Warp: Advancing Simulation AI with Differentiable GPU Computing in Python

Join us for a deep dive into NVIDIA’s Warp framework and learn how it enables developers to create GPU-accelerated and differentiable simulation programs in Python. We'll cover the latest features in Warp for 3D data generation, computer-aided engineering, and robotics, and show how Warp seamlessly connects to machine learning frameworks such as PyTorch and JAX. We'll illustrate these concepts with in-depth examples, including trajectory optimization for aerial vehicles, finite-element analysis, and large-scale computational fluid dynamics. Finally, we’ll preview the Warp roadmap and how upcoming features will enable users to leverage the power of Tensor Cores for accelerated neural network inference and training.