Design, evaluation and application of approximate‐truncated Booth multipliers
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Bibliographic record
Abstract
Approximate computing provides a promising way to achieve low power design at the cost of acceptable error. As a core component in a processor, the performance of the multiplier is important. This study presents designs of approximate‐truncated Booth multipliers (ATBMs) using proposed approximate modified radix‐4 Booth encoders (AMBEs), approximate 4‐2 compressors (ACs) and gradually truncated partial products. The accuracy of the ATBMs is adjustable with the so‐called approximation factors that indicate the number of AMBEs and ACs used. The normalised mean error distance and the product of the power and delay are used to evaluate the error and the hardware performance of the multipliers. The results show that the proposed ATBMs outperform previous approximate Booth multipliers. Their validity is also shown with case studies of image processing, K‐means clustering and handwritten digit recognition.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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