An approach for reducing dynamic power consumption in synchronous sequential digital designs
Bibliographic record
Abstract
The problem of minimizing dynamic power consumption by scaling down the supply voltage of computational elements off critical paths is widely addressed in the literature for the case of combinational designs. The problem is NP-hard in general. To address this problem in the case of synchronous sequential digital designs, one needs to move some registers while applying voltage scaling. Moving these registers shifts some computational elements from critical paths, and can be done by basic retiming. Integrating basic retiming and voltage scaling to address this NP-hard problem cannot in general be done in polynomial run-time. We propose to first apply a guided retiming and then to apply supply voltage scaling on the retimed design. We devise new polynomial time algorithms to realize this guided retiming, and the supply voltage scaling on the retimed design. Experimental results on known benchmarks have shown that the proposed approach can reduce dynamic power consumption by factors as high as 61% for single-phase designs with minimal clock period. Also, they have shown that it can solve optimally the problem, and produce converter-free designs with reduced dynamic power consumption. For large size circuits from ISCAS'89 benchmark suite, the proposed algorithms run in 15s-1h.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".