Nonintrusive Automatic Compiler-Guided Reliability Improvement of Embedded Applications Under Proton Irradiation

Abstract

A method is presented for automated improvement of embedded application reliability. The compilation process is guided using Genetic Algorithms and a Multi-Objective Optimization Approach (MOOGA). Even though modern compilers are not designed to generate reliable builds, they can be tuned to obtain compilations that improve their reliability, through simultaneous optimization of their fault coverage, execution time, and memory size. Experiments show that relevant reliability improvements can be obtained from efficient exploration of the compilation solutions space. Fault-injection simulation campaigns are performed to assess our proposal against different benchmarks and the results are assessed against a real ARM-based System on Chip under proton irradiation.

A Compact Model to Evaluate the Effects of High Level C++ Code Hardening in Radiation Environments

“…Some results are shown in Table 6, namely for a BubbleSort sorting algorithm and a Dijkstra shortest path finder algorithm, with both on-chip memory (OCM), an external rad-hard memory (EXT), as well as neutron and proton irradiation. All these results were also verified during the two radiation campaigns briefly described in Section 3.4 We draw a few considerations here, which can be found by analyzing the results shown in Table 6, where a few C++ hardening configurations are compared with other configurations with hardening on specific aims [10]: mean work to failure (MWTF) maximization, fault coverage maximization (Max-ACE), trade-off optimization among execution time, memory size and fault coverage (Pareto), baseline compilation (O0) and code optimization (O3). All C++ versions were compiled using the -O3 optimization flag.…”

“…In the last step of this activity, our model has been used to identify the most critical storage areas, variables and data structures, that is, those which most affect reliability, in order to concentrate hardening efforts on the most relevant areas. In addition, the performance of the proposed C++ classes against other optimization techniques proposed by the same authors in [10] was compared.…”

“…Other recent approaches represent attempts to gain reliability improvements by introducing no modifications in either the application (code instrumentation) or in the system (specific components). These techniques seek to achieve improvements during the transformation from high level code (source code) to machine code (executable) by altering the code compilation method [10]. Each approach has its own advantages and disadvantages; for example, the disadvantage of producing unwanted overheads in processing time and storage needs can be achieved by applying software hardening techniques.…”

“…When comparing the different approaches from the user perspective, there are two that require either high user intervention levels (most TMR-based approaches), or very little intervention (such as the approach proposed in this paper), or no user intervention and the delegation of hardening to some form of Artificial Intelligence (such as MOOGA [10]). The first approaches require lot of human effort, for instance, to change the focus of hardening.…”

Empirical Mathematical Model of Microprocessor Sensitivity and Early Prediction to Proton and Neutron Radiation-Induced Soft Errors

“…In [19], the authors used linearregression techniques to backtrack the propagation of soft errors through processes dependent on many-core processor systems. Considering the application of non-intrusive SIHFT methods, the works described in [20] and [21] employed genetic algorithms that select the best compilation flags of certain applications for their reliability optimization. Rocha et al [22] have recently proposed a soft-error score, which combines supervised and unsupervised ML algorithms, to correlate application profiles and processor characteristics with fault-injection results.…”