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Comment by adam12 | Hacker News Reader

I started watching the videos in Part 1 and was disappointed to find out that I was going to have to create an AWS account. I really don't want to deal with accidentally racking up a large bill on AWS.

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For GPU instance, I would suggest https://www.hetzner.com/dedicated-rootserver/ex51-ssd-gpu?co....

It is only 99 euro/month.

The 99 euro setup fee is a dealbreaker if you'd want to use it just for some courses.

If your data is in S3 then data transfer fees can suck but def cheaper than $ 0.90 per hour if you're regularly leaving models to train overnight :)

If you have the hardware, you can do without an AWS account (you might need to be an "expert" to interpret the instructions to run on your own hardware instead of AWS). I used my gaming rig with a 1080 GTX Ti card.

Why? Why can't I just do it with my crappy hardware, and it take longer?

You can. Tensorflow has a CPU implementation. But, it's not a little longer, it's incredibly longer.

Like 5h on an upper-class GPU vs 50 days on the fastest CPU.

You can do it on a poorer graphics card, but that's only if it has enough GPU RAM, and only if its supports a relatively recent compute version.

You _can_ run it on a CPU, and that can work fine for very simple models (like the Tensorflow demos with MNIST) but anything much larger and things really start to take forever. Like, you'll be waiting for months.

I'm giving serious thought to buying or building a rig for these courses. What's "enough GPU RAM"?

A GTX 1060 with 6 GB of RAM is a good intro card. You can find them for < $350.

The AWS P2 instances recommended for the course ($0.90/hour) have half a K80, which has access to 12 GB of VRAM. The list price for that card is $5000.

The GTX 1080 Ti has almost as much VRAM as half a K80, 11GB, and can be found for around $700.

I'm finding Acer rigs with GTX 1070, 8GB RAM. I'll probably get one of those, thanks.

I've been trying to get it up and running using the latest versions of the libs. I have theanos finding my GPU now and running basic cuda code but cannot get the cuDNN libraries to be recognized even after installing a few versions of the Nvidia site. Ugh. Giving up for now.

Can this be done in Windows or is it better to install a Linux?

Better to install linux. Not all tools support Windows, and for those that do it is still a second class citizen and kind of annoying, e.g. look at installing CUDA/cuDNN on Windows vs Linux.

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