國立高雄大學圖資館 |

Language: English

Back

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Monte carlo methods for partial differential equations with applications to electronic design automationby Wenjian Yu, Michael Mascagni.
Author:	Yu, Wenjian.
other author:	Mascagni, Michael.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	xiv, 253 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Monte Carlo method.
Online resource:	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

Monte carlo methods for partial differential equations with applications to electronic design automation
LDR:02674nmm a2200325 a 4500 001 644954
003 DE-He213
005 20220902091111.0
006 m d
007 cr nn 008maaau
008 231208s2023 si s 0 eng d
020 $a 9789811932502$q(electronic bk.)
020 $a 9789811932496$q(paper)
024 7 $a 10.1007/978-981-19-3250-2 $2 doi
035 $a 978-981-19-3250-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA298
072 7 $a TJF $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a TJF $2 thema
082 0 4 $a 518.282 $2 23
090 $a QA298 $b .Y94 2023
100 1 $a Yu, Wenjian. $3 680483
245 1 0 $a Monte carlo methods for partial differential equations with applications to electronic design automation $h [electronic resource] / $c by Wenjian Yu, Michael Mascagni.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xiv, 253 p. : $b ill. (some col.), digital ; $c 24 cm.
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.
650 0 $a Monte Carlo method. $3 186286
650 0 $a Differential equations, Partial $x Numerical solutions $x Data processing. $3 210572
650 1 4 $a Electronics and Microelectronics, Instrumentation. $3 274412
650 2 4 $a Engineering Mathematics. $3 806481
700 1 $a Mascagni, Michael. $3 953663
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-19-3250-2
950 $a Engineering (SpringerNature-11647)