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Monte carlo methods for partial differential equations with applications to electronic design automation

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Monte carlo methods for partial differential equations with applications to electronic design automationby Wenjian Yu, Michael Mascagni.
作者:	Yu, Wenjian.
其他作者:	Mascagni, Michael.
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xiv, 253 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Monte Carlo method.
電子資源:	https://doi.org/10.1007/978-981-19-3250-2
ISBN:	9789811932502$q(electronic bk.)

Monte carlo methods for partial differential equations with applications to electronic design automation
Yu, Wenjian.

Monte carlo methods for partial differential equations with applications to electronic design automation[electronic resource] /by Wenjian Yu, Michael Mascagni. - Singapore :Springer Nature Singapore :2023. - xiv, 253 p. :ill. (some col.), digital ;24 cm.

Introduction -- Monte Carlo Method for Solving PDE -- A Monte Carlo Algorithm for the Telegrapher's Equations -- Basics of Floating Random Walk Method for Capacitance Extraction -- Pre-Characterization Techniques for FRW Based Capacitance Extraction -- Fast FRW Solver for 3-D Structures with Cylindrical Inter-Tier-Vias -- Fast FRW Solver for Structures with Non-Manhattan Conductors -- Technique for Capacitance Simulation with General Floating Metals -- Markov-Chain Random Walk and Macromodel-Aware Capacitance Extraction -- GPU-Friendly FRW Algorithm for Capacitance Extraction -- Distributed Parallel FRW Algorithm for Capacitance Simulation -- A Hybrid Random Walk Algorithm for 3-D Thermal Analysis.

The Monte Carlo method is one of the top 10 algorithms in the 20th century. This book is focusing on the Monte Carlo method for solving deterministic partial differential equations (PDEs), especially its application to electronic design automation (EDA) problems. Compared with the traditional method, the Monte Carlo method is more efficient when point values or linear functional of the solution are needed, and has the advantages on scalability, parallelism, and stability of accuracy. This book presents a systematic introduction to the Monte Carlo method for solving major kinds of PDEs, and the detailed explanation of relevant techniques for EDA problems especially the cutting-edge algorithms of random walk based capacitance extraction. It includes about 100 figures and 50 tables, and brings the reader a close look to the newest research results and the sophisticated algorithmic skills in Monte Carlo simulation software.

ISBN: 9789811932502$q(electronic bk.)

Standard No.: 10.1007/978-981-19-3250-2doiSubjects--Topical Terms:

186286
Monte Carlo method.

LC Class. No.: QA298

Dewey Class. No.: 518.282

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505 0 $a Introduction -- Monte Carlo Method for Solving PDE -- A Monte Carlo Algorithm for the Telegrapher's Equations -- Basics of Floating Random Walk Method for Capacitance Extraction -- Pre-Characterization Techniques for FRW Based Capacitance Extraction -- Fast FRW Solver for 3-D Structures with Cylindrical Inter-Tier-Vias -- Fast FRW Solver for Structures with Non-Manhattan Conductors -- Technique for Capacitance Simulation with General Floating Metals -- Markov-Chain Random Walk and Macromodel-Aware Capacitance Extraction -- GPU-Friendly FRW Algorithm for Capacitance Extraction -- Distributed Parallel FRW Algorithm for Capacitance Simulation -- A Hybrid Random Walk Algorithm for 3-D Thermal Analysis.
520 $a The Monte Carlo method is one of the top 10 algorithms in the 20th century. This book is focusing on the Monte Carlo method for solving deterministic partial differential equations (PDEs), especially its application to electronic design automation (EDA) problems. Compared with the traditional method, the Monte Carlo method is more efficient when point values or linear functional of the solution are needed, and has the advantages on scalability, parallelism, and stability of accuracy. This book presents a systematic introduction to the Monte Carlo method for solving major kinds of PDEs, and the detailed explanation of relevant techniques for EDA problems especially the cutting-edge algorithms of random walk based capacitance extraction. It includes about 100 figures and 50 tables, and brings the reader a close look to the newest research results and the sophisticated algorithmic skills in Monte Carlo simulation software.
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