一种SRAM型FPGA单粒子效应故障注入方法

随着FPGA在航天领域的广泛应用,SRAM型FPGA的单粒子故障也越来越引起人们的重视,用故障注入技术模拟单粒子效应是研究单粒子效应对SRAM器件影响的重要手段,该文主要研究SRAM型FPGA单粒子翻转、单粒子瞬态脉冲的故障注入技术,并在伴随特性的基础上,提出一种单粒子瞬态脉冲故障注入技术。该方法使注入故障脉冲宽度达到...     

面向航空环境的多时钟单粒子翻转故障注入方法

随着新型电子器件越来越多地被机载航电设备所采用,单粒子翻转(Single Event Upset, SEU)故障已经成为影响航空飞行安全的重大隐患。首先,针对由于单粒子翻转故障的随机性,该文对不同时刻发生的单粒子翻转故障引入了多时钟控制,构建了SEU故障注入测试系统。然后模拟真实情况下单粒子效应引发的多时间点故障,研究了单粒子效应对基于FPGA构成的时序电路的影响,并在线统计了被测模块的失效数据和失效率。实验结果表明,对于基于FPGA构建容错电路,采用多时钟沿三模冗余(Triple Modular Redundancy, TMR) 加固技术可比传统TMR技术提高约1.86倍的抗SEU性能;该多时钟SEU故障注入测试系统可以快速、准确、低成本地实现单粒子翻转故障测试,从而验证了SEU加固技术的有效性。     

一种静态随机存储器型现场可编程门阵列的单粒子软错误率的软件分析方法

静态随机存取存储器(SRAM)型现场可编程门阵列(FPGA)在当前空间电子设备中取得了广泛的应用,尽管它对空间辐射引起的单粒子翻转效应极其敏感。在FPGA的配置存储器中发生的单粒子翻转造成的失效机理不同于传统的存储器中的单粒子翻转。因此,如何评价这些单粒子翻转对系统造成的影响就成了一个值得研究的问题。传统的方法主要分为辐照实验和故障注入两种技术途径。本文中提出了一种新的方法,可以用来分析单粒子翻转对构建在FPGA上的系统造成的影响。这种方法基于对FPGA底层结构以及单粒子翻转带来的失效机理的深入理解,从布局布线之后的网表文件出发,寻找所有可能破坏电路结构的关键逻辑节点和路径。然后通过查询可配置资源与相应的配置数据之间关系来确定所有敏感的配置位。我们用加速器辐照实验和传统的故障注入方法验证了这种新方法的有效性。     

SRAM型FPGA单粒子翻转模拟系统研究

SRAM型FPGA在空间辐照环境下,容易受到单粒子效应的影响,导致FPGA存储单元发生位翻转,翻转达到一定程度会导致功能错误。为了评估FPGA对单粒子效应的敏感程度和提高FPGA抗单粒子的可靠性,对实现故障注入的关键技术进行了研究,对现有技术进行分析,设计了单粒子翻转效应敏感位测试系统,利用SRAM型FPGA部分重配置特性,采用修改FPGA配置区数据位来模拟故障的方法,加速了系统的失效过程,实现对单粒子翻转敏感位的检测和统计,并通过实验进行验证,结果表明:设计合理可行,实现方式灵活,成本低,为SRAM型FPGA抗单粒子容错设计提供了有利支持。     

微处理器故障注入工具与故障敏感度分析

总结了单粒子效应的各种表现形式,明确在集成电路抗单粒子加固时应着重考虑单粒子翻转和单粒子瞬变.通过分析、对比大量故障注入方法,设计了基于仿真的自动故障注入及分析系统,具有模型准确、运行速度快、自动化程度高等特点.采用此系统分析了一款32bit RISC微处理器对单粒子翻转和单粒子瞬变两种故障的敏感度.通过注入约2×105个故障,保证了实验的统计意义.试验分析指出,在设计加固微处理器时应该着重考虑存储单元、时钟信号和关键模块.     

基于定向故障注入的SRAM型FPGA单粒子翻转效应评估方法

介绍了一种基于定向故障注入的SRAM型FPGA单粒子翻转效应评估方法。借助XDL工具,该方法解析了Virtex-4 SX55型FPGA的帧地址与物理资源之间的对应关系;将电路网表中的资源按模块分组,利用部分重构技术分别对电路整体及各分组相关的配置帧进行随机故障注入,以评估电路整体及其子模块的抗单粒子翻转能力;按模块分组对电路分别进行部分三模冗余(TMR)加固和故障注入实验,以比较不同加固方案的效果。实验结果表明:电路的抗单粒子翻转能力与其功能和占用的资源有关;在FPGA资源不足以支持完全TMR的情况下,该方法可以帮助设计者找到关键模块并进行有效的电路加固。     

一种多模式SRAM单粒子试验系统的设计与实现

提出了一种基于NIOS II的异步SRAM单粒子效应检测系统,用于评估抗辐射加固SRAM电路的抗单粒子效应能力.该检测系统可以对异步SRAM进行四种工作模式下的动态和静态检测,利用该检测系统在重离子加速器上对一款异步SRAM进行了单粒子效应试验,获得了5种离子的试验数据,统计分析后得到了器件的单粒子翻转阈值、单粒子翻转饱和截面和单粒子翻转在轨错误率,并与国外同款电路进行了对比,最后依据试验结果给出了评估结论.     

高速A/D转换器单粒子效应实时评估系统和方法研究

提出了一种在线实时检测评估高速A/D转换器(ADC)的单粒子效应的测试方法。基于该方法搭建了部分模块可复用的单粒子效应测试评估系统。系统由时钟生成模块、待测ADC模块、D/A转换器(DAC)转换输出模块、FPGA控制模块与上位机模块构成。对待测ADC模块进行重构,可完成对不同ADC器件的测试评估,提升了模块可复用性和测试效率。该系统通过监测电源引脚的电流变化、ADC内部寄存器值翻转情况、经过高速DAC转换输出的模拟波形,可实时测试评估ADC器件的单粒子锁定(SEL)、单粒子翻转(SEU)、单粒子瞬态(SET)、单粒子功能中断(SEFI)等效应。基于该系统对自主研发的具有JESD204B接口的12位2.6 GS/s高速ADC进行了单粒子效应试验。试验分析表明,该系统能准确高效评估高速ADC器件的单粒子效应。     

商用CMOS工艺SRAM脉冲中子辐射效应实验

为研究互补金属氧化物半导体(CMOS)工艺静态随机处理内存(SRAM)脉冲中子辐射效应机理,对SRAM翻转效应进行了蒙特卡罗模拟。该模拟基于脉冲中子辐照下SRAM翻转是单粒子翻转的叠加的假设,计算了单位翻转和伪多位翻转在总翻转数中的百分比。在西安脉冲反应堆上对3种特征尺寸商用SRAM开展了脉冲工况实验研究,得到了单位翻转和伪2位翻转数据,结合模拟结果分析了SRAM在脉冲中子作用下的翻转机制。     

质子引入的6T SRAM单粒子翻转截面预测模型

提出了一种基于SOI工艺6T SRAM单元质子辐射的单粒子饱和翻转截面的预测模型,该模型通过器件物理来模拟辐照效应,利用版图和工艺参数来预测质子引入的单粒子饱和翻转截面。该模型采用重离子的SPICE测试程序对质子辐射的翻转截面进行预测,该方法简单高效,测试实例表明在0.15μm SOI工艺下,预测的质子引入的单粒子翻转饱和截面和实际测试的翻转截面一致。     

NEW APPROACH TO EMULATE SEU FAULTS ON SRAM BASED FPGAS简

Field Programmable Gate Arrays （FPGAs） offer high capability in implementing of com- plex systems, and currently are an attractive solution for space system electronics. However, FPGAs are susceptible to radiation induced Single-Event Upsets （SEUs）. To insure reliable operation of FPGA based systems in a harsh radiation environment, various SEU mitigation techniques have been provided In this paper we propose a system based on dynamic partial reconfiguration capability of the modern devices to evaluate the SEU fault effect in FPGA. The proposed approach combines the fault injection controller with the host FPGA, and therefore the hardware complexity is minimized. All of the SEU injection and evaluation requirements are performed by a soft-core which realized inside the host FPGA Experimental results on some standard benchmark circuits reveal that the proposed system is able to speed up the fault injection campaign 50 times in compared to conventional method.     

Dependability evaluation of Altera FPGA-based embedded systems subjected to SEUs

Dependability evaluation of embedded systems due to the integration of hardware and software parts is difficult to analyze. In this paper, we have proposed an experimental method to determine sensitivity to soft errors in an embedded system exploiting Altera SRAM-based FPGAs. The evaluation is performed using both the hardware and software parts of the embedded system in a single framework. To do this, the HDL hardware model of the target system as well as the C-written software codes of the target system, are required. Both permanent and transient faults are injected into the partially- or fully-synthesizable hardware of the target system and this can be performed during the design cycle of the system. The fault injection is composed of injecting SEUs into user design memory, and used configuration memory of the exploited FPGA. Using the experimental results, the sensitivity of Altera FPGAs to SEU faults are analyzed and derived. The analytical results reveal that the configuration memory is more significant than design memory to the SEUs due to the relative number of SRAM bits. Moreover, in this framework, in the case of injecting SEUs into user memory, the fault injection experiments are accelerated by the cooperation between a simulator and the FPGA.     

Estimating the SEU failure rate of designs implemented in FPGAs in presence of MCUs

Due to the continuous reduction of the transistor size in electronic devices, it is becoming more and more likely for an SEU (Single Event Upset) to provoke a flip on two or more memory cells in SRAM based FPGAs, which is called a MCU (Multiple Cell Upset). Fault injection in the configuration memory of these devices has been used for many years, in order to evaluate their reliability. Emulation of these injections using the bitstream file has always been a simple, fast and cheap solution. Most of the existent SEU emulation tools do not consider the injection of MCUs, and they do not discuss the implication MCUs have on the overall failure rate of the system.In this work, bitstream based SEU emulators are updated to consider MCUs. It is discussed the necessity of injecting faults on physically adjacent cells, in order to emulate appropriately the effect of MCUs. Adjacent MCU injection has been compared theoretically with an approach considering MCUs as bunches of independent SBUs, as it is done in other emulation platforms. A Zynq-based fault injection platform has been used, in order to apply this way of emulating MCUs and validate the proposal.     

A fast,flexible, and easy-to-develop FPGA-based fault injection technique

By technology down scaling in nowadays digital circuits, their sensitivity to radiation effects increases, making the occurrence of soft errors more probable. As a consequence, soft error rate estimation of complex circuits such as processors is becoming an important issue in safety- and mission-critical applications. Fault injection is a well-known and widely used approach for soft error rate estimation. Development of previous FPGA-based fault injection techniques is very time consuming mainly because they do not adequately exploit supplementary FPGA tools. This paper proposes an easy-to-develop and flexible FPGA-based fault injection technique. This technique utilizes debugging facilities of Altera FPGAs in order to inject single event upset (SEU) and multiple bit upset (MBU) fault models in both flip-flops and memory units. As this technique uses FPGA built-in facilities, it imposes negligible performance and area overheads on the system. The experimental results show that the proposed technique is on average four orders of magnitude faster than a pure simulation-based fault injection. These features make the proposed technique applicable to industrial-scale circuits.     

Error propagation analysis using FPGA-based SEU-fault injection

Error propagation analysis is one of the main objectives of fault injection experiments. This analysis helps designers to detect design mistakes and to provide effective mechanisms for fault tolerant systems. However, error propagation analysis requires that the chosen fault injection technique provides a high degree of observability (i.e., the ability to observe the internal values and events of a circuit after a fault is injected). Simulation-based fault injection provides a high observability adequate for error propagation analysis. However, the performance of the simulation-based technique is inadequate to handle today’s hardware complexity. As an alternative, FPGA-based fault injection can be used to accelerate the fault injection experiments, but the communication time needed for observing the circuit behavior from outside of the FPGA imposes severe limitations on the observability. In this paper, an observation technique for FPGA-based fault injection is proposed which significantly reduces the communication time as compared with previous scan-based observation techniques. Furthermore, this paper describes a SEU-fault injection technique based on a chain of parallel registers which reduces the time needed for injecting SEU faults as compared to the previous scan-based fault-injection techniques. As a case study, a 32-bit pipelined processor has been used in the fault injection experiments. The experimental results show that when a high degree of observability is required (e.g., error propagation analysis), the proposed fault injection technique is over 1166 times faster than simulation-based fault injection, whereas the traditional scan-based technique can achieve only a speedup of about 2–3 – which means that the proposed technique is about 500 times faster than the traditional scan-based technique. Such results are supported by theoretical performance analysis. This speed increase has been achieved without excessive increase in FPGA resource overhead, for example, the FPGA overhead of the proposed technique is only 2  3% higher than that of the traditional scan-based technique.     

An FPGA-based dynamically reconfigurable platform for emulation of permanent faults in ASICs

FPGA-based emulation of permanent faults in ASICs can considerably improve the fault simulation time compared to traditional software-based approaches. Moreover, a hardware-based solution provides realistic behavior during fault emulation which is often required in safety-critical systems' validation. Previous emulation approaches not only suffers from considerable area (for instrumentation) and reconfiguration (for fault injection) overheads but also provides limited coverage of the target faults (and fault sites). The latter is due to difficulties in establishing a fault model equivalence when the ASIC structural netlist is passed through the design automation phases of an FPGA. This paper presents a novel approach for fast emulation of permanent faults in ASICs on state-of-the-art dynamically reconfigurable SRAM-based FPGAs while achieving fault model equivalence. Our proposed approach leverages localized run-time in-place Look Up Table (LUT) reconfigurations to avoid the time-consuming bitstream generation process for every ASIC fault. Moreover, the speed of fault injection is enhanced by direct LUT configuration data modification inside a bitstream frame. This results in 17 and 4 times improvements in fault injection speeds over vendor-provided LUT modification libraries and existing partial bitstream based approaches respectively. However, this improvement is achieved at an average 1.2 and 1.1 times degradation in area and delay metrics for the considered mapped circuits which is affordable considering the benefits in terms of the emulation speed.     

Emulation-based fault analysis on RFID tags for robustness and security evaluation

This paper presents an FPGA (field-programmable gate array) based fault emulation system for analysis of fault impact on security and robustness of RFID (radio frequency identification) tags. This emulation system that deals with any RFID protocol consists of two tag-reader pairs, a fault injection module and an emulation controller all implemented in a single FPGA. The designed approach performs single event upset (SEU) and single event transient (SET) fault injection and permits with high flexibility to set communication scenarios and related parameters. Moreover, we propose a classification of produced errors to evaluate fault impacts and identify most sensitive tag flip-flops causing large number of failures and security concerns. The proposed fault injection approach provides suitable means to increase tags' security and robustness. In our experimentation campaign, an ultra-high frequency (UHF) tag architecture has been exposed to intensive SEU and SET fault injections. The duration of the campaign including results analysis is 30 min in where 6,215,316 faults are experimented. Our results have shown that the tag has tolerated 61.82% of SEUs and 67.83% of SETs. The flip-flops that constitute the tag FSM (finite state machine) have been identified as the most sensitive parts causing large number of failures.     

基于SRAM型FPGA单粒子效应的故障传播模型

SRAM型FPGA在辐射环境中易受到单粒子翻转的影响,造成电路功能失效.本文基于图论和元胞自动机模型,提出了一种针对SRAM型FPGA单粒子效应的电路故障传播模型.本文将单粒子翻转分为单位翻转和多位翻转来研究,因为多位翻转模型还涉及到了冲突处理的问题.本文主要改进了耦合度的计算方式,通过计算FPGA布局布线中的相关配置位,从而使得仿真的电路故障传播模型更接近于实际电路码点翻转的结果,与以往只计算LUT相关配置位的方法比较,平均优化程度为19.89%.最后阐述了本模型在故障防御方面的一些应用,如找出最易导致故障扩散的元胞.     

Hybrid time and hardware redundancy to mitigate SEU effects on SRAM-FPGAs: Case study over the MicroLAN protocol

SRAM-based field programmable gate arrays (FPGAs) are particularly sensitive to single event upsets caused by high-energy space radiation. Single Event Upset (In order to successfully deploy the SRAM-FPGA based designs in aerospace applications, designers need to adopt suitable hardening techniques. In this paper, we describe novel hybrid time and hardware redundancy (HT&HR) structures to mitigate SEU effects on FPGA, especially digital circuits that are designed with bidirectional ports. The proposed structures that combine time and hardware redundancy decrease the SEU propagation mechanisms among the redundant hard units. Analysis results and fault injection experiments on some standard ISCAS benchmarks and MicroLAN protocol, as a case study over the bidirectional ports, show that the capability of tolerating SEU effects in HT&HR technique increases up to 70 times with respect to solely hardware redundant versions. On average, the proposed method provides 39.2 times improvement against single upset faults and 14.9 times for double upset faults; however it imposes about 14.7% area overhead. Also, for the considered benchmarks, HT&HR circuits become 8.8% faster on the average than their TMR versions.