Could you kindly advise what kind of computer would make sense to purchase to begin learning about ML? I was assuming I'd get a 3080. Should I get a case that could potentially house 2 x 3080's? Does the case require any special cooling considerations, or just whatever will fit the cards? What CPU would you get?
And if you ARE actually running it that hard, you'd better budget for fairly frequent replacement cards.
And no, cards don't just keel over in a few months at 100%. Crypto miners ran that experiment. A typical card has years of 100% in it.
- Someone else is paying
- You expect to dabble
- You need burst capability
Buy if:
- Cost sensitive & capable
Are modern cards really so fragile you can expect them to die off under heavy use even if properly cooled and not overclocked?
Just buy a PC that you like for gaming(with an Nvidia gpu) and don't worry about ML yet - it's incredibly unlikely that you can pick something that would limit you in any way. Small datasets will run on anything, large datasets will take hours to process no matter what you run them on. It's not a "limit".
http://timdettmers.com/2018/12/16/deep-learning-hardware-gui...
make sure your motherboard and processor support whatever the newest version of PCIe is -- a major factor with deep learning is bandwidth moving data on/off the GPU.
AMD GPUs can theoretically be used for machine learning, but right now software support is lacking -- you will spent more time configuring and installing than learning. (AMD CPUs are fine though.)
it doesn't really matter that much though -- any gaming PC with a new-ish NVidia card can be used to do quite a bit of interesting ML.
Nvidia came to dominate the market at a time when AMD wasn't making particularly competitive GPUs, but that isn't really the case anymore. For anything not so expensive that nobody is really going to buy it anyway, the current and expected (in less than a month) AMD GPUs are competitive on performance.
The result is that a lot of large customers, who see value in not being locked into a single supplier, are going to be pushing for frameworks that work across multiple vendors. And then you could plausibly be wasting your time learning Nvidia-specific technology which is about to become disfavored. So you might want to wait and see.
Twice bitten... once shy? In any case, I'm going to let someone else be the guinea pig this time.
so the question is just -- when will it be very simple to install these packages for AMD GPUs, with enough mathematical operations implemented and optimized to let you do the things you want to do.
right now things sort of work, but it's definitely in a bleeding edge early adopter state. it's seemed like AMD is on the cusp of catching up for a couple years now, but it's taken longer than I expected.
True, but even once TF/PyTorch support AMD well it's highly possible that an unanticipated CUDA dependency will pop up in one's computational journey. NVidia subsidized CUDA seminars for a decade and now it's all over the place, both in the flagship frameworks and in the nooks and crannies.
GPUs are only really required in ML if you want to do deep neural network stuff. You can do plenty in CPU on reasonable data sets using any modern laptop.
If you’re just wanting to learn machine learning you don’t need anything particularly special. I think you would be happy with GTX 1070. There is also the cloud computing route where you basically rent the gpu from AWS. That will be initially more cost effective than buying your own hardware.
One thing to keep in mind if you do go with the 3080 is the power consumption. Ampere cards are going to be much more power hungry than previous generations, and you will need to budget about 320W just to the graphics card. The recommended power supply for the 3080 is 850W.
This has to do with transients, the 3000 series cards have some massive transients that can easily trip OCP protection on powersupplies not designed for that kind of transient. A 700W powersupply is able to handle those transients much better than a 500W PSU is.
Of course if money is an issue, you are well off with only a single 3080 :)
There is no point in buying the 20xx series anymore. The 30xx are twice as good for the same money (if you can get one).
You can get very far on any laptop before hardware becomes the main blocker. And before building an ML machine, there are cloud compute options available for far cheaper.