NVIDIA Warp Documentation#

Warp is a Python framework for GPU-accelerated simulation, robotics, and machine learning. Warp takes regular Python functions and JIT compiles them to efficient kernel code that can run on the CPU or GPU.

Warp comes with a rich set of primitives for physics simulation, robotics, geometry processing, and more. Warp kernels are differentiable and can be used as part of machine-learning pipelines with frameworks such as PyTorch, JAX and Paddle.

Quickstart#

Install Warp from PyPI:

$ pip install warp-lang

For conda, nightly builds, CUDA 13 builds, building from source, and driver requirements, see Installation.

Example Gallery#

The warp/examples directory contains examples covering physics simulation, geometry processing, optimization, and tile-based GPU programming. Install the optional dependencies with pip install warp-lang[examples] and run them from the command line:

python -m warp.examples.<example_subdir>.<example>

warp/examples/core#


dem	fluid	graph capture	marching cubes

mesh	nvdb	raycast	raymarch

sample_mesh	sph	torch	wave

2-D incompressible turbulence in a periodic box

warp/examples/fem#


diffusion 3d	mixed elasticity	apic fluid	streamlines

distortion energy	taylor green	kelvin helmholtz	magnetostatics

adaptive grid	nonconforming contact	darcy level-set optimization	elastic shape optimization