Graduate Student Ryan Pederson of Brigham Young University delivered this lecture for the Introduction to Radiation Effects Engineering online SCALE course.
Terrestrial radiation, primarily high‑energy neutrons generated by cosmic‑ray interactions in the atmosphere, poses a reliability challenge for field‑programmable gate array (FPGA)‑based network switches deployed in large‑scale data‑center and cloud environments. Because FPGA devices rely on extensive configuration memory, single‑event upsets (SEUs) can alter logic functions, routing, or internal control signals, potentially degrading network traffic. Understanding and mitigating these ground‑level radiation effects is essential for maintaining continuous operation of high‑density networking infrastructure.
The presentation details the physical mechanisms of neutron‑induced SEUs and their impact on configurable logic blocks and switch matrices, emphasizing the distinction between non‑persistent errors correctable by configuration scrubbing and persistent errors that require more aggressive protection. Mitigation strategies are examined, including periodic scrubbing against a golden configuration, duplication‑with‑compare (DWC) for error detection, and triple‑modular redundancy (TMR) for error masking, with discussion of resource constraints that limit full‑design replication.
A netlist‑level tool, SpiderNet, is introduced for automated partial replication of selected circuit elements, generating modified netlists that incorporate DWC or TMR. Fault‑injection experiments using a JTAG configuration manager on a NetFPGA Ethernet switch, combined with traffic‑generator monitoring and internal packet‑counter diagnostics, provide quantitative classification of error types and validation of mitigation effectiveness.
With this knowledge, learners can explain how terrestrial neutron flux influences FPGA switch reliability, compare the relative efficacy of scrubbing, DWC, and TMR, and devise partial TMR/DWC schemes that target the most vulnerable design regions to reduce persistent errors. They also acquire the ability to analyze fault‑injection data to identify and categorize error modes and to apply configuration‑scrubbing procedures that correct non‑persistent upsets, thereby informing robust design decisions for commercial network devices.