Desired Footprint by Technology Mapping Modification using a Genetic Algorithm in Odin II
Why this work is in the frame
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Bibliographic record
Abstract
Technology mapping is the transformation of a general Boolean logic network into a functional equivalent K-LUT network that can be implemented by the target FPGA device. Because an FPGA architecture is pre-determined, technology mapping is limited to the available resources. However, circuits can be optimized before the low-level synthesis phase. Odin II, part of the Verilog-to-routing project, is responsible for synthesis and elaboration. In the partial mapping phase of Odin II, some modifications are still possible for high-level modules-adder, multiplier-when there is no hard block available. When Odin II performs partial mapping to create soft logic, we can choose which implementation of a high-level module works best with respect to the desired goals: area versus speed. In this paper, we describe a method to modify circuit characteristics based on placement criteria. More specifically, after partial mapping circuit components during Verilog HDL code synthesis, there are still potential modifications in soft-logic circuit generation. We propose using a genetic algorithm during synthesis to adjust soft-logic circuit implementation in order to achieve the desired synthesis goal. We show that the approach provides promising results for a marginal cost in runtime.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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