Deploy doc preview for PR 2398 (0816fc0)

Author: cuda-python-bot

docs/pr-preview/pr-2398/cuda-bindings/latest/_sources/release/13.4.0-notes.rst.txt

@@ -18,7 +18,7 @@ Prerelease feature
 
 A new version of the ``nvrtc`` API is available as ``cuda.bindings._v2.nvrtc``.  The
 primary improvements are: (1) raising exceptions rather than returning error
-codes, (2) uses PEP8-compliant naming, and (3) is more performant.  This API is
+codes, (2) uses PEP8-compliant naming, and (3) more performance.  This API is
 still experimental and subject to change.
 
 Known issues

docs/pr-preview/pr-2398/cuda-bindings/latest/examples.html

@@ -1302,65 +1302,65 @@
   <section id="examples">
 <h1>Examples<a class="headerlink" href="#examples" title="Link to this heading">#</a></h1>
 <p>This page links to the <code class="docutils literal notranslate"><span class="pre">cuda.bindings</span></code> examples shipped in the
-<a class="extlink-cuda-bindings-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/">cuda-python repository</a>.
+<a class="extlink-cuda-bindings-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/">cuda-python repository</a>.
 Use it as a quick index when you want a runnable sample for a specific API area
 or CUDA feature.</p>
 <section id="introduction">
 <h2>Introduction<a class="headerlink" href="#introduction" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/clock_nvrtc.py">clock_nvrtc.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/clock_nvrtc.py">clock_nvrtc.py</a>
 uses NVRTC-compiled CUDA code and the device clock to time a reduction
 kernel.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>
 demonstrates cubemap texture sampling and transformation.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/simple_p2p.py">simple_p2p.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/simple_p2p.py">simple_p2p.py</a>
 shows peer-to-peer memory access and transfers between multiple GPUs.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/simple_zero_copy.py">simple_zero_copy.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/simple_zero_copy.py">simple_zero_copy.py</a>
 uses zero-copy mapped host memory for vector addition.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/system_wide_atomics.py">system_wide_atomics.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/system_wide_atomics.py">system_wide_atomics.py</a>
 demonstrates system-wide atomic operations on managed memory.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/vector_add_drv.py">vector_add_drv.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/vector_add_drv.py">vector_add_drv.py</a>
 uses the CUDA Driver API and unified virtual addressing for vector addition.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/vector_add_mmap.py">vector_add_mmap.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/vector_add_mmap.py">vector_add_mmap.py</a>
 uses virtual memory management APIs such as <code class="docutils literal notranslate"><span class="pre">cuMemCreate</span></code> and
 <code class="docutils literal notranslate"><span class="pre">cuMemMap</span></code> for vector addition.</p></li>
 </ul>
 </section>
 <section id="concepts-and-techniques">
 <h2>Concepts and techniques<a class="headerlink" href="#concepts-and-techniques" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py">stream_ordered_allocation.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py">stream_ordered_allocation.py</a>
 demonstrates <code class="docutils literal notranslate"><span class="pre">cudaMallocAsync</span></code> and <code class="docutils literal notranslate"><span class="pre">cudaFreeAsync</span></code> together with
 memory-pool release thresholds.</p></li>
 </ul>
 </section>
 <section id="cuda-features">
 <h2>CUDA features<a class="headerlink" href="#cuda-features" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py">global_to_shmem_async_copy.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py">global_to_shmem_async_copy.py</a>
 compares asynchronous global-to-shared-memory copy strategies in matrix
 multiplication kernels.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py">simple_cuda_graphs.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py">simple_cuda_graphs.py</a>
 shows both manual CUDA graph construction and stream-capture-based replay.</p></li>
 </ul>
 </section>
 <section id="libraries-and-tools">
 <h2>Libraries and tools<a class="headerlink" href="#libraries-and-tools" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py">conjugate_gradient_multi_block_cg.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py">conjugate_gradient_multi_block_cg.py</a>
 implements a conjugate-gradient solver with cooperative groups and
 multi-block synchronization.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py">nvidia_smi.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py">nvidia_smi.py</a>
 uses NVML to implement a Python subset of <code class="docutils literal notranslate"><span class="pre">nvidia-smi</span></code>.</p></li>
 </ul>
 </section>
 <section id="advanced-and-interoperability">
 <h2>Advanced and interoperability<a class="headerlink" href="#advanced-and-interoperability" title="Link to this heading">#</a></h2>
 <ul class="simple">
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/extra/iso_fd_modelling.py">iso_fd_modelling.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/extra/iso_fd_modelling.py">iso_fd_modelling.py</a>
 runs isotropic finite-difference wave propagation across multiple GPUs with
 peer-to-peer halo exchange.</p></li>
-<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/extra/jit_program.py">jit_program.py</a>
+<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/extra/jit_program.py">jit_program.py</a>
 JIT-compiles a SAXPY kernel with NVRTC and launches it through the Driver
 API.</p></li>
 </ul>

docs/pr-preview/pr-2398/cuda-bindings/latest/overview.html

@@ -1786,7 +1786,7 @@ <h3>Using ctypes<a class="headerlink" href="#using-ctypes" title="Link to this h
 <h3>CUDA objects<a class="headerlink" href="#cuda-objects" title="Link to this heading">#</a></h3>
 <p>Certain CUDA kernels use native CUDA types as their parameters such as <code class="docutils literal notranslate"><span class="pre">cudaTextureObject_t</span></code>. These types require special handling since they’re neither a primitive ctype nor a custom user type. Since <code class="docutils literal notranslate"><span class="pre">cuda.bindings</span></code> exposes each of them as Python classes, they each implement <code class="docutils literal notranslate"><span class="pre">getPtr()</span></code> and <code class="docutils literal notranslate"><span class="pre">__int__()</span></code>. These two callables used to support the NumPy and ctypes approach. The difference between each call is further described under <a class="reference external" href="https://nvidia.github.io/cuda-python/cuda-bindings/latest/tips_and_tricks.html#">Tips and Tricks</a>.</p>
 <p>For this example, lets use the <code class="docutils literal notranslate"><span class="pre">transformKernel</span></code> from
-<a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/60170774b8582f0a45bac0ea3f5040c0433b2d25/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>.
+<a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/0816fc0313ec8a01f659eef335950ebb2d5575ae/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>.
 The <a class="reference internal" href="examples.html"><span class="doc">Examples</span></a> page links to more samples covering textures, graphs,
 memory mapping, and multi-GPU workflows.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">simpleCubemapTexture</span> <span class="o">=</span> <span class="s2">&quot;&quot;&quot;</span><span class="se">\</span>

docs/pr-preview/pr-2398/cuda-bindings/latest/release/13.4.0-notes.html

@@ -1316,7 +1316,7 @@ <h2>Deprecation Notices<a class="headerlink" href="#deprecation-notices" title="
 <h2>Prerelease feature<a class="headerlink" href="#prerelease-feature" title="Link to this heading">#</a></h2>
 <p>A new version of the <code class="docutils literal notranslate"><span class="pre">nvrtc</span></code> API is available as <code class="docutils literal notranslate"><span class="pre">cuda.bindings._v2.nvrtc</span></code>.  The
 primary improvements are: (1) raising exceptions rather than returning error
-codes, (2) uses PEP8-compliant naming, and (3) is more performant.  This API is
+codes, (2) uses PEP8-compliant naming, and (3) more performance.  This API is
 still experimental and subject to change.</p>
 </section>
 <section id="known-issues">

docs/pr-preview/pr-2398/cuda-core/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: 8e54a97b5dfcaadfa8f333b1f5673fb5
+config: 61e8a9a81ab4168d0986cef9c1cf13af
 tags: 645f666f9bcd5a90fca523b33c5a78b7