Vessels: Efficient and Scalable Deep Learning Prediction on Trusted Processors, ACM Symposium on Cloud Computing (SoCC), Oct 2020 > International Papers

Vessels: Efficient and Scalable Deep Learning Prediction on Trusted Processors,

Kyungtae Kim, Chung Hwan Kim, Junghwan Rhee, Xiao Yu, Haifeng Chen, Dave Tian, and Byoungyoung Lee.

ACM Symposium on Cloud Computing (SoCC) 2020

0
0

Privacy Enhancing Computing HEPIC: Private Inference over Homomorphic Encryption with Client Intervention, ASPLOS 2026

Privacy Enhancing Computing Towards an Efficient Dataflow-flexible Accelerator by Finding Optimal Dataflows of DNNs, Future Generation Computer Systems, Sep 2025

Privacy Enhancing Computing An Accelerator for Low-computational Overhead Privacy-Preserving GNN Inference, HiPC 2025

Privacy Enhancing Computing SLOTHE: Lazy Approximation of Non-Arithmetic Neural Network Functions over Encrypted Data, USENIX Security 2025

Privacy Enhancing Computing Affinity-based Optimizations for TFHE on Processing-in-DRAM, ASPLOS 2025 Affinity-based Optimizations for TFHE on Processing-in-DRAM, ASPLOS 2025

Privacy Enhancing Computing LOHEN: Layer-wise Optimizations for Neural Network Inferences over Encrypted Data with high Performance or Accuracy, USENIX Security 2025

Privacy Enhancing Computing Affinity-based Optimizations of Homomorphic Encryption Operations on Processing-in-DRAM, DAC WIP 2024