A server-side CKKS GPU library fully interoperable with OpenFHE.

• Full CKKS implementation: Add, AddPt, AddScalar, Mult, MultPt, MultScalar, Square, Rotate, RotateHoisted, Bootstrap.
• OpenFHE interoperability for FIXEDMANUAL, FIXEDAUTO, FLEXIBLEAUTO and FLEXIBLEAUTOEXT.
• Hardware acceleration with Nvidia CUDA.
• High-performance NTT/INTT implementation.
• Hybrid Key-Switching.

If you use FIDESlib on your research, please cite our ISPASS paper.

@inproceedings{FIDESlib,
	title        = {{FIDESlib: A Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs}},
	author       = {Carlos Agulló-Domingo and Óscar Vera-López and Seyda Guzelhan and Lohit Daksha and Aymane El Jerari and Kaustubh Shivdikar and Rashmi Agrawal and David Kaeli and Ajay Joshi and José L. Abellán},
	year         = 2025,
	booktitle    = {2025 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
	publisher    = {IEEE},
	address      = {Ghent, Belgium},
	doi          = {https://doi.org/10.1109/ISPASS64960.2025.00045},
	url          = {https://github.com/CAPS-UMU/FIDESlib},
	note         = {Poster paper}
}

Ubuntu:

sudo apt install make build-essential cmake git libtbb-dev

In order to be able to compile the project, one must follow these steps:

git clone --recursive [email protected]:tiicrypto/tii-openfhe.git
cd tii-openfhe 
./build.sh

FIDESlib needs a patched version of OpenFHE in order to be able to access some internals needed for interoperability. This patched version will be automatically installed by the build.sh script

The build process produces the following artifacts:

• fideslib.a: The FIDESlib library to be statically linked to any client application.
• fideslib-test: The test suite executable.
• fideslib-bench: The benchmark suite executable.
• gpu-test: A dummy executable to search for the CUDA capable devices on the machine.
• dummy: Another dummy executable.

The following options can be used with CMake to configure the build. The default value for each option is denoted in boldface under the Values column:

Installing the library is as easy as running the following command:

cmake --build $PATH_TO_BUILD_DIR --target install -j

FIDESlib is currently ready to be consumed as a CMake library. The template project on the examples directory shows how to build and run a FIDESlib client application and contains examples of usage of most of the functionality provided by FIDESlib. Currently client applications consuming FIDESlib should use the CUDA compiler every time they include a FIDESlib header.

Note: all commands are prefixed with sudo, which may be not neccessary, as docker can be runned rootless. Additionally :W

In order to build the docker image, run the following command:

sudo docker build -t cuda-tests .

You can run binaries in the docker image via:

# Run tests
sudo docker run --rm --device=nvidia.com/gpu=all cuda-tests ./build/fideslib-test
# Run benchmarks
sudo docker run --rm --device=nvidia.com/gpu=all cuda-tests ./build/fideslib-bench

Check examples for projects that use FIDESlib.

Thanks to all main contributors:

• Carlos Agulló Domingo.
• Óscar Vera López.
• Seyda Guzelhan.
• Lohit Daksha.
• Aymane El Jerari.

This project was possible thanks to the following grants:

• Grant CNS2023-144241 funded by "MICIU/AEI/10.13039/501100011033" and the "European Union NextGenerationEU/PRTR".
• Grants NSF CNS 2312275 and 2312276, and supported in part from the NSF IUCRC Center for Hardware and Embedded Systems Security and Trust (CHEST).

If you have any question, comment, or suggestion, please contact:

• Carlos Agulló Domingo ([email protected]).
• Óscar Vera López ([email protected]).

Or feel free to open an issue or a general discussion on this repository.