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.
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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