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Title: Ultra-low-power and variation-aware digital signal processing
Author: Lu, Yue
ISNI:       0000 0004 7972 1424
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2019
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Internet of Things is a rapidly emerging technology that allows people and things to be connected anywhere and any time, using any path or network. The "things" in the IoT applications need external power to perform any function. As a result, IoT devices must offer superior power efficiency compared with previous digital applications. In terms of power-saving techniques, voltage scaling is regarded as one of the most efficient method. However, the aggressive scaling of the CMOS size and supply voltage have posed a increase concern about circuit reliability. This thesis studies the effects of process variation on the low-voltage digital signal processing circuits, with the aim to develop efficient methods to further achieve power saving at the circuit-level and provide corresponding cost-effective error mitigation techniques. This thesis presents three major contributions. First of all, the analysis of process variation on the adiabatic logic circuit (an energy recovery logic) is implemented and bit-serial implementation is proposed as an efficient method to improve the energyefficiency and robustness against variation. After that, our research emphasis in this thesis is shifted to low power and reliable serial computing. The second contribution demonstrates the advantages of serial computing on a FFT implementation in terms of area minimisation, power-saving and energy-scalable operation. The third contribution proposes several novel error-mitigation techniques for serial computing via path isolation, variable latency or time borrowing. The FIR evaluation results show that the proposed techniques can effectively mask or prevent timing errors with very low hardware cost and make serial circuit as a promising candidate for power-efficient and reliable computing in the IoT devices.
Supervisor: Kazmierski, Tomasz Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available