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Seems like a good speedup relative to the Titan, especially for the money. I’d be interested to see the performance relative to the 3080 though. There are obvio
by valine 6y ago
Seems like a good speedup relative to the Titan, especially for the money. I’d be interested to see the performance relative to the 3080 though. There are obviously vram limitations with the 3080 but it would still be interesting to see the difference in raw compute performance.
In games the 3090 only gives a 15% performance bump relative to the 3080. If that pattern holds for machine learning tasks there is probably a scenario where it makes sense to buy two 3080s rather than one 3090.
If you are vram constrained then obviously the 3090 the way to go.
- hhhhhuu 6y agoA 3080 with 20gb is planned already
- YetAnotherNick 6y agoVery likely not with the same price as 3080. I am guessing it won't be much cheaper than 3090 as vram is expensive.
- wombatmobile 6y agoIf this isn't OT... 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?
- gbrown 6y agoI'd honestly start with cloud options if learning is the only reason you're building the computer. You don't want to dump a bunch of money into depreciating GPUs if you're not going to end up using them. 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.
- valine 6y agoWell to start off I’m not advising buying two 3080s. I haven’t seen the benchmarks, and on top of that the 3080 doesn’t support SLI so if you do buy two of them you will need to be using software which can utilize two independent GPUs. 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.
- posix_compliant 6y agoNvidia recommends 750W for the power supply.
- secabeen 6y agoThat is true, but it all depends on how much the rest of your system uses. If you just have a mid-tier CPU and SSD, you may find that the rest of your system only uses 200W, and you can fit a 3080 on a 600W power supply. There are multiple reports of high-quality 600W PSUs working, so YMMV.
- leeter 6y agoIt's worth noting that this recommendation has nothing to do with delivered power.... a 500W can handle most systems on delivered power. 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.
- paol 6y agoIf you're just beginning a 3080 is overkill, never mind two. Get a used 1080ti (or even 2080ti if not overpriced), it'll be cheaper and even has a bit more RAM.
- gambiting 6y agoIf you're "learning about ML" there is no point in buying anything. Just get the cloud compute instead, and for home use and testing literally anything will do. I have friends who work with ML professionally and even they say it's just hard to justify running any computations at home once you factor in the electricity and hardware cost - GCP compute just beats the cost, easily.
- claudeganon 6y agoAgreed. If you’re just learning or building hobby stuff, you can use Colab, Paperspace, or any number of other services for free or very cheaply.
- emteycz 6y agoI want a gaming computer than won't limit my future ML learning. Are there any suggestions for that use case?
- cauthon 6y agoBuy whatever makes you feel happy. I agree with gambiting that anything you choose won’t limit you
- gambiting 6y agoThere's no such thing as long as you buy an actual mid to high tier GPU. Even an ancient GTX1070 would be more than enough - and for sufficiently large datasets even an RTX3090 will take hours to process whatever you're crunching. 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".
- claudeganon 6y agoSome off-the-shelf gaming PCs are not very Linux friendly though, so they should watch out for that, especially the laptop varieties. Getting a lot of the ML stuff working locally in Windows is a nightmare.
- l33tman 6y agoGo for it! Get a motherboard with reinforced PCIe slots for both GPUs though, the cheaper mobos only have one armoured slot. Also, you really should use the 3080 Founders Edition I guess for a dual setup as they blow out part of their heat in the back. Otherwise you need good air control and as thin 3080 cards as you can find (so there's some space between them in the case). Still waiting for good thermal benchmarks on this kind of setup... 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).
- duhi88 6y agoWoah, there. They said they were just learning. No need to purchase special hardware until you're trying to run state of the art models. 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.
- bitL 6y ago3080 has no NVLink, so 2x 3080 would communicate only via PCIe and it's unlikely they would form a single 20-40GB virtual RAM like what 2x2080Ti with NVLink did under Linux.
- kevingadd 6y agoI think for high throughput scenarios the 3090 probably has more headroom due to its higher TDP and better (larger) cooling solution, which might really matter here if you're driving the tensor cores at max the whole time.
- wnevets 6y agoMost video games probably aren't going to make the most of all of the extra CUDA cores on the 3090. I'm assuming that helps alot with machine learning, can someone who knows for sure confirm?
- Jhsto 6y agoMost parallel processing scales linearly with core count. But the 3090 is more interesting for machine learning because of its RAM, which it has 24GB against 3080's 10GB. With machine learning, you spent most of the time copying memory between the CPU and GPU, so being able to fit more data to it reduces computation latency.
- option 6y ago“ With machine learning, you spent most of the time copying memory between the CPU and GPU” - this is a sign that you are most likely doing it wrong. Yes, some operations are inherently bandwidth bound, but most important ones such as larger matrix multiplies (transformers) and convolutions are compute bound.
- Jhsto 6y agoSure, but compared to the 3080 I'd say that the main deal is the bigger RAM for copying reason than the increased core count.
- option 6y agoTIP: if you need to emulate a bigger batch with less RAM available - use gradient accumulation trick. Super easy to implement in Pytorch and it is already implemented as a single flag (accumulate_grad_batches) in Pytorch Lightning.
- p1esk 6y agoYour gradient accumulation trick involves multiple cpu to gpu transfers, which is precisely what the parent is trying to avoid with fitting a larger batch in gpu memory.
- p1esk 6y agoThere will be 20GB version of 3080 soon.
- oivey 6y agoThere’s been rumors of this, but it’s not confirmed. A big percentage of the cost of the 3090 (and 3080) is the GDDR6X. A 3080 with 20GB of GDDR6X will still be really expensive, so it’s unclear to me that they will actually release something like that. Potentially they could put that much RAM on a card and then use slower GDDR6, but that’s kind of an odd part in Nvidia’s product offerings because then the 3080 with more RAM would be slower in a lot of situations.
- bitL 6y agoThere are rumors about 48GB 3090 with older GDDR6 chips so having the same config for 3080 wouldn't be unexpected, at least until Micron could produce 2GB GDDR6X chips.
- duhi88 6y agowhat would be the benefit there? 20GB can't be that much cheaper than 24GB, right?
- nullifidian 6y ago2x 20gb 3080 for $1000 each is more cost effective than 2x 3090 for $1500 each, if your model fits into 20 gb.
- p1esk 6y agoMy guess is it’s going to be $999
- Sohcahtoa82 6y agoIt will be for the gamers who think that 10 GB isn't enough VRAM, and as a way for nVidia to have an answer for rumors that AMD's next GPU will have 16 GB.