A selection of physical simulations computed with Warp
## Quick Start
Simulate one million particles under gravitational attraction, in 20 lines:
```python
import warp as wp
import numpy as np
num_particles = 1_000_000
dt = 0.01
@wp.kernel
def gravity_step(pos: wp.array[wp.vec3], vel: wp.array[wp.vec3]):
i = wp.tid()
position = pos[i]
dist_sq = wp.length_sq(position) + 0.01 # softened distance
acc = -1000.0 / dist_sq * wp.normalize(position) # gravitational pull toward origin
vel[i] = vel[i] + acc * dt
pos[i] = pos[i] + vel[i] * dt
rng = np.random.default_rng(42)
positions = wp.array(rng.normal(size=(num_particles, 3)), dtype=wp.vec3)
velocities = wp.array(rng.normal(size=(num_particles, 3)), dtype=wp.vec3)
for _ in range(100):
wp.launch(gravity_step, dim=num_particles, inputs=[positions, velocities])
print(positions.numpy())
```
## Installing
Python version 3.10 or newer is required. Warp can run on x86-64 and ARMv8 CPUs on Windows and Linux, and on Apple Silicon (ARMv8) on macOS.
GPU support requires a CUDA-capable NVIDIA GPU and driver (minimum GeForce GTX 9xx).
The easiest way to install Warp is from [PyPI](https://pypi.org/project/warp-lang/):
```text
pip install warp-lang
```
You can also use `pip install warp-lang[examples]` to install additional dependencies for running examples and USD-related features.
For nightly builds, conda, CUDA 13 builds, building from source, and CUDA driver requirements, see the
[Installation Guide](https://nvidia.github.io/warp/stable/user_guide/installation.html).
## Tutorial Notebooks
The [NVIDIA Accelerated Computing Hub](https://github.com/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/README.md) also hosts Warp
tutorial notebooks that can be opened in Colab:
| Notebook | Colab Link |
|----------|------------|
| [01. Introduction to NVIDIA Warp](https://github.com/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/01__intro_to_warp.ipynb) | [](https://colab.research.google.com/github/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/01__intro_to_warp.ipynb) |
| [02. Ising Model](https://github.com/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/02__ising_model.ipynb) | [](https://colab.research.google.com/github/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/02__ising_model.ipynb) |
| [03. 2D Navier-Stokes Solver](https://github.com/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/03__navier_stokes_solver.ipynb) | [](https://colab.research.google.com/github/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/03__navier_stokes_solver.ipynb) |
| [04. Differentiable Simulations in Warp](https://github.com/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/04__differentiable_navier_stokes_solver.ipynb) | [](https://colab.research.google.com/github/NVIDIA/accelerated-computing-hub/blob/main/tutorials/warp/notebooks/04__differentiable_navier_stokes_solver.ipynb) |
## Running Examples
The [warp/examples](https://github.com/NVIDIA/warp/tree/main/warp/examples) directory contains examples
covering physics simulation, geometry processing, optimization, and tile-based GPU programming.
Before running examples, install the optional example dependencies using:
```text
pip install warp-lang[examples]
```
On Linux aarch64 systems (e.g., NVIDIA DGX Spark), the `[examples]` extra automatically installs
[`usd-exchange`](https://pypi.org/project/usd-exchange/) instead of `usd-core` as a drop-in replacement,
since `usd-core` wheels are not available for that platform.
Examples can be run from the command-line as follows:
```text
python -m warp.examples.
