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MICRO2024顶会

UFC: A Unified Accelerator for Fully Homomorphic Encryption

Minxuan Zhou, Yujin Nam, Xuan Wang, Youhak Lee, Chris Wilkerson, Raghavan Kumar, Sachin Taneja, Sanu Mathew, Rosario Cammarota, Tajana Rosing

2024年份
19被引次数
5顶会引用

摘要

Fully homomorphic encryption (FHE) is crucial for post-quantum privacy-preserving computing. Researchers have proposed various FHE schemes that excel at different encrypted computations, such as single-instruction multiple-data (SIMD) arithmetic or arbitrary single-data functions. Hybrid-scheme FHE, which exploits appropriate schemes for specific tasks, is essential for real-world applications requiring optimal performance and accuracy. However, existing FHE accelerators only adopt scheme-specific custom designs, leading to inefficiency or lack of capability to support applications in hybrid FHE settings. In this work, we propose a Unified FHE aCcelerator (UFC) that provides better performance and cost-efficiency than prior scheme-specific accelerators on hybrid FHE applications. Our design process involves a comprehensive analysis of processing flows to abstract the primitives covering all operations in hybrid FHE applications. The UFC architecture primarily comprises hardware function units for these primitives, diverging from the deeply pipelined units in previous designs. This approach enables high hardware utilization across different FHE schemes. Further-more, we propose several algorithm-hardware co-optimizations to minimize the hardware cost of supporting various data shuffling patterns in FHE. This enables high-throughput implementation of function units that provide good cost efficiency. We also propose several compiler-level optimizations to achieve high hardware utilization of the unified architecture for computing FHE data in various algorithmic parameter settings. We evaluate the performance of UFC on different FHE programs, including scheme-specific and hybrid-scheme workloads. Our experiments show that UFC provides up to 6.0 × speedup and 1.6 × delay-energy-area efficiency improvement over state-of-the-art FHE accelerators.

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