EFFACT: A Highly Efficient Full-Stack FHE Acceleration Platform

Fuente: arXiv
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Autori principali: Huang, Yi, Gong, Xinsheng, Kong, Xiangyu, Chen, Dibei, Zhu, Jianfeng, Zhu, Wenping, Li, Liangwei, Gao, Mingyu, Wei, Shaojun, Zhang, Aoyang, Liu, Leibo
Natura: Preprint
Pubblicazione: 2025
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author Huang, Yi
Gong, Xinsheng
Kong, Xiangyu
Chen, Dibei
Zhu, Jianfeng
Zhu, Wenping
Li, Liangwei
Gao, Mingyu
Wei, Shaojun
Zhang, Aoyang
Liu, Leibo
author_facet Huang, Yi
Gong, Xinsheng
Kong, Xiangyu
Chen, Dibei
Zhu, Jianfeng
Zhu, Wenping
Li, Liangwei
Gao, Mingyu
Wei, Shaojun
Zhang, Aoyang
Liu, Leibo
contents Fully Homomorphic Encryption (FHE) is a set of powerful cryptographic schemes that allows computation to be performed directly on encrypted data with an unlimited depth. Despite FHE's promising in privacy-preserving computing, yet in most FHE schemes, ciphertext generally blows up thousands of times compared to the original message, and the massive amount of data load from off-chip memory for bootstrapping and privacy-preserving machine learning applications (such as HELR, ResNet-20), both degrade the performance of FHE-based computation. Several hardware designs have been proposed to address this issue, however, most of them require enormous resources and power. An acceleration platform with easy programmability, high efficiency, and low overhead is a prerequisite for practical application. This paper proposes EFFACT, a highly efficient full-stack FHE acceleration platform with a compiler that provides comprehensive optimizations and vector-friendly hardware. We start by examining the computational overhead across different real-world benchmarks to highlight the potential benefits of reallocating computing resources for efficiency enhancement. Then we make a design space exploration to find an optimal SRAM size with high utilization and low cost. On the other hand, EFFACT features a novel optimization named streaming memory access which is proposed to enable high throughput with limited SRAMs. Regarding the software-side optimization, we also propose a circuit-level function unit reuse scheme, to substantially reduce the computing resources without performance degradation. Moreover, we design novel NTT and automorphism units that are suitable for a cost-sensitive and highly efficient architecture, leading to low area. For generality, EFFACT is also equipped with an ISA and a compiler backend that can support several FHE schemes like CKKS, BGV, and BFV.
format Preprint
id arxiv_https___arxiv_org_abs_2504_15817
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle EFFACT: A Highly Efficient Full-Stack FHE Acceleration Platform
Huang, Yi
Gong, Xinsheng
Kong, Xiangyu
Chen, Dibei
Zhu, Jianfeng
Zhu, Wenping
Li, Liangwei
Gao, Mingyu
Wei, Shaojun
Zhang, Aoyang
Liu, Leibo
Cryptography and Security
Hardware Architecture
Fully Homomorphic Encryption (FHE) is a set of powerful cryptographic schemes that allows computation to be performed directly on encrypted data with an unlimited depth. Despite FHE's promising in privacy-preserving computing, yet in most FHE schemes, ciphertext generally blows up thousands of times compared to the original message, and the massive amount of data load from off-chip memory for bootstrapping and privacy-preserving machine learning applications (such as HELR, ResNet-20), both degrade the performance of FHE-based computation. Several hardware designs have been proposed to address this issue, however, most of them require enormous resources and power. An acceleration platform with easy programmability, high efficiency, and low overhead is a prerequisite for practical application. This paper proposes EFFACT, a highly efficient full-stack FHE acceleration platform with a compiler that provides comprehensive optimizations and vector-friendly hardware. We start by examining the computational overhead across different real-world benchmarks to highlight the potential benefits of reallocating computing resources for efficiency enhancement. Then we make a design space exploration to find an optimal SRAM size with high utilization and low cost. On the other hand, EFFACT features a novel optimization named streaming memory access which is proposed to enable high throughput with limited SRAMs. Regarding the software-side optimization, we also propose a circuit-level function unit reuse scheme, to substantially reduce the computing resources without performance degradation. Moreover, we design novel NTT and automorphism units that are suitable for a cost-sensitive and highly efficient architecture, leading to low area. For generality, EFFACT is also equipped with an ISA and a compiler backend that can support several FHE schemes like CKKS, BGV, and BFV.
title EFFACT: A Highly Efficient Full-Stack FHE Acceleration Platform
topic Cryptography and Security
Hardware Architecture
url https://arxiv.org/abs/2504.15817