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With aggressive technology scaling, soft errors have become a major threat in modern computing systems. Several techniques have been proposed in the literature and implemented in actual devices as countermeasures to this problem. However, their effectiveness in ensuring error-free computing cannot be ascertained without an accurate reliability estimation methodology. This can be achieved by using the vulnerability metric: the probability of system failure as a function of the time the program data are exposed to transient faults. In this work, we present a gemV-tool, a comprehensive toolset for estimating system vulnerability, based on the cycle-accurate gem5 simulator. The three main characteristics of the gemV-tool are: (i) fine-grained modeling: vulnerability modeling at a fine-grained granularity through the use of RTL abstraction; (ii) accurate modeling: accurate vulnerability calculation of speculatively executed instructions; and (iii) comprehensive modeling: vulnerability estimation of all the sequential elements in the out-of-order processor core. We validated our vulnerability models through extensive fault injection campaigns with <3% correlation error and 90% statistical confidence. Using the gemV-tool, we made the following observations: (i) the vulnerability of two microarchitectural configurations with similar performance can differ by 82%; (ii) the vulnerability of a processor can vary by more than 10×, depending on the implemented algorithm; and (iii) the vulnerability of each component in the processor varies significantly, depending on the ISA of the processor. [ABSTRACT FROM AUTHOR]

Aggressive transistor scaling down and near-threshold computing have rendered modern microprocessor susceptible to soft errors. Software approaches that protect computations against soft errors are desirable because they offer flexible protection and are suitable for mixed-critical systems. In particular, fine-grain instruction duplication based techniques are deemed to be most effective; however, many of the existing instruction duplication techniques either suffer from many vulnerable intervals or are not suitable for multithreaded environments. In this paper, we present multithreded near zero silent data corruption (MZDC), a software scheme which provides high-level processor-wide error coverage in multithreaded environments. MZDC duplicates all programs' instructions and uses diagnosis block after replicated memory operations to overcome the inconsistency issue in a multithread environment. Statistical fault injection experiments on a dual-core ARM cortex-A53 $\mu$ architecturally simulated microprocessor show that on average, MZDC can achieve more than 37$\times$ better fault coverage than the state-of-the-art. [ABSTRACT FROM PUBLISHER]

Soft error is one of the most important design concerns in modern embedded systems with aggressive technology scaling. Among various microarchitectural components in a processor, cache is the most susceptible component to soft errors. Error detection and correction codes are common protection techniques for cache memory due to their design simplicity. In order to design effective protection techniques for caches, it is important to quantitatively estimate the susceptibility of caches without and even with protections. At the architectural level, vulnerability is the metric to quantify the susceptibility of data in caches. However, existing tools and techniques calculate the vulnerability of data in caches through coarse-grained block-level estimation. Further, they ignore common cache protection techniques such as error detection and correction codes. In this article, we demonstrate that our word-level vulnerability estimation is accurate through intensive fault injection campaigns as compared to block-level one. Further, our extensive experiments over benchmark suites reveal several counter-intuitive and interesting results. Parity checking when performed over just reads provides reliable and power-efficient protection than that when performed over both reads and writes. On the other hand, checking error correcting codes only at reads alone can be vulnerable even for single-bit soft errors, while that at both reads and writes provides the perfect reliability. [ABSTRACT FROM AUTHOR]

Decades of rapid aggressive technology scaling have brought the challenge of soft errors to modern computing systems. Sequential elements (registers) in the processor pipeline exposed to charge-carrying particles generate bit flips or soft errors that could translate into system failures. Next to the processor cache, the pipeline registers (PRs) - registers between two pipeline stages - account for more than 50% of soft-error failures in the system. In this paper, for the first time, we apply architectural correct execution models that quantitatively define the vulnerability (or exposure to soft errors) of microarchitectural components, and extend it to define the vulnerability of PRs - PR vulnerability (PRV). We develop gemV-Pipe, a simulation toolset for the systematic, accurate, and quantitative estimation and analysis of PRV. Our detailed ISA-aware analysis in gemV-Pipe reveals interesting facts on the data-access behavior of PRs: 1) the vulnerability of each PR is not proportional to their size; 2) the PR bits used for one instruction may not be used (and are thus not vulnerable) for another, which makes PRV extremely instruction-dependent; and 3) the functionality of stored data on the PR bits can be used to classify them as - instruction, control, and data bits - each of which differ in their instruction-specific behavior and vulnerability. Applying the insight gained, we perform design space exploration on selectively hardening the PR bits, and demonstrate that 75% improved reliability can be achieved for only <;15% power overhead. [ABSTRACT FROM PUBLISHER]

Reducing device dimensions, increasing transistor densities, and smaller timing windows, expose the vulnerability of processors to soft errors induced by charge carrying particles. Since these factors are only consequences of the inevitable advancement in processor technology, the industry has been forced to improve reliability on general purpose chip multiprocessors (CMPs). With the availability of increased hardware resources, redundancy-based techniques are the most promising methods to eradicate soft-error failures in CMP systems. In this work, we propose a novel customizable and redundant CMP architecture (UnSync) that utilizes hardware-based detection mechanisms (most of which are readily available in the processor), to reduce overheads during error-free executions. In the presence of errors (which are infrequent), the always forward execution enabled recovery mechanism provides for resilience in the system. The inherent nature of our architecture framework supports customization of the redundancy, and thereby provides means to achieve possible performance-reliability tradeoffs in many-core systems. We provide a redundancy-based soft-error resilient CMP architecture for both write-through and write-back cache configurations. We design a detailed RTL model of our UnSync architecture and perform hardware synthesis to compare the hardware (power/area) overheads incurred. We compare the same with those of the Reunion technique, a state-of-the-art redundant multicore architecture. We also perform cycle-accurate simulations over a wide range of SPEC2000, and MiBench benchmarks to evaluate the performance efficiency achieved over that of the Reunion architecture. Experimental results show that, our UnSync architecture reduces power consumption by 34.5 percent and improves performance by up to 20 percent with 13.3 percent less area overhead, when compared to the Reunion architecture for the same level of reliability achieved. [ABSTRACT FROM AUTHOR]

Aggressive technology scaling and near-threshold computing have made soft error reliability one of the leading design considerations in modern embedded microprocessors. Although traditional hardware/software redundancy-based schemes can provide a high level of protection, they incur significant overheads in terms of performance and hardware resources. The considerable overheads from such full redundancy-based techniques has motivated researchers to propose low-cost soft error protection schemes, such as symptom-based error protection schemes. The main idea behind a symptom-based error protection scheme is that soft errors in the system will quickly generate some symptoms, such as exceptions, branch mispredictions, cache or TLB misses, or unpredictable variable values. Therefore, monitoring such infrequent symptoms makes it possible to cover the manifestation of failures caused by soft errors. Symptom-based protection schemes have been suggested as shortcuts to achieve acceptable reliability with comparable overheads. Since the symptom-based protection schemes seem attractive due to their generality and simplicity, even state-of-the-art protection schemes exploit them as the baseline protections. However, our detailed analysis of the fault coverage and performance overheads of such schemes reveals that the user-visible failure coverage, particularly of ReStore, is limited (29% on average). By contrast, the runtime overheads are significant (40% on average) because the majority of the fault injection experiments, which were considered as detected/recovered failures by low-level symptoms, are actually benign faults by program-level masking effects. [ABSTRACT FROM AUTHOR]

Because the dangers of soft errors are increasing with continued technology scaling, reliability against soft errors is becoming an important design concern for modern embedded systems. Various schemes have been proposed to protect embedded systems from the threat of soft errors, but they incur considerable overheads in terms of cost and performance. Selective protection techniques seem promising because they can achieve high levels of protection with low overhead. Though these techniques can be applied to any system, the most vulnerable parts must first be identified. We, therefore, present CFA, a comprehensive failure analysis framework that can analyze the vulnerability of microarchitectural components and software instructions through intensive fault injection campaigns. With CFA, we also explore the vulnerability of ten benchmarks from the MiBench benchmark suite. We found that protecting a part of the system heavily affects the reliability of the other parts. Therefore, all combinations of protection methods must be examined to present the most efficient and effective protection guidelines. Throughout the experiments, we observed that protection methods offered by single-perspective analyses are sub-optimal. On the other hand, CFA finds the optimal solution in every case, reducing the AVF of a system by up to 82% with minimal protection. [ABSTRACT FROM AUTHOR]