Stochastic Spatial Routing for Reconfigurable
Bibliographic record
Abstract
FPGA placement and routing is time consuming, often serving as the major obstacle inhibiting a fast edit-compile-test loop in prototyping and development and the major obstacle preventing late-bound hardware and design mapping for reconfigurable systems. We introduce a stochastic search scheme which can achieve comparable route quality to traditional, software-based routers while being amenable to parallel, spatial implementation. We quantify the quality and performance of this route scheme using the Toronto Place-and-Route Challenge benchmarks. We sketch hardware implementations ranging from a minimal hardware-search assistance scheme which provides two orders of magnitude speedup, to FPGA-based schemes which provide greater speedup, to full hardware schemes which provide over three orders of magnitude routing acceleration. With parallel path searches, the time required for the spatial solution scales sublinearly in network size for the typical, limited-bisection networks used for practical reconfigurable systems.
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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".