Timing-Driven Approximate Logic Synthesis Based on Double-Chase Grey Wolf Optimizer
Xinyi Hu, Yuyang Ye, Tinghuan Chen, Hao Yan, Bei Yu · 2025
With the shrinking technology nodes, timing optimization becomes increasingly challenging. Approximate logic synthesis (ALS) can perform local approximate changes (LACs) on circuits to optimize timing with the cost of slight inaccuracy. However, existing ALS methods that focus solely on critical path depth reduction or area minimization are not optimal in timing optimization. This paper proposes an effective timing-driven ALS framework, where we employ a double-chase grey wolf optimizer to explore and apply LACs, simultaneously bringing excellent critical path shortening and area reduction under error constraints. Subsequently, it utilizes post-optimization under area constraints to convert area reduction into further timing improvement, thus achieving maximum critical path delay reduction. According to experiments on open-source circuits with 28nm technology, compared to the SOTA method, our framework can generate approximate circuits with greater critical path delay reduction under different error and area constraints.