Advertisement

Runtime Adaptability: The Key for Improving Parallel Applications

  • Arthur Francisco Lorenzon
  • Antonio Carlos Schneider Beck Filho
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

With the increasing complexity of parallel applications, which require more computing power, energy consumption has become an important issue. The power consumption of high-performance computing (HPC) systems is expected to significantly grow (up to 100 MW) in the next years (Dutot et al., Towards energy budget control in HPC. In: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 381–390. IEEE, Piscataway, 2017). Moreover, while general-purpose processors are being pulled back by the limits of the thermal design power (TDP), most of the embedded devices are mobile and heavily dependent on battery (e.g., smartphones and tablets). Therefore, the primary objective when designing and executing parallel applications is not to merely improve performance but to do so with minimal impact on energy consumption.

References

  1. 7.
    Beck, A.C.S., Lisbôa, C.A.L., Carro, L.: Adaptable Embedded Systems. Springer, Berlin (2012)Google Scholar
  2. 9.
    Benesty, J., Chen, J., Huang, Y., Cohen, I.: Pearson Correlation Coefficient, pp. 1–4. Springer, Berlin, (2009).  https://doi.org/10.1007/978-3-642-00296-0_5 Google Scholar
  3. 17.
    Butenhof, D.R.: Programming with POSIX Threads. Addison-Wesley Longman Publishing, Boston (1997)Google Scholar
  4. 21.
    Chandramowlishwaran, A., Knobe, K., Vuduc, R.: Performance evaluation of concurrent collections on high-performance multicore computing systems. In: 2010 IEEE International Symposium on Parallel Distributed Processing (IPDPS), pp. 1–12. IEEE, Piscataway (2010).  https://doi.org/10.1109/IPDPS.2010.5470404
  5. 22.
    Chapman, B., Jost, G., Pas, R.v.d.: Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation). MIT Press, Cambridge, MA (2007)Google Scholar
  6. 34.
    Dutot, P.F., Georgiou, Y., Glesser, D., Lefevre, L., Poquet, M., Rais, I.: Towards energy budget control in HPC. In: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 381–390. IEEE, Piscataway (2017)Google Scholar
  7. 38.
    Gropp, W., Lusk, E., Skjellum, A.: Using MPI (2Nd Ed.): Portable Parallel Programming with the Message-passing Interface. MIT Press, Cambridge (1999)CrossRefGoogle Scholar
  8. 41.
    Ham, T.J., Chelepalli, B.K., Xue, N., Lee, B.C.: Disintegrated control for energy-efficient and heterogeneous memory systems. In: IEEE HPCA, pp. 424–435. IEEE, Picataway (2013).  https://doi.org/10.1109/HPCA.2013.6522338
  9. 47.
    Hu, Z., Buyuktosunoglu, A., Srinivasan, V., Zyuban, V., Jacobson, H., Bose, P.: Microarchitectural techniques for power gating of execution units. In: Proceedings of the 2004 International Symposium on Low Power Electronics and Design, ISLPED ’04, pp. 32–37. ACM, New York (2004).  https://doi.org/10.1145/1013235.1013249
  10. 51.
    Joao, J.A., Suleman, M.A., Mutlu, O., Patt, Y.N.: Bottleneck identification and scheduling in multithreaded applications. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 223–234. ACM, New York (2012).  https://doi.org/10.1145/2150976.2151001
  11. 57.
    Karlin, I., Keasler, J., Neely, R.: Lulesh 2.0: updates and changes. pp. 1–9 (2013)Google Scholar
  12. 62.
    Le Sueur, E., Heiser, G.: Dynamic voltage and frequency scaling: the laws of diminishing returns. In: Proceedings of the 2010 International Conference on Power Aware Computing and Systems, HotPower’10, pp. 1–8. USENIX Association, Berkeley (2010)Google Scholar
  13. 63.
    Lee, J., Wu, H., Ravichandran, M., Clark, N.: Thread tailor: dynamically weaving threads together for efficient, adaptive parallel applications. ACM SIGARCH Comput. Archit. News 38(3), 270–279 (2010)CrossRefGoogle Scholar
  14. 64.
    Levy, H.M., Lo, J.L., Emer, J.S., Stamm, R.L., Eggers, S.J., Tullsen, D.M.: Exploiting choice: Instruction fetch and issue on an implementable simultaneous multithreading processor. In: International Symposium on Computer Architecture, pp. 191–191 (1996).  https://doi.org/10.1145/232973.232993
  15. 84.
    Oboril, F., Tahoori, M.B.: Extratime: Modeling and analysis of wearout due to transistor aging at microarchitecture-level. In: IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2012), pp. 1–12 (2012).  https://doi.org/10.1109/DSN.2012.6263957
  16. 85.
    Olukotun, K., Hammond, L.: The future of microprocessors. Queue 3(7), 26–29 (2005).  https://doi.org/10.1145/1095408.1095418 CrossRefGoogle Scholar
  17. 94.
    Quinn, M.: Parallel Programming in C with MPI and OpenMP. McGraw-Hill Higher Education (2004)Google Scholar
  18. 95.
    Raasch, S.E., Reinhardt, S.K.: The impact of resource partitioning on SMT processors. In: International Conference on Parallel Architectures and Compilation Techniques, pp. 15–25 (2003).  https://doi.org/10.1109/PACT.2003.1237998
  19. 114.
    Subramanian, L., Seshadri, V., Kim, Y., Jaiyen, B., Mutlu, O.: Mise: Providing performance predictability and improving fairness in shared main memory systems. In: IEEE International Symposium on High Performance Computer Architecture, pp. 639–650 (2013)Google Scholar
  20. 115.
    Suleman, M.A., Qureshi, M.K., Patt, Y.N.: Feedback-driven threading: power-efficient and high-performance execution of multi-threaded workloads on CMPS. SIGARCH Comput. Archit. News 36(1), 277–286 (2008).  https://doi.org/10.1145/1353534.1346317 CrossRefGoogle Scholar
  21. 121.
    Vogelsang, T.: Understanding the energy consumption of dynamic random access memories. In: Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO ’43, pp. 363–374. IEEE Computer Society, Washington (2010).  https://doi.org/10.1109/MICRO.2010.42
  22. 122.
    Wall, D.W.: Limits of instruction-level parallelism. In: Proceedings of the Fourth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS IV, pp. 176–188. ACM, New York (1991). s https://doi.org/10.1145/106972.106991

Copyright information

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Arthur Francisco Lorenzon
    • 1
  • Antonio Carlos Schneider Beck Filho
    • 2
  1. 1.Department of Computer ScienceFederal University of Pampa (UNIPAMPA)AlegreteBrazil
  2. 2.Institute of Informatics, Campus do ValeFederal University of Rio Grande do Sul (UFRGS)Porto AlegreBrazil

Personalised recommendations