Post-silicon Trace Signal Selection Using Genetic Algorithm

Post-silicon verification is used to locate and eliminate the bugs that escaped from the pre-silicon verification. The most serious challenge for post-silicon verification is the limited observability of internal signals. Automatic signal selection technique is used to select a signal combination that can maximize the restoration of the untraced states to solve this challenge. In previous studies, structure-based technology and simulation-based technology cannot run fast and have a high restoration quality at the same time. Machine learning based technology have to select circuits as training set carefully. In this paper, i) we extend the restoration ratio to be applicable to FPGA netlist resources and ii) we propose a new signal selection technology using genetic algorithm which extends simulation-based technology and can achieve faster operation speed while ensuring the restoration quality.