Hyena: Balancing Packing, Reuse, and Rotations for Encrypted Inference
Author:
Affiliation:
1. University of Utah,Kahlert School of Computing,Salt Lake City,Utah
2. Rutgers University,Department of Computer Science,New Brunswick,New Jersey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10646615/10646598/10646772.pdf?arnumber=10646772
Reference71 articles.
1. Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference
2. {GAZELLE}: A low latency framework for secure neural network inference;Juvekar;{USENIX} Security Symposium,2018
3. Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy;Gilad-Bachrach;International conference on machine learning,2016
4. F1: A Fast and Programmable Accelerator for Fully Homomorphic Encryption
5. Delphi
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