Practical Macromodels for Digital I/O

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Practical Macromodels for Digital I/O

• Paul Franzon
• paulf_at_ncsu.edu
• Madhavan Swaminathan, Michael Steer
• madhavan.swaminathan_at_ece.gatech.edu mbs_at_ncsu.edu

Acknowledgements Ambrish Varma, Bhyrav Mutnury
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Outline

• Background
• Macromodeling Needs
• Requirements for Successful Macromodels
• Macromodeling Techniques
• IBIS
• Numerical Models
• Physical
• Proposal The Way Forward

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I/O Macromodeling

• Replace full Spice driver model
• with
• Macromodel
• Hides proprietary information
• Speeds up simulation

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I/O Macromodeling

• Required Goals
• Vendor-independent format
• Have to capture TX, RX, and package parasitic
  essentials
• Sufficiently accurate to be useful
• Easy to automatically generate from Spice and
  Measurements
• Easy to verify
• Easy and fast to simulate

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I/O Macromodels

• Desirable Goals
• Unique solution
• Orthogonality
• Multiple Verification Approaches
• Physical basis
• Human readability
• Monotonic
• Simulator Independent
• Extendable to core noise SSN

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IBIS

• IBIS
• Input Output Buffer Information Specification
• EIA Standard 656 -A
• Behavioral model of I/O buffers
• Model is represented as set of VI and VT curves.
• Fast simulations
• Protects proprietary information contained in the
  IC
• http//www.eda.org/pub/ibis/

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Basic IBIS Model

• A Basic model consist of
• Four I-V curves - pullup and pulldown
• - PWR and GND Clamp
• Two Ramps -dv/dt_rise, dv/dt_fall
• Die Capacitance and
• Packaging information

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Spice2Ibis

• Automatically converts a Spice deck to an IBIS
  file
• Over 1,000 active users
• Over 3,000 lines of code
• Was critical to success of IBIS language

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IBIS Limitations

• IBIS hard to scale for use with high speed I/O
• Up to 100 ps delay error
• Subtle inflections missed
• SSN over-predicted

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IBIS Alternatives

• Current Work
• Numerical black-box methods
• Parametric Models
• Stievano, Maio, and Canavero, Politecnico di
  Torino
• Spline/Finite Time Difference
• Swaminathan, Georgia Tech

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Numerical Methods

• Black Box Modeling
• Static Term
• istatic(k) w1(k)f1(k) w2(k)f2(k)
• Captures output impedance of driver
• IBIS
• f1 and f2 are fitted VI tables. i.e. I(Vout)
• Spline
• f1 and f2 are numerically fitted power series,
  i.e. I(Vout, .)
• Parametric
• Basis functions Gaussian or Sigmoid

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Numerical Methods

• Black Box Modeling
• Dynamic Term
• IBIS i(k) w1(k)V1(k)f1(k) w2(k)V2(k)f2(k)
• output physical Ccomp
• Spline
• f1, f2 dynamic by numerically fitted load
  capacitance (captures di/dt)
• Parametric
• Calculated as a function of past values, using
  Basis functions
• e.g. RBF using Gaussians

Vn(T)
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Physical Model
Captures staged turn-on drivers Gain loss during
switching event (Vgs) Second order effects
f(Vds) wstep function only in break
before make drivers CML reduces CM dependence

• Circuit Level

M1(T)
S
G
Idsk(Vgs-Vt)2
D
M2(T)
or
etc.
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Comments on Models

• IBIS
• No numerical flexibility to capture subtle
  physical effects
• Most physical (but very first order)
• Easy to automate
• Spline/FTD
• Input waveform dependence
• Less physical
• More accurate
• Relatively hard to automate
• Numerical fitting of power series
• Parametric
• Input waveform dependence
• Least physical
• Most accurate
• Harder to automate model production
• More complex numerical procedures

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Proposal

• Collaborative Effort
• NC State University
• Georgia Tech
• Politecnico di Torino

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The Way Forward

1. Find the compromise between complexity and
   automation, while considering other goals

Spline
RBF
IBIS 4.0
RBF Sigmoid Power Series Reduced Order
Power Series Wavelet basis fns Neural net
fitting Etc.
If(Vout) ErrorCurrentSource If(Vout,Vdd/V
ss) M_at_OP Mf(T,Vdd) Etc. e.g. Numerically
fitted error fn
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The Way Forward

• Test on standard driver set
• Conventional, LVDS, DDR, Other CML, Emerging
• Test Spice model formats in Freeda
• Evaluate
• Metrics
• Accuracy in predicting delay, peak SSN, xmitted
  SSN, Xtalk, refn noise
• Accuracy outside range where fitted
• Macromodel utility factors listed earlier
• Esp. Complexity of model fit procedure

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The Way Forward

• 2. Promulgate alpha standard
• Develop SpicetoMacromodel
• 3. Evaluate and propagate more broadly

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Proposed Consortium

• Set up industry consortium to fund this work
• Benefits to consortium members
• IC vendor companies
• Macromodel tuned to their drivers
• Early access to successful macromodel formats
• First to market
• CAD companies
• Early access to successful formats
• Influence macromodel for simulator compatibility

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Discussion (on the day)

• Acknowledgement and contribution of the highly
  accurate black box techniques contributed by
  Prof. Flavio Canavero and his group.
• George Katopis
• 1. Study and development of a tool that helps the
  user with the selection of black box option based
  on "expected" accuracy and time.
• 2. Automatic generation of the black box models

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Conclusions

• Ease of Use is just as important as model
  accuracy
• All macromodels are numerical black box format
• Key question is complexity and type of functions
  used