ABC-FHE: A Resource-Efficient Accelerator Enabling Bootstrappable Parameters for Client-Side Fully Homomorphic Encryption

As the demand for privacy-preserving computation continues to grow, fully homomorphic encryption (FHE)—which enables continuous computation on encrypted data—has become a critical solution. However, its adoption is hindered by significant computational overhead, requiring 10000-fold more computation compared to plaintext processing. Recent advancements in FHE accelerators have successfully improved server-side performance, but client-side computations remain a bottleneck, particularly under bootstrappable parameter configurations, which involve combinations of encoding, encrypt, decoding, and decrypt for large-sized parameters. To address this challenge, we propose ABC-FHE, an area- and power-efficient FHE accelerator that supports bootstrappable parameters on the client side. ABCFHE employs a streaming architecture to maximize performance density, minimize area usage, and reduce off-chip memory access. Key innovations include a reconfigurable Fourier engine capable of switching between NTT and FFT modes. Additionally, an onchip pseudo-random number generator and a unified on-the-fly twiddle factor generator significantly reduce memory demands, while optimized task scheduling enhances the CKKS clientside processing, achieving reduced latency. Overall, ABC-FHE occupies a die area of 28.638 mm2 and consumes 5.654 W of power in 28 nm technology. It delivers significant performance improvements, achieving a 1112× speed-up in encoding and encryption execution time compared to a CPU, and 214× over the state-of-the-art client-side accelerator. For decoding and decryption, it achieves a 963× speed-up over the CPU and 82× over the state-of-the-art accelerator.