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Fine-Grained Module-Based Error Recovery in FPGA-Based TMR Systems
Space processing applications deployed on SRAM-based Field Programmable Gate Arrays (FPGAs) are vulnerable to radiation-induced Single Event Upsets (SEUs). Compared with the well-known SEU mitigation solution—Triple Modular Redundancy (TMR) with configuration memory scrubbing—TMR with module-based e...
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Published in: | ACM transactions on reconfigurable technology and systems 2018-03, Vol.11 (1), p.1-23 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Space processing applications deployed on SRAM-based Field Programmable Gate Arrays (FPGAs) are vulnerable to radiation-induced Single Event Upsets (SEUs). Compared with the well-known SEU mitigation solution—Triple Modular Redundancy (TMR) with configuration memory scrubbing—TMR with module-based error recovery (MER) is notably more energy efficient and responsive in repairing soft-errors in the system. Unfortunately, TMR-MER systems also need to resort to scrubbing when errors occur between sub-components, such as in interconnection nets, which are not recovered by MER. This article addresses this problem by proposing a fine-grained module-based error recovery technique, which can localize and correct errors that classic MER fails to do without additional system hardware. We evaluate our proposal via fault-injection campaigns on three types of circuits implemented in Xilinx 7-Series devices. With respect to scrubbing, we observed reductions in the mean time to repair configuration memory errors of between 48.5% and 89.4%, while reductions in energy used recovering from configuration memory errors were estimated at between 77.4% and 96.1%. These improvements result in higher reliability for systems employing TMR with fine-grained reconfiguration than equivalent systems relying on scrubbing for configuration error recovery. |
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ISSN: | 1936-7406 1936-7414 |
DOI: | 10.1145/3173549 |