Dodec: Random-Link, Low-Radix On-Chip Networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Network topology plays a vital role in chip design, it largely determines network cost (power and area) and significantly impacts communication performance in many-core architectures. Conventional topologies such as a 2D mesh have drawbacks including high diameter as the network scales and poor load balancing for the center nodes. We propose a methodology to design random topologies for on-chip networks. Random topologies provide better scalability in terms of network diameter and provide inherent load balancing. As a proof-of-concept for random on-chip topologies, we explore a novel set of networks -- do decs -- and illustrate how they reduce network diameter with randomized low-radix router connections. While a 4 × 4 mesh has a diameter of 6, our dodec has a diameter of 4 with lower cost. By introducing randomness, dodec networks exhibit more uniform message latency. By using low-radix routers, dodec networks simplify the router micro architecture and attain 20% area and 22% power reduction compared to mesh routers while delivering the same overall application performance for PARSEC.
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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 | 0.001 | 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 it