A GA-Based Method for High-Quality X-Filling to Reduce Launch Switching Activity in At-speed Scan Testing

Abstract

Power-aware X-filling is a preferable approach to avoiding IR-drop-induced yield loss in at-speed scan testing. However, the quality of previous X-filling methods for reducing launch switching activity may be unsatisfactory, due to low effect (insufficient and global-only reduction) and/or low scalability (long CPU time). This paper addresses this quality problem with a novel, GA (Genetic Algorithm) based X-filling method, called GA-fill. Its goals are (1) to achieve both effectiveness and scalability in a more balanced manner, and (2) to make the reduction effect of launch switching activity more concentrated on critical areas that have higher impact on IR-drop-induced yield loss.Evaluation experiments are being conducted on benchmark and industrial circuits, and initial results have demonstrated the usefulness of GA-fill.