RotR: Rotational redundant task mapping for fail-operational MPSoCs
Bibliographic record
Abstract
As transient and permanent failures are rise shrinking process technology, MPSoC systems with fail-operational behavior have become important, especially for safety-critical applications. We therefore propose RotR, a rotational task mapping approach for an active-redundancy-based system to facilitate parallel execution of redundant tasks. RotR maps tasks such that no single failure affects more than one copy of a redundant task, and utilizes a multi-functional voter task that adapts its functionality based on the system's redundancy state after each component failure. RotR mapping and the proposed voter task jointly enable fail-operational behavior by seamlessly transitioning from higher reliability (e.g., Triple Modular Redundancy) to lower reliability (e.g., Double Modular Redundancy) without requiring task remapping. Our results show that RotR improves a system's fault-tolerant lifetime on average by 37% and 48% over standard DMR and TMR systems, respectively. Furthermore, it improves the overall lifetime by 29% compared to the baseline system having no redundancy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".