NVIDIA Warp
- Software
- Simulators
- Library
A Python framework that JIT-compiles ordinary Python functions into kernels running on CPU or GPU, aimed at simulation, robotics and machine learning.
Made by NVIDIA, United States (checked on github.com/NVIDIA (opens in a new tab)).
Source on GitHub: github.com/NVIDIA/warp (opens in a new tab). Facts read at commit 5e7a8fe (opens in a new tab).
Licenses
- Code
- Apache-2.0 (opens in a new tab)
Read by Robotheca from LICENSE.md (opens in a new tab) (Apache-2.0) at commit 5e7a8fe (opens in a new tab), on 16 Oct 2026.
- Commercial use
- Yes
What it does
- Takes regular Python functions and JIT compiles them to efficient kernel code for CPU or GPU.
- Includes primitives for physics simulation, robotics, geometry processing and more.
- Warp kernels are differentiable and can be used in machine-learning pipelines with PyTorch, JAX and Paddle.
- Installs from PyPI as warp-lang, with optional extras for examples and USD features.
- Ships a set of examples covering physics simulation, geometry, optimization and tile-based GPU programming.
Written by Robotheca from the project's README (opens in a new tab) at commit 5e7a8fe.
Getting started
- Difficulty
- Advanced
- Hardware it needs, as the project states it
- Requires Python 3.10 or newer. Wheels exist for Windows (x86-64), Linux (x86-64 and AArch64) and macOS (Apple Silicon, CPU only). CUDA acceleration on Windows and Linux needs an NVIDIA R580-series or newer driver and a Turing (sm_75) or newer GPU; some examples need a CUDA-capable device.
- How to start
- The project's website (opens in a new tab)
Maintenance
- Status
- Active: a commit in the last 90 days
- Newest commit
- 16 Oct 2026 on main
- Latest release
- v1.18.0 (5 Oct 2026)
Checked on GitHub on 16 Oct 2026.
Links
Robots on Robotheca that use it
No robot on Robotheca is linked to it yet. Links come from a robot's robot.yaml, from its dependency files read as text, or from Robotheca's editors.
Robotheca lists software as a reference: nothing is hosted or run here, and every fact links to where it was read.