Secure ML Design Priv AI & Lab

Catalog description

This course explores the in-depth cutting-edge intersection of hardware acceleration, cryptography, and machine learning. Students will study specialized hardware architectures optimized for privacy-preserving machine learning computations, including FPGAs, GPUs, and ASICs for homomorphic encryption and secure multi-party computation. The course covers hardware/software co-design principles, implementation of cryptographic primitives in hardware, and optimization techniques for reducing overhead.