{"title":"一个集成的云平台,用于快速生成界面,作业调度,监控,绘图和案例管理的科学应用","authors":"W. Brewer, W. Scott, John Sanford","doi":"10.1109/ICCCRI.2015.24","DOIUrl":null,"url":null,"abstract":"The Scientific Platform for the Cloud (SPC) presents a framework to support the rapid design and deployment of scientific applications (apps) in the cloud. It provides common infrastructure for running typical IXP (Input-execute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and case manager. In this paper we (1) describe the design of the system architecture, (2) evaluate its applicability to a scientific workload, and (3) present a number of case studies which represent a wide variety of scientific applications including Population Genetics, Geophysics, Turbulence Physics, DNA analysis, and Big Data.","PeriodicalId":183970,"journal":{"name":"2015 International Conference on Cloud Computing Research and Innovation (ICCCRI)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Integrated Cloud Platform for Rapid Interface Generation, Job Scheduling, Monitoring, Plotting, and Case Management of Scientific Applications\",\"authors\":\"W. Brewer, W. Scott, John Sanford\",\"doi\":\"10.1109/ICCCRI.2015.24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Scientific Platform for the Cloud (SPC) presents a framework to support the rapid design and deployment of scientific applications (apps) in the cloud. It provides common infrastructure for running typical IXP (Input-execute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and case manager. In this paper we (1) describe the design of the system architecture, (2) evaluate its applicability to a scientific workload, and (3) present a number of case studies which represent a wide variety of scientific applications including Population Genetics, Geophysics, Turbulence Physics, DNA analysis, and Big Data.\",\"PeriodicalId\":183970,\"journal\":{\"name\":\"2015 International Conference on Cloud Computing Research and Innovation (ICCCRI)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Cloud Computing Research and Innovation (ICCCRI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCRI.2015.24\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Cloud Computing Research and Innovation (ICCCRI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCRI.2015.24","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Integrated Cloud Platform for Rapid Interface Generation, Job Scheduling, Monitoring, Plotting, and Case Management of Scientific Applications
The Scientific Platform for the Cloud (SPC) presents a framework to support the rapid design and deployment of scientific applications (apps) in the cloud. It provides common infrastructure for running typical IXP (Input-execute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and case manager. In this paper we (1) describe the design of the system architecture, (2) evaluate its applicability to a scientific workload, and (3) present a number of case studies which represent a wide variety of scientific applications including Population Genetics, Geophysics, Turbulence Physics, DNA analysis, and Big Data.