{"title":"Searching Simulation Scenarios on the Grid with ELSIGExplorer","authors":"I. Muntean, Laura Maria Dansorean","doi":"10.1109/SYNASC.2011.43","DOIUrl":null,"url":null,"abstract":"Grids became a commonplace for the computation of expensive numerical simulations. This work addresses the problem of searching for relevant simulations and for their results in a grid. This is challenging especially due to the large number of existing simulations, the small semantic differences between them, and the distributed nature of the grid environment. We propose a solution that addresses simultaneously these three challenges by integrating a latent semantic indexing algorithm a linguistic processing module with a grid application framework. This resulted in a novel prototype, ELSIG Explorer, capable of retrieving relevant scenarios computed with Grid SFEA on heterogeneous grids. We evaluated our approach on benchmark datasets from the medical domain and on a set of scenarios for simulating dynamic behavior of biological neural microcircuits in grid.","PeriodicalId":184344,"journal":{"name":"2011 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":"143 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 13th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2011.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Grids became a commonplace for the computation of expensive numerical simulations. This work addresses the problem of searching for relevant simulations and for their results in a grid. This is challenging especially due to the large number of existing simulations, the small semantic differences between them, and the distributed nature of the grid environment. We propose a solution that addresses simultaneously these three challenges by integrating a latent semantic indexing algorithm a linguistic processing module with a grid application framework. This resulted in a novel prototype, ELSIG Explorer, capable of retrieving relevant scenarios computed with Grid SFEA on heterogeneous grids. We evaluated our approach on benchmark datasets from the medical domain and on a set of scenarios for simulating dynamic behavior of biological neural microcircuits in grid.