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If 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. Sho

If 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 ago
I'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 ago
Well 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 ago
  Nvidia recommends 750W for the power supply.
  - secabeen 6y ago
    That 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 ago
    It'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 ago
If 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 ago
If 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 ago
  Agreed. 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 ago
    I want a gaming computer than won't limit my future ML learning. Are there any suggestions for that use case?
    - cauthon 6y ago
      Buy whatever makes you feel happy. I agree with gambiting that anything you choose won’t limit you
    - gambiting 6y ago
      There'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 ago
        Some 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 ago
Go 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 ago
  Woah, 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 ago
3080 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.

gbrown 6y ago

I'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 ago

Well 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 ago
Nvidia recommends 750W for the power supply.
- secabeen 6y ago
  That 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 ago
  It'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 ago

If 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 ago

If 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 ago
Agreed. 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 ago
  I want a gaming computer than won't limit my future ML learning. Are there any suggestions for that use case?
  - cauthon 6y ago
    Buy whatever makes you feel happy. I agree with gambiting that anything you choose won’t limit you
  - gambiting 6y ago
    There'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 ago
      Some 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 ago

Go 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 ago
Woah, 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 ago

3080 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.