Monte Carlo methods for partial differential equations with applications to electronic design automation / Wenjian Yu, Michael Mascagni.
Yu, Wenjian, author.; Mascagni, Michael, author.
2023
QA298
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Monte Carlo methods for partial differential equations with applications to electronic design automation / Wenjian Yu, Michael Mascagni.
Author Yu, Wenjian, author.
ISBN 9789811932502 (electronic bk.)
9811932506 (electronic bk.)
9789811932496
9811932492
DOI https://doi.org/10.1007/978-981-19-3250-2
Published Singapore : Springer, [2023]
Copyright ©2023
Language English
Description 1 online resource (xiv, 253 pages) : illustrations (some color)
Item Number 10.1007/978-981-19-3250-2 doi
Call Number QA298
Dewey Decimal Classification 518/.282
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Mascagni, Michael, author.
Available in Other Form Monte Carlo methods for partial differential equations with applications to electronic design automation.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Introduction
Monte Carlo Method for Solving PDE
A Monte Carlo Algorithm for the Telegraphers 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.

Browse Subjects

Show more subjects...

Statistics

from
to
Export