Machine Learning Applications in Electronic Design Automation

This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis...

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Detalles Bibliográficos
Otros Autores: Ren, Haoxing (-), Hu, Jiang
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cham : Springer International Publishing 2022.
Edición:1st ed. 2022.
Colección:Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b47353090*spi
Descripción
Sumario:This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification. Serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification; Covers classical ML methods, as well as deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO); Discusses machine learning ML's applications in electronic design automation (EDA), especially in the design automation of VLSI integrated circuits.
Descripción Física:1 recurso electrónico, XII, 583 páginas, 215 ilustraciones, 211 ilustraciones en color
Formato:Forma de acceso: World Wide Web.
ISBN:9783031130748