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Research on FPGA Based Evolvable Hardware Chips for Solving Super-High Dimensional Equations Group

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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

Solving a super-high dimensional equations group is widely used in science and engineering, but the slow solution speed is the biggest problem researchers face. Research on FPGA based evolvable hardware chips for solving the super-high dimensional equations group (SHDESC) is proposed in this paper. These chips can be implemented on a million-gate scale FPGA chip. The core architecture of SHDESC is a systolic array which consists of thousands of special arithmetic units and can execute many super-high dimensional matrix operations parallelly in short time as well as really achieve the purpose of high speed solution in hardware/software codesign. The experiments show that these chips can achieve high precision results in a short period of time to solve a super-high dimensional equations group.

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References

  1. Pan, Z., Kang, L., Chen, Y.: Evolutionary Computation. Tsinghua University Press, Beijing (1998)

    Google Scholar 

  2. de Garis, H.: Evolvable Hardware: Genetic Programming of a Darwin Machine. In: Artificial Neural Nets and Genetic Algorithms, pp. 441–449. Springer, Heidelberg (1993)

    Chapter  Google Scholar 

  3. Wu, Z.-j., Kang, L.-s., Zou, X.-f.: An Elite-subspace Evolutionary Algorithm for Solving Function Optimization Problems. Computer Applicafions 23(2), 13–15 (2003)

    Google Scholar 

  4. Tao, G., Kang, L., Li, Y.: A New Algorithm for Solving Inequality Constrained Function Optimization Problems. Wuhan University Journal of Natural Sciences 45(5B), 771–775 (1999)

    Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Li, K., Guo, Z., Chen, Z., Ge, B. (2010). Research on FPGA Based Evolvable Hardware Chips for Solving Super-High Dimensional Equations Group. 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_7

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_7

  • 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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