Iterative design method for video processors based on an architecture design language and its application to ELA deinterlacing
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a design methodology for dedicated real-time video processors. The methodology begins with a basic processor that is progressively morphed into a specialized processor through five systematic steps. It differs from standard methodologies for ASIP design which place exclusive emphasis on the extension of the instruction set. The proposed methodology takes a global look at various processor and system considerations. The last step consists of removing unnecessary functionality from the instruction set. The required flexibility is attained by the use of an architectural description language. We use a basic deinterlacing algorithm to demonstrate the effectiveness of the methodology and present details of the various phases of the design process. Using ELA deinterlacing as a benchmark, the final processor uses 20% fewer logic elements, achieves a global acceleration by a factor of 11, and an improvement in area-delay product of 14, with respect to the basic processor.
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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 | 0.001 | 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