this post was submitted on 19 Jul 2024
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[–] [email protected] 8 points 3 months ago (6 children)

Why use commercial graphics accelerators to run a highly limited "AI"-unique work set? There are specific cards made to accelerate machine learning things that are highly potent with far less power draw than 3090's.

[–] [email protected] 30 points 3 months ago (1 children)

Well yeah, but 10x the price....

[–] [email protected] 1 points 3 months ago* (last edited 3 months ago) (2 children)

Not if it's for inference only. What do you think the "AI accelerators" they're putting in phones now are? Do you think they'd be as expensive or power hungry as an entire 3090 for performance if they were putting them in small devices?

[–] [email protected] 8 points 3 months ago (1 children)

Ok,

Show me a PCE-E board that can do inference calculations as fast as a 3090 but is less expensive than a 3090.

[–] [email protected] 5 points 3 months ago

I'd be interested (and surprised) too

[–] [email protected] 1 points 3 months ago* (last edited 3 months ago) (1 children)

Yeah show me a phone with 48GB RAM. It’s a big factor to consider. Actually, some people are recommending a Mac Studio cause you can get it with 128GB RAM and more and it’s shared with the AI/GPU accelerator. Very energy efficient, but sucks as soon as you want to do literally anything other than inference

[–] [email protected] 1 points 3 months ago (1 children)

I wouldn’t say it particularly sucks. It could be used as a powerhouse hosting server. Docker makes it very easy to do no matter the os now a days. Really though I’d say its competition is more along the lines of ampere systems in terms of power to performance. It even beats amperes 128 core arm cpu at a power to performance ratio which is extremely impressive in the server/enterprise world. Not to say you’re gonna see them in data centers because price to performance is a thing as well. I just feel like it fits right into the niche it was designed for.

[–] [email protected] 1 points 3 months ago

How could you solve the problem of storage expansion? I assume there exists some kind of thunderbolt jbod thing or similar

[–] [email protected] 18 points 3 months ago

Because those specific cards are fuckloads more expensive.

[–] [email protected] 6 points 3 months ago

What are you recommending, I'd be interested in something that's similar in price to 3090.

[–] [email protected] 5 points 3 months ago (1 children)

It's for inference, not training.

[–] [email protected] 2 points 3 months ago (1 children)

Even better, because those are cheap as hell compared to 3090s.

[–] [email protected] 1 points 3 months ago

But can they run Crysis ?

[–] [email protected] 4 points 3 months ago* (last edited 3 months ago)

Would you link one? Because the only things I know of are the small coral accelerators that aren't really comparable, and specialised data centre stuff you need to request quotes for to even get a price, from companies that probably aren't much interested in selling one direct to customer.

[–] [email protected] 3 points 3 months ago

Huh?

Stuff like llama.cpp really wants a GPU, a 3090 is a great place to start.