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.

pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

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

LuxCore source repository

NanoRT, single header only modern ray tracing kernel.

A tiny software graphics and game engine

GPU Raytracer from scratch in C++/CUDA

Ray Aviary - evaluate multiple LLMs easily

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

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 toolkit to run Ray applications on Kubernetes

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

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

The old version of Buggregator, which uses Laravel framework, is no longer being actively developed. The new beta version, built with Spiral framework, is now available at https://github.com/buggregator/spiral-app and offers significant improvements in performance and stability, as well as a lighter docker image size of around 300mb.

Framework for Multi-Agent Deep Reinforcement Learning in Poker

GPU environment management and cluster orchestration

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