A complementary logic partitioning algorithm for a library-free logic synthesis paradigm
Bibliographic record
Abstract
This paper presents a novel approach for technology partitioning in a library free paradigm based on the use of virtual cells. Previous methods for library free logic partitioning rely on creating the largest possible partitions from a user defined criteria, predominately the stack length of the transistor level implementation. However, these methods can cause conflicting structures, defying the AND-OR-INVERT (AOI) and OR-AND-INVERT (OAI) representations that are used as templates for the virtual cells. The Complementary Logic Partitioning (CLP) algorithm, defines a partition as consisting of only two hierarchical levels of complementary nodes (AND and OR), as well as using the logical effort model for the migration of inputs to optimize the partitions to meet both the user defined limiting criteria and minimize the delay of the inputs. The CLP algorithm is compared against Synopsys' Design Compiler using Artisan standard cell library for a set of MCNC '91 benchmarks. Preliminary simulation results based on TSMC's 0.18 micron CMOS technology, show a reduction of more than 50% in the critical path delay can be achieved with CLP.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".