Skip to main content
SpringerLink
Log in

A Radar Signal Processing Case Study for Dataflow Programming of Manycores

  • Published:
Journal of Signal Processing Systems Aims and scope Submit manuscript

Abstract

The successful realization of next generation radar systems have high performance demands on the signal processing chain. Among these are advanced Active Electronically Scanned Array (AESA) radars in which complex calculations are to be performed on huge sets of data in real-time. Manycore architectures are designed to provide flexibility and high performance essential for such streaming applications. This paper deals with the implementation of compute-intensive parts of AESA radar signal processing chain in a high-level dataflow language; CAL. We evaluate the approach by targeting a commercial manycore architecture, Epiphany, and present our findings in terms of performance and productivity gains achieved in this case study. The comparison of the performance results with the reference sequential implementations executing on a state-of-the-art embedded processor show that we are able to achieve a speedup of 1.6x to 4.4x by using only 10 cores of Epiphany.

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

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10

Similar content being viewed by others

References

  1. Pettersson, J., & Wainwright, I. (2010). Radar signal processing with graphic processors (GPUs). Technical report. ISSN: 1401–5773.

  2. Olofsson, A., Nordström, T., & Ul-Abdin, Z. (2014). Kickstarting high-performance energy-efficient Manycore architectures with epiphany. In Proceedings of the Forty Eigth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

  3. Lee, E.A., & Messerschmitt, D.G. (1987). Synchronous data flow. In Proceedings of the IEEE, (Vol. 75 pp. 1235–1245).

  4. Bhattacharya, B., & Bhattacharyya, S.S. (2001). Parameterized dataflow modeling of DSP systems. IEEE Transactions on Signal Processing, 49(10), 2408–2421.

    Article  MathSciNet  Google Scholar 

  5. Eker, J., & Janneck, J.W. (2003). CAL language report specification of the CAL actor language. Berkeley: EECS Department. Technical Report UCB/ERL M03/48.

  6. Bhattacharyya, S.S., Eker, J., Janneck, J.W., Lucarz, C., Mattavelli, M., & Raulet, M. (2009). Overview of the MPEG reconfigurable video coding framework: Springer.

  7. Ul-Abdin, Z., & Svensson, B. (2012). Occam-pi for programming of massively parallel reconfigurable architectures. International Journal of Reconfigurable Computing, 2012(504815), 17.

    Google Scholar 

  8. Ul-Abdin, Z., & Yang, M. (2014). Dataflow programming of real-time radar signal processing on Manycores. In Proceedings of the IEEE Global Conference on Signal and Information Processing (GlobalSIP).

  9. Roquier, G., Wipliez, M., Raulet, M., Nezan, J.-F., & Déforges, O. (2008). Software synthesis of CAL actors for the MPEG reconfigurable video coding framework. In Proceedings of the 15th IEEE International Conference on Image Processing, (ICIP).

  10. Open RVC-CAL Compiler, “http://orcc.sourceforge.net/” [Online] Accessed: 3 August 2013.

  11. Yviquela, H., Boutellierc, J., Raulet, M., & Casseaua, E. (2013). Automated design of networks of transport-triggered architecture processors using dynamic dataflow programs. Signal Processing: Image Communication, 28(10), 1295–1302.

    Google Scholar 

  12. Jorre, D.S., Jack, D., Alberti, C., Mattavelli, M., & Brunet, S.C. (2013). Porting an MPEG-HEVC decoder to a low-power Many-core platform. In Proceedings of the Forty Seventh Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

  13. CAL ARM compiler. “http://sourceforge.net/projects/opendf/” [Online] Accessed: 3 August 2013.

  14. Janneck, J.W. (2011). A machine model for dataflow actors and its applications. In Proceedings of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

  15. Haid, W., Huang, K., Bacivarov, I., & Thiele, L. (2009). Multiprocessor SoC software design flows. IEEE Signal Processing Magazine, 26(6), 64–71.

    Article  Google Scholar 

  16. Kahn, G. (1974). The semantics of a simple language for parallel programming. In Proceedings of IFIP Congress 74.

  17. Bilsen, G., Engels, M., Lauwereins, R., & Peperstraete, J. (1996). Cycle-static dataflow. IEEE Transactions on Signal Processing, 44(2), 397–408.

    Article  Google Scholar 

  18. Lee, E.A., & Parks, T.M. (1995). Dataflow process networks. In Proceedings of the IEEE, (Vol. 83 pp. 773–801).

  19. Ericsson, P., & Ahlander, A. (2010). Requirements for Radar Signal Processing. SMECY Deliverable T4.1, Technical Report.

  20. Gebrewahid, E., Yang, M., Cedersjö, G., Ul-Abdin, Z., Janneck, J.W., Gaspes, V., & Svensson, B. (2014). Realizing efficient execution of dataflow actors on Manycores. In Proceedings of the IEEE International Conference on Embedded and Ubiquitous Computing.

  21. Yang, M., Savas, S., Ul-Abdin, Z., & Nordström, T. (2013). A communication library for mapping dataflow applications on Manycore architectures: Sixth Swedish Workshop on Mutlicore Computing (MCC).

  22. Cedersjö, G., & Janneck, J.W. (2012). Toward efficient execution of dataflow actors. In Proceedings of the Forty Six Asilomar Conference on Signals, Systems and Computers (ASILOMAR).

  23. Ul-Abdin, Z., hlander, A., & Svensson, B. (2013). Energy efficient synthetic-aperture radar processing on a Manycore architecture. In Proceedings of 42nd International Conference on Parallel Processing (ICPP).

Download references

Acknowledgments

The authors would like to thank Adapteva Inc. for giving access to their software development suite and hardware board. This research is part of the CERES research program funded by the Knowledge Foundation, STAMP project funded by the strategic research area ELLIIT, and HiPEC project funded by Swedish Foundation for Strategic Research (SSF).

Author information

Authors and Affiliations

  1. Centre for Research on Embedded Systems (CERES), Halmstad University, Halmstad, Sweden

    Zain Ul-Abdin

  2. Uppsala University, Uppsala, Sweden

    Mingkun Yang

Authors
  1. Zain Ul-Abdin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mingkun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zain Ul-Abdin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ul-Abdin, Z., Yang, M. A Radar Signal Processing Case Study for Dataflow Programming of Manycores. J Sign Process Syst 87, 49–62 (2017). https://doi.org/10.1007/s11265-015-1078-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11265-015-1078-1

Keywords

Search

Navigation