@@ -28,9 +28,13 @@ strategy for locating NVIDIA shared libraries:
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- Scans ` sys.path ` to find libraries installed via NVIDIA Python wheels.
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2 . ** Conda Environments**
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- - Leverages Conda-specific paths through our fork of ` get_cuda_paths() ` from Numba.
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+ - Leverages Conda-specific paths through our fork of ` get_cuda_paths() `
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+ from numba-cuda.
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- 3 . ** System Installations**
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+ 3 . ** Environment variables**
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+ - Relies on ` CUDA_HOME ` /` CUDA_PATH ` environment variables if set.
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+
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+ 4 . ** System Installations**
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- Checks traditional system locations through these paths:
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- Linux: ` /usr/local/cuda/lib64 `
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- Windows: ` C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.Y\bin `
@@ -39,10 +43,8 @@ strategy for locating NVIDIA shared libraries:
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- Versioned CUDA directories like ` /usr/local/cuda-12.3 `
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- Distribution-specific packages (RPM/DEB)
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EXCEPT Debian's ` nvidia-cuda-toolkit `
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- - Relies on ` CUDA_HOME ` /` CUDA_PATH ` environment variables if set, but falls
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- back to hardcoded paths when unset
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- 4 . ** OS Default Mechanisms**
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+ 5 . ** OS Default Mechanisms**
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- Falls back to native loader:
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- ` dlopen() ` on Linux
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- ` LoadLibraryW() ` on Windows
@@ -54,8 +56,8 @@ mechanism that ensures all libraries are found in the same way.
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The current implementation balances stability and evolution:
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- - ** Baseline Foundation:** Uses a fork of Numba 's ` cuda_paths.py ` that has been
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- battle-tested in production environments
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+ - ** Baseline Foundation:** Uses a fork of numba-cuda 's ` cuda_paths.py ` that has been
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+ battle-tested in production environments.
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- ** Validation Infrastructure:** Comprehensive CI testing matrix being developed to cover:
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- Various Linux/Windows environments
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