On atomic registers and randomized consensus in M&M systems
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Bibliographic record
Abstract
Motivated by recent distributed systems technology, Aguilera et al. introduced a hybrid model of distributed computing, called the message-and-memory model or m&m model for short. In this model, processes can communicate by message passing and also by accessing some shared memory (e.g., through some RDMA connections). We first consider the basic problem of implementing an atomic single-writer multi-reader (SWMR) register shared by all the processes in m&m systems. Specifically, we give an algorithm that implements such a register in m&m systems and show that it is optimal in the number of process crashes that it tolerates. This generalizes the well-known ABD implementation of an atomic SWMR register in a pure message-passing system. We then combine our register implementation for m&m systems with a randomized consensus algorithm of Aspnes and Herlihy, and obtain a randomized consensus algorithm for m&m systems that is also optimal in the number of process crashes that it can tolerate. Finally, we determine the minimum number of RDMA connections that is sufficient to implement a SWMR register, or solve randomized consensus, in an m&m system with t process crashes, for any given t .
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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