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Record W7100046808

177PARALLELIZATION OF FVCOM PARALLELIZATION OF THE FVCOM COASTAL OCEAN MODEL

2016· article· en· W7100046808 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsnot available
Fundersnot available
KeywordsGridSPMDFinite volume methodSoftwareMessage Passing InterfaceDomain decomposition methodsUnstructured gridDomain (mathematical analysis)Vectorization (mathematics)Interface (matter)
DOInot available

Abstract

fetched live from OpenAlex

The Finite Volume Coastal Ocean Model (FVCOM) is a publicly available software package for simulation of ocean processes in coastal areas. The unstructured grid approach used in the model is highly advantageous for resolving dynamics in regions with complex shorelines such as estu-aries, embayments, and archipelagos. A growing user community and a demand for large-scale, high resolution simulations has driven the need for the implementation of a portable and efficient parallelization of the FVCOM core code. The triangular grid approach used in FVCOM pre-cludes the utilization of schemes used previously in the parallelization of popular structured grid ocean models. This paper describes recent work on a SPMD paralleli-zation of FVCOM. The METIS partitioning libraries are employed to decompose the domain. Parallel operations are programmed with the Message Passing Interface (MPI) standard interface. Updates for flow quantities near the interprocessor domain boundaries are performed using a mixture of halo and flux summation approaches to mini-mize communication overhead. Evaluation of the imple-mentation efficiency is made on machines comprising several parallel architectures and interconnect types. The implementation is found to scale well on medium-sized ( ~ 256 processor) clusters. An execution time model is developed to expose bottlenecks and extrapolate the per-formance of FVCOM to increasingly available large MPP machines. Application to a model of water circulation in the Gulf of Maine shows that the parallelized code greatly increases the capabilities of the original core scheme by extending practical model simulation timescales and spa-tial resolution.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.722
Threshold uncertainty score0.362

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 science0.0000.000
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 head0.059
GPT teacher head0.396
Teacher spread0.337 · 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