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Modeling power and energy of the task-parallel Cholesky factorization on multicore processors

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Computer Science - Research and Development

Abstract

In this paper we introduce a model for the total energy consumption of the Cholesky factorization on a multicore processor. Our model assumes a task-parallel execution of the factorization process, with concurrency leveraged via a run-time as those recently proposed in projects like SMPSs, PLASMA or libflame, and decomposes the power usage into its system, static and dynamic components. A few simple experiments provide experimental data (parameters) with enough accuracy to assemble the model, which can then be used to estimate the actual power dissipation and energy consumption of the global algorithm. Experimental results on an 8-core platform equipped with Intel Xeon processors reveal the precision of the model.

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References

  1. The green500 list (2010). Available at http://www.green500.org

  2. Aliaga JI, Bollhoefer M, Martín A, Quintana-Ortí ES (2011) Exploiting thread-level parallelism in the iterative solution of sparse linear systems. Parallel Comput 37(3):183–202. doi:10.1016/j.parco.2010.11.002

    Article  MATH  MathSciNet  Google Scholar 

  3. AnandTech Forums: Power-consumption scaling with clockspeed and Vcc for the i7-2600K (2011). http://forums.anandtech.com/showthread.php?t=2195927

  4. Badia RM, Herrero JR, Labarta J, Pérez JM, Quintana-Ortí ES, Quintana-Ortí G (2009) Parallelizing dense and banded linear algebra libraries using SMPSs. Concurr Comput, Pract Exp 21:2438–2456

    Article  Google Scholar 

  5. Badia RM, Herrero JR, Labarta J, Pérez JM, Quintana-Ortí ES, Quintana-Ortí G (2009) Parallelizing dense and banded linear algebra libraries using SMPSs. Concurr Comput, Pract Exp 21(18):2438–2456

    Article  Google Scholar 

  6. Borkar S, Chien AA (2011) The future of microprocessors. Commun ACM 54(5):67–77

    Article  Google Scholar 

  7. Buttari A, Langou J, Kurzak J, Dongarra J (2009) A class of parallel tiled linear algebra algorithms for multicore architectures. Parallel Comput 35(1):38–53

    Article  MathSciNet  Google Scholar 

  8. Cilk project home page. http://supertech.csail.mit.edu/cilk/

  9. Dongarra J et al. (2011) The international ExaScale software project roadmap. Int J High Perform Comput Appl 25(1):3–60. doi:10.1177/1094342010391989

    Article  Google Scholar 

  10. Duranton M et al (2010) The HiPEAC vision. Available from http://www.hipeac.net/roadmap

  11. Esmaeilzadeh H, Blem E, St Amant R, Sankaralingam K, Burger D (2011) Dark silicon and the end of multicore scaling. In: Proc 38th annual int symp computer architecture, ISCA’11, pp 365–376

    Google Scholar 

  12. Feng W, Feng X, Ce R (2008) Green supercomputing comes of age. IT Prof 10(1):17–23

    Article  Google Scholar 

  13. FLAME project home page. http://www.cs.utexas.edu/users/flame/

  14. Golub GH, Loan CFV (1996) Matrix computations, 3rd edn. Johns Hopkins University Press, Baltimore

    MATH  Google Scholar 

  15. Paraver: the flexible analysis tool. http://www.cepba.upc.es/paraver

  16. PLASMA project home page. http://icl.cs.utk.edu/plasma/

  17. Quintana-Ortí G, Quintana-Ortí ES, van de Geijn RA, Zee FGV, Chan E (2009) Programming matrix algorithms-by-blocks for thread-level parallelism. ACM Trans Math Softw 36(3):14:1–14:26

    Article  Google Scholar 

  18. SMP superscalar project home page. http://www.bsc.es/plantillaG.php?cat_id=385

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Acknowledgements

The authors were supported by the CICYT project TIN2011-23283 of the Ministerio de Economía y Competitividad and FEDER.

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Authors and Affiliations

  1. Depto. de Sistemas Informáticos y Computación, Univ. Politècnica de València, 46.022, Valencia, Spain

    Pedro Alonso

  2. Depto. de Ingeniería y Ciencia de Computadores, Univ. Jaume I, 12.071, Castellón, Spain

    Manuel F. Dolz, Rafael Mayo & Enrique S. Quintana-Ortí

Authors
  1. Pedro Alonso
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  2. Manuel F. Dolz
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  3. Rafael Mayo
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  4. Enrique S. Quintana-Ortí
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Correspondence to Pedro Alonso.

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Alonso, P., Dolz, M.F., Mayo, R. et al. Modeling power and energy of the task-parallel Cholesky factorization on multicore processors. Comput Sci Res Dev 29, 105–112 (2014). https://doi.org/10.1007/s00450-012-0227-z

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  • DOI: https://doi.org/10.1007/s00450-012-0227-z

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