Explicit Moment Matching - Circuit Simulation - Lecture Slides, Slides of Computer Science

These are the Lecture Slides of Circuit Simulation which includres Model Order Reduction, Implicit Moment Matching, Krylov Subspace Methods, Gaussian Elimination, Delta Transformation, Projection Framework, Conventional Design Flow etc. Key important points are: Explicit Moment Matching, Model Order Reduction, Implicit Moment Matching, Krylov Subspace Methods, Gaussian Elimination, Delta Transformation, Projection Framework, Conventional Design Flow

Typology: Slides

2012/2013

Uploaded on 03/22/2013

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CSE245: Computer-Aided Circuit
Simulation and Verification
Lecture Note 4
Model Order Reduction (2)
1
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CSE245: Computer-Aided Circuit

Simulation and Verification

Lecture Note 4

Model Order Reduction (2)

Model Order Reduction: Overview

2

  • Explicit Moment Matching
    • AWE, Pade Approximation
  • Implicit Moment Matching (Projection Framework)
    • Krylov Subspace Methods
      • PRIMA, SPRIM
  • Gaussian Elimination
    • TICER, Y-Delta Transformation

Parasitic Extraction

4

R,L,C Extraction

Model Order Reduction

Moment Matching Projection method

  • Key ideal of Model Order reduction:

“Moments Matching” and “Projection”

  • Step1: identify internal state function and variables.
  • Step2: Compose moments matching. (Pade, Taylor expression).
  • Step3: Project matrix with matching moments. (Block Arnoldi (PRIMA) or block Lanczos (PVL))
  • Step4: Get the reduced state function.

Congruence Transformation

7

  • Definition:
    • Property: Congruence transformation preserves semidefiniteness of the matrix

Krylov Subspace

8

  • Given an n x n matrix A and a n x 1 vector r the Krylov subspace is defined as
  • Given an n x q matrix Vq whose column vectors are v 1 , v 2 , …, vq. The span of Vq is defined as

PRIMA

10

  • step 1. Circuit Formulation
    • step 2. Find the projection matrix Vq
      • Arnoldi Process to generate Vq

PRIMA: Properties

11

  • Preserves passivity, and hence stability
  • Matches moments up to order q (proof in next slide)
  • Original matrices A and C are structured.
  • But and do not preserve this structure in general

SPRIM

13

  • Suppose Vq is generated by Arnoldi process as in PRIMA. Partition Vq accordingly
  • Recall
  • Construct New Projection Matrix

SPRIM

14

  • Congruence Transformation
  • Now structure is preserved
    • Transfer function for the reduced order model

TICER ( TI me C onstant E quilibration R eduction)

16

    1. Calculate time constant for each node
    1. Eliminate quick nodes and slow nodes
  • Quick node: Eliminate if
  • Slow node: Eliminate if
    1. Insert new R’s/C’s between former neighbors of N
  • If nodes j and k had been connected to N through g (^) jN and g (^) kN , add a conductance of value gjN g (^) kN /G (^) N between j and k
  • If nodes j and k had been connected to N through c (^) jN and g (^) kN , add a capacitor of value cjN g (^) kN /G (^) N between j and k

TICER: Issues

17

  • Fill-in
    • The order that nodes are eliminated matters
      • Minimum Degree Ordering can be implemented to reduce fill-in
    • May need to limit number of incident resistors to control fill-in
  • Error control leads to low reduction ratio
  • Accuracy
    • Matches 0th^ moment at every node in the reduced circuit.
    • Only Correct DC op point guaranteed