Explainable Artificial Intelligence for Better Design of Very Large Scale Integrated Circuits - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Explainable Artificial Intelligence for Better Design of Very Large Scale Integrated Circuits write by Wei Zeng. This book was released on 2021. Explainable Artificial Intelligence for Better Design of Very Large Scale Integrated Circuits available in PDF, EPUB and Kindle. With the advance of Very Large Scale Integration (VLSI) technology, the design process of VLSI circuits becomes more complex, challenging, and time-consuming. Recent years have seen a rising trend of machine learning (ML) incorporated in VLSI design flow for better and more efficient design and implementation of integrated circuits. Explainable Artificial Intelligence (XAI) is an emerging technique that aims to perform prediction tasks while providing explanations for the predictions. XAI adds transparency and trustworthiness to ML models, leading to better human understanding and exploitation of the models. With ML being applied in VLSI design, it is desirable to adopt ideas from XAI for even better and more trustworthy outcomes of VLSI design. This dissertation explores the usage of Shapley Additive Explanation (SHAP)--a recent development in XAI, on different aspects and stages of VLSI design flow. Specifically, we propose three techniques that adopt SHAP in front-end and back-end design flows, including (a) SHAP-guided layout obfuscation for enhanced hardware security in split manufacturing, (b) explainable routability prediction, which accelerates the physical design flow and provides hints for improving the design, and (c) explainable-ML-guided approximate logic synthesis for area-efficient computing in error-tolerant applications. These are the first works that incorporate XAI into VLSI design methodology. All of them achieve better results than their conventional counterparts or existing works in similar settings.
Machine Learning in VLSI Computer-Aided Design
Machine Learning in VLSI Computer-Aided Design - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning in VLSI Computer-Aided Design write by Ibrahim (Abe) M. Elfadel. This book was released on 2019-03-16. Machine Learning in VLSI Computer-Aided Design available in PDF, EPUB and Kindle. This book provides readers with an up-to-date account of the use of machine learning frameworks, methodologies, algorithms and techniques in the context of computer-aided design (CAD) for very-large-scale integrated circuits (VLSI). Coverage includes the various machine learning methods used in lithography, physical design, yield prediction, post-silicon performance analysis, reliability and failure analysis, power and thermal analysis, analog design, logic synthesis, verification, and neuromorphic design. Provides up-to-date information on machine learning in VLSI CAD for device modeling, layout verifications, yield prediction, post-silicon validation, and reliability; Discusses the use of machine learning techniques in the context of analog and digital synthesis; Demonstrates how to formulate VLSI CAD objectives as machine learning problems and provides a comprehensive treatment of their efficient solutions; Discusses the tradeoff between the cost of collecting data and prediction accuracy and provides a methodology for using prior data to reduce cost of data collection in the design, testing and validation of both analog and digital VLSI designs. From the Foreword As the semiconductor industry embraces the rising swell of cognitive systems and edge intelligence, this book could serve as a harbinger and example of the osmosis that will exist between our cognitive structures and methods, on the one hand, and the hardware architectures and technologies that will support them, on the other....As we transition from the computing era to the cognitive one, it behooves us to remember the success story of VLSI CAD and to earnestly seek the help of the invisible hand so that our future cognitive systems are used to design more powerful cognitive systems. This book is very much aligned with this on-going transition from computing to cognition, and it is with deep pleasure that I recommend it to all those who are actively engaged in this exciting transformation. Dr. Ruchir Puri, IBM Fellow, IBM Watson CTO & Chief Architect, IBM T. J. Watson Research Center
AI for Big Data-Based Engineering Applications from Security Perspectives
AI for Big Data-Based Engineering Applications from Security Perspectives - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook AI for Big Data-Based Engineering Applications from Security Perspectives write by Balwinder Raj. This book was released on 2023-06-30. AI for Big Data-Based Engineering Applications from Security Perspectives available in PDF, EPUB and Kindle. Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications. AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big data–based engineering applications, faculty members across universities, and software developers.
Machine Learning-based Design and Optimization of High-Speed Circuits
Machine Learning-based Design and Optimization of High-Speed Circuits - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning-based Design and Optimization of High-Speed Circuits write by Vazgen Melikyan. This book was released on 2024-01-31. Machine Learning-based Design and Optimization of High-Speed Circuits available in PDF, EPUB and Kindle. This book describes machine learning-based new principles, methods of design and optimization of high-speed integrated circuits, included in one electronic system, which can exchange information between each other up to 128/256/512 Gbps speed. The efficiency of methods has been proven and is described on the examples of practical designs. This will enable readers to use them in similar electronic system designs. The author demonstrates newly developed principles and methods to accelerate communication between ICs, working in non-standard operating conditions, considering signal deviation compensation with linearity self-calibration. The observed circuit types also include but are not limited to mixed-signal, high performance heterogeneous integrated circuits as well as digital cores.
Utilizing Meta-design Information in a Framework Supporting the Synthesis of Very Large Scale Integrated Circuits
Utilizing Meta-design Information in a Framework Supporting the Synthesis of Very Large Scale Integrated Circuits - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Utilizing Meta-design Information in a Framework Supporting the Synthesis of Very Large Scale Integrated Circuits write by Anthony J. Gadient. This book was released on 1991. Utilizing Meta-design Information in a Framework Supporting the Synthesis of Very Large Scale Integrated Circuits available in PDF, EPUB and Kindle. We achieve this support by using meta-design information and machine learning techniques to incrementally characterize the design space and learn how each synthesis tool moves a design around that design space. The result is a self-improving design environment with a tool control capability that allows the designer to more efficiently produce an implementation that satisfies area and performance constraints."
