A Novel 2T2R CR-based TCAM Design for High-speed and Energy-efficient Applications
Bibliographic record
Abstract
A 2T2R current race (CR) based ternary content addressable memory (TCAM) design is proposed using resistive random-access memory (RRAM) technology. The suggested design adopts a match-line (ML) booster feature in sensing amplifier to improve search speed and tolerance to RRAM switching variations. An SR-latch cascading scheme is presented to further improve the speed and energy efficiency for large TCAM array. Additionally, a same clock phase cascading scheme is proposed to reduce latency in cascading structure, by placing evaluation phase of all stages in the same clock phase. With the suggested ML booster, our 64-bit 1-stage design has speed and energy consumption matching the best performance reported by other emerging non-volatile memory (eNVM) based TCAM design. Our 128-bit 2-stage design also has comparable speed and energy to SRAM-based TCAM design with significantly more compact size (90% reduction) and non-volatility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".