Quantum computing is an emerging technology on the verge of reshaping industries, while simultaneously challenging existing cryptographic algorithms. FALCON, a recent standard quantum-resistant digital signature, presents a challenging hardware implementation due to its extensive non-integer polynomial operations, necessitating FFT over the ringQ[x]/(xⁿ+1). This paper introduces an ultra-low-power and compact processor tailored for FFT/IFFT operations over the ring for efficient FALCON implementation. The proposed processor incorporates various optimization techniques, including twiddle factor compression and conflict-free scheduling. In an ASIC implementation using a 22 nm GF process, the proposed processor demonstrates an area occupancy of 0.15 mm²and a power consumption of 12.6 mW/28.1 mW at an operating frequency of 167 MHz/500 MHz for the non-pipelined/pipelined version of the processor. Since a hardware implementation of FFT/IFFT over the ring is currently non-existent, the execution time achieved by this processor is compared to the reference software implementation of FFT/IFFT of FALCON on a Raspberry Pi 4 with Cortex-A72, where the proposed pipelined processor achieves a speedup up to 3.8×. Furthermore, in comparison to dedicated state-of-the-art hardware accelerators for classic FFT, the pipelined architecture occupies 42% less area and consumes 64% less power, on average. The quantified speedup in the context of FALCON suggests that the proposed hardware design offers a promising solution for the efficient implementation of FALCON.
No takes yet. Share an insight, caveat, or question.
Alsuhli et al. (2024) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: