The effect of node size, heterogeneity, and network size on FPGA based NoCs
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
Modern FPGAs are used to implement complex Systems-on-Chip (SoCs) and more recently Networks-on-Chip (NoCs). NoCs consist of computing nodes that are connected via switches or routers to a network of point-to-point links that define the topology. Previous work has investigated appropriate topology choices for ASICs as dictated by their electrical characteristics. However, since a FPGA has a prefabricated interconnect, their NoC implementations are not restricted by these concerns. Preliminary work has looked at homogeneous multiprocessor networks-on-chip on FPGAs and suggests that these systems perform differently on FPGAs than ASICs. In this work, we looked at the effects of the number of nodes, node sizes and heterogeneity on NoC performance. Assuming that the network node is not the critical path, we found that NoC performance is only dependent on the number of nodes and is not impacted by the node size or heterogeneity of nodes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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