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  • 标题:The Optimization of Algorithms in the Process of Temporal Data Mining Using the Compute Unified Device Architecture
  • 本地全文:下载
  • 作者:Alexandru PIRJAN
  • 期刊名称:Database Systems Journal
  • 电子版ISSN:2069-3230
  • 出版年度:2010
  • 卷号:I
  • 期号:1
  • 页码:37-47
  • 出版社:Bucharest Academy of Economic Studies Publishing House
  • 摘要:Considering the importance and usefulness of real time data mining, in recent years the concern of researchers to discover new hardware architectures that can manage and process large volumes of data has increased significantly. In this paper the performance of algorithms for temporal data mining that are implemented in the new Compute Unified Device Architecture (CUDA) from the latest generation of graphics processing units (GPU) will be analyzed and reviewed. The performance will be evaluated taking into account the type of algorithm, data access, the problems' size, the GPU’s processor generation, the number of threads processed.
  • 关键词:Temporal data mining; MapReduce; CUDA; GPU; Fermi; thread; kernel.
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