Download Debug Automation from Pre-Silicon to Post-Silicon by Mehdi Dehbashi, Görschwin Fey PDF

By Mehdi Dehbashi, Görschwin Fey

ISBN-10: 3319093088

ISBN-13: 9783319093086

ISBN-10: 3319093096

ISBN-13: 9783319093093

This ebook describes automatic debugging methods for the insects and the faults which seem in numerous abstraction degrees of a method. The authors hire a transaction-based debug method of structures on the transaction-level, announcing the right kind relation of transactions. the automatic debug method for layout insects unearths the capability fault applicants at RTL and gate-level of a circuit. Debug concepts for good judgment insects and synchronization insects are validated, permitting readers to localize the main tough insects. Debug automation for electric faults (delay faults)finds the possibly failing speedpaths in a circuit at gate-level. a number of the debug techniques defined in achieving excessive prognosis accuracy and decrease the debugging time, shortening the IC improvement cycle and lengthening the productiveness of designers.

  • Describes a unified framework for debug automation used at either pre-silicon and post-silicon stages;
  • Provides techniques for debug automation of a approach at diverse degrees of abstraction, i.e., chip, gate-level, RTL and transaction level;
  • Includes thoughts for debug automation of layout insects and electric faults, in addition to an infrastructure to debug NoC-based multiprocessor SoCs.

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Additional info for Debug Automation from Pre-Silicon to Post-Silicon

Example text

LBA is as accurate as QBF [SFD10] in 82 % of the experiments (14 experiments), while MSPI and LMBA are as accurate as QBF [SFD10] in 71 % of the experiments (12 experiments). Overall, Fig. 13 compares the heuristic and random methods to the exact formal method with respect to the diagnosis accuracy. The diagram shows for which percentage of the experiments, each heuristic method is as accurate as the exact formal method. 2, LBA has a good accuracy but long run time. 6 Experimental Results 45 Fig.

First the faulty design is converted into CNF. Then additional constraints are inserted into the CNF. Line 2 fixes the number of fault candidates having an X value. This number is specified by L. 4 Minimization of Sensitized Path Intersection 37 Fig. 7 Automated debugging using MSPI method Fig. 8 MSPI function least on one output. At this point, different methods can be applied for finding the diagnostic traces. One method can be simply finding all existing diagnostic traces according to the applied constraints (replacing lines 5–13).

This number is specified by L. 4 Minimization of Sensitized Path Intersection 37 Fig. 7 Automated debugging using MSPI method Fig. 8 MSPI function least on one output. At this point, different methods can be applied for finding the diagnostic traces. One method can be simply finding all existing diagnostic traces according to the applied constraints (replacing lines 5–13). The weakness of this method is that usually there are many solutions with respect to L. Thus, the performance is biased by increasing the run time significantly.

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Debug Automation from Pre-Silicon to Post-Silicon by Mehdi Dehbashi, Görschwin Fey


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