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Design and Implementation of Parallelized Cholesky Factorization

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High Performance Computing and Applications

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5938))

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Abstract

The bottleneck of most data analyzing systems, signal processing systems, and intensive computing systems is matrix decomposition. The Cholesky factorization of a sparse matrix is an important operation in numerical algorithms field. This paper presents a Multi-phased Parallel Cholesky Factorization (MPCF) algorithm, and then gives the implementation on a multi-core machine. A performance result shows that the system can reach 85.7 Gflop/s on a single PowerXCell processor and bulk of computation can reach to 94% of peak performance.

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References

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Author information

Authors and Affiliations

  1. School of Electronic Engineering and Computer Science, Peking University, Beijing, 100871, China

    Bailing Wang

  2. Research Center of Computer Network and Information Security Technology, Harbin Institute of Technology, Harbin, 150001, China

    Bailing Wang

  3. IBM China System and Technology Lab, Beijing, 100000, China

    Ning Ge, Hongbo Peng, Qiong Wei, Guanglei Li & Zhigang Gong

Authors
  1. Bailing Wang
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  2. Ning Ge
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  3. Hongbo Peng
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  4. Qiong Wei
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  5. Guanglei Li
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  6. Zhigang Gong
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Editor information

Editors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, 200072, Shanghai, P.R. China

    Wu Zhang  & Weiqin Tong  & 

  2. Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada

    Zhangxin Chen

  3. Department of Mathematics, University of Wyoming, 1000 University Avenue, 82071-3036, Laramie, WY, USA

    Craig C. Douglas

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© 2010 Springer-Verlag Berlin Heidelberg

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Wang, B., Ge, N., Peng, H., Wei, Q., Li, G., Gong, Z. (2010). Design and Implementation of Parallelized Cholesky Factorization. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_54

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11841-8

  • Online ISBN: 978-3-642-11842-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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