Decentralized run-time recovery mechanism for transient and permanent hardware faults for space-borne FPGA-based computing systems
Bibliographic record
Abstract
One of the most important problems for mission critical space-borne computing systems employing FPGA devices is fault tolerance to transient and permanent hardware faults. In many cases, the ability for run-time self-recovery from such faults is a vital feature. This paper presents a method and mechanism for run-time recovery of FPGA-based System-on-Chip (SoC) based on Collaborative Macro-Function Units (CMFUs). Each CMFU consist of a macro-function specific data-path, control unit and circuits providing self-integration, self-synchronization and self-recovery functions for the CMFU, without centralized control. The proposed mechanism allows run-time scrubbing or relocation of faulty components of the SoC providing much higher flexibility and reliability of the system. This mechanism was implemented and tested on a Xilinx Kintex-7 FPGA platform. It was determined that the proposed approach can provide seamless run-time recovery for pipelined SoCs, while being transparent to the application.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".