2014
DOI: 10.1109/tc.2013.92
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Novel RNS Parameter Selection for Fast Modular Multiplication

Abstract: Abstract-The parameter selection of Residue Number Systems (RNS) has a great impact on its computational efficiency. This paper shows that a base extension, the most costly operation in RNS Montgomery multiplication, can be more efficient when the intervals between the RNS moduli are small. We propose a systematic RNS parameter selection procedure and two methods to select RNS moduli that lead to a reduced complexity. Our experimental results confirm the advantages of the selected moduli.

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Cited by 17 publications
(5 citation statements)
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“…Further optimization regarding µ i may be possible for efficient implementation (e.g. [15]). The proposed algorithm can be combined with such optimization, if necessary.…”
Section: Choice Of Approximation Functionmentioning
confidence: 99%
“…Further optimization regarding µ i may be possible for efficient implementation (e.g. [15]). The proposed algorithm can be combined with such optimization, if necessary.…”
Section: Choice Of Approximation Functionmentioning
confidence: 99%
“…Then the multiplication is performed in parallel on the individual residues in the RNS representations of the operands with reduction steps including a division by one of the moduli in each step [14]. The RNS domain is converted back to the original domain by Chinese remainder theorem (CRT) [26]. Although the RNS representations speed up the multiplication process significantly, they consume more power because of their high complexity and require a vast amount of hardware resources to be implemented on machines.…”
Section: Mathematical Background and Motivationmentioning
confidence: 99%
“…System. Hence, it has been chosen as a subject of implementation in many designs (Antão, Bajard, & Sousa, 2012), (Bajard, Kaihara, & Plantard, 2009), (Asif & Kong, 2017;Asif, Hossain, Kong, & Abdul, 2018;Asif, Andersson, Rodrigues, & Kong, 2018), (Bajard, Eynard, & Gandino, 2013), (Antão & Sousa, 2014), (Yang, Hu, & Qin, 2015), (Yao, Fan, Cheung, & Verbauwhede, 2014) and many more.…”
Section: Montgomery Multipliermentioning
confidence: 99%