he literature, we provide implementations of all three methods in GPU for leveled CKKS schemes. To ensure a fair comparison, we employ the most recent GPU implementation of the number-theoretic …

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.

Fully Homomorphic Encryption (FHE) enables privacy-preserving computation but is hindered by high computational overhead, with the key-switching operation being a primary performance bottleneck. …

Our solution, tested with varying numbers of mul-tiplicative depth, shows up to 26x performance improvement over non-accelerated implementations, proving the effectiveness of GPUs for FHE.

Jul 25, 2023 · Regardless of the performance benefits that can be achieved on a GPU platform, there are subtle challenges with GPU acceleration of FHE-based computing. We now perform a detailed …

Jul 31, 2024 · In this paper, we present a new approach to mitigate these challenges by integrating innovative data compression techniques, resulting in a staggering 90% reduction in data size.

In this work, we introduce FIDESlib, the first open-source server-side CKKS GPU library that is fully interoperable with well-established client-side OpenFHE operations.

For example, if we need to compute a*b*c*d, we can compute e=a*b and f=c*d using one level, and then compute e*f using the second level. Hence we use 2 levels (depth of 2) rather 3 if we were to do the …

This repository includes GPU implementations of the core functions for CKKS (e.g., base conversions, NTT, key-switching, etc.) to reproduce the results in the paper Over 100x Faster Bootstrapping in Fully …

The main HE schemes, such as BFV, BGV, and CKKS, work with large integers (polynomial coefficients), which are much larger than native word size. Many other non-HE primitives implemented in PALISADE …