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The High Performance Graph Data Mining and Machine Learning (HPGDML) 2017 workshop will be the first in a series of workshops organized on large graph data management and machine learning using high performance computing systems. The workshop will be held on 18th November 2017, at The Roosevelt New Orleans, New Orleans, USA co-located with the The IEEE International Conference on Data Mining (ICDM) 2017. HGDML'17 will be a half-day workshop.

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The topics of interest of the HPGDML'17 include multiple aspects of graph processing and machine learning on high performance systems, but not limited to:

  • Novel large graph data management systems

  • Deep Learning and its applications

  • Novel large graph processing frameworks and programming paradigms

  • Graph processing in many core processors such as GPGPUs/FPGAs, Xeon Phi, etc.

  • Graph data mining in HPC Clouds

  • Workflows which involve both graph data mining and machine learning

  • HPC graph databases and query languages

  • Novel graph partitioning algorithms

  • Application experiences of large graph processing on HPC environments

  • Benchmarks for large graph processing workloads

  • Performance characterization of large graph mining tasks

  • Scalable graph analysis algorithms and novel data structures

  • High performance streaming graph processing algorithms

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重要日期
  • 11月18日

    2017

    会议日期

  • 11月18日 2017

    注册截止日期

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IEEE 计算机学会
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