Extendable COTS multicomputer/CPU design for an MCAO control system
Bibliographic record
Abstract
Many reconstructors, or Real Time Controllers (RTC), for mono-conjugate AO systems are currently operating with many more about to be commissioned. The advent of faster and more efficient CPUs has permitted this task to be accomplished on a single processing element, for all but the highest order systems. However, the demands on the RTC increase by an order of magnitude or so in the case of a Multi-Conjugate AO (MCAO) system. Multiple Wavefront Sensors (WFS) and multiple deformable mirrors increase the complexity, processing load and data flow rates that the RTC must deal with. No currently available single processing unit is capable of meeting this demand and retain the advantages of a cost-effective, flexible system. Multiple processing units must be employed. We present in this paper a general architecture that addresses these issues. We present an analysis of the requirements of the Gemini South MCAO system on the RTC. This is followed by an algorithmic decomposition that simplifies the problem, lending itself to the use of commercially available multi-CPU single board computers. This is supported by the results of benchmark tests aimed at verifying the capabilities of one sample SBC. We conclude by presenting a description of the extendability of this architectural approach in the face of yet higher demands such as more mirrors, WFSs or complexity.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".