Fast fault injection techniques using FPGAs

L. Entrena
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引用次数: 4

Abstract

Summary form only given. As manufacturing technology progresses by reducing feature size, providing more integration density and increasing device functionality with lower voltages and more aggressive clock frequencies, the susceptibility to soft errors has grown to an unacceptable level in several application domains. Thus, designers need to assess the needs for soft error mitigation during the design cycle in order to adopt appropriate mitigation strategies. Fault injection is a widely used method to evaluate fault effects and fault tolerance. Fault injection is intended to provide information about fault effects covering several main goals: validate the design under test with respect to reliability requirements; detect weak areas that require error mitigation; and forecast the expected circuit behaviour in the occurrence of faults. In the first case, a typical fault injection approach consists in using a simulation tool to inject and propagate faults in a design model. However, simulation-based fault injection is quite slow. While it can be used to obtain statistical estimations of the soft error susceptibility of a circuit, identifying the critical components of a design is a much more complex task that generally requires huge fault injection campaigns in order to individually assess every component in the circuit. Similarly, huge fault injection campaigns are also required to validate highly protected designs in order to ensure a high fault coverage. In order to accelerate the fault injection process, emulation-based fault injection methods have been developed in recent years. These methods use FPGAs to prototype the circuit under test and support the fault injection mechanisms. This talk will describe recent advances in emulation-based fault injection with FPGAs that can provide unprecedented levels of performance, in the order of millions of faults per second, and support the analysis of Single Event Upset (SEU) and Single-Event Transient (SET) effects on complex circuits. Thanks to this dramatic boost in performance, detailed and accurate evaluations of soft error effects can be obtained to support the adoption of optimal error mitigation strategies. As an illustrative example, emulation-based fault injection enables full characterization of a microprocessor against soft errors on a gate/FF basis for a given workload. Multiple faults, such as Single Event Multiple Upset (SEMU) or Single Event Multiple Transient (SEMT), can also be successfully covered with these methods in an efficient manner.
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基于fpga的快速故障注入技术
只提供摘要形式。随着制造技术的进步,通过减小特征尺寸,提供更多的集成密度和增加器件功能,降低电压和更积极的时钟频率,软错误的易感性在几个应用领域已经发展到不可接受的水平。因此,设计人员需要在设计周期内评估软错误缓解的需求,以便采用适当的缓解策略。故障注入是一种广泛应用于评估故障影响和容错能力的方法。故障注入旨在提供有关故障影响的信息,包括几个主要目标:根据可靠性要求验证被测设计;检测需要减少错误的薄弱区域;并预测故障发生时的预期电路行为。在第一种情况下,典型的故障注入方法包括使用仿真工具在设计模型中注入和传播故障。然而,基于仿真的故障注入非常缓慢。虽然它可以用于获得电路软错误敏感性的统计估计,但识别设计的关键组件是一项更复杂的任务,通常需要大量的故障注入活动,以便单独评估电路中的每个组件。同样,为了确保高故障覆盖率,也需要大规模的故障注入活动来验证高度保护的设计。为了加快故障注入过程,近年来发展了基于仿真的故障注入方法。这些方法使用fpga对被测电路进行原型设计,并支持故障注入机制。本次演讲将介绍基于仿真的故障注入的最新进展,fpga可以提供前所未有的性能水平,以每秒数百万个故障的顺序,并支持分析复杂电路中的单事件干扰(SEU)和单事件瞬态(SET)效应。由于性能的显著提高,可以获得对软错误影响的详细和准确的评估,以支持采用最佳的错误缓解策略。作为一个说明性示例,基于仿真的故障注入可以在给定工作负载的门/FF基础上对微处理器的软错误进行全面表征。多个故障,例如单事件多次中断(SEMU)或单事件多次暂态(SEMT),也可以用这些方法以有效的方式成功地覆盖。
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