ray: An open source framework that provides a simple, universal API for building distributed applications

ray: An open source framework that provides a simple, universal API for building distributed applications

GitHub – ray-project/ray: An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

“Ray provides a simple, universal API for building distributed applications.

Ray accomplishes this mission by:

1. Providing simple primitives for building and running distributed applications.
2. Enabling end users to parallelize single machine code, with little to zero code changes.
3. Including a large ecosystem of applications, libraries, and tools on top of the core Ray to enable complex applications.

Ray Core provides the simple primitives for application building.

On top of Ray Core are several libraries for solving problems in machine learning:

• Tune: Scalable Hyperparameter Tuning
• RLlib: Scalable Reinforcement Learning
• RaySGD: Distributed Training Wrappers
• Datasets: Flexible Distributed Data Loading (alpha)…”

Source: github.com/ray-project/ray