FPGAs are susceptible to radiation-induced effects that change the data in the configuration memory. These effects can cause the malfunction of the system. Triple modular redundancy has extensively been used to improve the circuit's cross-section. However, TMR has shown to be particularly susceptible to radiation effects that affect more than one memory cell such as Multiple Cell Upsets (MCU) or micro-Single Event Functional Interrupts (micro-SEFI). This work describes a statistical technique to extract Multi-Cell Upset (MCU) and micro-SEFI events from raw radiation upset data. The technique uses Poisson statistics to identify patterns in the data. The most common patterns are selected using Poisson statistics. The selected patterns are used to reconstruct MCU events. The results show the distribution of MCU, micro-SEFis, and single-bit upsets for several radiation tests. Additionally, the results show the MCU distribution based on the number of bits affected by the event. This work details the process of reconstructing MCU data and also the process to use these data during a fault injection campaign. The results show that by using MCU fault injection it is possible to replicate failures seen in the radiation test and even induce more failures than seen in the radiation test. This shows the importance of extracting MCUs from radiation data and use them to evaluate TMR-protected designs.
College and Department
Ira A. Fulton College of Engineering and Technology; Electrical and Computer Engineering
BYU ScholarsArchive Citation
Perez Celis, Juan Andres, "Statistical Method for Extracting Radiation-Induced Multi-Cell Upsets and Anomalies in SRAM-Based FPGAs" (2021). Theses and Dissertations. 9287.
FPGA, radiation effects, multiple-cell upset, micro-SEFI, SEU, SEE, Poisson statistics