Data provenance and management in Radio Astronomy: a stream computing approach

Date
2011
Authors
Mahmoud, M
Ensor, A
Biem, A
Elmegreen, B
and Gulyaev, S
Supervisor
Item type
Chapter in Book
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract

New approaches for data provenance and data management (DPDM) are required for mega science projects like the Square Kilometer Array, characterized by extremely large data volume and intense data rates, therefore demanding innovative and highly efficient computational paradigms. In this context, we explore a stream-computing approach with the emphasis on the use of accelerators. In particular, we make use of a new generation of high performance stream-based parallelization middleware known as InfoSphere Streams. Its viability for managing and ensuring interoperability and integrity of signal processing data pipelines is demonstrated in radio astronomy. IBM InfoSphere Streams embraces the stream-computing paradigm. It is a shift from conventional data mining techniques (involving analysis of existing data from databases) towards real-time analytic processing. We discuss using InfoSphere Streams for effective DPDM in radio astronomy and propose a way in which InfoSphere Streams can be utilized for large antennae arrays. We present a case-study: the InfoSphere Streams implementation of an autocorrelating spectrometer, and using this example we discuss the advantages of the stream-computing approach and the utilization of hardware accelerators.

Description
Keywords
Stream Computing , Radio Astronomy , InfoSphere Streams
Source
Data Provenance and Data Management in eScience Studies in Computational Intelligence Volume 426, 2013, pp 129-156
Publisher's version
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