Logic block clustering of large designs for channel-width constrained FPGAs
Why this work is in the frame
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Bibliographic record
Abstract
In this paper we present a system level technique for mapping large, multiple-IP-block designs to channel-width constrained FPGAs. Most FPGA clustering tools [2, 3, 11] aim to reduce the amount of inter-cluster connections, hence reducing channel width needs. However, if this exceeds the FPGA's channel width (a hard constraint), then the circuit still cannot be routed. Previous work [11, 12] depopulates logic clusters (CLBs) to reduce channel width. By depopulating non-uniformly, i.e. depopulate more in hard-to-route regions, we show a graceful trade-off between channel width and CLB count. This makes it possible to target specific channel-width constraints during clustering with minimal CLB inflation. Results show channel width decreases of up to 20% with a 5% increase in area. Further decreases of nearly 50% are possible at 3.3 times the original area. Despite the area increase, this technique creates routable solutions from otherwise-unroutable circuits.
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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 it