Speeding up MuJoCo 460x with Jax
The article discusses the integration of JAX with MuJoCo for enhanced robotics simulation. It highlights the performance improvements achieved through JAX's parallel processing capabilities. The author provides examples and code snippets to illustrate the benefits of using JAX for data collection in robotic simulations.
- ▪MuJoCo is a simulation library for rigid-body robotics developed by Google.
- ▪JAX is a numerical computing library that allows for fast parallel simulation.
- ▪The article includes a comparison of MJX and MuJoCo, showing MJX's advantages in parallel environments.
Opening excerpt (first ~120 words) tap to expand
Speeding up MuJoCo 460x with JAX An introduction to JAX and MJX for fast robotics simulation. The Code Setup JAX Basics How to Write Bad JAX Basic JAX and MJX Using JIT to Speed Things Up How to Write Better JAX Parallelism Jitting the Whole Thing Looping with Scan A Full Data Collection Loop Conclusion Most roboticists know MuJoCo, Google’s simulation library for rigid-body robotics. Fewer have spent much time with JAX, Google’s numerical computing library for scientific computing and machine learning. JAX is fiddly, but for parallel simulation it can be outrageously fast. I’m currently working on a basic world model, which means I need to collect a bunch of simulation data to train it.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Alexinch.
Discussion
0 commentsMore from Alexinch
