Deploy latest docs: 979b65f

Author: cuda-python-bot

docs/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/cuda_bindings/examples/">cuda-python repository</a>.
+<a class="extlink-cuda-bindings-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/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/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/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/979b65fb2d9b59cc75f6298297b37e35cd1eef17/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/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: 3b4a93babebfe2947fe0d403ed821ab1
+config: 32ef7e9c337eff87fc0eccf5661fb60e
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/cuda-core/latest/.doctrees/10_minutes_to_cuda_core.doctree

@@ -44,7 +44,7 @@
 
 
 
-    <script src="_static/documentation_options.js?v=98377070"></script>
+    <script src="_static/documentation_options.js?v=3c4ff469"></script>
     <script src="_static/doctools.js?v=9bcbadda"></script>
     <script src="_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="_static/clipboard.min.js?v=a7894cd8"></script>
@@ -53,7 +53,7 @@
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+        DOCUMENTATION_OPTIONS.theme_switcher_version_match = '1.1.2.dev21';
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@@ -1005,7 +1005,7 @@ <h2>Capturing work in a CUDA graph<a class="headerlink" href="#capturing-work-in
 <span class="n">stream</span><span class="o">.</span><span class="n">sync</span><span class="p">()</span>
 </pre></div>
 </div>
-<p>See <a class="extlink-cuda-core-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/cuda_core/examples/cuda_graphs.py">cuda_graphs.py</a>
+<p>See <a class="extlink-cuda-core-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/979b65fb2d9b59cc75f6298297b37e35cd1eef17/cuda_core/examples/cuda_graphs.py">cuda_graphs.py</a>
 for a complete capture-and-replay example with a measured speedup.</p>
 <p>Beyond the stream capture shown here, <code class="docutils literal notranslate"><span class="pre">cuda.core</span></code> also provides an explicit
 graph interface (the <code class="xref py py-mod docutils literal notranslate"><span class="pre">cuda.core.graph</span></code> module) for building, inspecting, and
@@ -1082,7 +1082,7 @@ <h2>Working with CuPy and PyTorch<a class="headerlink" href="#working-with-cupy-
 <h2>Cleaning up<a class="headerlink" href="#cleaning-up" title="Link to this heading">#</a></h2>
 <p>Buffers, streams, events, graphs, and graph builders hold CUDA resources. They
 are released when garbage-collected, but you can release them explicitly with
-<code class="docutils literal notranslate"><span class="pre">close()</span></code>, which the <a class="extlink-cuda-core-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/7e7d3c14fc4ce848b58a8bf39c90ca1db89ce014/cuda_core/examples/">cuda.core examples</a> do in a
+<code class="docutils literal notranslate"><span class="pre">close()</span></code>, which the <a class="extlink-cuda-core-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/979b65fb2d9b59cc75f6298297b37e35cd1eef17/cuda_core/examples/">cuda.core examples</a> do in a
 <code class="docutils literal notranslate"><span class="pre">finally</span></code> block.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">graph</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>
 <span class="n">gb</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>