Nvidia Warp (a Python framework for writing high-performance code)
Warp is a Python framework for high-performance simulation and graphics, compiling functions for CPU or GPU. It supports spatial computing, differentiable kernels, PyTorch, JAX, and USD file generation. Installation options include PyPI and CUDA.
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Warp is a Python framework designed for high-performance simulation and graphics coding. It compiles regular Python functions into efficient kernel code for CPU or GPU execution, offering primitives for spatial computing in physics simulation, robotics, and more. Warp kernels are differentiable, compatible with machine learning frameworks like PyTorch and JAX. Users can install Warp from PyPI or build it from source for newer CUDA runtimes. The framework includes examples for computing vector lengths and various simulation methods, with scripts available on GitHub. Warp simulations can be run on CPU or CUDA devices, generating USD files for visualization in tools like Omniverse and Blender. The framework also integrates with Omniverse for extended functionality. Warp follows a versioning scheme similar to Python and is licensed under NVIDIA Software License. Contributions are welcome, and users are encouraged to cite Warp in research projects. The documentation provides detailed information on installation, usage, and advanced topics for users to explore.
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9 comments2.6 You may not use the Software in any manner that would cause it to become subject to an open source software license; subject to the terms in the “Components Under Other Licenses” section below.
2.7 You may not use the Software for the purpose of developing competing products or technologies or assist a third party in such activities.
Without a standard. Can we please focus on better C++ libraries for science so we can use any language for wrapping the result?
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