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Release v13.3 of the CUDA samples with CUDA 13.3 Toolkit (#435)
This is the release of the CUDA 13.3 samples, which include additions for CUDA Tile C++, and updated CCCL and Python samples.
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@@ -106,10 +106,19 @@ When returning a zero-copy view, the caller must close the buffers after use (e.
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- CUDA Toolkit 13.0 or newer
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- Python 3.10 or newer
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- `cuda-python` package (13.0.0+)
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- `cuda-core` package (>=0.6.0)
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- `cuda-core` package (>=1.0.0)
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- `numpy` package (>=2.3.2)
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- `pillow` package (10.0.0+)
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### Platform Support:
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This sample relies on `ManagedMemoryResource` with **concurrent host access**
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to managed allocations while GPU kernels are in flight. That behavior
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requires the device property `concurrent_managed_access=True`, which is only
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supported on Linux with HMM (Pascal and newer). On Windows (WDDM/MCDM/TCC)
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the property is `False`, so the sample exits early with a waive message and
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exit code `2` instead of attempting a run that would crash the process.
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## Installation
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```bash
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@@ -142,8 +142,8 @@ def blur_image_unified_memory(
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mr = ManagedMemoryResource(options)
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# Allocate unified memory buffers for source and destination images
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src_buf = mr.allocate(n_bytes, stream)
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dst_buf = mr.allocate(n_bytes, stream)
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src_buf = mr.allocate(n_bytes, stream=stream)
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dst_buf = mr.allocate(n_bytes, stream=stream)
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try:
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# Synchronize to ensure allocations are complete before CPU access
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stream.sync()
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@@ -197,6 +197,14 @@ def main():
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3. Unified memory with cuda.core.ManagedMemoryResource
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4. Kernel launch with cuda.core.launch and LaunchConfig
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"""
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if sys.platform == "win32":
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print(
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"This sample relies on ManagedMemoryResource with concurrent host "
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"access, which is not supported on Windows "
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"(concurrent_managed_access=False). Waiving this sample."
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)
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sys.exit(2)
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print("=" * 60)
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print("Image Blur with Unified Memory (cuda.core)")
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print("=" * 60)
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@@ -1,6 +1,6 @@
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# Image Blur with Unified Memory Sample Requirements
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cuda-python>=13.0.0
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cuda-core>=0.6.0
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cuda-core>=1.0.0
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numpy>=2.3.2
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pillow>=10.0.0
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