<title>Technology mapping in library-free logic synthesis</title>
Bibliographic record
Abstract
Library-free logic synthesis is an innovative approach that provides a fully customized design performance while avoiding the huge cost of developing and maintaining the extensive cell libraries. Its strength is coming from the use of a virtual library based on on-the-fly cell generation. However, the flexibility of the virtual library makes it impossible to exploit the existing methodologies that are based on the pre-characterized standard cell libraries. The authors developed a creative approach to map the design into customized CMOS complex gates using virtual library technique. This is a timing-driven process, which consists of four phases: logic transformation, logic partitioning, gate mapping and transistor re-ordering. The performance of CMOS complex gates and the logic path derived from the extracted transistor topology are used in guiding the synthesis process. The proposed mapping algorithm was used in combination with our topology-based performance estimation model to synthesize some of the MCNC91 benchmarks. The results show that our algorithm can achieve 42% improvement in area and 43% improvement in power compared to that same designs synthesized by Synposys' Design Analyzer.
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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 | 0.001 |
| 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 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".