Deploy doc preview for PR 1593 (93373c4)

Author: cuda-python-bot

docs/pr-preview/pr-1593/cuda-bindings/latest/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file records the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: d326e5850f719f722087eb0e89493768
+config: bf518cc9baa7b9fec829be468ca96b72
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/api.rst.txt

@@ -16,4 +16,5 @@ CUDA Python API Reference
    module/nvvm
    module/nvfatbin
    module/cufile
+   module/nvml
    module/utils

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/contribute.rst.txt

@@ -4,12 +4,17 @@
 Contributing
 ============
 
-Thank you for your interest in contributing to ``cuda-bindings``! Based on the type of contribution, it will fall into two categories:
-
-1. You want to report a bug, feature request, or documentation issue
-    - File an `issue <https://github.com/NVIDIA/cuda-python/issues/new/choose>`_ describing what you encountered or what you want to see changed.
-    - The NVIDIA team will evaluate the issues and triage them, scheduling
-    them for a release. If you believe the issue needs priority attention
-    comment on the issue to notify the team.
-2. You want to implement a feature, improvement, or bug fix:
-    - At this time we do not accept code contributions.
+Thank you for your interest in contributing to ``cuda-bindings``! Based on the
+type of contribution, it will fall into two categories:
+
+1. You want to report a bug, feature request, or documentation issue.
+
+   File an `issue <https://github.com/NVIDIA/cuda-python/issues/new/choose>`_
+   describing what you encountered or what you want to see changed. The NVIDIA
+   team will evaluate the issue, triage it, and schedule it for a release. If
+   you believe the issue needs priority attention, comment on the issue to
+   notify the team.
+
+2. You want to implement a feature, improvement, or bug fix.
+
+   At this time we do not accept code contributions.

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/environment_variables.rst.txt

@@ -15,7 +15,14 @@ Runtime Environment Variables
 Build-Time Environment Variables
 --------------------------------
 
-- ``CUDA_HOME`` or ``CUDA_PATH``: Specifies the location of the CUDA Toolkit.
+- ``CUDA_PATH`` or ``CUDA_HOME``: Specifies the location of the CUDA Toolkit. If both are set, ``CUDA_PATH`` takes precedence.
+
+  .. note::
+     The ``CUDA_PATH`` > ``CUDA_HOME`` priority is determined by ``cuda-pathfinder``.
+     Earlier versions of ``cuda-pathfinder`` (before 1.5.0) used the opposite order
+     (``CUDA_HOME`` > ``CUDA_PATH``). See the
+     `cuda-pathfinder 1.5.0 release notes <https://nvidia.github.io/cuda-python/cuda-pathfinder/latest/release/1.5.0-notes.html>`_
+     for details and migration guidance.
 
 - ``CUDA_PYTHON_PARSER_CACHING`` : bool, toggles the caching of parsed header files during the cuda-bindings build process. If caching is enabled (``CUDA_PYTHON_PARSER_CACHING`` is True), the cache path is set to ./cache_<library_name>, where <library_name> is derived from the cuda toolkit libraries used to build cuda-bindings.
 

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/examples.rst.txt

@@ -0,0 +1,68 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: LicenseRef-NVIDIA-SOFTWARE-LICENSE
+
+Examples
+========
+
+This page links to the ``cuda.bindings`` examples shipped in the
+`cuda-python repository <https://github.com/NVIDIA/cuda-python/tree/|cuda_bindings_github_ref|/cuda_bindings/examples>`_.
+Use it as a quick index when you want a runnable sample for a specific API area
+or CUDA feature.
+
+Introduction
+------------
+
+- `clock_nvrtc.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/clock_nvrtc.py>`_
+  uses NVRTC-compiled CUDA code and the device clock to time a reduction
+  kernel.
+- `simple_cubemap_texture.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py>`_
+  demonstrates cubemap texture sampling and transformation.
+- `simple_p2p.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/simple_p2p.py>`_
+  shows peer-to-peer memory access and transfers between multiple GPUs.
+- `simple_zero_copy.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/simple_zero_copy.py>`_
+  uses zero-copy mapped host memory for vector addition.
+- `system_wide_atomics.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/system_wide_atomics.py>`_
+  demonstrates system-wide atomic operations on managed memory.
+- `vector_add_drv.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/vector_add_drv.py>`_
+  uses the CUDA Driver API and unified virtual addressing for vector addition.
+- `vector_add_mmap.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/0_Introduction/vector_add_mmap.py>`_
+  uses virtual memory management APIs such as ``cuMemCreate`` and
+  ``cuMemMap`` for vector addition.
+
+Concepts and techniques
+-----------------------
+
+- `stream_ordered_allocation.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py>`_
+  demonstrates ``cudaMallocAsync`` and ``cudaFreeAsync`` together with
+  memory-pool release thresholds.
+
+CUDA features
+-------------
+
+- `global_to_shmem_async_copy.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py>`_
+  compares asynchronous global-to-shared-memory copy strategies in matrix
+  multiplication kernels.
+- `simple_cuda_graphs.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py>`_
+  shows both manual CUDA graph construction and stream-capture-based replay.
+
+Libraries and tools
+-------------------
+
+- `conjugate_gradient_multi_block_cg.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py>`_
+  implements a conjugate-gradient solver with cooperative groups and
+  multi-block synchronization.
+- `nvidia_smi.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py>`_
+  uses NVML to implement a Python subset of ``nvidia-smi``.
+
+Advanced and interoperability
+-----------------------------
+
+- `iso_fd_modelling.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/extra/iso_fd_modelling.py>`_
+  runs isotropic finite-difference wave propagation across multiple GPUs with
+  peer-to-peer halo exchange.
+- `jit_program.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/extra/jit_program.py>`_
+  JIT-compiles a SAXPY kernel with NVRTC and launches it through the Driver
+  API.
+- `numba_emm_plugin.py <https://github.com/NVIDIA/cuda-python/blob/|cuda_bindings_github_ref|/cuda_bindings/examples/extra/numba_emm_plugin.py>`_
+  shows how to back Numba's EMM interface with the NVIDIA CUDA Python Driver
+  API.

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/index.rst.txt

@@ -11,6 +11,7 @@
    release
    install
    overview
+   examples
    motivation
    environment_variables
    api

docs/pr-preview/pr-1593/cuda-bindings/latest/_sources/install.rst.txt

@@ -78,7 +78,7 @@ Installing from Source
 ----------------------
 
 Requirements
-^^^^^^^^^^^^
+~~~~~~~~~~~~
 
 * CUDA Toolkit headers[^1]
 * CUDA Runtime static library[^2]
@@ -87,11 +87,11 @@ Requirements
 
 [^2]: The CUDA Runtime static library (``libcudart_static.a`` on Linux, ``cudart_static.lib`` on Windows) is part of the CUDA Toolkit. If using conda packages, it is contained in the ``cuda-cudart-static`` package.
 
-Source builds require that the provided CUDA headers are of the same major.minor version as the ``cuda.bindings`` you're trying to build. Despite this requirement, note that the minor version compatibility is still maintained. Use the ``CUDA_HOME`` (or ``CUDA_PATH``) environment variable to specify the location of your headers. For example, if your headers are located in ``/usr/local/cuda/include``, then you should set ``CUDA_HOME`` with:
+Source builds require that the provided CUDA headers are of the same major.minor version as the ``cuda.bindings`` you're trying to build. Despite this requirement, note that the minor version compatibility is still maintained. Use the ``CUDA_PATH`` (or ``CUDA_HOME``) environment variable to specify the location of your headers. If both are set, ``CUDA_PATH`` takes precedence. For example, if your headers are located in ``/usr/local/cuda/include``, then you should set ``CUDA_PATH`` with:
 
 .. code-block:: console
 
-   $ export CUDA_HOME=/usr/local/cuda
+   $ export CUDA_PATH=/usr/local/cuda
 
 See `Environment Variables <environment_variables.rst>`_ for a description of other build-time environment variables.
 
@@ -100,7 +100,7 @@ See `Environment Variables <environment_variables.rst>`_ for a description of ot
    Only ``cydriver``, ``cyruntime`` and ``cynvrtc`` are impacted by the header requirement.
 
 Editable Install
-^^^^^^^^^^^^^^^^
+~~~~~~~~~~~~~~~~
 
 You can use: