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Empirical Mathematical Model of Microprocessor Sensitivity and Early Prediction to Proton and Neutron Radiation-Induced Soft Errors

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A mathematical model is described to predict microprocessor fault tolerance under radiation. The model is empirically trained by combining data from simulated fault-injection campaigns and radiation experiments, both with protons… Click to show full abstract

A mathematical model is described to predict microprocessor fault tolerance under radiation. The model is empirically trained by combining data from simulated fault-injection campaigns and radiation experiments, both with protons (at the National Center of Accelerators (CNA) facilities, Seville, Spain) and neutrons [at the Los Alamos Neutron Science Center (LANSCE) Weapons Neutron Research Facility at Los Alamos, USA]. The sensitivity to soft errors of different blocks of commercial processors is identified to estimate the reliability of a set of programs that had previously been optimized, hardened, or both. The results showed a standard error under 0.1, in the case of the Advanced RISC Machines (ARM) processor, and 0.12, in the case of the MSP430 microcontroller.

Keywords: radiation; mathematical model; model; microprocessor; soft errors; neutron

Journal Title: IEEE Transactions on Nuclear Science
Year Published: 2020

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