结合两级和多级近似逻辑综合的数字电路设计评价

Gabriel Ammes, P. Butzen, A. Reis, Renato P. Ribas
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引用次数: 0

摘要

近似电路正在成为机器学习、计算机视觉和信号处理等抗错误应用中节省面积、延迟和功耗的替代方案。这项工作通过探索近似数字电路设计中的两级和多级拓扑来评估逻辑综合方法。在这种策略中,两级(2L)近似逻辑综合(ALS)解锁了鲁棒函数优化,而多级(ML) ALS在结构简化上起作用。实验结果表明,与最先进的ML-ALS相比,2L- als和ML-ALS的平均面积和延迟优化改善了5%的错误率,在相同的误差约束下,电路面积减少了37%,延迟减少了31%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of Digital Circuit Design by Combining Two - and Multi-Level Approximate Logic Synthesis
Approximate circuits are emerging as an alternative to save area, delay, and power consumption in error-resilient applications such as machine learning, computer vision, and signal processing. This work presents an evaluation of a logic synthesis approach by exploring two- and multi-level topologies in approximating digital circuit design. In such a strategy, two-level (2L) approximated logic synthesis (ALS) unlocks robust function optimization, whereas multi-level (ML) ALS acts over the structure simplification. Experimental results of combined exploitation of 2L- and ML-ALS have shown improvement in the average area and delay optimization compared to the state-of-the-art ML-ALS for 5% of error rate, being a reduction of up to 37% in circuit area and up to 31% in delay for the same error constraint.
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