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December 22, 2009
Thirumale Niranjan, Sai Susarla, Chiranjib Bhattacharyya, and K. Gopinath.
In this tutorial, the presenters explained the details of modern storage systems and how to construct models for intelligent storage management.
A Tutorial Presented at the International Conference on High Performance Computing 2009 (HiPC ’09)
Applications are becoming more and more data intensive, leading to petascale and exascale storage systems. Consolidation in this space is occurring rapidly in the form of Cloud Storage. As more applications share a common storage infrastructure that itself gets more complex, the need for automated management increases. Reasoning about such systems requires sophisticated models. In this session, the presenters explained the details of modern storage systems, and how to construct models for intelligent storage management. The presenters surveyed different modeling approaches such as white-box, black-box and grey-box modeling, relative fitness modeling, and hierarchical/compositional modeling that others had employed in the past, and discussed successes and failures. The mathematical basis for much of model-based autonomics is in the area of statistical machine learning. The presenters elaborated on the range of machine learning tools, the mathematics behind them, and how they can be used for modeling. The session was concluded with a discussion on the many interesting open problems in the area.