System on Chip

Systems-on-a-chip (SoCs) integrate multiple functionalities onto a single chip, demanding efficient design, verification, and security. Current research emphasizes improving verification methodologies through machine learning, particularly reinforcement learning and attention-based models, to accelerate testing and bug localization, while also exploring efficient hardware architectures for AI and signal processing tasks, including novel neural network accelerators and optimized communication strategies. These advancements are crucial for creating more powerful, energy-efficient, and reliable SoCs for applications ranging from neurotechnology and robotics to mobile devices and IoT.