Using a Robust Metadata Management System to Accelerate Scientific Discovery at Extreme Scales

Abstract

Our previous work, which can be referred to as EMPRESS 1.0, showed that rich metadata management provides a relatively low-overhead approach to facilitating insight from scale-up scientific applications. However, this system did not provide the functionality needed for a viable production system or address whether such a system could scale. Therefore, we have extended our previous work to create EMPRESS 2.0, which incorporates the features required for a useful production system. Through a discussion of EMPRESS 2.0, this paper explores how to incorporate rich query functionality, fault tolerance, and atomic operations into a scalable, storage system independent metadata management system that is easy to use. This paper demonstrates that such a system offers significant performance advantages over HDF5, providing metadata querying that is 150X to 650X faster, and can greatly accelerate post-processing. Finally, since the current implementation of EMPRESS 2.0 relies on an RDBMS, this paper demonstrates that an RDBMS is a viable technology for managing data-oriented metadata.

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