Making your own server


(Nikhil J) #529

After lurking on the thread for a lot of months and procrastinating on my build, I’ve finally decided to bite the bullet and finish the build.

Here’s my draft of a build:
https://pcpartpicker.com/user/seasponge/saved/h7B9WZ

I procured a AORUS 1080Ti on Massdrop a couple months ago, and it’s been sitting on my desk. I’ve just ordered a 8700k, just to future proof the build, as I would like to use the PC for gaming too occasionally.

I’m really vague about what to choose for a z370 MOBO, I feel like the MSI - Z370M GAMING PRO AC Micro ATX LGA1151 Motherboard ticks all the boxes for a deep learning build, but am not sure if I’m missing something.
My thought process on the pick was filtering for 64GB max ram, 2 x16 pcie slots, 4-5 stars on pcpartpicker and sorted by price ascending.

I’m currently looking at getting a 500 gb SSD, but am also glancing at NVMe drives. Might leave that upgrade for the future if the desire grows.

Please critique my build/offer suggestions, as to what I might be overlooking.


(Robert Salita) #531

A private server can be made public by using localhost.me (free) or ngrok (free and paid tiers). You can gain desktop access using VNC, Splashtop. You can file share using Dropbox, Google Cloud and others.


(Cynosure) #532

That sounds rather high end setup (for a DL beginner student) to me. If you are serious about DL and have the budget for it, go for it.


#533

I’m running a Windows 10 laptop (GeForce 1060, Core i7, 512GB SSD) and trying to set up a Windows 10 GPU server using this guide:

http://wiki.fast.ai/index.php/Local_install_(Windows_only:cpu)

I ran into a problem I can’t solve:
keras.json doesn’t seem to get created for some reason. I think I need to run import keras to get it to create the file.
However, running import keras gives me the following error:

“RuntimeError: To use MKL 2018 with Theano you MUST set “MKL_THREADING_LAYER=GNU” in your environement.” (sic)

I tried creating this system variable, but it made no difference.
Has anybody had any success getting a Windows 10 GPU server working? Or should I just give up and dual boot Ubuntu?


#534

Pekoto,

Two things to consider here,

First, it looks like you are trying to setup version1 of the course which uses Theano. Theano is dead. Version 2 of the course uses a different framework called Pytorch. Configuring Windows 10 for this is a bit easier and some steps can be found here. In short, you just download cuda 9.0.176? get cudnn v7, install latest anaconda and github desktop. I just set this up today on a laptop similar to yours and it appears to be working.

Second, you may find it easier in the end to go Ubuntu. I have a desktop that is dual booted with dual drives for Win10 and ubuntu. Once the OS is installed, the setup closely resembles the paperspace setup script.


#535

Got it, thanks for your tips. I’m going to try installing Ubuntu.


(Andrea de Luca) #536

I did. I got a working w10 box (i7, gtx1070) with keras/TF and fastai/pytorch in separate conda envs.

What did go awry with your attempts?

However: How to set up Windows 10 for fast.ai


(Omar Amin) #537

Thanks for the very informative thread, I’m building my own box now, can you please revise this part list and let me know if there’s anything wrong?

https://pcpartpicker.com/list/4qPV3b

I may add another GPU later, that’s why I’ve chosen the x99 motherboard that supports up to 2 gpus * 16x PCI lanes

I’m in short budget, I already have the titan gpu, I’m just creating the box around it, and I noticed the warning of the incompatibility for the cpu and the motherboard, but i think it’s not on this specific version of the CPU & motherboard


#538

i have the 6850 with an X99 msi motherboard, pcpartpicker gave me the same warning, but I did not have an issue.

I would recommend an NVME drive over the SSD you have.
I would also recommend a 1080ti over the Xp.

The HD recommendation is based on my setup. I think the nvme helps alot with file read/write operations. A 1080ti should be cheaper in theory than an Xp and may perform faster. Refer to this thread.


(Andrea de Luca) #539

I think you won’t have any issues, but check “supported CPUs” on MSI website. If you are short on budget, consider a corsair cx850, cheaper than the one you selected, but still a quality product.

If you want to run two 12Gb cards, you’ll need more memory. I recommend 64Gb, but as already recommended, nvme drives will help with swap operations in case you prefer to stick with 32Gb.

You may want to consider Xeon CPUs and ECC registered memory. For a slightly higher price, you get greater stability and not to worry about data corruption over long timespans, not to mention higher density per module, which will give you more room for future updrades.
Finally, Xeon CPUs consume way less power than their core equivalents, despite having the same official TDP.


(kanishkd4@gmail.com) #540

Hi,

To all the members who have configured their own servers,

I’m getting a deep learning desktop but am trying to be cheap and get out of buying a monitor to set it up since I’ll try to use ssh through my laptop for all the work

Does anyone have experience with this sort of a set up or would it just be easier to buy a cheap monitor to manage it? I won’t be assembing it myself since a pre-assembled is the cheapest thing I can find with current GPU prices. I have linux on my laptop and a spare old laptop with windows lying around I can try to use to configure the desktop

thanks!


(RobG) #541

Yes just install openssh-server and you can terminal in remotely.

You will probably need some monitor to set up the machine (and ssh) in the first place, unless you can manage to create a configured image with ssh on the box at the outset. So check out the card’s ports and any monitor you currently have, so you can get the right adapters.

Similar story for wifi, if your box will have it, you may need to connect via ethernet first to set up wifi.


(Cynosure) #542

Not sure what you mean. if the new machine has already Ubuntu/Linux setup so then you can connect via ssh and would not need a monitor for the DL box most of the time.

I have a similar system too with monitor which i use rarely. in the beginning i need it definitely to setup the stuff.


(kanishkd4@gmail.com) #543

It comes with a trial version of windows I’ll have to remove and install Ubuntu. I gave in and got a cheap monitor
Thanks


(Matthijs) #544

You can probably use your TV for this (if you have one), using the HDMI output on your GPU.


(pommier) #545

Did you need to buy a specific dell PSU?


(Christina Young) #546

No, I bought mine 875W unit from KDMPOWER on eBay: http://stores.ebay.com/KDMPOWER
Looks like they are on vacation or something – If you aren’t sure, send them a message went they reopen on 3/19 and ask about your specific machine. My 875W is still going strong! :slight_smile:


#547

An item of interest the latest in Deep Learning boxes in the UK. I guess you have similar where you are :slight_smile:

https://www.scan.co.uk/3xs/info/nvidia-dgx-1

The entry level box can be yours for around £86,000, $120150 no pennies or cents here.
Or you can hire by the week, month, or year in the cloud


(Jon Gold) #548

Considering selling my rig - I built it in Oct 2017, but since then I’ve been doing most of my experiments on work resources + there’s not too much point having a great setup gathering dust when someone else could be using it.

https://pcpartpicker.com/b/dtQZxr / $1900 / Bay Area only


#549

@taewoo

I have real estate to host, available power, and a fiber optic connection on the East Coast United States.

Cost of Electricity is relatively low

We are building our own deep learning rigs and we are mining. We currently have around 40 - 1080Ti GPUs among others. We charge around $95 per kW per month to our mining clients, and I am sure that we can work out something similar for any of your machines. OR we could build you a machine to spec.

Please DM me for more information if you would like to discuss further.