Fast Heuristic Techniques for FPGA Placement based on Multilevel Clustering
Bibliographic record
Abstract
I hereby declare that I am the sole author of this thesis. I authorize the University of Guelph to lend this thesis to other institutions or individuals for the purpose of scholarly research. I further authorize the University of Guelph to reproduce this thesis by photo-copying or by other means, in total or in part, at the request of other institutions or individuals for the purpose of scholarly research. ii The University of Guelph requires the signatures of all persons using or photo-copying this thesis. Please sign below, and give address and date. iii Field-Programmable Gate Arrays (FPGAs) are semiconductor chips that can realize most digital circuits on site by specifying programmable logic and their interconnections. The use of FPGAs has grown almost exponentially because they dramatically reduce design turn-around time and start-up cost for electronic products compared with traditional
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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".