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Record W2151303839 · doi:10.1109/hcw.2000.843755

MoBiDiCK: a tool for distributed computing on the Internet

2002· article· en· W2151303839 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
TopicDistributed and Parallel Computing Systems
Canadian institutionsLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsComputer scienceServerDistributed computingParallel computingComputer clusterThe InternetComputationKernel (algebra)Modular designMessage passingWeb serverTheoretical computer scienceOperating systemAlgorithm

Abstract

fetched live from OpenAlex

We have developed a software tool called MoBiDiCK (Modular Big Distributed Computing Kernel) that is ultimately intended for distributed computing. In this paper, we detail the design and show results using the core components of MoBiDiCK running two different clients on a local cluster. MoBiDiCK is a database-driven system that can be used to marshal a large number of processors across the Internet in order to have them collaborate on a single computation. These utilize a message-passing API and control synchronization formalism we have developed that uses the HTTP standard and Web servers. CGI programs on the volunteer processors perform the computations. The problem domains best served by MoBiDiCK are parallel computing problems that are CPU-bound (not I/O-bound) and require minimal inter-process communication. The parallel tasks that we present include the analysis of databases of 3D protein structures and Monte Carlo simulations for ab-initio protein folding.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.386

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 communication0.0000.000
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 head0.037
GPT teacher head0.241
Teacher spread0.204 · 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