System reduction for nanoscale IC design. (2017)
- Record Type:
- Book
- Title:
- System reduction for nanoscale IC design. (2017)
- Main Title:
- System reduction for nanoscale IC design
- Further Information:
- Note: Peter Benner, editor.
- Other Names:
- Benner, Peter
- Contents:
- Preface; Contents; 1 Model Order Reduction of Integrated Circuitsin Electrical Networks; 1.1 Introduction; 1.2 Basic Models; 1.2.1 Coupling; 1.3 Simulation of the Full System; 1.3.1 Standard Galerkin Finite Element Approach; 1.3.2 Mixed Finite Element Approach; 1.4 Model Order Reduction Using POD; 1.4.1 Numerical Investigation; 1.4.2 Numerical Investigation, Position of the Semiconductor in the Network; 1.4.3 MOR for the Nonlinearity with DEIM; 1.4.4 Numerical Implementation and Results with DEIM; 1.5 Residual-Based Sampling; 1.5.1 Numerical Investigation for Residual Based Sampling. 1.6 PABTEC Combined with POD MOR1.6.1 Decoupling; 1.6.2 Model Reduction Approach; 1.6.3 Numerical Experiments; References; 2 Element-Based Model Reduction in Circuit Simulation; 2.1 Introduction; 2.2 Circuit Equations; 2.2.1 Graph-Theoretic Concepts; 2.2.2 Modified Nodal Analysis and Modified Loop Analysis; 2.2.3 Linear RLC Circuits; 2.2.3.1 Passivity; 2.2.3.2 Stability; 2.2.3.3 Reciprocity; 2.3 Model Reduction of Linear Circuits; 2.3.1 Balanced Truncation for RLC Circuits; 2.3.2 Balanced Truncation for RC Circuits; 2.3.2.1 RCI Circuits; 2.3.2.2 RCV Circuits; 2.3.2.3 RCIV Circuits. 2.3.3 Numerical Aspects2.4 Model Reduction of Nonlinear Circuits; 2.5 Solving Matrix Equations; 2.5.1 ADI Method for Projected Lyapunov Equations; 2.5.2 Newton's Method for Projected Riccati Equations; 2.6 MATLAB Toolbox PABTEC; 2.7 Numerical Examples; References; 3 Reduced Representation of Power Grid Models; 3.1Preface; Contents; 1 Model Order Reduction of Integrated Circuitsin Electrical Networks; 1.1 Introduction; 1.2 Basic Models; 1.2.1 Coupling; 1.3 Simulation of the Full System; 1.3.1 Standard Galerkin Finite Element Approach; 1.3.2 Mixed Finite Element Approach; 1.4 Model Order Reduction Using POD; 1.4.1 Numerical Investigation; 1.4.2 Numerical Investigation, Position of the Semiconductor in the Network; 1.4.3 MOR for the Nonlinearity with DEIM; 1.4.4 Numerical Implementation and Results with DEIM; 1.5 Residual-Based Sampling; 1.5.1 Numerical Investigation for Residual Based Sampling. 1.6 PABTEC Combined with POD MOR1.6.1 Decoupling; 1.6.2 Model Reduction Approach; 1.6.3 Numerical Experiments; References; 2 Element-Based Model Reduction in Circuit Simulation; 2.1 Introduction; 2.2 Circuit Equations; 2.2.1 Graph-Theoretic Concepts; 2.2.2 Modified Nodal Analysis and Modified Loop Analysis; 2.2.3 Linear RLC Circuits; 2.2.3.1 Passivity; 2.2.3.2 Stability; 2.2.3.3 Reciprocity; 2.3 Model Reduction of Linear Circuits; 2.3.1 Balanced Truncation for RLC Circuits; 2.3.2 Balanced Truncation for RC Circuits; 2.3.2.1 RCI Circuits; 2.3.2.2 RCV Circuits; 2.3.2.3 RCIV Circuits. 2.3.3 Numerical Aspects2.4 Model Reduction of Nonlinear Circuits; 2.5 Solving Matrix Equations; 2.5.1 ADI Method for Projected Lyapunov Equations; 2.5.2 Newton's Method for Projected Riccati Equations; 2.6 MATLAB Toolbox PABTEC; 2.7 Numerical Examples; References; 3 Reduced Representation of Power Grid Models; 3.1 Introduction; 3.2 System Description; 3.2.1 Basic Definitions; 3.2.2 Benchmark Systems; 3.2.2.1 A Test Circuit Example; 3.2.2.2 Linear Subdomain for Non-linear Electro-Quasistatic Field Simulations; 3.3 Terminal Reduction Approaches; 3.3.1 (E)SVDMOR; 3.3.2 TermMerg. 3.3.2.1 The k-Means Clustering Algorithm3.3.2.2 The Reduction Step; 3.3.3 SparseRC; 3.3.3.1 MOR via Graph Partitioning and EMMP; 3.3.4 MOR for Many Terminals via Interpolation; 3.3.4.1 Tangential Interpolation and the Loewner Concept; 3.4 ESVDMOR in Detail; 3.4.1 Stability, Passivity, Reciprocity; 3.4.1.1 Stability; 3.4.1.2 Passivity; 3.4.1.3 Reciprocity; 3.4.2 Error Analysis; 3.4.2.1 Particular Error Bounds; 3.4.2.2 Total ESVDMOR Error Bound; 3.4.3 Implementation Details; 3.4.3.1 The Implicitly Restarted Arnoldi Method; 3.4.3.2 The Jacobi-Davidson SVD Method; 3.4.3.3 Efficiency Issues. 3.4.3.4 Truncated SVD of the Input Response Moment Matrix MI3.4.3.5 Truncated SVD of the Output Response Moment Matrix MO; 3.5 Summary and Outlook; References; 4 Coupling of Numeric/Symbolic Reduction Methods for Generating Parametrized Models of NanoelectronicSystems; 4.1 Introduction; 4.1.1 Symbolic Modeling of Analog Circuits; 4.2 Hierarchical Modelling and Model Reduction; 4.2.1 Workflow for Subsystem Reductions; 4.2.2 Subsystem Sensitivities; 4.2.3 Subsystem Ranking; 4.2.4 Algorithm for Hierarchical Model Reduction; 4.3 Implementations; 4.4 Applications; 4.4.1 Differential Amplifier. … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2017
- Extent:
- 1 online resource (205 pages)
- Subjects:
- 621.3815
Mathematics
Integrated circuits -- Design and construction
Nanoelectronics -- Design and construction
TECHNOLOGY & ENGINEERING -- Mechanical
Integrated circuits -- Design and construction
Mathematics -- Applied
Technology & Engineering -- Electronics -- General
Computers -- CAD-CAM
Computers -- Programming -- Algorithms
Mathematical modelling
Electronics engineering
Computer-aided design (CAD)
Numerical analysis
Maths for engineers
Computer science
Electronics
Computer aided design
Algorithms
Engineering mathematics
Computers -- Computer Science
Maths for scientists
Electronic books - Languages:
- English
- ISBNs:
- 9783319072364
3319072366 - Related ISBNs:
- 9783319072357
3319072358 - Notes:
- Note: Includes bibliographical references and index.
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- British Library HMNTS - ELD.DS.360721
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