Benchmark Circuit

Benchmark circuits are standardized test cases used to evaluate the performance of algorithms and tools in electronic design automation (EDA), focusing on optimizing circuit design for metrics like size, speed, and power consumption. Current research emphasizes the application of machine learning, particularly employing transformer networks, U-Net variants, and reinforcement learning, to improve various EDA tasks such as logic synthesis, test generation, and routability prediction. These advancements aim to accelerate and enhance the design process for increasingly complex integrated circuits, leading to more efficient and reliable hardware.