Efficient Analog Integrated Circuit Sizing with GenAI
Exploring Generative Diffusion Models
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Beschreibung
This book focuses on the automation of analog integrated circuit design, particularly the sizing process. It introduces an innovative approach leveraging generative artificial intelligence, specifically denoising diffusion probabilistic models (DDPM). The proposed methodology provides a robust solution for generating circuit designs that meet specific performance constraints, offering a significant improvement over conventional techniques. By integrating advanced machine learning models into the design workflow, the book showcases a transformative way to streamline the process while maintaining accuracy and reliability.
Comprehensive description of generative diffusion models Implementation of generative AI for the design of analog integrated circuits Bypass the traditional manual design or direct optimization process by solving the inverse sizing problem
Autor*in
Pedro H. M. Eid
Themen in »Efficient Analog Integrated Circuit Sizing with GenAI«
Analog Integrated Circuit Sizing Applied Generative Artificial Intelligence Inverse Sizing Problem Electronic Design Automation Analog Synthesis with Generative AI