Machine Learning-based Design and Optimization of High-Speed Circuits

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 describ...

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Bibliographic Details
Main Author: Melikyan, Vazgen
Format: eBook
Language:English
Published: Cham Springer Nature Switzerland 2024, 2024
Edition:1st ed. 2024
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary: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. Describes methods of design and optimization of circuits which can exchange information at 128/256/512 GB per second; Includes methods for practically all types of high-speed circuits: mixed-signal, heterogeneous, digital, etc; Design methods presented are machine learning-based and apply to 14nm and below technologies of IC manufacturing
Physical Description:XVII, 338 p. 379 illus., 207 illus. in color online resource
ISBN:9783031507144