A scalable computing and memory architecture for variable block size motion estimation on Field-Programmable Gate Arrays
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we investigate the use of field-programmable gate arrays (FPGAs) in the design of a highly scalable variable block size motion estimation architecture for the H.264/AVC video encoding standard. The scalability of the architecture allows one to incorporate the system into low cost single FPGA solutions for low-resolution video encoding applications as well as into high performance multi-FPGA solutions targeting high-resolution applications. To overcome the performance gap between FPGAs and application specific integrated circuits, our algorithm intelligently increases its parallelism as the design scales while minimizing the use of memory bandwidth. The core computing unit of the architecture is implemented on FPGAs and its performance is reported. It is shown that the computing unit is able to achieve 28 frames per second (fps) performance for 640x480 resolution VGA video while incurring only 4% device utilization on a Xilinx XC5VLX330 FPGA. With 8 computing units at 37% device utilization, the architecture is able to achieve 31 fps performance for encoding full 1920x1088 progressive HDTV video.
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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