Using the Pilot Library to Teach Message-Passing Programming
Bibliographic record
Abstract
Message-passing is the staple of HPC codes, and MPI has long occupied the place of HPC's default programming paradigm, thus it would seem to be the natural choice for instructing undergraduates. Nonetheless, MPI is a low-level API, complex and tricky to use, with many pitfalls awaiting the inexperienced. The Pilot library was invented as an alternative HPC programming model for C and Fortran. Pilot-based codes, using a process/channel application architecture borrowed from Communicating Sequential Processes (CSP), can avoid some categories of errors, and the Pilot library with its integrated deadlock detector provides extensive checking and diagnosis of usage problems, which is especially important for students running cluster programs in their typical low-visibility environment with limited debugging tools. This paper gives an overview of programming in Pilot, with its compact API of point-to-point and collective operations. It explains reasons for preferring it as an introductory message-passing technique, describes free resources available to the instructor, and relates experiences of using Pilot with undergraduates over five years, including student reactions. Pilot is now available as free and open source.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.062 | 0.027 |
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".