Presentation
CHAM: A Customized Homomorphic Encryption Accelerator for Fast Matrix-Vector Product
DescriptionHomomorphic encryption (HE), enabling computation on encrypted data, suffers from poor performance due to enlarged data size and exploded amount of computation. Existing HE accelerators either target small HE operations (thus providing limited performance improvement for end-to-end applications) or fail to support fast-evolving HE algorithms. To better support various privacy-preserving applications (e.g., logistic regression and neural-network inference), we propose CHAM, an HE accelerator, for high-performance matrix-vector product, which can be easily extended to 2D/3D convolutions. Motivated by the evolution of algorithms, CHAM supports not only traditional HE operations, but also different types of ciphertexts and the conversion between them.
Event Type
Research Manuscript
TimeTuesday, July 11th4:40pm - 4:55pm PDT
Location3012, 3rd Floor
Security
Hardware Security: Primitives, Architecture, Design & Test