Parallel Computing

A documentation skill that teaches how to use Zarr, a Python library for storing large N-dimensional arrays with chunking and compression. It covers array creation, storage backends (local, cloud, memory), compression codecs, parallel computing with Dask, and integration with NumPy and Xarray for scientific computing workflows.

PufferLib is a high-performance reinforcement learning framework optimized for fast parallel training. It provides templates for creating custom environments, training scripts with PPO, and seamless integration with popular RL frameworks like Gymnasium and PettingZoo, achieving millions of steps per second.

A comprehensive documentation skill for Dask, a Python library for parallel and distributed computing. It provides detailed reference guides for working with larger-than-memory datasets using DataFrames, Arrays, Bags, and Futures, along with scheduler selection and best practices for performance optimization.