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Quantitative SEU Fault Evaluation for SRAM-Based FPGA Architectures and Synthesis Algorithms

机译:基于SRAM的FPGA架构和综合算法的定量SEU故障评估

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This paper studies the SEU (Single Event Upset) fault for SRAM-based FPGAs. Considering detailed fault behavior on various circuit elements in a post-layout FPGA application, we develop a simulation-based SEU evaluation tool that quantifies fault contribution for each configuration bit. Using this tool and MCNC benchmark circuits, we study the fault characteristics of FPGA circuits and architectures. We show that interconnects not only contribute to the lion share of functional failures, but also have higher failure rate per configuration bit than LUTs. Particularly, multiplexers in local interconnects have the highest failure rate per bit. We find that tuning LUT and cluster sizes helps to reduce the rate (up to 38% in our experiments). In addition, we evaluate two recent fault mitigation algorithms IPD and IPF, which reduce LUT faults by an average of 74% and 15% respectively. But when interconnects are taken into account, the reduction via IPD which considers only LUT faults is merely 6% on chip level. Yet the reduction via IPF which implicitly considers interconnect faults is still around 15%. Therefore, synthesis algorithm should be evaluated with interconnect faults and future algorithms should be developed with consideration of interconnect faults explicitly.
机译:本文研究了基于SRAM的FPGA的SEU(单事件翻转)故障。考虑到布局后FPGA应用中各种电路元件的详细故障行为,我们开发了基于仿真的SEU评估工具,该工具可量化每个配置位的故障贡献。使用该工具和MCNC基准电路,我们研究了FPGA电路和架构的故障特性。我们证明,互连不仅导致功能故障的比例最大,而且每个配置位的故障率比LUT高。特别是,本地互连中的多路复用器每位故障率最高。我们发现,调整LUT和群集大小有助于降低速率(在我们的实验中最高为38%)。此外,我们评估了两种最新的故障缓解算法IPD和IPF,它们分别将LUT故障平均减少了74%和15%。但是,当考虑到互连时,仅考虑LUT故障的IPD减少量仅为芯片水平的6%。但是,通过IPF隐式考虑到互连故障的减少仍然约为15%。因此,应该对综合算法进行互连故障评估,并在未来的算法中明确考虑互连故障。

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