Efficient LHC Data Distribution across 100Gbps 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
During Supercomputing 2012 (SC12), an international team of high energy physicists, computer scientists, and network engineers led by the California Institute of Technology (Caltech), the University of Victoria, and the University of Michigan, together with Brookhaven National Lab, Vanderbilt and other partners, smashed their previous records for data transfers using the latest generation of wide area network circuitsWith three 100 gigabit/sec (100 Gbps) wide area network circuits [1] set up by the SCinet, Internet2, CENIC, CANARIE and BCnet, Starlight and US LHCNet network teams, and servers at each of the sites with 40 gigabit Ethernet (40GE) interfaces, the team reached a record transfer rate of 339 Gbps between Caltech, the University of Victoria Computing Center in British Columbia, the University of Michigan, and the Salt Palace Convention Center in Utah. This nearly doubled last year's overall record, and eclipsed the record for a bidirectional transfer on a single link with a data flow of 187 Gbps between Victoria and Salt Lake.
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 | 0.002 | 0.001 |
| 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