Skip to main content

Efficiency of Parallel Computing Based on .Net 4.5

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 212))

Abstract

In recent decades, with the continuous development of the CPU, the speed of single-core processors is increasingly close to the limit. Therefore, multi-core processors, through the internal integration of multi cores, solve the bottleneck in the development of the CPU. Over the past decade, the pace of development of multi-core technology is very fast, but the development of the software has not kept up with the pace of hardware. Most software and program failed to fully utilize the performance of multi-core processors. This paper introduces the parallel programming knowledge of Microsoft .Net 4.5 through the design of an experiment seeking the largest prime number demonstrates parallel the implementation process. Meanwhile, through the comparison of the time consumption between the parallel computation and traditional method, the author draw a conclusion that the computation efficiency is greatly improved by parallel computation then the traditional method in case of large amount of data.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Parallel Computing Concepts via C# 4.0 logicchild. http://www.codeproject.com/Articles/71369/Parallel-Computing-Concepts-via-C-4-0. 4 Nov 2010

  2. Patterns of Parallel Programming, by Microsoft’s Stephen Toub

    Google Scholar 

  3. Chen G (1999) Parallel computing: architecture algorithm programming. Beijing Advanced Education Press

    Google Scholar 

  4. Isard M et al (2007) Dryad: distributed data-parallel programs from sequential building blocks. pp 59–72

    Google Scholar 

  5. Chen G (1988) A partitioning selection algorithm on multiprocessors. J Comput Sci Technol 3:241–250

    Article  MathSciNet  Google Scholar 

  6. Chen G et al (2008) Proceedings of the inaugural symposium on parallel algorithms, architectures and programming, 16–18 September 2008

    Google Scholar 

  7. Chen Y, Lin P, Bao Y, He Y (2009) Application of the distributed and parallel computation in spectroscopy signal processing. Spectrosc Spectral Anal 29(4)

    Google Scholar 

  8. Yu R, Wu L, Qu S (2011) Parallel computing and visualization method of radar net’s detection ability. Syst Eng Electron 33(11)

    Google Scholar 

  9. Li N, Chen Z, Gong G, Peng X (2010) Application of multi-core parallel computing technology in scene matching simulation. Syst Eng Electron 32(2)

    Google Scholar 

  10. Fan X, Wu R (2009) Parallel computing of clamp structure in tahoe frame. Chin J Comput Phys 26(5)

    Google Scholar 

  11. Wang Z, Hu H (2011) Parallel computation techniques for dynamic description logics reasoning. J Comput Res Dev 48(12)

    Google Scholar 

Download references

Acknowledgments

This Article is supported by the Government Instructor Projects of Huainan City (2001B30).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Hao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hao, W., Gu, R., Sun, K., Ren, P. (2013). Efficiency of Parallel Computing Based on .Net 4.5. In: Yin, Z., Pan, L., Fang, X. (eds) Proceedings of The Eighth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA), 2013. Advances in Intelligent Systems and Computing, vol 212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37502-6_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37502-6_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37501-9

  • Online ISBN: 978-3-642-37502-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics