Ruijiang Gao

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers

Ligong Han, Kai Xu, Hao Wang, Ruijiang Gao, Han Gao, Akash Srivastava

Fully homomorphic encryption (FHE) enables computation on encrypted data, but practical encrypted Transformer inference is bottlenecked by the sequential composition of many nonlinear blocks. We study whether Structured Newton Layer Parallelism (SNLP) can make this inter-layer co…Read more