可扩展的FPGA图形模型来检测路由故障

L. Sterpone, G. Cabodi, S. Finocchiaro, C. Loiacono, F. Savarese, B. Du
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引用次数: 1

摘要

构成基于SRAM的FPGA的配置存储器的SRAM单元使此类FPGA特别容易受到软错误的影响。当电离辐射破坏电路中存储的数据时,就会发生软错误。在写入新数据之前,错误将持续存在。软误差长期以来一直被认为是一个潜在的问题,因为辐射可能来自各种来源。本文提出了一种基于路由方面的FPGA故障模型。从已知FPGA模型的网表描述出发,提出了故障情况下SRAM节点行为的图模型。它还对配置位控制中的软错误可能产生的逻辑影响进行分类,提供可能的故障数量的统计信息。最后给出了基于一组复杂基准计算的故障度量的定义,证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable FPGA graph model to detect routing faults
The SRAM cells that form the configuration memory of an SRAM-based FPGA make such FPGAs particularly vulnerable to soft errors. A soft error occurs when ionizing radiation corrupts the data stored in a circuit. The error persists until new data is written. Soft errors have long been recognized as a potential problem as radiation can come from a variety of sources. This paper presents an FPGA fault model focusing on routing aspects. A graph model of SRAM nodes behavior in case of fault, starting from netlist description of well known FPGA models, is presented. It is also performed a classification of possible logical effects of a soft error in the configuration bit controlling, providing statistics on the possible numbers of faults. Finally it is reported the definition of fault metrics computed on a set of complex benchmarks proving the effectiveness of our approach.
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