I spent almost $2400 on my box. Finished it just a few weeks ago. I used parts of this article for inspiration. I only have 2 x NVIDIA GTX TITAN-X 12GB (bought used), not 3. I also used a 1600w power supply.
How does the Titan compare to the new 1080s for machine learning?
Slower but more memory (8GB vs. 12GB). Depending on the problem it could definitely matter.
There is also a new pascal based titan.
for my needs these cards are working just fine. I could post a picture of the rig if anyone wants to see it.
Convnet benchmarks say that a 1080 is only like 5% faster. 12GB of VRAM seemed more important. I just spent yesterday evening sticking a cooling rig onto a Titan X I bought on eBay. Great value atm if you're willing to get your hands dirty. Will admit that it was a struggle though.
Those GPUs are 1200 USD apiece, the rest seems like it would be about another 1200, so I'd say 4 to 5 grand realistically. The nice thing is that since the majority of the cost is focused on the GPUs, you can build the rest of the box and add GPUs later as needed.
That's pretty much right on. I just built a box with one Titan X and the total cost was about $2400.
Recently I built a similar machine with a single GTX 1080 for $2500 in Norway.