This project presents gECC, a versatile framework for ECC optimized for GPU architectures, specifically engineered to achieve high-throughput performance in EC operations. To maximize throughput, gECC incorporates batch-based execution (using Montgomery’s trick) of EC operations and microarchitecture-level optimization of modular arithmetic. For more details, please refer to our preprint gECC available on arXiv.
Copyright (C) 2024, BDTS/STCS/CGCL and Huazhong University of Science and Technology.
| Files | description |
|---|---|
| test | all performance analysis benchmarks |
| scripts | define finite field related parameters, generate test data for benchmark. |
| gecc/arith | implemente ec operation (with multiple coordinate system) and modular operation on finite filed |
| gecc/ecdsa | implemente ECDSA algorithm |
wget https://github.com/google/googletest/archive/release-1.10.0.tar.gz
tar xzvf release-1.10.0.tar.gz
cmake -BBuild -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=${HOME}/.local/opt/gtest .
cmake --build Build --target install
export GTEST_ROOT=${HOME}/.local/opt/gtest
To evaluate performance:
python3 ./dev-support/build.py -R -A 80
./bench.sh
gECC is developed in National Engineering Research Center for Big Data Technology and System, Cluster and Grid Computing Lab, Services Computing Technology and System Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China by Qian Xiong(qianxiong@hust.edu.cn), Weiliang Ma(weiliangma@hust.edu.cn) and Xuanhua Shi(xhshi@hust.edu.cn).
If you have any questions, please contact Qian Xiong(qianxiong@hust.edu.cn), Weiliang Ma(weiliangma@hust.edu.cn) and Xuanhua Shi(xhshi@hust.edu.cn). We welcome you to commit your modification to support our project.