Performance Evaluation and Design Trade-Offs for Network-on-Chip Interconnect Architectures
Why this work is in the frame
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Bibliographic record
Abstract
Multiprocessor system-on-chip (MP-SoC) platforms are emerging as an important trend for SoC design. Power and wire design constraints are forcing the adoption of new design methodologies for system-on-chip (SoC), namely, those that incorporate modularity and explicit parallelism. To enable these MP-SoC platforms, researchers have recently pursued scaleable communication-centric interconnect fabrics, such as networks-on-chip (NoC), which possess many features that are particularly attractive for these. These communication-centric interconnect fabrics are characterized by different trade-offs with regard to latency, throughput, energy dissipation, and silicon area requirements. In this paper, we develop a consistent and meaningful evaluation methodology to compare the performance and characteristics of a variety of NoC architectures. We also explore design trade-offs that characterize the NoC approach and obtain comparative results for a number of common NoC topologies. To the best of our knowledge, this is the first effort in characterizing different NoC architectures with respect to their performance and design trade-offs. To further illustrate our evaluation methodology, we map a typical multiprocessing platform to different NoC interconnect architectures and show how the system performance is affected by these design trade-offs.
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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 | 0.000 |
| 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