Machine Learning In Vlsi Computer Aided Design
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Machine Learning In Vlsi Computer Aided Design
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Author : Ibrahim (Abe) M. Elfadel
language : en
Publisher: Springer
Release Date : 2019-03-15
Machine Learning In Vlsi Computer Aided Design written by Ibrahim (Abe) M. Elfadel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-15 with Technology & Engineering categories.
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 thatI 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
Machine Learning For Vlsi Computer Aided Design
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Author : Mohamed Baker Alawieh
language : en
Publisher:
Release Date : 2020
Machine Learning For Vlsi Computer Aided Design written by Mohamed Baker Alawieh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Consumer electronics have become an integral part of people’s life putting at their disposal immense computational power that provides numerous applications. This has been enabled by the ceaseless down scaling of integrated circuit (IC) technologies which keeps pushing the performance boundary. Such scaling continues to drive, as a byproduct, an up scale in the challenges associated with circuit design and manufacturability. Among the major challenges facing modern IC Computer Aided Design (CAD) are those related to manufacturing and yield which are manifested through: (1) expensive modeling and simulation (e.g. large and complex designs); (2) entangled design and manufacturability (e.g., yield sensitive to design patterns); and (3) strict design constraints (e.g., high yield). While these challenges associated with retaining the robustness of modern designs continue to exacerbate, Very Large-Scale Integration (VLSI) CAD is becoming more critical, yet more challenging. Parallel to these developments are the recent advancements in Machine Learning (ML) which have altered the perception of computing. This dissertation attempts to address the aforementioned challenges in VLSI CAD through machine learning techniques. Our research includes efficient analog modeling, learning-assisted physical design and yield analysis, and model adaptation schemes tailored to the ever-changing IC environment. With aggressive scaling, process variation manifests itself among the most prominent factors limiting the yield of analog and mixed-signal (AMS) circuits. In modern ICs, the expensive simulation cost is one of the challenges facing accurate modeling of this variation. Our study develops a novel semi-supervised learning framework for AMS design modeling that is capable of significantly reducing the modeling cost. In addition, a new perspective towards incorporating sparsity in the modeling task is proposed. At the lithography stage, resolution enhancement techniques in general, and Sub Resolution Assist Feature (SRAF) insertion in particular, have become indispensable given the ever shrinking feature size. While different approaches have been proposed for SRAF insertion, the trade-off between efficiency and accuracy is still the governing principle. To address this, we recast the SRAF insertion process as an image translation task and propose a deep learning-based approach for efficient SRAF insertion. Besides, with complex designs, challenges at the physical design stage have exacerbated. Therefore, across-layers information sharing has become imperative for timely design closure. Particularly, in modern Field Programmable Gate Array (FPGA) place and route flows, leveraging routing congestion information during placement has demonstrated imperative benefit. Our study develops a new congestion prediction approach for large-scale FPGA designs that achieves superior prediction accuracy. Moreover, during fabrication, a critical first step towards improving production yield is to identify the underlying factors that contribute most to yield loss. And for that, wafer map defect analysis is a key. We present a novel wafer map defect pattern classification framework using confidence-aware deep selective learning. The use of ML for CAD tasks has the promise of delivering better performance and efficiency. However, one of the main characteristics of the field is that it is evolving with a fast rate of change. Therefore, by the time enough data is available to train accurate models under a given environment, changes start to occur. In this sense, the frequent restarts limit the returns on developing ML models. To address this, we develop a framework for the fast migration of classification models across different environments. Our approaches are validated with extensive experiments where they proved capable of advancing the VLSI CAD flow
Mobile Computing And Sustainable Informatics
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Author : Subarna Shakya
language : en
Publisher: Springer Nature
Release Date : 2021-07-22
Mobile Computing And Sustainable Informatics written by Subarna Shakya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-22 with Technology & Engineering categories.
This book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2021) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during 29–30 January 2021. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices, to personalized, embedded and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models and advanced informatics that supports the symbiosis of mobile computing and sustainable informatics.
Machine Learning Applications In Electronic Design Automation
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Author : Haoxing Ren
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Machine Learning Applications In Electronic Design Automation written by Haoxing Ren and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.
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.
Machine Learning In Modeling And Simulation
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Author : Timon Rabczuk
language : en
Publisher: Springer Nature
Release Date : 2023-10-03
Machine Learning In Modeling And Simulation written by Timon Rabczuk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Technology & Engineering categories.
Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.
Advancing Vlsi Through Machine Learning
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Author : Abhishek Narayan Tripathi
language : en
Publisher: CRC Press
Release Date : 2025-03-31
Advancing Vlsi Through Machine Learning written by Abhishek Narayan Tripathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Technology & Engineering categories.
This book explores the synergy between very large-scale integration (VLSI) and machine learning (ML) and its applications across various domains. It investigates how ML techniques can enhance the design and testing of VLSI circuits, improve power efficiency, optimize layouts, and enable novel architectures. This book bridges the gap between VLSI and ML, showcasing the potential of this integration in creating innovative electronic systems, advancing computing capabilities, and paving the way for a new era of intelligent devices and technologies. Additionally, it covers how VLSI technologies can accelerate ML algorithms, enabling more efficient and powerful data processing and inference engines. It explores both hardware and software aspects, covering topics like hardware accelerators, custom hardware for specific ML tasks, and ML-driven optimization techniques for chip design and testing. This book will be helpful for academicians, researchers, postgraduate students, and those working in ML-driven VLSI.
Proceedings Of The Third International Conference On Cognitive And Intelligent Computing Volume 2
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Author : Amit Kumar
language : en
Publisher: Springer Nature
Release Date : 2025-02-25
Proceedings Of The Third International Conference On Cognitive And Intelligent Computing Volume 2 written by Amit Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-25 with Computers categories.
This book presents original, peer-reviewed select articles from the International Conference on Cognitive and Intelligent Computing (ICCIC-2023), held on December 8–9, 2023, at Hyderabad, in India. The book focuses on the comprehensive nature of computational intelligence, cognitive computing, AI, ML, and DL in order to highlight its role in the modelling, identification, optimisation, prediction, forecasting, and control of future intelligent systems. It includes contributions from a methodological/application standpoint in understanding artificial intelligence and machine learning approaches and their capabilities in solving a wide range of problems in the real world.
The Iot Physical Layer
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Author : Ibrahim (Abe) M. Elfadel
language : en
Publisher: Springer
Release Date : 2018-09-03
The Iot Physical Layer written by Ibrahim (Abe) M. Elfadel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Technology & Engineering categories.
This book documents some of the most recent advances on the physical layer of the Internet of Things (IoT), including sensors, circuits, and systems. The application area selected for illustrating these advances is that of autonomous, wearable systems for real-time medical diagnosis. The book is unique in that it adopts a holistic view of such systems and includes not only the sensor and processing subsystems, but also the power, communication, and security subsystems. Particular attention is paid to the integration of these IoT subsystems as well as the prototyping platforms needed for achieving such integration. Other unique features include the discussion of energy-harvesting subsystems to achieve full energy autonomy and the consideration of hardware security as a requirement for the integrity of the IoT physical layer. One unifying thread of the various designs considered in this book is that they have all been fabricated and tested in an advanced, low-power CMOS process, namely GLOBALFOUNDRIES 65nm CMOS LPe.
Response Feature Technology For High Frequency Electronics Optimization Modeling And Design Automation
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Author : Anna Pietrenko-Dabrowska
language : en
Publisher: Springer Nature
Release Date : 2023-10-16
Response Feature Technology For High Frequency Electronics Optimization Modeling And Design Automation written by Anna Pietrenko-Dabrowska and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Technology & Engineering categories.
This book discusses response feature technology and its applications to modeling, optimization, and computer-aided design of high-frequency structures including antenna and microwave components. By exploring the specific structure of the system outputs, feature-based approaches facilitate simulation-driven design procedures, both in terms of improving their computational efficiency and reliability. These benefits are associated with the weakly nonlinear relationship between feature point coordinates and design variables, which—in the context of optimization—leads to inherent regularization of the objective functions. The book provides an overview of the subject, a definition and extraction of characteristic points, and feature-based design problem reformulation. It also outlines a number of numerical algorithms developed to handle local, global, and multi-criterial design, surrogate modeling, as well as uncertainty quantification. The discussed frameworks are extensively illustrated using examples of real microwave and antenna structures, along with numerous design cases. Introductory material on simulation-driven design, numerical optimization, as well as behavioral and physics-based surrogate modeling is also included. The book will be useful for readers working in the area of high-frequency electronics, including microwave engineering, antenna design, microwave photonics, magnetism and especially those who utilize electromagnetic (EM) simulation models in their daily routines.
Hardware Security
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Author : Mark Tehranipoor
language : en
Publisher: Springer Nature
Release Date : 2024-06-11
Hardware Security written by Mark Tehranipoor and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-11 with Technology & Engineering categories.
This book provides a look into the future of hardware and microelectronics security, with an emphasis on potential directions in security-aware design, security verification and validation, building trusted execution environments, and physical assurance. The book emphasizes some critical questions that must be answered in the domain of hardware and microelectronics security in the next 5-10 years: (i) The notion of security must be migrated from IP-level to system-level; (ii) What would be the future of IP and IC protection against emerging threats; (iii) How security solutions could be migrated/expanded from SoC-level to SiP-level; (iv) the advances in power side-channel analysis with emphasis on post-quantum cryptography algorithms; (v) how to enable digital twin for secure semiconductor lifecycle management; and (vi) how physical assurance will look like with considerations of emerging technologies. The main aim of this book is to serve as a comprehensive and concise roadmap for new learners and educators navigating the evolving research directions in the domain of hardware and microelectronic securities. Overall, throughout 11 chapters, the book provides numerous frameworks, countermeasures, security evaluations, and roadmaps for the future of hardware security.