An accurate and efficient SSO/SSN simulation methodology for 45 nm LPDDR

I/O interface

Dr. Souvik Mukherjee, Dr. Rajen Murugan (Texas Instruments Inc.)

Vinayakam Subramanian, Dr. Ji Zheng (Apache Design Solutions Inc.)

Introduction Needs:

Memory interface performance validation is becoming increasingly complex

Increasing speeds, design configurations, design cost optimization in die, package, board

Lower supply voltages allow for lower noise margins (due to SSO/SSN, crosstalk, ISI) on I/O performance metrics.

Look-ahead and comprehensive analysis needed during IO placement/package prototyping early analysis, signoff

Challenges: SSO/SSN analysis is a coupled Signal-Integrity and Power-Integrity problem.

Requires concurrent modeling and simulation of the chip-package-board Signal delivery network (SDN) and power delivery network (PDN).

Combine the varying (and often conflicting) simulation requirements of the SDN and PDN.

Requires a robust and automated environment to seamlessly integrate the system-level model constituents.

Needs to overcome the challenge of computation complexity of traditional simulations using transistor-level model of the I/O circuits.

An “ideal” SSO/SSN analysis methodology needs to accurately trade off between accuracy and efficiency of modeling, extraction and simulation flows

An “ideal” SSO/SSN analysis methodology needs to accurately trade off between accuracy and efficiency of modeling, extraction and simulation flows2

Proposed I/O Characterization Methodology An efficient and accurate “system-level” methodology for characterization of LPDDR I/Os

has been presented.

The proposed flow leverages the underlying physics of the SSO/SSN to optimize the modeling and simulation of the system-level constituents

System-level silicon measurements on a actual product have been performed to benchmark the accuracy of the proposed flow

3

Sentinel-SSO Methodology (1/2)

4

Sentinel-SSO Methodology (2/2)

Aggressor Modeling MethodologyAggressor Modeling Methodology

5

Performance benefit from Sentinel-SSO Macromodel

More than 2X performance improvement with negligible loss in accuracy

– 5hrs 10mins with full transistor level spice model for all the DDR bank IOs

– 2hrs 20mins with Sentinel-SSO Macromodel for all IOs except victim and two aggressors on each side

Red : Full Transistor model-based SPICE simulation

Blue: Sentinel-SSO macromodel-based simulation

6

Model-to-hardware correlation Silicon validation platform was set up with the device-memory interface. Software code was prepared to exercise the memory interface with minimal extraneous SOC activity. TDR measurements (for passive channel characterization) and link RLGC/S-parameter parasitic model

generation Micro-probing of data/strobe bit waveforms during LPDDR WRITE transactions (under controlled

environment) Noise measurements on Power Distribution network during LPDDR switching activity

7Block schematic of the hardware setup

TDR Simulation Flow

Import of Memory PCB layout in Sentinel-PSI

Import of Memory PCB layout in Sentinel-PSI

Model reduction, Technology stack-up, port-setup, analysis settings

Model reduction, Technology stack-up, port-setup, analysis settings

Parasitic extraction and s-parameter model output

Parasitic extraction and s-parameter model output

SPICE analysis with TDR pulse (@ probe locations) on extracted PCB

model

SPICE analysis with TDR pulse (@ probe locations) on extracted PCB

model

Overlay with measurement dataOverlay with measurement data

Import of Memory PCB, intermediate PCB, CHIP PCB layouts in Sentinel-

PSI

Import of Memory PCB, intermediate PCB, CHIP PCB layouts in Sentinel-

PSI

Model reduction, Technology stack-up, port-setup, analysis settings for

each PCB

Model reduction, Technology stack-up, port-setup, analysis settings for

each PCB

Parasitic extractions and s-parameter model outputs

Parasitic extractions and s-parameter model outputs

SPICE analysis with TDR pulse (@ probe locations) on cascaded PCB

models

SPICE analysis with TDR pulse (@ probe locations) on cascaded PCB

models

Overlay with measurement dataOverlay with measurement dataSimulation Flow with only Memory PCB

Simulation flow with full CHIP-MEMORY channel

Addition of socket modelsAddition of socket models

8

TDR characterization of memory and full channel (CHIP-to-MEMORY )

//i.cmpnet.com/planetanalog/features/Ansoft_flex/Fig4.jpg

Depiction of data bit routing (on DDR PCB w/o DDR IC) characterization with TDR setup

Red : SimulationGreen: Measurement

Model-to-hardware correlationTime (ps)

Imp

edan

ce (

ohm

s)

TDR methodology

9

SSO-SSN Simulation Flow

Import of Memory PCB, intermediate PCB, CHIP PCB

layouts in Sentinel-PSI

Import of Memory PCB, intermediate PCB, CHIP PCB

layouts in Sentinel-PSI

Model reduction, Technology stack-up, port-setup, analysis settings for

each PCB

Model reduction, Technology stack-up, port-setup, analysis settings for

each PCB

Parasitic extractions and coupled SI/PI s-parameter model outputs

Parasitic extractions and coupled SI/PI s-parameter model outputs

Addition of socket modelsAddition of socket models

Import of package in 3D EM ToolImport of package in 3D EM Tool

Model reduction, Technology stack-up, port-setup, analysis

settings for package

Model reduction, Technology stack-up, port-setup, analysis

settings for package

Parasitic extractions and coupled SI/PI s-parameter model outputs

Parasitic extractions and coupled SI/PI s-parameter model outputs

Output coupled SI/PI s-parameter model of package

Output coupled SI/PI s-parameter model of package

CHIP databaseCHIP database Sentinel-SSO connectivity and Sentinel-SSO connectivity and simulation frameworksimulation framework

Sentinel-SSO connectivity and Sentinel-SSO connectivity and simulation frameworksimulation framework

O/P waveform, timing data

O/P waveform, timing data

10

Supply bounce with activity

Pk-to-pk noise on VDDS-VSSS is ~230 mV(no MPU activity)

Yellow: DQS2Cyan: DQ22Magenta: CLKN/CLKPGreen: VDDS-VSSS

Measurement waveform capture: DQ22/DQS2/CLK/VDDS-VSSS (@100 MHz)

11

Model-to-hardware correlation for data waveform

Red : SimulationGreen: Measurement

Time (ns)

Vol

tage

(v)

12

Conclusions

13

-  Develop an efficient IO macromodeling capability to analyze system-level SSO/SSN on a high-speed digital memory interface.

   Demonstrated on an LPDDR memory interface for a 45nm SoC design.

Established model-to-hardware correlation.

   Innovative capability that alleviates the burden of traditional methodologies that are computationally prohibitive.