EvoJAX: Accelerate Neuroevolution with Hardware-Optimized Toolkit 🚀

We present EvoJAX, a scalable, general purpose, hardware-accelerated neuroevolution toolkit. Building on top of the JAX library, our toolkit enables neuroevolution algorithms to work with neural networks running in parallel across multiple TPU/GPUs. EvoJAX achieves very high performance by implementing the evolution algorithm, neural network and task all in NumPy, which is compiled just-in-time to run on accelerators. We provide extensible examples of EvoJAX for a wide range of tasks, including supervised learning, reinforcement learning and generative art. Since EvoJAX can find solutions to most of these tasks within minutes on a single accelerator, compared to hours or days when using CPUs, we believe our toolkit can significantly shorten the iteration time of conducting experiments for researchers working with evolutionary computation. Get started with W&B: http://wandb.me/intro Follow us: Twitter: http://twitter.com/weights_biases Linkedin: https://www.linkedin.com/company/weig... Check out Fully Connected, which features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, industry leaders sharing best practices, and more: https://wandb.ai/fully-connected