An analysis of fault partitioning algorithms for fault partitioned ATPG

Abstract

Generation of test vectors for the VLSI devices used in contemporary digital systems is becoming much more difficult as these devices increase in size and complexity. Automatic Test Pattern Generation (ATPG) techniques are commonly used to generate these tests. Since ATPG is an NP complete problem with complexity exponential to circuit size, the application of parallel processing techniques to accelerate the process of generating test vectors is an promising area of research. The simplest approach to parallelization of the test generation process is to simply divide the processing of the fault list across multiple processors. Each individual processor then performs the normal rest generation process on its own portion of the fault list, typically without interaction with the other processors. The major drawback of this technique, called fault partitioning, is that the processors perform redundant work generating test vectors for faults covered by vectors generated on another processor. This problem has been solved with the introduction of dynamic load balancing and detected fault broadcasting. Previous research has indicated that algorithmic fault partitioning moderately improves the performance of fault partitioned ATPG without detected fault broadcasting by reducing redundant work. However algorithmic fault partitioning can add significant preprocessing time to the ATPG process. This paper presents results that show that algorithmic partitioning is unnecessary prior to fault partitioned parallel ATPG using detected fault broadcasting and dynamic load balancing. Considering preprocessing time, random fault partitioning is shown to be the most efficient technique for partitioning faults prior to fault partitioned ATPG.