A Novel Virtual Channel Implementation Technique for Multi-core On-chip Communication
Bibliographic record
Abstract
In this paper, a new approach for implementing virtual channels (VC) for multi-core interconnection networks is presented. In this approach, the flits of different packets interleave in a channel with a single buffer of nominal depth by using a rotating flit-by-flit arbitration. The routing path of each flit is guaranteed because the flits belonging to the same packet are attached with an ID tag at each router so that they are differentiable at downstream routers. We present this on-chip communication of packets through sharing of channel and buffer, which is a novel method of virtual channel implementation. Furthermore, we demonstrate it by adding arbitrary virtual channels depending on the number of packet requests for a physical channel. In this way, NoC (Network-on-Chip) contention can be removed cheaply. Moreover, we discuss contention free communication where the depth of shared buffer does not affect the performance. A contention-free communication with small (one) buffer depth can create an efficient on-chip communication with high performance, small chip area and low power consumption.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".