Challenges and Solutions in Modeling and Simulation of Device Self-heating, Reliability Aging and Statistical Variability Effects

Transcription

1 Challenges and Solutions in Modeling and Simulation of Device Self-heating, Reliability Aging and Statistical Variability Effects Dehuang Wu, Joddy Wang 2018 Synopsys, Inc. 1

2 Outline Device aging, self-heating effects and impacts Challenges in circuit simulation and design verification SNPS solutions Summary 2018 Synopsys, Inc. 2

3 MOS Reliability is a Growing Concern [Wikipedia] [Alain Bravaix] More severely impact on design in advanced nodes Must be addressed at design stage prior to production 2018 Synopsys, Inc. 3

4 Reliability Aging in Automotive Applications Automotive electronics: Would you accept 10% probability for your car to break down? Connected devices: Shipments will top 2 billion units in 2015 need for low failure rate 200 components /ECU 50 Electronic Control Modules (ECUs) components components 285M 155M 300M 10 ppm/ component total failure probability = 10% 1010M 200M Aging Analysis is a way of modeling and predicting the failure modes and mean time to failure of complex systems 2018 Synopsys, Inc. 4

5 Device Self-Heating in Advanced Technology Nodes FINFET Better gate control, Short-channel effect, more conducting area per footprint Difficult to transfer Heat to substrate FDSOI Better gate control with planner structure, Vt modulation Difficult to transfer Heat to substrate due to oxide [TSMC OIP 2015] 2018 Synopsys, Inc. 5

6 Device Self-heating Effect Impact Analog/RF Designs 2018 Synopsys, Inc. 6

7 Holistic Requirements for Simulation-based Failure Rate Analysis HSPICE FineSim CustomSim 2018 Synopsys, Inc. 7

8 SPICE Model Requirements Beyond Compact Model LDE and Statistical Self-heating Local heat during current flow Confined structure Scaling and power density exacerbate the effect Interact with device aging Device Aging: HCI, BTI, TDDB Scaling exacerbate HCI Interaction of SHE Scaling drive more concerns in TDDB 2018 Synopsys, Inc. 8

9 Efficient Self-heating Simulation in HSPICE FinFET, FDSOI devices see stronger self-heating effect. Foundry SPICE model turns on SHE model component. Performance and convergence impact Auxiliary thermal network d g s b T [V] d g s b T Regular MOSFET stamping matrix - p/ vd - p/ vg - p/ vs - p/ vb Id/ T Ig/ T Is/ T Ib/ T - p/ T + 1/Rth+Cth/ t Vd Vg Vs Vb T RHS HSPICE efficient SHE solution No accuracy loss Close to run time w.r.t non-she 2018 Synopsys, Inc. 9

10 Comprehensive Device Aging Analysis (MOSRA) HSPICE, FineSim SPICE, CustomSim Custom Compiler Environment Aging simulation with built-in models, BTI, HCI, TDDB Aging-aware variation analysis Foundry certified for FinFET & Automotive grade flow Comprehensive setup, run for BTI, HCI, TDDB Detailed results of degradation effects Analyze results with Custom WaveView Fresh simulation Result browser Stress computation Post-stress simulation Monte Carlo simulation Degradation due to Device Aging Cross-probe to Custom WaveView 2018 Synopsys, Inc. 10

11 Efficient Monte Carlo Solution Failure rate estimation requires one million+ or more Monte Carlo samples Statistical Analysis 10 samples SRAM bit cell 128 cores approx. 10 hrs Statistics plot Industry adoption This technology is very useful and it will be used extensively Sigma Amplification: 100 simulations with 2x amplification factor match well with 100M simulated! Correlation analysis Importance analysis Histogram table Yield analysis, Q-Q plot, etc Synopsys, Inc. 11

12 Self-heating and Variation Aware MOSRA MOSRA is a 2-step simulation: 1) Age computation, 2) Post-age analysis Process variability impact need to be considered in both step simulations for accuracy 2018 Synopsys, Inc. 12

13 Simulation-based Failure Rate Analysis Flow (Simulator) (Simulator) (Simulator) 2018 Synopsys, Inc. 13

14 Comprehensive Tool Set and Features ISO Certified HSPICE High-Sigma Analysis Monte Carlo Custom Compiler Environment Aging EM / IR FineSim SPICE Smart Corner Simulation CustomSim High Cap. Monte Carlo Safe Operating Area Robust Design Corners Mixedsignal Design Outliers Violation Contributor 2018 Synopsys, Inc. 14

15 Summary Device aging and self-heating effects are important in advanced technology nodes and automotive applications Simulation based reliability and failure rate analysis impose holist requirements and challenges to circuit simulation Synopsys provides comprehensive solutions considering accuracy and turnaround time 2018 Synopsys, Inc. 15

16 Acknowledgements Thanks to Xuguang Shen, Zhaoping Chen, Yan Luo from HSPICE and SPICE model team, for their valuable discussions and contributions 2018 Synopsys, Inc. 16