Match Sensing Using Match-Line Stability in Content-Addressable Memories (CAM)
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Bibliographic record
Abstract
This paper presents a match-line (ML) sensing scheme that distinguishes a match from a miss by first shunting every ML with a fixed negative resistance, then exciting the MLs with an initial charge, and subsequently observing their voltage developments. It is shown that the voltage on the matched ML will grow to V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DD</sub> as in an unstable system, whereas the voltage on a missed ML will decay to zero, as in a stable system. Since the initial excitation charge on the ML's can be as low as the noise level in the system, this scheme can approach the minimum possible energy consumption level for match-line sensing. We have implemented, in 0.18 mum CMOS, a 144 times 144 ternary CAM array that includes the stability-based sensing scheme along with two previously-reported sensing schemes. The measured results confirm the power savings of the proposed sensing scheme. In addition, the CAM includes a pipelined search-line (SL) architecture that can reduce the SL portion of CAM power by up to 50%.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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