Skip to main content
SpringerLink
Log in

Scaling radio astronomy signal correlation on heterogeneous supercomputers using variousdata distribution methodologies

  • Original Article
  • Published:
Experimental Astronomy Aims and scope Submit manuscript

Abstract

Next generation radio telescopes will require orders of magnitude more computing power to provide a view of the universe with greater sensitivity. In the initial stages of the signal processing flow of a radio telescope, signal correlation is one of the largest challenges in terms of handling huge data throughput and intensive computations. We implemented a GPU cluster based software correlator with various data distribution models and give a systematic comparison based on testing results obtained using the Fornax supercomputer. By analyzing the scalability and throughput of each model, optimal approaches are identified across a wide range of problem sizes, covering the scale of next generation telescopes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Deller, A.T., Tingay, S.J., Bailes, M., West, C.: DiFX: a software correlator for very long baseline interferometry using multiprocessor computing environments. Publ. Astron. Soc. Pac. 119, 318–336 (2007)

    Article  ADS  Google Scholar 

  2. Deller, A.T., Brisken, W.F., Phillips, C.J., Morgan, J., Alef, W., Cappallo, R., Middelberg, E., Romney, J., Rottmann, H., Tingay, S.J., Wayth, R.: DiFX2: a more flexible, efficient, robust and powerful software correlator. Publ. Astron. Soc. Pac. 123, 275–287 (2011)

    Article  ADS  Google Scholar 

  3. Dodson, R., et al: Astronomical HPC: Intel’s Many Integrated Core in Astronomical Applications. Intel Supercomputing Conference (2012)

  4. Romein, J.W., Broekema, P.C., Meijeren, E., Schaaf, K., Zwart, W.H.: Astronomical real-time streaming signal processing on a Blue Gene/L supercomputer. Proceedings of the Eighteenth Annual ACM Symposium on Parallelism in Algorithms and Architectures, pp. 59–66 (2006)

  5. Romein, J.W., Broekema, P.C., Mol, J.D., Nieuwpoort, R.V.: The LOFAR correlator: implementation and performance analysis. Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, pp. 169–178 (2010)

  6. Nieuwpoort, R.V., Romein, J.W.: Correlating radio astronomy signals with many-core hardware. Int. J. Parallel Prog. 39(1), 88–114 (2011)

    Article  Google Scholar 

  7. Schaaf, K., Overeem, R.: COTS correlator platform. Exp. Astron. 17, 287–297 (2004)

    Article  ADS  Google Scholar 

  8. Harris, C., Haines, K., Staveley-Smith, L.: GPU accelerated radio astronomy signal convolution. Exp. Astron. 22, 129–141 (2008)

    Article  ADS  Google Scholar 

  9. Wayth, R.B., Greenhill, L.J., Briggs, F.H.: A GPU based real-time software correlation system for the Murchison Widefield Array prototype. Publ. Astron. Soc. Pac. 121(882), 857–865 (2009)

    Article  ADS  Google Scholar 

  10. Clark, M.A., La Plante, P.C., Greenhill, L.J.: Accelerating radio astronomy cross-correlation with Graphics Processing Units. arXiv:1107.4264v2 (2012)

  11. Ford, D., Faulkner, A., Alexander, P.: A Software Correlator for SKA. The SKA Publications. Memo 139 (2012)

  12. Fagg, G.E., Pjesivac-grbovic, J., Bosilca, G., Dongarra, J.J., Jeannot, E.: Flexible collective communication tuning architecture applied to open MPI. 2006 Euro PVM/MPI (2006)

  13. Jin, C., Klasky, S., Hodson, S., Yu, W., Lofstead, J., Abbasi, H., Schwan, K., Wolf, M., Liao, W., Choudhary, A., Parashar, M., Docan, C., Oldfield, R.: Adaptive IO System (ADIOS). Cray User Group (2008)

  14. Law, C.J., Bower, G.C.: All Transients, All the Time: Real-Time Radio Transient Detection with Interferometric Closure Quantities. arXiv:1112.0308v2 (2012)

Download references

Acknowledgments

The work was supported by iVEC through the use of advanced computing resources located at iVEC@Murdoch and iVEC@UWA.

Author information

Authors and Affiliations

  1. ICRAR, M468, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia

    Ruonan Wang

  2. iVEC@UWA, M024, The University of Western Australia, 35 Stirling Highway, Crawley, WA, 6009, Australia

    Christopher Harris

Authors
  1. Ruonan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christopher Harris
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ruonan Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, R., Harris, C. Scaling radio astronomy signal correlation on heterogeneous supercomputers using variousdata distribution methodologies. Exp Astron 36, 433–449 (2013). https://doi.org/10.1007/s10686-013-9340-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10686-013-9340-7

Keywords

Search

Navigation