Floorplanning with datapath optimization
Bibliographic record
Abstract
This paper presents a floorplanner for datapath with the capability of re-allocating data storage for minimizing the interconnect area and critical path delay without altering the number of functional units and the schedule. The tool has combined two novel approaches: 1-A placement and routing model to handle different architectural topologies (mux. and/or bus based) suitable for FPGA's. 2-An efficient formulation for the binding of register/interconnect and combined floorplanning. The complexity of the architectural and floorplanning model, and of the cost function, have led us to the use of a stochastic optimization process. The running time of the whole process indicates the viability of the method. We show through various examples how the floorplanner improves the area and critical path delay of the datapath compared to a plain floorplanner. The improvement is about 20% for the critical path delay when this objective is a stringent constraint.
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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) | 0.001 | 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".