Description
In this talk we introduce NVIDIA Warp, an open-source Python framework designed for accelerated differentiable computing. Warp enhances Python functions with just-in-time (JIT) compilation, allowing for efficient execution on CPUs and GPUs. The talk’s focus is on Warp’s application in physics simulation, perception, robotics, and geometry processing, along with its capability to integrate with machine-learning frameworks like PyTorch and JAX. Participants will learn the basics of Warp, including its JIT compilation process and the runtime library that supports various spatial computing operations. These concepts will be illustrated with hands-on projects based on research from institutions like MIT and UCLA, providing practical experience in using Warp to address computational challenges. Targeted at academics, researchers, and professionals in computational fields, the course is designed to inspire attendees and equip them with the knowledge and skills to use Warp in their work, enhancing their projects with efficient spatial computing.