1 Sources of Component Failures On-Die Temperature variations SEU - soft errors Parametric variations Random Defects random defects parametric variations.

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Presentation transcript:

1 Sources of Component Failures On-Die Temperature variations SEU - soft errors Parametric variations Random Defects random defects parametric variations catastrophic parametric deterministic transient Design errors soft errors design errors probabilistic permanent soft hard Demand integrated silicon debug and fault diagnosis solutions

2 Integrated Diagnosis for Design & Manufacturing  Three different tasks but similar underlying principles:  Design Error Diagnosis  Complementing either formal verification or simulation-based verification  Silicon Debug  Diagnosing design bugs using one or several fabricated devices  Fault Diagnosis  Based on a small number of failed chip data  Based on a large number of chip data

3 Reconfiguration  Situation: 100M transistors, unlikely all of them within spec range and completely functional  Reconfiguration may be imperative  Self-test -> diagnosis -> reconfiguration  Done in several steps: from wafer probe to field  Sounds familiar?  Memory: self-test, self-diagnosis, self-repair, fault tolerance  RF: adding digital circuitry for self-calibration  fine-tuning performance  more robust to process, temperature and voltage variations  yield improvement

4 Reliability & Re-configurability  Topics  Integrated diagnosis for design and manufacturing  Embedded memory  Random logic  Regular ASIC  Reconfiguration for reliable design  Self-calibration architectural design  Timing-error-tolerant architectural design  DFM – new computational and algorithmic aspects of OPC & PSM for sub-45nm technologies  Team  US: UCSB  Taiwan: NTHU, NTU  China: ZJU

5 Fundamental Algorithms  Hybrid Constraint Solver  Integrating Boolean SAT with Linear Integer Arithmetic Solving for Sequential Systems  For RTL & system-level verification, test and synthesis applications

6 Education  Architecture and System issues for nano technology

7 Collaboration  Kevin Wang – UCLA  Evelyn Hu – UCSB  Andy Yao - TsingHua

8 Prof. Yan  DFM: OPC and PSM for sub-50nm technology  Formal verification  Focus on computational and algorithmic aspects of nano- electronics