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. - 1st ed. 2023. - XIV, 253 p. 125 illus., 91 illus. in color. online resource.
Acceso multiusuario
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.
9789811932502
Electronics.
Engineering mathematics.
Electronics and Microelectronics, Instrumentation.
Engineering Mathematics.
TK7800-8360
621.381
Monte Carlo Methods for Partial Differential Equations With Applications to Electronic Design Automation [electronic resource] / by Wenjian Yu, Michael Mascagni. - 1st ed. 2023. - XIV, 253 p. 125 illus., 91 illus. in color. online resource.
Acceso multiusuario
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.
9789811932502
Electronics.
Engineering mathematics.
Electronics and Microelectronics, Instrumentation.
Engineering Mathematics.
TK7800-8360
621.381
