Power Efficient Rapid Hardware Development using CoDeL and Automated Clock Gating
Bibliographic record
Abstract
We present a platform for rapidly developing power efficient hardware architectures. We have developed a new language, called CoDeL, which allows hardware description at the algorithm level, and thus dramatically reduces design time. We have extended CoDeL to automatically insert clock gating at the behavioral level to reduce dynamic power dissipation in the resulting architecture. This is, to our knowledge, the first hardware design environment that allows an algorithmic description of a component and yet produces a power aware design. To estimate the power savings, we have developed an estimation framework, which is shown to be consistent with the power savings obtained using statistical power analysis using Synopsys tools. To evaluate our platform we use the CoDeL implementation of a two-dimensional discrete wavelet transform using the lifting technique. A simulation based power analysis on the designed circuit shows that CoDeL's clock gating reduces the power dissipation by up to 80%
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".