A novel technique for pipelined scheduling and allocation of data-flow graphs based on genetic algorithms
Why this work is in the frame
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Bibliographic record
Abstract
Genetic algorithms are exploited and applied to the development of a novel technique for the high-level synthesis of digital signal processing algorithms. The proposed technique performs the scheduling and allocation of functional units for the synthesis of both pipelined and non-pipelined data-paths. The salient feature of this technique is that it employs the order crossover operator in combination with a schedule building heuristic to overcome the well known encoding problem encountered when applying genetic algorithms to scheduling problems. The technique is demonstrated through its application to a benchmark fifth-order elliptic wave-digital filter. The results show that the technique produces the optimum schedules for non-pipelined data-paths, but requires further refinements to match the best existing schedules for pipelined data-paths.
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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 | 0.000 | 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