A server-side CKKS GPU library fully interoperable with OpenFHE.
-
Updated
Jul 22, 2026 - Cuda
A server-side CKKS GPU library fully interoperable with OpenFHE.
Open-source FHE client and toolchain. Build fully homomorphic encryption applications with the nb DSL, instrumented OpenFHE, FHETCH API or a CUDA-style library API, record one Polynomial IR trace, and deploy to the Niobium accelerator
Harness and example implementation the FHE fetch-by-similarity workload
A Skill for Anthropic Claude that enables Claude users to more easily create secure computation applications that use fully homomorphic encryption. The initial commit demonstrates an 11% improvement over non-skill Claude in satisfying application goals, at a cost increase of roughly 50% in tokens on the test suite.
Reference implementation of the BHDR regression kernel: BSGS-hoisted diagonal Kernel SHAP regression under CKKS FHE.
FHE Oracle — adversarial precision testing for Fully Homomorphic Encryption. Open-source edition (AGPL-3.0).
Unified attack-replay regression harness for FHE libraries (SEAL, OpenFHE, Lattigo, tfhe-rs).
Drop-in encrypted Fairlearn metrics over CKKS. Same API surface; ciphertext arithmetic via TenSEAL or OpenFHE.
Docker base image with pre-built OpenFHE libraries for creating language bindings and applications. Ready-to-use development environment for homomorphic encryption projects.
A Benchmarking Framework for Fully Homomorphic Encryption Libraries
Proxy simulation for evaluating encrypted LLM accuracy without running full CKKS inference. IIT Big Data X REU 2025, eScience 2025.
GPU-accelerated homomorphic blind vector recall for OpenFHE CKKS via FIDESlib. Encrypted cosine recall from minutes to single-digit seconds per query, bit-exact, with the secret key never on the GPU.
Research prototype for real Mamba-2-130M inference under CKKS/FHE (OpenFHE/FIDESlib-GPU): +0.12% PPL surrogate and a verified 24-layer, 3-token encrypted B300 path.
Application of Homomorphic Encryption for Financial Services
FPGA accelerator for exact OpenFHE DCRTPoly polynomial multiplication in Z_q[X]/(X^4096+1), on a PYNQ-Z2 (XC7Z020)
An Experimental FHE+iO Unification System
Privacy-preserving neural networks in C++ using OpenFHE. Analyzes performance impact (runtime/memory) on encrypted training and inference.
Add a description, image, and links to the openfhe topic page so that developers can more easily learn about it.
To associate your repository with the openfhe topic, visit your repo's landing page and select "manage topics."