GPU Development Loop

Coiled can make remote GPUs feel like part of the normal Python loop. The trick is to keep experiments interactive while making artifacts portable.

Common loop

• Start a GPU notebook for exploration.
• Move stable training code into a script or function.
• Log parameters and metrics.
• Return CPU-compatible artifacts when calling from a local CPU machine.

Function sketch

import coiled

@coiled.function(vm_type="g5.xlarge", keepalive="20 minutes")
def train(params):
    model = fit_model(params)
    return model.to("cpu")

Handoff habit

Keep checkpoints, metrics, and model cards somewhere durable. The GPU VM should be disposable.