Core algorithms for operators and graph of the AIDGE framework
Project description
Aidge Backend CUDA
Aidge Backend CUDA is the implementation library for CUDA-based operators within the Aidge framework.
Quick Start
Prerequisite:
aidge_core
pip install aidge-backend-cuda
[!WARNING] It is highly recommended to build this module from source rather than using the pypi package.
🛠 Build from Source
Prerequisite (in addition to previous one):
- Please review the global installation instructions before proceeding.
- If using a virtual environment, use the same one for all Aidge modules.
- CUDA ToolKit 12.6
12.4.1is the strict minimum, but12.6+is recommended.
- CUDnn9
- make sure to install the CUDA 12 compatible version
[!TIP] On Windows at least, CUDnn9 headers and libraries needs to be findable. One way is to add files from CUDnn to CUDA in their respective
bin/,lib/andinclude/. Or you could add these folders to your path.
1. Python or C++ installation using setup scripts
| Environment | C++ Development | Python Development |
|---|---|---|
| Windows | .\setup.ps1 -Modules backend_cuda -Tests -CppOnly |
.\setup.ps1 -Modules backend_cuda -Tests |
| Unix | ./setup.sh -m backend_cuda --tests --cpp-only |
./setup.sh -m backend_cuda --tests |
[!TIP] Use
Get-Help setup.ps1(Windows) or./setup.sh -h(Unix) for full documentation.
2. Python Installation using pip
Run these commands from the aidge_backend_cuda/ directory:
# Standard install
pip install . -v
# Install with testing dependencies
pip install .[test] -v && pytest
Editable Install (Experimental)
Use this for real-time development without re-installing.
pip install --no-build-isolation -ve . --config-settings=editable.rebuild=true -Cbuild-dir=build
3. C++ Installation (CMake)
A CMakePresets.json is provided for standard configurations.
# Configure, Build, and Install
cmake --preset clang-debug
cmake --build --preset clang-debug
cmake --install
# Run C++ Tests
ctest --test-dir build/
[!TIP] Create a
CMakeUserPresets.jsonto define your own local build configurations.
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