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Page No: 163-182
Abstract : Approximate computing is a promising technique to elevate the performance of digital
circuits which curtail the hardware requirements by exploiting the inherent error resilience of
certain applications such as digital signal processing, multimedia and machine learning.
Approximate multipliers and other approximation techniques can be integrated to increase the
performance of applications such as convolutional Neural Networks. In the proposed work, a
truncation based Booth multiplier is designed based on multi-level compressors such as 4:2, 5:2
and 6:3 counter. A compensation circuit is generated by selective modifications in k-map to
circumvent the carry appearing from the truncated part. By efficient mapping, hardware pruning
and output error reduction is achieved simultaneously. In the quest of power and accuracy tradeoff, Truncated and Approximate Booth Multipliers using compressors and counters (TABM-CC)
are proposed with a range of designs based on truncation factor w. When compared with the
state-of-the-art multipliers, TACBM outperforms in terms of accuracy and Area-Power savings.
Keyword Truncated and Approximate Booth Multipliers using compressors and counters
(TABM-CC), Compressors, Counters, Digital Signal Processing
Reference: