Continuous Online Self-Monitoring Introspection Circuitry for Timing Repair by Incremental Partial-Reconfiguration (COSMIC TRIP)
Bibliographic record
Abstract
We show that continuously monitoring on-chip delays at the LUT-to-LUT link level during operation allows a field-programmable gate array to detect and self-adapt to aging and environmental timing effects. Using a lightweight (<4% added area) mechanism for monitoring transition timing, a Difference Detector with First-Fail Latch, we can estimate the timing margin on circuits and identify the individual links that have degraded and whose delay is determining the worst-case circuit delay. Combined with Choose-Your-own-Adventure precomputed, fine-grained repair alternatives, we introduce a strategy for rapid, in-system incremental repair of links with degraded timing. We show that these techniques allow us to respond to a single aging event in less than 190ms for the toronto20 benchmarks. The result is a step toward systems where adaptive reconfiguration on the time-scale of seconds is viable and beneficial.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".