to to have excellent Linux support, while support for the 4090 is awful.

1. https://www.datacenterdynamics.com/en/news/nvidia-updates-ge...

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#384

Post by dnissley »

dagmx wrote: post #20
VikingCoder wrote: post #15

Earlier quoted context omitted.

If I were NVidia, I would be throwing everything I could at making entertainment experiences that need one of these to run... I mean, this is awfully close to being "Her" in a box, right?

I feel like a lot of people miss that Her was a dystopian future, not an ideal to hit. Also, it’s $3000. For that you could buy subscriptions to OpenAI etc and have the dystopian partner everywhere you go.

Please name the dystopian elements of Her.

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#385

Post by sliken »

pella wrote: post #282
moffkalast wrote: post #178

Earlier quoted context omitted.

I've seen some claims that it can do 512 GB/s on Reddit (not sure where they got that from), which would imply a ~300 bit bus with LPDDR5X depending on the frequency.

probably: "According to the Grace Blackwell's datasheet- Up to 480 gigabytes (GB) of LPDDR5X memory with up to 512GB/s of memory bandwidth. It also says it comes in a 120 gb config that does have the full fat 512 GB/s." via https://www.reddit.com/r/LocalLLaMA/comments/1hvj1f4/comment... "up to 512GB/s of memory bandwidth per Grace CPU" https://resources.nvidia.com/en-us-data-center-overview/hpc-...

Keep in mind the "full" grace is a completely different beast with Neoverse cores. This new GB10 uses different cores and might well have a different memory interface. I believe the "120 GB" config includes ECC overhead (which is inline on Nvidia GPUs) and Neoverse cores have various tweaks for larger configurations that are absent in the Cortex-x925.

I'd be happy to be wrong, but I don't see anything from Nvidia that implies a 512 bit wide memory interface on the Nvidia Project DIgits.

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#386

Post by dotancohen »

lolinder wrote: post #301
Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

This is a very important point. In general, Nvidia's relationship with Linux has been... complicated. On the one hand, at least they offer drivers for it. On the other, I have found few more reliable ways to irreparably break a Linux installation than trying to install or upgrade those drivers. They don't seem to prioritize it as a first class citizen, more just tolerate it the bare minimum required to claim it works…

  > Nvidia's relationship with Linux has been... complicated.
For those unfamiliar with Linus Torvalds' two-word opinion of Nvidia:

https://youtube.com/watch?v=OF_5EKNX0Eg

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#387

Post by DannyBee »

gnatman wrote: post #374

>> The IBM Roadrunner was the first supercomputer to reach one petaflop (1 quadrillion floating point operations per second, or FLOPS) on May 25, 2008. $100M, 2.35MW, 6000 ft^2 >>Designed for AI researchers, data scientists, and students, Project Digits packs Nvidia’s new GB10 Grace Blackwell Superchip, which delivers up to a petaflop of computing performance for prototyping, fine-tuning, and running AI models. $3000…

Digits is petaflops of FP4, roadrunner is petaflops of FP32. So at least a factor of 8 difference, but in practice much more. (IE I strongly doubt digits can do 1/8th petaflop of FP32)

Beyond that, the factors seem reasonable for 2 decades?

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#388

Post by shadowpho »

saidinesh5 wrote: post #358
Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

Is there any recent, powerful SBC with fully upstream kernel support? I can only think of raspberry pi...

Radha but that’s n100 aka x64

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#389

Post by sangnoir »

nickpsecurity wrote: post #373
Abishek_Muthian wrote: post #283

I'm looking at my Jetson Nano in the corner which is fulfilling its post-retirement role as a paper weight because Nvidia abandoned it in 4 years. Nvidia Jetson Nano, A SBC for "AI" debuted with already aging custom Ubuntu 18.04 and when 18.04 went EOL, Nvidia abandoned it completely without any further updates to its proprietary jet-pack or drivers and without them all of Machine Learning stack like CUDA, Pytorch et…

If its stack still works, you might be able to sell or donate it to a student experimenting. They can still learn quite a few things with it. Maybe even use it for something.

Using outdated tensorflow (v1 from 2018) or outdated PyTorch makes learning harder than it need to be, considering most resources online use much newer versions of the frameworks. If you're learning the fundamentals and working from first principle and creating the building blocks yourself, then it adds to the experience. However, most most people just want to build different types of nets, and it's hard to do when the code won't work for you.

Re: Nvidia's Project Digits is a 'personal AI supercomputer'

#390

Post by dotancohen »

tcdent wrote: post #367
mrybczyn wrote: post #355

Earlier quoted context omitted.

Eh? By all indications compute is now evolving SLOWER than ever. Moore's Law is dead, Dennard scaling is over, the latest fab nodes are evolutionary rather than revolutionary. This isn't the 80s when compute doubled every 9 months, mostly on clock scaling.

Fab node size is not the only factor in performance. Physical limits were reached, and we're pulling back from the extremely small stuff for the time being. That is the evolutionary part. Revolutionary developments are: multi-layer wafer bonding, chiplets (collections of interconnected wafers) and backside power delivery. We don't need the transistors to keep getting physically smaller, we need more of them, and at i…

All that comes with linear increases of heat, and exponential difficulty of heat dissipation (square-cube law).

There is still progress being made in hardware, but for most critical components it's looking far more logarithmic now as we're approaching the physical material limits.

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