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Record W2134391840 · doi:10.1109/ccece.2006.277495

A Formal CSP Framework for Message-Passing HPC Programming

2006· article· en· W2134391840 on OpenAlexaff
J. Carter, William B. Gardner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceMessage passingProgramming languageCommunicating sequential processesFormal methodsParallel computingSemantics (computer science)Operational semantics

Abstract

fetched live from OpenAlex

To help programmers of high-performance computing (HPC) systems avoid communication-related errors, we employ a formal process algebra, communicating sequential processes (CSP), which has a strict semantics for interprocess communication and synchronization. Verification tools are available for CSP-specified programs to prove the absence of failures such as deadlock, and to explore potential multiprocess interactions. By introducing a CSP abstraction layer on top of the popular MPI message-passing primitives, we create a framework, called CSP4MPI, designed to largely hide the complexity of parallel programming for HPC. CSP4MPI is comprised of a C++ class library that provides a CSP-based process model, and a "cookbook" of candidate solutions for HPC programmers not trained in CSP. Developers can prototype their systems using CSP, and use verification tools to examine possible points of failure before implementing via the CSP4MPI library. Alternatively, they may choose an existing, verified solution from a number of common parallel application archetypes. By using CSP4MPI, HPC developers leverage the benefits of formal specification and verification in their work, in addition to obtaining an alternate method to developing HPC applications

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.730
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.259
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations8
Published2006
Admission routes1
Has abstractyes

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