Run Control Communication for the Upgrade of the ATLAS Muon-to-Central Trigger Processor Interface (MUCTPI)
Bibliographic record
Abstract
The Muon-to-Central Trigger Processor Interface (MUCTPI) of the ATLAS experiment at the Large Hadron Collider (LHC) at CERN will be upgraded to an ATCA blade system for Run 3. The new design requires development of new communication models for control, configuration and monitoring. A System-on-Chip (SoC) with a programmable logic part and a processor part will be used for communication to the run control system and to the MUCTPI processing FPGAs. Different approaches have been compared. First, we tried an available UDP-based implementation in firmware for the programmable logic. Although this approach works as expected, it does not provide any flexibility to extend the functionality to more complex operations, e.g. for serial protocols. Second, we used the SoC processor with an embedded Linux operating system and an application-specific software written in C++ using a TCP remote-procedure-call approach. The software is built and maintained using the Yocto/OpenEmbedded framework. This approach was successfully used to test and validate the MUCTPI prototype. A third approach under investigation is the option of porting the ATLAS run control software directly to the embedded Linux.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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".