Robust Reconfigurable Scan Networks
Natalia Lylinaa, Chih-Hao Wangb and Hans-Joachim Wunderlichc
ITI, University of Stuttgart, Pfaffenwaldring 47, D-70569 Stuttgart, Germany
alylina@informatik.uni-stuttgart.de
bwangco@informatik.uni-stuttgart.de
cwu@informatik.uni-stuttgart.de
ABSTRACT
Abstract—Reconfigurable Scan Networks (RSNs) access the evaluation results from embedded instruments and control their operation throughout the device lifetime. At the same time, a single fault in an RSN may dramatically reduce the accessibility of the instruments. During post-silicon validation, it may prevent extracting the complete data from a device. During online operation, the inaccessibility of runtime-critical instruments via a defect RSN may eventually result in a system failure. This paper addresses both scenarios above by presenting robust RSNs. We show that by making a small number of carefully selected spots in RSNs more robust, the entire access mechanism becomes significantly more reliable. A flexible cost function assesses the importance of specific control primitives for the overall accessibility of the instruments. Following the cost function, a minimized number of spots is hardened against permanent faults. All the critical instruments as well as most of the remaining instruments are accessible through the resulting RSNs even in the presence of defects. In contrast to state-of-theart fault-tolerant RSNs, the presented scheme does not change the RSN topology and needs less hardware overhead. Selective hardening is formulated as a multi-objective optimization problem and solved by using an evolutionary algorithm. The experimental results validate the efficiency and the scalability of the approach.
Keywords: Reconfigurable Scan Networks, Selective Hardening, Multi-Objective Optimization, Synthesis.
