What is Ray?
Ray is an open-source platform designed for building distributed applications with ease. It is a flexible and scalable system that can handle a wide range of workloads, from simple data processing tasks to complex machine learning workflows.
What does Ray do?
What Ray does is provide developers with a powerful set of tools to build scalable and fault-tolerant distributed applications. Ray is built on top of Python and offers a simple and intuitive API that makes it easy to write and run distributed applications.
Ray is used in a wide range of applications, including machine learning, deep learning, data processing, and simulation. It is particularly useful for applications that require large amounts of computation and data processing, as it allows developers to easily scale their applications to handle massive workloads.
Some benefits of using Ray include:
Scalability: Ray is designed to scale quickly, making it perfect for applications that handle large amounts of data or processing power.
Fault-tolerance: Ray is built to be fault-tolerant, meaning it can automatically recover from failures and continue processing without interruption.
Ease of use: Ray provides a simple and intuitive API that makes it easy for developers to write distributed applications without worrying about the underlying infrastructure.
Flexibility: Ray is a flexible platform that can be used in various applications, from simple data processing tasks to complex machine learning workflows.
If you want to learn more about Ray, check out the following resources: