Lightning 1.8: Colossal-AI, Secrets for Apps, and more

Lightning 1.8, built through more than 550 commits from 52 contributors, introduces features aimed at improving large-scale model training, Lightning App development, and cluster usability. Its experimental Colossal-AI strategy supports multiple parallelism techniques and can reduce GPU requirements for models such as GPT-3 or enable training larger models with the same hardware, while FSDP enhancements add automatic layer wrapping for models that fit in CPU but not GPU memory. Lightning Apps gain encrypted secrets for securely providing credentials, as well as experimental configurable CLI commands that let users interact with running applications from a terminal. The release also adds customizable batch-size and learning-rate finder callbacks for tuning workflows, enables LightningCLI to be invoked directly from Python, and improves SLURM support through configurable preemption signals and automatic requeuing for array jobs.

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