Skip to main content
Log in

A Low Error, Hardware Efficient Logarithmic Multiplier

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

The ever-increasing requirement for high-performance signal processing blocks in artificial intelligence, IoT, and neural networks has rendered the Logarithmic arithmetic as front runner of advanced processors. As they require complex mathematical operations such as multiplication and division but they can be quickly done in the logarithmic domain as they are reduced to addition and subtraction operations, respectively. The task, though, is to move from binary to logarithmic and vice versa. Several algorithms have been suggested for the logarithmic and antilogarithmic conversion, but there is a compromise between hardware difficulty and accuracy. Within this work, we are introducing the correction circuit for both logarithmic and antilogarithmic conversion that is based on Mitchell’s algorithm. Here the correction terms are generated using a weighted average approach and are stored using 16 X 8 ROM. The terms for correction are selected using the characteristic of the logarithmic value. Then, these converters are used to design a logarithmic multiplier. To further simplify the multiplier, an optimized multiplier is proposed. It involves only the addition of a single term to the result before performing an antilogarithm operation, which also streamlined the application of the multiplier. The proposed multiplier and optimized multiplier involves only a memory unit and an adder apart from Mitchell’s logarithmic multiplier, so the hardware metrics are closely similar to Mitchell’s logarithmic multiplier while having a peak error rate of 9.4 \(\%\) and 7.5 \(\%\) which is 11.1 \(\%\) for Mitchell’s multiplier and has nearly 95\(\%\) of input combinations have less than 5\(\%\) error when multiplication is performed using proposed multipliers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analysed during the current study

References

  1. K.H. Abed, R.E. Siferd, Cmos vlsi implementation of a low-power logarithmic converter. IEEE Trans. Comput. 52(11), 1421–1433 (2003). https://doi.org/10.1109/TC.2003.1244940

    Article  Google Scholar 

  2. K.H. Abed, R.E. Siferd, Vlsi implementation of a low-power antilogarithmic converter. IEEE Trans. Comput. 52(9), 1221–1228 (2003). https://doi.org/10.1109/TC.2003.1228517

    Article  Google Scholar 

  3. M.S. Ansari, B.F. Cockburn, J.A. Han, Hardware-efficient logarithmic multiplier with improved accuracy. In: 2019 Design, Automation Test in Europe Conference Exhibition (DATE), pp. 928–931 (2019). https://doi.org/10.23919/DATE.2019.8714868

  4. M.S. Ansari, B.F. Cockburn, J. Han, An improved logarithmic multiplier for energy-efficient neural computing. IEEE Trans. Comput. 70(4), 614–625 (2021). https://doi.org/10.1109/TC.2020.2992113

    Article  MathSciNet  Google Scholar 

  5. M.G. Arnold, C. Walter, Unrestricted faithful rounding is good enough for some lns applications. In: Proceedings 15th IEEE Symposium on Computer Arithmetic. ARITH-15 2001, pp. 237–246 (2001). https://doi.org/10.1109/ARITH.2001.930125

  6. T.A. Brubaker, J.C. Becker, Multiplication using logarithms implemented with read-only memory. IEEE Trans. Comput. C–24(8), 761–765 (1975). https://doi.org/10.1109/T-C.1975.224307

    Article  MATH  Google Scholar 

  7. S. Chandra, E.E. Swartzlander, S. Nagle, Sign/logarithm arithmetic for fft implementation. IEEE Trans. Comput. C–32(6), 526–534 (1983). https://doi.org/10.1109/TC.1983.1676274

    Article  MATH  Google Scholar 

  8. V.K. Chippa, S.T. Chakradhar, K. Roy, A. Raghunathan, Analysis and characterization of inherent application resilience for approximate computing. In: 2013 50th ACM/EDAC/IEEE Design Automation Conference (DAC), pp. 1–9 (2013). https://doi.org/10.1145/2463209.2488873

  9. M. Combet, H. Van Zonneveld, L. Verbeek, Computation of the base two logarithm of binary numbers. IEEE Trans. Electr. Comput. EC–14(6), 863–867 (1965). https://doi.org/10.1109/PGEC.1965.264080

    Article  Google Scholar 

  10. H. Esmaeilzadeh, A. Sampson, L. Ceze, D. Burger, Architecture support for disciplined approximate programming. In: ASPLOS XVII (2012)

  11. S. Gandhi, M.S. Ansari, B.F. Cockburn, J. Han, Approximate leading one detector design for a hardware-efficient mitchell multiplier, In 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), pp. 1–4, (2019). https://doi.org/10.1109/CCECE.2019.8861800

  12. E.L. Hall, D.D. Lynch, S.J. Dwyer, Generation of products and quotients using approximate binary logarithms for digital filtering applications. IEEE Trans. Comput. C–19(2), 97–105 (1970). https://doi.org/10.1109/T-C.1970.222874

    Article  MATH  Google Scholar 

  13. N.G. Kingsbury, P.J.W. Rayner, Digital filtering using logarithmic arithmetic. Electron. Lett. 7(2), 56–58 (1971). https://doi.org/10.1049/el:19710039

    Article  Google Scholar 

  14. A. Klinefelter, J. Ryan, J. Tschanz, B.H. Calhoun, Error-energy analysis of hardware logarithmic approximation methods for low power applications. In: 2015 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2361–2364 (2015). https://doi.org/10.1109/ISCAS.2015.7169158

  15. G. Kmetz, Floating point logarithmic conversion system (1986). US Patent 4,583,180

  16. D.K. Kostopoulos, An algorithm for the computation of binary logarithms. IEEE Trans. Comput. 40(11), 1267–1270 (1991). https://doi.org/10.1109/12.102831

    Article  MathSciNet  MATH  Google Scholar 

  17. I. Kouretas, C. Basetas, V. Paliouras, Low-power logarithmic number system addition/subtraction and their impact on digital filters. IEEE Trans. Comput. 62(11), 2196–2209 (2013). https://doi.org/10.1109/TC.2012.111

    Article  MathSciNet  MATH  Google Scholar 

  18. F. Lai, C.E. Wu, A hybrid number system processor with geometric and complex arithmetic capabilities. IEEE Trans. Comput. 40(8), 952–962 (1991). https://doi.org/10.1109/12.83639

    Article  Google Scholar 

  19. D.M. Lewis, Interleaved memory function interpolators with application to an accurate lns arithmetic unit. IEEE Trans. Comput. 43(8), 974–982 (1994). https://doi.org/10.1109/12.295859

    Article  MATH  Google Scholar 

  20. W. Liu, J. Xu, D. Wang, C. Wang, P. Montuschi, F. Lombardi, Design and evaluation of approximate logarithmic multipliers for low power error-tolerant applications. IEEE Trans. Circuits Syst. I Regul. Pap. 65(9), 2856–2868 (2018). https://doi.org/10.1109/TCSI.2018.2792902

    Article  Google Scholar 

  21. R. Maenner, A fast integer binary logarithm of large arguments. IEEE Micro 7(6), 41–45 (1987). https://doi.org/10.1109/MM.1987.304914

    Article  Google Scholar 

  22. V. Mahalingam, N. Ranganathan, Improving accuracy in mitchell’s logarithmic multiplication using operand decomposition. IEEE Trans. Comput. 55(12), 1523–1535 (2006). https://doi.org/10.1109/TC.2006.198

  23. D.J. Mclaren, Improved mitchell-based logarithmic multiplier for low-power dsp applications. In: IEEE International [Systems-on-Chip] SOC Conference, 2003. Proceedings., pp. 53–56 (2003). https://doi.org/10.1109/SOC.2003.1241461

  24. J.N. Mitchell, Computer multiplication and division using binary logarithms. IRE Trans. Electr. Comput. EC–11(4), 512–517 (1962). https://doi.org/10.1109/TEC.1962.5219391

    Article  MathSciNet  MATH  Google Scholar 

  25. R. Muscedere, Difficult operations in the multi-dimensional logarithmic number system (2003)

  26. R. Muscedere, V. Dimitrov, G.A. Jullien, W.C. Miller, Efficient techniques for binary-to-multidigit multidimensional logarithmic number system conversion using range-addressable look-up tables. IEEE Trans. Comput. 54(3), 257–271 (2005). https://doi.org/10.1109/TC.2005.48

    Article  Google Scholar 

  27. D. Nandan, J. Kanungo, A. Mahajan, An efficient vlsi architecture design for logarithmic multiplication by using the improved operand decomposition. Integration 58, 134–141 (2017). https://doi.org/10.1016/j.vlsi.2017.02.003

    Article  Google Scholar 

  28. S.Z.M. Naziri, R.C. Ismail, A.Y.M. Shakaff, The design revolution of logarithmic number system architecture. In: 2014 2nd International Conference on Electrical, Electronics and System Engineering (ICEESE), pp. 5–10 (2014). https://doi.org/10.1109/ICEESE.2014.7154603

  29. V. Paliouras, T. Stouraitis, Logarithmic number system for low-power arithmetic, International Workshop on Power and Timing Modeling, Optimization and Simulation (Springer, Berlin, 2000), pp. 285–294

    Google Scholar 

  30. H. Saadat, H. Bokhari, S. Parameswaran, Minimally biased multipliers for approximate integer and floating-point multiplication. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(11), 2623–2635 (2018). https://doi.org/10.1109/TCAD.2018.2857262

    Article  Google Scholar 

  31. S.L. SanGregory, C. Brothers, D. Gallagher, R. Siferd, A fast, low-power logarithm approximation with cmos vlsi implementation. In: 42nd Midwest Symposium on Circuits and Systems (Cat. No.99CH36356), vol. 1, pp. 388–391 (1999). https://doi.org/10.1109/MWSCAS.1999.867287

  32. E.E. Swartzlander, A.G. Alexopoulos, The sign/logarithm number system. IEEE Transactions on Computers C–24(12), 1238–1242 (1975). https://doi.org/10.1109/T-C.1975.224172

    Article  MathSciNet  MATH  Google Scholar 

  33. F.J. Taylor, R. Gill, J. Joseph, J. Radke, A 20 bit logarithmic number system processor. IEEE Trans. Comput. 37(2), 190–200 (1988). https://doi.org/10.1109/12.2148

    Article  Google Scholar 

  34. L.K. Yu, D.M. Lewis, A 30-b integrated logarithmic number system processor. IEEE J. Solid-State Circuits 26(10), 1433–1440 (1991). https://doi.org/10.1109/4.90098

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bhaskara Rao Jammu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Harsha, L.G.S.S., Jammu, B.R., Bodasingi, N. et al. A Low Error, Hardware Efficient Logarithmic Multiplier. Circuits Syst Signal Process 41, 485–513 (2022). https://doi.org/10.1007/s00034-021-01793-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-021-01793-8

Keywords

Navigation