Open OnDemand: State of the platform, project, and the future

Open OnDemand: State of the platform, project, and the future
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Open OnDemand:平台、项目和未来的状态

DOI:
10.1002/cpe.6114
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发表时间:
2020
期刊:
Concurrency and Computation: Practice and Experience
影响因子:
--
通讯作者:
Gallo, Steven M.
Gallo, Steven M.
中科院分区:
--
文献类型:
--
作者:
Chalker, Alan;Franz, Eric;Rodgers, Morgan;Dockendorf, Trey;Johnson, Doug;Sajdak, Doris;White, Joseph P.;Plessinger, Benjamin D.;Zia, Mohammad;Gallo, Steven M.

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高性能计算(HPC)已经在科学和工程领域取得了显着的进步,并已成为不可或缺的研究工具。不幸的是,许多研究人员对HPC的使用和采用往往受到访问这些资源的复杂方式的阻碍。事实上,虽然Web已经成为几乎每个计算领域中远程计算服务的主要访问机制,但HPC是一个值得注意的例外。Open OnDemand是一个开源项目,通过提供对HPC资源的基于Web的访问来否定这一趋势(https://openondemand.org)。本文介绍了在3年项目中采用的挑战和其他可能与其他科学门户项目相关的经验教训。最后,我们描述了项目团队在Open OnDemand 2.0项目期间的未来计划,包括机器学习和GPU监控方面的具体开发。
High performance computing (HPC) has led to remarkable advances in science and engineering and has become an indispensable tool for research. Unfortunately, HPC use and adoption by many researchers is often hindered by the complex way these resources are accessed. Indeed, while the web has become the dominant access mechanism for remote computing services in virtually every computing area, HPC is a notable exception. Open OnDemand is an open source project negating this trend by providing web‐based access to HPC resources ( https://openondemand.org). This article describes the challenges to adoption and other lessons learned over the 3‐year project that may be relevant to other science gateway projects. We end with a description of future plans the project team has during the Open OnDemand 2.0 project including specific developments in machine learning and GPU monitoring.
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发表时间: 2015
影响因子: 2.1
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