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Power/Performance Exploration of Single-core and Multi-core Processor Approaches for Biomedical Signal Processing

  • Ahmed Yasir Dogan
  • David Atienza
  • Andreas Burg
  • Igor Loi
  • Luca Benini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6951)

Abstract

This study presents a single-core and a multi-core processor architecture for health monitoring systems where slow biosignal events and highly parallel computations exist. The single-core architecture is composed of a processing core (PC), an instruction memory (IM) and a data memory (DM), while the multi-core architecture consists of PCs, individual IMs for each core, a shared DM and an interconnection crossbar between the cores and the DM. These architectures are compared with respect to power vs performance trade-offs for a multi-lead electrocardiogram signal conditioning application exploiting near threshold computing. The results show that the multi-core solution consumes 66% less power for high computation requirements (50.1 MOps/s), whereas 10.4% more power for low computation needs (681 kOps/s).

Keywords

WBSN ECG Parallel Processing Near Threshold Computing 

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References

  1. 1.
    Mamaghanian, H., et al.: Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes. IEEE Transactions on Biomedical Engineering 12, 120–129 (2011)Google Scholar
  2. 2.
    Hanson, M.A., et al.: Body Area Sensor Networks: Challenges and Opportunities. IEEE Computer 42, 58–65 (2009)CrossRefGoogle Scholar
  3. 3.
    Rincon, F., et al.: Multi-Lead Wavelet-Based ECG Delineation on a Wearable Embedded Sensor Platform. Computers in Cardiology, 289–292 (2010)Google Scholar
  4. 4.
    Hanson, S., et al.: Exploring variability and performance in a sub-200 mV processor. IEEE J. Solid-State Circuits 43, 881–891 (2008)CrossRefGoogle Scholar
  5. 5.
    Zhai, B., et al.: A 2.60 pJ/Inst subthreshold sensor processor for optimal energy efficiency. In: Symposium on VLSI Circuits. Digest of Technical Papers, Honolulu (2006)Google Scholar
  6. 6.
    Wang, A., Chandrakasan, A.: A 180 mV FFT processor using sub- threshold circuit techniques. In: IEEE Int. Solid-State Circuits Conference. Dig. Tech. Papers (2004)Google Scholar
  7. 7.
    Dreslinski, R.G., et al.: Near-Threshold Computing: Reclaiming Moore’s Law Through Energy Efficient Integrated Circuits. Proceedings of the IEEE 98, 253–266 (2010)CrossRefGoogle Scholar
  8. 8.
    Chen, G., et al.: Millimeter-scale nearly perpetual sensor system with stacked battery and solar cells. In: Solid-State Circuits Conference. Digest of Technical Papers, San Francisco (2010)Google Scholar
  9. 9.
    Hanson, S., et al.: A Low-Voltage Processor for Sensing Applications With Picowatt Standby Mode. IEEE J. Solid-State Circuits 44, 1145–1155 (2009)CrossRefGoogle Scholar
  10. 10.
    Dreslinkski, R.G., et al.: An Energy Efficient Parallel Architecture Using Near Threshold Operation. In: 16th International Conference on Parallel Architecture and Compilation Techniques, Brasov, pp. 175–188 (2007)Google Scholar
  11. 11.
    Yu, P., et al.: An Ultra-Low-Energy Multi-Standard JPEG Co-Processor in 65 nm CMOS With Sub/Near Threshold Supply Voltage. IEEE J. Solid-State Circuits 45, 668–680 (2010)CrossRefGoogle Scholar
  12. 12.
    Krimer, E., et al.: Synctium: a Near-Threshold Stream Processor for Energy-Constrained Parallel Applications. Computer Architecture Letters 9, 21–24 (2010)CrossRefGoogle Scholar
  13. 13.
    Sun, Y., et al.: ECG signal conditioning by morphological filtering. Computers in Biology and Medicine 32(6), 465–479 (2002)CrossRefGoogle Scholar
  14. 14.
    Rahimi, A., et al.: A fully-synthesizable single-cycle interconnection network for Shared-L1 processor clusters. In: Design, Automation Test in Europe Conference Exhibition (DATE), pp. 1–6 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ahmed Yasir Dogan
    • 1
  • David Atienza
    • 1
  • Andreas Burg
    • 2
  • Igor Loi
    • 3
  • Luca Benini
    • 3
  1. 1.Embedded Systems Lab. (ESL) - EPFLLausanneSwitzerland
  2. 2.Telecommunications Circuits Lab. (TCL) - EPFLLausanneSwitzerland
  3. 3.UNIBO-Micrel LabBolognaItaly

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