First version of cuda.bindings.path_finder

cuda_bindings/cuda/bindings/_path_finder/README.md

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+# `cuda.bindings.path_finder` Module
+
+## Public API (Work in Progress)
+
+Currently exposes two primary interfaces:
+
+```
+cuda.bindings.path_finder._SUPPORTED_LIBNAMES  # ('nvJitLink', 'nvrtc', 'nvvm')
+cuda.bindings.path_finder._load_nvidia_dynamic_library(libname: str) -> LoadedDL
+```
+
+**Note:**
+These APIs are prefixed with an underscore because they are considered
+experimental while undergoing active development, although already
+reasonably well-tested through CI pipelines.
+
+## Library Loading Search Priority
+
+The `load_nvidia_dynamic_library()` function implements a hierarchical search
+strategy for locating NVIDIA shared libraries:
+
+0. **Check if a library was loaded into the process already by some other means.**
+   - If yes, there is no alternative to skipping the rest of the search logic.
+     The absolute path of the already loaded library will be returned, along
+     with the handle to the library.
+
+1. **Python Package Ecosystem**
+   - Scans `sys.path` to find libraries installed via NVIDIA Python wheels.
+
+2. **Conda Environments**
+   - Leverages Conda-specific paths through our fork of `get_cuda_paths()`
+     from numba-cuda.
+
+3. **Environment variables**
+   - Relies on `CUDA_HOME`/`CUDA_PATH` environment variables if set.
+
+4. **System Installations**
+   - Checks traditional system locations through these paths:
+     - Linux: `/usr/local/cuda/lib64`
+     - Windows: `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.Y\bin`
+       (where X.Y is the CTK version)
+   - **Notably does NOT search**:
+     - Versioned CUDA directories like `/usr/local/cuda-12.3`
+     - Distribution-specific packages (RPM/DEB)
+       EXCEPT Debian's `nvidia-cuda-toolkit`
+
+5. **OS Default Mechanisms**
+   - Falls back to native loader:
+     - `dlopen()` on Linux
+     - `LoadLibraryW()` on Windows
+
+Note that the search is done on a per-library basis. There is no centralized
+mechanism that ensures all libraries are found in the same way.
+
+## Implementation Philosophy
+
+The current implementation balances stability and evolution:
+
+- **Baseline Foundation:** Uses a fork of numba-cuda's `cuda_paths.py` that has been
+  battle-tested in production environments.
+
+- **Validation Infrastructure:** Comprehensive CI testing matrix being developed to cover:
+  - Various Linux/Windows environments
+  - Python packaging formats (wheels, conda)
+  - CUDA Toolkit versions
+
+- **Roadmap:** Planned refactoring to:
+  - Unify library discovery logic
+  - Improve maintainability
+  - Better enforce search priority
+  - Expand platform support
+
+## Maintenance Requirements
+
+These key components must be updated for new CUDA Toolkit releases:
+
+- `supported_libs.SUPPORTED_LIBNAMES`
+- `supported_libs.SUPPORTED_WINDOWS_DLLS`
+- `supported_libs.SUPPORTED_LINUX_SONAMES`
+- `supported_libs.EXPECTED_LIB_SYMBOLS`