MetFI: Model-driven Fault Simulation Framework
April 27, 2022 Β· Declared Dead Β· π IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems
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Authors
Endri Kaja, Nicolas Gerlin, Luis Rivas, Monideep Bora, Keerthikumara Devarajegowda, Wolfgang Ecker
arXiv ID
2204.13183
Category
cs.SE: Software Engineering
Cross-listed
cs.AR,
cs.LO
Citations
4
Venue
IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems
Last Checked
4 months ago
Abstract
Safety-critical designs need to ensure reliable operations under hostile conditions with a certain degree of confidence. The continuously higher complexity of these designs makes them more susceptible to the risk of failure. ISO26262 recommends fault injection as the proper technique to verify and measure the dependability of safety-critical designs. To cope with the complexity, a lot of effort and stringent verification flow is needed. Moreover, many fault injection tools offer only a limited degree of controllability. We propose MetaFI, a model-driven simulator-independent fault simulation framework that provides multi-purpose fault injection strategies such as Statistical Fault Injection, Direct Fault Injection, Exhaustive Fault Injection, and at the same time reduces manual efforts. The framework enables injection of Stuck-at faults, Single-Event Transient faults, Single-Event Upset faults as well as Timing faults. The fault simulation is performed at the Register Transfer Level (RTL) of a design, in which parts of the design targeted for fault simulation are represented with Gate-level (GL) granularity. MetaFI is scalable with a full System-on-Chip (SoC) design and to demonstrate the applicability of the framework, fault simulation was applied to various components of two different SoCs. One SoC is running the Dhrystone application and the other one is running a Fingerprint calculation application. A minimal effort of 2 persondays was required to run 38 various fault injection campaigns on both the designs. The framework provided significant data regarding failure rates of the components. Results concluded that Prefetcher, a component of the SoC processor, is more susceptible to failures than the other targeted components on both the SoCs, regardless of the running application.
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