Popular GitHub Repositories for Cache Simulator

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

Supercharge Your LLM with the Fastest KV Cache Layer

A flexible, high-performance 3D simulator for Embodied AI research.

Scalable Multi-modal RAG platform

A modular high-level library to train embodied AI agents across a variety of tasks and environments.

Community for applying LLMs to robotics and a robot simulator with ChatGPT integration

SAPIEN Manipulation Skill Framework, an open source GPU parallelized robotics simulator and benchmark, led by Hillbot, Inc.

Fluid, elastic data abstraction and acceleration for BigData/AI applications in cloud. (Project under CNCF)

Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.

6DoF Head tracking software

Unified KV Cache Compression Methods for Auto-Regressive Models

R-KV: Redundancy-aware KV Cache Compression for Reasoning Models

Scalable Multi-Agent RL Training School for Autonomous Driving

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

Brian is a free, open source simulator for spiking neural networks.

A LLM semantic caching system aiming to enhance user experience by reducing response time via cached query-result pairs.

Reinforcement learning environments with musculoskeletal models