使用Windows Azure云快速处理合成地震记录

Vedaprakash Subramanian, Liqiang Wang, En-Jui Lee, Po Chen
{"title":"使用Windows Azure云快速处理合成地震记录","authors":"Vedaprakash Subramanian, Liqiang Wang, En-Jui Lee, Po Chen","doi":"10.1109/CloudCom.2010.110","DOIUrl":null,"url":null,"abstract":"Currently, numerically simulated synthetic seismograms are widely used by seismologists for seismological inferences. The generation of these synthetic seismograms requires large amount of computing resources, and the maintenance of these observed seismograms requires massive storage. Traditional high-performance computing platforms is inefficient to handle these applications because rapid computations are needed and large-scale datasets should be maintained. The emerging cloud computing platform provides an efficient substitute. In this paper, we introduce our experience on implementing a computational platform for rapidly computing and delivering synthetic seismograms on Windows Azure. Our experiment shows that cloud computing is an ideal platform for such kind of applications.","PeriodicalId":130987,"journal":{"name":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":"{\"title\":\"Rapid Processing of Synthetic Seismograms Using Windows Azure Cloud\",\"authors\":\"Vedaprakash Subramanian, Liqiang Wang, En-Jui Lee, Po Chen\",\"doi\":\"10.1109/CloudCom.2010.110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Currently, numerically simulated synthetic seismograms are widely used by seismologists for seismological inferences. The generation of these synthetic seismograms requires large amount of computing resources, and the maintenance of these observed seismograms requires massive storage. Traditional high-performance computing platforms is inefficient to handle these applications because rapid computations are needed and large-scale datasets should be maintained. The emerging cloud computing platform provides an efficient substitute. In this paper, we introduce our experience on implementing a computational platform for rapidly computing and delivering synthetic seismograms on Windows Azure. Our experiment shows that cloud computing is an ideal platform for such kind of applications.\",\"PeriodicalId\":130987,\"journal\":{\"name\":\"2010 IEEE Second International Conference on Cloud Computing Technology and Science\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"38\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Second International Conference on Cloud Computing Technology and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CloudCom.2010.110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CloudCom.2010.110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38

摘要

目前,数值模拟合成地震记录被地震学家广泛用于地震推断。这些合成地震图的生成需要大量的计算资源,而这些观测到的地震图的维护需要大量的存储空间。传统的高性能计算平台处理这些应用程序的效率低下,因为需要快速计算并且需要维护大规模的数据集。新兴的云计算平台提供了一个有效的替代品。本文介绍了我们在Windows Azure上实现快速计算和交付合成地震记录的计算平台的经验。我们的实验表明,云计算是这类应用的理想平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid Processing of Synthetic Seismograms Using Windows Azure Cloud
Currently, numerically simulated synthetic seismograms are widely used by seismologists for seismological inferences. The generation of these synthetic seismograms requires large amount of computing resources, and the maintenance of these observed seismograms requires massive storage. Traditional high-performance computing platforms is inefficient to handle these applications because rapid computations are needed and large-scale datasets should be maintained. The emerging cloud computing platform provides an efficient substitute. In this paper, we introduce our experience on implementing a computational platform for rapidly computing and delivering synthetic seismograms on Windows Azure. Our experiment shows that cloud computing is an ideal platform for such kind of applications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信