Hardware Design
Hardware design research currently focuses on improving efficiency and automation across various domains, from AI accelerators to general-purpose processors. Key areas include developing novel architectures for neuro-symbolic AI, leveraging machine learning (particularly graph neural networks and large language models) for automated design and optimization, and exploring efficient approximate computing techniques. These advancements aim to address challenges in speed, power consumption, and design complexity, ultimately impacting the development of faster, more energy-efficient, and reliable hardware for diverse applications.
Papers
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