An Efficient Transposition Algorithm for Distributed Memory Computers
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Bibliographic record
Abstract
Data transposition is required in many numerical applications. When implemented on a distributed-memory computer, data transposition requires all-to-all communication, a time consuming operation. The Direct Exchange algorithm, commonly used for this task, is inefficient if the number of processors is large. We investigate a series of more sophisticated techniques: the Ring Exchange, Mesh Exchange and Cube Exchange algorithms. These data transposition schemes were incorporated into a parallel solver for the shallow-water equations. We compare the performance of these schemes with that of the Direct Exchange Algorithm and the MPI all-to-all communication routine, MPI_AllToAll. The numerical experiments were performed on a Cray T3E computer with 512 processors and on an ethernet-connected cluster of 36 Sun workstations. Both the analysis and the numerical results indicate that the more sophisticated Mesh and Cube Exchange algorithms perform better than either the simpler well-known Direct and Ring Exchange schemes or the MPI_AllToAll routine. We also generalize the Mesh and Cube Exchange algorithms to a d-dimensional mesh algorithm, which can be viewed as a generalization of the standard hypercube data transposition algorithm.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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