Data Provenance and Management in Radio Astronomy: A Stream Computing Approach

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 streamcomputing 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 usMahmoud S. Mahmoud AUT Institute for Radio Astronomy & Space Research, Auckland NZ e-mail: [email protected] Andrew Ensor AUT Institute for Radio Astronomy & Space Research, Auckland NZ e-mail: [email protected] Alain Biem IBM T J Watson Research Center, Yorktown Heights NY e-mail: [email protected] Bruce Elemgreen IBM T J Watson Research Center, Yorktown Heights NY e-mail: [email protected] Sergei Gulyaev AUT Institute for Radio Astronomy & Space Research, Auckland NZ e-mail: [email protected] 1 ar X iv :1 11 2. 25 84 v1 [ cs .D C ] 1 2 D ec 2 01 1 2 M.S. Mahmoud, A. Ensor, A. Biem, B. Elmegreen & S. Gulyaev ing this example we discuss the advantages of the stream-computing approach and the utilization of hardware accelerators.