Nappa: NNA-Compatible and Privacy-Preserving DNN Training Framework via Vector Decomposition

Nappa is a framework that protects data privacy during deep neural network (DNN, a type of AI model) training while working with specialized hardware accelerators (NNAs, custom chips that speed up neural networks). The framework uses vector decomposition (breaking down mathematical operations into simpler parts) to split computations across different hardware types, and includes an automatic compiler that converts AI models into encrypted computation graphs (mathematical instructions that run on encrypted data) that work on both trusted and untrusted hardware without losing speed or accuracy.