Which GPU(s) to Get for Deep Learning
Disclaimer: I work on Google Cloud.I saw a lot of "should we use Cloud, no its crazy a GPU only costs $X". The key is that if you believe GPUs are going to get updated every year, and/or the best thing for ML may change (see TPU and plenty of startups with custom hardware) then suddenly buying hardware for 24? 36? months isn't as obvious.We (and AWS and Microsoft) have K80s because Maxwell wasn't a sufficiently friendly all around part. We're all going to offer Pascal P100s and in the future V100s. The challenge for buying your own is that P100s are available now-ish and V100s may be available in less than 12 months.Buying a P100 or similar part today doesn't mean it won't still be working in a year, but it will suddenly mean you've bought a part that now has much worse !/$ in just N months. If you have an accounting team that is spreading your $Xk over those 36 months, the reality is that you have two options: tell everyone they have to make use the old parts ("we're not buying new GPUs until it's been 36 months!") or realize you're going to get a lot less use out of them.To be clear, the progress in this space is really impressive. And the same problem above applies to us (the cloud providers). Despite my obvious bias, if I were fired today, I'd be renting to do deep learning just based on the roadmap alone (not to mention the ability to suddenly spin up and down).Again, Disclosure: I work on Google Cloud and want to sell you things that train ML models :).