On the Programming Impact ofMulti-Core,Multi-Processor Nodes inMPI Clusters
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
Increasingly, multi-core processors, multi-processor nodes and multi-core, multi-processor nodes are finding their way into computer clusters. Clusters built using such nodes are already quite common and, inevitably, will become more so over time. As with any new technology, however, the potential benefits are seldom as easy to attain as we expect them to be. In this paper, we explore three fundamental issues related to the use of multi-core, multi-processor nodes in compute clusters using MPI: inter-communication (messaging) efficiency, cache effects (in particular processor affinity) and initial process distribution. Based on some initial experiments using a subset of the NAS parallel benchmarks running on a small scale cluster with dual core, dual processor nodes, we report results on the impact of these issues. From these results we attempt to extrapolate some simple, guidelines that are likely to be generally applicable for optimizing MPI code running on clusters with multi- core, multi-processor nodes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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