Timing-driven Approximate Logic Synthesis Based on Cooperative Search
Approximate logic synthesis (ALS) is a promising design paradigm for error-resilient applications. It can automatically generate circuits with optimized delay, area, and power at the cost of small errors. Existing methods mainly apply local approximate changes (LACs) to shorten critical paths or reduce area. However, given the large search space of LACs, they struggle to achieve a good trade-off between both objectives. This restricts the timing optimization potential of approximate circuits, particularly since area savings can be reinvested to enhance the drive strength of timing-critical gates. This paper leverages population-based search to explore LACs with positive timing influence in parallel. We develop two LAC search actions specialized in critical path shortening and area reduction, respectively. Guided by a recommender system aware of circuit topology and quality, individuals iteratively execute suitable LAC search actions and refine their explored LAC sets by conflict-free combinations, thus balancing reductions in critical path depth and area. Area savings are then reinvested to enhance the drive strength of timing-critical gates, enabling further timing improvement. Experimental results show that compared to a state-of-the-art area-driven method, our framework further reduces 20.3% critical path delay with comparable area savings, while being 7.9× faster.