ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Real-time PathTracing with global illumination and progressive rendering, all on top of the Three.js WebGL framework. Click here for Live Demo: https://erichlof.github.io/THREE.js-PathTracing-Renderer/Geometry_Showcase.html

A GLSL Path Tracer

NanoRT, single header only modern ray tracing kernel.

LuxCore source repository

A tiny software graphics and game engine

GPU Raytracer from scratch in C++/CUDA

CGA 3D 计算几何算法库 | 3D Compute Geometry Algorithm Library webgl three.js babylon.js等任何库都可以使用

A basic Ray Tracer that exploits numpy arrays and functions to work fast.

A parallel framework for population-based multi-agent reinforcement learning.

Buggregator is a beautiful, lightweight debug server build on Laravel that helps you catch your smpt, sentry, var-dump, monolog, ray outputs. It runs without installation on multiple platforms.

Framework for Multi-Agent Deep Reinforcement Learning in Poker

A toolkit to run Ray applications on Kubernetes

The MARL extension for RLlib. A benchmark for research and industry.

RayDP provides simple APIs for running Spark on Ray and integrating Spark with AI libraries.

TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.

Enable Ray in all PHP files on your system

Distributed Keras Engine, Make Keras faster with only one line of code.