Setting up up a deep learning box

After doing a number of courses on machine learning I now have some overview of what is available and how it all works. So now it is getting time to start doing some work from start to finish myself. To do some of the more interesting things you definitely need access to a system with a good GPU and the systems I have at home are not really suitable for this:

  • My work laptop has an Nvidia GT Quadro 1000M which has compute capability 2.1
  • My private laptop has a GPU (Nvidia GT 330M) which has compute capability 1.2
  • My server which does not have a GPU and so has compute capability 0

On the other hand popular frameworks like Tensorflow require, as of this writing, compute capability 3.0. This effectively rules out the use of my private and work laptops.

As alternatives, I considered starting of in the cloud by using Google or Amazon GPU offerings. But then the workflow there is also always to first setup some work at home and then do the same in the cloud. Also, costs can add up quite quickly if you go that way. Then another alternative is to get a new laptop or a new PC with a fast GPU. That seems nice since it opens up some more opportunities for gaming as well, but then I am not really a gamer, and it also feels like a bit of a shame to get another laptop/PC when my current one is still working fine (A Sony Vaio F11 laptop with 1.6GHz CPU). My current laptop is running linux most of the time and really still performs quite well.

Then I started looking at another possibility which is to add a GPU to my server. In fact, this turns out to be possible since my server has a free PCIe 2.0 x16 slot. Looking on the internet it seems that PCIe 3.0 cards should work without problems in PCI 2.0 so that makes it possible. Also, there is a way to setup a VM on KVM so that GPU accelerated computing can be used inside a VM, see for instance server world. This is preferred over running natively. The idea will be to do a lot of (long running) experiments locally and if I really want to do something big ‘rent’ some capacity in the cloud.

To do all this, I first had to upgrade my server which is now running Centos 6 on the virtual host to Centos 7. Well “upgrade” is a big word. It involved installing Centos 7 side by side to Centos 6 and getting everything to work again. Now that part is done. The next step is to get a nice graphics card (e.g. Nvidia GTX 1080 or 1070) and set that up in the server.  This will be interesting.

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