Multiplier Design using Machine Learning Alogorithms for Energy Efficiency

Authors

  • Jane Juma
  • R.M. Mdodo
  • David Gichoya

DOI:

https://doi.org/10.31838/jvcs/05.01.04

Keywords:

Cadence virtuoso; FinFET; Dynamic Logic; Domino logic; Manchester Carry Chain.

Abstract

Designers primary goal is to develop the Adder cell with improved performance viz. speed, fixed rise and fall time, as it the fundamental block in VLSI design process. The dynamic logic circuits are far better than the static logic circuits because it consumes
less power and speed performance also increased. But, cascading of several blocks in dynamic logic is found to be a wrong analysis. This drawback of increased complexity with mismatched cascading is overcome by using domino logic circuits. By using domino
logic circuits, the reduction of noise margins and increase the speed performance of the circuit is achieved. In this paper, domino logic based Manchester carry chain adder (MCC) is designed using FinFET 18nm technology in Cadence virtuoso. It is noticed that 4-bit and an 8-bit Manchester Carry Chain Adder (MCC) using domino logic design consumes less power and reduction in the delay of the proposed circuit compared with the previous architecture. Implementation results reveal that the 4-Bit MCC Adder has delay of 79.45% less compared to the existed standard design and power consumption also reduced to 94.15%.

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Published

2022-10-12

How to Cite

Jane Juma, R.M. Mdodo, & David Gichoya. (2022). Multiplier Design using Machine Learning Alogorithms for Energy Efficiency. Journal of VLSI Circuits and Systems, 5(01), 28–34. https://doi.org/10.31838/jvcs/05.01.04

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Articles