Extreme-scale computing services over MPI: Experiences, observations and features proposal for next-generation message passing interface
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
The message passing interface (MPI) is one of the most portable high-performance computing (HPC) programming models, with platform-optimized implementations typically delivered with new HPC systems. Therefore, for distributed services requiring portable, high-performance, user-level network access, MPI promises to be an attractive alternative to custom network portability layers, platform-specific methods, or portable but less performant interfaces such as BSD sockets. In this paper, we present our experiences in using MPI as a network transport for a large-scale distributed storage system. We discuss the features of MPI that facilitate adoption as well as aspects which require various workarounds. Based on use cases, we derive a wish list for both MPI implementations and the MPI forum to facilitate the adoption of MPI by large-scale persistent services. The proposals in the wish list go beyond the sole needs of distributed services; we contend that they will benefit mainstream HPC applications at extreme scales as well.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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