Helpful FYI: If you're interested in learning about Machine Learning (so you can use TensorFlow and Rescale, etc), I've found this to be an incredible resource: https://www.coursera.org/learn/machine-learning/
The GPU chip is Nvidia's GK104, which was released in 2012. Amazon's GPUs are similarly old. You'll train models twice as fast with a Titan X installed in your local machine, without having to deal with distributing the training.
When will we see the first cloud machine learning provider with up-to-date GPUs?
https://thevirtualhorizon.com/2016/04/09/whats-new-in-nvidia...
(tl;dr - you have to pay more to wrap the GPU access in a VM. Like, $550/more, plus a year of software support, according to that article. IANAL and haven't read any of the license details, so I don't know if there are more gotchas.)
How much RAM do GK104 chips have? Wikipedia seems to imply it's about 3GB, but that's even smaller than EC2 GPU instances' 4GB. Many modern models really need the maximum 12GB to train.
Is it? Their website (http://www.rescale.com/pricing/) says they have Kepler K520 and Tesla K40. No affiliation with them at all, and haven't logged in yet, but I've been looking for something like this too, so I was hopeful until I saw your comment...
It is not the only hardware on Rescale. K520 and K40 are definitely available - after you create a free account and login there is a very transparent price list of the hardware available to you.
Rescale pricing: "Price as low as $0.04/core/hour" - if I am reading this correctly, training on a K40 Nvidia GPU (with nearly 3000 cores) amounts to about $100/hour.
Bit pricey, no? Or am I not reading this right?
How do you plan on making your service's pricing competitive? Amazon's current spot market instances are ~30 cents per hour, which is twenty times cheaper.
I cannot comment on future per node pricing at the moment, but we are currently working on new offerings that should improve both performance (CUDA cores/node) and $/CUDA core metrics.
