Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pass-transistors have been the key building block for field-programmable gate array (FPGA) circuitry for many years due to the very small switch they enable. However, passtransistor performance and reliability have been degrading with technology scaling. Transmission gates are an alternative to pass-transistors; while larger, they are more robust. We develop a new FPGA circuit optimization flow and use it to investigate the area, delay and power impact of building FPGAs out of transmission gates instead of pass-transistors in a 22nm process. Our results show that transmission gate FPGAs are 15% larger than pass-transistor FPGAs but are 10-25% faster depending on the allowable level of “gate boosting”. Without gate boosting, transmission gate FPGAs are the better option with 14% lower area-delay product. If 200mV of gate boosting is possible however, pass-transistor FPGAs remain the slightly better choice with a 2% better area-delay product. We also show that transmission gates with a separate power supply for their gate terminal enable a low-voltage FPGA with 50% less power and good delay.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.004 |
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