A Memristive Multiplier Using Semi-Serial IMPLY-Based Adder
Why this work is in the frame
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Bibliographic record
Abstract
Memristors are among emerging technologies with many promising features, which makes them suitable not only for storage purposes but also for computations. In this work, focusing on in-memory computations, we first present our semi-serial IMPLY-based adder and perform an extensive analysis of its merits. In addition to providing a favorable balance between the number of steps and number of memristors, a key property of the presented adder is its compactness as compared to the state-ofthe-art adders. Next, using our semi-serial adder, we propose an IMPLY-based multiplier. We show that the proposed multiplier is more than 5× better than other works based on the figure of merit which gives equal weight to the number of steps (i.e., speed) and required die area. Additionally, we provide a deeper insight into IMPLY-based arithmetic units, their properties, design characteristics, and advantages or disadvantages compared to one another by proposing new figures of merit and performing comprehensive comparative analyses. This facilitates the process of design, or selection, of suitable units for the design engineers and researchers in the field.
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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 | 0.000 |
| 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) | 0.000 | 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