Power gradient based Design Space Exploration in high level synthesis for DSP kernels
Why this work is in the frame
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Bibliographic record
Abstract
Design Space Exploration (DSE) of integrated scheduling and module selection in high level synthesis for VLSI applications require an accurate optimization technique capable of reaching an optimal/near-optimal solution rapidly. This paper introduces a novel heuristic based multi objective optimization (exploration) process based on power gradient theory that simultaneously reduces the static power consumption at the usage of minimal control step (time step) during scheduling. The proposed iterative power aware integrated optimization approach is based on Priority Indicator (PI) function which is responsible for minimizing allocated hardware functional units during the scheduling process. The quality of final solution obtained by the proposed approach has been compared to a heuristic Genetic Algorithm (GA) based approach. Results for the benchmarks indicate an average power reduction of 11%, improvement in the quality of final solution of 5.07% and reduction in optimization/exploration runtime of 59%.
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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 | 0.001 |
| Open science | 0.001 | 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