Concurrent Error Detection in Finite-Field Arithmetic Operations Using Pipelined and Systolic Architectures
Why this work is in the frame
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Bibliographic record
Abstract
In this work, we consider detection of errors in polynomial, dual, and normal bases arithmetic operations. Error detection is performed by recomputing with the shifted operand method, while the operation unit is in use. This scheme is efficient for pipelined architectures, particularly systolic arrays. Additionally, one semisystolic multiplier for each of the polynomial, dual, type I, and type II optimal normal bases is presented. The results show that for having better or similar space and time overheads compared to a number of related previous work, the multipliers have generally a higher error-detection capability, e.g., the error-detection capability of the RESO-based scheme for single and multiple stuck-at faults in a polynomial basis multiplier is 100 percent. Finally, we also comment on how RESO can be used for concurrent error correction to deal with transient faults.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it