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How to Use NVIDIA Warp and MjWarp to Accelerate Robotics Simulation and Learning Workflows
Guide to GPU-accelerated robotics simulation with NVIDIA Warp
Hugging Face and NVIDIA published a guide on using NVIDIA Warp and MuJoCo Warp (MJWarp) to accelerate robotics simulation on GPUs.
The article demonstrates how to scale robot simulation from single CPU-based environments to up to 2,048 parallel GPU-accelerated environments, enabling faster batch processing for reinforcement learning and large-scale sampling workflows.
From the source
MuJoCo Warp (MJWarp), built on NVIDIA Warp, takes compatible MuJoCo models into that GPU-scale regime. In this article, we will move an SO-101 follower arm from a familiar MuJoCo workflow to as many as 2,048 parallel MJWarp environments and examine the technology and validation steps that make the transition possible.
huggingface.co
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