Scalable and deterministic timing-driven parallel placement for FPGAs
Bibliographic record
Abstract
This paper describes a parallel implementation of the timing-driven VPR~5.0 simulated annealing engine. By restricting the move distance to a confined neighborhood, it is possible to consider a large number of non-conflicting moves in parallel and achieve a deterministic result. The full timing-driven algorithm is parallelized, including the detailed timing analysis updates done periodically while placement progresses. The limited move slightly degrades the placement quality, but this is necessary to expose greater degrees of parallelism. The overall bounding box metric degrades about 11% and critical path delay metric degrades about 8% compared to VPR's original algorithm, but we show the amount of degradation is independent of the number of threads. Overall, the parallel implementation scales to a speedup of 123x using 25 threads compared to VPR. With additional tuning effort, we believe the algorithm can be scaled to a larger number of threads, perhaps even run on a GPU, with little additional quality degradation.
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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".