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Record W1497408952 · doi:10.1109/pact.1996.552669

Bulk Synchronous Parallel: practical experience with a model for parallel computing

2002· article· en· W1497408952 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsParallel computingBulk synchronous parallelComputer scienceParallel algorithm

Abstract

fetched live from OpenAlex

Valiant proposed the Bulk Synchronous Parallel (BSP) model as a possible model for parallel computing. He refers to BSP as a "bridging" model, being applicable to both system and algorithm design. The model allows hardware and software design to proceed independently but ensures compatibility between parallel computers and parallel programs. This paper explores the practical use of BSP, focusing on the portability and predictability it offers, without incurring any significant loss in efficiency. A BSP algorithm for sorting proposed by Gerbessiotis and Valiant is implemented in a portable fashion on three different parallel computers, specifically an Intel iPSC/860, a Transtech Parastation and an Alex AVX Series 2. The program uses a standard library of functions designed and implemented for each machine to support the BSP model. The measured performance of the program is compared to the BSP predictions and to other sorting results on similar machines to provide evidence for the utility of the BSP model.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.403
Threshold uncertainty score0.813

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 communication0.0000.001
Open science0.0010.000
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 head0.049
GPT teacher head0.303
Teacher spread0.254 · 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