Task Level Parallelization of All Pair Shortest Path Algorithm in OpenMP 3.0
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Bibliographic record
Abstract
OpenMP is a standard parallel programming language to develop parallel applications on shared memory machines. OpenMP is very suitable for designing parallel algorithms for regular applications where the amount of work is known apriori and therefore, distribution of work among the threads can be done at compile time. In irregular applications, the load changes dynamically at runtime and distribution of work among the threads can be done only at runtime. In the literature, it has been shown that OpenMP produces poor performance for irreg-ular applications. In 2008, the OpenMP 3.0 version introduced new features such as "tasks" to handle irregular computations. Not much work has gone into studying irregular algorithms in OpenMP 3.0. In this paper, we consider one graph problem, the all pair shortest path problem and its implementation in OpenMP 3.0. We show that for large number of vertices, the algorithm running on OpenMP 3.0 surpasses the one on OpenMP 2.5 by 1.6 times.
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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 | 0.000 | 0.001 |
| 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 it