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International Conference on Ubiquitous Computing Application and Wireless Sensor Network

International Conference on Ubiquitous Information Technologies and Applications

International Conference on Computer Science and its Applications

UCAWSN 2016, CUTE 2016, CSA 2016: Advances in Computer Science and Ubiquitous Computing pp 477–483Cite as

Linear Programming Computation Model Based on DPVM

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 421))

Abstract

Matrix manipulation of Linear Programming (LP) problems is a performance bottleneck in Single Instruction Single Data (SIMD) pattern. While, GPU is specialized for this compute-intensive and highly parallel computation, which is exactly what graphics rendering is about, due to the Single Instruction Multiple Data (SIMD) architecture. This paper introduces a Revised Simplex Method (RSM) on a GPU–Data Parallel Virtual Machine (DPVM). It assigns different routines for CPU and GPU according to respective characteristics: Iteration control and minimum value obtained are completed by CPU and Matrix multiplication by DPVM. In detail, we carefully organize the data as 4-channel textures, and efficiently implement the computation using Fetch4 technology of pixel shader. Numerical experiments are presented to verify the practical value and performance of this algorithm. The results are very promising. In particular, they reveal that our method not only can get correct optimal solution, but also is sixty-six faster than a traditional method on CPU, near 2.5 times faster than a lasted released MATLAB when LP problem size reaches 1200.

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Acknowledgements

The authors gratefully acknowledge the financial supports for this research from the National Natural Science Foundation of China (51409117, 61272208, 61572228), Jilin Province Department of Education “Thirteen Five” scientific and technological research projects [2016] No. 432, Fundamental Research Funds for the Central Universities Special (JCKY-QKJC47, JCKY-QKJC49).

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Authors and Affiliations

  1. Center for Computer Fundamental Education, Jilin University, Changchun, 130012, China

    Hongtao Bai

  2. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Lili He, Yu Jiang & Shanshan Jiang

  3. Information Engineering College, Yangzhou University, Yangzhou, 225009, China

    Jin Wang

Authors
  1. Hongtao Bai
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  2. Lili He
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  3. Yu Jiang
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  4. Jin Wang
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  5. Shanshan Jiang
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Corresponding author

Correspondence to Hongtao Bai .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. (Jong Hyuk) Park

  2. Department of Computer Science, Georgia State University, Atlanta, Georgia, USA

    Yi Pan

  3. Computer Science and Engineering, Gangneung-Wonju National University, Wonju, Korea (Republic of)

    Gangman Yi

  4. University Salerno, Fisciano, Italy

    Vincenzo Loia

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© 2017 Springer Nature Singapore Pte Ltd.

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Bai, H., He, L., Jiang, Y., Wang, J., Jiang, S. (2017). Linear Programming Computation Model Based on DPVM. In: Park, J., Pan, Y., Yi, G., Loia, V. (eds) Advances in Computer Science and Ubiquitous Computing. UCAWSN CUTE CSA 2016 2016 2016. Lecture Notes in Electrical Engineering, vol 421. Springer, Singapore. https://doi.org/10.1007/978-981-10-3023-9_74

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  • DOI: https://doi.org/10.1007/978-981-10-3023-9_74

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3022-2

  • Online ISBN: 978-981-10-3023-9

  • eBook Packages: EngineeringEngineering (R0)

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