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MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing
SIGNIFICANCE: Despite the ample progress made toward faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers to widespread use among the broad user community. AIM: An open-source, hi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728956/ https://www.ncbi.nlm.nih.gov/pubmed/34989198 http://dx.doi.org/10.1117/1.JBO.27.8.083008 |
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author | Fang, Qianqian Yan, Shijie |
author_facet | Fang, Qianqian Yan, Shijie |
author_sort | Fang, Qianqian |
collection | PubMed |
description | SIGNIFICANCE: Despite the ample progress made toward faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers to widespread use among the broad user community. AIM: An open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization. APPROACH: We have developed a configuration-free, in-browser 3D MC simulation platform—Monte Carlo eXtreme (MCX) Cloud—built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas. RESULTS: The front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using MCX over a dynamically expandable virtual cluster. CONCLUSION: MCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud. |
format | Online Article Text |
id | pubmed-8728956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-87289562022-01-06 MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing Fang, Qianqian Yan, Shijie J Biomed Opt Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics SIGNIFICANCE: Despite the ample progress made toward faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers to widespread use among the broad user community. AIM: An open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization. APPROACH: We have developed a configuration-free, in-browser 3D MC simulation platform—Monte Carlo eXtreme (MCX) Cloud—built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas. RESULTS: The front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using MCX over a dynamically expandable virtual cluster. CONCLUSION: MCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud. Society of Photo-Optical Instrumentation Engineers 2022-01-05 2022-08 /pmc/articles/PMC8728956/ /pubmed/34989198 http://dx.doi.org/10.1117/1.JBO.27.8.083008 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. |
spellingShingle | Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics Fang, Qianqian Yan, Shijie MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title_full | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title_fullStr | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title_full_unstemmed | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title_short | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
title_sort | mcx cloud—a modern, scalable, high-performance and in-browser monte carlo simulation platform with cloud computing |
topic | Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8728956/ https://www.ncbi.nlm.nih.gov/pubmed/34989198 http://dx.doi.org/10.1117/1.JBO.27.8.083008 |
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