- Describes the most suitable and efficient virtual platforms to include fault injection capabilities, aiming to support the soft error analysis of state-of-the-artprocessor models;
- Includes analysis and port of several benchmarks from embedded and HPC domains, including the Rodinia and NASA NAS Parallel Benchmark (NPB) suites;
- Introduces four novel, non-intrusive FI techniques enabling software engineers to perform in-depth and relevant soft error evaluation, addressing the gap between the available FI tools and the industry requirements;
- Explores machine learning techniques that can be used to enable the identification of individual (or combinations of) microarchitectural and software parameters that present the most substantial relation relationship with each detected soft error or failure.
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