1. On Timing- Independent False Path Identification Feng Yuan, Qiang Xu Cuhk Reliable Computing Lab, The Chinese University of Hong Kong ICCAD 2010

2. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

3. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

4. Introduction  False Path  The test vector which cannot propagate in function mode.  Used in STA of timing-driven placement.  In manufacturing testing is unnecessary and may cause over-testing.  Optimization does not help to improve the performance of the circuit.

5. Introduction (cont.)  Kinds of False Path  Timing-don’t-care false paths  Path in async. clock domain crossovers  Timing-independent false paths  Logically unsensitizable in function mode  Delay-dependent false paths  Logically sensitizable but dominated by one or more side-input signals all the time

6. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

7. Illegal State Identification  Previous Work[12]

8. False Path caused by Illegal State  If a path is activated only with illegal states in the circuit, this path is a false path.

9. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

10. Controlling Signal 0 x 0 1 x x 1 x 1 0 x x

11. Criterion  A path is a timing-independent false path iff there exist at least one on-path signal such that when it is a non-controlling value, one or more of its corresponding side-input signals are with controlling values in function mode.  Meet some illegal state?

12. Criterion (cont.)  A path is not a timing-independent false path iff there any on-path signal such that when it is a non-controlling value, one or more of its corresponding side-input signals are with non-controlling values in function mode.

13. Path Sensitizaton  Given a path P, to determine whether it is a timing-independent false path.  Propagate logic ‘0’and ‘1’ at launch point.

14. Proposed Examination Procedure  Phantom logic AND gate  Use AND gates and inverters to represent the illegal states.  Set output of AND gates to be logic ‘0’

15. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

16. Find False Path  The number of false paths is exponential to circuit size.  Find the root cause structures  Prime False path segment

18. Static Implication Learning  Consider illegal state: {FF0(1), FF2(1)}  Conduct implication for the inverse values of FF0(0), FF2(0) independently  FF0(0)=>B(0)=>G(0)  FF2(0)=>A(0)=>C(1) =>D(0)=>F(1)  Use counter-positive low

19. Suspicious Node Extraction  Suspicious Node  Starting point of S-Frontier  All the possible false segments can be detect.  The selected points are as less as possible.  Affect Node  The nodes have implications after Static Implication Learning.  Not all the affect nodes need to consider as the starting points.

20. S-Frontier Propagation  Do a BFS process to launch nodes with 0(1)  Created at each suspicious node  Launch 0(1) and propagate to new node  Add the implication and check if meet the illegal state.  Check the starting point is already in existing false path segment to avoid finding the same segment.

21. Outline  Introduction  Preliminaries  False Path Examination  Method  Experimental Results & Conclusion

22. Experiment Results  Benchmark  ISCAS’89  IWLS 2005  Environment  2GHz PC  1GB memory  Competitor  [5] Fast Identification of Untestable Delay Faults Using Implications

23. Experiment Results (cont.)  Use PrimeTime to fetch 5000 critical paths  Worse Case Delay(WCD)  Report the true critical paths delay

24. Experiment Results (cont.)  Use academic ATPG tool Atalanta [7]  Check whether we can find a solution to activate them.

25. Conclusion  Develop novel false path identification techniques by taking illegal states in the circuit into consideration.  The proposed solution find much more false paths than existing FPI techniques.