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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| Veröffentlicht in: | Journal of biomedical optics 2022-08, Vol.27 (8), p.083008-083008 |
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| creator | Fang, Qianqian Yan, Shijie |
| 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. |
| doi_str_mv | 10.1117/1.JBO.27.8.083008 |
| format | Article |
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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.</description><identifier>ISSN: 1083-3668</identifier><identifier>EISSN: 1560-2281</identifier><identifier>DOI: 10.1117/1.JBO.27.8.083008</identifier><identifier>PMID: 34989198</identifier><language>eng</language><publisher>United States: Society of Photo-Optical Instrumentation Engineers</publisher><subject>Accuracy ; Algorithms ; Cloud Computing ; Computer Simulation ; Computers ; Data communication ; Graphical user interface ; Hardware ; JavaScript ; Monte Carlo Method ; Monte Carlo simulation ; Open source software ; Optimization ; Proprietary ; Software ; Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics ; User interface ; User services</subject><ispartof>Journal of biomedical optics, 2022-08, Vol.27 (8), p.083008-083008</ispartof><rights>The Authors. 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.</rights><rights>2022. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 The Authors 2022 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c466t-172b38fc031a719d331ad82dda8e6157ab73e1c70b9b9820be8d0d104958f1453</citedby><orcidid>0000-0003-0805-935X ; 0000-0002-1983-4625</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2862346256/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2862346256?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,21388,27924,27925,33744,33745,43805,53791,53793,64385,64387,64389,72469,74302</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34989198$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fang, Qianqian</creatorcontrib><creatorcontrib>Yan, Shijie</creatorcontrib><title>MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing</title><title>Journal of biomedical optics</title><addtitle>J. Biomed. Opt</addtitle><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. 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Yan, Shijie</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c466t-172b38fc031a719d331ad82dda8e6157ab73e1c70b9b9820be8d0d104958f1453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Cloud Computing</topic><topic>Computer Simulation</topic><topic>Computers</topic><topic>Data communication</topic><topic>Graphical user interface</topic><topic>Hardware</topic><topic>JavaScript</topic><topic>Monte Carlo Method</topic><topic>Monte Carlo simulation</topic><topic>Open source software</topic><topic>Optimization</topic><topic>Proprietary</topic><topic>Software</topic><topic>Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics</topic><topic>User interface</topic><topic>User services</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fang, Qianqian</creatorcontrib><creatorcontrib>Yan, Shijie</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ProQuest Biological Science Collection</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of biomedical optics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fang, Qianqian</au><au>Yan, Shijie</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing</atitle><jtitle>Journal of biomedical optics</jtitle><addtitle>J. Biomed. Opt</addtitle><date>2022-08-01</date><risdate>2022</risdate><volume>27</volume><issue>8</issue><spage>083008</spage><epage>083008</epage><pages>083008-083008</pages><issn>1083-3668</issn><eissn>1560-2281</eissn><abstract>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.</abstract><cop>United States</cop><pub>Society of Photo-Optical Instrumentation Engineers</pub><pmid>34989198</pmid><doi>10.1117/1.JBO.27.8.083008</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-0805-935X</orcidid><orcidid>https://orcid.org/0000-0002-1983-4625</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | ISSN: 1083-3668 |
| ispartof | Journal of biomedical optics, 2022-08, Vol.27 (8), p.083008-083008 |
| issn | 1083-3668 1560-2281 |
| language | eng |
| recordid | cdi_pubmed_primary_34989198 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; ProQuest Central UK/Ireland; PubMed Central; ProQuest Central |
| subjects | Accuracy Algorithms Cloud Computing Computer Simulation Computers Data communication Graphical user interface Hardware JavaScript Monte Carlo Method Monte Carlo simulation Open source software Optimization Proprietary Software Special Section Celebrating 30 Years of Open Source Monte Carlo Codes in Biomedical Optics User interface User services |
| title | MCX Cloud—a modern, scalable, high-performance and in-browser Monte Carlo simulation platform with cloud computing |
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