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I have two Mac Studios. When I need "more GPU horsepower", I spin up a GPU VM for $0.40-$0.80/hour (depending on my needs) and work away. Then I shut it off. I
by erichocean 3y ago
I have two Mac Studios. When I need "more GPU horsepower", I spin up a GPU VM for $0.40-$0.80/hour (depending on my needs) and work away. Then I shut it off.
I can't be the only one doing ML development this way.
- ClassyJacket 3y agoSure. But there are alot more use cases for GPUs than machine learning, many of which are latency sensitive and must be done locally.
- sarathyweb 3y agoWould you mind sharing what cloud provider you use?
- erichocean 3y agohttps://www.runpod.io/ https://www.runpod.io/ I do have a Windows machine with an nVidia GPU (RTX 2070 Super), but I don't use it anymore (bought it years ago). ML on the cloud is way more convenient because you can trivially adjust your cost based on what you're doing: Training? spin up something big/expensive. Inference? cheaper (less VRAM) is usually fine. I also like that I can run multiple instances simultaneously, something that would be prohibitively expensive if I had to have multiple machines sitting around waiting for me to use them.