How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows

NVIDIA Warp is a Python framework for writing high-performance, GPU-accelerated kernels, while MuJoCo Warp (MJWarp) implements MuJoCo physics on top of it. This combination allows for running thousands of parallel robotics simulations on a single GPU, a significant speedup over traditional CPU-based approaches. The framework supports differentiability for integration into machine learning training loops and offers interoperability with PyTorch and JAX. The goal is to accelerate robotics learning workflows by keeping simulation and training data on the same device. This approach is demonstrated by migrating a robotic arm scene from a standard MuJoCo workflow to a massively parallel MJWarp environment.