{"title":"A GPU Query Accelerator for Geospatial Coordinates Computation","authors":"K. Yong, W. K. Ho, M. Chua, S. See","doi":"10.1109/ICCCRI.2015.26","DOIUrl":null,"url":null,"abstract":"People and things become mobile sensors that converge to our daily life. This has unwittingly collected humongous of time series of data with location. People are finding ways to turn this raw data into valuable information as a distinguished business analytic. Importantly, the demand of speedy computation with an appealing visualization is crucial to success. Thus, it reveals the potential economic benefits and becomes an overwhelming new research area that requiring sophisticated mechanisms and technologies to reach the demand. Over the past decade, there have attempts of using accelerators along with multicore CPUs in boosting large-scale data computation. We proposed an emerging SQL-like GPU query accelerator, Galactic a DB. In addition, we extended it to have the geo-spatial compute capabilities. The query operation executes parallelly with drawing support from a high performance and energy efficient NVIDIA Tesla technology. Our result has shown the significant speedup by using Galactic a DB.","PeriodicalId":183970,"journal":{"name":"2015 International Conference on Cloud Computing Research and Innovation (ICCCRI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","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.2015.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
People and things become mobile sensors that converge to our daily life. This has unwittingly collected humongous of time series of data with location. People are finding ways to turn this raw data into valuable information as a distinguished business analytic. Importantly, the demand of speedy computation with an appealing visualization is crucial to success. Thus, it reveals the potential economic benefits and becomes an overwhelming new research area that requiring sophisticated mechanisms and technologies to reach the demand. Over the past decade, there have attempts of using accelerators along with multicore CPUs in boosting large-scale data computation. We proposed an emerging SQL-like GPU query accelerator, Galactic a DB. In addition, we extended it to have the geo-spatial compute capabilities. The query operation executes parallelly with drawing support from a high performance and energy efficient NVIDIA Tesla technology. Our result has shown the significant speedup by using Galactic a DB.
人和物成为移动传感器,融入我们的日常生活。这无意中收集了大量的时间序列数据与位置。人们正在寻找方法,将这些原始数据转化为有价值的信息,作为杰出的业务分析。重要的是,对快速计算和吸引人的可视化的需求是成功的关键。因此,它揭示了潜在的经济效益,成为一个压倒性的新研究领域,需要复杂的机制和技术来达到需求。在过去的十年中,人们尝试使用加速器和多核cpu来提高大规模数据计算。我们提出了一个新兴的类似sql的GPU查询加速器,Galactic a DB。此外,我们对其进行了扩展,使其具有地理空间计算能力。查询操作在高性能和节能的NVIDIA Tesla技术的支持下并行执行。我们的结果显示了使用Galactic a DB的显著加速。