Evidence map›Paper›PMID 39503000›Full record

ArticleGeoscientific model development2024

Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community.

Christos I Efstathiou, Elizabeth Adams, Carlie J Coats, Robert Zelt, Mark Reed, John McGee, Kristen M Foley, Fahim I Sidi, David C Wong, Steven Fine and 1 more

Abstract read
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In one paragraph

Article in Geoscientific model development, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Christos I EfstathiouInstitute for the Environment, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Elizabeth AdamsInstitute for the Environment, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Carlie J CoatsInstitute for the Environment, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Robert ZeltResearch Computing, Information Technology Services, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mark ReedResearch Computing, Information Technology Services, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
John McGeeResearch Computing, Information Technology Services, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Kristen M FoleyCenter for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
Fahim I SidiCenter for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
David C WongCenter for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27709, USA.
Steven FineInstitute for the Environment, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Saravanan ArunachalamInstitute for the Environment, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

Funding

EPA EP-C-16-014Intramural EPA EPA999999
6 · The paper itself

Abstract

The Community Multiscale Air Quality Model (CMAQ) is a local- to hemispheric-scale numerical air quality modeling system developed by the U.S. Environmental Protection Agency (USEPA) and supported by the Community Modeling and Analysis System (CMAS) center. CMAQ is used for regulatory purposes by the USEPA program offices and state and local air agencies and is also widely used by the broader global research community to simulate and understand complex air quality processes and for computational environmental fate and transport and climate and health impact studies. Leveraging state-of-the-science cloud computing resources for high-performance computing (HPC) applications, CMAQ is now available as a fully tested, publicly available technology stack (HPC cluster and software stack) for two major cloud service providers (CSPs). Specifically, CMAQ configurations and supporting materials have been developed for use on their HPC clusters, including extensive online documentation, tutorials and guidelines to scale and optimize air quality simulations using their services. These resources allow modelers to rapidly bring together CMAQ, cloud-hosted datasets, and visualization and evaluation tools on ephemeral clusters that can be deployed quickly and reliably worldwide. Described here are considerations in CMAQ version 5.3.3 cloud use and the supported resources for each CSP, presented through a benchmark application suite that was developed as an example of a typical simulation for testing and verifying components of the modeling system. The outcomes of this effort are to provide findings from performing CMAQ simulations on the cloud using popular vendor-provided resources, to enable the user community to adapt this for their own needs, and to identify specific areas of potential optimization with respect to storage and compute architectures.

Identifiers

PMID39503000
PMCPMC11534021

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.