Supporting MPI collective communication on network processors
Bibliographic record
Abstract
We present work that extends our previous Myrinet port for LAM/MPI, MPI-NP, with collective communication primitives on the NIC. This work is another step in our experiment of making the NIC MPI aware. We believe that an MPI aware control program on the NIC can deliver a richer set of performance enhancements, not just restricted to better bandwidth/latency, to MPI applications. MPI collective communication involves considerable interactions between the communication subsystems of the nodes that are not of any direct interest to the application. By migrating these talkative components to the Myrinet network interface card we allow this dialog between the nodes to happen with minimum latency. We explore the advantage of supporting several MPI collective communication routines on the NIC. These include MPI /spl I.bar/Bcast (), MPI/spl I.bar/Barrier and MPI/spl I.bar/Comm/spl I.bar/Create ().
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".