4 papers
FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption
Lohit Daksha, Seyda Guzelhan, Kaustubh Shivdikar +10
Fully Homomorphic Encryption (FHE) enables computation directly on encrypted data but incurs massive computational and memory overheads, often exceeding plaintext execution by seve…
FIDESlib: A Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs
Carlos Agulló-Domingo, Óscar Vera-López, Seyda Guzelhan +7
Word-wise Fully Homomorphic Encryption (FHE) schemes, such as CKKS, are gaining significant traction due to their ability to provide post-quantum-resistant, privacy-preserving appr…
NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator
Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera +5
Graph Neural Networks (GNNs) are emerging as a formidable tool for processing non-euclidean data across various domains, ranging from social network analysis to bioinformatics. Des…
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption
Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal +9
Fully Homomorphic Encryption (FHE) enables the processing of encrypted data without decrypting it. FHE has garnered significant attention over the past decade as it supports secure…