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docs/cuda-bindings/latest/examples.html

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<section id="examples">
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<h1>Examples<a class="headerlink" href="#examples" title="Link to this heading">#</a></h1>
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<p>This page links to the <code class="docutils literal notranslate"><span class="pre">cuda.bindings</span></code> examples shipped in the
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<a class="extlink-cuda-bindings-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/">cuda-python repository</a>.
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<a class="extlink-cuda-bindings-examples reference external" href="https://github.com/NVIDIA/cuda-python/tree/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/">cuda-python repository</a>.
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Use it as a quick index when you want a runnable sample for a specific API area
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or CUDA feature.</p>
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<section id="introduction">
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<h2>Introduction<a class="headerlink" href="#introduction" title="Link to this heading">#</a></h2>
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<ul class="simple">
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/clock_nvrtc.py">clock_nvrtc.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/clock_nvrtc.py">clock_nvrtc.py</a>
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uses NVRTC-compiled CUDA code and the device clock to time a reduction
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kernel.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>
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demonstrates cubemap texture sampling and transformation.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/simple_p2p.py">simple_p2p.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/simple_p2p.py">simple_p2p.py</a>
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shows peer-to-peer memory access and transfers between multiple GPUs.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/simple_zero_copy.py">simple_zero_copy.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/simple_zero_copy.py">simple_zero_copy.py</a>
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uses zero-copy mapped host memory for vector addition.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/system_wide_atomics.py">system_wide_atomics.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/system_wide_atomics.py">system_wide_atomics.py</a>
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demonstrates system-wide atomic operations on managed memory.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/vector_add_drv.py">vector_add_drv.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/vector_add_drv.py">vector_add_drv.py</a>
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uses the CUDA Driver API and unified virtual addressing for vector addition.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/vector_add_mmap.py">vector_add_mmap.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/vector_add_mmap.py">vector_add_mmap.py</a>
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uses virtual memory management APIs such as <code class="docutils literal notranslate"><span class="pre">cuMemCreate</span></code> and
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<code class="docutils literal notranslate"><span class="pre">cuMemMap</span></code> for vector addition.</p></li>
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</ul>
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</section>
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<section id="concepts-and-techniques">
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<h2>Concepts and techniques<a class="headerlink" href="#concepts-and-techniques" title="Link to this heading">#</a></h2>
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<ul class="simple">
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py">stream_ordered_allocation.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py">stream_ordered_allocation.py</a>
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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
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memory-pool release thresholds.</p></li>
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</ul>
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</section>
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<section id="cuda-features">
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<h2>CUDA features<a class="headerlink" href="#cuda-features" title="Link to this heading">#</a></h2>
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<ul class="simple">
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py">global_to_shmem_async_copy.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py">global_to_shmem_async_copy.py</a>
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compares asynchronous global-to-shared-memory copy strategies in matrix
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multiplication kernels.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py">simple_cuda_graphs.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py">simple_cuda_graphs.py</a>
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shows both manual CUDA graph construction and stream-capture-based replay.</p></li>
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</ul>
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</section>
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<section id="libraries-and-tools">
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<h2>Libraries and tools<a class="headerlink" href="#libraries-and-tools" title="Link to this heading">#</a></h2>
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<ul class="simple">
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py">conjugate_gradient_multi_block_cg.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py">conjugate_gradient_multi_block_cg.py</a>
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implements a conjugate-gradient solver with cooperative groups and
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multi-block synchronization.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py">nvidia_smi.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py">nvidia_smi.py</a>
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uses NVML to implement a Python subset of <code class="docutils literal notranslate"><span class="pre">nvidia-smi</span></code>.</p></li>
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</ul>
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</section>
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<section id="advanced-and-interoperability">
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<h2>Advanced and interoperability<a class="headerlink" href="#advanced-and-interoperability" title="Link to this heading">#</a></h2>
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<ul class="simple">
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/extra/iso_fd_modelling.py">iso_fd_modelling.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/extra/iso_fd_modelling.py">iso_fd_modelling.py</a>
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runs isotropic finite-difference wave propagation across multiple GPUs with
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peer-to-peer halo exchange.</p></li>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/extra/jit_program.py">jit_program.py</a>
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<li><p><a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/extra/jit_program.py">jit_program.py</a>
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JIT-compiles a SAXPY kernel with NVRTC and launches it through the Driver
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API.</p></li>
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</ul>

docs/cuda-bindings/latest/overview.html

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<h3>CUDA objects<a class="headerlink" href="#cuda-objects" title="Link to this heading">#</a></h3>
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<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>
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<p>For this example, lets use the <code class="docutils literal notranslate"><span class="pre">transformKernel</span></code> from
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<a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/75e6960fa2fa150739a1dc5a4c32eaf951a4d068/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>.
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<a class="extlink-cuda-bindings-example reference external" href="https://github.com/NVIDIA/cuda-python/blob/e4208edc7365ade465b2900212a37268af57a46a/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py">simple_cubemap_texture.py</a>.
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The <a class="reference internal" href="examples.html"><span class="doc">Examples</span></a> page links to more samples covering textures, graphs,
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memory mapping, and multi-GPU workflows.</p>
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<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>

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