Software-based diagnosis for processors

  • Authors:
  • Li Chen;Sujit Dey

  • Affiliations:
  • University of California at San Diego, CA;University of California at San Diego, CA

  • Venue:
  • Proceedings of the 39th annual Design Automation Conference
  • Year:
  • 2002

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Abstract

Software-based self-test (SBST) is emerging as a promising technology for enabling at-speed test of high-speed microprocessors using low-cost testers. We explore the fault diagnosis capability of SBST, in which functional information can be used to guide and facilitate the generation of diagnostic tests. By using a large number of carefully constructed diagnostic test programs, the fault universe can be divided into fine-grained partitions, each corresponding to a unique pass/fail pattern. We evaluate the quality of diagnosis by constructing diagnostic-tree-based fault dictionaries. We demonstrate the feasibility of the proposed method by applying it to a processor example. Experimental results show its potential as an effective method for diagnosing larger processors.