| DOI | Resolve DOI: https://doi.org/10.1088/1742-6596/341/1/012003 |
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| Author | Search for: Charbonneau, A.1; Search for: Agarwal, A.; Search for: Anderson, M.; Search for: Armstrong, P.; Search for: Fransham, K.; Search for: Gable, I.; Search for: Harris, D.; Search for: Impey, R.1; Search for: Leavett-Brown, C.; Search for: Paterson, M.; Search for: Podaima, W.1; Search for: Sobie, R.J.; Search for: Vliet, M. |
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| Affiliation | - National Research Council of Canada
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| Format | Text, Article |
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| Conference | 25th High Performance Computing Symposium 2011, HPCS 2011, June 15-17 2011, Montreal, Quebec, Canada |
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| Subject | Batch jobs; Calibration data; Cloud systems; Data intensive; High-throughput computing; Input datas; Running applications; System use; Virtual machines; Physics; High energy physics |
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| Abstract | We show that distributed Infrastructure-as-a-Service (IaaS) compute clouds can be effectively used for the analysis of high energy physics data. We have designed a distributed cloud system that works with any application using large input data sets requiring a high throughput computing environment. The system uses IaaS-enabled science and commercial clusters in Canada and the United States. We describe the process in which a user prepares an analysis virtual machine (VM) and submits batch jobs to a central scheduler. The system boots the user-specific VM on one of the IaaS clouds, runs the jobs and returns the output to the user. The user application accesses a central database for calibration data during the execution of the application. Similarly, the data is located in a central location and streamed by the running application. The system can easily run one hundred simultaneous jobs in an efficient manner and should scale to many hundreds and possibly thousands of user jobs. © IOP Publishing Ltd. |
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| Publication date | 2012-02-09 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21270119 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 62199ecd-5f15-4f2d-a459-42212e41bc9e |
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| Record created | 2014-01-03 |
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| Record modified | 2020-04-21 |
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