Circuit Design and Machine Learning are an interestingly correlated duo. To improve the compute resources required for running Large Language Models (LLMs), we require that ICs are fabricated more quickly and efficiently and are also energy efficient. The traditionl IC Design route is often long and tiring ranging from 6 months to over an year. The efficient use of ML algorithms such as Gradient Descent and Reinforcement Learning can make this process faster.
To explore how ML algorithms can improve IC Design techniques, I collaborated with Prof. Sankaran Aniruddhan during my Junior year at IIT Madras. Our work on the same is published in IEEE and was presented at MWSCAS’ 25 at Michigan.
Elegant circuit design principles can help in designing better AI hardware. During Fall 24, I enrolled in Neuromorphic Computing to learn about efficient circuit design techniques to accelerate Machine Learning Hardware. Is the future of AI in analog computing? Learn more here.