I've considered setting up my own GPU server to reduce costs, but if you've got P100s for $200/month that means you're paying off the hardware in 4 years? I can

I've considered setting up my own GPU server to reduce costs, but if you've got P100s for $200/month that means you're paying off the hardware in 4 years? I can't compete with that. AWS was much easier to justify, since they're more expensive so the payoff is shorter. I was waiting on Google cloud's pricing to make any decision there: https://cloud.google.com/gpu/ https://cloud.google.com/gpu/ The only thing that concerns me is that your GPU+ instances only have a single P100, while someone like Google promises to let you attach up to 8 to a single machine. So if I wanted a single powerful machine for experimental work, the cloud providers are more expensive. But I'd have the same problem with buying my own hardware, because those cards are expensive. If you have only a single GPU, have you done any performance testing comparing consumer GPUs like the GTX 1080 with the commercial GPUs? I believe two advantages of the commercial ones are 1. Better interlinks between multiple GPUs and 2. Better floating point performance at the precision used in deep learning. Advantage #1 seems like it wouldn't matter with only a single GPU. I think AWS only has K80s, so that's in your favor. What motherboards/RAM/CPU/etc. are you using? If my estimate is right and you are pricing for a 4-year payoff just for capex, listing all of the hardware would make it an easy sell.