Wonder why AMD/Intel/Nvidia haven’t invented some sort of device that allows the processor and graphics to share memory like Apple has done.
This is what the attempted ARM acquisition by Nvidia was about - with the ARM talent, IP, etc they’d be able to integrate more than just memory (GPU, CPU, connectivity via Mellanox, etc).
Regulators shut it down (for good reason) but I can’t help but think we would have seen some really interesting and revolutionary platforms come from it.
However, even without this feature, you can implement this sort of thing manually in most cases and you’re already being careful on a GPU to respect the cache (only working with one contiguous set of data of memory at a time).
Really, we just need some good systems devs working on running these huge models.
Implementing the software support and getting operating systems to play along and fragmentation between GPU vendors, as always with GPUs on x86, have been the problems. From all accounts it's been working reasonably well on the consoles though.
Also chicken-and-egg: low GPU compute usage uptake outside of games has meant it's not improved lately.
Integrated GPUs also access system memory via the same bus as the CPU.
It’s not really a new technique. Apple just shipped a highly integrated unit with large memory bandwidth.
How much would a PC that can do that currently cost me and can I have it by tomorrow?
It's a great option if you have the hardware and want the speed. It's table stakes when other vendors like Nvidia, Intel, Qualcomm and Microsoft have acceleration though. Raw-compute-for-the-buck has always been a blowout with Apple Silicon GPUs, and it's not any prettier now that 4nm 40XX series cards are available. Hell, an Intel A770 with 16gb of VRAM is still cheaper than adding 16gb of RAM to a Mac Mini.
It's good stuff, but pitched a bit hard with all the marketing. From where I'm standing, it looks like Apple is playing catch-up with their GPUs and acceleration tech.
tentatively removes hat of jaded realism
You could go cheaper with a 3090 which has the same vram and it's just slower.
I think the best combo is a serious Nvidia pc for AI + a cheap MacBook air for portability.
That said, if you're fine with slower speeds then two P40s could get the job done for $150 each. (Not sure how much slower this would go though.)
At the moment, seems like Apple has an edge here. On PC for single GPU you need an NVIDIA A40, which used prices for is about $2500, and not at retail stores.
If you don't mind having two GPUs then two $800 3090 GPUs works, but that's a workstation build you'll have to order from Puget or something. That's probably faster than Apple.
My gut instinct is that there's some low hanging fruit here and in the next couple weeks 64B Llama will run comparably or faster on any PC with a single 4090/3090 and 64 or 128 GB of system memory. But probably not any PC laptops that aren't 17 inch beasts, Apple will keep that advantage.
You can get a 128GB UMA mac for less than a single 48GB a100, let alone a single 96GB a100.
I think Apple got incredibly lucky here, but I don’t see how the PC world catches them any time soon. We’ve all known that UMA is theoretically better for ages, but Apple’s timing couldn’t be better. And scale economies mean they can sell the same chip to people who need 100GB of system RAM and people who need 100GB of VRAM.
If they can get their GPU / neural performance up and sort out their terrible relationship with academic research, they could snipe ML away from nvidia. It seems very unlikely, but it’s kind of stunning that it’s even in the realm of possibility.
If Nvidia announced tomorrow that they were cancelling every datacenter deal they had, open-sourcing CUDA and publishing their entire patent library to the creative commons, I would still not believe you.
This is a fun project for people with Apple Silicon machines who want to participate in the AI happenings, but I don't think you can warp it into a call for Nvidia's head. Let's wait until Apple pulls the curtains on their rackmount Mac Pros, so we can compare it with Nvidia's ARM server offerings: https://www.nvidia.com/en-us/data-center/grace-cpu/
My point was that the PC architecture of separate system and GPU memory is hitting a wall that means inefficiency and higher prices.
I have little doubt that Nvidia’s attempted acquisition of ARM was in part because nvidia recognized this. I expect they are exploring other UMA approaches. But it will be hard in the fragmented, not-vertically-integrated model.
Apple’s advantage here is one platform that can scale: it is hard to imagine Grace and similar running Windows on developer’s desktops. Maybe!
But my point was that, shockingly, Apple has a chance here. A small chance, as I said, but I don’t think anyone (including Apple) saw just how soon UMA was going to become a competitive advantage.
If you think it's hard to imagine Nvidia hardware running on a developer desktop, wait until you hear about what happened when Macs tried entering the server market.
2. CPUs and GPUs typically disagree on whether they want high bandwidth or low latency, apple managed to keep both happy but it's very hard to do on a PC where the RAM,CPU, and GPU are quite far apart and also nowhere near as homogenous as Apple have them.
And also - vram is a moat that keeps the cost of "professional" cards absurdly high without making them actually faster than consumer cards.