An integer programming placement approach to FPGA clock power reduction
Bibliographic record
Abstract
Abstract — Clock signals are responsible for a significant por-tion of dynamic power in FPGAs owing to their high toggle fre-quency and capacitance. Clock signals are distributed to loads through a programmable routing tree network, designed to pro-vide low delay and low skew. The placement step of the FPGA CAD flow plays a key role in influencing clock power, as clock tree branches are connected based solely on the placement of the clock loads. In this paper, we present a placement-based approach to clock power reduction based on an integer linear programming (ILP) formulation. Our technique is intended to be used as an op-timization post-pass executed after traditional placement, and it offers fine-grained control of the amount by which clock power is optimized versus other placement criteria. Results show that the proposed technique reduces clock network capacitance by over 50 % with minimal deleterious impact on post-routed wirelength and circuit speed. I.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".