HECATE: Performance-Aware Scale Optimization for Homomorphic Encryption Compiler

Yongwoo Lee, Seonyeong Heo, Seonyoung Cheon, Shinnung Jeong, Changsu Kim, Eunkyung Kim, Dongyoon Lee, Hanjun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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, rescaling ciphertext is inevitable to optimize an FHE application, but since FHE requires programmers to match the rescaling 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. This work proposes HECATE, a new FHE compiler framework that optimizes scales of ciphertext reflecting their rescaling levels and performance impact. With a new type system that embeds the scale and rescaling level, and a new rescaling operation called downscale, HECATE makes various scale management plans, analyzes their expected performance, and finds the optimal rescaling points throughout the entire FHE application. This work implements HECATE on top of the MLIR framework with a Python frontend and shows that HECATE achieves 27% speedup over the state-of-The-Art approach for various FHE applications.

Original languageEnglish
Title of host publicationCGO 2022 - Proceedings of the 2022 IEEE/ACM International Symposium on Code Generation and Optimization
EditorsJae W. Lee, Sebastian Hack, Tatiana Shpeisman
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-204
Number of pages12
ISBN (Electronic)9781665405843
DOIs
Publication statusPublished - 2022
Event20th IEEE/ACM International Symposium on Code Generation and Optimization, CGO 2022 - Seoul, Korea, Republic of
Duration: 2022 Apr 22022 Apr 6

Publication series

NameCGO 2022 - Proceedings of the 2022 IEEE/ACM International Symposium on Code Generation and Optimization

Conference

Conference20th IEEE/ACM International Symposium on Code Generation and Optimization, CGO 2022
Country/TerritoryKorea, Republic of
CitySeoul
Period22/4/222/4/6

Bibliographical note

Funding Information:
We thank the anonymous reviewers for their valuable feedback. We also thank the CoreLab members for their support and feedback during this work. This work is supported by IITP-2020-0-01847, IITP-2020-0-01361 and IITP-2021-0-00853 through the Institute of Information and Communication Technology Planning and Evaluation (IITP) funded by the Ministry of Science and ICT. This work is also supported by Samsung SDS. (Corresponding author: Hanjun Kim)

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Control and Optimization

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