Implementing a cost-effective run-time reconfigurable system for stream applications
Bibliographic record
Abstract
In today’s consumer electronics the devices are crossing the boundaries by integrating the variety of functionalities to increase their market shares. As a result, the primary focus of designing consumer electronics lies upon implementation of cost-effective, multi-task and multi-mode operations. We suggest a methodology for a cost-effective implementation of the reconfigurable system based on run-time reconfigurable FPGAs. The methodology focuses on extraction of the architecture that remains static throughout the lifetime of the application. The static architecture is constructed by analyzing the tasks associated with event(s) and distinguishing the level of task that needs to be in hardware. With the given architecture the system maintains inter-communication and only replaces the tasks that are necessary via reconfiguration. The idea of the proposed system is employed on the image processing of an autonomous satellite docking system because of tight physical limitations and high speed requirements. Obtained results prove that the run-time reconfigurable system architecture can provide a very efficient way to mosaic the micro-architecture that reuses limited hardware resources in time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".