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TAAS: a timing-aware analytical strategy for AQFP-capable placement automation

Peiyan Dong, Yanyue Xie, Hongjia Li, Mengshu Sun, Olivia Chen, Nobuyuki Yoshikawa, Yanzhi Wang

2022Year
7Citations
1Top-tier citations

Abstract

Adiabatic Quantum-Flux-Parametron (AQFP) is a superconducting logic with extremely high energy efficiency. AQFP circuits adopt the deep pipeline structure, where the four-phase AC-power serves as both the energy supply and the clock signal and transfers the data from one clock phase to the next. However, the deep pipeline structure causes the stage delay of the data propagation is comparable to the delay of the zigzag clocking, which triggers timing violations easily. In this paper, we propose a timing-aware analytical strategy for the AQFP placement, TAAS, that immensely reduces timing violations under specific spacing constraints and wirelength constraints of AQFP. TAAS includes two main characteristics: 1) a timing-aware objective function that incorporates a four-phase timing model for the analytical global placement. 2) a unique detailed placement including the timing-aware dynamic programming technique and the time-space cell regularization. To validate the effectiveness of TAAS, various representative circuits are adopted as benchmarks. As shown in the experimental results, our strategy can increase the maximum operating frequency by up to 30% 40% with a negligible wirelength increase -3.41% 1%.

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