HECATE: Performance-Aware Scale Optimization for Homomorphic Encryption Compiler
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Date
2022
Publication Type
Conference Paper
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yes
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Abstract
Despite the benefit of Fully Homomorphic Encryption (FHE) that supports encrypted computation, writing an efficient FHE application is challenging due to magnitude scale management. Each FHE operation increases scales of ciphertext and leaving the scales high harms performance of the following FHE operations. Thus, resealing ciphertext is inevitable to optimize an FHE application, but since FHE requires programmers to match the resealing levels of operands of each FHE operation, programmers should rescale ciphertext reflecting the entire FHE application. Although recently proposed FHE compilers reduce the programming burden by automatically manipulating ciphertext scales, they fail to fully optimize the FHE application because they greedily rescale the ciphertext without considering their performance impacts throughout the entire application.
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published
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Book title
2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
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Pages / Article No.
193 - 204
Publisher
IEEE
Event
IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2022)
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Methods
Software
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Subject
Homomorphic encryption; Compiler; privacy-preserving machine learning; deep learning