Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference
2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)(2021)
摘要
As the application of deep learning continues to grow, so does the amount of data used to make predictions. While traditionally big-data deep learning was constrained by computing performance and off-chip memory bandwidth, a new constraint has emerged: privacy. One solution is homomorphic encryption (HE). Applying HE to the client-cloud model allows cloud services to perform inferences directly on...
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关键词
Deep learning,Privacy,Accelerator architectures,Seals,Real-time systems,Inference algorithms,Encryption
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