Introduction
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.
Call for paper
Submission Topics
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:
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Novel large graph data management systems
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Deep Learning and its applications
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Novel large graph processing frameworks and programming paradigms
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Graph processing in many core processors such as GPGPUs/FPGAs, Xeon Phi, etc.
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Graph data mining in HPC Clouds
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Workflows which involve both graph data mining and machine learning
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HPC graph databases and query languages
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Novel graph partitioning algorithms
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Application experiences of large graph processing on HPC environments
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Benchmarks for large graph processing workloads
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Performance characterization of large graph mining tasks
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Scalable graph analysis algorithms and novel data structures
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High performance streaming graph processing algorithms
All Comments
Important Date
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Nov 18
2017
Conference Date
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Nov 18 2017
Registration deadline
Sponsored By
Contact Information
- Toyotaro Suzumura
- su******@acm.org
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