Scheduling of turbo decoding on a multiprocessor platform to manage its processing effort variability
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Bibliographic record
Abstract
This paper presents means of mapping and scheduling portions of a wide-band code division multiple access (WCDMA) application on a homogeneous multi processor system-on-chip (MPSoC). We focus on the turbo decoder, which is a computationally intensive part of the application and which presents a significant processing variability. Our model allows deriving and validating a flexible scheduling method for turbo decoding tasks, which is adapted to the variable processing effort required by the decoder. Using a proposed performance model, the efficiency of this scheduling method is demonstrated. A proposed flexible scheduling (FS) method, when compared to a worst case execution time (WCET) scheduling method, allows increasing the number of users from 14 to 29, while keeping an acceptable quality of service, as reflected in a very small degradation of less than 0.15 dB of the decoding gain.
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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