1. Clustering Techniques and Statistical Fault Injection for Selective Mitigation of SEUs in Flip-Flops
- Author
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Astrophysics Group, Keele University ; Keele University, Techniques of Informatics and Microelectronics for integrated systems Architecture (TIMA) ; CNRS - Université Joseph Fourier - Grenoble I - Institut National Polytechnique de Grenoble (INPG), Cisco Systems ; Cisco Systems, Department of Electrical Engineering & Computer Science [Nashville] ; Vanderbilt University of Nashville, Evans, A., Nicolaidis, M., Wen, S.J., Rocha De Assis, T., Astrophysics Group, Keele University ; Keele University, Techniques of Informatics and Microelectronics for integrated systems Architecture (TIMA) ; CNRS - Université Joseph Fourier - Grenoble I - Institut National Polytechnique de Grenoble (INPG), Cisco Systems ; Cisco Systems, Department of Electrical Engineering & Computer Science [Nashville] ; Vanderbilt University of Nashville, Evans, A., Nicolaidis, M., Wen, S.J., and Rocha De Assis, T.
- Abstract
ISBN 978-1-4673-4953-6, International audience, In large SoCs, managing the effects of soft-errors in flip-flops is essential, however, selective mitigation is necessary to minimize the area and power costs. The identification of the optimal set of flip-flops to protect typically requires compute-intensive fault-injection campaigns. We present new techniques which group similar flip-flops into clusters to significantly reduce the number of fault injections. The number of required fault injections can be significantly lower than the total number of flip-flops and in one industrial design with over 100,000 flip-flops, by simulating only 2,100 fault injections, the technique identified a set of 4.1% of the flip-flops, which when protected, reduced the critical failure rate by a factor of 7x.