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Efficient Sign-Detection-Scheme Using Modular Computation Technique for the Moduli Set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5}

Received: 25 April 2023    Accepted: 19 May 2023    Published: 31 May 2023
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Abstract

In computer arithmetic, one of the most important things to consider in hardware design is the ability of the system to detect and display numbers with their signs. This when properly managed will reduce errors and ensure hardware reliability. But interestingly, detecting and knowing the sign of a residue number during arithmetic operation is very difficult. Magnitude Comparison, Scaling and Number conversions are some of the other difficult operations in Residue Number System (RNS). Unlike the weighted number system, it is even extremely difficult to determine the sign of a number in an RNS architecture thereby hampering the full implementation RNS in general purpose computing. In this paper, an efficient sign detection algorithm for detecting the sign of a number in an RNS architecture is presented. In formulating the algorithms, X maximum, (Xmax) is computed from the Dynamic Range, M=∏ki=1(mi). Modular Computation Technique is employed as a converter to compute X from the residues (r1, r2, r3) with respect to a given moduli set, say S= {m1, m2 ..., mn}. X is positive if X-Xmax<0 otherwise X is negative and the actual value is this case is computed as X-M. The moduli set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5} is used for the system design implementation and for numerical illustrations. It is observed that the scheme effectively detects the sign of RNS numbers and theoretical analysis showed that simple hardware resources and low-power modular adders are used in the design. It is also observed that the scheme when implemented practically can help project RNS to be used in general purpose computing.

Published in Science Frontiers (Volume 4, Issue 1)
DOI 10.11648/j.sf.20230401.12
Page(s) 8-16
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

RNS - Residue Number System, CRT - Chinese Remainder Theorem, MRC – Mixed Radix Conversion, Sign Detection

References
[1] Akkal, M., & Siy, P. (2008). Optimum RNS sign detection algorithm using MRC-II with special moduli set. Journal of Systems Architecture, 54 (10), 937-944.
[2] Al-Radadi, E., & Siy, P. (2003). RNS sign detector based on Chinese remainder theorem II (CRT II). Computers & Mathematics with Applications, 46 (10-11), 1559-1570. doi: 10.1016/S0898-1221(03)90147-7.
[3] Antão, S., & Sousa, L. (2013). The CRNS framework and its application to programmable and reconfigurable cryptography. ACM Transactions on Architecture and Code Optimization, 9 (4), 1-25. doi: 10.1145/2535918.
[4] Hiasat, A. (2018). Sign detector for the extended four-moduli set {2n-1, 2n +1, 22n+1, 2n+k}. Computers & Digital Techniques, 32 (2), 69-73. https://doi.org/10.1049/iet-cdt.2017.0088.
[5] Hiasat, A. (2016). A Sign Detector for a Group of Three-Moduli Sets. IEEE Transactions on Computers, 65 (12), 3580–3590. https://doi.org/10.1109/TC.2016.2547381
[6] Parhami, B. (2010). Computer Arithmetic: Algorithms and Hardware Designs (2nd ed.). Oxford University Press.
[7] Soderstrand, M., Jenkins, W., Jullien, G., & Taylor, F. (Eds.). (1986). Residue Number System Arithmetic: Modern Applications in Digital Signal Processing. IEEE Press. Piscataway, NJ.
[8] Sousa, L. & Martins, P. (2015). Sign Detection and Number Comparison on RNS 3-Moduli Sets. Springer Science+Business Media New York.
[9] Szabo, N., & Tanaka, R. (Eds.). (1967). Residue arithmetic and its application to computer technology. McGraw-Hill. New York.
[10] Ulman, Z. (1983). Sign detection and implicit-explicit conversion of numbers in residue arithmetic. IEEE Transactions on Computers, 32 (6), 590-594. doi: 10.1109/TC.1983.1676245.
[11] Vu, T. V. (1985). Efficient implementations of the Chinese remainder theorem for sign detection and residue decoding. IEEE Transactions on Computers, 34 (7), 646-651. doi: 10.1109/TC.1985.1676577.
[12] Xu, M., Bian, Z., & Yao, R. (2015). Fast sign detection algorithm for the RNS moduli set {2n+2-1, 2n-1, 2n}. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 23 (2), 379-383.
[13] Younes, D., & Steffan, P. (2013). Universal approaches for overflow and sign detection in residue number system based on {2n-1, 2n, 2n+1}. The Eighth International Conference on Systems (ICONS 2013).
Cite This Article
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    Mohammed Ibrahim Daabo, Valentine Aveyom. (2023). Efficient Sign-Detection-Scheme Using Modular Computation Technique for the Moduli Set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5}. Science Frontiers, 4(1), 8-16. https://doi.org/10.11648/j.sf.20230401.12

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    ACS Style

    Mohammed Ibrahim Daabo; Valentine Aveyom. Efficient Sign-Detection-Scheme Using Modular Computation Technique for the Moduli Set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5}. Sci. Front. 2023, 4(1), 8-16. doi: 10.11648/j.sf.20230401.12

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    AMA Style

    Mohammed Ibrahim Daabo, Valentine Aveyom. Efficient Sign-Detection-Scheme Using Modular Computation Technique for the Moduli Set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5}. Sci Front. 2023;4(1):8-16. doi: 10.11648/j.sf.20230401.12

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  • @article{10.11648/j.sf.20230401.12,
      author = {Mohammed Ibrahim Daabo and Valentine Aveyom},
      title = {Efficient Sign-Detection-Scheme Using Modular Computation Technique for the Moduli Set {2n-1, 2n, 2n+1, 2(n+1)-1, 22n-5}},
      journal = {Science Frontiers},
      volume = {4},
      number = {1},
      pages = {8-16},
      doi = {10.11648/j.sf.20230401.12},
      url = {https://doi.org/10.11648/j.sf.20230401.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sf.20230401.12},
      abstract = {In computer arithmetic, one of the most important things to consider in hardware design is the ability of the system to detect and display numbers with their signs. This when properly managed will reduce errors and ensure hardware reliability. But interestingly, detecting and knowing the sign of a residue number during arithmetic operation is very difficult. Magnitude Comparison, Scaling and Number conversions are some of the other difficult operations in Residue Number System (RNS). Unlike the weighted number system, it is even extremely difficult to determine the sign of a number in an RNS architecture thereby hampering the full implementation RNS in general purpose computing.  In this paper, an efficient sign detection algorithm for detecting the sign of a number in an RNS architecture is presented. In formulating the algorithms, X maximum, (Xmax) is computed from the Dynamic Range, M=∏ki=1(mi). Modular Computation Technique is employed as a converter to compute X from the residues (r1, r2, r3) with respect to a given moduli set, say S= {m1, m2 ..., mn}. X is positive if X-Xmaxn-1, 2n, 2n+1, 2(n+1)-1, 22n-5} is used for the system design implementation and for numerical illustrations. It is observed that the scheme effectively detects the sign of RNS numbers and theoretical analysis showed that simple hardware resources and low-power modular adders are used in the design. It is also observed that the scheme when implemented practically can help project RNS to be used in general purpose computing.},
     year = {2023}
    }
    

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    AB  - In computer arithmetic, one of the most important things to consider in hardware design is the ability of the system to detect and display numbers with their signs. This when properly managed will reduce errors and ensure hardware reliability. But interestingly, detecting and knowing the sign of a residue number during arithmetic operation is very difficult. Magnitude Comparison, Scaling and Number conversions are some of the other difficult operations in Residue Number System (RNS). Unlike the weighted number system, it is even extremely difficult to determine the sign of a number in an RNS architecture thereby hampering the full implementation RNS in general purpose computing.  In this paper, an efficient sign detection algorithm for detecting the sign of a number in an RNS architecture is presented. In formulating the algorithms, X maximum, (Xmax) is computed from the Dynamic Range, M=∏ki=1(mi). Modular Computation Technique is employed as a converter to compute X from the residues (r1, r2, r3) with respect to a given moduli set, say S= {m1, m2 ..., mn}. X is positive if X-Xmaxn-1, 2n, 2n+1, 2(n+1)-1, 22n-5} is used for the system design implementation and for numerical illustrations. It is observed that the scheme effectively detects the sign of RNS numbers and theoretical analysis showed that simple hardware resources and low-power modular adders are used in the design. It is also observed that the scheme when implemented practically can help project RNS to be used in general purpose computing.
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Author Information
  • Department of Computer Science, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana

  • Department of Computer Science, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana

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