System-Scenario-based Design Techniques in the Presence of Data Variables
This chapter describes necessary adaptation needed for the system scenario approach to work in the presence of data variables. After a brief introduction to the difference between control and data variable dependencies, we present techniques for scenario identification, scenario detection, and scenario switching. Finally, we show results from a real-life video encoder, demonstrating up to a factor of two energy reduction while maintaining the perceptual video quality and frame rate.
KeywordsSystem scenario Data variables Identification Detection Switching Polyhedral Clustering Monitoring Precomputation Gain evaluation Application demonstrator Dynamic voltage Frequency scaling
The research leading to these results has in part been performed within the context of the dual-PhD agreement between KU Leuven and NTNU. Furthermore, the authors would like to thank Associate Professor Sverre Hendseth at NTNU for his many contributions to the research.
- 1.M. Ashouei et al., A voltage-scalable biomedical signal processor running ECG using 13 pj/cycle at 1 mhz and 0.4 v, in Proceedings IEEE International Solid-State Circuits Conference (ISSCC) (2011), pp. 332–334Google Scholar
- 3.Atmel, SAM4L Xplained Pro user guide (2014)Google Scholar
- 4.M. Baka, F. Catthoor, D. Soudris, Proposed evaluation framework for exploration of smart PV module topologies, in European Photovoltaic Solar Energy Conference (PVSEC), Munich, Germany (2016), pp. 176–179Google Scholar
- 7.E. Hammari, F. Catthoor, P.G. Kjeldsberg, J. Huisken, K. Tsakalis and L. Iasemidis, Identifying data-dependent system scenarios in a dynamic embedded system, in The International Conference on Engineering of Reconfigurable Systems and Algorithms (ERSA’12), Las Vegas, USA (2012)Google Scholar
- 8.E. Hammari, P.G. Kjeldsberg, F. Catthoor, Run-time precomputation of data-dependent parameters in embedded systems. ACM Trans. Embed. Comput. Syst. 17(3), Article No. 68 (2018)Google Scholar
- 10.L. Iasemidis et al., Long-term prospective on-line real-time seizure prediction. Clin. Neuropathol. 116, 532–544 (2005)Google Scholar
- 11.M. Kallay, The complexity of incremental convex hull algorithms in R^d. Inf. Process. Lett. 19(4), 197 (1984)Google Scholar
- 12.C. Lee et al., MediaBench: a tool for evaluating and synthesizing multimedia and communications systems, in Proceedings of the Thirtieth Annual IEEE/ACM International Symposium on Microarchitecture (1997), pp. 330–335Google Scholar
- 14.National Instruments, NI myDAQ measurement board, http://www.ni.com/mydaq on December 7, 2015
- 15.S. Sun, D. Wang, S. Chen, A highly efficient parallel algorithm for H.264 encoder based on macro-block region partition, in High Performance Computing and Communications. Lecture Notes in Computer Science, vol. 4782 (2007)Google Scholar
- 16.Y. Yassin, P.G. Kjeldsberg, A. Perkis, F. Catthoor, Dynamic hardware management of the H264/AVC encoder control structure using a framework for system scenarios, in Euromicro Conference on Digital System Design, DSD 2016, Limassol, Cyprus (August, September 2016)Google Scholar
- 18.Z. Zhao, P. Liang, A highly efficient parallel algorithm for H.264 video encoder, in 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, Toulouse, France (May 2006)Google Scholar