Energy efficient mobile computing techniques in smartphones

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Energy efficient mobile computing techniques in smartphones

  1. 1. Energy efficient mobile computing techniques in Smartphones Ninad Hogade Electrical and Computer Engineering Colorado State University Fort Collins, USA Email: ninadho@rams.colostate.edu
  2. 2. Overview • • • • • • • • • • • Introduction Multicore Processor Memory Energy efficiency vs. computational efficiency Parallel programming Multithreaded applications Green design patterns Schedulers Application processors Conclusion References
  3. 3. Introduction • • • • • • • Continuously evolving mobile technology Multifunctional Energy source – an important role Consumer demands Limitations of current batteries Power consumption & energy efficiency Need of sophisticated methodologies
  4. 4. Multicore Processor • Multicore architectures & manufactures • Conventional trends used to increase performance • Architectural classifications – homogeneous MPSoC – heterogeneous MPSoC
  5. 5. Memory • Use in multimedia applications • Multiple power states • Memory management methods – Phase change memory (PCM) – Mobile RAM (MRAM) • Energy management techniques – Power aware virtual memory (PAVM) • Hybrid energy management mechanism
  6. 6. Energy efficiency vs. computational efficiency • • • • • • • Energy efficiency Computational efficiency CPU instructions to complete task Algorithms and their complexity Choosing the best algorithm Stepping up in the abstract level Fast and energy efficient application
  7. 7. Parallel Programming • • • • • Parallel computing Advantages Need of parallel programming Applications of parallel programming Examples
  8. 8. Multithreaded applications • Use of Multithreaded applications • CPU energy measurements for different number of threads • Limitations in multithreading • Dynamic Voltage and Frequency Scaling (DVFS)
  9. 9. Green design patterns • Higher levels of abstraction • Example of developing energy efficient application • Design Patterns • Types of design patterns • Creation of green software
  10. 10. Schedulers • • • • Need of schedulers Scheduling Algorithm Applications of schedulers Scheduling techniques in multiprocessor architectures • Advantages of using them in heterogeneous architectures
  11. 11. Application processors • Application Processors in latest smartphones • Application processor integration • Operational modes of smartphones – Connected mode – Idle mode • Difficulties in incorporating power-saving techniques • Reduced power consumption achieved by application processors
  12. 12. Conclusion
  13. 13. References • • • • • • • • • • • • • • • • • • Findlay Shearer. Power management in mobile devices, chapter Hierarchical View of Energy Conservation, pages 32-75. Newnes, 2008 ARM. Arm introduces industry’s fastest processor for low-power mobile and consumer applications. http://www.arm.com/about/newsroom/ 10548.php. (2005). BinHex 3.0. La 4ta. generación de procesadores Intel Core definirá el futuro del cómputo móvil en 2013. http://binhex3.com/?p=2913. (2012). Fuller, Samuel H; Millett, Lynette, Computing performance, game over or next level? The National Academies Press, Washington, D.C. 31-38 p.p. (2011). Carro, Luigi; Rutzig, Mateus Beck, Multi-core Systems on Chip, Handbook of Signal Processing Systems, 485-514 p.p. (2010). “Windows phone 7,” http://en.wikipedia.org/wiki/Windows Phone 7. Ran Duan, Mingsong Bi, Chris Gniady, “Exploring memory energy optimizations in smartphones,” IEEE, 2011. Agarwal, S., Nath, A. and Chaudhury, D. 2012. Sustainable Approaches and Good Practices in Green Software Engineering. International Journal of Research and Reviews in computer Science, 3(1):1425-1428. (24) Carro, Luigi; Rutzig, Mateus Beck, Multi-core Systems on Chip, Handbook of Signal Processing Systems, 485-514 p.p. (2010). Steigerwald, B. and Agrawal, A. 2011. Developing Green Software. Intel White Paper. Intel Corporation, Folsom, CA, USA. Yao, F., Demers, A. and Shenker, S. 1995. A scheduling model for reduced cpu energy. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science, FOCS’95, pages 374–379. Litke, A. Zotos, K., Chatzigeorgiou, A. and Stephanides, G. 2005. Energy consumption analysis of design patterns, in Proceedings of the International Conference on Machine Learning and Software Engineering, pp. 86–90. Sahin, C., Cayci, F., Gutierrez, I., Clause, J., Kiamilev, F., Pollock, L. and Winbladhy, K. 2012. Initial Explorations on Design Pattern Energy Usage. In Proceedings of the First ICSE International Workshop on Green and Sustainable Software, Zurich, Switzerland. Clauirton Siebra, Paulo Costa, Regina Miranda, Fabio Q B Silva, Andre Santos “The Software Perspective for Energy-Efficient Mobile Applications Development”. ACM, December, 2012, Bali, Indonesia. Tannenbaum, Andrew S., Woodhull, Albert S., Sistemas operativos: Diseño e Implementación, 2nd. Edition, Prentice Hall, 939 p.p. (1997). Wu, Fan; Agu, Emmanuel; Lindsay, Clifford; Adaptive CPU Scheduling to Conserve Energy in Real-Time mobile Graphics Applications, Advances in Visual Computing. Lectures Notes in Computer Science, Springer, 624-633 p.p. (2008). Sarathy, A., Kodi, A.K., and Louri, A.: ‘Low-power low-area network- on-chip architecture using adaptive electronic link buffers’, Electron. Lett., 2008, 44, (8), pp. 512–513 Soo-Yong Kim, Keunhwi Koo and Sang Woo Kim “Time-based power control architecture for application processors in smartphones”. Electronic Letters, 6th December 2012, Vol. 48 No. 25
  14. 14. Thank you

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