D. Elia, S. Fiore, Alessandro D'Anca, Cosimo Palazzo, Ian T Foster, Dean N. Williams, G. Aloisio
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引用次数: 16
Abstract
This work presents the I/O in-memory server implemented in the context of the Ophidia framework, a big data analytics stack addressing scientific data analysis of n-dimensional datasets. The provided I/O server represents a key component in the Ophidia 2.0 architecture proposed in this paper. It exploits (i) a NoSQL approach to manage scientific data at the storage level, (ii) user-defined functions to perform array-based analytics, (iii) the Ophidia Storage API to manage heterogeneous back-ends through a plugin-based approach, and (iv) an in-memory and parallel analytics engine to address high scalability and performance. Preliminary performance results about a statistical analytics kernel benchmark performed on a HPC cluster running at the CMCC SuperComputing Centre are provided in this paper.
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