Merge branch 'main' into test/api-docs-consistency-2326

Author: mdboom

README.md

@@ -5,7 +5,6 @@ CUDA Python is the home for accessing NVIDIA’s CUDA platform from Python. It c
 * [cuda.core](https://nvidia.github.io/cuda-python/cuda-core/latest): Pythonic access to CUDA Runtime and other core functionality
 * [cuda.bindings](https://nvidia.github.io/cuda-python/cuda-bindings/latest): Low-level Python bindings to CUDA C APIs
 * [cuda.pathfinder](https://nvidia.github.io/cuda-python/cuda-pathfinder/latest): Utilities for locating CUDA components installed in the user's Python environment
-* [cuda.coop](https://nvidia.github.io/cccl/unstable/python/coop.html): A Python module providing CCCL's reusable block-wide and warp-wide *device* primitives for use within Numba CUDA kernels
 * [cuda.compute](https://nvidia.github.io/cccl/unstable/python/compute/index.html): A Python module for easy access to CCCL's highly efficient and customizable parallel algorithms, like `sort`, `scan`, `reduce`, `transform`, etc. that are callable on the *host*
 * [numba-cuda-mlir](https://nvidia.github.io/numba-cuda-mlir/): An evolution of Numba CUDA that improves upon its technical foundation and performance to provide the future of CUDA Python JIT compilation. It currently supports developing CUDA **SIMT** kernels in Python, providing Python bindings for accelerated device libraries, and serving as a compiler for user-defined functions in accelerated libraries.
 * [numba.cuda](https://nvidia.github.io/numba-cuda/): A Python DSL that exposes CUDA **SIMT** programming model and compiles a restricted subset of Python code into CUDA kernels and device functions

cuda_python/DESCRIPTION.rst

@@ -10,7 +10,6 @@ CUDA Python is the home for accessing NVIDIA's CUDA platform from Python. It con
 * `cuda.core <https://nvidia.github.io/cuda-python/cuda-core/latest>`_: Pythonic access to CUDA Runtime and other core functionality
 * `cuda.bindings <https://nvidia.github.io/cuda-python/cuda-bindings/latest>`_: Low-level Python bindings to CUDA C APIs
 * `cuda.pathfinder <https://nvidia.github.io/cuda-python/cuda-pathfinder/latest>`_: Utilities for locating CUDA components installed in the user's Python environment
-* `cuda.coop <https://nvidia.github.io/cccl/unstable/python/coop.html>`_: A Python module providing CCCL's reusable block-wide and warp-wide *device* primitives for use within Numba CUDA kernels
 * `cuda.compute <https://nvidia.github.io/cccl/unstable/python/compute/index.html>`_: A Python module for easy access to CCCL's highly efficient and customizable parallel algorithms, like ``sort``, ``scan``, ``reduce``, ``transform``, etc. that are callable on the *host*
 * `numba-cuda-mlir <https://nvidia.github.io/numba-cuda-mlir/>`_: An evolution of Numba CUDA that improves upon its technical foundation and performance to provide the future of CUDA Python JIT compilation. It currently supports developing CUDA **SIMT** kernels in Python, providing Python bindings for accelerated device libraries, and serving as a compiler for user-defined functions in accelerated libraries.
 * `numba.cuda <https://nvidia.github.io/numba-cuda/>`_: A Python DSL that exposes CUDA **SIMT** programming model and compiles a restricted subset of Python code into CUDA kernels and device functions

cuda_python/docs/source/index.rst

@@ -10,7 +10,6 @@ multiple components:
 - `cuda.core`_: Pythonic access to CUDA Runtime and other core functionality
 - `cuda.bindings`_: Low-level Python bindings to CUDA C APIs
 - `cuda.pathfinder`_: Utilities for locating CUDA components installed in the user's Python environment
-- `cuda.coop`_: A Python module providing CCCL's reusable block-wide and warp-wide *device* primitives for use within Numba CUDA kernels
 - `cuda.compute`_: A Python module for easy access to CCCL's highly efficient and customizable parallel algorithms, like ``sort``, ``scan``, ``reduce``, ``transform``, etc. that are callable on the *host*
 - `numba-cuda-mlir`_: An evolution of Numba CUDA that improves upon its technical foundation and performance to provide the future of CUDA Python JIT compilation. It currently supports developing CUDA **SIMT** kernels in Python, providing Python bindings for accelerated device libraries, and serving as a compiler for user-defined functions in accelerated libraries.
 - `numba.cuda`_: A Python DSL that exposes CUDA **SIMT** programming model and compiles a restricted subset of Python code into CUDA kernels and device functions
@@ -21,7 +20,6 @@ multiple components:
 - `CUPTI Python`_: Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI)
 - `Accelerated Computing Hub`_: Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing.
 
-.. _cuda.coop: https://nvidia.github.io/cccl/unstable/python/coop.html
 .. _cuda.compute: https://nvidia.github.io/cccl/unstable/python/compute/index.html
 .. _numba-cuda-mlir: https://nvidia.github.io/numba-cuda-mlir/
 .. _numba.cuda: https://nvidia.github.io/numba-cuda/
@@ -52,7 +50,6 @@ be available, please refer to the `cuda.bindings`_ documentation for installatio
    cuda.core <https://nvidia.github.io/cuda-python/cuda-core/latest>
    cuda.bindings <https://nvidia.github.io/cuda-python/cuda-bindings/latest>
    cuda.pathfinder <https://nvidia.github.io/cuda-python/cuda-pathfinder/latest>
-   cuda.coop <https://nvidia.github.io/cccl/unstable/python/coop.html>
    cuda.compute <https://nvidia.github.io/cccl/unstable/python/compute/index.html>
    numba-cuda-mlir <https://nvidia.github.io/numba-cuda-mlir/>
    numba.cuda <https://nvidia.github.io/numba-cuda/>