High-Throughput Low-Energy Self-Timed CAM Based on Reordered Overlapped Search Mechanism
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Bibliographic record
Abstract
This paper introduces a reordered overlapped search mechanism for high-throughput low-energy content-addressable memories (CAMs). Most mismatches can be found by searching a few bits of a search word. To lower power dissipation, a word circuit is often divided into two sections that are sequentially searched or even pipelined. Because of this process, most of match lines in the second section are unused. Since searching the last few bits is very fast compared to searching the rest of the bits, we propose to increase throughput by asynchronously initiating second-stage searches on the unused match lines as soon as a first-stage search is complete. In our circuit implementation, each word circuit is independently controlled by a locally generated timing signal rather than a global signal. This allows the circuits to be in the required phase for their own local operation: evaluate or precharge, instead of having to synchronize their phase to the rest of the word circuits, which greatly reduces the cycle time. As a design example, a 128 × 64-bit CAM is implemented and evaluated by HSPICE simulation under a 90 nm CMOS technology. The proposed asynchronous CAM operates 5.98 times faster than a synchronous CAM with 14.2% smaller energy dissipation. The post-layout proposed CAM achieves 385-ps cycle delay time and 0.773 fJ/bit/search and is also evaluated under different corner conditions and PVT variations to guarantee it operates properly.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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