And you are here why?

Many years ago, when I was wood-working, one of my projects was an oak side-table. I spent months on it — hour after hour, night after night, bringing it to the correct finish. There was a kind of zen-like quality to the work, an introspective meditative state that I would be in, that would help ease away the daily burdens and leave me curiously refreshed. Oh, I’m glad I built that table — I still have it — but  the entirety of that experience was about building the table . The journey truly was the reward. And then I think about AWS. The entirety of my DevOps-y life with AWS has consisted of mastering an increasing number of bells and whistles associated with VPCs, ELBs, ECR, ECS, and whatnot. And that’s before you even get to the  Things That Are Not Three Letter Acronyms  like Aurora, Fargate, Snowflake, Aurora, and such-like. And, somewhere along the way, I realized that I had successfully confused the mastering of a complex process with the joy of delivering th...

Shiv Manne ran a whole bunch of tests against GPU instances from platform providers like AWS, GCE, Paperspace, Softlayer, etc., and   the results were…interesting . Not surprising mind you, just   interesting . The lede — high end GPUs get very expensive very fast. Yes, they train wicked fast, but the ROI, frankly, sux. In fact, the best deal seems to be to run lower-end single-GPU instances (more info on this   here ). Why single-GPU? Largely because,   right now , support for multi-GPU either doesn’t work, or when it does, seems to be surprisingly inefficient. Go figure! Paperspace   seems to be on the game here, both for costs, and for performance. In fact, if you’re just testing stuff, they’re pretty much your best bet, as seems to be   validated elsewhere   too. And, of course, the obvious remains — AWS is expensive, and GCE is not   . The results are below, but go take a look at   the whole post . Note : There is also  ...