Throughput-Oriented NoC Topology Generation and Analysis for High Performance SoCs
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new approach to the design and analysis of NoC topologies which is based on the transaction-oriented communication methods of on-chip components. We propose two algorithms that attempt to meet the communication requirement of an on-chip application using a minimum number of network resources for the task, by generating application-specific topologies. In addition, to aid the design process of complex systems, the design method incorporates a form of predictive analysis which can estimate the degree of contention in a given system without performing detailed simulation. This predictive analysis method is used to determine the minimum frequency of operation for generated topologies, and is incorporated into the topology generation process. The proposed design method was tested using real-word applications, including an MPEG4 decoder and a multi-window display application. The generated topologies were found to offer similar or better performance when compared with regular topologies. However, the topologies generated by our method were more economical, using, on average, half the network resources of regular topologies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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