Fault-tolerance for multistage interconnection networks
Bibliographic record
Abstract
A new fault-tolerant multistage interconnection network architecture is proposed. Using k redundant processors and f redundant switching elements per stage, the authors scheme can tolerate any k processor failures and any f switching element failures per stage. A fault-tolerant multistage interconnection network constructed using their scheme can operate as if it is a non-redundant multistage interconnection network. That is, no additional control information is necessary for routing even when some initial processors and initial switching elements have already failed and been replaced. Furthermore, the reconfiguring process of replacing failed processors and failed switching elements with spare ones can be carried out distributively. The authors scheme also compares favorably with other proposed fault-tolerant multistage interconnection architectures in terms of extra hardware requirements and it can also provide higher system reliability than other proposed schemes. Finally, even for systems with a large number of processors, n>or=1024, their scheme can still achieve very high reliability. Hence, their scheme is well-suited for use in long-life unmaintained applications.>
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".