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Robert Nishihara 5b2cc67251 Merge pull request #100 from amplab/objrefserialization 
implement serialization of object references inside of python objects
2016-06-10 16:43:11 -07:00
cmake/Modules
add FindNumPy.cmake
2016-03-10 14:46:26 -08:00
doc
renaming project, halo -> ray (#95)
2016-06-10 14:12:15 -07:00
include/ray
renaming project, halo -> ray (#95)
2016-06-10 14:12:15 -07:00
lib/python
renaming project, halo -> ray (#95)
2016-06-10 14:12:15 -07:00
protos
implement serialization of object references inside of python objects
2016-06-10 16:32:48 -07:00
src
implement serialization of object references inside of python objects
2016-06-10 16:32:48 -07:00
test
implement serialization of object references inside of python objects
2016-06-10 16:32:48 -07:00
thirdparty
build on mac os x (#96)
2016-06-10 15:35:49 -07:00
.gitignore
Initial commit
2016-02-07 14:18:40 -08:00
.gitmodules
link libraries statically and make halo work on Mac OS X
2016-06-10 13:16:07 -07:00
.travis.yml
adding continuous integration
2016-06-05 20:46:54 -07:00
CMakeLists.txt
renaming project, halo -> ray (#95)
2016-06-10 14:12:15 -07:00
LICENSE
switching to BSD (#90)
2016-06-06 12:07:36 -07:00
README.md
updating readme (#99)
2016-06-10 15:36:10 -07:00
requirements.txt
link libraries statically and make halo work on Mac OS X
2016-06-10 13:16:07 -07:00
setup.sh
build on mac os x (#96)
2016-06-10 15:35:49 -07:00

README.md

Ray

Ray is an experimental distributed execution framework with a Python-like programming model. It is under development and not ready for general use.

Design Decisions

For a description of our design decisions, see

Setup

  1. sudo apt-get update
  2. sudo apt-get install git
  3. git clone https://github.com/amplab/ray.git
  4. cd ray
  5. ./setup.sh
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Description
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.
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