Parallel Branch and Bound Algorithm - A comparison between serial, OpenMP and MPI implementations
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
This paper presents a comparison of an extended version of the regular Branch and Bound algorithm previously implemented in serial with a new parallel implementation, using both MPI (distributed memory parallel model) and OpenMP (shared memory parallel model). The branch-and-bound algorithm is an enumerative optimization technique, where finding a solution to a mixed integer programming (MIP) problem is based on the construction of a tree where nodes represent candidate problems and branches represent the new restrictions to be considered. Through this tree all integer solutions of the feasible region of the problem are listed explicitly or implicitly ensuring that all the optimal solutions will be found. A common approach to solve such problems is to convert sub-problems of the mixed integer problem to linear programming problems, thereby eliminating some of the integer constraints, and then trying to solve that problem using an existing linear program approach. The paper describes the general branch and bound algorithm used and provides details on the implementation and the results of the comparison.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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