Generic array-based MPSoC architecture
Bibliographic record
Abstract
Interest in NoC prototyping is continuously growing, as many recent processing chips are multi-cores. Prototyping such systems is a quite complex task. High level simulations validate the functionality of an application but do not guarantee functionality of all possible dedicated implementations. FPGA implementations give a higher level of confidence at low level, but their limited size only permits to validate parts of complex SoCs. We propose an array-based MPSoC architecture, matching requirements of applications where the data can be split into several subsets and processed in parallel, as is the case in numerous video processing algorithms. Since the array size is configurable, we are able to validate the low level FPGA implementation with a limited number of processing elements, but keep a high confidence in the full size final implementation. We have physically implemented a 2×2 Xtensa core system in a Virtex II Pro vp100 and tested it in a real time application.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".