Machine Learning Techniques For Vlsi Chip Design

Author : Abhishek Kumar,Suman Lata Tripathi,K. Srinivasa Rao
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 50,7 Mb
Release : 2023-06-26
Category : Computers
ISBN : 9781119910473

Get Book

Machine Learning Techniques for VLSI Chip Design by Abhishek Kumar,Suman Lata Tripathi,K. Srinivasa Rao Pdf

MACHINE LEARNING TECHNIQUES FOR VLSI CHIP DESIGN This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design. Artificial intelligence (AI) and machine learning (ML) have, or will have, an impact on almost every aspect of our lives and every device that we own. AI has benefitted every industry in terms of computational speeds, accurate decision prediction, efficient machine learning (ML), and deep learning (DL) algorithms. The VLSI industry uses the electronic design automation tool (EDA), and the integration with ML helps in reducing design time and cost of production. Finding defects, bugs, and hardware Trojans in the design with ML or DL can save losses during production. Constraints to ML-DL arise when having to deal with a large set of training datasets. This book covers the learning algorithm for floor planning, routing, mask fabrication, and implementation of the computational architecture for ML-DL. The future aspect of the ML-DL algorithm is to be available in the format of an integrated circuit (IC). A user can upgrade to the new algorithm by replacing an IC. This new book mainly deals with the adaption of computation blocks like hardware accelerators and novel nano-material for them based upon their application and to create a smart solution. This exciting new volume is an invaluable reference for beginners as well as engineers, scientists, researchers, and other professionals working in the area of VLSI architecture development.

Author : Ibrahim (Abe) M. Elfadel,Duane S. Boning,Xin Li
Publisher : Springer
Page : 694 pages
File Size : 50,6 Mb
Release : 2019-03-15
Category : Technology & Engineering
ISBN : 9783030046668

Get Book

Machine Learning in VLSI Computer-Aided Design by Ibrahim (Abe) M. Elfadel,Duane S. Boning,Xin Li Pdf

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

Author : Sandeep Saini,Kusum Lata,G.R. Sinha
Publisher : CRC Press
Page : 292 pages
File Size : 40,9 Mb
Release : 2021-12-31
Category : Technology & Engineering
ISBN : 9781000523843

Get Book

VLSI and Hardware Implementations using Modern Machine Learning Methods by Sandeep Saini,Kusum Lata,G.R. Sinha Pdf

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Author : Ibrahim (Abe) M. Elfadel,Duane S. Boning,Xin Li
Publisher : Unknown
Page : 128 pages
File Size : 51,6 Mb
Release : 2019
Category : Integrated circuits
ISBN : 3030046672

Get Book

Machine Learning in VLSI Computer-aided Design by Ibrahim (Abe) M. Elfadel,Duane S. Boning,Xin Li Pdf

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.

Author : A. F. Schwarz
Publisher : Academic Press
Page : 593 pages
File Size : 41,9 Mb
Release : 2014-05-10
Category : Technology & Engineering
ISBN : 9781483258058

Get Book

Handbook of VLSI Chip Design and Expert Systems by A. F. Schwarz Pdf

Handbook of VLSI Chip Design and Expert Systems provides information pertinent to the fundamental aspects of expert systems, which provides a knowledge-based approach to problem solving. This book discusses the use of expert systems in every possible subtask of VLSI chip design as well as in the interrelations between the subtasks. Organized into nine chapters, this book begins with an overview of design automation, which can be identified as Computer-Aided Design of Circuits and Systems (CADCAS). This text then presents the progress in artificial intelligence, with emphasis on expert systems. Other chapters consider the impact of design automation, which exploits the basic capabilities of computers to perform complex calculations and to handle huge amounts of data with a high speed and accuracy. This book discusses as well the characterization of microprocessors. The final chapter deals with interactive I/O devices. This book is a valuable resource for system design experts, circuit analysts and designers, logic designers, device engineers, technologists, and application-specific designers.

Author : Haoxing Ren,Jiang Hu
Publisher : Springer Nature
Page : 585 pages
File Size : 55,5 Mb
Release : 2023-01-01
Category : Technology & Engineering
ISBN : 9783031130748

Get Book

Machine Learning Applications in Electronic Design Automation by Haoxing Ren,Jiang Hu Pdf

​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.

Author : A. F. Schwarz
Publisher : Unknown
Page : 600 pages
File Size : 55,7 Mb
Release : 1993
Category : Computers
ISBN : STANFORD:36105004060534

Get Book

Handbook of VLSI Chip Design and Expert Systems by A. F. Schwarz Pdf

Offers a conceptual and methodological understanding of chip design, and of the fundamental principles in the computer-aided design of VLSI circuits and systems (CADCAS). The text covers where, why and how expert systems are used in subtasks of CADCAS, and in the integrated chip design system.

Author : Jose G. Delgado-Frias,W.R. Moore
Publisher : Springer Science & Business Media
Page : 318 pages
File Size : 54,7 Mb
Release : 2013-06-29
Category : Computers
ISBN : 9781489913319

Get Book

VLSI for Neural Networks and Artificial Intelligence by Jose G. Delgado-Frias,W.R. Moore Pdf

Neural network and artificial intelligence algorithrns and computing have increased not only in complexity but also in the number of applications. This in turn has posed a tremendous need for a larger computational power that conventional scalar processors may not be able to deliver efficiently. These processors are oriented towards numeric and data manipulations. Due to the neurocomputing requirements (such as non-programming and learning) and the artificial intelligence requirements (such as symbolic manipulation and knowledge representation) a different set of constraints and demands are imposed on the computer architectures/organizations for these applications. Research and development of new computer architectures and VLSI circuits for neural networks and artificial intelligence have been increased in order to meet the new performance requirements. This book presents novel approaches and trends on VLSI implementations of machines for these applications. Papers have been drawn from a number of research communities; the subjects span analog and digital VLSI design, computer design, computer architectures, neurocomputing and artificial intelligence techniques. This book has been organized into four subject areas that cover the two major categories of this book; the areas are: analog circuits for neural networks, digital implementations of neural networks, neural networks on multiprocessor systems and applications, and VLSI machines for artificial intelligence. The topics that are covered in each area are briefly introduced below.

Author : Chip Huyen
Publisher : "O'Reilly Media, Inc."
Page : 389 pages
File Size : 41,8 Mb
Release : 2022-05-17
Category : Computers
ISBN : 9781098107932

Get Book

Designing Machine Learning Systems by Chip Huyen Pdf

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references. This book will help you tackle scenarios such as: Engineering data and choosing the right metrics to solve a business problem Automating the process for continually developing, evaluating, deploying, and updating models Developing a monitoring system to quickly detect and address issues your models might encounter in production Architecting an ML platform that serves across use cases Developing responsible ML systems

Author : Bert Moons,Daniel Bankman,Marian Verhelst
Publisher : Springer
Page : 206 pages
File Size : 47,8 Mb
Release : 2018-10-23
Category : Technology & Engineering
ISBN : 9783319992235

Get Book

Embedded Deep Learning by Bert Moons,Daniel Bankman,Marian Verhelst Pdf

This book covers algorithmic and hardware implementation techniques to enable embedded deep learning. The authors describe synergetic design approaches on the application-, algorithmic-, computer architecture-, and circuit-level that will help in achieving the goal of reducing the computational cost of deep learning algorithms. The impact of these techniques is displayed in four silicon prototypes for embedded deep learning. Gives a wide overview of a series of effective solutions for energy-efficient neural networks on battery constrained wearable devices; Discusses the optimization of neural networks for embedded deployment on all levels of the design hierarchy – applications, algorithms, hardware architectures, and circuits – supported by real silicon prototypes; Elaborates on how to design efficient Convolutional Neural Network processors, exploiting parallelism and data-reuse, sparse operations, and low-precision computations; Supports the introduced theory and design concepts by four real silicon prototypes. The physical realization’s implementation and achieved performances are discussed elaborately to illustrated and highlight the introduced cross-layer design concepts.

Author : Patrick Girard,Shawn Blanton,Li-C. Wang
Publisher : Springer Nature
Page : 320 pages
File Size : 55,8 Mb
Release : 2023-03-13
Category : Technology & Engineering
ISBN : 9783031196393

Get Book

Machine Learning Support for Fault Diagnosis of System-on-Chip by Patrick Girard,Shawn Blanton,Li-C. Wang Pdf

This book provides a state-of-the-art guide to Machine Learning (ML)-based techniques that have been shown to be highly efficient for diagnosis of failures in electronic circuits and systems. The methods discussed can be used for volume diagnosis after manufacturing or for diagnosis of customer returns. Readers will be enabled to deal with huge amount of insightful test data that cannot be exploited otherwise in an efficient, timely manner. After some background on fault diagnosis and machine learning, the authors explain and apply optimized techniques from the ML domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing. These techniques can be used for failure isolation in logic or analog circuits, board-level fault diagnosis, or even wafer-level failure cluster identification. Evaluation metrics as well as industrial case studies are used to emphasize the usefulness and benefits of using ML-based diagnosis techniques.

Author : Thaddeus J. Kowalski
Publisher : Springer International Series in Engineering and Computer Science
Page : 248 pages
File Size : 54,5 Mb
Release : 1985-05-31
Category : Computers
ISBN : UOM:39015009814875

Get Book

An Artificial Intelligence Approach to VLSI Design by Thaddeus J. Kowalski Pdf

Author : Lizhong Chen,Drew Penney,Daniel Jiménez
Publisher : Springer Nature
Page : 124 pages
File Size : 53,6 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031017704

Get Book

AI for Computer Architecture by Lizhong Chen,Drew Penney,Daniel Jiménez Pdf

Artificial intelligence has already enabled pivotal advances in diverse fields, yet its impact on computer architecture has only just begun. In particular, recent work has explored broader application to the design, optimization, and simulation of computer architecture. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This book reviews the application of machine learning in system-wide simulation and run-time optimization, and in many individual components such as caches/memories, branch predictors, networks-on-chip, and GPUs. The book further analyzes current practice to highlight useful design strategies and identify areas for future work, based on optimized implementation strategies, opportune extensions to existing work, and ambitious long term possibilities. Taken together, these strategies and techniques present a promising future for increasingly automated computer architecture designs.

Author : Gerez
Publisher : John Wiley & Sons
Page : 344 pages
File Size : 54,9 Mb
Release : 2006-06
Category : Electronic
ISBN : 8126508213

Get Book

ALGORITHMS VLSI DESIGN AUTOMATION by Gerez Pdf

Market_Desc: · Electrical Engineering Students taking courses on VLSI systems, CAD tools for VLSI, Design Automation at Final Year or Graduate Level, Computer Science courses on the same topics, at a similar level· Practicing Engineers wishing to learn the state of the art in VLSI Design Automation· Designers of CAD tools for chip design in software houses or large electronics companies. Special Features: · Probably the first book on Design Automation for VLSI Systems which covers all stages of design from layout synthesis through logic synthesis to high-level synthesis· Clear, precise presentation of examples, well illustrated with over 200 figures· Focus on algorithms for VLSI design tools means it will appeal to some Computer Science as well as Electrical Engineering departments About The Book: Enrollments in VLSI design automation courses are not large but it's a very popular elective, especially for those seeking a career in the microelectronics industry. Already the reviewers seem very enthusiastic about the coverage of the book being a better match for their courses than available competitors, because it covers all design phases. It has plenty of worked problems and a large no. of illustrations. It's a good 'list-builder' title that matches our strategy of focusing on topics that lie on the interface between Elec Eng and Computer Science.

Author : Albert Chun-Chen Liu,Oscar Ming Kin Law
Publisher : John Wiley & Sons
Page : 244 pages
File Size : 41,8 Mb
Release : 2021-08-23
Category : Computers
ISBN : 9781119810476

Get Book

Artificial Intelligence Hardware Design by Albert Chun-Chen Liu,Oscar Ming Kin Law Pdf

ARTIFICIAL INTELLIGENCE HARDWARE DESIGN Learn foundational and advanced topics in Neural Processing Unit design with real-world examples from leading voices in the field In Artificial Intelligence Hardware Design: Challenges and Solutions, distinguished researchers and authors Drs. Albert Chun Chen Liu and Oscar Ming Kin Law deliver a rigorous and practical treatment of the design applications of specific circuits and systems for accelerating neural network processing. Beginning with a discussion and explanation of neural networks and their developmental history, the book goes on to describe parallel architectures, streaming graphs for massive parallel computation, and convolution optimization. The authors offer readers an illustration of in-memory computation through Georgia Tech’s Neurocube and Stanford’s Tetris accelerator using the Hybrid Memory Cube, as well as near-memory architecture through the embedded eDRAM of the Institute of Computing Technology, the Chinese Academy of Science, and other institutions. Readers will also find a discussion of 3D neural processing techniques to support multiple layer neural networks, as well as information like: A thorough introduction to neural networks and neural network development history, as well as Convolutional Neural Network (CNN) models Explorations of various parallel architectures, including the Intel CPU, Nvidia GPU, Google TPU, and Microsoft NPU, emphasizing hardware and software integration for performance improvement Discussions of streaming graph for massive parallel computation with the Blaize GSP and Graphcore IPU An examination of how to optimize convolution with UCLA Deep Convolutional Neural Network accelerator filter decomposition Perfect for hardware and software engineers and firmware developers, Artificial Intelligence Hardware Design is an indispensable resource for anyone working with Neural Processing Units in either a hardware or software capacity.