Computer-aided circuit simulation and its algorithms (EDA)

Responsible: Prof. Dr.-Ing. Ralf Sommer

target groups: 1st semester EIT_MA, II_MA

Teaching content

  • Introduction to circuit simulation
    history, simulation types, fields of application
  • Network theory as a basis for the automated compilation of circuit equations
    Kirchhoff equations, linear element relations Sparce tableau analysis (STA) Orthogonality of Kirchhoff equations Mesh currents and node potentials Mesh current analysis, RLA node analysis, super node analysis Modified node analysis Sections, fundamental section sets Automatic tree and mesh search and computer-aided STA
  • Solution of linear systems of equations (LU decomposition, pivoting, macro joke reordering, sparse matrix techniques)
  • Solution of nonlinear equations
    Newton-Raphson method Implementation of the Newton method (Newton equivalent circuit, convergence acceleration, simulation control)
  • Solution of differential equations
    Numerical integration methods (forward and backward Euler, trapezoidal rule, multistep methods, Runge-Kutta and Gear methods, predictor-corrector methods, exactness constraints for the construction of own integration methods, step size control: Nordsiek vector) Convergence of numerical integration methods, stability options and control parameters
  • Device models SPICE
    diode, bipolar transistor, MOS models and their parameters
  • Behavioural modelling - solution of behavioural models
  • Symbolic Analysis
    Overview of Symbolic Analysis and Analysis Programs Symbolic Simplification Algorithms (SAG, SBG, SDG) Symbolic Extraction of Poles and Zeros Automated Generation of Behavioral Models Automatic Equation Generation for Nonlinear Dynamic Systems Methods of Approximation of Symbolic DAE Systems
  • Statistical Analysis and Design Centration/Yield Optimization
    Introduction to Statistics - Basic Terms for Statistics of Device Scatter Automatic Dimensioning (Numerical) Automatic Design Constraints Generation, Feasibility Optimization, Nominal Optimization, Monte Carlo Analysis, Contributor Identification, Worst Case Distance Optimization (Yield Optimization)
  • Overview of statistical device modelling
  • Overview Device Aging and Aging Simulation (Cadence ReIXpert)
  • RF simulation method (Cadence SpectreRF)
    PSS - Periodic Steady State PAC - Periodic Alternating-Current PXF - Periodic Transfer-Function PNOISE - Periodic Noise PDISTO - Periodic Distortion QPSS - Quasi-Periodic Non-Linear Steady State QPNoise - Quasi-Periodic Noise HB - Harmonic Balance
  • Applications
    Overview of industrial design flows, Cadence Design Framework II design kits (Cadence Methodology Kits) Practical work with the Cadence Framework, WiCkeD and Analog Insydes