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FPGAs are increasingly being used in space and other harsh radiation environments. However, SRAM-based FPGAs are susceptible to radiation in these environments and experience upsets within the configuration memory (CRAM), causing design failure. The effects of CRAM upsets can be mitigated using triple-modular redundancy and configuration scrubbing. This work investigates the reliability of a soft RISC-V SoC system executing the Linux operating system mitigated by TMR and configuration scrubbing. In particular, this paper analyzes the failures of this triplicated system observed at a high-energy neutron radiation experiment. Using a bitstream fault analysis tool, the failures of this system caused by CRAM upsets are traced back to the affected FPGA resource and design logic. This fault analysis identifies the interconnect and I/O as the most vulnerable FPGA resources and the DDR controller logic as the design logic most likely to cause a failure. By identifying the FPGA resources and design logic causing failures in this TMR system, additional design enhancements are proposed to create a more reliable design for harsh radiation environments.
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Fault Injection of TMR Open Source RISC-V Processors using Dynamic Partial Reconfiguration on SRAM-based FPGAs
SRAM-based FPGAs are frequently used for critical functions in space applications. Soft processors implemented within these FPGAs are often needed to satisfy the mission requirements. The open ISA, RISC-V, has allowed for the development of a wide range of open source processors. Like all SRAM-based FPGA digital designs, these soft processors are susceptible to SEUs. This paper presents an investigation of the performances and relative SEU sensitivity of a selection of newly available open source RISC-V processors. Utilizing dynamic partial reconfiguration, this novel automatic test equipment rapidly deployed different implementations and evaluated SEU sensitivity through fault injection. Using BYU’s new SpyDrNet tools, fine-grain TMR was also applied to each processor with results ranging from a 20× to 500× reduction in sensitivity.
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- Award ID(s):
- 1738550
- PAR ID:
- 10345470
- Date Published:
- Journal Name:
- 2021 IEEE Space Computing Conference (SCC)
- Page Range / eLocation ID:
- 1 to 8
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/SCC49971.2021.00008
