As a ML/Dev Ops engineer, everyday increasingly I am seeing a large number power hungry workloads, different models being trained at the same time. That coupled the current issues of climate change: it got me thinking about the impact of these types of workloads on the environment.
For example, I have seen CV models that have to be trained slowly for 2+ weeks on multiple GPUs and rinse and repeat during a full year.
I was wondering if anyone else feels like the tradeoff of model accuracy/performance against impact on the environment is not being talked about too much.
I'd love to validate the value of knowing and offsetting one's cloud CO2 footprint.
Thanks for your time!