Area-efficient FPGA logic elements: Architecture and synthesis
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Bibliographic record
Abstract
We consider architecture and synthesis techniques for FPGA logic elements (function generators) and show that the LUT-based logic elements in modern commercial FPGAs are over-engineered. Circuits mapped into traditional LUT-based logic elements have speeds that can be achieved by alternative logic elements that consume considerably less silicon area. We introduce the concept of a trimming input to a logic function, which is an input to a K-variable function about which Shannon decomposition produces a cofactor having fewer than K -1 variables. We show that trimming inputs occur frequently in circuits and we propose low-cost asymmetric FPGA logic element architectures that leverage the trimming input concept, as well as some other properties of a circuit's AND-inverter graph (AIG) functional representation. We describe synthesis techniques for the proposed architectures that combine a standard cut-based FPGA technology mapping algorithm with two straightforward procedures: 1) Shannon decomposition, and 2) finding non-inverting paths in the circuit's AIG. The proposed architectures exhibit improved logic density versus traditional LUT-based architectures with minimal impact on circuit speed.
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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) | 0.001 | 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 it