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ULP-SRP: Ultra Low-Power Samsung Reconfigurable Processor for Biomedical Applications

Published:03 September 2014Publication History
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Abstract

The latest biomedical applications require low energy consumption, high performance, and wide energy-performance scalability to adapt to various working environments. In this study, we present ULP-SRP, an energy-efficient reconfigurable processor for biomedical applications. ULP-SRP uses a Coarse-Grained Reconfigurable Array (CGRA) for high-performance data processing with low energy consumption. We adopted a compact-size CGRA and modified it to support dynamically switchable three performance modes with fine-grained power gating in order to further optimize the energy consumption. The energy-performance scalability is also accomplished with multiple performance modes and a Unified Memory Architecture (UMA). Experimental results show that ULP-SRP achieved 59% energy reduction compared to previous works. A technique of dynamic CGRA mode changing gives 18.9% energy reduction. ULP-SRP is a good candidate for future mobile healthcare devices.

References

  1. Maryam Ashouei, Jos Hulzink, Mario Konijnenburg, Jun Zhoa, Filipa Duarte, et al. 2011. A voltage-scalable biomedical signal processor running ECG at 13pj/cycle 1MHZ 0.4v. In Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC'11).Google ScholarGoogle ScholarCross RefCross Ref
  2. Gregory Chen, Mathew Fojtik, Daeyeon Kim, David Fick, Junsun Park, et al. 2010. Millimeter-scale nearly perpetual sensor system with stacked battery and solar cells. In Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC'10).Google ScholarGoogle ScholarCross RefCross Ref
  3. Filipa Duarte, Jos Hulzink, Jun Zhao, Jan Stuijt, Jos Huisken, and Harmke De Groot. 2011. A 36uW heartbeat-detection processor for a wireless sensor node. ACM Trans. Des. Autom. Electron. Syst. 16, 4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Shu-Yu Hsu, Yao-Lin Chen, Po-Yoa Chang, Jui-Yuan Yu, Ten-Fang Yang, Ray-Jade Chen, and Chen-Yi Lee. 2011. A micropower biomedical signal processor for mobile healthcare applications. In Proceedings of the IEEE Asian Solid-State Circuits Conference.Google ScholarGoogle ScholarCross RefCross Ref
  5. Wonsub Kim, Donghoon Yoo, Haewoo Park, and Minwook Ahn. 2012. SCC based modulo scheduling for coarse-grained reconfigurable processors. In Proceedings of the International Conference on Field-Programmable Technology (ICFPT'12).Google ScholarGoogle ScholarCross RefCross Ref
  6. Sangjo Lee, Joonho Song, Minsoo Kim, Dohyung Kim, and Shihwa Lee. 2011. H.264/avc UHD decoder implementation on multi-cluster platform using hybrid parallelization method. In Proceedings of the 18th IEEE International Conference on Image Processing.Google ScholarGoogle ScholarCross RefCross Ref
  7. Bingfeng Mei, Serge Vernalde, Diederik Verkest, Hugo De Man, and Rudy Lauwereins. 2003. ADRES: An architecture with tightly coupled VLIW processor and coarse-grained reconfigurable matrix. In Proceedings of the International Conference on Field Programmable Logic and Applications (FPL'03).Google ScholarGoogle ScholarCross RefCross Ref
  8. Taewook Oh, Bernhard Egger, Hyunchul Park, and Scott Mahlke. 2009. Recurrence cycle aware modulo scheduling for coarse-grained reconfigurable architectures. In Proceedings of the International Conference on Languages, Compilers, Tools and Theory for Embedded Systems (LCTES'09). Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. B. Ramakrishna Rau. 1994. Iterative modulo scheduling: An algorithm for software pipelining loops. In Proceedings of the 27th International Symposium on Microarchitecture (MICRO'94). Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Inaki Romero, Bernard Grundlehner, Julien Penders, Jos Huisken, and Yahya H. Yassin. 2009. Low-power robust beat detection in ambulatory cardiac monitoring. In Proceedings of the IEEE Biomedical Circuits and Systems Conference.Google ScholarGoogle Scholar
  11. Srinivasa R. Sridhara, Michael Direnzo, Srinivas Lingam, Seok-Jun Lee, Raul Ruiz Blazquez, et al. 2011. Microwatt embedded processor platform for medical system-on-chip applications. IEEE J. Solid-State Circ. 46, 4.Google ScholarGoogle ScholarCross RefCross Ref
  12. Refet Firat Yazicioglu, Patrick Merken, Robert Puers, and Chris Van Hoof. 2008. A 200μ W eight-channel acquisition ASIC for ambulatory EEG systems. In Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC'08).Google ScholarGoogle Scholar
  13. Refet Firat Yazicioglu, Sunyoung Kim, Tom Torfs, Patrick Merken, and Chris Van Hoof. 2010. A 30μ W analog signal processor ASIC for biomedical signal monitoring. In Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC'10).Google ScholarGoogle Scholar
  14. Lennart Yseboodt, Michael De Nil, Jos Huisken, Mladen Berekovic, Quin Zhao, et al. 2007. Design of 100uW wireless sensor nodes for biomedical monitoring. J. Signal Process. Syst. 57, 1, 107--119. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Xiaodan Zou, Xiaoyuan Xu, Libin Yao and Yong Lian. 2009. A 1-v 450-nw fully integrated programmable biomedical sensor interface chip. IEEE J. Solid-State Circ. 44, 4.Google ScholarGoogle ScholarCross RefCross Ref

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      cover image ACM Transactions on Reconfigurable Technology and Systems
      ACM Transactions on Reconfigurable Technology and Systems  Volume 7, Issue 3
      Special Issue on 11th International Conference on Field-Programmable Technology (FPT'12) and Special Issue on the 7th International Workshop on Reconfigurable Communication-Centric Systems-on-Chip (ReCoSoC'12)
      August 2014
      199 pages
      ISSN:1936-7406
      EISSN:1936-7414
      DOI:10.1145/2664590
      Issue’s Table of Contents

      Copyright © 2014 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 3 September 2014
      • Accepted: 1 March 2014
      • Revised: 1 December 2013
      • Received: 1 July 2013
      Published in trets Volume 7, Issue 3

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