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
Most datacenter network (DCN) designs focus on maximizing bisection bandwidth rather than minimizing server-to-server latency. We explore architectural approaches to building low-latency DCNs and introduce Quartz, a design element consisting of a full mesh of switches. Quartz can be used to replace portions of either a hierarchical network or a random network. Our analysis shows that replacing high port-count core switches with Quartz can significantly reduce switching delays, and replacing groups of top-of-rack and aggregation switches with Quartz can significantly reduce congestion-related delays from cross-traffic. We overcome the complexity of wiring a complete mesh using low-cost optical multiplexers that enable us to efficiently implement a logical mesh as a physical ring. We evaluate our performance using both simulations and a small working prototype. Our evaluation results confirm our analysis, and demonstrate that it is possible to build low-latency DCNs using inexpensive commodity elements without significant concessions to cost, scalability, or wiring complexity.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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