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Workflow management for high volume supernova search

Published:08 March 2009Publication History

ABSTRACT

Observational astrophysics has recently become a data-intensive science after many decades of relative data poverty. As a result, many of the algorithms developed for processing astronomical data, although well established for low-volume data capture, do not scale well to today's high-volume sky surveys and transient searches. Specifically, problems may occur with data transfer, workflow management, efficient parallelization, and integration of legacy code. Observational astrophysics workflows present computational challenges unique in high performance computing, including 24/7 operations, time-critical processing, and very large numbers of relatively small data files which must all be processed and archived. We present a case study based on Sunfall, a distributed, parallel scientific workflow system we built for the Nearby Supernova Factory, the largest data-volume supernova search currently in existence. We describe innovative techniques for data transfer and workflow management, and discuss lessons learned in building a large-scale observational astrophysics workflow management system.

References

  1. Aldering, G., et al. Overview of the Nearby Supernova Factory. Proceedings of the SPIE, 2002, 61--72.Google ScholarGoogle ScholarCross RefCross Ref
  2. Aragon, C. and Aragon, D. B. A Fast Contour Descriptor Algorithm for Supernova Image Classification. SPIE Symposium on Electronic Imaging: Real-Time Image Processing, San Jose, CA, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  3. Aragon, C., Bailey, S., Poon, S., Runge, K. and Thomas, R. C. Sunfall: A Collaborative Visual Analytics System for Astrophysics. SciDAC, Seattle, WA, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  4. Aragon, C., Poon, S., Aldering, G., Thomas, R. C. and Quimby, R. Using Visual Analytics to Maintain Situational Awareness in Astrophysics. IEEE Symposium on Visual Analytics Science and Technology (VAST), Columbus, OH, 2008.Google ScholarGoogle Scholar
  5. Astier, P. SuperNova Legacy Survey (SNLS). A&A (447), 2006, 31--48.Google ScholarGoogle Scholar
  6. Bailey, S., Aragon, C., Romano, R., Thomas, R. C., Weaver, B. A. and Wong, D. How to Find More Supernovae with Less Work: Object Classification Techniques for Difference Imaging. Astrophysical Journal, 2007.Google ScholarGoogle Scholar
  7. Cao, J., Jarvis, S. A., Saini, S. and Nudd, G. R. GridFlow: Workflow Management for Grid Computing. Third IEEE International Symposium on Cluster Computing and the Grid (CCGrid'03), 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Foster, I. and Kesselman, C. The Grid 2: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco, CA, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. GPFS, IBM General Parallel File System, 2006, http://www03.ibm.com/systems/clusters/software/gpfs.html.Google ScholarGoogle Scholar
  10. HPSS, NERSC High Performance Storage System, 2007, http://www.nersc.gov/nusers/systems/HPSS/.Google ScholarGoogle Scholar
  11. HPWREN, High Performance Wireless Research and Education Network, 2004, http://hpwren.ucsd.edu.Google ScholarGoogle Scholar
  12. LSST, Large Synoptic Survey Telescope, 2008, http://lsst.org.Google ScholarGoogle Scholar
  13. Ludaescher, B., Altintas, I., Berkley, C., Higgins, D., Jaeger-Frank, E., Jones, M., Lee, E., Tao, J. and Zhao, Y. Scientific Workflow Management and the Kepler System. Concurrency and Computation: Practice & Experience (Special Issue on Scientific Workflows), 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. NASA, The Joint Dark Energy Mission, 2008, http://universe.nasa.gov/program/probes/jdem.html.Google ScholarGoogle Scholar
  15. NEAT, Near Earth Asteroid Tracking, 2007, http://neat.jpl.nasa.gov.Google ScholarGoogle Scholar
  16. NERSC, National Energy Research Scientific Computing Center, 2008, http://www.nersc.gov.Google ScholarGoogle Scholar
  17. PanSTARRS, Pan-STARRS: Panoramic Survey Telescope and Rapid Response System, 2008, http://panstarrs.ifa.hawaii.edu/.Google ScholarGoogle Scholar
  18. PDSF, NERSC Parallel Distributed Systems Facility, 2008, http://www.nersc.gov/nusers/systems/PDSF/.Google ScholarGoogle Scholar
  19. Perlmutter, S., Aldering, G., Goldhaber, G., et al. Measurements of Omega and Lambda from 42 High-Redshift Supernovae. Astrophysical Journal, 1999 (517), 1999, 565--586.Google ScholarGoogle ScholarCross RefCross Ref
  20. Ptolemy, The Ptolemy II software framework, 2004, http://ptolemy.eecs.berkeley.edu/ptolemyII.Google ScholarGoogle Scholar
  21. Riess, A. G., Filippenko, A. V., et al. Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant. Astrophysical Journal, 1998 (116), 1998, 1009--1038.Google ScholarGoogle Scholar
  22. Romano, R., Aragon, C. and Ding, C. Supernova Recognition Using Support Vector Machines. Proceedings of the 5th International Conference of Machine Learning Applications, Orlando, FL, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Sako, M. The Sloan Digital Sky Survey-II Supernova Survey: Search Algorithm and Follow-Up Observations. Astronomical Journal, 135, 2008, 348--373.Google ScholarGoogle Scholar
  24. Scheidegger, C., Koop, D., Freire, J. and Silva, C. Querying and Re-Using Workflows with VisTrails. ACM SIGMOD International Conference on Management of Data, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. SDSS, Sloan Digital Sky Survey, 2008, http://www.sdss.org.Google ScholarGoogle Scholar
  26. Silva, C., Freire, J. and Callahan, S. Provenance for Visualizations: Reproducibility and Beyond. IEEE Computing in Science & Engineering, 9 (5), 2007, 82--89. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. SNfactory, The Nearby Supernova Factory, 2008, http://snfactory.lbl.gov.Google ScholarGoogle Scholar
  28. SNLS, SuperNova Legacy Survey, 2008, http://www.cfht.hawaii.edu/SNLS/.Google ScholarGoogle Scholar
  29. UH88, University of Hawaii 2.2-meter telescope, 2004, http://www.ifa.hawaii.edu/88inch/.Google ScholarGoogle Scholar
  30. Wood-Vasey, W. M. Rates and Progenitors of Type Ia Supernovae Physics, University of California, Berkeley, 2004.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing
      March 2009
      2347 pages
      ISBN:9781605581668
      DOI:10.1145/1529282

      Copyright © 2009 ACM

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      Publication History

      • Published: 8 March 2009

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