As I have demonstrated, I've really not much of a clue when it comes to AI, but do users really need 12Gb GPU RAM, 100% of the time? Maybe it's possible to use one GPU for multiple users?
As I have demonstrated, I've really not much of a clue when it comes to AI, but do users really need 12Gb GPU RAM, 100% of the time? Maybe it's possible to use one GPU for multiple users?
60k users yesterday * 6GB each -> 360TB of data egress!
Normally, a scenario like this wouldn't involve bandwidth costs because GCP -> GCP same-region bandwidth is free, but Colab is technically not part of GCP, so the bandwidth charge is being assessed as egress to the public internet, which is pricy for that much data. Though it's probably still a lot cheaper than paying for the GPU-hours for that many users.
In other words, yes, this is an amazing amount of raw power - with a corresponding price tag.
EDIT: Almost, the VM runs on Colab, which only works with Google, and Google's charging for the upload to Colab? ...more like collaborator, amirite? dodges rotten eggs
The funny thing is the high egress fees Google charges for transferring data between two of its services (GCS -> Colab).