joschu / ray

A high-performance distributed execution engine

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Ray

image

image

Ray is a flexible, high-performance distributed execution framework.

Ray is easy to install: pip install ray

Example Use

Basic Python Distributed with Ray
# Execute f serially.


def f():
    time.sleep(1)
    return 1



results = [f() for i in range(4)]
# Execute f in parallel.

@ray.remote
def f():
    time.sleep(1)
    return 1


ray.init()
results = ray.get([f.remote() for i in range(4)])

Ray comes with libraries that accelerate deep learning and reinforcement learning development:

  • Ray Tune: Hyperparameter Optimization Framework
  • Ray RLlib: Scalable Reinforcement Learning

Installation

Ray can be installed on Linux and Mac with pip install ray.

To build Ray from source or to install the nightly versions, see the installation documentation.

More Information

Getting Involved

About

A high-performance distributed execution engine

License:Apache License 2.0


Languages

Language:Python 44.5%Language:C++ 35.8%Language:Java 15.3%Language:C 1.7%Language:Shell 1.3%Language:CMake 1.1%Language:Jupyter Notebook 0.2%Language:Ruby 0.0%Language:HTML 0.0%Language:CSS 0.0%