Better GPU Cluster Scheduling with Runhouse

The simple act of “send my code to my cluster and run it” is surprisingly challenging for most AI teams. Numerous AI deployment systems have been built around model checkpoints or containerized pipelines, but if you just have some Python training functions to run you’re out of luck. Doing this collaboratively on a shared fleet of compute is even harder, especially if boxes in the pool are coming up and down all the time.

“Obviously, the ideal case here is …

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