RDMA-based and SMP-aware Multi-port All-Gather on Multi-rail QsNet^II SMP Clusters
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Bibliographic record
Abstract
Clusters of symmetric multiprocessors (SMP) are more commonplace than ever in achieving high- performance. Scientific applications running on clusters employ collective communications extensively. Using shared memory communication among co- located processes on SMP nodes as well as remote direct memory access (RDMA) operations for inter- node communication and trying to overlap them is a proven technique in boosting the performance of collective operations. The effect is much more pronounced when efficient multi-port collectives on multi-rail networks are devised and implemented. In this work, we design and implement multi-port RDMA-based and SMP-aware all-gather algorithms with message striping over multi-rail QsNe <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">II</sup> directly at the Elan level. We compare our algorithms against RDMA-only traditional algorithms and the native elan_gather(). Our performance results indicate that the proposed SMP-aware Brack all-gather gains an improvement of up to 1.96 for 4KB messages over the native elanjgather(). Meanwhile, the direct algorithm achieves up to 1.49 improvement for 32 KB messages.
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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 | 0.002 | 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