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Improved DES on Heterogeneous Multi-core Architecture

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Data Science (ICPCSEE 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 901))

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Abstract

DES (Data Encryption Standard) is one of the most classical algorithms of cryptography and its higher security makes it hard to be broke for a very long time. However, along with the constant development of computer technology, especially in the 21st century, DES cannot be applied widely because of its low efficiency. Recently, the novel heterogeneous multi-core architecture represented by APU (Accelerated Processing Unit), provides a new solution for the above problems. APU integrates CPU and GPU in a groundbreaking manner and makes the algorithm to make full use of the performance advantage of heterogeneous multi-core system by realizing the HSA (Heterogeneous System Architecture) standard. This paper realizes DES on the fresh APU processor. By analyzing the performance, two kinds of improved schemes are proposed. The experimental results show that the running efficiency of algorithm can be greatly improved by using APU with reasonable optimization. In the same way, the other DES-like algorithm would also be optimized on these heterogeneous multi-core architecture.

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Acknowledgement

This work was supported by the Foundation of Beijing key laboratory on Trusted Computing (Project No. BZ005), the significant special project for Core electronic devices, high-end general chips and basic software products (2012ZX01039-004), and also supported by Beijing Key Laboratory on Integration and Analysis of Large Scale Stream Data.

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Correspondence to Chong Chen or Wenbo Zhang .

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Bao, Z., Chen, C., Zhang, W. (2018). Improved DES on Heterogeneous Multi-core Architecture. In: Zhou, Q., Gan, Y., Jing, W., Song, X., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 901. Springer, Singapore. https://doi.org/10.1007/978-981-13-2203-7_34

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  • DOI: https://doi.org/10.1007/978-981-13-2203-7_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2202-0

  • Online ISBN: 978-981-13-2203-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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