MetFI: Model-driven Fault Simulation Framework

TL;DR

MetaFI is a versatile, model-driven fault simulation framework that enables scalable, multi-strategy fault injection at RTL level, significantly reducing manual effort and providing valuable failure rate insights for complex safety-critical designs.

Contribution

This paper introduces MetaFI, a novel, simulator-independent fault injection framework that supports multiple fault strategies and targets RTL and gate-level representations, improving scalability and controllability.

Findings

Fault simulation applied to two different SoCs with minimal effort.

Prefetcher component shows higher failure susceptibility.

Framework provides detailed failure rate data for design components.

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.