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Copy file name to clipboardExpand all lines: README.md
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# CUDA-Python
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# cuda-python
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CUDA Python is the home for accessing NVIDIA’s CUDA platform from Python. It consists of multiple components:
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*[cuda.cooperative](https://nvidia.github.io/cccl/cuda_cooperative/): Pythonic exposure of CUB cooperative algorithms
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*[cuda.parallel](https://nvidia.github.io/cccl/cuda_parallel/): Pythonic exposure of Thrust parallel algorithms
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For access to NVIDIA Math Libraries, please refer to [nvmath-python](https://docs.nvidia.com/cuda/nvmath-python/latest).
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For access to NVIDIA CPU & GPU Math Libraries, please refer to [nvmath-python](https://docs.nvidia.com/cuda/nvmath-python/latest).
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CUDA Python is currently undergoing an overhaul to improve existing and bring up new components. All of the previously available functionalities from the cuda-python package will continue to be available, please refer to the [cuda.bindings](https://nvidia.github.io/cuda-python/cuda-bindings/latest) documentation for installation guide and further detail.
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## CUDA-Python as a metapackage
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## cuda-python as a metapackage
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CUDA-Python is structured to become a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
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`cuda-python` is being re-structured to become a metapackage that contains a collection of subpackages. Each subpackage is versioned independently, allowing installation of each component as needed.
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### Subpackage: `cuda.core`
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The `cuda.core` package offers idiomatic, pythonic access to CUDA Runtime and other functionalities.
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The goals are to
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1. Provide **idiomatic (“pythonic”)** access to CUDA Driver/Runtime
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1. Provide **idiomatic ("pythonic")** access to CUDA Driver, Runtime, and JIT compiler toolchain
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2. Focus on **developer productivity** by ensuring end-to-end CUDA development can be performed quickly and entirely in Python
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3.**Avoid homegrown** Python abstractions for CUDA for new Python GPU libraries starting from scratch
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4.**Ease** developer **burden of maintaining** and catching up with latest CUDA features
Copy file name to clipboardExpand all lines: cuda_bindings/README.md
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# `cuda.bindings`: Low-level CUDA interfaces
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CUDA Python is a standard set of low-level interfaces, providing full coverage of and access to the CUDA host APIs from Python. Checkout the [Overview](https://nvidia.github.io/cuda-python/cuda-bindings/latest/overview.html) for the workflow and performance results.
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`cuda.bindings` is a standard set of low-level interfaces, providing full coverage of and access to the CUDA host APIs from Python. Checkout the [Overview](https://nvidia.github.io/cuda-python/cuda-bindings/latest/overview.html) for the workflow and performance results.
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`cuda.bindings` is a subpackage of `cuda-python`.
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## Installing
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CUDA Python can be installed from:
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*PYPI
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* Conda (nvidia channel)
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*PyPI
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* Conda (conda-forge/nvidia channels)
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* Source builds
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Differences between these options are described in [Installation](https://nvidia.github.io/cuda-python/cuda-bindings/latest/install.html) documentation. Each package guarantees minor version compatibility.
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* Python 3.9 to 3.12
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## Developing
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We use `pre-commit` to manage various tools to help development and ensure consistency.
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```shell
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pip install pre-commit
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```
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### Code linting
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Run this command before checking in the code changes
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```shell
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pre-commit run -a --show-diff-on-failure
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```
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to ensure the code formatting is in line of the requirements (as listed in [`pyproject.toml`](./pyproject.toml)).
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### Code signing
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This repository implements a security check to prevent the CI system from running untrusted code. A part of the
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security check consists of checking if the git commits are signed. See
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