Machine Learning Applications in Electronic Design Automation
Language: English
Published by Springer International Publishing AG, CH, 2024
- Softcover
- New
Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
£ 104.69
Quantity: Over 20 available
Add to basketItem description from seller
?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.
Seller Inventory # LU-9783031130762
- Title
- Machine Learning Applications in Electronic Design Automation
- Author
- Jiang Hu, Haoxing Ren
- Publisher
- Springer International Publishing AG, CH
- Publication year
- 2024
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 3031130766
- ISBN 13
- 9783031130762
- Edition
- 2022 ed.
- Dimensions
- 15.6 x 3.07 x 23.39 cm
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.
"Synopsis" may belong to another edition of this title.
About the Author
Haoxing Ren (Mark) was born in Nanchang, China in 1976. He received two BS degrees in Electrical Engineering and Finance, and MS degree in Electrical Engineering from Shanghai Jiao Tong University, China in 1996, and 1999, respectively; MS in Computer Engineering from Rensselaer Polytechnic Institute in 2000; and PhD in Computer Engineering from University of Texas at Austin in 2006. From 2000 to 2015, he worked at IBM Microelectronics and Thomas J. Watson Research Center (after 2006) developing physical design and logic synthesis tools and methodology for IBM microprocessor and ASIC designs. He received several IBM technical achievement awards including the IBM Corporate Award for his work on improving microprocessor design productivity. After his 15 years tenue at IBM, he had a brief stint as a technical executive at a chip design start-up developing server-class CPUs based on IBM OpenPOWER technology. In 2016, Mark joined NVIDIA Research where he currently leads theDesign Automation research group, whose mission is to improve the quality and productivity of chip design through machine learning and GPU accelerated tools. He published many papers in the field of design automation including several book chapters in logic synthesis and physical design. He also received the best paper awards at International Symposium on Physical Design (ISPD) in 2013, Design Automation Conference (DAC) in 2019 and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems in 2021.
Jiang Hu received the B.S. degree in optical engineering from Zhejiang University (China) in 1990, the M.S. degree in physics in 1997 and the Ph.D. degree in electrical engineering from the University of Minnesota in 2001. He worked with IBM Microelectronics from January 2001 to June 2002. In 2002 he joined the electrical engineering faculty at Texas A&M University. His research interests include design automation of VLSI circuits and systems, computer architecture, hardware security and machine learning applications. Honors include receiving a best paper award at the ACM/IEEE Design Automation Conference in 2001, an IBM Invention Achievement Award in 2003, a best paper award at the IEEE/ACM International Conference on Computer-Aided Design in 2011, a best paper award at the IEEE International Conference on Vehicular Electronics and Safety in 2018 and a best paper award at the IEEE/ACM International Symposium on Microarchitecture in 2021. He has served as technical program committee members for DAC, ICCAD, ISPD, ISQED, ICCD, DATE, ISCAS, ASP-DAC and ISLPED. He is the general chair for the 2012 ACM International Symposium on Physical Design. He served as an associate editor for IEEE Transactions on CAD and the ACM Transactions on Design Automation of Electronic Systems. He received the Humboldt Research Fellowship in 2012. He was named an IEEE Fellow in 2016."About the title" may belong to another edition of this title.
Rarewaves.com USA
London, London, United Kingdom
AbeBooks seller since June 11, 2025
Shipping rates from United Kingdom to U.S.A.
| Item | 9 to 14 business days | 9 to 14 business days |
|---|---|---|
| First item | £ 0.00 | £ 0.00 |
Payment methods
Seller's business information
RAREWAVES.COM LIMITED
Elsley Court, 20-22 Great Titchfield Street
London, United Kingdom W1W 8BE
Right of withdrawal
If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.
Information regarding the right of withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).
We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.
We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.
We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.
We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.
You shall send back the goods or hand them over to Rarewaves.com USA, Unit 144 The Lightbox, 111 Power Road, W4 5PY, London, London, United Kingdom, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.
Exceptions to the right of withdrawal
The right of withdrawal does not apply to:
- The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
- The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.
Shipping terms
Please note that we do not offer Priority shipping to any country.
We currently do not ship to the below countries:
Russia
Belarus
Ukraine
Please do not attempt to place orders with any of these countries as a ship to address - they will be cancelled.