erwincoumans/tiny-differentiable-simulator

Health v2 · maintenance only

Adoption not part of the score

1371 stars · 138 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Tiny Differentiable Simulator (TDS) is a header-only C++ and CUDA physics library for rigid-body dynamics with zero dependencies, supporting forward/inverse dynamics, contact models, and actuator models. It is templatized to work with automatic differentiation scalar types (CppAD, Stan Math, ceres::Jet) or plain float/double, and can run thousands of simulations in parallel on a GPU for reinforcement learning and robotics research.

Use cases

• differentiable physics simulation for robotics research
• train reinforcement learning policies with GPU-parallel physics simulation
• compute gradients of rigid-body dynamics through automatic differentiation
• simulate articulated rigid bodies with contact and actuator models
• run deterministic cross-platform physics with fixed-point integer math
• close the sim-to-real gap by augmenting a simulator with neural networks

When to choose

• you need a dependency-free, header-only differentiable physics simulator in C++ or CUDA
• you want to run thousands of parallel simulations on a single GPU for RL or robotics
• you need gradients through rigid-body dynamics for system identification or policy optimization
• you require deterministic cross-platform simulation via fixed-point math

When to avoid

• you need a full-featured game physics engine with rendering, collision assets, and tooling
• you want a mature Python-first simulator like MuJoCo, PyBullet, or Isaac Gym
• you need extensive documentation and community support rather than a research codebase

Facets

library · maturity active

simulation machine-learning reinforcement-learning robotics graphics math robotics simulation reinforcement-learning machine-learning gpu-computing cpp cross-platform windows differentiable-simulation physics-engine rigid-body-dynamics automatic-differentiation header-only cuda sim2real zero-dependencies gpu linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="erwincoumans/tiny-differentiable-simulator")