Rapid exploration of cost-performance tradeoffs using dominance effect during design of hardware accelerators
Why this work is in the frame
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Bibliographic record
Abstract
Modern Very Large Scale Integration (VLSI) designs require a tradeoff between cost efficiency and performance (circuit speed). Furthermore, the Design Space Exploration (DSE) of the cost-performance tradeoffs for the multi objective VLSI designs should also be fast and efficient in nature. This paper presents a novel accelerated DSE approach for the exploration of cost-performance tradeoffs of modular multi (trio parametric. viz. cost, execution time and power consumption) objective VLSI hardware accelerators using hierarchical criterion analysis. The selection of the final design point is made after the tradeoffs are explored using the proposed approach. Results of the proposed approach when applied to various benchmarks yielded significant acceleration in the exploration process compared to current existing approaches with multi parametric objective.
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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 | 0.001 |
| 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