Practical Macromodels for Digital I/O

1. Practical Macromodels for Digital I/O Paul Franzon paulf@ncsu.edu Madhavan Swaminathan, Michael Steer madhavan.swaminathan@ece.gatech.edumbs@ncsu.edu Acknowledgements: Ambrish Varma, Bhyrav Mutnury

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

3. I/O Macromodeling • Replace full Spice driver model with • Macromodel • Hides proprietary information • Speeds up simulation

4. 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

5. I/O Macromodels • Desirable Goals • Unique solution • Orthogonality • Multiple Verification Approaches • Physical basis • Human readability • Monotonic • Simulator Independent • Extendable to core noise SSN

6. 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/

7. 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

8. Parser -Extracts all relevant information from Command file S2IBIS -Calls Spice, analyzes data Prints results IBIS Model S2IBIS Command File -Header information -Component Description SPICE -HSPICE,PSPICE, SPICE2 SPICE3,SPECTRE Circuit Layout 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

9. 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

10. IBIS Alternatives • Current Work: • Numerical black-box methods • “Parametric” Models: • Stievano, Maio, and Canavero, Politecnico di Torino • Spline/Finite Time Difference • Swaminathan, Georgia Tech

11. 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

12. 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)

13. Physical Model Captures staged turn-on drivers Gain loss during switching event (Vgs) Second order effects = f(Vds) w=step function only in break before make drivers CML reduces CM dependence • Circuit Level: M1(T) S G Ids=k(Vgs-Vt)2 D M2(T) or etc.

14. 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

15. Proposal • Collaborative Effort: • NC State University • Georgia Tech • Politecnico di Torino

16. The Way Forward • 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. I=f(Vout) ErrorCurrentSource* I=f(Vout,Vdd/Vss) M@OP M=f(T,Vdd) Etc. *e.g. Numerically fitted error fn

17. 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

18. The Way Forward 2. Promulgate alpha standard • Develop SpicetoMacromodel 3. Evaluate and propagate more broadly

19. 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

20. 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

21. 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