by DTE on 12/15/16, 4:00 PM with 5 comments
by MichaelBurge on 12/15/16, 11:13 PM
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.
by evervevdww221 on 12/15/16, 4:22 PM
I knew about paperspace the day it came out of yc.
at the time, we were working on a competing product.
but we eventually gave up on the idea. because business wise, amazon is too expensive for this kind of service, making the price not economical for end users.
I don't know too much about the technical details of paperspace, but I believe we did better at resource sharing and cost management. but it was still a tough sell, even for enterprise users.
by rco8786 on 12/15/16, 7:13 PM