Skip to content
BranchesTags

Repository files navigation

NVIDIA Warp (Preview)

Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.

Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.

A flow field visualization of a NanoVDB fluid simulation computed in Warp

Installing

Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:

pip install .

The Warp package will now be available to import as follows:

importwarpaswp

Building

For developers who want to build the library themselves the following tools are required:

  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)

After cloning the repository, users should run:

python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:

pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.

Running Examples

The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:

pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.

Built-in unit tests can be run from the command-line as follows:

python -m warp.tests

Omniverse

A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:

Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.

Learn More

Please see our GTC Presentation for more details on Warp.

Discord

We have a #warp channel on the public Omniverse Discord sever, come chat to us!

License

Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.

About

A Python framework for high performance GPU simulation and graphics

Resources

Readme
License
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all 
 blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
GitHub - mmarcinkiewicz/warp: A Python framework for high performance GPU simulation and graphics · GitHub
Skip to content
BranchesTags
Repository files navigation
NVIDIA Warp (Preview)
Warp is a Python framework for writing high-performance simulation and graphics code. Kernels are defined in Python syntax and JIT converted to C++/CUDA and compiled at runtime.
Warp is designed to make it easy to write programs for physics simulation, geometry processing, and procedural animation. Please refer to the project Documentation for detailed API and language reference.
A flow field visualization of a NanoVDB fluid simulation computed in Warp
Installing
Warp supports Python versions 3.7.x-3.9.x. Pre-built packages for Windows and Linux are available on the Releases page. To install in your local Python environment extract the archive and run the following command from the root directory:
pip install .

The Warp package will now be available to import as follows:
importwarpaswp
Building
For developers who want to build the library themselves the following tools are required:
  • Microsoft Visual Studio 2017 upwards (Windows)
  • GCC 4.0 upwards (Linux)
  • CUDA Toolkit 11.3 or higher
  • Git LFS installed (https://git-lfs.github.com/)
After cloning the repository, users should run:
python build_lib.py

This will generate the warp.dll / warp.so core library respectively. When building manually users should ensure that their CUDA_PATH environment variable is set and dynamic libraries can be found at runtime. After building the Warp package should be installed using:
pip install -e .

Which ensures that subsequent modifications to the libary will be reflected in the Python package.
Running Examples
The examples directory contains a number of scripts that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations in the examples/outputs directory. Before running examples users should ensure that the usd-core package is installed using:
pip install usd-core

USD files can be viewed or rendered inside NVIDIA Omniverse, Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations.
Built-in unit tests can be run from the command-line as follows:
python -m warp.tests

Omniverse
A Warp Omniverse extension is available in the extension registry inside Omniverse Kit or Create:
Enabling the extension will automatically install and initialize the Warp Python module inside the Kit Python environment. Please see the Omniverse Warp Documentation for more details on how to use Warp in Omniverse.
Learn More
Please see our GTC Presentation for more details on Warp.
Discord
We have a #warp channel on the public Omniverse Discord sever, come chat to us!
License
Warp is provided under the NVIDIA Source Code License (NVSCL), please see LICENSE.md for full license text.
About
A Python framework for high performance GPU simulation and graphics
Resources
Readme
License
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages