Machine Learning Based Design And Optimization Of High Speed Circuits
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Machine Learning Based Design And Optimization Of High Speed Circuits
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Author : Vazgen Melikyan
language : en
Publisher: Springer Nature
Release Date : 2024-01-31
Machine Learning Based Design And Optimization Of High Speed Circuits written by Vazgen Melikyan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Technology & Engineering categories.
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.
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.
Analog Circuits For Machine Learning Current Voltage Temperature Sensors And High Speed Communication
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Author : Pieter Harpe
language : en
Publisher: Springer
Release Date : 2023-03-26
Analog Circuits For Machine Learning Current Voltage Temperature Sensors And High Speed Communication written by Pieter Harpe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-26 with Technology & Engineering categories.
This book is based on the 18 tutorials presented during the 29th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, with specific contributions focusing on analog circuits for machine learning, current/voltage/temperature sensors, and high-speed communication via wireless, wireline, or optical links. This book serves as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development.
Smart Integrated Circuit Design And Methodology
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Author : Thomas Noulis
language : en
Publisher: CRC Press
Release Date : 2023-12-07
Smart Integrated Circuit Design And Methodology written by Thomas Noulis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Computers categories.
This book describes advanced flows and methodologies for the design and implementation of system-on-chip (SoC). It is written by a mixture of industrial experts and key academic professors and researchers. The intended audience is not only students but also engineers with system-on-chip and semiconductor background currently working in the semiconductor industry. Integrated Circuits are available in every electronic product, especially in emerging market segments such as 5G mobile communications, autonomous driving, fully electrified vehicles, and artificial intelligence. These product types require real-time processing at billions of operations per second. The development design cycle time is driving costs and time to market more than ever before. The traditional design methodologies have reached their limits and innovative solutions are essential to serve the emerging SoC design challenges. In the framework of the Circuit and System Society (CASS) Outreach Initiative 2022 call, the SMART Integrated Circuits design methodology – named SMARTIC – Seasonal School was performed in November 2022, in Thessaloniki (Greece). Features Core analog circuits of any system of chip, such as high-performance rectifiers and filters, are addressed in detail, together with their respective design methodology. New advanced methodologies towards design cycle speed up based on machine learning and artificial intelligence applications. Advanced analog design methodology based on gm/Id and lock up tables. A powerful flow for enabling fast time to market analog circuit design focusing on baseband circuits More exotic methodologies and applications with focus on digital-based analog processing in nanoscale CMOS ICs and the design and development of depleted monolithic active pixel sensors for high-radiation applications, together with all the respective challenges of this application.
Speeding Up Radio Frequency Integrated Circuit Sizing With Neural Networks
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Author : João L. C. P. Domingues
language : en
Publisher: Springer Nature
Release Date : 2023-03-20
Speeding Up Radio Frequency Integrated Circuit Sizing With Neural Networks written by João L. C. P. Domingues and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-20 with Computers categories.
In this book, innovative research using artificial neural networks (ANNs) is conducted to automate the sizing task of RF IC design, which is used in two different steps of the automatic design process. The advances in telecommunications, such as the 5th generation broadband or 5G for short, open doors to advances in areas such as health care, education, resource management, transportation, agriculture and many other areas. Consequently, there is high pressure in today’s market for significant communication rates, extensive bandwidths and ultralow-power consumption. This is where radiofrequency (RF) integrated circuits (ICs) come in hand, playing a crucial role. This demand stresses out the problem which resides in the remarkable difficulty of RF IC design in deep nanometric integration technologies due to their high complexity and stringent performances. Given the economic pressure for high quality yet cheap electronics and challenging time-to-market constraints, there is an urgent need for electronic design automation (EDA) tools to increase the RF designers’ productivity and improve the quality of resulting ICs. In the last years, the automatic sizing of RF IC blocks in deep nanometer technologies has moved toward process, voltage and temperature (PVT)-inclusive optimizations to ensure their robustness. Each sizing solution is exhaustively simulated in a set of PVT corners, thus pushing modern workstations’ capabilities to their limits. Standard ANNs applications usually exploit the model’s capability of describing a complex, harder to describe, relation between input and target data. For that purpose, ANNs are a mechanism to bypass the process of describing the complex underlying relations between data by feeding it a significant number of previously acquired input/output data pairs that the model attempts to copy. Here, and firstly, the ANNs disrupt from the most recent trials of replacing the simulator in the simulation-based sizing with a machine/deep learning model, by proposing two different ANNs, the first classifies the convergence of the circuit for nominal and PVT corners, and the second predicts the oscillating frequencies for each case. The convergence classifier (CCANN) and frequency guess predictor (FGPANN) are seamlessly integrated into the simulation-based sizing loop, accelerating the overall optimization process. Secondly, a PVT regressor that inputs the circuit’s sizing and the nominal performances to estimate the PVT corner performances via multiple parallel artificial neural networks is proposed. Two control phases prevent the optimization process from being misled by inaccurate performance estimates. As such, this book details the optimal description of the input/output data relation that should be fulfilled. The developed description is mainly reflected in two of the system’s characteristics, the shape of the input data and its incorporation in the sizing optimization loop. An optimal description of these components should be such that the model should produce output data that fulfills the desired relation for the given training data once fully trained. Additionally, the model should be capable of efficiently generalizing the acquired knowledge in newer examples, i.e., never-seen input circuit topologies.
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 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
High Speed And Lower Power Technologies
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Author : Jung Han Choi
language : en
Publisher: CRC Press
Release Date : 2018-09-03
High Speed And Lower Power Technologies written by Jung Han Choi and has been published by CRC Press 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 explores up-to-date research trends and achievements on low-power and high-speed technologies in both electronics and optics. It offers unique insight into low-power and high-speed approaches ranging from devices, ICs, sub-systems and networks that can be exploited for future mobile devices, 5G networks, Internet of Things (IoT), and data centers. It collects heterogeneous topics in place to catch and predict future research directions of devices, circuits, subsystems, and networks for low-power and higher-speed technologies. Even it handles about artificial intelligence (AI) showing examples how AI technology can be combined with concurrent electronics. Written by top international experts in both industry and academia, the book discusses new devices, such as Si-on-chip laser, interconnections using graphenes, machine learning combined with CMOS technology, progresses of SiGe devices for higher-speed electronices for optic, co-design low-power and high-speed circuits for optical interconnect, low-power network-on-chip (NoC) router, X-ray quantum counting, and a design of low-power power amplifiers. Covers modern high-speed and low-power electronics and photonics. Discusses novel nano-devices, electronics & photonic sub-systems for high-speed and low-power systems, and many other emerging technologies like Si photonic technology, Si-on-chip laser, low-power driver for optic device, and network-on-chip router. Includes practical applications and recent results with respect to emerging low-power systems. Addresses the future perspective of silicon photonics as a low-power interconnections and communication applications.
Using Artificial Neural Networks For Analog Integrated Circuit Design Automation
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Author : João P. S. Rosa
language : en
Publisher: Springer Nature
Release Date : 2019-12-11
Using Artificial Neural Networks For Analog Integrated Circuit Design Automation written by João P. S. Rosa and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-11 with Technology & Engineering categories.
This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices’ sizes to circuits’ performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices’ sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit’s performances as input features and devices’ sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.
Advancement Of Intelligent Computational Methods And Technologies
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Author : O.P. Verma
language : en
Publisher: CRC Press
Release Date : 2024-06-30
Advancement Of Intelligent Computational Methods And Technologies written by O.P. Verma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-30 with Computers categories.
The compiled volume originates from the notable contributions presented at the 1st International Conference on Advancementof Intelligent Computational Methods and Technologies (AICMT2023), which took place in a hybrid format on June 27, 2023,at Delhi Technical Campus, Greater Noida, Uttar Pradesh, India. This comprehensive collection serves as an exploration into the dynamic domain of intelligent computational methods and technologies, offering insights into the latest and upcoming trends in computation methods. AICMT2023’s scope encompasses the evolutionary trajectory of computational methods, addressing pertinent issues in real time implementation, delving into the emergence of new intelligent technologies, exploring next-generation problem-solving methodologies, and other interconnected areas. The conference is strategically designed to spotlight current research trendswithin the field, fostering a vibrant research culture and contributing to the collective knowledge base.
Topology Optimization And Ai Based Design Of Power Electronic And Electrical Devices
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Author : Hajime Igarashi
language : en
Publisher: Elsevier
Release Date : 2024-02-01
Topology Optimization And Ai Based Design Of Power Electronic And Electrical Devices written by Hajime Igarashi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-01 with Technology & Engineering categories.
Topology Optimization and AI-based Design of Power Electronic and Electrical Devices: Principles and Methods provides an essential foundation in the emergent design methodology as it moves towards commercial development in such electrical devices as traction motors for electric motors, transformers, inductors, reactors and power electronics circuits. Opening with an introduction to electromagnetism and computational electromagnetics for optimal design, the work outlines principles and foundations in finite element methods and illustrates numerical techniques useful for finite element analysis. It summarizes the foundations of deterministic and stochastic optimization methods, including genetic algorithm, particle swarm optimization and simulated annealing, alongside representative algorithms. The work goes on to discuss parameter optimization and topology optimization of electrical devices alongside current implementations including magnetic shields, 2D and 3D models of electric motors, and wireless power transfer devices. The work concludes with a lengthy exposition of AI-based design methods, including surrogate models for optimization, deep neural networks, and automatic design methods using Monte-Carlo tree searches for electrical devices and circuits. Assists researchers and design engineers in applying emergent topology design optimization to power electronics and electrical device design, supported by step-by-step methods, heuristic derivation, and pseudocodes Proposes unique formulations of AI-based design for electrical devices using Monte Carlo tree search and other machine learning methods Is richly accompanied by detailed numerical examples and repletes with computational support materials in algorithms and explanatory formulae Includes access to pedagogical videos on topics including the evolutionary process of topology optimization, the distribution of genetic algorithms, and CMA-ES