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Energy-Aware Design Space Exploration for GPGPUs

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Computer Science - Research and Development

Abstract

This work presents a novel approach for automatically determining the most power- or energy-efficient Graphics Processing Units (GPUs) with respect to given parallel computation problems.

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References

  1. Ahmad I, Ranka S (2012) Handbook of energy-aware and green computing, 1st edn. Chapman & Hall/CRC, London. Two volume set

    Google Scholar 

  2. Bakhoda A, Yuan G, Fung W, Wong H, Aamodt T (2009) Analyzing cuda workloads using a detailed gpu simulator. In: IEEE international symposium on performance analysis of systems and software, ISPASS 2009, pp 163–174

    Chapter  Google Scholar 

  3. Cebrian J, Guerrero G, Garcia J (2012) Energy efficiency analysis of gpus. In: IEEE 26th international parallel and distributed processing symposium workshops PhD forum (IPDPSW), 2012, pp 1014–1022. doi:10.1109/IPDPSW.2012.124

    Chapter  Google Scholar 

  4. Che S, Boyer M, Meng J, Tarjan D, Sheaffer J, Lee SH, Skadron K (2009) Rodinia: a benchmark suite for heterogeneous computing. In: IEEE international symposium on workload characterization, IISWC 2009, pp 44–54

    Google Scholar 

  5. Khronos Group: OpenCL Specification (2013). URL: http://www.khronos.org/registry/cl/

  6. Leng J, Hetherington T, ElTantawy A, Gilani S, Kim NS, Aamodt TM, Reddi VJ (2013) Gpuwattch: enabling energy optimizations in gpgpus. In: International symposium on computer architecture

    Google Scholar 

  7. Li S, Ahn JH, Strong R, Brockman J, Tullsen D, Jouppi N (2009) Mcpat: an integrated power, area, and timing modeling framework for multicore and manycore architectures. In: 42nd annual IEEE/ACM international symposium on microarchitecture, 2009. MICRO-42, pp 469–480

    Chapter  Google Scholar 

  8. Libuschewski P, Siedhoff D, Timm C, Gelenberg A, Weichert F (2013) Fuzzy-enhanced, real-time capable detection of biological viruses using a portable biosensor. In: Proceedings of the international joint conference on biomedical engineering systems and technologies (BIOSIGNALS). Publication

    Google Scholar 

  9. Luke S (2013) The ECJ Owner’s manual

  10. McIntosh-Smith S, Wilson T, Ibarra AA, Crisp J, Sessions RB (2012) Benchmarking energy efficiency, power costs and carbon emissions on heterogeneous systems. Comput J 55:192–205

    Article  Google Scholar 

  11. Moore G (1998) Cramming more components onto integrated circuits. Proc IEEE 86(1):82–85. doi:10.1109/JPROC.1998.658762

    Article  Google Scholar 

  12. NVIDIA Corporation: CUDA Architecture (2013). URL: http://www.nvidia.com/object/cuda_home_new.html

  13. Ramani K, Ibrahim A, Shimizu D, Powerred: a flexible modeling framework for power efficiency exploration in gpus

  14. Rofouei M, Stathopoulos T, Ryffel S, Kaiser W, Sarrafzadeh M (2008) Energy-aware high performance computing with graphic processing units. In: HotPower’08: proc of ACM SOSP workshop on power aware computing and systems (HotPower) 2008

    Google Scholar 

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Acknowledgements

Part of the work on this paper has been supported by Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876 “Providing Information by Resource-Constrained Analysis”, project B2. URL: http://sfb876.tu-dortmund.de

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Correspondence to Pascal Libuschewski.

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Libuschewski, P., Siedhoff, D. & Weichert, F. Energy-Aware Design Space Exploration for GPGPUs. Comput Sci Res Dev 29, 171–176 (2014). https://doi.org/10.1007/s00450-013-0237-5

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  • DOI: https://doi.org/10.1007/s00450-013-0237-5

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