Bibliographic record
Abstract
Remote direct memory access (RDMA) and point- to-point network fabrics both have their own advantages. MPI middleware implementations typically use one or the other, however, the appearance of the Internet Wide Area RDMA Protocol (iWARP), RDMA over IP, and protocol off-load devices introduces the opportunity to use a hybrid design for MPI middleware that uses both iWARP and a transport protocol directly. We explore the design of a new MPICH2 channel device based on iWARP and the stream control transmission protocol (SCTP) that uses SCTP for all point-to-point MPI routines and iWARP for all remote memory access routines (i.e., one-sided communication). The design extends the Ohio Supercomputer Center software- based iWARP stack and our MPICH2 SCTP-based channel device. The hybrid channel device aligns the semantics of the MPI routine with the underlying protocol that best supports the routine and also allows the MPI API to exploit the potential performance benefits of the underlying hardware more directly. We describe the design and issues related to the progress engine design and connection setup. We demonstrate how to implement iWARP over SCTP rather than TCP and discuss its advantages and disadvantages. We are not aware of any other software implementations of iWARP over SCTP, nor MPI middleware that uses both iWARP verbs and the SCTP API.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".