001452913 000__ 03610cam\a2200517\i\4500
001452913 001__ 1452913
001452913 003__ OCoLC
001452913 005__ 20230314003324.0
001452913 006__ m\\\\\o\\d\\\\\\\\
001452913 007__ cr\cn\nnnunnun
001452913 008__ 220908s2023\\\\si\a\\\\ob\\\\000\0\eng\d
001452913 019__ $$a1343866913
001452913 020__ $$a9789811932502$$q(electronic bk.)
001452913 020__ $$a9811932506$$q(electronic bk.)
001452913 020__ $$z9789811932496
001452913 020__ $$z9811932492
001452913 0247_ $$a10.1007/978-981-19-3250-2$$2doi
001452913 035__ $$aSP(OCoLC)1343953764
001452913 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dN$T$$dOCLCQ
001452913 049__ $$aISEA
001452913 050_4 $$aQA298
001452913 08204 $$a518/.282$$223/eng/20220908
001452913 1001_ $$aYu, Wenjian,$$eauthor.
001452913 24510 $$aMonte Carlo methods for partial differential equations with applications to electronic design automation /$$cWenjian Yu, Michael Mascagni.
001452913 264_1 $$aSingapore :$$bSpringer,$$c[2023]
001452913 264_4 $$c©2023
001452913 300__ $$a1 online resource (xiv, 253 pages) :$$billustrations (some color)
001452913 336__ $$atext$$btxt$$2rdacontent
001452913 337__ $$acomputer$$bc$$2rdamedia
001452913 338__ $$aonline resource$$bcr$$2rdacarrier
001452913 504__ $$aIncludes bibliographical references.
001452913 5050_ $$aIntroduction -- Monte Carlo Method for Solving PDE -- A Monte Carlo Algorithm for the Telegraphers Equations -- Basics of Floating Random Walk Method for Capacitance Extraction -- Pre-Characterization Techniques for FRW Based Capacitance Extraction -- Fast FRW Solver for 3-D Structures with Cylindrical Inter-Tier-Vias -- Fast FRW Solver for Structures with Non-Manhattan Conductors -- Technique for Capacitance Simulation with General Floating Metals -- Markov-Chain Random Walk and Macromodel-Aware Capacitance Extraction -- GPU-Friendly FRW Algorithm for Capacitance Extraction -- Distributed Parallel FRW Algorithm for Capacitance Simulation -- A Hybrid Random Walk Algorithm for 3-D Thermal Analysis.
001452913 506__ $$aAccess limited to authorized users.
001452913 520__ $$aThe Monte Carlo method is one of the top 10 algorithms in the 20th century. This book is focusing on the Monte Carlo method for solving deterministic partial differential equations (PDEs), especially its application to electronic design automation (EDA) problems. Compared with the traditional method, the Monte Carlo method is more efficient when point values or linear functional of the solution are needed, and has the advantages on scalability, parallelism, and stability of accuracy. This book presents a systematic introduction to the Monte Carlo method for solving major kinds of PDEs, and the detailed explanation of relevant techniques for EDA problems especially the cutting-edge algorithms of random walk based capacitance extraction. It includes about 100 figures and 50 tables, and brings the reader a close look to the newest research results and the sophisticated algorithmic skills in Monte Carlo simulation software.
001452913 588__ $$aDescription based on print version record.
001452913 650_0 $$aMonte Carlo method.
001452913 650_0 $$aDifferential equations, Partial$$xNumerical solutions$$xData processing.
001452913 655_0 $$aElectronic books.
001452913 7001_ $$aMascagni, Michael,$$eauthor.
001452913 77608 $$iPrint version:$$aYu, Wenjian.$$tMonte Carlo methods for partial differential equations with applications to electronic design automation.$$dSingapore : Springer Nature Singapore, 2022$$z9789811932496$$w(OCoLC)1334126131
001452913 852__ $$bebk
001452913 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-3250-2$$zOnline Access$$91397441.1
001452913 909CO $$ooai:library.usi.edu:1452913$$pGLOBAL_SET
001452913 980__ $$aBIB
001452913 980__ $$aEBOOK
001452913 982__ $$aEbook
001452913 983__ $$aOnline
001452913 994__ $$a92$$bISE