8 papers
WHET: Welding Homomorphic Encryption to Accelerator Architectures
Jongmin Kim, Hyesung Ji, Wonseok Choi +2
Fully homomorphic encryption (FHE) enables computations on encrypted data without decryption, offering strong data privacy at the expense of substantial computational and memory ov…
VIPIR: A Versatile GPU Framework for Integrating Private Information Retrieval Protocols
Jongmin Kim, Hyesung Ji, Jean-Luc Watson +3
While private information retrieval (PIR) enables private database services by fully concealing access patterns, it simultaneously requires high computational throughput, large mem…
GPIR: Enabling Practical Private Information Retrieval with GPUs
Hyesung Ji, Hyunah Yu, Jongmin Kim +3
Private information retrieval (PIR) allows private database queries; however, it is hindered by intense server-side computation and memory traffic. Numerous modern lattice-based PI…
Theodosian: A Deep Dive into Memory-Hierarchy-Centric FHE Acceleration
Wonseok Choi, Hyunah Yu, Jongmin Kim +3
Fully homomorphic encryption (FHE) enables secure computation on encrypted data, mitigating privacy concerns in cloud and edge environments. However, due to its high compute and me…
Rethinking LLM Inference Bottlenecks: Insights from Latent Attention and Mixture-of-Experts
Sungmin Yun, Seonyong Park, Hwayong Nam +10
Computational workloads composing traditional transformer models are starkly bifurcated. Multi-Head Attention (MHA) and Grouped-Query Attention are memory-bound due to low arithmet…
IVE: An Accelerator for Single-Server Private Information Retrieval Using Versatile Processing Elements
Sangpyo Kim, Hyesung Ji, Jongmin Kim +3
Private information retrieval (PIR) is an essential cryptographic protocol for privacy-preserving applications, enabling a client to retrieve a record from a server's database with…