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WHET: Welding Homomorphic Encryption to Accelerator Architectures

arXiv Security Archived Jun 11, 2026 ✓ Full text saved

arXiv:2606.11541v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables computations on encrypted data without decryption, offering strong data privacy at the expense of substantial computational and memory overheads. Prior efforts have steadily improved FHE performance through cryptographic and algorithmic enhancements or hardware acceleration, yet these two directions have progressed largely in isolation, hindering the full exploitation of available hardware capabilities. Th

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    Computer Science > Cryptography and Security [Submitted on 10 Jun 2026] WHET: Welding Homomorphic Encryption to Accelerator Architectures Jongmin Kim, Hyesung Ji, Wonseok Choi, Hyunah Yu, Jung Ho Ahn Fully homomorphic encryption (FHE) enables computations on encrypted data without decryption, offering strong data privacy at the expense of substantial computational and memory overheads. Prior efforts have steadily improved FHE performance through cryptographic and algorithmic enhancements or hardware acceleration, yet these two directions have progressed largely in isolation, hindering the full exploitation of available hardware capabilities. This work presents WHET, which introduces memory-centric, architecture-aware optimizations to better align cryptographic and algorithmic constructions with FHE accelerator architectures. We identify conventional FHE constructions as major sources of excessive working sets and heavy off-chip memory traffic. We propose accelerator-specific techniques, including fine-grained coefficient-to-slot transformation, plaintext compression, and intermediate modulus raising, to reduce the on-chip data footprint by minimizing temporary ciphertexts and plaintext loads. With these techniques applied, we observe additional opportunities to improve on-chip memory efficiency; hence, we introduce lightweight architectural refinements, including a special-purpose buffer and functional unit extensions. With these optimizations, WHET achieves 1.38-8.74\times per-area performance improvements over state-of-the-art FHE accelerators and the first-ever sub-millisecond CKKS bootstrapping. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2606.11541 [cs.CR]   (or arXiv:2606.11541v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.11541 Focus to learn more Submission history From: Jongmin Kim [view email] [v1] Wed, 10 Jun 2026 01:04:58 UTC (573 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
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    ◬ AI & Machine Learning
    Published
    Jun 11, 2026
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    Jun 11, 2026
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