Micro-Benchmarking MPI Partitioned Point-to-Point Communication
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
Modern High-Performance Computing (HPC) architectures have developed the need for scalable hybrid programming models. The latest Message Passing Interface (MPI) 4.0 standard has introduced a new communication model: MPI Partitioned Point-to-Point communication. This new model allows for the contribution of data from multiple threads with lower overheads than with traditional MPI point-to-point communication. In this paper, we design the first publicly available micro-benchmark suite for MPI Partitioned to measure various metrics that can give insight into the benefits of using this new model and scenarios where MPI point-to-point is better suited. Suggestions are provided to application developers on how to choose partition size for their application based on compute and message size. We evaluate MPI Partitioned communication with both a hot and cold CPU cache, system noise with different probability distributions, point-to-point communication directly, and with commonly used MPI communication patterns such as a halo exchange and Sweep3D.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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